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Signal recovery in PDM optical communication systems employing independent component analysis

Signal recovery in PDM optical communication systems employi...

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IEEE International Symposium on Circuits and Systems (ISCAS)

作者： E. S. Rosa L. T. Duarte J. M. T. Romano R. Suyama DSPCom-Laboratory of Signal Processing for Communications School of Electrical and Computer Engineering (FEEC) State University of Campinas-UNICAMP Sao Paulo Brazil Engineering Modeling and Applied Social Sciences-CECS Federal University of ABC UFABC Sao Paulo Brazil

There is a growing interest in employing digital signal processing methods to compensate the distortions typical of the next generation optical systems. For instance, several works considered the multi-user constant modulus algorithm (MU-CMA) to recover the transmitted signals in Polarization Division Multiplexing (PDM) systems. In this work, the same problem is tackled through independent component analysis methods. The obtained results point out that, differently from the MU-CMA, our proposal is robust against sources loss even when polarization dependent loss is present.

关键词： Optical fibers Optical distortion Optical polarization Optical fiber dispersion Integrated optics Chromatic dispersion

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Accelerating MatLab code using GPU: A review of tools and strategies

Accelerating MatLab code using GPU: A review of tools and st...

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International Conference on Artificial Intelligence, Management Science and Electronic Commerce (AIMSEC)

作者： Baida Zhang Shuai Xu Feng Zhang Yuan Bi Linqi Huang National laboratory for Parallel and Distributed Processing School of Computer National University of Defense Technology Changsha China Department of Information Engineering Academy of Armored Forces Engineering Beijing China Inspur (Beijing) Electronic Information Industry Company Limited Beijing China Naval Academy of Armament Beijing China School of Resources and Safety Engineering Central South University Changsha China

Lots of toolboxes of accelerating MatLab using GPU are available now[1], but, users are confused by which toolbox is best suitable for a particular task. Three toolboxes-Jacket, GPUmat, and parallel Computing Toolbox of MatLab are selected. For each toolbox, its advantages and pitfalls are reviewed, with an aim to allow the reader to identify which toolbox is appropriate for a given task. Strategies of whether a function should execute on GPU are given after a formula analysis. The analysis is also a framework for program automatically decides which function is cost-efficient to execute on GPU. A series of benchmark of different types of computing, including data transfer between GPU and CPU, data matrix Generation, matrix operation and GPU functions were tested in all three toolboxes. And the results show that Jacket is the best one. Some advices to improve the performance of toolboxes are given in the end.

关键词： Graphics processing unit Acceleration parallel processing computer architecture Conferences Licenses MATLAB

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Detection of Collagenous Colitis Based on Histopathology Image Segmentation of Colon

Detection of Collagenous Colitis Based on Histopathology Ima...

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Iranian Machine Vision and Image processing (MVIP)

作者： Vahid Malekian Mojgan Mokhtari Saeid Sadri Rasoul Amirfattahi Alireza Aghaie Digital Signal Processing Research Laboratory Department of Electrical and Computer Engineering Isfahan University of Technology Isfahan Iran School of Medicine Isfahan University of Medical Sciences Isfahan Iran Isfahan University of Technology Isfahan Isfahan IR

Collagenous colitis is prevalent among pathological diseases. Because of normal radiological and endoscopic appearances, the microscopic image of colon tissue is necessary and important material for investigation of this disease. In this paper, a computerized system is developed for collagenous colitis diagnosis. First, colon tissues are colored with Mason trichrome to make sub-epithelial collagen band to be appeared in blue. Second, preprocessing is done on the microscopic image of colon tissue, and then Color histogram features in HSV color space and Haar Wavelet energy in detail coefficients of sub-band images are implemented to characterize the histological structure representation for tissue classification. KNN Classifier is selected for this classification, which segments the sub-epithelial collagen band from the image, and finally, thickness of sub-epithelial collagen band is determined by morphological operations. Abnormal case will be recognized if the thickness of sub-epithelial collagen band be more than 10 μm. Fifty clinical image samples were employed in the training and testing procedures for the evaluation of system performance. Through the applied classification it was revealed that collagenous colitis can be diagnosed accurately.

关键词： Microscopy Image color analysis Colon Feature extraction Image segmentation Training Histograms

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AASVMES: An intelligent expert system for realization of Adaptive Autonomy using Support Vector Machine

AASVMES: An intelligent expert system for realization of Ada...

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International Conference on Control, Instrumentation, and Automation

作者： N. Hassanpour M. A. Zamani A. Fereidunian H. Lesani Systems and Machines Research Laboratory (SMRL) Control and Intelligent Processing Center of Excellence (CIPCE) School of ECE University of Tehran Tehran Iran Electrical and Computer Engineering Department K. N. Toosi University of Technology Tehran Iran

We earlier introduced a novel framework for realization of Adaptive Autonomy (AA) in human-automation interaction (HAI). This study presents an expert system for realization of AA, using Support Vector Machine (SVM), referred to as Adaptive Autonomy Support Vector Machine Expert System (AASVMES). The proposed system prescribes proper Levels of Automation (LOAs) for various environmental conditions, here modeled as Performance Shaping Factors (PSFs), based on the extracted rules from the experts' judgments. SVM is used as an expert system inference engine. The practical list of PSFs and the judgments of GTEDC's (the Greater Tehran Electric Distribution Company) experts are used as expert system database. The results of implemented AASVMES in response to GTEDC's network are evaluated against the GTEDC experts' judgment. Evaluations show that AASVMES has the ability to predict the proper LOA for GTEDC's Utility Management Automation (UMA) system, which changes in relevance to the changes in PSFs; thus providing an adaptive LOA scheme for UMA.

关键词： Support vector machines Training Expert systems Complexity theory Automation Adaptive systems Humans

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PARTICLE SWARM OPTIMIZATION（PSO）OF POWER ALLOCATION IN COGNITIVE RADIO SYSTEMS WITH INTERFERENCE CONSTRAINTS

PARTICLE SWARM OPTIMIZATION（PSO）OF POWER ALLOCATION IN COG...

引用

2011 4th IEEE International Conference on Broadband Network and Multimedia Technology

作者： Saeed Motiian Mohammad Aghababaie Hamid Soltanian-Zadeh Control and Intelligent Processing Center of Excellence School of Electrical and Computer Engineering Colleague of EngineeringUniversity of TehranTehran 14399-57131Iran School of Cognitive Sciences Institute for Research in Fundamental Sciences(IPM)Tehran 19548-56316 Iran Image Analysis Laboratory Radiology DepartmentHenry Ford HospitalDetroitMichigan 48202USA

Cognitive radio is used for enhancement of spectrum *** many works have been accomplished on the power allocation of cognitive radio,limited efforts have considered evolutionary *** this paper,we study this problem in the cognitive radio networks where interference constraints are defined for protection of quality of service（QoS）for both primary and secondary *** defined as functions of the signal-to-interference-plus-noise ratio（SINR） are matched for each secondary user which meets Nash’s *** general,the region of utilities that meets the constraints is *** is possible to make simplifications,generate a convex region,and then use common convex optimization approaches to obtain a ***,Particle Swarm Optimization（PSO）does not need such simplifications and thus its results are superior to those of the convex optimization *** is an evolutionary algorithm based on social intelligence,utilized in many optimization *** is a global optimizations algorithm that does not require the objective function be differentiable as required in classic optimization methods.

关键词： Cognitive radio Power allocation Particle Swarm Optimization（PSO）.

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A novel method for identification of COPD in inspiratory and expiratory states of CT images

A novel method for identification of COPD in inspiratory and...

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Middle East Conference on Biomedical engineering (MECBME)

作者： M. Parsa Hosseini Hamid Soltanian-Zadeh Shahram Akhlaghpoor Department of Electrical Engineering Islamic Azad University Tehran Iran Department of Radiology Henry Ford Health System Image Analysis and Communications Laboratory Detroit MI USA Control and Intelligent Processing Center of Excellence School of Electrical and Computer Engineering University of Tehran Tehran Iran Department of Radiology Tehran University of Medical Sciences Sina Hospital Tehran Iran

Chronic obstructive pulmonary disease (COPD) refers to a group of lung diseases that block airflow and cause a huge degree of human suffering. While there is no cure for COPD and the lung damage that results in this disease cannot be reversed, it is very important to diagnose it as early as possible. Additional to diagnosis, using a mathematical model to estimate severity of disease would be helpful for evaluation of treatment effects. This paper presents a new method for identifying COPD from three-dimensional (3-D) pulmonary X-ray CT images. The method has five main steps. First, corresponding positions of lungs in inspiration and expiration are found based on anatomical structures. Then, lung regions are segmented from the CT images by active contours. Next, the left and right lungs are separated using a sequence of morphological operations. Then, parenchyma variations in each lung are found as a relationship between inspiratory and expiratory states. Finally, a classifier is used to decide about the disease and its severity. A t-test is done to evaluate the results. Twelve patients with variable severity of COPD and twelve normal adults were included in this study. The proposed method may assist radiologists in the detection of COPD as a computer aided diagnosis (CAD) system.

关键词： Lungs Computed tomography Diseases Image segmentation Biomedical imaging Gaussian distribution

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Assessing lung volumetric variation to detect and stage COPD

Assessing lung volumetric variation to detect and stage COPD

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Middle East Conference on Biomedical engineering (MECBME)

Chronic obstructive pulmonary disease (COPD) is a devastating disease. In this paper, we propose a novel method for scoring of air trapping in the lungs for detection and evaluation of COPD. The proposed method finds volumetric changes of the lungs from inspiration to expiration. To this end, trachea CT images at full inspiration and expiration are compared. For this comparison, the lungs parenchyma in the inspiration and expiration images are found and changes in the surface and volume of the lungs between inspiration and expiration are used to define quantitative measures (features). Using these features, the subjects are classified into two groups of normal class and COPD patients using a Bayesian classifier. In addition, t-tests are applied to evaluate discrimination powers of the features for this classification. The main advantage of the proposed method is its ability to estimate air trapping in the lungs from CT images without human intervention. The proposed method may assists radiologists in the detection of COPD as a computer aided diagnosis (CAD) system. It may also assist them with the scoring of the disease (severity of air trapping in the lungs).

关键词： Lungs Computed tomography Diseases Active contours Image segmentation Charge carrier processes

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A joint multi rate optimization framework for video adaptation in H.264/AVC

A joint multi rate optimization framework for video adaptati...

引用

14th IEEE International Symposium on Consumer Electronics, ISCE 2010

作者： Semsarzadeh, Mehdi Hashemi, Mahmoud Reza Multimedia Processing Laboratory School of Electrical and Computer Engineering University of Tehran Iran

ISBN: (纸本)9781424466726

Due to the explosive growth in ubiquitous multimedia access, one needs to adapt the considerable number of preencoded video content to a wide variety of user constraints such as different resolution, bitrate, frame rate, processing power and platform. Current adaptation frameworks do not take the encoder into account. In other words the encoder optimizes its outcome for the base layer only, regardless of the remaining adaptation layers and the resulted distortion once the adaptation is applied. In this paper, a joint multi rate optimization algorithm has been proposed for H.264/AVC that generates an encoded bitstream that will have the minimum distortion across all the layers combined, hence providing an improved experience for a larger number of users. The proposed scheme, that only supports bitrate adaption, is independent of the adaptation algorithm and is applicable to most existing adaptation frameworks. Simulation results indicate that the proposed scheme improves the video quality by up to 0.8 dB. The quality improvement of the adapted content is more significant in lower bitrates where even small improvements are visually noticeable due to the inherent low quality in these bitrates. © 2010 IEEE.

关键词： Signal encoding

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Voxel based treatment prediction using diffusion anisotropy indices and spatial information in Glioblastoma Multiform tumor

Voxel based treatment prediction using diffusion anisotropy ...

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Iranian Conference of Biomedical engineering (ICBME)

作者： Hadi Sabahi Hamid Soltanian-Zadeh Lisa Scarpace Tom Mikkelsen Control and Intelligent Processing Center of Excellence School of Electrical and Computer Engineering University of Tehran Tehran Iran Image Analysis Laboratory Radiology Department Henry Ford Hospital Detroit MI USA Hermelin Brain Tumor Research Center Neurosurgery Department Henry Ford Health System Detroit MI USA

In this paper, we propose a method to predict the outcome of Bevacizumab therapy on Glioblastoma Multiform (GBM) tumors. The method uses diffusion anisotropy indices (DAI) and spatial information to predict the treatment response of each tumor voxel. These DAIs are Fractional Anisotropy, Mean Diffusivity, Relative Anisotropy, and Volume Ratio, extracted from Diffusion Tensor Imaging (DTI) data before treatment. The spatial information is considered as the distance of each tumor voxel from the tumor center, extracted from pre-treatment post-contrast T1-weighted Magnetic Resonance Images (pc-T1-MRI). DAIs and spatial information of each tumor voxel are considered as feature vector. DTI and pc-T1-MRI are gathered before and after the treatment of seven GBM patients. First, DAIs of all brain voxels and the distance of each tumor voxel from the tumor center are calculated. Second, the method registers pre-treatment DAI maps and post-treatment pc-T1-MRI to pre-treatment pc-T1-MRI. Next, the tumor is segmented using thresholding technique from pc-T1-MRI. Then, Gd-enhanced voxels of the pre- and post-treatment pc-T1-MRI are compared to label the feature vectors. Three classifiers were evaluated, including Support Vector Machine, K-Nearest Neighbor, and Artificial Neural Network. Classification results show a preference for K-Nearest Neighbor based on well-established performance measures.

关键词： Tumors Anisotropic magnetoresistance Diffusion tensor imaging Support vector machines Feature extraction Artificial neural networks

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Simulation research of communication networks based on prim algorithm

Simulation research of communication networks based on prim ...

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International Forum on Information Technology and Applications

作者： Yang, Chenghui Ren, ChuanJun College of Electrical Engineering Northwest University for Nationalities Lanzhou 730030 China National Laboratory for Parallel and Distributed Processing College of Computer Science National University of Defense Technology Changsha 410073 China

ISBN: (纸本)9780769541150

In order to improve the efficiency of the communication networks, we used the Kruskal algorithm and the Prim algorithm through algorithm comparison and analysis methods of data structure. A dynamic framework for the communication network installed system is built. Moreover, according to the actual framework of the communication network specific issues, the module chooses the Minimum Cost Spanning Tree Prim algorithm ultimately. The assumptions process and outcomes simulation have proper analysis and certification by C language. Experimental results show that the Minimum Cost Spanning Tree of Prim algorithm on the installed system for communication networks dynamic planning process have the advantage of speed and effectively reduce the waste of resources, which not only can ensure efficiency but also can effectively improve communication networks installed cost. © 2010 IEEE.

关键词： Costs

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