Digital Commons Network^™

Understanding Barriers To Optimal Supervision And Delivery Of The Nationalcertificate (Vocational) Curriculum Through Tvet College Lecturers’Reflective Evaluations, Angelona Rewhydah Williams, Karel Prins, Bongani Innocent Nkambule, Sindile Amina Ngubane

REID (Research and Evaluation in Education)

Propounded by reflective theory, this qualitative case study drew on TVET lecturers' reflective evaluations of factors that they considered to have a bearing on optimal supervision and delivery of the National Certificate (Vocational) curriculum. Data were collected from participants across three campuses of a TVET college in the Eastern Cape Province, South Africa. Twelve lecturers of different seniority were purposively sampled and interviewed in two focus group sessions. The first focus session involved six participants: four post-level 2 and two post-level 3 personnel recognized by the South African Council for Educators (SACE) as "office-based lecturers" and classified within the middle …

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 …

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 …

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 …

Number Sense Profile Of Prospective Elementary School Teachers In Blendedmathematics Learning, Welly Novitasari, Herwin Herwin, Supartinah Supartinah, Putri Wulandari, Budiharti Budiharti

REID (Research and Evaluation in Education)

Number sense is a skill that contributes significantly to learning mathematics. However, number sense is often positioned as a fundamental skill whose development is more focused on children. The contribution of number sense in mathematics is even more apparent at higher levels of education. Ironically, number sense seems ignored and has become a rarely studied topic in higher education. Thus, the student’s number sense ability profile seems buried with various problems. This study aims to reveal the profile of prospective elementary school teachers’ number sense abilities and the factors causing their failure in solving math problems during the implementation of …

Simulation Of Low-High Method In Adaptive Testing, Rukli Rukli, Noor Azeam Atan

REID (Research and Evaluation in Education)

The era of disruption significantly engineered a classic testing system into an adaptive testing system where each test taker takes a unique test. However, the carrying capacity of the adaptive testing system engineering is experiencing obstacles in terms of the method of presenting the test questions. The study aims to introduce the low-high adaptive tracking method with the item response theory approach, where the difficulty level of the questions is adapted to the test takers' abilities. The number of test questions in the question bank is 400 questions. Data analysis used the Bilog-MG program. The range of the difficulty level …

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 …

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 …

Developing A Pancasila Students' Character Instrument: Proof Of Construct Validity And Estimation Of Construct Reliability, Wiwin Mistiani, Edi Istiyono, Amir Syamsudin, Nor Hasnida Md. Ghazali

REID (Research and Evaluation in Education)

This study aims to prove construct validity and estimate construct reliability of the character scale of Pancasila students by using confirmatory factor analysis. The research approach used is quantitative with a sample of 200 high school students selected at random. This study measured the variables by six aspects, 15 indicators, and 20 questions. The six aspects include faith and piety to God Almighty, global nationality, cooperation, independence, critical reasoning, and creativity. The data analysis technique used is confirmatory factor analysis. The study results concluded that the instrument for assessing the character of Pancasila students in high school had a loading …

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 …

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 …

Genetic Algorithm-Based Design Solution Of An Area Lighting Scheme - A Case Study, Prabhat Mishra, Arnab Ganguly, Amartya Roy, Mihir Kumar Manna, Abhik Hazra

Manipal Journal of Science and Technology

In this paper, a Genetic Algorithm (GA)-based approach is taken for the lighting design of a specified area. The design of an area lighting scheme primarily depends upon the application of that area and accordingly target values of lighting design parameters are to be decided from relevant BIS (Bureau of Indian Standard) lighting codes. There are several design variables, viz., light distribution, aiming of the luminaire, pole spacing, luminaire mounting height, grid dimension over the field, etc. The task of a lighting designer is to achieve the target design parameters through a suitable combination of set design variables and design …

Optimized Thyroid Disease Classification Using Nature-Inspired Algorithms: Gwo & Woa, Sayan Mondal

NJF Intelligent Engineering Journal

Recently, there has been an upsurge in the number of cases of thyroid disease. Thyroid function is essential for metabolism, making the early diagnosis of thyroid dysfunction an urgent matter. The issue of class imbalance has not been thoroughly examined, even though there are multiple publications on the topic of thyroid disease detection. Furthermore, the binary-class problem has been the primary emphasis of previous research. This study intends to address these concerns by using the suggested strategy, which takes into account ten distinct thyroid illnesses. In order to choose the best features from the Thyroid dataset, this research proposes two …

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 …

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 …

Comparative Analysis Of Nature-Inspired Optimization Algorithms: Applications, Challenges And Future Directions, Prerna Mann

NJF Intelligent Engineering Journal

With the proliferation of data generation, the process of achieving optimal solutions is getting more complex. It is becoming increasingly clear that intelligent metaheuristics algorithms are the way to go for solving these complicated optimisation problems, particularly when faced with several restrictions. The development of effective methods for dealing with these optimisation challenges has prompted the creation of numerous new algorithms. These algorithms are either improving their ability to handle problems in many domains or are investigating new contexts in which they could be useful. The field is advancing at a quick pace, leaving many in the dark about its …

Single-Step Synthesis Of Activated Carbon From Arabica Spent Coffee Ground Using K2co3 As Activator Agent, Ghina Ivana Mieldan, Yuliusman Yuliusman

Journal of Materials Exploration and Findings

Activated carbon is a nanomaterial that is often used as an effective adsorbent. Activated carbon raw materials can use biomass, such as coffee grounds, which can be found along with the growth of public interest in coffee drinks. Chemical activators are used for activation to increase biomass carbon's adsorption capacity. Using K₂CO₃ activator to increase the specific surface area of activated carbon is more harmless than KOH. The use of spent coffee grounds as carbon source and food additive K₂CO₃ as an activator can make food-grade activated carbon that can be used for food. …

Effect Of Alkyd And Polyester Resin Compositions On Corrosion Resistance, Blistering, And Adhesion In Utilization Of Oily Sludge As Anti-Rust Coating Material, Gerets Land Kakalang, Yohanes David Kristianto, Johny Wahyuadi Mudaryoto

Journal of Materials Exploration and Findings

Oil sludge is a waste derived from upstream and downstream activities of the oil and gas industry which is estimated at 10,000 tonnes generated from all PERTAMINA downstream activities spread across various fields, processing units and depots throughout Indonesia. Oil sludge has the same characteristics as asphalt, where asphalt in previous studies can be used as an anti-rust coating, so that the handling of oily sludge can be topped up by reusing and having its own added value. The purpose of this research is to utilise waste oily sludge as an alternative anti-rust coating material and compare alkyd resin and …

A Comparative Study Of Conventional And Statistically Active Corrosion Methods For Corrosion Growth Assessment Of A 24-Inch Gas Pipeline, Rudi Rinaldi, Jaka Fajar Fatriansyah

Journal of Materials Exploration and Findings

Component failures in oil and gas pipelines can have fatal consequences, leading to operational downtimes and environmental damage. Knowledge of the corrosion growth rate is fundamental to pipeline integrity management, as it is essential for risk assessment and decisions related to asset management. This article aimed to compare two approaches for the corrosion growth estimation of the 24-inch offshore gas pipeline: the conventional method versus the Statistically Active Corrosion (SAC) method. This article is based on the in-line inspection (ILI) results of two consecutive assessments from 2020 to 2023 of the entire 73 km of the pipeline. The results show …

Comparative Analysis Of Risk-Based And Time-Based Inspection Application In Hydrocarbon And Chemical Industries: A Review, Azizar Azizar, Nofrijon Sofyan

Journal of Materials Exploration and Findings

RBI and TBI strategies are comparatively reviewed in terms of their contribution to maintaining asset integrity for asset owners in the hydrocarbon and chemical industries. The objective is to assess various methods on a cost-efficient and risk-managed operational safety basis. It utilizes common industry standards such as API 580 for RBI, and API 510, API 570, and API 653 for TBI, and also case studies and literature analysis. The analysis of data was conducted to examine how each approach deals with inspection planning and decision-making. They suggest that RBI's risk-based prioritization strategy leads to more effective management of high-risk assets, …

Using Technology To Manage A Distributed Workforce & Work Together Seamlessly, Indiana Continuing Legal Education Forum (Iclef)

Indiana Continuing Legal Education Forum 2024

Meeting proceedings of a seminar by the same name, held October 11, 2024.

The Value Of Qualified Asset Appraisals For Lawyers, Indiana Continuing Legal Education Forum (Iclef)

Indiana Continuing Legal Education Forum 2024

Meeting proceedings of a seminar by the same name, held October 29, 2024.

24th Annual Indiana Property Tax Institute, Indiana Continuing Legal Education Forum (Iclef)

Indiana Continuing Legal Education Forum 2024

Meeting proceedings of a seminar by the same name, held April 23, 2024.

Operating Fund Budget/ Expenditure Summary Report 2024-25, Csusb Budget Office

University Budget Office records

No abstract provided.

Comparison Of Fish And Macroinvertebrate Communities In Natural And Constructed Wetlands In The Red River Basin In Texas And Louisiana, Justin L. Rea

Biology Theses

This project plans to compare and contrast wetlands in northeast Texas and western Louisiana within the Mississippi River basin through sampling avian, fish, macroinvertebrate, amphibian, and reptile communities as well as hydrology, soil chemistry, and periphyton/algae biomass. The portion of the project that this study focuses on evaluated the fish and macroinvertebrate assemblages and their relationships within easement, natural and agricultural wetland types. A total of 15 wetlands were sampled consisting of 10 easements, 4 natural, and 1 agricultural wetland. The objectives of this project were to compare and contrast fish and macroinvertebrate assemblages in order to begin creating a …