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Articles 271 - 300 of 17464
Full-Text Articles in Entire DC Network
Conditioning Hierarchical Diffusion Transformers On Rf Circuit Parameters, Ethan Morton
Conditioning Hierarchical Diffusion Transformers On Rf Circuit Parameters, Ethan Morton
McKelvey School of Engineering Graduate Student Theses & Dissertations
As modern ML techniques have become increasingly advanced, they have begun to be integrated into wireless RF systems for classification, identification, and spectrum management. Deep Neural Networks (DNNs) enable RF system operators and designers to design more flexible systems with greater robustness to errors and attacks. However, neural networks require significant amounts of properly annotated data to train. Current data labeling methods lack the ability to obtain reliable true labels for circuit properties such as carrier frequency offset (CFO), power amplifier (PA) non-linearity, and in-phase/quadrature (IQ) imbalance. This thesis investigates the efficacy of a novel architecture, RF-Diffusion, for generating high-quality …
Using Ali-4 Z-Implication In Controller Design, Shamil Azer Ahmadov
Using Ali-4 Z-Implication In Controller Design, Shamil Azer Ahmadov
Chemical Technology, Control and Management
One of the widely used theories in the information processing is Professor Zadeh's fuzzy logic theory. Fuzzy implications form the basis of this theory. When processing information using fuzzy implication, the chosen judgment method and the type of implication affect the result. Referring to the review of the relevant literature on fuzzy implications, it can be noted that there are still unresolved problems and issues. For example, fuzzy implications cannot be used in processing imperfect information or information based on probabilistic and fuzzy uncertainty. Existing fuzzy implications face limitations in practical applications. Fuzzy implications only take into account inaccuracy, but …
Wavetable Modification In Frequency Domain: Fourier Analysis With Matlab Implementation, Caleb Kortens
Wavetable Modification In Frequency Domain: Fourier Analysis With Matlab Implementation, Caleb Kortens
Senior Honors Theses
One of the challenges in creating computer generated music is producing life-like sounds. Music produced through computer synthesis can often sound thin and synthetic rather than vibrant and energetic. Wavetable synthesis is a method of waveform generation that uses a wavetable, which is a set of single period waves, or frames, that have varying characteristics. This method allows a synthesizer to transition between waveforms to produce a sound with time varying tone and harmonic characteristics. This adds life and movement to computer generated sounds. Wavetable synthesis is often used to imitate actual instruments, but unique wavetables can be created that …
Open Multi-Agent Systems: The Free-Range-Zoo Framework And Moasei Competition, Ceferino J. Patino Iv
Open Multi-Agent Systems: The Free-Range-Zoo Framework And Moasei Competition, Ceferino J. Patino Iv
School of Computing: Dissertations, Theses, and Student Research
The field of multi-agent reinforcement learning (MARL) has made significant strides in addressing sequential decision-making problems under uncertainty. However, traditional MARL frameworks assume closed-world settings with fixed agent sets, static task distributions, and unchanging environment dynamics. This thesis presents two complementary contributions that advance the state of open-world multi-agent systems research: (1) the free-range-zoo framework, an open-source environment suite for MARL in open environments featuring dynamic agent populations, evolving task sets, and changing operational frames; and (2) the MOASEI Competition, an international benchmarking event that leverages free-range-zoo to evaluate how artificial agents handle openness in complex, partially observable domains. The …
Extraction And Interpretation Of Eeg Features For Diagnosis And Severity Prediction Of Ad And Ftd Using Deep Learning, Tuan Vo
Electronic Theses and Dissertations 2020 - Present
Alzheimer’s disease (AD) is the most common form of dementia and is characterized by progressive cognitive decline and memory impairment. Frontotemporal dementia (FTD), the second most prevalent form, primarily affects the frontal and temporal lobes and often leads to changes in personality, behavior, and language. Due to overlapping clinical symptoms, FTD is frequently misdiagnosed as AD. Electroencephalography (EEG) offers a portable, non-invasive, and cost-effective method for studying brain activity; however, its diagnostic utility for differentiating dementia subtypes is limited by signal complexity and noise. In this dissertation, I propose an EEG-based feature extraction framework that leverages deep learning to identify …
Llm For Clinical Named Entity Recognition: A Study On Rag With Pubmed And Umls, Apoorv Tripathi
Llm For Clinical Named Entity Recognition: A Study On Rag With Pubmed And Umls, Apoorv Tripathi
Electronic Theses and Dissertations 2020 - Present
The first step of biomedical NLP is recognizing clinical named entities, which consist of identifying and categorizing a variety of clinical entities such as diseases, symptoms, genetics, diagnostic tests, procedures, etc. from a body of unstructured clinical text. This study presents a PubMed and UMLS based Retrieval Augmented Generation framework which improves the performance of the Large Language Models to identify clinical entities by providing context. In particular, the framework consists of a two-stage pipeline, where candidate tokens are identified from initial LLM-based classification and refined with retrieved context from either PubMed or UMLS. The proposed framework is assessed across …
Integration Of Bayesian Networks And Neural Networks For High-Dimensional Data Analysis, Cooper Schmer
Integration Of Bayesian Networks And Neural Networks For High-Dimensional Data Analysis, Cooper Schmer
Department of Electrical and Computer Engineering: Dissertations, Theses, and Student Research
High-dimensional biomedical datasets, such as omics data, present significant challenges for predictive modeling due to noise, redundancy, and computational complexity. This thesis proposes a hybrid framework that integrates Bayesian Networks (BNs) and Artificial Neural Networks (NNs) to improve classification performance of such data sets while reducing input dimensionality. Central to this work is a novel feature selection method based on d-separation, a structural property of Bayesian networks that encodes conditional independence relationships.
The proposed approach introduces a count-based d-separation metric to quantify the relevance of variables to a target outcome, along with a thresholding scheme to balance feature selection robustness …
Enhancing Lane Detection In Autonomous Vehicles Using Data Augmentation For Adverse Environmental Conditions, Rutvikkumar Dave
Enhancing Lane Detection In Autonomous Vehicles Using Data Augmentation For Adverse Environmental Conditions, Rutvikkumar Dave
Electronic Theses and Dissertations 2020 - Present
To make sure that self-driving and connected automobile technologies are safe and work well, it’s really important that they can correctly identify lanes. But lane detection Algorithms typically have a hard time working well when the weather is bad, such when it rains, fogs, or goes too fast. The circumstances cause visual distortions that make existing computer vision systems less reliable, which makes it harder requires autonomous navigation systems to work well. This paper introduces a comprehensive lane detection system that integrates synthetic Weather-informed data augmentation combined with a Weather-aware Temporal Lane Detection Network (WTLDNet) to make it easier for …
Modelling Method Of Unmanned Vehicle Dynamics Based On Neural Network, Jun Wang, Min Liu, Xiaochuan Zhang, Yishan Ding, Juhui Feng, Ye Zhuang
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 …
Method For Testing And Evaluating Intelligence Level Of Virtual Forces Based On Operational Experiments, Dayong Liu, Zhiming Dong, Weidong Zhang, Wenjun Zhang, Jiancheng Gao
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, Xinhang Chen, Xiaodong Ling, Chengchang Lang, Shijun Zheng, Yiqi Tang
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 …
Model-Based System Verification: Theoretical Framework, Key Technologies, And Future Prospects, Bo Sun, Yi Ren, Silin Wang, Qi Liu, Zhidong Li
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 …
Large Language Model For X Language Simulation: Architecture, Key Technologies, And Typical Applications, Laichunyang Peng, Fei Ye, Xiaoming Guo, Jinglin Zhou
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 …
Space-Ground Integrated Collaborative Positioning Algorithm And Simulation For Trajectory Enhancement, Juhui Wei, Xinyong Zhang, Jiongqi Wang, Xuanying Zhou, Zhangming He
Space-Ground Integrated Collaborative Positioning Algorithm And Simulation For Trajectory Enhancement, Juhui Wei, Xinyong Zhang, Jiongqi Wang, Xuanying Zhou, Zhangming He
Journal of System Simulation
Abstract: To address the challenges of low credibility, weak consistency, and poor accuracy in the information of trajectory results from space-based and ground-based passive time difference positioning simulation systems, a space-ground integrated collaborative positioning method was proposed for trajectory enhancement. By analyzing the operating principle of the time difference positioning system, the influencing factors that measure positioning accuracy in different feature dimensions were obtained; spline smoothing was employed for data alignment between space-based and ground-based systems; a spline-constrained parametric trajectory model was proposed to further enhance the stability; an error-sensitive feature selection framework for improving simulation consistency was constructed to …
Intelligent Competition Platform And Mode Driven By Cloud-Native Simulation, Long Qin, Hesong Huang, Lujia Yin, Chuan Ai, Qi Zhang, Xinmeng Li
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, …
Review On Optimization Of Simulation Modeling Strategies For Spacecraft Orbit Avoidance, Guozheng Li, Rui Wang, Shichao Fan, Xintong Cai, Xinyue Zhai
Review On Optimization Of Simulation Modeling Strategies For Spacecraft Orbit Avoidance, Guozheng Li, Rui Wang, Shichao Fan, Xintong Cai, Xinyue Zhai
Journal of System Simulation
Abstract: The number of on-orbit spacecraft increases exponentially; the space environment becomes more complex, and the collision risk of on-orbit spacecraft increases significantly. On-orbit safety is thus severely threatened, posing higher requirements for orbit avoidance methods. The costs and risks of space activities are extremely high, making simulation an effective method to solve complex problems of orbit avoidance. The modeling, solution, and simulation methods for the two core issues of spacecraft orbit avoidance, "collision avoidance" and "pursuit-evasion games", were systematically reviewed, and the existing shortcomings were analyzed. The applications of technologies such as deep reinforcement learning in promoting orbit avoidance …
Vehicle Routing Optimization For Underground Mines Considering Fuzzy Demand And Time Tolerance, Guorong Wang, Haishun Deng, Ziming Kou, Xuanxuan Yan, Zhixiang Huang
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, Wenlong Meng, Yanbo Pu, Ya Gong
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 …
A Bilstm+Attention Method For Predicting The Intentions Of Air Combat Targets Based On Multi-Feature Continuous Time Series, Qiuni Li, Dong Wang, Chaozhe Wang, Zongcheng Liu
A Bilstm+Attention Method For Predicting The Intentions Of Air Combat Targets Based On Multi-Feature Continuous Time Series, Qiuni Li, Dong Wang, Chaozhe Wang, Zongcheng Liu
Journal of System Simulation
Abstract: To achieve advance prediction of enemy target intention, a three-layer air combat intention prediction method based on multi-feature continuous time series and BiLSTM+Attention, including trajectory prediction, threat assessment, and intention prediction was proposed. To prevent the onesidedness of intention prediction results caused by state information at a single moment, prediction was carried out from multiple state features and trajectory information in a continuous time series. An LSTM neural network was used to predict the trajectory of the target aircraft, and the threat assessment of the target aircraft before and after the prediction was conducted. The BiLSTM + Attention model …
Large-Scale Multi-Objective Evolutionary Algorithm Based On Multi-Region Dynamic Grouping, Binhao Liang, Jingxuan Wei, Fengqin Liang
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 …
Optimization Of Air Defense And Antimissile Firepower Resource Allocation Based On Adaptive Hybrid Evolution, Wei Liu, Delong Chen, Ze Liu, Rui Wang, Kaiwen Li, Tao Zhang
Optimization Of Air Defense And Antimissile Firepower Resource Allocation Based On Adaptive Hybrid Evolution, Wei Liu, Delong Chen, Ze Liu, Rui Wang, Kaiwen Li, Tao Zhang
Journal of System Simulation
Abstract: Air defense and antimissile firepower resource allocation is a core optimization problem in modern defense systems. Under complex conditions such as spatiotemporal constraints and firepower resource limitations, this problem involves the optimal configuration of limited interceptors and belongs to the class of NP-hard multi-constrained combinatorial optimization problems. This paper established a comprehensive mathematical model encompassing range constraints, time window constraints, feasibility matrices, and interception probability models. To address the high-dimensional nonlinearity of the problem, an adaptive hybrid evolutionary algorithm (AHEA) was proposed. The algorithm integrated problem-aware initialization, adaptive parameter control, seven specialized neighborhood search operators, and an adaptive strategy …
Mechanism Analysis Of Parasitic Torque In Electric Loading Systems, Xiaozhe Sun, Zhenyu Fu, Zhaoke Xu, Jianxin Li
Mechanism Analysis Of Parasitic Torque In Electric Loading Systems, Xiaozhe Sun, Zhenyu Fu, Zhaoke Xu, Jianxin Li
Journal of System Simulation
Abstract: To address the issues of sources and mechanisms of parasitic torque in electric loading systems for aircraft actuator loads, a functional model of the electric loading system was established. Numerical simulations and Monte Carlo methods were employed to analyze the sources of parasitic torque and its primary influencing factors. The influence mechanisms and degrees of the system's external inputs and internal disturbances on parasitic torque were analyzed and validated through single-parameter and multi-parameter analyses. The results indicate that parasitic torque is predominantly influenced by factors such as loading command frequency, sensor signal bias, and loading motor parameters. In particular, …
Simulation On Water Hammer Characteristics Of Bipropellant Attitude And Orbit Control Propulsion System, Xianwei Lang, Yantao Wang, Fang Zhang, Yizhen Zu, Xinyu Zhang, Weibin Xiang
Simulation On Water Hammer Characteristics Of Bipropellant Attitude And Orbit Control Propulsion System, Xianwei Lang, Yantao Wang, Fang Zhang, Yizhen Zu, Xinyu Zhang, Weibin Xiang
Journal of System Simulation
Abstract: To address the water hammer problem in bipropellant attitude and orbit control propulsion systems during start-up, shutdown, and periodic operation, the water hammer characteristics under different operating conditions are investigated using simulation methods. The water hammer characteristics of annular and branched propellant delivery lines are compared, and the effects of multiengine interactions under various operating conditions, as well as the influence of water hammer on engine performance, are analyzed. The results show that the attenuation rate of pressure fluctuation in the annular pipeline system is significantly higher than that in the branch pipeline system. Under the condition of multi-cycle …
Intersection Positioning Algorithm With Spatial Translation Based On Sar Scene Matching, Cheng'en Pu, Yumin Lai, Rui Shi, Yan Liao, Kezi Meng, Lifeng Qu
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, Yandong Nan, Jinda Zhu, Xinbin Lu, Zhiying Qin, Dandan Qi, Zhiheng Ding
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 …
Design And Application Of Collaborative Simulation System For Satellite Constellation Flight Missions, Dong Yan, Hanzhe Yang, Fangfang Jiang, Chengbao Liu, Peng Zhang
Design And Application Of Collaborative Simulation System For Satellite Constellation Flight Missions, Dong Yan, Hanzhe Yang, Fangfang Jiang, Chengbao Liu, Peng Zhang
Journal of System Simulation
Abstract: To meet the requirements of the collaborative drill for the ground operation and control system of the satellite constellation, as well as the verification and evaluation of in-orbit complex missions, the design ideas and implementation methods of the collaborative simulation system for satellite constellation flight missions were proposed. By adopting the time correction mechanism of the time-scale distributor, the time synchronization problem among the simulation nodes and the operation and control simulation system was solved. By adopting the communication technology based on improved PDXP + UDP, the problem of cross-node data interface and inter-satellite communication simulation was resolved. A …
Modeling And Simulation Of Target Characteristic Architecture Of Target Missile Based On Dodaf, Tuo Zhao, Yuqiao Liu, Yuan Ma, Yun Cheng, Shen Li
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 …
Overall Design Method Of Low Earth Orbit Communication Satellite Based On Mbse, Jiace Shang, Rui Zhang, Ya Dai, Hua Zhu, Siqi Hu, Linqiang Ge, Chenguang Shi
Overall Design Method Of Low Earth Orbit Communication Satellite Based On Mbse, Jiace Shang, Rui Zhang, Ya Dai, Hua Zhu, Siqi Hu, Linqiang Ge, Chenguang Shi
Journal of System Simulation
Abstract: Drawing on the model-centric design philosophy of model-based systems engineering (MBSE), this study constructs a model architecture suitable for the design and analysis of low Earth orbit communication satellites. This architecture adopts a multi-dimensional matrix approach. Vertically, it traverses the mission layer, system layer, satellite general design layer, and subsystem layer, achieving top-down hierarchical decoupling. Horizontally, it establishes a comprehensive view mapping mechanism covering the domains of requirements, functions, structure, and performance. Integrating the characteristics of product development, a modeling process covering the entire lifecycle—from mission demonstration and overall design to subsystem design and integration verification—has been established. The …
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
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. …
Limitations Of Signature-Based Network Intrusion Detection Under Modern Traffic Conditions, Henry Guidry
Limitations Of Signature-Based Network Intrusion Detection Under Modern Traffic Conditions, Henry Guidry
Cybersecurity Undergraduate Research Showcase
Network Intrusion Detection Systems are tools used to monitor network traffic and alert to suspicious or harmful activity before it can cause harm. Signature-based versions of these systems are a foundation for intrusion detection, operating by finding common patterns and forming malicious signatures. However, three developments in modern network environments have greatly impacted the significance of Network Intrusion Detection Systems. These three developments are the near-complete adoption of end-to-end encryption, the use of sophisticated packet fragmentation techniques, and the processing demands of high-throughput networks. Encryption makes deep packet inspection practically infeasible by transforming inspectable payloads into ciphertext, forcing NIDS to …