Digital Commons Network^™

Try It Together - Qualitative Coding With Atlas.Ti, Danping Dong, Bryan Leow

AI for Research Week

This hands-on session introduces Atlas.ti, a well-established qualitative data analysis tool for analyzing your transcripts and textual data. The session will cover coding data, extracting insights, creating visualizations, and exploring the tool's latest AI features.

Try It Together: Transcribing Your Audio With Whisper Api, Bella Ratmelia

AI for Research Week

In this hands-on session, we will explore using the Whisper API to transcribe audio recordings from interviews, focus groups, and speeches. The session will delve into best practices and address common issues that may arise during the transcription process.

Effect Of Social Media On Shaping The Agenda Of The Communicator In The Jordanian Tv Channels, Amer Khaled Ahmad Dr, Hamza Mohammad Nahar, Maram Mohammad Naji Manajreh Dr

Middle East Journal of Communication Studies

The study aimed to assess the extent to which communicators at Jordanian television channels use social media platforms as an information source, and the impact of these platforms on their news and information selection priorities. This was achieved using a survey tool distributed on an equal quota sample of (150) communicators from Jordanian television channels (Jordan TV, AlMamlaka TV, Roya TV). The study found that all the study subjects used social media platforms as a source of information, with the "X platform (formerly Twitter)" being the most used platform. The statement "understanding the audience's interests and preferences to produce tailored …

A Brief Introduction To General Topology, Richard P. Millspaugh

Open Educational Resources

The material in this text is intended to be accessible to undergraduates who have had an introduction to elementary set theory and proof techniques. It includes sufficient material from general topology to prove the two main topological results found in a standard first semester calculus course: the Intermediate Value Theorem and the Extreme Value Theorem. This material can be found in Chapters 2 through 6 and makes up the bulk of the text. Rather than approaching these topics through use of the standard euclidean metric, it defines the standard topology on R in terms of the usual order on R. …

Unveiling The Metaverse: A Survey Of User Perceptions And The Impact Of Usability, Social Influence And Interoperability, Mousa Al-Kfairy, Ayham Alomari, Mahmood Al-Bashayreh, Omar Alfandi, Mohammad Tubishat

All Works

This review explores the Metaverse, focusing on user perceptions and emphasizing the critical aspects of usability, social influence, and interoperability within this emerging digital ecosystem. By integrating various academic perspectives, this analysis highlights the Metaverse's significant impact across various sectors, emphasizing its potential to reshape digital interaction paradigms. The investigation reveals usability as a cornerstone for user engagement, demonstrating how social dynamics profoundly influence user behaviors and choices within virtual environments. Furthermore, the study outlines interoperability as a paramount challenge, advocating for establishing unified protocols and technologies to facilitate seamless experiences across disparate Metaverse platforms. It advocates for the adoption …

Singleadv: Single-Class Target-Specific Attack Against Interpretable Deep Learning Systems, Eldor Abdukhamidov, Mohammed Abuhamad, George K. Thiruvathukal, Hyoungshick Kim, Tamer Abuhmed

Computer Science: Faculty Publications and Other Works

In this paper, we present a novel Single-class target-specific Adversarial attack called SingleADV. The goal of SingleADV is to generate a universal perturbation that deceives the target model into confusing a specific category of objects with a target category while ensuring highly relevant and accurate interpretations. The universal perturbation is stochastically and iteratively optimized by minimizing the adversarial loss that is designed to consider both the classifier and interpreter costs in targeted and non-targeted categories. In this optimization framework, ruled by the first- and second-moment estimations, the desired loss surface promotes high confidence and interpretation score of adversarial samples. By …

Urban And Rural Bmi Trajectories In Southeastern Ghana: A Space-Time Modeling Perspective On Spatial Autocorrelation, Hsiao-Chien Shih, Xiaoxiao Wei, Li An, John Weeks, Douglas Stow

International Journal of Geospatial and Environmental Research

Spatial autocorrelation in model residuals can have a significant impact on the results of spatial or space-time models. This can result in misleading estimates of the influence of different factors, potentially exaggerating or even reversing the perceived effects of these factors. This study also considers the potential implications of the Modifiable Areal Unit Problem (MAUP) in the context of spatial-temporal models. In this case study for southeastern Ghana, we examined whether and how spatial autocorrelation in model residuals might generate bias in regression coefficients when explaining women’s body mass index (BMI) across urban and rural areas. Eigenvector spatial filtering, with …

Predictive Analysis Of Local House Prices: Leveraging Machine Learning For Real Estate Valuation, Joey Hernandez, Danny Chang, Santiago Gutierrez, Paul Huggins

SMU Data Science Review

This paper presents a comprehensive study examining the real estate market potential in the dynamic urban landscapes of Frisco and Plano, Texas. Combining traditional real estate analysis with cutting-edge machine learning techniques, the study aims to predict home prices and assess investment feasibility. Leveraging these findings, the study proposes a strategic focus on predictive modeling and investment potential identification, emphasizing the continual refinement of machine learning models with updated data to accurately forecast changes in the real estate market. By harnessing the predictive power of these models, investors can identify high-growth areas and optimize their investment decisions, thus capitalizing on …

A Symbolic Approach To Nonlinear Time Series Analysis, Ranjan Karki, Nibhrat Lohia, Michael B. Schulte

SMU Data Science Review

Current nonlinear time series methods such as neural networks forecast well. However, they act as a black box and are difficult to interpret, leaving the researchers and the audience with little insight into why the forecasts are the way they are. There is a need for a method that forecasts accurately while also being easy to interpret. This paper aims to develop a method to build an interpretable model for univariate and multivariate nonlinear time series data using wavelets and symbolic regression. The final method relies on multilayer perceptron (MLP) neural networks as a form of dimensionality reduction and the …

Intelligent Solutions For Retroactive Anomaly Detection And Resolution With Log File Systems, Derek G. Rogers, Chanvo Nguyen, Abhay Sharma

SMU Data Science Review

This paper explores the intricate challenges log files pose from data science and machine learning perspectives. Drawing inspiration from existing methods, LAnoBERT, PULL, LLMs, and the breadth of recent research, this paper aims to push the boundaries of machine learning for log file systems. Our study comprehensively examines the unique challenges presented in our problem setup, delineates the limitations of existing methods, and introduces innovative solutions. These contributions are organized to offer valuable insights, predictions, and actionable recommendations tailored for Microsoft's engineers working on log data analysis.

Baseball Decision-Making: Optimizing At-Bat Simulations, Varun Gopal, Krithika Kondakindi, Nibhrat Lohia, Morgan Williams

SMU Data Science Review

Pitch selection in baseball plays a crucial role, involving pitchers, catchers, and batters working together. This practice, dating back to early baseball, has seen teams try various methods to gain an advantage. This research aims to use reinforcement learning and pitch-by-pitch Statcast data to improve batting strategies. It also builds on previous statistical work (sabermetrics) to make better choices in pitch selection and plate discipline. The dataset used, including over 700,000 pitches for each full season and 200,000 pitches for the COVID-shortened 2020 season, encompasses a wealth of crucial metrics including pitch release point, velocity, and launch angle. This study …

Reevaluating Texas Energy Market Forecasts In The Wake Of Recent Extreme Weather Events, Robert A. Derner, Richard W. Butler Ii, Alexandria Neff, Adam R. Ruthford

SMU Data Science Review

This paper provides updated forecasts of energy demand in Texas and recognizes the impact of sustainable energy. It is important that the forecasts of the adoption of sustainable energy are reexamined after Winter Storm Uri crippled the Texas power grid and left many without power. This storm highlighted the issues the Texas power grid had and has continued to struggle with in supplying the state with energy. This paper will offer an overview of the relevant literature on the adoption of sustainable energy and relevant events that have occurred in the state of Texas that will give the reader the …

Multi-Class Emotion Classification With Xgboost Model Using Wearable Eeg Headband Data, James Khamthung, Nibhrat Lohia, Seement Srivastava

SMU Data Science Review

Electroencephalography (EEG) or brainwave signals serve as a valuable source for discerning human activities, thoughts, and emotions. This study explores the efficacy of EXtreme Gradient Boosting (XGBoost) models in sentiment classification using EEG signals, specifically those captured by the MUSE EEG headband. The MUSE device, equipped with four EEG electrodes (TP9, AF7, AF8, TP10), offers a cost-effective alternative to traditional EEG setups, which often utilize over 60 channels in laboratory-grade settings. Leveraging a dataset from previous MUSE research (Bird, J. et al., 2019), emotional states (positive, neutral, and negative) were observed in a male and a female participant, each for …

Building Effective Large Language Model Agents, Sydney Holder, Shreyash Taywade

SMU Data Science Review

The advancement of large language models (LLMs) has significantly expanded the influence of artificial intelligence across various sectors. This paper explores building LLM agents to power applications and examines what is necessary to build an efficient and helpful AI assistant. The research investigates the core components necessary to create specialized agents, facilitate collaboration in problem-solving, and improve human task performance. The development and application of tools designed to augment the capabilities of LLM agents are also explored. The paper addresses the potential risks of the unknowns, such as hallucinations, which can compromise the success of agent-based solutions within LLM applications. …

Game Recommendation Analysis Using Steam Profiles And Reviews, Robert Blue, Luis Garcia, Jacob Turner

SMU Data Science Review

Smaller game studios are at a disadvantage when it comes to getting their product noticed by users. This study aims to provide insights on how recommendation engines work so that these smaller studios can have their games noticed on Steam. Steam is one of the largest video game distribution services and they have a recommendation engine which promotes games to its user base. This study utilized user information such as number of games played, the type of games, and the hours played and created recommendation engines to identify the qualities in the game that are driving recommendations.

Leveraging Transformer Models For Genre Classification, Andreea C. Craus, Ben Berger, Yves Hughes, Hayley Horn

SMU Data Science Review

As the digital music landscape continues to expand, the need for effective methods to understand and contextualize the diverse genres of lyrical content becomes increasingly critical. This research focuses on the application of transformer models in the domain of music analysis, specifically in the task of lyric genre classification. By leveraging the advanced capabilities of transformer architectures, this project aims to capture intricate linguistic nuances within song lyrics, thereby enhancing the accuracy and efficiency of genre classification. The relevance of this project lies in its potential to contribute to the development of automated systems for music recommendation and genre-based playlist …

Engineering Thermodynamics, Paul J. Marchese

Open Educational Resources

This collection of assignments is designed for an introductory thermodynamics class. It includes comprehensive readings that cover the fundamental concepts, problem sets to reinforce learning through practical application, and YouTube videos that provide detailed explanations and visual demonstrations of the material. These resources can be utilized in a regular classroom setting or for independent study, offering flexibility to accommodate different learning environments and preferences.

Molecular-Level Studies Of Nanopatterned Biomolecules With Atomic Force Microscopy, Ashley R. Walker

LSU Doctoral Dissertations

Atomic force microscopy (AFM) is an analytical technique in which a tipped probe is gently scanned across the surface in a raster pattern to generate digital images of a sample at the nanoscale. The AFM instrument has three general operational modes, which are contact, non-contact and tapping-mode, that can be used to examine materials at the atomic level. Single-molecular details of biological molecules and other soft organic materials can be captured with minimal denaturation in either ambient or liquid environments when using tapping-mode AFM. In tapping-mode, the probe is driven to oscillate vertically while the tip is scanned across the …

Detecting Drifts In Data Streams Using Kullback-Leibler (Kl) Divergence Measure For Data Engineering Applications, Jeomoan Francis Kurian, Mohamed Allali

Engineering Faculty Articles and Research

The exponential growth of data coupled with the widespread application of artificial intelligence(AI) presents organizations with challenges in upholding data accuracy, especially within data engineering functions. While the Extraction, Transformation, and Loading process addresses error-free data ingestion, validating the content within data streams remains a challenge. Prompt detection and remediation of data issues are crucial, especially in automated analytical environments driven by AI. To address these issues, this study focuses on detecting drifts in data distributions and divergence within data fields processed from different sample populations. Using a hypothetical banking scenario, we illustrate the impact of data drift on automated …

Minimal Specialization: The Coevolution Of Network Structure And Dynamics, Annika King

Theses and Dissertations

The changing topology of a network is driven by the need to maintain or optimize network function. As this function is often related to moving quantities such as traffic, information, etc., efficiently through the network, the structure of the network and the dynamics on the network directly depend on the other. To model this interplay of network structure and dynamics we use the dynamics on the network, or the dynamical processes the network models, to influence the dynamics of the network structure, i.e., to determine where and when to modify the network structure. We model the dynamics on the network …

Explorando Las Ciencias Exactas: Teoría Y Aplicaciones En El Mundo De Los Números, Fabrício Moraes De Almeida, Daniel Méndez De La Cruz, Patricia Del Carmen Gerónimo Ramos, Josué Ojeda Montejo, Cristo Leon

STEM for Success Resources

Las ciencias exactas, compuestas por las matemáticas, la física y otras, nos ofrecen un marco fundamental para comprender el universo y su región fronteriza. En este fascinante viaje nos adentraremos en el mundo de los números, explorando tanto sus fundamentos teóricos como sus aplicaciones prácticas en diferentes áreas de un amplio espectro. Por lo tanto, el libro presenta los conceptos teórico-prácticos en los resultados obtenidos por los distintos autores y coautores en la producción de cada capítulo. Por encima de todo, Atena Editora ofrece divulgación científica con calidad y excelencia, esenciales para asegurar protagonismo entre las mejores editoriales de Brasil …

Memories Of Recipes In Twentieth-Century Irish Cookbooks, Gary Thompson

Dublin Gastronomy Symposium

This paper analyses and categorises the ways in which authors and their publishers have chosen to include the author’s culinary, food and personal memories within the texts of twenty twentieth century Irish Cookbooks. Cookbooks are subjects of culinary nostalgia with the reading of a recipe capable of triggering in the reader a memory of a meal enjoyed, a dish cooked in times past by a loved one, or recollections of the disgust felt for a food hated in childhood. Independent from the reader, the culinary memories of the author can be captured at the time of publication in the text …

Academic Search And Discovery Tools In The Age Of Ai And Large Language Models: An Overview Of The Space, Aaron Tay

AI for Research Week

In the ever-evolving landscape of academic research, “AI tools” for literature search and synthesis are currently getting a lot of attention. These tools promise to ramp up productivity, enabling us to accomplish more in less time or absorb more knowledge without drowning in endless reading. With the sheer number of these systems increasing daily, it's natural to wonder: are they really worth our time and money? And if they are, how should we go about picking the right one from the multitude of options?

In this talk, I will share my views on how the space has developed over two …

Crisis Management: Unveiling Information And Communication Technologies’ Revamped Role Through The Lens Of Sub-Saharan African Countries During Covid-19, Ruthbetha Kateule, Egidius Kamanyi, Mahadia Tunga

The African Journal of Information Systems

The management of COVID-19 pandemic has revealed inefficiencies in coordinating global response, particularly in African countries. Therefore, creating an urgent need to examine the literature on Information and Communication Technologies (ICT) in crisis management to appreciate its contextual role. Employing a systematic review, using the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA), this paper critically assessed the extent of the use of ICT in crisis management in Africa’s response to COVID-19 to reconstruct its resilience against future crises. Findings indicate that while countries with limited ICT infrastructure faced considerable challenges in utilizing ICT solutions in COVID-19 management, countries …

Linear Ode Systems Having A Fundamental Matrix Of The Form F(Mt), Kevin L. Shirley, Vicky W. Klima

CODEE Journal

We interweave scaffolded problem statements with exposition and examples to support the reader as they explore specific linear systems of differential equations with variable coefficients, $\vec{x}'(t)=A(t)\vec{x}(t)$ and initial value $\vec{x}(0)$. We begin with a constant $n\times n$ matrix $M$ and a real or complex-valued function $f$, analytic at the eigenvalues of $M$ with $f(0) = 1$, and construct a linear system of differential equations with solutions $x(t)=f(Mt)\vec{x}(0)$, where $t$ is a parameter in some interval including zero. In general, the solutions to the resulting non-autonomous system are more difficult to analyze than solutions to the constant coefficient case. However, some …

Recent Advance In Electrochemical Dehalogenative Deuteration, Peng-Fei Li, Guang-Sheng Kou, Li-Ping Qi, You-Ai Qiu

Journal of Electrochemistry

In recent years, the incorporation of deuterium atoms into organic compounds has emerged as a vital focus in the development of pharmaceutical molecules. This trend is driven by the increasing recognition of the significance of compounds containing deuterium atoms across various domains, including materials and biopharmaceuticals, where they have found widespread applications in mechanistic studies within the realms of chemistry and biology. Meanwhile, organic electrochemistry, as a relatively environmentally friendly catalytic mode with broad adaptability to redox reactions, has emerged as a crucial alternative to traditional halogen-deuterium exchange in the context of the reduction deuteration of halides. This approach circumvents …

Nickel-Catalyzed Α-Arylation Of Α-Cyanoacetates Enabled By Electrochemistry, Zi-Meng Li, Zhang-Jian Li, Anat Milo, Ping Fang, Tian-Sheng Mei

Journal of Electrochemistry

β-Amino acids have a wide range of applications in the field of pharmaceuticals. Utilizing a combination strategy of nickel catalysis and paired electrolysis, a catalytic α-arylation protocol of carbonyl compounds has been developed. This protocol affords various a-aryl-a-cyanoacetates, which can be reduced to high-value-added α-aryl-β-amino acids. The cross-coupling reaction of electron-deficient aryl bromides with a-cyanoacetates achieves the expected products with good yields and functional group compatibility under mild conditions. Excessive electron-richness in initial aryl bromides facilitates the self-coupling of desired products. DFT calculations confirm that the presence of electron-rich aryl substitutions decreases the …

Comparison Of Ligands In Palladium-Catalyzed Electrochemical Allyl 4-Pyridinylation, Wei-Jie Ding, Chun-Hui Yang, Zhong-Tao Feng, Shi-Rong Lu, Xu Cheng

Journal of Electrochemistry

4-CN-pyridine is a widely applied 4-pyridinylation reagent for diverse transformations. Conventionally, the reaction proceeds via an open-shell radical cross-coupling pathway. Following our previous study, in this work, we report the Pd-catalyzed allyl 4-pyrinylation reaction under electrochemical conditions. The reaction proceeds via radical-polar crossover pathway in which the role of phosphine ligand in reactivity and selectivity was extensively investigated.

Dna-Templated Nanofabrication Of Metal-Semiconductor Heterojunctions And Their Electrical Characterization, Chao Pang

Theses and Dissertations

Bottom-up nanofabrication, although still in its early stages with formidable challenges, is considered a potential alternative method to address the limitations of traditional top-down techniques by offering benefits including process simplification, cost reduction, and environmental friendliness. DNA-templated nanofabrication, one of the most powerful bottom-up methods, presents an innovative way to create advanced nanoelectronics. In this approach, nanomaterials with specific electronic, photonic, or other functions are precisely and programmably positioned on DNA nanostructures from a disordered collection of smaller parts. These self-assembled structures offer significant potential for improving many fields such as biosensing, drug delivery and electronic device manufacturing. This dissertation …

Novel In Situ Synthesis Of Copper Oxide Nanoparticles In Epoxy Network: Kinetics, Composite Mechanical And Dielectric Properties, Elena Bobina, Maxim Danilaev, Safaa.M.R.H. Hussein, Sergey Karandashov, Vladimir Kuklin, Ivan Lounev, Konstantin Faizullin

Karbala International Journal of Modern Science

>Mechanical properties of polymer composites with dispersed nanoparticles (CDNP) depend on interaction between the nanoparticles and the polymer matrix. Strength of polymer composites significantly decreases when there is no interaction between dispersed nanoparticles and the polymer. This limits the application of functional polymer composites with dispersed nanoparticles. In this study, CDNP based on ED-20 epoxy resin with dispersed copper oxide nanoparticles was obtained.These nanoparticles were synthesized in epoxy resin before curing: the nanoparticles were obtained by decomposition of copper hydroxide by heating its solution in ED-20 resin.The kinetics of copper oxide nanoparticles formation in CDNP samples were studied using two …