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检索条件"任意字段=5th International Conference on Pattern Recognition in Bioinformatics"

共 1336 条记录，以下是441-450 订阅

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21st international Workshops on Financial Cryptography and Data Security, FC 2017 held in conjuction with 5th Workshop on Encrypted Computing and Applied Homomorphic Cryptography, WAHC 2017, 4th Workshop on Bitcoin and Blockchain Research, BITCOIN 2017, 2nd Workshop on Advances in Secure Electronic Voting Schemes, VOTING 2017, 1st Workshop on Trusted Smart Contracts, WTSC 2017 and 1st Workshop on Targeted Attacks, TA 2017

21st International Workshops on Financial Cryptography and D...

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21st international Workshops on Financial Cryptography and Data Security, FC 2017 held in conjuction with 5th Workshop on Encrypted Computing and Applied Homomorphic Cryptography, WAHC 2017, 4th Workshop on Bitcoin and Blockchain Research, BITCOIN 2017, 2nd Workshop on Advances in Secure Electronic Voting Schemes, VOTING 2017, 1st Workshop on Trusted Smart Contracts, WTSC 2017 and 1st Workshop on Targeted Attacks, TA 2017

ISBN: (纸本)9783319702773

the proceedings contain 39 papers. the special focus in this conference is on Financial Cryptography and Data Security. the topics include: Preface: Bitcoin 2017: 4th workshop on bitcoin and blockchain research;Preface: VOTING 2017: Second workshop on advances in secure electronic voting schemes;Preface: WTSC 2017: First workshop on trusted smart contracts;Preface: TA 2017: First workshop on targeted attacks;Simple encrypted arithmetic library - SEAL v2.1;switch commitments: A safety switch for confidential transactions;pieceWork: Generalized outsourcing control for proofs of work;enhancing bitcoin transactions with covenants;decentralized prediction market without arbiters;An analysis of bitcoin OP_RETURN metadata;constant-deposit multiparty lotteries on bitcoin;exchange pattern mining in the bitcoin transaction directed hypergraph;incentivizing blockchain forks via whale transactions;mixing coins of different quality: A game-theoretic approach;smart contracts make bitcoin mining pools vulnerable;towards privacy-preserving multi-party bartering;batchVote: Voting rules designed for auditability;existential assertions for voting protocols;marked mix-nets;pseudo-code algorithms for verifiable re-encryption mix-nets;Using selene to verify your vote in JCJ;a roadmap to fully homomorphic elections: Stronger security, better verifiability;enabling vote delegation for boardroom voting;practical governmental voting with unconditional integrity and privacy;findel: Secure derivative contracts for ethereum;decentralized execution of smart contracts: Agent model perspective and its implications;multi-level access in searchable symmetric encryption;a concurrent perspective on smart contracts;an Empirical analysis of smart contracts: Platforms, applications, and design patterns;trust in smart contracts is a process, as well;defining the ethereum virtual machine for interactive theorem provers.

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Metrics for clustering comparison in bioinformatics 5

Metrics for clustering comparison in bioinformatics

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5th international conference on pattern recognition Applications and Methods, ICPRAM 2016

作者： Rossi, Giovanni University of Bologna Mura Anteo Zamboni 7 Bologna40126 Italy

ISBN: (纸本)9789897581731

Developing from a concern in bioinformatics, this work analyses alternative metrics between partitions. From both theoretical and applicative perspectives, a useful and interesting distance between any two partitions is HD, which counts the number of atoms finer than either one but not both. While faithfully reproducing the traditional Hamming distance between subsets, HD is very sensible and computable through scalar products between Boolean vectors. It properly deals with complements and axiomatically resembles the entropy-based variation of information VI distance. Entire families of metrics (including HD and VI) obtain as minimal paths in the weighted graph given by the Hasse diagram: submodular weighting functions yield path-based distances visiting the join (of any two partitions), whereas supermodularity leads to visit the meet. this yields an exact (rather than heuristic) approach to the consensus partition (combinatorial optimization) problem. © Copyright 2016 by SCITEPRESS-Science and Technology Publications, Lda. All rights reserved.

关键词： Hamming distance

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A Method for Calculating the Similarity of TF-IDF Texts for Synonyms in Biomedical Domains

A Method for Calculating the Similarity of TF-IDF Texts for ...

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2017 5th international conference on Frontiers of Manufacturing Science and Measuring Technology(FMSMT 2017)

作者： Miao Hao Ke Fan School of Computer Science and Technology Chongqing University of Posts and Telecommunications Institute for Bioinformatics Chongqing University of Posts and Telecommunications

ISBN: (纸本)9781510840232

In the traditional text similarity calculation, most of the TF-IDF method. TF-IDF establishes the word frequency vector for the text, and calculates the cosine between the vectors as the similarity of the text. the algorithm is widely used in many search engines, information retrieval system can be seen, but in the text of the vocabulary processing is not ideal. the synonyms between professional phrases are not perceived by models, and they are used as different words to calculate similarity. In this paper, synonymous with biomedical field as an example, in the TF-IDF model embedded synonyms recognition function. Firstly, this method acquires the synonyms of the vocabulary in the biomedical field and establishes the synonyms, then identifies the synonyms in the TF-IDF model and calculates the better weight of the phrase. the experimental results show that this method can effectively improve the precision of text similarity calculation in biomedical field, and it is a more effective than the traditional TF-IDF text similarity calculation method.

关键词： FT-IDF texts Synonyms Biomedical domains

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Design and Implementation of a Robust System for Recognizing Alphabets using Artifical Neural Network 5

Design and Implementation of a Robust System for Recognizing...

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5th international conference on Reliability, Infocom Technologies and Optimization (Trends and Future Directions) (ICRITO)

作者： Kapoor, Shubhankar Singh, Ashish Goswami, Utkarsh Kumar, Saswat Chitranshi, Gaurav Amity Univ Dept Elect & Commun Engn Noida Uttar Pradesh India

ISBN: (纸本)9781509014897

Language or pattern recognition is an ever-growing field in research. the motivation behind this work is the growing importance of foreign languages in everyday life. It is specifically focused on groups who might have to face a foreign language somewhere and can't seem to understand it. this will also be beneficial for partially visually impaired persons. It will help in recognizing the alphabets and letters written in a particular language stored in the database. the program was trained with different samples of a different letters of an alphabet and the data was stored. Using Artificial Neural Network and pattern recognition techniques, the hardware can now read whatever form of letter is presented in front of it. Using the neural network the success rate was found to be higher than 97%.

关键词： Artificial neural network supervised learning pattern recognition

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Molecular Modeling: Application of Support Vector Machines and Decision Trees for Anti-HIV Activity Prediction of Organic Compounds 5

Molecular Modeling: Application of Support Vector Machines a...

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5th international conference on Multimedia Computing and Systems (ICMCS)

作者： Bjij, Imane Hdoufane, Ismail Jarid, Abdellah Cherqaoui, Driss Villemin, Didier Fac Sci Semlalia Dept Chem BP 2390 Marrakech Morocco ENSI ISMRA LCMT CNRSUMR 6507 6 Blvd Marechal Juin F-14050 Caen France

ISBN: (纸本)9781509051465

Multivariate methods of pattern recognition, classification and discriminant analysis have been found most useful in many types of chemical and biological problems. Predicting the biological activity of molecules from their chemical structures is a principal problem in drug discovery. pattern recognition has gained attention as methods covering this need. In the present study classification models for inhibiting Human Immunodeficiency Virus (HIV) activity, based on Support Vector Machines (SVM) and Decision trees (DT), are developed. the obtained results indicate that SVM and DT can be employed as a forceful tool for quantitative structure-activity relationship studies.

关键词： pattern recognition SVM DT Drug Design HIV

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A novel algorithm for string matching with mismatches 5

A novel algorithm for string matching with mismatches

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5th international conference on pattern recognition Applications and Methods, ICPRAM 2016

作者： Vinod-Prasad, P. Sur College of Applied Sciences Ministry of Higher Education Muscat Oman

ISBN: (纸本)9789897581731

We present an online algorithm to deal with pattern matching in strings. the problem we investigate is commonly known as 'string matching with mismatches' in which the objective is to report the number of characters that match when a pattern is aligned with every location in the text. the novel method we propose is based on the frequencies of individual characters in the pattern and the text. Given a pattern of length M, and the text of length N, both defined over an alphabet of size σ, the algorithm consumes O(M) space and executes in O(MN/σ) time on the average. the average execution time O(MN/σ) simplifies to O(N) for patterns of size M ≤ σ. the algorithm makes use of simple arrays, which reduces the cost overhead to maintain the complex data structures such as suffix trees or automaton. © Copyright 2016 by SCITEPRESS -Science and Technology Publications, Lda. All rights reserved.

关键词： pattern matching

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Convolutional Neural Network Training with Artificial pattern for Bangla Handwritten Numeral recognition 5

Convolutional Neural Network Training with Artificial Patter...

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5th international conference on Informatics, Electronics and Vision (ICIEV)

作者： Akhand, M. A. H. Ahmed, Mahtab Rahman, M. M. Hafizur Khulna Univ Engn & Technol Dept Comp Sci & Engn Khulna Bangladesh Int Islamic Univ Malaysia KICT Dept Comp Sci Selangor Malaysia

ISBN: (纸本)9781509012695

recognition of handwritten numerals has gained much interest in recent years due to its various application potentials. the progress of handwritten Bangla numeral is well behind Roman, Chinese and Arabic scripts although it is a major language in Indian subcontinent and is the first language of Bangladesh. Handwritten numeral classification is a high-dimensional complex task and existing methods use distinct feature extraction techniques and various classification tools in their recognition schemes. Recently, convolutional neural network (CNN) is found efficient for image classification with its distinct features. In this study, a CNN based method has been investigated for Bangla handwritten numeral recognition. A moderated pre-processing has been adopted to produce patterns from handwritten scan images. On the other hand, CNN has been trained with the patterns plus a number of artificial patterns. A simple rotation based approach is employed to generate artificial patterns. the proposed CNN with artificial pattern is shown to outperform other existing methods while tested on a popular Bangla benchmark handwritten dataset.

关键词： Bangla Numeral Convolutional Neural Network pattern Generation Handwritten Numeral recognition

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State recognition of Egg Embryo in Vaccines Production Based on SVM

State Recognition of Egg Embryo in Vaccines Production Based...

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2017 5th international conference on Mechanical, Automotive and Materials Engineering（CMAME 2017）

作者： Yanwei Xu Menghui Chen Tancheng Xie School of Mechatronics Engineering Henan University of Science and Technology

the method for state recognition of egg embryo in biological vaccines production based on computer image processing and support vector machine was ***,the median filtering method was applied to eliminate noises in the images of egg embryo that were classified by the requirements of practical production,then the threshold segmentation method was used to segment the images,then the blood vessels and black blocks in the egg embryo images were selected as major characteristics to *** decision tree classification model with structure of binary tree was built on support vector machine,and the model was trained with the toolkit LIBSVM,the penalty factor C = 2,RBF kernel parameter γ=3.0512 e-05 and the precision of cross validation accuracy is 98.913%.Finally,100 egg embryos were randomly selected as the test samples to do pattern recognition,and compared with manual test *** comparison result showed that the discriminant accuracy of SVM classifier on weak embryo,polluted embryo or dead embryo was 100%,and it of SVM classifier on live embryo was 94.62%.

关键词： egg embryo pattern recognition support vector machine computer image processing

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pattern recognition in real time using neural networks: An application for pressure measurement 5

Pattern recognition in real time using neural networks: An a...

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5th international conference on pattern recognition Applications and Methods, ICPRAM 2016

作者： Piroozan, Parham Department of Mechanical Engineering California State Polytechnic University 3801 W Temple Ave. PomonaCA91768 United States

ISBN: (纸本)9789897581731

Retrieving information in real time from fringe patterns is a topic of great importance in scientific and engineering applications of optical methods. this paper describes an application of neural networks for real time pressure measurement using fringe pattern recognition. It is based on the capability of neural networks to recognize signals that are similar but not identical to the signals which were used to train the network. In this investigation a pressure sensor, which was part of the wall of the wind tunnel, and an optical apparatus were used to produce moirÉ fringes. the fringe patterns generated were analyzed by a back propagation neural network at the speed of the recording device, which was a CCD camera with a pixel resolution of 649 (H) x 491 (V). this method of information retrieval was used to measure the pressure fluctuations in the boundary layer flow. A second neural network was used to recognize the pressure patterns and to provide input to a control system that was capable to preserve the stability of the flow. © Copyright 2016 by SCITEPRESS -Science and Technology Publications, Lda. All rights reserved.

关键词： Pressure sensors

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Global LBP Features for Iris recognition using Blood Vessel Segmentation 5

Global LBP Features for Iris Recognition using Blood Vessel ...

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5th international conference System Modeling and Advancement in Research Trends (SMART)

作者： Bhagat, Kanchan S. Pati, Pramod B. Chaudhari, Jitendra P. JT Mahajan Coll Engn Dept Elect & Telecommun Faizpur India Jhulelal Inst Technol Nagpur Maharashtra India Charotar Univ Sci & Technol Charusat Space Res & Technol Ctr Changa Gujarat India

ISBN: (纸本)9781509035434

Iris recognition is found to be one of the most reliable and efficient technique for biometrics identification. In this paper iris recognition using blood vessel segmentation is proposed. After blood vessel segmentation, the segmented iris image is recognized using global texture features. the GLCM, Gabor and Local Binary patterns are used for feature extraction. the for training of the extracted features using well known SVM classifier. the performance of the system is evaluated on DRIVE and High Resolution Image Databases. the system performs better for the combined features of GLCM and Gabor as compared to individually. the results of LBP are found to be more promising. this proposed approach of iris recognition using blood vessel segmentation is robust and secure and has the ability to recognize retinal images from the photographs of the known iris images. the system is more efficient in terms of accuracy as well as time complexity.

关键词： GLCM Gabor Local Binary pattern Blood Vessel Segmentation SVM

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