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Development Of Critical Thinking Scale Of Upper Secondary School Students In Social Studies By Applying Computerized Dynamic Assessment, Non Worathanaphimmakorn, Kamonwan Tangdhanakanond

Journal of Education Studies

The purposes of this pilot study were 1) to develop the critical thinking scale of upper secondary school students in social studies by applying computerized dynamic assessment, and 2) to validate the critical thinking scale of upper secondary school students in social studies by applying computerized dynamic assessment. The sample consisted of 100 upper secondary school students by purposive sampling. The research instrument used was the critical thinking scale by applying computerized dynamic assessment. Data were analyzed by using content validity, item validation including the difficulty and discrimination indexes, and internal consistency in terms of Cronbach’s alpha coefficient. Results revealed …

Containerization On A Self-Supervised Active Foveated Approach To Computer Vision, Dario Dematties, Silvio Rizzi, George K. Thiruvathukal

Computer Science: Faculty Publications and Other Works

Scaling complexity and appropriate data sets availability for training current Computer Vision (CV) applications poses major challenges. We tackle these challenges finding inspiration in biology and introducing a Self-supervised (SS) active foveated approach for CV. In this paper we present our solution to achieve portability and reproducibility by means of containerization utilizing Singularity. We also show the parallelization scheme used to run our models on ThetaGPU–an Argonne Leadership Computing Facility (ALCF) machine of 24 NVIDIA DGX A100 nodes. We describe how to use mpi4py to provide DistributedDataParallel (DDP) with all the needed information about world size as well as global …

Preparation Of Β-Ni (Oh)2 Nanosheet–Modified Glassy Carbon For Pseudocapacitors, Muhammad Buchari Setia Putra, Aliyah Aliyah, Afiten Rahmin Sanjaya, Respati Kevin Pramadewandaru, Hoeil Chung, Tribidasari Anggraningrum Ivandini

Makara Journal of Science

β-Nickel hydroxide (Ni(OH)₂) nanosheet–modified glassy carbon for pseudocapacitors was successfully prepared. The nanosheets were synthesized via a conventional growth seeding method combined with hydrothermal treatment. Transmission electron microscopy (TEM) characterization indicated the hexagonal structure of the nanosheets of around 15 nm in size, and X-ray diffraction (XRD) pattern confirmed the β-phase lattice crystal. These nanosheets used to modify the glassy carbon surface, increased the electroactive surface area by around 15 times. Furthermore, electrochemical investigation of the modified glassy carbon revealed an excellent performance and a specific capacitance of 628.01 F g⁻¹ at a 1 A g^{−1 …}

Pseudo-Siamese Network Combined With Label-Free Raman Spectroscopy For The Quantification Of Mixed Trace Amounts Of Antibiotics In Human Milk: A Feasibility Study, Jing Yi Mou, Muhammad Usman, Jia Wei Tang, Quan Yuan, Zhang Wen Ma, Xin Ru Wen, Zhao Liu, Liang Wang

Research outputs 2022 to 2026

The utilization of antibiotics is prevalent among lactating mothers. Hence, the rapid determination of trace amounts of antibiotics in human milk is crucial for ensuring the healthy development of infants. In this study, we constructed a human milk system containing residual doxycycline (DXC) and/or tetracycline (TC). Machine learning models and clustering algorithms were applied to classify and predict deficient concentrations of single and mixed antibiotics via label-free SERS spectra. The experimental results demonstrate that the CNN model has a recognition accuracy of 98.85% across optimal hyperparameter combinations. Furthermore, we employed Independent Component Analysis (ICA) and the pseudo-Siamese Convolutional Neural Network …

Prevalent Chronic Infections Modulate T-Cell Phenotypes And Functions Enhancing Hiv Susceptibility, Dissemination, And Persistence In African Population, Thomas F. Marandu, Mkunde S. Chachage

Tanzania Journal of Science

While many studies have associated HIV prevalence with socio-economic status, few have explored the host's immunity status prior to HIV infection. High HIV prevalence in Africa may in part be contributed by a high prevalence of other persistent infections that modulate the host immunity towards phenotypes that promote HIV acquisition. In this narrative review, we examined how four most prevalent pathogens in Africa (human papillomavirus, herpesviruses, Mycobacterium tuberculosis, and helminth infections) modulate immunity to favor their survival and in turn, also influence HIV acquisition. We have described how these pathogens expand the number of memory and activated T cells, increase …

Enhancing Tumor Classification Through Machine Learning Algorithms For Breast Cancer Diagnosis, Lawrence Agbota, Edmund F. Agyemang, Priscilla Kissi-Appiah, Lateef Moshood, Akua Osei- Nkwantabisa, Vincent Agbenyeavu, Abraham Nsiah, Augustina Adjei

School of Mathematical & Statistical Sciences Faculty Publications

In cancer diagnosis, machine learning helps improve cancer detection by providing doctors with a second perspective and allowing for faster and more accurate determination and decisions. Numerous studies have used both classic machine learning approaches and deep learning to address cancer classification. In this study, we examine the efficacy of five commonly used machine learning algorithms; both traditional and deep learning models namely, Logistic Regression, Support Vector Machines (SVM), Random Forest (RF), Decision Tree and Deep Neural Networks (DNN). We analyze their ability to properly classify tumors as Benign or Malignant using the Wisconsin breast cancer dataset (WBCD). Random Forest …

On The Size Of Maximal Binary Codes With 2, 3, And 4 Distances, Alexander Barg, Alexey Glazyrin, Wei-Jiun Kao, Ching-Yi Lai, Pin-Chieh Tseng, Wei-Hsuan Yu

School of Mathematical & Statistical Sciences Faculty Publications

We address the maximum size of binary codes and binary constant weight codes with few distances. Previous works established a number of bounds for these quantities as well as the exact values for a range of small code lengths. As our main results, we determine the exact size of maximal binary codes with two distances for all lengths n≥6 as well as the exact size of maximal binary constant weight codes with 2, 3, and 4 distances for several values of the weight and for all but small lengths.

Application Of Time-Varying Mortality Rate Model In Pension System: A Case Of Tanzania, Samya Suleiman, John Andongwisye, Emmanuel E. Sinkwembe, Karl Lundengård

Tanzania Journal of Science

The current increase in the ageing population, driven by a decrease in mortality rates, has impacted most pay-as-you-go defined benefit pension schemes. The resulting increase in the dependency ratio places a greater burden on these schemes. Many pension funds currently use static lifetables to project future obligations, overlooking the gradual decline in mortality rates. This study explores the application of a time-varying mortality rate model to forecast Tanzanian mortality rates. The time-varying model was successfully employed together with multi state method to project and analyse the funding ratio and cashflow to asset value ratio of the mandatory Tanzania Public Service …

Diffusion-Steered Algorithm For Improving Quality Of Images Generated By Electrical Capacitance Tomography Measurement System, George Nyotoka, Nassor Ally, Josiah Nombo

Tanzania Journal of Science

Electrical Capacitance Tomography (ECT) is a non-invasive, non-intrusive, radiation-free, robust, and cost-efficient measurement system that generates cross-sectional images of industrial operations by measuring differences in dielectric properties within a container. Despite its advantages, the poor quality of reconstructed images limits its applicability. Researchers have explored both non-iterative and iterative methods to address this issue, yet the resulting image quality remains insufficient for high-stakes applications where accurate decision-making is critical. This study proposes a novel algorithm that integrates the ECT model with a diffusion-steered image denoising functional, enhancing the quality of ECT reconstructed images beyond existing methods. Empirical comparisons show that …

Gambaran Klaim Pelayanan Dialisis Di Rumah Sakit Dan Rekomendasi Kebijakan Di Level Daerah: Studi Kasus Kota Pematangsiantar, Syarif Rahman Hasibuan, Chandra Istanti Prasetyo, Ede Surya Darmawan, Vetty Yulianty Permanasari

Jurnal Ekonomi Kesehatan Indonesia

Chronic kidney disease is a global health issue affecting more than 10% of the world's population and poses a significant disease burden, especially in developing countries. In Indonesia, the National Health Insurance program (JKN) has enabled access to dialysis care for patients with chronic kidney failure, but it also presents challenges in sustaining financing. This study aims to analyze the trends in dialysis service claims in Pematangsiantar City during the period from 2017 to 2022 and project the service needs until 2025. The research design is descriptive-analytic, using claim data from BPJS Health related to dialysis procedures. Analysis is conducted …

Assessing The Impact Of Tuberculosis On Economic Growth In Asean Countries: A Conceptual Framework And Panel Data Analysis, Agus Fitriangga, Alex Alex

Jurnal Ekonomi Kesehatan Indonesia

Tuberculosis (TB) remains a major global health issue, particularly in Southeast Asia, where its impact extends beyond public health to affect economic performance. This study evaluates the economic implications of TB incidence on gross domestic product (GDP) growth across eight ASEAN countries from 2000 to 2020. We employed a panel data regression approach, utilizing Common Effect Model (CEM), Fixed Effects Model (FEM), and Random Effects Model (REM) to analyze the relationship between TB incidence and economic growth. The dataset included annual GDP figures, TB incidence rates, foreign direct investment (FDI), labor force size, and trade openness, sourced from international databases. …

The Analysis Of A Co-Dynamic Ebola And Malaria Transmission Model Using The Laplace Adomian Decomposition Method With Caputo Fractional-Order, Akeem Olarewaju Yunus, Morufu Oyedunsi Olayiwola

Tanzania Journal of Science

The study presents a novel mathematical framework for addressing Ebola and malaria concerns in Sub-Saharan Africa that combines Laplace transformation with Caputo fractional order derivative. It takes into account socioeconomic aspects that influence disease dynamics and uses the basic reproduction number to quantify transmission dynamics. Extensive numerical simulations using Maple 18 software are used to investigate the effect of fractional order derivatives on disease dynamics. It shows how the Laplace-Adomian decomposition approach simplifies nonlinear equations and generates control solutions. It emphasizes the necessity of turning discoveries into concrete plans and encourages stakeholders to be proactive in implementing them. Overall, the …

Image Reconstruction Method Based On Iterative Linear Back Projection And Logistic Forward Solver For Electrical Capacitance Tomography Measurement System, Alfred Mwambela, Josiah Nombo

Tanzania Journal of Science

Image reconstruction is one of the important tasks in the application of electrical capacitance tomography (ECT) systems. Though numerous algorithms have been implemented, it is often challenging to obtain satisfactory images in all imaging regions by the use of a single algorithm due to the soft-field nature of ECT systems. The preferred iterative reconstruction algorithms are highly computationally inefficient. A new iterative reconstruction algorithm is proposed which combine iterative Linear Back Projection and Logistic Regression. In this method, the solution to the ECT forward problem is implemented using logistic regression, whereas the ECT inverse problem is solved using the algebraic …

Performance Comparison Of Deep Learning Models In Predicting Hiv Incidences In Tanzania, Zaituni Kaijage, Honest Kimaro, Hellen Maziku

Tanzania Journal of Science

Human immunodeficiency virus infection/acquired immune deficiency syndrome (HIV/AIDS) is a global pandemic that has claimed more than 40 million lives since it was discovered in the late 1970s. In sub-Saharan Africa, including Tanzania. Different measures to combat the diseases have failed to be attained, like the UNAIDS 90-90-90 target, which aimed to reduce HIV by 2020, and it was moved to 2030. The availability of proper tools to control and monitor diseases and ensure proper early intervention is very important. Prediction of disease trends using Machine Learning (ML) models can improve speed towards attaining the UNAIDS targets by providing accurate …

The Global Impact Of The Hlrc Journal On Digital Teaching And Learning Research And Best Practices In Higher Education, Erwin Krauskopf, Gary J. Burkholder

Higher Learning Research Communications

We are pleased to publish the first regular issue (Volume 14, Issue 1) of Higher Learning Research Communications (HLRC) for 2024. Because of our strategic decisions, the journal has advanced in the Scimago journal rank (SJR), which measures the frequency with which content published in a journal was cited in other journals during the three previous years. The SJR provides a numerical indicator of a journal's relative importance and impact within its field. We announce that HLRC has been ranked 612 out of 1,506 journals among all education journals indexed by Scopus, classifying HLRC as within the second quartile of …

Student Partners In Ai Literacy: A Library And Writing Center Collaboration, A. P. Anderson

Velma K. Waters Library Faculty Publications

Student voices are valuable but often overlooked in discussions surrounding the role of AI in higher education. AI Literacy education efforts that treat students only as a potential audience for instruction rather than as potential instructors themselves miss out on the passion, curiosity, and complex questions that students can bring to these conversations. If we center student voices in AI Literacy education discussions, and encourage both their enthusiasm and skepticism, students can become comfortable and confident in leading discussions about AI in the classroom and in their lives. In my proposed poster presentation, I will share insights from an AI …

Hierarchical Quantized Autoencoders: Using Hierarchical Models For Data Compression Across Multiple Domains, Armani Lorenzo Rodriguez

Theses and Dissertations

In the era of vast data processing and transmission, sending data over a channel for downstream operations is a very common occurrence. The bandwidth of this data channel acts as a limiting factor in this operation, capping the amount of data that can be sent over a time period. Therefore, in addition to pursuing advancements in networking technology, there exists a need for more efficient means of data compression. Learned compression is the application of machine learning models to the data compression problem, and in this study, we leverage the ability of neural networks to learn the underlying structure of …

Children's Mathematical Engagement Based On Their Awareness Of Coding Toy Design Features, Joseph Kozlowski, Jessica Shumway, Patricia Moyer-Packenham, Jody Clarke-Midura, Victor Lee

Teacher Education and Leadership Faculty Publications

Tangible coding toys are designed to make coding accessible to young children, and because of their tangible and spatial nature, they are also viewed as tools for engaging children in mathematics. Research is needed to understand children's awareness of toys' design features and how they afford mathematical engagement. We conducted a qualitative study of 106 5-to-6-year-old children completing coding tasks (42 hours of video). Our research questions focused on children's perceptions of design features, mathematical engagement, and how different design features afforded mathematics engagement. Results indicated (a) children perceived a variety of design features across coding toys; (b) children engaged …

Comparison Of Value At Risk Using Historical And Monte Carlo Methods On Pt Xyz Stock Portofolio, Eka Fitriani, Yulial Hikmah, Ira Rosianal Hikmah

Jurnal Administrasi Bisnis Terapan

One way to achieve profits in a company is through investment activities. However, everything has risks. Investing can also be risky. Therefore, the relationship between risk and investment is important because it will influence the determination of investment selection. The problem faced by investors is choosing an efficient portfolio, or a portfolio that provides the smallest risk. This risk can be done by measuring risk, one of which is using the Value at Risk (VaR) measure. Measurement using Value at Risk has several methods that are quite popular, namely the Historical Method, Variance-Covariance, and Monte Carlo. In this research, the …

Ai Literacy Innovations: Chatgpt's Integration Into A First-Year Information Literacy Program, Taylor J. Greene, Douglas R. Dechow

Library Presentations, Posters, and Audiovisual Materials

In the dynamic field of information technology, integration of Artificial Intelligence (AI) literacy into information literacy instruction is now essential to ensure the ethical and productive use of generative AI by our students. This poster demonstrates our innovative approach to embedding AI literacy within the first-year information literacy program at an R2 research university. We used a two-pronged strategy: an “AI Literacy” section in Canvas and practical demonstrations of applying ChatGPT in live library sessions. The Canvas module section equips students with foundational knowledge and critical thinking about using generative AI for research and learning activities. It covers AI fundamentals, …

Fourth Grade Teachers’ Experiences Addressing Low Reading Achievement, Sametria S. Alexander

Walden Dissertations and Doctoral Studies

The research problem addressed in this study was the low reading achievement scores of fourth grade students and fourth grade reading teachers’ struggles raising reading achievement. The purpose of the study was to explore fourth grade reading teachers’ experiences of finding strategies and interventions to improve reading achievement. The theoretical frameworks were Gough and Tunmer’s simple view of reading and Chall’s stages of reading development. The research questions addressed fourth grade reading teachers’ use of strategies and approaches and fourth grade reading teachers’ beliefs about school support. The study used a basic qualitative approach with semistructured interviews from 10 U.S. …

Teacher Development- Going Beyond Conventional To A Collaborative Approach, Scott Robinson

Graduate Teacher Education

Professional development (PD) is a foundation of growth for K-12 educators. PD is the mechanism that allows teachers to improve their teaching by learning new materials or strategies. Teacher learning is essential in providing students with a high-quality education. Not all PD models are equal or designed the same way. There are many types of PD, and some models significantly impact teacher motivation, effectiveness, and student outcomes. Teachers expressed that traditional methods of PD were not meeting their needs and that a more collaborative approach would provide more opportunities for professional growth. Studies indicated that while a moderate amount of …

Control And Management Of The Balance Of Active And Reactive Power In A Power Supply System With A Solar Power Plant, Narzullo Nuriddinovich Mirzoyev, Siroj Sobirovich Nurov

Chemical Technology, Control and Management

This article discusses the development of a measurement and control system for monitoring and managing the balance of active and reactive power at power plants based on “Green” energy sources. Monitoring and management of the balance of active and reactive power based on a measurement and control system, calculated expressions are developed to solve the problem of reactive power compensation when transmitting electricity at power plants based on “green” energy sources. Reactive power is calculated based on measured active power, and combined reactive power sources generate the reactive power required by the network based on control signals. Schemes for connecting …

Assessment Of Metrological Errors Of Recognition Metrics In The Intelligent Control And Regulation System Of The Cotton Harvesting Machine, Erkin Uljaev, Utkirjon Murodillaevich Ubaydullaev, Azizjon Abdulla Ugli Abdulhamidov

Chemical Technology, Control and Management

This article presents a method for assessing the error of metrics of an intelligent system for monitoring and regulating the width of the working gap of the harvesting apparatus of a cotton picker. To assess the error, the calculation of the average value of the standard deviation of metrics, absolute systematic and random errors, as well as absolute and relative total errors are used. The results of these calculations will allow us to determine the accuracy of the recognition system and opportunities for its improvement.

Structural And Parametric Identification Of Recycling Systems, Khusan Igamberdiev, Madina Mirxalilovma Fozilova

Chemical Technology, Control and Management

The issue of identifying recirculation systems with a specific control loop, in which information and control information about various technological processes circulate, is being considered. A methodology for identifying recirculation systems has been developed, based on algorithms for structural identification of the model based on the results of assessing the sensitivity of the optimum of control parameters and a fuzzy inference algorithm based on production rules that contribute to solving the problem of parametric identification.

Synthesis Of An Adaptive Neuro-Fuzzy Control System For Steam Generator Temperature, Isomiddin Xakimovich Siddikov, Dilnoza Maxamadjanovna Umurzakova

Chemical Technology, Control and Management

This paper is devoted to the modeling and synthesis of an adaptive neuro-fuzzy control system for steam generator temperature. Temperature control systems play an important role in industry because accurate and stable control is a prerequisite for the efficient operation of steam systems. Traditional control methods based on mathematical models and fixed parameter controllers may have limitations in providing optimal performance and adapting to changing operating conditions. The paper proposes a synthesized system combining fuzzy logic and adaptation methods to achieve more accurate and stable temperature control. A detailed structural diagram of the system, modeling, and tuning methods are presented. …

Research Of The Fuzzy Control System For Adjusting Thread Tension During The Warping Process, To'xtamurod Hayitmurodovich Avezov, Zokhid Ergashboyevich Iskandarov

Chemical Technology, Control and Management

The paper considered issues of research into a fuzzy control system for the warping process. During the warping process, the reasons that cause defects in the final finished product have been studied, firstly (remove this word) which are thread breakage, thread tangling, the formation of loops on or under the belt, hanging loose threads and similar factors. To study the warping process, its mathematical model is constructed. Kinematic parameters of stationary movement corresponding to the equilibrium mode were determined by solving the nonlinear functional matrix - equation of movement. The process of breakage the warp of the threads under oscillation …

Decision-Making Algorithms For Drilling Instrument Control Systems, Fuzayl Fozil Ugli Odilov

Chemical Technology, Control and Management

The control of the movement of the drilling tool and the structure of the well are considered. An effective control algorithm for drilling systems that provides control of well trajectory parameters is analyzed. In technological processes, it is necessary to control several parameters or several systems at the same time. It is considered necessary to create decision-making algorithms for the formation of managerial effects for the control system of such technological processes. The controlled oriented type of the bottom of the drill string was analyzed. Work was carried out on the decision-making algorithm for the processing of control effects. The …

Using A Neural Network To Remove Noise From Images, Anvar Asatilloyevich Ravshanov

Chemical Technology, Control and Management

This article proposes modern approaches to the problem of noise reduction in images using neural networks and also analyses the possibilities of noise reduction using neural networks. The convolutional neural network model and the Mediana, Sobel filter were considered for image denoising. The quality improvement of the trained neural network and the comparison with classical noise reduction methods have been carried out.

Association Of Longitudinal Changes In 24-H Blood Pressure Level And Variability With Cognitive Decline, Jesus D. Melgarejo, Kristina Vatcheva, Silvia Mejia-Arango, Sokratis Charisis, Luis J. Mena, Rosa P. Mavarez, Antonio Garcia, Ney Alliey Rodriguez, John Blangero, Gladys Maestre

School of Medicine Publications

Objective:

A high office blood pressure (BP) is associated with cognitive decline. However, evidence of 24-h ambulatory BP monitoring is limited, and no studies have investigated whether longitudinal changes in 24-h BP are associated with cognitive decline. We aimed to test whether higher longitudinal changes in 24-h ambulatory BP measurements are associated with cognitive decline.

Methods:

We included 437 dementia-free participants from the Maracaibo Aging Study with prospective data on 24-h ambulatory BP monitoring and cognitive function, which was assessed using the selective reminding test (SRT) and the Mini-Mental State Examination (MMSE). Using multivariate linear mixed regression models, we analyzed …