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Peptide sequence tag-based blind identification-based SVM model

Peptide sequence tag-based blind identification-based SVM mo...

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9th international conference on Machine Learning and Applications, ICMLA 2010

作者： Li, Hui Liu, Chunmei Liu, Xumin Diakite, Macire Burge, Legand Yakubu, Abdul-Aziz Southerland, William Dept. of Systems and Computer Science Howard Univ. Washington DC 20059 United States Dept. of Computer Science Rochester Institute of Technology Rochester NY 14623 United States Dept. of Mathematics Howard University 2400 6th Street NW Washington DC 20059 United States Dept. of Biochemistry Howard University 2400 6th Street NW Washington DC 20059 United States

ISBN: (纸本)9780769543000

Identifying the ion types for a mass spectrum is essential for interpreting the spectrum and deriving its peptide sequence. In this paper, we proposed a novel method for identifying ion types and deriving matched peptide sequences for tandem mass spectra. We first divided our dataset into a training set and a testing set and then preprocessed the data using a Support Vector Machine and a 5-fold cross validation based dual denoting model. then we constructed a syntax tree and generated a rule set to match the mass values from experimental mass spectra with the mass spectral values from corresponding theoretical mass spectra. Finally we applied the proposed algorithm to a tandem mass spectral dataset consisting of 2656 spectra from yeast. Compared with other methods, the experimental results showed that the proposed method can effectively filter noise and successfully derive peptide sequences. © 2010 IEEE.

关键词： Support vector machines

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discrete Synapse Recurrent Neural Network for nonlinear system modeling and its application on seismic signal classification

Discrete Synapse Recurrent Neural Network for nonlinear syst...

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2010 6th IEEE World Congress on Computational Intelligence, WCCI 2010 - 2010 international Joint conference on Neural Networks, IJCNN 2010

作者： Park, Hyung O. Dibazar, Alireza A. Berger, theodore W. DRB140 1042 Downey way Los Angeles CA 90089 United States United States USA United States

ISBN: (纸本)9781424469178

For a lumped nonlinear modeling of the relationship between input and output sequences, discrete Synapse Recurrent Neural Network (DSRNN) is proposed using fully Recurrent Neural Network (RNN) structure and Extended Kalman Filter (EKF) algorithm for its training. the training process is more efficient and there is less output error and more stability than in the previous study using feedforward networks. DSRNN is applied to a task of seismic signal classification to discriminate footsteps and vehicles from background. Temporal features of the signals were modeled using data recorded in the deserts of Joshua Tree, CA. the proposed classifier showed 0.3% false recognition rate for the recognition of human footsteps, 0.9% for vehicle, and 0.0% for background. the models were able to reject quadrupedal animal's footsteps (in this study a trained dog). the system rejected dog's footsteps with 0.2% false recognition rate. © 2010 IEEE.

关键词： Recurrent neural networks

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Membrane protein prediction using wavelet decomposition and pseudo amino acid based feature extraction

Membrane protein prediction using wavelet decomposition and ...

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international conference on Emerging Technologies

作者： Hayat, Maqsood Khan, Asifullah Department of Computer and Information Sciences Pakistan Institute of Engineering and Applied Sciences Nilore Islamabad Pakistan

ISBN: (纸本)9781424480586

Membrane proteins play an important role in many biological processes and are attractive drug targets. In this study, membrane proteins are classified using two feature extraction and several classification strategies. the first feature extraction strategy is pseudo amino acid (PseAA) composition;utilizing hydrophobicity and hydrophilicity for reflecting the sequence order effects, while the second method is discrete wavelet analysis (DWT);analyzing the different components of a signal localized both in space and scale domains. the nearest neighbor, probabilistic neural network, support vector machine, random forest, and Adaboost are used as basic learning mechanisms. the predicted results of the base learners are combined using majority voting to form an ensemble classifier. the best accuracy obtained for the Jackknife and independent dataset test is 85.4% and 95.3%, respectively. Using performance measures such as MCC, Sensitivity, Specificity, and F-measure, it has been observed that PseAA based prediction is significantly higher than that of the DWT, and is also the best reported, so far. © 2010 IEEE.

关键词： discrete wavelet transforms

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Computing n-Variate Orthogonal discrete Wavelet Transforms on Graphics Processing Units

Computing <i>n</i>-Variate Orthogonal Discrete Wavelet Trans...

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6th international conference on Large-Scale Scientific Computing (LSSC 2009)

作者： Dechevsky, Lubomir Gundersen, Joakim Bang, Borre Narvik Univ Coll N-8505 Narvik Norway

ISBN: (纸本)9783642125348

In [4,5] an algorithm was proposed for isometric mapping between smooth n-variate n-dimensional vector fields and fractal curves and surfaces, by using orthonormal wavelet bases. this algorithm matched only the orthonormal bases of scaling functions (the "V-spaces" of multiresolution analyses). In the present communication we shall consider a new algorithm which matches the orthonorrnal bases of wavelets (the "W-spaces" of multiresolution analyses). Being of Cantor diagonal type, it was applicable for both bounded and unbounded domains, but the complexity of its implementation was rather high. In [3] we proposed a simpler algorithm for the case of boundary-corrected wavelet basis on a bounded hyper-rectangle. hi combination with the algorithm for the "V-spaces" from [4,5], the new algorithm provides the opportunity to compute multidimensional orthogonal discrete wavelet transform (DWT) in two ways via the "classical" way for computing multidimensional wavelet transforms, and by using a commutative diagram of mappings of the bases, resulting in an equivalent computation on graphics processing units (GPUs). the orthonormality of the wavelet bases ensures that the direct and inverse transformations of the bases are mutually ad joint (transposed in the case of real entries) orthogonal matrices, which eases the computations of matrix inverses in the algorithm. 1D and 2D orthogonal wavelet transforms have been first implemented for parallel computing on GPUs using C++ and OpenGL shading language around the year 2000: our new algorithm allows to extend general-purpose computing on GPUs (GPGPU) also to higher-dimensional wavelet transforms. If used in combination with the Cantor diagonal type algorithm of [4,5] (the "V-space" basis matching) this algorithm can in principle be applied for computing DWT of n-variate vector fields defined on the whole R(n). However, if boundary-corrected wavelets are considered for vector-fields defined on a bounded hyper-rectangle in R(n), th

关键词： Graphics processing unit

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Evolutionary algorithm for protein structure prediction

Evolutionary algorithm for protein structure prediction

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international conference on Natural Computation

作者： Mansour, Nashat Kanj, Fatima Khachfe, Hassan Department of Computer Science and Mathematics Lebanese American University Lebanon Department of Biology and Biomedical Sciences Lebanese International University Lebanon

ISBN: (纸本)9781424459612

A protein is characterized by its 3D structure, which defines its biological function. the protein structure prediction problem has real-world significance where several diseases are associated with the wrong folding of proteins. Predicting protein structures is computationally intractable. In this paper, we present an improved genetic algorithm (GA) for predicting 3D structures of proteins based on the hydrophobic polar model. We evaluate our proposed GA on a number of protein sequences. the generated protein structures demonstrate improvement over previously published results. © 2010 IEEE.

关键词： Genetic algorithms

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HMM training by a hybrid of chaos optimization and Baum-Welch algorithms for discrete speech recognition

HMM training by a hybrid of chaos optimization and Baum-Welc...

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作者： Cheshomi, Somayeh Rahati-Q, Saeed Akbarzadeh-T, Mohammah-R. Islamic Azad University Mashhad Iran Ferdowsi University Mashhad Iran

ISBN: (纸本)9788988678275

HMM has high power to describe complex phenomena. the Baum-Welch (BW) algorithm is very popular estimation method that use for estimating HMM model parameters but it start with an initial guess and finally converge to a local optimum in practice. Chaos often exists in nonlinear systems. It has many good properties such as ergodicity , stochastic properties, regularity and high sensitivity to initial states .In this paper by use of these properties of chaos, an effective hybrid CHAOS-BW optimization method is proposed that uses the Chaos Optimization algorithm to optimize the initial values of Baum Welch algorithm. this algorithm not only overcomes the shortcoming of becoming trapped in local optimum of the BW algorithm, but is also fast and requires less storage than other hybrid optimization algorithms such as GABW, PSOBW and GAPSOBW. Experimental results on Persian digit dataset show that the propose method has both qualities of global search as well as rapid convergence. Comparison with several other more conventional approaches also reveals superior performance of the proposed model.

关键词： Hidden Markov models

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Utility Greedy discrete Bit Loading for Interference Limited Multi-Cell OFDM System

Utility Greedy Discrete Bit Loading for Interference Limited...

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international conference on Wireless Communications, Networking and Mobile Computing (WiCom)

作者： Xinghui Su Tiejun Lv Xuefen Yu Shaoshi Yang Yonghua Li Key Laboratory of Universal Wireless Communications Ministry of Education Beijing University of Posts and Telecommunications Beijing China

In this contribution we present the solution of the utility greedy discrete bit loading for interference limited multicell OFDM networks. Setting the utility as the sum of consumed power proportions, the algorithm follows greedy way to achieve the maximum throughput of the system. Simulation has shown that the proposed algorithm has better performance and lower complexity than the traditional optimal algorithm. the discussion of the results is provided .

关键词： Loading Interference Partitioning algorithms throughput Resource management Complexity theory OFDM

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A Robust Audio Watermarking Algorithm Based on Statistical Characteristics and DWT+DCT Transforms

A Robust Audio Watermarking Algorithm Based on Statistical C...

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international conference on Wireless Communications, Networking and Mobile Computing (WiCom)

作者： Rajkiran Ravula Suresh Rai Department of Electrical and Computer Engineering Louisiana State University Baton Rouge LA USA

this paper considers quantization based audio watermarking algorithm based on both discrete Wavelet Transforms (DWT) and discrete Cosine Transform (DCT). the embedding information used is a binary image. Different techniques like Arnold Transform and Linear Feedback Shift Register are used for image encryption. Different wavelet filters are considered and the performance is evaluated. Watermark embedding is performed by mean quantization of DCT values of n th level low frequency components where n ε {3, 4, 5}. Low frequency components contains majority of the signals energy, which helps provide robustness. Synchronization codes are embedded in the low frequency components of the audio signal, and it makes algorithm more robust against desynchronized attacks. Experimental results show that the proposed algorithm is inaudible and robust against common signal processing techniques. Our results are better than those obtained using techniques involving only single domain transformations such as [2], [9] and [10].

关键词： Watermarking discrete wavelet transforms Quantization discrete cosine transforms Robustness Signal processing algorithms

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Block-based image error concealment using fragile watermarking in error-prone channels

Block-based image error concealment using fragile watermarki...

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Iranian Machine Vision and Image Processing (MVIP)

作者： Razieh Keshavarzian Ali Aghagolzadeh Hadi Seyedarabi Javad Musevi Niya Faculty of Electrical and Computer Engineering University of Tabriz Tabriz Iran

the transmission of block-coded images over wireless channels results in lost blocks. In this paper, we propose a new error concealment method for covering up the high packet losses of an original image after its transmission through an error-prone channel. In this scheme, discrete Wavelet Transform (DWT) is applied to each block of the original image in order to produce a lower resolution copy of the each block. then, we choose approximation coefficients of each block as replica of the block and embed it into a remote block of the image in the spatial domain. It is shown that the proposed scheme provides significant improvement over existing algorithms in terms of both subjective and objective evaluations. this technique can be implemented for wireless channels to combat degradations in a backward-compatible scheme.

关键词： Watermarking discrete wavelet transforms Pixel PSNR Image reconstruction Decoding Approximation methods

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Deblocking filters for block-based ICA transform coding

Deblocking filters for block-based ICA transform coding

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international conference on Emerging Technologies, ICET

作者： Asim Munir Bushra Asghar Muhammad Nadeem Department of Computer Science International Islamic University Islamabad Pakistan

Deblocking is required when data rate of a video stream is low. Images taken from such video streams also contain blocking artifacts. Similarly, when the images are compressed by ICA (Independent Component Analysis) transform coding, the resultant decompressed images are blocky. this paper describes the outcome of applying deblocking filters on ICA decoded images by using two schemes namely, “deblocking filter for low bit rate MPEG-4 video” and “low complexity deblocking method for DCT coded video signals”, respectively. the experiment is conducted on three sets of images at different quantization parameter. According to the results, the deblocking filter of scheme1 provides better SNR ratio than that of scheme2.

关键词： Signal to noise ratio Transform coding Filtering algorithms Image edge detection discrete cosine transforms Low pass filters

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