Digital Commons Network^™

Qualitative Study: Storytelling For Complex Concepts And Critical Thinking. Nurse Educators' Experience, Carine A. Mcdonald

Dissertations

Current patient acuity necessitates nurses' need to think critically and problem-solve in care facilities. The nurse educators' perspectives on how storytelling impacts students' critical thinking and conceptual learning are crucial. This study explored nurse educators' experiences who employed storytelling teaching strategies in the classroom for critical thinking skills and learning complex concepts. The research question was, "What are the experiences of nurse educators as they use instructional storytelling in the classroom for complex concepts and critical thinking?" Three associated sub-questions were: "How do nurse educators describe the process of incorporating storytelling in their classrooms?" "What challenges are described by nurse …

Optimizing Medical Iot Disaster Management With Data Compression, Nunudzai Mrewa, Athirah Mohd Ramly, Angela Amphawan, Tse Kian Neo

Journal of Informatics and Web Engineering

In today's technological landscape, the convergence of the Internet of Things (IoT) with various industries showcases the march of progress. This coming together involves combining diverse data streams from different sources and transmitting processed data in real-time. This empowers stakeholders to make quick and informed decisions, especially in areas like smart cities, healthcare, and industrial automation, where efficiency gains are evident. However, with this convergence comes a challenge – the large amount of data generated by IoT devices. This data overload makes processing and transmitting information efficiently a significant hurdle, potentially undermining the benefits of this union. To tackle this …

Efficient Primary Education Service Delivery In The Local Nigerian Government, Kezia Igwebueze

Walden Dissertations and Doctoral Studies

The inefficient service delivery of local government in Nigeria in the provision and maintenance of primary education and educational facilities is problematic. There is the dearth of instructional, recreational, residential, and social facilities in the learning environment that enable teachers and learners to carry out their work and assimilate efficiently. The purpose of this qualitative case study was to explore the determining factors that influence the culture of inefficiency in the primary education service delivery function across local government councils in Nigeria and investigate how the culture of efficiency can be recreated. Sutherland’s differential association theory provided the theoretical foundation …

Pediatric Spinal Ependymoma With Chromothripsis Of Chromosome 6: A Case Report And Review Of The Literature., Keela R. Scott, Melissa Gener, Elena Repnikova

Manuscripts, Articles, Book Chapters and Other Papers

BACKGROUND: Ependymomas are the third most common central nervous system tumor in the pediatric population; however, spinal ependymomas in children are rare. Ependymomas affecting the spinal cord most frequently occur in adults of 20-40 years of age. The current World Health Organization classification system for ependymomas is now composed of ten different entities based on histopathology, location, and molecular studies, with evidence that the new classification system more accurately predicts clinical outcomes.

CASE PRESENTATION: We present the case of a 16-year-old Caucasian female patient with a history of type 2 neurofibromatosis with multiple schwannomas, meningioma, and spinal ependymoma. Chromosome analysis …

Workplace Factors That Motivate Organizational Representative Employees In Nigeria, Ebenezer Oladapo Sowunmi

Walden Dissertations and Doctoral Studies

Proper identification of motivational factors may assist in understanding how employees may be motivated to maximize their full potential. The purpose of this qualitative case study was to investigate the workplace motivating factors influencing organizational representative employees in Nigeria, while recognizing the critical role of employee motivation in organizational success. The research questions addressed the factors that drive organizational representative employees, focusing on intrinsic, extrinsic, and social motivators in the Nigerian workplace. Maslow’s hierarchy of needs and Herzberg’s two-factor theory were used to frame the study. Data were collected from in-depth interviews with 16 organizational representative employees. Findings from thematic …

3d Learning Spaces For Second Language Learning, Emma Olson

Honors Program: Senior Projects (Public)

Many language teaching techniques and approaches have been used and adapted to culminate in the development of Communicative Language Teaching, which focuses on developing functional proficiency and communicative competence. 3D learning spaces are becoming increasingly more popular for language learning as well, and more specifically, socially-based virtual worlds (or “metaverses”) make good educational tools for developing communicative competence, as they engage learners in situational and experiential learning through increasing authenticity, lowering anxiety levels (i.e., affective filters), and allowing for the development of tools that can support both structured and spontaneous speaking opportunities. After a brief literature review, this thesis therefore …

A Sense Of Touch: Asics Are The Receptor For A Proton Synaptic Messenger Between Merkel Cells And An Afferent Nerve, Public Relations

Browse All News

No abstract provided.

Resolving The Topology Of Encircling Multiple Exceptional Points, Chitres Guria, Qi Zhong, Sahin Kaya Ozdemir, Yogesh S.S. Patil, Ramy El-Ganainy, Jack Gwynne Emmet Harris

Michigan Tech Publications

Non-Hermiticity has emerged as a new paradigm for controlling coupled-mode systems in ways that cannot be achieved with conventional techniques. One aspect of this control that has received considerable attention recently is the encircling of exceptional points (EPs). To date, most work has focused on systems consisting of two modes that are tuned by two control parameters and have isolated EPs. While these systems exhibit exotic features related to EP encircling, it has been shown that richer behavior occurs in systems with more than two modes. Such systems can be tuned by more than two control parameters, and contain EPs …

Photovoice: A Method To Interrogate Positionality And Critical Reflexivity, H. Shellae Versey

The Qualitative Report

Photovoice is a visual method for interrogating subjective perspectives. Rather than solely relying on investigator-developed tools, photovoice allows participants to inform research by “showing” their lived realities through photographs, resulting in a more collaborative, inclusive, and community-informed process. Though applicable to a wide range of social science research, photovoice remains relatively underutilized, especially as a tool for interrogating reflexivity. Given its power to reveal the unseen, this paper considers the potential for photovoice as a self-reflexive tool by turning the lens towards the investigator. Though typically used by the researcher to enhance transparency and navigate power differentials in community-based participatory …

What Is Love? On Love, Lust, And Limerence, Philosopher's Discussion Group

The Philosopher's Stone

• What is Love? On Love, Lust, and Limerence

Energy And Angular Distributions In 250 Ev Electron And Positron Collisions With Argon Atom, K. Tőkési, Robert D. Dubois

Physics Faculty Research & Creative Works

We present energy and angular differential cross sections for single ionization in collisions between electrons and positrons with argon atoms at 250 eV. We treat the collision classically using the three-body approximation where the target atoms are described within the single active electron approximation using a Garvey model potential and only the outermost electron is involved in the collision dynamics. Our present classical trajectory Monte Carlo model is shown to describe the ionization cross sections reasonably well and agree with existing experimental data. We show that the energy distributions, both for electron and positron impact, have the same shape and …

Editorial Preview, Su-Cheng Haw

Journal of Informatics and Web Engineering

This editorial highlights all 19 papers in the February issue that deal with the practical aspects of Machine Learning (ML), Artificial Intelligence (AI), Data Mining (DM), the Internet of Things (IoT), and other topics in Computer Science. This issue also includes suggestions for several worthwhile works that deserve further research. With effective from this volume, we will be publishing triannually in our February, June and October issues.

Term Standardisation With Lda Model To Detect Service Disruption Events Using English And Manglish Tweets, Noraysha Yusuf, Maizatul Akmar Ismail, Tasnim M.A. Zayet, Kasturi Dewi Varathan, Rafidah Md Noor

Journal of Informatics and Web Engineering

Rapid transit is one of Malaysia's most important transportation modes, where commuters use public transportation to travel. Any disruption in the rapid transit service affects their daily routines. Therefore, detecting such service disruption has become fundamental. In this study, the disruption in Malaysia's rapid transit service was assessed using English and Manglish (a combination of English and Malay) tweets through Latent Dirichlet Allocation (LDA). The gathered tweets were classified into event and non-event tweets and LDA was applied to the event tweets. Manglish event tweets were pre-processed using the proposed term standardisation technique. As a result, LDA has proved its …

Modelling Of Virtual Campus Tour In Minecraft, Liyana Tan Lin, Han-Foon Neo

Journal of Informatics and Web Engineering

Virtual tours have revolutionized the way to explore and experience places from the comfort of our own home. Through advanced technology and immersive digital platforms, virtual tours offer a compelling alternative to tradition face-to-face visits. Whether a famous landmark, museum, real estate or natural wonders, virtual tours offer a unique opportunity to navigate and discover these places form a distance. Meanwhile, creating a virtual tour in Minecraft can provide a unique and immersive experience that sets the users apart from other virtual tour platforms. Minecraft is one of the most popular video games in the world and boasts a large …

Implementation Of Grover’S Algorithm & Bernstein-Vazirani Algorithm With Ibm Qiskit, Yang-Che Liu, Mei-Feng Liu

Journal of Informatics and Web Engineering

Quantum logic gates differ from classical logic gates as the former involves quantum operators. The conventional gates such as AND, OR, NOT etc., are generally classified as classical gates, however, some of the quantum gates are known as Pauli gates, Toffoli gates and Hadamard gates, respectively. Normally classical states only involve 0 and 1, whereas quantum states involve the superpositions of 0 and 1. Hence, underlying principles of algorithm implementation for classical logic gate and quantum logic gate are indeed different. In this paper, we introduce significant concepts of quantum computations, analyse the discrepancy between classical and quantum gates, compare …

A Campus-Based Chatbot System Using Natural Language Processing And Neural Network, Tuan-Jun Goh, Lee-Ying Chong, Siew-Chin Chong, Pey-Yun Goh

Journal of Informatics and Web Engineering

A chatbot is designed to simulate human conversation and provide instant responses to users. Chatbots have gained popularity in providing automated customer support and information retrieval among organisations. Besides, it also acts as a virtual assistant to communicate with users by delivering updated answers based on users' input. Most chatbots still use the traditional rule-based chatbot, which can only respond to pre-defined sentences, making the users unlikely to use the chatbot. This paper aims to design and build a campus chatbot for the Faculty of Information Science & Technology (FIST) of Multimedia University that facilitates the study life of FIST …

Personalized Healthcare: A Comprehensive Approach For Symptom Diagnosis And Hospital Recommendations Using Ai And Location Services, Seng-Keong Tan, Siew-Chin Chong, Kuok-Kwee Wee, Lee-Ying Chong

Journal of Informatics and Web Engineering

Utilizing digital advancements, an integrated Flask-based platform has been engineered to centralize personal health records and facilitate informed healthcare decisions. The platform utilizes a Random Forest model-based symptom checker and an OpenAI API-powered chatbot for preliminary disease diagnosis and integrates Google Maps API to recommend proximal hospitals based on user location. Additionally, it contains a comprehensive user profile encompassing general information, medical history, and allergies. The system includes a medicine reminder feature for medication adherence. This innovative amalgamation of technology and healthcare fosters a user-centric approach to personal health management.

Vision-Based Gait Analysis For Neurodegenerative Disorders Detection, Vincent Wei Sheng Tan, Wei Xiang Ooi, Yi Fan Chan, Tee Connie, Michael Kah Ong Goh

Journal of Informatics and Web Engineering

Parkinson’s Disease (PD) is a debilitating neurodegenerative disorder that affects a significant portion of aging population. Early detection of PD symptoms is crucial to prevent the progression of the disease. Research has revealed that gait attributes can provide valuable insights into PD symptoms. The gait acquisition techniques used in current research can be broadly divided into two categories: vision-based and sensor-based. The markerless vision-based classification model has become a prominent research trend due to its simplicity, low cost and patient comfort. In this study, we propose a novel markerless vision-based approach to obtain gait features from participants' gait videos. A …

Adaptive Gaussian Wiener Filter For Ct-Scan Images With Gaussian Noise Variance, Kai Liang Lew, Chung Yang Kew, Kok Swee Sim, Shing Chiang Tan

Journal of Informatics and Web Engineering

Medical imaging plays an important role in modern healthcare, with Computed Tomography (CT) being essential for high-resolution cross-sectional imaging. However, Gaussian noise often occurs within the CT scan images and makes it difficult for image interpretation and reduces the diagnostic accuracy, creating a significant obstacle to fully utilizing CT scanning technology. Existing denoising techniques have a hard time balance between noise reduction and preserving the important image details, failing to enable the optimal diagnostic precision. This study introduces Adaptive Gaussian Wiener Filter (AGWF), a novel filter aims to denoise CT scan images that have been corrupted with various Gaussian noise …

Comparison Of Machine Learning Methods For Calories Burn Prediction, Alfred Tan Jing Sheng, Zarina Che Embi, Noramiza Hashim

Journal of Informatics and Web Engineering

This paper focuses on the prediction of calories burned during exercise using machine learning techniques. Due to a growing number of obesity and overweight people, a healthy lifestyle must be adopted and maintained. This study explores and compares several machine learning regression models namely LightGBM, XGBoost, Random Forest, Ridge, Linear, Lasso, and Logistic to assess their calories burned prediction performance that can be used in systems such as fitness recommender systems supporting a healthy lifestyle. Our findings show that the LightGBM for predicting calorie burn has a good accuracy of 1.27 mean absolute error, giving users reliable recommendations. The proposed …

Goholiday: Development Of An Improvised Mobile Application For Boutique Hotels And Resorts, Iftiaj Alom, Ismail Ahmed Al-Qasem Al-Hadi, Neesha Jothi, Sook Fern Yeo

Journal of Informatics and Web Engineering

One of the main challenges boutique hotels and resorts face is the direct outreach to tourists and customers. As a result, these independent hotels often resort to online platforms such as Agoda and Airbnb to expand their customer base. However, this approach comes at the cost of losing revenue to Online Travel Agencies (OTAs) that solely focus on room sales, hindering the establishment of a strong brand image for boutique hotels and resorts. Considering the heavy reliance on OTAs, this paper focuses on the development of GoHoliday, a cross-platform mobile app prototype that aims to bridge the gap between boutique …

Weather-Based Arthritis Tracking: A Mobile Mechanism For Preventive Strategies, Jin-Lun Goh, Sin-Ban Ho, Chuie-Hong Tan

Journal of Informatics and Web Engineering

Arthritis is a common joint disorder characterised by symptoms such as swelling, pain, stiffness, and limited joint movement. It primarily affects older individuals, women, and athletes. The advent of information technology has created opportunities for patients to manage their health conditions more effectively. Research indicates that weather can affect arthritis symptoms, with many patients experiencing severe discomfort during rainy weather due to the expansion of already inflamed tissues. However, there is currently no mobile application mechanism available that combines weather forecasting with health recommendations for arthritis patients, which means that patients may not have access to important information that could …

Electric Vehicle Health Monitoring With Electric Vehicle Range Prediction And Route Planning, Jayapradha Jayaram, J Chetan, Barun Nayak

Journal of Informatics and Web Engineering

The automotive industry is experiencing a revolutionary wave due to the rapid spread of electric vehicles (EVs), which is paving the way for a fundamental and long-lasting revolution in the way we approach transportation. The global movement to reduce greenhouse gas emissions and lessen the environmental impact of traditional internal combustion engine vehicles has seen a significant boost in the popularity of electric vehicles as people come together to support environmentally conscious and sustainable mobility solutions. But the ecology surrounding electric vehicles must continue to flourish if the particular problems that EVs present are to be successfully addressed. Chief among …

Spectrum, Volume 52, Issue 3, Sacred Heart University

Newspapers (Obelisk & Spectrum)

Highlights include: SHU to purchase Notre Dame High School for $15 Million -- New Executive Director of Undergraduate Admissions --Mixtape Art Gallery, Eco To-Go at 63's Leaves Students Unimpressed -- SHU Shares Because SHU Cares -- Finding Weekly Peace through Guided Meditation -- Celebrating Love and Laughter: Valentine's Day at SHU -- Sports: Men's Golf Teeing Up for Last NEC Season -- The Powerhouse of Pioneers: Women's Wresting

A Lung Cancer Detection With Pre-Trained Cnn Models, Chai Chee Chiet, Khoh Wee How, Pang Ying Han, Yap Hui Yen

Journal of Informatics and Web Engineering

Lung cancer is a common cancer in Malaysia, affecting the majority of male citizens. The early detection of lung cancer will decrease its death rate. The only way to detect lung cancer is with a CT scan, and it also requires the doctor to check the scan to confirm the disease. In another way, the computer's support for the detection and diagnosis tool will assist doctors in determining lung cancer more accurately and efficiently. There are three main objectives for this research work. The first target is to study state-of-the-art research work to detect and recognize lung cancer from CT …

Plant Disease Detection And Classification Using Deep Learning Methods: A Comparison Study, Pei-Wern Chin, Kok-Why Ng, Naveen Palanichamy

Journal of Informatics and Web Engineering

The presence issue of inaccurate plant disease detection persists under real field conditions and most deep learning (DL) techniques still struggle to achieve real-time performance. Hence, challenges in choosing a suitable deep-learning technique to tackle the problem should be addressed. Plant diseases have a detrimental effect on agricultural yield, hence early detection is crucial to prevent food insecurity. To identify and categorise the indications of plant diseases, numerous developed or modified DL architectures are utilised. This paper aims to observe the performance of the YOLOv8 model, which has better performance than its predecessors, on a small-scale plant disease dataset. This …

Prediction Of Student’S Academic Performance Through Data Mining Approach, Muhammad Mubashar Hussain, Shahzad Akbar, Syed Ale Hassan, Muhammad Waqas Aziz, Farwa Urooj

Journal of Informatics and Web Engineering

The universities and institutes produce a large amount of student data that can be used in a disciplinary way and useful information can be extracted by using an automated approach. Educational Data Mining (EDM) is an emerging discipline used in the educational environment to deal with big student data and extract useful information. The data mining of students’ data can help the At-risk students as well as the stakeholders by the early warning. This study aims to predict the performance of the students based on student-related data to increase the overall performance. In existing studies, insufficient attributes and complexity of …

Hybrid Crow Search And Rbfnn: A Novel Approach To Medical Data Classification, Marai Ali, Faisal Khan, Muhammad Nouman Atta, Abdullah Khan, Asfandyar Khan

Journal of Informatics and Web Engineering

The Radial Basis Function Neural Network (RBFNN) is frequently employed in artificial neural networks for diverse classification tasks, yet it encounters certain limitations, including issues related to network latency and local minima. To tackle these challenges, researchers have explored various algorithms to enhance learning performance and alleviate local minima problems. This study introduces a novel approach that integrates the Crow Search Algorithm (CSA) with RBFNN to augment the learning process and address the local minima issue associated with RBFNN. The study evaluates the performance of this innovative model by comparing it to state-of-the-art models like Flower-pollination-RBNN (FP-NN), Artificial Neural Network …

An In-Depth Analysis On Efficiency And Vulnerabilities On A Cloud-Based Searchable Symmetric Encryption Solution, Prithvi Chaudhari, Ji-Jian Chin, Soeheila Moesfa Bt Mohamad

Journal of Informatics and Web Engineering

Searchable Symmetric Encryption (SSE) has come to be as an integral cryptographic approach in a world where digital privacy is essential. The capacity to search through encrypted data whilst maintaining its integrity meets the most important demand for security and confidentiality in a society that is increasingly dependent on cloud-based services and data storage. SSE offers efficient processing of queries over encrypted datasets, allowing entities to comply with data privacy rules while preserving database usability. Our research goes into this need, concentrating on the development and thorough testing of an SSE system based on Curtmola’s architecture and employing Advanced Encryption …

Baltimore Proof Of Claim

Catholic Dioceses in Bankruptcy

No abstract provided.