Computer Sciences Commons^™

A Hybrid Mcdm Approach For Industrial Robots Selection For The Automotive Industry, Abduallah Gamal, Mona Mohamed

Neutrosophic Systems with Applications

The use of robots in various stages of the production process is now commonplace across practically all sectors of the economy. Additionally, even for present-day small and medium-sized businesses, this has developed into a very powerful need in recent years and continues to grow in importance. The selection of an industrial robot is a very complicated decision-making issue due to the fact that there are numerous aspects and criteria that are in conflict with one another, as almost all of the earlier research emphasized. In addition, the many sophisticated requirements that have been added to these robots by the makers …

A Hybrid Mcdm Approach For Industrial Robots Selection For The Automotive Industry, Abduallah Gamal, Mona Mohamed

Neutrosophic Systems with Applications

The use of robots in various stages of the production process is now commonplace across practically all sectors of the economy. Additionally, even for present-day small and medium-sized businesses, this has developed into a very powerful need in recent years and continues to grow in importance. The selection of an industrial robot is a very complicated decision-making issue due to the fact that there are numerous aspects and criteria that are in conflict with one another, as almost all of the earlier research emphasized. In addition, the many sophisticated requirements that have been added to these robots by the makers …

Metric Ensembles Aid In Explainability: A Case Study With Wikipedia Data, Grant Forbes, R. Jordan Crouser

Computer Science: Faculty Publications

In recent years, as machine learning models have become larger and more complex, it has become both more difficult and more important to be able to explain and interpret the results of those models, both to prevent model errors and to inspire confidence for end users of the model. As such, there has been a significant and growing interest in explainability in recent years as a highly desirable trait for a model to have. Similarly, there has been much recent attention on ensemble methods, which aim to aggregate results from multiple (often simple) models or metrics in order to outperform …

Convolutional Neural Networks Analysis Reveals Three Possible Sources Of Bronze Age Writings Between Greece And India, Shruti Daggumati, Peter Z. Revesz

School of Computing: Faculty Publications

This paper analyzes the relationships among eight ancient scripts from between Greece and India. We used convolutional neural networks combined with support vector machines to give a numerical rating of the similarity between pairs of signs (one sign from each of two different scripts). Two scripts that had a one-to-one matching of their signs were determined to be related. The result of the analysis is the finding of the following three groups, which are listed in chronological order: (1) Sumerian pictograms, the Indus Valley script, and the proto-Elamite script; (2) Cretan hieroglyphs and Linear B; and (3) the Phoenician, Greek, …

Managing Cyber Defense As A Business Threat For Small And Medium Enterprises, Binh Quang Vo

Doctoral Dissertations and Projects

The U.S small and medium businesses (SMBs) are constantly attacked by cybercriminals. Alarmingly, the number of victimized SMBs is growing considerably every year. This results in the increasing loss of billions of dollars and risks to the national economy. The problem addressed was the rising number of cyberattacks critically harming SMBs resulting in revenue loss, damages to reputation, and business closure. The purpose of this research was to reveal the contemporary barriers and challenges that impact cybersecurity competencies of SMBs. This study used semi-structured interviews of participants who are currently working as cyber professionals in SMBs across industries. The goal …

A Graphical User Interface Using Spatiotemporal Interpolation To Determine Fine Particulate Matter Values In The United States, Kelly M. Entrekin

Honors College Theses

Fine particulate matter or PM2.5 can be described as a pollution particle that has a diameter of 2.5 micrometers or smaller. These pollution particle values are measured by monitoring sites installed across the United States throughout the year. While these values are helpful, a lot of areas are not accounted for as scientists are not able to measure all of the United States. Some of these unmeasured regions could be reaching high PM2.5 values over time without being aware of it. These high values can be dangerous by causing or worsening health conditions, such as cardiovascular and lung diseases. Within …

Gconet+: A Stronger Group Collaborative Co-Salient Object Detector, Peng Zheng, Huazhu Fu, Deng Ping Fan, Qi Fan, Jie Qin, Yu Wing Tai, Chi Keung Tang, Luc Van Gool

Machine Learning Faculty Publications

In this paper, we present a novel end-to-end group collaborative learning network, termed GCoNet+, which can effectively and efficiently (250 fps) identify co-salient objects in natural scenes. The proposed GCoNet+ achieves the new state-of-the-art performance for co-salient object detection (CoSOD) through mining consensus representations based on the following two essential criteria: 1) intra-group compactness to better formulate the consistency among co-salient objects by capturing their inherent shared attributes using our novel group affinity module (GAM); 2) inter-group separability to effectively suppress the influence of noisy objects on the output by introducing our new group collaborating module (GCM) conditioning on the …

Domain Specific Analysis Of Privacy Practices And Concerns In The Mobile Application Market, Fahimeh Ebrahimi Meymand

LSU Doctoral Dissertations

Mobile applications (apps) constantly demand access to sensitive user information in exchange for more personalized services. These-mostly unjustified-data collection tactics have raised major privacy concerns among mobile app users. Existing research on mobile app privacy aims to identify these concerns, expose apps with malicious data collection practices, assess the quality of apps' privacy policies, and propose automated solutions for privacy leak detection and prevention. However, existing solutions are generic, frequently missing the contextual characteristics of different application domains. To address these limitations, in this dissertation, we study privacy in the app store at a domain level. Our objective is to …

Leveraging Artificial Intelligence And Machine Learning For Enhanced Cybersecurity: A Proposal To Defeat Malware, Emmanuel Boateng

Cybersecurity Undergraduate Research Showcase

Cybersecurity is very crucial in the digital age in order to safeguard the availability, confidentiality, and integrity of data and systems. Mitigation techniques used in the industry include Multi-factor Authentication (MFA), Incident Response Planning (IRP), Security Information and Event Management (SIEM), and Signature-based and Heuristic Detection.

MFA is employed as an additional layer of protection in several sectors to help prevent unauthorized access to sensitive data. IRP is a plan in place to address cybersecurity problems efficiently and expeditiously. SIEM offers real-time analysis and alerts the system of threats and vulnerabilities. Heuristic-based detection relies on detecting anomalies when it comes …

Geophysical Characterization Of Underground Storage In Salt Domes During The Clean Energy Transition, Joses B. Omojola

LSU Master's Theses

Safely transforming geological formations into cost-effective underground storage is critical for the US energy security and global energy transition. Seasonal energy demand requires relatively cheap, impermeable, non-reactive materials for storing vast amounts of natural gas and hydrogen. Due to their low risk of fracturing and leakage, salt formations are ideal for these purposes however, pressure variations during drawdown, differential salt creep, and reactivation of pre-existing fractures along boundary shear zone(s) (BSZ) can be detrimental to salt cavern safety and long-term cavern operations. Several environmental disasters at storage facilities in the US and Europe, have created a need to understand how …

Tc-Net: A Modest & Lightweight Emotion Recognition System Using Temporal Convolution Network, Muhammad Ishaq, Mustaqeem Khan, Soonil Kwon

Computer Vision Faculty Publications

Speech signals play an essential role in communication and provide an efficient way to exchange information between humans and machines. Speech Emotion Recognition (SER) is one of the critical sources for human evaluation, which is applicable in many real-world applications such as healthcare, call centers, robotics, safety, and virtual reality. This work developed a novel TCN-based emotion recognition system using speech signals through a spatial-temporal convolution network to recognize the speaker's emotional state. The authors designed a Temporal Convolutional Network (TCN) core block to recognize long-term dependencies in speech signals and then feed these temporal cues to a dense network …

Applying Hallgren’S Algorithm For Solving Pell’S Equation To Finding The Irrational Slope Of The Launch Of A Billiard Ball, Sangheon Choi

Mathematical Sciences Technical Reports (MSTR)

This thesis is an exploration of Quantum Computing applied to Pell’s equation in an attempt to find solutions to the Billiard Ball Problem. Pell’s equation is a Diophantine equation in the form of x² − ny² = 1, where n is a given positive nonsquare integer, and integer solutions are sought for x and y. We will be applying Hallgren’s algorithm for finding irrational periods in functions, in the context of billiard balls and their movement on a friction-less unit square billiard table. Our central research question has been the following: Given the cutting sequence of the billiard …

On The Accelerated Noise-Tolerant Power Method, Zhiqiang Xu

Machine Learning Faculty Publications

We revisit the acceleration of the noise-tolerant power method for which, despite previous studies, the results remain unsatisfactory as they are either wrong or suboptimal, also lacking generality. In this work, we present a simple yet general and optimal analysis via noise-corrupted Chebyshev polynomials, which allows a larger iteration rank p than the target rank k, requires less noise conditions in a new form, and achieves the optimal iteration complexity (Equation presented) for some q satisfying k ≤ q ≤ p in a certain regime of the momentum parameter. Interestingly, it shows dynamic dependence of the noise tolerance on the …

Causality: Hypergraphs, Matter Of Degree, Foundations Of Cosmology, Cliff Joslyn, Andres Ortiz-Muñoz, Edgar Daniel Rodriguez Velasquez, Olga Kosheleva, Vladik Kreinovich

Departmental Technical Reports (CS)

The notion of causality is very important in many applications areas. Because of this importance, there are several formalizations of this notion in physics and in AI. Most of these definitions describe causality as a crisp ("yes"-"no") relation between two events or two processes -- cause and effect. However, such descriptions do not fully capture the intuitive idea of causality: first, often, several conditions are needed to be present for an effect to occur, and, second, the effect is often a matter of degree. In this paper, we show how to modify the current description of causality so as to …

Foundations Of Neural Networks Explain The Empirical Success Of The "Surrogate" Approach To Ordinal Regression -- And Recommend What Next, Salvador Robles, Martine Ceberio, Vladik Kreinovich

Departmental Technical Reports (CS)

Recently, a new efficient semi-heuristic statistical method -- called Surrogate Approach -- has been proposed for dealing with regression problems. How can we explain this empirical success? And since this method is only an approximation to reality, what can we recommend if there is a need for a more accurate approximation? In this paper, we show that this empirical success can be explained by the same arguments that explain the empirical success of neural networks -- and these arguments can also provide us with possible more general techniques (that will hopefully lead to more accurate approximation to real-life phenomena).

Towards Decision Making Under Interval Uncertainty, Juan A. Lopez, Vladik Kreinovich

Departmental Technical Reports (CS)

In many real-life situations, we need to make a decision. In many cases, we know the optimal decision in situations when we know the exact value of the corresponding quantity x. However, often, we do not know the exact value of this quantity, we only know the bounds on the value x -- i.e., we know the interval containing $x$. In this case, we need to select a decision corresponding to some value from this interval. The selected value will, in general, be different from the actual (unknown) value of this quantity. As a result, the quality of our decision …

Low-Probability High-Impact Events Are Even More Important Than It Is Usually Assumed, Aaron Velasco, Olga Kosheleva, Vladik Kreinovich

Departmental Technical Reports (CS)

A large proportion of undesirable events like earthquakes, floods, tornados occur in zones where these events are frequent. However, a significant number of such events occur in other zones, where such events are rare. For example, while most major earthquakes occur in a vicinity of major faults, i.e., on the border between two tectonic plates, some strong earthquakes also occur inside plates. We want to mitigate all undesirable events, but our resources are limited. So, to allocate these resources, we need to decide which ones are more important. For this decision, a natural idea is to use the product of …

What Do Goedel's Theorem And Arrow's Theorem Have In Common: A Possible Answer To Arrow's Question, Miroslav Svitek, Olga Kosheleva, Vladik Kreinovich

Departmental Technical Reports (CS)

Kenneth Arrow, the renowned author of the Impossibility Theorem that explains the difficulty of group decision making, noticed that there is some commonsense similarity between his result and Goedel's theorem about incompleteness of axiomatic systems. Arrow asked if it is possible to describe this similarity in more precise terms. In this paper, we make the first step towards this description. We show that in both cases, the impossibility result disappears if we take into account probabilities. Namely, we take into account that we can consider probabilistic situations, that we can make probabilistic conclusions, and that we can make probabilistic decisions …

Automatic Assessment Of Oral Reading Fluency From Children's Read Speech In The Filipino Language, Francis Dimzon

Software Technology Dissertations

With the end view of helping the Philippine education system in its literacy initiatives, this study aims to develop methods for automatic assessment of oral reading fluency from children's read speech in the Filipino language. Thus, this study seeks to design methods of automatically extracting and analyzing prosodic features of children's read speech in Filipino. To achieve this, the four-fold set of research activities was conducted to describe an automated oral reading fluency assessment system. It consisted of 1) building a children's Filipino speech corpus, 2) designing methods of extracting and analyzing prosodic features, 3) developing methods of automatically assessing …

Wormholes, Superfast Computations, And Selivanov's Theorem, Olga Kosheleva, Vladik Kreinovich

Departmental Technical Reports (CS)

While modern computers are fast, there are still many practical problems that require even faster computers. It turns out that on the fundamental level, one of the main factors limiting computation speed is the fact that, according to modern physics, the speed of all processes is limited by the speed of light. Good news is that while the corresponding limitation is very severe in Euclidean geometry, it can be more relaxed in (at least some) non-Euclidean spaces, and, according to modern physics, the physical space is not Euclidean. The differences from Euclidean character are especially large on micro-level, where quantum …

Discussing The History Of Ideas In A Data Science Seminar, Lubomir Stanchev

Computer Science and Software Engineering

As one part of an NSF-sponsored Data Science Fellowship at Cal Poly, San Luis Obispo, a group of faculty offered a unique one- unit quarter-long seminar on the history of ideas behind the core principles of Data Science. We present an overview of this seminar, its learning objectives, and outcomes and lessons learned.

What You Don't See: The Impact Of Hidden Game Mechanics On Players, Jan Virsunen

ART 108: Introduction to Games Studies

Since the rise of technology in the early nineteen sixties the art of gaming became an increasingly popular form of entertainment for many people throughout the years. As time progressed so did the advancements in technology which allowed for video games to become more immersive, captivating, and complex. Due to these advancements in tech, it generated a wide variety of ways for developers to increase game complexities. However, as the complexity of video games has increased, so too has the number of hidden game mechanics. These game mechanics are seen as the underlying systems and rules that govern how the …

Analyzing Syntactic Constructs Of Java Programs With Machine Learning, Francisco Ortin, Guillermo Facundo, Miguel Garcia

Department of Computer Science Publications

The massive number of open-source projects in public repositories has notably increased in the last years. Such repositories represent valuable information to be mined for different purposes, such as documenting recurrent syntactic constructs, analyzing the particular constructs used by experts and beginners, using them to teach programming and to detect bad programming practices, and building programming tools such as decompilers, Integrated Development Environments or Intelligent Tutoring Systems. An inherent problem of source code is that its syntactic information is represented with tree structures, while traditional machine learning algorithms use -dimensional datasets. Therefore, we present a feature engineering process to translate …

Everything Is A Matter Of Degree: The Main Idea Behind Fuzzy Logic Is Useful In Geosciences And In Authorship, Christian Servin, Aaron Velasco, Edgar Daniel Rodriguez Velasquez, Vladik Kreinovich

Departmental Technical Reports (CS)

This paper presents two applications of the general principle -- the everything is a matter of degree -- the principle that underlies fuzzy techniques. The first -- qualitative -- application helps explain the fact that while most earthquakes occur close to faults (borders between tectonic plates or terranes), earthquakes have also been observed in areas which are far away from the known faults. The second -- more quantitative -- application is to the problem of which of the collaborators should be listed as authors and which should be simply thanked in the paper. We argue that the best answer to …

Conflict Situations Are Inevitable When There Are Many Participants: A Proof Based On The Analysis Of Aumann-Shapley Value, Sofia Holguin, Vladik Kreinovich

Departmental Technical Reports (CS)

When collaboration of several people results in a business success, an important issue is how to fairly divide the gain between the participants. In principle, the solution to this problem is known since the 1950s: natural fairness requirements lead to the so-called Shapley value. However, the computation of Shapley value requires that we can estimate, for each subset of the set of all participants, how much gain they would have gained if they worked together without others. It is possible to perform such estimates when we have a small group of participants, but for a big company with thousands of …

Integrity First, Service Before Self, And Excellence: Core Values Of Us Air Force Naturally Follow From Decision Theory, Martine Ceberio, Olga Kosheleva, Vladik Kreinovich

Departmental Technical Reports (CS)

By analyzing data both from peace time and from war time, the US Air Force came with three principles that determine success: integrity, service before self, and excellent. We show that these three principles naturally follow from decision theory, a theory that describes how a rational person should make decisions.

People Prefer More Information About Uncertainty, But Perform Worse When Given This Information: An Explanation Of The Paradoxical Phenomenon, Jieqiong Zhao, Olga Kosheleva, Vladik Kreinovich

Departmental Technical Reports (CS)

In a recent experiment, decision makers were asked whether they would prefer having more information about the corresponding situation. They confirmed this preference, and such information was provided to them. However, strangely, the decisions of those who received this information were worse than the decisions of the control group -- that did not get this information. In this paper, we provide an explanation for this paradoxical situation.

How People Make Decisions Based On Prior Experience: Formulas Of Instance-Based Learning Theory (Ilbt) Follow From Scale Invariance, Palvi Aggarwal, Martine Ceberio, Olga Kosheleva, Vladik Kreinovich

Departmental Technical Reports (CS)

To better understand human behavior, we need to understand how people make decisions, how people select one of possible actions. This selection is usually based on predicting consequences of different actions, and these predictions are, in their turn, based on the past experience. For example, consequences that occur more frequently in the past are viewed as more probable. However, this is not just about frequency: recent observations are usually given more weight that past ones. Researchers have discovered semi-empirical formulas that describe our predictions reasonably well; these formulas form the basis of the Instance-Based Learning Theory (ILBT). In this paper, …

Investigating The Use Of Recurrent Neural Networks In Modeling Guitar Distortion Effects, Caleb Koch, Scott Hawley, Andrew Fyfe

[Archive] Belmont University Research Symposium (BURS)

Guitar players have been modifying their guitar tone with audio effects ever since the mid-20th century. Traditionally, these effects have been achieved by passing a guitar signal through a series of electronic circuits which modify the signal to produce the desired audio effect. With advances in computer technology, audio “plugins” have been created to produce audio effects digitally through programming algorithms. More recently, machine learning researchers have been exploring the use of neural networks to replicate and produce audio effects initially created by analog and digital effects units. Recurrent Neural Networks have proven to be exceptional at modeling audio effects …

The Beginning, Development And Impact Of Chatgpt In The Digital Age, Zhixiao Zhao, Dongbo Wang

Journal of Scientific Information Research

[Purpose/significance]The emergence of ChatGPT has brought significant changes to the whole society, and to this day, its impact is still spreading, Experts, scholars and news media have broadly discussed it. As a major progress in the field of natural language processing, ChatGPT carries too much attention and expectations. As an important battlefield in the field of natural language processing, information resource management should give full play to the advantages of disciplines under this technological change and drive the development of disciplines with technology.[Method/process] Starting from the origin of ChatGPT, this paper introduces the development path of GPT model, and summarizes …