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Cyber Security and Resilience (CSR), IEEE International Conference on

作者： Sumit Kumar Paul D.A. Knox Electrical and Computer Engineering University Of Ottawa Ottawa Canada School of Engineering Design and Teaching Innovation (and School of Electrical Engineering and Computer Science) University Of Ottawa Ottawa Canada

ISBN: (数字)9798350375367

ISBN: (纸本)9798350375374

Service users seek guarantees that their private data shared with service providers is handled securely and used only for intended purposes. Additionally, they may want assurances that their data will not be shared with other parties and deleted after a time. However, they have no control over the remote environments where the service provider stores and processes their data. While related privacy legislation exists, service providers do not always comply with such policies. Therefore, copies of private data can be retained and used later for malicious purposes or shared unethically. To solve these problems, a framework is proposed leveraging the trusted execution environment, which is protected against rollback and other attacks without involving additional parties, trust assumptions, or resources. Some freely available blockchain byproducts are used in a simple yet novel way to achieve that. Performance metrics of the framework's implementation show its suitability for dealing with real-life scenarios.

关键词： Measurement Privacy Data privacy Costs Process control Legislation Blockchains

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Critical Tools for Machine Learning: Working with Intersectional Critical Concepts in Machine Learning systems design 22

Critical Tools for Machine Learning: Working with Intersecti...

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5th ACM Conference on Fairness, Accountability, and Transparency, FAccT 2022

作者： Klumbyte, Goda Draude, Claude Taylor, Alex S. Faculty of Electrical Engineering and Computer Science University of Kassel Germany Centre for Human-Computer Interaction Design City University of London United Kingdom

ISBN: (纸本)9781450393522

This paper investigates how intersectional critical theoretical concepts from social sciences and humanities research can be worked with in machine learning systems design. It does so by presenting a case study of a series of speculative design workshops, conducted in 2021. These workshops drew on intersectional feminist methodologies to construct interdisciplinary interventions in the design of machine learning systems, towards more inclusive, accountable, and contextualized systems design. The concepts of "situating/situated knowledges", "figuration", "diffraction", and "critical fabulation/speculation"were taken up as theoretical and methodological tools for concept-led design workshops. This paper presents the design framework of the workshops and highlights tensions and possibilities with regards to interdisciplinary machine learning systems design towards more inclusive, contextualized, and accountable systems. It discusses the role that critical theoretical concepts can play in a design process and shows how such concepts can work as methodological tools that nonetheless require an open-ended experimental space to function. It presents insights and discussion points regarding what it means to work with critical intersectional knowledge that is inextricably connected to its historical and socio-political roots, and how this reframes what it might mean to design fair and accountable systems. © 2022 Owner/Author.

关键词： systems analysis

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A Study of Two Types of Introductory Exercise Problems for Network Programming Learning with Python 23

A Study of Two Types of Introductory Exercise Problems for N...

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11th International Conference on computer and Communications Management, ICCCM 2023

作者： Lu, Xiqin Funabiki, Nobuo Ueda, Kiyoshi Kao, Wen-Chung Department of Information and Communication Systems Distributed System Design Lab. Okayama University Okayama Japan Department of Computer Science Control Software Lab. Nihon University Koriyama Japan Department of Electrical Engineering National Taiwan Normal University Taipei Taiwan

ISBN: (纸本)9798400707735

Network programming is the act of writing computer codes for communications between programs or processes in different computers across networks. It is crucial for applications and services using networks, including e-commerce, gaming, and social media. However, university courses of educating it are very limited. As a result, it has become important to develop and offer IT tools to support self-studies of network programming by novices. In this paper, we present a study of two types of introductory exercise problems, namely, Grammar-concept Understanding Problem (GUP) and Comment Insertion Problem (CIP), for self-studies of five basic network protocols of TCP/IP, ARP, SMTP, POP3, and SSH with Python. A GUP instance requests to answer the keyword such as a library function in the given source code that corresponds to the grammar concept described in the question. A CIP instance requests to insert the comment at each blank of the code. String matching is adopted to mark any answer at the browser-based answer interface. Through solving them, it is expected to understand the meaning of important words and the code structure for network programming. As preliminary evaluations, we generated six GUP and CIP instances respectively, and assigned them to 10 students in Okayama University, Japan. The results confirmed that the proposal is proper for novices to learn network programming with Python. © 2023 ACM.

关键词： Python

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Hybrid Blockchain and IoT Driven Framework for Supply Chain Optimization by Enhancing Transparency, Efficiency and Cost Reduction 3

Hybrid Blockchain and IoT Driven Framework for Supply Chain ...

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3rd International Conference on Electronics and Renewable systems, ICEARS 2025

作者： Pradeep Kumar, S. Basha, C.H. Hussaian Prasath, C. Arun Amirthayogam, G. Lathif, Syed Ismail Abdul Leelavathi, R. Rajalakshmi Engineering College Computer Science Design Department Thandalam Chennai602105 India Sr University Department of Electrical and Electronics Engineering Warangal506371 India Mahendra Engineering College Department of Ece Namakkal637503 India Vel Tech Rangarajan Dr. Sagunthala R&d Institute of Science and Technology School of Computing Department of Computer Science and Engineering Chennai600062 India Srm Institute of Science and Technology Department of Data Science and Business Systems Chennai603203 India Velalar College of Engineering and Technology Department of Biomedical Engineering Erode638012 India

ISBN: (纸本)9798331509675

Blockchain technology represents a modern supply chain management revolution which fixes operational challenges while providing enhanced transparency at reduced costs. The research develops HB-SCOF (Hybrid Blockchain-Enabled Supply Chain Optimization Framework) which combines blockchain self-verification databases with automatic smart contracts to maintain continuous supply chain observation and evaluate data credibility. The framework integrates tamper-proof transaction tracking mechanisms with unified supply chain network connectivity for securing data transmission as a trust delivery method through unbreakable shared databases. The retail-industry case study demonstrated a 25% decrease in expenses stemming from agency elimination alongside enhanced flow management and better stock distribution. The system demonstrates its effectiveness through assessments of key performance indicators including transaction speed and data accuracy together with business cost efficiency. This part looks at implementation methods through training stakeholders in addition to transforming organizational policies which produce successful outcomes. Blockchain technology labs verify its capability to enhance supply chain management efficiency while showing realistic deployment methods. © 2025 IEEE.

关键词： Smart contract

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Self-aligned dual-beam superresolution laser direct writing with a polarization-engineered depletion beam

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Photonics Research 2024年第6期12卷 1194-1200页

作者： GUOLIANG CHEN DEWEI MO JIAN CHEN QIWEN ZHAN School of Optical-Electrical and Computer Engineering University of Shanghai for Science and TechnologyShanghai 200093China Shanghai Key Laboratory of Modern Optical System University of Shanghai for Science and TechnologyShanghai 200093China Zhangjiang Laboratory Shanghai 201204China

A fiber-based,self-aligned dual-beam laser direct writing system with a polarization-engineered depletion beam is designed,constructed,and *** system employs a vortex fiber to generate a donut-shaped,cylindrically polarized depletion beam while simultaneously allowing the fundamental mode excitation beam to pass *** results in a co-axially self-aligned dual-beam source,enhancing stability and mitigating assembly *** size of the central dark spot of the focused cylindrical vector depletion beam can be easily adjusted using a simple polarization rotation *** a depletion wavelength of 532 nm and an excitation wavelength of800 nm,the dual-beam laser direct writing system has demonstrated a single linewidth of 63 nm and a minimum line spacing of 173 *** optimization of this system may pave the way for practical superresolution photolithography that surpasses the diffraction limit.

关键词： polarization beam depletion

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Prediction Analysis of Greeting Gestures based on Data Augmentation and LSTM

Prediction Analysis of Greeting Gestures based on Data Augme...

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International Conference on Machine Learning and Cybernetics (ICMLC)

作者： Angga Wahyu Wibow Eri Sato-Shimokawara Kurnianingsih Department of Computer Science Graduate School of System Design Tokyo Metropolitan University Tokyo Japan Department of Electrical Engineering Politeknik Negeri Semarang Semarang Indonesia

ISBN: (数字)9798331528041

ISBN: (纸本)9798331528058

The field of Human Activity Recognition (HAR) is growing significantly in several areas but little research focuses on cultural behavior. How machine learning can explain human activity as a promotional tool in understanding cultural differences in a region is very challenging. Studies using Recurrent Neural Network (RNN), especially Long Short-Term Memory (LSTM), require large data when used to research human activity recognition. Using small data is a challenge when using LSTM. This study aims to determine which data augmentation is most appropriate when used using LSTM to predict Japanese greeting gestures, namely eshaku, keirei, saikeirei, waving hands, and Indonesian greeting gestures, namely the movement of bringing both hands together in front of the chest with a slight bow of the head. This study proposes to compare several data augmentations, namely jittering, scaling, permutation, cropping, reverse, time shifting, frequency domain, and synthetic data generation. We evaluate model performance using the Mean Squared Error (MSE), Root Mean Squared Error (RMSE), Mean Absolute Error (MAE), and coefficient of determination (R 2 ) metrics. The experimental results show that Time Shifting has the best MSE, RMSE, and MAE values compared to others and Frequency Domain has the best R 2 values compared to others. This study concludes that Time Shifting and Frequency Domain are the best data augmentation methods when using LSTM in predicting greeting gestures using small data. These findings provide valuable insights into the effectiveness of various data augmentation methods in motion prediction tasks with limited data sets, as well as the importance of selecting appropriate data augmentation methods in human motion analysis. Future work could use data from two or more people using model explanations generated by machine learning and developing a new method for cultural behavior.

关键词： Hands Recurrent neural networks Frequency-domain analysis Machine learning Data augmentation Human activity recognition Cultural differences Motion analysis Long short term memory Synthetic data

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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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2024 IEEE Global Communications Conference, GLOBECOM 2024

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

ISBN: (纸本)9798350351255

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. © 2024 IEEE.

关键词： Costs

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Enhancing Usability with Virtual Imagery: Insights into Feedback Mechanism from a BCI-VR Integrated system 10

Enhancing Usability with Virtual Imagery: Insights into Feed...

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10th International Conference on Virtual Reality, ICVR 2024

作者： Lu, Annan Huang, Mengjie Tang, Luyao Yang, Rui Xi'an Jiaotong-Liverpool University School of Advanced Technology Suzhou China University of Liverpool School of Electrical Engineering and Computer Science Liverpool United Kingdom Xi'an Jiaotong-Liverpool University Design School Suzhou China

ISBN: (纸本)9798350364231

The integration of brain-computer interface (BCI) and virtual reality (VR) technologies has fostered innovative applications in medical rehabilitation, education, and entertainment. One prominent application is the motor imagery (MI)-based BCI-VR system, which allows users to control the system through imagined movements without physical motion. Despite these advancements, the usability of a such system remains a significant challenge, primarily due to limited user feedback mechanisms. This study addresses this gap by designing and evaluating four haptic feedback modes to enhance user interaction in MI-based BCI-VR systems. Specifically, the research introduces a novel approach by integrating pseudo-haptic feedback - the illusion of touch created through visual and auditory stimuli - alongside traditional physical feedback. Using a within-subjects experimental design, the study assesses the impact of different combinations of physical and pseudo-haptic feedback on haptic perception, user workload, and satisfaction. The results indicate that the combination of both pseudo-haptic and physical feedback significantly enhances user satisfaction (M=2.25, SD=0.46) and perceived vibration level (M=9.25, SD=1.03), although it also increases the workload. These findings suggest that carefully balanced haptic feedback can improve the usability and overall user experience of MI-based BCI-VR systems, providing practical insights for system optimization. © 2024 IEEE.

关键词： Brain computer interface

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EEG based stress classification by using difference plots of variational modes and machine learning

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Journal of Ambient Intelligence and Humanized Computing 2023年第12期14卷 16347-16360页

作者： Salankar, Nilima Qaisar, Saeed Mian School of Computer Science University of Petroleum and Energy Studies Dehradun India Persistent System Limited IT Park Maharashtra Nagpur India Department of Electrical and Computer Engineering EFfat University Jeddah22332 Saudi Arabia Communication and Signal Processing Lab Energy and Technology Research Center Effat University Jeddah22332 Saudi Arabia

The recent trend in healthcare is to use the automated biomedical signals processing for an augmented and precise diagnosis. In this context, an original approach is presented for categorization of stress and non-stress classes by processing the multichannel Electroencephalogram (EEG) signals. The EEG signals are decomposed by using the "Empirical Mode Decomposition" (EMD) and "Variational Mode Decomposition" (VMD), respectively render the "Intrinsic Mode Functions" (IMFs) and Modes. The Second Order Difference Plots (SODPs) are traced for each IMF and Mode. Shapes of SODPs are used to discriminate the two intended categories. The feature space includes areas, Central Tendency Measures (CTMs) and means of SODPs. It is derived from first 7 IMFs and Modes. The identification of stress and non-stress categories is performed by using the robust machine learning algorithms namely, the Support Vector Machine (SVM), Boosting with Random Forest (RF) and Multilayer Perceptron Neural Network (MLPNN). The applicability is tested by using a publicly available EEG signals dataset, recorded during mental arithmetic test. A detailed evaluation is carried out at the subset, individual channel and lobes wise. Noteworthy highest accuracies of subset wise 99.89%, channel wise 98.89% and lobe wise 99.99% are obtained respectively. © 2022, The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.

关键词： Empirical mode decomposition

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Novel MEMS-IMU/Wi-Fi integrated indoor pedestrian location algorithm

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Harbin Gongcheng Daxue Xuebao/Journal of Harbin engineering University 2025年第3期46卷 609-617页

作者： Zhu, Minghong Yu, Fei Jin, Ming Liu, Juan Wang, Zhenpeng Faculty of Electrical Engineering and Computer Science Ningbo University Ningbo315211 China College of Mathematical Sciences Harbin Engineering University Harbin150001 China System Engineering Institute of Sichuan Aerospace Chengdu610100 China

A novel integration strategy for accurately estimating pedestrian location has been developed by combining microelectromechanical systems-inertial measurement units (MEMS-IMUs) and Wi-Fi data. This approach enables the effective use of MEMS-IMU devices in smartphones. The research work included: establishing a position estimation model relative to the reference coordinate system based on the pedestrian dead reckoning algorithm;directly using the output of the gyroscope in the IMU as the original observation value, and adopting the Wi-Fi position data at a fixed frequency for system correction, then designing the extended Kalman filter algorithm to estimate the real-time position coordinates of pedestrians;creating the motion trajectory of pedestrians and verifying the effectiveness and feasibility of the algorithm by collecting the data of mobile phone sensors and wireless signal access point. The results show that when using integrated MEMS-IMU and Wi-Fi positioning, the position error becomes significantly smaller than that of IMU-only positioning. The findings also indicate that Wi-Fi information can assist MEMS inertial sensors to more accurately complete indoor pedestrian navigation and positioning tasks. © 2025 Editorial Board of Journal of Harbin engineering. All rights reserved.

关键词： Extended Kalman filters

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