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bioinformatics Study with an Implementation of Two Feature Extraction Algorithms for Protein Sequences

Bioinformatics Study with an Implementation of Two Feature E...

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3rd international conference on Material Science, Environment Science and Computer Science (MSESCS 2014)

作者： Qiao, Shanping Univ Jinan Sch Informat Sci & Engn Jinan 250022 Peoples R China

ISBN: (纸本)9783038350118

Predicting subcellular localizations of proteins is related to multi-label learning. A serial of computational approaches have been developed. This study focuses on the extracting protein features. The feature vector influences the performance of a predicting algorithm significantly. In this paper, two feature extraction algorithms named composition-transition-distribution and class pattern frequency were introduced and implemented in Java, respectively: This program provided a friendly graphical user interface where users can get these two kinds of features easily and quickly. Moreover, the results can be saved into a specified file for later use. Finally, this program can be compressed into a single jar file and runs on a computer which installed the proper JRE. We hope that this program would give researchers some help in the future.

关键词： protein subcellular localization prediction feature extraction algorithm Java

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3rd international conference on Frontiers in Intelligent Computing: Theory and Applications, FICTA-2014

3rd International Conference on Frontiers in Intelligent Com...

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3rd international conference on Frontiers in Intelligent Computing: Theory and Applications, FICTA-2014

ISBN: (纸本)9783319119328

The proceedings contain 95 papers. The special focus in this conference is on Data Warehousing and Mining, Machine Learning, Mobile and Ubiquitous Computing, AI, E-commerce and Distributed Computing and Soft Computing, Evolutionary Computing, Bio-inspired Computing and *** topics include: Approximation neural network for phoneme synthesis;pattern-matching for speaker verification;online clustering algorithm for restructuring user web search results;optimal computer based analysis for detecting malarial parasites;a survey of dynamic program analysis techniques and tools;extended self organizing map with probabilistic neural network for pattern classification problems;fuzzy rule-based adaptive proportional derivative controller;sentence completion using text prediction systems;architectural recommendations in building a network based secure, scalable and interoperable internet of things middleware;mean interleaved round robin algorithm;cryptanalysis of image encryption based on permutation-substitution using chaotic map and Latin square image cipher;windowed Huffman coding with limited distinct symbols by least recently used symbol removable;theme interception sequence learning;energy efficient distributed topology control technique with edge pruning;dynamic cache resizing in flashcache;heuristic for context detection in time varying domains;construction of automated concept map of learning using hashing technique;analysis of estimation techniques for feature based navigation of unmanned air vehicles;curved videotext detection and extraction;an approach to utilize FMEA for autonomous vehicles to forecast decision outcome;diffusion and encryption of digital image using genetic algorithm;character recognition using teaching learning based optimization;the fuzzy robust graph coloring problem;detection of moving object and image steganography using integer wavelet transform based on color space approach.

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A Density based clustering with Artificial Immunity inspired preprocessing 3

A Density based clustering with Artificial Immunity inspired...

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3rd international conference on Advances in Computing, Communications and Informatics (ICACCI)

作者： Paul, Swama Kamal Bhaumik, Parama Tata Consultancy Serv Informat Technol Kolkata India Jadavpur Univ Informat Technol Kolkata India

ISBN: (纸本)9781479930807

In this paper we propose an algorithm which can identify varied shaped clusters from wide variety of input dataset with high degree of accuracy in presence of noise. The initial data processing module adopts a novel approach of Artificial Immune system to reduce data redundancy while preserving the original data patterns. The clustering module pursues a density based approach to identify clusters from the compressed dataset produced by the preprocessing module. We introduced several new concepts like selective Antigenic binding, Local Reachability Factor, Global Reachability Factor to effectively recognize clusters with varied shape, varied density and low intercluster separation with acceptable computational cost. We performed experimental evaluation of our algorithm with wide variety of real and synthetic dataset and obtained higher cluster success rate for all dataset when compared to DBSCAN.

关键词： Density based clustering algorithms pattern recognition Artificial Immune Systems Detecting varied shaped clusters Machine Learning

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Multi-objective clustering of tissue samples for cancer diagnosis 3

Multi-objective clustering of tissue samples for cancer diag...

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3rd international conference on Advances in Computing, Communications and Informatics (ICACCI)

作者： Acharya, Sudipta Thadisina, Yamini Saha, Sriparna Indian Inst Technol Patna Dept Comp Sci & Engn Patna 800013 Bihar India

ISBN: (纸本)9781479930807

In the field of pattern recognition, the study of the gene expression profiles for different tissue samples over different experimental conditions has became feasible with the arrival of micro-array based technology. In cancer research, classification of tissue samples is necessary for cancer diagnosis, which can be done with the help of micro-array technology. In this article we have presented a multi-objective optimization (MOO) based clustering technique utilizing AMOSA (Archived Multi-Objective Simulated Annealing) as the underlying optimization strategy for classification of tissue samples from cancer data sets. As objective functions three cluster validity indices namely, XB, PBM, and FCM indices are optimized simultaneously to form more accurate clusters of tissue samples. The presented clustering technique is evaluated for two open source benchmark cancer data sets, which are Brain tumor data set and Adult Malignancy data set. In order to evaluate the quality or goodness of produced clusters two cluster quality measures viz, Adjusted Rand Index (ARI) and Classification Accuracy (% CoA) are calculated for each data set. Comparative results of the presented clustering algorithm with 10 state-of-the-art existing single-objective, multi-objective based clustering algorithms are shown for two benchmark data sets.

关键词： cancer genetics medical computing patient diagnosis pattern classification pattern clustering simulated annealing tumours AMOSA ARI FCM indices MOO based clustering technique PBM indices XB indices adjusted rand index adult malignancy data set archived multiobjective simulated annealing brain tumor data set cancer data sets cancer diagnosis classification accuracy cluster quality measures cluster validity indices gene expression profiles microarray based technology multiobjective clustering multiobjective optimization optimization strategy pattern recognition tissue samples classification Cancer Clustering algorithms Indexes Linear programming Measurement Optimization Tumors

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Experimental research in applying generative design and 3D printers in user participating design

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3rd international conference on Design, User Experience, and Usability: Theories, Methods, and Tools for Designing the User Experience, DUXU 2014, Held as Part of 16th international conference on Human-Computer Interaction, HCI international 2014

作者： Lee, Lin-Chien James Lin, Ming-Huang Institute of Applied Arts National Chiao Tung University Taiwan

ISBN: (纸本)9783319076676

This research applied an open structure of generative design in order to provide parametric sliders for users to adjust a digital model under the designer's plan. Moreover, the design outcome can be printed immediately using 3D printing technology, to experiment with users' preferences and see the effects of generative design in modifying pattern, regular/irregular and detail transformations on a product. Three types of feature modification on i-phone4 case were chosen as simulations by 3 design experts. Five experienced and five young designers were asked to manipulate a digital generative design model as they want. Then 2D rendering images and 3D printed mockups were presented for subjects to compare with their original design. The result demonstrated that experienced and young designers both can recognized their work in 3D print mockups. Experienced designers can use the limited tool to make distinct outcomes for more satisfaction form tan subjects. Young designers expected to obtain 3D printed mockup to help their design decision in design process. © 2014 Springer international Publishing Switzerland.

关键词： Mockups

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Target recognition technology based on wavelet transform 3

Target recognition technology based on wavelet transform

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3rd international conference on Advanced Engineering Materials and Architecture Science (ICAEMAS)

作者： Chen, Yu Song, Yulong Huo, Furong Changchun Univ Sci & Technol Sch Optoelect Engn Changchun 130022 Peoples R China Changchun Inst Opt Fine Mech & Phys Changchun 130022 Peoples R China

ISBN: (纸本)9783038352679

Hybrid optoelectronic joint transform correlator is a very effecitve tool to recognize a target, which has important application in military and industry field. However, in actual applications, under some situations, such as complex target background or insufficient contour information etc., the intensity of correlation peaks will be weak. Sometimes, the weak intensity of correlation peaks can not be recognized by joint transform correlator. Wavelet transform is adopted to process the joint target image. The principles of joint transform correlator and wavelet transform are given in this paper. As an actual example, a tank target is adopted to test the feasibility and effectiveness of this method. From computer simulation, we can get good experimental effect. After wavelet transform of joint target image, the intensity of correlation peaks has been increased obviously. Optical experiments confirm the feasibility and effectiveness of this method further. Amounts of experiments prove wavelet transform can extract the target contour effectively. Based on the principle of the proposed algorithm, the target recognizing rate can be increased to a higher level.

关键词： pattern recognition Joint transform correlator Target recognition Wavelet transform cluttered background

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Metric generalization and modification of classification algorithms based on formal concept analysis 3

Metric generalization and modification of classification alg...

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3rd international Workshop "What can FCA do for Artificial Intelligence"?, FCA4AI 2014, Co-Located with the European conference on Artificial Intelligence, ECAI 2014

作者： Kolmakov, Evgeny Faculty of Computational Mathematics and Cybernetics Lomonosov Moscow State University Russia

FCA-based classifiers can deal with nonbinary data representation in different ways: use it directly or binarize it. Those algorithms that binarize data use metric information from the initial feature space only as a result of scaling (feature binarization procedure). Metric approach in this area allows one significantly reducing classification refusals number and provides additional information which can be used for classifier training. In this paper we propose an approach which generalizes some of existing FCA classification methods and allows one to modify them. Unlike other algorithms, the proposed classifier model uses initial metric information together with order object-attribute dependencies.

关键词： Classification Formal concept analysis pattern recognition

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. New ART2/ART2A Algorithm Apply to Entire Real Number Field

. New ART2/ART2A Algorithm Apply to Entire Real Number Field

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3rd international conference on Materials and Products Manufacturing Technology (ICMPMT 2013)

作者： Xu Yongcheng Li Yue Shen Guoji Dong Bin Natl Univ Def Technol Lab Sci & Technol Integrated Logist Support Changsha Hunan Peoples R China China Aerodynam Res & Dev Ctr Mianyang Sichuan Peoples R China

ISBN: (纸本)9783037859162

In this paper, two shortcomings of standard ART2/ART2A algorithm were revealed through theoretical analysis: (1)Standard ART2/ART2A algorithm is only suitable for the case in the nonnegative real number field because of a limit of pretreating process in F-1 layer;(2)Even through all input patterns are shifted to the nonnegative real number field through coordinate transformation, the standard ART2/ART2A algorithm can not correctly recognize those patterns which have same phase, but different amplitudes. As a result, the standard ART2/ART2A algorithm is not quite suitable for universal pattern recognition. So this paper presented a new nonlinear transforming function in F-1 layer and a new competitive learning formula in F-2 layer for traditional ART2/ART2A algorithm. The applicable scope of the new ART2/ART2A algorithm is expanded to entire real number field from nonnegative real number field. The result of typical calculation example shows that the presented algorithm is effective.

关键词： Adaptive Resonance Theory ART2 ART2A Neural Network pattern recognition

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Consideration for Interpretation of Brain Activity pattern during Car Driving Based on Human Movements 1

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3rd international conference on Design, User Experience, and Usability (DUXU)

作者： Shimizu, Shunji Inoue, Hiroaki Nara, Hiroyuki Miwakeichi, Fumikazu Hirai, Nobuhide Kikuchi, Senichiro Watanabe, Eiju Kato, Satoshi Tokyo Univ Sci SUWA Tokyo 162 Japan Hokkaido Univ Sapporo Hokkaido 060 Japan Inst Stat Mathmat Tokyo Japan Tokyo Med & Dent Univ Tokyo Japan Jichi Med Univ Tokyo Japan

ISBN: (数字)9783319076386

ISBN: (纸本)9783319076386;9783319076379

The purpose in this research is to contribute to developing of assistive robot and related-apparatus. Recently, there is a pressing need to develop a new system which assists and acts for car driving and wheelchair for the elderly as the population grows older. In terms of developing a new system, it is thought that it is important to examine behaviors as well as spatial recognition. Therefore, experiments have been performed for an examination of human spatial perceptions, especially right and left recognition, during car driving using NIRS. In previous research, it has been documented that there were significant differences at dorsolateral prefrontal cortex at left hemisphere during virtual driving task and actual driving. In this paper, brain activity during car driving was measured and detailed analysis was performed by segmentalizing brain activity during car driving on the basis of subjects' motion. So, we report the relationship between brain activity and movement concerned with perception during driving in this paper.

关键词： brain information processing during driving task spatial cognitive task determining direction NIRS

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recognition of facial expression via kernel PCA network 3

Recognition of facial expression via kernel PCA network

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3rd international conference on Information Technology and Management Innovation, ICITMI 2014

作者： Hu, De Kun Ye, An Sheng Li, Li Zhang, Li Key Laboratory of Pattern Recognition and Intelligent Information Processing Institutions of Higher Education of Sichuan Province Chengdu University Chengdu China

ISBN: (纸本)9783038352396

In this work, a kernel principle component analysis network (KPCANet) is proposed for classification of the facial expression in unconstrained images, which comprises only the very basic data processing components: cascaded kernel principal component analysis (KPCA), binary hashing, and block-wise histograms. In the proposed model, KPCA is employed to learn multistage filter banks. It is followed by simple binary hashing and block histograms for indexing and pooling. For comparison and better understanding, We have tested these basic networks extensively on many benchmark visual datasets(such as the JAFFE [13] database, the CMU AMP face expression database, a part of the Extended Cohn-Kanade (CK+) database), The results demonstrate the potential of the KPCANet serving as a simple but highly competitive baseline for facial expression recognition. © 2014 Trans Tech Publications, Switzerland.

关键词： Database systems

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