Computer Sciences Commons^™

New Types Of Soft Sets” Hypersoft Set, Indetermsoft Set, Indetermhypersoft Set, And Treesoft Set”: An Improved Version, Florentin Smarandache

Neutrosophic Systems with Applications

This is an improved paper of [10], where we recall the definitions together with practical applications of the Soft Set and its extensions to HyperSoft Set, IndetermSoft Set, IndetermHyperSoft Set, and TreeSoft Set.

Proposing A Measure Of Ethicality For Humans And Ai, Alejandro Jorge Napolitano Jawerbaum

Electronic Theses and Dissertations

Smarter people or intelligent machines are able to make more accurate inferences about their environment and other agents more efficiently than less intelligent agents. Formally: ‘Intelligence measures an agent’s ability to achieve goals in a wide range of environments.’ (Legg, 2008)

In this dissertation we extend this definition to include ethical behaviour and we will offer a mathematical formalism and a way to estimate how ethical an action is or will be, both for a human and for a computer, by calculating the expected values of random variables. Formally, we propose the following measure of ethicality, which is computable, or …

An Introduction To Bipolar Pythagorean Refined Sets, R. Janani, A. Francina Shalini

Neutrosophic Systems with Applications

The aim of this paper is to introduce the new concept of a Bipolar Pythagorean refined set by combining the two notions called a Bipolar Pythagorean set and a Pythagorean refined set. Also, the basic operations and algebraic properties of the Bipolar Pythagorean refined set are discussed with suitable examples.

An Introduction To Bipolar Pythagorean Refined Sets, R. Janani, A. Francina Shalini

Neutrosophic Systems with Applications

The aim of this paper is to introduce the new concept of a Bipolar Pythagorean refined set by combining the two notions called a Bipolar Pythagorean set and a Pythagorean refined set. Also, the basic operations and algebraic properties of the Bipolar Pythagorean refined set are discussed with suitable examples.

Algebraic Product Is The Only "And-Like"-Operation For Which Normalized Intersection Is Associative: A Proof, Thierry Denœx, Vladik Kreinovich

Departmental Technical Reports (CS)

For normalized fuzzy sets, intersection is, in general, not normalized. So, if we want to limit ourselves to normalized fuzzy sets, we need to normalize the intersection. It is known that for algebraic product, the normalized intersection is associative, and that for many other "and"-operations (t-norms), normalized intersection is not associative. In this paper, we prove that algebraic product is the only "and"-operation (even the only "and-like" operation) for which normalized intersection is associative.

Cybersecurity Safeguards: What Cybersecurity Safeguards Could Have Prevented The Intelligence/Data Breach By A Member Of The Air National Guard, Christopher Curtis Royal

Cyber Operations and Resilience Program Graduate Projects

Jack Teixeira, a 21-year-old IT specialist Air National Guard found himself on the wrong side of the US law after sharing what is considered classified and extremely sensitive information about USA's operations and role in Ukraine and Russia war. Like other previous cases of leakage of classified intelligence, the case of Teixeira raises concerns about the weaknesses and vulnerability of federal agencies' IT systems and security protocols governing accessibility to classified documents. Internal leakages of such classified documents hurt national security and can harm the country, especially when such secretive intelligence finds its way into the hands of enemies. Unauthorized …

Simulation And Analysis Of Self-Assembling Slat-Based Dna Ribbons, Lukas Vaughan, Hunter J. Fleming

Computer Science and Computer Engineering Undergraduate Honors Theses

Though still in its infancy, the design of DNA crisscross slats presents great potential in the algorithmic self-assembly of DNA. The provision for higher levels of cooperativity allows for fewer errors through the natural proofreading of slat placement, leading to more robust assembly. Highly accurate simulations of self-assembling DNA squares have been achieved by following the kinetic Tile Assembly Model. Building on that foundation, this study seeks to calibrate the system parameters of a kinetic simulator for self-assembling DNA slats to match experimental results and to use those ranges of parameters to perform exploratory simulations of systems not yet tested …

Arabic Dysarthric Speech Recognition Using Adversarial And Signal-Based Augmentation, Massa Baali, Ibrahim Almakky, Shady Shehata, Fakhri Karray

Machine Learning Faculty Publications

Despite major advancements in Automatic Speech Recognition (ASR), the state-of-the-art ASR systems struggle to deal with impaired speech even with high-resource languages. In Arabic, this challenge gets amplified, with added complexities in collecting data from dysarthric speakers. In this paper, we aim to improve the performance of Arabic dysarthric automatic speech recognition through a multi-stage augmentation approach. To this effect, we first propose a signal-based approach to generate dysarthric Arabic speech from healthy Arabic speech by modifying its speed and tempo. We also propose a second stage Parallel Wave Generative (PWG) adversarial model that is trained on an English dysarthric …

S2cd: Self-Heuristic Speaker Content Disentanglement For Any-To-Any Voice Conversion, Pengfei Wei, Xiang Yin, Chunfeng Wang, Zhonghao Li, Xinghua Qu, Zhiqiang Xu, Zejun Ma

Machine Learning Faculty Publications

In this paper, we propose a Self-heuristic Speaker Content Disentanglement (S2CD) model for any to any voice conversion without using any external resources, e.g., speaker labels or vectors, linguistic models, and transcriptions. S2CD is built on the disentanglement sequential variational autoencoder (DSVAE), but improves DSVAE structure at the model architecture level from three perspectives. Specifically, we develop different structures for speaker and content encoders based on their underlying static/dynamic property. We further propose a generative graph, modelled by S2CD, so as to make S2CD well mimic the multi-speaker speech generation process. Finally, we propose a self-heuristic way to introduce bias …

Fooctts: Generating Arabic Speech With Acoustic Environment For Football Commentator, Massa Baali, Ahmed Ali

Machine Learning Faculty Publications

This paper presents FOOCTTS, an automatic pipeline for a football commentator that generates speech with background crowd noise. The application gets the text from the user, applies text pre-processing such as vowelization, followed by the commentator's speech synthesizer. Our pipeline included Arabic automatic speech recognition for data labeling, CTC segmentation, transcription vowelization to match speech, and fine-tuning the TTS. Our system is capable of generating speech with its acoustic environment within limited 15 minutes of football commentator recording. Our prototype is generalizable and can be easily applied to different domains and languages.

Why Unit Two-Variable-Per-Inequality (Utvpi) Constraints Are So Efficient To Handle: Intuitive Explanation, Saeid Tizpaz-Niari, Martine Ceberio, Olga Kosheleva, Vladik Kreinovich

Departmental Technical Reports (CS)

In general, integer linear programming is NP-hard. However, there exists a class of integer linear programming problems for which an efficient algorithm is possible: the class of so-called unit two-variable-per-inequality (UTVPI) constraints. In this paper, we provide an intuitive explanation for why an efficient algorithm turned out to be possible for this class. Namely, the smaller the class, the more probable it is that a feasible algorithm is possible for this class, and the UTVPI class is indeed the smallest -- in some reasonable sense described in this paper.

Industry-Academia Collaboration: Main Challenges And What Can We Do, Olga Kosheleva, Vladik Kreinovich

Departmental Technical Reports (CS)

How can we bridge the gap between industry and academia? How can we make them collaborate more effectively? In this essay, we try to come up with answers to these important questions.

Towards A Psychologically Natural Relation Between Colors And Fuzzy Degrees, Victor L. Timchenko, Yuriy P. Kondratenko, Olga Kosheleva, Vladik Kreinovich, Nguyen Hoang Phuong

Departmental Technical Reports (CS)

A natural way to speed up computations -- in particular, computations that involve processing fuzzy data -- is to use the fastest possible communication medium: light. Light consists of components of different color. So, if we use optical color computations to process fuzzy data, we need to associate fuzzy degrees with colors. One of the main features -- and of the main advantages -- of fuzzy technique is that the corresponding data has intuitive natural meaning: this data comes from words from natural language. It is desirable to preserve this naturalness as much as possible. In particular, it is desirable …

Why Attitudes Are Usually Mutual: A Possible Mathematical Explanation, Julio C. Urenda, Vladik Kreinovich

Departmental Technical Reports (CS)

In this paper, we provide a possible mathematical explanation of why people's attitude to each other is usually mutual: we usually have good attitude who those who have good feelings towards us, and we usually have negative attitudes towards those who have negative feelings towards, Several mathematical explanations of this mutuality have been proposed, but they are based on specific approximate mathematical models of human (and animal) interaction. It is desirable to have a solid mathematical explanation that would not depend on such approximate models. In this paper, we show that a recent mathematical result about relation algebras can lead …

How To Select A Model If We Know Probabilities With Interval Uncertainty, Vladik Kreinovich

Departmental Technical Reports (CS)

Purpose: When we know the probability of each model, a natural idea is to select the most probable model. However, in many practical situations, we do not know the exact values of these probabilities, we only know intervals that contain these values. In such situations, a natural idea is to select some probabilities from these intervals and to select a model with the largest selected probabilities. The purpose of this study is to decide how to most adequately select these probabilities.

Design/methodology/approach: We want the probability-selection method to preserve independence: If, according to the probability intervals, the two …

Multi-Object Tracking: A Computer Vision Paradigm, Natalie Friede

Computer Science and Computer Engineering Undergraduate Honors Theses

This paper delves into advancements and hurdles encountered in multi-object tracking, a critical aspect of computer vision, with a special emphasis on 'referring understanding.' This technique integrates natural language queries into multi-object tracking tasks, thus broadening the scope for practical applications. The innovative referring multi-object tracking (RMOT) approach emerges as a promising solution in this regard. The effectiveness of RMOT was tested using the Refer-KITTI dataset, a dataset specializing in traffic scenes. The evaluation revealed RMOT's ability to handle a diverse range of referent objects, its robust temporal dynamics, and a high level of adaptability. While the paper acknowledges the …

Smartbrush: Text And Shape Guided Object Inpainting With Diffusion Model, Shaoan Xie, Zhifei Zhang, Zhe Lin, Tobias Hinz, Kun Zhang

Machine Learning Faculty Publications

Generic image inpainting aims to complete a corrupted image by borrowing surrounding information, which barely generates novel content. By contrast, multi-modal inpainting provides more flexible and useful controls on the inpainted content, e.g., a text prompt can be used to describe an object with richer attributes, and a mask can be used to constrain the shape of the inpainted object rather than being only considered as a missing area. We propose a new diffusion-based model named SmartBrush for completing a missing region with an object using both text and shape-guidance. While previous work such as DALLE-2 and Stable Diffusion can …

Moving Lab-Based In-Person Training To Online Delivery: The Case Of A Continuing Engineering Education Program, Catherine Maware, David M. Parsley Ii, Kun Huang, Gerry M. Swan, Nelson Akafuah

Institute of Research for Technology Development Faculty Publications

Background: Online learning has recently surged due to the COVID-19 global pandemic. Because of the pandemic, many universities were forced to move to online learning, and various online teaching and learning environments emerged, both asynchronous and synchronous.

Objective: This study explores how a large university in the Southeastern United States of America converted an in-person Lean Manufacturing professional course into synchronous online learning for industry participants.

Method: The study analysed the performance of 212 in-person and 43 online industry participants and examined the views of online participants about the training. Paired t-tests, one-way multivariate analysis of covariance (MANCOVA), and univariate …

Controllable Language Generation Using Deep Learning, Rohola Zandie

Electronic Theses and Dissertations

The advent of deep neural networks has sparked a revolution in Artificial Intelligence (AI), notably with the creation of Transformer models like GPT-X and ChatGPT. These models have surpassed previous methods in various Natural Language Processing (NLP) tasks. As the NLP field evolves, there is a need to further understand and question the capabilities of these models. Text generation, a crucial part of NLP, remains an area where our comprehension is limited while being critical in research.

This dissertation focuses on the challenging problem of controlling the general behaviors of language models such as sentiment, topical focus, and logical reasoning. …

Activation Of The Renin–Angiotensin–Aldosterone System Is Attenuated In Hypertensive Compared With Normotensive Pregnancy, Robin C. Shoemaker, Marko Poglitsch, Hong Huang, Katherine Vignes, Aarthi Srinivasan, Cynthia Cockerham-Morris, Aric Schadler, John Anthony Bauer, John O'Brien

UK CARES Faculty Publications

Hypertension during pregnancy increases the risk of adverse maternal and fetal outcomes, but the mechanisms of pregnancy hypertension are not precisely understood. Elevated plasma renin activity and aldosterone concentrations play an important role in the normal physiologic adaptation to pregnancy. These effectors are reduced in patients with pregnancy hypertension, creating an opportunity to define the features of the renin–angiotensin–aldosterone system (RAAS) that are characteristic of this disorder. In the current study, we used a novel LC-MS/MS-based methodology to develop comprehensive profiles of RAAS peptides and effectors over gestation in a cohort of 74 pregnant women followed prospectively for the development …

Terrain And Adversary-Aware Autonomous Robot Navigation, Aniekan Ufot Inyang

Electronic Theses and Dissertations

In autonomous robot navigation, the robot is able to understand the environment around it for intelligent navigation. From its world model of this environment, it generates a global plan for navigation from a position to a goal based on different factors. This research aims to implement autonomous robot navigation by learning terrain affordances: traversability (moving quickly) and concealment (staying hidden from an adversary) using the Preference-based Inverse Reward Learning (PbIRL) methodology. The PbIRL methodology reduces the barrier of generating initial demonstration data to learn the terrain affordances by using a human expert’s preferences to learn individual weights over the terrain …

Generalized Double Statistical Convergence Sequences On Ideals In Neutrosophic Normed Spaces, Jeyaraman M., Iswariya S., Pandiselvi R.

Neutrosophic Systems with Applications

In this present research, having view in the Neutrosophic norm (u, v, w), which we presented I2-lacunary statistical convergence and I2-lacunary convergence strongly, looked into interactions between them, and made a few findings regarding the respective categories. At least went further to look at how both of such case approaches relate to I2-statistical convergence within the relevant Neutrosophic normed space.

Ber Analysis Of Bpsk Modulation Scheme For Multiple Combining Schemes Over Flat Fading Channel, Zuhaib Nishtar, Jamil Afzal

Neutrosophic Systems with Applications

Focus of the study was to provide error-free communication in mobile communication with higher data rates, spectral efficiency, and energy efficient. Basically, work was done to investigate the performance of the Binary Phase Shift Keying (BPSK) modulation technique for multiple combining schemes and the behavior of signal in wireless communication where multipath propagation and uncertainty in the system. We use the Multiple-input Multiple-output (MIMO) and antenna diversity to get many copies of the same signal; some of them were faded, but some had sufficient information. Then the next step was to combine or select the best signal to achieve the …

Topology Optimization For Artificial Neural Networks, Justin Mills

Masters Theses & Specialist Projects

This thesis examines the feasibility of implementing two simple optimization methods, namely the Weights Power method (Hagiwara, 1994) and the Tabu Search method (Gupta & Raza, 2020), within an existing framework. The study centers around the generation of artificial neural networks using these methods, assessing their performance in terms of both accuracy and the capacity to reduce components within the Artificial Neural Network’s (ANN) topology.

The evaluation is conducted on three classification datasets: Air Quality (Shahane, 2021), Diabetes (Soni, 2021), and MNIST (Deng, 2012). The main performance metric used is accuracy, which measures the network's predictive capability for the classification …

If Everything Is A Matter Of Degree, Why Do Crisp Techniques Often Work Better?, Miroslav Svitek, Olga Kosheleva, Vladik Kreinovich

Departmental Technical Reports (CS)

Numerous examples from different application domain confirm the statement of Lotfi Zadeh -- that everything is a matter of degree. Because of this, one would expect that in most -- if not all -- practical situations taking these degrees into account would lead to more effective control, more effective prediction, etc. In practice, while in many cases, this indeed happens, in many other cases, "crisp" methods -- methods that do not take these degrees into account -- work better. In this paper, we provide two possible explanations for this discrepancy: an objective one -- explaining that the optimal (best-fit) model …

Resource Provisioning For Data-Intensive User-Facing Applications, Huiyang Li

Computer Science and Engineering Dissertations - Archive

Data-intensive, User-facing Services (DUSes) such as web searching, digital marketing, online social networking, and online retailing are critical workloads in clouds and datacenters. Meeting stringent query tail-latency Service Level Objectives (SLO) for DUS queries is essential for optimal user experience and business success. However, achieving these objectives is challenging due to the scale-out nature of DUese workloads and the varying resource demands of queries with different fanouts. Additionally, the design and configuration options for clusters significantly impact query performance. In this dissertation, we present solutions of DUSes performance online and offline optimization. We highlight the importance of reducing query tail …

Deep Learning For Molecular Property Prediction, Hehuan Ma

Computer Science and Engineering Dissertations - Archive

Drug discovery has always been a crucial task for society, and molecular property prediction is one of the fundamental problem. It is responsible for identifying the target properties or severe side-effects, so that certain molecules can be selected as the candidates of drugs. Traditional methods usually conduct a series of biochemical experiments to test the molecular properties, which may take up to decades. Nowadays, this process can be facilitated due to the rapid growth of deep learning methods. I present my work toward solving this critical problem by utilizing deep learning techniques. My research study can be summarized in three …

Formalizing Stack Safety As A Security Property, Sean Noble Anderson, Roberto Blanco, Leonidas Lampropoulos, Benjamin C. Pierce, Andrew Tolmach

Computer Science Faculty Publications and Presentations

The term stack safety is used to describe a variety of compiler, runtime, and hardware mechanisms for protecting stack memory. Unlike “the heap,” the ISA-level stack does not correspond to a single high-level language concept: different compilers use it in different ways to support procedural and functional abstraction mechanisms from a wide range of languages. This protean nature makes it difficult to nail down what it means to correctly enforce stack safety.

Compact Representatives Of Databases And Responsible Data Management, Suraj Shetiya

Computer Science and Engineering Dissertations - Archive

With the advent of advanced computational models, we are being constantly judged by AI systems, complex algorithmic systems based on data that has been collected about us. These analysis are critical as they span many wide spread areas of our lives. For instance, these systems have been shown to find effective ways to fight back and make informed decisions during the COVID-19 pandemic. The wide spread use of these models naturally give rise to a few questions regarding explaining decisions that these systems have made, fairness questions in various parts of these systems. In this dissertation, we present three important …

Fuzz Testing Of Zigbee Protocol Implementations, Mengfei Ren

Computer Science and Engineering Dissertations - Archive

ABSTRACT: In recent years, we have witnessed the increasing of the Internet of Things (IoT) devices deployed by many areas, such as home automation, healthcare, manufacture, and smart vehicle. Among the numerous IoT wireless standards available, Zigbee stands out as one of the most globally popular choices, with major companies like Amazon, Samsung, IKEA, Huawei, and Xiaomi incorporating it into their products. Notably, Zigbee has even been utilized in NASA's Mars mission, where it serves as the communication radio between the flying drone and the Perseverance rover. However, with the rapid growth of Zigbee's global market presence, the incentive for …