2025 March - 92 articles
To tackle the issues of small target sizes, missed detections, and false alarms in aerial drone imagery, alongside the constraints posed by limited hardware resources during model deployment, a streamlined object detection approach is proposed to enh...
Alzheimer’s disease (AD) is a persistent neurologic disorder that has no cure. For a successful treatment to be implemented, it is essential to diagnose AD at an early stage, which may occur up to eight years before dementia manifests. In this...
How can we encourage individuals to engage with beneficial ideas, while eschewing dark ideas such as science denial, conspiracy theories, or populist rhetoric? This paper investigates the mechanisms underpinning individuals’ engagement with ide...
Usable security and privacy in public services are critical considerations in today’s digital age, where governments increasingly rely on technology to deliver services efficiently while safeguarding sensitive information. Successful usage of t...
Household food waste poses significant environmental, social, and financial challenges. This systematic literature review examines the role of games and gamification in mitigating food waste, addressing four key research questions: how these interven...
Over recent years, digital and intelligent technologies have been driving the transformation of discipline-specific information services in academic libraries toward user experience optimization and service innovation. This study constructs a quality...
Federated learning (FL) is a machine learning technique where clients exchange only local model updates with a central server that combines them to create a global model after local training. While FL offers privacy benefits through local training, p...
Based on Automation ML (AML), Intelligent Production Lines (IPLs) for Industry 4.0 can effectively organize multi-dimensional data and models. However, this process requires interdisciplinary and multi-team contributions, which often involve the dual...
Nowadays, grammatical error correction (GEC) has a significant role in writing since even native speakers often face challenges with proficient writing. This research is focused on developing a methodology to correct grammatical errors in the Romania...
Latent tuberculosis infection (LTBI) poses a significant public health challenge, especially in populations with high HIV prevalence and limited healthcare access. Early detection and targeted interventions are essential to prevent the progression of...
The Multi-Layer Blockchain Security Model (MLBSM) proposed in 2024 was designed to safeguard Internet of Things (IoT) networks, as well as similar network architectures, against transaction privacy leakage in public blockchain systems. MLBSM also add...
Human-centered approaches are vital to manage the rapid growth of artificial intelligence (AI) in higher education, where AI-driven applications can reshape teaching, research, and student engagement. This study presents the Human-Centered AI for Sys...
Computer games have emerged as valuable tools for education and training. In particular, serious games, which combine learning with entertainment, offer unique potential for engaging users and enhancing knowledge acquisition. This paper presents a ca...
Recent advances in artificial intelligence (AI) have created opportunities to enhance medical decision-making for patients with discordant chronic conditions (DCCs), where a patient has multiple, often unrelated, chronic conditions with conflicting t...
Electronic Medical Records (EMRs) have the potential to enhance decision-making in the healthcare sector. However, healthcare providers encounter various challenges when using computer-based systems such as EMRs in clinical decision-making. This stud...
With the emergence of artificial intelligence (AI), machine-learning (ML), and chatbot technologies, the field of education has been transformed drastically. The latest advancements in AI chatbots (such as ChatGPT) have proven to offer several benefi...
This Special Issue offers a collection of research and model approaches to fundamental principles, mechanisms, and model architectures closely linked to the conceptual foundations of contemporary neural network research laid down by Stephen Grossberg...
Voice activity detection (VAD) is the process of automatically determining whether a person is speaking and identifying the timing of their speech in an audiovisual data. Traditionally, this task has been tackled by processing either audio signals or...
The rapid development of vehicular networks has facilitated the extensive acquisition of vehicle trajectory data, which serve as a crucial cornerstone for a variety of intelligent transportation system (ITS) applications, such as traffic flow managem...
The frequent emergence of multiple diseases in tomato plants poses a significant challenge to agriculture, requiring innovative solutions to deal with this problem. The paper explores the application of machine learning (ML) technologies to develop a...
Advancements in the field of artificial intelligence have been rapid in recent years and have revolutionized various industries. Various deep neural network architectures capable of handling both text and images, covering code generation from natural...
In the aluminum electrolysis production workshop, heavy-load overhead cranes equipped with multi-functional operation terminals are responsible for critical tasks such as anode replacement, shell breaking, slag removal, and material feeding. The real...
Wireless sensors deployed in large agricultural areas can monitor and collect data in real time, helping to achieve smart agriculture. But the complexity of the environment and the random deployment method seriously affect the coverage quality. The l...
Breast cancer is among the primary causes of cancer-related deaths globally, highlighting the critical need for effective and early diagnostic methods. Traditional diagnostic approaches, while valuable, often face limitations in accuracy and accessib...
In substation working environments, analog dial gauges are widely used for equipment monitoring. Accurate reading of dial values is crucial for real-time understanding of equipment operational status and enhancing the intelligence of substation equip...
Ontologies are critical for organizing and interpreting complex domain-specific knowledge, with applications in data integration, functional prediction, and knowledge discovery. As the manual curation of ontology annotations becomes increasingly infe...
This study analyses future trends in lifelong learning in the Peruvian context. Using the DeflyCompass model, an artificial intelligence tool, the main trends affecting the evolution of postgraduate studies were identified, including the impact of ge...
The online calibration algorithm for camera and LiDAR helps solve the problem of multi-sensor fusion and is of great significance in autonomous driving perception algorithms. Existing online calibration algorithms fail to account for both real-time p...
An ultralow-power, high-performance online-learning and anomaly-detection system has been developed for edge security applications. Designed to support personalized learning without relying on cloud data processing, the system employs sample-wise lea...
Diabetic retinopathy (DR) is the main ocular complication of diabetes. Asymptomatic for a long time, it is subject to annual screening using dilated fundus or retinal photography to look for early signs. Fundus photography and optical coherence tomog...
This paper proposes a solution for guiding visually impaired people to reach predefined locations marked with preregistered passive ultra-high-frequency RFID tags inside public buildings (e.g., secretary’s offices and information desks). Our ap...
The advancement of e-health systems has resulted in substantial enhancements in healthcare delivery via effective data management and accessibility. The use of digital health solutions presents dangers to sensitive health information, including unaut...
MRF-Mixer is a novel deep learning method for magnetic resonance fingerprinting (MRF) reconstruction, offering 200× faster processing (0.35 s on CPU and 0.3 ms on GPU) and 40% higher accuracy (lower MAE) than dictionary matching. It develops a...
This paper explores how generative AI can enhance the modelling and optimization of maintenance policies by incorporating real-time problem-solving techniques into structured maintenance frameworks. Maintenance policies, evolving from simple calendar...
Complex software applications traverse a multitude of running or idling states that depend on their implementation phase (development, testing, debugging, and exploitation). The applications can be monitored by letting them produce descriptive messag...
As yet, there is no systematic review focusing on benefits and issues of commercial deep learning-based auto-segmentation (DLAS) software for prostate cancer (PCa) radiation therapy (RT) planning despite that NRG Oncology has underscored such necessi...
Traditional text classification models predominantly rely on static text representations, failing to capture temporal variations in language usage and evolving semantic meanings. This limitation reduces their ability to accurately classify time-sensi...
Reliable system design is an important component to ensure data processing speed, service availability, and an improved user experience. Several studies have been conducted to provide data processing speeds for health monitors using clouds or edge de...
Wireless power transfer using beamforming technology has recently gained significant attention for sensor networks and embedded systems. This technology uses array antennas and mid-range RF power (15–20 dBm) rectifiers for efficient power deliv...
Conventional inspections in car damage assessments depend on visual judgments by human inspectors, which are labor-intensive and prone to fraudulent practices through manipulating damages. Recent advancements in artificial intelligence have given ris...
Terrestrial and satellite communications, tactical data links, positioning, navigation, and timing (PNT), as well as distributed sensing will continue to require precise timing and the ability to synchronize and disseminate time effectively. However,...
Services rendered by bug hunters have increasingly become an indispensable component of the security culture of organizations. By pre-emptively locating vulnerabilities in their information systems, organizations reduce the risk and the potential imp...
The integration of Deep Learning and Symbolic Artificial Intelligence (AI) offers a promising hybrid framework for enhancing diagnostic accuracy and explainability in critical applications such as COVID-19 detection using computerized tomography (CT)...
Currently, certain complex issues are classified as NP-hard problems, for which there is no exact solution, or they cannot be solved in a reasonable amount of time. As a result, metaheuristic algorithms have been developed as an alternative. These al...
The ability to capture long-distance dependencies is critical for improving the prediction accuracy of spatiotemporal prediction models. Traditional ConvLSTM models face inherent limitations in this regard, along with the challenge of information dec...
The accelerating digitalization of the public and private sectors has made information technologies (IT) indispensable in modern life. As services shift to digital platforms and technologies expand across industries, the complexity of legal, regulato...
In recent years, the misuse of large language models (LLMs) has emerged as a significant issue. This paper focuses on a specific attack method known as the greedy coordinate gradient (GCG) jailbreak attack, which compels LLMs to generate responses be...
Given a question–image input, a visual commonsense reasoning (VCR) model predicts an answer with a corresponding rationale, which requires inference abilities based on real-world knowledge. The VCR task, which calls for exploiting multi-source...
The consensus algorithm is the core technology of blockchain systems to maintain data consistency, and its performance directly affects the efficiency and security of the whole system. Practical Byzantine Fault Tolerance (PBFT) plays a crucial role i...
Aspect-based sentiment analysis (ABSA) through joint task learning aims to simultaneously identify aspect terms and predict their sentiment polarities. However, existing methods face two major challenges: (1) Most existing studies focus on the sentim...
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