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41st Latin American computing Conference, CLEI 2015

作者： Cardoso, Ismael Gomes Mota, Bruno Barbosa, Jorge Luis Victória Da Rosa Righi, Rodrigo Applied Computing Graduate Program - Unisinos Av. Unisinos 950 Sâo Leopoldo RS Brazil

ISBN: (纸本)9781467391436

The use of recommender systems is widespread in several everyday systems. People are now exposed to different offerings, based on their interests, in order to anticipate decisions. However, in a different way recommender systems for accessibility domain require further studies and researches. In order to provide resources for people with special needs, we developed the Vulcanus, a recommender system designed for people with disabilities, offering access to resources according user's needs. The recommender system approaches concepts from ubiquitous computing, such as user profiles, context awareness, trails management, and similarity analysis. Vulcanus uses two different approaches: resources patterns and categories patterns;where different systems can use it, for example as a Web Service. Vulcanus was evaluated in different scenarios. These scenarios used more than 800 thousands of trails that simulate wheelchair users using resources along six months. The obtained results show that both approaches are able to provide relevant recommendations, providing resources that in fact can support users' needs. © 2015 IEEE.

关键词： Recommender systems

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Gamification strategies for mobile device applications: A systematic review 12

Gamification strategies for mobile device applications: A sy...

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12th Iberian Conference on Information Systems and Technologies, CISTI 2017

作者： Cechetti, Nathalia Pinto Biduki, Daiana De Marchi, Ana Carolina Bertoletti Graduate Program in Applied Computing - PPGCA/ICEG Universidade de Passo Fundo - UPF Passo Fundo Brazil

ISBN: (纸本)9789899843479

In the quest to engage and motivate users on the use of mobile applications, the gamification concept has been excelling in the market since incorporates game elements in a non-game context. Scoring systems, challenges, competitions and badges, are some of the elements implemented in many fields, such as health, education, ecological awareness, among others. In this context, this study aimed to systematically review available literature to identify gamification strategies used in mobile applications. A search was conducted in ACM, Science Direct and Scopus databases, from March to June 2016. A total of 402 studies were found, 23 of which met the eligibility criteria. The results demonstrated the heterogeneity of gamification elements being used and the impact they caused in the applications, especially as a motivational factor for users. This study provides the basis for future research on gamification methods and emphasizes the importance of this concept to increase engagement and provide enjoyment to users. © 2017 AISTI.

关键词： Mobile computing

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A machine learning pipeline for extracting decision-support features from traffic scenes 12

A machine learning pipeline for extracting decision-support ...

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12th International Workshop on Agents in Traffic and Transportation, ATT 2022

作者： Fraga, Vitor A. Schreiber, Lincoln V. Kunst, Rafael Barbosa, Jorge Luis V. Ramos, Gabriel de O. Graduate Program in Applied Computing Universidade do Vale do Rio dos Sinos São Leopoldo Brazil

Traffic systems play a key role in modern society. However, these systems are increasingly suffering from problems, such as congestions. A well-known way to efficiently reduce this kind of problem is to perform traffic light control intelligently through reinforcement learning (RL) algorithms. In this context, extracting relevant features from the traffic environment to support decision-making becomes a central concern. Examples of such features include vehicle counting on each queue, identification of vehicles’ origins and destinations, among others. Recently, the advent of deep learning has paved to way to efficient methods for extracting some of the aforementioned features. However, the problem of identifying vehicles and their origins and destinations within an intersection has not been fully addressed in the literature, even though such information has shown to play a role in RL-based traffic signal control. Building against this background, in this work we propose a deep learning pipeline for extracting relevant features from intersections based on traffic scenes. Our pipeline comprises three main steps: (i) a YOLO-based object detector fine-tuned using the UAVDT dataset, (ii) a tracking algorithm to keep track of vehicles along their trajectories, and (iii) an origin-destination identification algorithm. Using this pipeline, it is possible to identify vehicles as well as their origins and destinations within a given intersection. In order to assess our pipeline, we evaluated each of its modules separately as well as the pipeline as a whole. The object detector model obtained 98.2% recall and 79.5% accuracy. The tracking algorithm obtained a MOTA of 72.6% and a MOTP of 74.4%. Finally, the complete pipeline obtained an error of 7.53% in terms of origin and destination counts. © 2021 Copyright for this paper by its authors.

关键词： Object detection

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ProFog: A Proactive Elasticity Model for Fog computing-based IoT Applications 17

ProFog: A Proactive Elasticity Model for Fog Computing-based...

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17th International Conference on Web Information Systems and Technologies, WEBIST 2021

作者： Barth, Guilherme Gabriel da Rosa Righi, Rodrigo da Costa, Cristiano André Rodrigues, Vinicius Facco Applied Computing Graduate Program Universidade do Vale do Rio dos Sinos São Leopoldo Brazil

ISBN: (纸本)9789897585364

Today, streaming, Artificial Intelligence, and the Internet of Things (IoT) are being some of the main drivers to accelerate process automation in various companies. These technologies are often connected to critical tasks, requiring reliable and scalable environments. Although Fog computing has been on the rise as an alternative to address those challenges, we perceive a gap in the literature related to adaptability on the number of resources on both cloud and fog layers. Multiple studies suggest different Cloud-Fog architectures for IoT implementations, but not thoroughly addressing elasticity control mechanisms. In this context, this article presents ProFog as a proactive elasticity model for IoT-based Cloud-Fog architectures. ProFog uses the ARIMA prediction model to anticipate load behaviors, so triggering scaling actions as close to when they are required as possible. This strategy allows the delivery of new resources before reaching an overloaded or underloaded state, benefiting performance, and energy saving. We developed a ProFog prototype that showed an improvement of 11.21% in energy consumption in favor of ProFog. © 2021 by SCITEPRESS – Science and Technology Publications, Lda. All rights reserved.

关键词： Internet of things

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Evaluation of Convolutional Neural Networks for COVID-19 Classification on Chest X-Rays 10th

Evaluation of Convolutional Neural Networks for COVID-19 C...

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10th Brazilian Conference on Intelligent Systems, BRACIS 2021

作者： Zeiser, Felipe André Costa, Cristiano André da Ramos, Gabriel de Oliveira Bohn, Henrique Santos, Ismael Righi, Rodrigo da Rosa Graduate Program in Applied Computing Universidade do Vale do Rio dos Sinos São Leopoldo Brazil

ISBN: (纸本)9783030916985

Early identification of patients with COVID-19 is essential to enable adequate treatment and to reduce the burden on the health system. The gold standard for COVID-19 detection is the use of RT-PCR tests. However, due to the high demand for tests, these can take days or even weeks in some regions of Brazil. Thus, an alternative for detecting COVID-19 is the analysis of Digital Chest X-rays (XR). Changes due to COVID-19 can be detected in XR, even in asymptomatic patients. In this context, models based on deep learning have great potential to be used as support systems for diagnosis or as screening tools. In this paper, we propose the evaluation of convolutional neural networks to identify pneumonia due to COVID-19 in XR. The proposed methodology consists of a preprocessing step of the XR, data augmentation, and classification by the convolutional architectures DenseNet121, InceptionResNetV2, InceptionV3, MovileNetV2, ResNet50, and VGG16 pre-trained with the ImageNet dataset. The obtained results for our methodology demonstrate that the VGG16 architecture presented a superior performance in the classification of XR, with an Accuracy of 85.11 %, Sensitivity of 85.25 %, Specificity of 85.16 %, F1-score of 85.03 %, and an AUC of 0.9758. © 2021, Springer Nature Switzerland AG.

关键词： COVID-19

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Memoryless: A Two-phase Methodology for Setting Memory Requirements on Serverless Applications 17

Memoryless: A Two-phase Methodology for Setting Memory Requi...

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17th International Conference on Web Information Systems and Technologies, WEBIST 2021

作者： da Rosa Righi, Rodrigo Borges, Gabriel da Costa, Cristiano André Rodrigues, Vinicius Facco Applied Computing Graduate Program Universidade do Vale do Rio dos Sinos São Leopoldo Brazil

ISBN: (纸本)9789897585364

Serverless computing, also known as Function as a Service, is a new paradigm that aims to separate the user of the platform from details about any infrastructure deployment. The problem lies in the fact that all the current Serverless platforms require the user to specify at least the needed memory usage for their Serverless offerings. Here we have a paradox since the users must be involved in technical issues to run their applications efficiently, both in terms of execution time and financial costs. To the best of our knowledge, the state-of-the-art lacks on providing studies regarding the best memory size for a particular application setting. In this context, this work presents Memoryless, a computational methodology that is in charge of removing the completion of memory limits by the user when launching Serverless demands. To accomplish this, we introduce in the literature a twopass algorithm composed of a microbenchmark where users inform simple application parameters (first pass) and receive from the hypervisor the memory required to run their demands. In addition to user abstraction, financial cost also drives our research, since commonly this metric is directly proportional to the selected memory size. We implemented Memoryless using NodeJS, Kubeless, and Kubernetes. The result confirms that the proposed methodology is capable of lowering the memory needs to run an application while maintaining expected execution times. This benefits both cloud administrators (who can run more Serverless demands for different users in parallel) and cloud users, who will pay less on using the cloud, so exploring better the pay-as-you-go policy. © 2021 by SCITEPRESS – Science and Technology Publications, Lda. All rights reserved.

关键词： Abstracting

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A proposal for postpartum support based on natural language generation model

A proposal for postpartum support based on natural language ...

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2018 International Conference on Computational Science and Computational Intelligence, CSCI 2018

作者： Zeni Montenegro, Joao Luis Andre Da Costa, Cristiano Da Rosa Righi, Rodrigo Roehrs, Alex Farias, Elson Romeu SOFTWARELAB Applied Computing Graduate Program Universidade Do Vale Do Rio Dos Sinos Sao Leopoldo Brazil

ISBN: (纸本)9781728113609

This article presents a Multifaceted Natural Language Generation Model to help women in a postpartum. This proposal supports speech and text interactions, developing responses through an ontology model and retrieval based-method techniques oriented to the welfare of women after the birth of their baby. We show a case study, introducing an architecture model of conversational agents, a scenario and a simulation of this proposal. Our results presented a better performance in response time generated from a retrieval based-method(two seconds), and similar response accuracy, slightly better for semantic queries (20% better). © 2018 IEEE.

关键词： Ontology

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Code Autocomplete Using Transformers 10th

Code Autocomplete Using Transformers

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10th Brazilian Conference on Intelligent Systems, BRACIS 2021

作者： Meyrer, Gabriel T. Araújo, Denis A. Rigo, Sandro J. CWI Software São Leopoldo Brazil Applied Computing Graduate Program UNISINOS São Leopoldo Brazil

ISBN: (纸本)9783030916985

In software development, code autocomplete can be an essential tool in order to accelerate coding. However, many of these tools built into the IDEs are limited to suggesting only methods or arguments, often presenting to the user long lists of irrelevant items. Since innovations introduced by transformer-based models that have reached the state of the art performance in tasks involving natural language processing (NLP), the application of these models also in tasks involving code intelligence, such as code completion, has become a frequent object of study in recent years. In these paper, we present a transformer-based model trained on 1.2 million Java files gathered from top-starred Github repositories. Our evaluation approach was based on measuring the model’s ability to predict the completion of a line, proposing a new metric to measure the applicability of the suggestions that we consider better adapted to the practical reality of the code completion task. With a recently developed Java web project as test set, our experiments showed that in 55.9% of the test cases the model brought at least one suggestion applicable, while the best baseline model presented this in 26.5%. © 2021, Springer Nature Switzerland AG.

关键词： Software design

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Ubiquitous computing in light of human phenotypes: foundations, challenges, and opportunities

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Journal of Ambient Intelligence and Humanized computing 2023年第3期14卷 2341-2349页

作者： Bavaresco, Rodrigo Simon Barbosa, Jorge Luis Victória Applied Computing Graduate Program - PPGCA University of Vale do Rio dos Sinos - UNISINOS Av. Unisinos São Leopoldo Rio Grande do Sul93.022-000 Brazil

The interest in human phenotypes has leveraged interdisciplinary efforts encouraging a better understanding of the broad spectrum of psychological and behavioral disorders. Moreover, the usage of mobile and wearable devices along with unobtrusive computational capabilities provides an extensive amount of information that allows the characterization of phenotypes. This article describes the human phenotype through the lens of computational range and reviews state-of-the-art computational phenotyping. Furthermore, the article discusses computational phenotyping’s extension concerning the combination of intelligent environments and personal mobile devices, addressing technical, managerial, and ethical challenges. This combination reinforces ubiquitous computational capabilities for phenotyping as a facilitator of interdisciplinary information convergence in favor of clinical and biomedical research. © 2022, The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.

关键词： Wearable technology

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GUGA: A tool for participatory cities

GUGA: A tool for participatory cities

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18th IEEE Symposium on Computers and Communications, ISCC 2013

作者： Schunke, Luana Carine De Oliveira, Luiz Paulo Luna Villamil, Marta Becker Applied Computing Graduate Program University of Vale Do Rio Dos Sinos-Unisinos S˜ao Leopoldo-RS Brazil

ISBN: (纸本)9781479937554

Participatory cities are those that allow the participation of citizens in the construction and improvement of their common daily life. In this work we present a tool for that participation, allowing the citizens to register the occurrences as well as take knowledge about the global geographic status of their city in on a variety of contexts (security, transit, etc.). However, a tool like that, fed by the people, certainly will deal with a large amount of information, distributed geographically. To accomplish that, a precise criterion for visualizing the resultant density distribution of occurrences must be used. In this paper, we also propose an automatic method for that visualization based on Voronoi Diagrams. The Voronoi polygons divide the region according to the concentration of occurrences. In this scheme, the area of each Voronoi polygon defines the density of the occurrences of the specific categories which are shown in the city map in color and transparency intensities for visualization. This can easily reveal the space distribution of important issues, in a variety of contexts such as criminality, commercial and industrial activities, drugs traffic, illumination concerns, and others. © 2013 IEEE.

关键词： Visualization

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