Study on the Development of Human Resources Services in Xinxiang

With the continuous economic growth,human resources service industry also plays an important role in the economic development.In order to explore the development of human resources service industry in Xinxiang,based on a survey of more than 50 enterprises and organizations in Xinxiang,Xinxiang’s human resources service industry has a bright future,however,there are still some problems in the aspects of enterprise scale,personnel skills and agglomeration management.Therefore,different countermeasures are put forward for different roles to solve the development obstacles and promote the development of industry agglomeration,building a new type of human resources to serve the ecological industry chain.

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.

A Novel Architecture of Metadata Management System Based on Intelligent Cache

This paper introduces a novel architecture of metadata management system based on intelligent cache called Metadata Intelligent Cache Controller （MICC）. By using an intelligent cache to control the metadata system, MICC can deal with different scenarios such as splitting and merging of queries into sub-queries for available metadata sets in local, in order to reduce access time of remote queries. Application can find results patially from local cache and the remaining portion of the metadata that can be fetched from remote locations. Using the existing metadata, it can not only enhance the fault tolerance and load balancing of system effectively, but also improve the efficiency of access while ensuring the access quality.

General review of National Digital Library development in the National Library of China

As an important part of National Digital Library(NDL),the National Digital Library Project(NDLP),which was launched in 2005,has attracted wide attention of the society in general.This paper introduces the general situation of the project from the following aspects,namely,the characteristics,objectives and contents.It also expounds on the basic ideas and the overall structure of the project and gives an introduction to the design of its basic platform,its application platform,its business management system and its standardization control system.In this paper,the digital resources construction and service delivery of the National Library of China(NLC)are introduced to cover both its present operation as well as those in conjunction with the opening of its new library building during its second-phase of library development.Finally,the most important and difficult point in the construction of the National Digital Library Project is analyzed from the following four perspectives:1)The long-term preservation of digital resources;2)the construction of knowledge organization system;3)the organic integration of the digital library and the traditional library;and 4)the risk of project management and system integration.

Energy potential assessment and techno-economic analysis of micro hydro-photovoltaic hybrid system in Goda Warke village,Ethiopia

Rural Ethiopia has significant untapped potential for hydro and solar energy generation systems.However,challenges arise from seasonal variations and unfavourable topographic positions of flowing rivers,hindering the efficient exploitation of these resources.Despite the country’s abundance in hydro and solar energy resources,>75%of the population still lack access to electricity from the national grid.This work deals with energy resource potential assessment and techno-economic analysis of micro hydro-photovol-taic(PV)hybrid systems,considered in the case study of Goda Warke village,located in the Yaya Gulele district.A novel framework is proposed that utilizes the Natural Resource Soil Conservation Service curve number method to assess the energy potential of micro-hydro energy in ungauged basins,specifically at the exit point of the Girar River basin catchment.The average monthly flow rate in the basin is 0.975 m3/s,while the area exhibits a solar radiation potential of 5.39 kWh/m^(2)/day.Energy policy promotes expanding ac-cess to modern energy sources and utilization of indigenous energy resources.Simulation results indicate that the hydro/PV/diesel generator(DG)/battery and hydro/PV/battery systems are the most optimal choices based on net present cost,with the inclusion of a DG for economic comparison.Micro-hydro energy covers most of the electric load in the area,achieving a capacity factor of 47.5%.The cost of energy and net present cost were found to be sensitive to variables such as the price of diesel fuel,pipe head loss,and the growth of the village load.The optimized system demonstrated a hydro energy potential of 1405.37 MWh/year and a PV energy output of 274.04 MWh/year,resulting in a levelized cost of energy of 0.0057 and 0.049$/kWh for the hydro and PV components,respectively.

GSA and BIGD:Filling the Gap of Bioinformatics Resource and Service in China

In the 2017 first issue of this Journal - Genomes, Proteomes and Bioinformatics - a special database article entitled ＂GSA： Gen- ome Sequence Archive＂ is published. This article provides a brief introduction to the platform developed by the authors from the BIG Data Center （BIGD） of Beijing Institute of Genomics （BIG）, Chinese Academy of Sciences （CAS）. The aim of the GSA project is to collect, integrate, and archive raw sequence data submitted by domestic and international users. It is one of the major activities being carried on by a team of around 50 young bioinformaticians at BIGD. In addition to the GSA system, they are also working on several bioinformatics service-orientated projects as described in one of their recent publications .

The current status of community mental health services in three northern areas of China

Objective:This study investigated and discussed the current status of community mental health service in three northern areas of China(Beijing,Harbin,and Karamay)in an effort to improve the community mental health services in China.Methods:In this study 176 residents from communities of the three northern areas of China were involved and divided into 18 groups.The study was conducted according to a self-prepared structured interview outline.Results:The analysis was conducted based on the following four perspectives:1.commu-nity residents’understanding of the mental health problems and how they treated psychiatric patients;2.community residents’access to and application of mental health information;3.com-munity residents’attitude to accept mental health services and the factors influencing community residents to seek help from mental health services;and 4.community residents’attitude and will-ingness to participate in the activities of community mental health services.Conclusion:Based on the investigation and analysis regarding the current status of the com-munity mental health services in three northern areas of China,it is concluded that the residents do not have s clear and complete understanding of mental health.The characteristics of mental health services had a regional correlation.Currently,the mental health services do not work effectively,and the residents are somewhat passive in obtaining information about mental health.Community mental health services should be offered according to different individual needs of the residents and the actual situations of each region.

Load Feedback-Based Resource Scheduling and Dynamic Migration-Based Data Locality for Virtual Hadoop Clusters in OpenStack-Based Clouds

With cloud computing technology becoming more mature, it is essential to combine the big data processing tool Hadoop with the Infrastructure as a Service（Iaa S） cloud platform. In this study, we first propose a new Dynamic Hadoop Cluster on Iaa S（DHCI） architecture, which includes four key modules： monitoring,scheduling, Virtual Machine（VM） management, and VM migration modules. The load of both physical hosts and VMs is collected by the monitoring module and can be used to design resource scheduling and data locality solutions. Second, we present a simple load feedback-based resource scheduling scheme. The resource allocation can be avoided on overburdened physical hosts or the strong scalability of virtual cluster can be achieved by fluctuating the number of VMs. To improve the flexibility, we adopt the separated deployment of the computation and storage VMs in the DHCI architecture, which negatively impacts the data locality. Third, we reuse the method of VM migration and propose a dynamic migration-based data locality scheme using parallel computing entropy. We migrate the computation nodes to different host（s） or rack（s） where the corresponding storage nodes are deployed to satisfy the requirement of data locality. We evaluate our solutions in a realistic scenario based on Open Stack.Substantial experimental results demonstrate the effectiveness of our solutions that contribute to balance the workload and performance improvement, even under heavy-loaded cloud system conditions.

An Optimal Resource Provision Policy in Cloud Computing Based on Customer Profiles

Conventional resource provision algorithms focus on how to maximize resource utilization and meet a fixed constraint of response time which be written in service level agreement（SLA）.Unfortunately,the expected response time is highly variable and it is usually longer than the value of SLA.So,it leads to a poor resource utilization and unnecessary servers migration.We develop a framework for customer-driven dynamic resource allocation in cloud computing.Termed CDSMS（customer-driven service manage system）,and the framework’s contributions are twofold.First,it can reduce the total migration times by adjusting the value of parameters of response time dynamically according to customers’profiles.Second,it can choose a best resource provision algorithm automatically in different scenarios to improve resource utilization.Finally,we perform a serious experiment in a real cloud computing platform.Experimental results show that CDSMS provides a satisfactory solution for the prediction of expected response time and the interval period between two tasks and reduce the total resource usage cost.