Ai Literacy: An Annotated Oer Bibliography,
2026
University of Nevada, Las Vegas
Ai Literacy: An Annotated Oer Bibliography, Houy Yvonne
UNLV Best Teaching Practices Expo
"Scalable, discipline-agnostic AI literacy instruction can be implemented incrementally without requiring full course redesign in higher education, supporting both technical understanding and critical engagement with the social and ethical dimensions of AI: The curated list of open educational resources (OER) on this poster enable a flexible, modular approach to teaching foundational AI literacy. The annotated list includes self-paced, hands-on projects with complementary educator-guided activities and discussion to support conceptual understanding of machine learning, training data, and algorithmic bias, drawing on OER such as Code.org’s AI curriculum, MIT RAISE’s Day of AI, and the multi-lingual Elements of AI course. Many resources …
Ai-Driven Multispectral Drone Monitoring For Afforestation In Arid Environments,
2026
Chapman University
Ai-Driven Multispectral Drone Monitoring For Afforestation In Arid Environments, Hesham Morgan, Ali Elgendy, Brandon Tran, Tamer Ismail, Mohamed M. Moursy, Yehya Kh. Shehadeh, Ahmed Elgharib, Ahmed Abdullah Al-Dughairi, Ali El Mubarak, Khaled Allam Harhash, Hesham El-Askary
Mathematics, Physics, and Computer Science Faculty Articles and Research
Monitoring large-scale afforestation projects in arid and semi-arid environments requires accurate, high-resolution, and repeatable methods to assess tree survival and growth. In this study, we integrated unmanned aerial vehicle (UAV) multispectral imaging with an advanced object detection framework to evaluate vegetation establishment in the Shuayb Al-Budai afforestation site, part of the Imam Turki bin Abdullah Royal Natural Reserve, Kingdom of Saudi Arabia (KSA). Multispectral datasets were acquired using a MicaSense Altum-PT sensor and processed through a masked Region-based Convolutional Neural Network (RCNN) with two backbone architectures: ResNet-101 and VGG19-BN. The Mask R-CNN–ResNet-101 model achieved superior performance, with an overall accuracy …
A Deep Learning-Based Approach For Bot Detection In Trending Hashtags On X,
2026
Department of Robotics & Artificial Intelligence, University is Shaheed Zulfikar Ali Bhutto Institute of Science and Technology, Islamabad 44090, Pakistan
A Deep Learning-Based Approach For Bot Detection In Trending Hashtags On X, Mehboob Hussain, Muhammad Rizwan Rashid Rana, Muhammad Imran, Muhammad Shoaib, Muhammad Hasaan Mujtaba
Makara Journal of Technology
The widespread presence of bots on social media platforms, such as X (formerly Twitter), poses a significant threat to the integrity of online information by facilitating the dissemination of misinformation and manipulating public discourse. This study proposes a robust deep learning-based framework, DeepBot, to detect bot participation in trending hashtags and discussions on X. The approach uses a dataset sourced from Kaggle, comprising user profile metadata, including follower count, tweet frequency, account verification status, and engagement metrics. The data were subjected to comprehensive preprocessing, including noise removal, part-of-speech (POS) tagging, and word embedding using the pre-trained GloVe model. RoBERTa is …
Cognition Is Not Content: A Structural Account Of Processing Conditions,
2026
CUNY Lehman College
Cognition Is Not Content: A Structural Account Of Processing Conditions, Griselda Poe
Publications and Research
Human cognition has been described in terms of content. This description becomes insufficient once artificial systems make output observable apart from subject attribution, intention, and relational context. Under this contrast condition, what becomes visible is a layered structure in which output, reconstruction, evaluation, and termination do not necessarily coincide. The same input may register as complete under one processing condition while remaining unresolved under another. This separability means that content-based description does not merely omit an additional variable: it can mislocate a processing difference as a difference in meaning, personality, intention, ability, or attitude. This is not a proposal for …
The Role Of Human-Centered Artificial Intelligence In Crewed Mars Missions,
2026
Lynn University
The Role Of Human-Centered Artificial Intelligence In Crewed Mars Missions, Jordan Neuman
Student Publications and Presentations
The suggestion of implementing Artificial Intelligence (AI) in crewed missions to the Martian surface can revolutionize mission operations, psychological support, and ethical decision‑making under challenging conditions. This study is a structured, qualitative literature review of current AI research for the future of human space exploration. It uses publicly available peer‑reviewed journal articles and NASA/ESA technical reports on AI for Mars missions. Using Perplexity, the researcher first prompted the AI tool to identify recurring topics across these sources and generate themes. The researcher independently reviewed all sources to confirm and refine those themes. Three themes—mission autonomy, local resource utilization and life‑support, …
Dynamic-Query Robustness Of Ann Indexes Under Time-Indexed Drift,
2026
Harrisburg University of Science and Technology
Dynamic-Query Robustness Of Ann Indexes Under Time-Indexed Drift, Stellamaris Nakacwa, Majid Shaalan
Harrisburg University Other Works
Approximate nearest-neighbor search is a central retrieval primitive in dense question-answering and retrieval-augmented generation systems. Existing ANN evaluation protocols typically measure recall, latency, throughput, and search-effort sensitivity under a fixed-query assumption: a query vector is submitted to an index, approximate neighbors are retrieved, and the result is compared with exact nearest-neighbour ground truth. This assumption is appropriate for conventional vector-search benchmarking, but it is less complete for multi-step, distributed, and agent-controlled retrieval pipelines in which the retrieval-facing query may be refined, recomputed, or displaced across execution steps. This paper introduces a time-driven dynamic query evaluation framework for ANN search. The …
Temperature-Induced Uncertainty In Fixed-Context Retrieval-Augmented Generation,
2026
William & Mary
Temperature-Induced Uncertainty In Fixed-Context Retrieval-Augmented Generation, Steven Zeng, Murat Kuzlu
Cybersecurity Undergraduate Research Showcase
This study examines how decoding temperature affects output uncertainty in a fixed-context retrieval-augmented generation (RAG) system. We define uncertainty as the semantic dispersion among repeated answers under the same fixed retrieved context, with greater dispersion interpreted as higher uncertainty. To isolate this answer-generation variability from retrieval drift, each question was paired with a fixed retrieved context, and repeated generations differed only in temperature. The experiment used nine questions drawn from a machine-learning textbook corpus, with three questions each at easy, moderate, and hard difficulty. Each question was evaluated at five temperatures (0.0, 0.25, 0.5, 0.75, and 1.0) over 30 iterations, …
Method For Testing And Evaluating Intelligence Level Of Virtual Forces Based On Operational Experiments,
2026
Army Arms University of PLA, Beijing 100072, China; PLA 32302 TroopsArmy Arms University of PLA, Beijing 100072, China; PLA 32302 Troops
Method For Testing And Evaluating Intelligence Level Of Virtual Forces Based On Operational Experiments, Dayong Liu, Zhiming Dong, Weidong Zhang, Wenjun Zhang, Jiancheng Gao
Journal of System Simulation
Abstract: The intelligence level of virtual forces is a key factor affecting the credibility and effectiveness of tactical confrontation simulations. To address the current lack of a testing and evaluation system, a method for testing and evaluating the intelligence level of virtual forces based on operational experiments is proposed. Guided by operational experiment theory, the method stimulates the intelligent behavior of virtual forces by constructing dynamic confrontation environments, and collects, calculates, analyzes, and evaluates their intelligence performance data according to a systematic process. The overall architecture, logical functional modules, and basic evaluation process of the method are designed. A "4M" …
Research On Control Of Coaxial Dual-Rotor Unmanned Aerial Vehicle Based On Improved Reaching Law,
2026
Key Laboratory of Reliability Technology Research for Electromechanical Products, Zhejiang Sci-Tech University, Hangzhou 310018, China
Research On Control Of Coaxial Dual-Rotor Unmanned Aerial Vehicle Based On Improved Reaching Law, Xinhang Chen, Xiaodong Ling, Chengchang Lang, Shijun Zheng, Yiqi Tang
Journal of System Simulation
Abstract: To address the issues of significant chattering, slow convergence speed, and large overshoot in the control system of a coaxial dual-rotor unmanned aerial vehicle, a control method based on an improved double-power and hyperbolic function integral sliding mode reaching law was proposed. A novel reaching law was designed to achieve fast convergence when the system state is far from the sliding surface and smooth transition when approaching the sliding surface, thereby enhancing the overall convergence speed of the system and ensuring that the system reaches the sliding surface within a finite time. The saturation characteristic of the hyperbolic function …
Large Language Model For X Language Simulation: Architecture, Key Technologies, And Typical Applications,
2026
School of Information Science and Technology, Beijing University of Chemical Technology, Beijing 100020, China
Large Language Model For X Language Simulation: Architecture, Key Technologies, And Typical Applications, Laichunyang Peng, Fei Ye, Xiaoming Guo, Jinglin Zhou
Journal of System Simulation
Abstract: General-purpose large language models lack training on X language-specific corpora, and traditional fine-tuning methods lack targeted adaptation to the interdisciplinary integration and multimodule coupling of X language, resulting in problems such as non-standard syntax and semantic deviation in generated code. To address these issues, this paper systematically proposed the definition and integrated architecture of a large language model for X language simulation. Modeling subclasses were defined according to the disciplines and classes of X language, and dedicated adapters were constructed for each subclass. By merging their weights during the inference phase, the incremental integration of multi-domain modeling skills was …
Vehicle Routing Optimization For Underground Mines Considering Fuzzy Demand And Time Tolerance,
2026
School of Mechatronics Engineering, Anhui University of Science and Technology, Huainan 232001, China
Vehicle Routing Optimization For Underground Mines Considering Fuzzy Demand And Time Tolerance, Guorong Wang, Haishun Deng, Ziming Kou, Xuanxuan Yan, Zhixiang Huang
Journal of System Simulation
Abstract: To solve the problem of material demand fluctuation and different time windows in auxiliary transportation of underground mines, a routing optimization method for material distribution considering fuzzy demand and time tolerance was proposed. Based on the fuzzy credibility theory, uncertain demand was constrained by fuzzy chance constraints, and a multi-objective routing optimization model for underground mine auxiliary transportation was constructed with the objectives of minimizing the total operating cost of vehicles and maximizing time tolerance. A multi-objective genetic algorithm with mixed dominance strength was designed to solve the model. By calculating the deviation difference of Pareto frontier solutions, …
Auv Path Planning Integrating Local-Global Strategies In Unknown Environments,
2026
School of Computer Science and Technology, Harbin Institute of Technology (Weihai), Weihai 264209, China
Auv Path Planning Integrating Local-Global Strategies In Unknown Environments, Wenlong Meng, Yanbo Pu, Ya Gong
Journal of System Simulation
Abstract: Existing path planning algorithms often struggle to efficiently explore and generate high-quality trajectories. To address this issue, this paper proposes a path planning algorithm that integrates local-global strategies. By employing the rolling window technique, the global one-time path planning problem is transformed into an iterative process of multiple local planning stages. During the global exploration phase, the rolling window is used to determine high-level path branches and to identify branch waypoints, thereby refining the calculation of local paths. In the local exploration phase, an improved RRT-Connect algorithm is proposed, which combines adaptive circular sampling with dynamic step length to …
Modelling Method Of Unmanned Vehicle Dynamics Based On Neural Network,
2026
Intelligent Game and Decision Lab (Military Intelligence Institute), Beijing 100001, China
Modelling Method Of Unmanned Vehicle Dynamics Based On Neural Network, Jun Wang, Min Liu, Xiaochuan Zhang, Yishan Ding, Juhui Feng, Ye Zhuang
Journal of System Simulation
Abstract: To address the challenges of high data acquisition costs of test data on dynamic characteristics between tires and soft terrain and low speed of numerical calculation for unmanned vehicles in complex terrestrial environments, a modeling method of unmanned vehicle dynamics based on a neural network was proposed. Tire-terrain contact dynamics models were built by using discrete element method (DEM) simulations for tire-terrain contact and experimental data, thereby creating a dataset of tire contact forces for various tire materials in terrestrial environments. The neural network was applied to regressively learn the dataset, and a nonlinear neural network tire model was …
Large-Scale Multi-Objective Evolutionary Algorithm Based On Multi-Region Dynamic Grouping,
2026
School of Computer Science and Technology, Xidian University, Xi'an 710126, China
Large-Scale Multi-Objective Evolutionary Algorithm Based On Multi-Region Dynamic Grouping, Binhao Liang, Jingxuan Wei, Fengqin Liang
Journal of System Simulation
Abstract: The decision variable dimension of large-scale multi-objective optimization problems can reach hundreds or even thousands. For existing large-scale multi-objective evolutionary algorithms based on decision variable analysis, which usually consume a large amount of computational resources for grouping and fail to consider the interactions between convergence-related variables and diversity-related variables, a large-scale multi-objective evolutionary algorithm based on multi-region adaptive dynamic grouping was proposed. The algorithm employed a Gaussian mixture model to partition the decision space into multiple regions; within each region, feature vectors were constructed for each decision variable, and spectral clustering was utilized to perform grouping. To validate …
Intelligent Competition Platform And Mode Driven By Cloud-Native Simulation,
2026
College of Systems Engineering, National University of Defense Technology, Changsha 410073, China
Intelligent Competition Platform And Mode Driven By Cloud-Native Simulation, Long Qin, Hesong Huang, Lujia Yin, Chuan Ai, Qi Zhang, Xinmeng Li
Journal of System Simulation
Abstract: To solve the problems faced by the adversarial competition mode of agents, including difficult development and deployment, low resource utilization, poor reusability, and difficulty in accessing reinforcement learning algorithms, a new agent simulation training platform was designed. The software components of the competition platform were decoupled based on cloud-native technology; a high-performance simulation engine for the competition environment was proposed; a new method of an embedded reinforcement learning model for an intelligent control terminal was designed, with multiple online and offline policy-based reinforcement learning algorithms set. The experiment demonstrates that the development and deployment of the system is efficient, …
Intersection Positioning Algorithm With Spatial Translation Based On Sar Scene Matching,
2026
Sichuan Institute of Aerospace System Engineering, Chengdu 610100, China
Intersection Positioning Algorithm With Spatial Translation Based On Sar Scene Matching, Cheng'en Pu, Yumin Lai, Rui Shi, Yan Liao, Kezi Meng, Lifeng Qu
Journal of System Simulation
Abstract: To address the problem that the positioning precision of the inertial navigation system cannot meet the requirements of autonomous positioning when the aircraft flies, an autonomous positioning method with spatial translation based on circular scanning scene matching of SAR was proposed. The spatial translation positioning model of the aircraft was established according to the position of the ground matching points obtained by single point and single circular scanning scene matching of SAR, the oblique distance between the matching points and the aircraft, and the inertial measurement information of the aircraft. The characteristic information of the matching point sequence was …
State Monitoring Of Nuclear Power Connection Sleeve Quality Inspection Equipment Driven By Digital Twin,
2026
College of Mechanical Engineering, Hebei University of Science and Technology, Shijiazhuang 050018, Chin
State Monitoring Of Nuclear Power Connection Sleeve Quality Inspection Equipment Driven By Digital Twin, Yandong Nan, Jinda Zhu, Xinbin Lu, Zhiying Qin, Dandan Qi, Zhiheng Ding
Journal of System Simulation
Abstract: To address the problems of delayed state perception, single monitoring dimension, and insufficient visualization in the quality inspection equipment for nuclear power connection sleeves, a state monitoring method driven by digital twin was proposed. A digital twin-based collaborative state monitoring framework for the inspection equipment was constructed. Based on the OPC UA technology, a multi-source information interconnection model was established. A finite state machine model was employed to discretize and logically drive the inspection process, and a hierarchical verification strategy was proposed to establish a multi-dimensional motion state monitoring mechanism. A surrogate model coupling the radial basis interpolation function …
Modeling And Simulation Of Target Characteristic Architecture Of Target Missile Based On Dodaf,
2026
PLA 63867 Troops
Modeling And Simulation Of Target Characteristic Architecture Of Target Missile Based On Dodaf, Tuo Zhao, Yuqiao Liu, Yuan Ma, Yun Cheng, Shen Li
Journal of System Simulation
Abstract: In view of the problems of incomplete elements and missing architecture in the research of target characteristics of target missiles, this paper introduced the panoramic view, operational view, and capability view models in the DoDAF from the perspective of system engineering. According to the view development sequence of "panoramic description, operational decomposition, and capability matching", a target characteristic architecture of the target missile was constructed, which included target elements such as maneuvering characteristics and infrared radiation characteristics. The mapping relationship among "operational layer, capability layer, and target characteristic layer" of the target missile was obtained, and the architecture was …
Dynamic Model-Driven Verification Framework For Modular Aerial Bomb Systems,
2026
School of Automation Engineering, University of Electronic Science and Technology of China, Chengdu 611731, China
Dynamic Model-Driven Verification Framework For Modular Aerial Bomb Systems, Wenlong Li, Shuhan Sang, Yusheng Liu, Haiyan He, Zan Liang, Wenqiang Yuan, Biao Niu, Weifeng Luo
Journal of System Simulation
Abstract: To address the problems of high verification costs, difficulty in covering dynamic behaviors, and lack of quantitative closed loops in the design stage of modular complex equipment, a dynamic model-driven modular system verification framework was proposed. Based on model-based systems engineering (MBSE) modeling, a structural coupling quantification model was constructed using the number of interfaces, signal interaction frequency, and dependency intensity. Dynamic tests were conducted in high-fidelity virtual simulation to collect data; performance rating for indicators such as accuracy, response, and stability, as well as system's comprehensive rating, were obtained, and the rating feedback was used for iterative optimization. …
Model-Based System Verification: Theoretical Framework, Key Technologies, And Future Prospects,
2026
Beijing Institute of Spacecraft System Engineering, Beijing 100094, China
Model-Based System Verification: Theoretical Framework, Key Technologies, And Future Prospects, Bo Sun, Yi Ren, Silin Wang, Qi Liu, Zhidong Li
Journal of System Simulation
Abstract: Traditional system verification methods face significant challenges in terms of efficiency, coverage, and traceability. To address these issues, this paper introduced model-based system verification (MBSV), which deeply integrated verification activities within the model-based systems engineering model system and evolution process. It presented the foundational logic of MBSV and proposed a multiview unified verification modeling strategy based on system modeling language (SysML), integrating requirements, structure, behavior, and constraints. The paper discussed the algorithms for selecting representative paths and reducing equivalent classes to enhance verification efficiency, the principles of test path search, as well as the intelligent path search mechanism based …
