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Congress on Evolutionary Computation

作者： Lucas Borges De Moraes Adriano Fiorese Rafael Stubs Parpinelli Graduate Program in Applied Computing Santa Catarina State University Joinville Brazil

The success of cloud computing technology has leveraged the emergence of a large number of new companies providing cloud computing services. Choosing which cloud providers are the most suitable to attend consumers desired quality of service has become a hard problem. In order to qualify such providers, performance indicators (PIs) are useful tools for systematic and synthesized information collection. Thus, the problem approached in this work is to find the best set of cloud computing providers that satisfies a customer's request, with the least amount of providers and the lowest price. Hence, this work proposes a hybrid Genetic Algorithm (GA) to address this problem. In experiments, three approaches, using PIs as input, are employed: a simple matching algorithm, a GA and the proposed hybrid matching-GA approach. The hybrid method combines the qualities of both the matching algorithm and the GA showing promising results.

关键词： Cloud computing Genetic algorithms Quality of service Computational modeling Measurement Databases Encoding

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A Method to Suggest Alternative Routes Based on Analysis of Automobiles' Trajectories

A Method to Suggest Alternative Routes Based on Analysis of ...

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Conferencia Latinoamericana En Informatica (CLEI)

作者： João Pedro Schmitt Fabiano Baldo Santa Catarina State University Graduate Program in Applied Computing Joinville Brazil

ISBN: (纸本)9781728104386

Inexperienced drivers usually use the most-known paths to move inside the cities, while drivers with a better knowledge of the road network normally taken alternative routes that are shorter, faster or safer. This knowledge about roads usage, when shared with other drivers, could offer more paths options to distribute the traffic load across the city by suggesting alternative routes. However, the problem lies in how to suggest alternative route directions for ordinary drivers considering knowledge gathered from experienced drivers. In order to try to solve this problem, it is proposed an algorithm, named TODS - Trajectory Outlier Detection and Segmentation, to group and segment car road trajectories in standard and alternative routes based on city roads usage in different day times periods. After that, the segmentation results are suggested as driving directions for ordinary drivers. To evaluate the results was performed a qualitative comparison with TRA-SOD algorithm considering the segmentation process. The tests were executed using two trajectories datasets collected by drivers in San Francisco - USA and Joinville - Brazil. The results assessment indicate that TODS is superior to TRA-SOD due to its segmentation characteristics. Besides that, it has been observed that the time period of the day influences how routes are used along the day.

关键词： Trajectory Standards Roads Urban areas Clustering algorithms Automobiles

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Cetacean translation initiative: A roadmap to deciphering the communication of sperm whales

arXiv

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arXiv 2021年

作者： Andreas, Jacob Beguš, Gašper Bronstein, Michael M. Diamant, Roee Delaney, Denley Gero, Shane Goldwasser, Shafi Gruber, David F. de Haas, Sarah Malkin, Peter Payne, Roger Petri, Giovanni Rus, Daniela Sharma, Pratyusha Tchernov, Dan Tønnesen, Pernille Torralba, Antonio Vogt, Daniel Wood, Robert J. MIT CSAIL CambridgeMA United States Department of Linguistics University of California BerkeleyCA United States Department of Computing Imperial College London United Kingdom IDSIA University of Lugano Switzerland Twitter United Kingdom School of Marine Sciences Haifa University Israel Exploration Technology Lab National Geographic Society Dominica Sperm Whale Project Dominica Department of Biology Carleton University Canada Simons Institute for the Theory of Computing University of California BerkeleyCA United States Department of Natural Sciences Baruch College and The Graduate Center PhD Program in Biology City University of New York New YorkNY United States Google Research Ocean Alliance GloucesterMA United States ISI Foundation Turin Italy Marine Bioacoustics Lab Zoophysiology Department of Biology Aarhus University Denmark School of Engineering and Applied Sciences Harvard University CambridgeMA United States

The past decade has witnessed a groundbreaking rise of machine learning for human language analysis, with current methods capable of automatically accurately recovering various aspects of syntax and semantics — including sentence structure and grounded word meaning — from large data collections. Recent research showed the promise of such tools for analyzing acoustic communication in nonhuman species. We posit that machine learning will be the cornerstone of future collection, processing, and analysis of multimodal streams of data in animal communication studies, including bioacoustic, behavioral, biological, and environmental data. Cetaceans are unique non-human model species as they possess sophisticated acoustic communications, but utilize a very different encoding system that evolved in an aquatic rather than terrestrial medium. Sperm whales, in particular, with their highly-developed neuroanatomical features, cognitive abilities, social structures, and discrete click-based encoding make for an excellent starting point for advanced machine learning tools that can be applied to other animals in the future. This paper details a roadmap toward this goal based on currently existing technology and multidisciplinary scientific community effort. We outline the key elements required for the collection and processing of massive bioacoustic data of sperm whales, detecting their basic communication units and language-like higher-level structures, and validating these models through interactive playback experiments. The technological capabilities developed by such an undertaking are likely to yield cross-applications and advancements in broader communities investigating non-human communication and animal behavioral research. © 2021, CC BY-NC-ND.

关键词： Signal encoding

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An Energy Efficient Mesh LNN Routing Protocol Based on Ant Colony optimization

An Energy Efficient Mesh LNN Routing Protocol Based on Ant C...

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IEEE International Conference on Industrial Informatics (INDIN)

作者： Vinícius de Figueiredo Marques Janine Kniess Rafael Stubs Parpinelli Graduate Program in Applied Computing Santa Catarina State University Joinville SC Brazil

Low-power and Lossy network (LNN) is commonly deployed in Internet of Things applications. It consists of a considerable amount of devices, also known as motes, with sensory capacity and wireless connectivity deployed in a wide geographical area. Such devices face limitations in terms of energy, memory and processing. A common topology in LNN is a mesh-like one. The communication between nodes often happens in a multi-hop fashion due to their limited transmission range. There is a need of efficient routing protocols, in terms of energy consumption. The present paper depicts a routing algorithm based on ant colony optimization. It also shows details about its implementation in the Contiki OS network system and analysis of its performance in comparison with the default Contiki's mesh routing protocol. Results shown that the proposed algorithm had a better performance in terms of packet delivery rate, duty cycling and energy consumption.

关键词： Routing protocols Energy consumption Routing Measurement Mathematical model Ant colony optimization Wireless sensor networks

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Analysis of positional and geometric accuracy of objects in survey with unmanned aerial vehicle (UAV) 38

Analysis of positional and geometric accuracy of objects in ...

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38th Annual IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2018

作者： Soares, Gabriel Inocencio, Leonardo Campos Veronez, Maurício Roberto Da Silveira, Luiz Gonzaga Bordin, Fabiane Marson, Fernando Pinho Advanced Visualization and Geoinformatics Laboratory UNISINOS São Leopoldo RS Brazil Graduate Program on Applied Computing UNISINOS Av. UNISINOS 950 São Leopoldo RS93022-000 Brazil

ISBN: (纸本)9781538671504

This study aimed the analysis of the positional and geometric accuracy of objects in orthomosaics obtained through different unmanned aerial vehicle (UAV) data processing software covering an area located within Universidade do Vale do Rio dos Sinos - UNISINOS in São Leopoldo, RS. A total of nine ground control points (GCP) and twenty checkpoints were surveyed in order register and classify the processed orthomosaics according to the cartographic accuracy standard - Padrão de Exatidão Cartográfica (PEC). Four software was employed to process the UAV data: Pix4D mapper, Agisoft PhotoScan, Menci APS and Bentley Context Capture. The results obtained from each software were compared and identified the smallest distortions when processing with and without ground control points. The flight was executed at a height of 90m with 60% sidelap and 80% overlap using an ST800 UAV equipped with a Sony NEX-7 small format non-metric camera with 24 megapixels resolution. The software GeoPEC was used to classify the orthomosaics according to PEC. For data processed with ground control points all orthomosaics were classified “Class A” in 1/500 scale, however, only Menci APS did not present a trend line via t-student test. On the other hand, Menci APS presented the worst results without the ground control points. In processing with GCP, all orthomosaics obtained optimum results with an approximated error of 2,5 m2 about 0,03% of the area. © 2018 IEEE

关键词： Cartographic Accuracy Standard Ground Control Points Orthomosaic Unmanned Aerial Vehicle

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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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Data Science Approach to Analysis of Lattes CV Data 4

Data Science Approach to Analysis of Lattes CV Data

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4th Annual International Symposium on Information Management and Big Data, SIMBig 2017

作者： De Santana, Thiago Luís Viana Santos, Rafael Applied Computing Graduate Program INPE – Nat. Inst. for Space Research Brazil Applied Computing Graduate Program INPE – Nat. Inst. for Space Research Brazil

The Lattes Platform is an online database of academical records. It is used by the research and educational community of Brazil (and some other countries), being of great value for identification of researchers and their relationships with other researchers and, for that, it can be considered a specialized kind of social network. In spite of its usefulness, the main interface of access to its data does not allow any type of analysis, just basic reports. In this paper, we present a new tool and approach to analysis of groups of records from the Lattes Platform which is simpler and more flexible than other similar tools proposed in the past.

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Fraud detection in water meters using pattern recognition techniques 17

Fraud detection in water meters using pattern recognition te...

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32nd Annual ACM Symposium on applied computing, SAC 2017

作者： Detroz, Juliana Patrícia Da Silva, André Tavares PPGCA - Graduate Program in Applied Computing UDESC - Santa Catarina State University Brazil

ISBN: (纸本)9781450344869

Water supply utilities have been increasingly looking for solutions to reduce water wastage. Many efforts have been made aiming to promote a better management of this resource. Fraud detection is one of these actions, as the irregular violations are usually held precariously, thus, causing leaks. In this context, the use of technology in order to automate the identification of potential frauds can be an important support tool to avoid water waste. Thus, this research aims to apply pattern recognition techniques in the implementation of an automated detection of suspected irregularities cases in water meters, through image analysis. The proposed computer vision system is composed of three steps: the detection of the water meter location, obtained by OPF classifier and HOG descriptor, detecting the seals through morphological image processing and segmentation methods;and the classification of frauds, in which the condition of the water meter seals is assessed. We validated the proposed framework using a dataset containing images of water meter inspections. At the last step, the proposed framework reached an average accuracy up to 81.29%. We concluded that a computer vision system is a promising strategy and has potential to benefit the analysis of fraud detection. Copyright 2017 ACM.

关键词： Object detection

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Prior Experience as an Influencer in the Momentary User Experience: An Assessment in Immersive Virtual Reality Game Context

Prior Experience as an Influencer in the Momentary User Expe...

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Symposium on Virtual Reality (SVR)

作者： Ericles Andrei Bellei Daiana Biduski Láýs Andressa Brock Diego Inácio Patrício Jhônatan de Lima de Souza Ana Carolina Bertoletti De Marchi Rafael Rieder Graduate Program in Applied Computing (PPGCA) University of Passo Fundo (UPF) Passo Fundo Rio Grande do Sul Brazil

ISBN: (纸本)9781728106052

Excellence in user experience (UX) has become a leading factor in developing successful products. In the context of virtual reality (VR), UX evaluations can be effective methods for understanding the acceptability, potential, and success of a product. However, different audiences have different perceptions regarding UX and its facets. With this in mind, the aim of this study is to determine whether the existence of prior experience (PE) can beget significant influence on Momentary UX when wearing the HTC VIVE to interact with a VR game. To assess, we asked two groups of users with different PEs to participate in a VR game session with HTC VIVE. An evaluation framework of UX in games was used to determinate how different user's backgrounds can influence UX. From the results obtained, some considerations are presented about the factors that influenced UX, concluding that prior experience with VR technology does not significantly affect Momentary UX.

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Blended learning and media centers: A bibliometric analysis

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Social Sciences and Humanities Open 2024年 10卷

作者： Challco, Geiser Chalco Silva, Wesley Vieira da Setton Gonçalves, Bruno de Almeida Levino, Natallya Bittencourt, Ibsen Mateus Kaczam, Fabíola de Oliveira, Elaine Harada Teixeira Martins, Flavio Pinheiro de Lima Filho, Walter Araujo de Araújo, Ronaldo Ferreira Bittencourt, Ig Ibert Paiva, Ranilson Oscar Araújo Department of Engineering and Technology (DETEC) Federal Rural University of Semi-Árido (UFERSA) RN Pau dos Ferros 59900-000 Brazil Scholarship CNPq Research Productivity (D Level) and Professor Faculty of Economics Administration and Accounting Federal University of Alagoas (UFAL) Maceió 57072-900 Brazil Faculty of Economics Administration and Accounting Federal University of Alagoas (UFAL) Maceió 57072-900 Brazil Leader of the Laboratory of Applied Public Administration (LAPA) of the Public Administration Course Campus Arapirca Federal University of Alagoas Arapiraca 57309-005 Brazil Faculty of Economics Business and Accounting Federal University of Alagoas Maceio 57072-900 Brazil Postgraduate Program in Administration Federal University Santa Maria (UFSM) Building 74C 2nd floor Room 4209 97105-900 Brazil Institute of Computing Federal University of Amazonas Amazonas Manaus Brazil The Bartlett School of Sustainable Construction University College London—UCL London WC1E 6BT United Kingdom Visiting Researcher at Leiden University ou Pesquisador Visitante na Universidade de Leiden Institute of Human Sciences Communication and Arts Federal University of Alagoas Alagoas Maceio 57072-900 Brazil Harvard Graduate School of Education Harvard University Cambridge MA United States Center of Excellence for Social Technologies Federal University of Alagoas Brazil Universidade Federal de Alagoas - Instituto de Computação Brazil

Blended learning can be considered an approach that combines face-to-face and online periods in education through the integration of some technological resources, such as media centers. The present research sought to investigate the panorama of scientific production on blended learning and identify evidence of how media centers are used to support this type of teaching. This is a bibliometric study carried out based on the principles of the Systematic Literature Review (SLR). Although the results indicate an increase in production, a high rate of authors with only one published work was identified, which can be interpreted as an expanding topic. The United States stood out as the country that contributed the most with research and the areas of Computer Science and Education among the fields of research with the highest number of articles. © 2024 The Author(s)

关键词： Blended learning Hybrid education Media centers Systematic review

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