Efficient Management Research Articles

Efficient Container Logistics System Model

Objective – Although there has been much research on containers and yard operations at the port, it has remained a fascinating subject of study on the logistics side because modernity, education, industries, and human behavior have changed and developed all the time. Moreover, they have continued to play significant roles in the international shipping industry and have affected the dependent economy and trade globally. The aims of this study were (1) to study container management systems and (2) to analyze the factors affecting an efficient container yard management system. Methodology – This research is classified as applied research, which consists of field surveys using the case record/report form (CRF) and data gathered through observation. A sample frame of 400 vehicles was chosen for a specific case study of an empty container terminal operation area in Bangkok port. Findings – Performance metrics for container terminal management or yard operations based on truck turnaround time were calculated by applying the Confidence Interval Theory. The data were analyzed using the SPSS program's binary logistic regression method to consider the relationship between the independent and dependent variables. The results of the research have been found. The inbound container management system has been better delivered in time than the outbound, which has implemented a total operation within 16.12 minutes. Additionally, some factors have significantly impacted container yard performance, such as activity type, route, container size, distance, and tools. Novelty – This might be incurred by multifarious reasons, such as operational stages, waiting time, data transmission, task and tool allocation, areas, traffic congestion, searching the container in blocks, etc. Type of Paper: Empirical research JEL Classification: E2, E3. Keywords: Empty Container Terminal, Container Yard, Container Management System, Binary logistic regression Reference to this paper should be made as follows: Nopparit, O; Saenchaiyathon, K. (2024). Efficient Container Logistics System Model, J. Bus. Econ. Review, 9(1), 63–72. https://doi.org/10.35609/jber.2024.9.1(3)

Genetic landscape and clinical outcomes of autosomal recessive polycystic kidney disease in Kuwait

BackgroundAutosomal recessive polycystic kidney disease (ARPKD), a rare genetic disorder characterized by kidney cysts, shows complex clinical and genetic heterogeneity. This study aimed to explore the genetic landscape of ARPKD in Kuwait and examine the intricate relationship between its genes and clinical presentation to enhance our understanding and contribute towards more efficient management strategies for ARPKD. MethodsThis study recruited 60 individuals with suspected ARPKD from 44 different families in Kuwait. The participants were of different ethnicities and aged 0–70 years. Additionally, 33 were male, 15 were female, and 12 had indeterminant sex due to congenital anomalies. Comprehensive clinical data were collected. Mutations were identified by next-generation whole exome sequencing and confirmed using Sanger sequencing. ResultsOf the 60 suspected ARPKD cases, 20 (33.3 %) died within hours of birth or by the end of the first month of life and one (1.7 %) within 12 months of birth. The remaining 39 (65.0 %) cases were alive, at the time of the study, and exhibited diverse clinical features related to ARPKD, including systematic hypertension (5.0 %), pulmonary hypoplasia (11.7 %), dysmorphic features (40.0 %), cardiac problems (8.3 %), cystic liver (5.0 %), Potter syndrome (13.3 %), developmental delay (8.3 %), and enlarged cystic kidneys (100 %). Twelve mutations, including novel truncating mutations, were identified in 31/60 cases (51.7 %) from 17/44 families (38.6 %). Additionally, 8/12 (66.7 %) mutations were in the PKHD1 gene, with the remaining four in different genes: NPHP3, VPS13P, CC2D2A, and ZNF423. ConclusionsThis study highlights the spectrum of clinical features and genetic mutations of patients with ARPKD in Kuwait. It highlights the necessity for personalized approaches to improve ARPKD diagnosis and treatment, offering crucial insights into managing ARPKD.

INNOVATIONS IN SCHOOL ROOM RESERVATION MANAGEMENT: TOWARDS SMART AND SUSTAINABLE SOLUTIONS

Abstract The efficient management of school room reservations is crucial for maximizing resource utilization and ensuring smooth operations within educational institutions. Traditional room reservation systems often suffer from inefficiencies, leading to underutilization of spaces, scheduling conflicts, and increased administrative burden. This research paper explores the development and implementation of smart and sustainable solutions for school room reservation management. The suggested approach makes use of contemporary technologies to expedite the classroom reservation process, giving teachers, administrators, and students effective means of scheduling and overseeing room reservations. The technology has significantly improved classroom utilization rates and overall operational efficiency in our institution, according to preliminary tests. The school room reservation system provides a scalable solution for improving the management of educational facilities by lowering scheduling conflicts, minimizing downtime between courses, and enabling better resource allocation. Future improvements could incorporate support for mobile platforms, integrate with current school management systems, and introduce new capabilities in response to user feedback and changing needs. In general, the establishment of this school room reservation system is a step toward the modernization of facilities management procedures in academic establishments, which will ultimately lead to the creation of a more efficient and cooperative learning environment. Index Term : Frontend development HTML, CSS, React, Backend NodeJS, Express, MongoDB

Innovative Solutions for Gallery Administration: A Case Study of Modern Dashboards

Abstract : Efficient management solutions are necessary for the complicated and numerous responsibilities involved in the administration of art galleries and exhibitions. The design, use, and effects of advanced dashboard administration interfaces for gallery management are examined in this study. The study looks at the key components of a successful gallery dashboard, such as user experience, data integration, security, and user interface design. The study used a mixed-methods approach, combining user surveys, case studies, and expert interviews to identify the critical elements of effective gallery administration. The results show that well-designed dashboards greatly increase operational effectiveness, facilitate better decision-making, and offer strong assistance for curatorial tasks. The study ends with suggestions for creating and putting into practice gallery dashboard systems that can adapt to the changing requirements of contemporary art galleries, stressing the significance of customization, both user-centric design and scalability. This study adds to the body of knowledge about digital technologies in art management and provides useful information for software developers and gallery managers. Keywords – DotNet , Php, WordPress , Steamlight.

BIKE RENTAL SYSTEM

Abstract The Bike Rental Management System is an innovative web application designed to revolutionize the rental process of bicycles for short-term urban use. It offers a comprehensive solution that caters to both customers and administrators, ensuring a seamless experience for all users.At its core, the system boasts a user-friendly interface that simplifies the process of searching for available bikes, selecting preferred options, and completing rentals. Real-time availability information is provided, empowering customers to make informed decisions. The secure payment processing feature guarantees a safe and convenient transaction experience, instilling trust and reliability in the system.For administrators, the system includes a robust admin panel that allows for efficient management of bikes, user accounts, and rentals. This panel provides a comprehensive overview of the rental operations, enabling administrators to make informed decisions and optimize the rental process for better efficiency.The technology stack behind the system is equally impressive, utilizing Java Servlet for backend logic, JDBC for database connectivity, JavaScript for client-side interactivity, and Bootstrap for responsive design. This ensures a smooth and seamless user experience across different devices and platforms.One of the key advantages of the Bike Rental Management System is its contribution to promoting eco-friendly urban mobility. By encouraging the use of bicycles for short-distance travel, the system helps reduce traffic congestion and carbon emissions, ultimately leading to a cleaner and greener environment. Additionally, the system promotes healthier lifestyles by encouraging physical activity through cycling.In conclusion, the Bike Rental Management System is a comprehensive and innovative solution that offers a wide range of benefits for both users and the environment. Its user-friendly interface, secure payment processing, efficient admin panel, and eco-friendly initiatives make it a standout choice for urban mobility solutions. Index Terms – Bike Rental, JDBC, User Authentication, Product Management, Admin Panel, Payment Processing, Scalability, Rental Process.

Система комплексной диагностики элементов высокоскоростного подвижного состава и инфраструктуры: анализ и внедрение

Objective: to consider the issue of integrated diagnostics of the undercarriage equipment of high-speed rolling stock and track infrastructure, to analyze the impact of operational factors on the technical condition of rolling stock, to identify the main problems and propose possible solutions, to consider the prospects of domestic development in the field of integrated diagnostics of rolling stock and infrastructure. Methods: analysis of design features and impact on train operation safety, criteria and parameters of running stability and passenger comfort of the undercarriage equipment of the high-speed electric train “Sapsan”, description of prerequisites and stages of creation, testing and operation of the system of continuous monitoring of parameters of the dynamic system “undercarriage and track” of electric trains “Sapsan”, analysis of the impact of the main operational factors on the technical condition of the rolling stock undercarriage equipment. Results: the key role of the undercarriage equipment of the Sapsan electric train in ensuring operational safety and passenger comfort has been determined. The necessity of creating and implementing a system for continuous monitoring of dynamic reactions in the system “undercarriage equipment - track infrastructure” has been identified. The results of experimental operation of the prototype of the system in the Sapsan electric trains are considered on the example of research of track sections with increased impact on the rolling stock and problems of running stability of the electric train. It is revealed that vertical accelerations of axlebox units with significant amplitudes allow to reveal vertical irregularities of the track up to 3 m long, and constant registration of increased lateral accelerations of the bogie frame shows the necessity of solving the issues related to the geometry of wheel-rail contact at sinuous movement of rolling stock in terms of conicity. The current state and prospects of development of domestic systems of complex diagnostics are determined. Practical importance: the considered diagnostic system allows to carry out complex analysis of problems of technical condition of undercarriage equipment and infrastructure, to determine interdependence and level of influence of operational factors, which is the way to increase reliability and fault tolerance of rolling stock, operational safety and passenger comfort. Its integration into the digital platform will increase the efficiency of rolling stock maintenance planning and enterprise resource management.

Diagnostics of financial security management efficiency of agricultural enterprises

Subject. The article discusses ensuring the efficiency of financial security management of agricultural enterprises. Objectives. The study aims at the diagnostics of financial security management efficiency of agricultural enterprises. Methods. The study draws on general scientific and special methods, like analysis, synthesis, modeling, abstraction, systematization and generalization of obtained results. Results. The comprehensive assessment of the financial condition management process of enterprises in the Lugansk People's Republic reflects the level of achievement of management goals. My approach rests on the symbiosis of several areas of assessment: the level of financial security of the enterprise, determined by target parameters of financial condition; management performance in the field of financial security; the efficiency of using the resource potential of the enterprise. Conclusions. The financial security management of agricultural enterprises in the region is low, which is mainly due to a decrease in their financial condition and the land resource potential. The identified trends in the system of ensuring the financial security of enterprises should form the basis of a new concept for agriculture development in the region.

A robust optimization to dynamic supplier decisions and supply allocation problems in the multi-retail industry

The research focuses on multi-retail distribution with a strategic distribution network. Challenges include intense competition, logistical and transportation complexities requiring robust infrastructure like warehouses and efficient supply chain management, as well as operational inefficiencies and distribution costs. To address these issues, a model is applied to make strategic decisions, such as determining the necessary number of facilities to minimize total supply chain network operational costs and infrastructure for retail distribution. The outcome is a model that introduces a novel approach to enhancing supply chain efficiency and effectiveness from production to distribution stages, thereby reducing system costs, including ordering costs and inventory handling. Costs and loss costs resulting from remaining products produced can be minimized by considering networks, multiple suppliers, multiple warehouses, Distribution Centers (DC), multiple retailers, and multiple products, factoring in the distances between facilities in the network. Subsequently, comprehensive testing of inspection, distribution, and retail parameters is conducted, with a focus on specific periods and product types. When applying this model, certain characteristics need to be considered regarding the importance of selecting efficient suppliers of goods, such as procurement, performance improvement, and the number of supply chains and supply chain systems. This research introduces novelty in production methods that can lead to increased customer satisfaction, sales, market share, profit margins, more effective brand advertising, and revenue streams. In this process, the research undergoes a training, testing, and validation process in forming a strategic multi-retail distribution network model, spanning a total of 52 epochs. This process yields accuracy values for training at 90 %, testing at 92 %, and validation at 94 %

A High‐Performance Passive Radiative Cooling Metafabric with Janus Wettability and Thermal Conduction

AbstractWith the development of industry and global warming, passive radiative cooling textiles have recently drawn great interest owing to saving energy consumption and preventing heat‐related illnesses. Nevertheless, existing cooling textiles often lack efficient sweat management capacity and wearable comfort under many practical conditions. Herein, a hierarchical cooling metafabric that integrates passive radiation, thermal conduction, sweat evaporation, and excellent wearable comfort is reported through an electrospinning strategy. The metafabric presents excellent solar reflectivity (99.7%, 0.3–2.5 µm) and selective infrared radiation (92.4%, 8–13 µm), given that the unique optical nature of materials and wettability gradient/micro‐nano hierarchical structure design. The strong moisture‐wicking effect (water vapor transmission (WVT) of 2985 g m−2 d−1 and directional water transport index (R) of 1029.8%) and high heat‐conduction capacity can synergistically enhance the radiative cooling efficiency of the metafabric. The outdoor experiment reveals that the metafabric can obtain cooling temperatures of 13.8 °C and 19.3 °C in the dry and sweating state, respectively. Meanwhile, the metafabric saves ≈19.3% of annual energy consumption compared with the buildings with HAVC systems in Shanghai. The metafabric also demonstrates desirable breathability, mechanical strength, and washability. The cost‐effective and high‐performance metafabric may offer a novel avenue for developing next‐generation personal cooling textiles.

Irrigation and Agricultural Opportunities: Evaluating Hemp (Cannabis sativa L.) Suitability and Productivity in Lebanon

Within the prevalent challenges posed by climate change and decreasing resources, this research underscores the importance of adopting sustainable agricultural practices combined with efficient water resource management. Employing comprehensive climate and soil suitability analyses, this research analyzed the capacity of hemp (Cannabis sativa L.) to adapt to Lebanon’s heterogeneous environmental landscapes across two distinct growing seasons (autumn and spring). Both climate and edaphic suitability mapping were conducted to study hemp’s suitability. AquaCrop v.7.1 was used to simulate seed yield, biomass production, irrigation needs and yield water productivity in the different agro-homogeneous zones of Lebanon for the two considered seasons. The findings revealed that approximately 30% and 19% of Lebanon’s land exhibit suitability for hemp cultivation during the spring and autumn seasons, respectively. According to AquaCrop model simulations, under the prevailing climatic conditions, the predicted seed yield will range from 3.7 to 5.6 t ha−1 under rainfed conditions and will reach 11.1 t ha−1 for irrigated cultivation. Moreover, employing efficient irrigation techniques during the spring season showed a significant improvement in both yield and biomass of hemp. The enhancement was evident, with notable increases of 112.22% in yield and 96.43% in biomass compared to rainfed conditions. This research highlights the importance of identifying suitable regions within Lebanon capable of supporting hemp cultivation in a sustainable manner. Such research not only promises economic development but also aligns with broader global sustainability objectives.

NAVIGATING THE APPLICATION OF ARTIFICIAL INTELLIGENCE IN PROJECT MANAGEMENT: A SCIENTOMETRIC ANALYSIS

This comprehensive literature review delves into the extensive body of research exploring the role of artificial intelligence (AI) in project management. Its primary objective is to amalgamate current knowledge while discerning prevalent trends, challenges, and advantages associated with incorporating AI into project management methodologies. The study employed bibliometric analysis using VOSViewer® software to scrutinize 246 pertinent publications sourced from the Scopus database, spanning the years 2013 to 2023. The findings from the Association Strength and Density Analysis revealed distinct clusters: Cluster 1 elucidated strong associations with terms like «construction project» «technology» «algorithm» «performance» and «time»; Cluster 2 emphasized «case stud,» «decision» and «cost»; while Cluster 3 concentrated on «literature» «industry» and «framework» Moving forward, promising areas for further exploration encompass the refinement of AI algorithms, exploration of AI’s impact on project outcomes, and the fusion of AI with emergent technologies like blockchain and the Internet of Things (IoT). This research serves as a foundational roadmap for future investigations aiming to leverage AI to enhance project management effectiveness and efficiency. Keywords: scientometric analysis, bibliometric review, project management, artificial intelligence, Machine Learning, cluster analysis, research trends.

Developing a strategic plan for efficient management of industrial waste in the machinery sector at United Tractors Company

United Tractors Company prioritizes sustainable waste management practices. This study investigated their current system, aiming to identify opportunities for improvement in efficiency and environmental impact. The research focused on how effectively United Tractors manages their waste streams, from minimizing generation at the source to responsibly processing and disposing of unavoidable waste. The analysis revealed a successful integrated waste management system at United Tractors, encompassing practices like composting, recycling, and proper treatment of hazardous materials. This approach demonstrates their commitment to minimizing their environmental footprint. The study went beyond current practices, identifying promising advancements in waste processing technologies like gasification and bioethanol production. These techniques offer exciting possibilities for further reducing waste and potentially even generating valuable resources from waste materials. The effectiveness of United Tractors' system can be attributed to their comprehensive approach. The study conducted a detailed waste collection study to understand the composition and volume of waste generated across various departments. This data-driven approach allowed for a thorough cost analysis and an evaluation of the operational efficiency within the waste management system. Importantly, the study highlighted the potential benefits of incorporating advanced waste processing techniques for even greater sustainability in the future. While further feasibility studies are needed before full-scale implementation, these findings pave the way for United Tractors to develop and implement even more sustainable waste management practices in the coming years

Electric underwater tools for sun coral management

Sun coral, identified as Tubastraea coccinea and Tubastraea tagusensis, are invasive marine species originally from the Pacific Ocean that have become a significant threat to native biodiversity and ecosystems in Brazil. The rapid growth and unique reproduction strategies of Tubastraea species have facilitated their success as invasive species. In the past two decades, Brazil has experienced a notable loss of biodiversity, partially attributed to invasive species, as reported by the Brazilian Platform on Biodiversity and Ecosystem Services. Current management efforts primarily involve manual removal, often employing sledgehammers and chisels, carried out by environmental government agencies, in partnership with NGOs and volunteers. However, the need for more efficient management strategies emphasizes the important role of engineering and technology in improving environmental management. To address this issue, our work focuses on the development and prototyping of two underwater tools: an impact hammer and a rotating brush. These tools are designed with ergonomic features, operating time, and size considerations suitable for use by SCUBA divers. Our prototypes have successfully met the required specifications and offer potential for large-scale manufacturing, promising more effective measures for controlling invasive sun coral in Brazil.

Developing a strategic plan for efficient management of industrial waste in the machinery sector at United Tractors Company

United Tractors Company prioritizes sustainable waste management practices. This study investigated their current system, aiming to identify opportunities for improvement in efficiency and environmental impact. The research focused on how effectively United Tractors manages their waste streams, from minimizing generation at the source to responsibly processing and disposing of unavoidable waste. The analysis revealed a successful integrated waste management system at United Tractors, encompassing practices like composting, recycling, and proper treatment of hazardous materials. This approach demonstrates their commitment to minimizing their environmental footprint. The study went beyond current practices, identifying promising advancements in waste processing technologies like gasification and bioethanol production. These techniques offer exciting possibilities for further reducing waste and potentially even generating valuable resources from waste materials. The effectiveness of United Tractors' system can be attributed to their comprehensive approach. The study conducted a detailed waste collection study to understand the composition and volume of waste generated across various departments. This data-driven approach allowed for a thorough cost analysis and an evaluation of the operational efficiency within the waste management system. Importantly, the study highlighted the potential benefits of incorporating advanced waste processing techniques for even greater sustainability in the future. While further feasibility studies are needed before full-scale implementation, these findings pave the way for United Tractors to develop and implement even more sustainable waste management practices in the coming years

Electric underwater tools for sun coral management

Sun coral, identified as Tubastraea coccinea and Tubastraea tagusensis, are invasive marine species originally from the Pacific Ocean that have become a significant threat to native biodiversity and ecosystems in Brazil. The rapid growth and unique reproduction strategies of Tubastraea species have facilitated their success as invasive species. In the past two decades, Brazil has experienced a notable loss of biodiversity, partially attributed to invasive species, as reported by the Brazilian Platform on Biodiversity and Ecosystem Services. Current management efforts primarily involve manual removal, often employing sledgehammers and chisels, carried out by environmental government agencies, in partnership with NGOs and volunteers. However, the need for more efficient management strategies emphasizes the important role of engineering and technology in improving environmental management. To address this issue, our work focuses on the development and prototyping of two underwater tools: an impact hammer and a rotating brush. These tools are designed with ergonomic features, operating time, and size considerations suitable for use by SCUBA divers. Our prototypes have successfully met the required specifications and offer potential for large-scale manufacturing, promising more effective measures for controlling invasive sun coral in Brazil.

METHOD OF THE SERVER HORIZONTAL LOAD BALANCING FOR REDUCING ENERGY CONSUMPTION

Background. Server horizontal load balancing is a crucial aspect of modern computing systems, particularly in cloud computing environments. The efficient management of incoming flows of applications is essential to ensure optimal resource utilization and minimize energy consumption. This study focuses on developing a method for managing the incoming flow of applications to reduce energy consumption in server horizontal load balancing. Objective. The primary objective is to develop a method for managing the incoming flow of applications to reduce energy consumption in server horizontal load balancing. This involves identifying the maximum permissible number of applications that can simultaneously enter the system for service, ensuring that the volume of resources used is close to the total maximum possible amount of resources. The method aims to minimize the variance of the elements of the sequence of maximum allowable numbers of applications and the dispersion of the elements of the sequences of volumes of resources used. Methods. The method involves several key steps: Input Load Smoothing Scheme: A static control method is proposed to smooth the incoming load. This involves developing a scheme for smoothing the incoming load, which is a set of values of the maximum allowable number of requests (sequence {ki}) arriving at the system input for a small time interval ∆ti. The sequence is selected to ensure that the volume of resources used is close to the total maximum possible amount of resources. Genetic Algorithm: The selection of the sequence {ki} is carried out using a genetic algorithm. The algorithm involves crossover, mutation, and selection operations to minimize the variance of the elements of the sequence and the dispersion of the elements of the sequences of volumes of resources used. Resource Allocation: The method involves allocating resources for the maintenance of a given type of service. The parameters of the server, which are characterized as the resources of the system serving the applications, are usually calculated for the average values of the parameters of the input stream. Delay Introduction: To manage the application processing process and prevent resource shortages, a delay is introduced for a part of the applications that coincide with a surge in load. The delay time is determined so that delayed applications do not enter the system until the previous burst of load is successfully serviced in the resource-consuming functional block. Results. The results of the study include the development of a method for managing the incoming flow of applications to reduce energy consumption in server horizontal load balancing. The method involves the use of a genetic algorithm to select the sequence {ki} that minimizes the variance of the elements of the sequence and the dispersion of the elements of the sequences of volumes of resources used. Conclusions. The study concludes that the proposed method for managing the incoming flow of applications can effectively reduce energy consumption in server horizontal load balancing. The method involves the use of a genetic algorithm to select the sequence {ki} that ensures efficient use of system resources and minimizes the variance of the elements of the sequence and the dispersion of the elements of the sequences of volumes of resources used. The method can be applied in various scenarios where efficient use of system resources is crucial, such as in cloud computing environments.

Deep reinforcement learning based controller placement and optimal edge selection in SDN-based multi-access edge computing environments

Multi-Access Edge Computing (MEC) can provide computility close to the clients to decrease response time and enhance Quality of Service (QoS). However, the complex wireless network consists of various network hardware facilities with different communication protocols and Application Programming Interface (API), which result in the MEC system's high running costs and low running efficiency. To this end, Software-defined networking (SDN) is applied to MEC, which can support access to massive network devices and provide flexible and efficient management. The reasonable SDN controller scheme is crucial to enhance the performance of SDN-assisted MEC. At First, we used the Convolutional Neural Networks (CNN)-Long Short-Term Memory (LSTM) model to predict the network traffic to calculate the load. Then, the optimization objective is formulated by ensuring the load balance and minimizing the system cost. Finally, the Deep Reinforcement Learning (DRL) algorithm is used to obtain the optimal value. Based on the controller placement algorithm ensuring the load balancing, the dynamical edge selection method based on the Channel State Information (CSI) is proposed to optimize the task offloading, and according to CSI, the strategy of task queue execution is designed. Then, the task offloading problem is modeled by using queuing theory. Finally, dynamical edge selection based on Lyapunov's optimization is introduced to get the model solution. In the experiment studies, the assessment method evaluated the performance of two sets of baseline algorithms, including SAPKM, the PSO, the K-means, the LADMA, the LATA, and the OAOP. Compared to the baseline algorithms, the proposed algorithms can effectively reduce the average communication delay and total system energy consumption and improve the utilization of the SDN controller.

Sleep duration and leisure activities are involved in regulating the association of depressive symptoms, muscle strength, physical function and mild cognitive impairment

BackgroundIn order to lessen the burden of Alzheimer's disease (AD), timely and efficient management and intervention methods for mild cognitive impairment (MCI) are crucial. MCI is seen as a transitional stage between normal aging and dementia. Although sarcopenia is an important risk factor for MCI, it is unclear what factors mediates and regulates the brain-muscle communication. Our objective was to investigate the indirect moderating effects of sleep duration and leisure activity on depressive symptoms, sarcopenia and MCI. MethodPanel data from the 2015 China Health and Retirement Longitudinal Study (CHARLS) database was used in this investigation. we used Bootstrap sampling to determine the relationship between sleep duration, leisure activity, depressive symptoms, sarcopenia, and MCI in mediation and indirect moderation models. The outcome measurements were odds ratio (OR) and confidence interval (CI). ResultAfter adjusting for confounding variables, we discovered that sarcopenia and its traits, such as handgrip strength, gait speed, standing test, and muscle mass, were significantly correlated with MCI. Second, the results implied that depressive symptoms played a role in modulating the link between physical function, muscle strength, and MCI. This moderating effect was impacted by short sleep duration and moderate to high levels of leisure activities. ConclusionWe discovered that MCI was highly correlated not only with physical function and muscle strength but also with depressed symptoms, which acted as a partially mediating factor in this connection. Handgrip strength, gait speed, and standing test mediated the correction of MCI caused by depression symptoms. Importantly, leisure activities and sleep duration had indirect moderating effects on the above associations, and future management policies should take these factors into account.

Latest Innovations in Facilities and Infrastructure Management: Implementation of an Efficient Management System

Schools face significant challenges in managing facilities and infrastructure due to limited awareness of security risks, maintenance procedures, and damage prevention strategies. This research addresses this gap by developing a facilities and infrastructure management system using the ADDIE model. This system not only aims to improve the efficiency and effectiveness of school asset management but also serves as a practical learning tool for vocational high school students specializing in office management and business services. This research employed a Research and Development (R&D) approach. The data conducted by using questionnaire and analyzed descriptively. The developed facilities and infrastructure management system underwent evaluation, and the findings confirmed its highly recommended and effectiveness in streamlining school asset management. Additionally, the system proved to be a suitable educational tool for vocational students, enhancing their practical skills and knowledge.

Virtual Assistant by using Large Language Model

Abstract— This paper presents the development of a virtual assistant named “Pragyan,” utilizing a Large Language Model (LLM) for natural language understanding and response generation. The virtual assistant is designed to interact with users through text and speech inputs, providing informative and conversational responses. Pragyan is built with a frontend user interface, a backend server, and a database for efficient communication and data management. The performance evaluation and result analysis demonstrate the effectiveness and user-friendliness of the virtual assistant Keywords: Virtual Assistant, Large Language Model, Natural Language Processing, Frontend, Backend, Database, Performance Evaluation, Result Analysis.