Deep Attention Network for Enhanced Hand Gesture Recognition System
Since technology is growing in all fields, researchers are developing more advanced technologies in human–computer communication and security systems. The flexible wrist hinge and crowded background make it difficult to distinguish hands in ...
Emotion Recognition System via Facial Expressions and Speech Using Machine Learning and Deep Learning Techniques
Patients in hospitals frequently exhibit psychological issues such as sadness, pessimism, eccentricity, and anxiety. However, hospitals normally lack tools and facilities to continuously monitor the psychological health of patients. It is ...
Aspect Oriented Sentiment Analysis on Customer Reviews on Restaurant Using the LDA and BERT Method
This study presents a new approach for administering point-of-view-based assessment exams. The purpose of our ranking is to gain a sense of the best and most hilariously bad works of art. Given a collection of free-text clients, a specific object ...
Energy-Efficient Task Scheduling in Fog Computing Based on Particle Swarm Optimization
Recently, continuous growth in use of Internet of Things (IoT) produces huge amount of data during processing, which increases load on Cloud Computing network. Cloud computing does not support low latency for real-time applications. To overcome ...
Utilizing Deep Learning Models and Transfer Learning for COVID-19 Detection from X-Ray Images
COVID-19 has been a global pandemic. Flattening the curve requires intensive testing, and the world has been facing a shortage of testing equipment and medical personnel with expertise. There is a need to automate and aid the detection process. ...
A Corpus-Based Auto-encoder-and-Decoder Machine Translation Using Deep Neural Network for Translation from English to Telugu Language
There is a huge demand for machine translation to design automated auto-encoders that can convert English to the Telugu language. Neural machine translation (NMT) is a new and effective technology that has significantly benefited traditional ...
Miniaturized Wearable Antenna with Reduced Specific Absorption Rate and Enhanced Bandwidth
A semi-flexible dual-band antenna at 2.25/5.93 GHz for wearable applications is proposed in this paper. The proposed antenna has dimensions of 19 mm × 12 mm × 0.508 mm and consists of a corrugated monopole with a slit of L-shape inverting at the ...
Forecasting the Disease Using Discrete Deep Learning Algorithms
Predictive modelling is the foundation of the disease prediction system. Based on the symptoms that the client provides as input to the system, it forecasts the client’s illness. The system evaluates the client’s or patient’s reported symptoms as ...
RI-CDVS: Robust and Imperceptible Compressed Domain Video Steganography Using H.265 Codec
The development of steganography methods has raised growing worries about steganography abuse. As the significant demand for digital video processing is on the rise from last decade, data security becomes a crucial issue. Motion vector ...
Novel Framework for Improving the Correctness of Reference Answers to Enhance Results of ASAG Systems
Usage of online learning platforms increases day by day and henceforth, there emerges the need for automated grading systems to assess the learner’s performance. Evaluating these answers demands for a well-grounded reference answer which aids a ...
PubExN: An Automated PubMed Bulk Article Extractor with Affiliation Normalization Package
Biomedical article extraction is the preliminary step for every biomedical application. These applications are helpful in finding the gene, disease, chemical, drugs, protein entities. Finding entities relation such as gene–gene entities, drug-...
An Interval-Valued Trapezoidal Intuitionistic Fuzzy TOPSIS Approach for Decision-Making Problems
The Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) is a well-known multi-criteria decision-making strategy that has been widely used in research decision-making problems. Furthermore, interval-valued trapezoidal ...
Supporting User Protection Requirements in Cloud-Based Data Outsourcing
The cloud is nowadays widely used for storing and managing data, and leveraging scalable and flexible IT infrastructures while guaranteeing continuous data and application availability from anywhere at any time. The cloud market is characterized ...
Bidirectional Recurrent Network and Neuro-fuzzy Frequent Pattern Mining for Heart Disease Prediction
In recent days medical clinics need more analysis in heart disease because of most dangerous disease caused mostly worldwide affected by the people. By analyzing the characteristic features are high dimension due to complex structure of data ...
A Toolchain for Synthesizing and Validating Safety Architectures
- Yuri Gil Dantas,
- Tiziano Munaro,
- Carmen Carlan,
- Vivek Nigam,
- Simon Barner,
- Shiqing Fan,
- Alexander Pretschner,
- Ulrich Schöpp,
- Sergey Tverdyshev
Autonomous vehicles handle complicated tasks that may lead to harm when performed incorrectly. These harms, in particular when caused by system faults, may be avoided by the deployment of safety architectural patterns, such as the Heterogeneous ...
Sensitivity Analysis of the Spatial Parameters in Modelling the Evolutionary Interaction Between Autonomous Vehicles and Other Road Users
The road user network is a dynamic, ever-evolving population in which road users interact to share and compete for road space. The advent of autonomous road vehicles (ARVs) will usher in numerous opportunities and challenges in road user dynamics. ...
Implementing Post-quantum Cryptography for Developers
Widely used public key cryptography is threatened by the development of quantum computers. Post-quantum algorithms have been designed for the purpose of protecting sensitive data against attacks with quantum computers. National Institute of ...
On the Complexity of Predicting Election Outcomes and Estimating Their Robustness
When dealing with real-world election data and preferences, it is often realistic to assume that the given data are incomplete or noisy. The reasons for such deficiencies are manifold and range from cost-intensive elicitation to transmission ...
Effects of English-Medium Instruction on Students’ Willingness to Communicate in L2 in EMI Universities
Immersive language experiences have been proven to help foster a stronger willingness to communicate (WTC) in the second language (L2). The study investigated the predictability of communication apprehension (CA) and perceived competence (PC) ...
Innovations and Strategies During Online Teaching in an EdTech Low-Resourced University
The study focused on identifying innovations deployed by lecturers when teaching online during the COVID-19 pandemic at the University of Zambia. The interpretivist worldview anchors the study. Researchers adopted a descriptive qualitative case ...
The Effectiveness of a Blended Learning-Based Life Design Course: Implications of Instruction and Application of Technology
Due to the outbreak of the COVID-19 pandemic in 2021 in Taiwan, we have adapted the face-to-face Life Design course to a blended learning approach with educational technology to cope with the problem of cross-generational confusion and ...
Review on LiDAR-Based Navigation Systems for the Visually Impaired
Visual impairment is a condition that hinders the ability to navigate effectively through surroundings in day-to-day life. Many tools have been designed to help those who are visually impaired navigate. One of the most popular tools is the white ...
Optimal Cost Modeling Scheme for Efficient Intra-Prediction Mode in Video Compression
It can be seen that the success rate of the video compression standard H.264 is quite high owing to its wide range of adoption. However, the legacy version of video compression techniques built on the top of H.264 might ensure reduced bitrate ...
Uncovering Strategies and Commitment Through Machine Learning System Introspection
Deep neural networks are naturally “black boxes”, offering little insight into how or why they make decisions. These limitations diminish the adoption likelihood of such systems for important tasks and as trusted teammates. We design and employ an ...
Integration of Heuristics-Based Energy Optimal Clustering Topology, Routing and Transmission Scheduling for Enhancing Lifetime in IoT Networks
IoT network is future network enabling connected world and man and machines. It is envisioned to provide better comfort to humans and it can revolutionize applications such as smart home, health care, security surveillance, smart meters etc. IoT ...
Deep Learning-Based Approach to Identify the Potato Leaf Disease and Help in Mitigation Using IOT
The major reason for minimizing crop productivity is various diseases in plants. To eliminate the disease-induced losses in plants during growth as well as to increase crop productivity, former disease detection and prevention on the crop are the ...
Analysis of Online Teaching Environment and Satisfaction in the Context of the Epidemic
Many educational institutions have adopted e-learning under the COVID-19 pandemic to maintain school teaching activities. Most teachers were encouraged to use online instruction in early February 2020. Thus, online education has become a sensitive ...
Design and Implementation of Fast and Cost-Effective FPGA-Based Fuzzy Rainbow Tradeoffs
Time/memory tradeoffs are techniques used in cryptanalysis to trade increased memory usage with decreased computation time. We consider the fuzzy-rainbow tradeoff, a powerful technique used in 2010 to attack the GSM A5/1 cipher. We extend the ...
A Steady-State Grouping Genetic Algorithm for the Rainbow Spanning Forest Problem
Given a connected, undirected and edge-colored graph, the rainbow spanning forest (RSF) problem aims to find a rainbow spanning forest with the minimum number of rainbow trees, where a rainbow tree is a connected acyclic subgraph of the graph ...
A Review on Machine Unlearning
Recently, an increasing number of laws have governed the useability of users’ privacy. For example, Article 17 of the General Data Protection Regulation (GDPR), the right to be forgotten, requires machine learning applications to remove a portion ...