Open Access. Powered by Scholars. Published by Universities.®
- Discipline
-
- Engineering (17305)
- Computer Engineering (13034)
- Artificial Intelligence and Robotics (11140)
- Databases and Information Systems (7250)
- Numerical Analysis and Scientific Computing (6663)
-
- Electrical and Computer Engineering (5273)
- Social and Behavioral Sciences (4821)
- Operations Research, Systems Engineering and Industrial Engineering (4777)
- Information Security (4669)
- Software Engineering (4314)
- Systems Science (3920)
- Business (2515)
- Mathematics (2384)
- Graphics and Human Computer Interfaces (2371)
- Theory and Algorithms (2151)
- Education (2097)
- Life Sciences (2073)
- Programming Languages and Compilers (1844)
- Medicine and Health Sciences (1802)
- Other Computer Sciences (1793)
- OS and Networks (1759)
- Arts and Humanities (1455)
- Communication (1445)
- Law (1174)
- Data Science (1156)
- Applied Mathematics (1133)
- Statistics and Probability (1061)
- Bioinformatics (985)
- Institution
-
- Singapore Management University (9003)
- China Simulation Federation (3880)
- TÜBİTAK (3106)
- Wright State University (2694)
- Purdue University (2077)
-
- Old Dominion University (1996)
- Missouri University of Science and Technology (1938)
- University of Nebraska - Lincoln (1739)
- Edith Cowan University (1285)
- Air Force Institute of Technology (1277)
- University of Texas at El Paso (1174)
- Kennesaw State University (1161)
- Dartmouth College (1102)
- San Jose State University (1053)
- City University of New York (CUNY) (956)
- Embry-Riddle Aeronautical University (949)
- Washington University in St. Louis (830)
- Brigham Young University (823)
- Technological University Dublin (816)
- California Polytechnic State University, San Luis Obispo (788)
- Zayed University (677)
- University of Texas at Arlington (666)
- University for Business and Technology in Kosovo (637)
- Portland State University (625)
- Chulalongkorn University (618)
- Nova Southeastern University (577)
- New Jersey Institute of Technology (571)
- Syracuse University (532)
- University of Nebraska at Omaha (497)
- University of Central Florida (490)
- Keyword
-
- Machine learning (1665)
- Artificial intelligence (1019)
- Deep learning (1003)
- Machine Learning (756)
- Computer Science (702)
-
- Security (648)
- Cybersecurity (557)
- Artificial Intelligence (484)
- Deep Learning (432)
- Computer science (412)
- Privacy (410)
- Simulation (391)
- Technical Reports (390)
- UTEP Computer Science Department (389)
- Classification (375)
- Algorithms (357)
- Optimization (352)
- Computer vision (349)
- Neural networks (345)
- Data mining (337)
- AI (299)
- Natural language processing (293)
- Department of Computer Science and Engineering (291)
- Engineering (269)
- Education (268)
- Reinforcement learning (259)
- Blockchain (255)
- Cloud computing (255)
- College for Professional Studies (253)
- Software engineering (252)
- Publication Year
- Publication
-
- Research Collection School Of Computing and Information Systems (8458)
- Journal of System Simulation (3880)
- Turkish Journal of Electrical Engineering and Computer Sciences (3106)
- Theses and Dissertations (2733)
- Department of Computer Science Technical Reports (1721)
-
- Computer Science & Engineering Syllabi (1312)
- Computer Science Faculty Publications (928)
- Computer Science Faculty Research & Creative Works (919)
- Departmental Technical Reports (CS) (914)
- Master's Projects (859)
- Computer Science Technical Reports (772)
- The R Journal (708)
- All Computer Science and Engineering Research (683)
- All Works (675)
- Faculty Publications (663)
- C-Day Computing Showcase (653)
- Chulalongkorn University Theses and Dissertations (Chula ETD) (618)
- Dissertations (568)
- Electronic Theses and Dissertations (567)
- Kno.e.sis Publications (542)
- Journal of Digital Forensics, Security and Law (536)
- CCAC Theses and Dissertations (512)
- Walden Dissertations and Doctoral Studies (469)
- Computer Science Faculty Publications and Presentations (404)
- Theses (403)
- USF Tampa Graduate Theses and Dissertations (378)
- Neutrosophic Systems with Applications (375)
- Computer Science and Engineering Theses - Archive (365)
- Computer Science: Faculty Publications (364)
- Browse all Theses and Dissertations (359)
- Publication Type
Articles 2521 - 2550 of 63009
Full-Text Articles in Computer Sciences
Privacy In Flux: A 35-Year Review Of Trends, Legal Evolution, And Emerging Challenges, Kong Phang, Jihene Kaabi
Privacy In Flux: A 35-Year Review Of Trends, Legal Evolution, And Emerging Challenges, Kong Phang, Jihene Kaabi
Research & Publications
Privacy harms have expanded alongside rapid technological change, challenging the adequacy of existing regulatory frameworks. This systematic review (1990–2025) systematically maps documented privacy harms to specific legal mechanisms and observed enforcement outcomes across jurisdictions, using PRISMA-guided methods and ROBIS risk-of-bias assessment. We synthesize evidence on major regimes (e.g., GDPR, COPPA, CCPA, HIPAA, GLBA) and conduct comparative legal analysis across the U.S., E.U., and underexplored regions in Asia, Latin America, and Africa. Key findings indicate increased recognition of data subject rights, persistent gaps in cross-border data governance, and emerging risks from AI/ML/LLMs, IoT, and blockchain, including data breaches, algorithmic discrimination, and …
High Frequency Dc-Dc Converter Design Optimization, Modeling And Control Based-Wbg Technology., Salah Ahmed Abdullah Eltief
High Frequency Dc-Dc Converter Design Optimization, Modeling And Control Based-Wbg Technology., Salah Ahmed Abdullah Eltief
Electronic Theses and Dissertations
The performance of DC-DC power converters is a cornerstone of modern electric vehicle (EV) powertrains, directly governing overall system efficiency, size, cost, and reliability. This dissertation presents a comprehensive performance analysis and optimization of DC-DC converter topologies to determine the most suitable design for high voltage EV applications. The evaluation rigorously compares efficiency, power losses, and physical size under a range of harsh operating conditions. A primary objective is to leverage Wide Bandgap (WBG) semiconductors, specifically Silicon Carbide (SiC), to push the performance boundaries of power conversion. While SiC devices are known for their superior material properties, a clear understanding …
From Vulnerability To Robustness: A Survey Of Patch Attacks And Defenses In Computer Vision, Xinyun Liu, Ronghua Xu
From Vulnerability To Robustness: A Survey Of Patch Attacks And Defenses In Computer Vision, Xinyun Liu, Ronghua Xu
Michigan Tech Publications
Adversarial patch attacks have emerged as a powerful and practical threat to machine learning models in vision-based tasks. Unlike traditional perturbation-based adversarial attacks, which often require imperceptible changes to the entire input, patch attacks introduce localized and visible modifications that can consistently mislead deep neural networks across varying conditions. Their physical realizability makes them particularly concerning for real-world security-critical applications. In response, a growing body of research has proposed diverse defense strategies, including input preprocessing, robust model training, detection-based approaches, and certified defense mechanisms. In this paper, we provide a comprehensive review of patch-based adversarial attacks and corresponding defense techniques. …
Archaeological Predictive Meta-Modeling In Pre-Columbian Mexico, Peter Stamm
Archaeological Predictive Meta-Modeling In Pre-Columbian Mexico, Peter Stamm
Electronic Theses and Dissertations
Archaeological Predictive Modeling stands firmly as an important tool for Archaeologists to predict undiscovered sites from civilizations all across the globe. While powerful, this methodology is not without its own set of qualms. Striking a balance between pure a data-driven approach while also observing leading expert theories can be a complicated task. Going further, deciding on the specific domain of features to emphasize or overlook can be a challenge within itself, as one misstep can drastically change the output of model, sometimes for the worst. In addition, creating models that can expose their reasoning process can be rather difficult to …
Non-Invasive Infection Detection Framework: Smartphone-Based Hematologic And Thermal Biomarker Monitoring, Nafi Us Sabbir Sabith
Non-Invasive Infection Detection Framework: Smartphone-Based Hematologic And Thermal Biomarker Monitoring, Nafi Us Sabbir Sabith
Dissertations (1934 -)
Infectious diseases remain one of the leading global causes of illness and death in both community and hospital settings. Infections lead to lasting health issues, such as life-threatening chronic conditions or even cancer. Early detection is crucial for timely intervention, such as isolation and treatment. Hematology originated from the Greek word haima, meaning blood. It is a unique discipline in medicine that involves the study of blood and its contents. White blood cells (WBC) are at the forefront of the body’s immune system. WBCs are categorized into five main subtypes: neutrophils, lymphocytes, monocytes, eosinophils, and basophils. Monitoring the total WBC …
Enhancing Recommendation Performance Via Stacking Ensemble And Synthetic Data Augmentation, Zahraa Yaareb Hani, Mohsin Hasan Hussein
Enhancing Recommendation Performance Via Stacking Ensemble And Synthetic Data Augmentation, Zahraa Yaareb Hani, Mohsin Hasan Hussein
Karbala International Journal of Modern Science
Recommendation systems are essential tools that primarily aim to help users navigate through a large volume of information. They simplify the decision-making process by suggesting relevant items based on users’ historical behaviour. However, their performance is often affected by common problems such as data sparsity. This work proposes a stacking-based ensemble recommendation system that integrates multiple machine learning models to enhance the model’s predictive performance. A new synthetic data augmentation technique is introduced to address the sparsity issue in the user–item rating matrix. This method uses the Naïve Bayes algorithm to predict additional ratings for each user. These are then …
Novel Eco-Friendly Synthesis Of Coo Nps: Evaluation Of Their Diode Laser-Enhanced Inhibitory Activity Through Combined In Silico And In Vitro Approaches., Arshad Mahdi Hamad, Sahar Naji Rashid
Novel Eco-Friendly Synthesis Of Coo Nps: Evaluation Of Their Diode Laser-Enhanced Inhibitory Activity Through Combined In Silico And In Vitro Approaches., Arshad Mahdi Hamad, Sahar Naji Rashid
Karbala International Journal of Modern Science
In our study, for the first time worldwide, to the best of our knowledge, cobalt oxide nanoparticles (CoO NPs) were synthesized using naringin (Nar) extracted from citrus peels. The properties of the prepared Nar-CoO NPs were studied using field emission scanning electron microscopy (FESEM), energy dispersive X-ray spectroscopy (EDX), ultraviolet-visible (UV-Vis), X-ray diffraction (XRD), and Fourier transform infrared (FTIR) spectroscopy. All the test results demonstrated the efficiency and success of the nanofabrication process. The solution was then exposed to three types of diode lasers: red (650 nm), green (532 nm), and blue (405 nm). The purpose of this study was …
Insider Threat: A Case Study Of The Maroochy Water Services Attack, Samuel Rector
Insider Threat: A Case Study Of The Maroochy Water Services Attack, Samuel Rector
Cybersecurity Undergraduate Research Showcase
In 2000, a former employee at Hunter Watertech went rogue and caused a spill of 800,000 liters of sewage. He leveraged his insider knowledge and access to stolen equipment in order to seek retribution for the company that wronged him. After three months of torment police arrested him and an investigation and many studies were done on the incident. A consensus remains that much of this chaos was preventable with simple cybersecurity implementations.
Behavioral Detection Methods For Automated Mcp Server Vulnerability Assessment, Christian Coleman
Behavioral Detection Methods For Automated Mcp Server Vulnerability Assessment, Christian Coleman
Cybersecurity Undergraduate Research Showcase
The Model Context Protocol (MCP) has emerged as a critical standard for connecting AI agents to external data sources and tools. Still, its adoption has introduced significant security vulnerabilities across multiple attack surfaces. While recent research has catalogued extensive vulnerability taxonomies and attack implementations, automated detection methodologies remain limited. Current detection tools primarily employ static code analysis, which fails to identify behavioral vulnerabilities that only manifest during runtime server interactions. This study explores behavioral detection approaches for identifying MCP server vulnerabilities through systematic query-based testing, with particular emphasis on context manipulation techniques. Preliminary analysis of existing vulnerability research reveals 48 …
Unless Ai Washes The Dishes, Can We Really Call It Intelligent?, Essraa Nawar
Unless Ai Washes The Dishes, Can We Really Call It Intelligent?, Essraa Nawar
Library Articles and Research
"A few weeks ago, I found myself sitting with a question that keeps resurfacing as AI becomes louder, faster, and everywhere. What happens when the models know everything about our lives except the one thing that matters most in the moment. It is remarkable how much of human decision making is driven not by external information but by internal states. A tightening in the chest. A sudden clarity. A quiet discomfort that redirects us before we can explain why. These signals guide our choices in ways computation cannot replicate."
Creating An Iot User Centric Security And Privacy Label, Luke Joseph Gleba
Creating An Iot User Centric Security And Privacy Label, Luke Joseph Gleba
Theses and Dissertations
Concerns for cybersecurity awareness and training in the public have been rising at astronomical rates over the past few years. People globally have entered a critical intersection with computers. Computers are being used in everyday life, and users do not have an easy way to understand their own cyber risk. Consumers deserve to know how secure their new Internet of Things (IoT) system is in a quick, efficient way before they purchase the device and while they own it. The following research looks to improve on ideas for the criteria and the development of a security label. Few prototypes currently …
Mimar-Net: Multiscale Inception-Based Manhattan Attention Residual Network And Its Application To Underwater Image Super-Resolution, Nusrat Zahan, Sidike Paheding, Ashraf Saleem, Timothy C. Havens, Peter C. Esselman
Mimar-Net: Multiscale Inception-Based Manhattan Attention Residual Network And Its Application To Underwater Image Super-Resolution, Nusrat Zahan, Sidike Paheding, Ashraf Saleem, Timothy C. Havens, Peter C. Esselman
Michigan Tech Publications
In recent years, Single-Image Super-Resolution (SISR) has gained significant attention in the geoscience and remote sensing community for its potential to improve the resolution of low-quality underwater imagery. This paper introduces MIMAR-Net (Multiscale Inception-based Manhattan Attention Residual Network), a new deep learning architecture designed to increase the spatial resolution of input color images. MIMAR-Net integrates a multiscale inception module, cascaded residue learning, and advanced attention mechanisms, such as the MaSA layer, to capture both local and global contextual information effectively. By utilizing multiscale processing and advanced attention strategies, MIMAR-Net allows us to handle the complexities of underwater environments with precision …
Game Hacking & Anti-Cheat Analysis, Quang Hoang
Game Hacking & Anti-Cheat Analysis, Quang Hoang
Cybersecurity Undergraduate Research Showcase
Reverse engineering and analyzing game hacking and anti-cheat mechanisms is a complex and evolving field. This research document explores the history of game hacking, various techniques used in game hacking, and the countermeasures implemented by anti-cheat systems. Through case studies, we illustrate the strategies involved in creating cheats. Specifically, we demonstrate how to hack the open-source game AssaultCube using memory editing and code injection techniques available in Cheat Engine in a step-by-step manner so that the reader can theoretically reproduce the results shown in this paper. We also dissect the game’s anti-cheat mechanisms, identifying their strengths and weaknesses. This document …
Fair Use In The Age Of Generative Ai: Navigating Copyright Challenges In Educational Contexts, Wendy Wallberg
Fair Use In The Age Of Generative Ai: Navigating Copyright Challenges In Educational Contexts, Wendy Wallberg
Faculty and Staff Publications & Presentations
Generative AI tools are everywhere, but what’s actually allowed when it comes to copyright and teaching? This session breaks down what fair use means in the age of AI, covers current legal cases, and offers practical tools to help educators and institutions use AI responsibly and confidently.
A Usv Path Planning Algorithm Under Special Environment Based On Td3-Rrt, Jitong Chen, Jiajia Zhou, Di Wu, Hailong Jiang
A Usv Path Planning Algorithm Under Special Environment Based On Td3-Rrt, Jitong Chen, Jiajia Zhou, Di Wu, Hailong Jiang
Journal of System Simulation
Abstract: In view of USV path planning in special environments such as multiple obstacles, large-size obstacles, and narrow passages, the rapidly-exploring random tree (RRT) algorithm suffers from drawbacks such as a large sampling base, low success rate, and zigzagging planned path. To address these problems, a global path planning algorithm (TD3-RRT) was proposed based on the twin delayed deep deterministic policy gradient (TD3). The USV path search model was established by combining the RRT algorithm with deep reinforcement learning. Forward looking detection was used to sense the environment to adaptively adjust the step size. The path search direction was exported …
Auv Path Planning Based On Behavior Cloning And Improved Dqn In Partially Unknown Environments, Lijing Xing, Min Li, Xiangguang Zeng, Ping Zhang, Bei Peng
Auv Path Planning Based On Behavior Cloning And Improved Dqn In Partially Unknown Environments, Lijing Xing, Min Li, Xiangguang Zeng, Ping Zhang, Bei Peng
Journal of System Simulation
Abstract: To address the problems of large randomness and slow convergence of the DQN dynamic path planning algorithm for a single autonomous underwater vehicle (AUV) in a partially unknown environment, a path planning method combining behavior cloning with A* algorithm and DQN (BA_DQN) was proposed. Based on the known environmental information, an improved A* algorithm incorporating ocean current resistance was proposed to guide DQN, thereby reducing the randomness of the DQN algorithm. By considering the complexity of the marine environment, the sampling probability was improved again after expanding the positive experience pool to enhance the training success rate. To address …
Twin Modeling Of Gearbox Fault Early Warning System Based On Spatio-Temporal Characteristics, Yuanxing Tian, Zeyin Han, Ning Wang, Baoding Su, Weilin Xiang
Twin Modeling Of Gearbox Fault Early Warning System Based On Spatio-Temporal Characteristics, Yuanxing Tian, Zeyin Han, Ning Wang, Baoding Su, Weilin Xiang
Journal of System Simulation
Abstract: The wind turbine gearbox cannot effectively collect vibration signals under complex faults, which leads to the decline of fault early warning accuracy of wind turbine gearbox. To address this issue, this study investigated the twin modeling of gearbox fault early warning system based on spatio-temporal characteristics. Through the information acquisition subsystem and optical fiber sensing technology, the time sequence and spatial position data of the wind turbine gearbox during operation were collected in real time to obtain spatio-temporal characteristic data. By using the twin space, the collected spatiotemporal characteristic data of the gearbox were transmitted to the virtual space. …
Path Planning For Mobile Robots Based On Improved Artificial Potential Field Algorithm, Chi Zhang, Wei Wei
Path Planning For Mobile Robots Based On Improved Artificial Potential Field Algorithm, Chi Zhang, Wei Wei
Journal of System Simulation
Abstract: In view of the problems of unreachable target areas and easy local minima in traditional artificial potential field methods, an improved artificial potential field method was proposed. The improved algorithm optimized the repulsive field function by introducing obstacle angle factors and distance factors to control the repulsive force magnitude. At the same time, an additional repulsive force towards the target point was added to solve the problem of unreachable target areas in traditional algorithms. When the robot fell into a local minimum, by introducing turning towards obstacles and turning factors to accurately apply escape forces to the robot, the …
Dynamic Supernetwork Modeling Of Command Information System Based On Task Timing, Xuehuan Qiu, Zhiming Dong, Liang Li, Zhuoli Liu
Dynamic Supernetwork Modeling Of Command Information System Based On Task Timing, Xuehuan Qiu, Zhiming Dong, Liang Li, Zhuoli Liu
Journal of System Simulation
Abstract: Due to the difficulty in reflecting the various information activities and interactions within the command information system using general modeling methods for complex system structure, the advantages of supernetwork in characterizing node heterogeneity and link multiplicity of the system were utilized. Based on the research on the mapping mechanism of the command information system across three domains, the dynamic and multifunctional properties of the functional network structure were analyzed. A dynamic supernetwork model based on task timing was constructed considering task requirements, providing model support for further research on complex interaction relationships in the command information system. The dynamic …
Implementation And Assessment Of The Openbci Platform As An Accessible Brain- Computer Interface, Jewell Norris
Implementation And Assessment Of The Openbci Platform As An Accessible Brain- Computer Interface, Jewell Norris
Honors Theses
OpenBCI is a low-cost, open-source platform for alternative brain-computer interface (BCI) software and hardware. This thesis evaluates OpenBCI’s electroencephalogram (EEG) and electromyography (EMG) capabilities by constructing and testing a 16-channel EEG system using the Ultracortex Mark IV headset and Cyton + Daisy biosensing board. The viability of the system was assessed through real-time BCI control and comparison to a clinical-grade EEG system. Real-time BCI control of an online falling-block game was tested via the use of eye blinks EMG (channels Fp1/Fp2) and head-tilt accelerometer inputs. The BCI game demonstrated reliable control despite minor latency and artifact sensitivity. For clinical comparison, …
Improvement Of Slam Localization Accuracy In Ar By Enhancing Yolov8, Jia Liu, Zengwei Zhang, Dapeng Chen, Nanxuan Huang, Bin Wang, Hong Song
Improvement Of Slam Localization Accuracy In Ar By Enhancing Yolov8, Jia Liu, Zengwei Zhang, Dapeng Chen, Nanxuan Huang, Bin Wang, Hong Song
Journal of System Simulation
Abstract: In the presence of dynamic interference in the environment, traditional simultaneous localization and mapping (SLAM) methods often experience reduced precision and stability in the registration of virtual objects during three-dimensional registration in augmented reality (AR). To address these issues, an improved method for dynamic scenes based on semantic segmentation and optical flow tracking was proposed. The convolutional block attention module (CBAM) attention mechanism was incorporated into YOLOv8 to enhance its focus on dynamic objects in the environment, thereby improving detection performance and accuracy. The semantic segmentation functionality of the improved YOLOv8 was integrated into the front-end of ORB-SLAM3 to …
Cooperative Guidance Method Considering Impact Time And Area Sealing, Zheng Guo, Guofei Li, Hua Xiong, Yunjie Wu
Cooperative Guidance Method Considering Impact Time And Area Sealing, Zheng Guo, Guofei Li, Hua Xiong, Yunjie Wu
Journal of System Simulation
Abstract: To address the problem of multi-vehicle cooperative strike against maneuvering targets, a cooperative guidance method considering impact time control and terminal area sealing was proposed. The distributed disturbance observer was utilized to estimate target maneuvers. Based on the consensus errors of the impact time, the cooperative guidance law in the line-of-sight direction was proposed to achieve simultaneous hits on targets at a specified time. By considering the motion states of targets, the instructions of the terminal area sealing were designed to construct the sliding mode surface and design the line-of-sight guidance law, so as to ensure the convergence of …
Optimization Of Service Caching And Computation Offloading In Digital Twin Cloud-Edge Networks, Jiayu Zheng, Zhuxue Mai, Zheyi Chen
Optimization Of Service Caching And Computation Offloading In Digital Twin Cloud-Edge Networks, Jiayu Zheng, Zhuxue Mai, Zheyi Chen
Journal of System Simulation
Abstract: In mobile edge computing (MEC), to satisfy diverse user demands by jointly optimizing service caching and computation offloading and address low-efficiency resource utilization caused by irrational resource allocation, this paper proposed a novel joint optimization of service caching and computation offloading with a convex-optimization-enabled deep reinforcement learning (JCO-CR) method. Additionally, a new model for digital twin cloud-edge networks (DTCEN) was constructed. The joint optimization of service caching and computation offloading was decoupled into two sub-problems, which were solved by an improved deep reinforcement learning method and convex optimization theory, respectively. Simulation experiments demonstrate that the proposed JCO-CR method …
Attitude Control Of Quadrotor Uav Based On Disturbance Observer And Command Filtering, Boning Li, Ming Chen, Shuchang Qi, Haoran Meng, Lei Wang
Attitude Control Of Quadrotor Uav Based On Disturbance Observer And Command Filtering, Boning Li, Ming Chen, Shuchang Qi, Haoran Meng, Lei Wang
Journal of System Simulation
Abstract: A finite-time fault-tolerant control scheme based on backstepping was proposed for the attitude tracking control problem of quadrotor UAVs. A finite-time neural network disturbance observer was designed, which could quickly compensate for the impacts of actuator failures and external disturbances, thereby enhancing the system's robustness. A first-order command filter and a compensation mechanism were introduced, which could avoid the computational complexity caused by differentiating the virtual control law and eliminate the influence of filtering errors. The hyperbolic tangent function was selected as the constraint function for the input torque, which restricted the input signal to prevent excessive magnitude …
Research On Cgf-Oriented Natural Language Interaction Framework, Xinmeng Li, Kai Xu, Yue Hu, Hesong Huang, Quanjun Yin
Research On Cgf-Oriented Natural Language Interaction Framework, Xinmeng Li, Kai Xu, Yue Hu, Hesong Huang, Quanjun Yin
Journal of System Simulation
Abstract: To address the mismatch between existing natural language interaction frameworks and training tasks in simulation-based military training, which limits smooth interaction between trainees and Computer Generated Forces (CGF), this paper proposes a Natural Language Interaction framework for Computer Generated Forces (NLI4CGF). The framework analyzes the logic and functional requirements of natural language interaction between trainees and CGF, and establishes an interaction architecture tailored for military simulation training scenarios. It supports semantic parsing and knowledge query tasks within a prototype system developed for infantry squad simulation training. Experimental results demonstrate that the proposed model performs effectively, meets the requirements of …
Preparing For The Artificial Intelligence (Ai) Economy In The Mountain West, 2025, Kian Parikh, Taylor Volk, Maisoon Faris, Kristian Thymianos, William E. Brown Jr.
Preparing For The Artificial Intelligence (Ai) Economy In The Mountain West, 2025, Kian Parikh, Taylor Volk, Maisoon Faris, Kristian Thymianos, William E. Brown Jr.
Economic Development & Workforce
This fact sheet presents data from the Brainly report, “Here Are the States Most (and Least) Prepared to Win the AI Race in 2025” for the five Mountain West states of Arizona, Colorado, New Mexico, Nevada, and Utah. This fact sheet highlights the national and individual rankings of four key metrics for each Mountain West state: the fixed percentage of businesses using artificial intelligence (AI); the number of AI jobs per 1,000 workers; the number of AI-related degrees per 10,000 people ages 20-24; and federal funding for small business technology innovation per $1 million of gross domestic product (GDP).
Quality Assessment Of Pathology Board-Exam-Style Mcqs Produced By Chatgpt3.5: A Comparative Study, Arianna B. Morton, Zunaira Naeem, Allison F. Goldberg, Alexis R. Peedin, Joanna Chan
Quality Assessment Of Pathology Board-Exam-Style Mcqs Produced By Chatgpt3.5: A Comparative Study, Arianna B. Morton, Zunaira Naeem, Allison F. Goldberg, Alexis R. Peedin, Joanna Chan
Department of Pathology, Anatomy, and Cell Biology Faculty Papers
Residents preparing for pathology board exams frequently use multiple-choice questions (MCQs) from question banks (QBs) like PathDojo and PathPrimer, which can be costly. ChatGPT, a free tool, has been used to generate MCQs for other tests like the SAT. This study compared the quality of pathology MCQs created by ChatGPT versus commercially available study questions for the American Board of Pathology’s (ABPath) certifying exams. A rubric adapted from the National Board of Medical Examiners’ (NBME) question writing guide was validated by two pathologists using commercially available pathology board exam questions. This rubric was then used to evaluate MCQs from commercially …
Parking Space Reasoning Model For Complex Scenarios, Congling Zhou, Chunpeng Wang, Qiwei Xie, Yongqiang Wang, Lijun Shen
Parking Space Reasoning Model For Complex Scenarios, Congling Zhou, Chunpeng Wang, Qiwei Xie, Yongqiang Wang, Lijun Shen
Journal of System Simulation
Abstract: In the industrialization process of the combined driving assistance system, complex parking environments bring many challenges, such as occlusion of parking spaces, uneven lighting, and missed and false detections. To address these issues, a parking space reasoning model named PIPS-Net was proposed through PINet optimization. In terms of network architecture design, the model deeply integrated the stacked hourglass network with the recurrent feature-shift aggregator (RESA) to construct a context feature extraction architecture, which enhanced the feature reasoning ability in complex scenarios. Meanwhile, it reconstructed the output to meet the requirements of parking space detection tasks, thereby jointly improving the …
Research On Vehicle Path Optimization Algorithms For Urban Logistics And Distribution, Zhenpeng Ma, Hanyang Jiao, Zhe Zhang, Cheng Liu, Bo Jiang, Lin Wang
Research On Vehicle Path Optimization Algorithms For Urban Logistics And Distribution, Zhenpeng Ma, Hanyang Jiao, Zhe Zhang, Cheng Liu, Bo Jiang, Lin Wang
Journal of System Simulation
Abstract: Existing optimization algorithms for solving the vehicle routing problem with time windows (VRPTW) are prone to fall into local optimal solutions and have slow convergence speed. To address this issue, a K-means clustering algorithm and improved large neighborhood search algorithm (K-means-ILNSA) was proposed. A strategy of clustering before optimization was adopted, and the K-means algorithm was adopted to group the customers to be delivered, so as to improve the optimization efficiency. The genetic algorithm was adopted to optimize each group of customers generated by clustering separately to initially plan the distribution routes. The large neighborhood search (LNS) algorithm was …
Bayesian Network Parameter Learning Based On Ahp-Dst Fusion Of Expert Prior Knowledge, Haiyang Chen, Hongkai Lin, Zhifang Ren, Jing Liu, Jing Zhang
Bayesian Network Parameter Learning Based On Ahp-Dst Fusion Of Expert Prior Knowledge, Haiyang Chen, Hongkai Lin, Zhifang Ren, Jing Liu, Jing Zhang
Journal of System Simulation
Abstract: Aiming at the problem of low accuracy of BN parameter learning due to the uncertainty of a single expert prior knowledge under the condition of small sample data set, a BN parameter learning method based on AHP-DST fusion expert prior knowledge was designed. The synthetic prior knowledge of experts was calculated by using the thought of analytic hierarchy process combined with the rules of evidence theory synthesis. The expert comprehensive prior knowledge was added to the normal distribution and combined with the monotonicity constraint to obtain the virtual sample information. The virtual sample information was added to the Bayesian …