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3rd international conference on Intelligent computing and Applications, ICICA 2016

3rd International Conference on Intelligent Computing and Ap...

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3rd international conference on Intelligent computing and Applications, ICICA 2016

ISBN: (纸本)9789811055195

The proceedings contain 59 papers. The special focus in this conference is on Intelligent computing and Applications. The topics include: Parallel palm print identification using fractional coefficients of palm edge transformed images on GPU;a secure spatial domain image steganography using genetic algorithm and linear congruential generator;Three-dimensional MRI brain image analysis on hadoop platform;performance evaluation of fingerprint trait authentication system;graphical password using an intuitive approach;a model of legal and procedural framework for cybercrime investigation in India using digital image forensics;comparative study of android-based M-Apps for farmers;Feature extraction of DICOM images using canny edge detection algorithm;design of 2-bit parallel asynchronous self-timed adder and 2-bit parallel adder using radix adder;block compressive sampling and wiener curvelet denoising approach for satellite images;efficient image secret sharing using parallel processing for row-wise encoding and decoding;TXGR: A reverse engineering tool to convert design patterns and application software into graph;Comparative analysis of image fusion using DCT, DST, DWT, walsh transform and kekre’s wavelet transform;ioT-based smart garbage management system;Event-driven SOA-based IoT architecture;FPGA implementation of AES algorithm for image, audio, and video signal;power extraction from small hydropower plant;enhancement of digital distance protection scheme with novel transducer;A hierarchical underwater wireless sensor network design for tracking ships approaching harbors using an aerial mobile sink (AMS) node;development of single and multi-jet conical nozzle based open jet facility for cold jet simulation;Neural deployment algorithm for WSN: A concept;energy-aware multi-objective differential evolution in cloud computing.

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Maximum Attribute Relative Approach of Soft Set Theory in Selecting Cluster Attribute of Electronic Government Data Set 3rd

Maximum Attribute Relative Approach of Soft Set Theory in Se...

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3rd international conference on Soft computing and Data Mining (SCDM)

作者： Jacob, Deden Witarsyah Yanto, Iwan Tri Riyadi Fudzee, Mohd Farhan Md Salamat, Mohamad Aizi Telkom Univ Dept Ind Engn Bandung West Java Indonesia Univ Ahmad Dahlan Dept Informat Syst Kampus 3 UADJalan Prof Dr Soepomo Yogyakarta Indonesia Univ Tun Hussein Onn Malaysia Fac Comp Sci & Informat Technol Parit Raja Johor Malaysia

ISBN: (纸本)9783319725505;9783319725499

Electronic government (e-government) is the use of information and communication technology to provide information and services for the citizen. Many researchers argue that it is very important to know what the dominant variable influences citizen in using e-government. A number studies have used empirical approach to know the variables, but very rarely use other technique such as data mining. One of the powerful data mining technique is Maximum Attribute Relative (MAR), the technique is based on a soft set theory by introducing the concept of the attribute relative in information systems. Therefore, we present the applicability of MAR for clustering attribute selection. The real data set is taken from a survey at Bandung District in Indonesia. A total 200 participants have jointed in this survey. Most respondents are female i.e. 105 persons and the rest are male i.e. 95 persons with alpha score yielded 0.846. At this stage of the research, we show how MAR can be used to select the best clustering and found that Facilitating Condition (FC) is the highest variable of the citizen behavior in adopting e-government service. Furthermore, the result also may potentially contribute to decision maker how to design a good e-government in order to reduce bureaucracy and further to improve public services.

关键词： Clustering Soft set theory Maximum attribute relative (MAR) e-Government Facilitating condition Effort expectancy Performance expectancy

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3rd workshop on advances in open runtime technology for cloud computing 19

3rd workshop on advances in open runtime technology for clou...

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proceedings of the 29th Annual international conference on Computer Science and Software Engineering

作者： Daryl Maier Xiaoli Liang Kenneth B. Kent IBM Canada Markham ON Canada University of New Brunswick Fredericton NB Canada

Modern language runtimes are complex, dynamic environments that involve a myriad of components that must work cooperatively to achieve the functional and performance requirements of a given language. Typical core runtime technologies include dynamic just-in-time compilers for performance, garbage collection for heap management, platform abstraction for ease of portability to different hardware and operating system environments, test infrastructure for quality control, developer tooling for diagnosis and tuning of the various components, and interoperability between different language *** services such as IBM Cloud or Amazon Web Services are increasingly becoming the environments where applications are developed, tested, and deployed, data are stored, and businesses are run. Many of the features that define a cloud (e.g. resiliency, elasticity, consistency, security) are realized through runtime technologies. Clouds are polyglot environments, and therefore advances in cloud development are directly driven by innovation in runtime technologies. However, cloud environments pose unique and often conflicting demands on runtime systems.that are generally less of a concern in isolated systems. Throughput performance (how many results can my application produce?), density (how many instances of my application can I create and run simultaneously in my provisioned environment?), startup performance (how quickly can I launch a new instance of my application?), and language interoperability are all examples of important considerations that require innovative *** goal of this workshop was to bring together industry and research communities to share and discuss ideas, challenges, and research results across a broad set of open-source runtime technologies (such as Eclipse OMR, LLVM, Eclipse OpenJ9, ***) for cloud environments. The focus on open technology solutions rather than proprietary was key as it allowed for greater collaboration amongst individu

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A tensor-based sub-mode coordinate algorithm for stock prediction 3

A tensor-based sub-mode coordinate algorithm for stock predi...

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3rd IEEE international conference on Data Science in Cyberspace, DSC 2018

作者： Huang, Jieyun Zhang, Yunjia Zhang, Jialai Zhang, Xi Key Laboratory of Trustworthy Distributed Computing and Service Ministry of Education Beijing University of Posts and Telecommunications Beijing China School of Electronic Information Sichuan University Chengdu China

ISBN: (纸本)9781538642108

The investment on the stock market is prone to be affected by the Internet. For the purpose of improving the prediction accuracy, we propose a multi-task stock prediction model that not only considers the stock correlations but also supports multi-source data fusion. Our proposed model first utilizes tensor to integrate the multi-sourced data, including financial Web news, investors' sentiments extracted from the social network and some quantitative data on stocks. In this way, the intrinsic relationships among different information sources can be captured, and meanwhile, multi-sourced information can be complemented to solve the data sparsity problem. Secondly, we propose an improved sub-mode coordinate algorithm (SMC). SMC is based on the stock similarity, aiming to reduce the variance of their subspace in each dimension produced by the tensor decomposition. The algorithm is able to improve the quality of the input features, and thus improves the prediction accuracy. And the paper utilizes the Long Short-Term Memory (LSTM) neural network model to predict the stock fluctuation trends. Finally, the experiments on 78 A-share stocks in CSI 100 and thirteen popular HK stocks in the year 2015 and 2016 are conducted. The results demonstrate the improvement on the prediction accuracy and the effectiveness of the proposed model. © 2018 IEEE.

关键词： Tensors

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3rd international conference on Industrial Networks and Intelligent systems. INISCOM 2017

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3rd international conference on Industrial Networksand Intelligent systems. INISCOM 2017

ISBN: (纸本)9783319741758

The proceedings contain 31 papers. The special focus in this conference is on Industrial Networks and Intelligent systems. The topics include: Optimization of multi-function sensor placement satisfying detection coverage;toward a real-time development and deployment of IoTs application for smart garden on OpenStack cloud;An energy-aware approach for event-driven multimedia data acquisition in WMSNs;Program popularity prediction approach for internet TV based on trend detecting;exact outage probability of two-way decode-and-forward scheme with energy harvesting from intermediate relaying station;enhancing performance of asynchronous cooperative relay network with partial feedback;outage probability for cognitive heterogeneous networks with unreliable backhaul connections;coupling statistical and agent-based models in the optimization of traffic signal control;optimizing vehicle routing with path and carbon dioxide emission for municipal solid waste collection in Ha Giang, Vietnam;energy-efficient data collection using lossless compression for industrial wireless sensor networks;Model-based sensitivity of a disaster tolerant active-active GENESIS cloud system;integrated sentiment and emotion into estimating the similarity among entries on social network;a functional optimization method for continuous domains;Data mining approaches for IP address clustering;a short survey on fault diagnosis of rotating machinery using entropy techniques;An intrusion detection system based on machine learning for CAN-Bus;A buck-boost multilevel inverter for PV systems.in smart cities;A new high step-up DC-DC converter for renewable energy applications;method for pseudo-probabilistic block encryption;Crack detection in rotating shafts using wavelet analysis, shannon entropy and multi-class SVM;Outage probability analysis of single energy constraint relay NOMA network.

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Multiparameter and index evaluation of voluntary distributed computing projects 3rd

Multiparameter and index evaluation of voluntary distributed...

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3rd international conference on Digital Transformation and Global Society, DTGS 2018

作者： Yakimets, Vladimir N. Kurochkin, Ilya I. Institute for Information Transmission Problems of Russian Academy of Sciences Moscow Russia The Russian Presidential Academy of National Economy and Public Administration Moscow Russia

ISBN: (纸本)9783030028428

In 2014–2015 years the very first sociological study of Russian crunchers [20] – volunteers who provide their computing resources for solving laborious tasks was conducted by authors. The study covered almost 650 people, which is a representative sample (more than 16% of total sample of about 4000 crunchers). A detailed analysis of that survey data led the authors to the idea of developing a new approach to evaluation of VDC projects. It is based on expert assessments of project quality on many criteria such as clarity of concept and vision, sound scientific platform, as well as existence of visualized results, availability of tools for encouraging crunchers, and so on. A new tool for assessing the quality of VDC projects (the YaK-index) is proposed and described in this paper. It was applied for evaluating some VDC projects to identify their strong and weak features, to make recommendations for improving their efficiency, to enhance the attractiveness for those interested in the VDC, and to create conditions for providing comparable information to the leadership of VDC projects. This paper describes the YaK-index idea and methodology, some stages of its development. Examples of visualization of comparable results of evaluating for a number of projects are given. © Springer Nature Switzerland AG 2018.

关键词： distributed computer systems

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3rd international conference on Signal and Information Processing, Networking and Computers, ICSINC 2017

3rd International Conference on Signal and Information Proce...

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3rd international conference on Signal and Information Processing, Networking and Computers, ICSINC 2017

ISBN: (纸本)9789811075209

The proceedings contain 61 papers. The special focus in this conference is on Signal, Information Processing, Networking and Computers. The topics include: An Energy Detection Based on Coefficient of Variation for Spectrum Sensing in Cognitive Radio;performance Analysis for User-Centric Cloud Radio Access Network in Millimeter Wave;millimeter Wave Cloud Radio Access Network Coverage and Capacity;Optimal Downtilts for 3D Beamforming Based on Greedy Algorithm in Massive MIMO Networks with Imperfect CSI;Dynamic User Scheduling Algorithms for Massive MIMO Multicast System;a Bat Algorithm Based on Centroid Strategy;an Optimized Daisy-chain Topology for Multi-load Interconnection in High–speed and High–density Electronic systems.Realization and Optimization of Pulse Compression Algorithm on OpenCL-Based FPGA Heterogeneous computing Platform;The Research of SAR Processing Performance Based on Multi-core GPU;A PHY-Based Secret Sharing Scheme in MIMO systems.ship Detection in Optical Satellite Images Based on Sparse Representation;application of Back Propagation Neural Network with Simulated Annealing Algorithm in Network Intrusion Detection systems.an Improved Binary Bee Colony Algorithm for Satellite Resource Scheduling Method;Automatic Liver Segmentation on CT Images;An Improved Blind Spectrum Sensing Algorithm Based on QR Decomposition and SVM;Sentiment Analysis Using Modified LDA;co-training Based on Multi-type Text Features;GNSS Spoofing Jamming Recognition Based on Machine Learning;TinyPEP: Tiny Pairwise-Key Establishment Protocol for Wireless Sensor Networks;An Innovative Indoor Location Algorithm Based on Supervised Learning and WIFI Fingerprint Classification;long Short-Term Memory Network for Wireless Channel Prediction;deep Learning and Machine Learning for Object Detection in Remote Sensing Images.

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3rd international Afro-European conference for Industrial Advancement, AECIA 2016

3rd International Afro-European Conference for Industrial Ad...

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3rd international Afro-European conference for Industrial Advancement, AECIA 2016

ISBN: (纸本)9783319608334

The proceedings contain 37 papers. The special focus in this conference is on Industrial Advancement. The topics include: Integrated autopilot complex system proposal for aircraft model application;maximizing the delivery rate for DTN networks;application to an automated manufacturing system;normalized compression distance based implementation for text data;adaptive methods of process state evaluation: the development of an application for engineering purposes;detection of finger flexions based on decision tree;a new fuzzy clustering algorithm to enhance lifetime of wireless sensor networks;exploratory data analysis of software requirements using statistics and kohonen’s self-organizing map;method for estimation of software requirements using neural network based classification technique;fall detection for elderly based on background subtraction and key points matching;active and reactive power robust control of doubly fed induction generator wind turbine to satisfy new grid codes;scalable addressing mechanism for structured P2P networks;improving the speed and quality of extreme learning machine by conjugate gradient method;new multi-criteria decision-making based on fuzzy similarity, distance and ranking;application in EOLES european project;analysis of air pollution in vertical profile using self-organizing maps;an enhanced delay time model to support evidence based maintenance in healthcare domain;a novel ant colony optimization based cryptanalysis of substitution cipher;software defined stochastic model for moving target defense;adaptive educational games using game metrics and the future of education.

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The Research of the SM2, SM3 and SM4 Algorithms in WLAN of Transformer Substation

The Research of the SM2, SM3 and SM4 Algorithms in WLAN of T...

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Electronic Information Technology and Computer Engineering (EITCE), international conference on

作者： Wang Tong Cui Wen Peng Li Tong Wang Liang Li Hao Chi Ying Ying Qiao Lei Liu Rui Power Grid Technology Center State Grid Liaoning Electric Power Research Institute Beijing Smartchip Microelectronics Company Limited Metering Center State Grid Liaoning Electric Power CO. LTD.

ISBN: (数字)9781728135847

ISBN: (纸本)9781728135854

With the gradual extension of artificial intelligence applications in terminal equipment, intelligent terminals based on edge computing are also widely used in power systems. The new embedded terminal device with local decision function can process the collected raw data locally and only report the key information, which can reduces the requirement of network bandwidth, so makes the wireless transmission meet the needs of more business scenarios. In order to collect a large number of terminal data in time, traditional substations need high network bandwidth. The data can only be transmitted over wire. The data in new transformer substation with intelligent terminal can be aggregated by wireless transmission. But the data security of wireless networks such as IEEE802.11ah, LoRa , NBIoT and WiFi cannot be guaranteed. At the same time, with the needs of social development, data security has risen to the height of national security. In order to realize the "security and controllability" of information systems. China Cryptographic Administration has published a series of encryption and decryption algorithms such as SM2, SM3, SM4. In this paper, based on the IEEE802.11ah standard, we study the application of SM2, SM3 and SM4 in LAN of transformer substation, and mainly focus on the identity authentication, key distribution and data encryption and decryption. In view of the three different stages, the system scheme designs are proposed respectively, and then we analyze their security and the additional system overhead in detail. The research of the SM2, SM3 and SM4 algorithms in LAN of transformer substation will further promote the popularization and application of intelligent terminal in substaion, and this will also ehance the level of intelligence of substation.

关键词： Substations Wireless LAN Security Protocols

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3rd international conference on Machine Learning, Optimization, and Big Data, MOD 2017

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3rd international conference on Machine Learning, Optimization, and Big Data, MOD 2017

ISBN: (纸本)9783319729251

The proceedings contain 49 papers. The special focus in this conference is on Machine Learning, Optimization, and Big Data. The topics include: Nonlinear methods for design-space dimensionality reduction in shape optimization;a differential evolution algorithm to develop strategies for the iterated prisoner’s dilemma;automatic creation of a large and polished training set for sentiment analysis on twitter;forecasting natural gas flows in large networks;a differential evolution algorithm to semivectorial bilevel problems;evolving training sets for improved transfer learning in brain computer interfaces;hybrid global/local derivative-free multi-objective optimization via deterministic particle swarm with local linesearch;artificial bee colony optimization to reallocate personnel to tasks improving workplace safety;multi-objective genetic algorithm for interior lighting design;improving support vector machines performance using local search;an elementary approach to the problem of column selection in a rectangular matrix;A simple and effective lagrangian-based combinatorial algorithm for S3VMs;A heuristic based on fuzzy inference systems.for multiobjective IMRT treatment planning;data-driven machine learning approach for predicting missing values in large data sets: A comparison study;mineral: Multi-modal network representation learning;visual perception of mixed homogeneous textures in flying pigeons;estimating dynamics of honeybee population densities with machine learning algorithms;SQG-differential evolution for difficult optimization problems under a tight function evaluation budget;age and gender classification of tweets using convolutional neural networks;approximate dynamic programming with combined policy functions for solving multi-stage nurse rostering problem;projective approximation based quasi-newton methods;a data mining tool for water uses classification based on multiple classifier systems.

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