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检索条件"任意字段=2021 10th International Conference on Computing and Pattern Recognition"

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DeepSpotCloud: Leveraging Cross-Region GPU Spot Instances for Deep Learning 10

DeepSpotCloud: Leveraging Cross-Region GPU Spot Instances fo...

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10th IEEE international conference on Cloud computing (CLOUD)

作者： Lee, Kyungyong Son, Myungjun Kookmin Univ Dept Comp Sci Seoul South Korea

ISBN: (纸本)9781538619933

Cloud computing resources that are equipped with GPU devices are widely used for applications that require extensive parallelism, such as deep learning. When the demand of cloud computing instance is low, the surplus of resources is provided at a lower price in the form of spot instance by AWS EC2. this paper proposes DeepSpotCloud that utilizes GPU-equipped spot instances to run deep learning tasks in a cost efficient and fault-tolerant way. thorough analysis about spot instance price history logs reveals that GPU spot instances show more dynamic price change pattern than other general types of cloud computing resources. To deal with the price dynamicity of the GPU spot instance, DeepSpotCloud utilizes instances in different regions across continents as a single resource pool. this paper also proposes a task migration heuristic by utilizing a checkpointing mechanism of existing deep learning analysis platform to conduct fast task migration when a running spot instance is interrupted. Extensive experiments using real AWS services prove that the proposed task migration method is effective even in a WAN environment with limited network bandwidth. Comprehensive simulations by replaying AWS EC2 price history logs reveal that DeepSpotCloud can achieve 13% more cost gain than a state-of-the-art interrupt-driven scheduling policy. the prototype of DeepSpotCloud is implemented using various cloud computing services provided by AWS to serve real deep learning tasks.

关键词： Graphics processing units Machine learning Cloud computing Fault tolerance Fault tolerant systems Checkpointing Continents

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xDaaS: Any Data as a Service 10

xDaaS: Any Data as a Service

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10th IEEE international conference on Semantic computing (ICSC)

作者： Palavalli, Amarnath Karri, Durgaprasad Pasupuleti, Swarnalatha VMware Palo Alto CA 94304 USA

ISBN: (纸本)9781509006625

Integration of products in enterprises comes with hard challenges due to several factors such as products developed in house, off the shelf, developed over different time lines, available as services over internet, ever changing product APIs, disconnected data models among the products, extensions developed by partners and customers and many more. We propose Semantic Data Platform (SDP), built around the semantics of the information derived out of product integration. this approach of semantic model based data sharing provides extreme loose coupling among products, makes extension of information from a given product possible with zero impact on rest of the system. Easy certification of integration enables evolution of products fairly independent of each other. SDP offers semantic federation and querying, therefore it can fetch any data irrespective of the product where the data lives. thus, 'Any Data from a product can be offered as a Service'.

关键词： Cloud computing Enterprise Data Integration Fact Oriented Modeling Object Role Modeling Ontology Ontology Design pattern ORM Semantic Data Platform

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Music Emotions recognition by Cognitive Classification Methodologies 16

Music Emotions Recognition by Cognitive Classification Metho...

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IEEE 16th international conference on Cognitive Informatics and Cognitive computing (ICCI*CC)

作者： Bai, Junjie Luo, Kan Peng, Jun Shi, Jinliang Wu, Ying Feng, Lixiao li, Jianqing Wang, Yingxu Chongqing Univ Sci & Technol Sch Elect & Informat Engn Chongqing Peoples R China Univ Calgary Brain Inst Schulich Sch Engn & Hotchkiss Calgary AB Canada Fujian Univ Technol Sch Informat Sci & Engn Fuzhou Fujian Peoples R China Southeast Univ Sch Instrument Sci & Engn Nanjing Jiangsu Peoples R China

ISBN: (纸本)9781538607718

Music emotions recognition (MER) is a challenging field of studies addressed in multiple disciplines such as musicology, cognitive science, physiology, psychology, arts and affective computing. In this paper, music emotions are classified into four types known as those of pleasing, angry, sad and relaxing. MER is formulated as a classification problem in cognitive computing where 548 dimensions of music features are extracted and modeled. A comprehensive set of classification algorithms are explored and comparatively studied for MER including Support Vector Machine (SVM), k-Nearest Neighbors (KNN), Neuro-Fuzzy Networks Classification (NFNC), Fuzzy KNN (FKNN), Bayes classifier and Linear Discriminant Analysis (LDA). Experimental results show that the SVM, FKNN and LDA algorithms are the most effective methodologies which obtain more than 80% accuracy for MER in performance.

关键词： music emotion recognition emotion classification feature extraction machine learning pattern recognition

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Proceedings of the 2021 10th international conference on System Modeling and Advancement in Research Trends, SMART 2021

Proceedings of the 2021 10th International Conference on Sys...

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10th international conference on System Modeling and Advancement in Research Trends, SMART 2021

ISBN: (纸本)9781665439701

the proceedings contain 133 papers. the topics discussed include: how to extract ‘feature architecture’ of your software;the role of car connectivity in future mobility;model for a sustainable development of the last mile delivery logistics by drones;the process of colorizing a data visualization;usage of game-theory in energy, cyber security and COVID-19;edge computing support for V2X communications on 5g technology;smart cities: the challenge of interoperable software architecture;data as a resource - data-driven economy and innovation;and nanoscale sensor networks DNA: a new paradigm for communication at the bottom.

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Transient pattern - the Model of Digital Layout 10

Transient Pattern - the Model of Digital Layout

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10th international conference on Digital and Interactive Arts (ARTECH)

作者： Gogova, Andrea Fac Multimedia Commun Tbu In Zlin Czech Republic

ISBN: (纸本)9781450384209

Unlike a rectangular grid arrangement, electronic writing has a character of a cross-linked and developing writing technique. the network of interconnected hypertext was compared with the human neural network Writing identity is reflected in the hypertext, as dynamic, flexible, variable, and even random. According to several authors [Manovich, 2001;Aarseth, 1997;Bootz and Baldwin, 2010 and others], the paradigm of digital mediation is manifested by changes in the approach to the production, storage, media distribution, and reception of literary, conceptual, or other "textual" artworks. In the position of an e-literature programmed form, Philippe Bootz reflected that those changes in the description of a procedural model of communication and the introduction of performative signs are a part of the aesthetic approach. the information which flows from the source (made by authors) to the target (reader's reading) could be embodied in the digital text and represented, manifested, or articulated by the digital text layout, which will be shaped on/in various interfaces, instead of the plane and rectangular of "screens". Digital text which is manifested by a layout should take place on/in current and future, digital and hybrid interfaces. this kind of layout could bring the reader into the text work, and closer to its essence. the posthumanistic approach of the digital layout problem solution will change the point of view, which is focused on a human, to the wider equal interrelations of technical, biological, and human intelligent actors. the flexible shape of complex and experimental digital layout solutions could be manifested on/in many different interfaces. In my work I propose a new definition of digital layout and a hypothetical solution - the model Transient pattern. the model offers a space in which the creation of a digital layout could take place in different solutions - free of a grid pattern organization. these considerations pave the way for a new approach to

关键词： Digital layout Hybrid intelligence Posthumanism Transient pattern

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A Proposed model for field workers Injuries' prevention based on machine learning 10

A Proposed model for field workers Injuries' prevention base...

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10th IEEE international conference on Intelligent computing and Information Systems, ICICIS 2021

作者： Abbas Sabet, Mohamed Farouk Dahroug, Ahmed Hegazy, Abdel Fattah Technology and Maritime Transport College of Computing and Information Technology Arab Academy for Science Cairo Egypt

ISBN: (纸本)9781665440769

the prosperity of the construction industry in Egypt at the expense of occupational safety and health of the worker there are several factors [1]. for the occurrence of these accidents, such as. Construction projects are being created temporarily. the difficulty of standardizing safety procedures in all construction projects;this study aims to design machine learning techniques, deep learning techniques, and failure to comply with the safe use of tools, and the association rules-based decision support system is objective to identify the reasons for injury and the results of the accident, effects of an accident at construction projects in Egypt also, explore the characteristics of top-ranking reason and effects. Various direct and indirect relations of top reasons and effects are also analyzed in this study. To determine the type of injury and reduce injuries the dataset was collected from Arab Contractors company in Egypt. the dataset consists of 5,800 work accident report from 2011 to 2019. © 2021 IEEE.

关键词： Deep neural networks

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10th international conference on Innovations in Bio-Inspired computing and Applications, IBICA 2019 and 9th World Congress on Information and Communication Technologies, WICT 2019

10th International Conference on Innovations in Bio-Inspired...

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10th international conference on Innovations in Bio-Inspired computing and Applications, IBICA 2019 and 9th World Congress on Information and Communication Technologies, WICT 2019

ISBN: (纸本)9783030493387

the proceedings contain 38 papers. the special focus in this conference is on Innovations in Bio-Inspired computing and Applications. the topics include: Soft computing approach on minimisation of indirect losses in power generation for efficiency enhancing;a machine learning prediction of automatic text based assessment for open and distance learning: A review;analysis of pre-processing techniques for odia character recognition;cluster-based under-sampling using farthest neighbour technique for imbalanced datasets;vehicle detection and classification: A review;methods for automatic gait recognition: A review;comparative performance exploration and prediction of fibrosis, malign lymph, metastases, normal lymphogram using machine learning method;decision forest classifier with flower search optimization algorithm for efficient detection of bhp flooding attacks in optical burst switching network;welcome message;towards the speed enhancement of association rule mining algorithm for intrusion detection system;review and implementation of 1-bit adder in cmos and hybrid structures;design and analysis of lol-p textile antenna;analytical study of scalability in coastal communication using hybridization of mobile ad-hoc network: An assessment to coastal bed of odisha;effect of environmental and occupational exposures on human telomere length and aging: A review;a review on vlsi implementation in biomedical application;comparative analysis of a dispersion compensating fiber optic link using fbg based on different grating length and extinction ratio for long haul communication;unsupervised learning method for mineral identification from hyperspectral data;short term load forecasting using empirical mode decomposition (emd), particle swarm optimization (pso) and adaptive network-based fuzzy interference systems (anfis).

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Conceptual framework supporting pattern design selection for scientificworkflow applications in cloud computing 10

Conceptual framework supporting pattern design selection for...

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10th international conference on Cloud computing and Services Science, CLOSER 2020

作者： Alkhanak, Ehab Nabiel Khan, Saif Ur Rehman Verbraeck, Alexander Van Lint, Hans Delft Netherlands Islamabad Pakistan Delft Netherlands

ISBN: (纸本)9789897584244

Scientific Workflow Applications (SWFA) play a vital role for both service consumers and service providers in designing and implementing large and complex scientific processes. Previously, researchers used parallel and distributed computing technologies, such as utility and grid computing to execute the SWFAs, these technologies provide limited utilization for the shared resources. In contrast, the scalability and flexibility challenges are better handled by using cloud-computing technologies for SWFA. Since cloud computing offers a technology that can significantly utilize the amounts of storage space and computing resources necessary for processing large-size and complex SWFAs. the workflow pattern design has provided the facility of re-using previously developed workflow solutions that enable the developers to adopt them for the considered SWFA. Inspired by this, the researchers have adopted several patterns of design to better design the SWFA. Effective pattern design that can consider challenges that may not become visible only in the implementation stage of a SWFA. However, the selection of the most effective pattern design in accordance with an execution method, data size, and problem complexity of a SWFA remains a challenging task. Motivated by this, we have proposed a conceptual framework that facilitates in recommending a suitable pattern design based on the quality requirements and capabilities are given and advertised by cloud consumers and providers, respectively. Finally, guidelines to assist in a smooth migrating of SWFA from other computation paradigms to cloud computing. © Copyright 2020 by SCITEPRESS - Science and Technology Publications, Lda. All rights reserved.

关键词： Cloud computing

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Benchmarking Annotation Procedures for Multi-channel Time Series HAR Dataset

Benchmarking Annotation Procedures for Multi-channel Time Se...

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19th IEEE international conference on Pervasive computing and Communications (IEEE PerCom)

作者： Avsar, Hulya Altermann, Erik Reining, Christopher Rueda, Fernando Moya Fink, Gernot A. ten Hompel, Michael TU Dortmund Univ Chair Mat Handling & Warehousing Joseph von Fraunhofer Str 2-4 D-44227 Dortmund Germany TU Dortmund Univ Pattern Recognit Embedded Syst Grp Joseph von Fraunhofer Str 2-4 D-44227 Dortmund Germany

ISBN: (纸本)9781665404242

this contribution evaluates semi-automated annotation for generating high-quality data for multi-channel time series Human Activity recognition. For this purpose, time series data that consists of Optical Motion Capturing and inertial measurements from on-body devices for industrial deployment is created, annotated, and revised by four individuals. the semi-automated annotation consists of predictions from a temporal convolutional neural-network, and manual revisions for generating high-quality and fine-grained annotations for Human Activity recognition. this annotation approach reduces the annotation effort keeping similar quality as compared to manual annotation.

关键词： Human Activity recognition Labelling Annotation Human Reliability Logistics Warehousing Deep Learning Semi-Automatic Annotation

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A Survey of Person Re-identification Based on Deep Learning 10

A Survey of Person Re-identification Based on Deep Learning

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10th international conference on computing and pattern recognition, ICCPR 2021

作者： Tian, Zimin Chen, Si Wang, Da-Han Lu, Junwen School of Computer and Information Engineering Xiamen University of Technology China Fujian Key Laboratory of Pattern Recognition and Image Understanding China

ISBN: (纸本)9781450390439

Person re-identification (Re-ID) has been a popular research topic in computer vision in recent years, and it has important application value in numerous fields, such as intelligent security. the person Re-ID task is to identify whether the pedestrians appearing under different cameras are the same person. the traditional person Re-ID methods mainly rely on the characteristics of manual design, and it has difficulty in solving the problems of person occlusion, posture change, and illumination variation. With the wide application of deep learning, the person Re-ID based on deep learning has brought new ideas for solving these problems, and has been widely concerned by scholars. this paper summarizes and analyzes the latest research trends of person Re-ID based on deep learning. In our work, the recent research works of person Re-ID are coarsely categorized into the supervised learning methods and the unsupervised learning methods according to whether the pedestrian images in the training set have real labels. We then describe the representative datasets used in the person Re-ID task. Finally, we conclude and discuss the future directions of the person Re-ID based on deep learning. © 2021 ACM.

关键词： Unsupervised learning

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