Management System Model Research Articles

Analysis of the organizational knowledge management system of nurse education centers with hybrid Fuzzy DEMATEL-network DEA method

On-the-job training is important for the growth of organizational human capital. The present paper evaluates the efficiency of on-the-job training using the DEA model and knowledge management system to illustrate the interactions of organizational knowledge management concepts for measuring the efficiency of on-the-job training courses for employees within the organizational knowledge management systems. In this research, the DEA method was used to evaluate the efficiency of knowledge management system and analyze the interdependencies of the system. Also, the EU Knowledge and Innovation Management Measurement and the Kirkpatrick models were employed to identify the indicators. This study was conducted on 27 education centers in Iran. The results of evaluating the effectiveness of the knowledge management system show that the factor of “educational resources and facilities” is the most affecting variable and the most affected variable is “educational effectiveness”. Then, based on the DEA method, the weights of the sub-factors of the model were determined, and the efficiency of each step and as a result the efficiency of the whole system was obtained. Inefficient units were discarded and finally the efficient units were ranked. This study can help the organizations to identify the factors affecting the effectiveness of knowledge management programs.

Conceptualizing a model for cloud-based hospital management systems for the South African public health sector

Background and Aim of Study: Real-time access of information in the healthcare environment is essential, as it not only helps medical personnel to have adequate and timely information, but it also assists patients to be served more easily. Hospitals in rural areas are operating at a low bandwidth and have poor IT infrastructure that causes intermittent networks leading to disruptions and slow service delivery. This necessitates the Hospital Management System (HMS) to be deployed in the cloud environment to reduce the challenges leading to poor service delivery. The aim of the study: to develop a model for cloud-based HMS for the South African public health sector. Material and Methods: This study identified three public district municipality hospitals in Gauteng Province, South Africa, that were already using HMS and used them for data collection. Each hospital had up to 50 healthcare workers, and this formed the population of 150 from the three hospitals, from which a sample size of 108 respondents was selected. Data were collected using a closed-ended questionnaire and analyzed quantitatively using SPSS v25. Results: The results demonstrated that the suggested model has a good prediction power of 60.9% (R2=0.609) and that with the exception of environmental aspects, the rest of the constructs has a significant contribution to the successful implementation of the cloud-based HMS. Social aspects had the highest prediction power of 60.0% (β=0.600) at p=0.001; followed by risk analysis and control with 41.3% (β=0.413) at p=0.009. On the other hand, environmental aspects had the least and non-significant prediction of 12.3%. Conclusions: This study contributes to the ongoing call to have seamless healthcare provision systems. The model developed in this study extends the research of modernizing healthcare provision by leveraging technological innovations.

О МОДЕРНИЗАЦИИ СИСТЕМНОЙ МОДЕЛИ УПРАВЛЕНИЯ АРКТИЧЕСКОЙ ЗОНЫ: НЕОКЛАССИЧЕСКИЙ И ИНСТИТУЦИОНАЛЬНЫЙ ПОДХОДЫ

In economic theory, quite often there are questions aimed at discussing the possibilities for developing the Arctic zone. Interest in this problem is due to many factors, among which, first of all, are the high expectations of institutional opportunities obtained as a result of the development of the Arctic zone. This is access to large-scale energy deposits on the continental shelf, priority development of the Northern Sea Route, as well as a way to make the territories of the Far North adjacent to this zone more accessible. However, the main thing in solving the problem posed is not so much the object of research itself, the significance of which no one doubts, but rather the use of an evidence-based methodological basis when choosing a management model that is authentic to the specifics of the Arctic zone. This is due to the fact that the neoclassical version of the mechanism has serious limitations in this matter. Consequently, the fundamental task, according to the authors, in the discourse of modernizing the systemic management model in the Arctic zone is the use of an institutional direction, which opens up the opportunity to rethink the principles of the core of neoclassics and update them taking into account emerging modern material

Integration Model of Academic Information Systems and Learning Management Systems with REST Web Services Using External Databases

ICT products like Academic Information Systems (AIS) and LMS are commonlyutilized in Indonesian universities. These two ICT tools will be of tremendous use tohigher education institutions in managing their academic business procedures. The twosystems are still not connected in many higher institutions, nevertheless, for examplewhen it comes to handling academic data. If the management and integration processis carried out conventionally, it will be challenging and inefficient due to the massivevolume of data and complexity of these two systems. Observing these issues, theresearcher plans to study the two REST-based Web Service systems' connection andmake use of the External Database functionality, which will be utilized to synchronizedata in real-time from AIS to E-Learning. It is hoped that the integration modelresulting from research can be a solution for integration between AIS and LMS and canbe implemented in many higher education institutions.

Integrated Management Systems: The Case of a Penitentiary in the State of Paraíba

Objective: The objective of this article is to evaluate how the Procurador Romero Nóbrega Penitentiary, in Patos - PB, has internalized in its administration practices an integrated perspective of its ISO 14001 environmental management, ISO 9001 quality and OHSAS 18001 occupational health and safety systems. Theoretical reference: An Integrated Management System (IMS) acts in the interconnection of other systems, aiming to achieve planned management of the execution of services in order to satisfy the internal and external needs of organizations, bringing together information and experiences from different areas in a single environment of work. This integration comprises a tool capable of discovering specific paths to be followed to achieve the desired objectives, in addition to creating an organizational culture of permanent or continuous improvement in its activities. Method: As a methodology, a qualitative, exploratory and descriptive approach was used to understand how prison management occurs in terms of the incorporation of management systems. Results and conclusion: The study showed that the penitentiary does not comply with the penal executive norm and, with regard to the management system models studied, the unit internally needs investment in its structure, in its human capital and, in the external context, more public policies to achieve sustainable management. Implications of the research: The research is of great relevance to the prison system and the academic world, showing the possibility of making penal units sustainable, aggregating management systems and enhancing the achievement of prison sustainability. Originality/value: Scientific production in Brazil on the implementation of sustainable prisons is incipient, therefore, the research seeks to contribute to helping gaps in the thematic literature, as well as drawing the State's attention to alternatives for the prison system by integrating systems with sustainability goals, respecting environmental, social, economic and human values.

Establishing a dynamic and static knowledge model of the manufacturing cell management system: An active push approach

The workshop operation management (WOM) system contains a large amount of multi-source heterogeneous data, but these data often lack effective correlation, posing challenges in extracting valuable information for achieving unified system modelling at the knowledge level. Due to the lack of knowledge active support in the actual WOM system, managers could only passively rely on their own past experiences. To bridge this gap, the knowledge active push method for optimal operation management of the manufacturing cell (OOMMC) is studied based on knowledge graph (KG). Firstly, a dynamic knowledge model is established according to the knowledge application scenario of manufacturing cell, in which the Local Tangent Space Alignment (LTSA) + k-means algorithm is used for active abnormal warning. Secondly, a static knowledge model based on user needs using feature vocabulary and naive Bayesian classifier is established, where managers can obtain knowledge from the KG based on professional noun keywords or simple query questions. These two models complement and promote each other: the dynamic knowledge model using a service-based collaborative filtering method to push the nearest knowledges in the KG to users, effectively inspiring them to retrieve more relevant knowledge. While the static knowledge model evaluates the effectiveness of previously pushed knowledge by setting the knowledge demand index and providing feedback to the system to ensure accuracy of knowledge push. Finally, an active push simulation system is designed and developed to verify the feasibility and effectiveness of the proposed architecture and key enabling technologies.

Federated double DQN based multi-energy microgrid energy management strategy considering carbon emissions

Multi-energy microgrids (MEMG) play an important role in promoting carbon neutrality and achieving sustainable development. This study investigates an effective energy management strategy (EMS) for MEMG. First, an energy management system model that allows for intra-microgrid energy conversion is developed, and the corresponding Markov decision process (MDP) problem is formulated. Subsequently, an improved double deep Q network (iDDQN) algorithm is proposed to enhance the exploration ability by modifying the calculation of the Q value, and a prioritized experience replay (PER) is introduced into the iDDQN to improve the training speed and effectiveness. Finally, taking advantage of the federated learning (FL) and iDDQN algorithms, a federated iDDQN is proposed to design an MEMG energy management strategy to enable each microgrid to share its experiences in the form of local neural network (NN) parameters with the federation layer, thus ensuring the privacy and security of data. The simulation results validate the superior performance of the proposed energy management strategy in minimizing the economic costs of the MEMG while reducing CO2 emissions and protecting data privacy.

Urban water resources management with energy constraint and carbon emission intensity under uncertainty: A dual objective optimization model

Water production, utilization and recycle in urban system associated with a large amount of energy consumption and carbon emission that has increasingly international attention under sustainable development goals. In this study, a comprehensive urban water resources system management model is proposed under water-energy-carbon nexus and multiple uncertainties. The water-energy-carbon nexus was reflected in the processes of water extraction, water production and sewage treatment, and two objectives of maximizing the system benefit and minimizing carbon emission is transformed into two linear programming problem through the dual-objective interval fractional programming. Considering the interaction among water supply/demand, pollutants discharge control, energy consumption and self-energy utilization, indirect carbon emission as the main constraints, the developed model is applied to a typical water and energy sources shortage area of Qingdao city in north China. Multiple scenarios related to energy consumption and carbon emission control are designed to search the relationship among energy consumption, carbon emission and water resources allocation schemes. The results indicated that water demand as the main driving factor of energy consumption and carbon emission in urban water system cannot be directly limited through water supply structure adjustment. Through introducing self-energy supply (sludge utilization) and energy consumption control, water resources allocation schemes and water supply structure would be changed to improve energy saving potential with an obvious decrease trend of carbon emission intensity from 0.7921 tCO2/MWh to 0.5544 tCO2/MWh. The model could effectively provide reasonable urban water system management strategies under different water allocation demands and carbon emission challenges scenarios and deal with multiple uncertainties in decision-making process.

Manajemen Inovasi Mode Hybrid Menuju Sekolah Kejuruan Mandiri Energi

The issue of new and renewable energy sources in the future will increasingly have a very important role in meeting energy needs. The use of fossil fuels for conventional power plants over a long period of time will deplete petroleum resources. Renewable Energy (RE) is increasingly in demand worldwide due to environmental concerns. The new policy requires power grids to supply a certain percentage of their load with Renewable Energy Sources (RES). The aim of writing this article is to provide an innovative management model to accelerate towards energy independent schools based on renewable energy, hybrid wind and solar energy mode. The method used in this study is a qualitative approach with document study as a data source and descriptive analysis methods. This article discusses the management model in controlling the Hybrid system towards efficiency of system input and output. In addition, there is a discussion about the school community regarding energy sources and its application in schools in protecting the environment. This study found that the renewable energy management system model using a combination of HRES technology using Homer and GA, GA-based optimization is more cost-effective than Homer with a COE of at least 0.163 $/kWh and 0% unmet load. This GA based system has more PV penetration and less co2 emissions than Homer. HRES optimization is mostly achieved using artificial methods or commercial software, the artificial methods used are based on fuzzy. This study also recommends the Home PRO and Retscreen control systems as the most widely used commercial software in optimization and MPPT as the most widely used control method to ensure stability, protection and power balance of the system. This method is often used based on practical optimization, neural networks and fuzzy logic. Artificial methods are the most widely used methods in optimization because of their higher efficiency, good accuracy, and fast convergence. The disadvantage of this method is that it requires a complicated processing program. High efficiency and speed of classical methods, accuracy. The hybrid method uses the advantages of each method by maximizing performance and minimizing optimization processing time.

Traditional Institutions and Economic Transformation of West Aceh Coastal Community in Indonesia: A Sustainable Energy Policy

This study develops energy for adapting customary institutional policies in creating food security for coastal communities. This development has not been on target under the village potential determined interactively by the government at the village level in Aceh. This study is designed using a qualitative approach and case study methods based on previous research which focuses on SDGs development achievements in improving the Keujruen Blang traditional institution as one of the traditional institutions that function as rice paddy management which can create food security for farming communities in the coastal region of Aceh. West Secondary and primary data collection techniques and in-depth interviews follow the objectives set. The results of the research show that the energy of SDGs development policies is based on traditional institutions and can be carried out through a model approach to implementing public policy with a bottom-up method that must be carried out by the village government and traditional institutions of Keujreun Blang in the West Aceh region with a model management system scheme, organizational development and bureaucratic processes directed, and must form methods of controlling conflict and analyzing the success and failure factors of the community in creating transformative development of the Keujreun Blang traditional institutional organization as a reference for the economic welfare of the farming community.

Elevating Organizational Competitiveness: Deconstruction of Information System Management Models and Concepts Using Machine Learning

This article discusses the role of machine learning in addressing the challenges of Information System (IS) management in today's business environment. It highlights the importance of data analytics, predictive maintenance, and security threat identification in overcoming the complexity of IS management. The article presents a custom framework that modifies paradigms for IS management, including data collection, continuous monitoring, machine learning model selection, and seamless integration. This approach is proven effective in solving problems and boosting competitiveness. The article provides risk mitigation techniques, realistic implementation methodologies, and case studies to help organizations embrace this innovative journey. The article concludes by highlighting the importance of implementing this novel paradigm as a necessary first step towards a data-driven, globally competitive future

Design and Manufacture Ballast Management System Model for Reduce Ship Rolling Motion

The safety of maritime transportation is a critical aspect that must be addressed to ensure the well-being of ships and their crew. Frequent ship accidents highlight the need for improvements in the maritime transportation system. One of the causes of ship accidents is ship instability, leading to a loss of balance and even sinking. Ship stability is influenced by both internal and external factors, including human negligence in observing and addressing ship instability. This research aims to design and create a management ballast system model that can be operated automatically as a solution to reduce ship rolling motion. This system enables the ship to maintain balance using automatic side ballast tank management by utilizing two wing tanks on either side of the ship. The ballast management system will be equipped with an accurate ship roll angle detector, the Initial Measurement Unit sensor, a microcontroller, and a series of actuators, including relays as voltage control switches for the pump motor. This research involves simulation and testing/experiments at various angles, namely 5, 10, and 15 degrees. Simulations are conducted under conditions with and without the ballast management system, which is then confirmed through experiments under the same conditions. The expected outcome of this research is that the created ballast management system can be used to reduce ship rolling.

Waste LCA and the future

Life cycle assessment (LCA) models quantifying the environmental aspects of waste management have become an integral part of waste management decision-making over the last two decades and have provided ample knowledge on both environmental benefits and drawbacks in the way we handle waste. Waste management and LCA modelling of waste management systems will soon be challenged by profound changes necessary in our societies and sectors to meet sustainable development goals. Foreseen changes in energy, material, and nutrient provision will directly and indirectly affect waste management in terms of its operation and goals. This study reflects on anticipated changes in society and industrial sectors and how these changes may affect waste management and LCA modelling of waste management systems in terms of waste input, the modelling of technologies and systems and exchanges of energy, materials, and nutrients, as well as how it may affect impact assessment and the interpretation of results. The study provides practical recommendations for LCA modelling of future waste management systems, which will hopefully lead to robust assessments that can support decision-making in an evolving society subject to great changes.

Research on prediction model of electric vehicle thermal management system based on particle swarm optimization- Back propagation neural network

The variation of temperature in various components of the Electric Vehicle Thermal Management (EVTM) system is the main factor affecting energy consumption. A good temperature prediction method is a prerequisite for optimizing energy strategies. The temperature variation of each component in the thermal management system is influenced by various factors, such as ambient temperature, vehicle speed, and air conditioning compressor speed. Therefore, this paper proposes a temperature prediction method based on Particle Swarm Optimization (PSO) and Back propagation Neural Network (BP). The PSO-BP method is used to update the weights and thresholds of the neural network. Real-time data collected from road experiments are used to ensure the accuracy of the influencing factors. Simulation results show that compared to the BP neural network, the proposed PSO-BP prediction method reduces the prediction errors by 66%, 75%, and 25% respectively.

Improving Service Delay in Smart Parking System in Smart Cities with 5G

Rapid urbanization and population growth leads to substantial increase in vehicular traffic while reducing empty spaces. This necessitates an enhanced parking systems to efficiently address the parking space management. The smart city and Internet of Things (IoT) holds a very high potential to solve this problem. However, the data traffic generation at the edge is increasing rapidly. Tremendous growth in IoT is putting a high congestion on cloud services. To ease up the congestion issue, we have proposed an efficient fog-based communication model for the smart city parking management. In this work, we have proposed a parking system management model based on 5G with low latency and green communication. Our model reduces congestion at the cloud and enable faster processing by addressing the parking system locally. Furthermore, our model finds out the nearby parking without putting additional load to the cloud. Simulation result shows the performance efficiency of the proposed model in terms of response time, average cost and service delay.

Towards the Model of Learning Management System for Elementary and Secondary Education

This study aims to evaluate teachers' perceptions of the platform X as the Learning Management System (LMS) that is used during and after the Covid-19 pandemic. The Platform X is claimed as a better platform than other LMS because it becomes a solution for many schools in terms of easy implementation, integration, and response to the needs of the students as digital natives. Using the Technology Acceptance Model (TAM), the research evaluates the perception of the 110 teachers in some provinces in Indonesia regarding the usefulness (perceived usefulness), and the ease of use of the LMS. The researchers use the quantitative and qualitative (mixed) method in the design of the research. The researchers surveyed the self-efficacy (the mastery of the LMS) and the features of the LMS to see the teachers’ perceived usefulness. The researchers also surveyed the quality of the system and the quality of the service to evaluate the ease of use of the LMS. The interview with the 4 respondents is conducted to clarify and complete some responses in the survey. The result of the study said that the teachers have a good perception regarding the usefulness and ease of use of the LMS. The result stresses the easy implementation of the LMS, the integration of the application, and the ability of the LMS to respond to the needs of the students as digital natives.

Type-2 fuzzy chance-constrained linear fractional programming model for a water resource management system: A case study of Taiyuan city, China

Abstract Uncertainties arising from extreme climate events and human activities pose a challenge to the efficient allocation of water resources. In this study, a type-2 fuzzy chance-constrained linear fractional programming (T2F-CCLFP) is developed to support the water resource management system under uncertainty by incorporating type-2 fuzzy sets, chance-constrained programming, and fractional programming into a comprehensive multi-objective optimization framework. The model enables the trade-off between economic, social, and environmental sustainability and provides water supply solutions associated with different levels of fuzzy uncertainty and risk of violating constraints. The T2F-CCLFP model is applied to Taiyuan, Shanxi Province, China, to support its water resource management. Results reveal that: (i) the industrial structure is transitioning toward diverse industries from energy and heavy industry dominance; (ii) external water transfer will be the major water-supply sources for the city in the future, accounting for 55 and 50% of the total water supply in 2025 and 2030, respectively; (iii) the water-supply security of the city is enhanced by provoking the utilization of reclaimed water (the annual growth rate is 13.9%). The results are helpful for managers in adjusting the current industry structure, enhancing water supply security, and contributing to the sustainable development of socio-economic and water systems.

IRRIGATION SYSTEM REFORM IN GEORGIA: A BRIEF LEGAL AND ECONOMIC ANALYSIS

Effective irrigation and drainage systems have always been the most significant components of the sustainable development of Georgian agriculture. Almost half a million hectares of agricultural land is irrigated by irrigation systems in Georgia. The increase of reclamation areas is the basis for the growth of agricultural products, which, in turn, is a prerequisite for Georgia's position restoration as an exporting country. Taking into account that one of the main tasks of the country is the rehabilitation, modernization, raising of the technical level, and the technological and organizational perfection of its effective functioning in order to increase the fertility and yield of the soil, the development of the law of Georgia on water user organizations is on the agenda. That is the first attempt to legally regulate the land artificial irrigation issues, which will contribute to overcoming the three main challenges in the irrigation system: (1) perfect operation of the irrigation system and supply of irrigation water to users; (2) maintaining systems in good condition and (3) increasing revenues to carry out the above two activities. The paper highlights the challenges of the reclamation system of Georgia. The possibilities of implementing a new model of irrigation system management are analyzed. The legal and economic aspects of the ongoing reforms in the irrigation sector are discussed. Establishing an affordable, reliable, stable irrigation system in Georgia will help strengthen the agro-sector and the country's economy as a whole.

Retracted: Artificial Intelligence Technology Based on Deep Learning in Building Construction Management System Modeling

Retracted: Artificial Intelligence Technology Based on Deep Learning in Building Construction Management System Modeling

Process Approach in Determining the Accounting Model and Quality Cost Analysis

Every year the requirements of consumers to the quality of products are steadily increasing and expanding. A company seeking to strengthen its position in a competitive market must constantly invest in quality. To determine the volume of investments, making strategic decisions, complete and reliable information on the costs of quality is required. The backbone of any organization is the business process, so the quality cost model should reflect the total costs of each process, not randomly selected quality costs. The process approach in the classification of quality costs allows raising hidden costs to the surface, which makes it possible to evaluate and optimize them. Since not all quality costs are obvious, this makes them difficult to accurately measure and quantify. There are also many areas where quality assurance activities and processes overlap. To determine the classification of quality costs based on a process approach, the article uses a typical process model of a quality management system for an automotive enterprise and an optimal quality model, also known as the Prevention-Assessment-Failure (PAF) model. This classification in the future will allow you to analyze and manage quality costs, and will also become a source of necessary information for making strategic decisions. Thus, with the help of this classification of costs, it is possible to achieve a balance between meeting the quality requirements of consumers and the costs incurred for this purpose. Also, the classification of quality costs presented in the article makes it possible to evaluate the effectiveness of measures aimed at improving quality, and, in general, the effectiveness of the quality management system implemented at the enterprise.