Engineering Commons^™

Survey On Deep Neural Networks In Speech And Vision Systems, M. Alam, Manar D. Samad, Lasitha Vidyaratne, ‪Alexander Glandon, Khan M. Iftekharuddin

Computer Science Faculty Research

This survey presents a review of state-of-the-art deep neural network architectures, algorithms, and systems in speech and vision applications. Recent advances in deep artificial neural network algorithms and architectures have spurred rapid innovation and development of intelligent speech and vision systems. With availability of vast amounts of sensor data and cloud computing for processing and training of deep neural networks, and with increased sophistication in mobile and embedded technology, the next-generation intelligent systems are poised to revolutionize personal and commercial computing. This survey begins by providing background and evolution of some of the most successful deep learning models for intelligent …

A Novel Spatiotemporal Prediction Method Of Cumulative Covid-19 Cases, Junzhe Cai

School of Computing: Dissertations, Theses, and Student Research

Prediction methods are important for many applications. In particular, an accurate prediction for the total number of cases for pandemics such as the Covid-19 pandemic could help medical preparedness by providing in time a sufficient supply of testing kits, hospital beds and medical personnel. This thesis experimentally compares the accuracy of ten prediction methods for the cumulative number of Covid-19 pandemic cases. These ten methods include two types of neural networks and extrapolation methods based on best fit linear, best fit quadratic, best fit cubic and Lagrange interpolation, as well as an extrapolation method from Revesz. We also consider the …

Suffix Tree, Minwise Hashing And Streaming Algorithms For Big Data Analysis In Bioinformatics, Sairam Behera

School of Computing: Dissertations, Theses, and Student Research

In this dissertation, we worked on several algorithmic problems in bioinformatics using mainly three approaches: (a) a streaming model, (b) sux-tree based indexing, and (c) minwise-hashing (minhash) and locality-sensitive hashing (LSH). The streaming models are useful for large data problems where a good approximation needs to be achieved with limited space usage. We developed an approximation algorithm (Kmer-Estimate) using the streaming approach to obtain a better estimation of the frequency of k-mer counts. A k-mer, a subsequence of length k, plays an important role in many bioinformatics analyses such as genome distance estimation. We also developed new methods that use …

Representational Learning Approach For Predicting Developer Expertise Using Eye Movements, Sumeet Maan

School of Computing: Dissertations, Theses, and Student Research

The thesis analyzes an existing eye-tracking dataset collected while software developers were solving bug fixing tasks in an open-source system. The analysis is performed using a representational learning approach namely, Multi-layer Perceptron (MLP). The novel aspect of the analysis is the introduction of a new feature engineering method based on the eye-tracking data. This is then used to predict developer expertise on the data. The dataset used in this thesis is inherently more complex because it is collected in a very dynamic environment i.e., the Eclipse IDE using an eye-tracking plugin, iTrace. Previous work in this area only worked on …

A Distance Based Multisample Test For High-Dimensional Compositional Data With Applications To The Human Microbiome, Qingyang Zhang, Thy Dao

Mathematical Sciences Faculty Publications and Presentations

Background

Compositional data refer to the data that lie on a simplex, which are common in many scientific domains such as genomics, geology and economics. As the components in a composition must sum to one, traditional tests based on unconstrained data become inappropriate, and new statistical methods are needed to analyze this special type of data.

Results

In this paper, we consider a general problem of testing for the compositional difference between K populations. Motivated by microbiome and metagenomics studies, where the data are often over-dispersed and high-dimensional, we formulate a well-posed hypothesis from a Bayesian point of view and …

Ppmexplorer: Using Information Retrieval, Computer Vision And Transfer Learning Methods To Index And Explore Images Of Pompeii, Cindy Roullet

Graduate Theses and Dissertations

In this dissertation, we present and analyze the technology used in the making of PPMExplorer: Search, Find, and Explore Pompeii. PPMExplorer is a software tool made with data extracted from the Pompei: Pitture e Mosaic (PPM) volumes. PPM is a valuable set of volumes containing 20,000 historical annotated images of the archaeological site of Pompeii, Italy accompanied by extensive captions. We transformed the volumes from paper, to digital, to searchable. PPMExplorer enables archaeologist researchers to conduct and check hypotheses on historical findings. We present a theory that such a concept is possible by leveraging computer generated correlations between artifacts using …

Electro-Optic Satellite Constellation Design Using Multi-Objective Genetic Algorithm, Yasin Tamer

Theses and Dissertations

Satellite constellation design is a complex, highly constrained, and multidisciplinary problem. Unless optimization tools are used, tradeoffs must be conducted at the subsystem level resulting in feasible, but not necessarily optimal, system designs. As satellite technology advances, new methods to optimize the system objectives are developed. This study is based on the development of a representative regional remote sensing constellation design. This thesis analyses the design process of an electrooptic satellite constellation with regional coverage considerations using system-level optimization tools. A multi objective genetic algorithm method is used to optimize the constellation design by utilizing MATLAB and STK integration. Cost, …

Parallelization Of The Advancing Front Local Reconnection Mesh Generation Software Using A Pseudo-Constrained Parallel Data Refinement Method, Kevin Mark Garner Jr.

Computer Science Theses & Dissertations

Preliminary results of a long-term project entailing the parallelization of an industrial strength sequential mesh generator, called Advancing Front Local Reconnection (AFLR), are presented. AFLR has been under development for the last 25 years at the NSF/ERC center at Mississippi State University. The parallel procedure that is presented is called Pseudo-constrained (PsC) Parallel Data Refinement (PDR) and consists of the following steps: (i) use an octree data-decomposition scheme to divide the original geometry into subdomains (octree leaves), (ii) refine each subdomain with the proper adjustments of its neighbors using the given refinement code, and (iii) combine all subdomain data into …

Enhanced Traffic Incident Analysis With Advanced Machine Learning Algorithms, Zhenyu Wang

Computational Modeling & Simulation Engineering Theses & Dissertations

Traffic incident analysis is a crucial task in traffic management centers (TMCs) that typically manage many highways with limited staff and resources. An effective automatic incident analysis approach that can report abnormal events timely and accurately will benefit TMCs in optimizing the use of limited incident response and management resources. During the past decades, significant efforts have been made by researchers towards the development of data-driven approaches for incident analysis. Nevertheless, many developed approaches have shown limited success in the field. This is largely attributed to the long detection time (i.e., waiting for overwhelmed upstream detection stations; meanwhile, downstream stations …

Deep Learning-Based, Passive Fault Tolerant Control Facilitated By A Taxonomy Of Cyber-Attack Effects, Dean C. Wardell

Theses and Dissertations

In the interest of improving the resilience of cyber-physical control systems to better operate in the presence of various cyber-attacks and/or faults, this dissertation presents a novel controller design based on deep-learning networks. This research lays out a controller design that does not rely on fault or cyber-attack detection. Being passive, the controller’s routine operating process is to take in data from the various components of the physical system, holistically assess the state of the physical system using deep-learning networks and decide the subsequent round of commands from the controller. This use of deep-learning methods in passive fault tolerant control …

Static And Dynamical Properties Of Multiferroics, Sayed Omid Sayedaghaee

Graduate Theses and Dissertations

Since the silicon industrial revolution in the 1950s, a lot of effort was dedicated to the research and development activities focused on material and solid-state sciences. As a result, several cutting-edge technologies are emerging including the applications of functional materials in the design and enhancement of novel devices such as sensors, highly capable data storage media, actuators, transducers, and several other types of electronic tools. In the last two decades, a class of functional materials known as multiferroics has captured significant attention because of providing a huge potential for new designs due to possessing multiple ferroic order parameters at the …

Optimal Collaborative Path Planning For Unmanned Surface Vehicles Carried By A Parent Boat Along A Planned Route, Ari Carisza Graha Prasetia, I-Lin Wang, Aldy Gunawan

Research Collection School Of Computing and Information Systems

In this paper, an effective mechanism using a fleet of unmanned surface vehicles (USVs) carried by a parent boat (PB) is proposed to complete search or scientific tasks over multiple target water areas within a shorter time . Specifically, multiple USVs can be launched from the PB to conduct such operations simultaneously, and each USV can return to the PB for battery recharging or swapping and data collection in order to continue missions in a more extended range. The PB itself follows a planned route with a flexible schedule taking into consideration locational constraints or collision avoidance in a real-world …

Covid-19 And Mental Health/Substance Use Disorders On Reddit: A Longitudinal Study, Amanuel Alambo, Swati Padhee, Tanvi Banerjee, Krishnaprasad Thirunarayan

Computer Science and Engineering Faculty Publications

COVID-19 pandemic has adversely and disproportionately impacted people suffering from mental health issues and substance use problems. This has been exacerbated by social isolation during the pandemic and the social stigma associated with mental health and substance use disorders, making people reluctant to share their struggles and seek help. Due to the anonymity and privacy they provide, social media emerged as a convenient medium for people to share their experiences about their day to day struggles. Reddit is a well-recognized social media platform that provides focused and structured forums called subreddits, that users subscribe to and discuss their experiences with …

Machine Learning Augmentation Micro-Sensors For Smart Device Applications, Mohammad H. Hasan

Department of Mechanical and Materials Engineering: Dissertations, Theses, and Student Research

Novel smart technologies such as wearable devices and unconventional robotics have been enabled by advancements in semiconductor technologies, which have miniaturized the sizes of transistors and sensors. These technologies promise great improvements to public health. However, current computational paradigms are ill-suited for use in novel smart technologies as they fail to meet their strict power and size requirements. In this dissertation, we present two bio-inspired colocalized sensing-and-computing schemes performed at the sensor level: continuous-time recurrent neural networks (CTRNNs) and reservoir computers (RCs). These schemes arise from the nonlinear dynamics of micro-electro-mechanical systems (MEMS), which facilitates computing, and the inherent ability …

Under Impact Of Non-Motor Vehicle Violation An Analysis On Vehicle Operation Efficiency, Sun Di, Zhou Jin, Sijia Liu, Xiaoming Zhang, Xueying Gao

Journal of System Simulation

Abstract: In order to study the impact of non-motor vehicle violations on motor vehicle traffic efficiency at signalized intersections, the non-motor vehicle traffic behaviors are analyzed. An actual intersection is selected as study object, the main violation behaviors of on selected intersection are analyzed by using the linear regression model. For traffic light violation behavior of non-motor vehicles, the violation rate is modeled by using logistic model, and the results are analyzed. At the signal controlled intersection, non-motor vehicle violations affect the normal motor vehicles, and time is delayed. The delay time of motor vehicle under non-motor vehicle …

Time-Varying Parameter System Modeling Method Based On Zonotope-Ellipsoid Double Filtering, Ziyun Wang, Peiyu Wang, Yacong Zhan

Journal of System Simulation

Abstract: The traditional system modeling method using zonotopes as the feasible parameter sets islikely to increase the computational complexity of the algorithm due to the increasing dimensions of the zonotope shape matrix. This paper proposes a time-varying parameter modeling systems method based on zonotope-ellipsoid double filtering technique. Considering the time-varying parameters, a zonotope with the minimum volume is obtained during the iterations of the intersection with the constraint strip. After transforming the shape matrix of the zonotope, the dimensionality reduction is performed, instead of directly finding the row sum of the extended shape matrix, to reduce the algorithm conservativeness originated …

Research On Configurable Simulation Integration Technology For Equipment Software, Yuanyuan Wang, Yuxin Duan, Guangzhao Song

Journal of System Simulation

Abstract: The problems of the traditional distributed digital simulation system are analyzed. The method of constructing the digital simulation system based on the equipment software is studied. The configurable simulation integration middleware is designed. The overall structure of the configurable middleware is designed and the design ideas of each module are briefly summarized. An example of a digital simulation system with networked transformation of equipment shows that the middleware can be effectively and flexibly configured and can provide support for constructing digital simulation system with software, which can be promoted and used in other simulation systems.

Research On Multi-Objective Optimization Method Based On Model, Jianjun Liu, Guangya Si, Yanzheng Wang, Dachuan He

Journal of System Simulation

Abstract: There is a model-based algorithm for the optimization of multiple objective functions by means of black-box evaluation is proposed. The algorithm iteratively generates candidate solutions from a mixture distribution over the solution space and updates the mixture distribution based on the sampled solutions’ domination count, such that the future search is biased towards the set of Pareto optimal solutions. The proposed algorithm seeks to find a mixture distribution on the solution space so that each component of the mixture distribution is a degenerate distribution centered at a Pareto optimal solution and each estimated Pareto optimal solution is uniformly spread …

Research And Application Of A Lightweight Real-Time Human Posture Detection Model, Hongkun Zhu, Jiawei Yin, Wenyu Feng, Hua Liang, Minrui Fei, Kun Zhang

Journal of System Simulation

Abstract: The traditional OpenPose model has good accuracy but slow speed in human posture detection. In order to accelerate the detection speed and reduce the model on condition of the detection precision, based on the traditional OpenPose model, the residual network with second-order term fusion is used to extract the low-level features, the weights of the trained model are pruned by the L1 norm weight, and an improved OpenPose model is proposed. Experiments show that when the detection accuracy is approximately equal to original model, the model size reduces to about 8%, the parameters reduces by nearly 83%, and the …

Construction And Test Method Of A Semi-Physical Simulation System For Laser Driving Guidance Weapon, Zhang Xiang, Mengyan Liu, Zhang Peng, Kewei Zhu, Xiaodong Yan

Journal of System Simulation

Abstract: To achieve the previous semi-physical simulation of the laser beam-guided weapon, the two-dimensional translation system must be used. But the technical index of the two-dimensional translation system is not high enough to meet the requirements of the relative motion simulation speed and acceleration of the projectile. To solve the problem, a new method and test method for the semi-physical simulation system of laser driving guidance weapon is proposed. The “two-axis turret + load bracket” simulation system construction method is adopted to replace the linear motion of the two-dimensional translation system by the rotational angular motion of the …

Two Gd Atoms Adsorbed On Zigzag Graphene Nanoribbon:A First-Principles Study, Weifeng Xie, Zuo Xu

Journal of System Simulation

Abstract: A giant Rashba-type spin splitting is highly critical for the application of spintronics, but one-dimensional magnetic systems are rarely involved. In order to explore the characteristics and strength of Rashba effect in one-dimensional magnetic systems, two Gd atoms adsorbed on Zigzag graphene nanoribbon system is proposed. The characteristics and strength of the Rashba effect in different magnetization directions and the magnetic anisotropy of the system are analyzed through the first-principles calculations. The results show that the antiferromagnetic ground state system has strong Rashba strength and out-of-plane magnetic anisotropy. In addition, the Rashba effect in magnetic system needs to …

Generalized Zero-Inflated Binomial Distribution Model Aimed At Air Quality Data Analysis, Benyue Su, Pengpeng Xu, Sheng Min

Journal of System Simulation

Abstract: For the problem of the quality monitoring and counting of excessive gas emissions in chemical industry parks, a generalized zero-inflated binomial distribution model is constructed. Statistics show that the times of number of excessive gas emissions has a typical zero-inflated feature. The traditional zero-inflated Poisson model and negative binomial regression model and so on will underestimate the probability of zero inflation. A generalized zero-inflated binomial distribution model is constructed by extending the traditional binomial regression model to a more general form. This model satisfies the characteristic that the expectation is less than the variance, and better solves the problems …

Hyper-Heuristic De Algorithm For Solving Zero-Wait Fermentation Process Schedulinge, Shen Peng, Wang Yan, Zhicheng Ji, Jianhua Zhang

Journal of System Simulation

Abstract: A class of zero-wait fermentation process scheduling issues with batch process characteristics are researched. In order to solve the problem of easy deterioration in the process, a super heuristic difference algorithm is proposed, and the maximum makespan is minimized as the optimization goal. The algorithm is divided into two layers. The upper layer is an improved adaptive differential evolution algorithm to select and sort the heuristic operations in lower layer. The lower layer is combined and sorted into a new algorithm to operate on the problem domain, adding simulated annealing algorithm to avoid falling into local optimization. The method …

Modeling And Relevance Analysis Of Urban Epidemic Transmission And Work Resumption Intensity, Gan Mi, Yunyi Tian, Wenchang Zhang, Xihan Zhao

Journal of System Simulation

Abstract: On the basis of multi-source big data, the model for analyzing the population migration changes and manpower gaps caused by the COVID-19 epidemic in 34 typical cities across the country is constructed , and the work resumption intensity of other cities is predicited by using the migration base constructed. The SEIR model is used to estimate the basic reproduction number in each city since the simulate results show that it can emulate the transmission trend of this epidemic accurately, and the retrospective matrix analysis of the work resumption intensity is combined with the manpower gap to summarize the anti-epidemic …

Research On Dynamic Flexible Job Shop Scheduling Problem Based On Dynamic Interaction Layer, Zhang Xiang, Wang Yan, Zhicheng Ji

Journal of System Simulation

Abstract: In order to quickly response to the unforeseen circumstances in flexible job shop, a dynamic flexible job shop scheduling model is constructed, which takes the overall production time and the completion time of emergency orders as the optimization objectives. For the model, a dynamic interaction layer (DIL) model, which has a better performance on DFJSP, is proposed to replace the scroll window. Particle swarm genetic hybrid algorithm (PSGA) is designed to combine the particle swarm optimization algorithm with the genetic algorithm to enhance the ability of local search. Aiming at the unexpected urgent orders in flexible job shop, …

Echo Simulation And Verification Of High Resolution Range Profile, Xiaolin Li, Cheng Yu, Haifei Zang, Shuge Wang, Liu Li, Qingqing Yuan

Journal of System Simulation

Abstract: In order to realize the echo simulation and verification of high-resolution range profile in laboratory environment, the multi-scattering point model and wideband LFM echo signal model are given, and the time-domain convolution and high-precision delay realization methods in echo simulation process are described. According to the different signal bandwidth forms of the tested equipments, a wideband echo simulator is used to realize the corresponding high-resolution range image echo. By comparing with the digital simulation results of the target characteristic modeling software, the fidelity of the high-resolution range echo simulation is verified. Simulation verification is carried out with an aircraft …

Multi-Agent Simulation Model For Covid-19 Virus Prevention And Control, Lihu Pan, Shipeng Qin, Xiaowen Li, Feiping Lu, Fenyu Yang

Journal of System Simulation

Abstract: The prevention and control of the novel coronavirus (COVID-19) is the priority work to maintain the public health security of the world nowadays. The COVID-19 prevention and control model using multi-agent modeling and simulation technology is proposed. The model can simulate the different dynamic development trend of the epidemic under different prevention and control measures. Taking Taiyuan as an example, according to the researched COVID-19 transmission rules, the prevention and control simulation of COVID-19 has been achieved under the designing rule of the interactive infection process and status transition process between various resident agents. Multi-scenario simulation experiments are realized …

Design And Implementation Of Cloth Virtual Simulation System For Group Performance, Xiaotian Sun, Boxiang Xiao, Zhengdong Liu

Journal of System Simulation

Abstract: Clothing plays an important role in group performance activities and affects directly the overall performance effect. In order to achieve the goal of virtual design and virtual exercise of group performance costume, a virtual simulation system is designed and implemented. The human body model is established by CLO3D, and then individual clothing model is constructed. After the human body and clothing model are imported into Unity, the clothing material is adjusted and the texture map is added. The group model is generated by copying individual clothing models of human body and clothing in Unity. The interactive interface of virtual …

Optimal Scheduling And Decision Making Method For Dynamic Flexible Job Shop, Wang Yan, Ding Yu

Journal of System Simulation

Abstract: For multi-objective dynamic flexible job-shop scheduling, an improved multi-objective differential evolution algorithm is proposed. The adaptive cross-mutation operator is introduced into the differential evolution algorithm to improve its global search capability. The fast non-dominated sorting method based on immunological principles is introduced to improve the quality of the solution set in the selection and sorting. An improved TOPSIS-G1-EVM comprehensive decision-making method is proposed. The comprehensive weight of G1-EVM is calculated by Nash equilibrium theory. The comprehensive weight and TOPSIS evaluation system are combined to evaluate each dispatching scheme. The experimental results show that the optimal scheduling algorithm is superior …

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 …