Resource Management Mechanisms Research Articles

Statement of Retraction: An Efficient Resource Management Mechanism Based on Developed Political Optimizer in Fog Computing

Statement of Retraction: An Efficient Resource Management Mechanism Based on Developed Political Optimizer in Fog Computing

Efficient Predictive Regulation Algorithms for AGV System in Industrial Internet

<p>In recent years, the industrial Internet has developed rapidly. In order to improve the reliability, real-time, and economy, Automated Guided Vehicle (AGV) in intelligent manufacturing system becomes an indispensable technology. However, the current AGV system relies too much on the fixed network bandwidth environment in information transmission and management. When the traffic demand changes frequently, this form of network configuration lacks network resource management mechanism. Further, it leads to the problems of delay, waste of network flow, and inability to dynamically allocate network resources. So it is vital to improve the AGV system. Therefore, this paper proposes three predictive control algorithms and a Network Cable Scheduling algorithm to manage the network resources. They are Markov Chain Linear Programming Regulation (MCLPR) algorithm, Prophet Linear Programming Regulation (PLPR) algorithm, and Machine Learning Linear Programming Regulation (MLLPR) algorithm. The experimental results show that PLPR and MLLPR algorithm have high efficiency in the aspect of regulation. MLLPR algorithm has the lowest cost. MLLPR algorithm has the strongest leakage limitation ability, followed by PLPR algorithm. The balance regulation efficiency of MLLPR in none “4 + 1” mode is the highest in different network cable modes.</p> <p> </p>

Effect of oasis and irrigation on mountain precipitation in the northern slope of Tianshan Mountains based on stable isotopes

Water is one of the scarcest resources in arid regions, and irrigation is an important means to improve crop yield and ensure food security. The Xinjiang features an integrated irrigation agriculture and oasis economy paradigm. However, the understanding of the impact mechanism and quantitative analysis of irrigation on precipitation is inadequate now. With the aim of clarifying the response relationship between mountain precipitation and irrigation in oasis, we clarify and quantify the moisture sources of precipitation using the Hybrid Single Particle Lagrangian Integrated Trajectory (HYSPLIT) model and multisource data (including field-collected isotopes data, C-Isoscape, ERA5, and GDAS). The results obtained show: (1) Isotope analysis provides valuable insights into the climate background and precipitation recycling. The Local Meteoric Water Line's lower slope and intercept than Global Meteoric Water Line suggest a severe arid climate and strong sub-cloud evaporation. The intercept (13.44) of Local Meteoric Water Line in Mountain Areas exceeds the global average, indicating significant moisture recycling in mountain areas (MA). The d-excess in MA is prominent year-round, highlighting the influence of recycled moisture. (2) The oasis and irrigation influence the local precipitation through offset, remote, combination, and delayed effects. The offset effect hinders precipitation formation in irrigation areas (IA) due to the counteracting irrigation-induced humidification and cooling effect. Through the interaction of westerly circulation and local mountain-oasis hydrological cycle, irrigation-induced moisture is transported to MA and uplifted, which is remote effect. The combination effect synergistically enhances precipitation intensity, especially in intricate MA, through the combined influence of terrain's forced uplift and convective cells. Furthermore, the mountainous precipitation influenced by the mountain-oasis hydrological cycle often exhibits a delayed effect. (3) Based on HYSPLIT model tracking results, the contribution ratio of oasis and irrigation induced evapotranspiration to summer precipitation in MA is approximately 19.60%, ranging from 13.68% to 28.49%. The findings provide insights into the mechanisms of irrigation and water resource management in the northern slope of Tianshan Mountains.

Green pesticide practices and sustainability: empirical insights into agricultural services in China

ABSTRACT In a world grappling with the overuse of pesticides, China emerges as a key consumer and producer, facing substantial challenges in environmental and agricultural sustainability. This study investigates how agricultural services can foster eco-friendly pesticide use among farmers. It leverages data from the ‘China Land Economic Survey’ (2020-2021) by Nanjing Agricultural University, covering 52 villages and 2600 households. Using a multi-dimensional fixed effects model and propensity score matching, the research addresses biases inherent in the data. Results show that agricultural business services significantly boost green pesticide adoption, outperforming agricultural technology and input sectors. These services increase the use of safer pesticides and the recycling of their containers by 11.6% and 6%, respectively. Farmer satisfaction and regular internet use also play a role in reinforcing this trend. Based on these insights, it recommends enhancing support for low-toxicity pesticides and recycling programmes, creating tailored policies for diverse agricultural needs, and implementing resource management and incentive mechanisms to promote sustainable practices. These strategies aim to bolster sustainable agriculture, balancing environmental health with economic viability.

AMIS-MU: Edge Computing Based Adaptive Video Streaming for Multiple Mobile Users

The increasing demand for online high-quality video streaming has brought huge challenges to the traditional client-server video streaming systems due to the high feedback delay, rigorous bandwidth requirement, and the lack of a mechanism of centralized resource management between users. In this work, we propose AMIS-MU, an edge computing-based mobile video streaming system that optimizes the watching experience of users via playback adaptation and channel resource allocation. AMIS-MU fully explores the power of edge servers from three perspectives. First, by pre-caching videos from the cloud, AMIS-MU analyzes video contents at the edge, and achieves a nearly imperceptible content-based playback speed adaptation. Second, as the edge server controls the channel resources of users in a centralized fashion, AMIS-MU adaptively updates the channel configuration to optimize the overall watching experience. Last, the plenty of computational power available at the edge enables a more intelligent playback control by using deep reinforcement learning (DRL). We propose a novel usage of DRL which significantly reduces the complexity of the cross-layer joint optimization problem and solve the non-convex channel resource allocation problem by Lyapunov optimization. Experiments show that AMIS-MU outperforms other existing algorithms in terms of average QoE and fairness.

Research on the impact mechanism of flexible human resources management on the civic behavior of employee organizations

Research on the impact mechanism of flexible human resources management on the civic behavior of employee organizations

Retracted: Regulatory Mechanism of Financial Market Resource Management Driven by Big Data

Retracted: Regulatory Mechanism of Financial Market Resource Management Driven by Big Data

A novel funnel and ontological mechanism for sustainable Green Human Resource Management (GHRM)

A novel funnel and ontological mechanism for sustainable Green Human Resource Management (GHRM)

Evaluating green financing mechanisms for natural resource management: Implications for achieving sustainable development goals

China has made noteworthy strides in achieving the Sustainable Development Goals (SDGs), including natural resource management. The country’s economic expansion has put more strain on its natural resources during Covid-19 pandemic, which has contributed to environmental deterioration, the extinction of species, and climate change. Consequently, green finance can create new opportunities for assisting natural resource management practices that support environmental, social, and economic sustainability. In order to realize the SDGs, this study employs a hybrid Fuzzy Multi-Criteria Decision Making (MCDM) approach based on the Analytical Hierarchy Process (AHP) and Visekriterijumska Optimizacija i Kompromisno Resenje (VIKOR) to assess and prioritize important criteria, sub-criteria, and green financing mechanisms for natural resource management in China. Therefore, this study identified six criteria, eighteen sub-criteria, and six green financing strategies for promoting sustainable development and natural resource management methods in China. According to the Fuzzy AHP findings, financial sustainability (0.192), institutional feasibility (0.176), and environmental impact (0.171) are the most crucial criteria. While, the Fuzzy VIKOR findings reveal that carbon markets, green bonds, and green investment funds are the best financial solutions for reaching sustainable development and effective resource management practices in China. This research enables policymakers, investors, and other stakeholders improve sustainable development and natural resource management in China.

Creating social value at the bottom of the pyramid: Elaborating resource orchestration via social intermediaries

Overcoming constrained resources and enabling social, environmental, and economic value creation for stakeholders remains a managerial challenge. Small enterprises in the bottom of the pyramid (BoP) context offer an opportunity to extract insights into orchestration of resources amidst such challenges. Extensive qualitative data collected via text analysis, field visits, and expert interviews with two social intermediaries and managers of eleven small enterprises operating in BoP markets were analyzed to understand how small enterprises engage with stakeholders to structure, bundle, and leverage resources, as well as how they address environmental contingencies and social challenges in poverty settings. The findings highlight that companies must move beyond an economic resource focus and engage a diverse stakeholder network, leveraging social intermediaries for resource orchestration throughout lifecycle stages. The emergent framework elaborates on Resource Orchestration Theory (ROT), with propositions related to resource management mechanisms, capabilities offered by social intermediaries, and contingencies for social value creation.

ANALYSIS OF EMPLOYEE LOYALTY - A CASE STUDY OF PINGDINGSHAN BRANCH OF BANK OF CHINA

This article aims to investigate the employee loyalty in the context of banking industry and takes the staff of Pingdingshan Branch of Bank of China as research target to study the influencing factors of employee loyalty. The article will focus on the following sections. First, the relevant concepts and associated analysis lay the foundation for further research. Secondly, the theoretical research model is designed to develop the questionnaire and collect relevant information.Finally, the structural equation model is established to verify the hypothesis and draw a conclusion. It is concluded that the human resource management mechanism, personal factors, internal factors and external factors have the employee loyalty. Based on the findings, to provide relevant advice to the Pingdingshan Branch of the Bank of China and others.

Fog computing network security based on resources management

Fog computing paradigm is designed as an extension of cloud computing due to the need for a supporting platform that is capable of providing the requirements of the Internet of Things (IoT). However, due to its features, fog obviously confronts numerous security and privacy risks, such as huge scale geolocation, heterogeneity, and mobility. Indeed, there are many problems resulting from security violations and breaches. Thus, to exceed these problems, we propose an efficient access control system, ameliorated with appropriate monitoring function and risk estimation to detect abnormal user’s behavior and then deactivating illegitimate anomaly actions. Indeed, based on the risk value, we compute the trust level that will then be made into an access certificate, which would be provided to the user. This security certificate is used to authenticate and authorize users in case of re-connection in another time, without repeating the whole access control process from the beginning. Moreover, a comprehensive resource management mechanism is proposed to ameliorate the system performance and so to maintain low latency. Our aim is to further enhance data security, privacy and resource management for IoT users. To demonstrate the efficiency, feasibility, and security of our proposed scheme, we perform an extensive simulation using Network Security Simulator (Nessi2).

Delay reduction in MTC using SDN based offloading in Fog computing.

Fog computing (FC) brings a Cloud close to users and improves the quality of service and delay services. In this article, the convergence of FC and Software-Defined-Networking (SDN) has been proposed to implement complicated mechanisms of resource management. SDN has suited the practical standard for FC systems. The priority and differential flow space allocation have been applied to arrange this framework for the heterogeneous request in Machine-Type-Communications. The delay-sensitive flows are assigned to a configuration of priority queues on each Fog. Due to limited resources in the Fog, a promising solution is offloading flows to other Fogs through a decision-based SDN controller. The flow-based Fog nodes have been modeled according to the queueing theory, where polling priority algorithms have been applied to service the flows and to reduce the starvation problem in a multi-queueing model. It is observed that the percentage of delay-sensitive processed flows, the network consumption, and the average service time in the proposed mechanism are improved by about 80%, 65%, and 60%, respectively, compared to traditional Cloud computing. Therefore, the delay reductions based on the types of flows and task offloading is proposed.

Water resource management and financial performance in high water‐sensitive corporates

AbstractWater is a valuable resource in the world, and water resource management is an important aspect of corporate social responsibility. Does water resource management affect corporate financial performance? What is the influencing path? To find the potential relationship and influencing mechanism between water resource management and corporate financial performance, based on configuration thinking, we selected 259 A‐share listed manufacturing corporates from 2015 to 2021 as research samples, using fuzzy set qualitative comparative analysis method (fsQCA) to explore the configuration and influencing path of water resource management affecting financial performance. Then we analyzed it with the configuration that CSR score (excluding “environmental responsibility”) affects financial performance. Our results show that: (1) poor water management and low CSR score will lead to bad corporate financial performance, but the former's severity of negative impact on corporate financial performance is more than that of the latter. Specific configurations indicate that companies with little water‐related concrete actions implemented and technology innovation will severely hurt the financial performance. (2) Good water resources management cannot directly achieve high financial performance while high CSR score can make it, indicating that water resource management is a necessary but not sufficient condition for high corporate financial performance. Our research has unmasked the "black box" influencing mechanism of water resource management on corporate financial performance to some extent, which makes the configuration relationship between water resource management and financial performance clearer, therefore owns certain theoretical significance and practical value in the field of CSR and environmental management.

Spatio-temporal variations in the ecological vulnerability of the Upper Mzingwane sub-catchment of Zimbabwe

Profiling eco-environmentally vulnerable (EV) areas can contribute to the development of mechanisms for environmental protection and sustainable management of ecological resources. Land cover change, population density, annual precipitation, mean temperature, remotely sensed indices, actual evapotranspiration, land surface temperature (LST), and runoff for the catchment for 1990, 2000, 2011, and 2020 were used to assess spatiotemporal ecological vulnerability. Spatial principal component analysis (SPCA) was used to assess thematic vulnerability for each year. The analytical hierarchical process (AHP) was then used to determine the weighting of the thematic maps to produce the final ecological vulnerability maps. Our results showed that most of the sub-basin had low and moderate vulnerability in 1990, 2000, 2011, and 2020, with the combined proportion of these areas being 80.6%, 55.45%, 83.92%, and 85.1%, respectively. The areas classified as high vulnerability decreased steadily over the investigated years, except in 2000, where an increase was observed. Most areas in the southern parts of the sub-basin were classified as moderately vulnerable, while high vulnerability values were recorded in the northern areas. The southern parts of the Upper Mzingwane basin are drier and less populated than the northern parts. The spatial architecture of vulnerability presented will help inform decision makers in mitigation planning and overall disaster risk management initiatives in the basin.

Analysis of Mechanisms for Resource Management in IoT: Performance of Mutual Authentication in the Context of Fog and EDGE-Fog Computing

The Internet is now experiencing an unprecedented expansion with the development of connected objects. At its inception the IoT, like any revolution, its objectives were quite limited. Its main objective was to reduce the effort of human data entry in order to allow the storage and automatic processing of the latter. Moreover, objects generate a lot of data that they cannot store or process by themselves, hence the need for external support. This is how Cloud Computing comes to answer this problem, making the success of IoT. This technology guarantees the storage, availability, processing, etc. of data, its integration into the latter is known as "Cloud of Things" CoT. The data generated should not only be stored, but rather processed in order to derive knowledge, decision making. The objective of our work is to analyze mutual authentication management models of IoT devices to optimize resources trying to provide solutions in the face of resource availability. To carry out this work, we analyzed the application areas and the challenges of IoT. Then, we studied IoT security threats. Our work ends with a study and an analysis mechanism of mutual authentication management models of IoT based on uncertificated Authentication mechanisms, Elliptic curve cryptography authentication, Mutual Authentication in the context of Fog Computing.

The problems of functioning of the existent management system of defense resources of the security and defense of Ukraine sector

In the conditions of military aggression, resource limitation, actual transition to weapons, military equipment and standards of NATO member countries, the issue of centralization of the existing defense resource management system of the security and defense sector of Ukraine is becoming more and more urgent. A constellation of scientists was engaged in researching the issue of defense resource management, but new challenges are not taken into account in the construction of the existing defense resource management mechanism, which determines the relevance of this study. The paper is devoted to the analysis of the legal framework for the regulation of the defense resource management system. The paper highlights the problems of legislative regulation of the existing defense resource management system of the security and defense sector of Ukraine in the context of resource limitations and full-scale military aggression of the Russian Federation. The purpose of the paper is to identify and study the actual problems of the functioning of the existing defense resource management system of the security and defense sector of Ukraine. Identified inconsistencies and problems in the regulatory support of the defense resource management system. There is a well-founded need to establish a system of obtaining weapons, military equipment, and military materials with the international assistance of Lend-Lease partner countries, automating planning and provisioning processes at the tactical, operational, and strategic levels, bringing the resource provision system closer to the principles and standards of NATO member states. The domestic legislation does not sufficiently fully and effectively ensure the functioning of the existing defense resources management system of the security and defense sector of Ukraine. This requires a clear distribution of powers between the management bodies for each separate area of defense resource management, coordination of priorities, ways and measures for providing defense resources and taking into account the experience of advanced NATO countries for its implementation in the domestic system.

Federated Learning-Based Resource Management with Blockchain Trust Assurance in Smart IoT

Resource management is a key issue that needs to be addressed in the future smart Internet of Things (IoT). This paper focuses on a Federated Learning (FL)-based resource management mechanism in IoT. It incorporates blockchain technology to guarantee the security of the FL model parameters exchange. We propose an IoT resource management framework incorporating blockchain and federated learning technologies; then, a specific FL-based resource management with a blockchain trust assurance algorithm is given. We use a Support Vector Machine (SVM) classifier to detect malicious nodes in order to avoid the impact on the performance of the FL-based algorithm. Finally, we perform simulation to verify the SVM classification effect and the proposed algorithm performance. The results show that the SVM-based malicious node identification accuracy can be acceptable. Moreover, the proposed algorithm obtains better performance when malicious nodes are excluded from the FL selected participant.

Climate change, water resources, and wastewater reuse in Cyprus

This study aims to gain a deeper understanding of climate change and wastewater usage in Cyprus. Focusing on water resources, the study was done in Cyprus. The significance of selecting Cyprus as our case study arises from the fact that it is not only one of the Mediterranean Sea countries worldwide with water resource concerns but also faces a serious danger of drought in the next years. Documentary analysis and summation of what numerous sources mentioned regarding the freshwater situation in Cyprus were used to collect data. The objective of this research was to understand the water resources available in Cyprus and the quality of fresh water, then to examine the practices and mechanisms of freshwater resource management in Cyprus, and finally to investigate the challenges faced by various water resources in Cyprus and the various means to overcome them. The initial objective was to determine the different water resources in Cyprus. Second, we analyzed the many strategies employed to manage these resources and the diverse management structures in Cyprus. In light of the foregoing, this study's main objective was to understand climate change and wastewater utilization better. Thus, linking formal and informal institutions in the management of these water resources, as well as the issues and solutions they face in dealing with salt water. Water conservation is not an individual concern. All parties are involved, including the government, non-governmental groups, local inhabitants, and all stakeholders, with differing opinions.

Exploring Mechanisms for Sustainable Resource Management: An Empirical Study on Human, Social, Economic & Environmental Resources in Bangladesh

Sustainable resource management aims to concurrently produce favorable effects for the environment, society, and the economy. The SDGs provide strategies, goals, activities, and management practices that resource management practitioners can apply in the fields of development outcomes in Bangladesh. Advancing the societal aspect of sustainability is challenging in developing countries like Bangladesh because large portions of the population live below the International Poverty Line. This study is done from secondary sources rely on observations to investigate past preparing frameworks examination with certain recommendations of new contemplations, strategies, procedures, and applications Ensuring air and water quality, reducing food and water consumption, decreasing waste, enhancing energy efficiency, sharing of renewable energy and conserving ecologically valuable lands are the challenges of SDG globally. The interrelationship between different factors and their influence on Human, Social, Economic, and Environmental Resources in Bangladesh is highly sensitive and volatile for the accuracy of monitoring. This study aims to Explore Mechanisms for Sustainable Resource Management in Bangladesh in the areas of human, social, economic, and environmental Resources sustainable quality, systems, analysis, and policy. The findings of this study can be used for policy intervention for future sustainable development of the SRM from the perspective of resource Mechanism analysis, renewable resources, and following the three R's: reduce, reuse, and recycle.