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International Conference on computer Supported Cooperative Work in Design

作者： António Correia Dennis Paulino Hugo Paredes Benjamim Fonseca Shoaib Jameel Daniel Schneider Jano Moreira de Souza INESC TEC and University of Trás-os-Montes e Alto Douro UTAD Vila Real Portugal School of Computer Science and Electronic Engineering Colchester Campus University of Essex UK Tércio Pacitti Institute of Computer Applications and Research NCE/UFRJ Rio de Janeiro Brazil Systems Engineering and Computer Science Program (PESC/COPPE/UFRJ) Rio de Janeiro Brazil

ISBN: (纸本)9781728165981

It has been a quarter of a century since the publication of the first edition of the IEEE International Conference on computer Supported Cooperative Work in Design (CSCWD) held in 1996 in Beijing, China. Despite some attempts to empirically examine the evolution and identity of the field of CSCW and its related communities and disciplines, the scarcity of scientometric studies on the IEEE CSCWD research productivity is noteworthy. To fill this gap, this study reports on an exploratory quantitative analysis of the literature published in the IEEE CSCWD conference proceedings with the purpose of visualizing and understanding its structure and evolution for the 2001-2019 period. The findings offer valuable insights into the paper and author distribution, country and citation-level productivity indicators, degree of collaboration, and collaboration index. Through this analysis we also expect to get an initial overview of the IEEE CSCWD conference concerning the main topics being presented, most cited papers, and variances in the number of keywords, full-text views, and references.

关键词： Productivity Visualization Statistical analysis Conferences Bibliometrics Collaboration Collaborative work

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A Parallel Ray Tracing Architecture Suitable for Application-Specific Hardware and GPGPU Implementations

A Parallel Ray Tracing Architecture Suitable for Application...

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Euromicro Symposium on Digital system Design

作者： Alexandre S. Nery Nadia Nedjah Felipa M.G. Franca Lech Jozwiak LAM-Computer Architecture and Microelectronics Laboratory Systems Engineering and Computer Science Program COPPE Universidade Federal do Rio de Janeiro Brazil Department of Electrical Engineering-Electronic Systems Eindhoven University of Technology Netherlands Universidade do Estado do Rio de Janeiro Rio de Janeiro RJ BR

The Ray Tracing rendering algorithm can produce high-fidelity images of 3-D scenes, including shadow effects, as well as reflections and transparencies. This is currently done at a processing speed of at most 30 frames per second. Therefore, actual implementations of the algorithm are not yet suitable for interactive real-time rendering, which is required in games and virtual reality based applications. Fortunately, the algorithm allows for massive parallelization of its computations. In this paper, we present a parallel architecture for ray tracing based on a uniform spatial subdivision of the scene and exploiting an embedded computation of ray-triangle intersections. This approach allows for a significant acceleration of intersection computations, as well as, a reduction of the total number of the required intersections checks. Furthermore, it allows for these checks to be performed in parallel and in advance for each ray. In this paper we discuss and analyze an ASIP-based implementation using FPGAs and a GPGPU-based parallel implementation of the proposed architecture. The performance of both implementations are reported and compared.

关键词： Ray tracing Graphics processing unit Instruction sets computer architecture Registers Image color analysis Hardware

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Extrinsic LiDAR-Robot And LiDAR-Camera Calibration For Multi-sensor Fusion*

Extrinsic LiDAR-Robot And LiDAR-Camera Calibration For Multi...

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IEEE Latin American Robotics Symposium, LARS

作者： Gilmar Pereira Da Cruz Hector Azpúrua Fernando Lizarralde Gustavo Medeiros Freitas Graduate Program in Electrical Engineering Universidade Federal de Minas Gerais - Av. Antônio Carlos 6627 Belo Horizonte MG Brazil Department of Computer Science Universidade Federal de Minas Gerais MG Brasil Electrical Engineering Program - COPPE Universidade Federal do Rio de Janeiro RJ Brasil

ISBN: (数字)9798331508807

ISBN: (纸本)9798331508814

In mobile robotics, an essential requirement for the fusion of different sensors is that measurements are expressed with respect to the same reference. In this sense, the transformation between sensors and robot is necessary to ensure better sensor fusion. Therefore, this article proposes an extrinsic sensor calibration based on markers and associated to three orthogonal planes. This technique is applied to two calibration approaches, LiDAR-Robot and LiDAR-Camera. The first one calculates the transformation between a 3D LiDAR sensor and a robot, and the second system calculates the transformation between a 3D LiDAR and an embedded RGB camera. To demonstrate the efficiency of our method, we performed simulations on the coppeliaSim simulator and experiments in the laboratory. Then, the results show that it is possible to calibrate the sensors with the methodologies.

关键词： Visualization Laser radar Three-dimensional displays Robot vision systems Sensor fusion Cameras Sensor systems Sensors Calibration Registers

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Deep learning-based real time detection for cardiac objects with fetal ultrasound video

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Informatics in Medicine Unlocked 2023年 36卷

作者： Iriani Sapitri, Ade Nurmaini, Siti Naufal Rachmatullah, Muhammad Tutuko, Bambang Darmawahyuni, Annisa Firdaus, Firdaus Rini, Dian Palupi Islami, Anggun Intelligent System Research Group Faculty of Computer Science Universitas Sriwijaya Palembang 30139 Indonesia Doctoral Program Faculty of Engineering Universitas Sriwijaya Palembang 30139 Indonesia Department of Informatics Engineering Faculty of Computer Science Universitas Sriwijaya Palembang 30139 Indonesia

Fetal cardiac anatomical structure interpretation by ultrasound (US) is a key part of prenatal assessment. Unfortunately, the numerous speckles in US video, the small size of fetal cardiac structures, and unfixed fetal positions make manual detection processes difficult. To alleviate such problems, a deep learning model was developed to fully automate the processing of fetal echocardiographs with 2-dimensional cross-sectional images. The weakness of such an approach is that a physician immediately interprets US video with 3-dimensional objects to diagnose patients in clinical practice. To improve fetal cardiac anatomical structure interpretation via US for accurate and real time diagnosis, this paper proposes a real-time fetal cardiac substructure detection using US video with the You Only Look Once (YOLO) framework. In YOLO, an end-to-end neural network makes predictions for cardiac substructure objects, boxes, and class probabilities simultaneously. To achieve reliable performance, 40 fetal echocardiography videos were trained with the new YOLOv7 architecture and fine-tuned to work optimally and run efficiently. We conducted with nine fetal cardiac substructure objects such as the left atrium, right atrium, left ventricle, right ventricle, tricuspid valve, pulmonary valve, mitral valve, aortic valve, and aorta. The results yielded the highest mean average precision of 82.10%, reaching 17 frames per second (FPS) for nine cardiac substructure objects in 0.3 ms. The main finding of our study is that with even a limited number of US videos, YOLOv7 can detect fetal cardiac substructure objects in real-time. Such a network can work efficiently to detect small fetal cardiac objects automatically in a rapid phase with the help of proper fine-tuning. This work mainly assists medical experts in the fetal cardiac anatomy diagnostic process. © 2022 The Authors

关键词： computer vision Fetal echocardiography Object detection YOLOv7

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Deep Learning Networks for Handwritten Bangla Character Recognition

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IAENG International Journal of Applied Mathematics 2023年第4期53卷 1页

作者： Begum, H. Islam, M.M. Eva, H.S. Emon, N.H. Siddique, F.A. Department of Electrical and Electronic Engineering East West University A/2 Aftabnagar Dhaka Bangladesh Department of Electrical Engineering and Computer Science South Dakota State University United States Engineering and Design Department Reverie Power and Automation Engineering Limited Bangladesh Program in Smart System Integrated Solutions Aalto University Finland

In recent years, deep convolutional networks (DCNN) have gained popularity for different classification (or recognition) tasks. In this paper, three well known DCNN structures were used, i.e., AlexNet, SqueezeNet and GoogLeNet, and their classification performances in recognizing handwritten Bangla isolated characters were compared. These networks have simpler structures compared to the recent DCNNs. Experiments on a standard Bangla database revealed that the overall performance of GoogLeNet is slightly better than the other two networks. Further analysis using saliency maps of the test samples revealed the important features that are learned by the networks for classifying characters. This information led us to understand why classification of some samples fail and how to rectify these. © (2023), (International Association of Engineers). All Rights Reserved.

关键词： Classification (of information)

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Extracting Semantic Information from Patent Claims Using Phrasal Structure Annotations

Extracting Semantic Information from Patent Claims Using Phr...

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Brazilian Conference on Intelligent systems (BRACIS)

作者： Danilo Silva de Carvalho Felipe Maia Galvão França Priscila Machado Vieira Lima Systems Engineering and Computer Science Program-COPPE Universidade Federal do Rio de Janeiro Rio de Janeiro Brazil Instituto Tércio Pacitti (NCE) Universidade Federal do Rio de Janeiro Rio de Janeiro Brazil

The rapid change of trading values from tangible assets to Intelectual Property has put both businesses and academia in a race to acquire and protect the rights to exploit such property. This is mainly accomplished in the form of patent issuing by the governments, being time consuming and complicated due to the vast amount of documents that need to be analyzed in order to assert the novelty or validity of a patent application. Patent information retrieval research is thus growing quickly to support document analysis across multiple domains and information systems. One of the big challenges in patent analysis is the identification of the elements of innovation (concepts, processes, materials) and the relations between them, in the patent text. This paper presents a method for extracting semantic information from patent claims by using semantic annotations on phrasal structures, abstracting domain ontology information and outputting ontology-friendly structures to achieve generalization. An extraction system built upon the method is briefly evaluated on a document sample from INPI, the Brazilian patent office, a challenging information source.

关键词： Semantics Patents Syntactics Data mining Training Ontologies Testing

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Digital Technology in Health Education Trend Mapping through Bibliometrics Analysis

Digital Technology in Health Education Trend Mapping through...

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International Conference on Informatics, Multimedia, Cyber and Information system (ICIMCIS)

作者： Fairuz Iqbal Maulana Dian Lestari Vandha Pradwiyasma Widartha Nirwana Haidar Wahyu Dirgantara Computer Science Department School of Computer Science Bina Nusantara University Jakarta Indonesia Faculty of Medicine Airlangga University Surabaya Indonesia Information System of Industrial Engineering Faculty Telkom University Bandung Indonesia Informatics Engineering Study Program University of Madura Pamekasan Indonesia Department of Electrical Engineering University of Merdeka Malang Malang Indonesia

ISBN: (纸本)9781665473286

This study examines the mapping of research data on digital technology in the field of health education using bibliometric analysis method. Data was collected by identifying keywords in the Scopus database and sorting them out to sort the studies from the last 10 years (2012–2021). Through this step, a total of 1482 documents were obtained (articles, journals, proceedings, books, and others). The data is then processed using the VOSViewer instrument to obtain a visualization of the mapping analysis. This study also analyzes the network types of authors and co-authors through the VOSViewer instrument. The result of this study indicates that the most document types published within ten years are Articles (66.5%), Review (22.9 % ), Conference Paper (4.2 % ), and others. The most studied subjects are Medicine (55.7%), Nursing (9.0%), Health Professions (8.2%), Social sciences (7.8%), engineering (3.9%), computer science (2.6 % ), Environmental science (2.6 % ), Biochemistry-Genetics and Molecular Biology (2.2%), Psychology (1.6%), and Dentistry (1.3%). This study offers a written communication process and the nature and direction of developing descriptive means of counting and analyzing the various phases of communication as well as recognizing the authorship and direction of its symptoms in documents on the subject of digital technology in the health sector.

关键词： Training Pediatrics Instruments Education Bibliometrics Transportation Psychology

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Exploring Personal Knowledge Ecologies: Dealing with Digital Platform Asymmetries

Exploring Personal Knowledge Ecologies: Dealing with Digital...

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International Conference on computer Supported Cooperative Work in Design

作者： Marcos Antonio De Almeida Jano Moreira De Souza António Correia Daniel Schneider Systems Engineering and Computer Science Program (PESC/COPPE/UFRJ) Rio de Janeiro Brazil Faculty of Information Technology University of Jyväskylä Jyväskylä Finland Postgraduate Program in Informatics PPGI/UFRJ Rio de Janeiro Brazil Tércio Pacitti Institute of Computer Applications and Research NCE/UFRJ Rio de Janeiro Brazil

ISBN: (数字)9798350349184

ISBN: (纸本)9798350349191

The rise of artificial intelligence agents and information technology platforms governed by data-driven algorithms has had profound impacts on the way knowledge work is managed and carried out. Concerning the novel uses of digital work platforms, the arising tensions might suggest that the socio-technical design frameworks adopted by major tech firms are becoming less viable and in some cases ineffective. We propose a conceptual architecture to support a socio-technical framework for exploring Personal Knowledge Ecologies in the context of the digital knowledge economy. This framework aims to increase the degree of individual freedom for the interoperation of these knowledge information infrastructures.

关键词： Knowledge engineering Sociotechnical systems computer architecture Ecology Software Heterogeneous networks Complexity theory

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Correction: Thiazole-fused androstenone and ethisterone derivatives: potent β- and γ-actin cytoskeleton inhibitors to treat melanoma tumors

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RSC medicinal chemistry 2025年第4期16卷 2025 Apr 3页

作者： Sanjay Adhikary Subrata Roy Shailesh Budhathoki Siam Chowdhury Abbey Stillwell Alexei G Basnakian Alan Tackett Nathan Avaritt Mohamed Milad Mohammad Abrar Alam Department of Chemistry and Physics College of Sciences and Mathematics Arkansas State University Jonesboro Arkansas 72467 USA malam@astate.edu. Environmental Sciences Program College of Sciences and Mathematics Arkansas State University Jonesboro AR 72467 USA. Molecular Biosciences Program College of Sciences and Mathematics Arkansas State University Jonesboro AR 72467 USA. Computer Science The College of Engineering and Computer Science Arkansas State University Jonesboro AR 72468 USA. Department of Pharmacology and Toxicology University of Arkansas for Medical Sciences 4301 W. Markham St Little Rock AR 72205 USA. Central Arkansas Veterans Healthcare System W. 7th St Little Rock AR 72205 USA. Department of Biochemistry and Molecular Biology University of Arkansas for Medical Sciences Little Rock AR 72205 USA. The Department of Mathematics and Statistics Arkansas State University Jonesboro AR 72467 USA. Arkansas Biosciences Institute Arkansas State University Jonesboro AR 72467 USA.

[This corrects the article DOI: 10.1039/D4MD00719K.].

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Exploring Low Rate Dos Attack Detection Methods: A Bibliometric Analysis and Roadmap for Further Research

Exploring Low Rate Dos Attack Detection Methods: A Bibliomet...

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International Conference on Data and Software engineering (ICODSE)

作者： Anteng Widodo Adian Fatchur Rochim Budi Warsito Doctoral Program of Information System School of Postgraduated Studies Diponegoro University Semarang Indonesia Department of Information System Faculty of Engineering Muria Kudus University Kudus Indonesia Department of Computer Engineering Faculty of Engineering Diponegoro University Semarang Indonesia Department of Statistics Faculty of Science and Mathematics Diponegoro University Semarang Indonesia

Low-Rate Denial of Service (LDoS) attacks, an emerging breed of DoS attacks, present a formidable challenge in terms of their detectability. Within the realm of network security, these attacks cast a substantial shadow over the availability and integrity of services. This study seeks to delve into the intricate mechanics of LDoS attacks and explore the landscape of developed detection methodologies. Employing bibliometric analysis, we employ a multifaceted approach to gather research insights pertaining to LDoS attack detection. This approach encompasses the examination of evolving research trends, scrutiny of widely cited scientific publications within the same domain, identification of prolific researchers shaping the field, and a judicious selection of reputable publishers for dependable information acquisition. Furthermore, our study undertakes a meticulous categorization and classification of previously proposed LDoS detection methods documented in well-established scientific literature. This endeavor not only provides a more profound comprehension of the evolutionary trajectory and thematic thrusts within LDoS attack detection research, but it also facilitates the identification of gaps and directions for future exploration. The culmination of these analytical efforts culminates in a comprehensive framework. This contribution manifests through structured categorization, classification, and a forward-looking research roadmap, which collectively serve as valuable tools for both current and aspiring researchers engaged in LDoS attack detection. In summary, this research not only delves into the complexities of LDoS attacks and their mechanisms but also augments the current understanding of detection capabilities. Through its nuanced contributions, this paper extends a helpful guide to the dynamic realm of LDoS attack detection, thus catalyzing advancements and insights for the future.

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