Conferences related to Data Analysis

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2018 15th IEEE Annual Consumer Communications & Networking Conference (CCNC)

IEEE CCNC 2018 will present the latest developments and technical solutions in the areas of home networking, consumer networking, enabling technologies (such as middleware) and novel applications and services. The conference will include a peer-reviewed program of technical sessions, special sessions, business application sessions, tutorials, and demonstration sessions


2018 24th International Conference on Pattern Recognition (ICPR)

ICPR will be an international forum for discussions on recent advances in the fields of Pattern Recognition, Machine Learning and Computer Vision, and on applications of these technologies in various fields

  • 2016 23rd International Conference on Pattern Recognition (ICPR)

    ICPR'2016 will be an international forum for discussions on recent advances in the fields of Pattern Recognition, Machine Learning and Computer Vision, and on applications of these technologies in various fields.

  • 2014 22nd International Conference on Pattern Recognition (ICPR)

    ICPR 2014 will be an international forum for discussions on recent advances in the fields of Pattern Recognition; Machine Learning and Computer Vision; and on applications of these technologies in various fields.

  • 2012 21st International Conference on Pattern Recognition (ICPR)

    ICPR is the largest international conference which covers pattern recognition, computer vision, signal processing, and machine learning and their applications. This has been organized every two years by main sponsorship of IAPR, and has recently been with the technical sponsorship of IEEE-CS. The related research fields are also covered by many societies of IEEE including IEEE-CS, therefore the technical sponsorship of IEEE-CS will provide huge benefit to a lot of members of IEEE. Archiving into IEEE Xplore will also provide significant benefit to the all members of IEEE.

  • 2010 20th International Conference on Pattern Recognition (ICPR)

    ICPR 2010 will be an international forum for discussions on recent advances in the fields of Computer Vision; Pattern Recognition and Machine Learning; Signal, Speech, Image and Video Processing; Biometrics and Human Computer Interaction; Multimedia and Document Analysis, Processing and Retrieval; Medical Imaging and Visualization.

  • 2008 19th International Conferences on Pattern Recognition (ICPR)

    The ICPR 2008 will be an international forum for discussions on recent advances in the fields of Computer vision, Pattern recognition (theory, methods and algorithms), Image, speech and signal analysis, Multimedia and video analysis, Biometrics, Document analysis, and Bioinformatics and biomedical applications.

  • 2002 16th International Conference on Pattern Recognition


2018 26th Signal Processing and Communications Applications Conference (SIU)

The general scope of the conference ranges from signal and image processing to telecommunication, and applications of signal processing methods in biomedical and communication problems.

  • 2017 25th Signal Processing and Communications Applications Conference (SIU)

    Signal Processing and Communication Applications (SIU) conference is the most prominent scientific meeting on signal processing in Turkey bringing together researchers working in signal processing and communication fields. Topics include but are not limited to the areas of research listed in the keywords.

  • 2016 24th Signal Processing and Communication Application Conference (SIU)

    Signal Processing Theory, Statistical Signal Processing, Nonlinear Signal Processing, Adaptive Signal Processing, Array and Multichannel Signal Processing, Signal Processing for Sensor Networks, Time-Frequency Analysis, Speech / Voice Processing and Recognition, Computer Vision, Pattern Recognition, Machine Learning for Signal Processing, Human-Machine Interaction, Brain-Computer Interaction, Signal-Image Acquisition and Generation, image Processing, video Processing, Image Printing and Presentation, Image / Video / Audio browsing and retrieval, Image / Video / Audio Watermarking, Multimedia Signal Processing, Biomedical Signal Processing and Image Processing, Bioinformatics, Biometric Signal-Image Processing and Recognition, Signal Processing for Security and Defense, Signal and Image Processing for Remote Sensing, Signal Processing Hardware, Signal Processing Education, Radar Signal Processing, Communication Theory, Communication Networks, Wireless Communications

  • 2015 23th Signal Processing and Communications Applications Conference (SIU)

    Signal Processing Theory Statistical Signal Processing Nonlinear Signal Processing Adaptive Signal Processing Array and Multichannel Signal Processing Signal Processing for Sensor Networks Time-Frequency Analysis Speech / Voice Processing and Recognition Computer Vision Pattern Recognition Machine Learning for Signal Processing Human-Machine Interaction Brain-Computer Interaction Signal-Image Acquisition and Generation image Processing video Processing Image Printing and Presentation Image / Video / Audio browsing and retrieval Image / Video / Audio Watermarking Multimedia Signal Processing Biomedical Signal Processing and Image Processing Bioinformatics Biometric Signal-Image Processing and Recognition Signal Processing for Security and Defense Signal and Image Processing for Remote Sensing Signal Processing Hardware Signal Processing Education Radar Signal Processing Communication Theory Communication Networks Wireless Communications

  • 2014 22nd Signal Processing and Communications Applications Conference (SIU)

    SIU will be held in Trabzon, Turkey at the Karadeniz Technical University Convention and Exhibition Centre on April 23, 2014. SIU is the largest and most comprehensive technical conference focused on signal processing and its applications in Turkey. Last year there were 500 hundred participants. The conference will feature renowned speakers, tutorials, and thematic workshops. Topics include but are not limited to: Signal Procesing, Image Processing, Communication, Computer Vision, Machine Learning, Biomedical Signal Processing,

  • 2013 21st Signal Processing and Communications Applications Conference (SIU)

    Conference will discuss state of the art solutions and research results on existing and future DSP and telecommunication systems, applications, and related standardization activities. Conference will also include invited lectures, tutorials and special sessions.

  • 2012 20th Signal Processing and Communications Applications Conference (SIU)

    Conference will discuss state of the art solutions and research results on existing and future DSP and telecommunication systems, applications, and related standardization activities. Conference will also include invited lectures, tutorials and special sessions.

  • 2011 19th Signal Processing and Communications Applications Conference (SIU)

    Conference will bring together academia and industry professionals as well as students and researchers to present and discuss state of the art solutions and research results on existing and future DSP and telecommunication systems, applications, and related standardization activities. The Conference will also include invited lectures, tutorials and special sessions.

  • 2010 IEEE 18th Signal Processing and Communications Applications Conference (SIU)

    S1.Theory of Signal-Processing S2.Statistical Signal-Processing S3.Multimedia Signal-Processing S4.Biomedical Signal-Processing S5.Sensor Networks S6.Multirate Signal-Processing S7.Pattern Recognition S8.Computer Vision S9.Adaptive Filters S10.Image/Video/Speech Browsing, Retrieval S11.Speech/Audio Coding S12.Speech Processing S13.Human-Machine Interfaces S14.Surveillance Signal Processing S15.Bioinformatics S16.Self-Learning S17.Signal-Processing Education S18.Signal-Processing Systems S1

  • 2009 IEEE 17th Signal Processing and Communications Applications Conference (SIU)

    The scope of the conference is to cover recent topics in theory and applications of Signal Processing and Communications.

  • 2008 IEEE 16th Signal Processing and Communications Applications Conference (SIU)

    Signal Processing, Image Processing, Speech Processing, Pattern Recognition, Human Computer Interaction, Communication, Video and Speech indexing, Computer Vision, Biomedical Signal Processing

  • 2007 IEEE 15th Signal Processing and Communications Applications (SIU)

  • 2006 IEEE 14th Signal Processing and Communications Applications (SIU)

  • 2005 IEEE 13th Signal Processing and Communications Applications (SIU)

  • 2004 IEEE 12th Signal Processing and Communications Applications (SIU)


2018 40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)

The conference program will consist of plenary lectures, symposia, workshops and invitedsessions of the latest significant findings and developments in all the major fields of biomedical engineering.Submitted papers will be peer reviewed. Accepted high quality papers will be presented in oral and postersessions, will appear in the Conference Proceedings and will be indexed in PubMed/MEDLINE


2018 European Conference on Antennas and Propagation (EuCAP)

Antennas & related topics e.g. theoretical methods, systems, wideband, multiband, UWBPropagation & related topics e.g. modelling/simulation, HF, body-area, urbanAntenna & RCS measurement techniques


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Periodicals related to Data Analysis

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Automatic Control, IEEE Transactions on

The theory, design and application of Control Systems. It shall encompass components, and the integration of these components, as are necessary for the construction of such systems. The word `systems' as used herein shall be interpreted to include physical, biological, organizational and other entities and combinations thereof, which can be represented through a mathematical symbolism. The Field of Interest: shall ...


Biomedical Engineering, IEEE Transactions on

Broad coverage of concepts and methods of the physical and engineering sciences applied in biology and medicine, ranging from formalized mathematical theory through experimental science and technological development to practical clinical applications.


Broadcasting, IEEE Transactions on

Broadcast technology, including devices, equipment, techniques, and systems related to broadcast technology, including the production, distribution, transmission, and propagation aspects.


Circuits and Systems for Video Technology, IEEE Transactions on

Video A/D and D/A, display technology, image analysis and processing, video signal characterization and representation, video compression techniques and signal processing, multidimensional filters and transforms, analog video signal processing, neural networks for video applications, nonlinear video signal processing, video storage and retrieval, computer vision, packet video, high-speed real-time circuits, VLSI architecture and implementation for video technology, multiprocessor systems--hardware and software-- ...


Communications Letters, IEEE

Covers topics in the scope of IEEE Transactions on Communications but in the form of very brief publication (maximum of 6column lengths, including all diagrams and tables.)


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Most published Xplore authors for Data Analysis

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Xplore Articles related to Data Analysis

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Shared and Subject-Specific Dictionary Learning (ShSSDL) Algorithm for Multisubject fMRI Data Analysis

[{u'author_order': 1, u'affiliation': u'Department of Electrical and Electronic EngineeringThe University of Melbourne', u'full_name': u'Asif Iqbal'}, {u'author_order': 2, u'affiliation': u'Department of Electrical and Electronic Engineering, The University of Melbourne, Melbourne, VIC, Australia', u'full_name': u'Abd-Krim Seghouane'}, {u'author_order': 3, u'affiliation': u'Department of Computer Science and Electrical EngineeringUniversity of Maryland', u'full_name': u'T\xfclay Adalı'}] IEEE Transactions on Biomedical Engineering, 2018

Objective: Analysis of functional magnetic resonance imaging (fMRI) data from multiple subjects is at the heart of many medical imaging studies, and approaches based on dictionary learning (DL) are recently noted as promising solutions to the problem. However, the DL-based methods for fMRI analysis proposed to date do not naturally extend to multisubject analysis. In this paper, we propose a ...


Composite Indicators for Smart Campus: Data Analysis Method

[{u'author_order': 1, u'affiliation': u'dept of Astronautical Electrical and Energy Engineering, University of Rome La Sapienza, DIAEE, Italy', u'full_name': u'L. Pompei'}, {u'author_order': 2, u'affiliation': u'dept of Astronautical Electrical and Energy Engineering, University of Rome La Sapienza, DIAEE, Italy', u'full_name': u'B. Mattoni'}, {u'author_order': 3, u'full_name': u'F. Bisegna'}, {u'author_order': 4, u'affiliation': u'dept of Astronautical Electrical and Energy Engineering, University of Rome La Sapienza, DIAEE, Italy', u'full_name': u'F. Nardecchia'}, {u'author_order': 5, u'affiliation': u'Department of Industrial Engineering, University of Catania, DIIM, Italy', u'full_name': u'A. Fichera'}, {u'author_order': 6, u'affiliation': u'Department of Industrial Engineering, University of Catania, DIIM, Italy', u'full_name': u'A. Gagliano'}, {u'author_order': 7, u'affiliation': u'Department of Industrial Engineering, University of Catania, DIIM, Italy', u'full_name': u'A. Pagano'}] 2018 IEEE International Conference on Environment and Electrical Engineering and 2018 IEEE Industrial and Commercial Power Systems Europe (EEEIC / I&CPS Europe), None

The concept of Smart Campus started developing in the last years as a possible adaptation of the Smart city model to the university campuses. The transformation of a standard campus into a Smart Campus requires the development of an evaluation framework which allow to assess the state of the art by means of composite indicators. Following a new methodology, the ...


Research on Energy Consumption Data Analysis Method of Tram System

[{u'author_order': 1, u'affiliation': u'China Railway Tunnel Bureau Electrification Engineering Co., Ltd., Beijing, 100102, China', u'full_name': u'Chen Lin'}, {u'author_order': 2, u'affiliation': u'China Railway Tunnel Bureau Electrification Engineering Co., Ltd., Beijing, 100102, China', u'full_name': u'Wang Dongping'}] 2018 IEEE International Conference of Intelligent Robotic and Control Engineering (IRCE), None

In view of the traditional tram energy consumption analysis method be lack of judge and analysis of abnormal data as well as is difficult to effectively discover the characteristics of energy consumption data and the potential relationship between data, an integration method of tramcar energy consumption analysis with control charts and grey correlation analysis is proposed. By using the control ...


Risk Data Analysis Based Anomaly Detection of Ship Information System (SIS)

[{u'author_order': 1, u'affiliation': u'Shanghai Ocean University, College of Engineering Science and Technology, Shanghai, 201306, China', u'full_name': u'Bowen Xing'}, {u'author_order': 2, u'affiliation': u'Shanghai Ocean University, College of Engineering Science and Technology, Shanghai, 201306, China', u'full_name': u'Shouqi Cao'}, {u'author_order': 3, u'affiliation': u'Shipbuilding Industry Corporation (CSIC), Institute of China, No. 704, Shanghai, 200030, China', u'full_name': u'Xiao Chen'}] 2018 IEEE International Conference on Environment and Electrical Engineering and 2018 IEEE Industrial and Commercial Power Systems Europe (EEEIC / I&CPS Europe), None

Due to the vulnerability and high-risk of ship environment, ship information system (SIS) should be protected from cyber-attack around the clock. Therefore, in this paper, according to the cooperative control structure of SIS, a risk data analysis based anomaly detection mode is proposed. The risk data are determined by all the related data even in different subsystems which are formulated ...


Sensor Data Analysis Using Moving Average Filter and 256-Point FFT for Wireless Sensor Networks

[{u'author_order': 1, u'affiliation': u'Department of Electronics and Telecommunication, Sardar Patel Institute of Technology, Mumbai, Maharashtra', u'full_name': u'Mayur Chauhan'}, {u'author_order': 2, u'affiliation': u'Department of Electronics and Telecommunication, Sardar Patel Institute of Technology, Mumbai, Maharashtra', u'full_name': u'Pratik Thorwe'}, {u'author_order': 3, u'affiliation': u'Department of Electronics and Telecommunication, Sardar Patel Institute of Technology, Mumbai, Maharashtra', u'full_name': u'Monodeep J. Mukherjee'}, {u'author_order': 4, u'affiliation': u'Department of Electronics and Telecommunication, Sardar Patel Institute of Technology, Mumbai, Maharashtra', u'full_name': u'Y. Srinivas Rao'}] 2018 9th International Conference on Computing, Communication and Networking Technologies (ICCCNT), None

Wireless Sensor Networks (WSNs) are in demand in numerous fields recently and are evolving in terms of efficiency day by day. WSNs however face problems such as latency while dealing with large data values in the sensor nodes. Therefore we propose an algorithm for fast and meaningful analysis of data values for the nodes in the WSNs. We utilize a ...


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Educational Resources on Data Analysis

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eLearning

No eLearning Articles are currently tagged "Data Analysis"

IEEE-USA E-Books

  • Data Analysis

    This chapter presents data analysis techniques pertinent to various radio channels. The chapter first discusses the analysis of a single radio channel measurement to estimate the impulse response and the frequency response of the channel using basic spectral analysis techniques. It commences with the discrete Fourier transform (DFT) and the effect of the window functions on the estimated channel response. Then, the chapter addresses statistical analysis of time and space series. It defines and uses the RUNS test to determine the stationarity of a process. The last part of the chapter addresses high resolution parameter estimation techniques used in double directional analysis such as space‐alternating generalized expectation (SAGE), multiple signal classification (MUSIC) and estimation of signal parameters via the rational invariance technique (ESPRIT). This is followed by a discussion on the estimation of multiple input--multiple output (MIMO) channel capacity.

  • DATA ANALYSIS AND MACHINE LEARNING EFFORT IN HEALTHCARE

    This chapter examines the ideology of data‐driven healthcare and explores how new projects are defined and what is delivered as a proof of concept (POC). It discusses prerequisites and personnel qualifications for data science in healthcare; with a contributed subsection on the role of highperformance computing (HPC). The chapter provides a description of medical data and list the issues arising during data acquisition and transformation; a contributed subsection discusses de‐identification data sharing. It overviews the main themes of machine learning; the intention is to provide the readers with ideas and keywords for future independent exploration. The chapter presents a case study: prediction of rare adverse events based on traditional, nonspecific medical data. The enabling technology is unified electronic medical records (EMRs) that allow access, search, and simple sorting or comparison of hundreds of standard clinical features for millions of patients.

  • Stream Data Analysis in Prolog

    Today many applications routinely generate large quantities of data. The data often takes the form of a time series, or more generally just a stream -- an ordered sequence of records. Analysis of this data requires stream processing techniques, which differ in significant ways from what current database query languages and statistical analysis tools support today. There is a real need for better stream data analysis systems. Stream analysis, like most data analysis, is best done in a way that permits interactive exploration. It must support "ad hoc" queries by a user, and these queries should be easy to formulate and run. It seems then that stream data analysis is best done in some kind of powerful programming environment. A natural approach here is to analyze data with the stream processing paradigm of transducers (functional transformations) on streams. Data analyzers can be composed from collections of functional operators (transducers) that transform input data streams to output streams. A modular, extensible, easy-to-use library of transducers can be combined in arbitrary ways to answer stream data analysis queries of interest. Prolog offers an excellent start for an interactive data analysis programming environment. However most Prolog systems have limitations that make development of real stream data analysis applications challenging. We describe an approach for doing stream data analysis that has been taken in the Tangram project at UCLA. Transducers are implemented not directly in Prolog, but in a functional language called Log(F) that can be translated to Prolog. Many stream processing programs are easy to develop this way. A by-product of our approach is a practical way to interface Prolog and database systems.

  • Data Analysis and Uncertainty

    This chapter contains sections titled: 4.1 Introduction, 4.2 Dealing with Uncertainty, 4.3 Random Variables and Their Relationships, 4.4 Samples and Statistical Inference, 4.5 Estimation, 4.6 Hypothesis Testing, 4.7 Sampling Methods, 4.8 Conclusion, 4.9 Further Reading

  • Molecular Bioengineering and Nanobioscience: Data Analysis and Processing Methods

    This chapter contains sections titled: * Introduction * Data Analysis and Processing Methods for Genomics in the Postgenomic Era * From Genomics to Proteomics * Protein Structure Determination * Conclusions

  • Microarray Data Analysis: General Concepts, Gene Selection, and Classification

    This chapter contains sections titled: * Introduction * From Microarray to Gene Expression Data * Identification of Differentially Expressed Genes * Classification: Unsupervised Methods * Classification: Supervised Methods * Conclusions

  • Soft Computing in Signal and Data Analysis: Neural Networks, NeuroFuzzy Networks, and Genetic Algorithms

    This chapter contains sections titled: * Introduction * Adaptive Networks * Neural Networks * Learning * Structural Adaptation * Neuro-Fuzzy Networks * Genetic Algorithms

  • Microarray Data Analysis: Gene Regulatory Networks

    This chapter contains sections titled: * Introduction * Boolean Models * Differential Equation Models * Bayesian Models * Conclusions

  • Proteomic Data Analysis: Pattern Recognition for Medical Diagnosis and Biomarker Discovery

  • DataMining Techniques for Microarray Data Analysis



Standards related to Data Analysis

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Guide for the statistical analysis of electrical insulation breakdown data


IEEE Application Guide for Distributed Digital Control and Monitoring for Power Plants


IEEE Recommended Practice for Inertial Sensor Test Equipment, Instrumentation, Data Acquisition, and Analysis

Recommended practices for gyroscope and accelerometer testing are discussed, ranging from the equipment and instrumentation employed to the way that tests are carried out and data are acquired and analyzed.


IEEE Recommended Practice for Radar Cross-Section Test Procedures

This recommended practice establishes processes for the measurement of the electromagnetic scattering from objects. It is written for the personnel responsible for the operation of test ranges, and not for the design of such ranges. It recommends procedures for testing and documenting the quality of the measurement system, for calibrating the measurement system, for carrying out the radar scattering measurements, ...