This study investigates the structural, thermal, and mechanical properties of Se–Te–Cd chalcogenide glassy alloys by introducing Cd doping into the Se₉₀Te₁₀ system....
PEDOT:PSS-based hydrogel strain sensors have been widely adopted in wearable electronics, human-machine interfaces, and flexible electronics, owing to their wide...
This study presents an energy-aware path-tracking framework for autonomous mobile robots using an Enhanced Whale Optimization Algorithm (E-WOA) to tune a fractional-order...
Tech Science Press is pleased to announce the latest enhancements to the Intelligent Journal System (IJS), introducing an updated interface and a series of workflow improvements to support manuscript...
On 17 June, Clarivate released the 2026 edition of the Journal Citation Reports (JCR). In this year's release, 18 journals published by Tech Science Press (TSP) have received their updated...
Flaviviruses, including Dengue, West Nile, Zika, and Japanese encephalitis viruses, are arthropod-borne RNA viruses that pose an increasing global health...
Cytokines, as key signaling molecules, are involved in the regulation of physiological and pathological processes such as inflammation, immunity, and...
Severe immune-mediated complications following viral infections and vaccinations, including COVID-19 and anti–SARS-CoV-2 immunization, display remarkable...
Structural health monitoring (SHM) of ship piping systems is a core component of predictive maintenance strategies for complex marine engineering systems....
In bearing fault diagnosis for Prognostics and Health Management (PHM), the overall performance of data-driven models is strongly influenced by the coupled...
In industrial and service robotics, autonomous mobile robots must achieve accurate trajectory tracking while maintaining low energy consumption to avoid...
Objectives: Metabolic substrate deficiency is a key factor in many pathologies, with organ vulnerability depending on specialized metabolic profiles....
Cellular senescence and the Senescence-Associated Secretory Phenotype (SASP) play both physiological and pathological roles in the cardiovascular system....
Enterovirus 71 (EV71), a member of the family Picornaviridae, genus Enterovirus, is an agent of hand, foot, and mouth disease (HFMD) and remains a persistent...
Nowadays, battery electric vehicles are increasingly used, from passenger cars to heavy-duty commercial vehicles, trains, and ships, all in an effort...
The big challenge in developing wind energy over the past century, which has focused on environmentally friendly production methods to meet the requirements...
In response to the high energy consumption, large load fluctuations, and insufficient adaptability associated with conventional control strategies in...
Breast cancer (BC) is the most frequently diagnosed malignancy in women worldwide and remains one of the leading causes of cancer-related mortality, with...
Classic Hodgkin lymphoma (CHL) constitutes a B-cell malignant lymphoid neoplasm derived from the germinal center. Despite current treatment protocols...
Antibody–drug conjugates (ADCs) are a promising strategy in non-small cell lung cancer (NSCLC), but early-generation drugs were limited by suboptimal...
Unfavorable epidemiological forecasts indicating a significant increase in cancer incidence and mortality, as well as limitations of traditional cancer...
The rapid evolution of chemical biology, medicinal chemistry, and molecular pharmacology continues to drive the discovery of innovative anticancer compounds...
Cancer development and therapeutic response are governed not only by genetic alterations but also by dynamic regulatory mechanisms at the epigenetic and...
The transition toward decentralized smart grids is reshaping the way energy is generated, exchanged, controlled, and consumed. The increasing penetration...
Cancer remains one of the leading causes of morbidity and mortality worldwide, and its onset and progression are closely linked to dysregulated epigenetic...
The tumor microenvironment (TME) plays a crucial role in cancer progression, metastasis, and resistance to therapy, prompting a shift in focus from targeting...
Tumor biomarkers have become an essential foundation for advancements in cancer diagnosis, prognosis, and targeted therapy. As oncology moves towards...
We propose a special issue titled "Innovative Smart Polymeric Materials for Sustainable Energy Solutions: Bridging Advances in Energy and Biomedical...
Artificial Intelligence of Things (AIoT) is considered a collaborative application of artificial intelligence (AI) and the Internet of Things (IoT). The...
Flaviviruses, including Dengue, West Nile, Zika, and Japanese encephalitis viruses, are arthropod-borne RNA viruses that pose an increasing global health...
Cytokines, as key signaling molecules, are involved in the regulation of physiological and pathological processes such as inflammation, immunity, and...
Severe immune-mediated complications following viral infections and vaccinations, including COVID-19 and anti–SARS-CoV-2 immunization, display remarkable...
Structural health monitoring (SHM) of ship piping systems is a core component of predictive maintenance strategies for complex marine engineering systems....
In bearing fault diagnosis for Prognostics and Health Management (PHM), the overall performance of data-driven models is strongly influenced by the coupled...
In industrial and service robotics, autonomous mobile robots must achieve accurate trajectory tracking while maintaining low energy consumption to avoid...
Objectives: Metabolic substrate deficiency is a key factor in many pathologies, with organ vulnerability depending on specialized metabolic profiles....
Cellular senescence and the Senescence-Associated Secretory Phenotype (SASP) play both physiological and pathological roles in the cardiovascular system....
Enterovirus 71 (EV71), a member of the family Picornaviridae, genus Enterovirus, is an agent of hand, foot, and mouth disease (HFMD) and remains a persistent...
Nowadays, battery electric vehicles are increasingly used, from passenger cars to heavy-duty commercial vehicles, trains, and ships, all in an effort...
The big challenge in developing wind energy over the past century, which has focused on environmentally friendly production methods to meet the requirements...
In response to the high energy consumption, large load fluctuations, and insufficient adaptability associated with conventional control strategies in...
Breast cancer (BC) is the most frequently diagnosed malignancy in women worldwide and remains one of the leading causes of cancer-related mortality, with...
Classic Hodgkin lymphoma (CHL) constitutes a B-cell malignant lymphoid neoplasm derived from the germinal center. Despite current treatment protocols...
Antibody–drug conjugates (ADCs) are a promising strategy in non-small cell lung cancer (NSCLC), but early-generation drugs were limited by suboptimal...
Unfavorable epidemiological forecasts indicating a significant increase in cancer incidence and mortality, as well as limitations of traditional cancer...
The rapid evolution of chemical biology, medicinal chemistry, and molecular pharmacology continues to drive the discovery of innovative anticancer compounds...
Cancer development and therapeutic response are governed not only by genetic alterations but also by dynamic regulatory mechanisms at the epigenetic and...
The transition toward decentralized smart grids is reshaping the way energy is generated, exchanged, controlled, and consumed. The increasing penetration...
Cancer remains one of the leading causes of morbidity and mortality worldwide, and its onset and progression are closely linked to dysregulated epigenetic...
The tumor microenvironment (TME) plays a crucial role in cancer progression, metastasis, and resistance to therapy, prompting a shift in focus from targeting...
Tumor biomarkers have become an essential foundation for advancements in cancer diagnosis, prognosis, and targeted therapy. As oncology moves towards...
We propose a special issue titled "Innovative Smart Polymeric Materials for Sustainable Energy Solutions: Bridging Advances in Energy and Biomedical...
Artificial Intelligence of Things (AIoT) is considered a collaborative application of artificial intelligence (AI) and the Internet of Things (IoT). The...
Federated unlearning (FU) enables the removal of specific data contributions from federated learning (FL) models to comply with regulations such as the General Data Protection Regulation (GDPR). However, most existing FU methods are designed for the FedAvg paradigm, where all clients share a single global model. In practice, personalized federated learning (pFL) methods such as FedPer, FedRep, Ditto, and FedBN have become widely adopted due to their superior handling of non-IID data. These methods decompose…
With the rapid expansion of the Internet of Medical Things (IoMT), the importance of digital identity–based security has significantly increased. However, conventional static authentication mechanisms are insufficient to effectively address various identity misuse and abuse attacks. In this study, we model digital identity as a dynamic security entity and propose an AI-based framework that integrates a risk scoring model—combining unsupervised anomaly detection with context-aware analysis—and a multi-level risk-adaptive access control mechanism (Permit, Step-Up, Restrict). Experimental…
Connected automated driving increasingly relies on cooperative perception from onboard sensors, roadside units (RSUs), smart traffic lights, and vehicle-to-everything (V2X) links, but communication uncertainty can concentrate residual risk on vulnerable road users (VRUs). This study proposes an Ethical-Improved risk-allocation objective for edge-assisted Internet of Vehicles (IoV) cooperative autonomous driving. The objective internalizes responsibility as a bounded risk weight, normalizes equality and maximin terms, and adds explicit VRU tail-risk and VRU/Ego ratio penalties. The evaluation is…
Understanding the determinants of travel mode choice (TMC) in urban contexts is essential for effective transport planning and policy development. Past studies predominantly employed traditional discrete choice models because of their simplicity, diversity, and high interpretability; however, they rely on restrictive assumptions. Although machine learning (ML) techniques have shown promising predictive capabilities, comparative assessments of traditional and ML approaches, particularly considering hyperparameter optimisation, remain limited. This study addresses this gap by comparing a traditional model…
The unique topological properties of the electronic band structures in topological materials have increasingly attracted attention in both fundamental research and next-generation technological applications. With the rise of machine learning, the connection between topological materials and machine learning has deepened significantly. This review systematically summarizes the interaction between these two fields, tracing the history of their mutual promotion and synergistic development. We further examine the transformative impact of machine learning across multiple domains of topological…
Addressing the two critical challenges of missed detection of distant small targets and difficulty in identifying occluded targets under complex road conditions, this paper proposes YOLO-PBE, an improved high-precision vehicle detection model based on YOLOv11n. First, to tackle the fine-grained feature loss caused by conventional strided convolutions during downsampling, we add a high-resolution P2 detection layer and introduce SPD-Conv, a lossless spatial-to-depth feature transformation technique, for feature extraction. By preserving complete pixel-level information, the model's…
The proliferation of Internet of Things (IoT) devices has introduced unprecedented security challenges, necessitating efficient intrusion detection systems (IDS) capable of operating under severe resource constraints. This research presents a hardware-informed empirical study of quantized neural-network-based intrusion detection for resource-constrained IoT platforms, using an ARM Cortex-M4 deployment target as a reference. We evaluate FP32, FP16, and INT8 TensorFlow Lite model variants derived from a lightweight 1D-CNN and assess their trade-offs in clean-data accuracy, model size,…
Plants are fundamental to global food security; however, plant diseases significantly reduce agricultural productivity, making early and accurate detection essential. Traditional inspection approaches rely heavily on manual observation, which is labor-intensive, subjective, difficult to scale, and susceptible to human error. In contrast, artificial intelligence (AI) combined with computer vision (CV) offers an effective solution for early-stage disease detection, minimizing yield losses while overcoming the limitations of manual monitoring systems. In this study, a novel deep…
High-mobility Unmanned Aerial Vehicle (UAV) swarm networks suffer from fast-varying connectivity and interference, and therefore routing decisions must jointly account for link instability and topology changes. By leveraging mobile edge computing (MEC) capabilities, each UAV can perform online routing decisions locally without relying on centralized controllers. This paper develops a Predictive-Q learning framework for dynamic routing under interference and mobility, where the Q-value is trained by a multi-factor reward that explicitly models retransmission costs, predicts…
Accurate forecasting of cryptocurrency prices remains an open challenge because classical statistical models cannot capture the non-linear, sentiment-driven dynamics of these markets. This study compares three hybrid deep learning architectures—VAR-LSTM, XGBoost-LSTM, and CNN-LSTM—to determine which best forecasts Bitcoin (BTC), Ethereum (ETH), and Dogecoin (DOGE) closing prices, and to quantify the marginal predictive value of Twitter sentiment integration. Six years of hourly OHLCV data (2017–2023) are augmented with VADER-scored Twitter sentiment polarity. Each model is formulated…
Automatic Number Plate Recognition (ANPR) is widely used in Intelligent Transportation Systems (ITS) and smart parking applications, but running deep learning-based ANPR directly on low-power edge devices remains difficult because of computation time, memory, and latency limitations. In this study, we develop an edge-oriented ANPR pipeline for an Internet of Things (IoT)-based sensor-triggered stop-and-go smart parking platform, targeting deployment on a resource-constrained edge device. The pipeline combines YOLOv8 for license plate detection, PaddleOCR for text…
The deployment of supervised anomaly detection is typically limited by the high cost of annotation, privacy constraints, and the scarcity of anomalous samples. These constraints have motivated the use of vision-language pre-trained models for zero-shot anomaly detection. However, existing CLIP-based methods still face three limitations: a shared set of prompts is applied across feature layers, anomaly maps are fused by fixed strategies, and image-level anomaly scores are determined solely by global image-text similarity. These limitations…
Automated library migration reduces refactoring costs but challenges traditional evolutionary algorithms, which often suffer from premature convergence and poor recall in sparse, complex API mapping spaces. To address this, we propose QIMIG, a multi-objective optimization framework integrating quantum-inspired encoding with quality-aware and greedy heuristic filtering. QIMIG utilizes a probabilistic Q-bit representation to maintain population diversity and avoid local optima. Simultaneously, its heuristic components leverage historical usage context to filter semantic noise and guide the search
Multimodal Sentiment Analysis (MSA) integrates diverse modalities to identify emotional states, yet performance often suffers in scenarios with missing data. In this situation, despite the promising results of recent methods, the failure of part methods to fully exploit the latent valid information contained in incomplete modalities may degrade predictive performance. Besides, to address the oversight of varying contributions across modalities to sentiment understanding, the score-based weighting schemes in the exhibited methods remain overly sensitive to…
Modern malware is increasingly employing polymorphism, packing, and metamorphism to evade traditional signature-based detection. Because of this, there is an urgency to have more reliable classification systems. Visual malware analysis, where binaries are converted into grayscale images, has demonstrated potential in revealing structural patterns of malware family classification. However, recent methods mostly rely on single-stream, lightweight Convolutional Neural Networks (CNNs). These models have a major blind spot. The visual representation textures can be heavily obscured…
This study proposes a Multi-Stage Sparrow Search Algorithm (MS-SSA) for precise structural damage identification. Initially, the structural static displacement sensitivity formulation is derived via the Sherman-Morrison-Woodbury formula, and an objective function is constructed by integrating the sensitivity equations with the L2-norm penalty. Subsequently, MS-SSA is implemented to sequentially achieve preliminary damage localization and accurate quantification. In the localization phase, a constrained narrow-bound search space is predefined to identify potential damage regions. Leveraging this feedback, the…
Guest Editors: Hung-Yu Lin; Hsing-Ju Wu Deadline: 31 May 2027
Guest Editors: Carlos Vargas-Salgado; Dácil Diaz-Bello Deadline: 30 April 2027
Guest Editors: Leonardo Di G. Sigalotti; Carlos A. Vargas; Carlos E. Alvarado-Rodríguez Deadline: 30 April 2027
Guest Editors: Sabrina Tosi; Annabelle Lewis Deadline: 30 April 2027
Guest Editors: Wenlong Sun; Mengyao Li Deadline: 31 March 2027
Guest Editors: Wenbing Zhao; Pan Wang Deadline: 31 March 2027
Guest Editors: Wenfeng Zheng; Choon Kit Chan; Kyungtae Kang; Chao Liu Deadline: 31 March 2027
Guest Editors: Joanna Zawitkowska; Małgorzata Mitura-Lesiuk; Maciej Dubaj Deadline: 28 February 2027
Guest Editors: Wei-Chiang Hong; Yi Liang; Ming-Wei Li; Zhong-Yi Yang Deadline: 15 February 2027
Guest Editors: Jungpil Shin; Yong Seok Hwang Deadline: 31 January 2027
Guest Editors: Denise Mafra; Jessyca Sousa de Brito Deadline: 31 January 2027
Guest Editors: Qi Chen; Yunhui Tang Deadline: 31 December 2026
Guest Editors: Hung-Yu Lin Deadline: 31 December 2026
Guest Editors: Hoon Ko; Marek R. Ogiela Deadline: 31 December 2026
Guest Editors: Víctor García Deadline: 31 December 2026
Guest Editors: Dawei Jiang; Miaojun Xu; Bo Jiang; Zijian Wu Deadline: 31 December 2026






