Digital Commons Network^™

The Logical Reasoning Dilemma Of Llms: A Mapping Deficit In Representation Acquisition, Yiling Wu

Theses

Currently, Large Language Models (LLMs) based on the Generative Pre-trained Transformer architecture have made breakthroughs in multilingual language processing tasks and performed similar language processing capabilities to humans. However, their performance in dealing with tasks involving reasoning, especially logical reasoning, show significant shortcomings. In this paper, we argue that logical reasoning competence requires a certain type of representation acquisition capability. Based on this, in order to assess whether LLMs have the potential to overcome the shortcomings of their logical reasoning competence in their subsequent development, this work compares the representation acquisition processes of humans and LLMs. This comparison reveals that …

A Theory Of Innovation Diffusion: A Simulation Study, Chiquan Guo, Sudipto Sarkar, Sergio Garcia, Russell Adams

Marketing Faculty Publications

This study uses the agent-based modeling technique to discover propositions on innovation diffusion that are empirically testable. It finds the adoption rate is positively related to (1) the size of the population, (2) the degree of heterogeneity in consumer learning in the population, (3) the degree of heterogeneity in consumer innovativeness in the population, and (4) the fit-in- desire in the population for innovation. This research adds insights to the innovation diffusion literature and lays the groundwork for future empirical research.

Constraining Giant Planet Occurrence Rates With The Multi-Band Imaging Survey For High-Alpha Planets (Mishaps) Observations Of 47 Tucanae, Alison Crisp

LSU Doctoral Dissertations

Though the confirmed exoplanet population has now reached over 5,500 planets, we still have a plethora of unanswered questions, e.g., regarding their formation mechanisms, true demographics, occurrence rates, and habitability. One remaining question is whether hot Jupiters formed in situ or migrated to their current orbits, so close to their host stars that their periods are 10 days or less. This question can potentially be answered by probing the effects of elemental abundances on hot Jupiter occurrence rates. These rates have been found to correlate with metallicity, but the specific elements responsible for the correlation have largely been unresolved. The …

Radially Symmetric Positive Solutions Of The Dirichlet Problem For The P-Laplace Equation, Bo Yang

Faculty Articles

We consider the p-Laplace boundary value problem with the Dirichlet boundary condition. A new lower estimate for positive solutions of the problem is obtained. As an application of this new lower estimate, some sufficient conditions for the existence and nonexistence of positive solutions for the p-Laplace problem are obtained.

Modeling Fire Behavior: Increasing Fidelity In High-Complexity Fire Models, Jenna Sjunneson Mcdanold

Theses

Recent technological advances have yielded several high-complexity models for fire behavior. Low-intensity burns present difficulties in modeling due to a strong sensitivity to wind and fuels. This dissertation explores support research to improve representation of low-intensity fire in these high-complexity fire simulations. We focus on three areas: (i) data-driven modeling with a Spatially Extended Radiant heat Fire model (SERF), (ii) fuel heterogeneity with our model Distribution of Understory using Elliptical Transport (DUET), and (iii) research on whole system dynamics using chaos theory. To increase simulated resolution of low-intensity fire behavior, we employ an observational data set to develop SERF with …

Freedom As The Physical Notion. Mechanics Of A Material Point, Michael Vigdorowitsch

Karbala International Journal of Modern Science

This is a novel conceptual attempt to introduce freedom as a consistent physical notion. The present consideration is limited to mechanics of a material point. Adapted to physical representation, freedom is tested throughout the paper to conform to its general perception. It is first tried on such physical notions (but not restricted to) as potency of a set, Lagrangian, action, degrees of freedom. Defined as angular and essentially nonlinear variable, it appears to be dual as that the domain affords and that the material point possesses within the domain, not necessarily equal to one another. Freedom has to degrade if …

Human Capital Development And Industrial Sector Growth In Sub Saharan African Countries. An Augmented Pooled Mean Group Estimator, Enongene Betrand Ewane, Etah Ivo Ewane

Arab Economic and Business Journal

Human capital is considered a vital catalyst for industrial sector growth. However, the lack of relevant skills and technical expertise can be a great setback to industrial growth. Thus, this study aimed to examine the effect of human capital development on industrial sector growth in Sub Saharan African (SSA) countries. The study makes use of World Bank data from 1972 to 2021 using a heterogeneous dynamic panel modeling. Due to cross-sectional dependence, both the first and second-generation unit root tests were examined in the study showing evidence of mixed order of integration. The study employed other econometric methods in the …

Factors Affecting Adoption Of Cooking Gas In Ilorin Metropolis, Nigeria, Muhammad-Bashir Owolabi Yusuf, Ridwan Olabisi Yusuff, Dauda Ishola Jimoh

Arab Economic and Business Journal

This research delved into the influencing factors behind the adoption of cooking gas in the Ilorin metropolis. The primary aim was to investigate the growing trend of adopting cooking gas in this area. The study utilized Binary Logistic Regression as its analytical method to assess the relationships between various variables. The findings unveiled several key insights. Firstly, there exists a noteworthy negative correlation between the age of households and their inclination toward adopting cooking gas (0.641, p < 0.05). On the other hand, the level of education displayed a positive but insignificant association with gas adoption. Factors like Family Size, Occupation, Safety, and the Availability of other energy sources demonstrated a positive yet insignificant correlation with the adoption of cooking gas. Notably, household income exhibited a statistically significant positive relationship with cooking gas adoption (1.547, p < 0.05). Conversely, the presence of gas shops showed an insignificant positive relationship with households' decisions to adopt cooking gas. Moreover, the level of awareness and social influence exhibited insignificant negative associations with households' decisions to adopt cooking gas. Aligned with these findings, the study proposes recommendations for action. It suggests that the Nigerian government should focus on elevating educational standards and promoting an improved quality of life to incentivize fuel substitution. This shift can lead to more efficient energy usage and mitigate adverse environmental, social, and health impacts. This approach can significantly reduce wood energy consumption, subsequently relieving pressure on wood resources and aiding in the effort to combat deforestation.

Modeling Per Capita Income And Its Dependence On Literacy Rate, Jasneet Kaur Wadhwa, Arun P

Arab Economic and Business Journal

This paper challenges the idea that India's economic liberalization in 1991 was solely responsible for the transition in Per Capita Income (PCI). The paper investigates the complex dynamics between educational attainment, economic policies, and their impact on PCI in India. By analyzing the relationship between PCI and literacy rate, the study aims to answer the intriguing question of whether the strong correlation observed between PCI and the literacy rate is a mere coincidence. Additionally, looking at the diode equation's good fit to the data on PCI vs literacy rate, for the period 1980-2020, the study attempts to determine whether or …

Investigating The Relationship Between Self-Efficacy, Science Teaching Beliefs, And Science Teaching Practices In Pre-Service Science Education, Carolyn Kress, Kiran Willis, Jesse Wilcox, Diva Dodiya, Pranav Kota, Jerrid Kruse

Summer Undergraduate Research Program (SURP) Symposium

This study explored pre-service secondary science teachers’ self-efficacy, science teaching beliefs, and science teaching practices. We measured self-efficacy (Science Teaching Efficacy Belief Instrument-B), science teaching beliefs (Teacher Belief Instrument), and effectiveness (Local Systemic Classroom Change Observation Protocol) three times throughout the semester. Overall, there was a significant increase in self-efficacy, science teaching beliefs, and effectiveness between measures one and three. However, three different trends were observed when looking at participants in smaller groups: the Dunning-Kruger effect, consistent growth, and the false consensus effect.

Stochastic Solutions For Hyperbolic Pde, Abdol-Reza Mansouri, Zachary Selk

Journal of Stochastic Analysis

No abstract provided.

(Arise) Achievements In Research, Inquiry And Scholarship Exhibition 2024, Office Of Undergraduate Research

(ARISE) Achievements in Research, Inquiry and Scholarship Exhibition

No abstract provided.

A New Approach: Ordinal Predictive Maintenance With Ensemble Binary Decomposition (Opmeb), Ozlem Ece Yurek, Derya Birant

Turkish Journal of Electrical Engineering and Computer Sciences

Predictive maintenance (PdM), a fundamental element of modern industrial systems, employs machine learning to monitor equipment conditions, estimate failure probabilities, and optimize maintenance schedules. Its core objective is to enhance equipment reliability, extend lifespan, and minimize costs through data-driven insights by enabling efficient maintenance scheduling, reducing downtime, and optimizing resource allocation. In this paper, we propose a novel ordinal predictive maintenance with ensemble binary decomposition (OPMEB) method for the PdM domain, considering the hierarchical nature of class labels reflecting the machine's health status, including categories like healthy, low risk, moderate risk, and high risk. The proposed OPMEB method was validated …

Enrichment Of Turkish Question Answering Systems Using Knowledge Graphs, Okan Çi̇ftçi̇, Fati̇h Soygazi̇, Selma Teki̇r

Turkish Journal of Electrical Engineering and Computer Sciences

Recent capabilities of large language models (LLMs) have transformed many tasks in Natural Language Processing (NLP), including question answering. The state-of-the-art systems do an excellent job of responding in a relevant, persuasive way but cannot guarantee factuality. Knowledge graphs, representing facts as triplets, can be valuable for avoiding errors and inconsistencies with real-world facts. This work introduces a knowledge graph-based approach to Turkish question answering. The proposed approach aims to develop a methodology capable of drawing inferences from a knowledge graph to answer complex multihop questions. We construct the Beyazperde Movie Knowledge Graph (BPMovieKG) and the Turkish Movie Question Answering …

Ensemble Learning For Accurate Prediction Of Heart Sounds Using Gammatonegram Images, Sinam Ashinikumar Singh, Sinam Ajitkumar Singh, Aheibam Dinamani Singh

Turkish Journal of Electrical Engineering and Computer Sciences

The analysis of heart sound signals constitutes a pivotal domain in healthcare, with the prediction of imbalanced heart sounds offering critical diagnostic insights. However, the inherent diversity in cardiac sound patterns presents a substantial challenge in predicting imbalanced signals. Many scientific disciplines have focused a great deal of emphasis on the problem of class inequality. We introduce an ensemble learning approach employing a convolutional neural network model-based deep learning algorithm to effectively tackle the challenges associated with predicting imbalanced heart sound signals. We use a Gammatone filter bank to extract relevant features from the heard sound signal. Our approach leverages …

Detection And Classification Of Unauthorized Use Of Irrigation Motors In Agricultural Irrigation, Önder Ci̇velek, Sedat Görmüş, Hali̇l İbrahi̇m Okumuş, Orhan Gazi̇ Kederoglu

Turkish Journal of Electrical Engineering and Computer Sciences

The decarbonisation of electricity generation requires the real-time monitoring and control of grid components in order to efficiently and timely dispatch demand. This highly automated system, known as the Smart Grid, relies on smart or sensor-equipped distribution network components to optimise energy flow and minimise losses. However, energy theft, a major obstacle to efficient resource utilisation, poses a significant challenge to achieving this goal. This study proposes and evaluates a real-time telemetry and control system designed to mitigate energy theft in agricultural irrigation applications. The system increases energy efficiency by tracking the energy use in agricultural irrigation. The key challenge …

A New Dynamic Classifier Selection Method For Text Classification, İsmai̇l Terzi̇, Alper Kürşat Uysal

Turkish Journal of Electrical Engineering and Computer Sciences

The primary objective of employing multiple classifier systems (MCS) in pattern recognition is to enhance classification accuracy. Dynamic classifier selection (DCS) and dynamic ensemble selection (DES) are two purposeful forms of multiple classifier systems. While DES involves the selection of a classifier set followed by decision combination, DCS opts for the choice of a single competent classifier, eliminating the necessity for classifier combination. As a consequence, DCS methods exhibit superior efficiency in terms of processing time and memory usage compared to DES methods. Moreover, a substantial performance gap exists between the performance of Oracle and both DES and DCS methods. …

A Real-Time Embedded System Designed For Nilm Studies With A Novel Competitive Decision Process Algorithm, Sai̇d Mahmut Çinar, Rasi̇m Doğan, Emre Akarslan

Turkish Journal of Electrical Engineering and Computer Sciences

This paper explores the determination of any load or load combination in a power system at any moment. This process requires measurements at the main electric utility service entry of a house, known as nonintrusive measurement. To accurately identify loads, total harmonic distortion, RMS, third harmonic currents, and power consumption are considered their fingerprints. Based on these fingerprints, an algorithm called the competitive decision process is developed and integrated into an embedded system. This algorithm has a two-level decision mechanism. In the first stage, the winner loads with the highest similarity scores from each feature are determined, and the loads …

Multi-Label Voice Disorder Classification Using Raw Waveforms, Gökay Di̇şken

Turkish Journal of Electrical Engineering and Computer Sciences

Automated voice disorder systems that distinguish pathological voices from healthy ones have been developed with the aid of machine learning methods. Both clinicians and patients can benefit from these systems as they provide many advantages, compared to the invasive techniques. These systems can produce binary (healthy/pathological) or multi-class (healthy/selected pathologies) decisions. However, multiple disorders might exist in an individual’s voice. Multi-label classification should be considered in such cases. By this time, only a single report is available on this topic, where hand-crafted features were used, and a data augmentation technique was utilized to overcome class imbalances. In this study, a …

Machine Learning-Driven Prediction Of Severe Thrombocytopenia Risk In Crrt Patients, Michael Li, Divakar Sharma Md

Research Scholars

No abstract provided.

Adding A Teacher Dashboard To A Functioning Web App, Melanie Jensen

Instructional Psychology and Technology Graduate Student Projects

A teacher dashboard was added to an existing web-based application that teaches math-fact fluency. The author describes the process of analysis, design, development, and implementation. Challenges faced at each stage are described, and design decisions are discussed.

Network Intrusion Detection Based On Machine Learning Strategies: Performance Comparisons On Imbalanced Wired, Wireless, And Software-Defined Networking (Sdn) Network Traffics, Hi̇lal Hacilar, Zafer Aydin, Vehbi̇ Çağri Güngör

Turkish Journal of Electrical Engineering and Computer Sciences

The rapid growth of computer networks emphasizes the urgency of addressing security issues. Organizations rely on network intrusion detection systems (NIDSs) to protect sensitive data from unauthorized access and theft. These systems analyze network traffic to detect suspicious activities, such as attempted breaches or cyberattacks. However, existing studies lack a thorough assessment of class imbalances and classification performance for different types of network intrusions: wired, wireless, and software-defined networking (SDN). This research aims to fill this gap by examining these networks’ imbalances, feature selection, and binary classification to enhance intrusion detection system efficiency. Various techniques such as SMOTE, ROS, ADASYN, …

K-3 Teachers’ Perspectives Of Response To Intervention In Closing Reading Achievement Gaps, Sarwat Suraiya

Walden Dissertations and Doctoral Studies

General education teachers are directly responsible for implementing the Response to Intervention (RTI) process to close achievement gaps for their struggling readers. The problem in this study was the experiences of K-3 teachers with inconsistent implementation of RTI to support struggling readers at a southeastern school. When the RTI process is not implemented consistently, results can adversely affect closing achievement gaps of struggling readers. The purpose of this basic qualitative study was to explore K-3 teachers’ experiences with inconsistent implementation of the RTI process for struggling readers in a southeastern school. This study was based on Ely’s conditions of change …

Detection And Mitigation Of Misleading Pheromone Trails In Foraging Robot Swarms, Ryan Luna, Qi Lu

Computer Science Faculty Publications

This study addresses the overlooked aspect of security in swarm robotics by exploring the vulnerabilities of stigmergic communication in foraging robot swarms. More specifically, we study the swarm's susceptibility to attacks that introduce misleading pheromone trails. Simulated scenarios in which detractor robots lay misleading trails to deceive benign foraging robots effectively reduce the foraging performance of the swarm. We analyze the impact of the attack on the swarm and evaluate the reduction of foraging efficiency. We introduce a defense mechanism using distance-based clustering (DBSCAN) along with a cluster grouping method to isolate large batches of detractors early in the simulation. …

2024 Summer Undergraduate Research Program, University Of Northern Iowa. Summer Undergraduate Research Program.

Summer Undergraduate Research Program (SURP) Symposium Programs

The program for the Summer Undergraduate Research Symposium of the College of Humanities, Arts and Sciences.

Adaptable Quantum Education Platform Using Learning Objects, Krishna Puja Anumula

Master's Theses

In recent years, the need to make classroom learning more interactive and engaging has become increasingly important. The lack of workforce in interdisciplinary fields such as quantum networking and quantum internet requires a new approach that addresses every learner’s individual needs. To address this challenge, this thesis introduces an adaptive learning platform rooted in the theory of learning objects and Kolb’s experiential learning model. The platform aids educators and learners in designing and utilizing various learning objects for quantum networking and quantum internet.

The platform enables educators and learners to build their own lessons and lesson plans using learning objects …

Tuning Pid Controller For Quadrotor Using Particle Swarm Optimization, Eric X. Rodriguez, Qi Lu

Computer Science Faculty Publications

Energy expenditure for quadrotor control has a likelihood of being costly given parameter-dependent controllers that are less than optimal. The cost can grow proportionally when applied to multiple quadrotors for tracking and collaborative navigation tasks. This research aims to establish a basic approach to tuning PID (Proportional-Integral-Derivative) parameters for a simulated quadrotor drone. A PID controller for autonomy provides a straightforward method for correcting robotic movement based on its current state. However, applying a PID system to a flight controller poses challenges with an inherently under-actuated system, which includes the likelihood of large overshoots and lengthy adjustment times. To address …

Efficient Deep Neural Network Compression For Environmental Sound Classification On Microcontroller Units, Shan Chen, Na Meng, Haoyuan Li, Weiwei Fang

Turkish Journal of Electrical Engineering and Computer Sciences

Environmental sound classification (ESC) is one of the important research topics within the non-speech audio classification field. While deep neural networks (DNNs) have achieved significant advances in ESC recently, their high computational and memory demands render them highly unsuitable for direct deployment on resource-constrained Internet of Things (IoT) devices based on microcontroller units (MCUs). To address this challenge, we propose a novel DNN compression framework specifically designed for such devices. On the one hand, we leverage pruning techniques to significantly compress the large number of model parameters in DNNs. To reduce the accuracy loss that follows pruning, we propose a …

Antimicrobials Produced By Ants: Chemical Properties And Microbe Specificity, Katy Chon

Master's Theses

Antibiotic resistance is a growing public health concern worldwide, and for over a decade, we have been witnessing the growth of difficult to treat infectious diseases caused by bacteria that are becoming resistant to antibiotics. This resistance can be mostly related to the misusing and improper use of antibiotics in both humans and animals. To restore this problem, humans have turned to new sources for the production of antibiotics. In this study, we focused on using ants. Social insects, including ants and bees, have faced strong disease pressures during their evolution and have developed a range of methods to fight …

Glitch Veto Based On Unphysical Gravitational Wave Binary Inspiral Templates, Raghav Girgaonkar, Soumya D. Mohanty

Physics & Astronomy Faculty Publications

Transient signals arising from instrumental or environmental factors, commonly referred to as glitches, constitute the predominant background of false alarms in gravitational wave searches with ground-based detectors. Therefore, effective data analysis methods for vetoing glitch-induced false alarms are crucial to enhancing the sensitivity of a search. We present a veto method for glitches that impact matched filtering-based searches for binary inspiral signals. The veto uses unphysical sectors in the space of chirp time parameters as well as an unphysical extension including negative chirp times to efficiently segregate glitches from gravitational wave signals in data from a single detector. Inhabited predominantly …