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20th Annual ACM/IEEE International Conference on Human-Robot Interaction, HRI 2025

作者： Morris, Nyomi Carrine Williams, Tom Jelen, Ben Colorado School of Mines MIRRORLab GoldenCO United States Rose-Hulman Institute of Technology Department of Computer Science and Software Engineering Terre HauteIN United States

ISBN: (纸本)9798350378931

Survivors of domestic abuse face significant challenges securing recovery resources, such as housing, mental health care, and social connections. Accessing these resources requires survivors to disclose their status as survivors of domestic abuse;a process that can be traumatic and emotionally burdensome. In this work, we consider how social robots might help domestic abuse survivors to address challenges surrounding self-disclosure. To do so, we conducted a three-session co-design workshop involving 8 participants from a domestic abuse shelter. Our results provide three key contributions: (1) new insights into the benefits and barriers to self-disclosure;(2) new insights into the ways that social robots can help survivors to better achieve those benefits and overcome those barriers before, during, and after disclosure, including key design recommendations associated with each of these phases;and (3) observations into how a trauma-informed computing perspective may enable more effective design work in Human-Robot Interaction. © 2025 IEEE.

关键词： Social robots

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Digitally Controlled Misalignment-Tolerant Inductive Power Transfer System with Adaptive Hybrid Compensation for CC/CV Charging of E-Scooter

Digitally Controlled Misalignment-Tolerant Inductive Power T...

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Annual IEEE Conference on Applied Power Electronics Conference and Exposition (APEC)

作者： Niranjan Shrestha V. S. R. Varaprasad Oruganti Sheldon Williamson Department of Electrical Computer and Software Engineering Ontario Tech University Oshawa Canada

ISBN: (数字)9798331516116

ISBN: (纸本)9798331516123

This paper presents a digitally controlled Inductive power transfer (IPT) system for charging Electric scooters (E-scooters), utilising an adaptive hybrid compensation network design. This system ensures constant current (CC) and constant voltage (CV) charging, with misalignment. It leverages the advantages of double-sided inductor-capacitor-capacitor (DS-LCC) and LCC-series (LCC-S) topologies, which respectively provide CC and CV output. A Type-II digital anti-windup PI control method with a selectable compensation network is introduced, allowing both CC and CV modes to operate with zero voltage switching (ZVS) under misalignment conditions. This approach reduces system losses and enhances the stability and efficiency of the IPT system. A 270W/85-kHz IPT-based E-scooter charger was designed and simulated in the MATLAB/Simulink environment, and an experimental prototype was developed to evaluate the performance of the proposed charger as per SAE J2954 standards. Testing under three different coupling conditions perfect alignment, 5 cm misalignment, and 10 cm misalignment demonstrated that the output parameters remained constant across all conditions, confirming the effectiveness of the proposed control technique.

关键词： Couplings Adaptive systems Stability criteria Motorcycles Zero voltage switching Hybrid power systems Topology Voltage control Standards Testing

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Machine Learning Methods for Multimodal Classification of Personality Traits Using Social Media Data

Machine Learning Methods for Multimodal Classification of Pe...

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International Russian Smart Industry Conference (SmartIndustryCon)

作者： Vladislav Tsyglyaev Alena Rusak Alexander Belozubov Faculty of Software Engineering and Computer Systems ITMO University Saint-Petersburg Russia

ISBN: (数字)9798331511241

ISBN: (纸本)9798331511258

In this paper, we investigate the effectiveness of various machine learning methods for the multimodal classification of personality traits using the HEXACO model and open data from social media users. Particular attention is paid to the analysis of data obtained from user profiles, including statistical, visual, and audio characteristics. For each personality trait from the HEXACO model, a machine learning model is trained that determines the manifestation degree of this trait (low, medium, high). The influence of different types of information, both individually and in combination, on the weighted F1-score is considered. The study provides a comparative analysis of traditional machine learning methods that use all features and approaches with the selection of the most significant features. A strategy for combining data from different modalities using early merger is evaluated. The experimental results demonstrate that early merger models using selected features from different modalities provide the best result of the weighted F1-score, which varies depending on the personality trait from 0.76 to 0.85.

关键词： Support vector machines Industries Visualization Social networking (online) Corporate acquisitions Machine learning Feature extraction Vectors Data models Open data

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Integrating Modern Portfolio Theory into Information Security Control Selection Optimisation

Integrating Modern Portfolio Theory into Information Securit...

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IT Innovation and Knowledge Discovery (ITIKD), International Conference on

作者： Muhammad Zaid Abrahams Josef J Langerman Academy of Computer Science and Software Engineering University of Johannesburg Johannesburg South Africa

ISBN: (数字)9798350355468

ISBN: (纸本)9798350355475

Risk management and optimised security control selection in information technology, particularly information security, is crucial for identifying and mitigating organisational threats. Information security control selection and planning are challenging due to limited resources such as funding, time and staffing. This research article is an academic exposition in which a quantitative method of evaluating cyber security risk and utilizing principles of Modern Portfolio Theory (MPT) to optimize the allocation of resources and funding to select security controls to mitigate an organization's specific security risk and in addition reduce and organisations attack surface as the identified Return on Investment (ROI). This article details and illustrates a novel model that uses quantitative risk evaluation methods such as Monte Carlo simulations as opposed to the widely used qualitative methods in the aim to provide organisations with empirical data to make informed decisions, using Modern Portfolio Theory (MPT), when selecting and managing a portfolio of security controls such as Anti-DDOS solutions, Endpoint Detection and Response (EDR) and Cloud Access Security Broker (CASB) solutions.

关键词： Technological innovation Monte Carlo methods Information security Organizations Planning Resource management computer crime Portfolios Risk mitigation Investment

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Resilient Electricity Network Recovery Operation Following Seismic Events

Resilient Electricity Network Recovery Operation Following S...

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Grid Edge Technologies Conference & Exposition (Grid Edge), IEEE PES

作者： Shaila Arif Nirmal-Kumar C. Nair Department of Electrical Computer and Software Engineering The University of Auckland Auckland New Zealand

ISBN: (数字)9798350352528

ISBN: (纸本)9798350352535

Seismic events, globally, are known to impact electricity networks, causing disruptions in the provision of energy and affecting the recovery well-being of communities. Contingency analysis is an established method for understanding network vulnerability, evaluating possible failure situations, and developing specific measures to minimize, which enhance the security of supply. However, current N-1 approaches often fail to effectively handle the dynamic and evolving natures of highimpact natural disturbances. This paper presents modelling based approach illustrated using scenario-based simulations to illustrate network recovery operational planning using contingency analysis. In this study, the N-2 contingency analysis is performed and solutions are proposed to improve the system resilience using the IEEE 39 bus. The identification of potentially viable credible islands is a major contribution of this work.

关键词： Analytical models Seismic measurements Fault tolerance Electricity Prevention and mitigation Contingency management Planning Security Resilience Meteorology

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Multi-view User Preference Modeling for Personalized Text-to-Image Generation

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IEEE Transactions on Multimedia 2025年 27卷 3082-3091页

作者： Zhang, Huaiwen Wu, Tianci Wei, Yinwei Inner Mongolia University College of Computer Science China National & Local Joint Engineering Research Center of Intelligent Information Processing Technology for Mongolian China Inner Mongolia Key Laboratory of Mongolian Information Processing Technology Hohhot010021 China Shandong University School of Software Jinan China

Personalized text-to-image generation aims to synthesize images tailored to individual user preferences. Existing methods primarily generate customized content using a few reference images, which often struggle to mine user preferences from historical records, and thus fail to synthesize truly personalized content. In addition, it is difficult to directly incorporate the extracted feature of user preferences into the feature space of the generation model, since there exists a considerable gap between them. In this paper, we propose a novel multi-view personalized text-to-image generation method based on the diffusion model, named MVP-Diffusion, which learns instance- and user-level preferences from historical records and integrates them into the generation model. For instance-level user preference modeling, we employ a chain-of-thought prompting strategy to deduce preference keywords and integrate them into input prompts with the aid of a large language model. For user-level preference modeling, we construct a learnable embedding for each user to capture more comprehensive preferences by analyzing their historical records. An adaptive user preference fusion module is proposed to inject user preferences into the generation model via a set of learnable parameters. Experimental results demonstrate that the proposed method significantly enhances the personalization of the generated images compared to the other personalized text-to-image generation methods. © 1999-2012 IEEE.

关键词： Adaptation models User preference Text to image Large language models Training Analytical models Image synthesis Feature extraction Diffusion models Symbols

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Evaluation of Retired Lithium-ion Batteries for Second-life Applications through Electrochemical Impedance Spectroscopy

Evaluation of Retired Lithium-ion Batteries for Second-life ...

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Annual IEEE Conference on Applied Power Electronics Conference and Exposition (APEC)

作者： Latha Anekal Sheldon Williamson Department of Electrical Computer and Software Engineering Ontario Tech University Oshawa Canada

ISBN: (数字)9798331516116

ISBN: (纸本)9798331516123

The rapid growth of electric transportation will generate a substantial number of retired batteries. Recycling the retired LIBs is being looked at worldwide to recover the expensive raw materials from used batteries. Alternatively, the retired electric vehicle (EV) batteries can be reused directly or refurbished for second-life applications. Nevertheless, Lithium-ion batteries (LIBs) degrade during their first-life usage, hence ensuring safety, efficiency, and reliability in second-life applications is crucial. This study investigates LIB degradation using electrochemical impedance spectroscopy (EIS) to assess the battery condition at the end of its primary use. A Samsung 21700 nickel cobalt aluminium (NCA) battery is cycled to 80% of its initial capacity and equivalent circuit model (ECM) parameters obtained through electrochemical impedance spectroscopy (EIS) are analyzed. Individual ECM parameters are evaluated to acquire the health indicators. Although the battery capacity decreased by 20%, resistive components such as bulk resistance, charge transfer resistance and Warburg resistance increased by 140%, 150% and 132% respectively. Given the relative capacity and resistance, the battery is well-suited for second-life applications such as grid frequency regulation, uninterruptible power supply, electric forklifts, and material handling equipment. Other health indicators such as Loss of lithium inventory (LLI) and loss of active materials (LAM) are also captured.

关键词： Resistance Lithium-ion batteries Degradation Transportation Stability analysis Recycling Safety Uninterruptible power systems Thermal stability Electrochemical impedance spectroscopy

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Adversarial Threats and Defense Mechanisms in Machine Learning-Based SQL Injection Detection: A Security Analysis

Adversarial Threats and Defense Mechanisms in Machine Learni...

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International Conference on Computing, Networking and Communications (ICNC)

作者： Ranwa Al Mallah Alejandro Quintero Electrical and Computer Engineering Royal Military College of Canada Kingston Canada Polytechnique Montreal Computer and Software Engineering Québec Canada

ISBN: (数字)9798331520960

ISBN: (纸本)9798331520977

QL injection (SQLi) is a type of cyber attack where malicious code is inserted into a SQL query through an input field in a web application. This exploit targets vulnerabilities in the application’s software that allows unsanitized or improperly validated user inputs to be executed as part of a database query. As a result, an attacker can gain unauthorized access to the database, retrieve, modify, or delete data, bypass authentication mechanisms, or perform other malicious actions. In Artificial Intelligence (AI), Machine Learning (ML) techniques are used to automatically detect SQL injections before they reach the web application. However, machine learning techniques are themselves vulnerable to attacks. We conduct an in-depth security analysis of a highly realistic threat model, experimentally demonstrating the effectiveness of poisoning and evasion attacks on a machine learning-based SQL injection detector. We then propose a defense mechanism tailored to the ML algorithm, and designed to protect the system against such attacks. This research highlights the consequences of inadequate management of AI technology in this field.

关键词： Training Threat modeling Databases Perturbation methods Prevention and mitigation Neural networks Machine learning SQL injection Malware Security

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An Efficient Privacy-Preserving Access Control Scheme for Cloud Computing Services

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IEEE Transactions on Consumer Electronics 2025年

作者： Xiong, Ling Wang, JunKai Yu, Linsheng Xiong, Neal Wu, Hanzhou Xihua university School of Computer and Software Engineering Chengdu610039 China Sul Ross State University School of Department of Computer Science and Mathematics AlpineTX79830 United States Shanghai University School of Computer and Software Shanghai China

To meet the future system requirements of Cloud Computing Services (CCSs) for large numbers of users, multiple services and high efficiency, authentication and access control technologies will evolve in a more secure and efficient direction. The integration of authentication and access control into a single module is critical to improving privacy and efficiency. However, current schemes may involve trade-offs and hard choices between privacy and efficiency. To overcome such limitations, our work proposes an efficient privacy-preserving scheme with integrated authentication and access control for CCSs environments. Unlike traditional authentication techniques, our scheme determines not only the legitimacy of the users identity but also the access permissions of remote users during the authentication process. Users will possess the capability to obtain entry to an array of cloud computing providers via utilization of a credential including the corresponding identity and permission. Moreover, the access permissions of different cloud service providers contained within a single credential are protected by a key-based Merkle tree technology to protect users privacy. That our proposed framework is impregnable within the context of the random oracle paradigm is indicated by the outcome of the security evaluation. Furthermore, the proposed framework exhibits superior computational and communicational proficiencies in contrast to relevant schemes. Therefore, this work effectively enhances the efficiency of services, which has important meaning for the use of the access control technology in CCSs environments. © 2025 IEEE.

关键词： Differential privacy

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Universal Construction for Linearizable but Not Strongly Linearizable Concurrent Objects 10th

Universal Construction for Linearizable but Not Strongly L...

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10th International Symposium on Dependable software engineering: Theories, Tools and Applications, SETTA 2024

作者： Wang, Chao Wu, Peng Petri, Gustavo Jia, Qiaowen He, Youlin Lv, Yi Liu, Zhiming Centre for Research and Innovation in Software Engineering College of Computer and Information Science Southwest University Chongqing China and State Key Laboratory of Computer Science Institute of Software Chinese Academy of Sciences Beijing China Arm Research Cambridge United Kingdom China Great Wall Technology Group Co. Ltd. Shenzhen China University of Chinese Academy of Sciences Beijing China

ISBN: (纸本)9789819606016

Strong linearizability is a variant of linearizability and is more suitable for verification. In this paper we investigate the following two problems: (1) for which deterministic sequential specifications there exist linearizable but not strongly linearizable objects;(2) can we capture any violation scheme of strong linearizability for practical objects that are linearizable but not strongly linearizable. To deal with the first problem, we propose two classes of deterministic sequential specifications called inclusively-permutative sequential specifications and exclusively-permutative sequential specifications. The first class of sequential specifications contains sequential specifications of counter, register, max-register, snapshot, set, queue, stack and priority queue. The second class of sequential specifications contains sequential specifications of blocking queue, blocking stack and blocking priority queue. To establish these results, we propose a uniform methodology to construct a wait-free, linearizable but not strongly linearizable object for these two classes of sequential specifications. Our universal construction is based on the classical universal construction, and it additionally permits each operation to change the "take-effect-order" of previous operations. To deal with the second problem, we use bi-branch distinguishable executions to represent violations of strong linearizability. We investigate eight objects that are linearizable but not strongly linearizable, and we show that for each object, it has a pair of bi-branch distinguishable executions such that our universal construction can generate another pair of bi-branch distinguishable executions with the same set of histories. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

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