Resource Management Method Research Articles

Enhancing Streamflow Modeling by Integrating GRACE Data and Shared Socio-Economic Pathways (SSPs) with SWAT in Hongshui River Basin, China

Climatic variability and the quantification of climate change impacts on hydrological parameters are persistently uncertain. Remote sensing aids valuable information to streamflow estimations and hydrological parameter projections. However, few studies have been implemented using remote sensing and CMIP6 data embedded with hydrological modeling. This research studied how changing climate influences the hydro-climatic parameters based on the earth system models that participated in the sixth phase of the Coupled Model Intercomparison Project (CMIP6). GRACE evapotranspiration data were forced into the Soil and Water Assessment Tool (SWAT) to project hydrologic responses to future climatic conditions in the Hongshui River basin (HRB) model. A novel approach based on climate elasticity was utilized to determine the extent to which climate variability affects stream flow. CMIP6 SSPs (shared socio-economic pathways) for the second half of the 20th century (1960–2020) and 21st century (2021–2100) projected precipitation (5–16%) for the whole Hongshui River basin (HRB). The ensemble of GCMs projected an increase of 2 °C in mean temperature. The stream flow is projected to increase by 4.2% under SSP-1.26, 6.2% under SSP-2.45, 8.45% under SSP-3.70, and 9.5% under SSP-5.85, based on the average changes throughout the various long-term future scenarios. We used the climate elasticity method and found that climate change contributes 11% to streamflow variability in the Hongshui River basin (HRB). Despite the uncertainty in projected hydrological variables, most members of the modeling ensemble present encouraging findings for future methods of water resource management.

Tree Rings Record of Long-Term Atmospheric Hg Pollution in the Monte Amiata Mining District (Central Italy): Lessons from the Past for a Better Future

Trees may represent useful long-term monitors of historical trends of atmospheric pollution due to the trace elements stored along the tree rings caused by modifications in the environment during a tree’s life. Chestnut (Castanea sativa Mill.) tree trunk sections were used to document the yearly evolution of atmospheric Hg in the world-class mining district of Monte Amiata (MAMD; Central Italy) and were exploited until 1982. An additional source of Hg emissions in the area have been the active geothermal power plants. A marked decrease (from >200 µg/kg to <100 µg/kg) in Hg contents in heartwood tree rings is recorded, likely because of mine closure; the average contents (tens of µg/kg) in recent years remain higher than in a reference area ~150 km away from the district (average 4.6 µg/kg). Chestnut barks, recording present-day Hg pollution, systematically show higher Hg concentrations than sapwood (up to 394 µg/kg in the mining area). This study shows that tree rings may be a good record of the atmospheric Hg changes in areas affected by mining activity and geothermal plants and can be used as a low-cost biomonitoring method for impact minimization and optimal resource and land management.

The Effect of Sustainable Human Resource Management Practices on Customer Satisfaction, Service Quality, and Institutional Performance in Hotel Businesses

The purpose of the current research seeks to explore the influence of sustainable Human Resource Management (HRM) practices on customer satisfaction, service quality, and institutional performance in inner-city hotel businesses. The information was gathered by studying Cypriot inner-city hotels. A quantitative method was used to gather data from HRM managers, staff, and patrons at every inner-city hotel under study. The questionnaires were specifically employed by the researchers. Based on the findings of this study, human resource management techniques have a substantial effect on customer satisfaction. The most important relationship was discovered between customer satisfaction and institutional performance, which is an important result. This finding has tremendous importance since it is the first time that it has been demonstrated in a study pertaining to the inner-city hotel business. Customer satisfaction is influenced by both HRM and service quality practices. Ultimately, this research supports the close association between HRM practices and hotel performance. Both human resource management methods and service quality practices have shown their impact on client happiness. Lastly, the research provides evidence for the close relationship between hotel performance and HRM practices.

ISPA: Exploiting Intra-SM Parallelism in GPUs via Fine-Grained Resource Management

Emerging GPUs have multiple Streaming Multiprocessors (SM), while each SM is comprised of CUDA Cores and Tensor Cores. While CUDA Cores do the general computation, Tensor Cores are designed to speed up matrix multiplication for deep learning applications. However, a GPU kernel often either uses CUDA Cores or Tensor Cores, leaving the other processing units idle. Although many prior research works have been proposed to co-locate kernels to improve GPU utilization, they cannot leverage the Intra-SM CUDA Core-Tensor Core Parallelism. Specifically, ISPA designs persistent and elastic block to solve the thread slot and shared memory contention between co-located kernels. ISPA also adopts the register allocation method to manage the register contention. These resource management methods are applicable for both white-box kernels and <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$cudnn$</tex-math></inline-formula> kernels. Experimental results on an Nvidia 2080Ti GPU show that ISPA improves the system-wide throughput by 15.3% for white-box workloads, and 7.1% for <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$cudnn$</tex-math></inline-formula> -based workloads compared with prior co-location work.

Hierarchical Cross-Domain Satellite Resource Management: An Intelligent Collaboration Perspective

The expansion of satellite applications induces the formation of the multi-domain satellite system (MDSS) containing multiple domains with specific applications such as earth resource remote sensing and the Internet of remote things. Resource management is pivotal in enhancing the scheduling capability of the MDSS. However, this is challenging since the dynamic buffer space and communication opportunity, as well as the uncertain data traffic, exacerbate the difficulty of matching satellite resources with data traffic. Moreover, the coexistence of resource competition and collaboration across domains aggravates the dilemma of cross-domain collaboration. In this paper, we propose a hierarchical cross-domain collaborative resource management framework that can flexibly allocate the mission data through local intra-domain and global cross-domain scheduling. Then, to match the uncertain demands of missions with dynamic and limited resources, we propose a multi-agent reinforcement learning-based resource management method to guide collaboration for multi-satellite data carry-forward in a domain. Further, considering resource competition and collaboration in MDSS, we propose a domain-satellite nested matching game data scheduling algorithm to achieve pair-wise stable collaboration of cross-domain satellites. The simulation results indicate that the proposed algorithm improves the amount of offloaded data by 64.4% and 12.7% compared to the non-collaborative and the non-cross-domain schemes, respectively.

Green Human Resource Management: Mapping the Research Trends for Sustainable and Agile Human Resources in SMEs

While individual SMEs may have a minor environmental footprint, their collective influence is characterized as significant. Through the dynamics of their employees, green human resource management can help SMEs reduce their environmental footprint. However, SMEs face difficulties in implementing such strategies and achieving sustainable business continuity. The current research aims to propose the theoretical framework of a business model that will help SMEs adjust to the new environment, address their sustainable goals and gaps in the field, and build a resilient, agile business ecosystem. To approach the research issue, we used the R-based Bibliometrix tool. Using the Scopus database, 368 papers were selected and analyzed as part of the study’s five steps. Bibliometric tools such as Biblioshiny, VOSviewer, and R Studio have been used to illustrate the findings. The study’s findings highlight a few different factors that will serve as the foundation for the proposed model. Green competencies, both natural and acquired, as well as the requirement to provide green motivation, are identified as critical for the development of the new business model. Furthermore, the combination of this set of factors contributes to the achievement of green organizational citizenship behavior, which is one of the most important factors in helping SMEs adopt green human resource management methods. Finally, all the above factors are under the wing of the principles of environmental management, which drive businesses to enhance and boost their environmental performance.

Proactive Self-Healing Approaches in Mobile Edge Computing: A Systematic Literature Review

The widespread use of technology has made communication technology an indispensable part of daily life. However, the present cloud infrastructure is insufficient to meet the industry’s growing demands, and multi-access edge computing (MEC) has emerged as a solution by providing real-time computation closer to the data source. Effective management of MEC is essential for providing high-quality services, and proactive self-healing is a promising approach that anticipates and executes remedial operations before faults occur. This paper aims to identify, evaluate, and synthesize studies related to proactive self-healing approaches in MEC environments. The authors conducted a systematic literature review (SLR) using four well-known digital libraries (IEEE Xplore, Web of Science, ProQuest, and Scopus) and one academic search engine (Google Scholar). The review retrieved 920 papers, and 116 primary studies were selected for in-depth analysis. The SLR results are categorized into edge resource management methods and self-healing methods and approaches in MEC. The paper highlights the challenges and open issues in MEC, such as offloading task decisions, resource allocation, and security issues, such as infrastructure and cyber attacks. Finally, the paper suggests future work based on the SLR findings.

Downscaling Simulation of Groundwater Storage in the Beijing, Tianjin, and Hebei Regions of China Based on GRACE Data

Gravity Recovery and Climate Experiment (GRACE)-derived groundwater storage anomalies (GWSA) have been used to highlight groundwater depletion in regional aquifer systems worldwide. However, the use of GRACE products in smaller areas is limited owing to the coarse spatial resolution of the data product. This study utilized a dynamic downscaling method to improve the GWSA resolution from 1° to 0.05° by constructing a groundwater storage numerical model in the Beijing, Tianjin, and Hebei regions of China (BTH). The results indicate that: (1) the GRACE-derived and calculated GWSA had a good match with an average root mean squared error (RMSE) of 2.61 cm equivalent water height (EWH) and an average Nash–Sutcliffe efficiency coefficient (NSE) of 0.84 for the calibration period. (2) The hydraulic gradient coefficient and specific yield had the highest sensitivity, and transmissivity had the lowest sensitivity; however, different forcing data had no obvious influence on the GWSA. (3) The downscaled results not only exhibited time series variations that were consistent with those of the GRACE-derived solutions but also revealed a finer spatial heterogeneity of the GWSA along with increasing correlation coefficients between the GRACE-derived GWSA and the in situ measurements of groundwater levels by 0.06 and reducing the RMSE by 8.85%. (4) The downscaled results reflected the spatiotemporal change characteristics of groundwater storage in different hydrogeological units and administrative regions well. This study demonstrates the potential applications of the proposed downscaling method for both regional and local groundwater resource management.

Data Interworking Model and Analysis for Harmonization of Smart Metering Protocols in IoT-Based AMI System

In the energy sector, since the adoption of remote device management for massive advanced metering infrastructure (AMI) devices and Internet of Things (IoT) technology using a representational state transfer (RESTful) architecture, a blurred boundary has been developed between traditional AMI and IoT. With respect to smart meters, the standard-based smart metering protocol, called the device language message specification (DLMS) protocol, still has a predominant role in the AMI industry. Thus, we aim to propose a novel data interworking model in this article that embraces the DLMS protocol in AMI using the most promising IoT protocol, the so-called lightweight machine-to-machine (LwM2M) protocol. We provide a 1:1 conversion model using the correlation of the two protocols with an analysis of the object modeling and resource management methods of both the LwM2M and DLMS protocols. The proposed model utilizes a complete RESTful architecture, which is the most beneficial in the LwM2M protocol. It improves the average packet transmission efficiency and packet delay on the plaintext and encrypted text (session establishment and authenticated encryption) by 52.9%p and 9.9%p, respectively, and by 11.86 ms for both cases, compared to the encapsulation method of the LwM2M protocol, KEPCO's current approach. This work provides the key idea to unify the protocol for the remote metering and device management of field devices into the LwM2M protocol, and it is expected that this work will improve the efficiency in the operation and management of KEPCO's AMI system.

Types and Forms of Fishermen Conflicts in the Utilization of Coastal Resources in Maros Regency, South Sulawesi Province

Maros Regency is an area that has potential coastal resources. The social interaction of fishing communities in the coastal regions of Maros Regency is relatively high in the effort to utilize fishery resources. This is marked by the various fishing gear used by fishers, so the phenomenon of fisherman conflict becomes a social process that also colours the social interactions of these fishing groups. Differences in resource utilization and management methods can trigger social conflicts between fishers involving other stakeholder components. This study aims to analyze the types and forms of conflicts in the use of coastal resources that occur in the coastal areas of Maros Regency, South Sulawesi Province. The methods used are observation, interviews and Focus Group Discussion (FGD) with qualitative data analysis to describe the types and forms of conflicts in the use of coastal resources, and quantitatively with spatial analysis methods using Geographic Information System (GIS) applications to analyze conflict locations. The results showed that the types of fishing conflicts in the Maros Regency’s coastal areas were agrarian conflicts, class conflicts, technological conflicts, and conflicts of perception. The forms of conflict in the use of natural resources (including fishery resources) are horizontal conflicts (traditional fishers and klitik net fishermen) with semi-modern fishermen (cantrang fishermen) and vertical conflicts (semi-modern fishermen and cantrang fishers) with the government ( Maros District Fisheries Service, Camat and Village Heads, both open (manifest) and closed (latent).

Multi-Agent Reinforcement Learning for Dynamic Resource Management in 6G in-X Subnetworks

The 6G network enables a subnetwork-wide evolution, resulting in a “network of subnetworks”. However, due to the dynamic mobility of wireless subnetworks, the data transmission of intra-subnetwork and inter-subnetwork will inevitably interfere with each other, which poses a great challenge to radio resource management. Moreover, most existing approaches require the instantaneous channel gain between subnetworks, which are usually difficult to be collected. To tackle these issues, in this paper we propose a novel effective intelligent radio resource management method using multi-agent deep reinforcement learning (MARL), which only needs the sum of received power, named received signal strength indicator (RSSI), on each channel instead of channel gains. However, to directly separate individual interference from RSSI is an almost impossible thing. To this end, we further propose a novel MARL architecture, named GA-Net, which integrates a hard attention layer to model the importance distribution of inter-subnetwork relationships based on RSSI and excludes the impact of unrelated subnetworks, and employs a graph attention network with a multi-head attention layer to exact the features and calculate their weights that will impact individual throughput. Experimental results prove that our proposed framework significantly outperforms both traditional and MARL-based methods in various aspects.

A Survey on Resource Management for 6G Heterogeneous Networks: Current Research, Future Trends, and Challenges

The sixth generation (6G) mobile communication system is expected to meet the different service needs of modern communication scenarios. Heterogeneous networks (HetNets) have received a lot of attention in recent years due to their potential as a novel structure for evolutionary networks. When compared to homogeneous networks, HetNets provide more potential for spatial spectrum reuse and higher quality of service (QoS). However, effective resource management (RM) solutions are essential to prevent interference and accomplish spectrum sharing due to mutual interference. This paper presents a comprehensive review of resource management in 6G HetNets. The study aims to give crucial background on HetNets to aid in the creation of more effective methods in this field of study. First, a detailed examination of recent work is presented in resource management aspects such as power allocation, user association, mode selection, and spectrum allocation. Second, we identify the most severe challenges associated with the current resource management methods and propose suitable solutions. Finally, several open issues and emerging areas of research are highlighted.

An intelligent resource management method in SDN based fog computing using reinforcement learning

An intelligent resource management method in SDN based fog computing using reinforcement learning

Особливості управління проєктними витратами

The article defines the features of project cost management, provides examples of the use of project cost management tools. It is substantiated that understanding the peculiarities of project cost management is extremely important for project managers. It is proved that the use of modern project cost management tools is an important component of successful project implementation and achievement of goals. It has been established that it is necessary to carefully plan, monitor, and control costs at different stages of the project using modern tools and methods of resource management, namely Lean Six Sigma, Total Cost Management, Activity-Based Costing, Cost-Benefit Analysis, Value Management, Target Costing, etc., as well as using modern project digitalization programs (Microsoft Project, GanttProject, Primavera P6, Asana, Trello, etc.) that can be used to manage project costs, which allows you to effectively control and monitor project costs. The article provides examples of mistakes that can lead to an incorrect estimate of the project cost, which can lead to budget overruns, delays in the project schedule, and failure to achieve project goals. The article establishes that the main mistakes in planning the project budget may include: insufficient research of the factors of influence and forecasting shortcomings may lead to an incorrect assessment of the total project costs (some factors may not be taken into account, such as changes in market prices, changes in exchange rates, cost of resources, inflation, failure to take into account possible changes in technology, other factors and risks, such as changes in the timing, scope of the project); insufficient attention to cost minimisation opportunities (possibly not taking into account cost savings opportunities, such as the use of more efficient technologies or reduced material costs); underestimation of difficulties and possible changes (insufficient resource capacity, team qualifications or difficulties in collecting data, not taking into account changes in the market or technology, resistance to change) and other factors. It is proved that the use of modern project cost management tools will increase the efficiency of cost management and achieve success in project implementation.

Human Resource Management as an Area of Changes in a Healthcare Institution.

The underlying objective of the paper was to investigate the areas that require changes in human resource management in healthcare institutions. The practical objective of the study was to formulate recommendations targeted at the management staff of a healthcare institution, which allow to increase the adaptability and development capacity of medical personnel with the use of appropriate instruments and methods of human resource management. The quantitative research was conducted among 652 patients using the services of primary health care clinics located in the Silesian province in Poland, in 2019. The share of women in the research sample was 61%, and men - 39%. 11% of the respondents were students, 27% - people of retirement age, and 62% were economically active. An anonymous survey questionnaire was used. Calculations were performed using Statistica software. Mann-Whitney U-test and correlation analysis using Gamma (Γ) coefficients were used. The results of the empirical research showed that the respondents positively assessed most of the examined elements (over 70% of positive opinions). Negative opinions did not exceed the error threshold and amounted up to 5%. The presented results allowed to conclude that the expectations and preferences of patients should be constantly monitored, have an impact on the management of medical personnel and imply introducing changes in the weakest areas. The conducted research made it possible to identify the needs and expectations of patients and to develop possible solutions to improve human resource management in healthcare entities. In order to improve the operating conditions of the clinic, managers should constantly monitor patient satisfaction and, if necessary, introduce changes to raise service standards. This will allow early detection of shortcomings and the introduction of necessary changes in the clinic.

Human Resource Management Model of Large Companies Based on Mathematical Statistics Equations

Abstract The article applies mathematical statistics to the dynamic analysis of the demand for talents in large companies. Prediction of the overall demand for talents through the use of deep learning models. We use the theory of diminishing marginal utility to solve the degree of enterprise human resource investment under each index. Based on the analysis of traditional human resource management methods, this paper uses the three-dimensional fuzzy model to construct a new three-dimensional fuzzy model of human resource management model. The research found that the algorithm proposed in this paper can improve the quality of data training and improve the matching of people and posts.

APPRAISAL PERFORMANCE AND TRAINING OF HRM PRACTICES ON EMPLOYEES’ TURNOVER INTENTION AND ORGANIZATIONAL LOYALTY: THE MEDIATING ROLE OF PSYCHOLOGICAL EMPOWERMENT

It is widely accepted that HRM techniques might have a comparative advantage when organizational commitment is taken into consideration. On the other hand, turnover intention has become a trend and is increasing in today’s work engagement. The primary objective of this study is to establish a relationship between human resource management techniques and organizational loyalty and their effect on turnover intention Data of 330 employees from selected different industries were collected from Rahim yar khan Pakistan. The findings indicate a correlation between Performance Appraisal and Training and Development (HRM practices) and organizational loyalty, which contributes to an inverse relationship between employee turnover intention and performance appraisal. Increased employee loyalty will boost organizational effectiveness through the retention of competent and experienced personnel, hence minimizing turnover intentions. As such, this study contributes to the body of information regarding the impact of human resource management methods on organizational loyalty and intention to leave. The data results might be used as a reference or guideline for future related studies.

PERSONNEL DEVELOPMENT MANAGEMENT

The article considers the current goals of staff development, areas of staff development, some principles of staff development, namely: individuality, interest of the company and employee in career development, material incentives, moral incentives. compulsory professional growth, social and psychological comfort and objectivity. The process of personnel development management has many aspects, as evidenced by the large number of points of view and different management methods. they include: professional growth, continuing education in the workplace, staff development, renewal of human resource management methods. talent management and other combinations of these aspects. Particular attention is paid to staff development strategies. After all, the need to train staff who are able to qualitatively solve a wide range of problems, necessitates a strategy of staff development. Situational and system strategies, as well as their components, as a set of actions and a sequence of decisions to assess, analyze and develop the necessary system of influence on staff to ensure the achievement of the necessary overall competitive potential to implement the chosen development strategy. Directive, interactive and personal methods of personnel development are also highlighted. It is noted that the basis of directive methods is the interaction of the student with the mentor, instructor, teacher, coach. There are such methods as: lectures, seminars, mentoring, instruction, training, secondment. In turn, interactive methods are seen as the participation of staff in training, in which a large role is given to modern technological capabilities. Interactive methods are presented: adaptation of personnel in the organization, distance learning, online conferences and webinars, video lessons. And personal methods are based on self-education and self-training of staff. Considerable attention is also paid to the types and forms of staff training. The need to synchronize detailed personnel development programs with the main business strategy is considered. After all, a successful program of personnel development management in the organization starts from the synchronization of personnel development strategy and enterprise development strategy.

ELECTRE III for Human Resource Management: A Study of Recruitment and Retention Strategies

This paper presents the application of the ELECTRE III multi-criteria decision making method for human resource management. The case study conducted involves the evaluation of different recruitment and retention strategies using multiple criteria such as cost, time to fill a position, quality of candidates, retention rate, diversity and inclusion, employee satisfaction, and compliance. The study demonstrates the step-by-step process of how to conduct an ELECTRE III analysis, including the identification of criteria and alternatives, the calculation of concordance and discordance indices, and the determination of final rankings using the global outranking relation. The results of this analysis can be used by organizations to make informed decisions about recruitment and retention strategies that best align with their goals and objectives. The study highlights the importance of data quality and the need for sensitivity analysis to check the robustness of the results. Additionally, it is suggested that future research could be conducted on how to effectively communicate the results of the analysis to stakeholders and decision-makers, and on comparing the results of this analysis with other methods.

Development of Human Resource Management in Off-Campus Educational Institutions in the Context of COVID-19：Take an off-campus educational institution in Beijing as an example

In recent years, due to the increasing demand for education by parents and students, a large number of off-campus education and training institutions have been created, and a large number of people have also been attracted to join the industry. The rapid development of this industry has created tens of millions of employment opportunities, but due to the short development time of the industry, there is a lack of a reasonable personnel management system. In the wake of the COVID-19 outbreak in 2020, many industries have been hit. In the off-campus education and training industry, due to improper personnel management and communication, a large number of personnel were lost. This article will take an off-campus educational institution in Beijing as an example to study the company's human resource management methods and policies in the "post-epidemic era", and find out the problems and solve them. The study found that such enterprises currently do not pay enough attention to grass-roots employees, lack of respect, inadequate communication, perfunctory manpower adjustment policies, and inadequate incentives for personnel, and put forward corresponding solutions according to each type of problem.