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2021

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Articles 1381 - 1410 of 3477

Full-Text Articles in Computer Sciences

Editorial Board Jun 2021

Editorial Board

Karbala International Journal of Modern Science

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Automatic Detection Of Citrus Fruit And Leaves Diseases Using Deep Neural Network Model, Asad Khattak, Muhammad Usama Asghar, Ulfat Batool, Muhammad Zubair Asghar, Hayat Ullah, Mabrook Al-Rakhami, Abdu Gumaei Jun 2021

Automatic Detection Of Citrus Fruit And Leaves Diseases Using Deep Neural Network Model, Asad Khattak, Muhammad Usama Asghar, Ulfat Batool, Muhammad Zubair Asghar, Hayat Ullah, Mabrook Al-Rakhami, Abdu Gumaei

All Works

Citrus fruit diseases are the major cause of extreme citrus fruit yield declines. As a result, designing an automated detection system for citrus plant diseases is important. Deep learning methods have recently obtained promising results in a number of artificial intelligence issues, leading us to apply them to the challenge of recognizing citrus fruit and leaf diseases. In this paper, an integrated approach is used to suggest a convolutional neural networks (CNNs) model. The proposed CNN model is intended to differentiate healthy fruits and leaves from fruits/leaves with common citrus diseases such as Black spot, canker, scab, greening, and Melanose. …


Understanding Ransomware Trajectory To Create An Informed Prediction, J. D. Klusnick Jun 2021

Understanding Ransomware Trajectory To Create An Informed Prediction, J. D. Klusnick

University Honors Theses

Ransomware is a form of extortion in which digital files are rendered inaccessible until a ransom payment is made. Modern ransomware emerged in 2006 and its destructive influence has been expanding ever since. In recent years cybercriminals have evolved who they target, what computer systems they target, and how they infect those systems. Meanwhile, cybersecurity experts have modelled ransomware methods allowing them to innovate their defense techniques across three paradigms: recovery, detection, and prevention. Ultimately either ransomware attackers or ransomware defenders will dominate this ongoing conflict. A review of the literature indicates that the ransomware crime wave will likely be …


Characterizing Soil Stiffness Using Thermal Remote Sensing And Machine Learning, Jordan Ewing, T. Oommen, Paramsothy Jayakumar, Russell Alger Jun 2021

Characterizing Soil Stiffness Using Thermal Remote Sensing And Machine Learning, Jordan Ewing, T. Oommen, Paramsothy Jayakumar, Russell Alger

Michigan Tech Publications, Part 1

Soil strength characterization is essential for any problem that deals with geomechanics, including terramechanics/terrain mobility. Presently, the primary method of collecting soil strength parameters through in situ measurements but sending a team of people out to a site to collect data this has significant cost implications and accessing the location with the necessary equipment can be difficult. Remote sensing provides an alternate approach to in situ measurements. In this lab study, we compare the use of Apparent Thermal Inertia (ATI) against a GeoGauge for the direct testing of soil stiffness. ATI correlates with stiffness, so it allows one to predict …


Rebalancing Shared Mobility Systems By User Incentive Scheme Via Reinforcement Learning, Matthew Brian Schofield Jun 2021

Rebalancing Shared Mobility Systems By User Incentive Scheme Via Reinforcement Learning, Matthew Brian Schofield

Theses and Dissertations

Shared mobility systems regularly suffer from an imbalance of vehicle supply within the system, leading to users being unable to receive service. If such imbalance problems are not mitigated some users will not be serviced. There is an increasing interest in the use of reinforcement learning (RL) techniques for improving the resource supply balance and service level of systems. The goal of these techniques is to produce an effective user incentivization policy scheme to encourage users of a shared mobility system to slightly alter their travel behavior in exchange for a small monetary incentive. These slight changes in user behavior …


Windows Kernel Hijacking Is Not An Option: Memoryranger Comes To The Rescue Again, Igor Korkin Jun 2021

Windows Kernel Hijacking Is Not An Option: Memoryranger Comes To The Rescue Again, Igor Korkin

Journal of Digital Forensics, Security and Law

The security of a computer system depends on OS kernel protection. It is crucial to reveal and inspect new attacks on kernel data, as these are used by hackers. The purpose of this paper is to continue research into attacks on dynamically allocated data in the Windows OS kernel and demonstrate the capacity of MemoryRanger to prevent these attacks. This paper discusses three new hijacking attacks on kernel data, which are based on bypassing OS security mechanisms. The first two hijacking attacks result in illegal access to files open in exclusive access. The third attack escalates process privileges, without applying …


Adapting An Agent-Based Model Of Infectious Disease Spread In An Irish County To Covid-19, Elizabeth Hunter, John D. Kelleher Jun 2021

Adapting An Agent-Based Model Of Infectious Disease Spread In An Irish County To Covid-19, Elizabeth Hunter, John D. Kelleher

Articles

The dynamics that lead to the spread of an infectious disease through a population can be characterized as a complex system. One way to model such a system, in order to improve preparedness, and learn more about how an infectious disease, such as COVID-19, might spread through a population, is agent-based epidemiological modelling. When a pandemic is caused by an emerging disease, it takes time to develop a completely new model that captures the complexity of the system. In this paper, we discuss adapting an existing agent-based model for the spread of measles in Ireland to simulate the spread of …


Algebraic Graph-Assisted Bidirectional Transformers For Molecular Property Prediction, Dong Chen, Kaifu Gao, Duc Duy Nguyen, Xin Chen, Yi Jiang, Guo-Wei Wei, Feng Pan Jun 2021

Algebraic Graph-Assisted Bidirectional Transformers For Molecular Property Prediction, Dong Chen, Kaifu Gao, Duc Duy Nguyen, Xin Chen, Yi Jiang, Guo-Wei Wei, Feng Pan

Mathematics Faculty Publications

The ability of molecular property prediction is of great significance to drug discovery, human health, and environmental protection. Despite considerable efforts, quantitative prediction of various molecular properties remains a challenge. Although some machine learning models, such as bidirectional encoder from transformer, can incorporate massive unlabeled molecular data into molecular representations via a self-supervised learning strategy, it neglects three-dimensional (3D) stereochemical information. Algebraic graph, specifically, element-specific multiscale weighted colored algebraic graph, embeds complementary 3D molecular information into graph invariants. We propose an algebraic graph-assisted bidirectional transformer (AGBT) framework by fusing representations generated by algebraic graph and bidirectional transformer, as well as …


Turkic Interlingua: A Case Study Of Machine Translation In Low-Resource Languages, Jamshidbek Mirzakhalov Jun 2021

Turkic Interlingua: A Case Study Of Machine Translation In Low-Resource Languages, Jamshidbek Mirzakhalov

USF Tampa Graduate Theses and Dissertations

Machine Translation (MT) has the potential to bridge the gap between the developed world and the marginalized communities by making information more accessible in real-time. While there are over 7000 spoken languages in the world, only about a hundred have access to high-quality MT systems and even fewer enjoy the benefits of more advanced language technologies. Unfortunately, resource scarcity and the lack of digital infrastructure are only some of the many challenges associated with globalizing NLP. Many large-scale multilingual studies and datasets often get little to no feedback from native speakers or linguistic experts of the languages involved, leading to …


Development And Prospect Of Simulation Research In China, Xiaogang Qiu, Duan Hong, Xie Xu, Mengna Zhu Jun 2021

Development And Prospect Of Simulation Research In China, Xiaogang Qiu, Duan Hong, Xie Xu, Mengna Zhu

Journal of System Simulation

Abstract: It is important to treat modeling and simulation (M&S) as a discipline to advance its development. In China, M&S has been researched and applied over 40 years, and is gradually becoming an independent discipline. Modeling and simulating the complex systems are the challenge, however, this also brings grand opportunity for M&S to widen and improve itself. Since 1980s, the M&S community in China has realized the broad applications of M&S, comprehended M&S from multiple perspectives, conducted extensive research on basic questions, and discussed the composition of the basic simulation theory. By summarizing these achievements, the future works that have …


Multiple Object Tracking And Kinematic Simulation For Short Track Speed Skating, Li Qi, Hanlin Mo, Xiangdong Wang, Li Hua Jun 2021

Multiple Object Tracking And Kinematic Simulation For Short Track Speed Skating, Li Qi, Hanlin Mo, Xiangdong Wang, Li Hua

Journal of System Simulation

Abstract: Aiming at the problem that it is difficult to obtain the motion data of each athlete in the short track speed skating competition, an algorithm flow of multiple object tracking and kinematic simulation is proposed. A local matching metric is proposed to deal with the partial occlusion in monocular video and improve the tracking stability and robustness. The motion simulation method based on homography mapping and derivative of fitted curve is realized to estimate kinematic parameters such as velocity and acceleration. The experiments on Skating Track Multiple ObjectTracking (STMOT) verified the effectiveness and superiority of the proposed methods.


Decomposition Furnace Outlet Temperature Prediction Based On Elasticnet And Lstm, Guangyu Yu, Xueping Dong, Xiangmin Wang, Gan Min Jun 2021

Decomposition Furnace Outlet Temperature Prediction Based On Elasticnet And Lstm, Guangyu Yu, Xueping Dong, Xiangmin Wang, Gan Min

Journal of System Simulation

Abstract: The outlet temperature of the decomposition furnace is a key indicator in the cement production process. Aiming at the problem that traditional prediction methods only consider the influence of wind, coal, and materials, a temperature prediction model of ElasticNet combined with Long Short-Term Memory (LSTM) neural network is proposed. The ElasticNet-LSTM export temperature prediction model is constructed by using the ElasticNet method to estimate the parameters of different variables, fully considering the influencing factors and realizing the variable screening, and analyzing the influence of the number of hidden layers and nodes on the accuracy of the neural network. Simulation …


A Shared Memory Based Parallel Hierarchical Interest Matching Algorithm, Wenjie Tang, Junwei Cheng, Yiping Yao, Zhu Feng Jun 2021

A Shared Memory Based Parallel Hierarchical Interest Matching Algorithm, Wenjie Tang, Junwei Cheng, Yiping Yao, Zhu Feng

Journal of System Simulation

Abstract: Interest matching plays an important role in distributed simulation. However, because of huge number of simulation entities and frequent change of regions, interest matching consumes tremendous computation in large scale simulations. The ubiquity of multicore urges us to improve the performance of interest matching by parallelization. A shared memory based parallel hierarchical interest matching algorithm is propose to solve the problem. It maps subscribe regions into a full binary tree, and compares update regions with the tree in parallel. Due to the associative relationship between adjacent nodes, unnecessary comparisons can be eliminated. The experimental results demonstrate that the …


Time-Delay Estimation For Mimo Delay Systems With Unknown Structures, Xuguang Wang, Mengjie Feng, Su Jie, Jiale Quan Jun 2021

Time-Delay Estimation For Mimo Delay Systems With Unknown Structures, Xuguang Wang, Mengjie Feng, Su Jie, Jiale Quan

Journal of System Simulation

Abstract: In the unknown-structure delay system modeling, time-delays lead to a mismatch between the system inputs and outputs on the timeline and cause low system modeling accuracy. A time-delay estimation method is proposed for the unknown-structure MIMO (Multiple-Input Multiple-Output) delay systems. A general mathematical description is given from the algebraic point of view, the delay correlation function is defined, and a quantitative constraint between system input-output and time-delay is constructed. A greedy time-delay search algorithm is introduced based on the delay correlation function. Simulation experiments and real data experiments show the availability of the proposed method.


Fault Detection Of Wind Turbine Bearing Based On Bo-Sdae Multi-Source Signal, Dinghui Wu, Zhichao Zhu, Xinhong Han Jun 2021

Fault Detection Of Wind Turbine Bearing Based On Bo-Sdae Multi-Source Signal, Dinghui Wu, Zhichao Zhu, Xinhong Han

Journal of System Simulation

Abstract: Due to the discrepancy within signals from sensors of wind turbines caused by environmental interference, the fault detection results of wind turbine bearing will be affected and the multi-source signal fault diagnosis method is proposed to improve the reliability of fault detection. The time-domain and frequency-domain features of bearing vibration signals, noise signals and temperature signals are used for feature extraction,and then the features are transmitted to the stacked denoising autoencoders, which are optimized the hidden layer node structure by the Bayesian optimization algorithm to achieve multi-source signal feature fusion. Softmax function is used for classification. Experiments show that …


Rapid Development Technology Of Virtual Maintenance Training Simulation Model For Aviation Equipment, Rongqiang Li, Aibing Wen, Bin Hua, Jiajun Li, Jiang Bing Jun 2021

Rapid Development Technology Of Virtual Maintenance Training Simulation Model For Aviation Equipment, Rongqiang Li, Aibing Wen, Bin Hua, Jiajun Li, Jiang Bing

Journal of System Simulation

Abstract: Taking the practical application of the aircraft virtual maintenance training as the demand, the basic development process and technical means of the aircraft virtual maintenance training simulation model are analyzed, which solves the technical bottleneck in the popularization and application of the large-scale engineering. Aiming at the crucial problems such as the low efficiency in the development of maintenance training simulation model and the difficulties in updating the model, a rapid development process to support the large-scale engineering applications is proposed. The principles and implementation ways of three key technologies supporting the rapid development of virtual maintenance training simulation …


Day-Ahead Dispatching Model Of Source-Load Coordination Based On Response Behavior To Real-Time Pricing, Liu Yun, Han Song, Qiuli Huang Jun 2021

Day-Ahead Dispatching Model Of Source-Load Coordination Based On Response Behavior To Real-Time Pricing, Liu Yun, Han Song, Qiuli Huang

Journal of System Simulation

Abstract: In order to give full play to the regulating role of electricity price on the market, considering the difference of consumers' response behavior to real-time pricing, consumers are divided into short-term consumers, mixed consumers and long-term consumers, and the real-time pricing models of three types of consumers are constructed based on the electricity price elasticity matrix. On this basis, a day-ahead dispatching model of source-load coordination based on consumer’s response behavior to real-time pricing is established. With the help of the MOST toolkits in MATPOWER and the Mosek solver, the arithmetic analysis is developed in a modified IEEE 57-buses …


Spatial Knowledge Representation Model Of Simulation Scenario Based On Ontology, Zhu Jie, Hongjun Zhang Jun 2021

Spatial Knowledge Representation Model Of Simulation Scenario Based On Ontology, Zhu Jie, Hongjun Zhang

Journal of System Simulation

Abstract: Military simulation scenario has abundant spatial knowledge and is closely related to various models of combat simulation. In view of the lack of uniform specification for the description of simulation scenario knowledge, it is necessary to construct a spatial knowledge representation model in line with spatial thinking to effectively analyze the spatial entities and their interrelationships in simulation scenario. The ontology method is used to establish spatial knowledge domain ontology and form the formal description specification of spatial knowledge concept; the spatial knowledge structure is described hierarchically by using the method of concept knowledge tree, clarifying the semantic logic …


Performance Analysis Of Cognitive Cooperative Systems Based On Quadrature Spatial Modulation, Guo Hui, Xuejiao Guo, Ting Qiao, Liu Meng Jun 2021

Performance Analysis Of Cognitive Cooperative Systems Based On Quadrature Spatial Modulation, Guo Hui, Xuejiao Guo, Ting Qiao, Liu Meng

Journal of System Simulation

Abstract: The cognitive cooperative communication system based on quadrature spatial modulation (QSM) is proposed to solve the problems of inter-channel interference and inter-antenna synchronization. The mean power allocation algorithm is used to analyze performance of the system. In addition, the relay nodes and the destination node decode their received signals with the maximum likelihood detection algorithm. The exact closed expressions of outage probability under random relay selection (RRS), suboptimal relay selection (SRS) and optimal relay selection (ORS) are derived respectively. The approximate outage probabilities in the high signal-to-noise ratio region are derived, and the diversity gains of three relay …


An Improved Differential Evolution Algorithm For Fractional Order System Identification, Yu Wei, Henghui Liang, Luo Ying Jun 2021

An Improved Differential Evolution Algorithm For Fractional Order System Identification, Yu Wei, Henghui Liang, Luo Ying

Journal of System Simulation

Abstract: In order to build a high-precision fractional-order model, which needs to identify more parameters, an improved differential evolution algorithm is proposed for the identification of fractional-order systems. In the mutation strategy, the basis vector is randomly selected from the optimal individual population, and the scaling factor and cross-probability factor are adaptively adjusted according to the information of the successfully mutated individual during the search process to improve the exploration and mining capabilities of the algorithm. By solving the five test functions, the improved algorithm is proved to have strong solving ability. Taking the fractional-order model of permanent magnet synchronous …


Auxiliary Application Of Wearable Computing Equipment In Industrial Intelligent Operation And Maintenance, Shen Yi, Wu Gang, Zhou Rui Jun 2021

Auxiliary Application Of Wearable Computing Equipment In Industrial Intelligent Operation And Maintenance, Shen Yi, Wu Gang, Zhou Rui

Journal of System Simulation

Abstract: Virtual operation and intelligent operation and maintenance based on wearable integrated computing devices have become a trend of lean industrial production. The operation and maintenance efficiency of tobacco production equipment can be directly improved by using mixed reality, virtual simulation and other technologies, combined with virtual interactive assistance applications . Combining 5G, IoT and big data technologies, a system design of wearable smart devices is proposed based on smart glasses with multi-dimensional spatial information synchronization, computer vision and natural perceptual interaction, and a set of design scheme for auxiliary operation and maintenance of cigarette equipment is innovated. The intelligent …


Landscape-Based Mutational Sensitivity Cartography And Network Community Analysis Of The Sars-Cov-2 Spike Protein Structures: Quantifying Functional Effects Of The Circulating D614g Variant, Gennady M. Verkhivker, Steve Agajanian, Deniz Yasar Oztas, Grace Gupta Jun 2021

Landscape-Based Mutational Sensitivity Cartography And Network Community Analysis Of The Sars-Cov-2 Spike Protein Structures: Quantifying Functional Effects Of The Circulating D614g Variant, Gennady M. Verkhivker, Steve Agajanian, Deniz Yasar Oztas, Grace Gupta

Mathematics, Physics, and Computer Science Faculty Articles and Research

We developed and applied a computational approach to simulate functional effects of the global circulating mutation D614G of the SARS-CoV-2 spike protein. All-atom molecular dynamics simulations are combined with deep mutational scanning and analysis of the residue interaction networks to investigate conformational landscapes and energetics of the SARS-CoV-2 spike proteins in different functional states of the D614G mutant. The results of conformational dynamics and analysis of collective motions demonstrated that the D614 site plays a key regulatory role in governing functional transitions between open and closed states. Using mutational scanning and sensitivity analysis of protein residues, we identified the stability …


Discussing Digital Twin From Of Modeling And Simulation, Zhang Lin, Lu Han Jun 2021

Discussing Digital Twin From Of Modeling And Simulation, Zhang Lin, Lu Han

Journal of System Simulation

Abstract: The development and evolution of modeling and simulation technology, and its importance in scientific and technological progress are briefly reviewed. The intrinsic relation between digital twin and modeling and simulation is revealed by analyzing the background and concept of digital twin. The way to build and evaluate a digital twin based on modeling and simulation theoretical methods is discussed. to ensure the credibility.


Multi-View Human Action Recognition Based On Deep Neural Network, Zhao Ying, Lu Yao, Zhang Jian, Qidi Liang, Long Wei Jun 2021

Multi-View Human Action Recognition Based On Deep Neural Network, Zhao Ying, Lu Yao, Zhang Jian, Qidi Liang, Long Wei

Journal of System Simulation

Abstract: A novel deep neural network named CNN+CA(Convolutional Neural Network plus Context Attention) model is constructed and a new recognition algorithm based on sequence matching is presented to improve the recognition accuracy of MVHAR (Multi-view Human Action Recognition). A CNN(Convolutional Neural Network) is designed to automatically learn multi-view fusion features; the CA (Context Attention) module is introduced to selectively focus on the parts of the features that are relevant for the recognition task; the proposed recognition algorithm based on sequence matching is used to realize MVHAR. The experimental results on the IXMAS dataset and the i3DPost dataset …


Design And Simulation For Compensatory Controller Of Aircraft Rudder Electro-Hydraulic Loading System, Xiaolin Liu, Jingyi Wu Jun 2021

Design And Simulation For Compensatory Controller Of Aircraft Rudder Electro-Hydraulic Loading System, Xiaolin Liu, Jingyi Wu

Journal of System Simulation

Abstract: The electro-hydraulic loading system of aircraft rudder is a torque servo system which is a special equipment for testing the performance of rudder. In order to reduce the influence of surplus force in loading system, a control method for PID controller tuned in real time by radial basis function neural network based on particle swarm optimization is proposed. The characteristics of global and hyper parameter optimization of particle swarm optimization are used to improve the control effect of the controller. The learning coefficient based on annealing is used to accelerate the network convergence speed. Simulation results show that, compared …


An Artificial Emotion Model For The Mutual Mapping Between Discrete State And Dimensional Space, Zhihang Tian, Xiaming Chen, Dazhi Jiang Jun 2021

An Artificial Emotion Model For The Mutual Mapping Between Discrete State And Dimensional Space, Zhihang Tian, Xiaming Chen, Dazhi Jiang

Journal of System Simulation

Abstract: Emotional intelligence is an important component and development direction of machine intelligence. The purpose of artificial emotion model is to construct emotion models for machines to develope systematic ability of emotion understanding and expression. However, the existing methods are still insufficient in artificial emotion modeling ability. Aiming at the key factor of personalization in the construction of artificial emotion model, this paper proposes a method of mutual mapping between discrete emotion state and dimension space state, and constructs a machine personalized artificial emotion model based on Big Five personality model and emotion state transfer model. The relevant experimental results …


System Reliability Modeling In Competitive Failure Considering Zoned Shock Effect, Qiguo Hu, Gao Zhan Jun 2021

System Reliability Modeling In Competitive Failure Considering Zoned Shock Effect, Qiguo Hu, Gao Zhan

Journal of System Simulation

Abstract: Shocks have certain effects on system reliability, and how to quantify the degree of shock loads becomes the key of system reliability analysis. The reliability modeling problem of system suffered from different shock strength is researched based on degradation process competing with sudden failure. Shock process is descripted by extreme shock and two types of degradation processes are descripted by Wiener process under the condition of shifting failure threshold. Aiming at different intensity shocks on the system, the different shock load suffered by zoned shock effect is partitioned, the distribution function of the two types of failure processes is …


Time-Varying Ocean Channel Modeling Method, Yuehua Pei, Su Wei, Jincheng Tao, Xialin Jiang Jun 2021

Time-Varying Ocean Channel Modeling Method, Yuehua Pei, Su Wei, Jincheng Tao, Xialin Jiang

Journal of System Simulation

Abstract: For the ocean channel with extremely complicated situation, an underwater acoustic channel modeling algorithm which can reflect the sparsity, time-varying and space-varying characteristics is proposed. Based on the prior information obtained from the sea trials in a specific sea area, the statistical characteristics of the channel impulses response structure with time and space are obtained. According to the obtained channel sparsities and non-zero position vectors’ statistics, a time-varying underwater acoustic channel model match the real environment is generated. Based on the measured data of marine communication in specific sea area, the simulation results show that the proposed …


Bilingual Harmony Micro-Simulation Model And Computational Experiment, Shouming Zhang, Zhiping Wang, Guihong Bi, Zhenghua Zeng Jun 2021

Bilingual Harmony Micro-Simulation Model And Computational Experiment, Shouming Zhang, Zhiping Wang, Guihong Bi, Zhenghua Zeng

Journal of System Simulation

Abstract: Under the background of urbanization, the weak connection of social networks has increased, which has challenged the protection of vulnerable languages. A new social network with remote weak connection is constructed based on the improved modeling method of agent social circle network; in addition to considering the influence of language status and the language population ratio on the language evolution mechanism of different populations, a new mechanism is introduced for the influence of bilinguals on the transition from monolingual to bilingual, and the influence of language attitudes and network connections on language choice behaviors; an improved agent language level …


Explicit Model Predictive Control For Intelligent Vehicle Lateral Trajectory Tracking, Leng Yao, Shuen Zhao Jun 2021

Explicit Model Predictive Control For Intelligent Vehicle Lateral Trajectory Tracking, Leng Yao, Shuen Zhao

Journal of System Simulation

Abstract: To ensure the accuracy, driving stability and online real-time of intelligent vehicle tracking control, an explicit model predictive tracking control method is designed. The cost functions and constraints for tracking accuracy and driving stability in the prediction time domain are proposed. The tracking control problem is transformed into the optimization of the active steering angle with dynamic disturbances. To improve the real-time performance, the traditional model predictive control system is transformed into an equivalent explicit polyhedral piece-wise affine (PPWA) system, and the active steering angle of front wheel is gained by the explicit law on parameter partition. Carsim and …