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IEEE Region 10 International Conference TENCON

作者： Marastika wicaksono aji bawono Diana Purwitasari Mauridhi Hery Purnomo Departement of Technology Management Sepuluh Nopember Institute of Technology Telkom University Bogor West Java Departement of Informatics Engineering Sepuluh Nopember Institute of Technology Surabaya East Java Departement of Electrical Engineering Departement of Computer Engineering Sepuluh Nopember Institute of Technology Surabaya East Java

In digital development 4.0, store brands are very important. The problem in this research is the lack of consumer trust to buy quality goods in e-commerce store accounts so that it affects consumer satisfaction. This study aims to address this question feedback from the problems of the customer, then on the other hand a questionnaire with the PLS-SEM (Partial Least Squares Structural Equation Modeling) model to determine the dimensions of the variables selected according to customer experience. To achieve this aim, both negative and positive customer comments were compiled to assess customer satisfaction, employing a comparative analysis method through Naive Bayes algorithm. The overarching goal was to achieve optimal results and extract valuable insights regarding the determinants that influenced customer satisfaction within the domain of online transactions. This research also has an impact on buyers so they can have an understanding of the factors that support trust in customer satisfaction, so that individuals do not hesitate in making purchasing decisions to shop online. The results showed that the algorithm initially recorded a modest accuracy score of 0.37. Meanwhile, after implementing hyperparameter tuning, the accuracy increased significantly to 0.62. In the aspect of Smart PLS questionnaire analysis, a standardized Normed Fit Index (NFI) of 0.707 was recorded, which was slightly below the established threshold of 0.90. The standardized root mean square residual (SRMR) was measured at 0.071, falling below the specified value of 0.08, indicating a commendable model fit. However, the RMS theta value at 0.240 exceeded the threshold of 0.102.

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Decoding the Granular Puzzle of Macromolecules: Efficient 3D Protein Structure Alignment in the Age of Big Data with Apache Spark

Decoding the Granular Puzzle of Macromolecules: Efficient 3D...

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IEEE International Conference on Big Data

作者： Bożena Małysiak-Mrozek Paulina Pawłowicz Vaidy Sunderam Che-Lun Hung Andrzej Kwiecień Dariusz Mrozek Department of Distributed Systems and Informatic Devices Silesian University of Technology Gliwice Poland Department of Applied Informatics Silesian University of Technology Gliwice Poland Department of Computer Science Emory University Atlanta GA USA Institute of Biomedical Informatics National Yang Ming Chiao Tung University Taipei City Taiwan

ISBN: (数字)9798350362480

ISBN: (纸本)9798350362497

Proteins are complex biological information granules that play a crucial role in various cellular processes within living organisms. Processing 3D protein structures, which are the most informative from the biological point of view, is both intricate and time-consuming. In particular, performing 3D protein structure searches against large protein datasets involves identifying similarities and conducting structural alignments across numerous molecules (granules). This task demands advanced methods for matching identical and similar regions within protein structures and substantial computational resources to handle large collections of macromolecular data efficiently. In this paper, we present our parallel implementation of scalable 3D structural alignment on the Apache Spark big data platform. We describe a customized approach that leverages Spark data transformations within the data processing pipeline for the alignment process. Our experimental results demonstrate that this solution, tightly integrated with the Spark processing model, is both efficient and scalable, even with the increasing volume of protein structure data.

关键词： Proteins Solid modeling Three-dimensional displays Pipelines Cluster computing Big Data Biology Organisms Decoding Sparks

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UniDSeg: unified cross-domain 3D semantic segmentation via visual foundation models prior 24

UniDSeg: unified cross-domain 3D semantic segmentation via v...

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Proceedings of the 38th International Conference on Neural Information Processing Systems

作者： Yao Wu Mingwei Xing Yachao Zhang Xiaotong Luo Yuan Xie Yanyun Qu School of Informatics Xiamen University Institute of Artificial Intelligence Xiamen University School of Computer Science and Technology East China Normal University and Chongqing Institute of East China Normal University School of Informatics Xiamen University and Institute of Artificial Intelligence Xiamen University and Key Laboratory of Multimedia Trusted Perception and Efficient Computing Ministry of Education of China Xiamen University

ISBN: (纸本)9798331314385

3D semantic segmentation using an adapting model trained from a source domain with or without accessing unlabeled target-domain data is the fundamental task in computer vision, containing domain adaptation and domain generalization. The essence of simultaneously solving cross-domain tasks is to enhance the generalizability of the encoder. In light of this, we propose a groundbreaking universal method with the help of off-the-shelf Visual Foundation Models (VFMs) to boost the adaptability and generalizability of cross-domain 3D semantic segmentation, dubbed UniDSeg. Our method explores the VFMs prior and how to harness them, aiming to inherit the recognition ability of VFMs. Specifically, this method introduces layer-wise learnable blocks to the VFMs, which hinges on alternately learning two representations during training: (i) Learning visual prompt. The 3D-to-2D transitional prior and task-shared knowledge is captured from the prompt space, and then (ii) Learning deep query. Spatial Tunability is constructed to the representation of distinct instances driven by prompts in the query space. Integrating these representations into a cross-modal learning framework, UniDSeg efficiently mitigates the domain gap between 2D and 3D modalities, achieving unified cross-domain 3D semantic segmentation. Extensive experiments demonstrate the effectiveness of our method across widely recognized tasks and datasets, all achieving superior performance over state-of-the-art methods. Remarkably, UniDSeg achieves 57.5%/54.4% mIoU on "A2D2/sKITTI" for domain adaptive/generalized tasks. Code is available at https://***/Barcaaaa/UniDSeg.

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Cultivate Smart and Healthy Ageing 9th

Cultivate Smart and Healthy Ageing

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9th EAI International Conference on IoT Technologies for HealthCare, HealthyIoT 2022

作者： Andreou, Andreas Mavromoustakis, Constandinos X. Markakis, Evangelos Mastorakis, George Batalla, Jordi Mongay Pallis, Evangelos Dobre, Ciprian Department of Computer Science University of Nicosia and University of Nicosia Research Foundation Nicosia Cyprus Department of Electrical and Computer Engineering Hellenic Mediterranean University Heraklion Crete Greece Department of Management Science and Technology Hellenic Mediterranean University Agios Nikolaos Crete Greece Warsaw University of Technology Warsaw Poland Department of Industrial Design and Production Engineering School of Engineering University of West Attica Athens Greece National Institute for Research and Development in Informatics Bucharest Romania

ISBN: (纸本)9783031286629

The essential criterion for developing an intelligent age-friendly environment is evaluating and monitoring the provision of services. Our research aims to allow the deployment of a broad range of digital healthcare solutions interconnected in an IoT network ecosystem. Through their interoperability, we will be able to cultivate age-friendly smart homes for older adults. Thus, we will enable interpreted living and wellbeing. The intelligent integrations of digital solutions will allow the acquisition and evaluation of health-related data. Standardization, interoperability and scalability of the integration will increase efficiency in healthcare, improving older adults’ Quality of Life (QoL). Also, interpreting their needs will allow key stakeholders to optimize the Quality of Service (QoS). The proposed Internet of Health (IoH) framework will encapsulate sustainable and affordable innovative solutions and their benefits for a comfortable, meaningful, and independent life in an intelligent environment. Therefore, the frame mediated by edge computing, in-home and community settings will be able to interact with healthcare networks contributing to hospitalizations and institutional care. © 2023, ICST institute for computer Sciences, Social informatics and Telecommunications Engineering.

关键词： Internet of things

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ECG-Image-Database: A Dataset of ECG Images with Real-World Imaging and Scanning Artifacts;A Foundation for computerized ECG Image Digitization and Analysis

arXiv

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arXiv 2024年

作者： Reyna, Matthew A. Deepanshi Weigle, James Koscova, Zuzana Campbell, Kiersten Shivashankara, Kshama Kodthalu Saghafi, Soheil Nikookar, Sepideh Motie-Shirazi, Mohsen Kiarashi, Yashar Seyedi, Salman Clifford, Gari D. Sameni, Reza Department of Biomedical Informatics Emory University AtlantaGA30322 United States School of Electrical and Computer Engineering Georgia Institute of Technology AtlantaGA30332 United States Department of Biomedical Engineering Georgia Institute of Technology AtlantaGA30332 United States

Objective: We introduce ECG-Image-Database, a large and diverse collection of electrocardiogram (ECG) images generated from ECG time-series data that exhibit real-world scanning, imaging, and physical artifacts. This dataset addresses the need for digitizing paper-based and non-digital ECGs for computerized analysis, providing a foundation for developing robust machine and deep learning models capable of ECG image digitization. Approach: We used ECG-Image-Kit, an open-source Python toolkit, to generate realistic images of 12-lead ECG printouts from raw ECG time-series data. We include images with realistic distortions, including noise, wrinkles, stains, and perspective shifts generated both digitally and physically. The toolkit was applied to 977 12-lead ECG records from the PTB-XL database and 1,000 from Emory Healthcare to create high-fidelity synthetic ECG images. These 1,977 unique images were subjected to both programmatic distortions using ECG-Image-Kit and to physical effects, such as soaking, staining, and mold growth, followed by scanning and photography under various lighting conditions to create real-world artifacts, producing a total of 35,595 images. Main results: The resulting dataset includes 35,595 software-labeled ECG images (generated from 1,977 unique records) from different sources (in Germany and the USA) with a wide range of imaging artifacts and distortions. The dataset provides ground truth time-series data alongside the corresponding images, offering a reference for training and evaluating machine and deep learning models for ECG digitization and classification. The images vary in quality, ranging from clear scans of clean papers to noisy photographs of degraded papers, enabling the development of more generalizable and robust digitization algorithms. Significance: ECG-Image-Database addresses a critical gap in cardiovascular research by supporting the development of machine learning models capable of classifying or converting ECG images int

关键词： Photography

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Age-of-Information and Energy Optimization in Digital Twin Edge Networks

Age-of-Information and Energy Optimization in Digital Twin E...

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IEEE Conference on Global Communications (GLOBECOM)

作者： Yongna Guo Yaru Fu Yan Zhang Tony Q. S. Quek School of Electrical Engineering and Computer Science KTH Royal Institute of Technology Stockholm Sweden School of Science and Technology Hong Kong Metropolitan University China Department of Informatics University of Oslo Oslo Norway Information Systems Technology and Design Singapore University of Technology and Design Singapore

ISBN: (数字)9798350351255

ISBN: (纸本)9798350351262

In this paper, we study the intricate realm of digital twin synchronization and deployment in multi-access edge computing (MEC) networks, with the aim of optimizing and balancing the two performance metrics Age of Information (AoI) and energy efficiency. We jointly consider the problems of edge association, power allocation, and digital twin deployment. However, the inherent randomness of the problem presents a significant challenge in identifying an optimal solution. To address this, we first analyze the feasibility conditions of the optimization problem. We then examine a specific scenario involving a static channel and propose a cyclic scheduling scheme. This enables us to derive the sum AoI in closed form. As a result, the joint optimization problem of edge association and power control is solved optimally by finding a minimum weight perfect matching. Moreover, we examine the one-shot optimization problem in the contexts of both frequent digital twin migrations and fixed digital twin deployments, and propose an efficient online algorithm to address the general optimization problem. This algorithm effectively reduces system costs by balancing frequent migrations and fixed deployments. Numerical results demonstrate the effectiveness of our proposed scheme in terms of low cost and high efficiency.

关键词： Measurement Multi-access edge computing Costs Numerical analysis Power control Information age Digital twins Synchronization Resource management Optimization

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Integrating Blockchain technology with PKI for Secure and Interoperable Communication in 5G and Beyond Vehicular Networks

Integrating Blockchain Technology with PKI for Secure and In...

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Consumer Communications and Networking Conference, CCNC IEEE

作者： Fetulhak Abdurahman Shewajo Abdelwahab Boualouache Sidi Mohammed Senouci Ines El-Korbi Bouziane Brik Kinde Anlay Fante DRIVE Lab University of Burgundy Nevers France Faculty of Electrical and Computer Engineering Jimma Institute of Technology Jimma University Jimma FSTM University of Luxembourg Luxembourg Computer Science Department College of Computing and Informatics Sharjah University Sharjah UAE

Security and privacy are crucial in V2X networks due to sensitive user information. Public Key Infrastructure (PKI) is widely used in C-ITS to ensure security and privacy. However, the practical implementation of PKI faces challenges in achieving seamless communication across diverse ITS projects worldwide. The absence of interoperability between PKI systems and unre-solved issues in existing PKI standards hinder global adoption. Despite available security standardizations using centralized PKI technology for V2X, a universally adopted PKI-based security architecture is necessary. Furthermore, the progress made in 5G V2X technology has demonstrated significant potential for revolutionizing V2X communication in the future. Enhancing the level of trust through integration of the 5G Core Network (5GC) into the PKI security mechanism can lead to more secure and efficient V2X communication. To address these challenges, we propose a blockchain-based architecture that integrates the 5GC network with the PKI infrastructure, aiming to enhance privacy and security in 5G V2X communication. Our solution is designed to be distributed and interoperable, aligned with existing ETSI ITS PKI standard. By utilizing Hyperledger Fabric (HLF) platform, a permissioned blockchain framework, we present the architecture and conduct a comprehensive security analysis to ensure compliance with security and privacy requirements of V2X communications.

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MDD-Glyphs: Immersive Insights Through Multidimensional Distribution Glyphs

arXiv

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arXiv 2024年

作者： Gall, A. Heim, A. Gröller, E. Heinzl, C. TU Wien Faculty of Informatics Austria University of Passau Faculty of Computer Science and Mathematics Germany Fraunhofer Institute for Integrated Circuits IIS Division Development Center X-ray Technology Germany

Analyzing complex and large data as generated in non-destructive testing (NDT) is a time-consuming and mentally demanding challenge. Such data is heterogeneous and integrates primary and secondary derived data from materials or material systems for spatial, spatio-temporal as well as high-dimensional data analysis. Currently, materials experts mainly rely on conventional desktop systems using standard 2D visualization techniques for this purpose. Our framework is a novel immersive visual analytics system, which supports the exploration of complex spatial structures and derived multidimensional abstract data in an augmented reality setting. It includes three novel visualization techniques: MDD-Glyphs, TimeScatter, and ChronoBins, each facilitating the interactive exploration and comparison of multidimensional distributions from multiple datasets and time steps. A qualitative evaluation conducted with materials experts and novices in a real-world case study demonstrated the benefits of the proposed visualization techniques. This evaluation also revealed that combining spatial and abstract data in an immersive environment improved their analytical capabilities and facilitated to better and faster identify patterns, anomalies, as well as changes over time. Copyright © 2024, The Authors. All rights reserved.

关键词： Augmented reality

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Benchmark for CEC 2024 Competition on Multiparty Multiobjective Optimization

arXiv

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arXiv 2024年

作者： Luo, Wenjian Xu, Peilan Yang, Shengxiang Shi, Yuhui School of Computer Science and Technology Harbin Institute of Technology Shenzhen518055 China School of Artificial Intelligence Nanjing University of Information Science and Technology Nanjing210044 China School of Computer Science and Informatics The De Montfort University LeicesterLE1 9BH United Kingdom Department of Computer Science and Engineering Southern University of Science and Technology Shenzhen518055 China

The competition focuses on Multiparty Multiobjective Optimization Problems (MPMOPs), where multiple decision makers have conflicting objectives, as seen in applications like UAV path planning. Despite their importance, MPMOPs remain understudied in comparison to conventional multiobjective optimization. The competition aims to address this gap by encouraging researchers to explore tailored modeling approaches. The test suite comprises two parts: problems with common Pareto optimal solutions and Biparty Multiobjective UAV Path Planning (BPMO-UAVPP) problems with unknown solutions. Optimization algorithms for the first part are evaluated using Multiparty Inverted Generational Distance (MPIGD), and the second part is evaluated using Multiparty Hypervolume (MPHV) metrics. The average algorithm ranking across all problems serves as a performance benchmark. © 2024, CC BY-NC-SA.

关键词： Multiobjective optimization

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Weaving Indigeneity and Culture into the Fabric of HCI Futures

Weaving Indigeneity and Culture into the Fabric of HCI Futur...

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2025 CHI Conference on Human Factors in Computing Systems, CHI EA 2025

作者： Farao, Jaydon Pillai, Ajit G. Mthoko, Hafeni Samuel, Marly Muudeni Elmimouni, Houda Lazem, Shaimaa HCI Lab. The University of Cape Town Western Cape Cape Town South Africa Affective Interactions Lab. The University of Sydney SydneyNSW Australia Independent Institute of Education Cape Town South Africa School of Simulation and Visualisation Glasgow School of Art Glasgow United Kingdom Department of Computer Science University of Manitoba WinnipegMB Canada Informatics Research Institute City of Scientific Research and Technology Applications New Borg El-Arab Alexandria Egypt

ISBN: (纸本)9798400713958

Interconnectedness and relationality have become integral to technology development and innovation, which has led to indigenous and cultural philosophies and approaches becoming important in developing effective and inclusive design practices. This workshop challenges the dominant paradigms in Human-computer Interaction (HCI) by exploring the potential of indigeneity and culture to inform design methodologies. We invite participants to reflect on how such approaches can move HCI research toward more inclusive, culturally diverse, and mutually beneficial synergies. Through constructive conflict and co-creation, we aim to illuminate the potential of indigenous and cultural approaches in HCI practice, inspiring vital shifts towards decolonial and pluralistic design. We welcome HCI researchers and practitioners and indigenous scholars and experts interested in disrupting traditional methods and embracing indigenous and cultural lenses to join this critical conversation. © 2025 Copyright held by the owner/author(s).

关键词： community connectedness futuring indigenous practices

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