This image provides a comprehensive visual summary of our review paper on strategies to enhance tomato resistance against both biotic and abiotic stresses. At the...
Emerging evidence has indicated that sex hormone receptors, including androgen receptor (AR), estrogen receptor-α (ERα), and estrogen receptor-β (ERβ), play an...
This research is about improving the value of agave bagasse residues by extracting cellulose to develop eco-friendly composite materials for biomedical applications....
Berlin (Germany) and Henderson (USA), 12 June 2025 – ResearchGate, the professional network for researchers, and Tech Science Press, a publisher of fully open access journals in science...
The 120th Annual Meeting of the American Urological Association (AUA2025) was successfully held in Las Vegas from April 26 to 29, attracting over 20,000 professionals in the field of urology...
Legged robots have always been a focal point of research for scholars domestically and internationally. Compared to other types of robots, quadruped robots...
Response analysis of structures involving non-probabilistic uncertain parameters can be closely related to optimization. This paper provides a review...
The evaporation of micrometer and millimeter liquid drops, involving a liquid-to-vapor phase transition accompanied by mass and energy transfer through...
Resource allocation remains a challenging issue in communication networks, and its complexity is continuously increasing with the densification of the...
Accurate medical diagnosis, which involves identifying diseases based on patient symptoms, is often hindered by uncertainties in data interpretation and...
Customer segmentation according to load-shape profiles using smart meter data is an increasingly important application to vital the planning and operation...
Conventional fault diagnosis systems have constrained the automotive industry to damage vehicle maintenance and component longevity critically. Hence,...
Magneto-electro-elastic (MEE) materials are a specific class of advanced smart materials that simultaneously manifest the coupling behavior under electric,...
The emergence of various technologies such as terahertz communications, Reconfigurable Intelligent Surfaces (RIS), and AI-powered communication services...
As Natural Language Processing (NLP) continues to advance, driven by the emergence of sophisticated large language models such as ChatGPT, there has been...
Time series segmentation has attracted more interests in recent years, which aims to segment time series into different segments, each reflects a state...
The high performance of IoT technology in transportation networks has led to the increasing adoption of Internet of Vehicles (IoV) technology. The functional...
Software-Defined Networking (SDN) represents a significant paradigm shift in network architecture, separating network logic from the underlying forwarding...
Since the 1950s, when the Turing Test was introduced, there has been notable progress in machine language intelligence. Language modeling, crucial for...
Steganography is a technique for hiding secret messages while sending and receiving communications through a cover item. From ancient times to the present,...
Image steganography is one of the prominent technologies in data hiding standards. Steganographic system performance mostly depends on the embedding strategy....
The tumor microenvironment encompasses not only the tumor cells themselves, but also the surrounding fibroblasts, immunological and inflammatory cells,...
Machine vision detection and intelligent recognition are important research areas in computer vision with wide-ranging applications in manufacturing,...
Object detection and tracking in videos has become an increasingly important area of research due to its potential applications in a variety of domains...
With the progress of science and technology, more and more complex engineering structures are serving in extreme environments. In the service life of...
Extracellular vesicles (EVs) are phospholipid bilayer vesicles released from tumor and non-tumor cells for intercellular communication. EVs contain...
The peridynamics proposed by Silling [1] is a non-local theory of solid mechanics. It redefines the problems by using integral equations rather than partial...
In modern time, experts started to use interdisciplinary properties with the developing of technology and science. Thus, these disciplines provide more...
More than half of the world population is living in cities. It requires extended infrastructure and various services to support the densely concentrated...
Legged robots have always been a focal point of research for scholars domestically and internationally. Compared to other types of robots, quadruped robots...
Response analysis of structures involving non-probabilistic uncertain parameters can be closely related to optimization. This paper provides a review...
The evaporation of micrometer and millimeter liquid drops, involving a liquid-to-vapor phase transition accompanied by mass and energy transfer through...
Resource allocation remains a challenging issue in communication networks, and its complexity is continuously increasing with the densification of the...
Accurate medical diagnosis, which involves identifying diseases based on patient symptoms, is often hindered by uncertainties in data interpretation and...
Customer segmentation according to load-shape profiles using smart meter data is an increasingly important application to vital the planning and operation...
Conventional fault diagnosis systems have constrained the automotive industry to damage vehicle maintenance and component longevity critically. Hence,...
Magneto-electro-elastic (MEE) materials are a specific class of advanced smart materials that simultaneously manifest the coupling behavior under electric,...
The emergence of various technologies such as terahertz communications, Reconfigurable Intelligent Surfaces (RIS), and AI-powered communication services...
As Natural Language Processing (NLP) continues to advance, driven by the emergence of sophisticated large language models such as ChatGPT, there has been...
Time series segmentation has attracted more interests in recent years, which aims to segment time series into different segments, each reflects a state...
The high performance of IoT technology in transportation networks has led to the increasing adoption of Internet of Vehicles (IoV) technology. The functional...
Software-Defined Networking (SDN) represents a significant paradigm shift in network architecture, separating network logic from the underlying forwarding...
Since the 1950s, when the Turing Test was introduced, there has been notable progress in machine language intelligence. Language modeling, crucial for...
Steganography is a technique for hiding secret messages while sending and receiving communications through a cover item. From ancient times to the present,...
Image steganography is one of the prominent technologies in data hiding standards. Steganographic system performance mostly depends on the embedding strategy....
The tumor microenvironment encompasses not only the tumor cells themselves, but also the surrounding fibroblasts, immunological and inflammatory cells,...
Machine vision detection and intelligent recognition are important research areas in computer vision with wide-ranging applications in manufacturing,...
Object detection and tracking in videos has become an increasingly important area of research due to its potential applications in a variety of domains...
With the progress of science and technology, more and more complex engineering structures are serving in extreme environments. In the service life of...
Extracellular vesicles (EVs) are phospholipid bilayer vesicles released from tumor and non-tumor cells for intercellular communication. EVs contain...
The peridynamics proposed by Silling [1] is a non-local theory of solid mechanics. It redefines the problems by using integral equations rather than partial...
In modern time, experts started to use interdisciplinary properties with the developing of technology and science. Thus, these disciplines provide more...
More than half of the world population is living in cities. It requires extended infrastructure and various services to support the densely concentrated...
Road construction and traffic congestion are increasingly recognized as major contributors to environmental and public health challenges in urban Nigeria, particularly in Rivers State. Despite growing urbanization, a gap remains in localized data on the combined effects of air and noise pollution in hydrocarbon-polluted environments. This study addresses that gap by conducting a preliminary environmental health assessment focused on the Port Harcourt Ring Road project. Air quality and noise levels were monitored in situ at 20…
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Data curation is vital for selecting effective demonstration examples in graph-to-text generation. However, evaluating the quality of Knowledge Graphs (KGs) remains challenging. Prior research exhibits a narrow focus on structural statistics, such as the shortest path length, while the correctness of graphs in representing the associated text is rarely explored. To address this gap, we introduce a dual-perspective evaluation framework for KG-text data, based on the computation of structural adequacy and semantic alignment. From a…
Ensuring a sustainable and eco-friendly environment is essential for promoting a healthy and balanced social life. However, decision-making in such contexts often involves handling vague, imprecise, and uncertain information. To address this challenge, this study presents a novel multi-criteria decision-making (MCDM) approach based on picture fuzzy hypersoft sets (PFHSS), integrating the flexibility of Schweizer-Sklar triangular norm-based aggregation operators. The proposed aggregation mechanisms—weighted average and weighted geometric operators—are formulated using newly defined operational laws under the…
This study proposes an advanced vision-based technology for detecting glass products and identifying defects in a smart glass factory production environment. Leveraging artificial intelligence (AI) and computer vision, the research aims to automate glass detection processes and maximize production efficiency. The primary focus is on developing a precise glass detection and quality management system tailored to smart manufacturing environments. The proposed system utilizes the various YOLO (You Only Look Once) models for glass detection, comparing…
This study presents a novel hybrid topology optimization and mold design framework that integrates process fitting, runner system optimization, and structural analysis to significantly enhance the performance of injection-molded parts. At its core, the framework employs a greedy algorithm that generates runner systems based on adjacency and shortest path principles, leading to improvements in both mechanical strength and material efficiency. The design optimization is validated through a series of rigorous experimental tests, including three-point bending…
Deep learning-based object detection has revolutionized various fields, including agriculture. This paper presents a systematic review based on the PRISMA 2020 approach for object detection techniques in agriculture by exploring the evolution of different methods and applications over the past three years, highlighting the shift from conventional computer vision to deep learning-based methodologies owing to their enhanced efficacy in real time. The review emphasizes the integration of advanced models, such as You Only Look Once…
Soilcrete is a composite material of soil and cement that is highly valued in the construction industry. Accurate measurement of its mechanical properties is essential, but laboratory testing methods are expensive, time-consuming, and include inaccuracies. Machine learning (ML) algorithms provide a more efficient alternative for this purpose, so after assessment with a statistical extraction method, ML algorithms including back-propagation neural network (BPNN), K-nearest neighbor (KNN), radial basis function (RBF), feed-forward neural networks (FFNN), and support…
Recent advancements in computational and database technologies have led to the exponential growth of large-scale medical datasets, significantly increasing data complexity and dimensionality in medical diagnostics. Efficient feature selection methods are critical for improving diagnostic accuracy, reducing computational costs, and enhancing the interpretability of predictive models. Particle Swarm Optimization (PSO), a widely used metaheuristic inspired by swarm intelligence, has shown considerable promise in feature selection tasks. However, conventional PSO often suffers from premature convergence and…
Embedding optical fiber sensors into composite materials offers the advantage of real-time structural monitoring. However, there is an order-of-magnitude difference in diameter between optical fibers and reinforcing fibers, and the detailed mechanism of how embedded optical fibers affect the micromechanical behavior and damage failure processes within composite materials remains unclear. This paper presents a micromechanical simulation analysis of composite materials embedded with optical fibers. By constructing representative volume elements (RVEs) with randomly distributed reinforcing fibers,…
Wireless technologies and the Internet of Things (IoT) are being extensively utilized for advanced development in traditional communication systems. This evolution lowers the cost of the extensive use of sensors, changing the way devices interact and communicate in dynamic and uncertain situations. Such a constantly evolving environment presents enormous challenges to preserving a secure and lightweight IoT system. Therefore, it leads to the design of effective and trusted routing to support sustainable smart cities. This…
The increasing deployment of Internet of Things (IoT) devices has introduced significant security challenges, including identity spoofing, unauthorized access, and data integrity breaches. Traditional security mechanisms rely on centralized frameworks that suffer from single points of failure, scalability issues, and inefficiencies in real-time security enforcement. To address these limitations, this study proposes the Blockchain-Enhanced Trust and Access Control for IoT Security (BETAC-IoT) model, which integrates blockchain technology, smart contracts, federated learning, and Merkle tree-based integrity…
Early and accurate detection of Heart Disease (HD) is critical for improving patient outcomes, as HD remains a leading cause of mortality worldwide. Timely and precise prediction can aid in preventive interventions, reducing fatal risks associated with misdiagnosis. Machine learning (ML) models have gained significant attention in healthcare for their ability to assist professionals in diagnosing diseases with high accuracy. This study utilizes 918 instances from publicly available UCI and Kaggle datasets to develop and…
Applying domain knowledge in fuzzy clustering algorithms continuously promotes the development of clustering technology. The combination of domain knowledge and fuzzy clustering algorithms has some problems, such as initialization sensitivity and information granule weight optimization. Therefore, we propose a weighted kernel fuzzy clustering algorithm based on a relative density view (RDVWKFC). Compared with the traditional density-based methods, RDVWKFC can capture the intrinsic structure of the data more accurately, thus improving the initial quality of the…
Flip-chip technology is widely used in integrated circuit (IC) packaging. Molded underfill transfer molding is the most common process for these products, as the chip and solder bumps must be protected by the encapsulating material to ensure good reliability. Flow-front merging usually occurs during the molding process, and air is then trapped under the chip, which can form voids in the molded product. The void under the chip may cause stability and reliability problems. However,…
Unmanned aerial vehicle (UAV) imagery poses significant challenges for object detection due to extreme scale variations, high-density small targets (68% in VisDrone dataset), and complex backgrounds. While YOLO-series models achieve speed-accuracy trade-offs via fixed convolution kernels and manual feature fusion, their rigid architectures struggle with multi-scale adaptability, as exemplified by YOLOv8n’s 36.4% mAP and 13.9% small-object AP on VisDrone2019. This paper presents YOLO-LE, a lightweight framework addressing these limitations through three novel designs: (1) We…
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