Search Results (2,034)

This paper presents an autonomous perfectly secure low-bit-rate voice communication system (APS-VCS) based on the mixed-excitation linear prediction voice coder (MELPe), Vernam cipher, and sequential key distillation (SKD) protocol by public discussion. An authenticated public channel can be selected in a wide range, from internet connections to specially leased radio channels. We found the source of common randomness between the locally synthesized speech signal at the transmitter and the reconstructed speech signal at the receiver side. To avoid information leakage about open input speech, the SKD protocol is not executed on the actual transmitted speech signal but on artificially synthesized speech obtained by random selection of the linear spectral pairs (LSP) parameters of the speech production model. Experimental verification of the proposed system was performed on the Vlatacom Personal Crypto Platform for Voice encryption (vPCP-V). Empirical measurements show that with an adequate selection of system parameters for voice transmission of 1.2 kb/s, a secret key rate (KR) of up to 8.8 kb/s can be achieved, with a negligible leakage rate (LR) and bit error rate (BER) of order for various communications channels, including GSM 3G and GSM VoLTE networks. At the same time, by ensuring perfect secrecy within symmetric encryption systems, it further highlights the importance of the symmetry principle in the field of information-theoretic security. To our knowledge, this is the first autonomous, perfectly secret system for low-bit-rate voice communication that does not require explicit prior generation and distribution of secret keys. Full article

El Caño Martín Peña (CMP), a cluster of eight historically informal neighborhoods in San Juan, Puerto Rico, faces long-standing challenges of inadequate infrastructure, persistent flooding, and displacement pressures. In response, the G8 collective—a coalition representing these communities—and the Martín Peña Canal Community Land Trust (CLT) establishment have developed a participatory planning model prioritizing resilience and housing security. This unique and exemplary model of a participatory planning case study, grounded in document analysis and participant observation, explores how the G8 and CLT have driven transformative improvements in CMP, addressing informality, mitigating flood risks, and preventing displacement. Findings highlight how community-driven governance fosters trust and enhances long-term sustainability, offering valuable insights for equitable urban development and spatial justice. Full article

Japan is facing challenges associated with its super-aging society, including increased social security burdens and a rise in the elderly workforce due to a declining younger labor force. Extending the healthy life expectancy is one countermeasure, necessitating lifestyle improvements such as frailty prevention and ensuring adequate sleep duration. This study investigated the relationship between heart rate variability (HRV) and sleep duration among older adults (aged ≥ 65) using electrocardiogram (ECG) and three-axis accelerometer data from the Allostatic State Mapping by the Ambulatory ECG Repository (ALLSTAR) database, recorded between January 2019 and March 2021. Inclusion criteria required a sinus rhythm and recording durations ≥80%. Continuous 24 h ECG and accelerometer data were analyzed for 55,154 participants (mean age 76 ± 6). The results consistently showed significant differences in HRV metrics, including MRRI, SDRR, ULF, LF, HF, and LF/HF, across sleep duration groups (G1–G4). Short-sleep groups (G4) exhibited decreased MRRI and SDRR and increased LF/HF, suggesting active lifestyles but reduced HRV. Conversely, long-sleep groups (G1) showed increased MRRI and reduced LF/HF but exhibited age-related declines in SDRR and ULF. These findings indicate that both insufficient and excessive sleep may contribute to HRV reduction in older adults. This study provides critical insights for improving elderly lifestyles through tailored interventions in exercise and sleep management. Full article

The application of artificial intelligence (AI) in tall buildings’ development provides transformative opportunities for facing population growth pressures and sustainability challenges in cities. This study presents a comprehensive review of both the current literature and the theoretical framework of AI and its role in construction, specifically analyzing the convergence of AI and skyscraper development. The research methodology combines scholarly sources, AI image generation techniques, an analytical approach, and a comparative analysis of traditional versus AI-enhanced approaches. This study identifies key domains where AI significantly impacts skyscraper evolution, including design optimization, energy management, construction processes, and operational efficiencies. It highlights short-term benefits like enhanced architectural design through rapid generative design iterations and material optimization, alongside long-term implications involving adaptive building technologies and sustainability enhancements. Additionally, it addresses the advantages and challenges of adopting AI in architecture, considering various factors (e.g., sustainability, security, and occupant well-being), as well as the impact of different climates on AI in architecture and construction. It also explores transformative applications across diverse skyscraper functions and how AI can bridge different cultures and technologies. The findings reveal AI’s substantial potential in TBs’ design and management, (i.e., structural optimization, energy saving, safety protocols, and operational efficiency) by leveraging innovative technologies such as machine learning, computer vision, and predictive modeling. In conclusion, AI’s dual role as both a revolutionary tool that enhances traditional architectural methods and a catalyst for new design paradigms prioritizing sustainability and resilience has been reflected. Ultimately, this research underscores the importance of balancing AI innovation with established architectural principles to foster a favorable urban future that embraces both technological advancement and foundational design values. This study serves as a base for future research in the AI field. Full article

The secure and effective use of marginal water resources, such as brackish water, plays a crucial role in ensuring food security and promoting the sustainable development of agricultural land. This paper conducted indoor soil column experiments to simulate the infiltration of brackish water (0, 1, 3, and 5 g L⁻¹) in order to study the effects of infiltration on the movement of soil water and salt, aiming to address the critical challenge of utilizing marginal water resources in coastal saline-alkali areas. The result showed that, as salt content increases, the movement speed of the moisture front and soil infiltration rate gradually decrease over the same period of time. The moisture front progress and infiltration volume showed a positive correlation. The moisture content of the soil profile gradually decreased, within the soil depth range of 0–40 cm, except for the 5 g L⁻¹ saline water infiltration, and the Cl⁻ content increased, while the other treatments showed a trend of first decreasing and then increasing. The higher salt content at the same depth, the higher the Na⁺ and Cl⁻ contents. Under different irrigation water volume conditions, the soil profile conductivity shows a trend of first decreasing and then increasing. The research findings advance fundamental understanding of salinity-driven soil hydrological processes, offering theoretical support for the sustainable utilization of brackish water, balancing agricultural water demand and soil health in coastal areas. Full article

Coherent spatial data are crucial for informed land use and regional planning decisions, particularly in the context of securing a crisis-proof food supply and adapting to climate change. This dataset provides spatial information on climate-robust and high-yield agricultural arable land in Brandenburg, Germany, based on the results of a classification using bio-economic climate simulations. The dataset is intended to support regional planning and policy makers in zoning decisions (e.g., photovoltaic power plants) by identifying climate-robust arable land with high current and stable future production potential that should be reserved for agricultural use. The classification method used to generate the dataset includes a wide range of indicators, including established approaches, such as a soil quality index, drought, water, and wind erosion risk, as well as a dynamic approach, using bio-economic simulations, which determine the production potential under future climate scenarios. The dataset is a valuable resource for spatial planning and climate change adaptation, contributing to long-term food security especially in dry areas such as the state of Brandenburg facing increased production risk under future climatic conditions, thereby serving globally as an example for land use planning challenges related to climate change. Full article

The cassava production system in Colombia is relevant for food security and agro-industrial development, especially in the Caribbean region. To optimize this system, it is necessary to understand the technical and socioeconomic particularities of the crop, which facilitates cost improvements and increased yields. Two main market segments are recognized in this country, cassava for human consumption and for industrial purposes (starch and animal feed). There is still no comprehensive study on the characterization of industrial cassava production systems; therefore, this work aims to identify typologies of farmers according to their technological and socioeconomic characteristics, to contribute to research and production planning. The information related to sociodemographic and technological conditions was collected through a structured survey applied to 53 organizations selected by random sampling that compiles consensual information of 1470 producers. The data were analyzed with descriptive statistics and a multivariate analysis of variables, such as cultivated area, yield, and proximity to markets, using the Gower method. The results indicated that in the Caribbean industrial cassava production, the average age of farmers is 47 years, with mostly men (72%), and a predominant educational level of secondary school (35%). Two groups of farmers were identified from multivariate analysis, from which group 2 (G2) represented four producer organizations (119 producers) and showed the highest yields and a larger cultivated area, suggesting that a larger scale of production is associated with better yields, which is associated with major access to technological tools and possibly technical knowledge. However, the most cassava producers (49 producer organizations and 1361 producers) had a lower cultivated area and yield, confirming that the technological level and management optimization is related to competitiveness and profitability. Full article

In disaster scenarios, e.g., earthquakes, tsunamis, and wildfires, communication infrastructure often becomes severely damaged. To rapidly restore damaged communication systems, we propose a UAV-based mobile base station equipped with Public Safety LTE (PS-LTE) technology to provide standalone communication capabilities. The proposed system includes PS-LTE functionalities, mission-critical push-to-talk, proximity-based services, and isolated E-UTRAN operation to ensure the reliable and secure communication for emergency services. We provide a simulation result to achieve the radio coverage of mobile base station. By using this radio coverage, we find an appropriate location of the end device for performing the outdoor experiments. We develop a prototype of a proposed mobile base station and test its operation in an outdoor environment. The experimental results provide a sufficient data rate to make an independent mobile base station to restore communication infrastructure in areas that experienced environmental disasters. This prototype and experimental results offer a significant step forward in creating agile and efficient communication solutions for emergency scenarios. Full article

Transforming irrigation practices is essential to address aquifer depletion and food security in Mediterranean regions facing climate change and water scarcity. Developing local and national resilience to climate change requires capacity building to boost soil health and adaptation to drought. Recent attempts undertaken by the SEALACOM Project reduced irrigation rates in protected agriculture. The purpose of this work is to enhance traditional farmer’s practices and promote the potential of advanced fertigation of field crops (i.e., potato and zucchini) cultivated under two different pedo-climatic conditions to improve water and nutrient use efficiency. Results showed the yield of zucchini and potato on SEALACOM plots with continuous fertigation was 22% and 17.8%, respectively, which was higher than the yield with traditional irrigation and fertilization practices. Elite potato tuber size was 40% higher in SEALACOM plots (p < 0.05). The farmer applied 359 L of water to produce 1 kg of fresh zucchini compared to 225 L by the SEALACOM Project, indicating a significant, 60% water saving in the SEALACOM practice. Compared to farmer’s practices of potato production, the SEALACOM Project achieved more than 50% higher water productivity. In zucchini production, farmers applied 19.5% more nitrogen and 19.6% more phosphorus fertilizers. Compared to 58 kg of N applied by the farmers, the SEALACOM Project applied 38 kg of N to produce 1 ton of Zucchini, showing a 34% saving in major nutrient application. To cultivate 1 kg of fresh potato tubers, SEALACOM utilized 4.06 g of nitrogen and 1.34 g of phosphorus, compared to the traditional practice, which required 13.2 g of nitrogen and 2.25 g of phosphorus. Water and nutrient saving and higher productivity and commerciality of the final product have a high positive impact on the farmer’s income and positive attitude towards the adoption of modern, sustainable practices. Full article

We consider a secure integrated sensing and communication (ISAC) scenario, where a signal is transmitted through a state-dependent wiretap channel with one legitimate receiver with which the transmitter communicates and one honest-but-curious target that the transmitter wants to sense. The secure ISAC channel is modeled as two state-dependent fast-fading channels with correlated Rayleigh fading coefficients and independent additive Gaussian noise components. Delayed channel outputs are fed back to the transmitter to improve the communication performance and to estimate the channel state sequence. We establish and illustrate an achievable secrecy-distortion region for degraded secure ISAC channels under correlated Rayleigh fading, for which we show that the signal-to-interference-plus-noise is not a sufficient statistic. We also evaluate the inner bound for a large set of parameters to derive practical design insights. The presented results include parameter ranges for which the secrecy capacity of a classical wiretap channel setup is surpassed and for which the channel capacity is approached. Thus, we illustrate for correlated Rayleigh fading cases that our secure ISAC methods can (i) eliminate the need for the legitimate receiver to have a statistical advantage over the eavesdropper and (ii) provide communication security with minimal rate penalty. Full article

The civil engineering sector operates within a complex ecosystem of stakeholders, requiring efficient management and maintenance of structural and infrastructural assets. In this context, there is an increasing need for robust tools to track critical events (e.g., alerts, unusual behaviors) and support decision-making processes related to maintenance and interventions. At the same time, ensuring secure and prompt payments is essential for timely and effective responses. This paper investigated the potential of smart contracts, integrated with blockchain technology, to automate and optimize asset management and maintenance processes. The proposed framework examines how these technologies can enhance operational efficiency, security, and event traceability, providing a structured approach for both routine operations and emergency interventions. Although smart contracts have been widely applied in the construction phase of infrastructure projects, their use in long-term asset management remains largely unexplored. As a conceptual study, this work does not present a quantitative analysis but instead lays the groundwork for future research and real-world applications of blockchain-based smart contracts in infrastructure management and safety procedures. Full article

With the advent of NextG wireless networks, the reliance on centralized identity and service management systems poses significant challenges, including limited interoperability, increased privacy vulnerabilities, and the risk of unauthorized tracking or monitoring of user activity. To address these issues, there is a critical need for a decentralized framework that empowers users with self-sovereignty over their subscription information while maintaining trust and privacy among network entities. This article presents a novel framework to enable Self-Sovereign Federated NextG (SSFXG) wireless communication networks. The SSFXG framework separates identity management from the service management layer typically controlled by network operators to foster interoperability functionalities with enhanced privacy and trace-resistant assurances in the NextG landscape. The proposed model relies on blockchain technology as an infrastructure to enable single-authority-free service provisioning and boost mutual trust among federated network components. Further, the SSFXG framework facilitates subscribers’ self-sovereignty over their subscription information while ensuring anonymity and enhanced privacy preservation, avoiding unnecessary network activity monitoring or tracking. Preliminary evaluations demonstrated the effectiveness and efficiency of the proposed framework, making it a promising solution for advancing secure and interoperable NextG wireless networks. Full article

This study optimizes the 3D extrusion printing parameters—water-to-flour ratio (X₁), temperature (X₂), and printing speed (X₃)—for raw (RFB) and extruded (EFB) dehulled Andean fava bean flours to maximize print quality and minimize structural defects. A 2³ central composite design combined with response surface methodology (RSM) was used to identify the optimal conditions for achieving geometric precision, surface homogeneity, and textural stability. Physicochemical analyses showed that extrusion cooking substantially modified the composition and rheology of the flour. Compared with RFB, EFB exhibited lower protein and fiber contents, a higher proportion of digestible carbohydrates, and reduced rheological parameters (τ₀, K, G′, G″), which facilitated printing. The evaluation of different parameter combinations revealed notable differences between the two flours, with X₁ and X₂ exerting the greatest influence on print quality. For RFB, the highest desirability (0.853) was achieved at X₁ = 0.806, X₂ = 23.18 °C, and X₃ = 2470.5 mm/min, yielding more uniform and firmer printed structures. In contrast, EFB reached a desirability of 0.844 at X₁ = 1.66 °C, X₂ = 56.82 °C, and X₃ = 1505.43 mm/min, indicating its outstanding geometric accuracy and robustness. In conclusion, raw flour requires higher hydration and lower temperatures to prevent excessive viscosity. In contrast, extruded flour benefits from low water and high temperatures to achieve stable structures and firm textures. These findings demonstrate the feasibility of using Andean fava bean flour in 3D food printing to create nutrient-dense, functional foods with improved printability. This work offers practical applications for developing personalized foods—such as customized meals for individuals with specific dietary requirements—while contributing to sustainable and secure food production. Future research should address long-term storage, post-printing drying methods, and scaling production. Full article

The convergence of cloud computing and the Industrial Internet of Things (IIoT) has significantly transformed industrial operations, enabling intelligent, scalable, and efficient systems. This survey provides a comprehensive analysis of the role cloud computing plays in IIoT ecosystems, focusing on its architectural frameworks, service models, and application domains. By leveraging centralized, edge, and hybrid cloud architectures, IIoT systems achieve enhanced real-time processing capabilities, streamlined data management, and optimized resource allocation. Moreover, this study delves into integrating artificial intelligence (AI) and machine learning (ML) in cloud platforms to facilitate predictive analytics, anomaly detection, and operational intelligence in IIoT environments. Security challenges, including secure device-to-cloud communication and privacy concerns, are addressed with innovative solutions like blockchain and AI-powered intrusion detection systems. Future trends, such as adopting 5G, serverless computing, and AI-driven adaptive services, are also discussed, offering a forward-looking perspective on this rapidly evolving domain. Finally, this survey contributes to a well-rounded understanding of cloud computing’s multifaceted aspects and highlights its pivotal role in driving the next generation of industrial innovation and operational excellence. Full article

Given the burgeoning necessity for high-speed, efficient, and secure wireless communication in 6G, visible light communication (VLC) has emerged as a fervent subject of discourse within academic and industrial circles alike. Among these considerations, it is imperative to construct scalable multi-user VLC systems, meticulously addressing pivotal issues such as power dissipation, alignment errors, and the safeguarding of user privacy. However, traditional methods like multiplexing holography (MPH) and multiple focal (MF) phase plates have shown limitations in meeting these diverse requirements. Here, we propose a novel spatial multiplexing holography (SMH) theory, a comprehensive solution that overcomes existing hurdles by enabling precise power allocation, self-designed power coverage, and secure communication through orbital angular momentum (OAM). The transformative potential of SMH is demonstrated through simulations and experimental studies, showcasing its effectiveness in power distribution within systems of VR glasses users, computer users, and smartphone users; enhancing power coverage with an 11.6 dB improvement at coverage edges; and securing data transmission, evidenced by error-free 1080P video playback under correct OAM keys. Our findings illustrate the superior performance of SMH in facilitating seamless multi-user communication, thereby establishing a new benchmark for future VLC systems in the 6G landscape. Full article