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11th IEEE International Conference on Computational Cybernetics and Cyber-Medical systems, ICCC 2024

作者： Nagy, Balint Molnar, Gyorgy Joos, Antal Nagy, Eniko Institute of Computer Engineering University of Dunaújváros Department of Mathematics Dunaújváros Hungary Budapest Business University Faculty of Finance and Accountancy Department of Applied Quantitative Methods Budapest Hungary Institute of Electrophysics Óbuda University Kandó Kálmán Faculty of Electrical Engineering Department of Natural Sciences Budapest Hungary Óbuda University Kandó Kálmán Faculty of Electrical Engineering Budapest Hungary Széchenyi University János Csere Apáczai Faculty Győr Hungary Antal Bejczy Center for Intelligent Robotics Institute of Cyberphysical Systems Óbuda University John von Neumann Faculty Budapest Hungary

ISBN: (纸本)9798350350142

Investigating chaotic systems is a fertile field considering that chaos is an exotic chapter in the theory of differential equations, and it has useful applications in the theory of communications. In this work a well-known chaotic system is investigated from the bifurcation point of view and some applications are also introduced. The data studied are also visualized for better clarity. The results observed can be helpful in the encryption methods of the implementation of different communication channels. © 2024 IEEE.

关键词： Chaotic systems

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Density-aware Domain Generalization for LiDAR Semantic Segmentation

Density-aware Domain Generalization for LiDAR Semantic Segme...

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IEEE/RSJ International Conference on Intelligent Robots and systems (IROS)

作者： Jaeyeul Kim Jungwan Woo Ukcheol Shin Jean Oh Sunghoon Im Department of Electrical Engineering and Computer Science DGIST Daegu Republic of Korea Robotics Institute Carnegie Mellon University Pittsburgh Pennsylvania United States

ISBN: (数字)9798350377705

ISBN: (纸本)9798350377712

3D LiDAR-based perception has made remarkable advancements, leading to the widespread adoption of LiDAR in autonomous driving systems. Despite these technological strides, variations in LiDAR sensors and environmental conditions can significantly deteriorate the performance of perception models, primarily due to changes in the density of point clouds. Recent studies in domain generalization have aimed to mitigate this challenge; however, they often rely on the availability of sequential data and ego-motion, which limits their applicability. To address these limitations, we propose two novel methods that enable network operation in a density-aware fashion without any constraints, thereby ensuring consistent performance despite fluctuations in point cloud density. First, we design the network to be density-aware by utilizing the kernel occupancy information from the 3D sparse convolution as geometric features. Subsequently, we further enhance density awareness by incorporating voxel-wise density prediction as an auxiliary task in a self-supervised manner. Our method demonstrates superior performance over current state-of-the-art approaches, achieving this without the need for specific data prerequisites. Our approach is compatible with a variety of 3D backbone architectures, enhancing domain generalization performance by 18.4% while adding a minimal computational overhead of only 7ms.

关键词： Point cloud compression Three-dimensional displays Laser radar Fluctuations Convolution Semantic segmentation Robustness Sensors Kernel Intelligent robots

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Translating Natural Language Specifications into Access Control Policies by Leveraging Large Language Models 6

Translating Natural Language Specifications into Access Cont...

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6th IEEE International Conference on Trust, Privacy and Security in Intelligent systems, and Applications, TPS-ISA 2024

作者： Lawal, Sherifdeen Zhao, Xingmeng Rios, Anthony Krishnan, Ram Ferraiolo, David San AntonioTX United States University of Texas Department of Information Systems and Cyber Security San AntonioTX United States Department of Electrical & Computer Engineering San AntonioTX United States National Institute of Standards and Technology GaithersburgMD United States

ISBN: (纸本)9798350386745

This paper investigates the application of large language models (LLMs) for the automated translation and information extraction of access control policies from a natural language source. Prior research in this domain have predominantly relied on manual methods, traditional natural language processing (NLP), or a hybrid approach involving machine learning and artificial neural networks combined with NLP techniques. We demonstrate a significant advancement by leveraging the power of LLMs to achieve improved efficiency and accuracy in these tasks. Our study focuses on applying cutting-edge prompt engineering techniques designed to optimize LLM performance in the specific context of access control policy information extraction. The findings highlight the potential of LLMs to streamline the process of converting human-readable requirements into formal, machine-interpretable policies, ultimately contributing to the automation and security of access control systems. © 2024 IEEE.

关键词： Natural language processing systems

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Thermally robust compact single Bragg grating silicon modulator for photonic computing

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Applied Optics 2025年第16期64卷 4646-4653页

作者： Meng Zhang Nicholas Gangi Amir Begović Alexer Chen Bowen Liu Z Rena Huang Department of Electrical Computer and Systems Engineering Rensselaer Polytechnic Institute Troy New York 12180 USA Department of Physics Applied Physics and Astronomy Rensselaer Polytechnic Institute Troy New York 12180 USA

We report, to our knowledge, a novel compact, thermally operated optical modulator with 6-bit resolution. The device comprises a slow-light photonic structure, a Bragg grating with a footprint of $10\,\,{\unicode{x00B5}{\rm m}}$ by $50\,\,{\unicode{x00B5}{\rm m}}$ . This single Bragg-grating modulator (SBG-M) operates based on thermally induced band edge shift of the photonic stop band and demonstrates almost constant normalized mean square error (NMSE) lower than 0.001 from room temperature to ${40^\circ}{\rm C}$ , while maintaining thermal robustness up to ${65^\circ}{\rm C}$ limited by the Johnson noise of the on-chip photodetector. The clock frequency, computing accuracy, power consumption, thermal stability, and fabrication-induced spectrum non-ideality are thoroughly studied. The SBG-M achieves a measured lowest NMSE of $5.0 \times {10^{- 4}}$ , with an average power consumption of 5.29 mW. Compared to other optical devices such as micro-ring resonators and slow-light incorporated Mach–Zehnder modulators, the reported device demonstrates significant advantages in compactness, lower power consumption, and thermal robustness.

关键词： Optical computing Optical modulators Phase shift Quantum computation Silicon modulators Silicon photonics

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Privacy-preserving Biometric-driven Data for Student Identity Management: Challenges and Approaches 21

Privacy-preserving Biometric-driven Data for Student Identit...

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29th ACM Conference on User Modeling, Adaptation and Personalization, UMAP 2021

作者： Fidas, Christos Belk, Marios Portugal, David Pitsillides, Andreas University of Patras Department of Electrical and Computer Engineering Greece Cognitive Ux GmbH Germany University of Coimbra Institute of Systems and Robotics Portugal University of Cyprus Department of Computer Science Cyprus

ISBN: (纸本)9781450383677

Biometric technologies are being considered lately for student identity management in Higher Education Institutions, as they provide several advantages over the traditional knowledge-based and token-based authentication methods, i.e., biometrics provide high security entropies, convenience and a sense of technological modernity to the end-users. While biometric technologies have many benefits from both a security and usability point of view, still there is a need for innovative user identity management solutions that continuously identify and authenticate students during academic and teaching activities. In addition, biometrics entail several threats and weaknesses with regards to the privacy of data stored about the user, which negatively affect the user acceptance and the wider adoption of biometrics due to regulatory and legal issues. In this paper, we refer to our ongoing research on intelligent and continuous online student identity management for improving security and trust in European Higher Education Institutions. We further highlight based on the literature, existing challenges, threats and state-of-the-art approaches with regards to preserving the privacy of biometric-driven data. © 2021 Owner/Author.

关键词： Blockchain

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The Privacy Attitudes Questionnaire (PAQ) Turned 20: What’s Next for a Generalized Measure of Privacy Attitudes? 67th

The Privacy Attitudes Questionnaire (PAQ) Turned 20: What’s...

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67th International Annual Meeting of the Human Factors and Ergonomics Society, HFES 2023

作者： Giang, Wayne C. W. Iglar, Alyssa Chignell, Mark Samavi, Reza Nathan, Kopiha Department of Industrial and Systems Engineering University of Florida GainesvilleFL United States Department of Mechanical and Industrial Engineering University of Toronto TorontoON Canada Department of Electrical Computer and Biomedical Engineering Toronto Metropolitan University TorontoON Canada Vector Institute India Healthcare Insurance Reciprocal of Canada TorontoON Canada

Attitudes and concerns related to privacy are not homogeneous, but instead differ based on the individual and context at hand. Understanding how these attitudes and concerns vary could inform product, service, and policy design. Questionnaires, such as the Privacy Attitudes Questionnaire (PAQ), can be used to evaluate and derive implications from people’s privacy orientations in numerous domains, including healthcare, social media, and e-commerce. Our objective is to refine the PAQ to reflect areas of privacy concern in today’s landscape. The panel will serve as a forum for conversation about areas of privacy concern, guided by our panelists’ expertise and questions about demographic and user considerations for the revised PAQ, a framework-inspired understanding of privacy, and privacy in healthcare. Insights and perspectives arising from the discussion panel will be considered for subsequent revisions of the PAQ. © 2023 Human Factors and Ergonomics Society.

关键词： attitudes concerns context healthcare privacy questionnaire

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Disassembly Sequence Planning:A Survey

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IEEE/CAA Journal of Automatica Sinica 2021年第7期8卷 1308-1324页

作者： Xiwang Guo MengChu Zhou Abdullah Abusorrah Fahad Alsokhiry Khaled Sedraoui the College of Computer and Communication Engineering Liaoning Shihua UniversityFushun 113001China the Department of Electrical and Computer Engineering New Jersey Institute of TechnologyNewark NJ 07102 USA the Center of Research Excellence in Renewable Energy and Power Systems King Abdulaziz UniversityJeddah 21481Saudi Arabia the Department of Electrical and Computer Engineering Faculty of Engineeringand the Center of Research Excellence in Renewable Energy and Power SystemsKing Abdulaziz UniversityJeddah 21481Saudi Arabia

It is well-recognized that obsolete or discarded products can cause serious environmental pollution if they are poorly be *** contain reusable resource that can be recycled and used to generate desired economic ***,performing their efficient disassembly is highly important in green manufacturing and sustainable economic *** typical examples are electronic appliances and electromechanical/mechanical *** paper presents a survey on the state of the art of disassembly sequence *** can help new researchers or decision makers to search for the right solution for optimal disassembly *** reviews the disassembly theory and methods that are applied for the processing,repair,and maintenance of obsolete/discarded *** paper discusses the recent progress of disassembly sequencing planning in four major aspects:product disassembly modeling methods,mathematical programming methods,artificial intelligence methods,and uncertainty *** survey should stimulate readers to be engaged in the research,development and applications of disassembly and remanufacturing methodologies in the Industry 4.0 era.

关键词： Artificial intelligence(AI) disassembly sequence planning(DSP) intelligent optimization modeling methods multiobjective optimization single-objective optimization uncertainty.

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Optimal Control of Discrete-Time Multivariate Point Processes with Finite-Time Steady State

Optimal Control of Discrete-Time Multivariate Point Processe...

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IEEE Conference on Decision and Control

作者： A. Agung Julius Yunshi Wen Ruixuan Yan Department of Electrical Computer and Systems Engineering Rensselaer Polytechnic Institute Troy New York

Multivariate point processes (MPP) are widely used to model the occurrence of multiple interrelated events in complex systems. They are used in a variety of fields to analyze data and define models that can make predictions about future events. In this paper, we consider finite-state MPP, which are products of finite state automata (FSA) and MPP. Specifically, the events in the MPP trigger state transitions in the FSA, while the intensities of the point processes are defined as functions of the FSA state and the history of the MPP. Further, we assume that some of the event types are controllable, i.e., they are not random but can be triggered. We formulate an optimal control problem for such system, which can then be expressed as optimal control for a Markov Decision Process (MDP) with infinite states. When the system has appropriate finite-time steady state properties, we use the concept of stochastic bisimulation of MDP to reduce the MDP into a finite state one, thereby allowing us to use standard optimal control techniques to calculate the optimal policy. We demonstrate the effectiveness of our method on a simplified sleep-wake cycle model, for the problem of optimally scheduling naps to maximize the length of wakefulness intervals.

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Enhancing Mild Cognitive Impairment Detection through Efficient Magnetic Resonance Image Analysis

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computers, Materials & Continua 2024年第8期80卷 2081-2098页

作者： Atif Mehmood Zhonglong Zheng Rizwan Khan Ahmad Al Smadi Farah Shahid Shahid Iqbal Mutasem K.Alsmadi Yazeed Yasin Ghadi Syed Aziz Shah Mostafa M.Ibrahim Department of Computer Science and Technology Zhejiang Normal UniversityJinhua321002China Zhejiang Institute of Photoelectronics&Zhejiang Institute for Advanced Light Source Zhejiang Normal UniversityJinhua321004China Department of Data Science and Artificial Intelligence Zarqa UniversityZarqa13100Jordan School of Chemical and Environmental Engineering College of ChemistryChemical Engineering andMaterials ScienceSoochow UniversitySuzhou215123China Department of Management Information Systems College of Applied Studies and Community ServiceImam Abdulrahman Bin Faisal UniversityDammam32244Saudi Arabia Department of Computer Science Al Ain UniversityAbu Dhabi999041United Arab Emirates Department of Electrical Engineering Faculty of EngineeringMinia UniversityMinia61519Egypt Healthcare Technology and Innovation Theme Faculty Research Centre for Intelligent HealthcareCoventry UniversityCoventryCV48BWUK

Neuroimaging has emerged over the last few decades as a crucial tool in diagnosing Alzheimer’s disease(AD).Mild cognitive impairment(MCI)is a condition that falls between the spectrum of normal cognitive function and ***,previous studies have mainly used handcrafted features to classify MCI,AD,and normal control(NC)*** paper focuses on using gray matter(GM)scans obtained through magnetic resonance imaging(MRI)for the diagnosis of individuals with MCI,AD,and *** improve classification performance,we developed two transfer learning strategies with data augmentation(i.e.,shear range,rotation,zoom range,channel shift).The first approach is a deep Siamese network(DSN),and the second approach involves using a cross-domain strategy with customized *** performed experiments on the Alzheimer’s Disease Neuroimaging Initiative(ADNI)dataset to evaluate the performance of our proposed *** experimental results demonstrate superior performance in classifying the three binary classification tasks:NC ***,NC ***,and MCI ***,we achieved a classification accuracy of 97.68%,94.25%,and 92.18%for the three cases,*** study proposes two transfer learning strategies with data augmentation to accurately diagnose MCI,AD,and normal control individuals using GM *** findings provide promising results for future research and clinical applications in the early detection and diagnosis of AD.

关键词： Alzheimer’s disease mild cognitive impairment normal control transfer learning classification augmentation

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On the Impact of Measurements on Location Estimation Using Sensors Fusion

On the Impact of Measurements on Location Estimation Using S...

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IEEE Southeastcon

作者： Yazan A. Alqudah Hakki Erhan Sevil Department of Electrical and Computer Engineering University of West Florida (UWF) Pensacola FL USA Department of Intelligent Systems and Robotics University of West Florida (UWF) Pensacola FL USA

This paper investigates the impact of measurements availability on the accuracy of position prediction using a mobile device equipped with GPS, acceleration, and gyro sensors. The paper also discusses the effects of the sampling factor for the available data. The experiment results emphasize the importance of sampling factor in achieving robust and reliable location estimation, particularly in challenging environments where GPS signals may be intermittent or compromised. The insights gained from this study may contribute to the advancement of location estimation-based applications, fostering improved autonomous systems in real-world scenarios.

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