Resource Management System Research Articles

Intelligent wireless resource management in industrial camera systems: Reinforcement Learning-based AI-extension for efficient network utilization

In this paper, we present an innovative method for replacing wired communication within an operational agile production cell with wireless communication, using a minimal number of access points. Our approach utilizes Reinforcement Learning (RL) to optimize the layout and minimize the required number of access points. We introduce an Artificial Intelligence (AI) agent that facilitates cooperative interaction between cameras and access points, optimizing camera stream utilization and radio coverage. This solution benefits from the recent standardization of The fifth generation of mobile communications (5G) Network Resource Management (NRM) features of the User Equipment (UE) attached to the cameras. To accommodate the dynamic nature of the production cell, our optimization algorithms run during cell operation, necessitating extended training times.Our contributions extend beyond the state-of-the-art by offering a Digital Twin (DT) environment equipped with physics and radio propagation capabilities, fast raytracing for radio propagation modeling, curriculum-learning-based reinforcement learning, and a Physical Twin (PT) of the radio-connected camera with self-adjusting scene setup capabilities. This comprehensive proposal combines the efficiency of 5G radio utilization with precise modeling and high-resolution simulations, while also significantly improving training speed.In the Agile Robotics for Industrial Automation Competition (ARIAC) 2020 environment, our methods showed compelling results, with curriculum learning achieving a remarkable 3x speed-up compared to non-curriculum approaches. We also demonstrated that high Quality of Service (QoS) demands can be reduced to just 2% of total time while maintaining consistent productivity Key Performance Indicators (KPIs). Furthermore, we explored the integration of these methods into Internet of Things (IoT) devices with limited performance capabilities. In conclusion, our approach offers significant benefits and savings for IoT devices, networks, edge clouds, and industry players.

Resource management system database maintenance in cloud computing

The Resource Management System (RMS) is a comprehensive solution designed to optimize resource allocation, enhance project efficiency, and streamline customer interactions within a dynamic business environment. The system encompasses four key components: projects, resources, customers, and business units. It offers a range of functionalities including create, update, retrieve, and delete operations to facilitate seamless operations and data management. The RMS is built using Spring Boot (Java) for the backend, providing a robust and scalable foundation. The front end is developed using React, ensuring a modern and user-friendly interface. Data is managed in a MySQL database, offering reliability and data integrity. Communication between frontend and backend is achieved through RESTful APIs. Resource Management system typically manage and allocate non-human resources and as well human resources throughout an organization, However, if we choose to pursue human resources management, we will recruit, hire, train, manage employees and staff which is also a variation of resources. It provides comprehensive solution designed to optimize resource allocation, enhance project efficiency, and streamline customer interactions within a dynamic business environment.

The role of information technology (IT) performance in the relationship between high-performance work systems and competitive advantage

Human resources that are of high quality create a competitive advantage for companies, thus Human Resource Management (HRM) and High-Performance Work Systems (HPWS) that are good become key success factors that need to be considered by every company. This study aims to investigate the influence of Human Resource Management (HRM) and High-Performance Work Systems (HPWS) on Information Technology (IT) Performance and Competitive Advantage of a company. The method used in this study is a quantitative approach with a questionnaire as the data collection method. The research sample consisted of 191 supervisors, managers, and executives of manufacturing companies located in Medan, Indonesia. Data analysis was conducted using SmartPLS 4.0 software. The results showed that Human Resource Management significantly affects IT Performance but does not directly affect Competitive Advantage. Meanwhile, HPWS Capability does not affect IT Performance but significantly affects Competitive Advantage. IT Performance significantly affects Competitive Advantage. IT Performance also mediates the relationship between Human Resource Management and Competitive Advantage. However, it is not significant in mediating the relationship between HPWS Capability and Competitive Advantage. These findings underscore that Human Resource Management (HRM) and High-Performance Work Systems (HPWS) play pivotal roles in shaping Information Technology (IT) performance and competitive advantage within companies, thus impacting the overall success and sustainability of companies.

ПІДХОДИ ДО РЕАЛІЗАЦІЇ ЦИФРОВОЇ ТРАНСФОРМАЦІЇ БІЗНЕС-ПРОЦЕСІВ ПІДПРИЄМСТВА: УПРАВЛІНСЬКИЙ АСПЕКТ

The article is devoted to the study of approaches to managing the digital transformation of business entities. It presents differences in the interpretation of the essence of the concepts of digitalization, digitization, and digital transformation. Three main areas of the enterprise affected by digital transformation have been identified: work with clients, operational business processes, and business models of the enterprise. Digitalization of enterprise business processes will influence changes in value formation and structural changes, and will also depend on them. It is substantiated that the level of use of digital technologies will be greatly influenced by the financial capabilities of the enterprise. An algorithm for the digital transformation of an enterprise has been developed, which makes it possible to choose priority areas for optimizing business processes through varying degrees of digitalization. This algorithm provides a preparatory stage at which it is recommended to carry out a detailed diagnosis of the external environment and assess the degree of penetration of digital technologies into the industry in which the activity is carried out. It provides for diagnostics of the enterprise taking into account available resources and identification of business processes that require innovative changes and solutions. The developed algorithm provides for partial optimization of individual business processes (installation of ERP-, CRM-, HRM- and other resource management systems, document management, logistics, etc.) and significant changes in several business processes using AI, BigData, IoT, cloud technologies, etc. The algorithm ends with the implementation stage, at which the necessary software and technological solutions are implemented. Transformation of operational processes through automation will provide economies of scale and increase productivity. The elements of digitalization of business processes of the enterprise are characterized. Three variable blocks in the transformation of business models are considered: digital modifications of individual processes, the introduction of new digital business models, and digital globalization. Conclusions about the main advantages of enterprises that have carried out digital transformation are drawn.

Modular toolsets for integrating HPC clusters in experiment control systems

New particle/nuclear physics experiments require a massive amount of computing power that is only achieved by using high performance clusters directly connected to the data acquisition systems and integrated into the online systems of the experiments. However, integrating an HPC cluster into the online system of an experiment means: Managing and synchronizing thousands of processes that handle the huge throughput. In this work, modular components that can be used to build and integrate such a HPC cluster in the experiment control systems (ECS) will be introduced. The Online Device Control library (ODC) [1] in combination with the Dynamic Deployment System (DDS) [2, 3] and FairMQ [4] message queuing library offers a sustainable solution for integrating HPC cluster controls into an ECS. DDS as part of the ALFA framework [5] is a toolset that automates and significantly simplifies a dynamic deployment of user-defined processes and their dependencies on any resource management system (RMS) using a given process graph (topology). ODC, in this architecture, is the tool to control and communicate with a topology of FairMQ processes using DDS. ODC is designed to act as a broker between a high level experiment control system and a low level task management system e.g.: DDS. In this work the architecture of both DDS and ODC will be discussed, as well as the design decisions taken based on the experience gained of using these tools in production by the ALICE experiment at CERN to deploy and control thousands of processes (tasks) on the Event Processing Nodes cluster (EPN) during Run3 as a part of the ALICE O2 software ecosystem [6].

Research on Human Resource Management Optimization and Decision Support System Construction Based on Electric Power Enterprise Strategy

Abstract At the present stage, the development of electric power enterprises needs to update the concept of human resource management by fully combining it with their actual situation and constructing a systematic human resource management model so as to occupy a favorable position in the market competition. This paper brings the classification rule mining algorithm based on the ant colony algorithm into human resource planning decision-making, adds an adaptive mechanism to the ant colony algorithm, updates the algorithm strategy, and improves the quality of algorithmic decision rules. Establish a fuzzy comprehensive judgment model for performance appraisal and salary decision-making in electric power enterprises and design a comprehensive system of dynamic decision support for human resource management in electric power enterprises. Analyze the effect of α, β and ρ values on the performance of the adaptive ant colony algorithm and determine the utility of the classification rule mining algorithm based on the adaptive ant colony algorithm for human resources planning and decision-making. Combine the evaluation level and scoring factors of employees in electric power enterprises to obtain the employee performance appraisal rankings and determine their remuneration packages. The practical benefits of the HRM dynamic decision support system designed in this paper are examined by a system reliability test. The reliability of the human resource management decision-making system designed in this paper is maintained at 0.93~0.97, and the decision-making reliability of traditional system 1 and traditional system 2 is maintained at 0.90~0.92 and 0.90~0.91, respectively. The decision-making system for human resource management in electric power enterprises constructed in this paper is more advantageous for practical operation.

Deep Q-Learning-Based Resource Management in IRS-Assisted VLC Systems

Deep Q-Learning-Based Resource Management in IRS-Assisted VLC Systems

Research on Development of Higher Vocational Education Resources and Construction of Management System under Learning Migration Theory

Abstract This paper discusses how to construct a higher vocational education resource development and management system under the framework of learning transfer theory in order to improve the utilization efficiency of educational resources and the quality of education. This study explores how to effectively develop and manage higher vocational education resources under the guidance of learning transfer theory. This paper constructs a new resource management framework for higher vocational education by adopting the statistical and geometric migration criterion. The study results show that the utilization efficiency of higher vocational education resources is significantly improved through the transfer learning algorithm, for example, the matching degree of learning resources is increased by 30% and the teaching effect is enhanced by 20% after applying the transfer learning method. In addition, student learning effectiveness increased by 25% by implementing an improved learning migration framework. The study’s conclusion points out that the development and management of higher vocational education resources can be effectively optimized through the rational use of transfer learning theory, thus improving the quality and efficiency of teaching.

Digital Human Resource Management in Maritime Enterprises

This study investigates the adoption of Digital Human Resource Management (DHRM) systems in the maritime industry of the Riau Islands (Kepri), Indonesia. Through qualitative research involving interviews, observations, and literature reviews with HR leaders from marine tourism, fisheries, and port logistics, the study identifies eight key areas of DHRM adoption: Digital Recruitment, Digital Performance Management, Digital Training and Development, Digital Communication, Employee Data Management, Digital Employee Engagement, Digital Diversity and Inclusion, and Adoption of New Technology. The findings reveal significant opportunities for enhancing efficiency, improving objective performance tracking, and streamlining recruitment processes. However, challenges persist, including limited human resources, reliance on centralized decision-making, inadequate technological infrastructure, and a predominant focus on seagoing workforce development. These barriers impede the full implementation of DHRM. Despite these challenges, the research underscores DHRM’s potential to foster digital innovation and gain a competitive edge within the maritime sector. In conclusion, addressing these challenges through targeted strategies will be essential for maximizing the benefits of DHRM and advancing the digital transformation of human resource practices in the industry

OPTIMISING THE USE OF IRRIGATED LANDS IN KAZAKHSTAN: SYSTEM ANALYSIS AND RESOURCE MANAGEMENT

This article explores the challenges and opportunities in optimizing the use of irrigated lands in Kazakhstan, focusing on system analysis and resource management. The research purpose is to identify strategic improvements in irrigation practices and regional water governance, while aiming to enhance water resource management efficiency and sustainability in agriculture. The main directions of the study involve analyzing Kazakhstan's reliance on external water sources, infrastructural inefficiencies, and region-specific strategies for sustainable agricultural practices. Methodologically, the research relies on regional case studies, national statistical data, and quantitative analyses, including correlations and descriptive statistics. It also applies frameworks like Integrated Water Resources Management, Socio-Ecological Systems, Water-Energy-Food Nexus, and Participatory Water Management. The research results highlight Kazakhstan's vulnerability due to its significant dependence on external water sources, accounting for 46% of its water supply, and inefficiencies in its aging irrigation infrastructure. The practical value of this research is in offering comprehensive, actionable recommendations to policymakers, agricultural stakeholders, and local communities for improving infrastructure, adopting efficient irrigation techniques, and fostering international collaboration. The research novelty lies in its interdisciplinary application of multiple strategic frameworks to develop tailored strategies addressing the unique challenges across Kazakhstan's economic districts, balancing agricultural productivity with sustainable water management practices.

Smart Animal Repelling Device: Utilizing IoT and AI for Effective Anti-Adaptive Harmful Animal Deterrence

The coexistence of human populations with wildlife often leads to conflicts in which harmful animals cause damage to crops and property and threaten human welfare. Certain limitations influence the effectiveness and environmental impacts of traditional methods used to repel animals. The present research outlines a growth of solutions that utilize the Internet of Things and machine learning techniques to address this issue. This study centers on a Smart Animal Repelling Device (SARD) that seeks to safeguard crops from ungulate assaults, substantially reducing production expenditures. This is achieved by developing virtual fences that use Artificial Intelligence (AI) and ultrasonic emission. This study introduces a comprehensive distributed system for resource management in Edge or Fog settings. The SARD framework leverages the principle of containerization and utilizes Docker containers to execute Internet of Things (IoT) applications in microservices. The software system inside the suggested structure can include various IoT applications and resources and power management strategies for Edge and fog computing systems. The experimental findings demonstrate that the intelligent animal-repellent system effectively uses animal detection on power-efficient computational methods. This implementation ensures the system maintains high mean average accuracy (93.25%) while simultaneously meeting real-time demands for anti-adaptive harmful animal deterrence.

A Review on Mineralization on Sustainable Dryland Agriculture

Sustainable dryland agricultural production relies on efficient and integrated systems for resource management, including irrigation and dryland farming, with water and soil conservation and efficient utilization of nutrients. The global annual production of crop-based food exceeds 200 million tons, however, about half is produced from irrigated and flood-prone areas and about a quarter of total crop production is fed to livestock. Due to increased water requirements for irrigation and other purposes, the water stress will grow in the next decades. In some regions, climate change threatens food production and will trigger major shifts in both the water and the nutrient budgets. Therefore, it is important to assess the potential of adaptation options in order to mitigate impacts on food security.

СУТНІСТЬ І ВИДИ ІТ У ПРОМИСЛОВОСТІ

The relevance of conducting scientific research dedicated to the development of Information Technology (IT) management in industry is determined by the direct impacts that this field exerts on the global economy, enterprise productivity, competitiveness of national industries, and overall societal quality of life. The contemporary landscape is rich with compelling reasons for conducting scientific research in the field of IT management in industry. Taking into account the analysis of the role and classification of IT, there are grounds to assert that the development of IT management is a key factor in the modern industrial environment. IT not only allows enterprises to increase productivity and reduce costs but also makes them more competitive and ready for market challenges. It has been proven that IT in industry differs from other sectors in its focus on automation and control, the use of the Internet of Things for data collection, active utilization of analytics and artificial intelligence for decision-making, integration of production processes, and supply chain management. These substantiated characteristics help enterprises achieve greater efficiency and resilience. Additionally, IT in industry contributes to the realization of the concept of sustainable development, where enterprises can more effectively utilize resources and reduce environmental impact. This is an important aspect in the context of modern requirements for sustainability and environmental responsibility. It is argued that IT in industry can facilitate the transition to a circular economy, where enterprises minimize waste and maximize resource reuse. This can be achieved through the implementation of resource management systems and material recycling. Overall, IT in industry plays a significant role in achieving efficiency, sustainability, and competitiveness for enterprises in the modern world. The provided classification helps managers understand which specific IT solutions can be beneficial for particular tasks and contributes to better resource management and strategic decision-making in industrial enterprises.

Carbon and financial performance nexus of the heavily polluting companies in the context of resource management during COVID-19 period

The depletion of fossil fuels and the new EU climate policy goals to achieve a zero-emission economy after 2050 encourage highly polluting companies to increase the efficiency of energy conversion from non-renewable energy sources, develop renewable energy sources and implement resource management systems in production. Studying the relationship between environmental performance and financial performance of firms is particularly important in times of the Covid-19 pandemic, as companies' decisions to limit or continue green investments and low-emission transformation may impact access to external financing sources. The aim of this study is to identify the shape of the relationship between the carbon and financial results of heavily polluting enterprises in the context of resource management and to assess the impact of the Covid-19 pandemic on the considered relationship. For a panel sample of Polish enterprises representing highly polluting industries with manufacturing plants covered by the EU ETS in 2009–2021, a third-degree polynomial describing this relationship was estimated. A U-shaped relationship was identified between carbon emission intensity and return on sales and return on assets, which can be explained by the ‘too-little-of-a-good-thing’ effect. Increase in share of renewable energy in the production structure significantly reduces firms’ profitability, which can be explained by the relatively high costs associated with the development of renewable energy and the changing legal regulations regarding this type of investment. It has been shown that companies with high carbon emission intensity achieved lower sales profits and return on assets compared to companies with lower carbon intensity during the Covid-19 pandemic. The lower scale of allocation of free emission allowances compared to previous years, combined with the increase in emission allowance prices under the influence of shocks generated by the pandemic, had a negative impact on the profitability of heavily polluting companies. The modelling results provide important information to managers who, based on them, can make more informed decisions regarding the use of natural resources in production and the involvement of enterprises in investments aimed at the use of cleaner production technologies and the development of renewable energy.

Investigating electronic human resource management systems, sustainable innovation, and organizational agility on sustainable competitive advantage in the manufacturing industries

Investigating electronic human resource management systems, sustainable innovation, and organizational agility on sustainable competitive advantage in the manufacturing industries

To study the development path of museum intangible cultural heritage tourism industry in the era of digital economy

Abstract The museum incorporates historical resources, stores them in a systematic classification, and then presents them as objects for viewing and learning training. Intangible cultural heritage is the aesthetic crystallization of the wisdom and aesthetics of ancient Chinese people. Combining museums and intangible cultural heritage culture and developing the intangible cultural heritage cultural tourism industry of museums can fully utilize the advantages of museums in terms of location and dissemination, as well as achieve high-quality promotion of intangible cultural heritage culture. The digital era has brought new changes and numerous challenges to the development environment and spatial design methods of the intangible cultural heritage tourism industry in museums. This paper builds a museum intangible cultural heritage cultural tourism platform based on digital tour interaction technology. It considers the advantages of the development of the cultural tourism industry from the “museum + intangible cultural heritage” model, establishes a digital resource management system for museums, digital talent training, and management mode, and digital branding in light of the current development status and challenges of the museum intangible cultural heritage cultural tourism industry. Additionally, we will create a digital resource management system for museums, a digital talent training and management model, and a digital brand marketing system to boost the industry’s ecological development.

THE THEORETICAL ANALYSIS OF APPROACHES TO FORMATION OF THE NATIONAL SYSTEM OF AGRICULTURAL ENTERPRISE PERSONNEL MANAGEMENT

This article attempts to consider a modern approach to a comprehensive assessment of the efficiency of the personnel management system at domestic enterprises. The article analyses the main target ways of development of personnel management, taking into account the military realities in Ukraine. An assessment of modern and perspective approaches to the formation of a personnel management system for Ukrainian enterprises has been carried out. Examples of perspective directions for choosing priorities to improve the effectiveness of the national system of personnel management are provided. An effective human resource management system enables managers to achieve the goals of the enterprise, to introduce innovative technologies, which will lead to an increase in financial results and competitiveness of the enterprise. The purpose of the scientific research is to study the issues related to the formation of an effective human resources management system. The information base of the study includes monographs, Internet resources, articles and textbooks by foreign and domestic authors. The article summarises the theoretical foundations of existence and characteristics of human resource management systems and analyses the concept of ‘effective human resource management system’. The issues of effective human resources management at enterprises are discussed and the trends in the development of world management are taken into account. The theoretical aspects of formation of efficient human resource management systems at enterprises are studied. The methodology for evaluating the effectiveness of human resource management systems based on the selection of efficiency criteria for the economic, social and organisational subsystems of a complex system is described.

Unleashing Organisational Potential: Exploring the Transformative Power of Cutting-Edge HR Analytics - A Systematic Review

Due to globalization, organizations have integrated human resource (HR) analytics into their operations. The study employs Paul’s Theory-Context-Construct-Methodology (TCCM) theory, context, construct, and methods framework and integrates data from Scopus and Web of Science databases, with 64 relevant publications after filtering articles. Findings comprise theories, contexts, industries, participants, constructs, research techniques, and annual publication trends. The identified theories include the resource-based view (RBV), technology environment organization (TOE) paradigm, diffusion of innovation, social exchange theory, and more. India leads in contextual studies, but manufacturing and service industries dominate. HR Professionals are the major population, and performance expectancy is a commonly studied construct. The majority of studies use the questionnaire method to conduct studies on HR Analytics. The study investigates the cultural disparities, longitudinal surveys, the influence of artificial intelligence (AI) on human resource functions, and challenges encountered by machine learning technology. The study emphasizes human resource management system (HRMS) models, comparative analytics, leadership tactics, and the impact of HR Analytics during crises. Leading journals include "The Journal of Organizational Effectiveness" and “The International Journal of Organizational Analysis," The study addresses gaps in the literature groups into four frameworks and provides a critical analysis of identified research gaps thereby offering insights for HR practitioners, experts, and stakeholders in HR Analytics.

Study on the Role of Public Sector Human Resource Management in Educational Management Reforms

Abstract The principles and methods of human resource management have been introduced into the field of education for some time, but the analysis of the current state of research, specifically on educational management, is still insufficient. The first part of this paper analyzes the measures that are related to human resource management in education management reform in each sector and further investigates the factor analysis method in the public sector human resource management system. By constructing the factor analysis model and factor calculation method, we can provide an algorithmic basis for studying the role of public sector human resource management in education management reform. The article utilizes the factor analysis method to conduct an empirical study by using the educational resources of different schools in 11 cities of Province A as test objects. According to the study, the first principal component has seven-factor loadings that are higher than 0.72, which indicates that all seven factors have a positive impact on the allocation efficiency of higher vocational education. The second principal component has four-factor loadings greater than 0.80, suggesting that all four factors have a positive effect on the allocation efficiency output of higher vocational education. From the sample data of the school education resource allocation status of each city, it can be obtained that the school education resource allocation status of city A is the most favorable, with the highest overall score of 43,153.1, followed by city B and city D, with 25,431.9 and 12,136.4, respectively. This indicates that the education resource allocation effect of these three cities is better and belongs to the upstream level in province Z.

Conceptualizing a Research Model for Analysing the Factors that Influence the Implementation of Cloud Computing-Based Human Resource Management System (CC-HRMS)

Conceptualizing a Research Model for Analysing the Factors that Influence the Implementation of Cloud Computing-Based Human Resource Management System (CC-HRMS)