Computer Sciences Commons^™

Pedestrian Navigation Using Artificial Neural Networks And Classical Filtering Techniques, David J. Ellis

Theses and Dissertations

The objective of this thesis is to explore the improvements achieved through using classical filtering methods with Artificial Neural Network (ANN) for pedestrian navigation techniques. ANN have been improving dramatically in their ability to approximate various functions. These neural network solutions have been able to surpass many classical navigation techniques. However, research using ANN to solve problems appears to be solely focused on the ability of neural networks alone. The combination of ANN with classical filtering methods has the potential to bring beneficial aspects of both techniques to increase accuracy in many different applications. Pedestrian navigation is used as a …

Use Of Lidar In Automated Aerial Refueling To Improve Stereo Vision Systems, Michael R. Crowl

Theses and Dissertations

The United States Air Force (USAF) executes five Core Missions, four of which depend on increased aircraft range. To better achieve global strike and reconnaissance, unmanned aerial vehicles (UAVs) require aerial refueling for extended missions. However, current aerial refueling capabilities are limited to manned aircraft due to technical difficulties to refuel UAVs mid-flight. The latency between a UAV operator and the UAV is too large to adequately respond for such an operation. To overcome this limitation, the USAF wants to create a capability to guide the refueling boom into the refueling receptacle. This research explores the use of light detection …

The Impact Of Changing The Size Of Aircraft Radar Displays On Visual Search In The Cockpit, Justin R. Marsh

Theses and Dissertations

Advances in sensor technology have enabled our fighter aircraft to find, fix, track, target, engage (F2T2E) at greater distances, providing the operator with more data within the battlefield. Modern aircraft are designed with larger displays while our legacy aircraft are being retrofitted with larger cockpit displays to enable display of the increased data. While this modification has been shown to enable improvements in human performance of many cockpit tasks, this effect is often not measured nor fully understood at a more generalizable level. This research outlines an approach to comparing human performance across two display sizes in future F-16 cockpits. …

Cyber Risk Assessment And Scoring Model For Small Unmanned Aerial Vehicles, Dillon M. Pettit

Theses and Dissertations

The commercial-off-the-shelf small Unmanned Aerial Vehicle (UAV) market is expanding rapidly in response to interest from hobbyists, commercial businesses, and military operators. The core commercial mission set directly relates to many current military requirements and strategies, with a priority on short range, low cost, real time aerial imaging, and limited modular payloads. These small vehicles present small radar cross sections, low heat signatures, and carry a variety of sensors and payloads. As with many new technologies, security seems secondary to the goal of reaching the market as soon as innovation is viable. Research indicates a growth in exploits and vulnerabilities …

Algorithm Selection Framework: A Holistic Approach To The Algorithm Selection Problem, Marc W. Chalé

Theses and Dissertations

A holistic approach to the algorithm selection problem is presented. The “algorithm selection framework" uses a combination of user input and meta-data to streamline the algorithm selection for any data analysis task. The framework removes the conjecture of the common trial and error strategy and generates a preference ranked list of recommended analysis techniques. The framework is performed on nine analysis problems. Each of the recommended analysis techniques are implemented on the corresponding data sets. Algorithm performance is assessed using the primary metric of recall and the secondary metric of run time. In six of the problems, the recall of …

Using Knowledge Bases For Question Answering, Yunshi Lan

Dissertations and Theses Collection (Open Access)

A knowledge base (KB) is a well-structured database, which contains many of entities and their relations. With the fast development of large-scale knowledge bases such as Freebase, DBpedia and YAGO, knowledge bases have become an important resource, which can serve many applications, such as dialogue system, textual entailment, question answering and so on. These applications play significant roles in real-world industry.

In this dissertation, we try to explore the entailment information and more general entity-relation information from the KBs. Recognizing textual entailment (RTE) is a task to infer the entailment relations between sentences. We need to decide whether a hypothesis …

Distributed Adaptive State Estimation And Tracking By Using Active-Passive Sensor Networks, Akhilesh Raj, Sarangapani Jagannathan, Tansel Yucelen

Electrical and Computer Engineering Faculty Research & Creative Works

Heterogeneous sensor networks (HSN) find a wide range of applications in the field of military and civilian environments, where sensor nodes are utilized to estimate the position of a target with both dynamics and control input being unknown for the purposes of tracking. In the HSN, nodes are considered active depending upon their ability to sense the target output while the others are taken passive. Accurate estimation requires local information exchange among the spatially located sensor nodes, so that the active nodes as well as the passive nodes converge simultaneously to the same value. The local information exchange among the …

When The Bank Comes To You: Branch Network And Customer Omnichannel Banking Behavior, Mi Zhou, Dan Geng, Vibhanshu Abhishek, Beibei Li

Research Collection School Of Computing and Information Systems

Banks today have been increasingly reducing their physical presence and redirecting customers to digital channels, and yet, the consequences of this strategy are not well studied. This paper investigates the effects of banks' branch network changes (i.e., branch openings and branch closures) on customer omnichannel banking behavior. Using approximately 0.85 million (33 months') anonymized individual-level banking transactions from a large commercial bank in the United States, this paper shows the asymmetric effects of branch openings and branch closures on customer omnichannel banking behavior. In particular, we find that branch openings increase customers' branch transactions; however, the first branch opening leads …

Vehicle Routing Problem For Multi-Product Cross-Docking, Aldy Gunawan, Audrey Tedja Widjaja, Benjamin Gan, Vincent F. Yu, Panca Jodiawan

Research Collection School Of Computing and Information Systems

Cross-docking is a logistic technique that can reduce costs occurred in a supply chain network while increasing the flow of goods, thus shortening the shipping cycle. Inside a cross-dock facility, the goods are directly transferred from incoming vehicles to outgoing vehicles without storing them in-between. Our research extends and combines this cross-docking technique with a well-known logistic problem, the vehicle routing problem (VRP), for delivering multiple products and addresses it as the VRP for multi-product cross-docking (VRP-MPCD). We developed a mixed integer programming model and generated two sets of VRP-MPCD instances, which are based on VRPCD instances. The instances are …

Cyber-Physical Security With Rf Fingerprint Classification Through Distance Measure Extensions Of Generalized Relevance Learning Vector Quantization, Trevor J. Bihl, Todd J. Paciencia, Kenneth W. Bauer Jr., Michael A. Temple

Faculty Publications

Radio frequency (RF) fingerprinting extracts fingerprint features from RF signals to protect against masquerade attacks by enabling reliable authentication of communication devices at the “serial number” level. Facilitating the reliable authentication of communication devices are machine learning (ML) algorithms which find meaningful statistical differences between measured data. The Generalized Relevance Learning Vector Quantization-Improved (GRLVQI) classifier is one ML algorithm which has shown efficacy for RF fingerprinting device discrimination. GRLVQI extends the Learning Vector Quantization (LVQ) family of “winner take all” classifiers that develop prototype vectors (PVs) which represent data. In LVQ algorithms, distances are computed between exemplars and PVs, and …

Reliability Analysis Of Power Grids And Its Interdependent Infrastructures: An Interaction Graph-Based Approach, Upama Nakarmi

USF Tampa Graduate Theses and Dissertations

Large blackouts with significant societal and economic impacts result from cascade of failures in the transmission network of power grids. Understanding and mitigating cascading failures in power grids is challenging due to the large number of components and their complex interactions, wherein, in addition to the physical topology of the system, the physics of power flow and functional dependencies among components largely affect the spatial distribution and propagation of failures. In this dissertation, data-driven interaction graphs, which help in capturing the underlying interactions and influences among the components during cascading failures, are used for capturing the non-local nature of propagation …

Lung Nodule Malignancy Prediction From Computed Tomography Images Using Deep Learning, Rahul Paul

USF Tampa Graduate Theses and Dissertations

Lung cancer has a high incidence and mortality rate. The five-year relative survival rate for all lung cancers is 18%. Due to the high mortality and incidence rate of lung cancer worldwide, early detection is essential. Low dose Computed Tomography (CT) is a commonly used technique for screening, diagnosis, and prognosis of non-small cell lung cancer (NSCLC). The National Lung Screening Trial (NLST) compared low-dose helical computed tomography (LDCT) and standard chest radiography (CXR) for three annual screens and reported a 20% relative reduction in lung cancer mortality for LDCT compared to CXR. As such, LDCT screening for lung cancer …

Analysis Of Identification Method For Bacterial Species And Antibiotic Resistance Genes Using Optical Data From Dna Oligomers, Ryan L. Wood, Tanner Jensen, Cindi Wadsworth, Mark Clement, Prashant Nagpal, William G. Pitt

Faculty Publications

Bacterial antibiotic resistance is becoming a significant health threat, and rapid identification of antibiotic-resistant bacteria is essential to save lives and reduce the spread of antibiotic resistance. This paper analyzes the ability of machine learning algorithms (MLAs) to process data from a novel spectroscopic diagnostic device to identify antibiotic-resistant genes and bacterial species by comparison to available bacterial DNA sequences. Simulation results show that the algorithms attain from 92% accuracy (for genes) up to 99% accuracy (for species). This novel approach identifies genes and species by optically reading the percentage of A, C, G, T bases in 1000s of short …

Research On Cavitation Evolution Model In Venturi Tube, Guihua Han, Yanan Liu, Junpeng Shao, Cijun Zhang

Journal of System Simulation

Abstract: The dynamic cavitation model of venturi tube air-water two-phase flow was established according to the time variation of air precipitation and digestion process in water. FLUENT three-dimension numerical simulation were studied to simulate the air-water two-phase flow, and the variation law of venturi tube throat diameter and inlet pressure on vapor volume fraction were obtained. The results of numerical simulation and experiments show that the vapor volume fraction increases following the increase of the inlet pressure. If the throat diameter is increased, the inlet pressure can be increased as the compensation to achieve the same cavitation effect. The …

Self-Organizing Aggregation Behavior Modeling Of Swarm Robots Based On Ant Colony Algorithm, Yang Wei, Zeng Liang, Xinchen Kang

Journal of System Simulation

Abstract: Aiming at the formation of aggregation behavior model of swarm robots, a self-organizing motion model based on particle system mechanics and perceptual state weighting is established to realize the autonomous transfer of robot motion state. The aggregation degree and uniformity index of aggregation behavior are established, and the aggregation performances of different models are analyzed by experiment, which lay a foundation for the formation of self-organized aggregation behavior model of swarm robots. Using the selected model, the self-organizing aggregation behavior simulation experiments are conducted in two cases with boundary constraints and no boundary constraints. The maximum coverage of …

Auv Vertical Plane Control Based On Improved Pid Neural Network Algorithm, Runan Huang, Ding Ning

Journal of System Simulation

Abstract: An improved PID neural network controller is designed for the movement control of a small low-speed autonomous underwater vehicle (AUV) in vertical plane, and the global control of the depth and pitch angle of the underwater vehicle in vertical plane is obtained. The AUV simulation control system is built by using REMUS underwater vehicle model in Simulink. The simulation results show that the improved control method with better dynamic performance has solved the original excessive saturation issue, and can adapt to different learning rates and network initial weight,and is of certain reference value to the practical application …

Research On Motion Cueing Algorithm Based On Vr Motion Simulator, Xiaolu Li, Jianfeng Yan, Cangsu Xu, Zongming Wu, Yuanhui Zhang, Junjiang Zhu

Journal of System Simulation

Abstract: Aiming at the phase delay and the false suggest of the classical motion-sensing simulation algorithm in VR motion simulator that lead to insufficient consistency between virtual and real movement and cause VR motion sickness disease, an improved motion-sensing simulation algorithm is proposed. Based on the classical simulation algorithm, the algorithm compromises the vestibular sensory system, feeds back the output error, and applies the fuzzy control algorithm to modify and forecast the input acceleration and angular velocity. This improved motion-sensing simulation algorithm is trained in the condition of virtual choppy terrain. The MATLAB/Simulink simulation results show that the improved motion-sensing …

Control Improvement And Simulation Of Dfig Under Power Grid Failure, Hongyang Zhang, Zhentang Shi, Zhifeng Zhang

Journal of System Simulation

Abstract: Following the increasing scale of installed wind power, the wind turbines, as an important part of the future energy internet, its ability to cope with the fault of the power grid becomes more and more important. Aiming at the transient characteristics of doubly fed induction generator (DFIG) under power grid fault, a comprehensive control strategy, based on the classification of power grid faults, the optimization of controller parameters and auxiliary equipments, is proposed. Compared with the traditional control method, the large control error and response lag is overcome, and the fine control is realized. Based on MATLAB and VC++ …

Shielding Modeling And Simulation Of Coastal Building To Vts Radar, Chunhui Zhou, Zhou Ling, Langxiong Gan, Xiaodong Cheng, Junjie Gao

Journal of System Simulation

Abstract: In order to study the shielding influence of coastal building on the VTS radar, a mathematical expression model of shielding area is proposed. The expression model are divided into finite continuous 3D shielding area, infinite continuous 3D shielding area, finite discontinuous 3D shielding area and infinite discontinuous 3D shielding area. The range and height of the shielding area are calculated, according to the expression model and spatial geometric relation. In addition, 3ds MAX is used in the modeling and simulation of shielding area. Taking the influence of Prince's Bay Cruise Terminal Building on the radar Shekou radar as an …

Interference Management Mechanism In Next Generation Dense Wlan, Ronghui Hou, Xiaoyao Ma, Liu Yi, Hongyan Li

Journal of System Simulation

Abstract: Aiming at the unfairness and low throughput in a wireless local area network with dense access points and terminals deployment, a user-centered resource allocation method which can configure the specific channel and power level for each user is proposed. This method can maximize the network throughput while ensuring the minimum throughput requirement for each user. The proposed interference management mechanism and user identification method can be easily implemented in the current wireless local area network system. Simulation results show that the proposed resource allocation scheme enhances about 47.3% throughput to a basic service set. In particular, 190% improvement can …

Cuckoo Search Algorithm With Dynamic Step And Discovery Probability, Jingsen Liu, Xiaozhen Liu, Li Yu

Journal of System Simulation

Abstract: In order to further improve the low accuracy and slow convergence speed of algorithm search, a cuckoo search algorithm with dynamic step size and probability of discovery is proposed. The algorithm dynamically constrains the Levy's moving step of each generation by introducing the step adjustment factor, which makes the Levy's flight mechanism adaptive. In the probability of finding, the random inertia weight with uniform distribution and F distribution is used to change the fixed value of the probability of discovery, to strengthen the diversity of the population and to keep the balance between global search and local exploration. The …

Algorithms And Framework For Computing 2-Body Statistics On Graphics Processing Units, Napath Pitaksirianan

USF Tampa Graduate Theses and Dissertations

Various types of two-body statistics (2-BS) are regarded as essential components of low-level data analysis in scientific database systems. In relational algebraic terms, a 2-BS is essentially a Cartesian product between two datasets (or two instances of the same dataset) followed by a user-defined aggregate. The quadratic complexity of these computations hinders the timely processing of data. Thus using modern parallel hardware has become an obvious solution to meet such challenges. This dissertation presents our recent work in designing and optimizing parallel algorithms for 2-BS computation on Graphics Processing Units (GPUs). The unique architecture, however, provides abundant opportunities for optimizing …

Modelling And Simulation For NoX Emission Concentration Of Scr Denitrification System, Dong Ze, Laiqing Yan

Journal of System Simulation

Abstract: The selective catalytic reduction (SCR) denitrification system has the features of non-linearity, large lag and strong disturbance, when the operating condition changes. Based on mutual information (MI) and Kernel-based Orthogonal Projections to Latent Structures (KOPLS), the model for NO_x emission concentration is proposed. The time-delay of each input variable is estimated by mutual information, and phase space construction is performed, KOPLS is utilized to modelling. KOPLS shows the merits of strong generalization, nonlinear fitting and anti-noise in the simulation of benchmark datasets. According to field data analysis, RMSE of MI-KOPLS in training and test are reduced by 17% …

Moea/D Algorithm Based On The Hybrid Framework For Multi-Objective Evolutionary Algorithm, Hongjun Tian, Wang Lei, Qidi Wu

Journal of System Simulation

Abstract: Aimto the difficulties of designing the bonding mechanism of global optimization algorithm and local search strategy for hybrid multi-objective evolutionary algorithm, and of improving the performance of multi-objective evolutionary algorithms, based on the feedback control idea, a systematic and modular hybrid MOEA/D algorithm combining the global optimization and local search is proposed. In the algorithm, a diversity measure method based on crowded entropy is designed; a local search strategy based on simplified quadratic approximation and population diversity enhancement strategy for MOEA/D is proposed. The numerical experiments show that the proposed HMOEA/D can achieve a balance between diversity …

Research On Approximate Reference Algorithm Of Svdbn Based On Sliding Window, Haiyang Chen, Chai Bing, Ruilan Wang, Cao Lu

Journal of System Simulation

Abstract: Structure-variable dynamic Bayesian networks (SVDBN) have the special advantage in dealing with the uncertainty of the unstable processes. In order to overcome the disadvantage that the inference algorithms of the SVDBN are unable to apply online, introducing the concepts of SVDBN sliding window and the window width, the online approximate inference mechanism of structure-variable dynamic Bayesian networks based on sliding window is explained, and two online algorithms are proposed, that is the recursive inference algorithm of structure-variable discrete dynamic Bayesian networks (SVDDBN) based on sliding window and the fast inference algorithm of SVDDBN based on sliding window. Experimental simulations …

Integrated Simulation Test Platform For Environment Perception And Planning Decision Of Intelligent Vehicle, Sun Jian, Runhan Huang, Li Lin, Qiyuan Liu, Yudi Li

Journal of System Simulation

Abstract: The simplicity of testing modules and the lack of high-fidelity and high-density traffic scenes are the primary issues in the intelligent vehicle' simulation test. To solve these problems, a "software in the loop" integration test platform is built. The environmental perception module is integrated on the basis of the PreScan, the planning decision-making module designed by MATLAB/Simulink and the virtual traffic flow environment from Vissim. Based on this platform, high-fidelity traffic flow scenes can be generated rapidly to support the test of environment perception and decision-making integratedly and effectively. Moreover, the intelligent vehicle's influence on the traffic flow …

Tele-Robot Control System With Online Virtual Simulation Prediction, Lingyan Hu, Kangbai Shi, Bichun Zhang, Shaoping Xu

Journal of System Simulation

Abstract: When a tele-robot with virtual simulation system works in a complicated environment, the virtual scene may not synchronize with the real one. This may cause the operator on the master side to give wrong instruction. This paper presents a tele-robot with online virtual model correction. The virtual simulation system on the master side builds a virtual model of environment and robot on the slave side. It predicts the motion of the slave robot in real time according the commands from the operator. In order to ensure the virtual scene synchronize with the real one, the measured data on the …

Monocular Depth Image Mark-Less Pose Estimation Based On Feature Regression, Chen Ying, Shen Li

Journal of System Simulation

Abstract: Monocular camera mark-less pose estimation system suffers low accuracy, robustness and efficiency due to variety of action, self-occlusion of human body. A method of feature exaction from point clouds was proposed, in which a single-to-multiple (S2M) feature regressor and a joint position regressor were designed to quickly and accurately predict the 3D positions of body joints from a single depth image without any temporal information. Experiment result shows that the estimation accuracy is superior to that of state-of-the-arts and multi-camera based methods.

Cascade Transmission Evaluation Of Ecosystem Damage Caused By Dust Migration, Guangqiu Huang, He Tong, Qiuqin Lu

Journal of System Simulation

Abstract: To solve the cascade transmission evaluation of ecosystem damage caused by dust migration in mining area, the migration network is constructed by dust migration path, and the potential hazard source path is identified. The definition of Petri-net simulation model of ecosystem damage with cascade propagation (PN-EDCP) is given, and the general method of abstracting migration paths network into a Petri net model is expounded. By introducing the concepts of attributes and methods of place objects into Petri net model, the real meaning of the model is clear, and the ability of describing and analyzing the logical relationship between ecosystem …

Demand Forecasting Of Wartime Spares Based On Evidence Theory, Yunjing Zhang, Xinxin Wang, Wang Yang, Guangming Tang

Journal of System Simulation

Abstract: A new method based on evidence theory is proposed to solve the lack of data for the demand prediction of spares in wartime. Utilizing Markov chain model to research the rule of spares demand of peacetime from the historical data. A Markov chain transfer probability adjustment strategy, based on the change of combat intensity, is designed, which can be used to simulation the rule of spares demand in wartime. Under the experience of experts and the combination of the Fuzzy theory and evidence theory, the spares demand is wartime is forecasted. The simulation example shows that the …