Digital Commons Network^™

Ensemble Learning Models For Large-Scale Time Series Forecasting In Supply Chain, Minjuan Zhang

Dissertations

Machine learning and AI techniques are transforming supply chain forecasting, driven by the expanding availability of data assets. These advanced methods offer powerful opportunities to optimize management processes, reduce operational costs, and enhance strategic decision-making, which is crucial for enterprise success. However, conventional statistical approaches, such as Autoregressive Integrated Moving Average Models (ARIMA), dynamic regression, and Unobserved Component Models (UCMs)—which have long dominated time series forecasting—often fall short in accuracy and scalability. These traditional models face limitations in batch processing, handling large-scale data, addressing uncertainty-induced disruptions, and synchronizing demand-supply scenarios.

To address these challenges, a novel class of AI-powered ensemble …

A Case Report Of Long-Latency Evoked Diaphragm Potentials After Exposure To Acute Intermittent Hypoxia In Post-West Nile Virus Meningoencephalitis, Joseph F. Welch, Erica A. Dale, Jayakrishnan Nair, Paul W. Davenport, Emily J. Fox, Gordon S. Mitchell

Department of Physical Therapy Faculty Papers

We present a case report of a 42-year-old female with post-West Nile virus meningoencephalitis who exhibited unique, long-latency diaphragm potentials evoked by transcranial and cervical magnetic stimulation after exposure to acute intermittent hypoxia (AIH). The subject was recruited for a study investigating AIH effects on respiratory motor function in healthy individuals. She had contracted West Nile virus infection 5 years before assessment that resulted in hospitalization and persistent allodynia but was not reported to the research team. During the study, transcranial (TMS) and cervical (CMS) magnetic stimulation were performed before and 30-60 min after a single presentation of AIH [15, …

Machine Learning Methods For Pattern Recognition Analysis Of Genomic And Molecular Data, Kuang Du

Dissertations

While immune therapies achieve remarkable success in treating various cancers, only a subset of patients achieves a durable clinical response, and many exhibit innate or acquired resistance. Precision medicine aims to tailor treatments to individual patients based on specific biological markers, ensuring that each patient receives the therapy most likely to be effective. Predictive biomarkers and gene signatures offer potential for more personalized treatment strategies by identifying patients likely to benefit. Recent studies suggest that gene signatures, comprising sets of genes, hold predictive value for certain clinical variables. Typically derived from biological expert knowledge, these signatures demonstrate substantial predictive potential, …

Knowledge Diffusion In Networks Of Artificial Learners, Ehsan Beikihassan

Dissertations

The dissertation draws inspiration from the topic of peer learning in the social sciences and the study of information dissemination and knowledge diffusion in network science. In particular, it introduces and studies a setting involving a population or network of artificial learners, with the objective of optimizing aggregate performance measures under constraints on training resources. In this context, natural knowledge diffusion processes in networks of interacting artificial learners are studied. The term "natural" refers to processes that emulate human peer learning, where the internal state and learning processes of students remain largely opaque, and the main degree of freedom lies …

Interactive Visualization Workflows For Mitigating Analytical Uncertainty, Kaustav Bhattacharjee

Dissertations

This dissertation takes a process-centric and stakeholder-first perspective for handling analytical uncertainty: the form of uncertainty that confronts data analysts' insight-generation processes in high-consequence decision-making scenarios. The cost of an incorrect decision when data is used for movie recommendations as opposed to when personal data is used to drive insights or when data-driven modeling is used to drive real-time decisions for maintaining the health of a grid are vastly different in terms of consequences. This dissertation looks at analytical uncertainty in two real-world scenarios: i) how sensitive information leakage can be prevented during the open data release process with data …

Decomposition Of Diisopropyl Methylphosphonate (Dimp) Exposed To Elevated Temperatures And Combustion Products Of Reactive Materials, Elif Irem Senyurt

Dissertations

The safe and efficient destruction of chemical weapon agents (CWAs) stockpiles remains a critical global challenge. Understanding the thermophysical properties, decomposition mechanisms, and interactions of CWAs with their environment is crucial for developing effective strategies to mitigate their threats. Diisopropyl methylphosphonate (DIMP) and Dimethyl methylphosphonate are commonly used nerve agent surrogates. This dissertation focuses on DIMP and DMMP, investigates their properties and behavior under conditions relevant to prompt defeat scenarios.

The thermophysical properties of DIMP and DMMP were experimentally characterized, including vapor-liquid surface tension (3-60 °C) and viscosities of neat and aqueous solutions. Results revealed significant non-ideal behavior in aqueous …

Visual Analytic Techniques For Interpretable Algorithmic Ranking Systems, Jun Yuan

Dissertations

Rankings have a profound impact on the increasingly data-driven society. From leisurely activities like the movies to watch, the restaurants to patronize; to highly consequential decisions, like making educational and occupational choices or getting hired by companies— these are all driven by sophisticated yet mostly opaque algorithmic rankers. A small change in how these rankers order the data items can have profound consequences, like deterioration of the prestige of a university or a job applicant missing out on being on the list of the top candidates for an organization. These scenarios necessitate data-driven and human-centered innovation to make rankers accessible, …

Crowd-Sourced Learning For Computer Graphics Applications, Yunhao Zhang

Dissertations

Computer Graphics (CG) revolves around virtual content creation using computational methods, spanning applications from games to visual effects. Typically, the creation of CG content is led by expert practitioners who guide computational algorithms towards satisfactory results. Thus, creating CG content often requires manual iterations encompassing algorithm design, parameter tuning, and aesthetic feedback. This work investigates how to leverage crowd-sourcing to streamline such creation processes, focusing on animation and simulation. In animation, a novel crowd-sourcing framework is proposed for combat animation, enabling users to analyze motion similarities, and retrieve matching motions using novel crowd-sourced motion features. Such features enable quantifying previously …

Construction Of An Instrument For Evaluating The Teaching Process In Highereducation: Content And Construct Validity, Risky Setiawan, Wagiran Wagiran, Yasir Alsamiri

REID (Research and Evaluation in Education)

This study aims to reveal the content validity, construct validity, and reliability of the instrument for evaluating the teaching process in higher education. This research is development research applying the ADDIE model from Molenda. The indicators evaluated consist of context, inputs, processes, and products. The sample consisted of 1200 students from eight faculties, each represented by three study programs. Data analysis uses three stages: content validity test analysis using the V-Aiken method involving six panellists or experts; construct validity test using Confirmatory Factor Analysis (CFA). Quantitative descriptive analysis and interpretive qualitative analysis used the Miles and Huberman method. The results …

Constructing And Providing Content Validity Evidence Through The Aiken's Vindex Based On The Experts' Judgments Of The Instrument To Measuremathematical Problem-Solving Skills, Nia Kania, Yaya S. Kusumah, Jarnawi Afgani Dahlan, Elah Nurlaelah, Ferit Gürbüz, Ebenezer Bonyah

REID (Research and Evaluation in Education)

Test content-based proof of validity is a type of evidence that supports the validity of a measuring instrument. This research aims to develop a mathematical problem-solving assessment instrument utilizing five experts. This study is classified as developmental research and follows a research design that includes two separate stages: the preliminary design stage and the prototype stage. However, its application is restricted to Prototype 1 and Prototype 2, specifically for expert evaluation. This instrument was designed explicitly for grade VIII students studying mathematics, covering all the topics from the odd semesters. The analysis progressed through three distinct stages— curriculum analysis, content …

Stability Of Estimation Item Parameter In Irt Dichotomy Considering The Number Of Participants, Zulfa Safina Ibrahim, Heri Retnawati, Alfred Irambona, Beatriz Eugenia Orantes Pérez

REID (Research and Evaluation in Education)

This research is related to item response theory (IRT) which is needed to measure the goodness of a test set, while item parameter estimation is needed to determine the technical properties of a test item. Stability of item parameter estimation is conducted to determine the minimum sample that can be used to obtain good item parameter estimation results. The purpose of this study is to describe the effect of the number of test takers on the stability of item parameter estimation with the Bayes method (expected a posteriori, EAP) on dichotomous data. The minimum sample for stability is 1,000 participants …

Predictor Factors For Teacher Innovative Behavior During Curriculum Reform: The Role Of Cognitive Flexibility, Positive Affect, And Negative Affect, Khairunnisa Syafira Dumbi, Stephanie Yuanita Indrasari

REID (Research and Evaluation in Education)

Teacher innovative behavior is a key capability for maximizing teacher performance as well as the student learning process, especially when teachers face new changes in their education system such as curriculum reform. However, insufficient attention has been given to understanding the interaction of predictor factors to encourage teacher innovative behavior. This study aims to assess the role of cognitive flexibility, positive affect, and negative affect in predicting teacher innovative behavior. A cross-sectional and quantitative design was used for this study. The data collection procedure used convenience sampling, with questionnaires distributed online via social media through several teacher communities. Three instruments …

Automatic Generation Of Physics Items With Large Language Models (Llms), Moses Oluoke Omopekunola, Elena Yu Kardanova

REID (Research and Evaluation in Education)

High-quality items are essential for producing reliable and valid assessments, offering valuable insights for decision-making processes. As the demand for items with strong psychometric properties increases for both summative and formative assessments, automatic item generation (AIG) has gained prominence. Research highlights the potential of large language models (LLMs) in the AIG process, noting the positive impact of generative AI tools like ChatGPT on educational assessments, recognized for their ability to generate various item types across different languages and subjects. This study fills a research gap by exploring how AI-generated items in secondary/high school physics aligned with educational taxonomy. It utilizes …

Changing Images Of Favorite Schools After The Student Admission System Reform In Indonesia, Janu Arlinwibowo, Sri Fajar Martono, Ikhya Ulumudin, Hermanto Waruwu, Yufridawati Yufridawati, Yunita Murdiyaningrum, Gupita Nadindra Fatima, Benjamin Leong Tack Khang

REID (Research and Evaluation in Education)

The study aims to unearth public perceptions of the label of favorite schools after the implementation of student admission reform in Indonesia, namely the zoning system, and to explore the underlying causes. Adopting a qualitative method with a phenomenological approach, this study involved participants from nine provincial education services, nine regency education services, 72 teachers, and 72 parents. Data collected through in-depth interviews and focus groups reveal three distinctive perceptions of favorite schools. The first view posits that after the implementation of the zoning system, the quality among schools is relatively similar, indicating that the new policy is effective in …

Online Versus Face-To-Face Instruction: Entry Level Accounting Students Are Performing About The Same, Nancy L. Johnson, Candalyn B. Rade

The North American Accounting Studies

Students today demonstrate strong aptitude for using online learning resources resulting from most completing high school during the COVID-19 pandemic. Learning resources available for instructional design include faculty created, publisher provided, and a plethora of online videos. This study aimed to understand if scores on graded assignments differ between online (OL) and face-to-face (F2F) sections of entry-level accounting, differences in student learning resources access, and if access correlates with performance on graded assignments. Findings revealed students performed similarly in OL and F2F sections on many, but not all graded assignments. Video resource access was higher for OL students and was …

Pengaruh Loneliness Di Tempat Kerja Serta Peran Perceived Organization Support Dan Resilience Terhadap Psychological Well-Being Di Jabodetabek, Nurisqia Caesar Pramadhani

Jurnal Manajemen dan Usahawan Indonesia

This study explores the impact of workplace loneliness on the psychological well-being of Generation Z and Millennial employees in the Greater Jakarta area, considering the role of perceived organisational support and resilience as moderating variables. Using a cross-sectional survey approach with 334 respondents, this study found that loneliness at work negatively affects psychological well-being. In contrast, POS and resilience have a significant positive influence. Resilience was also shown to moderate the relationship between workplace loneliness and psychological well-being, strengthening individuals' ability to deal with loneliness constructively. These results emphasise the importance of developing organisational policies that support employees' social connectedness …

Annual Report 2023-2024, Houston Academy Of Medicine - Texas Medical Center Library

Annual Reports: 1943 - Present

This file contains the Annual Report for the library from 2023-2024.

Smallpox Outbreaks And Immunization Policies In Tanzania From The Late Nineteenth Century To The First World War, Lorne Larson

Zamani: A Journal of African Historical Studies

An estimated 300 million people died globally from smallpox in the 20th century alone. There was very much a North/South divide in the existence of the disease in that period, with countries across South America, Africa and Asia recording the majority of cases. In 1966 the World Health Organization launched an intensive effort to finally eliminate the disease. The last known endemic case of smallpox was reported in Somalia in 1977, and that outbreak was promptly contained. In 1980 smallpox was declared eradicated – the only infectious disease affecting humans to achieve this distinction. This remains among the most notable …

'Evading The Tax Collector’: Native Responses To The Head Tax In Colonial Njombe, Tanzania, 1920-1960, Peter Chaula, Hezron Kangalawe

Zamani: A Journal of African Historical Studies

Tax collection was one of the core preoccupations of the colonial government in Tanganyika (now Tanzania) and other colonies in the Africa that persisted even after independence. Direct taxation formed the basis of colonial taxation in Tanganyika. Head tax was a dominant form of direct taxation with its burden being borne primarily by Africans. This article uses the colonial Njombe District of Tanganyika to explore the responses of the African taxpayers to the head tax. The available data indicates that colonial head tax policies and practices in Njombe elicited varied responses from Africans with covert forms forming the mainstay of …

Major Trends In Oral Historiography In Mainland Tanzania, 1960s To The Present: A Review Of Published Sources, Albertus K. Onyiego

Zamani: A Journal of African Historical Studies

This article examines the role of oral methodology in reconstructing historical knowledge in Mainland Tanzania over the last six decades. Although greater attention is paid to the period from the 1960s onwards, efforts have been made to illuminate on the use of oral methodology in the period before. The article is organised into four temporal sections, each representing a distinct phase of oral methodology. The first section explores the role of oral methodology before independence. It will be noticed that the gradual use of oral sources in the writing of history in Mainland Tanzania started way back during German and …

Review Of Water Brings No Harm: Management Knowledge And The Struggle For Waters Of Kilimanjaro, Maxmillian J. Chuhila

Zamani: A Journal of African Historical Studies

Water Brings No Harm is a key text that enables readers to understand the competing claims to resource control between government authorities and local communities on the ground. Scholarship on the relationship between local knowledge and expert knowledge in resource management and control suggests an asymmetrical relationship in which expert opinion assumes the primary responsibility.1 Bender contrasts traditional and imposed systems of resource ownership and management, arguing that there has been a struggle from both sides, as each side believes it has a rightful claim to ownership and management of water source.

Review Of Decolonising Sociology: An Introduction, Armstrong K. Matogwa

Zamani: A Journal of African Historical Studies

Decolonizing Sociology is one of the few works in sociology that makes critical assessment of the discipline. It is a kind of self-critique within the discipline that aims to reveal epistemic setbacks that have existed for decades. To arrive to the point, Meghji, has situated his thesis along decolonial sociology, which interrogates dominant sociological theories in the context of imperialism. By so doing, he makes three main arguments as follows; first, what is called sociology is colonial in nature as it is based on the ideas of the Western thinkers namely Marx, Durkheim and Weber which emerged and institutionalized during …

Optimizing Bioethanol Production From Solanum Torvum (Devil's Thorn): An Evaluation Of Conversion Efficiency And Invasive Plant Management Potential, Jaya Ashwin D S, Navaneeth K, Abhay Mahesh Baadkar, Supriya S Sundar, Bhoomika B J

Manipal Journal of Science and Technology

Solanum torvum, commonly known as the Devil’s thorn, is an invasive species present in India that causes negative ecological consequences. However, given its abundance and high starch content in the plant, it could be utilized as a potential feedstock for sustainable biofuel production. We aim to explore the feasibility of bioethanol production from S. torvum and its potential as a means of managing this invasive species. The study will take on a comprehensive approach, including techniques for optimizing starch extraction and improving its accessibility. Fermentation with suitable strains of microorganisms, and analysis of bioethanol yield. In addition, the study will …

A Predictive Iot And Cloud Framework For Smart Healthcare Monitoring Using Integrated Deep Learning Model, Preeti Rani, Umesh Chandra Garjola, Haider Abbas

NJF Intelligent Engineering Journal

The researchers developed a deep learning-based smart healthcare monitoring system based on IoT and cloud technology. The proposed system integrates IoT sensors for real-time collection of physiological data, such as ECG, blood pressure, and heart rate, with cloud computing for secure storage and advanced analytics. Utilizing the Bi-LSTM model with fuzzy inference systems (FIS), the framework enhances the accuracy and efficiency of heart disease prediction. According to the evaluation, the model performs better in terms of accuracy, precision, recall, and F1 score than traditional LSTM and FLSTM models. By enabling early detection and personalized interventions, the system aims to reduce …

Real-Time Congestion Control And Load Optimization In Cloud-Manets Using Predictive Algorithms, Preeti Rani, Mohammed Hussien Falaah

NJF Intelligent Engineering Journal

Cloud-MANET environments require a system to balance load and control congestion. As a result of integrating real-time network metrics with predictive traffic algorithms, the proposed model optimizes the management of dynamic topologies, network bandwidth constraints, and fluctuating traffic loads. In addition to energy-aware multi-path routing, the framework incorporates adaptive congestion control mechanisms to ensure data transmission is efficient and stable. This algorithm provides higher packet delivery ratios, reduces end-to-end delays, and increases throughput over existing algorithms, according to the evaluation results. Hybrid Cloud-MANET systems can benefit from this approach by optimizing resource utilization and network performance.

New Forced Convection Flow Of Nanofluid Within A Partially Filled Porous~Straight Channel, Ammar I. Alsabery, Ali Sahib Abosinee

NJF Intelligent Engineering Journal

This study specifically examines how the movement and dispersion of nanoparticles affect heat transfer in a linear channel that contains a partially porous medium. The existing body of literature is lacking a comprehensive understanding of the convective heat transfer of nanofluids in porous channels. This presents an open research topic that demands further investigation. The porous channel is modelled using Finite Element Method (FEM) for steady flow. The assumption of thermal equilibrium model is made between the solid phases and nanofluid. The non-uniform distribution of nanoparticles within the channel is postulated. Consequently, the equation for the distribution of volume fraction …

A Predictive Framework Combining Iot And Machine Learning Regression Models For Smart Precision Farming, Kusum Yadav, Nesreen Abdou El-Hadiede

NJF Intelligent Engineering Journal

In this paper, the Internet of Things (IoT) and machine learning algorithms that incorporate regressor are integrated to improve precision agriculture. Data from Internet of Things sensors like temperature sensors, humidity sensors, and soil sensors can be collected and analysed using machine learning algorithms like Support Vector Machines (SVMs) and Multilayer Perceptrons (MLPs). By using the proposed system, crop yield will be optimised, resource usage will be minimised, and the environmental impact of agriculture will be reduced. A comparison of predictive accuracy and error metrics, such as RMSE, demonstrated the effectiveness of automated monitoring, predicting crop health issues, and implementing …

Biological Abnormalities In Long Covid Disease: A Mini Review, Abbas F. Almulla, Hanaa Addai Ali

NJF Biomedicine Journal

Long COVID (LC) is characterized by prolonged, diverse symptoms affecting multiple organ systems, including but not limiting to the immune, neurological, and cardiovascular systems. This mini review explores the biological abnormalities underpinning LC, focusing on immune dysregulation, chronic inflammation, oxidative stress, and mitochondrial dysfunction as key contributors to its persistence. Recent studies indicate that LC may involve sustained elevation of pro-inflammatory cytokines, autoimmunity, and T-cell exhaustion, all of which perpetuate a state of low-grade chronic inflammation. Additionally, oxidative and nitrosative stress linked to mitochondrial damage exacerbates fatigue, mood and cognitive symptoms, while hormonal imbalances and metabolic disturbances further complicate the …

Comparative Analysis Of Atracurium And Rocuronium In General Anesthesia: Distribution And Effects On Vital Signs, Omaima Abbass, Ahmed Maki Radeef

NJF Biomedicine Journal

Background: The Muscle relaxants are necessary in anesthesia management that used to facilitate the intubation and for ensure muscle relaxation during surgery. The Rocuronium and Atracurium are two most commonly used non-depolarizing muscle for relaxants of muscles, which each have novel effects on hemodynamic parameters, since they are major for maintaining stability during surgical procedures.

Objective: The present study aims to compare the hemodynamic effects of both Rocuronium and Atracurium during surgery apparatus in adult patients that undergoing general anesthesia, their effect on systolic blood pressure and diastolic blood pressure, mean arterial pressure (MAP), heart rate, and oxygen …

The Effect Of Types Anesthesia On Neonate's Apgar Score In Cesarean Section, Ahmed Maki Radeef, Ali Mejbel. M. Alkhafaji, Asawer Hasan Najm

NJF Biomedicine Journal

Background: The type of anesthesia is important in maternal and fetal well-being. There is different information about the effect of general and spinal anesthesia on APGAR scores and hemodynamic stability for maternal, so in this study, a comparison was made following these two methods.

Objective: To compare anesthetic types regarding feto-maternal outcomes. Determine the effect of anesthesia type on neonate APGAR score, determine the effect of anesthesia type on the material's hemodynamic stability, and determine the effect of induction time on neonate APGAR score. Materials and Methods: This study is a clinical trial and 60 term pregnant women …