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16th International Conference on ENTERprise Information Systems, CENTERIS 2024 - 12th International Conference on Project MANagement, ProjMAN 2024 - 14th International Conference on Health and Social Care Information Systems and Technologies, HCist 2024

作者： Durand R, José Ribamar Junior, Geraldo Braz Da Silva, Italo Francyles Santos Da Costa Oliveira, Rui Miguel Gil Applied Computing Group Federal University of Maranhão Vila Bacanga São Luís65080-805 Brazil Graduate Program in Adult Health - PPGSAD Federal University of Maranhão Vila Bacanga São Luís65080-805 Brazil

Penile cancer, although rare, has an increasing mortality rate in Brazil, highlighting the need for effective diagnostic methods. Artificial Intelligence (AI) in histopathological analysis can speed up and objectify diagnosis, but designing an ideal architecture is challenging. In this study, we propose a neural architecture search (NAS) methodology for detecting penile cancer in digital histopathology images. We explored different configurations of stem blocks and the inclusion of attention mechanisms, highlighting specific preferences depending on the magnification of the images. The results showed that the NAS methodology enabled the discovery of more accurate and optimized architectures for this task, surpassing conventional models. The proposed models achieve 89.5% and 88.5% F1-Score for 40X and 100X magnification, respectively. © 2025 The Author(s).

关键词： Lung cancer

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HistAttentionNAS: A CNN built via NAS for Penile Cancer Diagnosis using Histopathological Images

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Procedia Computer Science 2025年 256卷 764-771页

作者： José Ribamar Durand R. Geraldo Braz Junior Italo Francyles Santos da Silva Rui Miguel Gil da Costa Oliveira Applied Computing Group - Federal University of Maranhão Vila Bacanga São Luís 65080-805 Brazil Graduate Program in Adult Health - PPGSAD - Federal University of Maranhão Vila Bacanga São Luís 65080-805 Brazil

关键词： Penile Cancer Detection Histopathologic Classification Neural Architecture Search

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An IoT Transport Architecture for Passenger Counting: A Real Implementation 17

An IoT Transport Architecture for Passenger Counting: A Real...

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17th IFIP/IEEE International Symposium on Integrated Network Management, IM 2021

作者： Kniess, Janine Rutke, Julio Cezar Castaneda, William Alberto Cruz Santa Catarina State University Graduate Program in Applied Computing Brazil

ISBN: (纸本)9783903176324

A smart urban mobility considers the technological-based development in transport systems, services and their use to improve the movement of people and goods inter or intra-cities. Cities increasingly face problems caused by traffic and need to find solutions to improve mobility and to reduce congestion and pollution. In this paper, we present a Passenger Counting Scheme into buses. Embedded counting algorithms based on Computer Vision are proposed to count passenger arrivals and departures in real time. Experiments in a real scenario expose that the proposed scheme achieved a high percentage of success in passenger count. © 2021 IFIP.

关键词： Smart city

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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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DCANon: Towards Distributed Certification Authority (CA) with Non-fungible Token (NFT) 37th

DCANon: Towards Distributed Certification Authority (CA) wit...

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37th International Conference on Advanced Information Networking and Applications, AINA 2023

作者： Descio-Trineto, Rafael Pillon, Maurício Koslovski, Guilherme Miers, Charles Graduate Program in Applied Computing Santa Catarina State University Joinville Brazil

ISBN: (纸本)9783031290558

Distributed applications rely on Certification Authorities (CAs) entities associated with a few institutions around the world. There are countless trusted institutions on the networks, e.g., universities, governments, banks, making effective use of CAs. Although largely used, the decentralized management of CAs is an administrative challenge. In this context, the joint emergence of digital ledgers and Non-Fungible Tokens (NFTs) compose a new opportunity to effectively decentralize single assets safely. Towards Distributed Certification Authority with Non-Fungible Token (DCANon) is a distributed Certification Authority (CA) built to trusted institutions and supported by Non-Fungible Token (NFT) concepts. DCANon changes the way revocation may be find, permitting that all consortium member crawler the blockchain for revoked certificates, independently from which CA this revocation occurs. A proof-of-concept prototype was implemented with Hyperledger Fabric demonstrating the benefits of DCANon. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Distributed ledger

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DeepScheduling: Grid computing Job Scheduler Based on Deep Reinforcement Learning 34th

DeepScheduling: Grid Computing Job Scheduler Based on Deep R...

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34th International Conference on Advanced Information Networking and Applications, AINA 2020

作者： Casagrande, Lucas C. Koslovski, Guilherme P. Miers, Charles C. Pillon, Maurício A. Graduate Program in Applied Computing Santa Catarina State University Joinville Brazil

ISBN: (纸本)9783030440404

Grid systems are large-scale platforms which consume a considerable amount of energy. Several efficient resource/power management strategies were proposed by the specialized literature. However, most of the proposed strategies are rule-based policies which do not exploit workload patterns. Deploying the same set of rules on systems using different usage patterns, and platform settings, may lead to a sub-optimized setup. Due to the complex nature of grid systems, tailoring such a system-specific policy is not a straightforward task. In this paper, we explore a Deep Reinforcement Learning (DRL) method to build an adaptive energy-aware scheduling policy. We trained our algorithm using real workload traces from Grid’5000 platform. Our experiments pointed out an energy setup saving up to 7%, as well as average requests waiting time reduction of 27%. Finally, the resuslts clarify the importance of explore the workload to build system-specific policies. © 2020, Springer Nature Switzerland AG.

关键词： Reinforcement learning

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SSL-C4.5: Implementation of a Classification Algorithm for Semi-supervised Learning Based on C4.5 9th

SSL-C4.5: Implementation of a Classification Algorithm for S...

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9th Brazilian Conference on Intelligent Systems, BRACIS 2020

作者： Ortiz-Díaz, Agustín Alejandro Bayer, Flavio Roberto Baldo, Fabiano Graduate Program in Applied Computing Santa Catarina State University Joinville Brazil

ISBN: (纸本)9783030613792

Classification algorithms have been extensively studied in many of the major scientific investigations in recent decades. Many of these algorithms are designed for supervised learning, which requires labeled instances to achieve effective learning models. However, in many of the real human processes, data labeling is expensive and time-consuming. Because of this, alternative learning paradigms have been proposed to reduce the cost of the labeling process without a significant loss of model performance. This paper presents the Semi-Supervised Learning C4.5 algorithm (SSL-C4.5) designed to work in scenarios where only a small part of the data is labeled. SSL-C4.5 was implemented over the J48 implementation of the C4.5 algorithm available at the WEKA platform. The J48 was modified incorporating a metric for semi-supervised learning. This metric aims at inducing decision tree models able to analyze and extract information from the entire training dataset, including instances of unlabeled data in scenarios where they are the majority. The assessment performed using eight different benchmark datasets showed that the new proposal has achieved promising results compared to the supervised version of C4.5. © 2020, Springer Nature Switzerland AG.

关键词： Decision trees

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An improved evolutionary hybrid method for cloud provider selection 8

An improved evolutionary hybrid method for cloud provider se...

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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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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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