Search Results (640)

Reliable acupoint localization is essential for developing artificial intelligence (AI) and extended reality (XR) tools in traditional Korean medicine; however, conventional annotation of 2D images often suffers from inter- and intra-annotator variability. This study presents a low-cost dual-camera imaging system that fuses infrared (IR) and RGB views on a Raspberry Pi 5 platform, incorporating an IR ink pen in conjunction with a 780 nm emitter array to standardize point visibility. Among the tested marking materials, the IR ink showed the highest contrast and visibility under IR illumination, making it the most suitable for acupoint detection. Five feature detectors (SIFT, ORB, KAZE, AKAZE, and BRISK) were evaluated with two matchers (FLANN and BF) to construct representative homography pipelines. Comparative evaluations across multiple camera-to-surface distances revealed that KAZE + FLANN achieved the lowest mean 2D Error (1.17 ± 0.70 px) and the lowest mean aspect-aware error (0.08 ± 0.05%) while remaining computationally feasible on the Raspberry Pi 5. In hand-image experiments across multiple postures, the dual-camera registration maintained a mean 2D error below ~3 px and a mean aspect-aware error below ~0.25%, confirming stable and reproducible performance. The proposed framework provides a practical foundation for generating high-quality acupoint datasets, supporting future AI-based localization, XR integration, and automated acupuncture-education systems. Full article

The transportation industry and transportation infrastructure are undergoing a profound transformation due to advances in the development of artificial intelligence (AI) algorithms that are not just a concept of the future but a reality. Advanced algorithms, predictive systems, and intelligent automation contribute to optimizing logistics, reducing costs, increasing safety, and reducing traffic congestion. AI is also used to optimize routes by analyzing multiple variables, such as distance, traffic, time constraints, and user preferences, to generate optimal routes between departure and destination points. Route planning systems can be integrated with real-time data on traffic, planned or unforeseen events, and other conditions that may affect the trip. AI algorithms can use this data to adapt routes and estimated arrival times based on changes in traffic or other conditions. The purpose of this article is to develop a model for predicting traffic flows at intersections based on historical and real-time data. The focus is on the genetic algorithm used to optimize a Long Short-Term Memory (LSTM) encoder–decoder. Specifically, the research aims to determine how well the proposed model performs when the data is optimized using the genetic algorithm. The results obtained for the proposed GA-LSTM show an average TTS reduction of −18.7%, a maximum improvement of −27.3%, an RMSE of 0.003587, and an MSE of 0.00348 compared to traditional models used in real time for traffic management. Finally, the performance of GA-LSTM was compared with the results reported in the literature to demonstrate the usefulness of the proposed algorithm. Full article

Rural areas across Europe, particularly in the Balkans, are confronting a challenging and uneven negative transformation, marked by depopulation, economic stagnation and the degradation of their vernacular heritage. Assessing the unique dynamics and historical reality of these settlements proves difficult because conventional sustainability assessment systems are typically urban-focused and static. To address the methodological shortfall, this research introduces the Living Palimpsest Profile (LPP), a novel framework that conceptualizes rural settlements as layered landscapes in which time is treated as an endogenous variable in the sustainability equation. Employing the palimpsest metaphor, the LPP integrates a rigorous qualitative assessment, validated through convergent verification, with a hierarchical Framework of Visions. The framework was applied successfully to two Balkan case studies, demonstrating capacity to capture local specificity and inform contextual policy segmentation in line with the Sustainable Development Goals (SDGs). Given its significant transferability to other heritage-rich regions, the LPP is positioned as an essential methodological solution for the sustainable development of vernacular settlements worldwide. Full article

In recent years, telework (TW) has been seen as a feasible and flexible alternative to deal with global and market risks; however, companies’ lack of vision and planning to implement it has generated the reality that TW, far from bringing advantages, generates personal and social labour conflicts. The objective of this research is to design a TW adoption sustainable process (TW-ASP) that guides the development of organizational strategies to maximize benefits and mitigate challenges for companies, employees, and society. This qualitative study comprises three phases: a review of previous research in Web of Science, identification and inter-relation of relevant variables, and TW-ASP design using Cooper’s stage-gate methodology. The process includes three stages, and each one has a gate: TW thinking, TW decision, and TW adoption. Each stage and gate is structured according to linkages between technological, organizational, labour, and social variables. TW-ASP positions TW as a sustainable initiative requiring a holistic and systemic approach. This study offers a proposal that can serve as a reference for designing organizational strategies aimed at sustainability. Full article

Background: Exposure therapy is an established intervention for treating specific phobias. This study evaluates a Virtual Exposure Therapist (VET), a virtual reality (VR)-based system enhanced with artificial intelligence (AI), designed to reduce spider fear symptoms. Methods: The VET system delivers three progressive exposure scenarios involving interactive 3D spider models and features an adaptive relaxation mode triggered when physiological stress exceeds preset thresholds. AI integration is rule-based, enabling real-time adjustments based on session duration, head movement (degrees/s), and average heart rate (bpm). Fifty-five participants (aged 18–35) with self-reported moderate to high fear of spiders completed seven sessions using the VET system. Participants were not clinically diagnosed, which limits the generalizability of findings to clinical populations. Ethical approval was obtained, and informed consent was secured. Behavioral responses were analyzed using AR(p)–GARCH (1,1) models to account for intra-session volatility in anxiety-related indicators. The presence of ARCH effects was confirmed through the Lagrange Multiplier test, validating the model choice. Results: Results demonstrated a 21.4% reduction in completion time and a 16.7% decrease in average heart rate across sessions. Head movement variability declined, indicating increased user composure. These changes suggest a trend toward reduced phobic response over repeated exposures. Conclusions: While findings support the potential of AI-assisted VR exposure therapy, they remain preliminary due to the non-clinical sample and absence of a control group. Findings indicate expected symptom improvement across sessions; additionally, within-session volatility metrics (persistence/half-life) provided incremental predictive information about later change beyond session means, with results replicated using simple volatility proxies. These process measures are offered as complements to standard analyses, not replacements. Full article

Background/Objectives: Outpatient stroke rehabilitation is expanding as inpatient episodes shorten. Virtual reality (VR) exergaming can extend practice and standardize progression, but setting-specific effectiveness and implementation factors remain unclear. This scoping review mapped VR exergaming in outpatient stroke care and identified technology typologies and functional outcomes. Methods: Guided by the JBI Manual and PRISMA-ScR, searches of MEDLINE, Embase, CENTRAL, Scopus, and Web of Science were conducted in April 2025. The study included adults post-stroke undergoing VR exergaming programs with movement tracking delivered in clinic-based outpatient or home-based outpatient settings. Interventions focused on functional rehabilitation using interactive VR. Results: Sixty-six studies met the criteria, forty-four clinic-based and twenty-two home-based. Serious games accounted for 65% of interventions and commercial exergames for 35%. Superiority on a prespecified functional endpoint was reported in 41% of trials, 29% showed within-group improvement only, and 30% found no between-group difference; effects were more consistent in supervised clinic programs than in home-based implementations. Signals were most consistent for commercial off-the-shelf and camera-based systems. Gloves or haptics and locomotor platforms were promising but less studied. Head-mounted display interventions showed mixed findings. Adherence was generally high, and adverse events were infrequent and mild. Conclusions: VR exergaming appears clinically viable for outpatient stroke rehabilitation, with the most consistent gains in supervised clinic-based programs; home-based effects are more variable and sensitive to dose and supervision. Future work should compare platform types by therapeutic goal; embed mechanistic measures; strengthen home delivery with dose control and remote supervision; and standardize the reporting of fidelity, adherence, and cost. Full article

Background/Objectives: This study evaluated the effects of virtual reality (VR) on functionality, quality of life, and motivation in children with cerebral palsy (CP). Methods: The systematic review was registered in PROSPERO (CRD42022321170) and conducted using the keywords physical therapy OR physiotherapy AND “Virtual Reality”. Studies were screened based on title, abstract, and full-text review. The PEDro scale was used to assess methodological quality, and the GRADE system was applied to determine the level of certainty of the evidence. Results: A total of 10 studies showed improvements in balance, 6 in gross motor function, and 8 in upper limb coordination. Additional gains were found in daily functioning (6), gait (4), motivation (3), and spasticity (1–2). Overall, virtual reality enhanced motor abilities and engagement compared with conventional therapy, underscoring its value as a playful and motivating tool in rehabilitation. All outcome measures showed positive changes, particularly in functionality and quality of life. The primary outcomes with the most favorable responses to intervention were gross motor function and balance, followed by motivation and adherence. However, the generalities of the findings are limited due to variabilities in outcome reporting and measurement tools. Conclusions: The findings indicated clinical improvements in key outcome measures following VR interventions. Nonetheless, there were significant variabilities in the evaluation instruments used across studies. Despite this, the clinical evidence supported the integration of VR into neurorehabilitation processes for children with CP. Full article

Driving in snowy conditions challenges both human drivers and autonomous systems. Snowfall and ice accumulation impair vehicle control and affect driver perception and performance. Road markings are often obscured, forcing drivers to rely on intuition and memory to stay in their lane, which can lead to encroachment into adjacent lanes or sidewalks. Current lane detectors assist in lane keeping, but their performance is compromised by visual disturbances such as ice reflection, snowflake movement, fog, and snow cover. Furthermore, testing these systems with users on actual snowy roads involves risks to driver safety, equipment integrity, and ethical compliance. This study presents a low-cost virtual reality simulation for evaluating winter lane detection in controlled and safe conditions from a human-in-the-loop perspective. Participants drove in a simulated snowy scenario with and without the detector while quantitative and qualitative variables were monitored. Results showed a 49.9% reduction in unintentional lane departures with the detector and significantly improved user experience, as measured by the UEQ-S (p = 0.023, Cohen’s d = 0.72). Participants also reported higher perceived safety, situational awareness, and confidence. These findings highlight the potential of vision-based lane detection systems adapted to winter environments and demonstrate the value of immersive simulations for user-centered testing of ADASs. Full article

The use of saline water (low-quality water) in irrigation is a reality in many regions, especially in areas where fresh water is scarce, like semi-arid regions. However, it is important to adopt strategies to minimize the damage caused by salt stress to plants. The use of soil conditioners can help improve soil structure and water retention capacity, reducing salinity effects. The objective was to analyze the potential of a soil conditioner (hydrogel) as a mitigator of salty stress by irrigation with saline water in ornamental sunflower. Two sunflower cycles were carried out in a protected environment with a factorial 4 × 4 consisting of four doses of hydrogel polymer (0.0, 0.5, 1.0, and 1.5 g kg⁻¹) and four different levels of irrigation with saline water (0.5, 2.0, 3.5, and 5.0 dS m⁻¹). Plant biomass and physiological parameters, such as chlorophyll fluorescence measurements and gas exchange parameters, stomatal conductance, transpiration, and photosynthesis, were evaluated. Ornamental sunflower showed better performance with a saline water of 0.5 dS m⁻¹ without the use of hydrogel. At higher salinity levels, with a hydrogel dose of 1.5 g kg⁻¹, the sunflower achieved favorable performance, promoting gains in some gas exchange variables in plants irrigated with saline water at 3.5 dS m⁻¹ and in fluorescence-related variables within the range of 2.0 to 3.5 dS m⁻¹. This positive effect of hydrogel indicates its potential as a mitigating strategy against the adverse effects of salinity, contributing to the maintenance of plant vigor and physiological functionality in saline environments. Full article

Fractional-order chaotic systems have received increasing attention over the past few years due to their ability to effectively model memory and complexity in nonlinear dynamics. Nonetheless, most of the research conducted so far has been on constant-order formulations, which still have some limitations in terms of adaptability and reality. Thus, to evade these limitations, we present a recently designed four-dimensional hyperchaotic Chen system with variable-order fractional (VOF) derivatives in the Liouville–Caputo sense. In comparison with constant-order systems, the new system possesses excellent performance in numerous aspects. Firstly, with the use of variable-order derivatives, the system becomes more adaptive and flexible, allowing the chaotic dynamics of the system to evolve with changing fractional orders. Secondly, large-scale numerical simulations are conducted, where phase portrait orbits and time series for differences in VOF directly illustrate the effect of the order function on the system’s behavior. Thirdly, qualitative analysis is performed with the help of phase portraits, time series, and Lyapunov exponents to confirm the system’s hyperchaotic behavior and sensitivity to initial and control parameters. Finally, the model developed demonstrates a wide range of dynamic behaviors, which confirms the sufficient efficiency of VOF calculus for modeling complicated nonlinear processes. Numerous analyses indicate that this research not only shows meaningful findings but also provides thoughtful methodologies that might result in subsequent research on fractional-order chaotic systems. Full article

Since the 1960s, theories on the relationship between people and their environment have explored how elements of the built environment may directly or indirectly influence human behavior. In this context, neuroarchitecture is emerging as an interdisciplinary field that integrates neuroscience, architecture, environmental psychology, and cognitive science, with the aim of providing empirical evidence on how architectural spaces affect the human brain. This study investigates the potential of neuroarchitecture to inform environmental design by clarifying its current conceptual framework, examining its practical applications, and identifying the context in which it is being implemented. Beginning with an in-depth analysis of the definition of neuroarchitecture, its theoretical foundations, and the range of interpretations within the academic community, the study then offers a critical review of its practical applications across various design fields. By presenting a comprehensive overview of this emerging discipline, the study also summarizes the measurement techniques commonly employed in related research and critically evaluates design criteria based on observed human responses. Ultimately, neuroarchitecture represents a promising avenue for creating environments that deliberately enhance psychological and physiological well-being, paving the way toward truly human-centered design. Nevertheless, neuroarchitecture is still an emerging experimental field, which entails significant limitations. The experiments conducted are still limited to virtual reality and controlled experimental contexts. In addition, small and heterogeneous population samples have been tested, without considering human variability. Full article

Traditional training methods for first responders are often limited by time, resources, and safety constraints, which reduces their consistency and effectiveness. This study focused on two main issues: whether exposure to virtual reality training scenarios induces measurable physiological changes in heart rate and heart rate variability, and whether these responses differ between police and firefighter contexts. The aim of this study was to explore the integration of virtual reality technologies into responder training and to evaluate how biomedical monitoring can be used to assess training effectiveness. A pilot measurement was conducted with ten participants who completed systematic crime scene investigation scenarios in both domains. Heart activity was continuously recorded using a wearable sensor and analyzed for heart rate and heart rate variability parameters, while cognitive load and task performance were also assessed. The collected data were statistically evaluated using tests of normality and paired comparisons between baseline and virtual reality phases. The results showed a significant increase in heart rate and a decrease in heart rate variability during virtual reality exposure compared to baseline, with higher cognitive load and success rates in police scenarios compared to firefighter scenarios. These findings indicate that virtual reality scenarios can elicit measurable psychophysiological responses and highlight the potential of combining immersive technologies with biomedical monitoring for the development of adaptive and effective training methods for first responders. Full article

Background/Objectives: Incomplete spinal cord injury (iSCI) represents a significant challenge in neurorehabilitation, with conventional limitations including recovery plateaus and declining patient motivation. Virtual reality (VR) and augmented reality (AR) have emerged as promising technologies to supplement traditional therapy through gamification and multisensory feedback. This systematic review and meta-analysis evaluates the effectiveness of VR and AR interventions for improving balance and locomotor function in patients with incomplete spinal cord injury. Methods: A systematic review was conducted following PRISMA guidelines, with searches in PubMed, Scopus, Web of Science, Science Direct, and Google Scholar. Randomized controlled trials and high-quality controlled studies evaluating VR/AR interventions in patients with iSCI (American Spinal Injury Association Impairment Scale [AIS] classifications B, C, or D) for a minimum of 3 weeks were included. A random-effects meta-analysis (Standardized Mean Difference, SMD; 95% Confidence Interval, CI) was conducted for the balance outcome. Results: Eight studies were included (n = 142 participants). The meta-analysis for balance (k = 5 studies) revealed a statistically significant improvement with a large effect size (SMD = 1.21, 95% CI: 0.04–2.38, p = 0.046). For locomotor function, a quantitative meta-analysis was not feasible due to a limited number of methodologically homogeneous studies; a qualitative synthesis of this evidence remained inconclusive. Substantial heterogeneity was observed in the balance analysis (I² = 81.5%). No serious adverse events related to VR/AR interventions were reported. Conclusions: VR/AR interventions show potential as an effective adjunctive therapy for improving balance in patients with iSCI, though the benefit should be interpreted with caution due to considerable variability between studies. The current evidence for locomotor function improvements is insufficient to draw conclusions, highlighting a critical need for more focused research. Substantial heterogeneity indicates that effectiveness may vary according to specific intervention characteristics, populations, and methodologies. Larger multicenter studies with standardized protocols are required to establish evidence-based clinical guidelines. Full article

Rotary dryers are widely used in industry for their ease of operation in processing large volumes of material continuously despite persistent challenges in energy efficiency, cost-effectiveness, and safety. Addressing the need for effective operator training, the purpose of this study is to develop virtual reality (VR) environments for industrial rotary dryers. Visual and behavioral aspects were considered in the methodology for developing the environments for two application cases—ammonium nitrate and low-rank coal drying. Visual aspects considered include the industrial-scale geometry and detailed components of the rotary dryer, while behavioral aspects were governed by mathematical modeling of heat and mass transfer phenomena. The case studies of ammonium nitrate and low-rank coal were selected due to their industrial relevance and contrasting drying characteristics, ensuring the versatility and applicability of the developed VR environments. The main contribution of this work is the embedding of validated mathematical models—expressed as ordinary differential equations—into these environments. The numerical integration of these models provides key process variables, such as solid temperature and moisture content along the rotary dryer, thereby enhancing the behavioral realism of the developed VR environments. Full article

This study interrogates whether Augmented Reality (AR) enhances vocabulary and content acquisition within Content and Language Integrated Learning (CLIL), situating the question in the broader debate on how immersive, multimodal technologies shape achievement and engagement. This study’s novelty lies in its direct AR-versus-print comparison in a real CLIL classroom using markerless, smartphone-based technology. Using a mixed-methods, classroom-based experiment, we drew on a convenience sample of 129 secondary students (ages 16–18), assigning them to an AR intervention (n = 64) or a print-based control (n = 65). Both cohorts received parallel instruction covering identical objectives and materials; vocabulary attainment was gauged using matched pretest and post-test measures, while engagement, attitudes, and perceived usefulness were captured through paired pre- and post-surveys and open-ended prompts. Quantitative analyses compared change scores across conditions and were complemented by qualitative summaries of learner comments. Results indicate that exposure to AR exerted a positive influence on learners’ engagement and supported learning processes, with perceptible shifts in students’ views of AR between baseline and post-intervention; nevertheless, effects were heterogeneous across instruments, items, and subgroups, suggesting that benefits accrued in a targeted rather than uniform fashion. Compared to the print-based group, students using AR demonstrated greater gains on visually supported vocabulary and content items, while other items showed no significant differences between groups. We conclude that AR constitutes a promising pedagogical resource for CLIL, capable of scaffolding vocabulary/content development and motivating participation, while the observed variability underscores the need for principled, context-sensitive integration. Future work should specify boundary conditions—such as task type, prior proficiency, cognitive load, and technology familiarity—and employ robust mixed-methods designs to determine for whom, and under which instructional circumstances, AR yields the greatest and most sustainable gains. Full article