Road traffic accidents regarding commercial vehicles have been demonstrated as an important culprit restricting the steady development of the social economy, which are closely related to the distracted behavior of drivers. However, the existing drive...
As a safety-related application, visual systems based on deep neural networks (DNNs) in modern unmanned aerial vehicles (UAVs) show adversarial vulnerability when performing real-time inference. Recently, deep ensembles with various defensive strateg...
For successful human–robot collaboration, it is crucial to establish and sustain quality interaction between humans and robots, making it essential to facilitate human–robot interaction (HRI) effectively. The evolution of robot intelligen...
Deep neural networks (DNNs) have been widely utilized in automatic visual navigation and recognition on modern unmanned aerial vehicles (UAVs), achieving state-of-the-art performances. However, DNN-based visual recognition systems on UAVs show seriou...
Physical activity recognition based on sensors is a growing area of interest given the great advances in wearable sensors. Applications in various domains are taking advantage of the ease of obtaining data to monitor personal activities and behavior...
Human activity recognition has gained more interest in several research communities given that understanding user activities and behavior helps to deliver proactive and personalized services. There are many examples of health systems improved by huma...
Queue systems are practically used in various institutions and commercial enterprises constituting a challenge for the intelligent environments in smart cities. The management of the flow of customers guarantees the elimination or reduction of the qu...
This paper introduces a novel system that utilizes OpenPose for skeleton estimation to enable a tabletop robot to interact with humans proactively. By accurately recognizing upper-body poses based on the skeleton information, the robot autonomously a...
Automated vision-based hazard detection algorithms are being rapidly developed to provide hazard alerts for construction workers. However, these alerting systems often apply a fixed low-beta alerting threshold, which can cause excessive false alarms,...
This study introduces a novel system, termed NAVIBox, designed to proactively identify vehicle–pedestrian risks using vision sensors deployed within edge computing devices in the field. NAVIBox consolidates all operational components into a sin...
Cyberattacks, especially Advanced Persistent Threats (APTs), have become more complex. These evolving threats challenge traditional defense systems, which struggle to counter long-lasting and covert attacks. Cybersecurity Knowledge Graphs (CKGs), ena...
This review examines respiratory complications in autoimmune rheumatic diseases within intensive care units (ICUs). The respiratory system, primarily affected in diseases like rheumatoid arthritis, systemic lupus erythematosus, and scleroderma, often...
Recently, deep learning algorithms have been increasingly applied in construction for activity recognition, particularly for excavators, to automate processes and enhance safety and productivity through continuous monitoring of earthmoving activities...
Driver distraction is a key factor contributing to traffic accidents. However, in existing computer vision-based methods for driver attention state recognition, monocular camera-based approaches often suffer from low accuracy, while multi-sensor data...
A personalized framework for smart home automation is introduced, utilizing machine learning to predict user activities and allow for the context-aware control of living spaces. Predicting user activities, such as ‘Watch_TV’, ‘Sleep...
Educational institutions are increasingly focused on supporting students who may be facing academic challenges, aiming to enhance their educational outcomes through targeted interventions. Within this framework, leveraging advanced deep learning tech...
Failure to rescue (FTR), defined as death following a potentially treatable postoperative complication, has emerged as a critical quality metric in thoracic surgery. In patients undergoing lung cancer resection, who are often at high risk due to como...
This study presents the design and validation of an integrated fire safety system that leverages edge AI, hybrid sensing, and precision suppression to overcome the latency and collateral limitations of conventional smoke detection and sprinkler syste...
Spodoptera frugiperda is a globally significant migratory agricultural pest that requires proactive monitoring. Understanding the molecular mechanisms underlying the interactions between pathogenic microorganisms and S. frugiperda is crucial for enha...
This study presents a method to support ship trajectory prediction at waterway confluences using historical Automatic Identification System (AIS) data. The method is meant to improve the recognition accuracy of ship behavior trajectory, assist in the...
Plantations are not inherently normal, yet they have been normalized within traditional agricultural landscapes. This is the premise through which we explore why plantations thrive despite numerous social and ecological drawbacks. Accordingly, the ai...
In this paper, the concept of symmetry is utilized to inform the structural design of our multi-sensor fusion framework—that is, the hierarchical feature extraction and spatial–temporal correlation modeling exhibit symmetrical properties...
Preventable adverse drug events (ADEs) remain a significant threat in community settings, a challenge that is critical in community pharmacy settings where continuity of care and healthcare access can be limited. This qualitative study explored the p...
Oral health’s association with general health, morbidity, and mortality in older adults highlights its importance for healthy aging. Poor oral health is not an inevitable consequence of aging, and a proactive, multidisciplinary approach to earl...
In the shift toward sustainable and resource-efficient manufacturing, Artificial Intelligence (AI) is playing a transformative role in overcoming the limitations of traditional production scheduling methods. This study, based on a Systematic Literatu...
Traditionally, traffic characteristics such as speed, volume, and travel time are obtained from a range of sensors and systems such as inductive loop detectors (ILDs), automatic number plate recognition cameras (ANPR), and GPS-equipped floating cars....
Urban Air Mobility (UAM) emerges as a transformative approach to address urban congestion and pollution, offering efficient and sustainable transportation for people and goods. Central to UAM is the Operational Digital Twin (ODT), which plays a cruci...
The integration of advanced computer vision and artificial intelligence (AI) techniques into collaborative robotic systems holds the potential to revolutionize human–robot interaction, productivity, and safety. Despite substantial research acti...
The primary purpose of video surveillance is to monitor public indoor areas or the boundaries of secure facilities to safeguard them against theft, unauthorized access, fire, and various other potential threats. Security cameras, equipped with integr...
Pedestrian safety is a major concern in urban areas, and crosswalks are one of the most critical locations where accidents can occur. This research introduces an intelligent crosswalk, employing sensor fusion and machine learning techniques to distin...
Digital twins (DTs), virtual replicas that integrate mechanistic modeling with real-time clinical data, are emerging as powerful tools in healthcare with particular promise in pediatrics, where age-dependent physiology and ethical considerations comp...
Within the vast landscape of the Built Environment, where challenges of uncertainty abound, this paper ventures into a detailed exploration of antifragile planning. Antifragility, a concept rooted in the capacity of systems to not only withstand but...
This paper presents the design of an autonomous humanoid robot designed to optimize and enrich customer service in showrooms, e.g., electronic equipment, mobile network operators, and generally in stores with various articles. The proposed humanoid r...
Despite advanced aviation safety systems, recurring operational failures demonstrate that current safety management system (SMS) implementation practices remain predominantly reactive, with organizations adopting SMS frameworks theoretically embracin...
Vehicle fault detection and diagnosis (VFDD) along with predictive maintenance (PdM) are indispensable for early diagnosis in order to prevent severe accidents due to mechanical malfunction in urban environments. This paper proposes an early voicepri...
Construction accidents continue to threaten worker safety despite advances in management systems. Existing research catalogs accident attributes but rarely explains how triggers like human error, equipment failure, or procedural lapses interact with...
High-Speed Rail (HSR) has long been proposed as a transformative infrastructure project for Australia; yet, despite multiple feasibility studies and significant government expenditure, it remains unrealized. This study investigates the key barriers p...
Integration of machine learning (ML) and artificial intelligence (AI) into point-of-care (POC) sensor systems represents a transformative advancement in healthcare. This integration enables sophisticated data analysis and real-time decision-making in...
This qualitative study examines how school administrators enact “heartfelt leadership”—a socially and emotionally attuned form of leadership—within Türkiye’s bureaucratic school cultures. Using semi-structured inter...
Malware detection using hybrid features, combining binary and hexadecimal analysis with DLL calls, is crucial for leveraging the strengths of both static and dynamic analysis methods. Artificial intelligence (AI) enhances this process by enabling aut...
This study contributes to the broader sustainability discourse by evaluating public knowledge, awareness, and practices regarding air pollution among residents of Hanoi, Vietnam, focusing on its causes, health impacts, and mitigation strategies. A cr...
Background: One in four New Zealanders identify as disabled. Disabled people, including Māori (the indigenous people of New Zealand (NZ)), experience health disparities. Systemic and individual health professional (HP) biases are factors that ma...
Pedestrian panic behavior is a primary cause of overcrowding and stampede accidents in public micro-road network areas with high pedestrian density. However, reliably detecting such behaviors remains challenging due to their inherent complexity, vari...
With the acceleration of urbanization and the continuous expansion of building stock, building maintenance plays a critical role in ensuring structural safety, extending service life, and promoting sustainable development. In recent years, the applic...
Interest in advanced driver assistance systems (ADAS) is booming in recent years. One of the most effervescent ADAS features is blind spot detection (BSD), which uses radar sensors or cameras to detect vehicles in the blind spot area and alerts the d...
The main purpose of a detection system is to ascertain the state of an individual’s eyes, whether they are open and alert or closed, and then alert them to their level of fatigue. As a result of this, they will refrain from approaching an accid...
As the frequency of cyberattacks rises, extracting actionable cyber threat intelligence (CTI) from diverse online sources has become critical for proactive threat detection and defense. Named entity recognition (NER) serves as a foundational task in...
Acute kidney injury (AKI) is a frequent and severe complication in trauma patients, affecting up to 28% of intensive care unit (ICU) admissions and contributing significantly to morbidity, mortality, and long-term renal impairment. Trauma-related AKI...