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GranDIHC-BR: Grand Research Challenges in Human-computer Interaction in Brazil for 2025-2035 24

GranDIHC-BR: Grand Research Challenges in Human-Computer Int...

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23rd Brazilian Symposium on Human Factors in Computing systems, IHC 2024

作者： Pereira, Roberto Darin, Ticianne Silveira, Milene Selbach Department of Informatics Federal University of Paraná Paraná Curitiba Brazil Virtual University Institute Federal University of Ceará Ceará Fortaleza Brazil School of Technology Pontifical Catholic University of Rio Grande do Sul Rio Grande do Sul Porto Alegre Brazil

ISBN: (纸本)9798400712241

The II GranDIHC-BR is a collaborative initiative to identify Grand Research Challenges for Human-computer Interaction (HCI) and define a research agenda for the next decade (2025-2035) in Brazil. A diverse group of researchers and practitioners identified seven critical societal and technological challenges for the country and the field: (1) New Theoretical and Methodological Approaches, (2) Ethics and Responsibility, (3) Plurality and Decoloniality, (4) Socio-Cultural Impacts, (5) Human-Data Interaction, (6) Implications of Artificial Intelligence, and (7) Interaction with Emerging technologies. We reflect on the challenges and lessons learned from managing such a large-scale collaborative effort and identify areas for the community to address in the coming years. This initiative fosters a deeper sense of community and sets a course for a decade of impactful research and development in Brazil. This paper is presented bilingually in English and Portuguese as a testament to its situated and universal implications. © 2024 Copyright held by the owner/author(s).

关键词： Ethical technology

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A Study on Coherence Length and Interferometry in Digital Holographic Microscopy 23

A Study on Coherence Length and Interferometry in Digital Ho...

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23rd international conference on Control, Automation and systems, ICCAS 2023

作者： Koga, Takahiro Kim, Hyun-Woo Cho, Myungjin Lee, Min-Chul Kyushu Institute of Technology Department of Computer Science and Networks Fukuoka Iizuka820-8502 Japan School of ICT Robotics and Mechanical Engineering Iitc Hankyong National University Kyonggi-do Anseong17579 Korea Republic of

ISBN: (纸本)9788993215274

Digital Holographic Microscopy (DHM) can display 3D profiles of microscopic objects and is expected to be used in a wide range of fields such as microbiology, microstructural investigation, and disease diagnosis. Since these fields require detailed information of the object, acquiring an accurate 3D profile is the most important. However, DHM requires several experimental equipments, and it does not define appropriate lasers for interferometers. Therefore, in this paper, we implement an experiment and find the optimum laser for the most accurate 3D profiles of interferometers by comparing 3D profiles using two types of interferometers and three types of lasers with different wavelengths. The results show that the relationship between the laser's coherence length and the optical path length of the interferometer is related to the accuracy of the 3D profiles. They also show that the accuracy of the 3D profile is higher when the coherence length is longer than the optical path length plus twice the height of the object. © 2023 ICROS.

关键词： Computational Imaging

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Intelligent Live Video Streaming for Object Detection 23

Intelligent Live Video Streaming for Object Detection

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23rd IEEE international conference on High Performance Computing and Communications, 7th IEEE international conference on Data Science and systems, 19th IEEE international conference on Smart City and 7th IEEE international conference on Dependability in Sensor, Cloud and Big Data systems and Applications, HPCC-DSS-SmartCity-DependSys 2021

作者： Chen, Mingkang Sun, Jingtao Aida, Kento Figueiredo, Renato J. Ku, Yun-Jung Subratie, Kensworth The Graduate University for Advanced Studies Sokendai Department of Informatics Tokyo Japan National Institute of Informatics Tokyo Japan University of Florida Electrical and Computer Engineering Florida United States

ISBN: (纸本)9781665494571

These days, sensors and cameras are being deployed on an increasingly large scale. Furthermore, the rapid development of machine learning models for computer vision now presents novel opportunities for the use of artificial intelligence (AI) and Internet of Things (IoT) combinations in various application scenarios. However, challenges remain in supporting low-latency video streaming from distributed mobile IoT devices under dynamic network environments, and overcoming video data quality degradation that results from weather 'noise', which reduces the accuracy of AI-based data analyses such as object detection. In this paper, we propose a live video stream processing system for supporting intelligent services that integrates the following features. First, to cope with dynamic networks and achieve low latency, our approach employs a peer-to-peer (P2P)-based virtual network at the edge and a multi-tiered architecture composed of IoT cameras, edge, and cloud servers. Second, we construct a flexible messaging system for video analysis built upon SINETStream, which is a messaging system that adopts a topic-based pub/sub model. Third, we implement a framework that can remove weather-related (rain, snow, and fog) noise by applying weather classification and adaptive noise removal models that improve the accuracy of video analysis from data collected outdoors. The latency, throughput, and image quality benchmark experiments conducted to validate the feasibility of our proposed system showed that the process resulted in image quality improvements of approximately 30% (on average). © 2021 IEEE.

关键词： Image quality Adaptation models Image edge detection Object detection Streaming media Throughput Internet of Things

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Cooperative Task Offloading for Internet of Vehicles in Cloud-edge Computing 23

Cooperative Task Offloading for Internet of Vehicles in Clou...

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作者： Gu, Linjie Xu, Xiaolong Qi, Lianyong Zhang, Yiwen Zhang, Xuyun Dou, Wanchun Changwang School of Honors Nanjing University of Information Science and Technology Nanjing China School of Computer and Software Nanjing University of Information Science and Technology Nanjing China School of Information Science and Engineering Qufu Normal University China School of Computer Science and Technology Anhui University Anhui China Macquarie University The Department of Computing Sydney Australia Nanjing University State Key Laboratory for Novel Software Technology Nanjing China

ISBN: (纸本)9781665494571

In order to support computing-intensive and service-sensitive Internet of Vehicles (IoV) applications, Digital Twin and edge computing are attractive solutions. Most of the existing IoV service offloading solutions only consider edge-cloud collaboration, but the cooperation between small cell eNodeB(SCeNB) nodes should not be ignored. Through reasonable cooperative computing between nodes, service delays far lower than offloading tasks to the cloud can be obtained. We generate and maintain the simulation of cooperation between SCeNB nodes by constructing a Digital twin to simulate SCeNB nodes in the small cell manager (SCM), thereby realizing user task offloading positions, sub-channel allocation and computing resource allocation. After that, we proposed an algorithm AUC-AC based on the dominant actor critic network and the auction-mechanism. In the DT of each SCeNB node, the global strategy is learned via deep reinforcement learning model. Numerical results show that our proposed experimental scheme is better than several baseline algorithms in terms of service delay. © 2021 IEEE.

关键词： Cloud computing Smart cities Computational modeling Reinforcement learning Digital twins Delays Numerical models

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Clean Code - Delivering A Lightweight Course 23

Clean Code - Delivering A Lightweight Course

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23rd international conference on Control systems and computer Science technologies, CSCS 2021

作者： Chirvase, Alexandru Ruse, Laura Muraru, Mihnea Mocanu, Mariana Ciobanu, Vlad University Politehnica of Bucharest Computer Science Department Romania

ISBN: (纸本)9781665439398

Unknowingly we surround ourselves with code. Our technological world revolves around it and its quality impacts us. 85 billion USD are lost annually worldwide because of our lack of interest in improving the way we write code. Our educational institutions currently do not address this issue proportional to its impact. This paper describes a complete technical course on code quality as a straightforward solution. Practical work, periodic examinations and reviews will be executed in compliance with modern teaching techniques, simulating a workplace environment. © 2021 IEEE.

关键词： Teaching

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On Performance of Cooperative V2X Communication with Vehicular Platoon systems 23

On Performance of Cooperative V2X Communication with Vehicul...

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作者： Zhou, Siyuan Wu, Qianqian Tan, Guoping Yang, Dengsong Ni, Baili College of Computer and Information Hohai University Nanjing China Jiangsu Intelligent Transportation and Intelligent Driving Research Institute Nanjing China Hohai University Key Laboratory of Water Big Data Technology of Ministry of Water Resources Nanjing China Jiangsu Expressway Company Limited China

ISBN: (纸本)9781665494571

With the development of intelligent traffic system, it is critical to use vehicle platooning to improve the safety and efficiency of vehicles. Vehicle-to-everything (V2X) communication technology is the key to guarantee the stability of platooning and cooperative communication technique can be leveraged to improve the communication coverage. In this paper, we first constructed an Amplify-and-forward (AF) relay communication network for vehicular platooning where the base station (BS) or the road side unit (RSU) can be selected as the relay node. Then, we carried out the performance analysis of the communication success probability by using stochastic geometry. The distribution of the locations of vehicles and RSUs is modeled by Poisson line process (PLP) and the spatial layout of BSs is modeled by a 2D Poisson point process (PPP). The BS or RSU is selected as the relay node according to their location. By deriving the association probability to BS or RSU, we derive the analytical solution of the success probability of the system. Simulation results verify our analysis and reveal the impact of the system parameters on the relay network performance. © 2021 IEEE.

关键词： Smart cities Simulation Roads Vehicle driving Stochastic processes Stability analysis Topology

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An LWE-Based Multi-Key Privacy-Preserving Distributed Deep Learning∗ 23

An LWE-Based Multi-Key Privacy-Preserving Distributed Deep L...

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作者： Antwi-Boasiako, Emmanuel Zhou, Shijie Liao, Yongjian Danso, Ebenezer Kwaku School of Information and Software Engineering University of Electronic Science and Technology of China Chengdu China Ghana Institute of Management and Public Administration Computer Science Department Accra Ghana China University for Development Studies Ghana

ISBN: (纸本)9781665494571

Privacy preservation in distributed deep learning (DDL) has received a lot of attention recently. One key approach to preserving privacy for DDL is the use of Homomorphic Encryption (HE), which allows computation on ciphertexts without decryption. Although current applications of HE provide some level of privacy to DDL, they are not post-quantum resistant and multi-key compliant. The use of same key by all participants could lead to collusion attacks and possible leakage of sensitive information from a participant's local dataset in the distributed deep learning setting. Furthermore, most of the privacy solutions provided for the DDL assume that all learning participants must be present before the start of the protocol. Hence, such solutions do not allow a new participant to benefit from the utility of the joint learning of other participants, for which it was not present. To address the above problems, we propose a new privacy preserving solution for DDL that uses an LWE-based Multi-key approach. Our proposed privacy preserving DDL solution is multi-key compliant, post-quantum resistant and has an additional property of allowing a new participant to benefit from the utility of an already trained collaborative deep learning system. We prove that our privacy-preserving distributed deep learning system is secured. We note that our proposed solution generally provides a robust privacy-preserving solution for the DDL and at the same time has great potential to reduce communication and computation costs associated with similar systems. © 2021 IEEE.

关键词： Deep learning Resistance Privacy Protocols Costs Collaboration Cryptography

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Texture Analysis for Images with Forested Areas 23

Texture Analysis for Images with Forested Areas

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23rd international conference on Control systems and computer Science technologies, CSCS 2021

作者： Concea, Andreea Nitescu, Tudor Ichim, Loretta Popescu, Dan University Politehnica of Bucharest Faculty of Automatic Control and Computer Science Bucharest Romania

ISBN: (纸本)9781665439398

The information on the structure of the forest has been of high interest for a long time, being related to the possibilities of maximizing the wood production in the conditions of ensuring ecological stability, but also of detecting and preventing illegal deforestation. The main objective of this paper is the texture analysis of forested areas from remote images, obtained by UAV. The forested area will be highlighted by separating it from the rest (background image). To achieve this goal, efficient texture features will be used such as: fractal dimension, lacunarity, LBP histogram, mean intensity and contrast. The obtained accuracy of 90.5% is a good result in the conditions of some real images. © 2021 IEEE.

关键词： Image classification

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Supercapacitor Digital Twin Management System Based on Cloud Environment 23

Supercapacitor Digital Twin Management System Based on Cloud...

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作者： Yang, Yingze Zhao, Qinxian Gao, Dianzhu Rong, Jieqi Fan, Yunsheng Li, Heng Peng, Jun School of Computer Science and Engineering Central South University Changsha410083 China School of Automation Central South University Changsha410083 China Hunan Engineering Laboratory of Rail Vehicles Braking Technology Changsha410083 China

ISBN: (纸本)9781665494571

With the continuous promotion of the green transportation concept, supercapacitors have gained popularity for their excellent charging and discharging characteristics. However, the unreasonable management of supercapacitor will lead to poor safety and reliability of the supercapacitor system. Aiming at this problem, a supercapacitor cloud management system based on the digital twin is proposed in this paper, which improves the computing power and data storage capacity through cloud computing for the whole life cycle state monitoring of supercapacitors. Firstly, the mathematical modeling of the supercapacitor system is carried out, and the state parameters during the charging and discharging of the supercapacitor are obtained in real-time at the physical layer and uploaded to the data interaction network. Secondly, in the network layer, all data related to the supercapacitor are measured and transmitted to the cloud through IoT, and a digital twin cloud model of the supercapacitor management system is established to evaluate the usage status of the supercapacitor by using the real-time data in the data interaction network. Finally, the supercapacitor charging and discharging control strategy is adjusted in real-time based on the state evaluation results at the control layer and given a visualization window visible to users. The application of the supercapacitor system in the digital twin is explored by developing a parameter estimation algorithm suitable for cloud computing. The experimental results verify the feasibility and practicality of the proposed supercapacitor cloud management system. © 2021 IEEE.

关键词： Cloud computing Smart cities Supercapacitors Real-time systems Data models Digital twins Topology

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GranDIHC-BR 2025-2035 - GC3: Plurality and Decoloniality in HCI 24

GranDIHC-BR 2025-2035 - GC3: Plurality and Decoloniality in ...

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23rd Brazilian Symposium on Human Factors in Computing systems, IHC 2024

作者： de Oliveira, Leander Cordeiro Valença, George Amaral, Marília Abrahão Almeida, Leonelo Dell Anhol Bim, Silvia Amélia Salgado, Luciana Cardoso de Castro Gasparini, Isabela da Silva, Claudia Bordin Rodrigues Paraná Curitiba Brazil Pernambuco Recife Brazil Paraná Curitiba Brazil Niterói Rio de Janeiro Brazil Santa Catarina Joinville Brazil Paraná Curitiba Brazil

ISBN: (纸本)9798400712241

Discussions about the relationship between technologies in social contexts have been present in the Brazilian Human-computer Interaction (HCI) community for years, including in the "Grand Challenges of Research in Human-computer Interaction in Brazil" from 2012-2022. The challenge presented here seeks to continue these discussions, including and expanding through Plurality, the intersections between diversity, equity, accessibility, and inclusion. This challenge also proposes a critical analysis of the methods and theories used in HCI research and productions, seeking a decolonial perspective of scientific and technological processes in our Brazilian and Latin American territorial reality, which often originated in the global north and replicated in other regions. Besides geographical positions, it also considers how body and identity can generate exclusion or inclusion. We also discuss that the decoloniality process corroborates plurality and thus influences the creation of our theories, methodologies, actions, practices, technologies, interactive computational systems, and, consequently, the people who use them. This paper is presented bilingually in English and Portuguese as a testament to its situated and universal implications. © 2024 Copyright held by the owner/author(s).

关键词： Interactive computer systems

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