Conferences related to Data models

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2023 Annual International Conference of the IEEE Engineering in Medicine & Biology Conference (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 full papers will be peer reviewed. Accepted high quality papers will be presented in oral and poster sessions,will appear in the Conference Proceedings and will be indexed in PubMed/MEDLINE.


ICC 2021 - IEEE International Conference on Communications

IEEE ICC is one of the two flagship IEEE conferences in the field of communications; Montreal is to host this conference in 2021. Each annual IEEE ICC conference typically attracts approximately 1,500-2,000 attendees, and will present over 1,000 research works over its duration. As well as being an opportunity to share pioneering research ideas and developments, the conference is also an excellent networking and publicity event, giving the opportunity for businesses and clients to link together, and presenting the scope for companies to publicize themselves and their products among the leaders of communications industries from all over the world.


2020 22nd European Conference on Power Electronics and Applications (EPE'20 ECCE Europe)

Energy conversion and conditioning technologies, power electronics, adjustable speed drives and their applications, power electronics for smarter grid, energy efficiency,technologies for sustainable energy systems, converters and power supplies


2020 IEEE International Conference on Industrial Engineering and Engineering Management (IEEM)

All topics related to engineering and technology management, including applicable analytical methods and economical/social/human issues to be considered in making engineering decisions.


2020 IEEE International Conference on Industrial Technology (ICIT)

ICIT focuses on industrial and manufacturing applications of electronics, controls, communications, instrumentation, and computational intelligence.


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Periodicals related to Data models

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Antennas and Propagation, IEEE Transactions on

Experimental and theoretical advances in antennas including design and development, and in the propagation of electromagnetic waves including scattering, diffraction and interaction with continuous media; and applications pertinent to antennas and propagation, such as remote sensing, applied optics, and millimeter and submillimeter wave techniques.


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-- ...


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Most published Xplore authors for Data models

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Xplore Articles related to Data models

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Evolutionary Learning and Problem Solving

Fundamentals of Computational Intelligence: Neural Networks, Fuzzy Systems, and Evolutionary Computation, None

This chapter explores many specific applications of evolutionary algorithms for problem solving. The covered applications are aimed generally at assisting us to make more intelligent decisions by providing a better understanding of the world around us. The chapter starts with the basics of regression analysis and identified that evolutionary optimization can be applied not only to adjust parameters of a ...


Routing Protocols for Wireless Sensor Networks

Wireless Sensor Networks: Technology, Protocols, and Applications, None

This chapter contains sections titled:IntroductionBackgroundData Dissemination and GatheringRouting Challenges and Design Issues in Wireless Sensor NetworksRouting Strategies in Wireless Sensor NetworksConclusionReferences


An effective image representation for visual information retrieval

2000 10th European Signal Processing Conference, 2000

This paper presents an agent-oriented approach to visual information retrieval. A new data model is introduced to represent image content in a top- down fashion and a deductive agent-oriented database structure is proposed to facilitate visual information representation, indexing, query, searching and maintenance. In addition, the integration of techniques in image understanding and information retrieval is adopted for effective and ...


Validation and Evaluation for Visual Attention Models

Selective Visual Attention: Computational Models and Applications, None

This chapter assesses the performance of the saliency detection models described in the previous chapters. As with many other cases in engineering, a developed visual attention model needs to be critically benchmarked against other models, and then fully tested before being used in particular applications and situations. A number of qualitative and quantitative evaluation methods, as well as related ground-truth ...


Dual Port Sram - Data In Buffer

Dual Port Sram - Data In Buffer, 12/15/2011

Course content reaffirmed: 06/2015--There are several important timings that must be considered when designing the Data In Buffer that go beyond amplifying the input signal to drive the data to be written into the bit cell. The control timing must be such that the hold time for data in from the customer can be zero and not cause a change ...


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Educational Resources on Data models

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IEEE.tv Videos

Piero P Bonissone - Lazy Meta-Learning - Creating Customized Model Ensembles on Demand
Deep Learning and the Representation of Natural Data
BSIM Spice Model Enables FinFET and UTB IC Design
Evolving Fuzzy Systems: A Granular Computing Design Framework
20 Years of Neural Networks: A Promising Start, A brilliant Future- Video contents
Temporal Pattern Mining in Symbolic Time Point and Time Interval Data
Vladimir Cherkassky - Predictive Learning, Knowledge Discovery and Philosophy of Science
Bringing Biological Models to Life: The Power of Agent-based Modeling and Visualization
Panel Q&A - Big Data: 2016 Technology Time Machine
Active Space-Body Perception and Body Enhancement using Dynamical Neural Systems
Keynote: Ted Rappaport - Terahertz Communication - B5GS 2019
Visual Wake Words Challenge - Aakanksha Chowdhery - LPIRC 2019
IEEE Themes - Learning about human behavior from mobile phone data
A Closer Look at NFV Execution Models - Zhi-Li Zhang - IEEE Sarnoff Symposium, 2019
Probabilistic AI: Quantum & Probabilistic Computing - Jean Simatic at INC 2019
Digital Neuromorphic Design of a Liquid State Machine for Real-Time Processing - Nicholas Soures: 2016 International Conference on Rebooting Computing
LPIRC: Developing Mobile Computer Vision Models
IMS 2011 Microapps - Local Fundamental Frequency Enhancements for X-Parameter Models
2015 IEEE Honors: IEEE Alexander Graham Bell Medal - Frank Kelly
An In-Depth Look At Baidu's (BIDU) Artificial Intelligence Aspirations - ICRC San Mateo, 2019

IEEE-USA E-Books

  • Evolutionary Learning and Problem Solving

    This chapter explores many specific applications of evolutionary algorithms for problem solving. The covered applications are aimed generally at assisting us to make more intelligent decisions by providing a better understanding of the world around us. The chapter starts with the basics of regression analysis and identified that evolutionary optimization can be applied not only to adjust parameters of a regression model but also to do so in light of criteria that are not related to the mean squared error. This served as a foundation for extending evolutionary modeling to time series prediction in which the model coefficients and structure can be varied simultaneously and evaluated in light of information criteria. There are voluminous examples of applying evolutionary optimization to adjust the weights and/or topology of neural networks. One example described in the chapter treats the problem of controlling a cart-pole system comprising multiple poles.

  • Routing Protocols for Wireless Sensor Networks

    This chapter contains sections titled:IntroductionBackgroundData Dissemination and GatheringRouting Challenges and Design Issues in Wireless Sensor NetworksRouting Strategies in Wireless Sensor NetworksConclusionReferences

  • An effective image representation for visual information retrieval

    This paper presents an agent-oriented approach to visual information retrieval. A new data model is introduced to represent image content in a top- down fashion and a deductive agent-oriented database structure is proposed to facilitate visual information representation, indexing, query, searching and maintenance. In addition, the integration of techniques in image understanding and information retrieval is adopted for effective and efficient visual information retrieval.

  • Validation and Evaluation for Visual Attention Models

    This chapter assesses the performance of the saliency detection models described in the previous chapters. As with many other cases in engineering, a developed visual attention model needs to be critically benchmarked against other models, and then fully tested before being used in particular applications and situations. A number of qualitative and quantitative evaluation methods, as well as related ground-truth databases, are introduced in this chapter. Common benchmarks include simple man-made visual patterns, human-labelled images and eye tracking data, which are first given in Sections 6.1-6.3. The quantifying estimation of performance of the computational models is listed in Sections 6.4-6.6. The most commonly used criteria are PPV, TPR, F-measure, ROC and AUC, as introduced in Section 6.4. The statistical criteria for both static and dynamic scene - NNS and KL distance - are presented in Section 6.5. Then Section 6.6 shows the criterion of Spearman's rank-order correlation with visual conspicuity. Each type of ground-truth, the associated evaluation methods and their advantages and disadvantages are discussed whenever needed and possible.

  • Dual Port Sram - Data In Buffer

    Course content reaffirmed: 06/2015--There are several important timings that must be considered when designing the Data In Buffer that go beyond amplifying the input signal to drive the data to be written into the bit cell. The control timing must be such that the hold time for data in from the customer can be zero and not cause a change on the pin to propagate all the way to the bit cell and disturb what was just written. This tutorial makes a deeper evaluation of the timing paths that must be considered between clock and data in.

  • Table of Contents

    The following topics are dealt with: learning (artificial intelligence); security of data; computer crime; cryptography; Internet; Big Data; support vector machines; text analysis; invasive software; Internet of Things.

  • DATA‐DRIVEN PROGNOSTICS FOR BATTERIES SUBJECT TO HARD FAILURE

    This chapter considers data‐driven remaining useful life (RUL) of a battery prediction, which is typically made on the basis of projecting the trajectory of the system's health indicator, often called the degradation signal. Two most commonly used health indicators of batteries are capacity and internal resistance, while other health‐dependent variables such as battery self‐discharge rate may also be considered. By analyzing the evolution paths of the health indicating variables/degradation signals, it is possible to infer not only the current but also the future health status of the unit being studied. The chapter introduces a method specifically developed for battery RUL prediction under hard failure. In this method, a joint modeling scheme is used to take into consideration both the degradation data and the time‐to‐failure data. To better assess the performance of the prognostic algorithm, alternative interval prediction, the maximum power interval (MPI), is introduced as opposed to confidence intervals and mean/median‐based intervals.

  • Simulation of emergency evacuation in virtual reality

    A virtual reality system was developed to simulate emergency evacuations during fires. The spreading of the flame and smoke in the virtual fire was modeled based on numerical fire simulations, so that the conditions are similar to real life. A multi-grid, multi-base-state database model was used to overcome the disadvantages of traditional smoke spreading simulations. Textured images and particle systems provide visualization of the flame and smoke. The system immerses the user in a virtual environment with detailed interactions between the users and the virtual environment. The system can show which evacuation methods are effective for building safety evaluations.

  • Flies outsmart men

    Precopulatory courtship is a high-cost non-well understood phenomenon of the animal world. Drosophila’s courtship shows marked structural similarities with mammalian counterparts, suggesting its study to dissect origins, purpose and modalities of the phenomenon. From courtship videos, using a mathematical symbolic dynamics approach, we show that D. body language allows to express in addition to a coarse-grained population group membership also finer, individual information. From a formal language point of view, D.’s body language is shown to have a complexity of language equal to or even excelling that of human language.

  • Handling disynchronization phenomena with HMM in connected speech

    Anticipation and retention phenomena between the different phonatory organs have been widely studied in the speech perception and production domain. However, few automatic speech recognition systems are able to handle them. In this paper, we define a product of valuated transitions automata handling these difficulties. Then, we use such automata in a recognition system based on HMM. This method is evaluated in two different contexts : bimodal and unimodal speech recognition. The results show an improvement for the the product model against a synchronous one of 1.9% in the bimodal field and of 1.2% in the unimodal one.