Open Access. Powered by Scholars. Published by Universities.®
- Discipline
-
- Artificial Intelligence and Robotics (1401)
- Engineering (792)
- Computer Engineering (430)
- Numerical Analysis and Scientific Computing (329)
- Operations Research, Systems Engineering and Industrial Engineering (302)
-
- Social and Behavioral Sciences (271)
- Systems Science (254)
- Software Engineering (232)
- Information Security (205)
- Medicine and Health Sciences (205)
- Databases and Information Systems (199)
- Data Science (187)
- Cybersecurity (181)
- Graphics and Human Computer Interfaces (179)
- Education (165)
- Electrical and Computer Engineering (155)
- Theory and Algorithms (134)
- Business (129)
- Life Sciences (125)
- Other Computer Sciences (117)
- Programming Languages and Compilers (110)
- Arts and Humanities (96)
- Physics (92)
- Mathematics (87)
- Applied Mathematics (73)
- Statistics and Probability (72)
- Educational Technology (62)
- OS and Networks (61)
- Institution
-
- Singapore Management University (641)
- China Simulation Federation (248)
- Old Dominion University (242)
- Kennesaw State University (220)
- Missouri University of Science and Technology (108)
-
- Zayed University (87)
- Neutrosophic Systems with Applications (81)
- Edith Cowan University (54)
- Chapman University (51)
- University of Arkansas, Fayetteville (45)
- Karbala International Journal of Modern Science (44)
- University of Texas at El Paso (43)
- Air Force Institute of Technology (42)
- City University of New York (CUNY) (42)
- Michigan Technological University (41)
- University of Nebraska - Lincoln (41)
- Dartmouth College (38)
- Portland State University (37)
- Utah State University (34)
- Indian Statistical Institute (33)
- University of Texas Rio Grande Valley (32)
- Embry-Riddle Aeronautical University (31)
- University of South Carolina (30)
- Chulalongkorn University (29)
- United Arab Emirates University (29)
- Mesopotamian Academic Press (28)
- Marquette University (26)
- TÜBİTAK (26)
- University of South Alabama (26)
- Wright State University (26)
- Keyword
-
- Artificial intelligence (178)
- Machine learning (178)
- Deep learning (107)
- Artificial Intelligence (93)
- Machine Learning (93)
-
- AI (80)
- Cybersecurity (77)
- Large language models (65)
- Deep Learning (59)
- Generative AI (56)
- Large Language Models (54)
- Computer Science (40)
- Large language model (35)
- Natural language processing (35)
- Computer vision (31)
- Reinforcement learning (29)
- Security (28)
- ChatGPT (26)
- Humans (25)
- Path planning (25)
- Computer Vision (24)
- Generative artificial intelligence (24)
- Higher education (24)
- Natural Language Processing (24)
- Computer science (23)
- Deep reinforcement learning (23)
- LLM (23)
- Neural networks (23)
- Simulation (22)
- Training (22)
- Publication
-
- Research Collection School Of Computing and Information Systems (571)
- Journal of System Simulation (248)
- C-Day Computing Showcase (183)
- Theses and Dissertations (118)
- All Works (87)
-
- Neutrosophic Systems with Applications (81)
- Computer Science Faculty Research & Creative Works (70)
- Computer Science Faculty Publications (64)
- Research outputs 2022 to 2026 (45)
- Karbala International Journal of Modern Science (44)
- Michigan Tech Publications (31)
- Dissertations and Theses Collection (Open Access) (30)
- Chulalongkorn University Theses and Dissertations (Chula ETD) (29)
- Faculty Publications (28)
- Faculty Scholarship (28)
- Mesopotamian Journal of Computer Science (28)
- Open Access Theses & Dissertations (27)
- Turkish Journal of Electrical Engineering and Computer Sciences (26)
- Electrical & Computer Engineering Faculty Publications (25)
- Master's Theses (25)
- Master’s Dissertations (25)
- Graduate Theses and Dissertations (24)
- Journal of Cybersecurity Education, Research and Practice (23)
- Cybersecurity Undergraduate Research Showcase (22)
- Computer Science Faculty Publications and Presentations (21)
- McKelvey School of Engineering Graduate Student Theses & Dissertations (21)
- Computer Science Faculty Research and Publications (20)
- Honors Theses (20)
- Theses (20)
- Tanzania Journal of Engineering and Technology (TJET) (19)
- Publication Type
- File Type
Articles 751 - 780 of 3497
Full-Text Articles in Computer Sciences
Synergistic Modeling Of Hydrogel Gelation Via Time-Delay Dynamics And Machine Learning Algorithms, Mine Babaoglu, Dipesh ., Pankaj Kumar, Jagjit Singh Dhatterwal, Mansoor Alsulami
Synergistic Modeling Of Hydrogel Gelation Via Time-Delay Dynamics And Machine Learning Algorithms, Mine Babaoglu, Dipesh ., Pankaj Kumar, Jagjit Singh Dhatterwal, Mansoor Alsulami
Mathematical Modelling and Numerical Simulation with Applications
This paper presents an integrated framework in which delay differential equation (DDE) modeling and machine learning (ML) approaches are coupled to study hydrogel formation kinetics, with emphasis on delayed crosslinker addition. Conventional mechanistic models disclose many physical and kinetic complexities of reacting mixtures; they seldom depict the nonlinear and time-evolving complexities inherent in developing polymer networks. To address this, a mathematical model is developed that examines how the insertion of crosslinkers affects system stability and equilibrium. Analytical and numerical results show that delays nearing critical levels cause bifurcation behavior with substantial implications on gelation kinetics. Sophisticated machine learning systems, including …
Neutrosophic Set Model For Controlling Electronic Waste Requirements Management Policies To Minimize Ecological Impact And Improving Resilience And Sustainability, Mohamed Abouhawwash, Nitin Mittal, Sudeep Tanwar
Neutrosophic Set Model For Controlling Electronic Waste Requirements Management Policies To Minimize Ecological Impact And Improving Resilience And Sustainability, Mohamed Abouhawwash, Nitin Mittal, Sudeep Tanwar
Neutrosophic Systems with Applications
The growing issue of electronic waste (e-waste) necessitates management approaches that promote sustainability and resilience while reducing environmental effects, particularly considering global disruptions and pressure on manufacturers to implement extended producer responsibility laws. There is a research gap in our knowledge of the link between sustainability and resilience since most of the literature currently available on e-waste management focuses on either operational efficiency or sustainability. This study proposes multi-criteria decision making (MCDM) methodology for controlling electronic waste requirements management policies to minimize ecological impact and improving resilience and sustainability. We use the EDAS methodology to rank the alternatives. The criteria …
Application Of Dematel Based On Bipolar Neutrosophic Sets For Sustainable Agriculture Practices, Lazim Abdullah, Nor Liyana Amalini Binti Mohd Kamal
Application Of Dematel Based On Bipolar Neutrosophic Sets For Sustainable Agriculture Practices, Lazim Abdullah, Nor Liyana Amalini Binti Mohd Kamal
Neutrosophic Systems with Applications
The development of natural capital is a fundamental objective within sustainable agricultural systems, where the optimization of both crop and livestock production is vital to addressing global food demands. Despite this imperative, major agricultural sectors such as paddy and rubber production, often fall short of satisfying consumption needs. This study aims to identify and prioritize the most influential criteria for sustainable agriculture using the Bipolar Neutrosophic Set-based Decision-Making Trial and Evaluation Laboratory (BNS-DEMATEL) method. Expert evaluations were elicited from five agricultural specialists using linguistic assessments to analyze the performance and interdependencies among sustainability criteria. Computational analyses were conducted using MATLAB …
Evaluating And Ranking Genai Chatbots Under Uncertainty: A Type-2 Neutrosophic Rancom–Marcos Mcdm Framework, Hend Ahmed, Abduallah Gamal
Evaluating And Ranking Genai Chatbots Under Uncertainty: A Type-2 Neutrosophic Rancom–Marcos Mcdm Framework, Hend Ahmed, Abduallah Gamal
Neutrosophic Systems with Applications
Owing to integrate GenAI chatbots to enhance productivity across various tasks, this research presents T2NN-RANCOM-MARCOS multi-attribute decision-making model, which employs Type-2 Neutrosophic Number (T2NN) to handle uncertain data, the RANCOM method, distinguished by its easy, highly repeatable, less time consuming, more appropriate to deal with problems exceeds 5 criteria with expert errors to assign subjective weights to criteria and MARCOS method to evaluate and rank eight GenAI chatbots against six main criteria are included 23 sub-criteria: Quality of Information, Understanding and Reasoning, Expression Style and Persona, Safety and Harm, Trust and Confidence and Economic are primarily derived from QUEST evaluation …
Drawing On Uncertainty Methodologies Of Neutrosophic Hypersoft Sets In Cognitive Computing-Driven Healthcare Systems, Mona Mohamed, Nurhan Alaa
Drawing On Uncertainty Methodologies Of Neutrosophic Hypersoft Sets In Cognitive Computing-Driven Healthcare Systems, Mona Mohamed, Nurhan Alaa
Neutrosophic Systems with Applications
A new paradigm called cognitive computing simulates human reasoning and decision-making through integrating advanced techniques such as artificial intelligence (AI) and natural language processing (NLP). Cognitive computing systems, in contrast to traditional systems, can handle both structured and unstructured data, adjust to new information, and offer context-sensitive insights. This study examines how cognitive computing improves decision-making, personalization, and human-machine collaboration in various fields. Cognitive computing in the healthcare sector processes clinical notes, imaging data, and electronic health records to help physicians with diagnosis, treatment planning, and patient engagement. This study examines key applications, including their role in diagnostic support, where …
Lens: Lightweight And Explainable Llm-Based Apt Detection At The Edge For 6g Security, Suhib Bani Melhem, Muhammed Golec, Abdulmalik Alwarafy, Yaser Khamayseh
Lens: Lightweight And Explainable Llm-Based Apt Detection At The Edge For 6g Security, Suhib Bani Melhem, Muhammed Golec, Abdulmalik Alwarafy, Yaser Khamayseh
All Works
Expected to be deployed in the early 2030s, sixth-generation (6G) wireless networks, with their high speed and integration with cutting-edge technology such as intelligent edge computing, expand the attack surface and face serious cyber threat risks such as Advanced Persistent Threats (APTs). This type of cyber attack can imitate benign network traffic and operate for long periods of time without being detected by traditional detection systems. This paper introduces LENS, a lightweight and explainable LLM-based network security framework designed to address this cybersecurity threat for 6G environments. LENS uses a fine-tuned DistilBERT model to convert raw network streams into natural …
Ai Exposure And The Future Of Work: Linking Task-Based Measures To U.S. Occupational Employment Projections, Erik Vasilauskas, Michael Horrigan
Ai Exposure And The Future Of Work: Linking Task-Based Measures To U.S. Occupational Employment Projections, Erik Vasilauskas, Michael Horrigan
Reports
No abstract provided.
Memoir On A General Property Of A Very Extensive Class Of Transcendental Functions, Niels Henrik Abel 1802--1829, John Little
Memoir On A General Property Of A Very Extensive Class Of Transcendental Functions, Niels Henrik Abel 1802--1829, John Little
Mathematics and Computer Science Department Faculty Scholarship
We present this new commentary and translation anticipating the 200th anniversary of the work, commonly known as Abel's ``Paris memoir.'' This is recognized today as one of Abel's most original and influential works. It is significant mostly because it marked the first appearance of a form of a result in the theory of algebraic curves and Riemann surfaces that has come to be known as ``Abel's theorem.'' However, Abel's original understanding of the meaning and context of his result was quite different from the typical modern formulation and the development of the modern understanding has been a long and tortuous …
Polymorphism Crystal Structure Prediction With Adaptive Space Group Diversity Control, Sadman Saadeed Omee, Lai Wei, Jianjun Hu
Polymorphism Crystal Structure Prediction With Adaptive Space Group Diversity Control, Sadman Saadeed Omee, Lai Wei, Jianjun Hu
Faculty Publications
Crystalline materials can form different structural arrangements (i.e., polymorphs) with the same chemical composition, exhibiting distinct physical properties depending on how they are synthesized or the conditions under which they operate. For example, carbon can exist as graphite (soft, conductive) or diamond (hard, insulating). Computational methods that can predict these polymorphs are vital in materials science, which help understand stability relationships, guide synthesis efforts, and discover new materials with desired properties without extensive trial-and-error experimentation. However, effective crystal structure prediction (CSP) algorithms for inorganic polymorph structures remain limited. ParetoCSP2 is proposed, a multi-objective genetic algorithm for polymorphism CSP that incorporates …
Synthesis And Characterization Of Fe-Zn Bimetallic Nanoparticles Via Two-Step Laser Ablation And Their Antibacterial Activity, Hudhaifa M. Mohammed, Sahar Naji Rashid
Synthesis And Characterization Of Fe-Zn Bimetallic Nanoparticles Via Two-Step Laser Ablation And Their Antibacterial Activity, Hudhaifa M. Mohammed, Sahar Naji Rashid
Karbala International Journal of Modern Science
In this study, Nd: YAG laser at a wavelength of (1064 nm), energies of (300 and 400 mJ), and a pulse repetition rate of (3 Hz) was used to synthesize metallic nanoparticles from iron and zinc individually using a one-step pulsed laser ablation approach, followed by the two-step synthesis of bimetallic nanoparticles. The physical properties of the synthesized nanoparticles were then investigated using UV-visible (UV-Vis), X-ray diffraction (XRD), field-emission scanning electron microscopy (FESEM), and energy-dispersive X-ray (EDX) techniques. The results of characterization of the obtained NPs confirmed the formation of core-shell nanocomposites, as evidenced by the increased absorbance intensity of …
Constructions Of Compact Dupin Hypersurfaces With Non-Constant Lie Curvatures, Thomas E. Cecil
Constructions Of Compact Dupin Hypersurfaces With Non-Constant Lie Curvatures, Thomas E. Cecil
Mathematics and Computer Science Department Faculty Scholarship
A hypersurface M in the unit sphere Sn ⊂ Rn+1 is Dupin if along each curvature surface of M, the corresponding principal curvature is constant. If the number g of distinct principal curvatures is constant on M, then M is called proper Dupin. In this expository paper, we give a detailed description of two important types of constructions of compact proper Dupin hypersurfaces in Sn. One construction was published in 1989 by Pinkall and Thorbergsson [35], and the second was published in 1989 by Miyaoka and Ozawa [26]. Both types of examples have the …
Non-Invasive Detection Of Choroidal Melanoma Via Tear-Derived Protein Corona On Gold Nanoparticles: A Machine Learning Approach, Hakimeh Rakhshandeh, Ahmad Nasiraei, Hamid Riazi-Esfahani, Babak Masoomian, Fariba Ghassemi, Mojtaba Arjmand, Saeed Heidari Keshel, Fatemeh Atyabi, Rassoul Dinarvand
Non-Invasive Detection Of Choroidal Melanoma Via Tear-Derived Protein Corona On Gold Nanoparticles: A Machine Learning Approach, Hakimeh Rakhshandeh, Ahmad Nasiraei, Hamid Riazi-Esfahani, Babak Masoomian, Fariba Ghassemi, Mojtaba Arjmand, Saeed Heidari Keshel, Fatemeh Atyabi, Rassoul Dinarvand
Wills Eye Hospital Papers
This study investigates the feasibility of using tear sample analysis, based on protein corona formation on gold nanoparticles combined with electrospray ionization mass spectrometry (ESI-MS) and machine learning techniques, as a non-invasive approach for the detection of choroidal melanoma. The aim is to assess whether protein-nanoparticle interactions can support early and reliable identification of this ocular condition. Tear samples were collected using Schirmer strips from six healthy individuals and six patients diagnosed with choroidal melanoma, with subsequent augmentation to 18 samples per group. Gold nanoparticles (AuNPs, ~ 20 nm) were synthesized via citrate reduction and incubated with tear samples to …
Green Synthesis Of Copper And Silver Nanostructured Particles From Eremurus Plant Extract And Comparison Of Their Optical Properties And Antibacterial Activities, Doaa Ayad Kamil, Ali F. Al-Rawaf, Mohammed Yarub Hani, H.H. Obeed, Tabarek Falah Deindee, Mohammed Ridha Shaeed
Green Synthesis Of Copper And Silver Nanostructured Particles From Eremurus Plant Extract And Comparison Of Their Optical Properties And Antibacterial Activities, Doaa Ayad Kamil, Ali F. Al-Rawaf, Mohammed Yarub Hani, H.H. Obeed, Tabarek Falah Deindee, Mohammed Ridha Shaeed
Karbala International Journal of Modern Science
In the present investigation, silver (Ag) and copper (Cu) nanostructured particles were synthesized from Eremurus plant by means of an environmentally benign methodology in which plant extracts served as both reducing and stabilizing agents. The resultant nanostructured particles were subjected to characterization techniques, including X-ray diffraction (XRD), Fourier-transform infrared spectroscopy (FTIR), field-emission scanning electron microscopy (FESEM), and energy-dispersive X-ray spectroscopy (EDXS). XRD analysis confirmed development of Ag nanostructured particles with face-centered cubic (fcc) structure and also Cu nanostructured particles with cubic form. Moreover, the average crystallite dimensions obtained for Ag and Cu were 18.3 nm and 65.7 nm, …
Fabrication And Characterization Of Epoxy Resin Co-Doped With 2,5-Diphenyloxazole And Cerium Fluoride Nanoparticles For Radiation Detection, Akapong Phunpueok, Jaruwan Seangrit, Sarawut Jaiyen, Krittiya Sreebunpeng, Wuttichai Chaiphaksa, Kewalee Nilgumhang, Voranuch Thongpool
Fabrication And Characterization Of Epoxy Resin Co-Doped With 2,5-Diphenyloxazole And Cerium Fluoride Nanoparticles For Radiation Detection, Akapong Phunpueok, Jaruwan Seangrit, Sarawut Jaiyen, Krittiya Sreebunpeng, Wuttichai Chaiphaksa, Kewalee Nilgumhang, Voranuch Thongpool
Karbala International Journal of Modern Science
This paper presents the fabrication and characterization of a plastic scintillator prepared from epoxy resin doped with 2,5-diphenyloxazole (PPO) and cerium fluoride nanoparticles (CeF3 NPs) for radiation detection. The CeF3 NPs were prepared by a chemical process and examined by X-ray diffraction (XRD) and scanning electron microscopy (SEM); it was found that the prepared particles were true CeF3 NPs with an average particle size of approximately 17 nm. The CeF3 NPs were co-doped with PPO into epoxy resin and formed into a plastic scintillator of 3 cm in diameter and 2 cm in length. Analysis of …
An Unsupervised Time Series Anomaly Detection Approach For Efficient Online Process Monitoring Of Additive Manufacturing, Frida Cantu, Salomon Ibarra, Arturo Gonzales, Jesus Barreda, Chenang Liu, Li Zhang
An Unsupervised Time Series Anomaly Detection Approach For Efficient Online Process Monitoring Of Additive Manufacturing, Frida Cantu, Salomon Ibarra, Arturo Gonzales, Jesus Barreda, Chenang Liu, Li Zhang
Computer Science Faculty Publications
Online sensing plays an important role in advancing modern manufacturing. The real-time sensor signals, which can be stored as high-resolution time series data, contain rich information about the operation status. One of its popular usages is online process monitoring, which can be achieved by effective anomaly detection from the sensor signals. However, most existing approaches either heavily rely on labeled data for training supervised models, or are designed to detect only extreme outliers, thus are ineffective at identifying subtle semantic off-track anomalies to capture where new regimes or unexpected routines start. To address this challenge, we propose an matrix profile-based …
Heuristic Weight Initialization For Transfer Learning In Classification Problems, Musulmon Lolaev, Anand Paul, Jeonghong Kim
Heuristic Weight Initialization For Transfer Learning In Classification Problems, Musulmon Lolaev, Anand Paul, Jeonghong Kim
School of Public Health Faculty Publications
Transfer learning is the predominant method for adapting pre-trained models on another task to new domains while preserving their internal architectures and augmenting them with requisite layers in Deep Neural Network models. Training intricate pre-trained models on a sizable dataset requires significant resources to fine-tune hyperparameters carefully. Most existing initialization methods mainly focus on gradient flow-related problems, such as gradient vanishing or exploding, or other existing approaches that require extra models that do not consider our setting, which is more practical. To address these problems, we suggest employing gradient-free heuristic methods to initialize the weights of the final new-added fully …
Overcoming Variable Illumination In Photovoltaic Snow Monitoring: A Real-Time Robust Drone-Based Deep Learning Approach, Amna Mazen, Ashraf Saleem, Kamyab Yazdipaz, Ana Dyreson
Overcoming Variable Illumination In Photovoltaic Snow Monitoring: A Real-Time Robust Drone-Based Deep Learning Approach, Amna Mazen, Ashraf Saleem, Kamyab Yazdipaz, Ana Dyreson
Michigan Tech Publications
Snow accumulation on photovoltaic (PV) panels can cause significant energy losses in cold climates. While drone-based monitoring offers a scalable solution, real-world challenges like varying illumination can hinder accurate snow detection. We previously developed a YOLO-based drone system for snow coverage detection using a Fixed Thresholding segmentation method to discriminate snow from the solar panel; however, it struggled in challenging lighting conditions. This work addresses those limitations by presenting a reliable drone-based system to accurately estimate the Snow Coverage Percentage (SCP) over PV panels. The system combines a lightweight YOLOv11n-seg deep learning model for panel detection with an adaptive image …
Hybrid Path Planner For Centralized Multi-Robotic Long-Vehicle Based On Adaptive Dimensionality And Grey Wolf Algorithm, Noor Kadhim Ayoob, Ali Hadi Hasan
Hybrid Path Planner For Centralized Multi-Robotic Long-Vehicle Based On Adaptive Dimensionality And Grey Wolf Algorithm, Noor Kadhim Ayoob, Ali Hadi Hasan
Karbala International Journal of Modern Science
The present robot planning methods pay no attention to the impact of the robot's size and the space it occupies in the environment on path planning. This paper presents a centralized hybrid method to plan optimal paths for multiple robotic long vehicles (RLVs) competing with each other to reach one common goal, taking into account the space that must be available to the RLV at each step to avoid narrow spaces that are too small to pass through. The environment analysis for each RLV is improved by assigning constant weight to the obstacles and calculating two new parameters: safety (SF) …
Retracted: Idea Density And Grammatical Complexity As Neurocognitive Markers, Diego Iacono, Gloria Feltis
Retracted: Idea Density And Grammatical Complexity As Neurocognitive Markers, Diego Iacono, Gloria Feltis
Department of Neurology Faculty Papers
Language, a uniquely human cognitive faculty, is fundamentally characterized by its capacity for complex thoughts and structured expressions. This review examines two critical measures of linguistic performance: idea density (ID) and grammatical complexity (GC). ID quantifies the richness of information conveyed per unit of language, reflecting semantic efficiency and conceptual processing. GC, conversely, measures the structural sophistication of syntax, indicative of hierarchical organization and rule-based operations. We explore the neurobiological underpinnings of these measures, identifying key brain regions and white matter pathways involved in their generation and comprehension. This includes linking ID to a distributed network of semantic hubs, like …
Exploring Students' Perceptions Of Genai Tools In Higher Education: A Case Study, Dina Mansour Tbaishat, Maha Waleed Elfadel
Exploring Students' Perceptions Of Genai Tools In Higher Education: A Case Study, Dina Mansour Tbaishat, Maha Waleed Elfadel
All Works
As artificial intelligence transforms the educational landscape, generative artificial intelligence (GenAI) tools have become influential in enhancing learning experiences. Despite their growing presence in higher education, limited research explores how university students, especially learners in non-Western contexts, perceive these tools. This study investigates students' perceptions at a university in the UAE, focusing on five dimensions: perceived benefits, institutional support, technological self-efficacy, ethical considerations and user satisfaction. The findings reveal that students generally expressed strong agreement regarding the benefits of GenAI, demonstrated a clear sense of ethical awareness and felt confident in their technological abilities. While satisfaction levels were generally high, …
Enhancing Fault Tolerance In Distributed Systems Using Shared Checkpoint Replica Mechanisms, Ameer A. Mousa, Mahdi S. Almhanna
Enhancing Fault Tolerance In Distributed Systems Using Shared Checkpoint Replica Mechanisms, Ameer A. Mousa, Mahdi S. Almhanna
Journal of Intelligent Informatics, Networking, and Cybersecurity
Fault tolerance is a critical requirement in distributed systems, as node and network failures can cause significant data loss, service disruption, and performance degradation. Traditional fault-tolerance methods often provide partial solutions, relying on separate recovery models for errors and delayed responses, while also incurring high resource costs. This paper aims to design and implement a more robust and efficient fault-tolerant architecture based on the concept of a shared checkpoint replica. In the proposed system, a master server and multiple slave servers collaboratively process client requests, share checkpoint replicas, and ensure seamless recovery in case of failures. To evaluate the approach, …
Optimization Of Multi-Target Interception Scheme Based On Performance Simulation Modeling, Hanwen Liu, Zhimin Zhuo, Xue Yang
Optimization Of Multi-Target Interception Scheme Based On Performance Simulation Modeling, Hanwen Liu, Zhimin Zhuo, Xue Yang
Journal of System Simulation
Abstract: The air attack scenarios faced by air defense weapons and equipment show the trend of saturation, diversification and intelligence. It is very important to establish multi-target interception efficiency model and optimize interception scheme according to simulation. The current intercepting efficiency index mainly considers the whole operation process, and can not guide the optimization of the intercepting scheme of specific intercepting rounds. The generation of interception schemes mainly relies on experience and simple mathematical model, which is difficult to cope with the increasingly complex and changeable battlefield environment. Therefore, an interception scheme advantage index that comprehensively considers interception probability and …
Design And Prediction Of Deep Fuzzy Neural Network, Chengbiao Wei, Taoyan Zhao, Jiangtao Cao, Ping Li
Design And Prediction Of Deep Fuzzy Neural Network, Chengbiao Wei, Taoyan Zhao, Jiangtao Cao, Ping Li
Journal of System Simulation
Abstract: A deep fuzzy neural network (DFNN) is proposed to solve the problem that the deep neural network has poor interpretability and the correction of the model is not targeted when dealing with the big data regression prediction problem. The proposed deep fuzzy neural network adopts an adaptive fuzzy Cmeans (AFCM) clustering algorithm in structural learning. The structure of the model, namely the number of rules and the antecedent parameters of the rules, is determined by calculating the introduced validity function. The identification of consequent parameters uses an improved grey wolf optimization (IGWO) algorithm. By replacing the linear decreasing strategy …
Kill Chain Efficiency Evaluation Model Based On Gray Dematel-Anp, Zejing Zhao, Junliang Shang, Yanpei Qin
Kill Chain Efficiency Evaluation Model Based On Gray Dematel-Anp, Zejing Zhao, Junliang Shang, Yanpei Qin
Journal of System Simulation
Abstract: In modern conflict scenarios, the kill chain is integral to the comprehensive understanding, orchestration, and execution of military operations. Accurately appraising the efficiency of the kill chain is imperative for gaining insights into battle dynamics and strategically distributing military assets. However, traditional assessments of kill chain efficacy have been hampered by fragmented and isolated indicators that frequently overlook the interplay and influence among various segments of the kill chain. To address these limitations, based on the characteristics of each phase of the kill chain and the OODA loop theory, a new set of performance evaluation indices has been proposed. …
Optimization Method For Multi Agricultural Machinery Collaborative Operation Based On Genetic Algorithm And A* Algorithm, Yiran Yu, Huicheng Lai, Guxue Gao, Guo Zhang, Wangyinan Peng, Longfei Yang, Junhao Huang
Optimization Method For Multi Agricultural Machinery Collaborative Operation Based On Genetic Algorithm And A* Algorithm, Yiran Yu, Huicheng Lai, Guxue Gao, Guo Zhang, Wangyinan Peng, Longfei Yang, Junhao Huang
Journal of System Simulation
Abstract: To address the uneven task distribution among multiple agricultural machines (referred to as farm machinery) and the high time cost due to numerous turning points at intersections, this paper proposes a task planning method that combines a pre-heat multi grouped genetic algorithm (PHMGA) with the turn A* algorithm (tA*). PHMGA allocates tasks to each piece of farm machinery based on the known environment, ensuring balanced workload through a cost objective function that considers travel, operation, and turning distances. It also designs various operators and strategies to search for nearoptimal solutions. The tA* algorithm is used to select paths …
Research On The Truth, Function And Common Principles Of Simulation, Haohua Xu, Bin Xiao, Yunhao Cui
Research On The Truth, Function And Common Principles Of Simulation, Haohua Xu, Bin Xiao, Yunhao Cui
Journal of System Simulation
Abstract: Simulation applications are becoming increasingly widespread and have a greater impact, while the theoretical foundation of simulation is relatively weak. This article provides a new definition of simulation by analyzing the common activities of simulation, which can include both virtual and real simulation forms; referring to Popper's three worlds theory, this paper discusses the objective authenticity of simulation from a philosophical perspective; From a methodological perspective, this paper elaborates on the methodological characteristics of simulation as an indirect cognitive object, revealing its significance in integrating human-machine intelligence and promoting knowledge evolution. It also discusses the common principles of simulation, …
A Model Combining Self-Attention And Weight Sharing For Human Activity Recognition, Lun Ma, Yue Yang, Daihe Wang, Guisheng Liao, Xing Li
A Model Combining Self-Attention And Weight Sharing For Human Activity Recognition, Lun Ma, Yue Yang, Daihe Wang, Guisheng Liao, Xing Li
Journal of System Simulation
Abstract: With the prevalence of wearable devices, human activity recognition based on wearable sensor data has garnered significant attention. The central issue in this field is how to extract effective behavioral information from raw sensor data to form corresponding feature vectors. Currently, convolutional neural networks and recurrent neural networks have been widely utilized for feature extraction from multisensory data. However, these networks struggle to globally capture the crucial temporal features inherent of human activity over time. To address this, a multi-CNN-BiLSTM-self attention (Multi-CBSA) model based on self-attention and weight sharing has been proposed, taking into consideration the logical correlations among …
Wingtip Docking Control Of Composite Aircraft Based On Adrc Theory, Chunlei Xie, Hongxia Hu, Weibo Han
Wingtip Docking Control Of Composite Aircraft Based On Adrc Theory, Chunlei Xie, Hongxia Hu, Weibo Han
Journal of System Simulation
Abstract: The process of wingtip docking in composite aircraft is challenged by significant unsteady vortex aerodynamic disturbances arising from the close-range coupling of wingtips, thereby posing considerable constraints on docking precision and flight safety. This study endeavors to address the intricate task of airborne wingtip docking control amidst wingtip vortex disturbances through a comprehensive investigation of airborne wingtip docking control technology, grounded in the tenets of active disturbance rejection control (ADRC) theory. Initially, a mathematical model encapsulating the dynamics of three-channel attitude/displacement during the docking operation, incorporating both the wingtip docking mechanism and the wingtip vortex model, is established. …
Solving The Vehicle Routing Problem Based On Deep Reinforcement Learning, Ming Jiang, Tao He
Solving The Vehicle Routing Problem Based On Deep Reinforcement Learning, Ming Jiang, Tao He
Journal of System Simulation
Abstract: The capacitated vehicle routing problem (CVRP) is a well-known combinatorial optimization challenge recognized as NP-hard due to its significant complexity. Building upon existing research, this paper introduces a novel end-to-end deep reinforcement learning approach based on a multi-pointer Transformer to tackle the CVRP. The proposed algorithm employs an invertible residual network in the encoder to encode input features, effectively reducing memory consumption. In the decoder, a multipointer network determines the probability distribution of solutions. To further enhance the performance of CVRP solutions, the algorithm leverages the symmetry in combinatorial optimization by implementing multi-trajectory parallel processing during both training …
Anthem 2.0: Automated Reasoning For Answer Set Programming, Jorge Fandinno, Zachary Hansen, Yuliya Lierler, Christoph Glinzer, Jan Heuer, Torsten Schaub, Tobias Stolzmaan, Vladimire Lifschitz
Anthem 2.0: Automated Reasoning For Answer Set Programming, Jorge Fandinno, Zachary Hansen, Yuliya Lierler, Christoph Glinzer, Jan Heuer, Torsten Schaub, Tobias Stolzmaan, Vladimire Lifschitz
Computer Science Faculty Publications
ANTHEM 2.0 is a tool to aid in the verification of logic programs written in an expressive fragment of CLINGO ’s input language named MINI-GRINGO, which includes arithmetic operations and simple choice rules but not aggregates. It can translate logic programs into formula representations in the logic of here-and-there and analyze properties of logic programs such as tightness. Most importantly, ANTHEM 2.0 can support program verification by invoking first-order theorem provers to confirm that a program adheres to a first-order specification or to establish strong and external equivalence of programs. This paper serves as an overview of the system’s capabilities. …