Global Selection And Local Differentiation Fusion For Vehicle Re-Identification,
2025
College of Information and Control Engineering, Xi 'an University of Architecture and Technology, Xi'an 710055, China; Xi'an Key Labratory of Building Manufactaring Intelligent & Automation Technology, Xi'an 710055, China
Global Selection And Local Differentiation Fusion For Vehicle Re-Identification, Shengjun Xu, Mengqian Zhang, Bohan Zhan, Guanghui Liu, Yuebo Meng
Journal of System Simulation
Abstract: To address the interference issues of different perspectives, complex backgrounds, and lighting intensity in vehicle re-identification caused by cross lens multi view differences, a vehicle reidentification network integrating global selection and local differentiation is proposed. Based on Resnet50 backbone network, a three-branch complementary network integrating global and local features is designed. The global branch is used to learn overall appearance information of the vehicle, while the local branch captures differential details of the vehicle. Based on attention mechanism, a context feature selection module (CFSM) is proposed to effectively separate vehicle information from complex background information, and a detail feature …
Vehicle Routing Problem With Drones Considering Zoned Distribution Of Epidemic Prevention Materials,
2025
School of Management, Hefei University of Technology, Hefei 230009, China; Intelligent Management of Space System Anhui Engineering Research Center, Hefei 230009, China
Vehicle Routing Problem With Drones Considering Zoned Distribution Of Epidemic Prevention Materials, Huawei Ma, Boying Yan
Journal of System Simulation
Abstract: To address the shortcomings of current contactless delivery methods in the collaborative distribution of epidemic prevention supplies, we introduce a specialized model called the vehicle routing problem with drones considering zoned distribution (VRPD-ZD). In order to solve the problem, a linear programming model is established with the shortest delivery time as the optimization objective, and a two-stage heuristic algorithm is proposed. The initial solution is generated by greedy algorithm in the first stage. In the second stage, we develop a Tabu search algorithm with genetic algorithm (TSGA) hybrid. This enhanced algorithm integrates a taboo list and employs advanced chromosome …
Cooperative Control Method Of Mixed Traffic At Signalized Intersection,
2025
Vehicle Measurement, Control and Safety Key Laboratory of Sichuan Province, Xihua University, Chengdu 610039, China; China Automotive Engineering Research Institute Co. Ltd. Chongqing 401122, China
Cooperative Control Method Of Mixed Traffic At Signalized Intersection, Qiushi Huang, Yanyang Wang, Changliang Wu, Junfu Huang, Shenggen Zhang, Haoxuan Luo
Journal of System Simulation
Abstract: A hierarchical decoupling cooperative control method for signal light mixed traffic platoon is designed with the goal of improving the traffic environment at signalized intersections. In the research of upper layer signal control, a calculation model for vehicle delay time at intersections is selected, with the goal of minimizing the average delay time of vehicles. A genetic algorithm based upper layer control strategy for intersection signal lights is proposed and verified; in the research of lower layer mixed platoon control, a "1+N" form is used to establish a dynamic model of the mixed platoon. A vehicle energy consumption model …
Path Planning Of Mobile Robot Based On The Integration Of Multi-Scale A* And Optimized Dwa Algorithm,
2025
Mechanical and Automotive Engineering, Xiamen University of Technology, Xiamen 361024, China; Fujian Provincial Key Laboratory of Advanced Design and Manufacturing for Bus Coach, Xiamen 361024, China
Path Planning Of Mobile Robot Based On The Integration Of Multi-Scale A* And Optimized Dwa Algorithm, Jianmin Xu, Lei Song, Dongdong Deng, Yaoruo Chen, Wei Yang
Journal of System Simulation
Abstract: In order to solve the problems of sharply increasing computational and time costs, as well as poor flexibility of the traditional A* algorithm and dynamic window approach (DWA) in the face of largescale complex environmental path planning, a fusion algorithm based on the A* algorithm of the multiscale map approach(MMA) and the improved DWA algorithm is proposed. A multi-scale map set is established and an obstacle proportion factor is added to the heuristic function of the A* algorithm. The A* algorithm is used to calculate the optimal path on the coarse-scale map, and the optimal path is mapped onto …
Driverless Vehicles Distribution Problem In Communities In Cooperation Of Storage Points,
2025
Transportation Engineering College, Dalian Maritime University, Dalian 116026, China
Driverless Vehicles Distribution Problem In Communities In Cooperation Of Storage Points, Xiaolong Diao
Journal of System Simulation
Abstract: With the development of smart communities, the distribution of driverless vehicles in communities has become a focus of government, operators and researchers. The joint cooperation of storage points in communities is designed to balance the the distribution of each storage point and avoid the high input cost of driverless vehicles, which means that driverless vehicles can travel between different storage points. The driverless vehicle distribution problem proposed in this paper includes the unloading subproblem and the driverless vehicle scheduling subproblem. For the unloading subproblem, the unloading scheme of vehicles at storage points is optimized with the aim of minimizing …
Novel Multi-Gait Strategy For Stable And Efficient Quadruped Robot Locomotion,
2025
College of Intelligence Science and Technology, National University of Defense Technology, Changsha 410073, China
Novel Multi-Gait Strategy For Stable And Efficient Quadruped Robot Locomotion, Daoxun Zhang, Xieyuanli Chen, Zhengyu Zhong, Ming Xu, Zhiqiang Zheng, Huimin Lu
Journal of System Simulation
Abstract: Inspired by the natural gait transition mechanism of quadruped animals, a multi-gait motion strategy is proposed to realize the stable and efficient motion of quadruped robots on different terrains in response to the trade-off between motion energy efficiency and motion stability. The gait is defined based on the duty cycle parameters and phase bias to form the switching basis. Secondly, the affine transformation of gait parameters and the finite state machine are introduced to establish the switching sequence, which realizes the timely gait switching. The speed-gait mapping is designed based on the cost of transport (CoT) and the stability …
Design Of Robust Behavior Tree Control Architecture For Agents In Dynamic Task Environment,
2025
College of System Engineering, National University of Defense Technology, Changsha 410073, China
Design Of Robust Behavior Tree Control Architecture For Agents In Dynamic Task Environment, Qiwei Wang, Qi Zhang, Shuo Yang, Yong Peng
Journal of System Simulation
Abstract: In recent years, the environment in which agents perform tasks has become more open and dynamic, which puts forward higher requirements for the robustness of task planning and behavior scheduling of agents. As a classic behavior control architecture, behavior tree has the characteristics of modularity, behavior parameterization, and structure of both plan representation and reaction, which can effectively support the behavior representation, decision making and scheduling of agents. Based on the hybrid behavior strategy , this paper proposes a robust behavior tree control architecture for dynamic task environment to realize the prudent decision-making and reactive control of agents. The …
Uav Path Planning In Complex Environments And Its Improved Artificial Rabbits Optimization Algorithm,
2025
Guizhou Provincial Characteristic Key Laboratory of System Optimization and Scientific Computation, College of Big Data and Information Engineering, Guizhou University, Guiyang 550025, China
Uav Path Planning In Complex Environments And Its Improved Artificial Rabbits Optimization Algorithm, Anlin Yin, Zhuhong Zhang
Journal of System Simulation
Abstract: The work probes into the model design of reliable and effective UAV path planning in complex obstacle environments and its related optimization algorithm. In the model design, a weight coefficient method and cylindrical coordinate system-based single-objective path planning model is developed to solve the UAV's flight path, in which the distance, angle, height and threat cost are taken as performance indices and obstacles in the ground and spatial regions are regarded as constraints. In the algorithm design, the SPM chaotic mapping is used to improve the initial population distribution of the artificial rabbit optimization algorithm in view of the …
Research On The Digital Twin Architecture And Application Of Cnc System,
2025
Shenyang CASNC Technology Co. , LTD, Shenyang 110168, China
Research On The Digital Twin Architecture And Application Of Cnc System, Xiyang Zhang, Xusheng Lin, Rui Zhou, Yi Hu
Journal of System Simulation
Abstract: In response to the intelligent and digital requirements for virtual debugging, performance evaluation, and machining quality optimization of CNC systems in the field of production and manufacturing, a five dimensional digital twin system of CNC systems combining virtual and real is constructed based on digital twin technology. And combined with relevant new generation information technology, the digital twin system is modeled in multiple fields, including information models, mechanism models, and digital threads, to achieve comprehensive simulation and analysis of physical entities and processing processes. The study also verifies the feasibility of data transmission between CNC systems and digital twin …
Design And Function Analysis Of New Steering System For Autonomous Vehicle,
2025
College of Mechanical and Equipment Engineering, Hebei University of Technology, Handan 056038, China
Design And Function Analysis Of New Steering System For Autonomous Vehicle, Peng Ji, Jinpeng Zhao, Limin Jiang
Journal of System Simulation
Abstract: For the current requirements of regulations and technical maturity, the steering system for autonomous vehicles must have the driver takeover function, explore the permanent magnet coupling device embedded in the steering system, and design a new steering system, which can realize the switch between automatic driving mode and driver takeover mode. The overall design of the new steering system is carried out. The system can realize the functions of steering wheel silence, road sense simulation, overload protection and mechanical steering redundancy, and realize the redundant design of steering system without adding additional hardware. The key component of the system, …
Research On Path Planning Method For Autonomous Underwater Vehicles Based On Improved Informed Rrt,
2025
Hohai University, Changzhou 213022, China; Jiangsu Provincial Key Laboratory of Transmission and Distribution Equipment Technology, Changzhou 213022, China
Research On Path Planning Method For Autonomous Underwater Vehicles Based On Improved Informed Rrt, Bensheng Qi, Yan Li, Hongxia Miao, Jialin Chen, Chenglin Li
Journal of System Simulation
Abstract: In response to the autonomous underwater vehicle (AUV) path planning problem in complex underwater environments, an improved path planning algorithm based on Informed rapidly-exploring random trees (RRT) is proposed in this study. A target-biased sampling strategy and a target-biased extension strategy are employed to address the issue of lack of goal orientation in the sampling process, ensuring that target nodes become sampling points during random sampling. During path points extension, non-target sampling points are guided in the direction of the target point, thereby enhancing the algorithm's ability to search for the target during random sampling and extension processes. A …
Making The Most Of Artificial Intelligence And Large Language Models To Support Collection Development In Health Sciences Libraries,
2025
Chapman University
Making The Most Of Artificial Intelligence And Large Language Models To Support Collection Development In Health Sciences Libraries, Ivan Portillo, David Carson
Library Articles and Research
This project investigated the potential of generative AI models in aiding health sciences librarians with collection development. Researchers at Chapman University’s Harry and Diane Rinker Health Science campus evaluated four generative AI models—ChatGPT 4.0, Google Gemini, Perplexity, and Microsoft Copilot—over six months starting in March 2024. Two prompts were used: one to generate recent eBook titles in specific health sciences fields and another to identify subject gaps in the existing collection. The first prompt revealed inconsistencies across models, with Copilot and Perplexity providing sources but also inaccuracies. The second prompt yielded more useful results, with all models offering helpful analysis …
Effects Of Technical Debt On Software Interoperability,
2025
Department of Computer Science and Engineering, University of Dar es Salaam, P.O Box 33335, Dar es Salaam, Tanzania
Effects Of Technical Debt On Software Interoperability, Leonard Peter Binamungu
Tanzania Journal of Engineering and Technology (TJET)
Technical debt (TD) refers to sub-optimal development decisions that make the software costly to maintain and evolve. Examples of TD include structural complexity, violation of coding styles, and code complexity. Existing research has investigated the nature, causes and indicators of TD, as well as tools and strategies for managing TD. However, although TD could hinder the ability of a software system to be interoperable with others, existing literature has limited evidence on how TD affects systems interoperability. This limits the ability of software engineering teams to manage TD in ways that do not hinder systems interoperability. To fill this void, …
Using Satellite Image Segmentation To Detect Trails,
2025
University of Arkansas Little Rock
Using Satellite Image Segmentation To Detect Trails, Jeremy Reynolds
Theses and Dissertations
This masters thesis proposes an innovative approach to satellite image segmentation by focusing on the detection and mapping of walking, hiking, and biking trails. The motivation behind this project comes from the underexplored area in segmentation techniques for trail identification and offers potential benefits for urban planning, environmental monitoring, and public health. The problem statement addresses the need for a model that can differentiate between various trail types and other natural or man-made elements. The project aims for efficiency and scalability in processing satellite imagery across different compute hardware. The work details several stages: researching existing segmentation techniques, specifically road …
Multiparametric Mri Along With Machine Learning Predicts Prognosis And Treatment Response In Pediatric Low-Grade Glioma,
2025
Thomas Jefferson University
Multiparametric Mri Along With Machine Learning Predicts Prognosis And Treatment Response In Pediatric Low-Grade Glioma, Anahita Fathi Kazerooni, Adam Kraya, Komal Rathi, Meen Chul Kim, Arastoo Vossough, Nastaran Khalili, Ariana Familiar, Deep Gandhi, Neda Khalili, Varun Kesherwani, Debanjan Haldar, Hannah Anderson, Run Jin, Aria Mahtabfar, Sina Bagheri, Yiran Guo, Qi Li, Xiaoyan Huang, Yuankun Zhu, Alex Sickler, Matthew R Lueder, Saksham Phul, Mateusz Koptyra, Phillip Storm, Jeffrey Ware, Yuanquan Song, Christos Davatzikos, Jessica Foster, Sabine Mueller, Michael J Fisher, Adam Resnick, Ali Nabavizadeh
Department of Neurosurgery Faculty Papers
Pediatric low-grade gliomas (pLGGs) exhibit heterogeneous prognoses and variable responses to treatment, leading to tumor progression and adverse outcomes in cases where complete resection is unachievable. Early prediction of treatment responsiveness and suitability for immunotherapy has the potential to improve clinical management and outcomes. Here, we present a radiogenomic analysis of pLGGs, integrating MRI and RNA sequencing data. We identify three immunologically distinct clusters, with one group characterized by increased immune activity and poorer prognosis, indicating potential benefit from immunotherapies. We develop a radiomic signature that predicts these immune profiles with over 80% accuracy. Furthermore, our clinicoradiomic model predicts progression-free …
Scalable And Ethical Insider Threat Detection Through Data Synthesis And Analysis By Llms,
2025
Dakota State University
Scalable And Ethical Insider Threat Detection Through Data Synthesis And Analysis By Llms, Haywood Gelman, John Hastings
Research & Publications
Insider threats wield an outsized influence on organizations, disproportionate to their small numbers. This is due to the internal access insiders have to systems, information, and infrastructure. Signals for such risks may be found in anonymous submissions to public web-based job search site reviews. This research studies the potential for large language models (LLMs) to analyze and detect insider threat sentiment within job site reviews. Addressing ethical data collection concerns, this research utilizes synthetic data generation using LLMs alongside existing job review datasets. A comparative analysis of sentiment scores generated by LLMs is benchmarked against expert human scoring. Findings reveal …
Artificial Intelligence In Health Care: Business Opportunities And Ethical Challenges,
2025
Bentley University
Artificial Intelligence In Health Care: Business Opportunities And Ethical Challenges, Ankita Srivastava,, Marco Marabelli, Jeffrey Moriarty
Ethics Publication
Artificial intelligence (AI), and in particular generative AI (GAI), are making incredible progress toward automation. The pervasive and invasive nature of these technologies are affecting every industry, and health care is no exception. This paper summarizes insights derived from a panel that the Hoffman Center for Business Ethics and the Center for Health and Business at Bentley University hosted in March 2024. The panel invited three qualified health care professionals: Evan Carey, Susan Persky and John Torous. The panelists are all active in multiple aspects of AI in health care but represent a focus on the key areas of policy …
Comparing Unidirectional, Bidirectional, And Word2vec Models For Discovering Vulnerabilities In Compiled Lifted Code,
2025
Dakota State University
Comparing Unidirectional, Bidirectional, And Word2vec Models For Discovering Vulnerabilities In Compiled Lifted Code, Gary Mccully, John Hastings, Shengjie Xu, Adam Fortier
Research & Publications
Ransomware and other forms of malware cause significant financial and operational damage to organizations by exploiting long-standing and often difficult-to-detect software vulnerabilities. To detect vulnerabilities such as buffer overflows in compiled code, this research investigates the application of unidirectional transformer-based embeddings, specifically GPT-2. Using a dataset of LLVM functions, we trained a GPT-2 model to generate embeddings, which were subsequently used to build LSTM neural networks to differentiate between vulnerable and non-vulnerable code. Our study reveals that embeddings from the GPT-2 model significantly outperform those from bidirectional models of BERT and RoBERTa, achieving an accuracy of 92.5\% and an F1-score …
Ai 101: What It Can (And Can't) Do For You,
2025
Arkansas State University - Jonesboro
Ai 101: What It Can (And Can't) Do For You, April Sheppard
Staff and Faculty Scholarship
In this presentation, April defines AI, describes how it works, reviews some pros and cons, and finally discusses what AI can actually accomplish in its current iteration.
Chalkboards To Chatbots: Helping Faculty Harness Ai For The Future Of Higher Education,
2025
Regis University
Chalkboards To Chatbots: Helping Faculty Harness Ai For The Future Of Higher Education, Justin C. Grace
Regis University Student Publications (comprehensive collection)
Integrating artificial intelligence (AI) into nursing education presented significant opportunities yet posed challenges due to varied faculty readiness. This Doctor of Nursing Practice (DNP) quality improvement (QI) project evaluated an educational intervention aimed at enhancing nursing faculty's AI proficiency and confidence at Regis University’s Rueckert-Hartman College for Health Professions. Using a mixed-methods, pre- and post-intervention design, validated surveys assessed changes in faculty perceptions, knowledge, and skills related to AI. The intervention included a digital toolkit with nine instructional videos demonstrating practical AI applications using FreedAI’s large language model, ChatGPT, supported by voiceover narration and closed captioning. Data analysis involved descriptive …
