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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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Anais Brasileiros de Dermatologia: who wrote this century-old history?

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Anais Brasileiros de Dermatologia 2025年第3期100卷 527-538页

作者： Grimaldi, Helena Cargnelutti Camargo, Sandro da Silva Private Clinic RS Bagé Brazil Graduate Program in Applied Computing Federal University of Pampa RS Bagé Brazil

The Anais Brasileiros de Dermatologia (ABD), an official publication of the Brazilian Society of Dermatology, has been published since 1925. ABD is considered the most influential dermatological journal in Latin America. By 2025, the journal will mark a significant milestone, celebrating a century of history. Over this time, it has published 99 volumes and 6,299 contributions from more than 10,800 authors. To analyze the trajectory of the journal, this study employs an applied research approach characterized by descriptive objectives and a quantitative nature. This research was based on a documentary procedure that encompassed all contributions already published in the journal. The main goal of the work was to identify the most prominent authors who have contributed to the journal and to map the largest co-authorship communities. The authors hope that this research serves as a formal recognition of the researchers who have written the history of the ABD. © 2025 Sociedade Brasileira de Dermatologia

关键词： Authorship Bibliometrics Periodical Scientific communication and diffusion

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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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Investigating the computation of smoothed deceptive routes in topographic terrains for agent-based simulation systems

Investigating the computation of smoothed deceptive routes i...

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Computational Intelligence in Security, Defence and Biometrics (CISDB), IEEE Symposium on

作者： Luigi P. Souza Thiago R. S. Leão Crhistopher Lenhard Edison P. Freitas Luis A. L. Silva Graduate Program in Computer Science Federal Univ. of Santa Maria Santa Maria Brazil Undergraduate Course in Computer Science Federal Univ. of Santa Maria Santa Maria Brazil Institute of Informatics Federal Univ. of Rio Grande do Sul Porto Alegre Brazil Applied Computing Department Federal Univ. of Santa Maria Santa Maria Brazil

ISBN: (数字)9798331508296

ISBN: (纸本)9798331508302

The capacity to deceptively move in hilly terrains is fundamental to agents in simulation systems for tactical and strategic military training. Such an ability to deceive the adversary can ensure a relevant advantage by hiding the real goals of a mission. Using pairs of real and deceptive mission goals, this paper investigates the planning of realistic deceptive routes for simulated agents. With real-world terrain elevation maps, it shows how to explore pathfinding algorithms with relevant path-smoothing characteristics (Theta* and WJPS*, contrasting with the standard $A^{*}$ algorithm) in terrains with pronounced relief features. The study analyzes the effects of terrain elevation costs and the representation of relief contour lines on the determination of more realistic deceptive paths. This work also investigates how users can adjust a Last Topographic Deceptive Point ($L D P_{T}$) calculation to enhance the pathfinding algorithm’s ability to produce more deceptively dense and topographically aware routes. Experimental results for different deceptive topographic path planning strategies are evaluated according to statistical models showing that Theta*, despite being slower than the base $A^{*}$ method in most cases, generated smoothed paths while maintaining a similar deception density for the proposed strategies. On the other hand, WJPS outperformed both in execution time for certain strategies while maintaining the smoothed path characteristic and resulting in a path with lower deceptive capacity.

关键词： Training Hands Biometrics Costs Path planning Planning Security Standards Computational intelligence

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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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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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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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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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