Application Of Management System Research Articles

A Brief Discussion on Innovations in Student Fee Management Systems in Higher Education Institutions Under the Network Environment

As the reform of the higher education system in China continues to deepen, the scale of institutions expands, and the channels for fee collection diversify, the types and quantities of invoices have also seen rapid growth. The application of student fee management systems in universities enhances the accuracy of fee management, showcasing advantages in intelligence, precise record-keeping, and statistical capabilities—qualities that traditional manual fee collection cannot match. However, several issues remain unresolved in practice. In traditional student fee management processes, the systems used are often isolated, preventing effective data sharing. Various problems have surfaced in student fee management, and addressing these issues is crucial for ensuring timely and full fee collection, which is key to promoting the rapid development of higher education.

Construction and Application of Place Name and Address Management System Based on Elasticsearch

Abstract. Place names and addresses serve as essential references for locating information about people's living, production, and various activity sites. They are a crucial component of public geographic framework data and act as tools and bridges for social communication in daily production and life. This paper presents a comprehensive system for managing place names and addresses by integrating a multi-level address model, data synchronization between PostgreSQL and Elasticsearch, and advanced query capabilities to ensure efficient and accurate data management. The system implements full lifecycle management of place names and addresses, fully leveraging the advantages of relational databases and distributed search engines. It provides essential functions such as address standardization, real-time updates, maintenance management, conditional queries, and statistical analysis. It has been successfully implemented in the National platform for common geospatial information service, laying the foundation for the next steps in refining social governance based on place names and addresses, and further advancing the digital transformation of government operations.

Numerical thermal analysis and structural optimization of cascaded PCM heat sinks for thermal management of electronics

In the present study, an innovative cascaded phase change material (PCM) heat sink using organic PCMs was proposed for electronic thermal management. The design arranges multiple PCMs with progressively lower melting points along the heat transfer path, allowing active control of the melt front. A numerical model with 5 % accuracy was developed to evaluate thermal performance. Based on the validated model, the effects of PCM stage numbers, PCM volume fractions, fin types, and fin volume fractions were analyzed. The fin volume fractions were further optimized using a support vector machine (SVM) and genetic algorithm (GA) methods. Results showed that a three-stage PCM heat sink with pin fins and increasing configurations outperformed single-stage PCM heat sinks, enhancing heat transfer by up to 36.7 %. Additionally, the innovative cascaded PCM heat sink with a uniform 20 % fin volume fraction across the three stages achieved a 38.8 % improvement compared to single-stage configurations. When the fin volume fractions were set to 24.1 %, 17.6 %, and 13.0 % for the three stages, thermal performance of the innovative cascaded PCM heat sink was enhanced by up to 39.8 % compared to single-stage configurations. The findings provide valuable insights for the design and application of PCM-based thermal management systems, potentially leading to more efficient solutions for various engineering fields.

Intelligent Financial Management Systems Innovations and Applications in the Digital Era

With the advancement of digital transformation, intelligent financial management systems have played a significant role in improving the efficiency, accuracy, and decision-making capabilities of corporate financial management. This study explores the performance and impact of three intelligent financial management systems — Digital Processing Methods and Financial Reimbursement Document System (System A), Industrial Digitalization Industry Enterprise Growth Evaluation System (System B), and Cloud-based Intelligent Financial Management Tools (System C) — in practical applications through case study methods. The results show that these systems have significantly improved the efficiency and accuracy of financial management, enhanced decision-making capabilities, and reduced operational costs through automated processes, data mining, and machine learning techniques. The study also points out challenges in the implementation process, such as data quality, user acceptance, and system integration issues, and predicts future development trends. Finally, the paper discusses the limitations of the research and proposes directions for future research.

Strategi Pengelolaan Aset Desa Berbasis Aplikasi Sistem Pengelolaan Aset Desa (Sipades) Di Desa Kekeri Kecamatan Gunungsari Kabupaten Lombok Barat

This research is based on the results of observations which found several problems in the Village Asset Management Strategy Based on the "SIPADES" Village Asset Management System Application in Kekeri Village, Gunungsari District, West Lombok Regency, namely: Lack of direction from the Social, Community and Village Empowerment Service regarding guidelines for using the System application Village Asset Management, there is no special emphasis on the use of the Village Asset Management System application, there is no updating of the Village Asset Management System application every year. The aim of this research is to determine the Village Asset Management Strategy Based on the "SIPADES" Village Asset Management System Application in Kekeri Village, Gunungsari District, West Lombok Regency. This research is a descriptive study with a qualitative approach. To obtain information and data, researchers used semistructured interviews and documentation methods. The inhibiting factors were lack of budget due to not having original village income and funds not being received on time, lack of guidance and competency improvement from related agencies, the Sipades application had not been running optimally and was still not can access. Efforts made to overcome obstacles include budgeting a larger budget, seeking budget from other income by increasing the PADes or from third party donations and further efforts by exchanging budget functions first, holding training related to village asset management and bringing in parties related to village asset management to provide guidance to village officials, BPD, LPM budgeted from the APBDes.

IMPLEMENTASI E-GOVERNMENT MELALUI APLIKASI SISTEM PENGELOLAAN ASET DESA (SIPADES) DI DESA DUKUHSARI KECAMATAN JABON KABUPATEN SIDOARJO

The study aims to describe and analyze how implementation of e-government through the village asset management system application in the Dukuhsari Village Jabon District Sidoarjo Regency. The study uses qualitative descriptive data collection techniques through interviews, observation, and documentation. The data analysis model in this study is data collection, data reduction, data presentation, and drawing conclusions. Results from the study indicate that an organizational indicator, there is an organizational structure in the Dukuhsari Village government and the government has provided a facility for implementing the asset management system application, but there is still a lack of human resource capabilities. From the interpretation indicator in the socialization dimension, the policy has not been optimal because of the lack of suitable socialisation to so the operator does not understand the procedures for using the asset management system application. In the application dimension, it shows that the technical conditions experienced obstacles in the form of frequent application often errors during working hours thus disrupting the operator from inputting village assets into the asset management system application.

Model of Utilization Knowledge Management System Application

Model of Utilization Knowledge Management System Application

Advancing SDGs and performance management strategies for security personnel in higher education

Orientation: Performance management aligns individual and organisational goals, enhancing employee motivation, sustaining organisational success.Research purpose: The study aimed to investigate challenges experienced by security managers with performance management systems in a tertiary institution in Durban, South Africa.Motivation for the study: Understanding challenges delivers insights to advance organisational effectiveness, support sustainable development, and enhance human resources (HR) practices in the higher education security sector.Research approach/design and method: A qualitative approach was used. Twelve security managers were purposively selected for semi-structured interviews. Data were analysed using thematic analysis and NVivo software.Main findings: The study identified three challenges, namely inadequate training, education, development and communication, technological barriers and low computer literacy, limited resource allocation, inconsistent rewards, and a lack of transparency. These challenges were found to hinder performance management system application, reducing employee engagement and productivity.Practical/managerial implications: The study recommends the institution increase adult basic education and training in technological skills and literacy. Enhancing feedback mechanisms, conducting performance needs assessments, and implementing fair reward strategies may improve sustainable development of performance management practices.Contribution/value-add: The study advocates for practical strategies in response to the challenges faced by security managers to enhance performance aligned with sustainable development goals 4 (quality education), 8 (decent work and economic growth), 10 (reduced inequalities) and 16 (peace, justice and strong institutions), contributing to sustainable HR, embracing contextualised performance management application in developing countries.

A portable application framework for energy management and information systems (EMIS) solutions using Brick semantic schema

This paper introduces a portable framework for developing, scaling and maintaining energy management and information systems (EMIS) applications using an ontology-based approach. Key contributions include an interoperable layer based on Brick schema, the formalization of application constraints pertaining metadata and data requirements, and a field demonstration. The framework allows for querying metadata models, fetching data, preprocessing, and analyzing data, thereby offering a modular and flexible workflow for application development. Its effectiveness is demonstrated through a case study involving the development and implementation of a data-driven anomaly detection tool for the photovoltaic systems installed at the Politecnico di Torino, Italy. During eight months of testing, the framework was used to tackle practical challenges including: (i) developing a machine learning-based anomaly detection pipeline, (ii) replacing data-driven models during operation, (iii) optimizing model deployment and retraining, (iv) handling critical changes in variable naming conventions and sensor availability (v) extending the pipeline from one system to additional ones.

A Taxonomy of Knowledge Management Systems in the Micro-Enterprise

Knowledge Management Systems enhance innovation, increase operational efficiency, and improve decision-making in business organisations. The administrative and resource overheads required to implement and maintain such systems inherently exclude the smallest of firms from reaping these benefits. This research aims to identify, evaluate, and summarize the distribution of research on knowledge management and supporting systems across business size classifications with a particular focus on micro-enterprises. It also seeks to establish if existing knowledge management models, practices, and systems have invested due consideration in their design to cater for the limited resources typically found in the micro-enterprise. It contributes new insight into the applicability of knowledge management systems to micro-enterprises and it stimulates a possible re-think of how such systems can cater to the specific constraints of this prolific business type. This taxonomy is the result of a thorough analysis of 168 research papers from a total of 10511 papers published in reputable conference proceedings since 2012. It focuses on key knowledge management themes covered, including the size of the enterprise, the adoption challenges, the potential benefits, the technologies used, and the aspects of the knowledge management cycle that are being employed. Furthermore, it draws on this analysis to highlight the appropriateness of existing knowledge management systems to the distinctive risk and opportunity characteristics of the micro-enterprise.

Coupling optimization of protruding fin and PCM in hybrid cooling system and cycle strategy matching for lithium-ion battery thermal management

Based on liquid cooling and phase change material (PCM), a fin-enhanced composite thermal management system suitable for high power and extended cycle operations of lithium-ion battery module at high ambient temperature is proposed in this work. The coupling effect between the protruding fin structure and PCM thickness, as well as the addition of expanded graphite to the PCM, are investigated to optimize hybrid cooling arrangement. The results show that synergistic optimization of the protruding fin structure and PCM arrangement can enhance heat diffusion from the batteries to the cooling water, improve PCM utilization, and ensure sufficient latent heat. And then, the expanded graphite-modified PCM can make heat absorption and phase transition more uniform, and battery temperatures can be further decreased by up to 7.45 °C with 16 wt% expanded graphite. Clearly, the coupling optimization improves the cooling performance and applicability of conventional thermal management systems, while the temperature difference and maximum temperature in the optimized system have been regulated to within 4.30 °C and 46.78 °C under 40 °C environment and 5C discharge, respectively. Moreover, the cyclic charging and discharging strategies are designed and matched, and using the matching strategy with a fixed charge or discharge rate of 1C provides lower temperatures and better temperature uniformity, which can always control the temperatures below 47.22 °C and temperature difference below 4.69 °C. The optimized system with cycle strategy matching ensures the repeatability of battery operation and provides cooling solutions for different application scenarios.

Edge–cloud collaborative estimation lithium-ion battery SOH based on MEWOA-VMD and Transformer

The State of Health (SOH) of lithium-ion batteries significantly impacts the performance, safety, and reliability of the battery, making it a crucial component of the battery management system. Addressing the issues of inadequate accuracy and lack of robustness in current SOH estimation methods, this study introduces a novel methodology for estimating SOH in lithium-ion batteries. It leverages the multi-population evolution whale optimization algorithm optimized variational mode decomposition (MEWOA-VMD) in conjunction with Transformer architecture. This framework enhances the efficiency and accuracy of SOH estimation by leveraging the computational capabilities of edge devices for real-time data processing, as well as the robust data processing power and model training advantages offered by cloud computing. Specifically, MEWOA is utilized to optimize VMD parameters, enabling MEWOA-VMD to fully decompose the capacity signal of lithium-ion batteries. This results in a component showing a global attenuation trend and a set of fluctuating components that represent capacity regeneration, thereby minimizing the impact of capacity regeneration on SOH estimation. Subsequently, all components are collectively input into the Transformer, marking the first application of this method for input. To enhance convergence speed and training efficiency, the layer normalization (LN) layer within the neural network architecture is proactively advanced. Finally, various artificial neural networks are compared and validated on three publicly available datasets. Furthermore, Gaussian noise is introduced into the original data to validate robustness. To confirm the practical applicability of the proposed method, real-world vehicle data is used for SOH estimation. The results indicate that the proposed method achieves a maximum MSE of no more than 0.009% across three publicly available datasets, showcasing improved accuracy and stability in SOH estimation. The practical applicability is further validated using real-world vehicle data, proving the proposed method’s potential for application in edge cloud-based battery management systems.

Assessing the potential of functionally-enhanced periphyton in supplying rice plant phosphorus nutrition in paddy fields

This study investigates the potential of functionally-enhanced periphyton enriched with phosphate-solubilizing bacteria (PSB) as a novel biofertilizer to improve the growth parameters and yield attributes of plants in rice paddy fields. The research represents the first farm-scale investigation of the PSB-enhanced periphyton. The study aimed to assess the ability of the periphytic biomass to act as a reservoir for phosphorus (P), regulating its bioavailability to rice plants and decreasing the demand for chemical inputs at the field-scale. In order to achieve this, superior P-solubilizing bacteria isolates were utilized to prepare the functionally-enhanced periphyton. The research revealed that PSB-enhanced periphyton acts as a controlled-release biofertilizer, minimizing P losses during low-demand growth stages and enhancing P supply during high-demand growth phases. The findings demonstrated that P concentration declined significantly (by 75.2%) in the paddies' overlying water under periphyton application. Conversely, periphyton increased soil P availability (24.2%) and plant P content (16.0%). The research shines a light in the possibility of utilizing the functionally-enhanced periphyton as an effective inoculant for sustainable rice production, with implications for reducing the heavy reliance on chemical inputs in agricultural systems. This research serves as a bridge between laboratory and greenhouse experiments and real farm conditions, offering practical applications for sustainable management of agrifood systems. The investigation's results enable a deeper understanding of periphyton and its role in sustainable rice production, providing a reliable source for researchers, producers, and policymakers involved in sustainable production systems.

Development of Geospatial Asset Management System for Higher Education

Abstract: The integration of Geographic Information System (GIS) for asset management was addressed in this study. Geographic Information System (GIS) as a decision support system was integrated within the process of asset management to strengthen the monitoring of tangible assets within the organization. The main objective of this study is to design and develop a Location-Based Asset Management Application System. A waterfall model was utilized to create the system. GeoJSON was used to represent geographical features or attributes of the data gathered. A standardized adapted evaluation form was used to determine the Functionality, Performance, Robustness, and Workmanship of the developed application and interpreted using descriptive analysis. The analysis shows that the developed system is excellent in terms of Functionality, Performance, Robustness, and Workmanship. Based on the study's findings, the developed spatial asset management system is an effective way of monitoring and delivering asset management information and resources to its various constituents. It is highly recommended that a designed system should be utilized and use the developed systems to proactively respond and adapt to the modern world in delivering and managing resources.

Magnetic Field Mapping-Based Battery Management System (BMS) for Lead Acid Application

Lead Acid Batteries (LAB) are a widely used technology in Energy Storage Systems (ESS) due to their abundant and low-cost materials, non-flammable water-based electrolyte, and high recyclability rate. The main applications for LABs are in mobility, data centers, and telecommunications. According to the Consortium of Battery Innovation (CBI), the market for lead acid batteries is projected to increase 150 GWh between 2025 and 2030. Therefore, it is fundamental to identify emerging failure modes in LABs in ESS systems to reduce battery degradation and to extend the use life.An important failure mode in flooded LABs is acid stratification. This research explores H+ concentration changes in H2SO4 (sulfuric acid) electrolyte as a correlation of acid stratification. The objective is to develop a non-invasive, non-destructive, and accurate real-time battery monitoring system. The Magnetic Field Probing (MFP) technique, popular in the medical imaging field, shows a promising solution for ESS performance evaluation. This technique can measure induced magnetic field changes based on variation in H+ concentration in the cell during cycling. See Figure. 1 (a). MFP provides early onset notification of stratification in flooded LABs with capability to discern other failure modes in non-flooded lead batteries.A set of experimental trials measured pH and magnetic field variation of H2SO4 electrolyte. See Figure. 1 (a). The preliminary results demonstrated changes in electrolyte pH due to possible stratification. See Figure. 1 (b). A correlation between the output voltage resulting from the interaction of the induced magnetic field and the changes in the electrolyte concentration was found. See Figure 1(c) The optimal AC input frequency maximizes the induced magnetic field response. The value found for optimal AC input frequency was 32kHz, which depends on the physical properties of the magnetic field inductors (air core solenoid coils). The experimental results showed and concluded that the induced magnetic field across the tested cell is also inversely proportional to the distance between coils attached to the cell.Further research involves the use of magneto-resistors to establish a magnetic field mapping in lead acid cells as they are being cycled. Magnetic field response is measured while lead acid cells are cycled from 100% to 20% state of charge range. In the future, this study will provide insights and findings to model and predict cell stratification in lead acid cells with electrochemical computational simulations.Keywords: Energy storage systems, lead acid batteries, acid stratification, magnetic field, non-invasive method Figure 1

Enhanced multi-constraint dung beetle optimization-kernel extreme learning machine for lithium-ion battery state of health estimation with adaptive enhancement ability

Accurately estimating the state of health (SOH) of lithium batteries is a critical and challenging task in battery management systems. Data-driven models are widely used for SOH estimation but still suffer from the difficulty of balancing speed, accuracy, and adaptability. Therefore, this study constructs the dung beetle optimization algorithm to optimize the kernel extreme learning machine model. This paper addresses the issues of long iteration time and mismatches in kernel function mapping in data-driven models. To improve the model's generality, an adaptive learning kernel function is designed to complement the polynomial kernel function and form a joint function. This joint function is then introduced into a single implicit-layer extreme learning machine, which achieves fast speed and strong adaptive capability. To enhance the algorithmic parameter search capability, the optimal Latin hypercube idea, and the Osprey algorithm's global exploration strategy are introduced, which effectively improves the algorithm's global search capability. Additionally, it successfully regulated the positional update through the design of the logarithmic weighting factor, which improved the local search and convergence capabilities of the algorithm. The experiment validates the effectiveness and rationality of the proposed model for advancing battery management system applications.

Development and application of distribution network multi-state management and control system

Development and application of distribution network multi-state management and control system

An improved microgrid energy management system based on hybrid energy storage system using ANN NARMA-L2 controller

This research describes an intelligent Energy Management System (EMS) for a microgrid application that employs a Nonlinear Autoregressive Moving Average Level 2 (NARMA-L2) artificial neural network (ANN). The hybrid energy resources (PV/WIND), a hybrid energy storage system (HESS) with batteries and supercapacitors (SC), and loads are all integrated into the microgrid. Maximum Power Point Tracking (MPPT) in a photovoltaic (PV) system is based on the Nonlinear Autoregressive with exogenous inputs (NARX) approach. The flowchart, rules, memberships, and scenarios that allocate energy among various components based on battery State of Charge (SoC), PV/wind power, and load factors are described in the article. To validate the EMS's effectiveness, simulation tests under various conditions are presented. Supercapacitors (SCs) reduce DC bus voltage swings, lowering battery stress and extending battery life, it has been demonstrated using various load variations, as well as various sun irradiation and wind speed values under various conditions. The simulation results in the MATLAB/Simulink environment, validate the effectiveness of the proposed approach and produce effective DC BUS stabilizing and maintaining frequency stability of system that shows the importance and efficiency of the control strategy used.

IntDEM: an intelligent deep optimized energy management system for IoT-enabled smart grid applications

IntDEM: an intelligent deep optimized energy management system for IoT-enabled smart grid applications

Assessment of Occupational Health and Safety Management System Implementation in General Hospital

Objective: This study aims to assess the application of Occupational Health and Safety Management System (OHSMS) in Kertosono Regional General Hospital by identifying the obstacles and strategies that exist, as well as successful system implementation for health sector.Methods: This study utilized a mixed-methods design to assess OHSMS effectiveness and employee perceptions before and after implementation.Findings: Results show a statistically significant decrease in incidents at work after implementation of an OHSMS, which confirms that the global safety performance of this plant is affected by the OHSMS. By contrast, though inadequate instruction, lack of continuous leadership dedication and investment were some major obstacles to successful operation of OHSMS.Novelty: The findings from this study suggest the importance of structured safety management systems designed for public healthcare workers, and provide practical suggestions to bolster the effectiveness of OHSMS in Indonesia.Research Implications: The results also emphasize the importance of ongoing education and training, strong leadership support, as well as providing sufficient resources to promote a culture of safety in healthcare settings. Future research might instead seek upper bounds benefit of an OHSMS for safety or examine how technology can be integrated to provide monitoring, training function on a continuous basis.