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international Electric Drives Production conference (EDPC)

作者： Arnim Reger Cedric Oette Ana Paula Aires Rolf Steinhilper Fraunhofer Projectgroup Processinnovation Fraunhofer IPA Bayreuth Germany Chair of Manufacturing and Remanufacturing Technology Bayreuth University Germany

With the introduction of energy management systems, an analysis of load profiles of manufacturing plants becomes increasingly important. Each manufacturing plant is characterized by a process and product specific power consumption. Often, electric drives are the main power consumers. In this paper methods for pattern recognition in load profiles of electric drives are presented on the example of a multiaxial lathe. A transfer of techniques used for speech recognition e.g. Hidden Markov Models, Fourier and Wavelet Transforms to manufacturing application is discussed. In combination with energy measurement systems, those techniques proved to be a good solution regarding energy efficiency calculations and derivation for key performance indicators. the investigated methods can also be applied to other process data with significant cost advantages, because a lot of process information can be extracted from a single sensor.

关键词： Hidden Markov models Manufacturing Viterbi algorithm Training pattern recognition Maximum likelihood estimation Energy consumption

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Poster: Towards finding unknown genes: the GenomePro framework

Poster: Towards finding unknown genes: The GenomePro framewo...

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IEEE international conference on Computational Advances in Bio and Medical Sciences (ICCABS)

作者： Michael Robinson Naphtali Rishe School of Computer & Information Sciences Florida International University Miami Florida USA

We present a data processing framework aimed at facilitating the discovery of unknown genes in any genome, extracting DNA, RNA or Protein sub-sequences of any length. Using our GenomePro framework, we process raw input data files, of any size, in multiple formats such as NGS, fasta, and GBK, extracting all sub-sequences, of lengths selected by the end user. the only limitations are the computer storage size and/or operating system restrictions. Our framework can be applied to any life form genome.

关键词： Genomics bioinformatics Fingerprint recognition Data mining Data structures DNA Proteins

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Differentiating sub-groups of online depression-related communities using textual cues 1

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16th international conference on Web Information Systems Engineering, WISE 2015

作者： Nguyen, thin O’Dea, Bridianne Larsen, Mark Phung, Dinh Venkatesh, Svetha Christensen, Helen Centre for Pattern Recognition and Data Analytics Deakin University Geelong Australia Black Dog Institute University of New South Wales Sydney Australia

ISBN: (数字)9783319261874

ISBN: (纸本)9783319261867

Depression is a highly prevalent mental illness and is a comorbidity of other mental and behavioural disorders. the Internet allows individuals who are depressed or caring for those who are depressed, to connect with others via online communities;however, the characteristics of these online conversations and the language styles of those interested in depression have not yet been fully explored. this work aims to explore the textual cues of online communities interested in depression. A random sample of 5,000 blog posts was crawled. Five groupings were identified: depression, bipolar, self-harm, grief, and suicide. Independent variables included psycholinguistic processes and content topics extracted from the posts. Machine learning techniques were used to discriminate messages posted in the depression sub-group from the *** predictive validity in depression classification using topics and psycholinguistic clues as features was found. Clear discrimination between writing styles and content, with good predictive power is an important step in understanding social media and its use in mental health. © Springer international Publishing Switzerland 2015.

关键词： Social networking (online)

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Shape matching and object recognition via common base triangle area descriptor

Shape matching and object recognition via common base triang...

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international conference on Electronics Information and Emergency Communication

作者： Dameng Hu Weiguo Huang Jianyu Yang Z. K. Zhu School of Urban Rail Transportation Soochow University Suzhou China

To obtain high recognition accuracy with low time complexity and to reduce the influence of contour deformation due to noise in shape matching, a novel shape matching method based on common base triangle area is proposed. Firstly, a common base triangle area descriptor of each contour point is defined based on the area functions of the triangles formed by its two neighbor points and other contour points. then the descriptor is local smoothed to keep more compact and robust to noise. Secondly, a match cost matrix is obtained by computing the common base triangle area descriptors of all the contour points on two shapes. Finally, the similarity between two shapes is measured on the basis of the match cost matrix by dynamic programming algorithm (DP). the experimental results indicate that this method is robust to contour deformation, and both the computational efficiency and the retrieval rate are essentially improved.

关键词： Shape Robustness Noise Object recognition Shape measurement Smoothing methods pattern analysis

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Message from the technical program co-chairs: ICVRV 2015

Proceedings - 2015 International Conference on Virtual Reali...

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Proceedings - 2015 international conference on Virtual Reality and Visualization, ICVRV 2015 2015年 x-xi页

作者： Wu, Wei Dong, Huailin Zhang, Xiaopeng Pan, Zhigeng Nakatsu, Ryohei State Key Lab of VR Technology and Systems Beihang University China Xiamen University China National Laboratory of Pattern Recognition Institute of Automation CAS China Hangzhou Normal University China Interactive and Digital Media Institute National University of Singapore Singapore

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Emotion recognition System Based on MAPL 5

Emotion Recognition System Based on MAPL

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5th IEEE international conference on Software Engineering and Service Science (ICSESS)

作者： Jiang, Huiping Song, Xiaoyuan Zhou, Zhengjie MinZu Univ China Beijing 100083 Peoples R China

ISBN: (纸本)9781479932795

A EEG signal-based emotion recognition system was designed. the system was developed to operate as a user-independent system, based on MAPL (minority affective picture library), EEG-signal database obtained from multiple ethnic objections. the system consisted of preprocessing, feature extraction and pattern classification stages. Preprocessing and feature extraction methods were devised so that emotion-specific characteristics could be extracted. a simple experiment was carried out, and the classification result is about 56.4%, which indicated that minorities emotion problems can be studied based MPAL emotion recognition system.

关键词： MAPL(minority affective picture library) Ethnic emotion pattern recognition

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ATM - Awesome Translation Machine

ATM - Awesome Translation Machine

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5th international conference on Digital Home (ICDH)

作者： Wang, Hongfei China Ship Dev & Design Ctr Wuhan 430064 Hubei Peoples R China

ISBN: (纸本)9781479942848

In this paper, we present the ATM (Awesome Translation Machine), which translates handwriting texts in English into Chinese, and then provides its pronunciations in both the two languages. Specifically, two types of the databases that contain characters and sentences for training the ATM are constructed. Various signal processing techniques are employed sequentially for processing and analyzing the image raw data. After all the preparation stages, we apply multiple pattern recognition techniques, i.e., principle component analysis, linear discriminant analysis, and support vector machines, for the purpose of character recognition. the identified characters are thereby automatically linked to their actual meanings stored. Extensive experiments are conducted to gauge the performance for different techniques.

关键词： Image capture Image processing Character recognition pattern recognition methods

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Highlights: Predicting the cross-immunoreactivity of hepatitis C virus hyper-variable region 1 peptides using polynomial neural networks

Highlights: Predicting the cross-immunoreactivity of hepatit...

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IEEE international conference on Computational Advances in Bio and Medical Sciences (ICCABS)

作者： James Lara Yury Khudyakov Livia Rossi Gilberto Vaughan Centers for Disease Control Division of Viral Hepatitis Atlanta GA USA Universidade Estadual Paulista Julio de Mesquita Filho Sao Paulo SP BR

Hepatitis C is a liver disease caused by infection with hepatitis C virus (HCV). the number of people infected with HCV is estimated at ~130 million word-wide. Approximately, 70%-80% of HCV-infected patients fail to clear the virus and develop chronic hepatitis C (CHC), which is a well-known risk factor for development of liver fibrosis, cirrhosis and hepatocellular carcinoma (HCC). At the present time, there are no preventive vaccines against HCV. In spite of the different strategies used for vaccine development against HCV, the development of a successful vaccine remains elusive. the HCV genome exhibits high degree of genetic diversity and divergence, which, in addition to HCV's rapid rate of mutation and capacity to escape from the host immune response, has hindered efforts towards the formulation of a broadly protective vaccine. For the study of humoral immunity responses to HCV infection, synthetic peptides derived from the HVR1 of the envelope protein 2 (E2) of HCV genome have been used as immunogens in small animals and non-human primates. HVR 1 peptides contain a neutralizing epitope and are typically very immunogenic in mice and non-human primates although the pattern of reactivity varies significantly depending on the HCV strain. the challenge of developing an efficacious vaccine(s) is finding immunogens capable of eliciting a humoral response that leads the immune system of the host to produce antibodies (Ab's) which broadly and strongly cross-immunoreact against all HCV strains circulating in human populations. the immune-reactivity properties of HCV proteins can be modeled in quantitative-structure-activity-relationship (QSAR) models. Polynomial neural networks, as non-parametric algorithms offer an ideal approach to QSAR studies. In this study, we built polynomial neural networks (PNN) to model the immune-reactivity properties of synthetic HCV HVR1 peptides and examined PNN performance to predict cross-immunoreactive patterns using amino-acid (aa)-base

关键词： Predictive models Liver Vaccines Reactive power Genomics bioinformatics Correlation

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Study of pattern recognition of Morphological Characters for Furniture Image Cognition 5

Study of Pattern Recognition of Morphological Characters for...

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5th international conference on Intelligent Systems Design and Engineering Applications (ISDEA)

作者： Zhang Hua Shen Huajie Hunan Univ Technol Zhuzhou 412007 Hunan Peoples R China Southwest Forestry Univ Kunming 650224 Yunnan Peoples R China

ISBN: (纸本)9781479942626

Based on the corresponding relationship between form and meaning, it analyzes the recognition pattern of furniture morphological characteristics combination with cognitive theory, analyzes the identification process of furniture morphological characteristics. Summarizes two kinds of pattern recognition method for morphological characteristics of furniture, and constructs general recognition model and cognitive pattern recognition model for furniture morphological characteristics. this conclusion suggests morphological feature recognition is the basic and important part of furniture image cognition, it shows people how to cognize furniture image in the product system of non stable. Rational recognition mode and method can ensure the image be accurately realized.

关键词： furniture morphological characteristics characteristics recognition identification method recognition pattern

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Algebraic pattern recognition

Algebraic Pattern Recognition

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5th international conference on Graphic and Image Processing (ICGIP)

作者： Przybylek, Michal R. Univ Warsaw Fac Math Informat & Mech PL-00325 Warsaw Poland

this paper offers an algebraic explanation for the phenomenon of a new and prosperous branch of evolutionary metaheuristics - "skeletal algorithms". We show how this explanation gives rise to algorithms for ... 详细信息

ISBN: (纸本)9781628410013

关键词： pattern recognition data mining theory discovery

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