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8th Brazilian Conference on Intelligent Systems, BRACIS 2019

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

ISBN: (纸本)9781728142531

Cloud computing (CC) popularization unleashed the creation and competition of a large number of new companies providing CC services, the so called Cloud Providers (CPs). Thus, select the smallest CP set with the lowest price that are the most suitable to a given request (customer's needs, such as demanded resources and desired service quality) becomes a hard problem. Nonetheless, robust search methods like metaheuristics ones are used to solve it, for instance Evolutionary Algorithms (EAs). Performance Indicators (PIs) were used to quantify features of each CP used later to select them using a method. This paper proposes an improved hybrid method which uses in sequence: a deterministic, an EA and a local search method to find the most suitable possible CP set in the solution search space. This hybrid method was tested and has the highest assertiveness among all others methods developed to solve this problem, becoming a promising solution to a real application. © 2019 IEEE.

关键词： Benchmarking

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SDN4Moodle: An SDN-based Toolset to Enhance QoS of Moodle Platform

SDN4Moodle: An SDN-based Toolset to Enhance QoS of Moodle Pl...

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2018 IEEE Symposium on Computers and Communications, ISCC 2018

作者： Marcondes, Anderson H. Da Silva Miers, Charles C. Pillon, Maurcio A. Koslovski, Guilherme P. Graduate Program in Applied Computing Santa Catarina State University Joinville Brazil

ISBN: (纸本)9781538669501

Network configuration, performance, and congestion impact the Quality of Service (QoS) of Moodle Learning Management System (LMS). Moreover, LMSs composing modules have different QoS demands for each activity. Upon a network, they compete for resources with applications for social media, streaming, chat, cloud file synchronization, games, among others. Eventually, the network congestion can leave the LMS service unavailable for students and professors. Recently, the popularization of Software Defined Networks (SDN) revolutionized the network management. We propose SDN4Moodle, a toolset to increase the QoS of Moodle services. SDN4Moodle was implemented in conformity to Moodle's plugin guidelines, and it is controlled by internal Moodle events. Each action performed by a Moodle's user is dynamically translated into network forwarding rules, and switches configuration. Our experimental results indicates SDN4Moodle, an open-source system, efficiently achieves flows isolation and bandwidth control on shared networks. © 2018 IEEE.

关键词： Quality of service

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On proposing a non-intrusive device and methodology to monitor motor degradation

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Journal of King Saud University - Engineering Sciences 2023年第3期35卷 215-223页

作者： Kuhn, Henrique Cafruni da Rosa Righi, Rodrigo Crovato, Cesar David Paredes Electrical Engineering Graduate Program Universidade do Vale do Rio dos Sinos São Leopoldo Brazil Applied Computing Graduate Program Universidade do Vale do Rio dos Sinos São Leopoldo Brazil

Monitoring the degradation of induction motors is an essential concern for industries, especially when there are high costs related to maintenance and their stops. Nowadays, there are many non-invasive ways to monitor the health status of induction motors, including sensors to measure temperature, magnetic field, vibration, current, and power. However, installing these sensors may not be a simple task since intrusive procedures such as engine disassembling, wire separation, and engine interruption are commonly observed. Thus, we propose MUCLA (Multiphase Clamp and Tracking - patent pending) as a new device and methodology for monitoring motor degradation by analyzing its stator current. MUCLA introduces a non-invasive current sensors array on a proposed clamp in the hardware perspective, while a spectral tracking methodology refers to our novelty in the software viewpoint. For end-users, the main MUCLA contribution relies on the combination of the simplicity of installation and the possibility of using the proposed device even when considering Variable-Frequency Drive powered engines. The results obtained with both simulation and practical tests show encouraging results over different input workloads and emulated degradation. Compared to the current initiatives, we can classify MUCLA as a better solution for industrial plants in terms of installation time, installation complexity, and cost. © 2021 The Authors

关键词： Induction motors

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Hidden Things and Implicit Interaction: Looking Back on How Invisibility Evolved as a Quality-In-Use Attribute 22

Hidden Things and Implicit Interaction: Looking Back on How ...

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21st Brazilian Symposium on Human Factors in computing Systems, IHC 2022

作者： De Souza Filho, José Cezar Sampaio, Andréia Libório Feitosa, Eduardo Luzeiro Institute of Computing Federal University of Amazonas Manaus Brazil Graduate Program in Computing Federal University of Ceará Quixadá Brazil

ISBN: (纸本)9781450395069

Invisibility in Ubiquitous computing (UbiComp) and Internet of Things (IoT) systems refers to the merge of technology in the environment or the interaction workload decrease so that users can focus on their daily activities. It has been a fundamental attribute for these systems since the UbiComp advent and has received different names and definitions over time. However, there is a lack of retrospective studies investigating how these perspectives contributed to the current concept of Invisibility. Therefore, this paper aims to understand how Invisibility evolved as a quality-in-use attribute. We applied the snowballing method to search for literature evidence about the attributes and interaction evaluation approaches related to Invisibility. We identified eight related attributes: Intelligibility, Accuracy, Control, Customization, Non-obtrusiveness, Diffusion, Transparency, and Understandability. Also, we observed that the existing evaluation approaches consider only part of these attributes. Our findings suggest opportunities to improve the approaches and for future research. © 2022 ACM.

关键词： Internet of things

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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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Executing distributed applications on SDN-based Data Center: A study with NAS Parallel Benchmark 7

Executing distributed applications on SDN-based Data Center:...

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2016 7th International Conference on the Network of the Future, NOF 2016

作者： Marcondes, Anderson H. S. Diel, Gustavo De Souza, Felipe R. Vieira, Paulo R. Fiorese, Adriano Koslovski, Guilherme P. Graduate Program in Applied Computing Santa Catarina State University Joinville SC Brazil

ISBN: (纸本)9781509046713

Software-Defined Networking (SDN) paradigm has decoupled data and control planes on traditional networks. In this context, a logically-centralized controller, with full knowledge on network resources and traffic loads, executes routing algorithms to identify forwarding paths, while networking resources (switches and routers) just work on packet forwarding. This work contributes by executing and characterizing a well-know distributed application, NAS parallel benchmark, atop an SDN-based data center. A comparison with different flow routing algorithms is presented, highlighting that an application can reduce its runtime when applying a multi-path routing. © 2016 IEEE.

关键词： Benchmarking

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Comparing Best and Quota Fragment Picker Protocols Applied to Protein Structure Prediction 20th

Comparing Best and Quota Fragment Picker Protocols Applied t...

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20th International Conference on Hybrid Intelligent Systems, HIS 2020 and 12th World Congress on Nature and Biologically Inspired computing, NaBIC 2020

作者： Will, Nilcimar Neitzel Parpinelli, Rafael Stubs UDESC Graduate Program in Applied Computing Santa Catarina State University Joinville Brazil

ISBN: (纸本)9783030730499

The use of fragment insertion in the protein structure prediction problem can be considered one of the most successful strategies to add problem-dependent information. The well known Rosetta suite provides two protocols for generating fragment libraries: Best and Quota. The first aims to maximize a given score function, while the second aims add fragment diversity. This paper presents the results with four proteins to verify the impact of using more secondary structure information through the quota protocol when compared to the best protocol. The tests were performed considering the PSIPRED, SPIDER2, and MUFold predictors. Results obtained are compared in terms of RMSD, processing time, and convergence. © 2021, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Forecasting

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Method for improvement of transparency: Use of text mining techniques for reclassification of governmental expenditures records in Brazil

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International Journal of Business Intelligence and Data Mining 2021年第2期18卷 155-196页

作者： de Oliveira Almeida, Gustavo Revoredo, Kate Cappelli, Claudia Maciel, Cristiano Graduate Program in Business Federal Fluminense University Niteroi/RJ Brazil Graduate Program in Informatics Federal University of Rio de Janeiro State Rio de Janeiro/RJ Brazil Computing Institute Mato Grosso Federal University Cuiabá/MT Brazil

Many countries have transparency laws requiring availability of data. However, often data is available but not transparent. We present the Transparency Portal of Brazilian Federal Government case and discuss limitations of public acquisitions data stored in free text format. We employed text-mining techniques to reclassify descriptive texts of measurement units related to products and services. The solution presented in KNIME and Java aggregated measurements in the original (n = 69,372 with 78% reduction in number of descriptions, 94% items classified) and in cross validation sample (n = 105,266 with 88% reduction, classifying 78% of items). In addition, we tested computational time for processing of texts for a wide range of data input sizes, suggesting the stability and scalability of the solution to process larger datasets. Finally, we produced analysis identifying probable input errors, suppliers and purchasing units with abnormal transactions and factors affecting procurement prices. We present suggestions for future research and improvements. Copyright © 2021 Inderscience Enterprises Ltd.

关键词： Transparency

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The Influence of Feature Selection on Job Clustering for an E-recruitment Recommender System 19th

The Influence of Feature Selection on Job Clustering for an ...

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19th International Conference on Artificial Intelligence and Soft computing, ICAISC 2020

作者： Junior, Joel J. S. Vilasbôas, Fabricio G. de Castro, Leandro N. Graduate Program in Electrical Engineering and Computing Mackenzie Presbyterian University São Paulo Brazil

ISBN: (纸本)9783030615338

Recommender systems aim to effectively recommend items to the user based on their profile. An online recruitment system recommends jobs for a candidate according to his profile and can also act in reverse, recommending more qualified candidates for a particular job. Defining which variables will be used impacts directly the recommendation quality so that, when using the most important variables, we have a better assertiveness in the process. The goal of this work is to select the most important features of an online recruitment database using feature selection techniques. More specifically, we used the algorithms of Mitra, SUD and ACA to perform feature selection. The datasets used were derived from the original dataset assuming three distinct scenarios: the dataset containing the attributes related with the jobs' features;the dataset containing the bag of words of the description feature of the jobs;and the dataset resulting from the union of the two previous ones. The features' subsets selected in each of the above scenarios had their performance evaluated in a clustering task. The results obtained in each scenario show a performance gain of the clustering process when feature selection is made over the original data. Also, it was observed that the jobs' features result in better performance than the other two cases. © 2020, Springer Nature Switzerland AG.

关键词： Recommender systems

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Internet of things scalability: Analyzing the bottlenecks and proposing alternatives 6

Internet of things scalability: Analyzing the bottlenecks an...

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2014 6th International Congress on Ultra Modern Telecommunications and Control Systems and Workshops, ICUMT 2014

作者： Gomes, Márcio Da Rosa Righi, Rodrigo Da Costa, Cristiano André Applied Computing Graduate Program Universidade Do Vale Do Rio Dos Sinos Brazil

ISBN: (纸本)9781479952915

Internet of Things, or IoT, is a new revolution of the Internet, supporting a connection between objects and humans yet more strong. This area is known by the huge quantity of data that can be generated from the RFID sensors at realtime. On managing this data, the IoT middleware introduces some time constrains regarding both accessing applications and filtering and storing data actions. Thus, middleware scalability is a key requirement for supporting the current growth of IoT. In this context, this article firstly presents μIB - Micro Internet of Things Benchmark - that aims at evaluating the scalability of EPC-compliant middlewares. μIB combines data from tags, RFID readers, sequential requests and number of threads to compose an evaluation setup to assess EPCIS and ALE components. We used this benchmark to evaluate Fosstrak, which is one of the most used IoT middlewares, in a single server. The tests emphasized that the exhaustion in one component influences the performance of the others directly. Following this research line, this article also describes the first ideas on redesigning the IoT middleware using techniques such as cloud virtualization and elasticity, service decomposition and multithreading programming. © 2014 IEEE.

关键词： Middleware

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