Engineering Commons^™

Research On Sliding Mode Control Of Robotic Arm Based On Fractional Calculus, Zhang Xin, Jiaxin Li

Journal of System Simulation

Abstract: An effective fractional order sliding mode control method is proposed for the nonlinear and uncertain robotic arm system by combining the advantages of the fractional calculus theory and the sliding mode control strategy. In the design of the controller, the fractional calculus is introduced into the sliding mode control by using the fractional order reaching law and the fractional order sliding mode control law respectively, and is proved by the Lyapunov theory to ensure the stability of the system. The proposed control method is applied to a two-joint robotic arm and is verified by the MATLAB simulation software. The …

Modeling Analysis And Prediction On Ncp Epidemic Transmission, Huaxiong Sheng, Wu Lin, Changliang Xiao

Journal of System Simulation

Abstract: The modeling analysis on the NCP (Novel Coronavirus Pneumonia) epidemic transmission before and after the closure of Wuhan is presented. On the basis of preprocessing the epidemic data, the classical SIR model and differential recurrence method are used to analyze and forecast the epidemic situation in the stage of control. The theoretical value and measured value fits well. In the stage of free transmission, the logistic model is used to compare and analyze the epidemic data five days in advance or later with the actual data to show the importance of taking the epidemic prevention measures in time. The …

Optimization Algorithm Based On Human Infection With Avian Influenza, Guangqiu Huang, Qiuqin Lu

Journal of System Simulation

Abstract: To get the global optimal solution of some complex nonlinear optimization problems, an optimization algorithm based on the human avian influenza infectious diseases is proposed by using its dynamic model of cross species transmission. Applies the H7N9 infectious disease model to create the operators S^u-S^u, I^u-I^u, S^u-I^u, I^u-S^u, S^u-D^u, I^u-D^u, and to enable the individuals to exchange information among the same species and cross-species. The S^u-S^u and I^u-I^u operators …

Research On Failure Modes Analysis Based On Weighted Evidence Theory, Lulu Shao, Jihong Han, Niu Kan, Xiaohu Liu, Shao Fang

Journal of System Simulation

Abstract: Aiming at the risk priority numbers of different failure modes being equal and the criticality of the fault modes changing greatly due to the tiny change of the risk parameters, a method of the failure modes analysis based on the weighted evidence theory is proposed from the perspective of the methodology of dealing with the uncertainty problem. The method qualifies the epistemic uncertainty existing in the expert evaluation of the risk parameters into the basic belief assignment and expert attribute weight respectively, and the information propagation and processing of the epistemic uncertainty is solved, and the ordered arrangement …

Design Of Virtual Training System For Horizontally Oriented Drill Based On Unity3d, Guojun Wen, Xia Yu, Yudan Wang, Zifei Hu, Wu Dan

Journal of System Simulation

Abstract: Aiming at the equipment shortage, serious resource loss and hidden dangers in traditional horizontally oriented drilling rig training, a design scheme of the horizontally oriented drilling rig virtual training system based on the Unity3D is proposed. An experimental platform is built to verify the feasibility. The solidworks, 3dsMax model construction, Unity3D software virtual animation and scene development, Rodrigues rotation matrix 3D trajectory algorithm derivation, data acquisition (DAQ), system software and hardware communication and other technical content are used in the program. The experimental results show that the scheme is feasible, the system has the good operability and true immersion …

High-Fidelity Simulation Of Video-Assisted Thoracoscopic Surgery Lobectomy, Peng Liu, Weixin Si, Zheng Rui, Xiangyun Liao, Dongliang Xu, Ping'an Wang

Journal of System Simulation

Abstract: The virtual reality simulator of the video-assisted thoracoscopic (VATS) surgery lobectomy is of great value to the surgeon's surgical training and planning. In order to simulate the high-fidelity video-assisted thoracoscopic lobectomy, a VATS lobectomy simulator to realistically and efficiently simulate the different surgical operations during the VATS lobectomy procedure is developed. Based on the Position-Based Dynamics framework, the deformation induced by tool-tissue and tissue-tissue interactions, soft tissue cuts as well as subsequent surgical suture operations is simulated. The Marching Cubes algorithm is employed to achieve the surface rendering, especially for the cutting process. The GPU parallel computing technique is …

Application Of Improved Inverse Decoupling Active Disturbance Rejection Internal Model Control In Grinding, Zhou Ying, Qiaojuan Jia, Zhang Yan, Mingxin Chang

Journal of System Simulation

Abstract: Aiming at the characteristics of the multivariable, strong coupling and large time delay of the grinding classification system, the improved inverse decoupling active disturbance rejection internal model control method is proposed. The inverse decoupling method is used to realize the decoupling of the grinding classification system, and the improved internal model control and linear active disturbance rejection control are adopted for the decoupled subsystem. By introducing the internal model compensator and the gain to compensate the time delay, the dependence of the system upon the model is reduced .The model mismatch, external disturbance and uncertainties are suppressed by adjusting …

Modeling And Simulation For Prevention And Control Of Drug Abuse And Drug-Related Crime Based On System Dynamics, Liu Feng

Journal of System Simulation

Abstract: In the existing drug abuse dynamics models, the drug users are assumed to be permanent immune to drugs after rehabilitation and the possibility of the recovery drug users being susceptible again is neglected. To solve the problem, through the system dynamics (SD) method, the evolution process of the drug-related crowds is analyzed, and a relevant model based on the transient immunity is constructed. The trends of the drug abuse and drug-related crime are predicted by the simulation experiments, and the sensitivity analysis indicates that the rate of contact and exposure to drugs is the most sensitive factor of the …

A Route Recovery Mechanism Using Hybrid Anti-Interference Method, Ziwen Sun, Yanqi Zhang, Yimin Xu

Journal of System Simulation

Abstract: Aiming at the jamming attacks in the industrial wireless sensor networks, a route recovery mechanism based on the WirelessHART graph routing is proposed. The jamming attack detection method is used to obtain the node and area being attacked by the jamming attack, the uncoordinated frequency hopping spread spectrum is used to generate the frequency hopping sequence of the node of being attacked by the jamming attack and that of the surrounding nodes, so that the traditional frequency hopping spread spectrum is performed on the nodes. Detects again, and combines the routing cost and the WirelessHART graph routing …

Non-Contact Object Size Acquisition Based On Visual-Inertial Sensor Fusion, Kang Lai, Yingmei Wei, Jiang Jie, Yuxiang Xie

Journal of System Simulation

Abstract: In consideration of the visual data and the data from the inertial measurement unit (IMU) having the different characteristics, the 6D pose of the visual sensor is recovered from the captured video by using the vision-based 3D reconstruction techniques, the obtained pose information and inertial measurements is fused via the spatial-temporal alignment, and based on the determined scale of the visual 3D reconstruction the non-contact measurement of a scene is performed. The proposed approach achieves a relative measurement error of about 3% in the non-contact object size estimation experiment. As it does not require the additional calibration object …

Optimization Design And Locomotion Characteristics Analysis Of Wheeled Traction Robot, Wu Wei, Li Bo, Nana Liu, Guangzhi Ma

Journal of System Simulation

Abstract: To evaluate quantitatively the dynamic locomotion characteristics and obstacle performance of the wheeled traction robot in horizontal well with single pipe diameter, the mechanical model of the crawling module of the wheeled traction robot is established and the structural and size parameters are optimized. The ADAMS model of the current robot is presented, and the Simulink models of three parts of the driving module, supporting mechanism and traction resistance are built. A specified method of the ADAMS/Simulink joint simulation modeling is proposed to analyze the locomotion characteristics and obstacle performance of the wheeled traction robot. The simulation results …

Prediction Of Flight Taxi-Out Time In A Busy Airport Based On Lwsvr, Zhiwei Xing, Songyue Jiang, Luo Qian, Luo Xiao

Journal of System Simulation

Abstract: Aiming at improving the accuracy of predicting the flight taxi-out time in a busy airport, based on the local regression and weighted support vector regression, a prediction model of the locally weighted support vector regression is proposed. The model uses the K nearest neighbor method to reduce the capacity of the training sample set and build a predictive model for each predicted sample. The bandwidth parameter of the Gaussian weighting function is optimized with the Mahalanobis distance between the forecast sample and training samples, and the weighting coefficients are obtained. Combining the airport departure flight data in simulation analysis, …

Two-Stage Dynamic Emergency And Disaster Resistance Operation Strategy For Active Distribution Network, Zhang Wei, Li Quan, Yuqiu Zhou, Yuhang Luo, Peifeng Xi

Journal of System Simulation

Abstract: The persistence and gradual change of the typhoons and other dynamic disasters, increase the complexity of the fault recovery process. In order to quickly restore the power to the active distribution network, a two-stage dynamic emergency operational strategy is proposed and the corresponding overall optimization model is established. The strategy includes the resource allocation plan, island partition scheme and cooperative scheme of the emergency repair and restoration. In the first stage, the pre-disaster resource allocation plan is made according to the travel time and attribute matching situation between the disaster-stricken areas and the repair resources. In the second stage, …

Simulation Research On Effectiveness Of Reward And Punishment Strategy In Open-Pit Mines, Xingxin Nie, Cunrui Bai

Journal of System Simulation

Abstract: Mining safety accidents occur frequently, and one of the main causes is the miners' Intentional Unsafe Behavior (IUB), and therefore implementing the reward and punishment strategy on it is the key coping strategy. In order to study how the reward and punishment strategy acts on the Intentional Unsafe Behavior (IUB) of the miners and how effective the strategy is, based on the Behavioral Economics + IUB Diffusion Theory, combined with the Multi-Agent model to analyze the influencing factors of the miners' IUB, and based on the work situation adaptability function and the unsafe behavior adaptability function, the simulation model …

Model And Simulation Of Interactive Dissemination Of Multiple Public Opinion Information Under Government Intervention, Zhiying Wang, Weikang Wang, Chaolong Yue

Journal of System Simulation

Abstract: In order to identify the interactive dissemination rules of the multiple public opinion information (POI) in major emergencies and make the intervention decisions more pertinently, an intervention model of interactive dissemination is proposed. The model integrates the characteristics of the unequal competition of multiple POI, expands the existing intervention model of the single POI dissemination, and could analyze the intervention measures from the global perspective of the interactive dissemination. Case analysis and simulation results show that the proposed model could well simulate the evolution of the interactive transmission of the multiple POI. Although the strong POI is more harmful …

A Real-Time Internet Of Things (Iot) Based Affective Framework For Monitoring Emotions In Infants, Alhagie Sallah

Electrical Engineering Theses

An increase in the number of working parents has led to a higher demand for remotely monitoring activities of babies through baby monitors. The baby monitors vary from simple audio and video monitoring frameworks to advance applications where we can integrate sensors for tracking vital signs such as heart rate, respiratory rate monitoring. The Internet of Things (IoT) is a network of devices where each device can is recognizable in the network. The IoT node is a sensor or device, which primarily functions as a data acquisition unit. The data acquired through the IoT nodes are wirelessly transmitted to the …

A Physics-Based Machine Learning Study Of The Behavior Of Interstitial Helium In Single Crystal W–Mo Binary Alloys, Adib J. Samin

Faculty Publications

In this work, the behavior of dilute interstitial helium in W–Mo binary alloys was explored through the application of a first principles-informed neural network (NN) in order to study the early stages of helium-induced damage and inform the design of next generation materials for fusion reactors. The neural network (NN) was trained using a database of 120 density functional theory (DFT) calculations on the alloy. The DFT database of computed solution energies showed a linear dependence on the composition of the first nearest neighbor metallic shell. This NN was then employed in a kinetic Monte Carlo simulation, which took into …

Using Taint Analysis And Reinforcement Learning (Tarl) To Repair Autonomous Robot Software, Damian Lyons, Saba Zahra

Faculty Publications

It is important to be able to establish formal performance bounds for autonomous systems. However, formal verification techniques require a model of the environment in which the system operates; a challenge for autonomous systems, especially those expected to operate over longer timescales. This paper describes work in progress to automate the monitor and repair of ROS-based autonomous robot software written for an a-priori partially known and possibly incorrect environment model. A taint analysis method is used to automatically extract the data-flow sequence from input topic to publish topic, and instrument that code. A unique reinforcement learning approximation of MDP utility …

A Capacitive Sensing Gym Mat For Exercise Classification & Tracking, Adam Goertz

Computer Science and Computer Engineering Undergraduate Honors Theses

Effective monitoring of adherence to at-home exercise programs as prescribed by physiotherapy protocols is essential to promoting effective rehabilitation and therapeutic interventions. Currently physical therapists and other health professionals have no reliable means of tracking patients' progress in or adherence to a prescribed regimen. This project aims to develop a low-cost, privacy-conserving means of monitoring at-home exercise activity using a gym mat equipped with an array of capacitive sensors. The ability of the mat to classify different types of exercises was evaluated using several machine learning models trained on an existing dataset of physiotherapy exercises.

Predicting Disease Progression Using Deep Recurrent Neural Networks And Longitudinal Electronic Health Record Data, Seunghwan Kim

McKelvey School of Engineering Graduate Student Theses & Dissertations

Electronic Health Records (EHR) are widely adopted and used throughout healthcare systems and are able to collect and store longitudinal information data that can be used to describe patient phenotypes. From the underlying data structures used in the EHR, discrete data can be extracted and analyzed to improve patient care and outcomes via tasks such as risk stratification and prospective disease management. Temporality in EHR is innately present given the nature of these data, however, and traditional classification models are limited in this context by the cross- sectional nature of training and prediction processes. Finding temporal patterns in EHR is …

Predicting Disease Progression Using Deep Recurrent Neural Networks And Longitudinal Electronic Health Record Data, Seunghwan Kim

McKelvey School of Engineering Graduate Student Theses & Dissertations

Electronic Health Records (EHR) are widely adopted and used throughout healthcare systems and are able to collect and store longitudinal information data that can be used to describe patient phenotypes. From the underlying data structures used in the EHR, discrete data can be extracted and analyzed to improve patient care and outcomes via tasks such as risk stratification and prospective disease management. Temporality in EHR is innately present given the nature of these data, however, and traditional classification models are limited in this context by the cross-sectional nature of training and prediction processes. Finding temporal patterns in EHR is especially …

A Framework For Vector-Weighted Deep Neural Networks, Carter Chiu

UNLV Theses, Dissertations, Professional Papers, and Capstones

The vast majority of advances in deep neural network research operate on the basis of a real-valued weight space. Recent work in alternative spaces have challenged and complemented this idea; for instance, the use of complex- or binary-valued weights have yielded promising and fascinating results. We propose a framework for a novel weight space consisting of vector values which we christen VectorNet. We first develop the theoretical foundations of our proposed approach, including formalizing the requisite theory for forward and backpropagating values in a vector-weighted layer. We also introduce the concept of expansion and aggregation functions for conversion between real …

Energy-Efficient Data Transmission With Clustering And Compressive Sensing In Wireless Sensor Networks, Alagirisamy Mukil

Student Works (2020-2029)

One of the most important application of wireless sensor network is environmental monitoring. The application involves lifetime of sensor nodes for longer duration associating its energy module. Wireless sensor nodes deployed in sensing field aggregate enormous amount of sensed data and transfer them to the sink. The inherent limitation of energy carried within the battery of sensor nodes fetches extreme difficulty to acquire adequate network lifetime, becoming a bottleneck in forwarding data to sink. Hence the motivation is to reduce the amount of data transfer and attain energy efficiency. This is achieved by clustering and compressive sensing techniques. First objective …

Partial Discharge Classification For Xlpe Cable Joints Using K Nearest Neighbors Algorithm, Mohd Salleh Muhammad Shairazi

Student Works (2020-2029)

Due to excellent mechanical and electrical properties, cross-linked polyethylene (XLPE) cables are commonly used in the power industry. However, cable joints are the weakest part of XLPE cables and are susceptible to insulation failures. Cable joint insulation breakup can cause large losses for power companies. It is therefore necessary to evaluate the consistency of the insulation for early detection of insulation failure. It is known that there is a link between the partial discharge (PD) and the quality of the insulation. PD analysis is an important tool for assessing the quality of insulation in cable joints. In this study, XLPE …

Hierarchical Multiagent Reinforcement Learning For Maritime Traffic Management, Arambam James Singh, Akshat Kumar, Hoong Chuin Lau

Research Collection School Of Computing and Information Systems

Increasing global maritime traffic coupled with rapid digitization and automation in shipping mandate developing next generation maritime traffic management systems to mitigate congestion, increase safety of navigation, and avoid collisions in busy and geographically constrained ports (such as Singapore's). To achieve these objectives, we model the maritime traffic as a large multiagent system with individual vessels as agents, and VTS (Vessel Traffic Service) authority as a regulatory agent. We develop a hierarchical reinforcement learning approach where vessels first select a high level action based on the underlying traffic flow, and then select the low level action that determines their future …

Development Of Fully Balanced Ssfp And Computer Vision Applications For Mri-Assisted Radiosurgery (Mars), Jeremiah Sanders

Dissertations and Theses (Open Access)

Prostate cancer is the second most common cancer in men and the second-leading cause of cancer death in men. Brachytherapy is a highly effective treatment option for prostate cancer, and is the most cost-effective initial treatment among all other therapeutic options for low to intermediate risk patients of prostate cancer. In low-dose-rate (LDR) brachytherapy, verifying the location of the radioactive seeds within the prostate and in relation to critical normal structures after seed implantation is essential to ensuring positive treatment outcomes.

One current gap in knowledge is how to simultaneously image the prostate, surrounding anatomy, and radioactive seeds within the …

Classification Of Labour Pain Using Electroencephalogram Signal Based On Wavelet Method, Chong Yeh Sai

Student Works (2020-2029)

Electroencephalogram (EEG) is the recording of electrical activity of the cerebral cortex through electrodes placed on the scalp. EEG is used to acquire neurophysiological signals for application in clinical diagnosis and brain computer interface (BCI). However, in practical settings the EEG signals are often contaminated by signal artifacts known as the biological and environmental artifacts. These artifacts degrade EEG signals, thereby obstructing clinical diagnosis or BCI applications by distorting the observed power spectrum. Procedures for automated removal of EEG artifacts are frequently sought after in pre-processing and filtering of the EEG signals. In recent years, a combination of independent component …

Enhancing Cellular Communications For Uavs Via Intelligent Reflective Surface, Dong Ma, Ming Ding, Mahbub Hassan

Research Collection School Of Computing and Information Systems

Intelligent reflective surfaces (IRSs) capable of reconfiguring their electromagnetic absorption and reflection properties in real-time are offering unprecedented opportunities to enhance wireless communication experience in challenging environments. In this paper, we analyze the potential of IRS in enhancing cellular communications for UAVs, which currently suffers from poor signal strength due to the down-tilt of base station antennas optimized to serve ground users. We consider deployment of IRS on building walls, which can be remotely configured by cellular base stations to coherently direct the reflected radio waves towards specific UAVs in order to increase their received signal strengths. Using the recently …

Multi-Objective Signal Timing Optimal Model For Rural-Urban Fringe Area Intersection, Xiaoyu Zhang, Chunfu Shao

Journal of System Simulation

Abstract: With the acceleration of the urbanization process in our country, the road traffic problems in the urban-rural fringe area are becoming serious. In order to improve the traffic efficiency, environmental benefits and traffic safety, a multi-objective optimal model for signal timing is established under the comprehensive consideration of several factors, such as the delay, capacity, number of stops and vehicle emissions. The genetic algorithm is used to solve the problem. A typical intersection is taken as the example for the analysis and the improved design schemes can be achieved and evaluated by the road traffic simulation. The …

Lightmap-Based Gi Collaborative Rendering System For Web3d Application, Shao Wei, Liu Chang, Jinyuan Jia

Journal of System Simulation

Abstract: For the real-time dynamic lighting rendering in low-end web environment, a view-independent collaborative real-time rendering system is presented. The whole system consists of a cloud renderer which produces the global illumination, a web renderer which computes the local illumination, and a scalable collaboration solution which takes the user behavior into account to adjust the range and frequency of the lighting computation. The cloud renderer computes the lighting data into the Lightmap, streams the Lightmap to the web client. After computing the direct light, the web renderer achieves the global illumination information by Sampling the Lightmap, and shows the …