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Lung Tumor Segmentation In Medical Imaging Using U-Net, J Jayapradha, Su-Cheng Haw, Naveen Palanichamy, Senthil Kumar Thillaigovindhan, Mutaz Al-Tarawneh Feb 2025

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 …

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A Hybrid Deep Learning Vgg-16 Based Svm Model For Vehicle Type Classification, Muhammad Imran, Jafar Usman, Muntazir Khan, Abdullah Khan Feb 2025

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, …

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Early Identification Of Parkinson's Disease Using Time Frequency Analysis On Eeg Signals, Tanvir Hasib, V Vijayakumar, Ramakrishnan Kannan Feb 2025

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 …

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Debugprograde: Improving Automated Assessment Of Coding Assignments With A Focus On Debugging, Amit Patel, Hardik Joshi Feb 2025

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 …

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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 Feb 2025

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 …

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Integrating Moral Values In Ai: Addressing Ethical Challenges For Fair And Responsible Technology, Khushboo Shah, Hiren Joshi, Hardik Joshi Feb 2025

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 …

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Creating An Android-Based Calisthenics Application To Assist Students In Improving Their Physical Fitness, Restyandito, Narendra Poetra Wisnoewardhana, Danny Sebastian Feb 2025

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 …

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Machine Learning Model For Predicting Net Environmental Effects, Sellappan Palaniappan, Rajasvaran Logeswaran, Shapla Khanam, Zhang Yujiao Feb 2025

Machine Learning Model For Predicting Net Environmental Effects, Sellappan Palaniappan, Rajasvaran Logeswaran, Shapla Khanam, Zhang Yujiao

Journal of Informatics and Web Engineering

Environmental sustainability is a global challenge in the face of increasing incidences of disasters affecting communities worldwide. This requires predicting net environmental effects accurately. While various approaches exist, we need more sophisticated prediction models that account for both environmental and social factors. This study presents a proof-of-concept machine learning model for predicting net environmental effects using synthetic data. We developed a multiple linear regression model incorporating nine key features: renewable energy usage, carbon emissions, air quality index, water usage, biodiversity impact, land use, public awareness, and environmental attitudes. We generated a synthetic dataset of 1000 samples using probability distributions and …

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Fiber Break Prevention Using Machine Learning Approaches, Zhan Heng Ng, Tee Connie, Kan Yeep Choo, Michael Kah Ong Goh, Nurul Ain Abdul Aziz, Hong Yeap Ngo Feb 2025

Fiber Break Prevention Using Machine Learning Approaches, Zhan Heng Ng, Tee Connie, Kan Yeep Choo, Michael Kah Ong Goh, Nurul Ain Abdul Aziz, Hong Yeap Ngo

Journal of Informatics and Web Engineering

Modern fiber-optic communication systems are built around optical fiber, which allows data to be sent by emitting infrared light pulses. It is widely used by telecommunications firms and is essential to the smooth transmission of information in internet communication as well as the transmission of telephone signals. Nonetheless, optical fibers intrinsic fragility raises a problem, especially in areas where building projects are taking place. Especially nowadays construction-related impact and crushing pressures can cause physical damage that jeopardizes the fiber optic's integrity. Therefore, this research emphasizes the necessity of taking preventative and mitigating actions to reduce the possibilities of fiber optic …

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Migraine Generative Artificial Intelligence Based On Mobile Personalized Healthcare, Michelle Ting-Ting Yong, Sin-Ban Ho, Chuie-Hong Tan Feb 2025

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 …

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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 Feb 2025

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 …

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Climate Change Analysis In Malaysia Using Machine Learning, Anishalache Subramanian, Naveen Palanichamy, Kok-Why Ng, Sandhya Aneja Feb 2025

Climate Change Analysis In Malaysia Using Machine Learning, Anishalache Subramanian, Naveen Palanichamy, Kok-Why Ng, Sandhya Aneja

Journal of Informatics and Web Engineering

Climate change presents significant challenges to ecosystems, economies, and societies globally. In Malaysia, a tropical country highly dependent on its natural resources, the impacts are evident in altered rainfall patterns, rising temperatures, and extreme weather events. Despite these challenges, many studies still predominantly rely on traditional statistical methods, which limit their capacity for making accurate climate predictions and developing effective policy solutions.This study effectively addresses the existing gap in research by analyzing extensive historical climate data using advanced machine learning (ML) techniques. The primary focus is on accurately forecasting trends in both precipitation patterns and surface air temperature fluctuations. Performance …

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Path To A Healthy Work-Life Balance: Mobile Application For Work And Personal Life Mastery, Erfan Rahmani, Zarina Che Embi Feb 2025

Path To A Healthy Work-Life Balance: Mobile Application For Work And Personal Life Mastery, Erfan Rahmani, Zarina Che Embi

Journal of Informatics and Web Engineering

Drawing insights from diverse organizational methods, this study endeavors to facilitate effective self-development and organization in the face of contemporary demands as solutions for integrating goal tracking, event coordination, and task management within a unified calendar framework in a mobile application. There are three primary objectives of this study: firstly, to explore essential functionalities crucial for addressing the multifaceted challenges of modern life; secondly, to design and develop a mobile application that seamlessly integrates these functionalities; and finally, to evaluate the usability of the application through rigorous testing and feedback mechanisms. Envisaged deliverables include a fully functional mobile application designed …

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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 Feb 2025

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 …

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

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.

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Application Of Information And Communication Technology In The Management Of Library In University Of Mkar, Mkar, Benue State, Joseph Lughlugh, Titilola Olaniyi Adegoke Dr, Saater Iorngulum Mr Feb 2025

Application Of Information And Communication Technology In The Management Of Library In University Of Mkar, Mkar, Benue State, Joseph Lughlugh, Titilola Olaniyi Adegoke Dr, Saater Iorngulum Mr

Library Philosophy and Practice (e-journal)

The study examined application of information and communication technology (ICT) in the management of library in University of Mkar, Mkar, Benue State. Three research questions guided and directed the study. Descriptive survey design was adopted for the study. The population of the study comprised 29 library staff in the University of Mkar. The study adopted census sampling procedure thus, all the 29 library staff participated in the study. One instrument tagged “application of information and communication technology in the management of library questionnaire (AICTMULQ)” was used for data collection. The instrument was validated by experts. The reliability of the instrument …

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Evaluating The New Nd: Yag Laser Method In Phytosynthesizing Silver Nanoparticles And Assessing Their Medical Applications., Arshad Mahdi Hamad, Qanat Mahmood Atiya Feb 2025

Evaluating The New Nd: Yag Laser Method In Phytosynthesizing Silver Nanoparticles And Assessing Their Medical Applications., Arshad Mahdi Hamad, Qanat Mahmood Atiya

Karbala International Journal of Modern Science

Silver nanoparticles (AgNPs) were synthesized via an innovative green synthesis method using amygdalin (Am) as a reducing agent and the Nd: YAG laser as a catalyst. We studied the properties of the nanoparticles using X-ray diffraction (XRD), field emission scanning electron microscopy (FESEM), energy dispersive X-ray spectroscopy (EDX), atomic force microscopy (AFM), ultraviolet-visible spectroscopy (UV), and Fourier transform infrared spectroscopy (FTIR) techniques. All the results of the examination demonstrate excellent structural and optical properties. In addition, the molecular docking of the complex composed of amygdalin and AgNPs was tested on three proteins concerned with the virulence of Pseudomonas aeruginosa and …

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Leveraging Network Science For Customer Segmentation And Product Recommendation, Ali Nasirzonouzi Feb 2025

Leveraging Network Science For Customer Segmentation And Product Recommendation, Ali Nasirzonouzi

Northeast Journal of Complex Systems (NEJCS)

The rapid growth in e-commerce has forced the development and implementation of enhanced customer segmentation and recommendation systems, improving business results and improving customer experience. Traditional approaches, such as RFM analysis and clustering algorithms like K-means, are very helpful in many situations but usually fail to catch complex interdependencies among customers and products. This paper proposes a new approach using network science methodologies, a bipartite graph model, toward the advancement of customer segmentation and product recommendation. It implements a bipartite graph of customers and products using the "Online Retail II" dataset and proceeds with community detection, segmenting customers into unique …

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Influence Of Oil Density On Self-Propelled Motion Of Belousov-Zhabotinsky Reaction Droplet, Vivek Bharat Meshram, Anupama Sebastian, Puthiyapurayil Sibeesh, T K Shajahan Feb 2025

Influence Of Oil Density On Self-Propelled Motion Of Belousov-Zhabotinsky Reaction Droplet, Vivek Bharat Meshram, Anupama Sebastian, Puthiyapurayil Sibeesh, T K Shajahan

Northeast Journal of Complex Systems (NEJCS)

Belousov-Zhabotinsky reaction serves as an example of the nonlinear chemical oscillator in which the reacting substance undergoes sequential oxidation and reduction. A droplet containing the BZ reaction, when placed within the oily environment, can self-propel. In this experimental work, we explore the effect of oil medium density on the BZ reaction droplet dynamics. In an oil medium with lower density, the BZ droplet exhibits higher speed and effective diffusivity but a shorter lifetime. Both the distance and speed of the droplet initially increase with droplet volume. However, beyond a critical volume, the distance decreases while the speed stays constant. Interestingly, …

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Volatility Modelling In Garch Frameworks: A Comparative Analysis Of Non-Gaussian Error Distributions With Skewed Parameters., Olatunbosun Adewale Akanbi, Timothy Olabisi Olatayo, Abass Ishola Taiwo Feb 2025

Volatility Modelling In Garch Frameworks: A Comparative Analysis Of Non-Gaussian Error Distributions With Skewed Parameters., Olatunbosun Adewale Akanbi, Timothy Olabisi Olatayo, Abass Ishola Taiwo

Al-Bahir

Forecasting volatility in financial time series remains challenging due to their asymmetric nature and excess kurtosis. This study evaluates and compares the performance of four variant of GARCH models incorporating skewed non-Gaussian error innovation distribution. The performances of these GARCH family of models under the skewed error innovation distributions were evaluated for three different unique data sets to have a more robust assessment of the performance of these skewed error innovation distributions. This study leverage on daily closing prices of Bitcoin, Naira to Dollar Exchange rates and daily Nigeria All Share Index between January 1, 2015 and January 26, 2024. …

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Optimal Investment In An Energy Storage System, Marta Castellini, Chiara D'Alpaos, Fulvio Fontini, Michele Moretto Feb 2025

Optimal Investment In An Energy Storage System, Marta Castellini, Chiara D'Alpaos, Fulvio Fontini, Michele Moretto

Fondazione Eni Enrico Mattei Working Papers

Renewable energy production plays a crucial role in the energy transition. However, many renewable energy sources (RES) are intermittent, and there is often a mismatch between energy production and consumption, which can be partially solved by storage. In this paper, we investigate the investment decision in a photovoltaic (PV) power plant coupled with a Battery Energy Storage System (BESS), namely an Energy Storage System (ESS). We aim to investigate the relationship between the net present value (NPV) of the investment and the technical implications related to the maximum amount of energy to be stored while also accounting for the impact …

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The Indiana Statesman, February 13, 2025, Indiana State University Feb 2025

The Indiana Statesman, February 13, 2025, Indiana State University

Student Newspaper

Scan & Pay: parking payments made easierpayments easier; Department of Biology “3 billion missing birds”; Japanese Club hosts “Chocolate Day”

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Kenyon Collegian - February 13, 2025 Feb 2025

Kenyon Collegian - February 13, 2025

The Kenyon Collegian

No abstract provided.

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The Economic Rhetoric Of Carbon Pricing, Jeff Todd Feb 2025

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 …

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2025 February 13 - Tennessee Weekly Drought Summary, Tennessee Climate Office, East Tennessee State University Feb 2025

2025 February 13 - Tennessee Weekly Drought Summary, Tennessee Climate Office, East Tennessee State University

Tennessee Climate Office Weekly Drought Summaries

No abstract provided.

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February 13, 2025, Caa Feb 2025

February 13, 2025, Caa

Minutes

No abstract provided.

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Towards More Sustainable Oceans: A Review Of The Pressing Challenges Posed By Marine Plastic Litter, Peter Yang Feb 2025

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 …

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07. Linear Response And Equilibrium Dynamics, Gerhard Müller Feb 2025

07. Linear Response And Equilibrium Dynamics, Gerhard Müller

Nonequilibrium Statistical Physics (2025)

Part seven of course materials for Nonequilibrium Statistical Physics (Physics 626), taught by Gerhard Müller at the University of Rhode Island. The available PDF includes both the lecture notes, additional materials, and exercises without solutions.

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Re: Butte Mine Flooding Site Cd, Cv 02-35 Bu-Rfc, 2024 Fourth Quarter Report, Mark Thompson, Dave Griffis Feb 2025

Re: Butte Mine Flooding Site Cd, Cv 02-35 Bu-Rfc, 2024 Fourth Quarter Report, Mark Thompson, Dave Griffis

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

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Non-Orientable Surfaces Bounded By Knots, Megan K. Fairchild Feb 2025

Non-Orientable Surfaces Bounded By Knots, Megan K. Fairchild

LSU Doctoral Dissertations

The non-orientable 4-genus of a knot $K$ in $S^{3}$ is defined to be the minimum first Betti number of a non-orientable surface $F$ in $B^{4}$ so that $K$ bounds $F$. We will survey the tools used to compute the non-orientable 4-genus, and use various techniques to calculate this invariant for non-alternating 11 crossing knots, torus knots, and Whitehead doubles. We also will view obstructions to a knot bounding a M\"{o}bius band given by the double branched cover of $S^{3}$ branched over $K$. Additionally, we discuss the problem of the Whitehead double of the Figure 8 knot and survey commonly used …

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