Digital Commons Network^™

Improved Accuracy For Heart Disease Diagnosis Using Machine Learning Techniques, Neeraja Joshi, Tejal Dave

Journal of Informatics and Web Engineering

This work primarily focuses on diagnosis of heart disease before explicit visit to the expert doctor. Machine learning based systems have been found useful in medical diagnosis applications because of their ability to learn human like expertise and to utilize acquired knowledge for diagnosis. This work is performs classification of heart disease utilizing subject’s vital parameters. Pathological laboratory results available after testing are not understood by common people and patients have to wait till they visit expert doctors for inference. In this paper, traditional methods like linear regression  to various machine learning based systems including back propagation neural network, support …

Implementing Identity-Based Signature Schemes For Secure Data Transfer In Cloud Computing Environments, Paul Osinuga, Ji-Jian Chin, Terry Shue Chien Lau

Journal of Informatics and Web Engineering

In this paper, we present the implementation of the Cha-Cheon Identity-Based Signature (IBS) scheme to enhance secure data transfer in cloud computing environments. Cloud computing rely on traditional Public Key Infrastructure (PKI) systems, which is burdened by certificate management infrastructure. The primary focus of this research to simplify key and certificate management by leveraging identity-based elliptic curve cryptography (ECC) within the Cha-Cheon IBS framework. We show that the proposed IBS solution integrates seamlessly with Amazon Web Services (AWS), utilizing services like S3 for secure data storage and KMS for key management. By applying ECC, the Cha-Cheon scheme achieves efficient cryptographic …

Lung Tumor Segmentation In Medical Imaging Using U-Net, J Jayapradha, Su-Cheng Haw, Naveen Palanichamy, Senthil Kumar Thillaigovindhan, Mutaz Al-Tarawneh

Journal of Informatics and Web Engineering

Tumors are a deadly condition often triggered by a range of abnormal modifications and genetic abnormalities. Early tumor diagnosis is essential due to the highly concerned nature of the disease. Early detection and treatment of tumors can significantly reduce mortality rates. This paper presents a model for tumor segmentation in medical imaging that uses the U-NET architecture to increase precision. The model’s encoding and decoding processes have been applied with skip connections to boost performance while simplifying model training. Images were cropped around the lower abdominal regions, and all images used in the study were then resized to 256*256 pixels …

A Hybrid Deep Learning Vgg-16 Based Svm Model For Vehicle Type Classification, Muhammad Imran, Jafar Usman, Muntazir Khan, Abdullah Khan

Journal of Informatics and Web Engineering

Car classification is important in daily life because there are many distinct types of automobiles made by various manufacturers. Although there are numerous methods for classifying autos, machine learning technologies have not been widely utilized, resulting in low accuracy levels. The goal of this paper is to create a machine learning system that is especially made to categories models of two Pakistan's top automakers, Toyota, and Honda. Ten Toyota models such as Avalon, Land Cruiser, Camry, Corolla, C-HR, Highlander, Prius, Tundra, RAV4, and Yaris and a dataset of Honda automobiles, which also includes 10 models (Accord, Civic, CR-V, Fit, HR-V, …

Early Identification Of Parkinson's Disease Using Time Frequency Analysis On Eeg Signals, Tanvir Hasib, V Vijayakumar, Ramakrishnan Kannan

Journal of Informatics and Web Engineering

Parkinson's Disease (PD) is a progressive neurological disorder. It affects movement and can significantly impact quality of life. Early and accurate diagnosis is crucial for effective management and intervention. Traditional diagnostic methods can be time-consuming and less effective in the early stages of the disease. This study aims to develop an automated approach for identifying PD using time-frequency image analysis of electroencephalogram (EEG) signals. The goal is to enhance diagnostic accuracy and efficiency, facilitating early detection. EEG signals, often contaminated with artifacts such as eye blinks and muscle movements etc., were first cleaned. Time-frequency images were then plotted from the …

Debugprograde: Improving Automated Assessment Of Coding Assignments With A Focus On Debugging, Amit Patel, Hardik Joshi

Journal of Informatics and Web Engineering

In education, the evaluation of programming assignments is challenging, especially to do with the debugging aspect. Self-grading technologies are unable to capture the level of understanding of students and context-bound responses. In light of these, we created DebugProGrade to take what we normally know about grading and improve it with semantic analysis and keyword extraction. DebugProGrade identified 1000 first-year BCA students who in Google Forms provided their answers to evaluate error detection and solution proposals for a basic C programming assignment. For the explanations’ specificity and for the context-level evaluation, the system employs the SBERT embedding, namely, the sentence-transformer bidirectional …

Optimising Phishing Detection: A Comparative Analysis Of Machine Learning Methods With Feature Selection, Mohamad Asraf Daniel, Siew-Chin Chong, Lee-Ying Chong, Kuok-Kwee Wee

Journal of Informatics and Web Engineering

Phishing is an act of cybersecurity attack that tricks people into sharing sensitive data. Due to the inefficiency of the current security technologies, researchers have been paying much attention to employing machine learning methods for phishing detection lately. In our proposed solution, the effectiveness of machine learning techniques with feature selection techniques for phishing detection is investigated. To be specific, Random Forest (RF) and Artificial Neural Network (ANN) are integrated with feature selection techniques, Principal Component Analysis (PCA) and Recursive Feature Elimination (RFE). The goal was to identify and classify the model with the highest accuracy. The experiments were evaluated …

Integrating Moral Values In Ai: Addressing Ethical Challenges For Fair And Responsible Technology, Khushboo Shah, Hiren Joshi, Hardik Joshi

Journal of Informatics and Web Engineering

Today, Artificial Intelligence (AI) has become an integral part of our day-to-day life. From personal task to professional life everywhere we need AI. All the sectors like - transport, education, healthcare, agriculture, we find AI everywhere. Each coin has two side, similarly AI has its own pros and cons. Main challenge with AI is ethics. There is no doubt in the work efficiency of AI but ultimately, it’s a machine without emotions hence whatever the decision it takes it purely without ethical values. Sometimes, this type of decision may lead to disasters, especially in the industry where human life is …

Creating An Android-Based Calisthenics Application To Assist Students In Improving Their Physical Fitness, Restyandito, Narendra Poetra Wisnoewardhana, Danny Sebastian

Journal of Informatics and Web Engineering

College students, particularly those heavily involved in coursework, frequently do not prioritize physical fitness. Regular exercise is essential for preserving physical fitness and facilitating demanding academic tasks. Although there are other fitness programs available, such as GYM, jogging, CrossFit, and Yoga, users sometimes fail to make full use of them because the content is confined to exercise videos and descriptions. This matter highlights the progress of the Android application Kali Tech, which specifically concentrates on organizing and documenting calisthenics workouts. This program employs the concept of gamification by utilizing student achievement levels to encourage students to be diligent in doing …

Migraine Generative Artificial Intelligence Based On Mobile Personalized Healthcare, Michelle Ting-Ting Yong, Sin-Ban Ho, Chuie-Hong Tan

Journal of Informatics and Web Engineering

Migraine is a complicated genetic disorder characterized by episodes of moderate-to-severe headaches that are usually unilateral and are frequently accompanied by nausea and increased sensitivity to sound and light. A migraine attack induces intense pain, hindering an individual from engaging in daily activities and potentially persisting for hours or even days. By the growth of the Internet of Things, we have new opportunities to try to apply it to the medical field. To identify the origin of a migraine, specialists need access to a patient's medical history and a comprehensive understanding of migraine symptoms for effective treatment. Determining the true …

Exploration Of The Impact Of Cyber Situational Awareness On Small And Medium Enterprises (Smes) In Malaysia, Tan Chee Keong, Sofiah Kadar Khan, Umar Farooq Khattak

Journal of Informatics and Web Engineering

The objective of this study is to explore the cyber situational awareness (CSA) level among the employees of small and medium-sized enterprises (SME) in Malaysia, by extending Endsley's situation awareness (SA) theory. It is crucial to understand the level of cyber situational awareness among employees as it sheds light on how well the employees understand the cyber threats and if they can handle them effectively. Literature has reviewed that SMEs are subject to a greater danger of cyber-attacks. Therefore, employees' awareness of cyber situations is of the utmost significance in studying cyber security. A convenient non-probability sampling method was chosen …

Personalized Drug Recommendation System Using Wasserstein Auto-Encoders And Adverse Drug Reaction Detection With Weighted Feed Forward Neural Network (Waes-Adr) In Healthcare, J Omana, P. N Jeipratha, K Devi, S Benila, K Revathi

Journal of Informatics and Web Engineering

In recent years, the use of deep learning approaches in healthcare has yielded promising results in a variety of fields, most notably in the detection of adverse drug reactions (ADRs) and drug recommendations. This paper promises a breakthrough in this field by using Wasserstein autoencoders (WAEs) for personalized medicine recommendation and ADR detection. WAEs' capacity to manage complex data distributions and develop meaningful latent representations makes them ideal for modeling heterogeneous healthcare data. This study intends to improvise the precision and efficiency of drug recommendation systems while also improving patient safety by combining WAEs and early ADR detection strategies. Previous …

2025 Draft Final Insufficiently Reclaimed Sites Quality Assurance Project Plan (Qapp), Pioneer Technical Services, Inc.

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

Collision Probabilities Between User Equipment Using 5g Nr Sidelink Time-Domain-Based Resource Allocation In C-V2x, Mehnaz Tabassum, Aurenice Oliveira

Michigan Tech Publications

Efficient resource allocation is a critical factor in ensuring reliable and low-latency communication in the fifth-generation New Radio (5G NR) sidelink-based Cellular Vehicle to Everything (C-V2X) networks. One of the critical challenges in adopting C-V2X systems is the potential for packet collisions between User Equipment (UE) when they share resources in the sidelink channel. For reliable and low-latency communication, especially in safety-critical applications, efficient resource allocation is essential. This paper explores collision-related issues that may arise in the 5G NR sidelink and the probability of collisions on resource blocks. To address these challenges, we propose an experimental time-domain resource allocation …

Implementing Identity-Based Signature Schemes For Secure Data Transfer In Cloud Computing Environments, Paul Osinuga, Ji-Jian Chin, Terry Shue Chien Lau

School of Engineering, Computing and Mathematics

In this paper, we present the implementation of the Cha-Cheon Identity-Based Signature (IBS) scheme to enhance secure data transfer in cloud computing environments. Cloud computingrely on traditional Public Key Infrastructure (PKI) systems, which is burdened by certificate management infrastructure. The primary focus of this research to simplify key and certificate management by leveraging identity-based elliptic curve cryptography (ECC) within the Cha-Cheon IBS framework. We show that the proposed IBS solution integrates seamlessly with Amazon Web Services (AWS), utilizing services like S3 for secure data storage and KMSfor key management. By applying ECC, the Cha-Cheon scheme achieves efficient cryptographic operations with …

Single-Cell Analysis Identifies Ifi27l2a As A Gene Regulator Of Microglial Inflammation In The Context Of Aging And Stroke In Mice, Lauren Vance, Anik Banerjee, Zachary Wise, Andrea Doan, John Ahn, Ting Wu, Jesus Bautista-Garrido, Juneyoung Lee, Chunfeng Tan, Joo Eun Jung, Louise D Mccullough, Joshua D Wythe, Sean P Marrelli

Faculty, Staff and Student Publications

Inflammation is a significant driver of ischemic stroke pathology in the brain. To identify potential regulators of inflammation, we performed single-cell RNA sequencing (scRNA-seq) of young and aged mouse brains following stroke and found that interferon alpha-inducible protein 27 like 2 A (Ifi27l2a) was significantly up-regulated, particularly in microglia of aged brain. Ifi27l2a is induced by interferons for viral host defense and has been linked with pro-inflammatory cellular mechanisms. However, its potential role in neurodegeneration is unknown. Using a combination of cell culture, experimental stroke models in mice, and human autopsy brain samples, we demonstrated that induction of Ifi27l2a occurs …

Evaluating The Impact Of Osteopathic Manipulative Medicine On Cytokine Modulation: A Pathway To Inflammatory Disease Management, Renee M. Chang, Krystal Robinson, Sharon Sengphanith, Grace Godffrey, Jacob Gofrey, Carissa Salamatin, Mark Santos Phd, Wesley Lockhart Do

Annual Research Symposium

No abstract provided.

Teaching Sprinting As A Specialized Skill In Elementary Physical Education, Dillon R. Martinez, Scott Klepadlo

Essays in Education

This article highlights the gap between current physical grade-level outcomes and the practical implementation of sprinting instruction in elementary schools. This emphasizes the need for higher education institutions to learn from practicing elementary teachers, who have successfully incorporated sprinting into their elementary curricula. While pre-service physical education teachers are not typically taught how to teach sprinting as a specialized skill, some elementary PE teachers have developed effective methods for doing so. This article suggests that higher education practitioners should examine these practitioners to inform and improve their teacher preparation programs. This paper outlines several practical applications currently used in elementary …

Classical Ballet: The Progressive Preservation Of Tradition, Caroline Peacock

Quest

Research Essay

Research in progress for ENGL 1302: Composition II

Faculty Mentor: Lisa Roy-Davis, PhD

I am pleased to introduce Caroline Peacock’s excellent work “Classical Ballet: The Progressive Preservation of Tradition,” a research essay she wrote for my English 1302 class in the fall 2023 semester. Adapted from Bruce Ballenger’s textbook, The Curious Writer, the Research Essay assignment encourages students to foreground the role of inquiry by narrating their questions and how their sources address and extend those questions. When students prioritize questions over answers, their writing then demonstrates the value of “thinking on the page,” or the forward …

Counter-Intuitive Links Between Cave Genesis And Subaerial Stream Dynamics In The Têt Valley–Lachambre Network, Eastern Pyrenees, France, Stéphane Jaillet, Gabriel Hez, Marc Calvet, Magali Delmas, Edwige Pons-Branchu, Yanni Gunnell

International Journal of Speleology

The Lachambre cave network (Eastern Pyrenees, France) is well suited to studying the interaction between vertical successions of low-gradient cave passages in the limestone and chronosequences of fluvial terraces in the adjacent valley. Investigations here focus on cave passages striking parallel to the Têt River, and on their topographic, geomorphological, sedimentological and geochronological relationship with the two youngest generations of Pleistocene fluvial terrace, T2 and T1. Results reveal that the longitudinal profiles of the terraces and modern thalweg (1.5–3%) are ten times steeper than the profiles of the subterranean passages (0.1–0.3%), which display typical characteristics of water table caves. The …

The Chanticleer, 2025-02-13, Coastal Carolina University

The Chanticleer Student Newspaper

The editorially independent student produced weekly newspaper of Coastal Carolina University.

Kenyon Collegian - February 13, 2025

The Kenyon Collegian

No abstract provided.

The Economic Rhetoric Of Carbon Pricing, Jeff Todd

Brooklyn Law Review

Economists overwhelmingly prefer the carbon pricing instruments of carbon taxes and cap-and-trade programs as the most cost-effective way to reduce greenhouse gases and combat climate change. By contrast, US lawmakers have largely eschewed carbon pricing, and legal scholars have mixed views about implementing it. In order for legal scholars to better understand economic studies on carbon pricing and incorporate those studies into their own climate change scholarship, this Article turns to the rhetoric of economics. Economists view problems like climate change through the metaphor of the market, so they embrace carbon pricing because it is a market-based approach that corrects …

Towards More Sustainable Oceans: A Review Of The Pressing Challenges Posed By Marine Plastic Litter, Peter Yang

Faculty Scholarship

Marine littering is a global challenge and a significant threat to a sustainable planet, requiring comprehensive and effective mechanisms to address it in a comprehensive manner. This study reports on a bibliometric analysis that has identified the extent to which the topic has been explored in the international literature, by focusing on geographical scope, the emphasis on (micro)plastic litter and on policy measures. Additionally, as a complement to the assessment of the recent literature on marine plastic litter, this study reviews some case studies, identifying some trends on how to cope with this problem. The findings underscore the imperative for …

A Collective History On Arkansas Regional Organ Recovery Agency (Arora) And Their Adaptation To Donation Culture, Tara Jones

Theses and Dissertations

Arkansas Regional Organ Recovery Agency (ARORA) is continually addressing the organ shortage in Arkansas by increasing organ and tissue donation rates in Arkansas. Hospitals, Funeral Homes, and other referral partners collaborated with ARORA in their efforts to increase organ and tissue donation. Interviews from former and current ARORA employees, along with data analysis, highlight how ARORA worked to honor Arkansans decision to be a registered donor while also improving the procurement of organs. The findings reveal how ARORA adapted to donation culture related to public, cooperation with referral partners, among other barriers to create ARORA’s mission of “Restoring Lives” This …

Quaker Campus, February 13, 2025 (Vol. 23, Issue 9), Whittier College

Quaker Campus

No abstract provided.

Arrhythmogenic Right Ventricular Cardiomyopathy: A Comprehensive Review, Taha Shaikh, Darren Nguyen, Jasmine Dugal, Michael Dicaro, Brianna Yee, Nazanin Houshmand, Kachon Lei, Ali Namazi

Department of Internal Medicine Faculty Research

Arrhythmogenic right ventricular cardiomyopathy (ARVC) is characterized by structural abnormalities, arrhythmias, and a spectrum of genetic and clinical manifestations. Clinically, ARVC is structurally distinguished by right ventricular dilation due to increased adiposity and fibrosis in the ventricular walls, and it manifests as cardiac arrhythmias ranging from non-sustained ventricular tachycardia to sudden cardiac death. Its prevalence has been estimated to range from 1 in every 1000 to 5000 people, with its large range being attributed to the variability in genetic penetrance from asymptomatic to significant burden. It is even suggested that the prevalence is underestimated, as the presence of genotypic mutations …

Comparison Of Levels Of Usage Of Summit K-12 And Language Acquisition Of Emergent Bilingual Students, Paula Cushanick

Walden Dissertations and Doctoral Studies

School districts are required to identify emergent bilingual (EB) students, provide appropriate bilingual education programs, and assess language acquisition progress to ensure equal educational opportunity. The problem investigated in this study was that, in 2022, only 38% of the EB student population in Southwestern School District (SSD, a pseudonym) demonstrated progress in achieving English language proficiency in the composite scores of the TELPAS assessment that included listening, speaking, reading, and writing language domains. The Summit K-12 computerized intervention program was instituted by SSD to address EB student language development. Guided by Sparrow’s holistic biliteracy framework, the purpose of this quasi-experimental, …

Staff Education On Accurate Blood Pressure Monitoring, Amy Wink

Walden Dissertations and Doctoral Studies

Hypertension is a prevalent diagnosis in the United States and a significant contributor to adult mortality. The annual burden of high blood pressure in the United States is approximately 131 million dollars, accounting for health care services and medication expenses. This educational project was initiated because the metric for the patient population at the veterans’ outpatient clinic exceeded the national hypertension indicator of 140/90. The facility’s data metric results were above the national average, necessitating addressing an identified gap in practice, performing blood pressure screenings accurately. The purpose of this educational project was to develop a module for nurses to …

Arbitrators Of Environmental Disputes: The Guardians Of Natural Resources, Isabella Mazzei

Pace Environmental Law Review

According to the International Energy Agency, to achieve net zero emissions by 2050, global investment in clean energy must more than triple, reaching $4 trillion. More investments in technology for clean energy and infrastructure means more transactions across major industries. This inevitably translates to the potential for more disputes, including environmental concerns. Most energy related disputes are predicted to arise in the oil and gas sector, the power generation sector, and the offshore renewable sector. Arbitration presents an appealing option to efficiently resolve these emerging conflicts. This paper highlights the growing importance of arbitration in resolving environmental disputes. To explore …