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检索条件"任意字段=2016 International Conference on Data Mining and Advanced Computing, SAPIENCE 2016"

共 3354 条记录，以下是381-390 订阅

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Analyzing game stickiness using clustering techniques

Analyzing game stickiness using clustering techniques

引用

international conference on Computer, Communication and Computational Sciences, ICCCCS 2016

作者： Andrat, Hycinta Ansari, Nazneen Computer Department St. Francis Institute of Technology Mumbai India Information Technology Department St. Francis Institute of Technology Mumbai India

ISBN: (纸本)9789811037726

The popularity of computer games has led to tremendous generation of gaming data. Such gaming data consists of gamer’s personal information along with the game genres played and the time spent by them on a particular game. This gaming data can be utilized by the gaming industry for the purpose of extracting the knowledge needed to monitor the stickiness of the games. The raw data related to computer games can be refined, which could provide game developers the number of the gamers attracted towards a particular game. If the count of the gamers for a specific game decreases as the time passes by, then game developers need to improve the game, in order to retain the gamers. As gaming industry adds to our country’s revenue to a great extent, certain technological advancements are required. Therefore, this study aims to use a data mining approach, i.e., clustering, for monitoring computer games stickiness. © Springer Nature Singapore Pte Ltd. 2018.

关键词： data mining

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Study on Smart Automated Sales System with Blockchain-Based data Storage and Management

Study on Smart Automated Sales System with Blockchain-Based ...

引用

12th KIPS international conference on Ubiquitous Information Technologies and Applications (CUTE) / 9th international conference on Computer Science and its Applications (CSA)

作者： Yoo, Minjae Won, Yoojae Chungnam Natl Univ Dept Comp Sci Engn Daejeon South Korea

ISBN: (纸本)9789811076053;9789811076046

Automated sales systems, a recent technology, offer a wide range of products and services. This technology has advanced by combining with Internet of Things (IoT) technology. However, because of the development of such technology, data storage and management systems with trusted third parties cannot efficiently defend against data forgery attacks. In this study, a blockchain network is applied to an automated sales system. A smart automated sales machine using smart contracts is proposed. This system enables users to know the quantity of products or status of service provision before they visit an automated sales system. In addition, the system administrator can immediately see the expense-reduction effect of system management and address any problems in the system.

关键词： Vending machine Blockchain Smart contract Internet of Things

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international conference on advanced computing and Intelligent Engineering, ICACIE 2016

International Conference on Advanced Computing and Intellige...

引用

international conference on advanced computing and Intelligent Engineering, ICACIE 2016

ISBN: (纸本)9789811068713

The proceedings contain 136 papers. The special focus in this conference is on advanced computing and Intelligent Engineering. The topics include: Insight on Symmetrical Posture Detection of Human Using SIFT;complete Forward and Reverse Text Transcription of Odia Braille and Hindi Braille;GPU Based Bag of Feature for Fast Activity Detection in Video;A New Approach Using Discrepancy Theory for MR Image Segmentation;error Detection and Correction Using Parity and Pixel Values of Image;computer-Aided Diagnosis of Type 2 Diabetes Mellitus Using Thermogram of Open Mouth;3D Surface Measurement through Easy-Snap Phase Shift Fringe Projection;Off-Line Handwritten Odia Character Recognition Using DWT and PCA;Lesion Volume Estimation from TBI–MRI;higher-Order Nonlinear Analysis with Core Tensor and Frame-Wise Approach for Dynamic Texture Synthesis;analytical Assessment of Security Mechanisms of Cloud Environment;BRRC: A Hybrid Approach Using Block Cipher and Stream Cipher;a Novel and Efficient Perceptual Image Encryption Based on Knight Moves and Genetic Operations;A Flow Marking Based Anti-spoofing Mechanism (FMAS) Using SDN Approach;cheating Immune Visual Cryptographic Scheme with Reduced Pixel Expansion;Securing Sensitive data Information Through Multiplicative Perturbation Approach Based on UML Modeling;secret Communication Combining Cryptography and Steganography;biometric-Based System for Intrusion Detection and Prevention Mechanism for Energy Efficiency in Wireless Sensor Networks;a Distinct Cyberattack: Phishing;designing and Simulation Tools of Renewable Energy Systems: Review Literature;biometric Identification (Analysis Based on Fingerprints and Faces);Design of a Medical Expert System (MES) Based on Rough Set Theory for Detection of Cardiovascular Diseases;relevant Slicing of Feature-Oriented Programs.

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Decision Rule Learning from Stream of Measurements-A Case Study in Methane Hazard Forecasting in Coal Mines 5th

Decision Rule Learning from Stream of Measurements-A Case St...

引用

5th international conference on Man-Machine Interactions (ICMMI)

作者： Kozielski, Michal Matyszok, Pawel Sikora, Marek Wrobel, Lukasz Silesian Tech Univ Inst Elect Gliwice Poland Silesian Tech Univ Inst Informat Gliwice Poland Inst Innovat Technol EMAG Katowice Poland

ISBN: (纸本)9783319677927;9783319677910

The approach based on the Very Fast Decision Rules algorithm in application to prediction of alarm state resulting from methane hazard in coal mines is presented in this work. The approach introduces the modification of rule induction process due to application of the Correlation rule quality measure. An evaluation of the introduced method on a real life stream data collected from coal mine sensors is performed. The results show advantages of the introduced method considering both the classification quality and the rule-based knowledge representation.

关键词： data stream mining Rule-based learning Classification

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international conference on advanced computing and Intelligent Engineering, ICACIE 2016

International Conference on Advanced Computing and Intellige...

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international conference on advanced computing and Intelligent Engineering, ICACIE 2016

ISBN: (纸本)9789811068744

The proceedings contain 69 papers. The special focus in this conference is on advanced computing and Intelligent Engineering. The topics include: Insight on Symmetrical Posture Detection of Human Using SIFT;complete Forward and Reverse Text Transcription of Odia Braille and Hindi Braille;GPU Based Bag of Feature for Fast Activity Detection in Video;A New Approach Using Discrepancy Theory for MR Image Segmentation;error Detection and Correction Using Parity and Pixel Values of Image;computer-Aided Diagnosis of Type 2 Diabetes Mellitus Using Thermogram of Open Mouth;3D Surface Measurement through Easy-Snap Phase Shift Fringe Projection;Off-Line Handwritten Odia Character Recognition Using DWT and PCA;Lesion Volume Estimation from TBI–MRI;higher-Order Nonlinear Analysis with Core Tensor and Frame-Wise Approach for Dynamic Texture Synthesis;analytical Assessment of Security Mechanisms of Cloud Environment;BRRC: A Hybrid Approach Using Block Cipher and Stream Cipher;a Novel and Efficient Perceptual Image Encryption Based on Knight Moves and Genetic Operations;A Flow Marking Based Anti-spoofing Mechanism (FMAS) Using SDN Approach;cheating Immune Visual Cryptographic Scheme with Reduced Pixel Expansion;Securing Sensitive data Information Through Multiplicative Perturbation Approach Based on UML Modeling;secret Communication Combining Cryptography and Steganography;biometric-Based System for Intrusion Detection and Prevention Mechanism for Energy Efficiency in Wireless Sensor Networks;a Distinct Cyberattack: Phishing;designing and Simulation Tools of Renewable Energy Systems: Review Literature;biometric Identification (Analysis Based on Fingerprints and Faces);Design of a Medical Expert System (MES) Based on Rough Set Theory for Detection of Cardiovascular Diseases;relevant Slicing of Feature-Oriented Programs.

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Integration of Python-Based MDSPLUS Interface for ICRH DAC Software

Integration of Python-Based MDSPLUS Interface for ICRH DAC S...

引用

international conference on advanced computing and Intelligent Engineering (ICACIE)

作者： Joshi, Ramesh Kulkarni, Swanand S. Kulkarni, S. V. Inst Plasma Res Ahmadabad 382428 Gujarat India Gujarat Technol Univ Ahmadabad 382424 Gujarat India

ISBN: (纸本)9789811068720;9789811068713

Ion cyclotron resonance heating (ICRH) data acquisition control system (DAC) system for 100 kW, 45.6 MHz has been designed for RF ICRH system. This system is used for control and monitoring for 2, 20, and 100 kW RF amplifier stages, respectively. ICRH system consists of different power supplies for each RF amplifier stages. PLC-based DAC has been used for various power supplies monitor, control, and interlocks. Acquired data has been stored in MDSPLUS tree in binary format with defined signal list. Python is an open source scripting language which has been used for core development of software system. Python is very popular programming language for embedded as well as high-level programming. MDSPLUS is an open source package used for data archival and visualization. It is data archival and analysis tools used in various fusion experiments for data logging and visualization with configuration. It has standard developed program interface available with most of the popular languages like Fortan, C++, Python, Java, MATLAB, and IDL for graphical display of data and browsing. The paper introduces the interface of Python-based API for integration of Python and MDSPLUS for ICRH DAC software. Module allows user to read/write data directly in binary tree of MDSPLUS hierarchy. Java-based jScope tool is a part of MDSPLUS database which is used for data visualization.

关键词： PLC-programmable logic controller DAC-data acquisition and control ICRH-ion cyclotron resonance heating Python

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Predicting earning per share with financial ratios 5th

Predicting earning per share with financial ratios

引用

5th international conference on Frontier computing, FC 2016

作者： Chen, You-Shyang Chou, Jerome Chih-Lung Huang, Hsiu-Chen Hwa Hsia University of Technology Taipei Taiwan

ISBN: (纸本)9789811031861

Predicting EPS (earning per share) with financial ratios is of high practical value. In this study, we applied two methods of data mining to predict EPS and compared their performance. We used three classifiers to find rules for predicting EPS from financial ratios, and compared the difference of prediction performance with and without data discretization. The experimental data set was extracted from the online financial database of Taiwan Economic Journal (TEJ) and collected from the 2009–2013 financial statements of six different industries. 26 condition attributes were selected from financial statements of listed public companies. The decision attribute, EPS, was classified into two and three classes. The result shows that there are three key determinants: Operating income per share, Times interest earned, and Total assets growth rate, and the method of with data discretization is of better prediction accuracy. © Springer Nature Singapore Pte Ltd. 2018.

关键词： data mining

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Production data analysis and pressure prediction of shale gas well in Fuling Jiaoshiba area 17

Production data analysis and pressure prediction of shale ga...

引用

17th IEEE international conference on Cognitive Informatics and Cognitive computing (ICCI*CC)

作者： Chen, Xuemei Bai, Junren Yi, Jun Peng, Jun Dong, Zhiming Chongqing Univ Sci & Technol Coll Elect & Informat Engn Chongqing Peoples R China

ISBN: (纸本)9781538633601

The production pressure of shale gas well is a key parameter for guiding the yield allocation, thus the prediction of production pressure based on historical data can significantly impair the optimization of the subsequent production. However, the strong nonlinear correlation among the historical production data weakens the effect of traditional linear prediction method. Hence, a novel prediction and data analysis method for the shale gas well production pressure based on Elman neural network is proposed in this paper. First, the adaptive segmentation algorithm is used to piecewise eliminate the incomplete and abnormal data to guarantee the accuracy of the prediction. Second, the correlation analysis of production data is developed by Spearman method. Finally, Elman neural network is applied in predicting the production pressure of shale gas well. Compared with BP neural network and curve fitting prediction, the experimental results of the shale gas in Fuling Jiaoshiba area indicate that the proposed method can effectively improve the prediction accuracy of production press.

关键词： production pressure of gas well correlation analysis Elman neural network intelligent control data Analytics

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On spectral graph embedding: A non-backtracking perspective and graph approximation

On spectral graph embedding: A non-backtracking perspective ...

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2018 SIAM international conference on data mining, SDM 2018

作者： Jiang, Fei He, Lifang Zheng, Yi Zhu, Enqiang Xu, Jin Yu, Philip S. Department of Computer Science Peking University China Department of Healthcare Policy and Research Weill Cornell Medical School Cornell University United States School of Computer Science and Educational Software Guangzhou University China Shanghai Institute for Advanced Communication and Data Science Fudan University Shanghai China Department of Computer Science University of Illinois Chicago United States

Graph embedding has been proven to be efficient and effec-tive in facilitating graph analysis. In this paper, we present a novel spectral framework called NOn-Backtracking Embed-ding (NOBE), which offers a new perspective that organizes graph data at a deep level by tracking the flow traversing on the edges with backtracking prohibited. Further, by analyz-ing the non-backtracking process, a technique called graph approximation is devised, which provides a channel to trans-form the spectral decomposition on an edge-to-edge matrix to that on a node-to-node matrix. Theoretical guarantees are provided by bounding the difference between the cor-responding eigenvalues of the original graph and its graph approximation. Extensive experiments conducted on various real-world networks demonstrate the efficacy of our methods on both macroscopic and microscopic levels, including clus-tering and structural hole spanner detection. © 2018 by SIAM.

关键词： Eigenvalues and eigenfunctions

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Public security big data processing support technology

Public security big data processing support technology

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international conference on Applications and Techniques in Cyber Security and Intelligence, ATCSI 2017

作者： Zhou, Yaqin The Third Research Institute of the Ministry of Public Security Shanghai201204 China

ISBN: (纸本)9783319670706

Fourth times a million police officers held in October 21, 2016 at the Central Political Committee learning seminars, the Political Bureau of the CPC Central Committee and the central politics and Law Committee Secretary Meng Jianzhu pointed out, we are in the era of big data, modern science and technology in the mobile Internet, big data, cloud computing and artificial intelligence as the representative is changing our mode of life, everything experience of human life are changing. Big data development of the human "third eyes", through massive data analysis, processing, mining, allows us to penetrate into the unknown world. To cultivate data culture, good at using big data thinking analysis, problem solving, decision support. © 2018, Springer international Publishing AG.

关键词： Big data

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