The Status and Role of Competency Model in Enterprise Human Resource Management

The competency model is a widely-used human resource management tool that can be applied to human resource management in different regions,different fields,different enterprises,and positions of different nature,which can improve the objectivity,reliability,authenticity and fairness of enterprise human resource management,give full play to the promotion of human resource management to the development of enterprise operations,and help enterprises achieve development and manage-ment goals.

Resource management and job scheduling of China earthquake grid experiment system: Construction of resource management and job dynamic scheduling model ProRMJS

Grid technique is taken as the third generation internet technology and resource management is the core of it. Aiming at the problems of resource management of CEDAGrid （China Earthquake Disaster Alleviation and Simulation Grid） in its preliminary construction, this paper presents a resource management and job scheduling model： ProRMJS to solve these problems. For platform supposed agreeably each computing node can provide computation service, ProRMJS uses ＂computation pool＂ to support scheduler, and then the scheduler allocates jobs dynamically according to computing capability and status of each node to ensure the stability of the platform. At the same time, ProRMJS monitors the status of job on each node and sets a time threshold to manage the job scheduling. By estimating the computing capability of each node, ProRMJS allocates jobs on demand to solve the problem of supposing each node can finish the job acquiescently. When calculating the computing capability of each node, ProRMJS allows for the various factors that affect the computing capability and then the efficiency of the platform is improved. Finally the validity of the model is verified by an example.

MODELING RADIO RESOURCE MANAGEMENT IN COGNITIVE RADIO SYSTEM BASED ON OFDMA USING COLORED PETRI NET

Cognitive Radio(CR) system based on Orthogonal Frequency Division Multiple Access(OFDMA),such as Wireless Regional Area Networks(WRAN) and Worldwide Interoperability for Microwave Access(WiMAX),often attempt to improve performance via dynamic radio resource management,which is characterized as concurrent processing of different traffic and nondeterministic system capacity.It is essential to design and evaluate such complex system using proper modeling and analysis tools.In the previous work,most of the communication systems were modeled as Markov Chain(MC) and Stochastic Petri Nets(SPN),which have the explicit limitation in evaluating adaptive OFDMA CR system with wide area traffic.In this paper,we develop an executable top-down hier-archical Colored Petri Net(CPN) model for adaptive OFDMA CR system,and analyze its performance using CPN tools.The results demonstrate that the CPN can model different radio resource manage-ment algorithms in CR Systems,and the CPN tools require less computational effort than Markov model using Matlab,with its flexibility and adaptability to the traffics which arrival interval and processing time are not exponentially distributed.

A Numerical Solution for the Integrated Analysis of Water Resources Management: Application to the Mero River Watershed, La Coruña, Spain

This research is concerned with new developments and practical applications of a physically-based numerical model that incorporates new approaches for a finite elements solution to the steady/transient problems of the joint ground/surface water flows. Python scripts are implemented in Geographic Information System (GIS) to store, represent and take decisions on the simulated conditions related to the water resources management at the scale of the watershed. The proposed surface-subsurface model considers surface and groundwater interactions to be 2-D horizontally distributed and depth-averaged through a diffusive wave approach for surface flood routing. Infiltration rates, overland flows and evapotranspiration processes are considered by a diffuse discharge from surface water, non-saturated subsoil and groundwater table. Recent developments also allow for the management of surface water flow control through the capacity of diversion on river beds, spillways and outflow operations of floodgates in weirs and dams of reservoirs. Practical application regards the actual hydrology of the Mero River watershed, with two important water bodies mainly concerned with the water resources management at the Cecebre Reservoir and the present flooding of a deep coal mining excavation. The MELEF model (Modèle d’éLéments Fluides, in French) was adapted and calibrated during a period of five years (2008/ 2012) with the help of hydrological parameters, registered flow rates, water levels and registered precipitation, water uses and water management operations in surface and groundwater bodies. The results predict the likely evolution of the Cecebre Reservoir, the flow rates in rivers, the flooding of the Meirama open pit and the local water balances for different hydrological components.

Resolution of Relationship between Organizational Performance and Human Resource Management through Nonlinear Modeling

The relation between the HRM and the firm performance is analyzed statistically by many researchers in the literature. However, there are very few nonlinear approaches in literature for finding the relation between Human Resource Management (FIRM) and firm performance. This paper exposes the relationship between human resource management and organizational performance through the use of nonlinear modeling technique. The modeling is proposed based on Radial Basis Function (RBF) which is nonlinear modeling technique in literature. The relation between 12 input and 9 output parameters is investigated in this research that is collected between 54 companies in Turkey which indicated that the relationship between organizational management performance and relationship management can be modelled through nonlinearly.

Blockchain in Smart Grid for Sustainable Management of Environmental Resources Usage

Blockchain is a distributed database that is shared among the nodes of a computer network.Blocks have certain storage capacity and,when filled,they are closed,and linked to the previously filled block,forming a chain.Blockchains are typically managed by a peer-to-peer method where nodes collectively adhere to a consensus algorithm protocol to add and validate new transaction blocks.The author makes a review of Blockchain applications in different areas,considerable challenges,her own experience with Blockchain in Smart Grid and other researchers`contributions.The paper presents the first stage of project“Smart Grid for Sustainable Management of Environmental Resources Usage”-describing Managed Objects classes for selected functional areas of Blockchain life cycle:Configuration,Security,and Performance.The author uses the life cycle of telecommunication networks as a reference.The models are designed for user interface developers,university professors,and students.

COMPREHENSIVE INTRODUCTION TO THE TECHNOLOGY OF GROUNDWATER MODELING AND OPTIMAL MANAGEMENT

Three numeric simulation and optimal management models on groundwater resources are introduced in this paper. These models stand for the present developing levels on the technology of groundwater modeling and optimal management in China, and show the practical application situations of the technology. Each of the technology of unique characteristics and purposes. According to the tests of the practical engineering, these models have played a very important role in solving the difficult problems of groundwater resources.

A simulation-based two-stage interval-stochastic programming model for water resources management in Kaidu-Konqi watershed,China

This study presented a simulation-based two-stage interval-stochastic programming （STIP） model to support water resources management in the Kaidu-Konqi watershed in Northwest China. The modeling system coupled a distributed hydrological model with an interval two-stage stochastic programing （ITSP）. The distributed hydrological model was used for establishing a rainfall-runoff forecast system, while random parameters were pro- vided by the statistical analysis of simulation outcomes water resources management planning in Kaidu-Konqi The developed STIP model was applied to a real case of watershed, where three scenarios with different water re- sources management policies were analyzed. The results indicated that water shortage mainly occurred in agri- culture, ecology and forestry sectors. In comparison, the water demand from municipality, industry and stock- breeding sectors can be satisfied due to their lower consumptions and higher economic values. Different policies for ecological water allocation can result in varied system benefits, and can help to identify desired water allocation plans with a maximum economic benefit and a minimum risk of system disruption under uncertainty.

A Game-Theoretic Perspective on Resource Management for Large-Scale UAV Communication Networks

As a result of rapid development in electronics and communication technology,large-scale unmanned aerial vehicles(UAVs)are harnessed for various promising applications in a coordinated manner.Although it poses numerous advantages,resource management among various domains in large-scale UAV communication networks is the key challenge to be solved urgently.Specifically,due to the inherent requirements and future development trend,distributed resource management is suitable.In this article,we investigate the resource management problem for large-scale UAV communication networks from game-theoretic perspective which are exactly coincident with the distributed and autonomous manner.By exploring the inherent features,the distinctive challenges are discussed.Then,we explore several gametheoretic models that not only combat the challenges but also have broad application prospects.We provide the basics of each game-theoretic model and discuss the potential applications for resource management in large-scale UAV communication networks.Specifically,mean-field game,graphical game,Stackelberg game,coalition game and potential game are included.After that,we propose two innovative case studies to highlight the feasibility of such novel game-theoretic models.Finally,we give some future research directions to shed light on future opportunities and applications.

Optimizing Decision-Making of A Smart Prosumer Microgrid Using Simulation

Distributed renewable energy sources offer significant alternatives for Qatar and the Arab Gulf region’s future fuel supply and demand.Microgrids are essential for providing dependable power in difficult-to-reach areas while incorporating significant amounts of renewable energy sources.In energy-efficient data centers,distributed generation can be used to meet the facility’s overall power needs.This study primarily focuses on the best energy management practices for a smart microgrid in Qatar while taking demandside load management into account.This article looked into a university microgrid in Qatar that primarily aimed to get all of its energy from the grid.While diesel generators are categorized as a dispatchable distributed generation with energy storage added to handle solar radiation from the sun and high grid power operating costs in the suggested scenario,wind turbines and solar Photovoltaic(PV)are classified as non-dispatchable distributed generators.The resulting linear math issues are assessed and displayed in MATLAB optimization software using a mixed-integer linear programming(MILP)strategy.According to the simulation results,the suggested energy management strategy reduced the university microgrid’s grid power costs by 38.8%,making it an affordable solution which is somehow greater than the prior case scenario’s 23%savings.The installed solar system capacity’s effects on the economy,society,and finances were also assessed,and it became clear that the best option for the smart microgrid was determined that would be 325 kW of solar PV,25 kW of wind turbine,and 600 kW of diesel generators,respectively.Given the current situation,university administrators are urged to participate in distributed generators and adopt cutting-edge designs for energy storage technologies due to the significant environmental and financial benefits.

Implementation of GIS and Geographic RDBMS Prototype for Water Resources Management. Zeuss-Koutine Basin (South of Tunisia)

The scarcity of shallow water, which is a delicate matter in southern Tunisia, is relatively compensated by groundwater resources. Indeed, the South contains 25% of water reserves of the country whom 10% are superficial water. The different hydrogeological studies show that the Zeuss-Koutine region is composed of several aquifer systems, which may be subdivided into two distinct levels;a superficial and a deep one. Such water resources show signs of localized over- exploitation which has a serious effect on the change of the hydrosystem characteristics in this region. Recently, Tunisia proves to be very interested in the contribution of new technology in particular Geographic Information System (GIS) to resolve the problem of water resources deficit in Tunisia essentially in semiarid southern part, in addition to the increased exploitation of groundwater resources, not renewable basically in last years. Hence, preserving water resources in the short and long term is a must. This fact might be achieved by the geographical information system (GIS). To respond to this object, detailed hydrological and hydrogeological studies are efficient, and a Geographic Relational Data Base Management System (RDBMS) by MERISE model was created in this study for organization of all these data in a structured way (method) and was easily exploitable under it. In addition, a lithostratigraphic correlation by the GIS is very important for understanding of the aquifer geometry and hydrodynamic interactions. The correlation among multi data shows a high degradation increasing from the South to the North (both quality and quantity of the Zeuss-Koutine groundwater). That is why another study of the water quality (salinity) and exploitation is considered crucial.

Research on logistics domain-oriented cloud resource management model and architecture

To address the challenges posed by resource shortage or surplus to enterprises productivity,Internet platforms have been widely used,which can balance shortage and surplus in broader environments. However,the existing resource management models lack openness,sharing ability and scalability,which make it difficult for many heterogeneous resources to co-exist in the same system. It is also difficult to resolve the conflicts between distributed self-management and centralized scheduling in the system. This paper analyzes the characteristics of resources in the distributed environment and proposes a new resource management architecture by considering the resource aggregation capacity of cloud computing. The architecture includes a universal resource scheduling optimization model which has been applied successfully in double-district multi-ship-scheduling multi-container-yard empty containers transporting of international shipping logistics. Applications in all these domains prove that this new resource management architecture is feasible and can achieve the expected effect.

Resource Schedule in Grid Based on Market Models

A new modern resource management method based on economic model is proposed. Giving mathematic description about economic model; analysis different resource scheduling methods based on deadline and budget constrained which present by Buyya, point out shortcoming of Buyya's schedule method. Considerate integrate factor of time and budget, by import a weight coefficient named a , puts forward a new resource schedule method named STPP based on economic models of Buyya. Contrast to old schedule strategy of Buyya through analysis and experiments, STPP policy is more flexible, and is easy to import other new QoS parameters.

Comparison and Assessment of Success of Models in Watershed Simulation and Management

In Jordan, Zarqa River Basin (ZRB) has been taken as a case study for applying water management models because of its limited water resources and due to the fact that the basin is dwelling with about 52% of Jordan’s population. The surface water resources are mainly used for agriculture because they are mixed with treated water and cannot be used for domestic purposes. This paper aims to demonstrate the contributions of Models in watershed management that provide indirect ways of assessing and confirming the success of models in water flow simulation. The method includes transferring the computed hydrologic parameters for Zarqa basin’s sub-catchments within Watershed Modeling System (WMS) into Water Resources Model (WRM) and HEC-1 models. Then the results of the HEC-1 and WRM models are compared according to their basin’s simulation with the real basin. The study includes description of the HEC-1, WRM models philosophy, the models representation, and simulation results and analysis of the Zarqa River Basin. Comparing the results of WRM and HEC-1 models proved their simulation efficiency in predicting the flow of Zarqa River Basin. Nevertheless, the philosophy of HEC-1 is a single storm event and is based on values of curve number, while WRM philosophy describes the water flow and availability, and demand and supply balance on a daily basis across the basin. The models’ predictions for the real flow definitely establish the modeling certainty and help the water resources’ developers to incorporate different basin features for watershed representation, simulation, and management. Hence, the certainty of the results in modeling provides indirect ways of assessing the success of models’ simulations.

Analysis of River Tributaries’ Streamflow Contribution Using WEAP Model: A Case of the Ngwerere and Kanakatampa Tributaries to the Chongwe River in Zambia

Ngwerere and Kanakatampa Streams are the main tributaries of the Chongwe River. The Ngwerere stream originates from the city of Lusaka and meanders through Lusaka City and Chongwe Town for an approximate distance of 41 km before joining into the upper part of Chongwe River. The Kanakatampa Stream is a tributary of the Chongwe River. It meanders from the Kanakatampa Area for approximately 52 km before discharging into the middle of the upper part of the Chongwe River. The Chongwe River Catchment which is a sub-catchment of the Zambezi Basin drew the attention of researchers and policymakers when the Chongwe River started drying up in the dry seasons causing a water crisis particularly in the downstream regions of the middle catchment. Therefore, it is important from the water resources management perspective, to assess the contribution of tributaries into the flows of the Chongwe River. Ngwerere and Kanakatampa streams are socially, economically, and environmentally important streams for the city of Lusaka and surrounding area. This study, therefore, concentrated on evaluating the flow contribution of the two streams to the Chongwe River using the Water Evaluation And Planning (WEAP) tool. The streamflow data (1970-2010) recorded at the Chongwe Great East Road Bridge gauging station were used in the WEAP embedded Parameter ESTimation (PEST) auto-calibration tool to calibrate (1970-1999) and validate (2000-2010) the model. The monthly streamflow model calibration and validation results were assessed using the correlation coefficient (CC), Coefficient of determination (R2), Nash-Sutcliffe Coefficient of Efficiency (NSE), and Percent bias (PBIAS). The model performance results achieved were PBIAS of 1.24%, CC = 0.81, R2 = 0.66 and NSE = 0.62 during the calibration period and a positive PBIAS of 2.94%, CC = 0.81, R2 = 0.67 and NSE = 0.62 during the validation period. The median of the flows (Q50) was obtained from the historical flow duration curves (FDCs) generated in averaged intervals of 10-year from 1970 to 2019. The results showed that on average, the Ngwerere and Kanakatampa Streams contribute 52.8% and 29.6% respectively, to the flow of the Chongwe River in the upper and middle Catchment. The results also showed that the contribution of the Ngwerere and Kanakatampa Streams to the Chongwe River discharge has been reducing historically at a rate of 0.65% per decade and 1.35% per decade respectively over a period of 50 years (1970-2019). Suggestions for sustainable management of the tributaries such as the Ngwerere and Kanakatampa Streams were provided in this study.

Efficient Energy-Aware Resource Management Model(EEARMM)Based Dynamic VM Migration

In cloud environment,an efficient resource management establishes the allocation of computational resources of cloud service providers to the requests of users for meeting the user’s demands.The proficient resource management and work allocation determines the accomplishment of the cloud infrastructure.However,it is very difficult to persuade the objectives of the Cloud Service Providers(CSPs)and end users in an impulsive cloud domain with random changes of workloads,huge resource availability and complicated service policies to handle them,With that note,this paper attempts to present an Efficient Energy-Aware Resource Management Model(EEARMM)that works in a decentralized manner.Moreover,the model involves in reducing the number of migrations by definite workload management for efficient resource utilization.That is,it makes an effort to reduce the amount of physical devices utilized for load balancing with certain resource and energy consumption management of every machine.The Estimation Model Algorithm(EMA)is given for determining the virtual machine migration.Further,VM-Selection Algorithm(SA)is also provided for choosing the appropriate VM to migrate for resource management.By the incorporation of these algorithms,overloading of VM instances can be avoided and energy efficiency can be improved considerably.The performance evaluation and comparative analysis,based on the dynamic workloads in different factors provides evidence to the efficiency,feasibility and scalability of the proposed model in cloud domain with high rate of resources and workload management.

Robust Resource Management Control for CO2 Emission and Reduction of Greenhouse Effect: Stochastic Game Approach

With the increasingly severe global warming, investments in clean technology, reforestation and political action have been studied to reduce CO2 emission. In this study, a nonlinear stochastic model is proposed to describe the dynamics of CO2 emission with control inputs: clean technology, reforestation and carbon tax, under stochastic uncertainties. For the efficient resources management, a robust tracking control is designed to force resources tracking a desired reference output. The worst-case effect of stochastic parametric fluctuations, external disturbances and uncertain initial conditions on the tracking performance is considered and minimized from the dynamic game theory perspective. This stochastic game problem, in which one player (stochastic uncertainty) maximizes the tracking error and another player (control input) minimizes the tracking error, could be equivalent to a robust minimax tracking problem. To avoid solving the HJI, a fuzzy model is proposed to approximate the nonlinear CO2 emission model. Then the nonlinear stochastic game problem could be easily solved by fuzzy stochastic game approach via LMI technique.