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Pricing of multi-energy network flow

Pricing of multi-energy network flow

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2010 IEEE International Energy Conference and Exhibition, EnergyCon 2010

作者： Schulze, Matthias Gasparovic, Goran Lee, Jieun High Voltage Laboratory Swiss Federal Institute of Technology Zurich Physikstrasse 3 8092 Zurich Switzerland Faculty of Electrical Engineering Mechanical Engineering and Naval Architecture University of Split R. Bokovia b. b. 21000 Split Croatia Dept. of Computer Science Korea Advanced Institute of Science and Technology Guseong-dong Yuseong-gu Daejeon 305-701 Korea Republic of

ISBN: (纸本)9781424493807

The network model bases upon the energy hub concept, which was developed by the Vision of Future Energy Networks (VoFEN) research group at ETH Zurich in the last years. Keynote of the concept is a combined optimization of different energy carrier. Synergetic effects are expected to give unusual optimization results, when allowing any possible energy conversion inside a specific area that constitute the hub. Costs for the energy consumption or production are generally used as the optimization criteria. Any technologies for conversion and storage are integrated in a coupling matrix, which links input and output. This paper deals with an extension to the optimization part by merging the network flows with the pricing of grid costs. The impact of network flow pricing is at first derived from theory, then translated into the energy hub concept and finally illustrated in an example. © 2010 IEEE.

关键词： Costs

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APyCA: Towards the automatic subtitling of television content in Spanish

APyCA: Towards the automatic subtitling of television conten...

引用

International Multiconference on computer Science and Information technology, IMCSIT

作者： Aitor Álvarez Arantza del Pozo Andoni Arruti Vicomtech Research Centre Donostia-San Sebastian Spain Vicomtech Research Centre Mikeletegi pasealekua 57 Miramon Teknologia Parkea 20009 Donostia-San Sebastian Spain Dept. of Computer Architecture and Technology The University of the Basque Country Donostia-San Sebastian Spain

Automatic subtitling of television content has become an approachable challenge due to the advancement of the technology involved. In addition, it has also become a priority need for many Spanish TV broadcasters, who will have to broadcast up to 90% of subtitled content by 2013 to comply with recently approved national audiovisual policies. APyCA, the prototype system described in this paper, has been developed in an attempt to automate the process of subtitling television content in Spanish through the application of state-of-the-art speech and language technologies. Voice activity detection, automatic speech recognition and alignment, discourse segment detection and speaker diarization have proved to be useful to generate time-coded colour-assigned draft transcriptions for post-editing. The productive benefit of the followed approach heavily depends on the performance of the speech recognition module, which achieves reasonable results on clean read speech but degrades as this becomes more noisy and/or spontaneous.

关键词： TV Information technology Iron computer science

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Elitist genetic algorithm guided by higher order statistic for blind separation of digital signals

Elitist genetic algorithm guided by higher order statistic f...

引用

Annual Conference of Industrial Electronics Society

作者： E. A. González J. M. Górriz J. Ramírez C. G. Puntonet Dept. Consulting and ICT Development Gonblan Consultores S.L.P. Granada Spain Department Signal Theory and Communications Facultad de Ciencias University of Granada Granada Spain Dept. Signal Theory and Communications University of Granada Granada Spain Dept. Architecture and Computer Technology University of Granada Granada Spain

A novel method for blind separation of digital signals based on elitist genetic algorithms is presented in this paper. Contrast function, consisting in a weighted sum of high order statistics measures (cumulants of different orders), plays the role of genetic fitness function, and also guide the genetic algorithm by a Gauss-Newton adaptation applied to the genetic population, that reduces the search space and provide faster convergence rate. The use of elitism assures the convergence of the algorithm. Several experiments were conducted on digital signals and mixing models, and the high amount of simulations derived from them provided the best combination of the constant parameters in terms of separation accuracy and convergence rate. In this sense, we also achieve a robust blind source separation method that efficiently adapts to the statistical nature of the mixing signals, within a low population of the genetic algorithm.

关键词： Biological cells Genetics Matrices Convergence Bismuth Source separation Gallium

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DSP structure to motion computation on reconfigurable hardware

DSP structure to motion computation on reconfigurable hardwa...

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Independent Component Analyses, Wavelets, Neural Networks, Biosystems, and Nanoengineering VII

作者： Botella, Guillermo García, Antonio Rodríguez, Manuel Meyer-Baese, Uwe Dept. Computer Architecture Universidad Complutense de Madrid 28040 Madrid Spain Dept. Electronics and Computer Technology University of Granada 18071 Granada Spain Dept. Architecture and and Computer Technology University of Granada 18071 Granada Spain Dept. Electrical and Computer Engineering Tallahassee FL 32310-6046 United States

ISBN: (纸本)9780819476098

Since the world presents a dynamically changing environment, we need synthetic systems that can process and respond to motion. The main contribution of this work is the efficient implementation of a biologically inspired DSP architecture for gradient motion estimation that borrows nature templates as inspiration and makes use of an specific model of human visual motion perception: Multi Channel Gradient Model. This model can be enhanced using psychophysical and bioinspired properties according to biological vision in order to mimic the behavior and the performance of the mammalians. The architecture is designed with an asynchronous pipeline, chaining several signal processing stages. Experimental results and resource consumption are discussed, analyzing the associated customization of the system. This work concludes with several comparisons with the actual contributions and examples for synthetic sequences and real image applications. © 2009 SPIE.

关键词： Real time systems

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High-efficiency low-cost accelerometer-aided gyroscope calibration

High-efficiency low-cost accelerometer-aided gyroscope calib...

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2009 International Conference on Test and Measurement, ICTM 2009

作者： Olivares, Alberto Olivares, Gonzalo Górriz, J.M. Ramírez, J. Dept. of Computer Architecture and Computer Technology University of Granada Granada Spain Dept. of Signal Theory Networking and Communications University of Granada Granada Spain

ISBN: (纸本)9781424447008

Inertial Measurement Units (IMUs) are gaining popularity in several application fields, such as navigation, body motion monitoring and indoors positioning. Microelectromechanical (MEMS) accelerometers and gyroscopes are used for this purpose since they offer a reasonable price-performance trade-off. However, they still present several undesired characteristics in their output that should be compensated through proper device calibration. Although accelerometers are quite easy to calibrate, gyroscopes need more complex systems and equipment to achieve an accurate calibration. This paper shows a novel calibration system using simple equipment (a bike wheel as a turntable) designed for an IMU which is used for a knee telerehabilitation system and composed of a triaxial accelerometer and a biaxial gyroscope. MEMS Accelerometers are usually more accurate and offer better performance than MEMS gyroscopes. Thus, accelerometer data is used to help calibrate the gyroscope by applying a novel, simple, yet accurate set of maneuvers. © 2009 IEEE.

关键词： Calibration

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computer aided diagnosis of alzheimer disease using support vector machines and classification trees

Computer aided diagnosis of alzheimer disease using support ...

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15th International Conference on Neuro-Information Processing, ICONIP 2008

作者： Salas-Gonzalez, D. Górriz, J.M. Ramírez, J. López, M. Álvarez, I. Segovia, F. Puntonet, C.G. Dept. of Signal Theory Networking and Communications University of Granada Granada 18071 Spain Dept. of Computer Architecture and Computer Technology University of Granada Granada 18071 Spain

ISBN: (纸本)3642030394

This paper presents a computer-aided diagnosis technique for improving the accuracy of the early diagnosis of the Alzheimer type dementia. The proposed methodology is based on the combination of support vector machine learning with linear kernels and classification trees. The classification tree technique allows to choose wisely the most discriminant set of voxels in the images. Thus, the classification tree produces a considerably improvement upon considering the support vector machine classifier only. © 2009 Springer Berlin Heidelberg.

关键词： computer aided diagnosis

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Selecting regions of interest for the diagnosis of alzheimer's disease in brain SPECT images using welch's t-test

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10th International Work-Conference on Artificial Neural Networks, IWANN 2009

ISBN: (纸本)3642024777

This paper presents a computer-aided diagnosis technique for the diagnosis of Alzheimer type dementia. The proposed methodology is based on the selection of voxels which present a Welch's t-test between both classes, Normal and Alzheimer images, greater than a given value. The mean and standard deviation of intensity values are calculated for selected voxels. They are chosen as feature vectors for two different classifiers: support vector machines with linear kernel and classification trees. The proposed methodology reaches an accuracy greater than 98 % in the classification task. © 2009 Springer Berlin Heidelberg.

关键词： computer aided diagnosis

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Analysis of brain SPECT images for the diagnosis of alzheimer disease using first and second order moments

Analysis of brain SPECT images for the diagnosis of alzheime...

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3rd International Work-Conference on the Interplay Between Natural and Artificial Computation, IWINAC 2009

作者： Salas-Gonzalez, D. Górriz, J.M. Ramírez, J. López, M. Álvarez, I. Segovia, F. Puntonet, C.G. Dept. of Signal Theory Networking and Communications University of Granada 18071 Granada Spain Dept. of Computer Architecture and Computer Technology University of Granada 18071 Granada Spain

ISBN: (纸本)3642022669

This paper presents a computer-aided diagnosis technique for improving the accuracy of the early diagnosis of the Alzheimer type dementia. The proposed methodology is based on the selection of the voxels which present greater overall difference between both modalities (normal and Alzheimer) and also lower dispersion. We measure the dispersion of the intensity values for normals and Alzheimer images by mean of the standard deviation images. The mean value of the intensities of selected voxels is used as feature for different classifiers, including support vector machines with linear kernels, fitting a multivariate normal density to each group and the k-nearest neighbors algorithm. The proposed methodology reaches an accuracy of 92 % in the classification task. © 2009 Springer Berlin Heidelberg.

关键词： computer aided diagnosis

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Selecting regions of interest for the diagnosis of alzheimer using brain SPECT images

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6th International Symposium on Neural Networks, ISNN 2009

作者： Salas-Gonzalez, Diego Górriz, Juan M. Ramírez, Javier Álvarez, Ignacio López, Míriam Segovia, Fermín Puntonet, Carlos G. Dept. of Signal Theory Networking and Communications University of Granada Granada 18071 Spain Dept. of Computer Architecture and Computer Technology University of Granada Granada 18071 Spain

ISBN: (纸本)3642015123

This paper presents a computer-aided diagnosis technique for improving the accuracy of the early diagnosis of the Alzheimer type dementia. The proposed methodology is based on the selection of those voxels which present a greater difference between normals and Alzheimer's type dementia patients. The mean value of the intensities of the selected voxels are used as features for different classifiers. The proposed methodology reaches an accuracy of 89% in the classification task. © 2009 Springer Berlin Heidelberg.

关键词： computer aided diagnosis

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computer aided diagnosis of Alzheimer’s disease using principal component analysis and bayesian classifiers 6

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6th International Symposium of Neural Networks, ISNN 2009

作者： López, Miriam Ramírez, Javier Górriz, Juan M. Álvarez, Ignacio Salas-Gonzalez, Diego Segovia, Fermin Puntonet, Carlos García Dept of Signal Theory Networking and Communications University of Granada Spain Dept of Architecture and Computer Technology University of Granada Spain

ISBN: (纸本)9783642012150

Functional brain imaging with PET (Positron Emission Tomography) and SPECT (Single Photon Emission Computed Tomography) has a definitive and well established role in the investigation of a variety of conditions such as Alzheimer’s Disease (AD). Nowadays the inspection of PET and SPECT images is performed by expert clinicians, but usually entails time consuming and subjective steps. This work aims at providing an automatic tool to assist the interpretation of SPECT and PET images for the diagnosis of AD. The main problem to be handled is the so-called small size sample, which consists in having a small number of available images compared to the large number of features. This problem is faced up by reducing intensively the dimension of the feature space by means of Principal Component Analysis (PCA). Our approach is based on bayesian classifiers, which uses the a posteriori information to determine to which class the subject belongs, yielding 88.6% and 98.3% accuracy for SPECT and PET images respectively. © Springer-Verlag Berlin Heidelberg 2009.

关键词： Principal component analysis

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