Computer Sciences Commons^™

Book Review: The Cyber Risk Handbook By Domenic Antonucci, Stanley Mierzwa

International Journal of Cybersecurity Intelligence & Cybercrime

No abstract provided.

Artificial Intelligence: A New Paradigm In Obstetrics And Gynecology Research And Clinical Practice, Pulwasha Iftikhar, Marcela V. Kuijpers, Azadeh Khayyat, Aqsa Iftikhar, Maribel Degouvia De Sa

Publications and Research

Artificial intelligence (AI) is growing exponentially in various fields, including medicine. This paper reviews the pertinent aspects of AI in obstetrics and gynecology (OB/GYN) and how these can be applied to improve patient outcomes and reduce the healthcare costs and workload for clinicians.

Herein, we will address current AI uses in OB/GYN, and the use of AI as a tool to interpret fetal heart rate (FHR) and cardiotocography (CTG) to aid in the detection of preterm labor, pregnancy complications, and review discrepancies in its interpretation between clinicians to reduce maternal and infant morbidity and mortality. AI systems can be used …

The Rise And Infiltration Of Pac-Man And Street Fighter, Angelic Phan

University Honors Theses

With the social, cultural, and economic influence of video games, it is important to examine why they have become such popular forms of entertainment. Particularly, why certain franchises have continued to persist among the growing industry. Two notable franchises are Pac-Man and Street Fighter, which are also most frequently discussed in scholarly texts. I supplement a literature review with an analysis of marketing texts to illuminate a series of shared factors that help explain both games' popularity despite the apparent dissimilarities of their content. First, my work helps us look across multiple scholarly papers to create a bigger picture …

Improving Ocr Accuracy Of Damaged Pictures With Generative Adversarial Networks, Pu Du

LSU Master's Theses

In this thesis, we focus on resolving the inpainting problem and improving Optical Character Recognition (OCR) accuracy of damaged text images at character level. We present a Generative Adversarial Network (GAN)-based model conditioned on class labels for image inpainting. This model is a deep convolutional neural network with encoder-decoder style architecture which can process images with holes at random locations. Experiments on the character images dataset demonstrate that our proposed model generates promising inpainting results and significantly improve OCR accuracy by reconstructing missing parts of damaged character images.

Apparatus For Securely Configuring A Target Device And Associated Methods, Timothy J. Pierson, Xiaohui Liang, Ronald Peterson, David Kotz

Other Faculty Materials

Apparatus and method securely transfer first data from a source device to a target device. A wireless signal having (a) a higher speed channel conveying second data and (b) a lower speed channel conveying the first data is transmitted. The lower speed channel is formed by selectively transmitting the wireless signal from one of a first and second antennae of the source device based upon the first data. The first and second antenna are positioned a fixed distance apart and the target device uses a received signal strength indication (RSSI) of the first signal to decode the lower speed channel …

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 …

Algorithms To Profile Driver Behavior From Zero-Permission Embedded Sensors, Bharti Goel

USF Tampa Graduate Theses and Dissertations

In this dissertation, we design algorithms to profile driver behavior from zero-permission sensors embedded in modern smartphones and wearables. These sensors are typically the accelerometer, gyroscope, magnetometer, pressure sensor and a few more than are now available in most modern smartphones and wearables. In order to profile driving behavior, we devised algorithms for detecting distraction while driving due to the use of modern-day smartphones (e.g., calling, texting and reading while driving) in real-time.

To do so, we conduct an experiment with 16 subjects on a realistic driving simulator, where each subject, where each subject carries a smartphone and a wearable …

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 …

Towards Safe Power Oversubscription And Energy Efficiency Of Data Centers, Sulav Malla

USF Tampa Graduate Theses and Dissertations

Data centers contribute to approximately 1% of the global electricity consumption, and billions of dollars are spent annually worldwide in construction of new data centers to meet the rising demand for cloud-based services. Given the high cost of construction, the power infrastructure in a data center is typically oversubscribed. Power oversubscription leads to efficient use of data center power hierarchy while simultaneously reducing the power provisioning cost. Power overload situations can occur in oversubscribed data centers. Power overload can lead to power capping of servers or even power outages – both of which degrade the performance of the services offered …

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 …

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 …

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 …

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 …

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 …

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 …

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 …

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 …

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 …

Parts Of Speech Tagging: Rule-Based, Bao Pham

Other Student Works

Parts of speech (POS) tagging is the process of assigning a word in a text as corresponding to a part of speech based on its definition and its relationship with adjacent and related words in a phrase, sentence, or paragraph. POS tagging falls into two distinctive groups: rule-based and stochastic. In this paper, a rule-based POS tagger is developed for the English language using Lex and Yacc. The tagger utilizes a small set of simple rules along with a small dictionary to generate sequences of tokens.

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 …

Improving The Efficiency Of Transport Systems Using Simulation, Bushuev Sergey, Kovalev Igor, Permikin Vadim, Anashkina Nataliia

Journal of System Simulation

Abstract: The article describes the possibilities of application of simulation modeling for the analysis of infrastructure and technology of transport services of enterprises. The main technological and possible economic effects for the enterprises arising at performance of modeling of a transport component of their work are resulted.

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 …

Optimal Multi-Stage Arrhythmia Classification Approach, Jianwei Zhang, Huimin Chu, Daniele Struppa, Jianming Zhang, Sir Magdi Yacoub, Hesham El-Askary, Anthony Chang, Louis Ehwerhemuepha, Islam Abudayyeh, Alexander Barrett, Guohua Fu, Hai Yao, Dongbo Li, Hangyuan Guo, Cyril Rakovski

Mathematics, Physics, and Computer Science Faculty Articles and Research

Arrhythmia constitutes a problem with the rate or rhythm of the heartbeat, and an early diagnosis is essential for the timely inception of successful treatment. We have jointly optimized the entire multi-stage arrhythmia classification scheme based on 12-lead surface ECGs that attains the accuracy performance level of professional cardiologists. The new approach is comprised of a three-step noise reduction stage, a novel feature extraction method and an optimal classification model with finely tuned hyperparameters. We carried out an exhaustive study comparing thousands of competing classification algorithms that were trained on our proprietary, large and expertly labeled dataset consisting of 12-lead …

Optimization Model And Method Of Urban Road Traffic Signal Control Under Rainfall Environment, Shaohu Tang, Zhou Jin, Chunlin Shang, Guorong Zheng

Journal of System Simulation

Abstract: The efficiency of urban road traffic operation fell obviously during a rain, and the existing road traffic signal control has not yet established a relevant signal optimization scheme. Considering the traffic operation scenario under the influence of rainfall and road water, an urban road traffic cyber physical systems is designed, a framework of urban road traffic control based on cyber physical systems is built, an optimization model of traffic signal control is established, and further more, the solution method of the model is designed by using BP neural network. Building a traffic simulation model of the example intersection, comparing …

Simulation Research And Application On Urban Rail Transit Fully Automatic Operation System, Du Heng, Chunhai Gao, Huang Qing, Huaiming Cang

Journal of System Simulation

Abstract: Following the development of the key technologies for the Fully Automatic Operation (FAO) of urban rail transit and the application of autonomous fully automatic operation system demonstration projects, more and more urban rail transit lines choose the FAO system. High availability, high reliability and high security also need high requirements on the testing and verification before the line is operated. Through the simulation research of the fully automatic operation system, combined with the comprehensive debugging and verification management platform of the Yanfang Line's fully automatic independent demonstration project, the scenario-based FAO system simulation model is established, the key technologies …