Computer Sciences Commons^™

A Multiple Case Study Of Meti Cybersecurity Education And Training : A Basis For The Development Of A Guiding Framework For Educational Approaches, Jeric Bacasdoon

World Maritime University Dissertations

No abstract provided.

Fuzzy Multi Criteria Decision Making Approach For Technology Selection For Emissions Reduction From Seaborne Transportation Under Uncertainty And Vagueness, Rachid Mouaici

World Maritime University Dissertations

No abstract provided.

Maritime Cybersecurity : Comparing Practices Between Developing Countries : The Case Study Of Kenya And Spain, Bibian Turyahumura

World Maritime University Dissertations

No abstract provided.

Review Of Cybersecurity Hardware Devices, Eriselda Malaj, Galia Marinova

UBT International Conference

In the modern world, cybersecurity is an important issue in the field of technology. The main security problem is the security of the data we receive on the server side after being sent by the client or by the sensors. Nowadays cybersecurity is seen as an area where software is more important than hardware and this led to an increase in the number of securities at the software level. By increasing security at the hardware level cyber security takes another dimension. Network infrastructure devices serve for the realization of communication of applications, data, services and multi-media. These devices include firewalls, …

Direct Digital Synthesis Optimization Based On Vhdl Code, Marsida Ibro, Gentiana Blakaj

UBT International Conference

In this paper, we will describe the synthesis of Direct Digital Synthesis (DDS) circuit using VHDL language. Nowadays the DDS are being used widely in the fields of telecommunication and especially as generators. The DDS circuits are used to generate analog signals with the use of fully digital circuits. The aim of this work is to present the implementation of DDS with the VHDL language, which offers compatibility with FPGA devices. Initially, the VHDL code was generated automatically via Matlab / Simulink model, designed by using HDL Coder components which are compatible with VHDL.

Finally, in order to optimize the …

Low Hydrophobic Mismatch Scores Calculated For Hla-A/B/Dr/Dq Loci Improve Kidney Allograft Survival, Dulat Bekbolsynov, Beata Mierzejewska, Jadwiga Borucka, Robert S. Liwski, Anna L. Greenshields, Joshua Breidenbach, Bradley Gehring, Shravan Leonard-Murali, Sadik A. Khuder, Michael Rees, Robert C. Green Ii, Stanislaw M. Stepkowski

Computer Science Faculty Publications

We evaluated the impact of human leukocyte antigen (HLA) disparity (immunogenicity; IM) on long-term kidney allograft survival. The IM was quantified based on physicochemical properties of the polymorphic linear donor/recipient HLA amino acids (the Cambridge algorithm) as a hydrophobic, electrostatic, amino acid mismatch scores (HMS\AMS\EMS) or eplet mismatch (EpMM) load. High-resolution HLA-A/B/DRB1/DQB1 types were imputed to calculate HMS for primary/re-transplant recipients of deceased donor transplants. The multiple Cox regression showed the association of HMS with graft survival and other confounders. The HMS integer 0-10 scale showed the most survival benefit between HMS 0 and 3. The Kaplan-Meier analysis showed that: …

The Dangers Of Doxing And Swatting: Why Texas Should Criminalize These Malicious Forms Of Cyberharassment, Hannah Mery

St. Mary's Law Journal

Abstract forthcoming.

The Ratio Method: Addressing Complex Tort Liability In The Fourth Industrial Revolution, Harrison C. Margolin, Grant H. Frazier

St. Mary's Law Journal

Emerging technologies of the Fourth Industrial Revolution show fundamental promise for improving productivity and quality of life, though their misuse may also cause significant social disruption. For example, while artificial intelligence will be used to accelerate society’s processes, it may also displace millions of workers and arm cybercriminals with increasingly powerful hacking capabilities. Similarly, human gene editing shows promise for curing numerous diseases, but also raises significant concerns about adverse health consequences related to the corruption of human and pathogenic genomes.

In most instances, only specialists understand the growing intricacies of these novel technologies. As the complexity and speed of …

Behind The Scenes: On The Relationship Between Developer Experience And Refactoring, Eman Abdullah Alomar, Mohamed Wiem Mkaouer, Anthony Peruma, Christian D. Newman, Ali Ouni

Articles

Refactoring is widely recognized as one of the efficient techniques to manage technical debt and maintain a healthy software project through enforcing best design practices, or coping with design defects. Previous refactoring surveys have shown that code refactoring activities are mainly executed by developers who have sufficient knowledge of the system’s design, and disposing of leadership roles in their development teams. However, these surveys were mainly limited to specific projects and companies. In this paper, we explore the generalizability of the previous results by analyzing 800 open-source projects. We mine their refactoring activities, and we identify their corresponding contributors. Then, …

Validation Of A Spatial Agent-Based Model For Taenia Solium Transmission (“Cystiagent”) Against A Large Prospective Trial Of Control Strategies In Northern Peru, Ian W. Pray, Francesco Pizzitutti, Gabrielle Bonnet, Eloy Gonzalez-Gustavson, Wayne Wakeland, William K. Pan, William E. Lambert, Armando E. Gonzalez, Hector H. Garcia, Seth E. O’Neal

Complex Systems Faculty Publications and Presentations

Background: The pork tapeworm (Taenia solium) is a parasitic helminth that imposes a major health and economic burden on poor rural populations around the world. As recognized by the World Health Organization, a key barrier for achieving control of T. solium is the lack of an accurate and validated simulation model with which to study transmission and evaluate available control and elimination strategies. CystiAgent is a spatially-explicit agent based model for T. solium that is unique among T. solium models in its ability to represent key spatial and environmental features of transmission and simulate spatially targeted interventions, such as ring …

Multi-Valued Solutions For The Equation Of Motion, Darcy-Jordan Model, As A Cauchy Problem: A Shocking Event, Chandler Shimp

Master's Theses

Shocks are physical phenomenon that occur quite often around us. In this thesis we examine the occurrence of shocks in finite amplitude acoustic waves from a numerical perspective. These waves, or jump discontinuities, yield ill-behaved solutions when solved numerically. This study takes on the challenge of finding both single- and multi-valued solutions.

The previously unsolved problem in this study is the representation of the Equation of Motion (EoM) in the form of the Darcy-Jordan model (DJM) and expressed as a dimensionless IVP Cauchy problem. Prior attempts to solve have resulted only in implicit solutions or explicit solutions with certain initial …

Generating Synthetic Training Data For Deep Learning-Based Uav Trajectory Prediction, Brendan T. Morris, Stefan Becker, Ronny Hug, Wolfgang Huebner, Michael Arens

Electrical & Computer Engineering Faculty Research

Deep learning-based models, such as recurrent neural networks (RNNs), have been applied to various sequence learning tasks with great success. Following this, these models are increasingly replacing classic approaches in object tracking applications for motion prediction. On the one hand, these models can capture complex object dynamics with less modeling required, but on the other hand, they depend on a large amount of training data for parameter tuning. Towards this end, we present an approach for generating synthetic trajectory data of unmanned-aerial-vehicles (UAVs) in image space. Since UAVs, or rather quadrotors are dynamical systems, they can not follow arbitrary trajectories. …

Multi-Object Localization In Robotic Hand, Tsing Tsow

USF Tampa Graduate Theses and Dissertations

We have developed a machine learning approach to localized objects inside a robotic hand using only images from 2D cameras. Specifically, we used deep learning method (You Only Look Once, YOLO) and Iterative closest Point (ICP) to estimate the 3D coordinates of the objects in a robotic hand. This method will also output the number of objects inside the robotic hand in addition to the coordinates of the objects. We have demonstrated the performance with simulation and obtained typical accuracy within a few pixels (couple mm) and counting accuracy of about 76%. We have also applied it to real images, …

Shape-Based Classification Of Partially Observed Curves, With Applications To Anthropology, Gregory J. Matthews, Karthik Bharath, Sebastian Kurtek, Juliet K. Brophy, George K. Thiruvathukal, Ofer Harel

Computer Science: Faculty Publications and Other Works

We consider the problem of classifying curves when they are observed only partially on their parameter domains. We propose computational methods for (i) completion of partially observed curves; (ii) assessment of completion variability through a nonparametric multiple imputation procedure; (iii) development of nearest neighbor classifiers compatible with the completion techniques. Our contributions are founded on exploiting the geometric notion of shape of a curve, defined as those aspects of a curve that remain unchanged under translations, rotations and reparameterizations. Explicit incorporation of shape information into the computational methods plays the dual role of limiting the set of all possible completions …

Informing Complexity: The Business Case For Managing Digital Twins Of Complex Process Facilities As A Valuable Asset, William Randell Mcnair

USF Tampa Graduate Theses and Dissertations

The Digital Twins of complex facilities, specifically 3D models created during their design, is a potentially valuable information asset. This three- article dissertation explores the business case for firms in the petrochemical process industry to manage throughout the facility lifecycle. A maturity model is provided to illustrate the stages of digital twin evolution and serves as a tool to help communicate each of the five levels of digital twin maturity achievable in various use cases. An industry analysis reviews existing literature and proposes a model to assess informing or insight value of digital twins from three perspectives. Next, an empirical …

Residential Curbside Recycle Context Analysis, Ntchanang Mpafe

USF Tampa Graduate Theses and Dissertations

Curbside recycling as a preferred mode of residential and municipal sustainability goals seems to have an overwhelming acceptance and adoption in the US. About 69.8 million out of 97.3 million (72%) single-family households in the United States have access to curbside recycling services (State of Curbside Recycling Report, 2020). Collectively, the programs divert about nine million tons of recyclables from landfill disposal each year (Cottom, 2019).

For a design that started in the 1980s in the US, its rapid universal adoption seems to have precluded a concerted effort in examining the coproduced nature (Households: service receptors and Municipalities: service providers) …

Check Your Tech - The Ethics Of Deepfakes In A Political Context, Dympna O'Sullivan, Damian Gordon, Ioannis Stavrakakis, Michael Collins

Conference papers

No abstract provided.

Check Your Tech - The Ethics Of Gamification In Education, Dympna O'Sullivan, Ioannis Stavrakakis, Damian Gordon, Anna Becevel

Conference papers

No abstract provided.

Automated Identification Of Stages In Gonotrophic Cycle Of Mosquitoes Using Computer Vision Techniques, Sherzod Kariev

USF Tampa Graduate Theses and Dissertations

In this paper, we design Computer Vision techniques to determine stages in the Gonotrophic cycle of mosquitoes. The dataset for our problem came from 125 adult female mosquitoes - each of which belonged to one of three species - Aedes aegypti, Culex quinquefasciatus, and Anopheles stephensi. The mosquitoes were raised in a lab and passed through all fourGonotrophic stages (Un-fed, Fully-fed, Semi-gravid, and Gravid). At each stage, their images were captured on a plain background via a Xiaomi smartphone, resulting in a dataset of 1784 images. The images were then augmented using standard techniques to generate a larger dataset of …

Beware Of Ips In Sheep's Clothing: Measurement And Disclosure Of Ip Spoofing Vulnerabilities, Alden Douglas Hilton

Theses and Dissertations

Networks not employing destination-side source address validation (DSAV) expose themselves to a class of pernicious attacks which could be prevented by filtering inbound traffic purporting to originate from within the network. In this work, we survey the pervasiveness of networks vulnerable to infiltration using spoofed addresses internal to the network. We issue recursive Domain Name System (DNS) queries to a large set of known DNS servers world-wide using various spoofed-source addresses. In late 2019, we found that 49% of the autonomous systems we tested lacked DSAV. After a large-scale notification campaign run in late 2020, we repeated our measurements in …

Detection Of Dental Apical Lesions Using Cnns On Periapical Radiograph, Chun-Wei Li, Szu-Yin Lin, He-Sheng Chou, Tsung-Yi Chen, Yu-An Chen, Sheng-Yu Liu, Yu-Lin Liu, Chiung-An Chen, Yen-Cheng Huang, Shih-Lun Chen, Yi-Cheng Mao, Patricia Angela R. Abu, Wei-Yuan Chiang, Wen-Shen Lo

Department of Information Systems & Computer Science Faculty Publications

Apical lesions, the general term for chronic infectious diseases, are very common dental diseases in modern life, and are caused by various factors. The current prevailing endodontic treatment makes use of X-ray photography taken from patients where the lesion area is marked manually, which is therefore time consuming. Additionally, for some images the significant details might not be recognizable due to the different shooting angles or doses. To make the diagnosis process shorter and efficient, repetitive tasks should be performed automatically to allow the dentists to focus more on the technical and medical diagnosis, such as treatment, tooth cleaning, or …

Eveloping A Suitability Assessment Criteria For Software Developers: Behavioral Assessment Using Psychometric Test, Jayati Gulati, Bharti Suri, Luiz Fernando Capretz, Bimlesh Wadhwa, Anu Singh Lather

Electrical and Computer Engineering Publications

A suitability assessment instrument for software developers was created using a psychometric criteria that identify the impact of behavior on the performance of software engineers. The instrument uses a questionnaire to help both individuals and IT recruiters to identify the psychological factors that affect the working performance of software engineers. Our study identifies the relationship between the behavioral drivers and the programming abilities of the subjects. In order to evaluate the instrument, a total of 100 respondents were compared on the basis of their programming skills and nine behavioral drivers. It was concluded that there is a direct relationship between …

Towards Accurate Run-Time Hardware-Assisted Stealthy Malware Detection: A Lightweight, Yet Effective Time Series Cnn-Based Approach, Hossein Sayadi, Yifeng Gao, Hosein Mohammadi Makrani, Jessica Lin, Paulo Cesar Costa, Setareh Rafatirad, Houman Homayoun

Computer Science Faculty Publications

According to recent security analysis reports, malicious software (a.k.a. malware) is rising at an alarming rate in numbers, complexity, and harmful purposes to compromise the security of modern computer systems. Recently, malware detection based on low-level hardware features (e.g., Hardware Performance Counters (HPCs) information) has emerged as an effective alternative solution to address the complexity and performance overheads of traditional software-based detection methods. Hardware-assisted Malware Detection (HMD) techniques depend on standard Machine Learning (ML) classifiers to detect signatures of malicious applications by monitoring built-in HPC registers during execution at run-time. Prior HMD methods though effective have limited their study on …

Facilitating Team-Based Data Science: Lessons Learned From The Dsc-Wav Project, Chelsey Legacy, Andrew Zieffler, Benjamin S. Baumer, Valerie Barr, Nicholas J. Horton

Statistical and Data Sciences: Faculty Publications

While coursework provides undergraduate data science students with some relevant analytic skills, many are not given the rich experiences with data and computing they need to be successful in the workplace. Additionally, students often have limited exposure to team-based data science and the principles and tools of collaboration that are encountered outside of school. In this paper, we describe the DSC-WAV program, an NSF-funded data science workforce development project in which teams of undergraduate sophomores and juniors work with a local non-profit organization on a data-focused problem. To help students develop a sense of agency and improve confidence in their …

Using Hyper-Dimensional Spanning Trees To Improve Structure Preservation During Dimensionality Reduction, Curtis Thomas Davis

USF Tampa Graduate Theses and Dissertations

Understanding relations in hyper-dimensional data is a prevalent problem, which is often approached by using dimensionality reduction. The structure preserved from the original data is often dependent on the type of dimension reduction algorithm used, and it can produce results that vary substantially from one another. Visualizing hyper-dimensional data helps to understand the data, but it presents a problem, as our visualizations rely upon two or three-dimensional displays. Current dimension reduction methods, used to reduce hyper-dimensional data to low-dimensional data, often produce results that fail to preserve the structure as the complexity of the data increases. This reduction in dimension …

Scheduling Optimization Research Based On Tabu Algorithm For Uncertainty Carrier Aircraft Support, Yangkai Meng, Wang Zheng, Jiali Fan

Journal of System Simulation

Abstract: In order to improve the scheduling stability of ship-borne and reduce the uncertainty risk during the operation, the deck scheduling mathematical model is designed. For the refueling uncertainty, the equipment failure distribution function is established, and the research method of guarantee operation risk factor value and fault opportunity influence factor is proposed. The uncertainty target function calculation model is derived and solved using the improved taboo algorithm to obtain the scheduling optimization scheme. Simulation experimental results verify the effectiveness and feasibility of the proposed research method.

Three-Dimensional Visual Dynamic Simulation Of Rice Leaf Cells, Deheng Zhao, Yingding Zhao, Hongyun Yang, Wenlong Yi

Journal of System Simulation

Abstract: To explore the evolution process of rice leaf cell morphology with the help of computer visualization technology, it is necessary to establish the biomechanical relationship between the cell geometry model and its deformation. A dynamic simulation method is proposed for the 3D visualization of leaf cells based on the physical-mechanical properties, in which the cytoskeleton topology is represented by a "half-edge" data structure, and the surface geometries are constructed using a bicubic Bézier surface. The control parameters of a deformed surface are determined through "vertex", "edge" or "face" topological unit query algorithms of the cytoskeleton, and the cell stress-strain …

Research On Simulation Data Mapping For Production Performance Digital Twin, Junfeng Wang, Yufan Zhang, Yaoqi Shao, Shiqi Li

Journal of System Simulation

Abstract: To fully use the real-time data of the physical workshop to realize the accurate mapping of the data to the virtual workshop and drive the simulation and optimization of the manufacturing system, a data mapping method for the digital twin simulation of production performance is proposed. The fusion process of simulation data and production logic model is analyzed from the aspects of simulation data modeling, storage and updating. Focusing on the production performance simulation requirements, the redundancy analysis, outlier analysis and elimination, statistics and fitting of the original production site sample data is preprocessed. The real-time mapping update process …

Research On The Network Of 3d Smoke Flow Super-Resolution Data Generation, Jinlian Du, Shufei Li, Xueyun Jin

Journal of System Simulation

Abstract: Aiming at the problem of low data generation efficiency due to the high complexity of solving the N-S equation of smoke flow field, a deep learning model which can generate high-resolution smoke flow data based on low-resolution smoke flow data solved by N-S equation is explored and designed. Based on the Generative Adversarial Network, the smoke data reconstruction network based on the sub voxel convolution layer is constructed. Considering the fluidity of smoke, time loss based on advection step is introduced into the loss function to realize high-precision smoke simulation. By extending the image super-resolution quality evaluation index, the …

Optimized-Xgboost Early Warning Of Wind Turbine Generator Front Bearing Fault, Le Wei, Xiaodong Hu, Yin Shi

Journal of System Simulation

Abstract: In order to identify the abnormal running state of the generator in time, a wind turbine generator front bearing fault early warning method based on Bayesian optimized extreme gradient boosting algorithm is proposed. The historical data collected by SCADA (Supervisory Control And Data Acquisition) are preprocessed by effective data preprocessing methods. The temperature prediction model of the front bearing of wind turbine generator is constructed based on the Bayesian-optimized XGBoost (eXtreme Gradient Boosting) algorithm and the fault early warning threshold of the front bearing of the wind turbine generator is determined based on the 3σ criterion. The experimental …