Yard crane (YC) operations are critical to the overall productivity of container terminals, especially as terminals move toward higher levels of automation. This study proposes a score-based dispatching strategy for twin RTGCs operating within a sing...
Anomaly detection systems are being studied to detect cyberattacks in industrial control systems (ICSs). Existing ICS anomaly detection systems monitor network packets or operational data. However, these anomaly detection systems cannot detect contro...
Promoting learners’ knowledge construction during inquiry-based learning has long been a central concern in the learning sciences. To support learners’ logical reasoning, this study developed an instructional system integrating generative...
With hybrid electric propulsion attracting increasing attention in the maritime sector, quantitative evaluation of fuel consumption benefits associated with energy storage system (ESS) integration remains limited. Through real operational data of 500...
Large language models (LLMs) are increasingly investigated for abstract screening in systematic reviews, yet it remains unclear whether screening errors attributed to linguistic complexity arise from intrinsic semantic sensitivity or from its interac...
Laboratories across educational levels have traditionally required in-person attendance, limiting practical activities to specific times and physical spaces. This paper presents a technological architecture based on a system-on-chip (SoC) and a conne...
This paper examines whether and how analyst logical inconsistency affects the stock price crash risk in China’s A-share market. The sample includes 3784 listed non-financial companies. The final sample comprises 12,460 firm-year observations fr...
This study aims to analyze and compare the disease activity control and quality of life of patients with rheumatoid arthritis (RA) who were treated with biological products in real-life settings. We tried to determine whether there is a symmetry in t...
This paper describes the modelling of Key Health Indicators (KHI) of frail individuals through non-invasive sensors located in their environment and wearable devices. Primary care professionals defined four indicators for daily health monitoring: sle...
Subarachnoid hemorrhage (SAH) and its major complication, cerebral vasospasm (CVS), present significant challenges for early diagnosis and risk stratification. In this study, we developed interpretable decision tree models to differentiate between he...
Industrial water treatment plants are increasingly dependent on cyber–physical systems (CPS) and automated control processes for their operational safety and efficiency. However, the embedding of digital control networks exposes these critical...
The security of programmable logic controllers (PLCs) that control industrial systems is becoming increasingly critical due to the ubiquity of the Internet of Things technologies and increasingly nefarious cyber-attack activity. Conventional techniqu...
BOOLE is a four-face educational platform integrating analog, combinational-logic, and sequential-logic activities with optional AI-assisted component identification and datasheet support. The system was developed through requirements translation, ci...
In response to the problems of rough modeling and insufficient coverage of edge interaction scenarios in autonomous driving tests, this paper proposes a scene generation method based on interaction coding. The method constructs a hierarchical paramet...
Failure Mode and Effects Analysis (FMEA) remains a fundamental risk management methodology in the automotive industry. This review provides a structured comparative analysis of the classical AIAG FMEA (4th edition, 2008) and the harmonized AIAG &...
This study introduces a novel approach for traffic control systems by using Large Language Models (LLMs) as traffic controllers. The study utilizes their logical reasoning, scene understanding, and decision-making capabilities to optimize throughput...
Analog electronic circuits play an essential role in many industrial applications and control systems. The traditional way of diagnosing failures in such circuits can be an inaccurate and time-consuming process; therefore, it can affect the industria...
In the context of the cross-disciplinary integration of data science and archival management, archival openness auditing stands as a critical process for public information access but faces challenges in processing long texts with sparse core informa...
This study explored whether computer-assisted, project-based learning instruction can help a twice-exceptional (2e) student increase classroom concentration, mathematical concepts, and problem-solving skills. This research used a case study design. T...
Meteorological data from automatic weather stations (AWS) in tea plantations is critical for agricultural management, but is often compromised by sensor errors and physical implausibilities that traditional quality control (QC) methods fail to detect...
As the application of high-altitude solar drones expands, ensuring their safety is paramount. Traditional safety modeling, which relies on manual expert analysis, struggles to keep pace with rapid development cycles. While Large Language Models (LLMs...
The Internet of Things (IoT) is an integrated environment as it merges physical smart objects to the Internet via wireless technologies to share data. The global connectivity of IoT devices brings the needs to ensure security and privacy for data own...
This paper presents an artificial intelligence (AI)-based energy management and control framework for renewable-powered smart microgrids operating under dynamic conditions. The proposed system integrates photovoltaic (PV) generation, battery energy s...
Under the background of the Rural Revitalization Strategy, Zhejiang Province is promoting “Zhejiang-style Vernacular Dwellings” as a crucial measure to enhance the rural living environment and architectural appearance. However, traditiona...
Normative AI assistants are increasingly used in domains governed by duties, permissions, prohibitions, exceptions, priorities, and institutional policies. Existing retrieval-augmented generation (RAG) and legal AI benchmarks evaluate answer accuracy...
Multi-Document Summarization (MDS) is a critical task in natural language processing that aims to condense document clusters into concise and comprehensive summaries. However, existing approaches based on large language models (LLMs) often lack struc...
The coffee leaf miner (Leucoptera coffeella) is a major pest of coffee crops and can cause significant economic losses. Early monitoring is essential to support decision-making for its control. This study aimed to evaluate the potential of fuzzy logi...
This study presents a fully automated, real-time robotic stacking system based on deep learning-driven visual perception, designed to optimize classification and handling tasks on industrial production lines. The proposed system integrates a YOLOv5s-...
Battery energy storage systems (BESSs) play a crucial role in integrating renewable energy sources into microgrids. However, robust BESS controllers are needed to carry out this function properly. Existing controllers suffer from overshoots and slow...
Email remains a major Initial Access vector for phishing and ransomware attacks, requiring security mechanisms that can combine multiple sources of threat evidence before malicious content reaches end users. Modern commercial email gateways already i...
We developed an augmented Sungka board that integrates traditional Filipino gameplay with embedded sensor technology. Each pit is equipped with load cell sensors and HX711 analog-to-digital converters to accurately detect marble distribution and move...
Parkinson’s disease (PD) is a progressive neurodegenerative disorder that impairs motor function, often causing tremors and difficulty with movement control. A promising diagnostic method involves analyzing hand-drawn patterns, such as spirals...
Innovation has been elevated beyond the traditional forces of production, by the emergence of a new wave of industrial upgrading and the technological revolution, to become a significant force in the advancement of human society. Can an enterprise gr...
Specialty crop industries generate heterogeneous knowledge across cultivation, pest and disease management, post-harvest handling, quality control, and marketing, yet this knowledge is often dispersed across technical documents, web resources, relati...
Which runtime governance mechanisms reduce physical risk when a learned controller drives a building’s climate, and under what conditions? We develop a closed-loop software-in-the-loop testbed in which a setpoint model trained on real occupancy...
This paper presents a maritime Internet of Things anti-theft architecture based on an ESP32 onboard node, local motion analysis, and LoRa mesh communication. The proposed detection pipeline uses a one-dimensional convolutional autoencoder trained on...
Mild cognitive impairment (MCI) is when brain function declines. MCI is the gray area transitioning from normal aging to the AD stage. Currently, the majority of early MCI diagnoses are processed through comprehensive neuropsychological tests. These...
Probiotics can alter brain function via the gut–brain axis. We investigated the effect of a probiotic mixture containing Bifidobacterium longum, Lactobacillus helveticus and Lactiplantibacillus plantarum. In a randomized, placebo-controlled, do...
The Multi-Demand Multidimensional Knapsack Problem (MDMKP) combines upper-bound capacities and lower-bound demands, producing a restrictive feasible region. We study three swap-based repair-intensification policies in a common hybrid framework: light...
Large Language Models (LLMs) show promise for supporting formative assessment by generating feedback on students’ written mathematical reasoning. However, practical use in educational settings remains constrained by the need to manually curate...
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Nephrology requires students to integrate nephron transport, hormonal regulation, medication effects, and serum and urine electrolyte patterns, which can be difficult to represent with static instructional materials. This study describes the developm...
Cloud computing (CC) refers to an Internet-based computing technology in which shared resources, such as storage, software, information, and platform, are offered to users on demand. CC is a technology through which virtualized and dynamically scalab...
Many training programs have been designed using modern software to restore the impaired cognitive functions in patients with acquired brain damage (ABD). The objective of this study was to evaluate the effectiveness of a computer-based training progr...
Based on the elemental composition of 359 samples of dry wines (Riesling, Chardonnay, Muscat, Cabernet Sauvignon, and Merlot) produced in the Krasnodar Territory (Russia), the influence of data clustering on the generalizing properties of neural netw...
The increasing dependence of financial supply chains on digital infrastructures has made it more necessary to design secure, resilient, and reliable networks than ever before. This research presents a self-healing framework based on blockchain and di...
We conducted a standardized spatial thinking ability test (STAT) to examine the spatial thinking abilities of a group of Chinese undergraduates with a focus on their spatial reasoning, which is a very important component of critical spatial thinking....
Fault Detection and Diagnosis (FDD) in complex industrial systems requires methods that can handle uncertain operating conditions, soft thresholds, evolving sensor behavior, and increasing volumes of heterogeneous data. Traditional model-based or rul...
Highway traffic incident management is a dynamic and time-dependent process, and rapidly and accurately predicting its complete sequence of actions and corresponding time schedule is essential for improving the refinement and intelligence of traffic...
Metric-based software security plays a crucial role in allowing software developers to make informed decisions about their development practices, while also allowing software users to evaluate the security risks associated with the software they use....
In this study, a decision-level detection framework is presented and evaluated; it integrates sensor data (e.g., temperature, humidity, gas readings) with machine learning (ML) models and computer vision-based smoke and fire detection systems, in an...
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