基于Community Intelligence的水电机组融合监测方法

介绍了基于CIA(Community Intelligence Agent)模型的水电机组融合监测框架:CIA模型包含消息处理层、行为控制层及核心功能层3个层次,各CIA与外界(如其他CIA)通过Request消息或Report消息联系;融合监测框架由维护域CIA系统和控制域CIA系统构成,维护域CIA系统各CIA之间通过实时现场总线(如CAN总线)或工业以太网实现交互、协作、关联动作及数据共享。将整个机组的状态数据划分为原始采样数据、瞬变状态数据、详细状态数据及概要状态数据4个层次,并针对不同层次的状态数据,进行选择性智能存储,以提高机组运动状态分析和故障诊断的针对性及有效性,节约存储空间。通过时间融合、运行工况融合、异常事件融合和冲突解决策略,实现融合监测系统中各CIA之间实时交互、协作及关联动作和机组状态数据的融合,有效地保证来自机组不同子系统的运动状态的关联性。

Effect of Community Interventions on Intelligence Development of Infants

Objective To assess the interventions effect on intelligence of the infants through the community. Methods A total of 309 newborns and their families were recruited in Xuhui district, Shanghai. They were asked to fill out the baseline questionnaires. The newborns＇ intelligence quotients were measured by Developmental Screening Test for Child Under Six, and physical examinations were conducted at the same time. The newborns were randomly assigned to intervention group （156 cases） and control group （153 cases）. The infants and their families were followed up every 6 months. A questionnaire of follow-up was completed by face-to-face interview at the communities and infant intelligence quotients were measured and had their physical check-ups again at the end of the 6th month. Results After 6 months＇ intervention, the means of MI and DQ in the intervention group were respectively 5.96 and 9.80 higher than those in control group after adjustment of the baseline scores. Conclusion Early intelligence education in the community may promote the intelligence development of infants.

The Influence Factors of Collective Intelligence Emergence in Knowledge Communities Based on Social Network Analysis

The advent of the age of Information shifts the environment we live in from off-line to on-line. The prospect of Collective Intelligence (CI) is promising. Based on this background, the aim of this paper is to discover the emergence mechanism and influence factors of CI in knowledge communities using the method of quantitative and qualitative analysis. On the basis of the previous research work, our model theorizes that the two dimensions of social network (i.e., interactive network structure and participant’s characteristics) affect two references of effectiveness (i.e. group knowledge production and participation of group decision). And this hypothetical model is validated with simulation data from “Zhihu” community. Our model has been useful since it offers some inspirations and directions to promote the level of CI in knowledge communities.

Analysis of on Intelligent Community Based on Multi-Living Agent

A new research method for intelligent community based on multi-living agent was presented. The intelligent community system architecture and the application specific intellectual endowment were analyzed in the paper. The prevalence of islands of information on data integration solution was given. This method can improve the integration of intelligent community and accelerate the development speed of the intelligent community.

Design of Remote Control System of Intelligent Community Based on Embedded Web Server

A multichannel remote control system for imelligent community based on the STC89C54 chip was designed with the technique of embedded Web server. The control system can monitor 255 signals and eight control signals of one node at the same time, and can be connected to the internet by the TCP/IP protocol. So the field control information can be shown dynamically in a remote computer by way of web pages. The system has high convenience and friendly monitoring interface, then especially is fit for the large conamunity and storage that need multipoint monitoring and frequent switching door.

Discrete Improved Grey Wolf Optimizer for Community Detection

Detecting communities in real and complex networks is a highly contested topic in network analysis.Although many metaheuristic-based algorithms for community detection have been proposed,they still cannot effectively fulfill large-scale and real-world networks.Thus,this paper presents a new discrete version of the Improved Grey Wolf Optimizer(I-GWO)algorithm named DI-GWOCD for effectively detecting communities of different networks.In the proposed DI-GWOCD algorithm,I-GWO is first armed using a local search strategy to discover and improve nodes placed in improper communities and increase its ability to search for a better solution.Then a novel Binary Distance Vector(BDV)is introduced to calculate the wolves’distances and adapt I-GWO for solving the discrete community detection problem.The performance of the proposed DI-GWOCD was evaluated in terms of modularity,NMI,and the number of detected communities conducted by some well-known real-world network datasets.The experimental results were compared with the state-of-the-art algorithms and statistically analyzed using the Friedman and Wilcoxon tests.The comparison and the statistical analysis show that the proposed DI-GWOCD can detect the communities with higher quality than other comparative algorithms.

Community Detection Applications in Mobile Networks:Towards Data-Driven Design for Next Generation Cellular Networks

The existing radio access network(RAN)is facing many challenges to meet the very strict speed and latency requirements by different mobile applications in addition to the increasing pressure to reduce operating cost.Innovation and development in RAN have been accelerated to tackle these challenges and to define how next generation mobile networks should look like.The role of machine learning(ML)and artificial intelligence(AI)driven innovations within the RAN domain is strengthening and attracting lots of attention to tackle many of the challenging problems.In this paper we surveyed RAN network base stations(BSs)clustering and its applications in the literature.The paper also demonstrates how to leverage community detection algorithms to understand underlying community structures within RAN.Tracking areas(TAs)novel framework was developed by adapting existing community detection algorithm to solve the problem of statically partitioning a set of BSs into TA according to mobility patterns.Finally,live network dataset in dense urban part of Cairo is used to assess how the developed framework is used to partition this part of the network more efficiently compared to other clustering techniques.Results obtained showed that the new methodology saved up to 34.6%of inter TA signaling overhead and surpassing other conventional clustering algorithms.

Intelligent health in the IS area:A literature review and research agenda

As the global demand for healthcare services continues to grow,improving the efficiency and effectiveness of the healthcare ecosystem has become a pressing concern.Information systems are transforming the healthcare delivery process,shifting the focus of healthcare services from passive disease treatment to proactive health prevention and the healthcare management model from hospital-centric to patient-centric.This study focuses on reviewing research in IS journals on the topic of e-health and is dedicated to constructing a theoretical model of intelligent health to provide a research basis for future discussions in this field.In addition,as the innovation of intelligent healthcare services has led to changes in its elements(e.g.,an increase in the number of stakeholders),there is an urgent need to sort out and analyze the existing research.

TOWARD COLLECTIVE INTELLIGENCE OF ONLINE COMMUNITIES:A PRIMITIVE CONCEPTUAL MODEL

Inspired by the ideas of Swarm Intelligence and the ＂global brain＂, a concept of ＂community intelligence＂ is suggested in the present paper, reflecting that some ＂intelligent＂ features may emerge in a Web-mediated online community from interactions and knowledge-transmissions between the community members. This possible research field of community intelligence is then examined under the backgrounds of ＂community＂ and ＂intelligence＂ researches. Furthermore, a conceptual model of community intelligence is developed from two views. From the structural view, the community intelligent system is modeled as a knowledge supernetwork that is comprised of triple interwoven networks of the media network, the human network, and the knowledge network. Furthermore, based on a dyad of knowledge in two forms of ＂knowing＂ and ＂knoware＂, the dynamic view describes the basic mechanics of the formation and evolution of ＂community intelligence＂. A few relevant research issues are shortly discussed on the basis of the proposed conceptual model.

Development of community health service-oriented computer-assisted information system for diagnosis and treatment of respiratory diseases

Objective:Community health services are an emerging trend.We have found in practice that diagnosis and treatment of respiratory diseases in the community are distinct.The respiratory department’s daily work involves a number of outpatient registration items and a vast workload.The routine manual operation is inefficient and it is not convenient to make effective statistical analysis of the outpatient data to identify the risk factors closely related to diseases.Therefore,it is imperative to process the outpatient information of patients with respiratory diseases effectively and efficiently in a unified manner by means of computer technology.Methods:The design and realization of the Community Health Service-oriented computerassisted Information System for Diagnosis and Treatment of Respiratory Diseases(CHS-DTRD)was completed as part of the community intervention study on bronchial asthma that was carried out jointly by the Nanjing First Hospital Affiliated to Nanjing Medical University and the Hospital of Nanjing University of Science&Technology,and based on 2 years of experience and the needs of an overall analysis.Results:The computer-assisted information system for diagnosis and treatment was developed using Java Server Page(JSP)technology and introducing the advanced Asynchronous JavaScript XML(AJAX)technique and MS-SQL Server was used in the background database.CHS-DTRD was composed of eight functional modules(outpatient data maintenance,outpatient appointment,intelligent analysis for disease risk factors,query and statistics,data dictionary maintenance,database manipulation,access control,and system configuration).CHS-DTRD featured a friendly interface,convenient operation,and stability and reliability.Conclusion:Community health-oriented diagnosis and treatment of respiratory diseases is simple,programmable,and intuitive,thus the workload of physicians is significantly reduced and the work efficiency is improved.This system facilitates an intelligent analysis of disease risk factors using data mining technology,and provides physicians with suggestions on intelligent analysis for diagnosis of disease and conclusion of disease causes.

Evolutionary Game-theoretic Analysis for Residential Users Considering Integrated Demand Response

As an important part of demand side,residential users have the characteristics of imperfect rationality and strong randomness,which are rarely considered in the existing study.Moreover,to effectively improve the energy efficiency,integrated demand response(IDR)is proposed as an effective measure to reduce the local energy supply pressure.This paper focuses on a scenario for IDR programs,in which the intelligent building aggregator(IBA)wants to encourage residential users to participate in IDR according to a proper contract price policy.To analyze how the participation degree tendency evolves over time,an evolutionary game approach is proposed considering residential users’bounded-rationality.A symmetric evolutionary game model and an asymmetric evolutionary game model are established,and the stability of equilibrium points in the above models is proven.Simulation results show that different contract price policies will obviously influence residential users’strategy,and affect the stable equilibrium points of the evolutionary game.The simulation results provide an effective reference for IBA to set proper and effective price incentives.

A new hybrid AI optimal management method for renewable energycommunities

In this study, we propose a hybrid AI optimal method to improve the efficiency of energy managementin a smart grid such as Renewable Energy Community. This method adopts a Time Delay Neural Networkto forecast the future values of the energy features in the community. Then, these forecasts are used by astochastic Model Predictive Control to optimize the community operations with a proper control strategy ofBattery Energy Storage System. The results of the predictions performed on a public dataset with a predictionhorizon of 24 h return a Mean Absolute Error of 1.60 kW, 2.15 kW, and 0.30 kW for photovoltaic generation,total energy consumption, and common services, respectively. The model predictive control fed with suchpredictions generates maximum income compared to the competitors. The total income is increased by 18.72%compared to utilizing the same management system without exploiting predictions from a forecasting method.

Appraisal of the Production-Oriented Approach： An Introduction

The production-oriented approach （POA） has been developed over a decade. It is driven by the need to improve English classroom instruction for university students in China （Wen, 2016）. It is also motivated by the aspiration to enhance the quality of foreign language education in other similar pedagogical contexts outside China. A volume of research has been done by Wen Qiufang and her research team, to formulate the theory of POA and to test its effectiveness in classroom pedagogy （e.g. Wen, 2016, 2015; Yang, 2015; Zhang, 2015）. At the moment, the POA is still at an early stage of theory building and almost all empirical research is done in the Chinese context. In order to improve the quality of this theory and to make it intelligible to the international academic community, a one-day symposium was held in Beijing Foreign Studies University on May 15, 2017. The symposium was entitled ＇The first international forum on innovative foreign language education in China： Appraisal of the POA＇. In the forum, leading experts in applied linguistics were invited to discuss the strengths and weaknesses of the POA and the directions for its future development. The symposium was the first attempt for the POA research team to discuss its latest work with international scholars. This Viewpoint section collects the responses of four experts who participated in the symposium, listed in alphabetical order. The collection of articles covers three topics related to the POA： its pedagogical application, its use for teacher training, and its research. Alister Cumming is Professor Emeritus and the former Head of the Centre for Educational Research on Languages and Literacies, University of Toronto, Canada. His article focuses primarily on POA research as an exemplary case of design-based research. Rod Ellis is Research Professor in the School of Education at Curtin University, Australia. He discusses POA in terms of pedagogy, teacher training and research, with both critiques and constructive suggestions. Paul Kei Matsuda is Professor of English and Director of Second Language Writing at Arizona State University, the writed states. He responds to POA from the perspective of an expert researcher and teacher of L2 writing. Charlene Polio is Professor and Associate Chair in the Department of Linguistics ＆ Germanic, Slavic, Asian ＆ African Languages atMichigan State University, the writed states. She conceptualises POA as a useful method to address some issues in pre-service teacher development. Overall, the articles in this section are insightful and reader-friendly. They are not only useful for the development of POA in particular, but may also be valuable to a broad range of researchers as they touch upon pertaining issues, as well as emerging topics, in the field of applied linguistics. We therefore find it necessary to make them accessible to a wide readership.