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检索条件"任意字段=21st International Conference on Distributed Computing and Intelligent Technology"

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intelligent Evaluation Method for Urban Public Space in the Big Data Era

Intelligent Evaluation Method for Urban Public Space in the ...

引用

international conference on Smart Grid and Electrical Automation (ICSGEA)

作者： Jia, Zhuang Nanjing Forestry Univ Nanjing 210037 Jiangsu Peoples R China

ISBN: (纸本)9781538628133

One of the key issues in unban public space design is how to establish an evaluation system for its usage. The modernization for urban public space management cannot be achieved without the decision support service by intelligent evaluation system. In the 21st century, more attention has been paid to human activities and needs in public space design, and with the development of mobile information technology, it become possible to have access to a large number of network data (social network, theme website, or search engines etc.), reflecting urban space quality and people's behavior characteristics. Based on the idea of Big Data, which uses cloud computing, this paper attempts to establish an intelligent evaluation method for urban public space by means of mobile information devices such as GPS, intelligent phone, social network, IC card and RFID communication technology.

关键词： big data public space intelligent evaluation system

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Is Open-Source Software Valuable for Software Defect Prediction of Proprietary Software and Vice Versa? 1st

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1st international conference on Soft computing: Theories and Applications, SoCTA 2016

作者： Kakkar, Misha Jain, Sarika Bansal, Abhay Grover, P.S. Department of Computer Science & Engineering Amity University Uttar Pradesh NoidaUttar Pradesh India Amity Institute of Information Technology Amity University Uttar Pradesh NoidaUttar Pradesh India KIIT Group of Colleges Gurugram India

ISBN: (纸本)9789811056864

Software Defect Prediction (SDP) models are used to identify the defect prone artifacts in a project to assist testing experts and better resource utilization. It is simple to build a SDP model for a project having historical data available. The problem arises when we want to build SDP model for a project, which has limited or no historical data available. In this paper, we have tried to find out whether data from Open-Source Software (OSS) projects is helpful in building SDP model for proprietary software having no or limited historical data. For collection of data for training SDP model a tool is developed which extract metric data from open-source software projects source codes. Three-benchmarked dataset from NASA projects are used as proprietary software dataset for which software defects are predicted. machine learning algorithms: LR, kNN, Naïve Bayes, Neural Network, SVM, and Random Forest are used to build SDP models. Using popular performance indicators such as precision, recall, F-measure, etc., the performances of these six SDP models are compared. The study concluded that when SDP models are trained using data from OSS projects then they are able to predict software defects for proprietary software with greater accuracy in comparison to SDP models predicting defects for OSS projects when trained using proprietary software data. © 2018, Springer Nature Singapore Pte Ltd.

关键词： Open source software

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Regression algorithms for efficient detection and prediction of DDoS attacks 3

Regression algorithms for efficient detection and prediction...

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3rd international conference on Applied and Theoretical computing and Communication technology (iCATccT)

作者： Dayanandam, Gudipudi. Reddy, E. Srinivasa Babu, Dasari. Bujji ANUCET Dept CSE Guntur India ANUCET Guntur India QISCET Dept MCA Ongole India

ISBN: (纸本)9781538611449

In the ICT era the need of depth investigation and analysis is required on network traffic. The analysis should focus on detecting DDoS attacks. In the 21st century the use of communication or transactions arc completely doing through online, the political activists, and international cyber terrorists are choosing the DDoS attacks as a powerful weapon for their illegal an un ethical activities. It is impossible to the human being to identify all these unethical activities, hence the need of machine based algorithms are required. In this paper we used GLM, GBM, NN, RF regression algorithms for detection and prediction of DDoS attacks, and also proved that by using regression algorithms we observed more accurate result than using KNN SVM algorithm.

关键词： distributed Denial of Service (DDoS) Machine learning smurf attacks Random Forest (RE) Neural Networks (NN) Generalized Linear Models (GLM) and stochastic Gradient Boosting (GBM)

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Constrained Power Loss Minimization of DC Microgrid Using Particle Swarm Optimization 1st

Constrained Power Loss Minimization of DC Microgrid Using Pa...

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1st international conference on Data Engineering and Communication technology (ICDECT)

作者： Angalaeswari, S. Jamuna, K. VIT Univ Sch Elect & Elect Engn Chennai Campus Madras Tamil Nadu India

ISBN: (纸本)9789811016752;9789811016745

The optimal power flow has been considered as the important issue in the power system network. There are many ways to optimize the power flow out of which power loss minimization and voltage profile improvement are considered as the efficient ways. The power loss minimization for distributed system has been performed with particle swarm optimization (PSO) algorithm and the results are compared with forward/backward load flow method. The analysis is also performed with and without addition of renewable sources. The results show that the inclusion of DG at various buses reduces the power loss and improves the voltage magnitude profile

关键词： Microgrid distributed generation Particle swarm optimization (PSO)

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Research on Real Time Processing and intelligent Analysis technology of Power Big Data 2017

Research on Real Time Processing and Intelligent Analysis Te...

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international conference on Big Data and Internet of Things (BDIOT)

作者： Xue, Jiarui Chen, Xiangzhou Ding, Huixia He, Xiao China Univ Min & Technol Beijing 11st Coll Rd Beijing 100089 Peoples R China China Elect Power Res Inst 15th Xiaoyingdong Rd Beijing 100085 Peoples R China ENSEA 6 Ave Ponceau F-95014 Cergy Pontoise France

ISBN: (纸本)9781450354301

This paper focuses on the research of all kinds of data in the power grid business system, and carries on the research of intelligent analysis technology. It focuses on breaking the technical difficulties of intelligent and efficient analysis and mining, distributed multi-stream real-time processing, developing large-scale stock data for power and high-frequency incremental data efficient analysis system prototype, for wide-area distributed multi-stream real-time computing, from the data quick access to valuable information to solve the problems in the grid business system to improve the overall business performance, to achieve support power Data real-time processing and other technology applications.

关键词： data information intelligence data flow distributed

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Challenges and Benefits of Deploying Big Data Analytics in the Cloud for Business Intelligence 21

Challenges and Benefits of Deploying Big Data Analytics in t...

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21st international conference on Knowledge - Based and intelligent Information and Engineering Systems (KES)

作者： Balachandran, Bala M. Prasad, Shivika Univ South Pacific Sch Comp Informat & Math Sci Fac FSTE Laucala Campus Suva Fiji

Cloud computing and big data analytics are, without a doubt, two of the most important technologies to enter the mainstream IT industry in recent years. Surprisingly, the two technologies are coming together to deliver powerful results and benefits for businesses. Cloud computing is already changing the way IT services are provided by so called cloud companies and how businesses and users interact with IT resources. Big Data is a data analysis methodology enables by recent advances in information and communications technology. However, big data analysis requires a huge amount of computing resources making adoption costs of big data technology is not affordable for many small to medium enterprises. In this paper, we outline the the benefits and challenges involved in deploying big data analytics through cloud computing. We argue that cloud computing can support the storage and computing requirements of big data analytics. We discuss how the consolidation of these two dominant technologies can enhance the process of big data mining enabling businesses to improve decision-making processes. We also highlight the issues and risks that should be addressed when using a so called CLaaS, cloud-based service model. (C) 2017 The Authors. Published by Elsevier B.V.

关键词： Cloud computing Big Data Analytics Cloud Analytics Security Privacy Business Intelligence MapReduce AaaS CLaaS

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Energy Efficient Cluster Head Selection in Energy-LEACH

Energy Efficient Cluster Head Selection in Energy-LEACH

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international conference on Communication on Networks (COMNET)

作者： Pambhar, Hiral Aghera, Kausa Tada, Naren VVP Engn Coll Rajkot Gujarat India

ISBN: (纸本)9789811027505;9789811027499

Wireless sensor network (WSN) is all time researched area as well as new concepts are introduced frequently. Here we will consider the hierarchical clustering routing protocol called LEACH and its variant as E-LEACH (energy leach). There may be a case in E-LEACH that selected cluster heads may be accumulated in certain specific area (or not distributed) due the consideration of only residual energy. Our proposed method includes the consideration of residual energy as well as selected cluster heads to be distributed in the entire wireless network. This balance load and increase the network life time.

关键词： Load balancing distributed cluster heads (CHs) Residual energy Energy efficient protocol Cluster heads (CHs) selection

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distributed Clustering Scheme to Relieving Broadcast storms in Vehicular Ad-Hoc Network 16th

Distributed Clustering Scheme to Relieving Broadcast Storms ...

引用

16th international conference on Hybrid intelligent Systems (HIS) / 8th World Congress on Nature and Biologically Inspired computing (NaBIC)

作者： Touil, Abdelali Ghadi, Fattehallah Ibn Zohr Univ Dept Comp Sci Lab Engn Sci LabSI Fac Sci BP 8106 Agadir Morocco

ISBN: (纸本)9783319529417;9783319529400

Nowadays, intelligent Transportation Systems (ITS) aim to reduce accidents, fuel consumption and roads congestion, for this reason Vehicular Ad-hoc Networks (VANETs) technology as special case of ITS represent the future of the smart vehicles, the use of this one in order to improve road traffic safety will be great challenge. As can be seen, the number of cars worldwide is growing day after day. The deployment of VANETs technology which is composed of several types of communications has interested many researchers. So that to stabilize and handle this number of vehicles, we have focused our search on Quality of Service (QoS) and increased packet delivery ratio between vehicles by implementing Clustering scheme. This paper describes a new distributed algorithm connectivity-based to form stable clusters. To evaluate our proposal scheme, we have conducted various simulations in OMNeT++ and SUMO simulators. The obtained results are promising in terms of packet delivery ratio and overhead.

关键词： VANETs Dynamic clustering Connectivity stability CH election QoS

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Implementation of DstC and PSO Algorithm Using CLD to Improve the Performance of MANET 1st

Implementation of DSTC and PSO Algorithm Using CLD to Improv...

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1st international conference on Data Engineering and Communication technology (ICDECT)

作者： Bhale, Sheetal Mishra, Abhilasha Khan, Mazher GS Mandals Marathwada Inst Technol Aurangabad Maharashtra India

ISBN: (纸本)9789811016752;9789811016745

Throughput is a valuable parameter for mobile ad hoc network (MANET), it is defined as a number of successfully received packets in a unit interval of time. In wireless communication for the extension of coverage as well as capacity MANET is used. In this paper cross-layer is designed between physical and network layer using received signal strength (RSS) as a cross-layer interaction parameter. The given technique proposes strong route formation in ad hoc on-demand distance vector (AODV) through cross-layer design (CLD), distributed space-time coding (DstC), and particle swarm optimization (PSO) in MANET. The simulation results show the improvement in performance of MANET.

关键词： Mobile ad hoc network (MANET) Ad hoc on-demand distance vector (AODV) Cross layer design (CLD) distributed space-time coding (DstC) Particle swarm optimization (PSO)

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Issues with DCR and NLSR in Named-Based Routing Protocol 1st

Issues with DCR and NLSR in Named-Based Routing Protocol

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1st international conference on Data Engineering and Communication technology (ICDECT)

作者： Goyal, Rajeev Goyal, Samta Jain Amity Univ Gwalior Madhya Pradesh India

ISBN: (纸本)9789811016783;9789811016776

Content-based routing, which is under a category of sophisticated routing protocol, is used to propose a routing protocol that can replace Internet protocol. Content-based routing is used to querying, fetching, and finding desired information where in the other routing based system;they forwarded the packets on DNS or data senses. Main issues with the past were constraints of the storage. We have seen in some papers that name-based routing is feasible to achieve content-based routing.

关键词： Content based routing Information centric network Named based content routing Fully qualified domain name Distance-based content routing Named-data link state routing protocol distributed hash tables

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