Engineering Commons^™

Fast 3d Medical Image Registration Based On Geometric Feature Invariants, Juping Gu, Tianyu Cheng, Jianping Wang, Hua Liang, Fengshen Zhao, Jiang Ling

Journal of System Simulation

Abstract: Aiming at the of large amount of computational data and low registration efficiency in 3D cranial medical image registration, a fast registration method based on geometric feature space constraints is proposed. The algorithm extracts three-dimensional contour point clusters, and proposes a feature construction method based on the optimal fitting ring of point clusters. The feature rings and the centroids of each layer are used as feature quantities, and the fast registration is completed by using Iterative Closest Point (ICP) method. The experimental results show that the method has less computation amount, high satisfactory registration accuracy and much faster registration …

Research On Improvement Of Parameters Calibration Method Of Microscopic Traffic Simulation Model, Chenjing Zhou, Yacong Gao, Rong Jian

Journal of System Simulation

Abstract: Model parameter calibration is the precondition of application of micro traffic simulation technology. In view of the lack of refined analysis in the model parameter calibration classification and calibration result determination, the corresponding improvement is proposed. The parameter calibration system divides global parameters and local parameters, provides a micro-simulation model parameter calibration method that combines engineering measurement and intelligent optimization. Based on the information entropy as the analysis index of the parameter calibration results, a method of parameter recursion after clustering is proposed. On the basis of the actual survey data of signalized intersections, A simulation experiments and …

Design And Simulation On A Novel Sliding Mode Control For Linear Induction Motor, Kaiwei Han, Wang Yan, Zhicheng Ji

Journal of System Simulation

Abstract: The speed-tracking problem of linear induction motors under the influence of unmatched disturbances is studied. Based on the extended disturbance observers, the novel sliding mode controllers are designed to make the motor have effective response characteristics under unmatched disturbances. The extended disturbance observersis designed for the unmatched disturbances in the linear induction motor model with edge effects. The observations of the disturbance derivatives are filtered. The novel sliding mode controllers are designed based on the observations of the disturbances and their derivatives. The simulations results show that the designed controller has effective response characteristics and robustness. In addition, it …

A Fast Latin Hyper Cube Experiment Design Method Based On Soduku Grouping, Tiantian Zhang, Li Ni, Guanghong Gong, Yuanjie Lu

Journal of System Simulation

Abstract: In order to solve the long optimization time and parameter level combination explosion in the complex experiment design space of Latin Hypercube design, which is one of the most popular method in experiment design, a fast Soduku grouping-based method is proposed. The optimal seed design is expanded and transformed in the grouped spaces. Experiments are conducted to compare the Soduku grouping-based Latin Hypercube design method with other two commonly used Latin Hypercube design methods in the middle and high dimension experiment space. The results show that Soduku grouping method is more efficient in computation and has better space-filling performance.

Container-Based Automatic Packaging Technology For Complex System Simulation Application, Wang Shuai, Zhu Feng, Yiping Yao, Wenjie Tang, Yuhao Xiao

Journal of System Simulation

Abstract: Container-based technology provides a new solution for the rapid and flexible deployment of complex system simulation applications. Container supports service-based packaging of simulation applications, which greatly reduces the difficulty of deploying simulation applications. Current packaging technology mainly relies on manually writing Dockerfile, which results in low packaging efficiency and human errors. A container-based automatic packaging technology for complex system simulation application is proposed, and the reusable library component template is defined. Combined image template is generated by combining simulation application and library component templates. Dockerfile is generated by the combined template after syntax optimization and error detection. The experiments …

Simulation Of Incentive Mechanism Simulation On Reverse Supply Chain Of Waste Products Based On Dual Drive, Dongshi Sun, Danlan Xie, Guan Feng, Ji Yuan

Journal of System Simulation

Abstract: In view of the current situation of coordination failure caused by different benefits of different entities in the waste reverse supply chain, based on system dynamics, a three-party evolutionary game model of residents, waste disposal institutions and production enterprises is constructed. Vensim simulation software is used to establish the stock-flow chart with the strategy selection probability as the horizontal variable. In the two cases of exogenous variable in constant and a time-trend, the simulation is carried out separately, and the strategy evolution path of the three parties is obtained without external interference. Through sensitivity analysis, the exogenous variables …

Effect Of New Titanium Alloy On Biomechanical Behavior Of Dental Implant, Jiwu Zhang, Qiguo Rong

Journal of System Simulation

Abstract: Titanium alloy materials have excellent mechanical properties, chemical stability and biocompatibility, and have become the main raw materials for implants. However, the biomechanical compatibility of medical titanium alloys still needs to be improved in order to meet the long-term safety and functionality of patient's clinical treatment requirement. New medical titanium alloy materials with high strength and low modulus play an important role in reducing the loosening and shedding of implants caused by stress shielding. The effects of new medical titanium alloy materials and traditional medical titanium alloy materials on implant structure and stress distribution of jaw are compared and …

Research On Real-Time Simulation Method Of Bi-Sar Echo In Time-Varying Sea Scene, Guijie Diao, Ni Hong, Zhe Liu, Li Yang

Journal of System Simulation

Abstract: Based on bistatic scattering mechanism and the geometric relationship of bistatic synthetic aperture radar (Bi-SAR), a real-time simulation method of Bi-SAR radio frequency echo in time-varying sea scene is proposed. For the couple scattering in time-varying sea scene, a Bi-SAR echo signal model is established on the basis of multipath scattering model. The Bi-SAR system response function for time-varying sea target is calculated in real-time, using high performance computing technology, high-capacity real-time access technology and full-switching system designing. The simulation results show the effectiveness of the method.

A Pmbldc Motor Measurement And Control System Available For Zynq Hardware-In-The-Loop Simulation, Zhiguo Zhou, Jiaen Sun, Jiabao Yu, Xuehua Zhou

Journal of System Simulation

Abstract: In order to solve the modeling of permanent magnet brushless dc(PMBLDC) motor, it is difficult to modify the control algorithm, inconvenient to add and remove the closed loop, and has poor real-time measurement and control capability. Based on hall sensor position detection algorithm and PID control algorithm, combined with piecewise linear method to generate PWM waveform, Simulink graphical modeling platform is used, and a new closed-loop measurement and control method is proposed. A sudden load and sudden speed simulation are carried out to verify the established PMBLDC motor measurement and control system. The simulation results show that the system …

Development Of Reduced Order Models Using Reservoir Simulation And Physics Informed Machine Learning Techniques, Mark V. Behl Jr

LSU Master's Theses

Reservoir simulation is the industry standard for prediction and characterization of processes in the subsurface. However, simulation is computationally expensive and time consuming. This study explores reduced order models (ROMs) as an appropriate alternative. ROMs that use neural networks effectively capture nonlinear dependencies, and only require available operational data as inputs. Neural networks are a black box and difficult to interpret, however. Physics informed neural networks (PINNs) provide a potential solution to these shortcomings, but have not yet been applied extensively in petroleum engineering.

A mature black-oil simulation model from Volve public data release was used to generate training data …

Integrating Deep Learning And Augmented Reality To Enhance Situational Awareness In Firefighting Environments, Manish Bhattarai

Electrical and Computer Engineering ETDs

We present a new four-pronged approach to build firefighter's situational awareness for the first time in the literature. We construct a series of deep learning frameworks built on top of one another to enhance the safety, efficiency, and successful completion of rescue missions conducted by firefighters in emergency first response settings. First, we used a deep Convolutional Neural Network (CNN) system to classify and identify objects of interest from thermal imagery in real-time. Next, we extended this CNN framework for object detection, tracking, segmentation with a Mask RCNN framework, and scene description with a multimodal natural language processing(NLP) framework. Third, …

Fusion-Features And Visual-Dictionary Image Recognition Methods For Apple Classification In Smart Manufacturing, Ahsiah Ismail

Student Works (2020-2029)

Smart manufacturing enables an efficient manufacturing process to optimize production. The optimization is performed through data analytics that requires reliable and informative data as input. Therefore, in this research, two image recognition feature extraction methods namely Curvelet Wavelet-Gray Level Co-occurrence Matrix (CWGLCM) and Fuzzy-Spatial Pyramid Matching (F-SPM) are proposed to provide reliable inputs for vision-based apple classification in smart manufacturing. Feature extraction is one of the major steps that could influent the efficiency of the manufacturing process. The CW-GLCM method is a feature extraction of fusion-features with Decision Tree classifier, while the F-SPM method uses a visual-dictionary based method to …

Energy-Efficient Communications In Wireless Powered Cognitive Radio Networks Based On Game Theory, Fadhil Mukhlif Aswad Al-Obaidy

Student Works (2020-2029)

There are challenging and prevalent problems related to spectrum resources with the interference of battery-based devices in future wireless networks. To address such challenges, this thesis proposes a theoretical framework for designing and analyzing the distributed power control algorithms in modern 5G cognitive networks. Previous experiments have shown that game theory tools can be used as a suitable and efficient technique to build scalable, balanced, and energy efficient for the distributed power control schemes in order to use it practically in battery-based devices in wireless networks. In reality, the power control issue is constructed as a non-cooperative game for which …

Identification Of Ecg Anomalies Through Deep Deterministic Learning, Uzair Iqbal

Student Works (2020-2029)

Electrocardiography (ECG) is a primary diagnostic tool for measuring the malfunctioning of the heart muscles in the context of morbidity of different cardiac diseases and arrhythmia. Different existing techniques and methods delivered accurate cardiac diseases myocardial infarction (heart stroke) and atrial fibrillation recognition. However, there are still some flaws in existing methods like recognition of special myocardial infarction situation flattened T wave in “Non-Specific ST-T Changes (nsst-t)” and reduction of computational cost in cardiac diseases recognition. Accurate recognition of cardiac diseases along with least computational complexity and feature analysis of flattened T wave in myocardial infarction remains an open job. …

Formal Concept Analysis Applications In Bioinformatics, Sarah Roscoe

School of Computing: Dissertations, Theses, and Student Research

Bioinformatics is an important field that seeks to solve biological problems with the help of computation. One specific field in bioinformatics is that of genomics, the study of genes and their functions. Genomics can provide valuable analysis as to the interaction between how genes interact with their environment. One such way to measure the interaction is through gene expression data, which determines whether (and how much) a certain gene activates in a situation. Analyzing this data can be critical for predicting diseases or other biological reactions. One method used for analysis is Formal Concept Analysis (FCA), a computing technique based …

Contextual-Bandit Anomaly Detection For Iot Data In Distributed Hierarchical Edge Computing, Mao V. Ngo, Tie Luo, Hakima Chaouchi, Tony Q.S. Quek

Computer Science Faculty Research & Creative Works

Advances in deep neural networks (DNN) greatly bolster real-time detection of anomalous IoT data. However, IoT devices can hardly afford complex DNN models, and offloading anomaly detection tasks to the cloud incurs long delay. In this paper, we propose and build a demo for an adaptive anomaly detection approach for distributed hierarchical edge computing (HEC) systems to solve this problem, for both univariate and multivariate IoT data. First, we construct multiple anomaly detection DNN models with increasing complexity and associate each model with a layer in HEC from bottom to top. Then, we design an adaptive scheme to select one …

Multi-User Verifiable Searchable Symmetric Encryption For Cloud Storage, Xueqiao Liu, Guomin Yang, Guomin Yang

Research Collection School Of Computing and Information Systems

In a cloud data storage system, symmetric key encryption is usually used to encrypt files due to its high efficiency. In order allow the untrusted/semi-trusted cloud storage server to perform searching over encrypted data while maintaining data confidentiality, searchable symmetric encryption (SSE) has been proposed. In a typical SSE scheme, a users stores encrypted files on a cloud storage server and later can retrieve the encrypted files containing specific keywords. The basic security requirement of SSE is that the cloud server learns no information about the files or the keywords during the searching process. Some SSE schemes also offer additional …

Extending The Functional Subnetwork Approach To A Generalized Linear Integrate-And-Fire Neuron Model, Nicholas Szczecinski, Roger Quinn, Alexander J. Hunt

Mechanical and Materials Engineering Faculty Publications and Presentations

Engineering neural networks to perform specific tasks often represents a monumental challenge in determining network architecture and parameter values. In this work, we extend our previously-developed method for tuning networks of non-spiking neurons, the “Functional subnetwork approach” (FSA), to the tuning of networks composed of spiking neurons. This extension enables the direct assembly and tuning of networks of spiking neurons and synapses based on the network’s intended function, without the use of global optimization ormachine learning. To extend the FSA, we show that the dynamics of a generalized linear integrate and fire (GLIF) neuronmodel have fundamental similarities to those of …

Communicating Uncertain Information From Deep Learning Models In Human Machine Teams, Harishankar V. Subramanian, Casey I. Canfield, Daniel Burton Shank, Luke Andrews, Cihan H. Dagli

Engineering Management and Systems Engineering Faculty Research & Creative Works

The role of human-machine teams in society is increasing, as big data and computing power explode. One popular approach to AI is deep learning, which is useful for classification, feature identification, and predictive modeling. However, deep learning models often suffer from inadequate transparency and poor explainability. One aspect of human systems integration is the design of interfaces that support human decision-making. AI models have multiple types of uncertainty embedded, which may be difficult for users to understand. Humans that use these tools need to understand how much they should trust the AI. This study evaluates one simple approach for communicating …

Analysis Of Glutathione Supplementation Effects On Female Metabolic Syndrome Condition Using Classification Techniques, Nur Rasyidah Hasan Basri

Student Works (2020-2029)

Lesser known to the public that main antioxidants in our body, Glutathione are also said to influence the metabolic syndrome (MS) condition. Oral supplementation consisting of glutathione precursors and vitamin C introduced in the study was to improve glutathione (GSH) status of the consumer and the main objective of this study is to investigate GSH effects on selected MS condition. Several known studies had proven that oral supplementation improved GSH level of consumer. However, there is no definite proof on how it’s affecting MS parameters. Also, there is less study carried out on the relationship between glutathione levels and metabolic …

Control Of A Human Arm Robotic Unit Using Augmented Reality And Optimized Kinematics, Carlo Canezo

USF Tampa Graduate Theses and Dissertations

There are more than 350000 amputees in the US who suffer loss of functionality in their daily living activities, and roughly 100000 of them are upper arm amputees. Many of these amputees use prostheses to compensate part of their lost arm function, including power prostheses. Research on 6-7 degree of freedom powered prostheses is still relatively new, and most commercially available powered prostheses are typically limited to 1 to 3 degrees of freedom. Due to the myriad of possible options for various powered protheses from different manufacturers, each configuration is governed by a distinct control scheme typically specific to the …

Cybersecurity Strategy Against Cyber Attacks Towards Smart Grids With Pvs, Fangyu Li, Maria Valero, Liang Zhao, Yousef Mahmoud

KSU Proceedings on Cybersecurity Education, Research and Practice

Cyber attacks threaten the security of distribution power grids, such as smart grids. The emerging renewable energy sources such as photovoltaics (PVs) with power electronics controllers introduce new potential vulnerabilities. Based on the electric waveform data measured by waveform sensors in the smart grids, we propose a novel cyber attack detection and identification approach. Firstly, we analyze the cyber attack impacts (including cyber attacks on the solar inverter causing unusual harmonics) on electric waveforms in distribution power grids. Then, we propose a novel deep learning based mechanism including attack detection and attack diagnosis. By leveraging the electric waveform sensor data …

Multi-Echo Quantitative Susceptibility Mapping For Strategically Acquired Gradient Echo (Stage) Imaging, Sara Gharabaghi, Saifeng Liu, Ying Wang, Yongsheng Chen, Sagar Buch, Mojtaba Jokar, Thomas Wischgoll, Nasser H. Kashou, Chunyan Zhang, Bo Wu, Jingliang Cheng, E. Mark Haacke

Computer Science and Engineering Faculty Publications

Purpose: To develop a method to reconstruct quantitative susceptibility mapping (QSM) from multi-echo, multi-flip angle data collected using strategically acquired gradient echo (STAGE) imaging. Methods: The proposed QSM reconstruction algorithm, referred to as “structurally constrained Susceptibility Weighted Imaging and Mapping” scSWIM, performs an ℓ1 and ℓ2 regularization-based reconstruction in a single step. The unique contrast of the T1 weighted enhanced (T1WE) image derived from STAGE imaging was used to extract reliable geometry constraints to protect the basal ganglia from over-smoothing. The multi-echo multi-flip angle data were used for improving the contrast-to-noise ratio in QSM through a weighted averaging scheme. The …

Investigating Factors Predicting Effective Learning In A Cs Professional Development Program For K–12 Teachers, Patrick Morrow

School of Computing: Dissertations, Theses, and Student Research

The demand for K-12 Computer Science (CS) education is growing and there is not an adequate number of educators to match the demand. Comprehensive research was carried out to investigate and understand the influence of a summer two-week professional development (PD) program on teachers’ CS content and pedagogical knowledge, their confidence in such knowledge, their interest in and perceived value of CS, and the factors influencing such impacts. Two courses designed to train K-12 teachers to teach CS, focusing on both concepts and pedagogy skills were taught over two separate summers to two separate cohorts of teachers. Statistical and SWOT …

Finite-Time State Estimation For An Inverted Pendulum Under Input-Multiplicative Uncertainty, Sergey V. Drakunov, William Mackunis, Anu Kossery Jayaprakash, Krishna Bhavithavya Kidambi, Mahmut Reyhanoglu

Publications

A sliding mode observer is presented, which is rigorously proven to achieve finite-time state estimation of a dual-parallel underactuated (i.e., single-input multi-output) cart inverted pendulum system in the presence of parametric uncertainty. A salient feature of the proposed sliding mode observer design is that a rigorous analysis is provided, which proves finite-time estimation of the complete system state in the presence of input-multiplicative parametric uncertainty. The performance of the proposed observer design is demonstrated through numerical case studies using both sliding mode control (SMC)- and linear quadratic regulator (LQR)-based closed-loop control systems. The main contribution presented here is the rigorous …

Research On Optimal Configuration Design Method Of Stewart Platform, Xuwei Fan, Lili Yang, Cheng Yu, Xiaoning Zhou, Yexin Zhang

Journal of System Simulation

Abstract: Based on the structural singularity and configuration singularity of parallel mechanism, a safety mechanism design scheme of the Stewart platform is proposed to improve the workspace efficiency and engineering practicability. Taking the Stewart platform without any particularity as the research object, and considering the singular constraints of the structure, a dexterity index is proposed to achieve the optimization of the structural parameters. Analyzing and constructing the kinematics model of the Stewart platform, analyzing the singularities of the configuration bifurcations of 16 typical extreme poses, a secure workspace verification algorithm is proposed to make the whole workspace free of singularity. …

Research On Adaptive Routing Algorithm For Wireless Weak-Connection Network, Hua Xiang, Hongjuan Yao, Wang Hai, Wang Zhao, Jietao Zhang, Lili Shu

Journal of System Simulation

Abstract: The wireless weak-connected network has the characteristics of long delay, high dynamic topology, and unstable links. With the lack of continuity from the source end to the destination end of network connection, in order to solve the problem of communication difficulty, the intelligence and adaptability of Physarum polycephalum are introduced, and the adaptive wireless weak-connected network routing algorithm is proposed. A wireless weak-connected network model is build and the mathematical relationships of link capacity is deduced. The next-hop selection strategy and optimal routing strategy is designed to achieve the best-effort delivery of data in wireless weak-connected network environmrnt. Simulation …

Visual Feedback Fuzzy Control For A Robot Manipulator Based On Svr Learning, Xianxia Zhang, Jinqiang Zhang, Zhiyuan Li, Shiwei Ma, Banghua Yang

Journal of System Simulation

Abstract: A fuzzy controller based on SVR learning is proposed for uncalibrated robot visual servoing. In this paper, a fuzzy controller is used to directly construct the nonlinear mapping between image features and robot joint motion. The fuzzy basis function of the fuzzy controller is taken as the kernel function of an SVR and the equivalent relationship between the SVR and the fuzzy controller is established. The learned support vector from the SVR is used as the rule of the fuzzy controller. Since all rules are learned from the data, there is no need to manually design the rules. …

Gru-Based Car-Following Behavior Simulation Model, Fei Rong, Liu Fang, Xie Guo, Hei Xinhong, Shasha Li, Hu Bo

Journal of System Simulation

Abstract: The accuracy of acceleration prediction can be effectively improved by the driver's memory in car-following behavior. A new car-following model based on the General Motors (GM) and the gate control unit (GRU) is proposed. The car-following data between small vehicles with similar driving behavior are obtained by data preprocessing. The established model is calibrated by the car-following data, and the optimal parameters and structure of the model are determined. According to car-following characteristics, the effectiveness of model is verified by simulation. It is confirmed that the model has high robustness and improved simulation accuracy comparing with the traditional models.

Estimation Of Space-Time Of Urban Building Population Based On Mobile Phone Big Data, Hu Yang, Xiaoyong Zhang, Xiao Di

Journal of System Simulation

Abstract: With the acceleration of the urbanization process, mastering the population distribution on a fine scale is of great significance for urban disaster assessment, emergency response management and public resource allocation. The rapid development of the Internet and the popularity of smartphones have prompted mobile phones to become the sensors of human activity. A method of urban building population estimation based on mobile phone big data is proposed. The method analyzes the crowd activity law of buildings with different functions based on mobile phone positioning big data in typical areas, calculates the population capacity of different functional buildings, and …