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Generation Expansion Planning Including Biomass Energy Sources with Global Environmental Consideration Using Improved Tabu Search

Generation Expansion Planning Including Biomass Energy Sourc...

引用

IEEE Region 10 International Conference TENCON

作者： Dulyatat Nualhong Songsak Chusanapiputt Sujate Jantarang Vuthichai Pungprasert Department of Computer Engineering Faculty of Engineering Mahanakom University of Technology Bangkok Thailand Electrical Engineering Department Electrical and Control System Engineering Division EGAT Public Company Limited Nonthaburi Thailand Department of Electrical Power Engineering Faculty of Engineering Mahanakom University of Technology Bangkok Thailand Department of Electrical Power Engineering University of Technology Bangkok Thailand Department of Computer Engineering Mahanakorn University of Technology Bangkok Thailand Research and Development Office EGAT Public Company Limited Nonthaburi Thailand Research and Development Office EGAT Public Company Limited Nonthaburi Thailand

This paper presents a development of improved Tabu search (ITS) and its application to a least-cost generation expansion planning (GEP) including biomass energy sources under global environmental impact consideration. A carbon tax is taken into account as counter measure to reduce CO 2 emission for introducing and promoting biomass energies to GEP problem based conventional fossil-fuel plants. The proposed ITS is conducted by the proposed a self-reforming candidate list strategies to improve search performance of a standard TS. The ITS approach is applied to the test system with 15 existing power plants, 5 types of conventional fossil-fuel and 2 types of biomass energy over a 14-year planning period. The simulation results reveal that the proposed ITS not only can yield optimal solution as well as dynamic programming, but also can remarkably reduce computational time. Moreover, the proposed method provides better solution superior to a standard Tabu search with promising results.

关键词： Biomass Carbon tax Counting circuits Energy measurement Automatic testing system testing Power generation Power system planning Strategic planning Computational modeling

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Towards new real-time processor: the multioperand MSB-first real-time adder

Towards new real-time processor: the multioperand MSB-first ...

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Euromicro Symposium on Digital system Design

作者： Kuspriyanto Y.Y. Kerlooza Laboratory of Computer and Control System Department of Electrical Engineering Bandung Institute of Technology Indonesia Hardware Laboratory Department of Computer Engineering Indonesian Computer University Indonesia

Arithmetic operation's execution time in real-time system is bounded by deadlines. The method commonly used to meet these deadlines is by employing any suitable process-scheduling algorithm, which may contain a potential weakness. If time needed to operate is longer than its deadline, then the result's quality will be poor. This is mainly caused by the algorithms of the arithmetic operations commonly used nowadays do not choose the most significant data to be processed first. This research tries to design new algorithm and its processing unit that works based on real-time principles, which starts its computation process from the highest valued digit and provides its intermediate-results that can be accessed anytime during the process. Designing tool used in this research is MAX+plus II Baseline 10.2 software. This research accomplishes in showing the performance of the new algorithm and its processing unit, which is better than the performance of the conventional algorithm.

关键词： Real time systems Laboratories Algorithm design and analysis control systems Hardware Digital arithmetic Process design Software tools Timing computer errors

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A 3-D deformable surface method for automatic hippocampus-amygdala complex segmentation

A 3-D deformable surface method for automatic hippocampus-am...

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2004 Nuclear Science Symposium, Medical Imaging Conference, Symposium on Nuclear Power systems and the 14th International Workshop on Room Temperature Semiconductor X- and Gamma- Ray Detectors

作者： Karimi, M.M. Batmanghelich, N. Soltanian-Zadeh, H. Lucas, C. Control and Intelligent Processing Center of Excellence Department of Electrical and Computer Engineering University of Tehran Tehran 14395-515 Iran Institute for Studies in Theoretical Physics and Mathematics Tehran Iran Department of Radiology Henry Ford Health System Detroit MI 48202 United States

In this paper, we propose an atlas-based method for hippocampus-amygdala complex segmentation. An atlas is registered on all subjects and its transformation is calculated for each subject. This transformation is applied to the structural segmentation of the complex in atlas to construct an initial surface for the hippocampus-amygdala complex of each subject. A possibility approach is introduced for the segmentation process. Two different kinds of deformation based on edges and information obtained from tissue segmentation are used to find different parts of the complex. A new energy is defined to use tissue information. This energy is adopted to expand the model to embed dominant gray matter points in the volume and also withdraw from dominant white matter and CSF points. The initial shape is divided into several parts. In the normal direction of the center of each part, we construct a profile which search for the best poult that maximizes this new energy. This algorithm is reliable for finding the overall shape of the complex. It overcomes the poor features of the complex such as weak edges and noise. The algorithm is examined on 5 different subjects and validated using two different validation methods. © 2004 IEEE.

关键词： Medical imaging

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A hierarchical tissue segmentation approach in brain MRI images

A hierarchical tissue segmentation approach in brain MRI ima...

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Image Processing, Biomedicine, Multimedia, Financial engineering and Manufacturing - International Forum on Multimedia Image Processing, IFMIP - Sixth Biannual World Automation Congress, WAC 2004

作者： Song, Tao Huang, Mingxiong Lee, Roland R. Gasparovic, Charles Jamshidi, Mo University of New Mexico Albuquerque NM United States Electrical and Computer Engineering Department University of New Mexico Autonomous Control Engineering Center University of New Mexico Radiology Department University of New Mexico New Mexico VA Health Care System MIND Imaging Center University of New Mexico Health Science Center

ISBN: (纸本)188933524X

Magnetic resonance imaging (MRI) is a widely used approach to obtaining high quality medical images of the brain. Post-processing MRI images with segmentation algorithms enhances the visualization and measurement of soft tissues and lesions. Segmented brain images contain information amenable to quantitative analysis (e.g., tissue component percentage in a region of interest (ROI)) and diagnostic interpretation (e.g., total lesion volume). A number of different segmentation algorithms have been developed for this purpose. In this paper, we propose a novel automated segmentation technique, hierarchical structure weighted probabilistic neural network (HSWPNN), based on multi-scale feature extraction, hierarchical labeling structure, and a modified weighted probabilistic neural network (PNN). Compared to other clustering algorithms, our method is relatively robust to noise and accurate. We compare our results to a model of ground truth.

关键词： Magnetic resonance imaging

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Expansion of Codd algebra operations with recursive objects

Expansion of Codd algebra operations with recursive objects

引用

International Forum on Strategic Technology, IFOST

作者： V.V. Govorushko V.B. Novoseltsev The Faculty of Computer Science and Engineering Control System Optimization Department Cybenetic Center Tomsk Polytechnic University Tomsk Russia

In this paper, we discuss the relational algebra and recursive relationships between binary and ternary relationships in entity-relationship modeling. We define the interpretation of the recursive tables that can be applied to the complicated relationships having the same participating entities. We propose a new approach to modeling that is suitable for representing self-similar objects and for creating hierarchical structures. It combines methods of the set theory for the recursive relations within a single modeling paradigm, allowing users to define self-similar, partially self-similar, or hierarchical systems in a consistent and flexible manner. The use of recursive relationships in the definitions of self-similar objects yields representations that can be rendered at varying levels of detail or precision at run time.

关键词： Algebra Relational databases Data models Set theory Mathematical model Logic functions computer science systems engineering and theory control systems Hierarchical systems

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Clustering-based framework for comparing fMRI analysis methods

Clustering-based framework for comparing fMRI analysis metho...

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IEEE International Symposium on Biomedical Imaging

作者： G.-A. Hossein-Zadeh A.-M. Golestani H. Soltanian-Zadeh Control and Intelligent Processing Center of Excellence Electrical and Computer Engineering Department Faculty of Engineering University of Tehran Tehran Iran Image Analysis Laboratory Radiology Department Henry Ford Health System Detroit MI USA

In this paper, a cluster-based framework is introduced for comparing analysis methods of functional magnetic resonance images (fMRI). In the proposed framework, fMRI data is replaced with a feature space and each method considered as a clustering method in the new space. As a result, different methods can be compared by means of a cluster validity measure. The feature space is computed using a non-parametric method (principal component analysis-PCA). Four subjects have been analyzed with three methods and the proposed cluster-based framework has evaluated performance of the methods. The results are identical to those of the modified receiver operating characteristics (ROC). This validates the proposed approach.

关键词： Clustering algorithms Algorithm design and analysis Image analysis Clustering methods Magnetic analysis Testing Accuracy Reproducibility of results Radiology Magnetic resonance

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Integrating MPEG-7 descriptors and pattern recognition: an environment for multimedia indexing and searching

Integrating MPEG-7 descriptors and pattern recognition: an e...

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Proceedings of the Latin American Web Congress (LA-Web)

作者： R. Matushima D.M. Hiramatsu R.M. Silveira W.V. Ruggiero C.E.M. da Costa M.M. Monteiro C. Hatori LARC-Laboratory of Computer Architecture and Networks Department of Computer and Digital System Engineering Escola Politécnica da Universidade de São Paulo Brazil Department of Computer Engineering and Digital System Escola Politécnica da Universidade de São Paulo Brazil Fundaćão Padre Anchieta Radio e TV Cultura Sao Paulo Brazil

This paper describes a music searching system based on an automatic indexing process created over a pattern recognition tool and MPEG-7 standard. We present a complete analysis of the involved technologies integration process and show a reference measure in the feasibility of this kind of application not only in the research environment but also in the production of real systems.

关键词： MPEG 7 Standard Pattern recognition Indexing TV Data mining computer networks Digital systems systems engineering and theory Libraries Humans

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Multiresolution automatic segmentation of T1-weighted brain MR images

Multiresolution automatic segmentation of T1-weighted brain ...

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IEEE International Symposium on Biomedical Imaging

作者： M. Zeydabadi R.A. Zoroofi H. Soltanian-Zadeh Control and Intelligent Processing Center of Excellence Electrical and Computer Engineering Department Faculty of Engineering University of Tehran Tehran Iran Radiology Department Henry Ford Health System Image Analysis and Communications Laboratory Detroit MI USA

Automatic segmentation of brain tissues is crucial to many medical imaging applications. We use a multi-resolution analysis and a power transform to extend the well-known Gaussian mixture model expectation maximization based algorithm for segmentation of white matter, gray matter, and cerebrospinal fluid from T1-weighted magnetic resonance images (MRI) of the brain. Experimental results with near 4000 synthetic and real images are included. The results illustrate that the proposed method outperforms six existing methods.

关键词： Image resolution Image segmentation Biomedical imaging Multiresolution analysis Image analysis Magnetic analysis Algorithm design and analysis Brain modeling Magnetic liquids Magnetic resonance

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MRSI brain tumor characterization using wavelet and wavelet packets feature spaces and artificial neural networks

MRSI brain tumor characterization using wavelet and wavelet ...

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Annual International Conference of the IEEE engineering in Medicine and Biology Society (EMBC)

作者： A. Yazdan-Shahmorad H. Soltanian-Zadeh R.A. Zoroofi Control and Intelligent Processing Center of Excellence Electrical and Computer Engineering Department Faculty of Engineering University of Tehran Tehran Iran Radiology Department Henry Ford Health System Image Analysis and Communications Laboratory Detroit MI USA

Magnetic resonance spectroscopic imaging (MRSI) is a non-invasive technique for assessing biochemical fingerprint of tissue composition. The need to differentiate between normal and abnormal tissues and determine type of abnormality before biopsy or surgery motivated development and application of MRSI. There are several technical reasons that make the brain easier than other organs to be examined with MRSI. This work presents our proposed methods and results for the analysis of the brain spectra of patients with three tumor types (malignant glioma, astrocytoma, and oligodendroglioma). After extracting features from MRSI data using wavelet and wavelet packets, we use artificial neural networks to determine the abnormal spectra and the type of abnormality. We evaluated the proposed methods using clinical and simulated MRSI data and biopsy results. The MRSI analysis results were correct 97% of the time when classifying the spectra of the clinical MRSI data into normal tissue, tumor, and radiation necrosis. They were correct 72% and 83% of the time when determining tumor types using the clinical and simulated MRSI data, respectively.

关键词： Wavelet packets Neoplasms Artificial neural networks Biopsy Magnetic resonance Spectroscopy Magnetic resonance imaging Fingerprint recognition Surgery Cancer

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Landing motion analysis of human-body model considering impact and ZMP condition

Landing motion analysis of human-body model considering impa...

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IEEE International Workshop on Intelligent Robots and systems (IROS)

作者： Byung Rok So Byung-Ju Yi Sang-Rok Oh Young Soo Kim School of Electrical Engineering and Computer Science Hanyang University Ansan Gyeonggi South Korea KIST Intelligent System Control Research Center South Korea Department of Medicine Hanyang University South Korea

This paper deals with modeling and analysis for the landing motion of a human-body model. First, the dynamic model of a floating human body and the impact model are derived and the external impulse exerted on the ground as well as the internal impulse experienced at the joints of the human body model are investigated. Second, a motion planning algorithm exploiting the kinematic redundancy is suggested to ensure stability in terms of ZMP stability condition during a series of landing phases. Four phases of landing motion are investigated. In simulation, the external and internal impulses experienced at the human joints and the ZMP history resulting from the motion planning are analyzed for two different configurations. A desired landing posture is suggested by comparison of the simulation results.

关键词： Motion analysis Biological system modeling Humans Manipulators Joints Kinematics Legged locomotion Service robots Equations Stability

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