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Appl. Sci., Volume 12, Issue 18 (September-2 2022) – 473 articles

Cover Story (view full-size image): An organic-scintillator-based radiation portal monitor (RPM) prototype system with novel imaging capabilities has been developed based on the neutron–gamma emission tomography technique. This enables the rapid detection and precise location of small amounts of special nuclear materials, using the time and energy correlations between fast neutrons and gamma rays from fission with low false-alarm rates. In combination with state-of-the-art detection sensitivity for a wide range of gamma-emitting radioactive sources, the novel imaging RPM concept is well suited to efficiently addressing global security threats from terrorism and the proliferation of nuclear weapons. View this paper
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14 pages, 7199 KiB  
Article
Internet of Things Meets Computer Vision to Make an Intelligent Pest Monitoring Network
by Bruno Cardoso, Catarina Silva, Joana Costa and Bernardete Ribeiro
Appl. Sci. 2022, 12(18), 9397; https://doi.org/10.3390/app12189397 - 19 Sep 2022
Cited by 8 | Viewed by 4637
Abstract
With the increase of smart farming in the agricultural sector, farmers have better control over the entire production cycle, notably in terms of pest monitoring. In fact, pest monitoring has gained significant importance, since the excessive use of pesticides can lead to great [...] Read more.
With the increase of smart farming in the agricultural sector, farmers have better control over the entire production cycle, notably in terms of pest monitoring. In fact, pest monitoring has gained significant importance, since the excessive use of pesticides can lead to great damage to crops, substantial environmental impact, and unnecessary costs both in material and manpower. Despite the potential of new technologies, pest monitoring is still done in a traditional way, leading to excessive costs, lack of precision, and excessive use of human labour. In this paper, we present an Internet of Things (IoT) network combined with intelligent Computer Vision (CV) techniques to improve pest monitoring. First, we propose to use low-cost cameras at the edge that capture images of pest traps and send them to the cloud. Second, we use deep neural models, notably R-CNN and YOLO models, to detect the Whitefly (WF) pest in yellow sticky traps. Finally, the predicted number of WF is analysed over time and results are accessible to farmers through a mobile app that allows them to visualise the pest in each specific field. The contribution is to make pest monitoring autonomous, cheaper, data-driven, and precise. Results demonstrate that, by combining IoT, CV technology, and deep models, it is possible to enhance pest monitoring. Full article
(This article belongs to the Special Issue Advanced IoT Technologies in Agriculture)
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<p>Types of computation (adapted from [<a href="#B14-applsci-12-09397" class="html-bibr">14</a>]).</p>
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<p>Network topology (adapted from [<a href="#B18-applsci-12-09397" class="html-bibr">18</a>]).</p>
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<p>Faster R-CNN general architecture (adapted from [<a href="#B24-applsci-12-09397" class="html-bibr">24</a>]).</p>
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<p>YOLOv5 general architecture (adapted from [<a href="#B26-applsci-12-09397" class="html-bibr">26</a>]).</p>
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<p>Part of a dataset image with WFs.</p>
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<p>Proposed IoT network.</p>
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<p>YOLOv5 (XLarge) performance (number of whitefly detections) for different image dimensions and sizes.</p>
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<p>Diagram of ESP32-CAM powered by solar panels.</p>
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<p>Trap structures at the edge.</p>
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<p>Example of a daily pest detection by the CV model.</p>
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<p>Part of the mobile app that allows users to monitor pests.</p>
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<p>More examples of trap structures at the edge.</p>
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<p>Another example of a daily pest detection by the CV model.</p>
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18 pages, 19543 KiB  
Article
Space Node Topology Optimization Design Considering Anisotropy of Additive Manufacturing
by Xianjie Wang, Fan Zhang, Zhenjiang Weng, Xinyu Jiang, Rushuang Wang, Hao Ren and Feiyun Zheng
Appl. Sci. 2022, 12(18), 9396; https://doi.org/10.3390/app12189396 - 19 Sep 2022
Cited by 2 | Viewed by 2125
Abstract
At present, a large number of scholars have conducted related research on topology optimization for additive manufacturing (AM). However, there are few relevant research reports on the impact of different directions of additive manufacturing on the optimal design and manufacturing results. In this [...] Read more.
At present, a large number of scholars have conducted related research on topology optimization for additive manufacturing (AM). However, there are few relevant research reports on the impact of different directions of additive manufacturing on the optimal design and manufacturing results. In this paper, using the bidirectional evolutionary optimization (BESO) method, anisotropic optimization analysis was carried out on space nodes that are currently popular in the field of additive manufacturing and topology optimization. The elastic constants in different directions were used as anisotropic material properties for optimization research in this paper through tensile testing, which was carried out on 316L stainless-steel specimens fabricated using Selective Laser Melting (SLM) technology. In addition, SEM analyses were performed to explore the microscopic appearance of the material. The study found that additive manufacturing is affected by the printing direction in terms of both macroscopic mechanical properties and microscopic material structure; the deformation obtained by anisotropic optimization was about 1.1–2.3% smaller than that obtained by isotropic optimization. Full article
(This article belongs to the Special Issue Porous Materials and Structures)
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<p>Schematic diagram of sensitivity filtering.</p>
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<p>Flowchart of topology optimization.</p>
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<p>Schematic diagram of SLM 316L stainless-steel metal specimen.</p>
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<p>Schematic diagram of sample printing: (<b>a</b>) printing direction; (<b>b</b>) finished product.</p>
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<p>Schematic diagram for adding properties of anisotropic materials.</p>
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<p>Initial shape and load layout of nodes (the green part is the design domain, the gray part is the ear plate area, the yellow arrow is the combined load of axial force and pressure, and the blue area is the binding boundary).</p>
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<p>Isotropic topology optimization results: (<b>a</b>) stress contour; (<b>b</b>) iterative curve.</p>
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<p>Schematic diagram of tensile test: (<b>a</b>) Zwick electronic universal testing machine; (<b>b</b>) sample clamping state.</p>
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<p>Stress–strain curve: (<b>a</b>) flat; (<b>b</b>) side; (<b>c</b>) vertical; (<b>d</b>) three directions.</p>
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<p>Anisotropy of additively manufactured sample (including yield strength, elastic modulus, tensile strength, and elongation).</p>
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<p>Surface topography before stretching: (<b>a</b>) flat-printed sample 200×; (<b>b</b>) vertical-printed sample 200×; (<b>c</b>) flat-printed sample 1000×; (<b>d</b>) vertical-printed sample 1000×.</p>
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<p>Surface photo of the sample after tensile test: (<b>a</b>) overall appearance of the flat-printed sample after stretching; (<b>b</b>) overall appearance of the vertically printed sample after stretching; (<b>c</b>) particles in the crack of the flat-printed sample; (<b>d</b>) particles in the cracks of the vertically printed sample; (<b>e</b>) crack morphology of the flat-printed sample; (<b>f</b>) crack morphology of the vertical-printed sample.</p>
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<p>Photo of the microscopic topography at the fracture: (<b>a</b>) flat-printed sample 200×; (<b>b</b>) vertical-printed sample 200×; (<b>c</b>) flat-printed sample 200×; (<b>d</b>) vertical-printed sample 200×.</p>
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<p>Displacement nephogram under isotropic optimization: (<b>a</b>) X-direction print, Y-direction scan; (<b>b</b>) X-direction print, Z-direction scan; (<b>c</b>) Y-direction print, X-direction scan; (<b>d</b>) Y-direction print, Z-direction scan; (<b>e</b>) Z-direction print, X-direction scan; (<b>f</b>) Z-direction print, Y-direction scan.</p>
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<p>Shape and displacement nephogram under anisotropic optimization: (<b>a</b>) X-direction print, Y-direction scan; (<b>b</b>) X-direction print, Z-direction scan; (<b>c</b>) Y-direction print, X-direction scan; (<b>d</b>) Y-direction print, Z-direction scan; (<b>e</b>) Z-direction print, X-direction scan; (<b>f</b>) Z-direction print, Y-direction scan.</p>
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<p>Shape and displacement nephogram under anisotropic optimization: (<b>a</b>) X-direction print, Y-direction scan; (<b>b</b>) X-direction print, Z-direction scan; (<b>c</b>) Y-direction print, X-direction scan; (<b>d</b>) Y-direction print, Z-direction scan; (<b>e</b>) Z-direction print, X-direction scan; (<b>f</b>) Z-direction print, Y-direction scan.</p>
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<p>Deformation comparison between anisotropy and isotropy (yellow line is the deformation in six directions after isotropic optimization; red line is the deformation in six directions after anisotropic optimization).</p>
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18 pages, 991 KiB  
Article
Anonymous Identity Based Broadcast Encryption against Continual Side Channel Attacks in the State Partition Model
by Qihong Yu, Jiguo Li and Sai Ji
Appl. Sci. 2022, 12(18), 9395; https://doi.org/10.3390/app12189395 - 19 Sep 2022
Cited by 2 | Viewed by 1624
Abstract
In the past 10 years, many side-channel attacks have been discovered and exploited one after another by attackers, which have greatly damaged the security of cryptographic systems. Since no existing anonymous broadcast encryption scheme can resist the side-channel attack, the paper presents an [...] Read more.
In the past 10 years, many side-channel attacks have been discovered and exploited one after another by attackers, which have greatly damaged the security of cryptographic systems. Since no existing anonymous broadcast encryption scheme can resist the side-channel attack, the paper presents an anonymous identity-based broadcast encryption against continual side-channel attacks in the state partition model (CLR-SS-AIBBE). Based on split-state technology, the proposed scheme divides the private key into two states, and the decryption operations are correspondingly divided into two steps. Based on the three static hypotheses for a bilinear group with composite order, the proposed scheme can be proved to be fully secure by the dual system encryption technology in the standard model. The leakage ratio about the private key can reach 1/3. Full article
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<p>The relationship between the three leakage models.</p>
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<p>The system’s framework of anonymous leakage-resilient IBBE in cloud storage services.</p>
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14 pages, 3590 KiB  
Article
Earthquake Risk Probability Evaluation for Najin Lhasa in Southern Tibet
by Jianlong Zhang, Ye Zhu, Yingfeng Ji, Weiling Zhu, Rui Qu, Zhuoma Gongqiu and Chaodi Xie
Appl. Sci. 2022, 12(18), 9394; https://doi.org/10.3390/app12189394 - 19 Sep 2022
Viewed by 1671
Abstract
The probabilistic seismic hazard analysis (PSHA) method is effectively used in an earthquake risk probability evaluation in seismogenic regions with active faults. In this study, by focusing on the potential seismic source area in Najin Lhasa, southern Tibet, and by incorporating the PSHA [...] Read more.
The probabilistic seismic hazard analysis (PSHA) method is effectively used in an earthquake risk probability evaluation in seismogenic regions with active faults. In this study, by focusing on the potential seismic source area in Najin Lhasa, southern Tibet, and by incorporating the PSHA method, we determined the seismic activity parameters and discussed the relationship of ground motion attenuation, the seismic hazard probability, and the horizontal bedrock ground motion acceleration peak value under different transcendence probabilities in this area. The calculation results show that the PSHA method divides the potential source area via specific tectonic scales and detailed tectonic markers, which reduces the scale of the potential source area and better reflects the uneven spatial distribution of seismic activity in the vicinity of Najin. The corrected attenuation relationship is also in line with the actual work requirements and is suitable for earthquake risk analysis. In addition, the major influences on the peak acceleration of ground motion in the study area are mainly in the potential source areas of Qushui (M7.5), Dangxiong (M8.5), and Kangma (M7.5). The peak horizontal ground motion acceleration (PGA) with a transcendence probability of 10% in 50 years is 185.9 cm/s2, and that with a transcendence probability of 2% in 50 years is 265.9 cm/s2. Full article
(This article belongs to the Section Earth Sciences)
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<p>Tectonic map. The red rectangular indicates the study area. The background colored in pink indicates the Tibet autonomous region, and the green part indicates the Qinghai province, China. Black lines indicate the boundaries of the earthquake statistical area. The dashed red lines indicate the main faults and terrain boundaries. YZSZ: Yarlung–Zangpo suture zone; BNSZ: Bangong–Nujiang suture zone; JRSZ: Jinsha River suture zone; MBT: Main Boundary Thrust.</p>
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<p>Division map of 18 potential seismogenic zones (red lines) according to this study. The numbers indicate the zone number. Black curves indicate the county boundaries.</p>
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<p>Transcendence probability curve of the horizontal peak acceleration of bedrock at the engineering site of Najin Lhasa.</p>
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<p>Response spectrum curve of the bedrock horizontal acceleration at the engineering site of Najin Lhasa.</p>
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<p>Horizontal bedrock PGA decay curve with epicentral distance (R).</p>
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<p>Attenuation curve of the response spectrum of horizontal bedrock acceleration (epicentral distance R = 50 km).</p>
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<p>Attenuation curve of the response spectrum of horizontal bedrock acceleration (epicentral distance R = 100 km).</p>
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12 pages, 3535 KiB  
Article
Design and Implementation of an Additively Manufactured Reactor Concept for the Catalytic Methanation
by Alexander Hauser, Michael Neubert, Alexander Feldner, Alexander Horn, Fabian Grimm and Jürgen Karl
Appl. Sci. 2022, 12(18), 9393; https://doi.org/10.3390/app12189393 - 19 Sep 2022
Cited by 6 | Viewed by 1687
Abstract
The methanation process is discussed as one way to chemically store renewable energy in a future energy system. An important criterion for its application is the availability of compact, low-cost reactor concepts with high conversion rates for decentralized use where the renewable energy [...] Read more.
The methanation process is discussed as one way to chemically store renewable energy in a future energy system. An important criterion for its application is the availability of compact, low-cost reactor concepts with high conversion rates for decentralized use where the renewable energy is produced. Current research focuses on the maximization of the methane yield through improved temperature control of the exothermic reaction, which attempts to avoid both kinetic and thermodynamic limitations. In this context, traditional manufacturing methods limit the design options of the reactor and thus the temperature control possibilities. The use of additive manufacturing methods removes this restriction and creates new freedom in the design process. This paper formulates the requirements for a novel methanation reactor and presents their implementation to a highly innovative reactor concept called ‘ADDmeth’. By using a conical reaction channel expanding from Ø 8 to 32 mm, three twisted, expanding heat pipes (Ø 8 mm in evaporation zone, Ø 12 mm in condenser zone) and a lattice structure for feed gas preheating and mechanical stabilization of the reactor, the design explicitly exploits the advantages of additive manufacturing. The reactor is very compact with a specific mass of 0.36 kg/kW and has a high share of functional volume of 52%. The reactor development was accompanied by tensile tests of additively manufactured samples with the used material 1.4404 (316 L), strength calculations for stability verification and feasibility studies on the printability of fine structures. Ultimate tensile strengths of up to 750 N/mm2 (at room temperature) and sufficiently high safety factors of the pressure-loaded structures against yielding were determined. Finally, the paper presents the manufactured bench-scale reactor ADDmeth1 and its implementation. Full article
(This article belongs to the Special Issue Applications of 3D Printing in Different Industries)
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<p>Schematic illustration of the main objectives of active temperature control for methanation reactors (adapted from [<a href="#B11-applsci-12-09393" class="html-bibr">11</a>] with permission of Elsevier).</p>
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<p>Geometry of the tensile samples (dimensions in mm).</p>
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<p>Mounted tensile sample incl. thermocouples.</p>
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<p>CAD cutaway scheme of ADDmeth1 highlighting the innovations and an exemplary gas pathway.</p>
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<p>Exemplary stress–strain curves (individual measurements) of tensile tests at room temperature for tensile samples additively manufactured in different spatial directions.</p>
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<p>Metal print sample (1.4404) with fine structures.</p>
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<p>ADDmeth1 with fittings and piping for reactants, product gas, cooling and instrumentation.</p>
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28 pages, 6720 KiB  
Article
Understanding and Predicting the Usage of Shared Electric Scooter Services on University Campuses
by Seyed Mohammad Hossein Moosavi, Zhenliang Ma, Danial Jahed Armaghani, Mahdi Aghaabbasi, Mogana Darshini Ganggayah, Yuen Choon Wah and Dmitrii Vladimirovich Ulrikh
Appl. Sci. 2022, 12(18), 9392; https://doi.org/10.3390/app12189392 - 19 Sep 2022
Cited by 9 | Viewed by 4570
Abstract
Electric vehicles (EVs) have been progressing rapidly in urban transport systems given their potential in reducing emissions and energy consumptions. The Shared Free-Floating Electric Scooter (SFFES) is an emerging EV publicized to address the first-/last-mile problem in travel. It also offers alternatives for [...] Read more.
Electric vehicles (EVs) have been progressing rapidly in urban transport systems given their potential in reducing emissions and energy consumptions. The Shared Free-Floating Electric Scooter (SFFES) is an emerging EV publicized to address the first-/last-mile problem in travel. It also offers alternatives for short-distance journeys using cars or ride-hailing services. However, very few SFFES studies have been carried out in developing countries and for university populations. Currently, many universities are facing an increased number of short-distance private car travels on campus. The study is designed to explore the attitudes and perceptions of students and staff towards SFFES usage on campus and the corresponding influencing factors. Three machine learning models were used to predict SFFES usage. Eleven important factors for using SFFESs on campus were identified via the supervised and unsupervised feature selection techniques, with the top three factors being daily travel mode, road features (e.g., green spaces) and age. The random forest model showed the highest accuracy in predicting the usage frequency of SFFESs (93.5%) using the selected 11 variables. A simulation-based optimization analysis was further conducted to discover the characterization of SFFES users, barriers/benefits of using SFFESs and safety concerns. Full article
(This article belongs to the Special Issue Novel Hybrid Intelligence Techniques in Engineering)
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<p>University of Malaya campus map.</p>
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<p>Methodology workflow.</p>
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<p>Random forest algorithm workflow.</p>
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<p>Percentage of SFFES use frequency based on four categories.</p>
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<p>Participants’ perceptions about the advantages/benefits of using SFFESs.</p>
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<p>Participants’ opinions about what reasons would prevent them from using the SFFESs.</p>
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<p>Safety concerns based on SFFES usage categories.</p>
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<p>Impact of road features on the perceptions of respondents who believed safety was an extremely preventative factor for riding an e-scooter.</p>
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<p>Cluster dendrogram of 22 variables.</p>
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<p>Correlation between the 22 independent variables.</p>
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<p>Importance score (weight) of variables based on three ML methods.</p>
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<p>Accumulated weights of variables.</p>
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<p>The error vs number of tree graphs for 11 important features.</p>
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<p>Test error and out-of-bag (OOB) error rate of the predicted model.</p>
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<p>Optimization results and importance of variables based on the first scenario: Always use SFFESs.</p>
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<p>Optimization results and importance of variables based on the second scenario: Frequently use SFFESs.</p>
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<p>Optimization results and importance of variables based on the second scenario: Occasionally use SFFESs.</p>
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<p>Optimization results and importance of variables based on the second scenario: Never use SFFESs.</p>
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28 pages, 19023 KiB  
Article
Geodetic Upper Crust Deformation Based on Primary GNSS and INSAR Data in the Strymon Basin, Northern Greece—Correlation with Active Faults
by Ilias Lazos, Ioannis Papanikolaou, Sotirios Sboras, Michael Foumelis and Christos Pikridas
Appl. Sci. 2022, 12(18), 9391; https://doi.org/10.3390/app12189391 - 19 Sep 2022
Cited by 17 | Viewed by 3080
Abstract
The Strymon basin (Northern Greece) belongs to the geodynamically active regime of the Aegean and, as expected, it hosts active faults. Nevertheless, the study area exhibits a low instrumentally and historically recorded seismicity. In order to comprehend the crustal deformation, we implemented GNSS- [...] Read more.
The Strymon basin (Northern Greece) belongs to the geodynamically active regime of the Aegean and, as expected, it hosts active faults. Nevertheless, the study area exhibits a low instrumentally and historically recorded seismicity. In order to comprehend the crustal deformation, we implemented GNSS- and InSAR-based techniques. Global Navigation Satellite System (GNSS) primary geodetic data recorded by 32 permanent stations over 7 years were analyzed and input in the triangulation methodology so as to calculate a series of deformational parameters. Moreover, a geostatistical methodology indicated the spatial distribution of each parameter, showing strain delimited up to 2750 × 109. These results are in broad agreement with palaeoseismological surveys and active fault mapping. Moreover, InSAR analysis, based on a 6-year data recording, concluded that no horizontal rates have been traced in the E–W direction; if they do exist, they would be below resolution (less than 2 mm/yr). Peak vertical subsidence values of a few mm/yr are traced towards the hanging wall of the Serres fault zone within the Quaternary sediments at the eastern margin of Strymon basin but are attributed mainly to groundwater extraction. However, it is noteworthy that geodetic strain analysis implies: (a) that a couple of areas need further study to trace potentially active faults by palaeoseismological means; (b) the fault trace of the Serres fault zone might be further prolonged 8–10 km eastwards, where Quaternary sediments cover the fault. Full article
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<p>(<b>a</b>) Map showing the location of inset map (<b>b</b>). (<b>b</b>) Map of the principal tectonic structures in the broader Aegean region (after [<a href="#B20-applsci-12-09391" class="html-bibr">20</a>,<a href="#B25-applsci-12-09391" class="html-bibr">25</a>,<a href="#B26-applsci-12-09391" class="html-bibr">26</a>,<a href="#B59-applsci-12-09391" class="html-bibr">59</a>,<a href="#B60-applsci-12-09391" class="html-bibr">60</a>,<a href="#B61-applsci-12-09391" class="html-bibr">61</a>,<a href="#B62-applsci-12-09391" class="html-bibr">62</a>,<a href="#B63-applsci-12-09391" class="html-bibr">63</a>,<a href="#B64-applsci-12-09391" class="html-bibr">64</a>,<a href="#B65-applsci-12-09391" class="html-bibr">65</a>,<a href="#B66-applsci-12-09391" class="html-bibr">66</a>,<a href="#B67-applsci-12-09391" class="html-bibr">67</a>,<a href="#B68-applsci-12-09391" class="html-bibr">68</a>]). The North Aegean Basin (NAB) and the North Aegean Trough (NAT) comprise the northern strand of the North Anatolian Fault (NAF), while the Central Aegean Trough represents the corresponding southern strand. The Corinth Gulf (CG) is the most extensionally growing region in the Aegean. In the Ionian Sea, the Apulian–Aegean Collision Zone (AACZ) is shown to the north and the Hellenic Arc to the south, separated and displaced by the right-lateral Cephalonia Transfer Fault Zone (CTFZ) in the middle. Hatched areas represent extension. Moment tensor solutions since 1997 from the RCMT catalogue [<a href="#B69-applsci-12-09391" class="html-bibr">69</a>] are also shown. The white rectangle indicates the location of the inset map (<b>c</b>). (<b>c</b>) Hillshade map showing the active/Neotectonic faults of the study area (F = Fault, FZ = Fault Zone). Recent earthquake spatial distribution (M<sub>L</sub> ≥ 0.5) since 2008 by the Institute of Geodynamics, National Observatory of Athens (IG-NOA), is also shown.</p>
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<p>Typical wine-glass valleys, related to the Tholos–Nea Zichni (TNFZ) fault zone, located at the eastern boundary of the Strymon Basin. The red solid line indicates the linear fault trace. White lines show the incised wine-glass valleys indicating footwall uplift. Overall, the fault trace separates uplift from subsidence, controlling the present-day sedimentation processes, and also demonstrating that the fault is active.</p>
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<p>(<b>a</b>) Geological map of the broader Strymon region, showing the alpine and post-alpine formations and the alpine compressional tectonics [<a href="#B85-applsci-12-09391" class="html-bibr">85</a>], as well as the active-neotectonic faults as shown in <a href="#applsci-12-09391-f001" class="html-fig">Figure 1</a>; (<b>b</b>) 16 permanent GNSS stations (black triangles), monitoring the broader Strymon region.</p>
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<p>Maximum (MaHE) and Minimum (MiHE) Horizontal Extension in the broader Strymon area: (<b>a</b>) MaHE (blue arrows) and MiHE (red arrows) parameters vectors; (<b>b</b>) MaHE values grid, based on the interpolation (kriging) geostatistical methodology; (<b>c</b>) MiHE values grid, based on the interpolation (kriging) geostatistical methodology.</p>
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<p>Velocity (V) parameter analysis, consisting of vectors and grid pattern, based on the interpolation (kriging) geostatistical methodology.</p>
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<p>Maximum Shear Strain (MaxSS) in the broader Strymon area: (<b>a</b>) MaxSS values (red circles) of the total examination points; (<b>b</b>) MaxSS values grid, based on the interpolation (kriging) geostatistical analysis.</p>
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<p>Area Strain (AS) in the broader Strymon area: (<b>a</b>) calculated dilatation (blue circles) and compaction (red circles) values; (<b>b</b>) dilatation values grid, based on the interpolation (kriging) geostatistical methodology; (<b>c</b>) compaction values grid, based on the interpolation (kriging) geostatistical methodology.</p>
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<p>Average LoS displacement rates for the period 2015–2020, derived by SNAPPING service on GEP using Sentinel-1 data from ascending track 102. White lines (a–e and f–k) correspond to spatial profiles shown in <a href="#applsci-12-09391-f008" class="html-fig">Figure 8</a>. Please note that, for the selected color scale, rates higher than ±4 mm/yr appear saturated to allow for the proper visualization of spatial variability of motion.</p>
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<p>Average LoS displacement rates for the period 2015–2020, derived by SNAPPING service on GEP using Sentinel-1 data from descending track 7. White lines (a–e and f–k) correspond to spatial profiles shown in <a href="#applsci-12-09391-f008" class="html-fig">Figure 8</a>. Please note that, for the selected color scale, rates higher than ±4 mm/yr appear saturated to allow for the proper visualization of spatial variability of motion.</p>
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<p>PSI displacement time series for ascending track 102 at the location of high subsidence rates within the basin. The calculated trend (low pass filtering) has been subtracted from observed LoS displacements to obtain the seasonal component. The annual seasonality and linear trend are consistent to water table variations in underground aquifers. Time series has been arbitrarily shifted for visualization purposes.</p>
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<p>Spatial profiles (<b>a</b>–<b>e</b> and <b>f</b>–<b>k</b>) showing LoS displacement rates across major fault zones from both ascending and descending satellite tracks (see <a href="#applsci-12-09391-f006" class="html-fig">Figure 6</a> and <a href="#applsci-12-09391-f007" class="html-fig">Figure 7</a>). For the calculations, average motion grids of 100 m spacing were used. Bars indicate the variability of motion within a buffer of 1–2 km, whereas dots the average calculated rates along the profiles.</p>
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11 pages, 4607 KiB  
Article
Design and Synthesis of 3D-Graphene@C/Co@N-C Composites with Broadband Microwave Absorption Performance
by Songyan Li, Xiaoxia Tian, Jiafu Wang and Shaobo Qu
Appl. Sci. 2022, 12(18), 9390; https://doi.org/10.3390/app12189390 - 19 Sep 2022
Cited by 1 | Viewed by 1652
Abstract
Improving the microwave absorption performance of Co-MOF-derived Co@N-C composite by constructing the morphology and spatial structure is a known challenge. In this work, under the action of the binder polyvinylpyrrolidone, 3D-graphene particles can be well decorated on the surface of the Co@N-C composite [...] Read more.
Improving the microwave absorption performance of Co-MOF-derived Co@N-C composite by constructing the morphology and spatial structure is a known challenge. In this work, under the action of the binder polyvinylpyrrolidone, 3D-graphene particles can be well decorated on the surface of the Co@N-C composite after high-temperature pyrolysis. In addition, due to the structural characteristics of MOFs, Co particles can be well covered by a carbon layer, which effectively solves the problem that magnetic metal particles are prone to corrosion and oxidation. The microwave absorption performances of the composite can be well adjusted by changing the average dotted density of the 3D-graphene on the Co@N-C composite. It is worth noting that the maximum reflection loss can reach −58.72 dB at the thickness of 1.64 mm, and the maximum effective absorption bandwidth can achieve 5.74 GHz at the 1.79 mm thickness, which almost covers the whole Ku band. Importantly, these results demonstrate that 3D-graphene@C/Co@N-C composites have great potential as high-efficiency microwave absorption materials. Full article
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<p>The SEM images of all composites. (<b>a</b>) The SEM image of CNC; (<b>b</b>) The SEM image of CNCG-1; (<b>c</b>) The SEM image of CNCG-2; (<b>d</b>) The SEM image of CNCG-3.</p>
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<p>The HR-TEM image of CNC.</p>
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<p>The XRD patterns and Raman spectra of all composites. (<b>a</b>) The XRD patterns of all composites; (<b>b</b>) The Raman spectra of all composites.</p>
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<p>The room-temperature hysteresis loops of all composites.</p>
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<p>The Raman spectra of CNCG-2. (<b>a</b>) The XPS spectrum of CNCG-2; (<b>b</b>) The Co 2p spectrum of CNCG-2; (<b>c</b>) The C 1s spectrum of CNCG-2; (<b>d</b>) The N 1s spectrum of CNCG-2.</p>
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<p>The electromagnetic parameters of all composites. (<b>a</b>) The <math display="inline"><semantics> <msup> <mi>ε</mi> <mo>′</mo> </msup> </semantics></math> of all composites; (<b>b</b>) The <math display="inline"><semantics> <mrow> <msup> <mi>ε</mi> <mo>″</mo> </msup> </mrow> </semantics></math> of all composites; (<b>c</b>) The <math display="inline"><semantics> <msup> <mi>μ</mi> <mo>′</mo> </msup> </semantics></math> of all composites; (<b>d</b>) The <math display="inline"><semantics> <mrow> <msup> <mi>μ</mi> <mo>″</mo> </msup> </mrow> </semantics></math> of all composites; (<b>e</b>) The <math display="inline"><semantics> <mrow> <mi>tan</mi> <mo> </mo> <msub> <mi>δ</mi> <mi>ε</mi> </msub> </mrow> </semantics></math> of all composites; (<b>f</b>) The <math display="inline"><semantics> <mrow> <mi>tan</mi> <mo> </mo> <msub> <mi>δ</mi> <mi>μ</mi> </msub> </mrow> </semantics></math> of all composites.</p>
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<p>The reflection loss curves of all composites. (<b>a</b>) The reflection loss curve of CNC; (<b>b</b>) The reflection loss curve of CNCG-1; (<b>c</b>) The reflection loss curve of CNCG-2; (<b>d</b>) The reflection loss curve of CNCG-3.</p>
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<p>The <math display="inline"><semantics> <mrow> <msup> <mi>ε</mi> <mo>′</mo> </msup> <mo>−</mo> <msup> <mi>ε</mi> <mrow> <mrow> <mo>″</mo> </mrow> </mrow> </msup> </mrow> </semantics></math> curves of all composites. (<b>a</b>) The <math display="inline"><semantics> <mrow> <msup> <mi>ε</mi> <mo>′</mo> </msup> <mo>−</mo> <msup> <mi>ε</mi> <mrow> <mrow> <mo>″</mo> </mrow> </mrow> </msup> </mrow> </semantics></math> curve of CNC; (<b>b</b>) The <math display="inline"><semantics> <mrow> <msup> <mi>ε</mi> <mo>′</mo> </msup> <mo>−</mo> <msup> <mi>ε</mi> <mrow> <mrow> <mo>″</mo> </mrow> </mrow> </msup> </mrow> </semantics></math> curve of CNCG-1; (<b>c</b>) The <math display="inline"><semantics> <mrow> <msup> <mi>ε</mi> <mo>′</mo> </msup> <mo>−</mo> <msup> <mi>ε</mi> <mrow> <mrow> <mo>″</mo> </mrow> </mrow> </msup> </mrow> </semantics></math> curve of CNCG-2; (<b>d</b>) The <math display="inline"><semantics> <mrow> <msup> <mi>ε</mi> <mo>′</mo> </msup> <mo>−</mo> <msup> <mi>ε</mi> <mrow> <mrow> <mo>″</mo> </mrow> </mrow> </msup> </mrow> </semantics></math> curve of CNCG-3.</p>
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<p>The <math display="inline"><semantics> <mrow> <msub> <mi>C</mi> <mn>0</mn> </msub> </mrow> </semantics></math> curves of all composites.</p>
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<p>The <math display="inline"><semantics> <mi>α</mi> </semantics></math> curve and <math display="inline"><semantics> <mrow> <mfenced close="|" open="|"> <mrow> <msub> <mi>Z</mi> <mrow> <mi>in</mi> </mrow> </msub> <mo>/</mo> <msub> <mi>Z</mi> <mn>0</mn> </msub> </mrow> </mfenced> </mrow> </semantics></math> curve of CNCG. (<b>a</b>) The <math display="inline"><semantics> <mi>α</mi> </semantics></math> curve of CNCG; (<b>b</b>) The <math display="inline"><semantics> <mrow> <mfenced close="|" open="|"> <mrow> <msub> <mi>Z</mi> <mrow> <mi>in</mi> </mrow> </msub> <mo>/</mo> <msub> <mi>Z</mi> <mn>0</mn> </msub> </mrow> </mfenced> </mrow> </semantics></math> curve of CNCG.</p>
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16 pages, 2491 KiB  
Article
AdaCB: An Adaptive Gradient Method with Convergence Range Bound of Learning Rate
by Xuanzhi Liao, Shahnorbanun Sahran, Azizi Abdullah and Syaimak Abdul Shukor
Appl. Sci. 2022, 12(18), 9389; https://doi.org/10.3390/app12189389 - 19 Sep 2022
Viewed by 2265
Abstract
Adaptive gradient descent methods such as Adam, RMSprop, and AdaGrad achieve great success in training deep learning models. These methods adaptively change the learning rates, resulting in a faster convergence speed. Recent studies have shown their problems include extreme learning rates, non-convergence issues, [...] Read more.
Adaptive gradient descent methods such as Adam, RMSprop, and AdaGrad achieve great success in training deep learning models. These methods adaptively change the learning rates, resulting in a faster convergence speed. Recent studies have shown their problems include extreme learning rates, non-convergence issues, as well as poor generalization. Some enhanced variants have been proposed, such as AMSGrad, and AdaBound. However, the performances of these alternatives are controversial and some drawbacks still occur. In this work, we proposed an optimizer called AdaCB, which limits the learning rates of Adam in a convergence range bound. The bound range is determined by the LR test, and then two bound functions are designed to constrain Adam, and two bound functions tend to a constant value. To evaluate our method, we carry out experiments on the image classification task, three models including Smallnet, Network IN Network, and Resnet are trained on CIFAR10 and CIFAR100 datasets. Experimental results show that our method outperforms other optimizers on CIFAR10 and CIFAR100 datasets with accuracies of (82.76%, 53.29%), (86.24%, 60.19%), and (83.24%, 55.04%) on Smallnet, Network IN Network and Resnet, respectively. The results also indicate that our method maintains a faster learning speed, like adaptive gradient methods, in the early stage and achieves considerable accuracy, like SGD (M), at the end. Full article
(This article belongs to the Special Issue AI-Based Image Processing)
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<p>The curve of loss functions by learning rate range test on the CIFAR10 dataset (Smallnet). The <span class="html-italic">x</span>-axis is learning rate, and the <span class="html-italic">y</span>-axis is training loss.</p>
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<p>The learning curve of testing accuracy on CIFAR10 under Smallnet.</p>
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<p>The learning curve of testing accuracy on CIFAR100 under Smallnet.</p>
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<p>The learning curve of testing accuracy on CIFAR10 under NIN.</p>
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<p>The learning curve of testing accuracy on CIFAR100 under NIN.</p>
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<p>The learning curve of testing accuracy on CIFAR10 under Resnet18.</p>
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<p>The learning curve of testing accuracy on CIFAR100 under Resnet18.</p>
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17 pages, 3224 KiB  
Article
Evading Logits-Based Detections to Audio Adversarial Examples by Logits-Traction Attack
by Songshen Han, Kaiyong Xu, Songhui Guo, Miao Yu and Bo Yang
Appl. Sci. 2022, 12(18), 9388; https://doi.org/10.3390/app12189388 - 19 Sep 2022
Cited by 2 | Viewed by 1560
Abstract
Automatic Speech Recognition (ASR) provides a new way of human-computer interaction. However, it is vulnerable to adversarial examples, which are obtained by deliberately adding perturbations to the original audios. Thorough studies on the universal feature of adversarial examples are essential to prevent potential [...] Read more.
Automatic Speech Recognition (ASR) provides a new way of human-computer interaction. However, it is vulnerable to adversarial examples, which are obtained by deliberately adding perturbations to the original audios. Thorough studies on the universal feature of adversarial examples are essential to prevent potential attacks. Previous research has shown classic adversarial examples have different logits distribution compared to normal speech. This paper proposes a logit-traction attack to eliminate this difference at the statistical level. Experiments on the LibriSpeech dataset show that the proposed attack reduces the accuracy of the LOGITS NOISE detection to 52.1%. To further verify the effectiveness of this approach in attacking detection based on logits, three different features quantifying the dispersion of logits are constructed in this paper. Furthermore, a richer target sentence is adopted for experiments. The results indicate that these features can detect baseline adversarial examples with an accuracy of about 90% but cannot effectively detect Logits-Traction adversarial examples, proving that Logits-Traction attack can evade the logits-based detection method. Full article
(This article belongs to the Special Issue AI, Machine Learning and Deep Learning in Signal Processing)
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<p>Logits-Traction attack.</p>
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<p>The schematic diagram of sparse logits (<b>a</b>) and dense logits (<b>b</b>).</p>
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<p>Logits of the original speech (<b>a</b>), adversarial example (<b>b</b>) and raw speech signal (<b>c</b>).</p>
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<p>Deployment of the detection system.</p>
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<p>Difference of each frame in Lingvo by five normal speech (<b>a</b>) and C&amp;W adversarial examples (<b>b</b>).</p>
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<p>Logits value statistics in Lingvo.</p>
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<p>Detecting C&amp;W adversarial examples by <math display="inline"><semantics> <mrow> <msup> <mi>σ</mi> <mo>+</mo> </msup> <msup> <mrow/> <mn>2</mn> </msup> </mrow> </semantics></math> feature in Lingvo.</p>
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<p>Detecting LT adversarial examples by <math display="inline"><semantics> <mrow> <msup> <mi>σ</mi> <mo>+</mo> </msup> <msup> <mrow/> <mn>2</mn> </msup> </mrow> </semantics></math> feature in Lingvo.</p>
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18 pages, 5583 KiB  
Article
Study on Spray Characteristics and Breakup Mechanism of an SCR Injector
by Chuanxin Bai, Kai Liu, Tong Zhao and Jinjin Liu
Appl. Sci. 2022, 12(18), 9387; https://doi.org/10.3390/app12189387 - 19 Sep 2022
Cited by 5 | Viewed by 1832
Abstract
Selective catalytic reduction (SCR) is currently one of the most efficient denitration technologies to reduce nitrogen oxide (NOx) emissions of diesel engines. AdBlue (urea water solution, UWS) is the carrier of the reducing agent of SCR, and the spray process of [...] Read more.
Selective catalytic reduction (SCR) is currently one of the most efficient denitration technologies to reduce nitrogen oxide (NOx) emissions of diesel engines. AdBlue (urea water solution, UWS) is the carrier of the reducing agent of SCR, and the spray process of UWS is one of the critical factors affecting denitration efficiency. In this paper, a non-air-assisted pressure-driven full process spray (NPFPS) model is proposed to illustrate the breakup mechanism and the spray distribution properties of UWS through computational fluid dynamics (CFD). In the NPFPS model, the mechanism of the primary breakup is described by the volume of fluid (VOF) approach, which realizes the quantitative study of the critical parameters determining spray characteristics such as the breakup length, inclination angle, droplet size of the primary breakup, and primary velocity. The distribution of the spray after the primary breakup is depicted by the discrete phase model (DPM) coupled with the Taylor analogy breakup (TAB) model, through which the degree of secondary breakup can be obtained including quantitative studies of the droplet size distribution and velocity distribution in the different cross-sections. To verify the accuracy and feasibility of the NPFPS model, the experimental data are employed to compare with the simulation data. The results are in good agreement, which indicate the practical value of the model. Full article
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<p>(<b>a</b>) Diagram of non-air-assisted injector structure and flow field of primary breakup. (<b>b</b>) Computational mesh and boundary conditions of primary breakup.</p>
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<p>(<b>a</b>) Cutaway view of the droplet development fluid domain. (<b>b</b>) Computational mesh and boundary conditions of droplet development process.</p>
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<p>Displacement curve of the needle valve.</p>
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<p>Development of the primary breakup at different times: (<b>a</b>) 0.5 ms; (<b>b</b>) 1 ms; (<b>c</b>) 1.5 ms; (<b>d</b>) 2 ms; (<b>e</b>) 2.5 ms; (<b>f</b>) 3 ms.</p>
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<p>Development of the primary breakup at different times: (<b>a</b>) 0.5 ms; (<b>b</b>) 1 ms; (<b>c</b>) 1.5 ms; (<b>d</b>) 2 ms; (<b>e</b>) 2.5 ms; (<b>f</b>) 3 ms.</p>
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<p>Initial radial velocity of the jet versus time.</p>
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<p>Jet breakup regimes.</p>
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<p>Comparison of simulated mean breakup length with empirical curve.</p>
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<p>Jet inclination angle: (<b>a</b>) simulation result; (<b>b</b>) experiment result [<a href="#B15-applsci-12-09387" class="html-bibr">15</a>]; (<b>c</b>) cause of jet inclination angle.</p>
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<p>Droplet: (<b>a</b>) diameter distribution; (<b>b</b>) aerodynamic Weber number distribution; (<b>c</b>) velocity distribution.</p>
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<p>Comparison of droplet size distributions between the simulation and experiment.</p>
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<p>Comparison of droplet size distribution at different distances from nozzle exits.</p>
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<p>Droplet radial velocity distribution at 30 mm from the nozzle exits.</p>
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<p>Droplet axial velocity distribution at 30 mm from the nozzle exits.</p>
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20 pages, 11008 KiB  
Article
Investigating the Energy-Efficient Structures Using Building Energy Performance Simulations: A Case Study
by Safeer Abbas, Omer Saleem, Mujasim Ali Rizvi, Syed Minhaj Saleem Kazmi, Muhammad Junaid Munir and Shahid Ali
Appl. Sci. 2022, 12(18), 9386; https://doi.org/10.3390/app12189386 - 19 Sep 2022
Cited by 6 | Viewed by 3110
Abstract
The use of energy efficient structures in the local construction industry assists in promoting green building concepts, leading to economical and eco-friendly solutions for self-sustained structures. The main aim of this study was to examine and compare the energy performance of various local [...] Read more.
The use of energy efficient structures in the local construction industry assists in promoting green building concepts, leading to economical and eco-friendly solutions for self-sustained structures. The main aim of this study was to examine and compare the energy performance of various local buildings. Detailed 3D building models (house, office, and warehouse buildings) were constructed and investigated for their cost and energy savings using building energy simulation tools (green building studio and insight). Moreover, the effects of various building materials for walls, window panels, and roof construction were explored, and a life-cycle cost analysis was performed. It was observed that the effect of the window-to-wall ratio was less severe in term of energy use in office buildings compared to normal houses due to the larger amount of space available for air circulation. Furthermore, the most efficient location for windows was found to be at the middle of the wall in comparison with the top and bottom positions. The effect of the orientation mainly depended on the symmetry of the building. More symmetric buildings, i.e., tested warehouse buildings (rectangular structure), showed an energy use difference of around 7 MJ/m2/year for a 360° orientation change. Tested house buildings exhibited an energy use difference of up to 25 MJ/m2/year. Three-pane glass windows also showed major improvements, and the total energy consumption for houses was reduced to 14%. Furthermore, wood walls showed comparable energy performance with brick walls without the use of insulation. According to US-LEED guidelines, the tested house, office, and warehouse buildings achieved 79, 89, and 88 points, respectively. The cost recovery period for house, office, and warehouse buildings was estimated to 54, 13, and 14 years, respectively, including running and maintenance costs. It can be argued that the Insight and Green Building Studio packages can assist construction stakeholders to determine the energy efficiency of the modeled building as well as to help in the selection of materials for optimized and improved design. Full article
(This article belongs to the Section Civil Engineering)
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<p>Model of the case study buildings: (<b>a</b>) House; (<b>b</b>) Office; (<b>c</b>) Warehouse.</p>
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<p>Different types of walls for office and warehouse buildings. (<b>a</b>) WO2: Masonry wall with insulation; (<b>b</b>) WO3: Wood wall without insulation; (<b>c</b>) WO4: Wood wall with insulation; (<b>d</b>) WO5: Straw bale wall; (<b>e</b>) WO6: Structurally insulated panel; (<b>f</b>) WO8: Insulated concrete foam; (<b>g</b>) WH1: Metal frame wall without insulation; (<b>h</b>) WH2: Metal frame wall with insulation.</p>
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<p>Different types of roof materials for office and warehouse buildings. (<b>a</b>) RO1; (<b>b</b>) RO2; (<b>c</b>) RO4; (<b>d</b>) RO5; (<b>e</b>) RW5; (<b>f</b>) RW6.</p>
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<p>Flowchart of adopted methodology.</p>
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<p>Insight energy analysis for house building. (<b>a</b>) Cooling load analysis; (<b>b</b>) Heating load analysis.</p>
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<p>Insight energy analysis for office building. (<b>a</b>) Cooling load analysis; (<b>b</b>) Heating load analysis.</p>
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<p>Effect of window material on energy use in tested house building. (<b>a</b>) Energy use; (<b>b</b>) Efficiency.</p>
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<p>Effect of window material on energy use in tested office building. (<b>a</b>) Energy use; (<b>b</b>) Efficiency.</p>
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<p>Effect of wall materials on energy use in tested house building. (<b>a</b>) Energy use; (<b>b</b>) Efficiency.</p>
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<p>Effect of wall materials on energy use in tested office building. (<b>a</b>) Energy use; (<b>b</b>) Efficiency.</p>
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<p>Effect of wall materials on energy use in tested warehouse building. (<b>a</b>) Energy use; (<b>b</b>) Efficiency.</p>
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<p>Effect of roof materials on energy use in tested house building. (<b>a</b>) Energy use; (<b>b</b>) Efficiency.</p>
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<p>Effect of roof materials on energy use in office building. (<b>a</b>) Energy use; (<b>b</b>) Efficiency.</p>
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<p>Effect of roof materials on energy use in tested warehouse building. (<b>a</b>) Energy use; (<b>b</b>) Efficiency.</p>
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<p>Effect of window position on energy use in tested house building. (<b>a</b>) Energy use; (<b>b</b>) Efficiency.</p>
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<p>Effect of window position on energy use in tested office building. (<b>a</b>) Energy use; (<b>b</b>) Efficiency.</p>
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<p>Effect of W/W ratio in energy use in tested house. (<b>a</b>) Energy use; (<b>b</b>) Efficiency.</p>
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<p>Effect of W/W ratio in energy use in tested office building. (<b>a</b>) Energy use; (<b>b</b>) Efficiency.</p>
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<p>Effect of building orientation in energy use. (<b>a</b>) House; (<b>b</b>) Office; (<b>c</b>) Warehouse.</p>
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13 pages, 2236 KiB  
Article
Three-Dimensional Change of Lip after Two-Jaw Surgery in Facial Asymmetry Using Facial Scanner
by Young-Jae Kim, Sung-Hwan Choi, Yoon Jeong Choi, Kee-Joon Lee, Sang-Hwy Lee and Hyung-Seog Yu
Appl. Sci. 2022, 12(18), 9385; https://doi.org/10.3390/app12189385 - 19 Sep 2022
Viewed by 2349
Abstract
A facial scanner and three-dimensional computed tomography (CT) were used to evaluate the three-dimensional change in lip asymmetry before and after two-jaw surgery for 22 patients with facial asymmetry (menton deviation > 3 mm). We used the labrale superius (Ls), deviated/non-deviated-side cheilions (Ch-D/Ch-ND), [...] Read more.
A facial scanner and three-dimensional computed tomography (CT) were used to evaluate the three-dimensional change in lip asymmetry before and after two-jaw surgery for 22 patients with facial asymmetry (menton deviation > 3 mm). We used the labrale superius (Ls), deviated/non-deviated-side cheilions (Ch-D/Ch-ND), and labrale inferius (Li) to construct the upper and lower lip planes to evaluate the lip asymmetry. A correlation analysis was performed to determine the factors related to the vertical change in the cheilions (ΔChZ-D/ND). In the transverse axis, Ch-D and Li moved to improve the asymmetry after surgery. All landmarks, except the Ls, moved backward in the anteroposterior axis. In the vertical axis, significant upward movement was observed in all hard tissue landmarks; however, there were no significant changes in the soft tissue. In the lip plane, the difference in the height of Ch-D and Ch-ND was significantly reduced (1.38 mm vs. 0.72 mm). In the anteroposterior axis, the ΔChZ-D/ND showed significant correlations with the mandibular setback. In the vertical axis, the ΔCh-ND showed significant correlations with the maxillary impaction of the non-deviated side. The improvement in lip asymmetry post-surgery was mainly achieved by the movement of the lower lip and Ch-D rather than the upper lip and Ch-ND. Full article
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<p>Registration of preoperative (T1) CT and FS images. The references used for superimposition were the forehead and the dorsum of the nose area (blue color), exocanthions, endocanthions, and nasal alas: N’, soft tissue nasion; Ex, exocanthion; En, endocanthion; Al, nasal ala; CT, computed tomography; and FS, facial scanner.</p>
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<p>Superimposition of preoperative (T1) and postoperative (T2) images of the facial scanner. The references used for superimposition were the forehead and nasal bridge area (blue color), exocanthions, endocanthions, and nasal alas. (<b>A</b>) Preoperative FS image, (<b>B</b>) postoperative FS image, and (<b>C</b>,<b>D</b>) superimposed images. N’, soft tissue nasion; Ex, exocanthion; En, endocanthion; and Al, nasal ala.</p>
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<p>Hard tissue and soft tissue landmarks used in this study. MSP, midsagittal plane; U3-D/ND, maxillary canine cusp tip on the deviated side/non-deviated side; U6-D/ND, maxillary 1st molar mesiobuccal cusp tip on the deviated side/non-deviated side; Mf-D/ND, mental foramen on the deviated side/non-deviated side; Me, menton; Ls, labrale superius; Li, labrale inferius; and Ch-D/ND, cheilion on the deviated side/non-deviated side.</p>
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<p>Changes in the upper and lower lip planes. The upper lip plane was established by connecting both sides of the Ch and Ls. The lower lip planes were also established by connecting both sides of the Ch and Li. (<b>A</b>–<b>C</b>) The lip planes on the FS images, (<b>D</b>) The coronal view of the lip planes, (<b>E</b>) The sagittal view of the lip planes, (<b>F</b>) The axial view of the upper lip plane, (<b>G</b>) The axial view of the lower lip plane. Green arrows indicate significant changes in the landmarks. MSP, midsagittal plane; FH, Frankfort horizontal plane; Ls, labrale superius; Ch-D/ND, cheilion on deviated side/non-deviated side; Li, labrale inferius; and Ls, labrale superius.</p>
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<p>Schematic diagram of the upper and lower lip planes. (<b>A</b>) The coronal view of schematic diagram, (<b>B</b>) The axial view of schematic diagram. Abbreviations: MSP, midsagittal plane; FH, Frankfort horizontal plane; Ls, labrale superius; Ch-D/ND, cheilion on the deviated side/non-deviated side; Li, labrale inferius; b − a, transverse lip asymmetry; a + b, lip width; c, vertical lip asymmetry; and d, anteroposterior lip asymmetry.</p>
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15 pages, 2054 KiB  
Article
Applications of Metaheuristics Inspired by Nature in a Specific Optimisation Problem of a Postal Distribution Sector
by Michał Berliński, Eryk Warchulski and Stanisław Kozdrowski
Appl. Sci. 2022, 12(18), 9384; https://doi.org/10.3390/app12189384 - 19 Sep 2022
Cited by 3 | Viewed by 1487
Abstract
This paper presents a logistics problem, related to the transport of goods, which can be applied in practice, for example, in postal or courier services. Two mathematical models are presented as problems occurring in a logistics network. The main objective of the optimisation [...] Read more.
This paper presents a logistics problem, related to the transport of goods, which can be applied in practice, for example, in postal or courier services. Two mathematical models are presented as problems occurring in a logistics network. The main objective of the optimisation problem presented is to minimise capital resources (Capex), such as cars or containers. Three methods are proposed to solve this problem. The first is a method based on mixed integer programming (MIP) and available through the CPLEX solver. This method is the reference method for us because, as an exact method, it is guaranteed to find the optimal solution as long as the problem is not too large. However, the logistic problem under consideration belongs to the class of NP-complete problems and therefore, for larger problems, i.e., for networks of large size, the MIP method does not find any integer solution in a reasonable computational time. Therefore, two nature-inspired heuristic methods have been proposed. The first is the evolutionary algorithm and the second is the artificial bee colony algorithm. Results indicate that the heuristics methods solve instances of large size, giving suboptimal solutions and therefore, enabling their application to real-life scenarios. Full article
(This article belongs to the Special Issue Metaheuristics for Real-World Optimization Problems)
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<p>Convergence curves plotted for the algorithms considered, for a logistic network of different sizes, for the BLP model. Each curve is an average of 20 independent runs. (<b>a</b>) 5-node. (<b>b</b>) 10-node. (<b>c</b>) 15-node. (<b>d</b>) 20-node. (<b>e</b>) 25-node. (<b>f</b>) 30-node.</p>
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<p>Convergence curves plotted for the algorithms considered, for a logistic network of different sizes, for the BLP model. Each curve is an average of 20 independent runs. (<b>a</b>) 5-node. (<b>b</b>) 10-node. (<b>c</b>) 15-node. (<b>d</b>) 20-node. (<b>e</b>) 25-node. (<b>f</b>) 30-node.</p>
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<p>Convergence curves plotted for the algorithms considered, for a logistic network of different sizes, for the ELP model. Each curve is an average of 20 independent runs. (<b>a</b>) 5-node. (<b>b</b>) 10-node. (<b>c</b>) 15-node. (<b>d</b>) 20-node. (<b>e</b>) 25-node. (<b>f</b>) 30-node.</p>
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<p>Convergence curves plotted for the algorithms considered, for a logistic network of different sizes, for the ELP model. Each curve is an average of 20 independent runs. (<b>a</b>) 5-node. (<b>b</b>) 10-node. (<b>c</b>) 15-node. (<b>d</b>) 20-node. (<b>e</b>) 25-node. (<b>f</b>) 30-node.</p>
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<p>Box plot of calculation time for heuristic methods for the BLP—(<b>a</b>) and ELP models—(<b>b</b>) model.</p>
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15 pages, 2859 KiB  
Article
A Partial Multiplicative Dimensional Reduction-Based Reliability Estimation Method for Probabilistic and Non-Probabilistic Hybrid Structural Systems
by Xuyong Chen, Yuanlin Peng, Zhifeng Xu and Qiaoyun Wu
Appl. Sci. 2022, 12(18), 9383; https://doi.org/10.3390/app12189383 - 19 Sep 2022
Viewed by 1544
Abstract
A new reliability estimation method based on partial multiplicative dimensional reduction is proposed for probabilistic and non-probabilistic hybrid structural systems. The proposed method is characterized by decorrelating interval input variables from random input variables using the partial multiplicative dimensional reduction method in conjunction [...] Read more.
A new reliability estimation method based on partial multiplicative dimensional reduction is proposed for probabilistic and non-probabilistic hybrid structural systems. The proposed method is characterized by decorrelating interval input variables from random input variables using the partial multiplicative dimensional reduction method in conjunction with the weakest-link theory. In this method, the failure statistics of the original performance function are equivalent to a statical chain of two elements, in which one of the two elements represents the failures due to random input variables and the other represents the failures due to interval variables. Rather than yielding an estimated interval of failure probability, the proposed method produces a single value for failure probability, which is more meaningful for engineering. In addition, the accuracy, validity, and superiority of the proposed method are demonstrated, and the error-related properties of the proposed method are investigated. Full article
(This article belongs to the Special Issue Soft Computing Application to Engineering Design)
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<p>Conceptional illustration of the proposed method.</p>
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<p>Flowchart of safety state determination.</p>
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<p>The flow chart of reliability estimation.</p>
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<p>Configuration of the cantilever beam.</p>
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<p>Comparison between the original function and the approximation obtained by the proposed method.</p>
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<p>Error histogram of the proposed method.</p>
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<p>Configuration of roof truss.</p>
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<p>Absolute error vs. failure probability.</p>
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<p>The finite element model of a plate arch bridge.</p>
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19 pages, 6236 KiB  
Article
Influence of FK209 Cobalt Doped Electron Transport Layer in Cesium Based Perovskite Solar Cells
by Ahmed Hayali, Roger J. Reeves and Maan M. Alkaisi
Appl. Sci. 2022, 12(18), 9382; https://doi.org/10.3390/app12189382 - 19 Sep 2022
Viewed by 1963
Abstract
The efficiency and stability of perovskite solar cells (PSCs) depend not only on the perovskite film quality, but they are also influenced by the charge carriers of both the electron and hole transport layers (ETL and HTL). Doping of the carrier transport layers [...] Read more.
The efficiency and stability of perovskite solar cells (PSCs) depend not only on the perovskite film quality, but they are also influenced by the charge carriers of both the electron and hole transport layers (ETL and HTL). Doping of the carrier transport layers is considered one of effective technique applied to enhance the efficiency and performance of the PSCs. FK209 cobalt TFSI and lithium TFSI salt were investigated as dopants for mesoporous TiO2 (M-TiO2) in the ETL. Herein, FK209 cobalt doping offers improved conductivity, reproducibility and stability compared to other doping or undoped M-TiO2 control device. It has been found that an optimum concentration of 2.5 mg FK209 cobalt in the M-TiO2 has resulted in an efficiency of 15.6% on 0.36 cm2 active device area, whereas, the undoped M-TiO2 yielded an average efficiency of 10.8%. The enhanced efficiency is due to the improved conductivity of the ETL while maintaining high transparency and low surface roughness with FK209 doping. The M-TiO2 doped with FK209 has a transparency of the 90% over the visible range and its measured energy gap was 3.59 eV. Perovskite films deposited on the M-TiO2 doped with FK209 has also a lower PL intensity indicating faster charge extraction. The measured lifetime of the perovskite films deposited on the optimised M-TiO2 film was 115.8 ns. Full article
(This article belongs to the Special Issue Selected Papers from ICAET 2022)
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<p>Left, AFM images of the surface morphology structure and roughness of the (<b>a</b>) undoped mesoporous TiO<sub>2</sub>, RMS = 34.5 nm; (<b>b</b>) M-TiO<sub>2</sub> doped with FK209, RMS = 16 nm; (<b>c</b>) FK209/Li<sup>+</sup>, RMS = 22.75 nm; (<b>d</b>) Li<sup>+</sup>, RMS = 25.46 nm. Right, contact angle measurement of (<b>a</b>) undoped M-TiO<sub>2</sub>, ɵ = 14°; (<b>b</b>) M-TiO<sub>2</sub> doped with FK209, ɵ = 4.2°; (<b>c</b>) FK209/Li<sup>+</sup>, ɵ = 9°; (<b>d</b>) Li<sup>+</sup>, ɵ = 13°.</p>
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<p>Left, SEM images of surface topography of the perovskite layer deposited on the (<b>a</b>) undoped M-TiO<sub>2</sub> and mesoporous TiO<sub>2</sub> doped with (<b>b</b>) FK209, (<b>c</b>) FK209/Li<sup>+</sup> and (<b>d</b>) Li<sup>+</sup>. Right, the histogram shows an average grains size for (<b>a</b>) undoped M-TiO<sub>2</sub>, 163.9 nm; (<b>b</b>) M-TiO<sub>2</sub> doped with FK209, 242 nm; (<b>c</b>) FK209/Li<sup>+</sup>, 210 nm; (<b>d</b>) Li<sup>+</sup>, 205 nm.</p>
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<p>Left, SEM images of surface topography of the perovskite layer deposited on the (<b>a</b>) undoped M-TiO<sub>2</sub> and mesoporous TiO<sub>2</sub> doped with (<b>b</b>) FK209, (<b>c</b>) FK209/Li<sup>+</sup> and (<b>d</b>) Li<sup>+</sup>. Right, the histogram shows an average grains size for (<b>a</b>) undoped M-TiO<sub>2</sub>, 163.9 nm; (<b>b</b>) M-TiO<sub>2</sub> doped with FK209, 242 nm; (<b>c</b>) FK209/Li<sup>+</sup>, 210 nm; (<b>d</b>) Li<sup>+</sup>, 205 nm.</p>
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<p>Optical transparency properties of mesoporous TiO<sub>2</sub> doped with FK209, FK209 /Li<sup>+</sup>, and Li<sup>+</sup>.</p>
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<p>Optical absorbance properties of mesoporous TiO<sub>2</sub> doped with FK209, FK209 /Li<sup>+</sup>, and Li<sup>+</sup>.</p>
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<p>Extrapolation of the energy gap of M-TiO<sub>2</sub> doped with FK209, FK209 /Li<sup>+</sup>, and Li<sup>+</sup>, using Tauc plot.</p>
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<p>Absorption of perovskite film deposited on M-TiO<sub>2</sub> doped with FK209, FK209/Li<sup>+</sup> and lithium.</p>
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<p>Energy gap of perovskite films deposited on M-TiO<sub>2</sub> doped with FK209, FK209/Li<sup>+</sup> and lithium, using Tauc plot.</p>
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<p>Photoluminescence spectra of perovskite films deposited on M-TiO<sub>2</sub> doped with FK209, FK209/Li<sup>+</sup> and lithium.</p>
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<p>Photoluminescence decay time of perovskite deposited on M-TiO<sub>2</sub> doped with FK209, FK209/lithium and lithium and measured using fluorescence PL decay lifetime.</p>
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<p>Left, schematic structure of the perovskite solar cell. Right, photograph of 2.5 × 2.5 cm<sup>2</sup> PSC fabricated in this study.</p>
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<p>An SEM image of the cross-section of the perovskite solar cell device fabricated in this study showing the different layers.</p>
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<p>The illuminated J-V characteristic curves of perovskite solar cells deposited on ETL of M-TiO<sub>2</sub> doped with FK209, FK209/Li<sup>+</sup> and lithium.</p>
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<p>Transparency of the M-TiO<sub>2</sub> doped with 1.5-mg, 2.5-mg and 5-mg concentrations of FK209 cobalt.</p>
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<p>Absorbance spectrum of the M-TiO<sub>2</sub> doped with 1.5-mg, 2.5-mg and 5-mg concentrations of FK209 cobalt.</p>
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<p>Energy gap of M-TiO<sub>2</sub> doped with various concentrations of FK209 (1.5 mg, 2.5 mg and 5 mg) using Tauc plot. Dotted lines represent the tangent to the slope for each plot.</p>
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<p>Statistical histogram of the PCE measured over 30 fabricated solar cells. The ETL was fabricated using C-TiO<sub>2</sub> prepared using DC-sputtering and M-TiO<sub>2</sub> doped with various concentrations of FK209.</p>
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<p>Device stability testing by measuring variations in the efficiency of the perovskite solar cells measured over 40 weeks period in weekly intervals. Devices were kept in ambient laboratory and tested under AM1.5, 100 mW/cm<sup>2</sup> illumination using ABET sunlight simulators with reference cell as a control.</p>
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27 pages, 9180 KiB  
Article
Design and Implementation of Cloud-Based Collaborative Manufacturing Execution System in the Korean Fashion Industry
by Minjae Ko, Changho Lee and Yongju Cho
Appl. Sci. 2022, 12(18), 9381; https://doi.org/10.3390/app12189381 - 19 Sep 2022
Cited by 6 | Viewed by 4175
Abstract
Recently, manufacturing companies have been improving quality and productivity, reducing costs, and producing customized products according to Industry 4.0. The global value chain (GVC) is also being reorganized and manufacturing companies are recovering the connectivity of value chains based on, e.g., the regional [...] Read more.
Recently, manufacturing companies have been improving quality and productivity, reducing costs, and producing customized products according to Industry 4.0. The global value chain (GVC) is also being reorganized and manufacturing companies are recovering the connectivity of value chains based on, e.g., the regional value chain (RVC) and reshoring. With the advent of Industry 4.0, many manufacturing companies are introducing smart factories. A new type of manufacturing execution system (MES), a core system of smart factories, is necessary, owing to the new technologies and the increase in collaboration between companies. Here, we present the framework, development, and application processes of a “cloud-based collaborative MES System” to support the value chain of “order-design-production-delivery” for the manufacture of personalized sportswear products in the fashion industry in Korea. To this end, first, nine future MES deployment directions and frameworks are presented. Second, we present the UML modeling, conceptual framework, and functional framework for MES system development, considering six future MES establishment directions such as cloud and collaboration. Third, the application and effect of the designed and developed cloud-based collaborative MES system are analyzed for design, fabric, printing, and sewing companies that play a role in each stage of the sportswear value chain. Full article
(This article belongs to the Special Issue Smart Manufacturing Systems in Industry 4.0)
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<p>Changes in manufacturing methods and production systems.</p>
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<p>Future Manufacturing Execution System (MES) development directions.</p>
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<p>Framework for future MES system.</p>
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<p>Value chain for sportswear manufacturing.</p>
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<p>Hub and spoke collaboration model for sportswear manufacturing.</p>
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<p>Analysis of the collaboration form for sportswear manufacturing.</p>
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<p>Detailed manufacturing process of sportswear.</p>
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<p>Component diagram for design of cloud-based collaborative MES.</p>
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<p>Communication diagram for design of cloud-based collaborative MES.</p>
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<p>Activity diagram for design of cloud-based collaborative MES.</p>
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<p>Class diagram for design of cloud-based collaborative MES.</p>
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<p>Conceptual framework for cloud-based collaborative MES.</p>
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<p>Functional framework for cloud-based collaborative MES.</p>
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<p>Status of work by process.</p>
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<p>Online work order sheet.</p>
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<p>Order information recognition using vision system in the cutting process.</p>
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<p>IoT device for sewing machine data collection.</p>
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<p>Management function of collaborative companies in the value chain.</p>
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<p>Confirmation of work orders via mobile system.</p>
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<p>Process work confirmation via mobile system.</p>
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<p>I/F with MES and enterprise resource planning (ERP).</p>
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<p>Analysis of process automation through application of MES system.</p>
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3 pages, 185 KiB  
Editorial
Special Issue on Development and Application of Particle Detectors
by Andrea Giachero and Luca Gironi
Appl. Sci. 2022, 12(18), 9380; https://doi.org/10.3390/app12189380 - 19 Sep 2022
Cited by 1 | Viewed by 1245
Abstract
Particle detection has been increasingly applied over a wide range of disciplines, including high-energy physics, astroparticles, space science and astronomy, biological sciences, medical imaging, remote sensing, environmental monitoring, cultural heritage, and homeland security [...] Full article
(This article belongs to the Special Issue Development and Application of Particle Detectors)
16 pages, 6346 KiB  
Article
Design and Kinematic Analysis of Cable-Driven Target Spray Robot for Citrus Orchards
by Xiulan Bao, Yuxin Niu, Yishu Li, Jincheng Mao, Shanjun Li, Xiaojie Ma, Qilin Yin and Biyu Chen
Appl. Sci. 2022, 12(18), 9379; https://doi.org/10.3390/app12189379 - 19 Sep 2022
Cited by 6 | Viewed by 2007
Abstract
In Southeast Asia, many varieties of citrus are grown in hilly areas. Compared with plain orchards, it is difficult for large spraying equipment to move in hilly orchards. Small spraying equipment can enter hilly orchards, but their spraying power cannot make droplets penetrate [...] Read more.
In Southeast Asia, many varieties of citrus are grown in hilly areas. Compared with plain orchards, it is difficult for large spraying equipment to move in hilly orchards. Small spraying equipment can enter hilly orchards, but their spraying power cannot make droplets penetrate into the canopy, resulting in low deposition rates within the canopy. As a kind of unstructured narrow space, the branches within the canopy are interlaced, thus a flexible manipulator that can move within the canopy is required. In this paper, a novel remote-controlled, cable-driven target spray robot (CDTSR) was designed to achieve a precise spray within the canopy. It consisted of a small tracked vehicle, a cable-driven flexible manipulator (CDFM), and a spray system. The CDFM had six degrees of freedom driven by a cable tendon. The forward and inverse kinematics model of the CDFM were established and then the semispherical workspace was calculated. Furthermore, while considering precise control requirements, the dynamics equations were derived. The experimental results demonstrated that the CFDM could move dexterously within the canopy with interlacing branches to reach pests and diseases areas in the canopy. The entire operation took 3.5 s. This study solved the problem of a low spray deposition rate within a canopy and has potential applications in agricultural plant protection. Full article
(This article belongs to the Special Issue Advances in Robotics and Mechatronics for Agriculture)
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<p>Example of a single dwarf citrus tree.</p>
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<p>(<b>a</b>) The overall model of the CDTSR: (1) nozzle; (2) cable-driven manipulator control box; (3) pesticide box; (4) diaphragm pump; (5) inlet pipe; (6) track vehicle control box; (7) track vehicle; (8) outlet pipe; (9) cable-driven manipulator. (<b>b</b>) CAD drawings with different viewing angles of the CDTSR (the unit is mm).</p>
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<p>(<b>a</b>) The overall model of the CDFM: (1) tendon; (2) support; (3) graphite copper sleeve; (4) shaft; (5) reel; (6) pulley; (7) cooling fan; (8) coupling; (9) stepper motor; (10)flange base; (11) connecting rod; (12) proximal arm segment; (13) distal arm segment; (14) cable locking. (<b>b</b>) CAD drawings with different viewing angles of the CDFM (the unit is mm).</p>
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<p>(<b>a</b>) The model of two adjacent joints and cable rope arrangement on a disc. (<b>b</b>) CAD drawings with different viewing angles of the connecting rod (the unit is mm).</p>
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<p>Multilevel mapping relationship of CDFM.</p>
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<p>The kinematic model of a single joint.</p>
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<p>Static analysis of CDFM.</p>
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<p>The coordinate transformation from base coordinate to end coordinate.</p>
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<p>The prototype of the CDTSR.</p>
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<p>The working space of the CDFM.</p>
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<p>(<b>a</b>) The reachable space and position of the CDFM; (<b>b</b>) dimensions of the model tree.</p>
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<p>The operations in the narrow space between branches: (<b>a</b>) initial state; (<b>b</b>) intermediate state one; (<b>c</b>) intermediate state two; (<b>d</b>) final state.</p>
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<p>The three states of the spray manipulator in spraying operations: (<b>a</b>) initial state of the spray manipulator; (<b>b</b>) spraying state of the spray manipulator for target 1; (<b>c</b>) spraying state of the spray manipulator for target 2.</p>
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<p>The measurement experiment to test the droplet diameter.</p>
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<p>Samples of coverage rates: (<b>a</b>) the coverage rate of the spraying center was 98.4%; (<b>b</b>) the coverage rate of the spraying margin was 64.3%.</p>
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17 pages, 12061 KiB  
Article
Applying Evolutionary Multitasking for Process Parameter Optimization in Polymerization Process of Carbon Fiber Production
by Liang Jin, Zude Zhou, Kunlun Li, Guoliang Zhang, Quan Liu, Bitao Yao and Yilin Fang
Appl. Sci. 2022, 12(18), 9378; https://doi.org/10.3390/app12189378 - 19 Sep 2022
Cited by 4 | Viewed by 1841
Abstract
Carbon fiber is becoming a key material for engineering applications due to its excellent comprehensive properties. The process parameter optimization is an important step in the polymerization process of carbon fiber production. At present, most of the research on process parameter optimization is [...] Read more.
Carbon fiber is becoming a key material for engineering applications due to its excellent comprehensive properties. The process parameter optimization is an important step in the polymerization process of carbon fiber production. At present, most of the research on process parameter optimization is usually carried out on a single production line, without considering the correlation between optimization problems. In this paper, a multiobjective mechanism model for the co-optimization of the polymerization process of carbon fiber production is established. Each of these submodels is a multiobjective process parameter optimization task, corresponding to the polymerization process of a production line. In order to solve the model effectively, we also designed an evolutionary multitasking algorithm based on transfer learning, which reuses the past experiences of one task to generate a population pool for the next iteration of another task, enabling explicit genetic transfer between different tasks and accelerating the population convergence speed. The proposed multitasking framework for operation optimization has been conducted on 10 different production conditions of the polymerization process. Experimental results show that compared with other implicit and explicit genetic algorithms, this algorithm is very competitive in generating effective solutions. This research provides important support for process parameter optimization and manufacturing of carbon fiber production, which will help engineers and technicians to make informed decisions. Full article
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<p>Carbon fiber production flow chart.</p>
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<p>Schematic diagram of polymerization unit.</p>
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<p>Flow chart of the proposed Tr-EGT.</p>
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<p>Average HV numerical curves of NSGA-II, MO-MFEA, EMT-EGT and Tr-EGT over 20 independent runs on task<math display="inline"><semantics> <msub> <mrow/> <mn>1</mn> </msub> </semantics></math>.</p>
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<p>Average HV numerical curves of NSGA-II, MO-MFEA, EMT-EGT and Tr-EGT over 20 independent runs on task<math display="inline"><semantics> <msub> <mrow/> <mn>2</mn> </msub> </semantics></math>.</p>
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<p>The average approximate PF was obtained by the multitask algorithms under Conditions 1, 7, and 8 over 20 runs in task<math display="inline"><semantics> <msub> <mrow/> <mn>1</mn> </msub> </semantics></math> and task<math display="inline"><semantics> <msub> <mrow/> <mn>2</mn> </msub> </semantics></math>.</p>
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18 pages, 4288 KiB  
Article
Improving IoT Data Security and Integrity Using Lightweight Blockchain Dynamic Table
by Saleem S. Hameedi and Oguz Bayat
Appl. Sci. 2022, 12(18), 9377; https://doi.org/10.3390/app12189377 - 19 Sep 2022
Cited by 10 | Viewed by 2892
Abstract
Over the past few years, the Internet of Things (IoT) is one of the most significant technologies ever used, as everything is connected to the Internet. Integrating IoT technologies with the cloud improves the performance, activity, and innovation of such a system. However, [...] Read more.
Over the past few years, the Internet of Things (IoT) is one of the most significant technologies ever used, as everything is connected to the Internet. Integrating IoT technologies with the cloud improves the performance, activity, and innovation of such a system. However, one of the major problems which cannot be ignored in such integration is the security of the data that are transferred between the client (IoT) and the server (cloud). Solving that problem leads to the use the of IoT technologies in more critical applications and fields. This paper proposes a new security framework by combining blockchain technology with the AES algorithm. Blockchain technology is used and modified to protect data integrity and generate unique device identification within minimal power consumption and best performance. The AES algorithm is used to improve the data confidentiality when being transmitted to the server. The outcomes demonstrated that the proposed solution improves the security system of the IoT healthcare data and proved its efficiency and power consumption compared to other methods. Full article
(This article belongs to the Special Issue Advances in Blockchain-enabled Internet of Things (IoT))
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<p>Blockchain architecture.</p>
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<p>Blockchain ledger.</p>
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<p>Dynamic blockchain table architecture.</p>
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<p>Multiple AES encryption architecture.</p>
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<p>Key exchange mechanism.</p>
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<p>Z1 IoT device.</p>
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<p>Time Overhead evaluation.</p>
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<p>Energy consumption overhead (CPU and Tx).</p>
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<p>Energy consumption overhead (Lx).</p>
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<p>Energy consumption overhead (CPU and Tx) of healthcare application.</p>
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<p>Energy consumption overhead (Lx) of healthcare application.</p>
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18 pages, 470 KiB  
Article
Target-Oriented Teaching Path Planning with Deep Reinforcement Learning for Cloud Computing-Assisted Instructions
by Tengjie Yang, Lin Zuo, Xinduoji Yang and Nianbo Liu
Appl. Sci. 2022, 12(18), 9376; https://doi.org/10.3390/app12189376 - 19 Sep 2022
Cited by 1 | Viewed by 1942
Abstract
In recent years, individual learning path planning has become prevalent in online learning systems, while few studies have focused on teaching path planning for traditional classroom teaching. This paper proposes a target-oriented teaching path optimization scheme for cloud computing-assisted instructions, in which a [...] Read more.
In recent years, individual learning path planning has become prevalent in online learning systems, while few studies have focused on teaching path planning for traditional classroom teaching. This paper proposes a target-oriented teaching path optimization scheme for cloud computing-assisted instructions, in which a sequence of learning contents is arranged to ensure the maximum benefit for a given group of students. First, to evaluate the teaching performance, we investigate various student models and define some teaching objectives, including the pass rate, the excellence rate, the average score, and related constraints. Second, a new Deep Reinforcement Learning (DRL)-based teaching path planning method is proposed to tackle the learning path by maximizing a multi-objective target while satisfying all teaching constraints. It adopts a Proximal Policy Optimization (PPO) framework to find a model-free solution for achieving fast convergence and better optimality. Finally, extensive simulations with a variety of commonly used teaching methods show that our scheme provides nice performance and versatility over commonly used student models. Full article
(This article belongs to the Special Issue New Engineering in Cloud Computing and Cloud Data)
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<p>Partially observable Markov decision process [<a href="#B8-applsci-12-09376" class="html-bibr">8</a>].</p>
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<p>(I) The teacher teaches a knowledge point; (II) The students study it with the changes in their student states; (III) The results of in-class and off-class tests for students are observed. During the continuous teaching process, a knowledge point chain, a student state chain, and a student test result chain are formed.</p>
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<p>Clip function.</p>
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<p>PPO: (I) Sampling by actor; (II) the collected data are sampled again and passed to the actor and critic; and (III) updating through the two different loss functions.</p>
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17 pages, 1977 KiB  
Article
Particulate Matter Concentrations and Fungal Aerosol in Horse Stables as Potential Causal Agents in Recurrent Airway Disease in Horses and Human Asthma and Allergies
by Anna Lenart-Boroń, Anna Bajor, Marek Tischner, Klaudia Kulik and Julia Kabacińska
Appl. Sci. 2022, 12(18), 9375; https://doi.org/10.3390/app12189375 - 19 Sep 2022
Cited by 3 | Viewed by 1931
Abstract
Exposure to bioaerosols associated with horse stable indoor environment and their health effects on people and horses has recently become of particular interest. Moreover, increasing frequency of recurrent airway disease (RAO) among horses made it necessary to search for the most probable causal [...] Read more.
Exposure to bioaerosols associated with horse stable indoor environment and their health effects on people and horses has recently become of particular interest. Moreover, increasing frequency of recurrent airway disease (RAO) among horses made it necessary to search for the most probable causal agents of this disease and methods of their eradication. The study was conducted in two horse stables in southern Poland (Kraków and Tarnów). Particulate matter (PM2.5, PM4, and PM10) concentrations were determined photometrically, the concentration of fungal aerosol was determined by a six-stage impactor, and next generation sequencing (NGS) was used to determine fungal community composition in one of these stables. The highest PM concentrations were observed in Tarnów, but fungal aerosol levels were higher in the Kraków stable. Based on the NGS results, the three most prevalent fungal species were Wallemia sebi, Aspergillus penicillioides, and Epicoccum nigrum, all highly allergenic and potentially involved in the occurrence of RAO in horses. Spores of the detected fungi can penetrate deeply into the respiratory system. Therefore, this study suggests that examinations of particulate matter and fungal aerosol concentrations, along with species composition assessment, should be regularly conducted in horse stables. Full article
(This article belongs to the Special Issue Fungi Associated with Indoor Environments and Materials)
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<p>(<b>A</b>). Location and schematic presentation of the Kraków stable. (<b>B</b>). Location and schematic presentation of the Tarnów stable.</p>
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<p>Share (%) of different aerodynamic diameters of airborne fungi in the Kraków (<b>A</b>) and Tarnów (<b>B</b>) horse stables at different times of the day (M—early morning-no activity; F—feeding; I.B.—indoor background, mid-day; A—afternoon, animals return; O.B.—outdoor background).</p>
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<p>Relative abundance (%) of fungal species, the share of which in the total number of reads exceeded 0.2% (<b>A</b>) and 10 most abundant fungal genera in the examined sample (<b>B</b>).</p>
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<p>Concentration of total fungal aerosol (CFU/m<sup>3</sup>) in different times of day compared with the inhalable particulate matter concentration (PM<sub>10</sub>; µg/m<sup>3</sup>). Kraków (<b>A</b>) and Tarnów (<b>B</b>) horse stables.</p>
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<p>Concentration of respirable fungal aerosol (CFU/m<sup>3</sup>) at different times of the day compared with the concentration of respirable particulate matter (µg/m<sup>3</sup>). Kraków (<b>A</b>) and Tarnów (<b>B</b>) horse stables.</p>
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12 pages, 5402 KiB  
Article
Novel Method for Monitoring Mining Subsidence Featuring Co-Registration of UAV LiDAR Data and Photogrammetry
by Jibo Liu, Xiaoyu Liu, Xieyu Lv, Bo Wang and Xugang Lian
Appl. Sci. 2022, 12(18), 9374; https://doi.org/10.3390/app12189374 - 19 Sep 2022
Cited by 9 | Viewed by 2367
Abstract
Addressing the problem that traditional methods cannot reliably monitor surface subsidence in coal mining, a novel method has been developed for monitoring subsidence in mining areas using time series unmanned aerial vehicle (UAV) photogrammetry in combination with LiDAR. A dynamic subsidence basin based [...] Read more.
Addressing the problem that traditional methods cannot reliably monitor surface subsidence in coal mining, a novel method has been developed for monitoring subsidence in mining areas using time series unmanned aerial vehicle (UAV) photogrammetry in combination with LiDAR. A dynamic subsidence basin based on the differential digital elevation model (DEM) was constructed and accuracy of the proposed method was verified, with the uncertainty of the DEM of difference (DoD) being quantified via co-registration of a dense matching point cloud of the time series UAV data. The root mean square error calculated for the monitoring points on the subsidence DEM was typically between 0.2 m and 0.3 m with a minimum of 0.17 m. The relative error between the maximum subsidence value of the extracted profile line on the main section after fitting and the measured maximum subsidence value was not more than 20%, and the minimum value was 0.7%. The accuracy of the UAV based method was at the decimeter level, and high accuracy in monitoring the maximum subsidence value was attained, confirming that an innovative strategy for monitoring mining subsidence was realized. Full article
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<p>Schematic for relationship between the working face, observation stations, and study area.</p>
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<p>The flow chart for subsidence monitoring via UAV.</p>
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<p>Selection of the stable region: (<b>a</b>) stable zone for collaborative registration; and (<b>b</b>) number of overlapping images computed for each pixel of the DOM.</p>
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<p>Histogram of the M3C2 distance: (<b>a</b>) LiDAR01.16−UAV06.14; (<b>b</b>) LiDAR01.16−UAV07.20; (<b>c</b>) LiDAR01.16−UAV09.07; (<b>d</b>) LiDAR01.16−UAV11.15; and (<b>e</b>) LiDAR01.16−UAV07.31.</p>
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<p>Development process for the dynamic subsidence basin at the working face: (<b>a</b>) 1−06.14; (<b>b</b>) 2−07.20; (<b>c</b>) 3−09.07; (<b>d</b>) 4−11.15; (<b>e</b>) 5−07.31; (<b>f</b>) 1−2; (<b>g</b>) 2−3; (<b>h</b>) 3−4; (<b>i</b>) 4−5; (<b>j</b>) 1−2; (<b>k</b>) 1−3; (<b>l</b>) 1−4; and (<b>m</b>) 1−5.</p>
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<p>Comparison of subsidence values about the monitoring points: (<b>a</b>) line A 07.20−06.14; (<b>b</b>) line A 09.07−06.14; (<b>c</b>) line A 11.15−06.14; (<b>d</b>) line A 07.31−06.14; (<b>e</b>) line B 07.20−06.14; (<b>f</b>) line B 09.07−06.14; (<b>g</b>) line B 11.15−06.14; and (<b>h</b>) line B 07.31−06.14.</p>
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<p>Curve fitting of subsidence and scattered points on the profile line: (<b>a</b>) strike 07.20−06.14; (<b>b</b>) strike 09.07−06.14; (<b>c</b>) strike 11.15−06.14; (<b>d</b>) strike 07.31−06.14; (<b>e</b>) dip 07.20−06.14; (<b>f</b>) dip 09.07−06.14; (<b>g</b>) dip 11.15−06.14; and (<b>h</b>) dip 07.31−06.14.</p>
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<p>Time series subsidence curve for the main section: (<b>a</b>) strike subsidence curve fitting; and (<b>b</b>) dip subsidence curve fitting.</p>
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<p>MinLoD threshold assessment of the significance for the variability in the DoD elevation: (<b>a</b>) minlod = 0.00 m; (<b>b</b>) minlod = 0.10 m; and (<b>c</b>) minlod = 0.20 m.</p>
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24 pages, 7443 KiB  
Article
Proposed New Analytical Method of Tower Load in Large-Span Arch Bridge Cable Lifting Construction
by Qian Huang, Xiaoguang Wu, Yunfei Zhang and Min Ma
Appl. Sci. 2022, 12(18), 9373; https://doi.org/10.3390/app12189373 - 19 Sep 2022
Cited by 8 | Viewed by 2444
Abstract
The cable lifting construction method is the most widely used construction method for large-span arch bridges. The correct calculation and analysis of cable lifting construction is essential to ensure the safety and linearity in the construction of arch bridges. The existing research mainly [...] Read more.
The cable lifting construction method is the most widely used construction method for large-span arch bridges. The correct calculation and analysis of cable lifting construction is essential to ensure the safety and linearity in the construction of arch bridges. The existing research mainly focuses on the construction scheme and finite element analysis of cable lifting for large-span arch bridges. There is relatively little research on calculation theory, and there is no analytical method for cable lifting construction of arch bridges. To calculate and analyze cable lifting construction more quickly and accurately, based on the deformation coordination principle and suspension cable theory, a practical calculation method is proposed to calculate the load of the tower acting by a cable system in the cable lifting construction of arch bridges. A large-span arch bridge under construction was used as a case study, and the correctness of the calculation method was verified by measuring the displacements of the tower top. A brief description of the structure, verification method, and verification process is presented. The displacement results are calculated by the numerical calculation software SAP2000, the actual measured displacement data are discussed and comparatively analyzed, and the correctness and calculation accuracy of the proposed calculation method are also evaluated. The results show that the calculation method has sufficient accuracy. The tower load calculation is mainly undertaken to prepare for the analysis of the tower mechanical properties; therefore, the calculation method is applied to towers of the case engineering, and the stability, load carrying capacity, and deformation of the tower are analyzed to verify whether its mechanical properties meet the engineering requirements. The results show that steel pipe columns of the buckle tower are prone to twisting instability. The normal stress of the tower’s part of the pressurized rod or pressurized bending rod is larger. Wind cable load calculation models and tower design-related recommendations are presented in this tower analysis. The tower load calculation method and tower mechanics analysis method in this study can provide guidance for the calculation and analysis of the cable lifting construction of large-span arch bridges. Full article
(This article belongs to the Special Issue Advanced Technologies for Bridge Design and Construction)
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<p>Cable lifting construction of large-span arch bridges: (<b>a</b>) Pingnan Third Bridge; (<b>b</b>) Jinghe Bridge.</p>
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<p>Simplified model of cable lifting system.</p>
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<p>Schematic diagram for calculating the forces acting on the towers from the main cable: (<b>a</b>) empty cable; (<b>b</b>) cable carrying load.</p>
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<p>Calculation diagram of the acting force of lifting cable on tower.</p>
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<p>Schematic diagram of calculating the forces acting on a tower from a towing cable: (<b>a</b>) left bank; (<b>b</b>) right bank.</p>
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<p>Schematic diagram of calculating the forces acting on a tower from a towing cable: (<b>a</b>) left bank; (<b>b</b>) right bank.</p>
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<p>Overall layout of cable lifting system.</p>
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<p>Overall numerical calculation model.</p>
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<p>Numerical calculation model of tower: (<b>a</b>) tower; (<b>b</b>) distribution beam at top of cable tower; (<b>c</b>) steel pipe column and universal rods; (<b>d</b>) universal rods; (<b>e</b>) distribution beam at top of buckle tower; (<b>f</b>) hinge seat distribution beam.</p>
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<p>Tower and measurement point layouts for engineering case: (<b>a</b>) left bank; (<b>b</b>) right bank.</p>
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<p>Deformation of tower at right bank (unit: mm): (<b>a</b>) Load 1; (<b>b</b>) Load 2; (<b>c</b>) Load 3.</p>
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<p>Buckle cables acting on the tower.</p>
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<p>First six orders of buckling mode characteristics of towers: (<b>a</b>) buckling mode 1; (<b>b</b>) buckling mode 2; (<b>c</b>) buckling mode 3; (<b>d</b>) buckling mode 4; (<b>e</b>) buckling mode 5; and (<b>f</b>) buckling mode 6.</p>
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<p>Maximum axial force diagram of the universal rods of the tower located on the right bank: (<b>a</b>) cable tower; (<b>b</b>) buckle tower.</p>
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<p>Location and number of steel pipe columns of the tower at the right bank.</p>
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<p>Normal stress of steel pipe column under each load condition.</p>
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<p>The changing tendency of normal stress with height for steel pipe columns: (<b>a</b>) No. 11 steel pipe column; (<b>b</b>) No. 7 steel pipe column.</p>
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<p>Maximum displacement of the tower top under each load condition: (<b>a</b>) left bank; (<b>b</b>) right bank.</p>
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<p>Deformation of the steel pipe columns along the longitudinal direction of the bridge.</p>
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18 pages, 1741 KiB  
Article
Comparison of Methods to Identify and Monitor Mold Damages in Buildings
by Pedro Maria Martin-Sanchez, Maria Nunez, Eva Lena Fjeld Estensmo, Inger Skrede and Håvard Kauserud
Appl. Sci. 2022, 12(18), 9372; https://doi.org/10.3390/app12189372 - 19 Sep 2022
Cited by 4 | Viewed by 4717
Abstract
Molds thrive in indoor environments, challenging the stability of building materials and occupants’ health. Diverse sampling and analytical techniques can be applied in the microbiology of buildings, with specific benefits and drawbacks. We evaluated the use of two methods, the microscopy of visible [...] Read more.
Molds thrive in indoor environments, challenging the stability of building materials and occupants’ health. Diverse sampling and analytical techniques can be applied in the microbiology of buildings, with specific benefits and drawbacks. We evaluated the use of two methods, the microscopy of visible mold growth (hereinafter “mold” samples) (tape lifts) and the DNA metabarcoding of mold and dust samples (swabs), for mapping mold-damage indicator fungi in residential buildings in Oslo. Overall, both methods provided consistent results for the mold samples, where nearly 80% of the microscopy-identified taxa were confirmed by DNA analyses. Aspergillus was the most abundant genus colonizing all materials, while some taxa were associated with certain substrates: Acremonium with gypsum board, Chaetomium with chipboard, Stachybotrys with gypsum board and wood, and Trichoderma with wood. Based on the DNA data, the community composition was clearly different between the mold and the dust, with a much higher alpha diversity in the dust. Most genera identified in the mold were also detected with a low abundance in the dust from the same apartments. Their spatial distribution indicated some local spread from the mold growth to other areas, but there was no clear correlation between the relative abundances and the distance to the damages. To study mold damages, different microbiological analyses (microscopy, cultivation, DNA, and chemistry) should be combined with a thorough inspection of buildings. The interpretation of such datasets requires the collaboration of skilled mycologists and building consultants. Full article
(This article belongs to the Special Issue Fungi Associated with Indoor Environments and Materials)
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<p>Sampling of mold and dust in this study. (<b>a</b>) Mold-damaged gypsum board where M62-M64 samples were collected; (<b>b</b>) mold growing on wood, sample M65; (<b>c</b>) tape lifts taken directly on discoloration of building materials; (<b>d</b>) dust sample collected by swabbing the upper doorframe, picture extracted from Martin-Sanchez et al. [<a href="#B22-applsci-12-09372" class="html-bibr">22</a>].</p>
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<p>Comparison of dust and mold mycobiota, as revealed by DNA metabarcoding: (<b>a</b>) NMDS plot showing the differences in the fungal community composition of 42 dust samples and 48 mold samples; (<b>b</b>) variation of the alpha diversity indices; (<b>c</b>) the most abundant fungal genera (RA ≥ 2%) identified in each sample type. Note that the genus <span class="html-italic">Serpula</span> was initially misidentified as <span class="html-italic">Austropaxillus</span> in the first automatic taxonomic assignment (<b>*</b>).</p>
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<p>Mold mycobiota, as revealed by DNA metabarcoding: (<b>a</b>) NMDS plot comparing the fungal community composition in 48 mold samples collected from different materials; (<b>b</b>) the most abundant fungal genera (RA ≥ 5%) identified in the mold samples collected from different materials, excluding those materials represented by a single sample, i.e., concrete, paint, and plastic.</p>
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<p>Venn diagrams showing the overlap in distribution of OTUs across sample types (dust and mold). (<b>a</b>) Mean percentage of overlapping and unique OTUs (with standard deviations), calculated on an apartment-by-apartment basis for the 11 apartments that included dust samples from both damaged and central rooms; (<b>b</b>) the same kind of data as “a” but calculated for the 25 apartments that only include dust from the damaged rooms; (<b>c</b>) overall percentages and number of OTUs (in parenthesis) for the same 25 apartments as “b”, without separated calculations by apartment.</p>
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17 pages, 5304 KiB  
Article
Supervised Learning-Based Image Classification for the Detection of Late Blight in Potato Crops
by Marco Javier Suarez Baron, Angie Lizeth Gomez and Jorge Enrique Espindola Diaz
Appl. Sci. 2022, 12(18), 9371; https://doi.org/10.3390/app12189371 - 19 Sep 2022
Cited by 16 | Viewed by 2221
Abstract
This article presents the application of supervised learning and image classification for the early detection of late blight disease in potato using convolutional neural network and support vector machine SVM. The study was realized in the Boyacá department, Colombia. An initial dataset is [...] Read more.
This article presents the application of supervised learning and image classification for the early detection of late blight disease in potato using convolutional neural network and support vector machine SVM. The study was realized in the Boyacá department, Colombia. An initial dataset is created with the acquisition of a large number of images directly from the crops. These images are pre-processed in order to extract the main characteristics of the late blight disease. A classification model is developed to identify the potato plants as healthy or infected. Several performance, efficiency, and quality metrics were applied in the learning and classification tasks to determine the best machine learning algorithms. Then, an additional data set was used for validation, image classification, and detection of late blight disease in potato crops in the department of Boyacá, Colombia. The results obtained in the AUC curve show that the CNN trained with the data set obtained an AUC equal to 0.97; and the analysis through SVM obtained an AUC equal to 0.87. Future work requires the development of a mobile application with advanced features as a technological tool for precision agriculture that supports farmers with increased agricultural productivity. Full article
(This article belongs to the Special Issue Computer Vision and Pattern Recognition Based on Deep Learning)
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<p>The flowchart of the methodology.</p>
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<p>Functional architecture.</p>
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<p>Samples of the data set used. (<b>A</b>) Healthy leaves, (<b>B</b>) leaves infected with late blight.</p>
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<p>Input image and output images of the data augmentation algorithm.</p>
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<p>Transformation to HSV, LAB, and grayscale space.</p>
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<p>Result obtained from the application of segmentation algorithm.</p>
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<p>Result obtained from the application of Range Threshold Segmentation.</p>
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<p>Proposed CNN Architecture.</p>
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<p>Prototype design for diagnostic visualization of a leaf from an image.</p>
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<p>Prototype designs of obtained data visualization for administrators.</p>
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<p>Confusion Matrices of the CNN Models.</p>
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<p>Confusion Matrices of Support Vector Machine (SVM) Models.</p>
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<p>ROC curve of convolutional neural network (CNN) models.</p>
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<p>ROC curves of the Support Vector Machine (SVM) models.</p>
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14 pages, 4293 KiB  
Article
Intelligent Timber Damage Monitoring Using PZT-Enabled Active Sensing and Intrinsic Multiscale Entropy Analysis
by Shuai Guo, Tong Shen, Li Li, Huangxing Hu, Jicheng Zhang and Zhiwen Lu
Appl. Sci. 2022, 12(18), 9370; https://doi.org/10.3390/app12189370 - 19 Sep 2022
Cited by 1 | Viewed by 1392
Abstract
Timber has been commonly used in the field of civil engineering, and the health condition of timber is of great significance for the whole structure in practical scenarios. However, due to mechanical load and environmental impact, timber-based constructions are vulnerable to termite attack, [...] Read more.
Timber has been commonly used in the field of civil engineering, and the health condition of timber is of great significance for the whole structure in practical scenarios. However, due to mechanical load and environmental impact, timber-based constructions are vulnerable to termite attack, microbial corrosion and fractures within their service lives. Thus, the damage monitoring of timber structures is very challenging under real situations. This paper presents an intelligent timber damage monitoring approach using Lead Zirconate Titanate (PZT)-enabled active sensing and intrinsic multiscale entropy analysis. The proposed approach adopts PZT-enabled active sensing to collect the signals depicting dynamic characteristics of the timber structure. The proposed intrinsic multiscale entropy analysis utilizes variational mode decomposition (VMD) to deal with the collected response signals. Decomposition of the response signals into a set of band-limited intrinsic mode functions (BLIMFs) denoting nonlinear and nonstationary characteristics. Then multiscale sample entropy (MSE) is employed to extract quantitative features, which are adopted as health condition indicators of timber structures. Finally, the convolutional neural network (CNN) fulfills the intelligent timber damage monitoring by using the quantitative features as the effective input. The research findings reveal the efficacy and superiority of the proposed method. Full article
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<p>The illustration of conventional coarse-graining procedure: (<b>a</b>) <math display="inline"><semantics> <mi>τ</mi> </semantics></math> is 2; (<b>b</b>) <math display="inline"><semantics> <mi>τ</mi> </semantics></math> is 3.</p>
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<p>The illustration of MSE procedures.</p>
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<p>The structure of the CNN model.</p>
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<p>Timber specimens of three groups. (<b>a</b>) Specimen of Group A; (<b>b</b>) Specimen of Group B; (<b>c</b>) Specimen of Group C.</p>
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<p>(<b>a</b>) A photo of the apparatus, (<b>b</b>) The schematic diagram of the apparatus.</p>
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<p>Sensor signal response of each type of timber damage mode. (<b>a</b>) Case 1, (<b>b</b>) Case 2, (<b>c</b>) Case 3, (<b>d</b>) Case 4, (<b>e</b>) Case 5, (<b>f</b>) Case 6.</p>
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<p>Sensor signal response of each type of timber damage mode. (<b>a</b>) Case 1, (<b>b</b>) Case 2, (<b>c</b>) Case 3, (<b>d</b>) Case 4, (<b>e</b>) Case 5, (<b>f</b>) Case 6.</p>
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<p>(<b>a</b>) The accuracy of training set and validation set; (<b>b</b>) The loss function of training set and validation set.</p>
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<p>(<b>a</b>) VMD + MSE + CNN timber damage identification results; (<b>b</b>) ALIF + MSE + CNN timber damage identification results; (<b>c</b>) EEMD + MSE + CNN timber damage identification results; (<b>d</b>) EMD + MSE + CNN timber damage identification results. In all confusion matrices, the abscissa and ordinate of confusion matrix denote the true label and predicted label of timber damage conditions, respectively.</p>
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2 pages, 156 KiB  
Editorial
Special Issue “Spine and Spinal Cord Biomechanics and Rehabilitation”
by Norihiro Nishida
Appl. Sci. 2022, 12(18), 9369; https://doi.org/10.3390/app12189369 - 19 Sep 2022
Viewed by 1337
Abstract
Spinal cord injuries are directly related to quality of life [...] Full article
21 pages, 1429 KiB  
Article
Application of Extension Engineering in Safety Evaluation of Chemical Enterprises
by Qilong Han, Peng Liu and Zhiqiang Ma
Appl. Sci. 2022, 12(18), 9368; https://doi.org/10.3390/app12189368 - 19 Sep 2022
Cited by 1 | Viewed by 1770
Abstract
To effectively analyze the safety risk of chemical enterprises and ensure the safety of production and management of enterprises, the contradiction problems in the process of index selection and risk early warning model in practical application are addressed. In this paper, extension engineering [...] Read more.
To effectively analyze the safety risk of chemical enterprises and ensure the safety of production and management of enterprises, the contradiction problems in the process of index selection and risk early warning model in practical application are addressed. In this paper, extension engineering is introduced into the safety-security field of chemical enterprises to extract hidden useful information from the production environment and outdoor environment data and provide decision support for the managers of chemical enterprises. First, based on data preprocessing and extension analysis, the safety-security data of chemical enterprises that meet the quality requirements and can be efficiently mined are searched. Then, the outdoor environment is combined in the paper to conduct the mining of these data in two aspects: (1) comprehensive analysis and evaluation of data quality; (2) key factors affecting factory safety mining, realizing the safety-security evaluation of intelligent factories in chemical enterprises. Based on the proposed chemical factory safety extension prerisk model, the risk assessment of the safety status of a chemical enterprise in Hebei Province is carried out. The research results of this paper provide a theoretical basis for the safety production analysis of such chemical enterprises and put forward practical suggestions for preventing possible accidents in the production process. Full article
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<p>SEDCI index screening and hierarchical division.</p>
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<p>Workshop index data box diagram.</p>
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<p>The production flow chart of a workshop in the chemical plant.</p>
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<p>The data collection scheme diagram of workshops in the chemical plant.</p>
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