Search Results (1,397)

A novel closed loop visual positioning system, termed YOLO–LaserGalvo (YLGS), is proposed for precise localization of welding torch tips in industrial welding automation. The proposed system integrates a monocular camera, an infrared laser distance sensor with a galvanometer scanner, and a customized deep learning detector based on an improved YOLOv11 model. In operation, the vision subsystem first detects the approximate image location of the torch tip using the YOLOv11-based model. Guided by this detection, the galvanometer steers the IR laser beam to that point and measures the distance to the torch tip. The distance feedback is then fused with the vision coordinates to compute the precise 3D position of the torch tip in real-time. Under complex illumination, the proposed YLGS system exhibits superior robustness compared with color-marker and ArUco baselines. Experimental evaluation shows that the system outperforms traditional color-marker and ArUco-based methods in terms of accuracy, robustness, and processing speed. This marker-free method provides high-precision torch positioning without requiring structured lighting or artificial markers. Its pedagogical implications in engineering education are also discussed. Potential future work includes extending the method to full 6-DOF pose estimation and integrating additional sensors for enhanced performance. Full article

This study examines the key factors influencing the quality of distance learning in higher education during the COVID-19 pandemic, a period when online learning became the dominant mode of education. Using a descriptive method and a 26-item questionnaire, data were collected from a representative sample of 360 students in Vojvodina, Serbia. The factors analyzed include computer literacy and technology access (Ph1), students’ ability to balance life obligations with study demands (Ph2), and their motivation for distance learning (Ph3). The results show that 89% of students had adequate IT access, 47% were able to reconcile study and personal obligations, and 70% reported strong motivation. Correlation analysis confirmed a statistically significant positive relationship between all three factors and students’ perceptions of well-organized distance learning, thus supporting the main research hypothesis. Beyond these findings, this study interprets digital literacy as adaptability, time management as resilience, and motivation as value orientation and future thinking—core dimensions of sustainability competences outlined in the European GreenComp framework. Distance learning is therefore positioned not only as an emergency response but also as a transformative pedagogy that integrates brain (knowledge), hands (skills), heart (values), and spirit (purpose), contributing to sustainable and resilient higher education. Full article

Student exam pass prediction (EPP) is a key task in educational assessment and can help teachers identify students’ learning obstacles in a timely manner and optimize teaching strategies. However, existing EPP models, although capable of providing quantitative analysis, suffer from issues such as complex algorithms, poor interpretability, and unstable accuracy. Moreover, the evaluation process is opaque, making it difficult for teachers to understand the basis for scoring. To address this, this paper proposes an approximate belief rule base (ABRB-a) student examination passing prediction method based on adaptive reference point selection using symmetry. Firstly, a random forest method based on cross-validation is adopted, introducing intelligent preprocessing and adaptive tuning to achieve precise screening of multi-attribute features. Secondly, reference points are automatically generated through hierarchical clustering algorithms, overcoming the limitations of traditional methods that rely on prior expert knowledge. By organically combining IF-THEN rules with evidential reasoning (ER), a traceable decision-making chain is constructed. Finally, a projection covariance matrix adaptive evolution strategy (P-CMA-ES-M) with Mahalanobis distance constraints is introduced, significantly improving the stability and accuracy of parameter optimization. Through experimental analysis, the ABRB-a model demonstrates significant advantages over existing models in terms of accuracy and interpretability. Full article

Microplastic pollution is an escalating environmental and public health issue. Defined as plastic particles less than 5 mm in size, microplastics have been found in oceans, rivers, food, drinking water, air, and even human tissues. While scientific research on microplastics has expanded significantly, public understanding and behavioral change remain limited. This literature scan synthesizes global findings on public awareness, perceptions, and responses to microplastics, drawing from surveys, focus groups, and online behavioral data collected by existing studies. It explores the following: (1) general knowledge and perceived environmental and health risks; (2) trust in scientific and governmental sources; (3) willingness to adopt behavioral changes; (4) attitudes toward policy and corporate responsibility. Public concern is high, especially regarding marine life and food safety, but varies across populations based on education, socioeconomic status, and media exposure. Despite growing concern, psychological distance and persistent knowledge gaps hinder meaningful action. Communication strategies such as school programs, media campaigns, and eco-labels show mixed success, while regulatory interventions like plastic bags or microbead bans are more effective when supported by clear public messaging. This literature scan highlights the need for interdisciplinary collaboration to close the knowledge–behavior–policy gap and strengthen public engagement, particularly in urban settings where consumption and waste generation are concentrated. Full article

This paper presents a structured strategy for integrating the Sustainable Development Goals (SDGs) into university courses by linking them to competencies and learning outcomes. The proposed methodology, based on fuzzy logic, evaluates the degree of alignment between teaching activities and selected SDGs through matrices that connect competencies with assessment activities and expected learning outcomes, improving the gap regarding the inclusion of the SDGs and their articulation in terms of competencies. The approach was applied to two subjects from the Master’s Degree in Renewable Energy and Energy Efficiency at the Distance University of Madrid: “Electricity Market” and “Wind Energy”. In both cases, the learning outcomes were redesigned, and the activities were adjusted to ensure meaningful incorporation of sustainability principles into the curriculum. The method enables quantification of each activity’s contribution to the SDGs and supports a critical review of curriculum design to ensure coherent integration. The results indicate that project-based activities show the highest alignment with the SDGs, particularly with Goals 7, and 12, which achieve an average rating of 0.7 (high). The developed tool provides a practical and replicable solution for sustainability-oriented curriculum planning and can be adapted to other disciplines and educational programs. Full article

This study investigates the challenges of promoting accessibility for deaf teachers and students in higher education, focusing on the development of inclusive teaching materials. A qualitative case study was conducted in ten teacher training programmes at the Federal University of Alagoas (Brazil), including nine distance learning courses and one face-to-face LIBRAS programme. Analysis of the Virtual Learning Environment revealed a predominance of text-based content, with limited use of Libras videos, visual resources, or assistive technologies. The integration of Brazilian Sign Language into teaching practices was minimal, and digital translation tools were rarely used or contextually appropriate. Educators reported limited training, technical support, and institutional guidance for the creation of accessible materials. Time constraints and resource scarcity further hampered inclusive practices. The results highlight the urgent need for institutional policies, continuous teacher training, multidisciplinary support teams, and the strategic use of digital technologies and Artificial Intelligence (AI). Compared with previous studies, significant progress has been made. The present study highlights the establishment of an Accessibility Centre (NAC) and an Accessibility Laboratory (LAB) at the university. These facilities are designed to support the development of policies for the inclusion of people with disabilities, including deaf students, and to assist teachers in designing educational resources, which is essential for enhancing accessibility and learning outcomes. Artificial intelligence tools—such as sign language translators including Hand Talk, VLibras, SignSpeak, Glove-Based Systems, the LIBRAS Online Dictionary, and the Spreadthesign Dictionary—can serve as valuable resources in the teaching and learning process. Full article

Posture recognition is critical in modern educational and office environments for preventing musculoskeletal disorders and maintaining cognitive performance. Existing methods based on human keypoint detection typically rely on convolutional neural networks (CNNs) and single-scale features, which limit representation capacity and suffer from overfitting under small-sample conditions. To address these issues, we propose MSBN-SPose, a Multi-Scale Bayesian Neuro-Symbolic Posture Recognition framework that integrates geometric features at multiple levels—including global body structure, local regions, facial landmarks, distances, and angles—extracted from OpenPose keypoints. These features are processed by a multi-branch Bayesian neural architecture that models epistemic uncertainty, enabling improved generalization and robustness. Furthermore, a lightweight neuro-symbolic reasoning module incorporates human-understandable rules into the inference process, enhancing transparency and interpretability. To support real-world evaluation, we construct the USSP dataset, a diverse, classroom-representative collection of student postures under varying conditions. Experimental results show that MSBN-SPose achieves 96.01% accuracy on USSP, outperforming baseline and traditional methods under data-limited scenarios. Full article

Distance learning has become essential to higher education, yet its application in military officer training presents unique academic, operational, and security challenges. For Lithuania’s future officers, remote education must foster not only knowledge acquisition but also decision-making, leadership, and operational readiness—competencies traditionally developed in immersive, in-person environments. This study addresses these challenges by integrating System Dynamics Modelling, Contemporary Risk Management Standards (ISO 31000:2022; Dynamic Risk Management Framework), and Learning Analytics to evaluate the interdependencies among twelve critical factors influencing the system resilience and effectiveness of distance military education. Data were collected from fifteen domain experts through structured pairwise influence assessments, applying the fuzzy DEMATEL method to map causal relationships between criteria. Results identified key causal drivers such as Feedback Loop Effectiveness, Scenario Simulation Capability, and Predictive Intervention Effectiveness, which most strongly influence downstream outcomes like learner engagement, risk identification, and instructional adaptability. These findings emphasize the strategic importance of upstream feedback, proactive risk planning, and advanced analytics in enhancing operational readiness. By bridging theoretical modelling, contemporary risk governance, and advanced learning analytics, this study offers a scalable framework for decision-making in complex, high-stakes education systems. The causal relationships revealed here provide a blueprint not only for optimizing military distance education but also for enhancing overall system resilience and adaptability in other critical domains. Full article

Heart failure with reduced ejection fraction (HFrEF) continues to impose a high burden of morbidity and mortality despite significant advances in pharmacologic and device-based therapy. Cardiac resynchronization therapy (CRT) and angiotensin receptor–neprilysin inhibitors (ARNIs) have independently demonstrated substantial benefits in symptoms, health-related quality of life (HRQoL), and survival. Cardiac rehabilitation (CR), incorporating structured exercise, education, and lifestyle optimization, is well established as an effective intervention in HFrEF, yet its role in the era of combined CRT and ARNI therapy remains insufficiently characterized. This literature review synthesizes current evidence on CR in HFrEF populations receiving CRT, ARNI, or both, highlighting its impact on HRQoL, exercise capacity, and functional outcomes. Across diverse study designs—including randomized trials, observational cohorts, and meta-analyses—CR consistently yielded clinically meaningful improvements in patient-reported HRQoL and objective measures such as six-minute walk distance (6MWD) and peak oxygen uptake. Data directly evaluating CR in patients concurrently receiving both CRT and ARNI are lacking; indirect evidence suggests CR is compatible with, and may add to, contemporary device and drug therapy. However, referral rates remain low, indicating an implementation gap despite strong evidence of benefit. The review underscores the importance of integrating CR into contemporary HFrEF care and identifies a pressing need for targeted prospective studies to define its role in patients receiving dual device–pharmacologic therapy. Full article

This paper introduces a new quadruped spider robot platform specializing in environmental reconnaissance and mapping. The robot measures 180 mm × 180 mm × 95 mm and weighs 385 g, including the battery, providing a compact yet capable platform for reconnaissance missions. The robot consists of an ESP32 microcontroller and eight servos that are disposed in a biomimetic layout to achieve the biological gait of an arachnid. One of the major design revolutions is in the power distribution network (PDN) of the robot, in which two DC-DC buck converters (LM2596M) are used to isolate the power domains of the computation and the mechanical subsystems, thereby enhancing reliability and the lifespan of the robot. The theoretical analysis demonstrates that this dual-domain architecture reduces computational-domain voltage fluctuations by 85.9% compared to single-converter designs, with a measured voltage stability improving from 0.87 V to 0.12 V under servo load spikes. Its proprietary Bluetooth protocol allows for both the sending and receiving of controls and environmental data with fewer than 120 ms of latency at up to 12 m of distance. The robot’s mapping system employs a novel motion-compensated probabilistic algorithm that integrates ultrasonic sensor data with IMU-based motion estimation using recursive Bayesian updates. The occupancy grid uses 5 cm × 5 cm cells with confidence tracking, where each cell’s probability is updated using recursive Bayesian inference with confidence weighting to guide data fusion. Experimental verification in different environments indicates that the mapping accuracy (92.7% to ground-truth measurements) and stable pattern of the sensor reading remain, even when measuring the complex gait transition. Long-range field tests conducted over 100 m traversals in challenging outdoor environments with slopes of up to 15° and obstacle densities of 0.3 objects/m² demonstrate sustained performance, with 89.2% mapping accuracy. The energy saving of the robot was an 86.4% operating-time improvement over the single-regulator designs. This work contributes to the championing of low-cost, high-performance robotic platforms for reconnaissance tasks, especially in search and rescue, the exploration of hazardous environments, and educational robotics. Full article

Background: Compared to other high-income countries, US women face higher maternal and infant mortality rates. Methods: This study used structural equation modeling (SEM) to examine cross-sectional, county-level associations between structural and intermediary social determinants of health (SDOHs) and maternal and infant mortalities, based on the World Health Organization’s Commission on Social Determinants of Health framework. Results: Our findings suggest maternal mortality may be linked to increased food insecurity, food assistance, distance to obstetric care, and decreased walkability and marriage rates. Our modeling also points toward a connection between infant mortality and increased food insecurity, food assistance, Black race, mental distress, and decreased walkability, education, and income. SEM revealed significant direct and indirect effects of these SDOHs. Notably, food insecurity and walkability had direct associations with both maternal and infant mortality in both SEM models. Conclusions: The findings underscore the need for policy, practice, and research efforts to address key SDOHs and reduce mortality disparities in the US. Full article

Integrating Artificial Intelligence (AI) into education poses new challenges and opportunities, particularly in the training of university professors, where Teaching Digital Competence (TDC) emerges as a key factor to leverage its potential. The aim of this study was to evaluate a structural model designed to measure TDC in relation to the educational use of AI. A quantitative methodology was applied using a validated questionnaire distributed through Google Forms between March and May 2024. The sample consisted of 368 university professors. The model examined relationships among key dimensions, including cognition, capacity, vision, ethics, perceived threats, ai-powered innovation, and job satisfaction. The results indicate that cognition is the strongest predictor of capacity, which in turn significantly influences vision and ethics. AI-powered innovation presented limited explained variance, while perceived threats from AI negatively affected capacity. Additionally, job satisfaction was mainly influenced by external factors beyond the model. The overall model fit confirmed its reliability in explaining the proposed relationships. This study highlights the critical role of cognitive training in AI for teachers and the importance of designing targeted professional development programs to enhance TDC. Although a generally positive attitude towards AI was identified, perceptions of threats remained low. Full article

Access to schools is crucial in determining an area’s functioning and development, especially regarding housing development. This article presents an analysis of the spatial accessibility of educational services in the city. In Poland, municipalities applied standards for the accessibility of schools in the 1980s and 1990s. In 2023, amendments to the Law on Planning and Spatial Development (The Act of 7 July 2023 amending the Act on Spatial Planning and Development and certain other Acts) reintroduced the obligation to consider the accessibility of education services in the planning documents of municipalities and established the applicable distances. This article presents a method for assessing the level of accessibility of primary schools using spatial–statistical indicators, with the city of Płock as an example. The analysis allowed us to present the spatial differentiation of the level of fulfilment and the level of fulfilment of needs according to the new planning guidelines. We deepened the analysis grounded in the 15-Min City concept to validate the findings, benchmarking the results against international frameworks and recognised good practices. Similar analysis can support local authorities of other municipalities in the spatial planning decision-making process. The authors formulated the following research questions: What criteria can be applied to evaluate the performance of existing educational facilities and determine optimal locations for new schools in planning educational services? Do time-based (15 min) benchmarks reveal different patterns than distance-only thresholds? The example of Płock shows the weaknesses of applying unified urban standards in areas with diverse types of spatial development and the need to modify them. To deepen the verification of the observed discrepancies, the study was extended to include an analysis based on the concept of the 15-Min City. The results revealed even greater disparities in accessibility, highlighting a strong contrast between central and peripheral districts. These findings remain consistent with the conclusions of international studies. Meanwhile, the applicable regulations in Poland provide relatively liberal accessibility thresholds. It may lead to an increase in the distance between residential development and educational facilities and other key elements of urban social infrastructure, thereby distancing national urban planning practices from the European principles of compact, 15 min, and sustainable cities. Full article

Personalized education, particularly for gifted students, has attracted increasing attention as digital tools expand opportunities to adapt learning to individual students’ needs, interests, and abilities. However, the conceptual ambiguity surrounding personalization, which is often conflated with differentiation or individualization, calls for a clearer understanding of its implementation in digital environments. This study presents a systematic literature review of research published between 2000 and 2024 on digital tools for the personalized education of gifted students. Following the PRISMA guidelines, a comprehensive search was conducted in SCOPUS and Web of Science, yielding 257 initial records. After applying inclusion and exclusion criteria, a final corpus of 55 studies was analyzed through temporal, geographic, educational, and curricular perspectives. Thematic coding was also applied. The results show a marked increase in publications after 2020, with the United States and Russia as leading contributors, and a predominant focus on secondary education and STEM/STEAM disciplines. Across studies, digital tools were found to support personalization by fostering autonomy, creativity, collaboration, and advanced cognitive skills, though significant challenges remain in terms of equity, teacher training, and data security. Following this review, we conclude that although digital tools hold substantial promise for advancing personalized learning, their broader implementation requires integrative and context-sensitive strategies. Full article

Education has become one of the important drivers of residential mobility. The school district system in China has transformed school choice into a competition for housing ownership based on family capital, resulting in the capitalization of education and gentrification. Understanding the patterns of education-driven residential mobility is therefore of significant importance for urban planning, educational policy and social equity research. In this study, we depicted and analyzed the heterogeneity of residential mobility formed by the interaction of schooling choice, diversity of family characteristics, and housing preferences. Based on the household questionnaire survey conducted in Tianjin, we identified five typical education-driven residential mobility patterns by using the K-Prototype clustering algorithm. The empirical results implied that in China, particularly in megacities like Tianjin with a strict school district system tied to housing, wealthy families approach high-quality education through their socio-economic advantages for cultural reproduction; families sacrifice living conditions to access leading schools by acquiring old second-hand housing or smaller new-commercial housing; lower-income families relocate to within a short distance of the city center to change home ownership status for basic school eligibility; and families opting out of school districts achieve residential improvements and display greater locational diversity in relocation. Education-driven residential mobility is reshaping urban space, and may intensify socio-spatial stratification, even influencing long-term urban sustainability through patterns of resource allocation, neighborhood stability, and social equity. While this study focuses on Tianjin, the impacts of such school-housing-linked policies hold broader relevance for global cities facing similar challenges. Full article