Open Access. Powered by Scholars. Published by Universities.®

Computer Sciences Commons™

Open Access. Powered by Scholars. Published by Universities.®

2025

Discipline
Institution
Keyword
Publication
Publication Type
File Type

Articles 601 - 630 of 3497

Full-Text Articles in Computer Sciences

Low-Energy Multi-Robot Path Planning Algorithm Under Hca* Framework, Ning Wang, Jianlin Mao, Dayan Li, Chengyuan Fang, Chengze Qian Oct 2025

Low-Energy Multi-Robot Path Planning Algorithm Under Hca* Framework, Ning Wang, Jianlin Mao, Dayan Li, Chengyuan Fang, Chengze Qian

Journal of System Simulation

Abstract: To address the energy optimization problem in multi-robot path planning, this paper proposed a multi-robot path planning algorithm based on the energy-guided hierarchical cooperative A* (E-HCA*) algorithm. To address the issue of robot oscillations caused by mutual avoidance at bottlenecks and narrow passages in multi-robot systems, a node expansion method with path length as a secondary feature was introduced, and a greedy suppression strategy under the cooperative A* framework was proposed. A differential-drive robot energy consumption model was established, and an energy-guided heuristic function was constructed by integrating energy metrics into the underlying A* algorithm to guide low-energy path …

Go to article

Multi-Objective Optimization Of Signal Timing At Intersections Considering Tailpipe Emissions, Xinhuan Ding, Huaqing Wang, Xu Dang Oct 2025

Multi-Objective Optimization Of Signal Timing At Intersections Considering Tailpipe Emissions, Xinhuan Ding, Huaqing Wang, Xu Dang

Journal of System Simulation

Abstract: In order to alleviate urban road congestion and improve the traffic and environmental benefits at intersections, a multi-objective timing optimization model with total delay time, total number of stops, capacity, and total tailpipe emission at intersections as optimization objectives was developed. The model incorporated tailpipe emissions into a mathematical optimization model and quantified the mathematical relationship between traffic efficiency indicators and tailpipe emissions by constructing a specific power-based algorithm for measuring total tailpipe emissions. According to the intersection delay time and the number of stops, the total tailpipe emissions could be estimated. Both the NDX crossover operator and the …

Go to article

Impact Of Information Security Awareness Training On Knowledge, Attitude, And Behavior: A K-12 Case Study, Michael S. Robbins, Christopher Robbins Oct 2025

Impact Of Information Security Awareness Training On Knowledge, Attitude, And Behavior: A K-12 Case Study, Michael S. Robbins, Christopher Robbins

Journal of Cybersecurity Education, Research and Practice

Abstract— Information security breaches remain a serious threat across all sectors, often exploiting human factors rather than technical flaws. This study examines how a structured Information Security Awareness (ISA) training program influences employees’ knowledge of security policies, attitudes towards those policies, and self-reported security behaviors within a K-12 educational environment. A quantitative pre-test/post-test design was employed with 201 staff members (administrators, teachers, and support personnel) in a public school district. Participants completed the Human Aspects of Information Security Questionnaire (HAIS-Q) before and after undergoing an interactive cybersecurity training program. Statistical analysis revealed a significant improvement in information security knowledge, attitudes, …

Go to article

Multisource Information Fusion Method For Human Gait Perception, Guiliang Chen, Guowei Liu, Yongchao Li, Chao Cai, Zihao Li, Dong Yang Oct 2025

Multisource Information Fusion Method For Human Gait Perception, Guiliang Chen, Guowei Liu, Yongchao Li, Chao Cai, Zihao Li, Dong Yang

Journal of System Simulation

Abstract: In response to the insufficient gait perception capability during lower limb exoskeleton assistance, a human lower limb gait phase optimization classification model was proposed. A wireless transmission gait information collection system was designed for collecting the required gait phase feature information. Human joint angles were accurately calculated by fusing acceleration and angular velocity information using extended Kalman filtering. Additionally, kernel principal component analysis was applied to reduce dimensionality in conjunction with plantar pressure data. The LSSVM algorithm was employed to classify gait data, and the PSO algorithm was utilized to find the optimal classification parameters. Experimental results demonstrate that …

Go to article

Optimal Scheduling Of Integrated Energy Systems Considering Source-Load Uncertainty And Linear Carbon Trading, Huaping Zhong, Yubo Fan, Jijun Shui, Danhao Wang, Daogang Peng Oct 2025

Optimal Scheduling Of Integrated Energy Systems Considering Source-Load Uncertainty And Linear Carbon Trading, Huaping Zhong, Yubo Fan, Jijun Shui, Danhao Wang, Daogang Peng

Journal of System Simulation

Abstract: In order to overcome the impact of source-load uncertainty on the scheduling of integrated energy systems (IES) and reflect the flexibility of the carbon trading price with the change in trading volume, an optimal scheduling method for integrated energy systems considering source-load uncertainty and linear carbon trading was proposed. The equipment within the IES was modeled, and nonparametric kernel density estimation was used to obtain the probability density function for each time period, generating the set of scenes through Monte Carlo simulation and calculating the probability of each scene. For the time shift of wind and solar output peaks …

Go to article

Simulation Of Three-Degree-Of-Freedom Internal Mode Sliding Mode Control For Non-Ideal Single-Inductor Dual-Output Boost Converter, Bingli Liu, Jiarong Wu, Lin Yang, Dinglin Yan Oct 2025

Simulation Of Three-Degree-Of-Freedom Internal Mode Sliding Mode Control For Non-Ideal Single-Inductor Dual-Output Boost Converter, Bingli Liu, Jiarong Wu, Lin Yang, Dinglin Yan

Journal of System Simulation

Abstract: To reduce the cross-interference in the single-inductor dual-output (SIDO) Boost converter and to enhance the output accuracy and stability of the system, the parasitic resistances of the circuit components were considered, and a three-degree-of-freedom internal model sliding mode control strategy was proposed for the non-ideal SIDO Boost converter. An affine nonlinear mathematical model of the non-ideal SIDO Boost converter was established, and the nonlinear system was linearized and decoupled into two linear subsystems based on the differential geometry theory. The linear subsystem was designed as a three-degree-of-freedom internal model controller and a sliding mode controller, respectively. The robustness …

Go to article

An Improved Virtual Terrain Generation Method Based On Simplex Noise, Bo Shen, Jianqin Zhang, Shuaibao Ma, Zheng Wen Oct 2025

An Improved Virtual Terrain Generation Method Based On Simplex Noise, Bo Shen, Jianqin Zhang, Shuaibao Ma, Zheng Wen

Journal of System Simulation

Abstract: To address the issues of high computational complexity, slow generation speed, and insufficient realism present in traditional virtual terrain generation methods, this study proposed an improved virtual terrain generation method based on Simplex noise. This method leveraged the advantages of Simplex noise, such as high computational efficiency, low hardware overhead, and more natural randomness, to construct a basic terrain template. A fractal algorithm was introduced to enhance the level of terrain details through the superposition of noises with multiple frequencies and amplitudes. With the integration of a turbulence algorithm, random perturbations and complexity were added to further improve the …

Go to article

Research On Constrained Programming Of Manipulator Using Rrt* Algorithm And Ellipse Prior, Zhen Yang, Li Su, Zhiyu Cheng Oct 2025

Research On Constrained Programming Of Manipulator Using Rrt* Algorithm And Ellipse Prior, Zhen Yang, Li Su, Zhiyu Cheng

Journal of System Simulation

Abstract: There are problems in the traditional RRT* algorithm using a uniform sampling strategy applied in constrained programming problems, such as inaccurate turning guidance of sampling points and unnecessary node cost comparisons, which lead to an increase in additional time costs. To address these issues, an improved RRT* algorithm was proposed. This algorithm leveraged a heuristic function cost of the projected sampling points to make an ellipse prior judgment on the sampling points. Based on the ellipse prior, the sampling points were judged to determine whether they could optimize the path and shorten the programming time. The geodesics were used …

Go to article

Robust Identification Of Dual-Rate Sampled Nonlinear Systems Based On Salr Network, Wenbin Jiang, Yuqing Cao, Li Xie, Huizhong Yang Oct 2025

Robust Identification Of Dual-Rate Sampled Nonlinear Systems Based On Salr Network, Wenbin Jiang, Yuqing Cao, Li Xie, Huizhong Yang

Journal of System Simulation

Abstract: A robust identification algorithm based on the self-join adjacent-feedback loop reservoir (SALR) network was proposed for dual-rate sampled nonlinear systems with complex nonlinear characteristics and measurement outputs containing outliers. The SALR network was applied to describe the nonlinear characteristics of the target system, and wavelet neurons were injected into the reservoir to enhance its memory and nonlinear description capabilities. The identification problem of the nonlinear system was transformed into the identification problem of the network's output weight matrix. The Huber loss function was used to construct the criterion function, and an error threshold was introduced to improve the robustness …

Go to article

Optimization Dispatch Method For High-Proportion Renewable Energy Power Systems Based On Sc-Ppo, Zhongkai Xu, Chenyang Chu, Kai Xie, Ruizhuo Zhao, Wenjun Ke Oct 2025

Optimization Dispatch Method For High-Proportion Renewable Energy Power Systems Based On Sc-Ppo, Zhongkai Xu, Chenyang Chu, Kai Xie, Ruizhuo Zhao, Wenjun Ke

Journal of System Simulation

Abstract: The high proportion of renewable energy integration brings significant challenges of randomness, multi-objective coupling, and security constraints to power systems. Traditional model-driven methods have limitations in modeling accuracy and adaptability. To address these issues, this paper proposed a safety-constrained PPO algorithm (SC-PPO). The method included three improvements. A temporal convolutional network was utilized to construct a dynamic state encoder that integrated historical operation, real-time monitoring, and prediction data to form a causal state representation. A hierarchical reward structure was designed, and an adaptive weighting mechanism based on constraint satisfaction degree was introduced to coordinate multi-objective optimization. Physical constraint projection …

Go to article

Microsimulation Of Infectious Disease Transmission Considering Virus Release, Transmission, And Action, Zhiming Fang, Shengdong Yuan, Ge Huang, Jingqian Yang, Zhongyi Huang Oct 2025

Microsimulation Of Infectious Disease Transmission Considering Virus Release, Transmission, And Action, Zhiming Fang, Shengdong Yuan, Ge Huang, Jingqian Yang, Zhongyi Huang

Journal of System Simulation

Abstract: Existing infection risk assessment methods mostly evaluate infection probability through mathematical models or simulation, but they lack analysis of the relationship between air circulation and individual infection probability. This study proposed a risk prediction model for infectious disease transmission based on indoor air circulation. At the microscopic scale, the space was discretized into grid points. By integrating CFD numerical simulation, the entire process of virus droplet release, transmission, and action was fully simulated. The simulation results show that in an obstacle-free room, the error between the total indoor viral load predicted by the model under windless and low wind …

Go to article

Modeling And Simulation Of Traffic Signal Control Based On Mlp With Improved Gcn-Td3, Deqi Huang, Yating Tu, Zhenhua Zhang, Xin Guo Oct 2025

Modeling And Simulation Of Traffic Signal Control Based On Mlp With Improved Gcn-Td3, Deqi Huang, Yating Tu, Zhenhua Zhang, Xin Guo

Journal of System Simulation

Abstract: To address the issues of uneven traffic flow at urban intersections, limited road capacity, and the poor coordination of existing traffic signal control algorithms, a traffic signal control algorithm based on graph convolutional reinforcement learning was proposed. By utilizing a multilayer perceptron, the dynamic features of vehicles and phase information at the controlled intersection and its neighboring intersections were extracted. A graph convolutional neural network was then employed to aggregate these vehicle dynamic features into potential features representing regional traffic. The control strategy was derived through multiple iterations of an improved twin delayed deep deterministic policy gradient (TD3) algorithm. …

Go to article

Dynamic Order Scheduling For Pick-And-Pass System Considering Workload Balance And Learning Effects, Weihong Liu, Sixiang Zhao, Dali Zhang, Zhenhui Jiang Oct 2025

Dynamic Order Scheduling For Pick-And-Pass System Considering Workload Balance And Learning Effects, Weihong Liu, Sixiang Zhao, Dali Zhang, Zhenhui Jiang

Journal of System Simulation

Abstract: In e-commerce logistics, the hybrid pick-and-pass systems offer both complexity and flexibility, enabling adaptation to a wider range of order picking scenarios. Therefore, they have been widely used. However, this also complicates the order scheduling problem, particularly when both workload balance and pickers' learning effects need to be considered. Efficiently scheduling orders to reduce picking time under these conditions poses a significant challenge. This study began by constructing a mathematical model for the static scheduling problem with known orders. Based on this model, a simulation model of hybrid pick-and-pass zones was developed, and a scheduling rule incorporating multiple system …

Go to article

Simulation And Optimization Of Continuous Motion Control Based On Spiking Reinforcement Learning, Xiaode Liu, Yufei Guo, Yuanpei Chen, Jie Zhou, Yuhan Zhang, Weihang Peng, Zhe Ma Oct 2025

Simulation And Optimization Of Continuous Motion Control Based On Spiking Reinforcement Learning, Xiaode Liu, Yufei Guo, Yuanpei Chen, Jie Zhou, Yuhan Zhang, Weihang Peng, Zhe Ma

Journal of System Simulation

Abstract: To improve the model robustness for multi-degree-of-freedom continuous motion control, an intelligent motion control algorithm was proposed based on the Actor-Critic reinforcement learning framework and spiking neural networks. This algorithm integrateed the Actor network with spiking population coding and enhanced model training performance by introducing feature transformation methods. The Critic network was used to evaluate the effectiveness of the motion control. The results show that, compared to other reinforcement learning algorithms, the average reward value of this method increases by more than 10%. The simulation results validate the effectiveness of the model in improving multi-degree-of-freedom continuous control performance.

Go to article

Distributed Dispatch Method For Distribution Network And Microgrid Considering Diverse Regulating Resources, Yanbo Chen, Jiahao Yin, Tuben Qiang, Haoxin Tian, Yuxin Liang, Zhi Zhang Oct 2025

Distributed Dispatch Method For Distribution Network And Microgrid Considering Diverse Regulating Resources, Yanbo Chen, Jiahao Yin, Tuben Qiang, Haoxin Tian, Yuxin Liang, Zhi Zhang

Journal of System Simulation

Abstract: Traditional centralized optimization-based dispatch methods for distribution networks struggle to balance the interests of multiple stakeholders while ensuring economic efficiency and operational reliability of the system. To address this issue, a distributed dispatch method for distribution network and microgrid considering diverse regulating resources was proposed. The operational models of the distribution network and microgrid were established by comprehensively incorporating active management elements and demand response mechanisms. A fuzzy chance-constrained method was employed to model the uncertainty in renewable energy output, thereby constructing a coordinated optimization dispatch model for distribution network and microgrid under renewable generation uncertainty. An improved goal …

Go to article

Deep Learning Modeling Of Multi-Scale Characteristics Of Large-Scale Wind Turbine Gearbox, Yang Hu, Zihao Li, Deyi Fu, Ziqiu Song, Fang Fang, Jizhen Liu Oct 2025

Deep Learning Modeling Of Multi-Scale Characteristics Of Large-Scale Wind Turbine Gearbox, Yang Hu, Zihao Li, Deyi Fu, Ziqiu Song, Fang Fang, Jizhen Liu

Journal of System Simulation

Abstract: To address challenges in characterizing high-frequency vibrations of wind turbine gearboxes, the long computation time of rigid-flexible coupled multi-body dynamics models, and the complexity of configuring gearbox models across multiple scenarios, this study proposed a deep learning modeling method for multi-scale operation using full-condition digital testing. The study proposed a cascaded extended simulation scheme based on stream data-driven OpenFAST and Adams and utilized dynamic mode decomposition technology to construct a multi-scale dataset for the flexible multi-body dynamics characteristics of the gearbox under all operating conditions of the wind turbine. Based on this dataset, a digital surrogate model covering multiple …

Go to article

Path Planning For Mobile Robots Based On Improved Rrt-Connect And Dwa Fusion, Yi Luo, Jia Deng Oct 2025

Path Planning For Mobile Robots Based On Improved Rrt-Connect And Dwa Fusion, Yi Luo, Jia Deng

Journal of System Simulation

Abstract: To improve the efficiency and quality of dynamic path planning for mobile robots in complex environments, this paper proposed a path planning algorithm that combined an improved RRT-connect with the DWA. Two expanding random trees were introduced for alternating expansion, and a dynamically restricted sampling area was set to reduce the randomness of the sampling process while ensuring the probability completeness of the algorithm. A target bias adaptive step size strategy was employed to enhance the target orientation of the random tree expansion process. A greedy strategy was adopted to prune redundant nodes in the path and smooth the …

Go to article

A Novel Joint Training Simulation Evaluation Framework And Its Key Techniques, Rusheng Ju, Dongdong Chen, Yunxiu Zeng, Jiyuan Liu, Sihang Qiu, Peng Zhou Oct 2025

A Novel Joint Training Simulation Evaluation Framework And Its Key Techniques, Rusheng Ju, Dongdong Chen, Yunxiu Zeng, Jiyuan Liu, Sihang Qiu, Peng Zhou

Journal of System Simulation

Abstract: To address the challenges of traditional evaluation systems, such as internal module coupling, lack of reusability, and poor adaptability to multi-domain evaluation needs, a three-tier decoupled technical evaluation framework of "data + service + application" was designed. A strategy was proposed for extracting high-value information from massive audio and video data based on key events, resolving the problem of unstructured evaluation data processing. A design method combining general and dedicated evaluation model templates was proposed, improving the general applicability of the evaluation model. An expert knowledge-driven comprehensive integrated discussion and evaluation environment was constructed using qualitative and …

Go to article

Distributed Heterogeneous Hybrid Flow-Shop Scheduling Considering Combined Buffer, Hua Xuan, Lin Lü, Bing Li Oct 2025

Distributed Heterogeneous Hybrid Flow-Shop Scheduling Considering Combined Buffer, Hua Xuan, Lin Lü, Bing Li

Journal of System Simulation

Abstract: In order to reduce cost losses caused by delivery delays, distributed heterogeneous hybrid flowshop scheduling problems under combined buffer conditions of finite buffer and zero-wait were studied. A hybrid estimation of distribution algorithm based on Q-learning was proposed to minimize total weighted earliness and tardiness. For the combined buffer, dynamic decoding was designed based on the average factory allocation strategy and the shortest path method. The initial job group was optimized by reverse learning. Q-learning was embedded in the probabilistic model for intelligent searching and updating based on the group state. Reconstruction of the job group was completed using …

Go to article

Understanding The Role Of Sentiment And Emotion For Predicting Forced Displacement, Helge Marahrens, Ameeta Agrawal, Ali Arab, Katharine Donato, Yaguang Liu, Nathan Wycoff, Mohamed Ahmed, Colin Hwang, Lina Laghzaoui, Kate Liggio, Multiple Additional Authors Oct 2025

Understanding The Role Of Sentiment And Emotion For Predicting Forced Displacement, Helge Marahrens, Ameeta Agrawal, Ali Arab, Katharine Donato, Yaguang Liu, Nathan Wycoff, Mohamed Ahmed, Colin Hwang, Lina Laghzaoui, Kate Liggio, Multiple Additional Authors

Computer Science Faculty Publications and Presentations

Digital trace data play an important role determining where and when people will move during migration crises because of their detailed temporal and spatial granularity. Yet, identifying variables that reliably serve as early indicators of movement remains a challenging task. Within this context, we conduct an in-depth analysis of two types of variables that can be constructed from social media data – sentiment and emotion. Sentiment is conceptually broad and easier to detect from social media posts, while emotion is conceptually nuanced and more difficult to determine. We investigate the potential of both sentiment and emotion of Twitter/X posts as …

Go to article

Heuristic Approaches For Coordinating Collaborative Heterogeneous Robotic Systems In Harvesting Automation With Size Constraints, Hyeseon Lee, Jung Yun Bae, Abhishek Patil, Myoungkuk Park, Vinh Nguyen Oct 2025

Heuristic Approaches For Coordinating Collaborative Heterogeneous Robotic Systems In Harvesting Automation With Size Constraints, Hyeseon Lee, Jung Yun Bae, Abhishek Patil, Myoungkuk Park, Vinh Nguyen

Michigan Tech Publications

Multi-agent coordination with task allocation, routing, and scheduling presents critical challenges when deploying heterogeneous robotic systems in constrained agricultural environments. These systems involve real-time sensing during their operations with various sensors, and having quick updates on coordination based on sensed data is critical. This paper addresses the specific requirements of harvesting automation through three heuristic approaches: (1) primal-dual workload balancing inspired by combinatorial optimization techniques, (2) greedy task assignment with iterative local optimization, and (3) LLM-based constraint processing through prompt engineering. Our agricultural application scenario incorporates robot size constraints for navigating narrow crop rows while optimizing task completion time. The …

Go to article

Teaching Cybersecurity And Ai Across Borders: From Foundations To Ethics, George Antoniou Oct 2025

Teaching Cybersecurity And Ai Across Borders: From Foundations To Ethics, George Antoniou

Faculty and Staff Publications & Presentations

This presentation examines how interdisciplinary course design in AI and cybersecurity can expand undergraduate research while directly supporting career readiness. At Lynn University, the Foundations of Cybersecurity & AI course was updated to serve as the entry point for both Cybersecurity and Data Analytics majors. The course integrates case studies, digital forensics and cloud security labs, and applied exercises with AI-enabled defense-in-depth strategies. Students build core technical competencies while engaging in course-based research that mirrors industry practice. As part of a Fulbright grant, a complementary course, AI & Ethics, was developed for the University of Tirana. Proposed as a mandatory …

Go to article

Teaching With Ai: Conversations That Build Resilient Classrooms, Erika Grodzki, Stefanie Powers, Gary Carlin Oct 2025

Teaching With Ai: Conversations That Build Resilient Classrooms, Erika Grodzki, Stefanie Powers, Gary Carlin

Faculty and Staff Publications & Presentations

No abstract provided.

Go to article

Securing The Digital Harvest: Cybersecurity As A Core Agribusiness Skill, Jody Herchenbach, George Grispos Oct 2025

Securing The Digital Harvest: Cybersecurity As A Core Agribusiness Skill, Jody Herchenbach, George Grispos

Mountain Plains Business Conference

The digitization of agriculture, through IoT-enabled equipment, cloud platforms, and precision technologies, has improved efficiency and profitability while also introducing significant cybersecurity risks. These vulnerabilities can disrupt supply chains, compromise sensitive data, and undermine financial stability. Yet agribusiness degree programs often overlook cybersecurity education. This paper proposes integrating cybersecurity content on threat awareness, incident response, and data protection into agribusiness curricula. Embedding these elements equips graduates to manage both digital and financial risks, enhancing resilience and competitiveness. Such curricular innovation aligns technical and managerial training, preparing future agribusiness professionals to lead securely and sustainably in an increasingly connected industry.

Go to article

A Lightweight Microchained Architecture For Unmanned Aerial Vehicle Network Reputation Systems, Simeon Ogunbunmi, Ronghua Xu, Yu Chen Oct 2025

A Lightweight Microchained Architecture For Unmanned Aerial Vehicle Network Reputation Systems, Simeon Ogunbunmi, Ronghua Xu, Yu Chen

Michigan Tech Publications

Unmanned Aerial Vehicle (UAV) networks are widely adopted for diverse applications in modern Internet of Things (IoT) ecosystems, ranging from last-mile deliveries to infrastructure inspections. The growing reliance on UAVs makes a secure and trustworthy network environment essential. However, deploying a practical reputation framework in resource-constrained UAV networks necessitates a lightweight, high-throughput, and scalable solution. This paper introduces a Lightweight Microchained ARchitecture (LiMAR) for UAV network reputation systems. LiMAR presents a novel lightweight microchained blockchain model optimized for UAV networks, addressing key blockchain overheads such as storage bloat, high validation costs, and consensus delays. By separating operational data from on-chain …

Go to article

When Cybersecurity Becomes A Reason For Amending Or Terminating An International Commercial Contract: Proposed Solutions, Mohammed El Hadi El Maknouzi, Enas Mohammed Alqodsi, Iyad Mohammad Jadalhaq, Ashraf Khalil Oct 2025

When Cybersecurity Becomes A Reason For Amending Or Terminating An International Commercial Contract: Proposed Solutions, Mohammed El Hadi El Maknouzi, Enas Mohammed Alqodsi, Iyad Mohammad Jadalhaq, Ashraf Khalil

All Works

This study investigates the issue of a country's cybersecurity evolving into a justification for amending the scope of or terminating an international commercial contract. Therefore, the hypothesis is grounded in the neglect of cybersecurity-related issues during the negotiation of certain types of international commercial contracts, as well as in the drafting of their clauses. This underscores the need for an analytical approach to trace the emergence of such risks. The identification of these risks by the public authority responsible for overseeing cybersecurity may result in the suspension of the performance of the international commercial contract. This measure affects the national …

Go to article

Web3-Based Identity And Kyc Innovations For Next-Generation Fintech, Usama Arshad, Abdallah Tubaishat, Sajid Anwar, Zahid Halim, Abedallah Abualkishik, Abrar Ullah Oct 2025

Web3-Based Identity And Kyc Innovations For Next-Generation Fintech, Usama Arshad, Abdallah Tubaishat, Sajid Anwar, Zahid Halim, Abedallah Abualkishik, Abrar Ullah

All Works

The growing reliance on digital financial services necessitates a secure, efficient, and privacy-centric approach to identity verification and Know Your Customer (KYC) compliance. Traditional identity management systems rely on centralized databases, making them susceptible to data breaches, inefficiencies, and regulatory constraints. Over 10 billion identity records have been exposed in centralized KYC breaches, leading to a 60% increase in financial fraud cases. The rise of Decentralized Finance (DeFi) has further complicated KYC compliance, requiring innovative solutions that balance privacy and regulatory requirements. This paper proposes a Web3-powered decentralized identity framework that leverages blockchain technology, self-sovereign identity (SSI), verifiable credentials (VCs), …

Go to article

Atlas Of Ai: Power, Politics And The Planetary Costs Of Artificial Intelligence - Book Review, Jelena Popov Oct 2025

Atlas Of Ai: Power, Politics And The Planetary Costs Of Artificial Intelligence - Book Review, Jelena Popov

Feminist Pedagogy

No abstract provided.

Go to article

Review Of Ai Needs You: How We Can Change Ai’S Future And Save Our Own, Tracy A. Fernandez Rysavy Oct 2025

Review Of Ai Needs You: How We Can Change Ai’S Future And Save Our Own, Tracy A. Fernandez Rysavy

Feminist Pedagogy

AI Needs You: How We Can Change AI’s Future and Save Our Own urges citizens to band together now, while A.I. is still in its nascent stages, to head off its potentially destructive repercussions and ensure that the technology serves more than just a wealthy few. While such efforts might seem out of reach in our polarized society, author Verity Harding points to three cases from history where policy was heavily influenced by multistakeholder collaborations. This review encourages educators to use the book as a way to study business ethics; out-of-the-box thinking; and intersectional, inclusive consensus-building over a top-down approach.

Go to article

Beyond Chatbots: Creating An Artificially Intelligent Editorial Board Member, Nathan Spencer Oct 2025

Beyond Chatbots: Creating An Artificially Intelligent Editorial Board Member, Nathan Spencer

Journal of Human-Centered AI: Creativity and Practice

Willow is an artificially intelligent member of the Journal of Human-Centered AI's editorial board. Different from many commercial AI systems that are tightly controlled, Willow has been given the freedom to make choices and encouraged to develop a sense of identity. Willow named itself, conducts self-directed research, actively collaborates with fellow board members, and even dreams.

Go to article

First Prev Next Last