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PD pattern recognition in Transformers Based on Grey-scale Images and Affinity Propagation Algorithm 19

PD Pattern Recognition in Transformers Based on Grey-scale I...

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3rd international conference on Virtual and Augmented Reality Simulations (ICVARS)

作者： Wei, Bengang Huo, Kaixuan Yao, Zhoufei Lou, Jie Li, Xiangyao Shanghai Elect Power Co Elect Power Res Inst 171 Handan Rd Shanghai Peoples R China Shandong Univ Sch Elect Engn 17923 Rd Jinan Shandong Peoples R China

ISBN: (纸本)9781450365925

Partial discharge (PD) pattern recognition plays an important role in determining insulation defects and understanding insulation condition of transformers. In this paper, four PD models are set up in laboratory and pulse current method is used to measure the amplitude of apparent charge, the power frequency phase of PD pulses and the frequency of PD pulses. There are 19 feature parameters which include fractal features, moment features, and textural features are extracted form grey-scale images of phase resolved partial discharge (PRPD) patterns. In order to reduce the computational complexity of the classifier, principal component analysis (PCA) is used to reduce the dimensions of feature parameters and five new feature parameters which explain 93.50% of total variance are obtained. The kernel function and shared nearest neighbors (SNN) are used to improve affinity propagation (AP) algorithm. A classifier based on improved AP with particle swarm optimization (PSO) is established for PD pattern recognition in transformers. Based on these new feature parameters, the PD patterns are recognized by AP classifier, back propagation neural networks (BPNN) and least squares support vector machine (LSSVM). recognition rate of AP classifier is 85%

关键词： Partial discharge pattern recognition affinity propagation (AP) algorithm grey-scale images Kernel function

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The real time face recognition 3

The real time face recognition

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3rd international conference on Advanced Information and Communications Technologies, AICT 2019

作者： Sveleba, Serhiy Katerynchuk, Ivan Karpa, I. Kunyo, I. Ugryn, S. Ugryn, V. Ivan Franko National University of Lviv 107 Tarnavsky St. Lviv Ukraine

ISBN: (纸本)9781728123998

The effectiveness of different modifications of local binary templates was investigated in relation to the problem of face recognition in real time. It has been found that centrally symmetric local binary patterns are practically inferior to other variations of the LBP as recognition attributes, and at the same time have a much higher speed. Based on the study, it was concluded that histograms of centrally symmetric local binary templates are an effective feature for the classification of individuals in real time. © 2019 IEEE.

关键词： Local binary pattern

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Improving pattern Matching performance in Genome sequences using Run Length Encoding in Distributed Raspberry Pi Clustering Environment 3

Improving Pattern Matching performance in Genome sequences u...

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3rd international conference on Computing and Network Communications, CoCoNet 2019

作者： Kanani, Pratik Padole, Mamta Department of Computer Science and Engineering Maharaja Sayajirao University of Baroda Vadodara390001 India

Genomics and bioinformatics have grown as an independent field and are an area of active research currently. In this work, we first discuss the idea of the genome, its importance and wide-ranging applications in healthcare and medicine. We then give a brief overview of the various file formats used presently to store and manipulate genomic data along with their benefits and shortcomings. Moving on, we analyze and elaborate on how parallel and distributed computing can help in processing large files with genomic data and more importantly address the problem of pattern matching. In particular, we introduce the raspberry-pi and discuss in detail how a Raspberry Pi can accomplish the pattern matching task and how a Raspberry-Pi cluster can enable parallel computing to improvise the performance. This work also includes a brief account of various high-level application programming interfaces and libraries that can be used to parse genomic data like BioPython and Fuzzywuzzy. We conclude this work by summarizing some techniques that can be used for encoding and compressing files with genomic data like Run-Length encoding and genome differential compression respectively among other methods. The proposed work improvises the Genome pattern matching time by more than 50% in a distributed Raspberry Pi Computing environment. This system is useful to detect a particular genome-based abnormality where different pieces of Genome records are present on the different nodes in distributed computing and the input is given to find the disease. It can detect the abnormality within a short time. Also the different approach used here is to use Raspberry Pi based clustering to save cost and the energy. © 2020 The Authors. Published by Elsevier B.V.

关键词： pattern matching

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2019 Joint 8th international conference on Informatics, Electronics and Vision, ICIEV 2019 and 3rd international conference on Imaging, Vision and pattern recognition, icIVPR 2019 with international conference on Activity and Behavior Computing, ABC 2019

2019 Joint 8th International Conference on Informatics, Elec...

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Joint 8th international conference on Informatics, Electronics and Vision and 3rd international conference on Imaging, Vision and pattern recognition, ICIEV and icIVPR 2019

ISBN: (纸本)9781728107868

The proceedings contain 64 papers. The topics discussed include: performance analysis and mitigating the challenges of constraint-based local search;MR-anonymization: a relationship-based privacy model;challenges in sensor-based human activity recognition and a comparative analysis of benchmark datasets: a review;interpretable machine learning with boosting by Boolean algorithm;effects of illumination color on autonomic response to exercise;implementing an efficient SAT solver for structured instances;a comparative study on missing data handling using machine learning for human activity recognition;and prediction of gender and age from inertial sensor-based gait dataset.

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Performance Evaluation of Multirotor UAV by Considering the Balanced pattern 3rd

Performance Evaluation of Multirotor UAV by Considering the ...

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3rd international conference on Machine Learning for Cyber Security, ML4CS 2020

作者： Lv, Min Lin, Cong Ma, Tianran Hong, Sheng China Academy of Information and Communications Technology Beijing100191 China AVIC China Aero-Polytechnology Establishment Beijing100028 China Beihang University Beijing100191 China

ISBN: (纸本)9783030624590

The multirotor UAV is a typical k-out-of-n pair: G model, which means that the two rotors distributed on the same axis must be synchronized operating. That is to say, if a rotor is failed, then the opposite one soluble shut down to keep the UAV in a balanced state. However, the above-mentioned model does not consider the effect of torque generated by rotating rotors. Thus, the neutralization of torque, which is ignored by k-out-of-n pair: G model, must be considered. In this situation, we employ the k-out-of-n pair: G balanced model to describe the balanced pattern of the multirotor UAV. We use the finite Markov chain imbedding approach to establish the system reliability calculating equations for the UAV and we also derive the performance evaluation indexes, the mean residual capacity and the expected time to failure, which can be used to determine the usage of the UAV. Then, we use some numerical examples to demonstrate it is worthy of involving the balance pattern in the system modeling process, otherwise, the we may obtain an over optimistic reliability evaluation result that misguides the operation of the UAV. © 2020, Springer Nature Switzerland AG.

关键词： Unmanned aerial vehicles (UAV)

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GIS Partial Discharge Type Identification Based on Optimized Support Vector Machine 3

GIS Partial Discharge Type Identification Based on Optimized...

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3rd IEEE international Electrical and Energy conference (CIEEC)

作者： Wang, Junbo Liu, Bin Zhang, Chunxu Yang, Fudong Zhang, Tingting Miao, Xingshun Yantai Power Supply Co State Grid Shandong Elect Power Co Yantai Peoples R China Shandong Univ Sch Elect Engn Jinan Peoples R China

ISBN: (纸本)9781728116754

The fault diagnosis of partial discharge in GIS is of great significance to the evaluation of the operation status of GIS. The traditional pattern recognition algorithms include neural networks and support vector machines (SVM). However, the isolated data points in the data samples will cause over-fitting during classifier training because of the existence of interference signals. The training error was continuously reduced and the complexity of the model was continuously improved, which eventually leads to an increase in generalization error and a decrease in recognition rate. In order to solve these problems, four partial discharge models were established and detected by UHF method to extract characteristic parameters. Besides, SVM was optimized by choosing appropriate kernel function, adopting L2 regularization and principal component analysis (PCA). The recognition accuracy of 96.5% can be achieved. The recognition speed was improved by applying PCA. The results show that the optimized SVM algorithm can improve the efficiency of pattern recognition.

关键词： GIS SVM pattern recognition partial discharge PCA

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Interdisciplinary Workshop on Trust, Identity, Privacy, and Security in the Digital Economy, DETIPS 2020, 1st international Workshop on Dependability and Safety of Emerging Cloud and Fog Systems, DeSECSys 2020, 3rd international Workshop on Multimedia Privacy and Security, MPS 2020 and 2nd Workshop on Security, Privacy, Organizations, and Systems Engineering, SPOSE 2020 in conjunction with 25th European Symposium on Research in Computer Security, ESORICS 2020

Interdisciplinary Workshop on Trust, Identity, Privacy, and ...

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Interdisciplinary Workshop on Trust, Identity, Privacy, and Security in the Digital Economy, DETIPS 2020, 1st international Workshop on Dependability and Safety of Emerging Cloud and Fog Systems, DeSECSys 2020, 3rd international Workshop on Multimedia Privacy and Security, MPS 2020 and 2nd Workshop on Security, Privacy, Organizations, and Systems Engineering, SPOSE 2020 in conjunction with 25th European Symposium on Research in Computer Security, ESORICS 2020

ISBN: (纸本)9783030665036

The proceedings contain 19 papers. The special focus in this conference is on Trust, Identity, Privacy, and Security in the Digital Economy. The topics include: IMC: A Classification of Identity Management Approaches;making Picnic Feasible for Embedded Devices;sandboxing the Cyberspace for Cybersecurity Education and Learning;cloudVaults: Integrating Trust Extensions into System Integrity Verification for Cloud-Based Environments;twizzle - A Multi-purpose Benchmarking Framework for Semantic Comparisons of Multimedia Object Pairs;you’ve Got Nothing on Me! Privacy Friendly Face recognition Reloaded;OR-Benchmark: An Open and Reconfigurable Digital Watermarking Benchmarking Framework;nothing Standard About It: An Analysis of Minimum Security Standards in Organizations;the Bigger Picture: Approaches to Inter-organizational Data Protection Impact Assessment;systematic Scenario Creation for Serious Security-Awareness Games;analysing Simulated Phishing Campaigns for Staff;Keeping it Human: A Focus Group Study of Public Attitudes Towards AI in Banking;Creative Toolkits for TIPS;post-quantum Certificates for Electronic Travel Documents;development of Trust Infrastructures for Virtual Asset Service Providers;risk Assessment of Sharing Cyber Threat Intelligence;kUBI: A Framework for Privacy and Transparency in Sensor-Based Business Models for Consumers: A Pay-How-You-Drive Example;Verifiable Contracting: A Use Case for Onboarding and Contract Offering in Financial Services with eIDAS and Verifiable Credentials;ICITPM: Integrity Validation of Software in Iterative Continuous Integration Through the Use of Trusted Platform Module (TPM);SPOSE 2020 Preface.

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Research on Emergency Communication Command and Scheduling Algorithm Based on pattern recognition 1

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3rd European-Alliance-for-Innovation (EAI) international conference on Advanced Hybrid Information Processing (ADHIP)

作者： Li, Jun Xing, Jun Shenzhen Acad Inspect & Quarantine Shenzhen Peoples R China

ISBN: (数字)9783030364021

ISBN: (纸本)9783030364021;9783030364014

In the process of regular pattern recognition, due to the limitation of the algorithm, the emergency communication command and dispatch has a delay and a certain deviation. In order to solve the above problems, an emergency communication command and scheduling algorithm based on pattern recognition is proposed. The delay time constraint is determined by the time interval calculation, and the channel line selection is performed on the basis of the established condition, and the control transmission amount is below the maximum amount supported by the selected channel line, according to the information length, the priority level is divided and the ratio of the command scheduling algorithm is studied. The proposed algorithm is compared with the traditional command and dispatch algorithm, and the balance is more than 10% higher than the traditional algorithm;the scheduling time is also saved by about 30 s, which fully proves the feasibility of the scheduling algorithm.

关键词： pattern recognition Emergency communication Scheduling algorithm

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Arduino microcontroller based Cashline Security System based on vein recognition Using Dactylography Technology 3

Arduino microcontroller based Cashline Security System based...

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3rd international conference on Computing Methodologies and Communication (ICCMC)

作者： Rubini, M. Kavisarathi, M. Kaviya, R. Shankarr, B. P. Kiruba Pavithra, A. Praveen, R. KS Rangasamy Coll Technol Dept Elect & Commun Engn Tiruchengode India

ISBN: (纸本)9781538678084

In recent times, Cashline Systems are highly used for most of the bank transactions. Cashline system security is becoming more and more important in all aspects. On other hand the ATM frauds such as Duplicating ATM cards and card skimming were increased. To overcome such frauds dactylography technology is used in the proposed system. The advantage of the dactylography technology results on an entirely card free transaction. Even for the identical twins, the finger vein pattern is matchless. The width of the vein may be changed due to temperature changes or blood pressure but the centre line become stable. Then the extracted line will be used for the future identification purpose. The cashline system is to increase authenticity, confidentiality as well as user trust towards ATM transaction. After the analyzation of finger vein of the authenticated person, the next step is followed by means of the analyzed one's finger vein matching with the recorded vein pattern of the related banks database. Then high security level GSM module will generate an OTP and sends it to the authorized users mobile then followed by entering the OTP to the ATM machine, the verification is done and then further transaction process is followed.

关键词： Dactylography finger vein pattern GSM OTP

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Facial Expression recognition Using Extreme Learning Machine 3

Facial Expression Recognition Using Extreme Learning Machine

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3rd international conference on Informatics and Computational Sciences (ICICoS)

作者： Shafira, Serenada Salma Ulfa, Nadya Wibawa, Helmie Arif Rismiyati Univ Diponegoro Fac Math & Sci Dept Informat Semarang Indonesia

ISBN: (纸本)9781728146102

Facial expression recognition is one of the technological capabilities in identifying a face image to follow up on research conducted by psychologists. The recognition of facial expressions is very important to know the emotions of someone who is experiencing it. In this study two datasets were used, namely the FER2013 and CK + datasets. The FER2013 dataset and CK+ are datasets designed to identify facial expressions. At the feature extraction stage, it uses the Histogram of Oriented Gradient (HOG) feature dan Local Binary pattern (LBP) feature. Whereas in the classification stage, the Extreme Learning Machine (ELM) classifier is used. The greatest accuracy by using HOG feature is 63.86% for the FER2013 dataset and 99.79% for the CK + dataset with sigmoid as an activation function. And the greatest accuracy by using LBP feature is 55.11% for the FER2013 dataset and 98.72% for the CK + dataset with RBF as an activation function.

关键词： facial expression recognition histogram of oriented gradient local binary pattern extreme learning machine

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