Digital Commons Network^™

Interprofessional Collaboration To Create Visual Supports In Preschool Classrooms: Perspectives Of Speech-Language Pathology Graduate Students, Shelby L. Klick

Master's Theses and Doctoral Dissertations

This study explored the perspectives of speech-language pathology (SLP) graduate students following participation in a Preschool Visual Supports interprofessional education (IPE) project. Though IPE initiatives have become more prevalent in healthcare, they are limited in preparing future education professionals. Using qualitative inquiry, this study aimed to explore and assess the impact of an interdisciplinary collaborative project and how participation might influence SLP students’ future approach to creating visual supports for young children and their confidence to do so. Thematic analysis was used to identify themes across five semi-structured interviews conducted with SLP graduate students at a Midwest university. The data …

How Math Games Engage Parents With Children, Greg M. Williamson

Master's Theses and Doctoral Dissertations

This research study begins to explore how the use of math games focused on foundation skills can potentially support parents and families in mathematics interactions. The primary goal was to examine parents' perceptions of the impact of math games on their engagement with their children. In addition, embedded guides were provided for parents to engage in mathematical discourse, and support specific math strategies. The qualitative study involved the families of six students who were entering fourth grade and attending a summer-school program. The students and their families engaged in a six-week intervention where they received two math board games and …

Digitized Asic (Adaptation, Standardization, Integration, And Compliance) Framework: An Innovation For Optimizing Technologies And Innovations For Medical And Higher Education., Joshua Owolabi

PCOM Scholarly Works

This article serves several specific purposes: Presenting transferable information on transforming innovative ideas into educational products with practical applications; showcasing a digitized version of a leading innovation aimed at optimizing technologies and innovations in medical education, health professions education, and higher education; advancing an evidence-based approach to integrating innovations into educational ecosystems and promoting education through innovations and technologies. A 10-step approach to developing the ASIC framework (ASIC stands for Adaptation, Standardization, Integration, and Compliance) is presented, with explanations and illustrations of the processes and activities involved. Empirical evidence and sound principles are provided in support of activities to assure …

Winter 2025: Elevate

The Weldon Times

A student-run publication from the Schulich School of Law at Dalhousie University.

Co-Editors in Chief: Faith Thomson, Kimberly Gilson

Predicting Early Hospital Readmissions For Diabetic Patients Using Machine Learning, Amanda Ferraz, Leonardo Oliveira

ICT

This project applies machine learning to predict whether diabetic patients will be readmitted to a hospital within 30 days of discharge. Early readmissions are a costly and critical issue in healthcare, often signalling gaps in post-discharge care and risk management. Diabetic patients face unfair high readmission rates compared to the general population. According to the CDC Diabetes Report Card 37.3 million people in the U.S. or 11.3% of the population had diabetes as of 2019 (CDC, 2021). Our goal here is to develop a binary classification model capable of flagging high risk patient (< 30-day readmission) based on their clinical, demographic, and administrative data. This lets healthcare institutions to take measures,

European Air Pollution And The Proposed Timelines Of Implementing The World Health Organization 2021 Air Quality Guidelines Ca3., Lukia Hartin

ICT

This research examines Ireland’s air pollution trends and evaluates whether current reductions in PM2.5, PM10, and NO₂ are sufficient to meet the WHO 2021 Air Quality Guidelines by 2040. Using four years of EPA-validated pollutant data (2020–2023), alongside Building Energy Rating (BER) and national transport datasets, the study applies the CRISP-DM methodology to guide analysis, preprocessing, modelling, and evaluation. Extensive data cleaning and alignment were required due to inconsistent station coverage, varying formats, and missing values. Forecasting models—including Random Forest, Gradient Boosting, SVR, and linear regression—were assessed using MSE, R², and trend significance to project pollutant levels across different Irish …

Investigation Of Photocathodic Corrosion Protection Of Zno/Zns Thin Film For Aisi 304 Stainless Steel In 3.5 Wt% Nacl Solution, Soravid Veerapong, Naw Blessing Oo, Boossayamas Dachbumroong, Parichart Chaum, Thanate Na Wichean, Oratai Jongprateep, Naray Pewnim, Gasidit Panomsuwan, Ratchatee Techapiesancharoenkij

Journal of Metals, Materials and Minerals

Photocathodic protection is an alternative cathodic protection technique to protect metals by photo-generated electrons from a coupled semiconductor film under solar light. In this report, ZnO nanorods and heterostructure ZnO/ZnS nanorod films  on FTO substrates were studied for their photocathodic protection for 304 stainless steels (304 SS) in a 3.5 wt% NaCl solution.  The ZnO and ZnO/ZnS nanorods were fabricated on FTO substrates by spray pyrolysis and hydrothermal processes. The photocathodic performances of the ZnO and ZnO/ZnS photoanodes coupled with 304 SS samples were examined by Open-Circuit Potential (OCP), polarization curve analysis, and electrochemical impedance spectra (EIS). The ZnO/ZnS photoanodes …

Investigation Into Parameters Affecting The Synthesis Of Hybrid Gold Nanoparticle/ Nitrogen-Doped Carbon Dot Colloids, Thammika Srisaman, Anyarat Watthanaphanit

Journal of Metals, Materials and Minerals

This study reports a two-step synthesis method for producing hybrid nanoparticles composed of gold nanoparticles (AuNPs) and nitrogen-doped carbon dots (CDs). Initially, we employed hydrothermal synthesis to fabricate CDs derived from mangosteen peel extract, which exhibits green light emission. Subsequently, the hybrid AuNPs/CDs were synthesized by inducing plasma in a solution containing CDs and a gold precursor, namely gold(III) chloride trihydrate. Our primary aim was to investigate the key parameters influencing the synthesis process. We assessed the colloidal properties of the AuNPs/ CDs by introducing a stabilizer, specifically sodium alginate, and examined how factors such as the presence of sodium …

Low-Cost High Performance Sustainable Triboelectric Nanogenerator Based On Laboratory Waste, Archana Panda, Kunal Kumar Das, Kushal Ruthvik Kaja, Venkataramana Gandi, Sunit Gourav Mohanty, Basanta Kumar Panigrahi

Journal of Metals, Materials and Minerals

The production of waste materials in laboratories is an unavoidable consequence of diverse experiments and activities. These materials can range from chemicals, solvents, and biological samples to electronic components, glassware, and plastics. Typically, this waste is classified into hazardous and non-hazardous categories, requiring careful disposal to avoid environmental and health risks. These can be repurposed for energy harvesting methods, such as using polymers in triboelectric nanogenerators (TENGs) or recycling metallic waste for electrodes. This approach reduces waste while advancing sustainable energy solutions. This technique demonstrates remarkable efficiency in utilizing diverse waste materials to transform various forms of mechanical energy into …

Efficacy Of Bifeo3 And Bi4ti3o12 Towards Photocatalytic Degradation Of Mg And Mb Dyes: A Comparative Study Under Solar Irradiation, Rasmirekha -, Rishabh Kamal, Debapriya -, Suresh Kumar Dash

Journal of Metals, Materials and Minerals

Bismuth-based perovskite material has been used as promising photocatalysts for photo catalytic degradation of toxic dyes with tailored crystallites and fine-tuned band gap for superior activity. BiFeO3 and Bi4Ti3O12 were synthesized by a simple sol-gel method and their crystal structure, morphology, and optical property were characterized by XRD, SEM, TEM, FTIR, EDS and UV–DRS. The XRD pattern exhibits the formation of rhombohedral and orthorhombic phase of bismuth ferrite and bismuth titanate. The study confirms the formation of non-uniform BiFeO3 and Bi4Ti3O12 nanoparticles with uniform particle distribution, with band gap energy (Eg) of 2.2 eV and 2.9 eV, respectively, from UV-DRS …

The Effect Of Fe-Nimnmo High Entropy Alloy Electrode On Enhancing The Weldability And Mechanical Properties Of Railway Steel 900a, Sarawut Chaowakarnkool, Kanokwan Uttarasak, Sittipong Jaipayuk, Narin Jantaping, Man Tuiprae

Journal of Metals, Materials and Minerals

The rail transport system is essential for moving passengers and heavy goods over long distances, with steel 900A being a common material used for rail tracks in Thailand. Prolonged exposure to heavy loads and variable environmental conditions can lead to rail track damage known as "engine burn”, which results from friction between the train’s wheels and the rail. The flux-cored arc welding (FCAW) process is employed to repair these burns due to its use of readily available electrode wires and the efficiency of the repair. However, welding high-carbon steel like rail steel 900A poses challenges, such as a tendency to …

Review On Surface Engineering Of Nmc For High Performance Of Lithium-Ion Batteries, Pongsakorn Kantichaimongkol, Thanyalux Wanotayan, Jiaqian Qin

Journal of Metals, Materials and Minerals

The lithium-ion battery stands as a highly promising energy storage system. Among its key components, the cathode material—particularly lithium nickel manganese cobalt oxide (LiNiMnCoO₂), or NMC—is of great importance due to its high specific capacity and cost-effectiveness. Despite its advantages, NMC faces certain challenges, with limited cycle performance being one of the most critical issues. To address this issue, extensive research has been dedicated to surface modification strategies for NMC materials. Studies have identified two primary approaches, doping and coating, both of which have proven effective in enhancing the material's long-term stability. This work systematically examines, categorizes, and compares recent …

Synergistic Effects Of Co-Ni Nanoalloys On Sio2@Tio2: A Novel Approach To Photocatalytic Tetracycline Degradation, Pratyush Kumar Sahu, Alaka Rath, Aslisha Champati, Ashish Madual, Pravat Manjari Mishra, Abanti Pradhan, Brundabana Naik

Journal of Metals, Materials and Minerals

To develop a cost-effective alternative to noble metal catalysts for photocatalysis, we synthesized a series of bimetallic Co-Ni nanoalloys on core-shelled SiO2@TiO2 nanostructures via a chemical reduction approach. The research demonstrates the photocatalytic behaviour of the Co-Ni alloy-enhanced SiO2@TiO2 (ST-Co, Ni) hybrid nanocatalyst, focusing on its crystalline structures, morphological shapes, chemical conditions, and optical properties, utilizing techniques such as X-ray diffraction, field emission scanning electron microscopy, UV-visible diffuse reflectance spectroscopy, photoluminescence spectroscopy, transmission electron microscope, and electrochemical analysis. The catalyst was evaluated for its effectiveness in degrading tetracycline, an overused antibiotic that persists in aquatic environments and is known for …

Studies Of Structural, Microstructural, Dielectric, And Electrical Characterization Of Binaznmoo6 Double Perovskite, Swati Panda, Supriya Barik, Ritu Purna Sahu, Adwit Prasad Sahu, S. Mishra, S. K. Parida

Journal of Metals, Materials and Minerals

This study investigates the structural, microstructural, dielectric, and electrical properties of BiNaZnMoO₆ (BNZM) ceramic synthesized using a conventional solid-state reaction method. Preliminary structural analysis using X-ray diffraction (XRD) suggests orthorhombic crystal symmetry. Scanning electron microscopy (SEM) micrographs reveal a uniform distribution of well-grown grains with well-defined grain boundaries, which may contribute to the enhanced dielectric properties. Energy dispersive X-ray spectroscopy (EDX) analysis confirms the presence of all constituent elements Bi, Na, Zn, Mo, and O in the studied sample. Dielectric spectra analysis as a function of frequency and temperature indicates the formation of high-quality dielectric materials, evidenced by a high …

Graphitic Carbon Nitride Loaded Bi4o5i2 For Elevated Photocatalytic Tetracycline Degradation, Subhasish Mishra, Barsha Marandi, Kali Sanjay, Rashmi Acharya

Journal of Metals, Materials and Minerals

As a robust photocatalyst, Bi4O5I2 have has attracted significant scientific interest owing to its narrow bandgap energy, escalated electronic properties and high stability. Nonetheless, the unfavourable band structure and higher recombination of excitons have restricted its diversified photocatalytic applications. In this context, binary heterojunction construction using Bi4O5I2 could be considered an effective strategy for spatial charge carrier separation across the hetero-interface, leading to an enhanced activity. In this study, we have prepared Bi4O5I2/g-C3N4 Z-scheme hetero-structures via a wet impregnation strategy that preserves the spherical structure of Bi4O5I2. The phase purity, chemical bonding, morphology and microstructure of the composite were confirmed …

Solar Radiation Assisted Photocatalytic Degradation Of Congo Red Using Ce Doped Lacoo3, Rishabh Kamal, Rasmirekha Pattanaik, Debapriya Pradhan, Suresh Kumar Dash

Journal of Metals, Materials and Minerals

A viable sol-gel synthesis technique was used to synthesize LaCoO3 and Ce doped LaCoO3 for degradation of congo red dye taking a renewable source of light i.e solar radiation. The crystalline structure, morphology, and optical properties of the synthesized catalysts were characterized by X-ray diffraction (XRD), X-ray photoelectron spectroscopy (XPS) analysis of Ce-doped LaCoO₃ confirmed the presence of La (3d), Ce (3d), Co (2p), C (1s), and O (1s) and their valence states in the perovskite matrix, Fourier-transform infrared spectroscopy (FTIR), scanning electron microscopy (SEM), and ultraviolet diffuse reflectance spectroscopy (UV-DRS). The XRD analysis with a prominent diffraction peak detected …

Green-Synthesized Yttrium-Doped Cerium Oxide Nanoparticles: A Promising Optical Material, Sasmita Sarangi, Nibedita Nayak, Binita Nanda, Tapas Sahoo

Journal of Metals, Materials and Minerals

This work focuses on the green synthesis, characterization, and optical properties of yttrium-doped cerium dioxide (CeO2) nanoparticles. A green approach was adopted using Acacia concinna fruit extract as surfactant and stabilizing agent. Their structural, morphological, and physical-chemical properties were characterized using different analytical techniques, like XRD, FE-SEM, FTIR, PL, Raman, UV-Visible Spectroscopy. XRD study validated the structure of cubic fluorite-type structure of CeO2 nanoparticles, with the average crystallite size ranging between 7-15 nm. Raman spectroscopy validated this structure with F2g band observed at 463 cm−1. FESEM images showed irregular spherical morphologies with grain sizes in the range of 50-60 nm. …

Microwave Absorption Properties Of Porous Activated Carbon/Nickel Oxide Composites Derived From Coconut Husks, Mohamad Zul Aqiman Shukeri, Nor Zakiah Yahaya, Ezzan Afifah Zainuddin, Nazri Mahmud, Liyana Zahid, Hasliza A. Rahim

Journal of Metals, Materials and Minerals

Porous Activated Carbon (AC) is a promising material for microwave absorbing materials, showing potential in communication and modern warfare. The study explores the process of creating porous AC from coconut husks using hydrochloric acid and carbonization at varying temperatures, followed by doping AC with nickel oxide to create an AC/NiO polymer composite with varying thicknesses. These composites are compared to AC composites loaded in a paraffin matrix. The dielectric and microwave (MW) properties of the AC/NiO and AC polymer composites at various thicknesses were analyzed using a Performance (PNA)-X Network Analyzer. The study also examines the carbon content and porosity …

Eco-Friendly Synthesis Of Flower-Like Hierarchical Structure Of Cuo Nps For Advancing Photocatalytic Efficiency And Antibacterial Applications, Yodchai Tangjaideborisut, Shanmugam Shanmugam, Supakorn Boonyuen, Govindasamy Siva, Prema Yugala, Joon Ching Juan, Choowin Phanawansombat, Atchariya Pitintharangkul, Seerangaraj Vasantharaj, Pornpan Pungpo, Pariya Na Nakorn

Journal of Metals, Materials and Minerals

In recent decades, environmental pollution caused by organic dyes and pathogenic microorganisms has posed significant challenges to both ecological and public health. Therefore, the development of multifunctional materials capable of simultaneously degrading dyes and exhibiting antibacterial properties is crucial for effective environmental remediation. Combining photocatalytic dye degradation with antibacterial activity offers a promising approach to address these dual concerns in a single process. The present study investigates the copper oxide nanparticles (CuNPs) were prepared by green synthetic method using bamboo extract for degradation of methylene blue and in inactivation of biological pathogens. The green synthesized CuONPs were characterized various spectroscopic …

Structural Tuning Of Bioi Toward Bi O /Agi Heterostructures Via Room-Temperature Ion Exchange For Improved Photocatalytic Activity, Varunya Atimayulerd, Sorawit Thueanbangyang, Kittiyaporn Singsumphan, Ganyaporn Wongwaen, Cheewita Suwanchawalit, Montri Aiempanakit

Journal of Metals, Materials and Minerals

In this work, a bismuth oxide/silver iodide (Bi2O3/AgI) heterojunction photocatalyst was successfully fabricated via a room-temperature ion exchange process using bismuth oxyiodide (BiOI) as a morphology-directing precursor. Building upon our previous work on solvent-modulated BiOI nanostructures, this study employs a chemical transformation route to develop interfacially connected heterostructures while preserving key morphological features. Structural, morphological, and optical characterizations, including X-ray diffraction, field-emission scanning electron microscopy, energy-dispersive X-ray spectroscopy, Fourier-transform infrared spectroscopy, and ultraviolet–visible diffuse reflectance spectroscopy, provided supporting evidence for the successful formation of Bi2O3/AgI heterojunctions with likely close interfacial contact. The optimized Bi2O3/AgI composite with a 50:50 mass ratio …

Facile Bio-Synthesis Of Cerium Oxide Nanoparticles, Characterization And Their Photocatalytic Potential In The Degradation Of Real Tannery Wastewater, Ganeshkumar Govindasamy, A. Babu Ponnusami

Journal of Metals, Materials and Minerals

The sustainable metal oxide photocatalysts using plant extract presents a viable alternative to conventional chemical synthesis techniques. In this study, spherical shaped cerium oxide nanoparticles were synthesized using ammonium ceric nitrate and Peepal Leaves (PL) extracted and used as a photocatalyst to remove hexavalent chromium and chemical oxygen demand from actual tannery wastewater. The characterization of cerium oxide nanoparticles was carried out using UV-Visible spectroscopy, X-ray diffraction, Fourier-transform infrared spectroscopy, Brunauer-Emmett-Teller surface area analysis, Field Emission-Scanning Electron Microscopy with energy-dispersive X-ray spectroscopy, Raman analysis, High Resolution-Transmission Electron Microscopy and Zeta potential analysis. The band gap energy of 3.25 eV was …

Dogs Emotion System, Muhammad Anas Baig

ICT

For our capstone project, we built a machine learning model that can look at pictures of dogs and figure out how they’re feeling, like if they’re happy, sad, or just chill. The idea came from how important pets are in people’s lives these days and how cool it would be to actually understand their emotions better using tech. This system will allow users to upload images of dogs, which are then analysed by a trained model to classify the dog's emotional states such as happy, sad, or neutral. We followed the CRISP-DM process to build it, which basically means we …

Cancer Registry Newsletter Vol. 06, Cancer Registry

Cancer Registry, AKUH Archives

• Messages
• Cancer Registry Team
• Cancer Committee Members
• Cancer Registry AKUH
• Our Mission
• Cancer Report
• Age-Group Distribution of Top Five Cancers
• Total Count with Gender Breakdown
• Top Ten Males 2025
• Top Ten Females 2025
• Data Release
• Top Ten Malignancies in Children (2025)
• Distribution of Malignancies According to the Geographical Area of Patients
• Poster Presentation
• Ongoing Projects
• Karachi Cancer Registry
• Implementing a Real-Time Cancer Registry Model
• Cancer Registry Website
• Quarterly Reporting of Cancer Registry Data
• National Media Highlights Scoping Review on Cancer Registries in Pakistan
• Achievements
• Activities
• Head and Neck Cancer Awareness Session 2025
• HIMS Appreciation Lunch 2025
• Independence Day Celebration
• Department …

Customer Service Support. Utilizing Machine Learning To Classify, Prioritize And Summarize Issues., Hoai Nhan Nguyen

ICT

This capstone project investigates the application of machine learning and natural language processing (NLP) to enhance customer support operations through automated ticket classification, prioritization, and summarization. Using the multilingual Customer Support Emails dataset from Kaggle, the project follows the CRISP-DM methodology, performing extensive data cleaning, preprocessing, feature engineering, and class balancing. Five machine learning models—Decision Tree, KNN, LinearSVC, Naive Bayes, and Random Forest—were evaluated using hyperparameter tuning, cross-validation, confusion matrix analysis, and learning curves. LinearSVC demonstrated the strongest performance for both queue and priority classification, achieving accuracies of 89.8% and 81.2% respectively, with consistent generalization across folds. For summarization, extractive …

Dogs Emotion System- Poster, Muhammad Anas Baig

ICT

This project is all about a deep learning-based “Dog Emotion System” that can figure out how dogs are feeling just by looking at their faces. We used a balanced set of 4,000 dog images with four different emotion categories and followed the CRISP-DM process to build it. The model was trained from scratch using a Convolutional Neural Network (CNN) without any pre-existing models. It is deployed using Steamlit, where people can upload pictures of their dogs and get their emotional state predicted in real time. The goal of this tech is to make it easier for pet owners to understand …

Comparison Of Statistical, Machine Learning, And Deep Learning Models For Time-Series Forecasting Using Weather Data From Dublin, Ireland., Erick Eduardo Rios Treviño

ICT

This study compares three time-series forecasting paradigms—statistical, machine learning, and deep learning—using ten-years of historical weather data from Dublin. The objective is to evaluate the performance of Prophet, XGBoost, and LSTM when forecasting daily solar radiation under multiple preprocessing strategies. An extensive data analysis was conducted, including descriptive statistics, inferential testing, stationarity assessment, outlier detection, feature selection, and exploratory visualisation. These steps revealed strong annual seasonality, nonlinear feature relationships, and variability across meteorological variables, informing the modelling framework and feature-engineering decisions. Four experiments were conducted using cleaned data, differenced data, log-transformed data, and cross-validation. Results show that XGBoost achieved the …

Enhancing Insider Threat Detection Through A Hybrid Approach Using Different Artificial Intelligence Techniques., Jose Roberto Da Silva Dure

ICT

Insider threats pose significant challenges in cybersecurity due to their origin from individuals with legitimate access. Traditional defenses often fail to detect malicious behavior embedded within normal activities. This study proposes a hybrid artificial intelligence framework that integrates unsupervised anomaly detection, supervised and ensemble learning, and deep learning to enhance insider threat detection. Using the CERT 4.1 dataset, features encompassing temporal, behavioral, network, and psychometric aspects were engineered. Anomaly detection models informed supervised and ensemble classifiers, while a multi-input deep learning architecture captured sequential and contextual patterns. Performance evaluation using ROC-AUC, precision, recall, F1-score, and cost-sensitive analysis demonstrates that the …

Strategic Analysis Of Employment Permit Statistics And Predictive Analytics For Workforce Planning In Ireland, Amy Souza, Thaynna Vieira

ICT

By analysing historical employment permit data from Enterprise.gov.ie (Enterprise.gov.ie, 2024), this project has the aim to use Data Analytics and Machine Learning to make predictions of employment permits trends across sectors and companies, providing insights to optimize workforce planning for Recruitment Agencies and guide international job seekers requiring work visas. The insights gained are intended to enhance strategic recruitment practices and empower job seekers to make informed career decisions in Ireland’s competitive labour market.

Predicting Repeat Purchases In E-Commerce Using Interpretable Machine Learning, Zahid Bhatti

ICT

This project investigates the prediction of repeat purchase behaviour in e-commerce using machine learning, with a focus on balancing predictive accuracy and interpretability. Large volumes of transactional and behavioural data are analysed to identify customer-level features that drive loyalty and repeat purchases. Various supervised learning models, including Random Forests and Logistic Regression, are evaluated for predictive performance, while SHAP (SHapley Additive Explanations) is employed to provide both global and local interpretability. The study aims to generate actionable insights for customer relationship management and marketing strategy, demonstrating how advanced predictive models can support informed business decisions without sacrificing transparency.

Predictive Analytics For Customer Churns In Financial Services., Thant Thiha

ICT

This project presents a customer churn prediction analysis in the telecommunications sector, achieving an ROC-AUC of approximately 0.86 using statistically validated features and interpretable AI models. Key churn drivers identified include the number of products held, customer age, and geographic location. Ensemble models, such as Random Forest and Gradient Boosting, provided the highest predictive performance. Ethical AI principles were applied to ensure fairness, transparency, privacy, and accountability. Business insights derived from the analysis inform targeted retention strategies, prioritising multi-product users, specific age groups, and geographic segments. Deployment recommendations include the tuned Random Forest model with ongoing monitoring, governance, and future …