Computer Sciences Commons^™

Interdisciplinary Communication By Plausible Analogies: The Case Of Buddhism And Artificial Intelligence, Michael Cooper

USF Tampa Graduate Theses and Dissertations

Communicating interdisciplinary information is difficult, even when two fields are ostensibly discussing the same topic. In this work, I’ll discuss the capacity for analogical reasoning to provide a framework for developing novel judgments utilizing similarities in separate domains. I argue that analogies are best modeled after Paul Bartha’s By Parallel Reasoning, and that they can be used to create a Toulmin-style warrant that expresses a generalization. I argue that these comparisons provide insights into interdisciplinary research. In order to demonstrate this concept, I will demonstrate that fruitful comparisons can be made between Buddhism and Artificial Intelligence research.

Active 2d-Dna Fingerprinting Of Wirelesshart Adapters To Ensure Operational Integrity In Industrial Systems, Willie H. Mims, Michael A. Temple, Robert F. Mills

Faculty Publications

The need for reliable communications in industrial systems becomes more evident as industries strive to increase reliance on automation. This trend has sustained the adoption of WirelessHART communications as a key enabling technology and its operational integrity must be ensured. This paper focuses on demonstrating pre-deployment counterfeit detection using active 2D Distinct Native Attribute (2D-DNA) fingerprinting. Counterfeit detection is demonstrated using experimentally collected signals from eight commercial WirelessHART adapters. Adapter fingerprints are used to train 56 Multiple Discriminant Analysis (MDA) models with each representing five authentic network devices. The three non-modeled devices are introduced as counterfeits and a total of …

Allure: A Multi-Modal Guided Environment For Helping Children Learn To Solve A Rubik's Cube With Automatic Solving And Interactive Explanations, Kausik Lakkaraju, Thahimum Hassan, Vedant Khandelwal, Prathamjeet Singh, Cassidy Bradley, Ronak Shah, Forest Agostinelli, Biplav Srivastava, Dezhi Wu

Faculty Publications

Modern artificial intelligence (AI) methods have been used to solve problems that many humans struggle to solve. This opens up new opportunities for knowledge discovery and education. We demonstrate ALLURE, a collaborative educational AI system for learning to solve the Rubik's cube that is designed to help students improve their problem solving skills. ALLURE can both find its own strategies for solving the Rubik's cube and explain those strategies to humans. In the future, ALLURE will also be able to collaborate with humans by building on user-provided strategies for solving the Rubik's cube and as well as generalize to other …

Explainable And Cooperative Autonomy Across Networks Of Distributed Systems, Peter Joseph Jorgensen

USF Tampa Graduate Theses and Dissertations

Large networks of complex systems-of-systems are commonplace and evermore present in both mundane and extraordinary facets of human existence. From the exponential growth of connectivity via the internet and other information networks, to the miniaturization of computers and sensors, to cross-domain sensor and communication networks, these networks of distributed systems-of-systems (NDSS) present incredible benefits and challenges. Autonomy is perhaps the most important and most difficult to achieve enabling technology for efficient performance of the NDSS. Giving each individual agent in a network the ability to manage its internal state in dynamic operating environments and in pursuit of multiple complex and …

Online Privacy Challenges And Their Forensic Solutions, Bandr Fakiha

Journal of the Arab American University مجلة الجامعة العربية الامريكية للبحوث

In the digital age, internet users are exposed to privacy issues online. Few rarely know when someone else is eavesdropping or about to scam them. Companies, governments, and individual internet users are all vulnerable to security breaches due to the challenges of online privacy ranging from trust and hierarchical control to financial losses. As systems advance, people are optimistic that forensic science will provide long-term interventions that surpass the current solutions, including setting stronger passwords and firewall protection. The future of online privacy is changing, and more practical interventions, such as email, malware, mobile, and network forensics, must be integrated, …

Ultrafast Error-Bounded Lossy Compression For Scientific Datasets, Xiaodong Yu, Sheng Di, Kai Zhao, Jiannan Tian, Dingwen Tao, Xin Liang, Franck Cappello

Computer Science Faculty Research & Creative Works

Today's scientific high-performance computing applications and advanced instruments are producing vast volumes of data across a wide range of domains, which impose a serious burden on data transfer and storage. Error-bounded lossy compression has been developed and widely used in the scientific community because it not only can significantly reduce the data volumes but also can strictly control the data distortion based on the user-specified error bound. Existing lossy compressors, however, cannot offer ultrafast compression speed, which is highly demanded by numerous applications or use cases (such as in-memory compression and online instrument data compression). In this paper, we propose …

Reducing Opioid Use Disorder And Overdose Deaths In The United States: A Dynamic Modeling Analysis, Erin J. Stringfellow, Tse Yang Lim, Keith Humphreys, Catherine Digennero, Celia Stafford, Elizabeth Beaulieu, Jack Homer, Wayne Wakeland, Multiple Additional Authors

Complex Systems Faculty Publications and Presentations

Opioid overdose deaths remain a major public health crisis. We used a system dynamics simulation model of the U.S. opioid-using population age 12 and older to explore the impacts of 11 strategies on the prevalence of opioid use disorder (OUD) and fatal opioid overdoses from 2022 to 2032. These strategies spanned opioid misuse and OUD prevention, buprenorphine capacity, recovery support, and overdose harm reduction. By 2032, three strategies saved the most lives: (i) reducing the risk of opioid overdose involving fentanyl use, which may be achieved through fentanyl-focused harm reduction services; (ii) increasing naloxone distribution to people who use opioids; …

Positive Rate-Dependent Action Potential Prolongation By Modulating Potassium Ion Channels, Candido Cabo

Publications and Research

Pharmacological agents that prolong action potential duration (APD) to a larger extent at slow rates than at the fast excitation rates typical of ventricular tachycardia exhibit reverse rate dependence. Reverse rate dependence has been linked to the lack of efficacy of class III agents at preventing arrhythmias because the doses required to have an anti-arrhythmic effect at fast rates may have pro-arrhythmic effects at slow rates due to an excessive APD prolongation. In this report we show that, in computer models of the ventricular action potential, APD prolongation by accelerating phase 2 repolarization (by increasing I_Ks) and decelerating …

Data As A Service Ecosystem For Data-Driven Research, Leonardo Vieira

Theses and Dissertations

For the last two decades, the cloud computing ecosystems has become a major defining force for America, because of their unique economic, social and national importance. These ecosystems have now taken their place alongside the nation’s other infrastructure such as the food/agricultural, energy healthcare, and roads/highways. Scientists, engineers, and researchers over the same period have experienced a tremendous growth in the need for resources to that support assorted research. Cloud computing enables these communities to undertake wide-ranging research efforts, while requiring no maintenance, management or significant invest of local resources. The genius of this project examines how create on-ramps for …

Assessing The Reidentification Risks Posed By Deep Learning Algorithms Applied To Ecg Data, Arin Ghazarian, Jianwei Zheng, Daniele Struppa, Cyril Rakovski

Mathematics, Physics, and Computer Science Faculty Articles and Research

ECG (Electrocardiogram) data analysis is one of the most widely used and important tools in cardiology diagnostics. In recent years the development of advanced deep learning techniques and GPU hardware have made it possible to train neural network models that attain exceptionally high levels of accuracy in complex tasks such as heart disease diagnoses and treatments. We investigate the use of ECGs as biometrics in human identification systems by implementing state-of-the-art deep learning models. We train convolutional neural network models on approximately 81k patients from the US, Germany and China. Currently, this is the largest research project on ECG identification. …

Making Curry With Rice: An Optimizing Curry Compiler, Steven Libby

Dissertations and Theses

In this dissertation we present the RICE optimizing compiler for the functional logic language Curry. This is the first general optimizing compiler for a functional logic language. Our work is based on the idea of compiling through program transformations, which we have adapted from the functional language compiler community. We also present the GAS system for generating new program transformations, which uses the power of functional logic programming to provide a flexible framework for describing transformations. This allows us to describe and implement a wide range of optimizations including inlining, shortcut deforestation, unboxing, and case shortcutting, a new optimization we …

Optimizing The Performance Of Parallel And Concurrent Applications Based On Asynchronous Many-Task Runtimes, Weile Wei

LSU Doctoral Dissertations

Nowadays, High-performance Computing (HPC) scientific applications often face per- formance challenges when running on heterogeneous supercomputers, so do scalability, portability, and efficiency issues. For years, supercomputer architectures have been rapidly changing and becoming more complex, and this challenge will become even more com- plicated as we enter the exascale era, where computers will exceed one quintillion cal- culations per second. Software adaption and optimization are needed to address these challenges. Asynchronous many-task (AMT) systems show promise against the exascale challenge as they combine advantages of multi-core architectures with light-weight threads, asynchronous executions, smart scheduling, and portability across diverse architectures.

In …

Edgenext: Efficiently Amalgamated Cnn-Transformer Architecture For Mobile Vision Applications, Muhammad Maaz, Abdelrahman Shaker, Hisham Cholakkal, Salman Khan, Syed Waqas Zamir, Rao Anwer, Fahad Shahbaz Khan

Computer Vision Faculty Publications

In the pursuit of achieving ever-increasing accuracy, large and complex neural networks are usually developed. Such models demand high computational resources and therefore cannot be deployed on edge devices. It is of great interest to build resource-efficient general purpose networks due to their usefulness in several application areas. In this work, we strive to effectively combine the strengths of both CNN and Transformer models and propose a new efficient hybrid architecture EdgeNeXt. Specifically in EdgeNeXt, we introduce split depth-wise transpose attention (SDTA) encoder that splits input tensors into multiple channel groups and utilizes depth-wise convolution along with self-attention across channel …

Assessment Of Sentinel-2 And Landsat-8 Oli For Small-Scale Inland Water Quality Modeling And Monitoring Based On Handheld Hyperspectral Ground Truthing, Qasem Abdel, Mohammed N. Assaf, Abdulla Al-Rawabdeh, Sameer Arabasi, Nathir A. Rawashdeh

Michigan Tech Publications, Part 1

This study investigates the best available methods for remote monitoring inland small-scale waterbodies, using remote sensing data from both Landsat-8 and Sentinel-2 satellites, utilizing a handheld hyperspectral device for ground truthing. Monitoring was conducted to evaluate water quality indicators: chlorophyll-a (Chl-a), colored dissolved organic matter (CDOM), and turbidity. Ground truthing was performed to select the most suitable atmospheric correction technique (ACT). Several ACT have been tested: dark spectrum fitting (DSF), dark object subtraction (DOS), atmospheric and topographic correction (ATCOR), and exponential extrapolation (EXP). Classical sampling was conducted first; then, the resulting concentrations were compared to those obtained using remote sensing …

Dynamic Prototype Convolution Network For Few-Shot Semantic Segmentation, Jie Liu, Yanqi Bao, Guo-Sen Xie, Huan Xiong, Jan-Jakob Sonke, Efstratios Gavves

Machine Learning Faculty Publications

The key challenge for few-shot semantic segmentation (FSS) is how to tailor a desirable interaction among sup-port and query features and/or their prototypes, under the episodic training scenario. Most existing FSS methods im-plement such support/query interactions by solely leveraging plain operations - e.g., cosine similarity and feature concatenation - for segmenting the query objects. How-ever, these interaction approaches usually cannot well capture the intrinsic object details in the query images that are widely encountered in FSS, e.g., if the query object to be segmented has holes and slots, inaccurate segmentation al-most always happens. To this end, we propose a dynamic …

Actuator Cyberattack Handling Using Lyapunov-Based Economic Model Predictive Control, Keshav Kasturi Rangan, Henrique Oyama, Helen Durand

Chemical Engineering and Materials Science Faculty Research Publications

Cybersecurity has gained increasing interest as a consequence of the potential impacts of cyberattacks on profits and safety. While attacks can affect various components of a plant, prior work from our group has focused on the impact of cyberattacks on control components such as process sensors and actuators and the development of detection strategies for cybersecurity derived from control theory. In this work, we provide greater focus on actuator attacks; specifically, we extend a detection and control strategy previously applied for sensor attacks and based on an optimization-based control technique called Lyapunov-based economic model predictive control (LEMPC) to detect attacks …

Test Methods For Image-Based Information In Next-Generation Manufacturing, Henrique Oyama, Dominic Messina, Renee O'Neill, Samantha Cherney, Minhazur Rahman, Keshav Kasturi Rangan, Govanni Gjonaj, Helen Durand

Chemical Engineering and Materials Science Faculty Research Publications

Typical control designs in the process systems engineering literature have assumed that the primary sensing methodologies are traditional instruments such as thermocouples. Dig- italization is changing the landscape for manufacturing, and data-based sensing modalities (e.g., image-based sensing) are becoming of greater interest for plant control. These considerations require novel test/evaluation solutions. For example, process systems engineering researchers may wish to test image-based sensors in simulation. In this work, we provide preliminary thoughts on how image-based technologies might be evaluated via simulation for process systems.

Quantum Computing And Resilient Design Perspectives For Cybersecurity Of Feedback Systems, Keshav Kasturi Rangan, Jihan Abou Halloun, Henrique Oyama, Samantha Cherney, Ilham Azali Assoumani, Nazir Jairazbhoy, Helen Durand, Simon Ka Ng

Chemical Engineering and Materials Science Faculty Research Publications

Cybersecurity of control systems is an important issue in next-generation manufac- turing that can impact both operational objectives (safety and performance) as well as process designs (via hazard analysis). Cyberattacks differ from faults in that they can be coordinated efforts to exploit system vulnerabilities to create otherwise unlikely hazard scenarios. Because coordination and targeted process manipulation can be characteristics of attacks, some of the tactics previously analyzed in our group from a control system cybersecurity perspective have incorporated randomness to attempt to thwart attacks. The underlying assumption for the generation of this randomness has been that it can be achieved …

Challenges And Opportunities For Next-Generation Manufacturing In Space, Kip Nieman, A. F. Leonard, Katie Tyrell, Dominic Messina, Rebecca Lopez, Helen Durand

Chemical Engineering and Materials Science Faculty Research Publications

With commercial space travel now a reality, the idea that people might spend time on other planets in the future seems to have greater potential. To make this possible, however, there needs to be flexible means for manufacturing in space to enable tooling or resources to be created when needed to handle unexpected situations. Next-generation manufacturing paradigms offer significant potential for the kind of flexibility that might be needed; however, they can result in increases in computation time compared to traditional control methods that could make many of the computing resources already available on earth attractive for use. Furthermore, resilience …

Theory About Factoring Service, Burhan Economy Rexhepi Ek

International Journal of Business and Technology

Factoring is one of the oldest and common methods of trade fi nance over the world with a long historical development. According to historians, Factoring is originated 4,000 years ago in the days of King Hammurabi of Mesopotamia whereby the fi rst literate societies were developed. Although Mesopotamia no longer exists, many of its great contributions to civilization have endured, including Factoring. The fi rst documented-use of factoring was widespread occurred in the American colonies before the revolution to serve for trade. With the abundance of the North American landscape, colonists cultivated and traded commodities like cott on, fur and …

Soft Wheat Quality Parameters Evaluation By Near Infrared Spectroscopy: From Field To Shelf Analysis, Kliton Bylykbashi

International Journal of Business and Technology

Near InfraRed Spectroscopy (NIRS) is a powerful tool that is widely applied in agro-food science and technology research for qualitative as well as quantitative analysis. It is one analytical technique that is taking place in this sector due to its low costs, reliability, rapidity and not invasive / non-destructive nature. NIRS along with chemometric modelling can provide accurate assessment of various grain quality attributes and the chemical composition of grain. The present work investigates the ability of using NIRS for the evaluation of different wheat quality parameters by using a portable spectroradiometer working in Visible – Short Wave InfraRed (Vis-SWIR: …

Types Of Suturing Materials In Oral Surgery, Biljana Evrosimovska

International Journal of Business and Technology

Aim: In everyday surgical practice, different types of suturing materials are available. They play an important role in tissue healing, facilitate the process of hemostasis, enable the reconstruction and reunification of tissue whose integrity has been compromised during surgery or trauma. The aim of this study is to examine the reaction of the tissue to different suturing materials, as well as to determine the speed of wound healing and the incidence of complications after their use, in order to prove which of them is most suitable for oral surgery procedure. Material and methods: These researches were done based on analyzes …

Can Democratic Subjectivity Be A Way Out Of Recent Crisis Of Democracy? The Case Of Turkey, Erdem Damar

International Journal of Business and Technology

Drawing from poststructuralist perspective with a specific emphasis on agonistic democracy, this paper emphasises on the notion of democratic subjectivity as a possible way out of the contemporary crisis of liberal democracy. The two faces of this crisis will be elaborated in the first part. While the crisis of democracy is largely produced by the implementations of conservative, technocratic and capitalist politics that embrace minimalist approaches to democracy by reducing it into a set of rules to govern politics, it also gains visibility to the emergence of a wide range of counter-mobilisations contesting these neoliberal variants. In that respect, post-structuralist …

An Unsupervised Deep Neural Network For Image Fusion, Peipei Zhou, Xinglin Hou

Journal of System Simulation

Abstract: Due to the low dynamic range of camera, can not be expressed in the different region of the high dynamic scene a single-exposure image. An unsupervised depth neural network is constructed to fuse the multi-exposure images into a high dynamic image. Based on the VGG-Net, encoding and decoding sub-networks are designed. Guided by the structural similarity of the images before and after fusion, a loss function suitable for image fusion is designed by introducing the weight factors based on the local image information, and the valid information of the different input images is given consideration. Compared with the …

Research And Simulation Of Internet Of Vehicles Task Offloading Based On Mobile Edge Computing, Peng Cheng, Wenzhu Zhang, Shuhan Xie, Zixuan Yang

Journal of System Simulation

Abstract: In order to use the computing resources of edge devices to provide high-quality services, a joint resource allocation and task offloading mechanism is designed for the Internet of Vehicles architecture based on mobile edge computing. In the mechanism, the original problem is decomposed into two sub-problems of resource allocation and offloading decision. The original problem is simplified into the resource allocation of maximizing system capacity, and the initial offloading set is obtained through the proportional resource allocation algorithm; the above problem is solved by the joint offloading decision-making and resource allocation mechanism. The stable experimental results are obtained …

Design And Realization Of 6-Dof Parachuting Simulation Training System, Xiaoguang Zhou, Peng Zhu, Yuanyuan Zhang, Huan Lu, Yuan Zhou

Journal of System Simulation

Abstract: Aiming at restoring the 6-DOF motion process of each stage during parachuting, a 6-DOF parachuting simulation training system is designed and implemented. The architecture of the simulator is designed, and the realization of the sub-systems such as the motion calculation, 6-DOF motion platform, control loading system, virtual reality scene, somatosensory system and management console is explained. Compared with the same type of parachute simulator, this system has introduced a 6-DOF motion platform which can drive the trainees to simulate the various postures of parachuting. It can also help the trainees master the control methods of parachute and enhance the …

A High Spectral-Efficiency Maritime Very-High-Frequency Communication Technology And Simulation, Xinyu Dou, Xiaohui Chen, Dequn Liang, Bin Lin

Journal of System Simulation

Abstract: Marine communications cannot follow the development route on land of developing high frequency resources and high spectral-efficiency modulation technologies in 5G and 6G high-speed communication. The data rate and spectral-efficiency of maritime communications are low and are difficult to be improved. A high spectral-efficiency maritime very-high-frequency (VHF) communication technology based on multi-carrier time-delay overlapping modulation (MC-TDOP) is proposed. The core is delaying the subcarriers in turn and directly overlapping them in time domain. The orthogonality between the subcarriers can be neglected, thus the spectral-efficiency can be further enhanced from the fundamental information modulations. The results show that the proposed …

Simulation Method Of Virtual Human Pose Optimization Based On Vr Peripherals, Muqing Wang, Lei Zhang, Xiumin Fan, Xiaomeng Luo, Wenmin Zhu

Journal of System Simulation

Abstract: The commonly used VR peripheral is the position tracker worn on the operator body and is not very convenient. Focus on the problem, a visual sensor combination-based scheme is proposed to realize the simple and real-time unmarked virtual human driven simulation. On the basis of the parameterized human model SMPL, by minimizing the objective function of multiple error terms, the driven accuracy of the virtual human is improved, and the fitted human body model conforming to the operator form and posture is calculated and the ergonomic evaluation is realized. The module is verified by a case of evaluation in …

Multi-Person Interactive Globe System Based On Ar Technology, Yiling Sun, Yi Chen, Guihua Shan, Xiaoxing Li

Journal of System Simulation

Abstract: The characteristic of multi-source, high-dimensional, time-varying and massive of the Earth big data is difficult to be understood and analyzed. Aiming at this problem and for the science popularization needs, an AR-based multi-person interactive globe system is proposed and implemented. A system architecture integrating AR technology is proposed to realize the seamless overlay combination effect of the virtual information and the physical globe. A data visualization display scheme is designed to realize the visualization of the Earth big data in three-dimensional space. A lightweight multi-person multi-terminal collaboration mechanism is proposed to improve the practicality and interestingness of the system. …

On Approximating Total Variation Distance, Arnab Bhattacharyya, Sutanu Gayen, Kuldeep S. Meel, Dimitrios Myrisiotis, A. Pavan, N. V. Vinodchandran

School of Computing: Faculty Publications

Total variation distance (TV distance) is a fundamental notion of distance between probability distributions. In this work, we introduce and study the computational problem of determining the TV distance between two product distributions over the domain {0, 1}ⁿ. We establish the following results.

1. Exact computation of TV distance between two product distributions is #P-complete. This is in stark contrast with other distance measures such as KL, Chi-square, and Hellinger which tensorize over the marginals.

2. Given two product distributions P and Q with marginals of P being at least 1/2 and marginals of Q being at most …