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Articles 13771 - 13800 of 63035
Full-Text Articles in Computer Sciences
Dynamics Of Dark Web Financial Marketplaces: An Exploratory Study Of Underground Fraud And Scam Business, Bo Ra Jung, Kyung-Shick Choi, Claire Seungeun Lee
Dynamics Of Dark Web Financial Marketplaces: An Exploratory Study Of Underground Fraud And Scam Business, Bo Ra Jung, Kyung-Shick Choi, Claire Seungeun Lee
International Journal of Cybersecurity Intelligence & Cybercrime
The number of Dark Web financial marketplaces where Dark Web users and sellers actively trade illegal goods and services anonymously has been growing exponentially in recent years. The Dark Web has expanded illegal activities via selling various illicit products, from hacked credit cards to stolen crypto accounts. This study aims to delineate the characteristics of the Dark Web financial market and its scams. Data were derived from leading Dark Web financial websites, including Hidden Wiki, Onion List, and Dark Web Wiki, using Dark Web search engines. The study combines statistical analysis with thematic analysis of Dark Web content. Offering promotions …
Kerberoasting: Case Studies Of An Attack On A Cryptographic Authentication Technology, D Demers, Hannarae Lee
Kerberoasting: Case Studies Of An Attack On A Cryptographic Authentication Technology, D Demers, Hannarae Lee
International Journal of Cybersecurity Intelligence & Cybercrime
Kerberoasting, an attack vector aimed at the Kerberos authentication protocol, can be used as part of an adversary’s attack arsenal. Kerberos is a type of network authentication protocol that allows a client and server to conduct a mutual verification before providing the requested resource to the client. A successful Kerberoasting attack allows an adversary to leverage the architectural limitations of Kerberos, providing access to user password hashes that can be subject to offline cracking. A cracked user password could give a bad actor the ability to maintain persistence, move laterally, or escalate privileges in a system. Persistence or movement within …
Generalization In Quantum Machine Learning From Few Training Data, Matthias C Caro, Hsin-Yuan Huang, M Cerezo, Kunal Sharma, Andrew Sornborger, Lukasz Cincio, Patrick J Coles
Generalization In Quantum Machine Learning From Few Training Data, Matthias C Caro, Hsin-Yuan Huang, M Cerezo, Kunal Sharma, Andrew Sornborger, Lukasz Cincio, Patrick J Coles
Faculty, Staff and Student Publications
Modern quantum machine learning (QML) methods involve variationally optimizing a parameterized quantum circuit on a training data set, and subsequently making predictions on a testing data set (i.e., generalizing). In this work, we provide a comprehensive study of generalization performance in QML after training on a limited number N of training data points. We show that the generalization error of a quantum machine learning model with T trainable gates scales at worst as [Formula: see text]. When only K ≪ T gates have undergone substantial change in the optimization process, we prove that the generalization error improves to [Formula: see …
Fdrl Approach For Association And Resource Allocation In Multi-Uav Air-To-Ground Iomt Network, Abegaz Mohammed, Aiman Erbad, Hayla Nahom, Abdullatif Albaseer, Mohammed Abdallah, Mohsen Guizani
Fdrl Approach For Association And Resource Allocation In Multi-Uav Air-To-Ground Iomt Network, Abegaz Mohammed, Aiman Erbad, Hayla Nahom, Abdullatif Albaseer, Mohammed Abdallah, Mohsen Guizani
Machine Learning Faculty Publications
In 6G networks, unmanned aerial vehicles (UAVs) can serve as aerial flying base stations (AFBS) with aerial mobile edge computing (AMEC) server capabilities. AFBS is an increasingly popular solution for delivering time-sensitive applications, extending network coverage, and assisting ground base stations in the healthcare systems for remote areas with limited infrastructure. Furthermore, the UAVs are deployed in the healthcare system to support the Internet of medical things (IoMT) devices in data collection, medical equipment distribution, and providing smart services. However, ensuring the privacy and security of patients’ data with the limited UAV resources is a major challenge. In this paper, …
Proceedings Of The Rust-Edu Workshop, Bart Massey
Proceedings Of The Rust-Edu Workshop, Bart Massey
Rust-Edu Workshop
The 2022 Rust-Edu Workshop was an experiment. We wanted to gather together as many thought leaders we could attract in the area of Rust education, with an emphasis on academic-facing ideas. We hoped that productive discussions and future collaborations would result. Given the quick preparation and the difficulties of an international remote event, I am very happy to report a grand success. We had more than 27 participants from timezones around the globe. We had eight talks, four refereed papers and statements from 15 participants. Everyone seemed to have a good time, and I can say that I learned a …
Reconfigurable Intelligent Surfaces And Capacity Optimization: A Large System Analysis, Aris L. Moustakas, George C. Alexandropoulos, Mérouane Debbah
Reconfigurable Intelligent Surfaces And Capacity Optimization: A Large System Analysis, Aris L. Moustakas, George C. Alexandropoulos, Mérouane Debbah
Machine Learning Faculty Publications
Reconfigurable Intelligent Surfaces (RISs), comprising large numbers of low-cost and almost passive metamaterials with tunable reflection properties, have been recently proposed as an enabling technology for programmable wireless propagation environments. In this paper, we present asymptotic closed-form expressions for the mean and variance of the mutual information metric for a multi-antenna transmitter-receiver pair in the presence of multiple RISs, using methods from statistical physics. While nominally valid in the large system limit, we show that the derived Gaussian approximation for the mutual information can be quite accurate, even for modest-sized antenna arrays and metasurfaces. The above results are particularly useful …
Did Usage Of Mental Health Apps Change During Covid-19? A Comparative Study Based On An Objective Recording Of Usage Data And Demographics, Maryam Aziz, Aiman Erbad, Mohamed Basel Almourad, Majid Altuwairiqi, John Mcalaney, Raian Ali
Did Usage Of Mental Health Apps Change During Covid-19? A Comparative Study Based On An Objective Recording Of Usage Data And Demographics, Maryam Aziz, Aiman Erbad, Mohamed Basel Almourad, Majid Altuwairiqi, John Mcalaney, Raian Ali
All Works
This paper aims to objectively compare the use of mental health apps between the pre-COVID-19 and during COVID-19 periods and to study differences amongst the users of these apps based on age and gender. The study utilizes a dataset collected through a smartphone app that objectively records the users' sessions. The dataset was analyzed to identify users of mental health apps (38 users of mental health apps pre-COVID-19 and 81 users during COVID-19) and to calculate the following usage metrics; the daily average use time, the average session time, the average number of launches, and the number of usage days. …
Artificial Neural Networks And Gradient Boosted Machines Used For Regression To Evaluate Gasification Processes: A Review, Owen Sedej, Eric Mbonimpa, Trevor Sleight, Jeremy M. Slagley
Artificial Neural Networks And Gradient Boosted Machines Used For Regression To Evaluate Gasification Processes: A Review, Owen Sedej, Eric Mbonimpa, Trevor Sleight, Jeremy M. Slagley
Faculty Publications
Waste-to-Energy technologies have the potential to dramatically improve both the natural and human environment. One type of waste-to-energy technology that has been successful is gasification. There are numerous types of gasification processes and in order to drive understanding and the optimization of these systems, traditional approaches like computational fluid dynamics software have been utilized to model these systems. The modern advent of machine learning models has allowed for accurate and computationally efficient predictions for gasification systems that are informed by numerous experimental and numerical solutions. Two types of machine learning models that have been widely used to solve for quantitative …
Computational Study On The Effectiveness Of Flavonoids From Marsilea Crenata C. Presl As Potent Sirt1 Activators And Nfκb Inhibitors, Sri Rahayu, Sasangka Prasetyawan, Sri Widyarti, Mochammad Fitri Atho’Illah, Gatot Ciptadi
Computational Study On The Effectiveness Of Flavonoids From Marsilea Crenata C. Presl As Potent Sirt1 Activators And Nfκb Inhibitors, Sri Rahayu, Sasangka Prasetyawan, Sri Widyarti, Mochammad Fitri Atho’Illah, Gatot Ciptadi
Karbala International Journal of Modern Science
Ovarian aging is a natural process in females, and it occurs due to an elevated ROS-induced inflammation caused by oxidative stress. SIRT-1 is a metabolic sensor that tightly regulates oxidative and inflammatory responses. However, this regulative function is antagonized by NFκB. Therefore, the objective of this study was to explore the pathways involved in aging and identify the flavonoid compounds from Marsilea crenata that might be useful as SIRT1 activators and NFκB inhibitors. The screening began with exploring the protein-protein interaction in the experimental process using BioGrid, and the role of the flavonoid was evaluated using STITCH. The interaction between …
Molecular Characterization Of Esbls And Ampc Β-Lactamases In Bacteria Isolated From Currency Notes Circulating In Mosul City, Iraq, Mahmood Zeki Al-Hasso, Shakir Ghazi Gergees, Zahraa Khairialdeen Mohialdeen
Molecular Characterization Of Esbls And Ampc Β-Lactamases In Bacteria Isolated From Currency Notes Circulating In Mosul City, Iraq, Mahmood Zeki Al-Hasso, Shakir Ghazi Gergees, Zahraa Khairialdeen Mohialdeen
Karbala International Journal of Modern Science
The Iraqi currency notes circulating in Mosul city were evaluated for the occurrence of ESBLs and AmpC b-lactamaseproducing bacteria. Four hundred and twenty-two Gram-positive and negative bacterial isolates with different antimicrobial resistance profiles were recovered from 250 samples collected during the period from April to July 2021, among which 150 isolates (35.5%) were multi-drug resistant (MDR). The study found that 16.4% and 14.8% of Gram negative isolates were positive for ESBLs and AmpC phenotypic detection tests, respectively. Interestingly, 6.6% of the isolates were simultaneously positive for both tests. Molecular characterization was carried out using PCR technique to determine the prevalent …
Molecular Docking And Dynamics Simulation Studies To Predict Multiple Medicinal Plants’ Bioactive Compounds Interaction And Its Behavior On The Surface Of Denv-2 E Protein, Arief Hidayatullah, Wira Eka Putra, Muhaimin Rifa’I, Sustiprijatno Sustiprijatno, Diana Widiastuti, Muhammad Fikri Heikal, Hendra Susanto, Wa Ode Salma, Hilal Mulyadi
Molecular Docking And Dynamics Simulation Studies To Predict Multiple Medicinal Plants’ Bioactive Compounds Interaction And Its Behavior On The Surface Of Denv-2 E Protein, Arief Hidayatullah, Wira Eka Putra, Muhaimin Rifa’I, Sustiprijatno Sustiprijatno, Diana Widiastuti, Muhammad Fikri Heikal, Hendra Susanto, Wa Ode Salma, Hilal Mulyadi
Karbala International Journal of Modern Science
The envelope protein (E) is a fusion class II protein that is essential for DENV fusion. We use two active compounds derived from commonly used plants in Indonesia: galangin and kaempferide. We ran a docking and 1000 ps molecular dynamic analysis with normal physiological parameters. During the simulation, galangin and kaempferide binding sites fluctuated. But chloroquine has lesser ligand mobility, hence keeping contact with fusion loops, whereas both drugs lose contact with hydrophobic pockets. However, the two active compounds have a more stable ligand configuration. Less than 2 Å alterations were seen in the RMSF simulation of the protein E …
Effective Immersive Analytics For Everyday Use, Benjamin D. Weidner
Effective Immersive Analytics For Everyday Use, Benjamin D. Weidner
Theses and Dissertations
Data visualization is an important field of work that takes in uncountable amounts of indexes to create an easy-to-read interpretation of what was previously unreadable. Immersive analytics is the new field that brings 3D data visualization to virtual reality, immersing users directly into the data. Focusing on bringing humans and computers closer together through natural function can benefit the world of data science. In order to accurately utilize this field to benefit this world, principles must be laid out and observed to see which techniques and methods are best fit for an everyday immersive analytics platform. Our findings show that, …
Transformnet: Self-Supervised Representation Learning Through Predicting Geometric Transformations, Muhammad Ali, Sayed Hashim
Transformnet: Self-Supervised Representation Learning Through Predicting Geometric Transformations, Muhammad Ali, Sayed Hashim
Computer Vision Faculty Publications
Deep neural networks need a big amount of training data, while in the real world there is a scarcity of data available for training purposes. To resolve this issue unsupervised methods are used for training with limited data. In this report, we describe the unsupervised semantic feature learning approach for recognition of the geometric transformation applied to the input data. The basic concept of our approach is that if someone is unaware of the objects in the images, he/she would not be able to quantitatively predict the geometric transformation that was applied to them. This self supervised scheme is based …
An Analysis Of Android Malware Detection Using Tree Learning Techniques, Kyler D. Dickey
An Analysis Of Android Malware Detection Using Tree Learning Techniques, Kyler D. Dickey
Student Theses and Dissertations
Android malware is a growing threat, coinciding with the increasing adoption of the Android platform. Malware detection methods used to maintain user privacy and system integrity are increasingly becoming the subject of research. Many new methods studied employ learning algorithms to detect malicious programs. This study investigates the use of byte and opcode frequency features as inputs for tree-based machine learning methods. The algorithm is optimized to reduce overfitting given input hyperparameter combinations and is tuned using cross-validation procedures. Lastly, the study deliberates on possible avenues for future research to gather more concrete evidence for the efficacy and cost-effectiveness of …
Image Dehazing Network Based On Densely Connected Residual Block And Channel Pixel Attention, Weidong Jin, Shuli Zhang, Peng Tang, Man Zhang
Image Dehazing Network Based On Densely Connected Residual Block And Channel Pixel Attention, Weidong Jin, Shuli Zhang, Peng Tang, Man Zhang
Journal of System Simulation
Abstract: Abstruct: A lot of research achievements have been made in image dehazing based on neural network,but there aiming at the fog residue, even the color distortion and texture loss, in complex outdoor image dehazing, an image dehazing network based on densely connected residual block and channel pixel attention is proposed. Densely connected residual blocks are used to extract and fuse the features of foggy images,and the repair module with channel pixel attention mechanism is used to repair the color and texture of the feature maps. The experimental results show that, compared with the existing methods, the proposed method and …
Research On Motion Recognition And Tracking For Space Survey And Launch Tasks, Bin Ren, Xiaoyu Wang
Research On Motion Recognition And Tracking For Space Survey And Launch Tasks, Bin Ren, Xiaoyu Wang
Journal of System Simulation
Abstract: Space survey and launch task has high precision and long cycle, and needs to be exposed to direct sunlight for a long time, so that the non-contact action calibration and comparison in a virtual working environment is an efficient way to improve the mission completion success rate. Aiming at the real-time motion tracking of aerospace personnel, a keyframe optimization algorithm for the action recognition is proposed. According to the bone data in the depth image, the bone features are extracted, and the keyframes are extracted by the feature threshold. The characteristic data of the keyframe is input into bi-directional …
Sensorless Control Of Pmsm Based On An Anfis Optimized Flux Sliding Mode Observer, Huilin Zhang, Yujie Jin, Haima Yang
Sensorless Control Of Pmsm Based On An Anfis Optimized Flux Sliding Mode Observer, Huilin Zhang, Yujie Jin, Haima Yang
Journal of System Simulation
Abstract: Aiming at the low estimation accuracy of rotor speed and position and the system chattering in sensorless control of permanent magnet synchronous motor (PMSM), an adaptive neuro-fuzzy inference system (ANFIS) is proposed to optimize the flux sliding mode observer(FSMO). Compared with the traditional sliding mode observer, the FSMO improves the estimation accuracy of the rotor flux. The FSMO optimized by ANFIS realizes the on-line adjustment of the observer gain and reduces the system chattering. The improved PLL improves the estimation accuracy of the rotor speed and position. A simulation platform is established to verify the results which show …
Simulation Of Unmanned Tank Clusters Cooperative Combat Based On Military Rules, Chunyan Wang, Hao Ren, Minchi Kuang, Danfeng Wu, Xiangshu Cao, Heng Shi
Simulation Of Unmanned Tank Clusters Cooperative Combat Based On Military Rules, Chunyan Wang, Hao Ren, Minchi Kuang, Danfeng Wu, Xiangshu Cao, Heng Shi
Journal of System Simulation
Abstract: Modern warfare is developing towards the unmanned, informatized, and intelligent form. Being the important combat equipment in the future land warfare, unmanned tanks have greater advantages of mobility, safety, and economy. Single unmanned tank can not fulfill the complex tasks of large-scale battles as the cooperation of unmanned tank clusters can do. Focuses on the collaborative applications of unmanned tank clusters, the single unmanned tank system model is established, including dynamic control, decision-making, and weapon armor. A collaborative perception model of unmanned tank clusters is designed considering the unmanned tank's own state and the fusion situation. Based on the …
Modeling Of Traffic Flow Velocity Control Strategy For Human-Machine Mixed Driving At Signalized Intersections, Jianxu Zhang, Shuai Hu, Hongyi Jin
Modeling Of Traffic Flow Velocity Control Strategy For Human-Machine Mixed Driving At Signalized Intersections, Jianxu Zhang, Shuai Hu, Hongyi Jin
Journal of System Simulation
Abstract: In order to analyze the influence of speed control strategy of autonomous vehicle on the operation characteristics of traffic flow, a deterministic decision-making model for intersections with artificially driven vehicles considering the driver's influence on the acquisition of driving information is constructed. An automatic driving speed control strategy considering the influence of the speed of preceding vehicle is proposed, and the continuous Cellular Automata update rules for signalized intersections are constructed respectively. By introducing the different penetration rates of automatic driving, road saturation and control area length parameters, the influence of CAV speed control strategy on the traffic …
Research On Passenger Ship Evacuation Simulation Based On Social Force Model, Qimiao Xie, Shuaishuai Guo
Research On Passenger Ship Evacuation Simulation Based On Social Force Model, Qimiao Xie, Shuaishuai Guo
Journal of System Simulation
Abstract: Aiming at the influence of group behavior and different evacuation methods on the passenger ship evacuation process. Three evacuation methods of passengers arriving at the assembly stations with and without group behavior are provided, and the passenger assembly time, congestion area, congestion timing and duration are analyzed. The simulation results show that the group behavior has a significant effect on the passenger assembly time and increases the variation range of the passenger assembly time, and the congestion area with and without group behavior remains the same. The influences of group behavior on the congestion timing and duration are complicated, …
Layout Planning Of Metro-Based Underground Logistics System Network Considering Fuzzy Uncertainties, Wanjie Hu, Jianjun Dong, Rui Ren, Zhilong Chen
Layout Planning Of Metro-Based Underground Logistics System Network Considering Fuzzy Uncertainties, Wanjie Hu, Jianjun Dong, Rui Ren, Zhilong Chen
Journal of System Simulation
Abstract: Aming at the network design and optimization of metro-based urban underground logistics under uncertainties, the facility components of two-tier metro-based underground logistics system (M-ULS) are proposed. Focus on the comprehensive costs and system utilization rate, a M-ULS network flow assignment model is established based on the expectation of environmental benefits of underground freight transport. a M-ULS network location-allocation-routing fuzzy random programming model is established, and a crisp linearization method is presented. A solution portfolio combining discrete binary chaos particle swarm optimization-genetic algorithm and exact algorithms is designed for combinatorial optimization. Effectiveness of the presented models and algorithms is verified …
Variable Pitch Control Of Wind Power Generation System Based On Wiener Model, Yue Xu, Li Jia, Xuanyi Fu
Variable Pitch Control Of Wind Power Generation System Based On Wiener Model, Yue Xu, Li Jia, Xuanyi Fu
Journal of System Simulation
Abstract: Strong nonlinearity and large fluctuation are the characteristics of wind power generation system. Quickly controlling the output power of wind turbines within the rated range under wind speed random changes is the major problem of wind power system control. Aiming at the pitch control of 5 MW wind turbines, a pitch control scheme for wind power generation systems based on the Wiener model is proposed. On the basis of the special structure in which the linear and nonlinear links of the Wiener model can be separated, the controlled object of a generalized wind power system with linear properties …
Parallel Live Performance Simulation Based On A Multidimensional Hierarchy And Application, Jingsi Yang, Tianyu Huang, Gangyi Ding, Lijie Li, Peng Li
Parallel Live Performance Simulation Based On A Multidimensional Hierarchy And Application, Jingsi Yang, Tianyu Huang, Gangyi Ding, Lijie Li, Peng Li
Journal of System Simulation
Abstract: A parallel simulation method is proposed for modern live performance. By decomposing the live performance process from the top down, this method assists creators in delivering stage design and control with time and space constraints, which is unattainable for traditional live performances. A multi-layer constraint hierarchy is constructed to apply parallel simulation to art performances. The live performance procedure is continuously optimized by leveraging the circulation of data between virtual and physical stages. The parallel simulation method for stage space has been applied to a digital TV stage for ten years. The experiments show that parallel live performance simulation …
Dynamic Obstacle Avoidance Control Of Three-Order Multi-Robot Cooperative Formation, Yuchao Zhang, Yuan Jiang, Jiyang Dai
Dynamic Obstacle Avoidance Control Of Three-Order Multi-Robot Cooperative Formation, Yuchao Zhang, Yuan Jiang, Jiyang Dai
Journal of System Simulation
Abstract: Aiming at the obstacle avoidance and consensus control of underwater vehicles formation in a 3D complex environment, a cooperative formation dynamic obstacle avoidance control algorithm is proposed. An adaptive repulsion gain term based on the speed of dynamic obstacles is established and it is introduced into the repulsion potential field function to enable the robot to safely avoid static and dynamic obstacles. The potential field function based on the gain term of the potential field and the communication weight between the AUVs are defined to solve the robots of easy self collision and leaving the formation. The total acceleration …
Research On Time-Dependent Vehicle Routing Problem With Multiple Time Windows, Nan Li, Rong Hu, Bin Qian, Huaiping Jin, Naikang Yu
Research On Time-Dependent Vehicle Routing Problem With Multiple Time Windows, Nan Li, Rong Hu, Bin Qian, Huaiping Jin, Naikang Yu
Journal of System Simulation
Abstract: Aiming at the time-dependent vehicle routing problem with multiple time windows (TD_VRPMTW) that considers urban traffic congestion, a hybrid discrete gray wolf optimizer (HDGWO) is proposed. In the HDGWO, a new grey wolf individual updating formula is designed, and the integer coding method based on customer permutation is adopted, so that the algorithm can directly perform the global search based on GWO individual updating mechanism in the discrete problem solution space.A population initialization strategy based on the nature of the problem is designed to generate the initial population with high quality and diversity.The information exchange formula of …
Rigid-Liquid Coupling Simulation Of Liquid-Filled Spacecraft Based On Openfoam, Zhijun Song, Zongyu Chen, Lü Jing, Tianshu Wang
Rigid-Liquid Coupling Simulation Of Liquid-Filled Spacecraft Based On Openfoam, Zhijun Song, Zongyu Chen, Lü Jing, Tianshu Wang
Journal of System Simulation
Abstract: Aiming at the design of the spacecraft attitude control system, a simulation software for the rigid-liquid coupling calculation of the liquid-filled spacecraft is built on the basis of the open source CFD software OpenFOAM. In the moving boundary problem, the N-S equation in the non-inertial frame is derived to improve the calculation efficiency, which avoids a large number of grid conversion calculations of the moving grid method in the traditional CFD software. PIMPLE algorithm is used to build the sloshing dynamics solution module, and the variable step length Runge-Kutta method is used to build the attitude …
Effectiveness Evaluation Method Of Space-Based Information Systems Based On Sem, Chi Han, Wei Xiong, Wenwen Liu, Xiaolan Yu, Ping Jian
Effectiveness Evaluation Method Of Space-Based Information Systems Based On Sem, Chi Han, Wei Xiong, Wenwen Liu, Xiaolan Yu, Ping Jian
Journal of System Simulation
Abstract: Aiming at the nonlinear emergence of effectiveness of the coupling and interaction of space-based information system (SIS), an operational effectiveness evaluation (OEE) model based on structural equation modeling (SEM) is proposed. Through the analysis of capacity requirements and system composition, the internal connections of sub-systems are obtained, and the effectiveness evaluation index system is constructed. By considering the synergistic interaction within SIS, the linear and nonlinear SEMs are constructed respectively to evaluate the effectiveness, and the analytical model of OEE is established on the basis of the corresponding parameter equations. With the background of integrated joint operations under …
Bioinformation Heuristic Genetic Algorithm For Solving Tsp, Jia Xu, Fengqing Han, Qixin Liu, Xiaoxia Xue
Bioinformation Heuristic Genetic Algorithm For Solving Tsp, Jia Xu, Fengqing Han, Qixin Liu, Xiaoxia Xue
Journal of System Simulation
Abstract: Genetic algorithm (GA) is one of the universal path optimization algorithms for traveling salesman problem (TSP). Aiming at the slow convergence and unstable solution of the traditional GA, a bioinformation heuristic genetic algorithm (BHGA) is proposed. By optimizing the fitness function and initial population, the gene sequence comparison technique in bioinformatics is introduced to carry out the cross recombination sorting. The gene reversal operation is used to implement mutation, to accelerate the convergence speed and get a better path solution. The numerical examples in TSPLIB database are solved by BHGA and the experimental simulation results show that the …
Design And Implementation Of Uav Swarm Self-Organizing Search Model, Kan Li, Yunpeng Li, Jiangbo Zhao
Design And Implementation Of Uav Swarm Self-Organizing Search Model, Kan Li, Yunpeng Li, Jiangbo Zhao
Journal of System Simulation
Abstract: The UAV swarm self-organizing search for moving target under the urban threat is an important implement of UAV swarm. Though Agent-based complex system modeling and simulation tools, the framework of UAV swarm search simulation model is constructed, and the self-organizing search model of UAV swarm is designed. Under the possible threats to the operational use of UAVs, the concept of self-organizing search for UAV swarm is preliminarily realized and demonstrated, and the solution of autonomous decision making for UAV swarm based on the probability-based finite state machine model is explored, which is analyzed and verified by a case. …
Servicing Method Of Lvc Experiment Resources Based On Object Metamodel, Nan Du, Yaxin Tan, Bin Feng
Servicing Method Of Lvc Experiment Resources Based On Object Metamodel, Nan Du, Yaxin Tan, Bin Feng
Journal of System Simulation
Abstract: In the process of live-virtual-constructive (LVC) experiment there are a large number of heterogeneous simulation resource objects. Aiming at the traditional object model not meeting the rapid response experiment requirements of equipment systems in informationized war, the object metamodel based on LVC experiment resource servitization method research is studied. The object metamodel based on resource description method is given, based on three basic resource servitization forms of object interaction, message passing, remote method invocation, virtualization infrastructure object(VIO), VIO-virtualization object model (VIO-VOM) components of publish/subscribe, VIO-VOM components of aggregation, composition, inheritance, callback mechanism, Localclass-VOM, Message-VOM components are proposed. The …