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IEEE International Requirements engineering Conference Workshops (REW)

作者： Itzhak Aviv Davor Svetinovic Seok-Won Lee Department of Information Systems The Academic College of Tel Aviv-Yaffo Tel-Aviv Israel Khalifa University Abu Dhabi UAE Vienna University of Economics and Business Vienna Austria Department of Software and Computer Engineering Ajou University South Korea

ISBN: (数字)9798350395518

ISBN: (纸本)9798350395525

The 1st International Workshop on Requirement engineering for Web3 systems (RE4Web3), held at the 32nd IEEE RE Conference 2024, fills in the space between traditional Requirements engineering (RE) and particular challenges posed by Web3 technologies. The workshop discussed changing RE artifacts, processes, and practices to efficiently build and operate emerging Web3 systems. The accepted papers showcase the diversity and depth of research in this emerging field, addressing key topics such as smart contract compatibility with Central Bank Digital Currencies, RE challenges in rollup construction, privacy and security in blockchain-based federated learning, and infrastructure requirements for blockchain-native information systems. The new findings described in these industry-focused papers add to the formation of the discipline and lay the cornerstone for future research and practice in RE integration with Web3 technologies.

关键词： Privacy Online banking Federated learning Conferences Smart contracts Requirements engineering Security

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Instructors' Perspectives on Capstone Courses in Computing Fields: A Mixed-Methods Study 2024

Instructors' Perspectives on Capstone Courses in Computing F...

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29th Working Group Reports on Innovation and Technology in computer Science Education, ITiCSE WGR 2024

作者： Hooshangi, Sara Shakil, Asma Dasgupta, Subhasish Davis, Karen C.C. Farghally, Mohammed Fitzpatrick, KellyAnn Gutica, Mirela Hardt, Ryan Riddle, Steve Seyam, Mohammed Department of Computer Science Virginia Tech BlacksburgVA United States School of Computer Science University of Auckland Auckland New Zealand Info Systems and Tech Mgmt Dept George Washington University WashingtonDC United States Computer Science and Software Engineering Dept. Miami University OxfordOH United States School of Computing Instruction Georgia Institute of Technology AtlantaGA United States School of Computing & Academic Studies British Columbia Institute of Technology BurnabyBC Canada Computer & Information Science University of St. Thomas Saint PaulVA United States School of Computing Newcastle University Newcastle upon Tyne United Kingdom

ISBN: (纸本)9798400712081

Team-based capstone courses are integral to many undergraduate and postgraduate degree programs in the computing field. They are designed to help students gain hands-on experience and practice professional skills such as communication, teamwork, and self-reflection as they transition into the real world. Prior research on capstone courses has focused primarily on the experiences of students. The perspectives of instructors who teach capstone courses have not been explored comprehensively. However, an instructor's experience, motivation, and expectancy can have a significant impact on the quality of a capstone course. In this working group, we used a mixed methods approach to understand the experiences of capstone instructors. Issues such as class size, industry partnerships, managing student conflicts, and factors influencing instructor motivation were examined using a quantitative survey and semi-structured interviews with capstone teaching staff from multiple institutions across different continents. Our findings show that there are more similarities than differences across various capstone course structures. Similarities include team size, team formation methodologies, duration of the capstone course, and project sourcing. Differences in capstone courses include class sizes and institutional support. Some instructors felt that capstone courses require more time and effort than regular lecture-based courses. These instructors cited that the additional time and effort is related to class size and liaising with external stakeholders, including industry partners. Some instructors felt that their contributions were not recognized enough by the leadership at their institutions. Others acknowledged institutional support and the value that the capstone brought to their department. Overall, we found that capstone instructors were highly intrinsically motivated and enjoyed teaching the capstone course. Most of them agree that the course contributes to their professional de

关键词： Students

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Model for Supporting Decisions of Investors, Taking into Consideration Multifactoriality and Turnover 2nd

Model for Supporting Decisions of Investors, Taking into Con...

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2nd International Conference on Applied Technologies, ICAT 2020

作者： Lakhno, V. Malyukov, V. Kasatkin, D. Blozva, A. Zhyrova, T. Kotenko, N. Kotova, M. Department of Computer Systems and Networks National University of Life and Environmental Sciences of Ukraine Kyiv Ukraine Department of Software Engineering and Cybersecurity Kyiv National University of Trade and Economics Kyiv Ukraine

ISBN: (纸本)9783030715021

This article describes a new analytical model for the mathematical support of decisions during the project’s evaluation process. Smart City technology development projects are considered as an example of a subject area for investment. Unlike existing solutions, the new model considers the multifactorial nature of data sets. The consecutiveness of investors’ steps in implementing their financial strategies was also taken into account. The model is focused on subsequent software implementation in intelligent cross-platform decision support systems. The proposed approach allows evaluating the attractiveness for investors (players) of the analyzed projects. Also, unlike the solutions previously proposed by the authors, the model considers situations in which players control a dynamic system in multidimensional project spaces. The results presented in the article were obtained based on the solution of a bilinear multistep quality game with several terminal sets. The scientific novelty of the work lies in the fact that, unlike existing solutions, this article considers a new class of bilinear multi-step games, which allows one to correctly and adequately describe investment processes, given the multifactorial nature of the problem statement. Thus, a solution for investors can be obtained analytically. The results of a computational experiment that were obtained using the prototype of decision support systems (DSS) module were described. © 2021, Springer Nature Switzerland AG.

关键词： Decision support systems

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Highly Sensitive Real-Time Detection of Surface Texture Changes

Highly Sensitive Real-Time Detection of Surface Texture Chan...

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International Conference on Modern Problems of Radio engineering, Telecommunications and computer Science

作者： Andrii Yarmilko Inna Rozlomii Yuliia Mysiura Department of Automated Systems Software Bohdan Khmelnytsky National University of Cherkasy Cherkasy Ukraine Department of Information Security and Computer Engineering Cherkasy State Technological University Cherkasy Ukraine Department of Information Technologies Bohdan Khmelnytsky National University of Cherkasy Cherkasy Ukraine

ISBN: (数字)9798331520564

ISBN: (纸本)9798331520571

Real-time surface analysis is becoming increasingly important in various fields, including industry, medicine, and transportation. This article examines the problem of remote monitoring of surface texture in real time. The authors review the methods and techniques used for this task, focusing on high-precision technologies such as computer vision, laser scanning, and image processing techniques. The paper examines the importance of this real-time approach to support accurate and rapid decisions in industrial processes and medical diagnostics. The authors propose a method for detecting texture artifacts with machine learning and analyze the performance and quality of possible variations of its application. Based on the discussion, the authors draw conclusions regarding the effectiveness and prospects of the proposed approach in real-time remote monitoring of surface textures. They emphasize the importance of further research in this direction and the use of innovative technologies to improve the accuracy and speed of the monitoring process. This article will be a valuable source of information for scientists, engineers and professionals in the field of industrial control and automation.

关键词： Industries computer vision Sensitivity Accuracy Clustering algorithms Machine learning Real-time systems Surface texture Surface treatment Remote monitoring

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The zero-tax data center: a use case through quantum resilient communications

The zero-tax data center: a use case through quantum resilie...

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International Conference on Transparent Optical Networks

作者： Daniel Lawo Michal Podleś Raphael Frantz Abraham Cano Aguilera Dismothenis Iliadis-Apostolidis Jeronimo Sanchez Sokol Kosta Idelfonso Tafur Monroy José Luis Imaña J.J. Vegas Olmos Department of Electrical Engineering Eindhoven University of Technology Eindhoven The Netherlands Department of Electronic Systems Aalborg University Copenhagen Denmark Department of Computer Architecture and Automation Complutense University of Madrid Spain Software Architecture NVIDIA Corporation Ofer Industrial Park Yokneam Israel

ISBN: (数字)9798350377323

ISBN: (纸本)9798350377330

Data centers, cloud and edge computing platforms are absorbing heavy AI-based workloads. This raises two concerns: how to reduce the networking overhead by host processors in order to focus only on AI-processing, and how to provide quantum resilient level protection for any connection running such workloads. In this paper, we will show case the concept of zero-tax data center, which is achieved through offloading of networking functions from the host to the network. In particular, the implementation of postquantum cryptography algorithms providing quantum resilient links and how the processing its complex processing is moved from host to network through the utilization of data-processing units.

关键词： Data centers Cloud computing Quantum computing Program processors Optical fiber networks Cryptography Network interfaces

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Concealing Sensitive Samples against Gradient Leakage in Federated Learning

arXiv

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arXiv 2022年

作者： Wu, Jing Hayat, Munawar Zhou, Mingyi Harandi, Mehrtash Department of Electrical and Computer Systems Engineering Monash University Australia Department of Data Science and AI Monash University Australia Department of Software Systems and Cybersecurity Monash University Australia

Federated Learning (FL) is a distributed learning paradigm that enhances users’ privacy by eliminating the need for clients to share raw, private data with the server. Despite the success, recent studies expose the vulnerability of FL to model inversion attacks, where adversaries reconstruct users’ private data via eavesdropping on the shared gradient information. We hypothesize that a key factor in the success of such attacks is the low entanglement among gradients per data within the batch during stochastic optimization. This creates a vulnerability that an adversary can exploit to reconstruct the sensitive data. Building upon this insight, we present a simple, yet effective defense strategy that obfuscates the gradients of the sensitive data with concealed samples. To achieve this, we propose synthesizing concealed samples to mimic the sensitive data at the gradient level while ensuring their visual dissimilarity from the actual sensitive data. Compared to the previous art, our empirical evaluations suggest that the proposed technique provides the strongest protection while simultaneously maintaining the FL performance. Code is located at https://***/JingWu321/DCS-2. Copyright © 2022, The Authors. All rights reserved.

关键词： Sensitive data

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Security and Efficiency Models for Cyber-Physical systems in Medical Devices

Security and Efficiency Models for Cyber-Physical Systems in...

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International computer Sciences and Information Technologies (CSIT)

作者： Inna Rozlomii Andrii Yarmilko Serhii Naumenko Department of Information security and computer engineering Cherkasy State Technological University Cherkasy Ukraine Department of Automated Systems Software Bohdan Khmelnytsky National University of Cherkasy Cherkasy Ukraine Department of Information Technologies Bohdan Khmelnytsky National University of Cherkasy Cherkasy Ukraine

ISBN: (数字)9798331542634

ISBN: (纸本)9798331542641

The article explores security and efficiency models applied in cyber-physical systems of medical devices, which are increasingly integrated into the IoT framework. It provides a detailed analysis of key threats to the confidentiality, integrity, and availability of data generated and processed by such devices, considering them as critical components of patient safety. Additionally, the article examines approaches to enhancing the efficiency of medical cyber- physical systems under constraints of limited energy consumption, low computational power, and restricted memory capacity. Solutions are proposed based on the implementation of lightweight cryptographic algorithms, such as lightweight block ciphers and digital signature algorithms, which help reduce energy consumption while ensuring a high level of security. The proposed models aim to ensure the secure processing and transmission of personal medical data, particularly in scenarios of limited network bandwidth and the need to minimize transmission delays. Moreover, the article discusses aspects of the real-time efficient operation of cyber- physical systems, which is critical for the uninterrupted and reliable functioning of medical devices. The article also includes a comparative analysis of existing protection methods and suggests new approaches to improving the overall reliability and efficiency of medical cyber-physical systems.

关键词： Energy consumption Analytical models Medical devices Computational modeling Memory management Cyber-physical systems Real-time systems Encryption Reliability Protection

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Development of a web system for recognizing the images taken by UAV

Development of a web system for recognizing the images taken...

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IEEE International Conference on Dependable systems, Services and Technologies (DESSERT)

作者： Oleh Kriuchenkov Olga Morozova Vyacheslav Kharchenko Artem Tetskyi Kamila Storchak Department of computer systems networks and cybersecurity National aerospace university “KhAI” Kharkiv Ukraine Department of Software Engineering of Automated Systems State University of Telecommunications Kyiv Ukraine

ISBN: (纸本)9798350333053

The paper focuses on development of a web system for recognizing the images taken by UAV. According to the concept, the development for such system includes three main steps: development of machine learning model, web system development and deployment. First step was taken from open-source ML model “EfficientNetB0”. Web system developed using the Python library “Streamlit”. For the last step deployment service “Heroku” was chosen. Basic requirements for the functionality, architecture and user interface of the web system developed in this project were formed.

关键词： Image recognition computer architecture User interfaces Streaming media Libraries Service-oriented architecture software tools

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Visualizing Student Attention in Smart Classrooms: A Preliminary Study

Visualizing Student Attention in Smart Classrooms: A Prelimi...

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International Conference on Innovations in Information Technology

作者： Medha Mohan Ambali Parambil Amna Mohammed Abdulla Alhammadi Fady Alnajjar Zouheir Trabelsi Luqman Ali Muhammed Swavaf Department of Information Systems and Security College of IT United Arab Emirate University Al Ain UAE Department of Computer Science and Software Engineering College of IT United Arab Emirate University Al Ain UAE

In recent years, there has been a swift progression in employing novel methods in classrooms to enhance students’ academic achievements, especially in line with the growing digitization of education. Such methods often encompass systems like facial recognition to monitor various aspects of students, including attendance, emotional states, and attention. These tools are capable of evaluating students’ presence and engagement in class, offering quantifiable metrics regarding their concentration and emotions. However, a prominent challenge has been the translation of this data into an accessible form that enables educators to assess and enhance their teaching techniques swiftly. Our suggested solution tackles this issue by offering a real-time visual depiction of students’ classroom status through different visualization techniques. These visual aids allow teachers to promptly recognize trends in student focus, thus aiding in the strategic alteration of teaching styles. Furthermore, these visual representations can be tailored to display various metrics and applied to tasks beyond monitoring attention, like overseeing attendance or assessing student progress. By integrating these advanced visualizations into the educational process, both teaching efficacy and the learning experience for students and teachers alike can be substantially elevated.

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AircraftVerse: a large-scale multimodal dataset of aerial vehicle designs 23

AircraftVerse: a large-scale multimodal dataset of aerial ve...

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Proceedings of the 37th International Conference on Neural Information Processing systems

作者： Adam D. Cobb Anirban Roy Daniel Elenius F. Michael Heim Brian Swenson Sydney Whittington James D. Walker Theodore Bapty Joseph Hite Karthik Ramani Christopher McComb Susmit Jha Computer Science Laboratory SRI International Mechanical Engineering Division Southwest Research Institute Intelligent Systems Division Southwest Research Institute Institute of Software Integrated Systems Vanderbilt University School of Mechanical Engineering Purdue University Department of Mechanical Engineering Carnegie Mellon University

We present AircraftVerse, a publicly available aerial vehicle design dataset. Aircraft design encompasses different physics domains and, hence, multiple modalities of representation. The evaluation of these cyber-physical system (CPS) designs requires the use of scientific analytical and simulation models ranging from computer- aided design tools for structural and manufacturing analysis, computational fluid dynamics tools for drag and lift computation, battery models for energy estimation, and simulation models for flight control and dynamics. AircraftVerse contains 27,714 diverse air vehicle designs - the largest corpus of engineering designs with this level of complexity. Each design comprises the following artifacts: a symbolic design tree describing topology, propulsion subsystem, battery subsystem, and other design details; a STandard for the Exchange of Product (STEP) model data; a 3D CAD design using a stereolithography (STL) file format; a 3D point cloud for the shape of the design; and evaluation results from high fidelity state-of-the-art physics models that characterize performance metrics such as maximum flight distance and hover-time. We also present baseline surrogate models that use different modalities of design representation to predict design performance metrics, which we provide as part of our dataset release. Finally, we discuss the potential impact of this dataset on the use of learning in aircraft design and, more generally, in CPS. AircraftVerse is accompanied by a data card, and it is released under Creative Commons Attribution-ShareAlike (CC BY-SA) license. The dataset is hosted at https://***/record/6525446 baseline models and code at https://***/SRI-CSL/AircraftVerse and the dataset description at https://***/.

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