Digital Commons Network^™

Linking Static And Dynamic Structures And Properties Of Materials With Computational And Mathematical Models, (Enoch) Sin Hang Ho

Theses and Dissertations

Terahertz (THz) spectroscopy is an effective technique to study and manipulate the structural dynamics of materials, due to its frequency range being very similar to the vibrational frequencies of collective atom motions in a host of materials. High-field and broadband THz radiation can be generated via optical rectification (OR) in nonlinear optical (NLO) crystals. The efficiency of OR response in an NLO crystal is determined by many factors, including molecular hyperpolarizability (β), 2nd order electric susceptibility (χ(2)), crystal structure, primary growth orientation, refractive index, absorption and phase matching condition. In this dissertation, I will focus on using computation methods and …

Quantifying Wellbore Effects During Co2 Sequestration In A Saline Aquifer, Uzoma Johnpaul Ajugwe

USF Tampa Graduate Theses and Dissertations

Carbon capture and storage (CCS) is a strategy for mitigating climate change by reducing greenhouse gas emissions from large stationary sources like fossil-fuel-fired power stations. One method of CCS involves carbon dioxide (CO2) sequestration in deep saline aquifers, where supercritical CO2 is injected into an aquifer. The success of such projects depends on accurate predictions of CO2 behavior within the subsurface, which are obtained through numerical simulations.

TOUGHREACT, a renowned simulation tool, models subsurface fluid flow, geochemical interactions, and solute transport, providing insights into the feasibility of CO2 sequestration projects. A critical aspect of these simulations is the apportioning of …

The Cellular Mechanisms Of Alzheimer's Disease Protection By The Pilra G78r Variant, Wenhan Cheng

Theses and Dissertations

Microglial dysfunction is increasingly linked to Alzheimer’s Disease (AD). Immune receptors like TREM2 and CD33 play opposing roles in microglial activity. TREM2 activation triggers immunoreceptor tyrosine-based activation motif (ITAM) signaling to promote microglial activities, including amyloid-β clearance, but variants in TREM2 such as R47H that impair its function increase AD risk. In contrast, CD33 is an inhibitory receptor that contains an immunoreceptor tyrosine-based inhibitory motif (ITIM) which transmits signals that suppress microglial function. An AD-protective variant in CD33 alters CD33 activity, potentially enhancing TREM2 function. PILRA is another inhibitory immune receptor expressed by microglia that contains an ITIM. A naturally …

Final 2025 Residential Metals Abatement Program (Rmap) Quality Assurance Project Plan (Qapp) Annual Update (Residential Parcels), Pioneer Technical Services, Inc.

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

Final 2025 Residential Metals Abatement Program (Rmap) Quality Assurance Project Plan (Qapp) Annual Update (Non-Residential Parcels And Residential Daycares), Pioneer Technical Services, Inc.

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

Final Unreclaimed Sites Quality Assurance Project Plan (Qapp), Pioneer Technical Services, Inc.

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

Quantum-Chemical Modeling Of Mechanisms And Selectivity In Open-Shell Organometallic Reactions, Michael T. Davenport

Theses and Dissertations

Quantum mechanical calculations have emerged as a powerful approach for directly evaluating reaction mechanisms and selectivity in transition metal-ligand complexes involving organometallic intermediates. Density functional theory (DFT) quantum mechanical methods enable the generation of potential energy surfaces and structures that define reaction mechanisms and allow for the evaluation of selectivity through statistical transition state theory. However, in certain cases, it is necessary to go beyond statistical treatments and incorporate atomic motion through molecular dynamics simulations. Additionally, many transition metal-mediated reactions involve unpaired electrons and spin state crossings. This dissertation focuses on the application of DFT-derived potential energy surfaces and molecular …

A Community-Based Study To Investigate Persistent Ambient Odors In Childs Park, Fl, Gennaro Saliceto

USF Tampa Graduate Theses and Dissertations

For many years, residents in Childs Park, Saint Petersburg, Florida, have reported unpleasant odors. Although there have been prior efforts to address the issue, the odors continue to be a concern for the community, who worry about possible health implications. This research aimed to equip residents with information to address the issue by identifying the presence of airborne pollutants that generate odors, quantifying the concentrations of toxic organic pollutants, and exploring the sources and environmental conditions that contribute to odors and their perception.

To accomplish these aims, the study utilized different methods. First, two walking measurement campaigns were conducted to …

Topic Shift Detection And Triggering In Natural Dialogue Systems: A Lightweight Approach, Rohith Perumandla

College of Computing and Digital Media Dissertations

This research address a key challenge in dialogue system: enabling the proactive, human-like shifting using lightweight approaching using MobileBERT (~25M) model was proposed and fine-tuned for topic shift detection, augmented with liguistic featuers for for topic trigger detection. Despite its smaller size (~25M parameters), the MobileBERT-based system achieved competitive results (F1 = 74.16%,) compared to the much larger XLNet model (~110M parameters, F1 = 79.95%), while offering greater efficiency. The topic trigger module, combining MobileBERT with linguistic features, further demonstrated effective performance (F1 = 71.61%).

Proceedings Of The Cuny Games Conference 11.0, Robert O. Duncan, Grace Axler-Diperte, Joe Bisz, Christina Boyle, Devorah Kletenik, Carolyn Stallard

Publications and Research

The CUNY Games Conference combines workshops, idea exchanges, interactive participant presentations, playtesting, and playing tabletop games into a one-day online event to promote and discuss game-based learning. The conference focuses on creative pedagogy, such as playful learning activities or games, that teachers can use in the classroom every day. The conference is online and features interactive presentations by attendees, informal idea exchange sessions, and workshops by the conference organizers.

The Discovery, Communication, And Implementation Of New Geologic Findings: Examining The Cascadia Earthquake, Saylor Brainard

University Honors Theses

The Cascadia Subduction Zone, located off the Coast of the Pacific Northwest, is at risk of generating a 9.0 magnitude earthquake in the near future. Despite its significance, the discovery of the seismic potential of Cascadia didn't occur until 1987, when geologist Brian Atwater searched for non-traditional forms of earthquake evidence. As decades of continued research fleshed out Atwater's initial discovery, the implications associated with the discovery became apparent, presenting Washington and Oregon with the high probability that a massive earthquake will take place within the next century. Communicating the severity of this geologic discovery to both the public and …

Re: Conditional Approval Letter For The Butte Priority Soils Operable Unit (Bpsou) 2025 Revised Draft Final Unreclaimed Sites Quality Assurance Project Plan (Qapp) (Dated May 15, 2025), Molly Roby

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

Pvc Biodegradation Potential Of Native Fungal Strains From Mt. Hood National And Tillamook State Forests, Bristol Ozturgut

University Honors Theses

Polyvinyl chloride (PVC) is a toxic, degradation-resistant environmental waste product. Recent research has revealed fungal enzymatic activity capable of biodegrading plastics. As PVC infiltrates local environments, it becomes imperative to determine the adaptability of local fungi to PVC substrates. In this experiment, 100 local native fungal strains sampled from the Tillamook State and Mt. Hood National forests and one commercial strain of common oyster mushroom were investigated for their ability to colonize and digest PVC by direct isolation on 0.1% and 0.2% PVC-enriched limited growth media. Substrates for positive cultures were imaged using Fourier transform infrared spectroscopy to analyze potential …

Blockchain-Based Physical Election Votes Digitally Secure Transfer, Mohanad A. Mohammed, Hala B. Abdul Wahab

Journal of Soft Computing and Computer Applications

Responsibility for maintaining election transparency over time and ensuring democratic values intact is held by the Iraqi Independent High Electoral Commission (IHEC). However, transferring physical election votes from election centers is a critical duty, where many challenges appear regarding accountability and security measures. This study proposes a system that utilizes blockchain technology to solve any challenges or difficulties and ensure an effective and improved election process by providing its highest trustworthiness and legitimacy and ensuring a decentralized security process. This system offers unique blockchain characteristics such as immutability, decentralization, and transparency, providing an extra level of security to the data …

Elemental Analysis Of Sediments In Johnson County, Kansas: Applications In Fluvial Suspended Sediment Tracing, Kiena Campbell

Undergraduate Theses, Capstones, and Recitals

This exploratory study investigates whether bulk elemental analysis of sediment samples using inductively coupled mass spectrometry (ICP-MS) can reveal chemical signatures that identify anthropogenic contributions to sedimentation and increased fluvial suspended sediment loads, and whether these contribution sources can be identified. Human activity, urbanization, and changes in land use increase erosion, resulting in higher-than-natural suspended sediments (SS) in waterways and increasing sedimentation in reservoirs across the state of Kansas. These threats to freshwater storage capacity are especially urgent given the projected rise in freshwater demand in the Great Plains region driven by climate change. Understanding the origin of anthropogenic SS …

Improving Culinary Informatics Through Meaningful Social Web Engineering, Suraya Nurain Kalid, Fahmi Mikail Fahrid, Sin-Ban Ho

Journal of Informatics and Web Engineering

This paper gives a good reflection about social web engineering aspirations to ardently see the truth to enlighten culinary concentration and wisdom. With the compassionate path to discover food and engage customers to share content with loving kindness spread to every corner. There are so many features realized, which include direct interfaces through intuitive interfaces to lead the daily food streamlining. May one engaged with constructive creation to grow compassions in every culinary living sharing. Contentment would develop in our heart involved in different phases put forward in this paper. The initial phase begins with honesty in planning and design. …

K-Means Clustering Optimization Of Toddler Malnutrition Status Using Elbow Method, Femmi Widyawati, Ahmad Yahya Dawod, Heru Agus Santoso

Journal of Informatics and Web Engineering

The problem of nutritional status is still a major challenge in the health sector in developing countries, including Indonesia. Malnutrition in toddlers can have serious long-term impacts on children's growth and development, including increased risk of disease, impaired cognitive function, and low productivity in the future. To overcome this problem, an in-depth analysis is needed to determine the distribution of nutritional status of toddlers in one of the provincial capitals in Indonesia, which can be used as a basis for planning more effective interventions. This study uses the K-Means algorithm to classify areas based on the prevalence of malnutrition in …

Facilitating Digital Experience Sharing Among Vehicles Through Utilisation Of Pre-Existing Communication Infrastructure, Asad Hussain, Umar Farooq, Ihsan Rabbi

Journal of Informatics and Web Engineering

Vehicular communication applications are expanding quickly because of the approach of related technologies, such as vehicular cloud and the Internet of Vehicles (IoV). The combination of the Internet of Things (IoT) and smart transportation is the Internet of vehicles. Data related to infotainment, safety, and effectiveness with different vehicles and the Sustainable framework of vehicles can be exchanged. However, after the appearance of such empowering advancements, still a huge number of ideas need research. Data sharing (related trips and navigation) of new/old models and other new/old model vehicles with the owner's agreement should be taken care of. This paper proposes …

Sentiment Analysis Of The 2024 General Election Through Twitter Using Long-Short-Term Memory Algorithm, Angga Wahyu W, Haidar Hilmy Andana, Junta Zeniarja, Aris Febriyanto

Journal of Informatics and Web Engineering

This study analyses sentiment related to the 2024 Indonesian Presidential Election using the Long Short-Term Memory (LSTM) algorithm. A total of 2,400 tweets in the Indonesian language were gathered, with approximately 400 tweets sampled per week. In the data preparation, lexicon-based sentiment tagging, oversampling for class balance, and the creation and training of an LSTM model are all included in the study approach. The built model consists of embedding layers, Conv1D, and two LSTM layers. The LSTM model was selected due to its ability to capture long-range contextual dependencies in sequential text data like tweets, facilitated by its gate mechanisms …

Sentiment Analysis Of The Israel-Palestine Conflict On X: Insights From The Indonesian Perspective Using A Long Short-Term Memory Algorithm, Mohammad Taleb Noori, Muhammad Alif Rahman, Agus Purnomo, Aripin

Journal of Informatics and Web Engineering

The Israel-Palestine conflict which has persisted for decades drives mounting global interest that consequently influences public opinion worldwide. This article examines the sentiment analysis of X (Twitter) data pertaining to the conflict using the Long Short-Term Memory (LSTM) model. This study presents public reactions through an analysis of 1,700 tweets collected between May and July 2023 which encapsulate key recent developments. In this study, several steps were conducted, namely 1) crawling process to get raw data; 2) preprocessing: cleansing, case folding, tokenization, stop word removal, and stemming; 3) modelling and validation using the LSTM model; 4) model evaluation based on …

Aspects-Based Sentiment Analysis Of Extreme Weather On Twitter Using Long Short-Term Memory, Tursun Abdurahmonov, Muhammad Nabil Toby Abiyyu, Dzikru Nur Khayat, M. Ary Heryanto

Journal of Informatics and Web Engineering

This study presents an aspect-based sentiment analysis of tweets related to extreme weather events in Indonesia, utilizing the Long Short-Term Memory (LSTM) model. The dataset was obtained through a Twitter crawling process, followed by a series of preprocessing steps including data cleaning, stop word removal, normalization, tokenization, and stemming. The three primary areas of emphasis in the study were kinds of bad weather forecasts, and the government or society reactions. Using a lexicon-based technique, sentiment labelling generated three groups: positive, neutral, and negative. A random oversampling method was employed to address the data imbalance. The model using the LSTM algorithm …

Sentiment Analysis And Topic Modelling On Twitter Related To Mobile Legends: Bang Bang Game Using Lexicon-Based, Lda, And Svm, Hikmal Muhammad, Fauzi Adi Rafrastara, Kristoforus Adrian Setiadi, Arley Japardi

Journal of Informatics and Web Engineering

Mobile Legends: Bang Bang (MLBB) has become a significant phenomenon within the global e-sports landscape, attracting millions of active players and fans. This study presents a comprehensive sentiment analysis and topic modelling of MLBB-related discussions on Platform Twitter, combining a lexicon-based approach, Latent Dirichlet Allocation (LDA), and Support Vector Machine (SVM) classification within a unified analytical pipeline. A dataset of 4,313 tweets was analysed, revealing that 70.8% expressed neutral sentiment, suggesting that much of the community's communication is informational rather than emotionally charged. Positive sentiments were associated with game content updates and rewards, while negative sentiments focused on technical and …

Analysis Of Forensic Disk Imaging Tools For Data Acquisition And Preservation, Michelle Chee Ern Lim, Brandon Chen Hong Chow, Le Ying Lim, Tarini Shanbagamaran, Darren Yong Jun Lim, Ngu War Hlaing, Ahmad Sahban Rafsanjani

Journal of Informatics and Web Engineering

The identification, preservation, analysis, and presentation of electronic evidence to support legal or organizational inquiries constitute the discipline of digital forensics, which is crucial to contemporary investigations. A crucial component of forensic inquiry, disk imaging guarantees precision, dependability, and legal defensibility. To preserve the original evidence, disk imaging makes an identical, bit-by-bit duplicate of a digital storage device, capturing hidden data, deleted material, and active files. Given the critical role of disk imaging in forensic investigations, selecting the right tool is crucial for accuracy, efficiency, and compliance with forensic standards. This study assesses widely used tools, including AccessData FTK Imager, …

Editorial: Augmented Intelligence For Enabling Knowledge-Driven Decision Making, Heru Agus Santoso

Journal of Informatics and Web Engineering

More flexible and cooperative decision-making processes are required as a result of society's digital transformation. The role of augmented intelligence, that is the synergistic fusion of artificial intelligence and human judgment in facilitating knowledge-driven strategies across various domains is examined in this thematic issue. The integration of business intelligence and software engineering, which forms the foundation for creating intelligent, scalable, and explicable systems, is essential to this investigation. The six chosen papers in this issue show how machine learning techniques can be used to mine and model both structured (such as health records indicators) and unstructured (such as product reviews, …

A Conceptual Approach To Predicting Seismic Events And Flood Risks Using Convolutional Neural Networks, Mahmoud Rehan, Wan-Noorshahida Mohd-Isa, Noramiza Hashim

Journal of Informatics and Web Engineering

This paper explores the application of convolutional neural networks (CNNs) in predictive modelling for seismic events and flood risks, with a particular focus on forecasting extreme quantile events that exceed historical data limits. Traditional risk assessment methods often struggle to estimate such extremes, highlighting the need for more advanced predictive models capable of handling rare but high-impact events. This research enhances CNN architecture to improve accuracy in high quantile predictions by integrating multi-source spatiotemporal data, addressing a critical research gap. The methodology involves incorporating diverse datasets, including geospatial, meteorological, and historical seismic or flood records, into CNN models to augment …

Exploring User Perceptions Of Security In Mobile Banking: A Study In Malaysia, Kai En Lim, Ying Han Pang, Shih Yin Ooi, Wan Xuan Kow, Tang Xing Cheang, Mao Wei Tan

Journal of Informatics and Web Engineering

Mobile banking has become increasingly popular in Malaysia due to its convenience and efficiency. However, persistent security concerns such as vulnerabilities to cyber attacks, malware and phishing affect user trust and impede adoption. This study aims to explore how users perceive and experience the security features of mobile banking applications. In spite of the implementation of security controls, understanding user perceptions and experiences remains essential, as these are core factors which influence mobile adoption. Thus, this study investigates the user experience of mobile banking security features in Malaysia. Specifically, we focus on the users’ perceptions, satisfaction levels and concerns. We …

Classification Of Smartphone Product Reviews On E-Commerce Using The Recurrent Neural Network (Rnn) Method, Rajibul Anam, Fernanda Tata Pradhana, Imam Abu Yasin, Junta Zeniarja

Journal of Informatics and Web Engineering

Understanding how consumers behave in e-commerce is essential for businesses, especially in today’s digital world where people rely heavily on online shopping platforms. A key part of this understanding comes from sentiment analysis, which looks at customer reviews to find out what buyers really think and feel about products. However, analysing these reviews is not always straightforward. Many people use informal language, slang, or mixed languages, which makes it hard for computers to interpret their opinions accurately. On top of that, there is often an imbalance in the types of data available, particularly in developing countries, where some opinions might …

Cyber Security Threats Of Using Generative Artificial Intelligence In Source Code Management, Sainag Nethala, Sandeep Kampa, Srinivas Reddy Kosna

Journal of Informatics and Web Engineering

Generative Artificial Intelligence (Generative AI) models are now broadly used for academic writing and software development for the sake of productivity and efficiency. Concerns on the impact of Artificial Intelligence (AI) tools on academic integrity and cybersecurity grow bigger with time. Generative AI is being used for code generation, editing, and review, raising ethical and security challenges. A big concern is the involuntary introduction of vulnerabilities into codebases. They can reproduce known bugs or malicious code that compromise software integrity because of the way models are trained: on large datasets. The tools may also pose additional security threats often encountered …

Dynamic Job Recommendation By Profiling Undergraduates Academic Performances, Bao-Ling Foo, Choo-Yee Ting, Hui-Ngo Goh, Albert Quek, Chin-Leei Cham

Journal of Informatics and Web Engineering

Job-seeking tasks are always challenging. Often, job recommendation systems require human intervention in the job-seeking process. Therefore, the study focuses on recommendation of most relevant job sectors and prioritizing companies based on a student’s profile. The objectives of this study are: (i) to identify important features that optimize job recommendation, (ii) to construct a predictive model that recommends most relevant job sectors, and (iii) to recommend companies by computing the similarity between student and job profiles. In this study, the dataset was collected from Graduate Tracer Study from a university. Additionally, a job dataset was collected to extend the training …

Exploring Big Data Management Approaches And Applications: A Case Study Of Real-Time Data Analytics In Air Traffic Management, Adeel Hashmi, Nouman Amjad, Muhammad Moiz Ullah Satti, Umar Hayat, Anam Mumtaz

Journal of Informatics and Web Engineering

The rapid proliferation of digital devices has generated vast amounts of data, presenting significant challenges in collection, processing, and analysis that traditional systems struggle to overcome. This study investigates big data management approaches, explicitly focusing on technologies capable of efficiently handling real-time data at scale. Within the context of Air Operations, we propose a Hadoop-based architecture designed to support the Observe-Orient-Decide-Act (OODA) loop and enhance air traffic management. By leveraging a distributed system deployed on a cloud-based platform, we demonstrate a cost-effective solution for optimised data processing and improved decision-making capabilities. Our analysis highlights the advantages of using Hadoop's distributed …