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检索条件"任意字段=Proceedings of the 2022 11th International Conference on Computing and Pattern Recognition"

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proceedings - 2015 IEEE international conference on Data Science and Data Intensive Systems;8th IEEE international conference Cyber, Physical and Social computing;11th IEEE international conference on Green computing and Communications and 8th IEEE international conference on Internet of things, DSDIS/CPSCom/GreenCom/ithings 2015

Proceedings - 2015 IEEE International Conference on Data Sci...

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2015 IEEE international conference on Data Science and Data Intensive Systems;8th IEEE international conference Cyber, Physical and Social computing;11th IEEE international conference on Green computing and Communications and 8th IEEE international conference on Internet of things, DSDIS/CPSCom/GreenCom/ithings 2015

ISBN: (纸本)9781509002146

the proceedings contain 111 papers. the topics discussed include: identification and validation of real-time health events through social media;active storage mechanism for cluster-wide RAID system;SMASH: a cloud-based architecture for big data processing and visualization of traffic data;sequential pattern mining system for analysis of programming learning history;a mixed and batching authentication protocol for grouped tags in mobile RFID system;scalable data representation in risk management information systems using an XQuery extension;operation-level performance control in the object store for distributed storage systems;exploiting collective spontaneous mobility to improve location prediction of mobile phone users;an event-based framework for the specification and runtime checking of timing constraints in wireless sensor and actuator networks;flow-control policies for wireless sequencer-based causal and total order communication;and malicious node traceback in opportunistic networks using Merkle trees.

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A methodology for procedural piano music composition with mood templates using genetic algorithms 11

A methodology for procedural piano music composition with mo...

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11th international conference of pattern recognition Systems, ICPRS 2021

作者： de Azevedo Santos, Luísa Rocha Silla, Carlos Nascimento da Costa-Abreu, Márjory Federal University of Rio Grande do Norte Natal Brazil PUC-PR Curitiba Brazil Department of Computing Sheffield Hallam University Sheffield United Kingdom

ISBN: (纸本)9781839534300

Creating music in an automatic way has been studied since the beginning of artificial intelligence. One of the biggest obstacles of music generation is the vagueness and subjectivity of the mood or emotion transmitted by a music piece. In this work, we experiment with the generation of piano music using template pieces, represented in MIDI format, as a mood directive. We generated a population of random pieces for templates of two opposing moods - happy and sad - and evolved them with a genetic algorithm until their intended mood was close enough to their respective templates. the fitness function that we implemented uses MIDI statistical features to calculate the distance between the given piece and the template. the generated music pieces were evaluated by human listeners thorough a questionnaire. this evaluation has shown that the generated music pieces were able to express the same mood as the template. However, they still sounded computer-generated, probably due to the lack of rhythm regularity and synchronicity. © 2021 Institution of Engineering and Technology. All rights reserved.

关键词： Music

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Monotony and surprise

引用

11th Annual international conference on computing and Combinatorics (COCOON 2005)

作者： Apostolico, A Univ Padua Dipartimento Ingn Informaz Padua Italy Purdue Univ Dept Comp Sci W Lafayette IN 47907 USA

ISBN: (纸本)3540280618

the extraction of recurrent patterns from sequences is a popular and intensive application, ubiquitous to many domains. Often, however, the process exposes more candidates than one can afford to inspect, thereby defying its whole purpose. While part of this problem is endemic, part of it can be attributed to the traditional definitions of what constitutes a pattern, that hinge alternatively on syntactic or statistical properties alone. It has been seen recently that this part of the problem may be mitigated by more prudent paradigms, in which the syntactic description of a pattern and the list of all of its occurrences are tightly intertwined. this approach leads to identify regions of monotonicity for some scores of surprise in use, within which it is enough to consider and weigh only extremal terms and values. this talk reviews concepts, constructs, and application results obtained along this line of research. © Springer-Verlag Berlin Heidelberg 2005.

关键词： pattern recognition

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Dimensionality Reduction Using External Context in pattern recognition Problems with Ordered Labels

Dimensionality Reduction Using External Context in Pattern R...

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11th international conference on Artificial Intelligence and Soft computing (ICAISC)

作者： Skubalska-Rafajlowicz, Ewa Krzyzak, Adam Rafajlowicz, Ewaryst Wroclaw Univ Technol Inst Comp Engn Control & Robot PL-50370 Wroclaw Poland Concordia Univ Dept Comp Sci & Software Engn Montreal PQ Canada

ISBN: (纸本)9783642293467;9783642293474

Our aim is to propose a new look at the dimensionality reduction in pattern recognition problems by extracting part of variables that are further called external context variables. We show how to incorporate them into the Bayes classification scheme with loss functions that depend on class labels that are ordered. then, the general form of the optimal context sensitive classifier is derived and the learning method that is based on kernel approximation is proposed.

关键词： pattern recognition

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Fast Polar Harmonic Transforms

Fast Polar Harmonic Transforms

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11th international conference on Control, Automation, Robotics and Vision (ICARCV 2010)

作者： Yang, Zhuo Kamata, Sei-ichiro Waseda Univ Grad Sch Informat Prod & Syst Tokyo Japan

ISBN: (纸本)9781424478132

Polar Harmonic Transform (PHT) is termed to represent a set of transforms those kernels are basic waves and harmonic in nature. PHTs consist of Polar Complex Exponential Transform (PCET), Polar Cosine Transform (PCT) and Polar Sine Transform (PST). they are proposed to represent invariant image patterns for two dimensional image retrieval and pattern recognition tasks. they are demonstrated to show superiorities comparing with other methods on describing rotation invariant patterns for images. Kernel computation of PHTs is also simple and has no numerical stability issue. However in order to increase the computation speed, fast computation method is needed especially for real world applications like limited computing environments, large image databases and realtime systems. this paper presents Fast Polar Harmonic Transforms (FPHTs) including Fast Polar Complex Exponential Transform (FPCET), Fast Polar Cosine Transform (FPCT) and Fast Polar Sine Transform (FPST) that are deduced based on mathematical properties of trigonometric functions. the proposed FPHTs are averagely over 6 similar to 8 times faster than PHTs that significantly boost computation process. the experimental results on both synthetic and real data are given to illustrate the effectiveness of the proposed fast transforms.

关键词： Fast Polar Harmonic Transform Fast Polar Complex Exponential Transform Fast Polar Cosine Transform Fast Polar Sine Transform image retrieval pattern recognition

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Cloud computing for Healthcare Services: Technology, Application and Architecture 11

Cloud Computing for Healthcare Services: Technology, Applica...

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11th international Symposium on Signal, Image, Video and Communications, ISIVC 2022

作者： Boudlal, Hicham Serrhini, Mohammed Tahiri, Ahmed Mohammed First University Laboratory of Acsa Faculty of Sciences Oujda Morocco Mohammed First University Laboratory of LaRI Faculty of Sciences Oujda Morocco

ISBN: (纸本)9781665487245

Cloud computing in healthcare becomes a growing field for improvement. the advent of cloud technology provides efficient and reliable outcomes to support healthcare services. Cloud technology reduces these costs for consumers and IT by improving clinical outcomes and quality of service for patients. Cloud technologies offer some of the best solutions for providing better medical services that easily and securely store and share medical information to improve operational efficiency and streamline costs for healthcare organizations. this article discusses the potential rule of cloud technology in healthcare, this may help to enhance the global healthcare scenario. Moreover, it presents the proposed architecture for healthcare services which is based on cloud computing. © 2022 IEEE.

关键词： Architecture

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Motor Fault Diagnosis Method Based on Deep Learning 11

Motor Fault Diagnosis Method Based on Deep Learning

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11th international conference of Information and Communication Technology, ICTech 2022

作者： Xu, Zhen Yu, Dong Hu, Yi University of Chinese Academy of Sciences Beijing100049 China Shenyang Institute of Computing Technology Chinese Academy of Sciences Shenyang110168 China

ISBN: (数字)9781665496940

ISBN: (纸本)9781665496940

Motors occupies an important position in the manufacturing *** at the problem of low accuracy of motor fault recognition,the temporal convolutional neural network(TCN) and attention mechanism are introduced. the fault diagnosis method based on TCN, by adding the SE-block module, improves the performance of the model at the cost of minimal *** experiments show that compared with the GRU model, LSTM model and the original TCN model,this method can better extract fault features in motor fault diagnosis, with higher accuracy and better generalization ability. © 2022 IEEE.

关键词： Failure analysis

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the Adoption of IoMT in Disease Prediction using Machine Learning: A benefit to Healthcare system 11

The Adoption of IoMT in Disease Prediction using Machine Lea...

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11th IEEE international conference on Communication Systems and Network Technologies, CSNT 2022

作者： Ramish, Md Pankaj, Ankit Lakra, Ankit Amity University Jharkhand Dept of Electronics and Communication Ranchi India DST-CIMS Banaras Hindu University Dept of Mathematics and Computing Varanasi India

ISBN: (纸本)9781665480383

Health information needs are also changing the information-fetching behavior, and that is observed around the globe. In this paper author has suggested the possibility of combining edge computing and machine learning algorithms into an Internet of medical things architecture focused on distributed computing. the paper is divided in two parts, First, the author proposed a model for collecting data usually produced by the front-end sensor frameworks on Internet of medical things devices using Edge computing and protocols such as Message Queuing Telemetry Transport (MQTT). Secondly, the author attempted to predict a disease correctly by looking at the patient's symptoms. Four diverse Machine learning algorithms K-Nearest Neighbor (KNN), Naïve Bayes, Decision tree, Random forest tree, were tested. the data set was collected from 2537 patients from the Apollo hospitals of India. To measure the performance, various performances metric is involved, and random forest gives the accuracy of 91%. © 2022 IEEE.

关键词： Decision trees

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Design pattern Detection by Using Correlation Feature Selection Technique 11

Design Pattern Detection by Using Correlation Feature Select...

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11th IEEE international conference on Communication Systems and Network Technologies, CSNT 2022

作者： Dewangan, Seema Rao, Rajwant Singh Technology Guru Ghasidas Vishwavidyalaya Dept. of Computer Science and Information Chhattisgarh Bilaspur India

ISBN: (纸本)9781665480383

Design pattern detection is a popular re-engineering job in software development. It provides essential information to the developers to recognize, sustain, and recycle the software. this article proposes a graph matching algorithm using a correlation-based feature selection technique to discover the design pattern (DP) instances from the software or system design. Usually, the feature selection method is used to choose the best instances from the dataset, which mostly matches the target feature. However, this paper has applied a correlation feature selection method to match the system design to the design pattern. We have taken three DPs comparing examples for this intention:•the first example for an entire match•the second example for a partial match•the third example of a not matchIn this experiment, we took the Abstract factory DP as a model graph, and the remaining twenty-two DPs are system or DPs. Software instances groups lots of classes and objects we converted into a graph. We observed that three of the 22 DPs are completely matched to the model DP, one pattern is not matched, and the remaining 18 patterns are only partially matched. © 2022 IEEE.

关键词： Systems analysis

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Study of Spiking Neural Network Architecture for Neuromorphic computing 11

Study of Spiking Neural Network Architecture for Neuromorphi...

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11th IEEE international conference on Communication Systems and Network Technologies, CSNT 2022

作者： Das, Rahul Biswas, Chiranjit Majumder, Swanirbhar Tripura University Department of Information Technology Agartala India

ISBN: (纸本)9781665480383

Deep learning's progress has resulted in a multi-layered character in a variety of applications in this field. Artificial Neural Networks are becoming the old procedure in the wide region of computing, using fifty-year-old principal concepts and models. Scientists are now presenting 3rd generation intelligent models in this current computer era. the brain like a big computer, routes information that it receives from the senses and body, and sends communications back to the body. But the brain can do much more than a machine can: humans think and experience reactions with their brain, and are the root of human intelligence. the 3rd generation Spiking Neural Network bridges the gap between deep learning, machine learning, and neuroscience in a biological approach, allowing neuroscience and machine learning to work together to achieve high-level computing efficiency using the neuromorphic computing. Spiking Neural Networks promise to make use of spikes, which are discrete functions that occur at predictable emphases rather than continuous values so that they are hardware implementable as well. © 2022 IEEE.

关键词： Neurology

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