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IGARSS 2015 - 2015 IEEE International Geoscience and Remote Sensing Symposium
The Geoscience and Remote Sensing Society (GRSS) seeks to advance science and technology in geoscience, remote sensing and related fields using conferences, education and other resources. Its fields of interest are the theory, concepts and techniques of science and engineering as they apply to the remote sensing of the earth, oceans, atmosphere, and space, as well as the processing, interpretation and dissemination of this information.
2014 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE)
IEEE International Conference on Fuzzy Systems is the largest technical event in the field of fuzzy systems. In 2014, International Joint Conference on Neural Networks will be part of the 2104 IEEE World Congress on Computational Intelligence.
2014 International Conference on Distributed Frameworks for Multimedia Applications (DFmA)
Papers are invited on all aspects of Advanced Computer Networks/Next Generation Internet or research areas aligned to it that include (but are not limited to) the following: Multimedia Communications and Systems, Networks/Internet & Communications, Internet Security and Monitoring, Grid and Cloud Computing.
The 11th International Content Based Multimedia Indexing Workshop is to bring together the various communities involved in all aspects of content-based multimedia indexing, retrieval, browsing and presentation.The conference will host invited keynote talks and regular, special and demo sessions with contributed research papers.
Scope of the conference is to provide medium to discuss advances and applications of fusion methodologies. Conference will include contributions in the areas of fusion methodologies, theory and representation, algorithms and modelling and simulation.
IEEE Internet Computing provides journal-quality evaluation and review of emerging and maturing Internet technologies and applications. The magazine targets the technical and scientific Internet user communities as well as designers and developers of Internet-based applications and enabling technologies. IC publishes refereed articles on the latest developments and key trends in Internet technologies and applications. A crossroads between academic researchers and ...
Artificial intelligence techniques, including speech, voice, graphics, images, and documents; knowledge and data engineering tools and techniques; parallel and distributed processing; real-time distributed processing; system architectures, integration, and modeling; database design, modeling, and management; query design, and implementation languages; distributed database control; statistical databases; algorithms for data and knowledge management; performance evaluation of algorithms and systems; data communications aspects; system ...
The scope of the IEEE Transactions on Systems, Man and Cybernetics Part B: Cybernetics includes computational approaches to the field of cybernetics. Specifically, the transactions welcomes papers on communication and control across machines or between machines, humans, and organizations. The scope of Part B includes such areas as computational intelligence, computer vision, neural networks, genetic algorithms, machine learning, fuzzy systems, ...
The IEEE Transactions on Sustainable Energy is a cross disciplinary and internationally archival journal aimed at disseminating results of research on sustainable energy that relates to, arises from, or deliberately influences energy generation, transmission, distribution and delivery. The journal will publish original research on theories and development on principles of sustainable energy technologies and systems.This journal will cover the following ...
Li Erguo; Yu Jinshou Intelligent Control and Automation, 2002. Proceedings of the 4th World Congress on, 2002
In this paper some existing problems in the linear principal component analysis methodology are discussed first. A nonlinear principal component analysis methodology based upon input-training neural network is presented for process fault diagnosis. The learning algorithm of input-training neural network is modified to improve its learning speed and avoid oscillation during learning. Then, input-training neural network and BP neural network ...
Min Zuo; Guangping Zeng; Xuyan Tu Modeling, Simulation and Visualization Methods (WMSVM), 2010 Second International Conference on, 2010
Text Categorization is an important research branch in the data mining domain. In this paper, an improved Naive Bayesian Classifier which is based on the Genetic Algorithms is proposed. It can make an effective Naive Bayesian classifier with excellent attributes Set in the field of text categorization. The experiments show that this method has a good classification performance.
Kyueun Yi; Jean-Luc Gaudiot IEEE Transactions on Computers, 2010
As network applications become increasingly sophisticated and Internet traffic is getting heavier, future network processors must continue processing computation-intensive network applications at line rates. Most programmable network processors on the market today, such as the Intel IXP2800, target relatively low performance (from 100 Mbps to 10 Gbps). However, low cost edge routers will find it hard to cope with the ...
Francesco Gullo; Giovanni Ponti; Andrea Tagarelli; Giuseppe Tradigo; Pierangelo Veltri Computer-Based Medical Systems, 2008. CBMS '08. 21st IEEE International Symposium on, 2008
Preprocessing mass spectrometry (MS) data has been recognized as a crucial preliminary phase in order to perform data management and knowledge discovery tasks on mass spectra. The huge dimensionality and heterogeneity of MS data make mandatory the use of tools that are able to guide the user in the MS preprocessing task. However, most MS preprocessing tools are typically designed ...
H. Knutsson; M. Borga Image Analysis and Processing, 1999. Proceedings. International Conference on, 1999
This paper presents a general strategy for designing efficient visual operators. The approach is highly task-oriented and what constitutes the relevant information is defined by a set of examples. The examples are pairs of images displaying a strong dependence in the chosen feature but are otherwise independent. Particularly important concepts in the work are mutual information and canonical correlation. Visual ...
Information Management and Engineering (ICIME), 2010 The 2nd IEEE International Conference on, 2010
This paper proposes novel method of embedding and extraction of data in Black and White picture images. The main focus of this method is on steganography in Black & white picture image. This method embeds more number of bits in a block as compared to earlier methods, which are limited to one or two bits. This method suggests the searching ...
Computers in Power Electronics, 1994., IEEE 4th Workshop on, 1994
One of the main tasks in power systems simulation is the selection of the devices models, including the corresponding parameters. A number of device models is available, but the extraction of the parameters of the actual (commercially available) devices, in order to be modelled requires usually a case-by-case study. This paper describes a tool that automatically obtains SPICE-compatible libraries of ...
High Performance Distributed Computing, 2002. HPDC-11 2002. Proceedings. 11th IEEE International Symposium on, 2002
Discovery Net is an application layer for providing grid-based knowledge discovery services. These services allow scientists to create and manage complex knowledge discovery workflows that integrate data and analysis routines provided as remote services. They also allow scientists to store, share and execute these workflows as well as publish them as new services. Discovery Net provides a higher level of ...
Computational Intelligence and Data Mining (CIDM), 2014 IEEE Symposium on, 2014
A novel pattern is an observation which is different as compared to the rest of the data. The task of novelty detection is to build a model which identifies novel patterns from a data set. This model has to be built in such a way that if a pattern is distant from the given training data, it should be classified ...
Automatic Speech Recognition and Understanding, 2005 IEEE Workshop on, 2005
Compared to the variation in utterances that users may exhibit in conversation with spoken dialogue systems, system utterances can be very rigid with little variation. One recent approach to dealing with this problem is a trainable sentence planner, which uses natural language generation techniques to create a large number of alternative utterances for a given content, by randomly combining an ...
This chapter contains sections titled: Clustering Concepts Similarity Measures Agglomerative Hierarchical Clustering Partitional Clustering Incremental Clustering DBSCAN Algorithm BIRCH Algorithm Clustering Validation Review Questions and Problems References for Further Study
This chapter contains sections titled: 13.1 Introduction, 13.2 Rule Representations, 13.3 Frequent Itemsets and Association Rules, 13.4 Generalizations, 13.5 Finding Episodes from Sequences, 13.6 Selective Discovery of Patterns and Rules, 13.7 From Local Patterns to Global Models, 13.8 Predictive Rule Induction, 13.9 Further Reading
This chapter contains sections titled: Market-Basket Analysis Algorithm Apriori From Frequent Itemsets to Association Rules Improving the Efficiency of the Apriori Algorithm FP Growth Method Associative-Classification Method Multidimensional Association-Rules Mining Review Questions and Problems References for Further Study
This chapter contains sections titled: 14.1 Introduction, 14.2 Evaluation of Retrieval Systems, 14.3 Text Retrieval, 14.4 Modeling Individual Preferences, 14.5 Image Retrieval, 14.6 Time Series and Sequence Retrieval, 14.7 Summary, 14.8 Further Reading
This chapter contains sections titled: Introduction System Architecture Mobile Device Components Energy Model Clustering Scheme Conclusion References
This chapter contains sections titled: Web Mining Web Content, Structure, and Usage Mining HITS and LOGSOM Algorithms Mining Path-Traversal Patterns PageRank Algorithm Text Mining Latent Semantic Analysis (LSA) Review Questions and Problems References for Further Study
This chapter provides an overview of the most common components that are used in the knowledge discovery process. It is structured according to the data- access and transformation, data integration, data preparation, data processing, data-mining, and visualization and knowledge delivery stages of the knowledge discovery process, from dealing with the source data to bringing new information to the knowledge of people or systems, which may need to react to it. The chapter starts by describing the basic components that can be used at each stage. Then it moves into more advanced usage patterns (for sampling, validation, bootstrapping). And it gives special attention to data dynamicity and its impact on the evolution of these components and usage patterns in a data-intensive context. The chapter presents a representative sample sufficient for readers to recognize the kinds of components that they will encounter and the ways in which these are evolving.
This chapter contains sections titled: A.1 Review of Univariate Random Variables, A.2: Some Common Probability Distributions
Genetic programming, a form of genetic algorithm that evolves programs and program-like executable structures, is a new paradigm for developing reliable, time- and cost-effective applications. The second volume of Advances in Genetic Programming highlights many of the most recent technical advances in this increasingly popular field. The twenty-three contributions are divided into four parts: Variations on the Genetic Programming Theme; Hierarchical, Recursive, and Pruning Genetic Programs; Analysis and Implementation Issues; and New Environments for Genetic Programming.The first part extends the core concepts of genetic programming through the addition of new evolutionary techniques -- adaptive and self-adaptive crossover methods, hill climbing operators, and the inclusion of introns into the representation.Creating more concise executable structures is a long-term research topic in genetic programming. The second part describes the field's most recent efforts, including the dynamic manipulation of automatically defined functions, evolving logic programs that generate recursive structures, and using minimum description length heuristics to determine when and how to prune evolving structures.The third part takes up the many implementation and analysis issues associated with evolving programs. Advanced applications of genetic programming to nontrivial real-world problems are described in the final part: remote sensing of pressure ridges in Arctic sea ice formations from satellite imagery, economic prediction through model evolution, the evolutionary development of stress and loading models for novel materials, and data mining of a large customer database to optimize responses to special offers.
This chapter contains sections titled: Graph Mining Temporal Data Mining Spatial Data Mining (SDM) Distributed Data Mining (DDM) Correlation Does Not Imply Causality Privacy, Security, and Legal Aspects of Data Mining Review Questions and Problems References for Further Study
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10 Ph.D. and Postdoc Scholarships
Hasso Plattner Institute (HPI)
Research Scientist - Physiological Data Modeling (210487)
The Henry M. Jackson Foundation
Senior Data Scientist
R&D Computer Scientist-GIS/Geospatial Modeling & Simulation (Early/Mid Career)
Sandia National Laboratories
R&D, Data Scientist (Early/Mid Career)
Sandia National Laboratories
Tenure-track faculty positions, The School of Computer Science and Engineering, University of Aizu
The University of Aizu
Computer Scientist C++, Java (Experienced)
Sandia National Laboratories
Computer Scientist C++, Java (Early/Mid Career)
Sandia National Laboratories
RD Computer Science (Entry/Mid Career)
Sandia National Laboratories
Social/Cyber Analytic Researcher (Experienced)
Sandia National Laboratories