Design Of Support System Research Articles

Design and analysis of cold mass support system for superconducting magnets without transport protection

Design and analysis of cold mass support system for superconducting magnets without transport protection

Indoor and Outdoor Mobility Monitoring for People Living with Dementia: Improving Their Independent Activity by Integrating Open Interface Sensors.

People living with dementia often experience mobility challenges and social isolation, which can impede their ability to perform activities of daily living independently. This paper presents the design and deployment of an open-source software-based context-aware support system, e.g., Home Assistant, integrated with a network of indoor and outdoor off the shelf sensors. The objective is to assist people living with dementia by sending timely, personalized reminders to enable independence and social contact. The proposed system also aims to reduce the care burden on family and caregivers by providing peace of mind. Initial findings demonstrate the technical feasibility of the approach and in assisting with activities of daily living with non-intrusive, sensor-assisted support and monitoring.

Deep reinforcement learning-driven decision support system design for precision agriculture: optimizing farming and resource use

Deep reinforcement learning-driven decision support system design for precision agriculture: optimizing farming and resource use

The Intention to Share the Professional Knowledge of University Lecturers: Empirical Evidence from Vietnam

The study aims to identify the factors that directly influence lecturers’ intentions to share professional knowledge at universities in Vietnam. A total of 315 survey samples were analyzed using quantitative methods, including reliability testing, exploratory factor analysis, correlation analysis, and binary logistic regression. The results indicate that attitude, reward mechanisms, confidence in knowledge, information technology, subjective norms, and perceived behavioral control directly influence university lecturers’ intentions to share professional knowledge. Based on these research findings, several governance implications are proposed to create policies, design support systems, and foster an environment that encourages knowledge sharing in education, thereby enhancing the effectiveness of training, research, and sustainable development for university lecturers.

To MILP or not to MILP? On AI techniques for the design and optimization of real-time systems

Abstract Artificial intelligence (AI) is becoming increasingly relevant in many contexts. In embedded real-time systems, most of the previous research has focused on real-time guarantees for AI workloads (RT-for-AI). Instead, this position paper discusses the potential benefits and application cases of the complementary direction of using AI to optimize real-time systems themselves (AI-for-RT). It presents a vision where AI techniques, such as supervised and reinforcement learning, support system design and online configuration activities that are traditionally addressed using Mixed-Integer Linear Programming (MILP) or heuristic methods. The paper discusses scenarios where AI can potentially outperform classical techniques—such as recursive real-time analysis, systems with complex hardware/software interactions, and dynamic resource management—highlighting the promise of AI in both design-time and runtime real-time systems optimization. Solutions are left to future work: the goal is to populate the “Roadmap Towards Learning-Enabled and Learning-Assisted Real-Time Systems”, which is the target of this special issue.

The Evolution of E-Learning and Teaching Using Artificial Intelligence

E-learning has transformed the landscape of education and professional training by providing accessible and flexible learning solutions. The integration of artificial intelligence (AI) into e-learning platforms has further revolutionized the learning experience by enabling personalized content delivery, intelligent tutoring systems, adaptive assessments, and real-time feedback. This study employs the TOPSIS method to evaluate and rank popular e-learning platforms, identifying Thinkific as the best-performing platform, followed by Codecademy, Learning, Pluralsight, and Skillshare in descending order. The results indicate that platforms emphasizing structured content, interactivity, specialized courses, and AI-driven features perform better in terms of user satisfaction and learning outcomes. The findings highlight the importance of selecting the right e-learning platform based on the learner’s objectives and the platform’s technological capabilities. AI enhances this process by offering data-driven insights and tailored learning paths, which significantly improve engagement and knowledge retention. Moreover, continuous improvements in course design, AI integration, and learner support systems are essential to maximize the effectiveness of online education. Future research could explore additional evaluation parameters, including AI-driven analytics and user feedback mechanisms, for a more comprehensive assessment of e-learning platforms. The significance of this research lies in evaluating and selecting effective e-learning platforms using the TOPSIS method, underlining the growing importance of AI in shaping modern digital education. As online education expands, understanding which platforms leverage AI to provide the best learning experiences is crucial for educators, students, and organizations. This study offers valuable insights into platform performance across multiple criteria, aiding in strategic decision-making, optimizing resource allocation, and enhancing overall educational quality. Additionally, it encourages continued innovation by identifying key factors—including AI functionalities—that influence learning success. Structured decision-making approaches like TOPSIS, when combined with emerging AI capabilities, provide a powerful framework for evaluating and improving digital learning strategies.

Discrete element analysis of horizontal soil arching effect in pile-supported retaining structures

Abstract This study focuses on the evolution of horizontal soil arching effects during the excavation of pile-supported retaining structures through the Discrete Element Method (DEM) using Particle Flow Code 2D (PFC2D). In the DEM model, square wall elements are constructed to simulate square piles, representing the horizontal cross-section of an excavation. The horizontal soil arching effect induced by excavation under varying parametric conditions was investigated. The results indicate that the soil arching effect progressively evolves through three characteristic stages during excavation — compaction, load transfer, degradation, and failure. The lateral earth pressure on the pile initially increases rapidly, followed by periodic fluctuations as excavation depth increases. When the wall displacement ratio exceeds 2.25%, the soil arching effect and support efficiency begin to decline, and when it surpasses 4%, the bearing capacity of the pile-supported retaining structures significantly deteriorates. By simulating the pile response under various net pile spacings, the study determines that an optimal net pile spacing of 1.5 to 2 times the square pile width maximizes the soil arching effect while enhancing pile-bearing capacity. These findings provide essential theoretical insights and technical guidance for the design of excavation support systems.

Engineering design of a superconducting magnet for gravity compensation

Abstract Magnetic compensation of gravity allows for ground-based experiments to be carried out under weightless conditions at reasonable cost and without time limitation of the systems such as zero-g airplanes or drop towers. In this paper a superconducting magnet for gravity compensation is described. The magnet warm bore diameter is 382mm and the centre magnetic field is about 2T. The magnet is comprised by nine solenoid coils wound on two separated mandrels. The magnet is conduction cooled by two GM cryocoolers. The cryostat design and analysis are present in this paper, including the heat load analysis and cold mass support system design. Thermal and mechanical design of the cold mass are discussed in this paper, especially the temperature difference and the mechanical stress in the cold mass assembly. Cooling down and charging results show that the magnet can run at its design current very well.

The impact of attention deficit hyperactivity disorder on medical students' academic performance and well-being: A letter to the editor.

Dear Editor, Attention Deficit Hyperactivity Disorder (ADHD) is a common neuropsychiatric condition characterized by developmentally inappropriate inattention and/or hyperactivity-impulsivity. ¹ Though this has traditionally been considered a childhood disorder, it is now being increasingly understood that ADHD symptoms may persist into adulthood. The estimated prevalence of clinician assessed ADHD in the adult population is estimated to lie between 5-10%. ² The disorder can cause significant functional impairment and academic underachievement, especially in a university environment. Transitioning into medical school brings a curriculum that is intense and very demanding, a challenge taken to a much higher level by students with ADHD. It changes the dimensions of self-regulation, time management, and organization. Some of the most essential skills for medical school students with ADHD are long lectures and clinical hour focus, time management concerning multiple deadlines, and juggling multifaceted coursework and clinical tasks. Most of the time, these academic and practical issues typically result in incomplete assignments and general underperformance in academics. Research consistently shows that such students generally have lower GPAs, high dropout rates, and longer times to attain medical degrees compared to their non-ADHD peers. ³ The ongoing academic challenges faced by these students can also impact their mental health, where they experience high levels of stress, anxiety, and depression.4 Furthermore, the academic difficulties that those with ADHD face, weaken their social interactions, leading to feelings of isolation and, eventually, social withdrawal. This compounded problem highlights the need for comprehensively designed support systems with individual differences for medical students with ADHD. Comprehensive care should be the approach when treating medical students diagnosed with ADHD. Some individualised academic accommodations that may help alleviate some academic stress include extended time on exams, note-taking services, and flexible deadlines for assignments. Also, such students should have access to mental health resources such as counselling and ADHD coaching. Professional development programs for faculty in medical schools can also help equip faculty with strategies to handle students with ADHD within the classroom and clinical settings. By applying the following methods, medical schools could allow students with ADHD to reach their maximum potential in both academic and professional life, thus contributing to improving their quality of life.

Study on the Asymmetric Failure Characteristics and Failure Mechanisms of Surrounding Rock During Excavation of a Deep Buried Small-Clearance Tunnel

In deeply buried, small-clearance tunnels, the failure of the surrounding rock is profoundly influenced by the superposition of stresses and the cumulative disturbance effects from multiple blasting events. Consequently, the failure characteristics and mechanisms of the surrounding rock are highly complex. Through a comprehensive analysis encompassing failure investigations, geological assessments, and surrounding rock pressure monitoring, this study systematically examines the spatio-temporal failure characteristics and geological discrepancies across 3 parallel tunnels (namely, a pilot tunnel, a left tunnel, and a right tunnel). The analysis reveals the asymmetric failure behavior of the surrounding rock and offers a detailed discussion of the underlying mechanisms. The temporal and spatial evolution of the surrounding rock pressure in these tunnels is carefully analyzed, with an emphasis on uncovering the asymmetric failure mechanisms during the excavation of deep, small-clearance tunnels. The results demonstrate that the failure of the surrounding rock exhibits significant asymmetry during excavation, with the damage being more pronounced on the valley side compared to the mountain side. Furthermore, the degree of damage in the advance tunnel is substantially greater than that in the backward tunnel, particularly in sections following the excavation of the backward tunnel. Additionally, the distribution of the surrounding rock pressure in the advance tunnel also exhibits pronounced asymmetry. The asymmetric failure of the surrounding rock is primarily attributed to the stress concentration in the deep valley and the disturbances introduced by the excavation process, which induces tangential stress concentrations in the surrounding rock mass. The findings of this study hold considerable significance for the design and optimization of tunnel support systems, as well as for disaster prevention strategies in deeply buried, small-clearance tunnels.

A Quantitative Legal Support System for Transnational Autonomous Vehicle Design

One of the key expectations of AI product manufacturers for their products is the ability to scale to larger markets, especially across legal systems, with fewer prototypes and lower adaptation costs. This paper focuses on the increasingly dynamic legal compliance challenges faced by designers of AI products in achieving this goal. Based on non-monotonic reasoning, we design an automated reasoning tool to help them better understand the legal implications of their designs in a transnational context and, ultimately, adjust the design of AI products more flexibly. This tool supports the quantitative representation of the strength of legal significance to help designers better understand the reasons for their decisions from their own perspective. To illustrate this functionality, a case study on traffic regulations across the UK, France, and Japan demonstrates the system’s ability to resolve legal conflicts—such as driving-side mandates and speed radar detector prohibitions—through quantitative evaluation.

Enhancing cervical spine health: a vibration-focused multibody dynamics model for neck support system design

Abstract Neck injuries can range from mild discomfort to severe disability. Despite the abundance of biomechanical models of the cervical spine in the literature, their capabilities for modal and frequency response analysis are limited. A comprehensive head-cervical spine model was developed to address this gap, enabling frequency domain analysis. A multi-body dynamics (MBD) model with 20 degrees-of-freedom (DoFs) was created using ADAMS software’s frequency response analysis capabilities. This model incorporates elements, including vertebrae, ligaments, and muscles. The validation was performed using OpenSim and existing experimental findings. The model was then employed to conduct a Design of Experiments (DoE) study, where key design factors of a conceptual neck support system were varied. Two vibration objective functions were selected to evaluate the parametric designs. The first function identifies the maximum value of the head’s acceleration, while the second measures overall vibration within the frequency range of interest. In a case study, the model’s capabilities were demonstrated, identifying key design parameters for the neck support system. The methodology has the potential to make significant contributions across multiple industries. Applications range from designing anti-vibration devices to reduce fatigue in the automotive and aerospace sectors to enhancing rehabilitation systems in healthcare, ultimately improving patient exercise effectiveness.

Recommended design of support systems for the Tiga Dihaji Dam intake tunnel, South Sumatra, based on Q-System

Abstract This research focuses on the intake tunnel of the Tiga Dihaji Dam in South Sumatra, including aspects of engineering geology, rock mass quality, and the recommended support systems based on the Q-System (Barton et al., 1974). The choice of Q-System classification is intended because this method uses 6 (six) qualitative parameters in determining the rock mass quality, namely Rock Quality Designation (RQD), Joint set number (Jn), Joint roughness number (Jr), Joint alteration number (Ja), Joint water reduction factor (Jw), and Stress Reduction Factor (SRF). Each of these parameters will determine the Q value, and statistical analysis was conducted to determine which parameters most influence the Q value at the construction site for the Tiga Dihaji Dam intake tunnel. Apart from being used to determine rock mass quality, the Q-System classification can also assess tunnel support systems. The research encompasses examining various facets of engineering geology, the collection of rock specimens, laboratory analyses, and evaluating core drilling results. The study’s findings reveal that the lithology unit at the depth of the tunnel alignment consists of carbonaceous claystone interbedded with carbonaceous sandstone. The rock masses are categorized as Poor (Q value ranging from 1 to 4) and Fair (Q value ranging from 4 to 10). The recommended support systems based on Q value, tunnel diameter of 5 m, and Excavation Support Ratio (ESR) are unsupported or spot bolting with a bolt length of 2.5 m, bolt diameter of 20 mm, bolt spacing of <1.6-2.0 m (in the roof) and 1.6-3.0 m (for tunnel wall). The parameter that most affects the Q value is the Joint water reduction factor (Jw).

Tunnel Face Mapping for Evaluate Support System Design of the Inlet Area at the Budong-Budong Dam Diversion Tunnel, West Sulawesi, Indonesia

Abstract A comprehensive advanced engineering geology investigation is essential for the construction of a tunnel. During the construction stage, tunnel face mapping is strongly suggested to observe and identify geological conditions that have not been recorded directly by the borehole data. Tunnel face mapping is conducted to identify changes or variations in geological engineering conditions prior to excavation. The Budong-Budong Dam diversion tunnel was excavated using an excavation method and a selection support system based on the Rock Mass Rating (RMR) classification determined in the design stage. However, the geology of tunnel construction poses unique challenges, primarily as it is located in volcanic rock and steep slope topography with a high potential for landslides and rock failures. This research aims to provide an evaluation of the tunnel excavation method and support system based on tunnel face mapping in the inlet side of tunnel. The two empirical methods used are Rock Mass Rating (RMR) and Q-System classifications. The results show that the inlet tunnel consists of tuffaceous sandstone and tuffaceous siltstone. According to RMR, the rock mass quality along the inlet tunnel side consists of a fair rock mass class with RMR values ranging from 42 to 53. According to Q-System, the inlet side of the tunnel is dominated by poor rock mass quality. The tunnel excavation method using top heading and bench excavation with 1.5 - 3 meters advance in heading is recommended based on RMR. The tunnel requires a combination of rock bolts and shotcrete represents the optimal support system for the inlet tunneling area. In order to mitigate risk and ensure the safety of the tunnel, it is recommended a numerical analysis to verify the empirical design.

Study on the Relationship between Learning Engagement and Vocational Competency Development Among Students in Higher Vocational Colleges

This study investigates the relationship between learning engagement and vocational competency development among students in higher vocational colleges. Guided by the Social Cognitive Career Theory (SCCT), this research explores how behavioral, emotional, and cognitive engagement dimensions influence vocational competency outcomes, including technical skills, problem-solving abilities, and professional identity. A cross-sectional survey design was employed, with data collected from 863 students across five higher vocational institutions in Anhui Province, China. The validated Learning and Study Strategies Inventory (LASSI) and vocational competency assessment tools were used to measure constructs. Structural equation modeling (SEM) revealed significant positive relationships between cognitive engagement (β = 0.42, p < .001) and vocational competency development, whereas behavioral engagement (β = 0.18, p < .05) showed a weaker effect. Emotional engagement was not statistically significant (β = 0.07, p* > .05). Moderation analysis indicated that program types (e.g., engineering vs. business) moderated the relationship between cognitive engagement and vocational competency (ΔR*² = 0.06, p < .01). Findings suggest that cognitive engagement plays a critical role in fostering vocational competencies, highlighting the need for instructional strategies that enhance deep learning and reflective practice. Implications for curriculum design and student support systems are discussed, emphasizing the importance of aligning teaching methods with competency standards outlined in China’s vocational education reforms. Limitations include reliance on self-reported data and regional sampling, calling for longitudinal studies and broader generalizability tests.

Exploring Student Perceptions of Blended Learning: Flexibility, ICT Literacy, and the Preference for Traditional Classroom Learning

Student participation remains a key challenge in blended learning (BL), particularly in the Faculty of Islamic Religion and Teacher Training and Education. Understanding students’ perceptions is essential to evaluate the effectiveness of BL and identify areas for enhancement. This study employed a quantitative, non-experimental survey design. Data were collected from 238 students at Universitas Islam Nusantara through an online questionnaire. Descriptive statistical methods were used to analyze the data and calculate mean scores across various dimensions of students’ perceptions. The findings indicate that students generally perceive blended learning positively, with an overall mean score of 3.45 on a 4-point scale. Flexibility was viewed favorably, while convenience received a moderate rating (mean score: 3.1). Students also reported high levels of ICT literacy, averaging 3.6. Despite these positive aspects, a notable proportion of students still preferred face-to-face learning, citing it as more effective and easier for active participation. The results suggest that while blended learning enhances flexibility and supports digital skill development, concerns about convenience and engagement persist. These findings highlight the need for improved instructional design and better support systems within BL environments. Blended learning is perceived as effective and beneficial, particularly in developing ICT literacy. However, to increase student participation and overall satisfaction, institutions should focus on improving the usability and interactivity of blended platforms, as well as providing targeted support to address learner preferences and challenges.

Study on the Design and Construction Methods of Auxiliary Workings for the Deepening of Shaft II in the Borynia Mine

This study explores the design and construction methods for auxiliary workings for the deepening of Shaft II at the Borynia Mine. The shaft, an essential intake structure for personnel and material transport, is being extended from 980 m to 1150 m to provide access to a new mining level at 1120 m. Given the challenging geological and operational conditions, a top-to-bottom deepening method was adopted, with excavation from a sub-level accessed via an auxiliary incline. The study details the planning and implementation of key auxiliary workings, including hoisting machine chamber and technological shaft inset. A comprehensive geotechnical analysis was conducted to assess rock mass properties, classify geological formations, and estimate mechanical parameters affecting excavation stability. The support system design was carried out using both analytical and numerical methods, ensuring safe and efficient construction. The applied primary and secondary support structures have successfully maintained excavation stability. The findings demonstrate the reliability of the adopted engineering solutions and their applicability in deep mining environments.

Social support as conduit for reintegrating prison inmates into mainstream Ghanaian society

This research investigates the role of social support services in the rehabilitation of inmates within Ghanaian prisons, specifically at Ankaful Maximum and Nsawam Medium security prisons. Guided by rehabilitation theory, and the functionalist theory, the study seeks to explore the current state, rationale, and experiences associated with social support services for the ultimate reintegration of inmates into mainstream society post-incarceration. Using a qualitative design, the research employed semi-structured interviews with 29 participants, including inmates (recidivists), prison officers, and social welfare staff. Thematic analysis was used to identify patterns and themes within the data. Findings revealed that while social support have the potential to reduce recidivism and foster self-sufficiency, their effectiveness is significantly hindered by systemic challenges such as insufficient funding, inadequate infrastructure, and unevendistribution of services across facilities. Despite these barriers, some success was noted at Nsawam medium security prison, where programs such as carpentry, masonry, and blacksmithing contributed to the rehabilitation and reintegration of inmates postincarceration. The study also highlighted a disconnect between policy intentions and actual outcomes, with participants emphasizing the need for greater governmental commitment to funding and inproving social support programs. In conclusion, theresearch underscores the potential of social support services in facilitating rehabilitation and ultimately boosting reintegration of inmates into mainstream society after incarceration. In order to make the potential a reality, there is the need for systemic reform to improve upon social support services in Ghanaian prisons. Recommendations made include the need for an integrated, multi stakeholder approach in delivering social support services in Ghanaian prisons. Non-governmental organizations (NGOs), civil society organizations (CSOs), and private-sector actors should collaborate with the Ghana Prisons Service to design and implement sustainable social support systems.

Students’ Confidence in Mathematics: A Comprehensive Literature Review

Confidence in mathematics significantly influences learners’ academic outcomes, motivation, and career aspirations, particularly in STEM-related fields. This literature review explores the interplay between intrinsic and extrinsic factors affecting students’ confidence in mathematics. The purpose is to examine how self-efficacy, motivation, anxiety, peer influence, teacher support, and family involvement shape students' beliefs about their mathematical competence. The method involves reviewing international and local empirical studies and theoretical frameworks, including Social Cognitive Theory and Self-Determination Theory. Results show that high self-efficacy and strong social support systems enhance students’ confidence, while math anxiety and negative stereotypes diminish it. Because these psychological and contextual elements collectively determine students’ academic behavior and resilience, the findings highlight the need for targeted interventions. This review contributes to the growing discourse on educational equity and mathematics achievement by providing a holistic understanding of confidence formation, offering implications for future pedagogical strategies, curriculum design, and school-based support systems.

DECISION TREE APPROACH FOR PLANTS STOPPAGE DECISION PROCESS DUE TO POWER LIMITATION CASE STUDY: STEEL COMPANY

By Mohamed Saied Essa Othman Hussein. Approach to the design and construction of an innovative decision support system to help management of multi-plant companies to choose a plant in case of power limitation is presented.