A Self-Attention Based Dynamic Resource Management for Satellite-Terrestrial Networks

The satellite-terrestrial networks possess the ability to transcend geographical constraints inherent in traditional communication networks,enabling global coverage and offering users ubiquitous computing power support,which is an important development direction of future communications.In this paper,we take into account a multi-scenario network model under the coverage of low earth orbit(LEO)satellite,which can provide computing resources to users in faraway areas to improve task processing efficiency.However,LEO satellites experience limitations in computing and communication resources and the channels are time-varying and complex,which makes the extraction of state information a daunting task.Therefore,we explore the dynamic resource management issue pertaining to joint computing,communication resource allocation and power control for multi-access edge computing(MEC).In order to tackle this formidable issue,we undertake the task of transforming the issue into a Markov decision process(MDP)problem and propose the self-attention based dynamic resource management(SABDRM)algorithm,which effectively extracts state information features to enhance the training process.Simulation results show that the proposed algorithm is capable of effectively reducing the long-term average delay and energy consumption of the tasks.

Ethics of Human Resources Management in the Cameroonian Health System, Medical Nomadism and the Ineffectiveness of the Fight against High Blood Pressure

Context/objectives: The fight against Chronic Non-Communicable Diseases (NCDs) is a long-term undertaking, which requires available, motivated and well-managed human resources (HR). The administrative management of skills on both qualitative and quantitative levels is one of the essential functions of a health system. To better implement policies of fight against High Blood Pressure (HBP) and other chronic diseases, it is important to establish strategies to retain health personnel. This loyalty requires favorable working conditions and consideration of the contribution-reward couple. Good working conditions are likely to reduce the phenomenon of medical nomadism;conversely, poor HR management can contribute to their exodus towards exotic “green pastures”, thus leading to an additional crisis in the Cameroonian health system. The fight against HBP is a complex, multifaceted and multifactorial reality that requires appropriate management model for all types of resources mainly HR. The main objective of this research is to show the impact of poor management of human resources in Cameroon health system on medical nomadism and the ineffectiveness of the fight against High Blood Pressure. Method: A cross-sectional descriptive survey among five hundred (500) health facilities in the center region of Cameroon has been conducted. A stratified probabilistic technique has been used, and the number of health facilities to be surveyed has been determined using the “sample size estimation table” of Depelteau. The physical questionnaires have been printed and then distributed to data collectors. After data collection, the latter were grouped during processing in Excel sheets. The Chi-square test was used for data with a qualitative value and that of Kolmogorov-Sminorf for data with a quantitative value to assess the normality and reliability of data. The Crochach’s Alpha reliability test allowed us to have a summary of the means and variances and then to search for intragroup correlations between variables. Descriptive analysis was possible with the XLSTAT 2016 software. Results: 43.60% of Health Facilities (HF) managers were unqualified. 82.20% of HF managers have staff in a situation of professional insecurity. They are mainly contractual (49.00), decision-making agents (24.40%), casual agents (08.80). The proportion of unstable personnel is average of 22.00% and very unstable, 12.00%.

Research on the Ideological and Political Education in the Curriculum of Human Resource Management in China

Based on the teaching concept of “Ideological and Political Education in the Curriculum”, taking the curriculum of “Human Resource Management” as an example, this paper explores the reform of ideological and political education design from the perspective of moral education objectives and teaching contents. The course takes “carrying forward the craftsmanship spirit” as the main line, and takes” constructing a pattern of high-quality education” as the main task, which not only cultivates students’ professional skills in human resource management, but also integrates ideological and political elements into all modules of human resource management, pays attention to students’ ideological trends and attaches importance to students’ ideological education. In the teaching content, the course introduces ideological and political elements such as craftsmanship spirit, entrepreneurship spirit and Chinese traditional culture. In the recruitment and selection section, the importance of craftsmanship spirit is emphasized, and talents who strive for excellence and excellence are advocated for selection. In the performance management section, combined with entrepreneurial spirit, the value of innovation driven and efficient execution is explored. When discussing about employee development, it is important to integrate socialist core values and balance individual and collective interests. In the chapter of corporate culture, we will delve into the essence of traditional Chinese culture, such as team harmony, integrity, and professionalism to cultivate a good organizational atmosphere. Ideological and political education in the curriculum of Human Resource Management uses case analysis, group discussions and other forms to enhance students’ political identity, ideological identity and emotional identity, so as to deepen students’ professional ideal and ethics education.

Digital Transformation of Enterprise Human Resource Management Enabled by Big Data

With the continuous development of big data technology,the digital transformation of enterprise human resource management has become a development trend.Human resources is one of the most important resources of enterprises,which is crucial to the competitiveness of enterprises.Enterprises need to attract,retain,and motivate excellent employees,thereby enhancing the innovation ability of enterprises and improving competitiveness and market share in the market.To maintain advantages in the fierce market competition,enterprises need to adopt more scientific and effective human resource management methods to enhance organizational efficiency and competitiveness.At the same time,this paper analyzes the dilemma faced by enterprise human resource management,points out the new characteristics of enterprise human resource management enabled by big data,and puts forward feasible suggestions for enterprise digital transformation.

Exploration of Human Resource Management in Enterprise Business Management

Human resource management is an integral part of enterprise operation and management,contributing to the avoidance of financial risks,alleviation of performance problems,promotion of organizational development,enhancement of operational efficiency,and fostering sustainable enterprise development.Enterprise management should prioritize attention to human resource management by establishing an independent human resource management department and strategically planning human resource management tasks.This involves building an information management platform,developing a professional human resource management model to mitigate market risks,actively recruiting human resource management talents to form a competent team,and enhancing the human resource management and supervision system.These measures are essential for comprehensively improving the level of enterprise operation and management.

The Impact of Human Resource Management on University Development

As competition in the education industry intensifies and the knowledge economy evolves,the significance of Human Resource Management(HRM)in university institutions.This study aims to explore how HRM affects the sustainable development and competitiveness improvement of universities.This article begins with a theoretical analysis to define the concept of HRM and its particular relevance within university education.The subsequent analysis examines the multi-dimensional framework of university development,encompassing its connotation,goals,and key influencing factors.The article further elaborates on the positive effects of HRM on university teaching quality,scientific research capabilities,organizational culture,and social services.On this basis,the main challenges currently faced by university HRM are discussed,such as talent mobility,institutional constraints,resource limitations,and internationalization pressure.Finally,optimization strategies are proposed,including building a scientific human resources system,enhancing talent training and development,fostering diversity among teaching staff,and improving decision-making efficiency and transparency.The conclusions of this study aim to provide strategic insights for university education managers to better utilize human resource advantages and promote the comprehensive and sustainable development of universities.

Countermeasures and Suggestions for Strengthening Human Resource Management in China’s Pharmaceutical Industry

Objective To provide reference and enlightenment for the development of human resource management in China’s pharmaceutical industry and to put forward some suggestions to promote the further development of pharmaceutical industry.Methods The method of literature review was used to analyze the current situation and existing problems of human resource management in China’s pharmaceutical industry.Results and Conclusion Only by continuously improving the human resource management skills and innovating management methods can pharmaceutical enterprises achieve long-term benefits with sustainable development.The formulation of human resource management strategy in pharmaceutical industry must be conducive to the realization of the business goals of enterprises.To achieve this overall goal,the human resources management department of enterprises must make the plan from a strategic perspective,formulate talent strategic planning which serves the overall strategic goal of the enterprise.As a result,human resource management will play an important role in the development of China’s pharmaceutical industry.

Optimization Analysis of Human Resource Management Strategies of Nantong University,a Local Comprehensive University in China

This study analyzes the current situation and challenges of Nantong University amid the rapid development of higher education,addressing aspects such as faculty structure,administrative management efficiency,and promotion mechanisms.Through questionnaire surveys and field research,coupled with SWOT analysis and various theoretical methods,a comprehensive analysis was conducted on Nantong University’s internal and external environment.The study proposes an improved comprehensive development strategy and implementation measures,which include updating management concepts,strengthening professional training,optimizing employment conditions,and improving salary systems.Ultimately,this study provides practical strategies for human resource management and the transformational development of Nantong University and other local comprehensive universities.

Research on the Status Quo and Countermeasures of Human Resource Management Outsourcing in China’s Pharmaceutical Enterprises

Objective To explore the current situation of human resource management outsourcing in China’s pharmaceutical enterprises,and to put forward some suggestions for enterprises and the government.Methods The current situation of human resource management outsourcing in China’s pharmaceutical enterprises was analyzed through the method of literature research.Results and Conclusion At present,the status of human resource management outsourcing in China’s pharmaceutical companies is that the level of human resource outsourcing companies is not high,and there are no relevant industry norms and laws.The information asymmetry between pharmaceutical enterprises and outsourcing companies results in adverse selection and moral hazard.Besides,the different culture of pharmaceutical enterprises and outsourcing companies leads to inefficient communication between enterprises and employee.To solve these problems,the government should promote and improve industry norms and laws to regulate the market.In addition,enterprises should clarify the motivation for outsourcing and make good decision on the outsourcing content.Meanwhile,enterprises should strengthen communication with employees to eliminate employees’concerns.

Research on Enterprise Human Resource Management Reform Strategy in the Era of Big Data

In the 21st century,with the development of the Internet,mobile devices,and information technology,society has entered a new era:the era of big data.With the help of big data technology,enterprises can obtain massive market and consumer data,realize in-depth analysis of business and market,and enable enterprises to have a deeper understanding of consumer needs,preferences,and behaviors.At the same time,big data technology can also help enterprises carry out human resource management innovation and improve the performance and competitiveness of enterprises.Of course,from another perspective,enterprises in this era are also facing severe challenges.In the face of massive data processing and analysis,it requires superb data processing and analysis capabilities.Secondly,enterprises need to reconstruct their management system to adapt to the changes in the era of big data.Enterprises must treat data as assets and establish a perfect data management system.In addition,enterprises also need to pay attention to protecting customer privacy and data security to avoid data leakage and abuse.In this context,this paper will explore the thinking of enterprise human resource management innovation in the era of big data,and put forward some suggestions on enterprise human resource management innovation.

Exploring the Digital Path of Human Resource Management in Innovation and Entrepreneurship Enterprises

The digitization of human resource management functions can enhance the adaptability of human resource management and promote the comprehensive digital development of innovative and entrepreneurial enterprises.This article first summarizes and evaluates the connotation and research status of the digitalization of enterprise human resource management.Secondly,it analyzes the influencing factors of digitalization of human resource management in innovative and entrepreneurial enterprises from three aspects:employee factors,organizational factors,and technological factors.Finally,it designs a digitalization plan for human resource management in innovative and entrepreneurial enterprises from four aspects:analyzing the current situation,preparing thoroughly,designing plans,and building systems.It emphasizes the value of digitalization of enterprise human resource management for innovative and entrepreneurial enterprises.

Ultra Dense Satellite-Enabled 6G Networks:Resource Optimization and Interference Management

With the evolution of the sixth generation(6G)mobile communication technology,ample attention has gone to the integrated terrestrial-satellite networks.This paper notes that four typical application scenarios of integrated terrestrial-satellite networks are integrated into ultra dense satellite-enabled 6G networks architecture.Then the subchannel and power allocation schemes for the downlink of the ultra dense satellite-enabled 6G heterogeneous networks are introduced.Satellite mobile edge computing(SMEC)with edge caching in three-layer heterogeneous networks serves to reduce the link traffic of networks.Furthermore,a scheme for interference management is presented,involving quality-of-service(QoS)and co-tier/cross-tier interference constraints.The simulation results show that the proposed schemes can significantly increase the total capacity of ultra dense satellite-enabled 6G heterogeneous networks.

Optimal and Effective Resource Management in Edge Computing

Edge computing is a cloud computing extension where physical compu-ters are installed closer to the device to minimize latency.The task of edge data cen-ters is to include a growing abundance of applications with a small capability in comparison to conventional data centers.Under this framework,Federated Learning was suggested to offer distributed data training strategies by the coordination of many mobile devices for the training of a popular Artificial Intelligence(AI)model without actually revealing the underlying data,which is significantly enhanced in terms of privacy.Federated learning(FL)is a recently developed decentralized profound learning methodology,where customers train their localized neural network models independently using private data,and then combine a global model on the core server together.The models on the edge server use very little time since the edge server is highly calculated.But the amount of time it takes to download data from smartphone users on the edge server has a significant impact on the time it takes to complete a single cycle of FL operations.A machine learning strategic planning system that uses FL in conjunction to minimise model training time and total time utilisation,while recognising mobile appliance energy restrictions,is the focus of this study.To further speed up integration and reduce the amount of data,it implements an optimization agent for the establishment of optimal aggregation policy and asylum architecture with several employees’shared learners.The main solutions and lessons learnt along with the prospects are discussed.Experiments show that our method is superior in terms of the effective and elastic use of resources.

Endogenous Security-Aware Resource Management for Digital Twin and 6G Edge Intelligence Integrated Smart Park

The integration of digital twin(DT)and 6G edge intelligence provides accurate forecasting for distributed resources control in smart park.However,the adverse impact of model poisoning attacks on DT model training cannot be ignored.To address this issue,we firstly construct the models of DT model training and model poisoning attacks.An optimization problem is formulated to minimize the weighted sum of the DT loss function and DT model training delay.Then,the problem is transformed and solved by the proposed Multi-timescAle endogenouS securiTy-aware DQN-based rEsouRce management algorithm(MASTER)based on DT-assisted state information evaluation and attack detection.MASTER adopts multi-timescale deep Q-learning(DQN)networks to jointly schedule local training epochs and devices.It actively adjusts resource management strategies based on estimated attack probability to achieve endogenous security awareness.Simulation results demonstrate that MASTER has excellent performances in DT model training accuracy and delay.

Artificial Intelligence Technique in Hydrological Forecasts Supporting for Water Resources Management of a Large River Basin in Vietnam

Hydrological forecasting plays an important role in water resource management, supporting socio-economic development and managing water-related risks in river basins. There are many flow forecasting techniques that have been developed several centuries ago, ranging from physical models, physics-based models, conceptual models, and data-driven models. Recently, Artificial Intelligence (AI) has become an advanced technique applied as an effective data-driven model in hydrological forecasting. The main advantage of these models is that they give results with compatible accuracy, and require short computation time, thus increasing forecasting time and reducing human and financial effort. This study evaluates the applicability of machine learning and deep learning in Hanoi water level forecasting where it is controlled for flood management and water supply in the Red River Delta, Vietnam. Accordingly, SANN (machine learning algorithm) and LSTM (deep learning algorithm) were tested and compared with a Physics-Based Model (PBM) for the Red River Delta. The results show that SANN and LSTM give high accuracy. The R-squared coefficient is greater than 0.8, the mean squared error (MSE) is less than 20 cm, the correlation coefficient of the forecast hydrology is greater than 0.9 and the level of assurance of the forecast plan ranges from 80% to 90% in both cases. In addition, the calculation time is much reduced compared to the requirement of PBM, which is its limitation in hydrological forecasting for large river basins such as the Red River in Vietnam. Therefore, SANN and LSTM are expected to help increase lead time, thereby supporting water resource management for sustainable development and management of water-related risks in the Red River Delta.

Investigating the Evolution of Human Resource Management in Enterprises in the Era of Big Data

Human resource(HR)management plays a crucial role in the overall management of enterprises,exerting a significant influence on their growth and development.With China now firmly entrenched in the era of big data,the conventional HR management approach is no longer adequate to meet the evolving demands of enterprise progress.Therefore,there is a pressing need to actively revamp the management strategies to improve the quality.This article outlines the importance of reforming enterprise HR management in the context of big data,scrutinizes the prevailing challenges in this domain,explores strategies for transforming HR management within enterprises in the era of big data,and provides illustrative examples to summarize valuable managerial insights,thereby offer enterprise leaders a valuable source of reference information.

Research on the Relationship Between Human Resource Management and Corporate Environmental Responsibility

The significance of human resource management in enterprise management is steadily growing,especially as businesses today are expected to shoulder their share of social responsibility.Among these responsibilities,corporate environmental responsibility assumes a pivotal role.This paper aims to investigate the interplay between human resource management practices and corporate environmental responsibility.The study employs various factors of human resource management practices as independent variables,using the current environmental status quo and environmental innovation capacity as intermediary variables,and adopts multiple regression analysis to scrutinize the influencing factors of corporate environmental responsibility.The findings underscore that when the working environment is favorable,enterprise human resource management practices can effectively enhance corporate environmental responsibility.Furthermore,when supported by environmentally responsible behavior,these human resources practices exhibit a positive influence on a company’s environmental responsibility.Consequently,this study provides practical recommendations for enhancing corporate environmental responsibility.

Fuzzy Logic Inference System for Managing Intensive Care Unit Resources Based on Knowledge Graph

With the rapid growth in the availability of digital health-related data,there is a great demand for the utilization of intelligent information systems within the healthcare sector.These systems can manage and manipulate this massive amount of health-related data and encourage different decision-making tasks.They can also provide various sustainable health services such as medical error reduction,diagnosis acceleration,and clinical services quality improvement.The intensive care unit(ICU)is one of the most important hospital units.However,there are limited rooms and resources in most hospitals.During times of seasonal diseases and pandemics,ICUs face high admission demand.In line with this increasing number of admissions,determining health risk levels has become an essential and imperative task.It creates a heightened demand for the implementation of an expert decision support system,enabling doctors to accurately and swiftly determine the risk level of patients.Therefore,this study proposes a fuzzy logic inference system built on domain-specific knowledge graphs,as a proof-of-concept,for tackling this healthcare-related issue.The system employs a combination of two sets of fuzzy input parameters to classify health risk levels of new admissions to hospitals.The proposed system implemented utilizes MATLAB Fuzzy Logic Toolbox via several experiments showing the validity of the proposed system.

What to Cache：Differentiated Caching Resource Allocation and Management in Information-Centric Networking

Information-centric networking(ICN) aims to improve the efficiency of content delivery and reduce the redundancy of data transmission by caching contents in network nodes. An important issue is to design caching methods with better cache hit rate and achieve allocating on-demand. Therefore, an in-network caching scheduling scheme for ICN was designed, distinguishing different kinds of contents and dynamically allocating the cache size on-demand. First discussing what was appropriated to be cached in nodes, and then a classification about the contents could be cached was proposed. Furthermore, we used AHP to weight different contents classes through analyzing users' behavior. And a distributed control process was built, to achieve differentiated caching resource allocation and management. The designed scheme not only avoids the waste of caching resource, but also further enhances the cache availability. Finally, the simulation results are illustrated to show that our method has the superior performance in the aspects of server hit rate and convergence.

Artificial Intelligence-Empowered Resource Management for Future Wireless Communications: A Survey

How to explore and exploit the full potential of artificial intelligence(AI)technologies in future wireless communications such as beyond 5G(B5G)and 6G is an extremely hot inter-disciplinary research topic around the world.On the one hand,AI empowers intelligent resource management for wireless communications through powerful learning and automatic adaptation capabilities.On the other hand,embracing AI in wireless communication resource management calls for new network architecture and system models as well as standardized interfaces/protocols/data formats to facilitate the large-scale deployment of AI in future B5G/6G networks.This paper reviews the state-of-art AI-empowered resource management from the framework perspective down to the methodology perspective,not only considering the radio resource(e.g.,spectrum)management but also other types of resources such as computing and caching.We also discuss the challenges and opportunities for AI-based resource management to widely deploy AI in future wireless communication networks.