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IEEE International Conference on Cloud computing Technology and Science (CloudCom)

作者： Marlon H. Schweigert Diego E.G.C. de Oliveira Guilherme P. Koslovski Maurício A. Pillon Charles C. Miers Graduate Program in Applied Computing (PPGCAP) Santa Catarina State University (UDESC) Brazil

The popularization increase of MMORPGs demands new technological approaches to supply users’ requirements with a lower cost of computational resources. Designing these architectures, from the network point of view, is relevant and impacts these games’ success. We analyze and identify the computational resources consumed by the architectures Rudy, Salz, and Willson, which are microservices architectures elaborated for MMORPGs. These architectures were analyzed and tested using automated clients on the architectures deployed in our private computational cloud to identify resource bottlenecks. We conclude the performance, from the point of view of response time, is related to better use of CPU, either by data storage microservices or by data processing microservices. In addition, the application of queuing systems or barriers to manage access or minimize the consumption of an internal service proved feasible, directly impacting the flow of data through the architecture.

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Perception Based Hybrid Intelligent Systems in Petroleum Applications

Perception Based Hybrid Intelligent Systems in Petroleum App...

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Conference of the North American Fuzzy Information Processing Society - NAFIPS

作者： L. B. Sheremetov I. Z. Batyrshin D. M. Filatov Research Program in Applied Mathematics and Computing Mexican Petroleum Institute Mexico Center for Computing Research National Polytechnic Institute Mexico

We describe the methods of processing of perception based information in hybrid intelligent systems. Several innovative techniques like a multi-set based algebra of qualitative perception-based uncertainties and perception-based data mining form the technological framework of the approach. In the paper, we discuss the algebra of strict monotonic operations and inference procedures based on perception-based evaluations of uncertainty of facts and rules. They are characterized by multi-set-based representation of evaluations of uncertainty and by multi-valued inference of conclusions in expert system rules. The proposed method is implemented in the CAPNET expert system shell. We also discuss the method of evaluation of perception-based patterns in time series data bases. The approach is illustrated by examples of diagnostics of excessive water production in petroleum wells combining both methods

关键词： Hybrid intelligent systems Petroleum Production Algebra Uncertainty Diagnostic expert systems Engines Data mining Information analysis Expert systems

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Analysis of human mobility behavior in Smart Cities and Smart Environments: A systematic literature review and taxonomy

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Journal of Smart Cities and Society 2024年第PRE-PRESS期Pre-press卷 1-36页

作者： Borges, Carlos Eduardo Liedtke Aranda, Jorge Arthur Schneider Barbosa, Jorge Luis Victória Applied Computing Graduate Program (PPGCA) University of Vale do Rio dos Sinos (UNISINOS) São Leopoldo Brazil

The analysis of human mobility behavior through computational techniques finds applications in various domains and provides valuable insights for urban planning, transportation services, and a deeper understanding of human interactions in Smart Cities and Smart Environments. In this scenario, this study presents a Systematic Literature Review (SLR) with the following main question: How are computational techniques being used to analyse human mobility behavior in Smart Cities and Smart Environments? A total of 5989 articles were initially found and filtered, resulting in 56 articles reviewed. As the main contributions, this study provides responses to 19 research questions. A list of the challenges and the computational techniques identified is provided. The algorithms, machine learning techniques and data-sources used by the reviewed studies are also presented and organized through taxonomies. A comprehensive discussion of the identified techniques is conducted, finishing with a compilation of challenges, open issues and research opportunities. To the best of our knowledge, this is the first study that reviewed human mobility behavior covering a wide range of scenarios, including urban mobility, public transport, points and regions of interest, ridesharing, bike-sharing, traffic analysis, driving behavior, electric vehicle charging stations planning, mobility on demand, crowd analysis and others.

关键词： Smart City Smart Environment behavior mobility crowd analysis

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Evaluation of Distance Education through Blended Learning: Comparisons and Important Factors for the Learning Process

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Creative Education 2014年第2期5卷 70-74页

作者： Júlio C. G. Bertolin Ana Carolina Bertoletti De Marchi Graduate Program in Applied Computing University of Passo Fundo Passo Fundo Brazil Graduate Program in Education University of Passo Fundo Passo Fundo Brazil

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Size segregation in the Brazil nut effect

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AIP Conference Proceedings 2013年第1期1558卷 2385-2388页

作者： Aline C. Soterroni Fernando M. Ramos Applied Computing Program National Institute for Space Research São José dos Campos Brazil Laboratory of Computing and Applied Mathematics National Institute for Space Research São José dos Campos Brazil

Granular materials are ubiquitous in nature and in our daily lives, and used in many industrial processes. Depending on the physical conditions that they are subjected, granular materials may present unusual behavior, combining properties of solids, liquids or gases, and displaying interesting and diversified phenomena. In this work we numerically simulated a granular system in order to investigate the phenomena of size segregation in the Brazil Nut Effect. Our simulations indicate that the phenomenon of size segregation results from the combined effect of two different mechanisms: buoyancy and convection. Increasing the vibration amplitude, the behavior of the system becomes less periodic and more turbulent, with evidence of deterministic chaos in the dynamics of the large particle.

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Stroke Lesion Detection Using Convolutional Neural Networks

Stroke Lesion Detection Using Convolutional Neural Networks

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2018 International Joint Conference on Neural Networks, IJCNN 2018

作者： Pereira, Danillo Roberto Filho, Pedro P. Rebouças De Rosa, Gustavo Henrique Papa, João Paulo De Albuquerque, Victor Hugo C. Department of Computing São Paulo State University Bauru SP Brazil Federal Institute of Education Science and Technology of Ceará CE Brazil Graduate Program in Applied Informatics University of Fortaleza Fortaleza CE Brazil

ISBN: (纸本)9781509060146

Stroke is an injury that affects the brain tissue, mainly caused by changes in the blood supply to a particular region of the brain. As consequence, some specific functions related to that affected region can be reduced, decreasing the quality of life of the patient. In this work, we deal with the problem of stroke detection in Computed Tomography (CT) images using Convolutional Neural Networks (CNN) optimized by Particle Swarm optimization (PSO). We considered two different kinds of strokes, ischemic and hemorrhagic, as well as making available a public dataset to foster the research related to stroke detection in the human brain. The dataset comprises three different types of images for each case, i.e., the original CT image, one with the segmented cranium and an additional one with the radiological density's map. The results evidenced that CNN's are suitable to deal with stroke detection, obtaining promising results. © 2018 IEEE.

关键词： Convolution

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A hybrid metaheuristic approach to optimize the content transmission in multimedia systems

A hybrid metaheuristic approach to optimize the content tran...

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International Conference on Informatics in Control, Automation and Robotics (ICINCO)

作者： Arthur T. Gómez Luan C. Nesi Marcio G. Martins Leonardo D. Chiwiacowsky Master Program on Applied Computing University of the Sinos Valley São Leopoldo/RS Brazil

The advent of the digital television in Brazil has allowed users to access interactive channels. Once interactive channels are available, the users are able to find multimedia content such as movies and breaking news programs, to send and/or receive emails, to access interactive applications and also other contents. In this context, a high demand of requests from users is expected. Therefore, from the content provider's point of view, the determination of transmission parameters is needed in order to ensure the best quality of transmission to every user. The aforementioned identification problem is modelled as an optimization problem and a solution procedure based on metaheuristic techniques is proposed. Genetic Algorithm and Tabu Search metaheuristics are employed separately and coupled in a hybrid scheme to define the best transmission policy, optimizing the transmission parameters, such as audio and video transmission rates. Based on the experimental results, the hybrid algorithm has produced better solutions which meet the quality requirements.

关键词： Genetic algorithms Optimization Mathematical model Multimedia communication Bandwidth Digital TV Servers

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Differential Evolution with Cluster-Based External Archive and Local Search for Multimodal Optimization

Differential Evolution with Cluster-Based External Archive a...

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Brazilian Conference on Intelligent Systems (BRACIS)

作者： Gabriel Dominico Mateus Boiani Rafael Stubs Parpinelli Graduate Program in Applied Computing Santa Catarina State University Joinville Santa Catarina Brazil

One of the main objectives in multimodal optimization is to find multiple optima solutions in a search space. Hence, population-based metaheuristics are suitable for this class of problems but their loss of diversity while converging may become a problem when tracking multiple optima. In this paper, we propose the use of a cluster-based external archive maintenance strategy along with the jDE algorithm, namely NCjDE-HJ ar . The DBSCAN algorithm is employed to group candidate solutions in an external archive representing multiple peaks that will feed the Hooke-Jeeves local search algorithm. Also, the Michalewicz mutation strategy is applied to refine the solutions found by the jDE algorithm. The proposed approach is compared with five state-of-the-art algorithms in terms of peak ratio and the results obtained show that the proposed modifications favor the finding more multimodal peaks.

关键词： Clustering algorithms Optimization Sociology Statistics Euclidean distance Search problems Convergence

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Concerns and limitations in agile software development: A survey with Paraguayan companies

arXiv

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arXiv 2017年

作者： Salinas, Myrian R. N. Neto, Adolfo Gustavo Serra Seca Emer, Maria Claudia F. P. Postgraduate Program in Applied Computing Academic Department of Informatics Federal University of Technology Parana Brazil

This year, the Agile Manifesto completes seventeen years and, throughout the world, companies and researchers seek to understand their adoption stage, as well as the benefits, barriers, and limitations of agile methods. Although we have some studies and questionnaire data at the global level, we know little about how the Paraguayan software community is adopting agile methods. The present work conducted a research to set up the current stage of adoption, initial concerns and barriers of implementation of agile methods in software development companies in Paraguay. An online survey was sent to representatives of 53 Paraguayan companies. Of these, 9 (17%) companies responded. The concern about adopting more agile methods (44.44% of respondents) was the lack of reliability in product quality if developed using agile methods. The main barrier was the lack of experience (66.66%) of the companies. Copyright © 2017, The Authors. All rights reserved.

关键词： Surveys

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Data classification and reinforcement learning to avoid congestion on SDN-based data centers

Data classification and reinforcement learning to avoid cong...

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GLOBECOM 2022 - 2022 IEEE Global Communications Conference

作者： Gustavo Diel Charles Christian Miers Maurício Aronne Pillon Guilherme Piêgas Koslovski Graduate Program in Applied Computing (PPGCAP) Santa Catarina State University (UDESC) Joinville Brazil

ISBN: (纸本)9781665435413

A contemporaneous data center (DC) hosts multiple competitive network data flows from different applications, sharing the intermediate switches capacities. In this context, congestion control and avoidance on Transmission Control Protocol (TCP) are critical tasks to ensure the quality of service for hosted applications. Specifically, Software Defined Networking (SDN) created an opportunity to avoid congestion once the centralized controller can gather ongoing and historical information from all network switches and flows. However, the data gathered is enormous, and fast-computing algorithms are crucial for decision-making. In this sense, this work proposes Reinforcement Learning- and SDN-aided Congestion Avoidance Tool (RSCAT), which uses data classification to determine if the network is congested and actor-critic reinforcement learning to find better TCP parameters. Our experimental analysis shows RSCAT could decrease the Flow Completion Time (FCT) of DCTCP and CUBIC variants in several cases without requiring any software update on DC end-points.

关键词： Data centers Protocols Software algorithms Decision making Reinforcement learning Quality of service Software

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