Engineering Commons^™

Mathematical Model For The Management Of The Wave Processes In Three-Winding Transformers With Consideration Of The Main Magnetic Flux In Mining Industry, M. S. Seheda, O. S. Beshta, P. F. Gogolyuk, Yu. V. Blyznak, R. D. Dychkovskyi, A. Smoliński

Journal of Sustainable Mining

The aim of the work is to study the wave processes in three-winding power transformers caused by impulse overvoltage, to create an improved mathematical model for reproducing the process of distribution and transmission of the impulse in the windings of a three-winding power transformer. A mathematical model has been developed for the study of internal overvoltage in the windings of three-winding power transformers, based on the proposed substitute circuit of an infinitesimal element, taking into account the longitudinal and transverse inductive connections between the turns of the winding, the electromagnetic connections between the windings and the flux splitting from the …

The Effect Of Blasting Using Low-Density Emulsion Explosives, Vinko Škrlec, Mario Dobrilović, Barbara Štimac Tumara, Vječislav Bohanek

Journal of Sustainable Mining

Low-density emulsion explosives are essentially blends of an emulsion matrix and a certain amount of gaseous phase inclusions acting as hot spots. With the addition of expanded polystyrene for gaseous sensibilization, the resulting explosive blend was developed to reduce peak values and pressure impulse of gaseous detonation products on surrounding rock. This resulted in a decrease in rock stress and a decrease in cracking zone width outside of the minefield boundary. The use of low-density emulsion explosives correlates with the decrease in the seismic effect of blasting, more precisely, the decrease of induced rock oscillation velocities. The low-density emulsion explosive …

Numerical Simulation On Effect Of Coal Pillar Width On Stability Of Retained Roadway: A Case Study Of Khe Cham Coal Mine, Vietnam, Quang Phuc Le, Tien Dung Le

Journal of Sustainable Mining

When extracting coal seams in Vietnam underground mines, coal pillars are often left unmined for the protection of retained roadways in the longwall mining method. During longwall mining operations, coal pillars are often placed where high-stress concentrations occur in the abutment pressure zone of adjacent panels, especially when extracting seams under hard-to-cave main roof conditions. The instability of coal pillars under the loading of the main roof may cause the roadway to collapse, threatening the safe operation of a coal mine. This paper presents a detailed numerical investigation of the effect of coal pillar width on the stability of retained …

Experimental Data For: "Effects Of Network Connectivity And Functional Diversity Distribution On Human Collective Ideation", Yiding Cao, Yingjun Dong, Minjun Kim, Neil G. Maclaren, Sriniwas Pandey, Shelley D. Dionne, Francis J. Yammarino, Hiroki Sayama

Systems Science and Industrial Engineering Faculty Scholarship

This is the dataset collected from our online human-subject experiments described in the following manuscript:

Yiding Cao, Yingjun Dong, Minjun Kim, Neil G. MacLaren, Sriniwas Pandey, Shelley D. Dionne, Francis J. Yammarino, and Hiroki Sayama:
"Effects of Network Connectivity and Functional Diversity Distribution on Human Collective Ideation"
https://arxiv.org/abs/2307.04284

Winona State University Alumni Blog: 2011-2022, Winona State University

Winona State University Blogs

The Winona State University (WSU) Alumni Blog includes articles and entries from May 2011- August 2022. Note: there may be format coding in the document.

On-Site Estimation Of Total Sugars In Flavored Milk Using A Glucometer, Erwin Oliver V. Fundador, Karyn Thea E. Rivera, Kriza Faye A. Calumba, Noreen Grace V. Fundador

ASEAN Journal on Science and Technology for Development

Sugar has been linked to obesity and chronic diseases. Unfortunately some "healthy products," such as flavored milk, contain high sugar. In the Philippines, such an issue is made worse by local brands not putting nutritional labels on their products. Thus, a cheap, home-based method to measure total sugars should be beneficial. In this paper, we have shown that after incubation with invertase and lactase, a glucometer can be used to measure total sugars in flavored milk on-site. All experiments except the weighing of invertase and lactose were done in a home setting for actual proof of concept. The total sugar …

Zno Varistors—Preparation Of Nano And Micro Sized Powders By Mechanical Methods For Low And High Voltage Varistors, Maura Kelleher

Books/Book Chapters

ZnO-Bi2O3-Sb2O3 varistors are as essential today as they have been since their discovery five decades ago. Their role is to protect other electronic components against oncoming surges of electrons and survive. The demands on varistors are increasing. Electronic components are becoming smaller and more sensitive, and the metal oxides from which varistors are made are precious. Every aspect of their structure (macro, micro, nano and atomic) determines how they perform and survive. Each stage and variable within the powder metallurgy process is important. The mechanical methods in preparing nano and micro sized metal oxide powders are outlined in this chapter.

Dice Are Blessed Or Cursed, Warren Campbell, Cameron Miller

SEAS Faculty Publications

Dice are cursed or blessed; that is, they roll low or high, but they are never fair. They cannot be manufactured with uniform density and geometric precision. This is particularly true of 20-sided dice or D20s. Faces are smaller than 6-sided dice, and manufacturing tolerances are similar. However, some dice are fairer than others. In our studies of plastic-mold dice about 1 in 4 test fair in 3000 rolls. We have used different statistical tests, including chi-square, modified Kolmogorov Smirnov, and double binomial tests. Of these, the method that consistently performed better is the chi-square goodness of fit test. The …

A 3d Dlt View Correction Tool For Manual Digitizing: A Cross-Platform Application For Correcting Shifted Image Coordinates Prior To Object Coordinate Reconstruction, William Moynihan

Theses, Dissertations and Capstones

While 3D direct linear transformation is a versatile motion capture method, care must be taken so that the cameras are not bumped or adjusted between the object space calibration phase and the end of video recording. Disturbing the cameras during this time will misalign the view, making the movement data invalid for the associated calibration. The purpose of this study was to design and validate a cross-platform software application for transforming image coordinates from a bumped camera to be compatible with the object space calibration and to determine the relationship between reconstruction error and changes to bumped camera views.

For …

Molecular Identification To Verify The Existence Of Helicotylenchus Dihystera In Coffee Plants At East Java, Indonesia, Ankardiansyah Pandu Pradana, Toyoshi Yoshiga

ASEAN Journal on Science and Technology for Development

Spiral nematodes Helicotylenchus sp. are known to infect a variety of plants, including coffee. This is in line with the studies and surveys of nematodes in Indonesia. However, to date, there has been no study reporting the nematode with molecular analysis. In this study, we surveyed the nematodes in Arabica coffee plantations in Bondowoso regency – Indonesia. These spiral nematodes were collected in DESS solution for morphological, morphometric and molecular analysis. The morphometric analysis was carried out under an Olympus BH-2 compound microscope with an attached calibrated Toupcam M20 camera. The molecular analysis was performed on the total DNA from …

Species Distribution Modelling Using Bioclimatic Variables On Critically Endangered Endemic Species (Macrocephalon Maleo) In Sulawesi, Septianto Aldiansyah, Khalil Abdul Wahid

ASEAN Journal on Science and Technology for Development

The island of Sulawesi isolates migratory fauna from Asia and Australia and creates animal combinations such as the Maleo (Macrocephalon Maleo). The Maleo population is experiencing a downward trend due to habitat fragmentation, deforestation and threats by humans. This study aims to model the potential distribution of Maleo using several famous current and future models as a result of climate change throughout the island of Sulawesi, not only in its natural habitat, but beyond its natural habitat. Bioclimatic variables and in situ attendance data were used in this study. The method used is Maximum Entropy by evaluating the GLM, SVM …

The Musical Descriptor Using Fast Fourier Transform (Fft): Examples In P Ramlee Songs, Ahmad Faudzi Musib, Sinin Hamdan, Kuryati Kipli, Aaliyawani Ezzerin Sinin, Johari Abdullah

ASEAN Journal on Science and Technology for Development

The musical descriptor can be characterize using quantitative evaluation of audio sounds. This paper evaluates the musical descriptors for P Ramlee instrumental songs utilizing the Fast Fourier Transform (FFT) from the audio sounds signal. In this study, Python programming language is used to develop a series of custom scripts to calculate the musical descriptors. The approach involved constructing musical descriptors from instrumental music through analysis and digital processing of the spectra. The signal data were first transformed using the FFT to extract frequencies and intensities, which are crucial for identifying the spectral signature of musical sounds. The FFT is particularly …

Electrochromic Polymers: From Electrodeposition To Hybrid Solid Devices, Haradou Sare, Dongmei Dong

College of Science & Mathematics Departmental Research

This paper reports on the linear colorimetric and electrochromic (EC) characteristics of electrodeposited polyaniline (PANI) films. This paper also investigates the infrared EC properties of acid-doped PANI films. The electrochemical polymerization method was employed to create a porous and thin PANI film layer onto PET-ITO substrates. This layer was capped with WO3 film to create a gel electrolyte sandwich structure that demonstrates the compatibility of PANI films with cathodic WO3 films in full devices. The electrodeposition of the film was fabricated by applying different voltages and time, with the optimal film quality achieved with the 1.7 V voltage and a …

Understanding Patient Profiles In Sickle Cell Disease Using Unsupervised Machine Learning, Raj Kamal Somavarapu

Browse all Theses and Dissertations

Sickle Cell Disease (SCD) is one of the most prevalent genetic blood disorders affecting millions of people worldwide. It is often accompanied by acute and/or chronic pain leading to increased healthcare costs and adverse outcomes. Effective management of SCD requires an understanding of the diverse physiological profiles. This study employs unsupervised machine learning, specifically K-means clustering to categorize the patients suffering with SCD into different clusters based on their vital signs. The main aim is to identify the groups that reflect similarities in physiological and pain profiles, allowing an in-depth analysis to reveal distinctive features distinguishing patient clusters. The project …

Freyr⁺: Harvesting Idle Resources In Serverless Computing Via Deep Reinforcement Learning, Hanfei Yu, Hao Wang, Jian Li, Xu Yuan, Seung Jong Park

Computer Science Faculty Research & Creative Works

Serverless computing has revolutionized online service development and deployment with ease-to-use operations, auto-scaling, fine-grained resource allocation, and pay-as-you-go pricing. However, a gap remains in configuring serverless functions - the actual resource consumption may vary due to function types, dependencies, and input data sizes, thus mismatching the static resource configuration by users. Dynamic resource consumption against static configuration may lead to either poor function execution performance or low utilization. This paper proposes Freyr+, a novel resource manager (RM) that dynamically harvests idle resources from over-provisioned functions to accelerate under-provisioned functions for serverless platforms. Freyr+ monitors each function's resource utilization in real-time …

Empowering Kokal: A Decolonized, Community-Led Development Model In Homa Bay County, Kenya, Kennedy Miruka

Regis University Student Publications (comprehensive collection)

In Homa Bay County, Kenya, a community-led development initiative called the Power Centre is transforming the fight against poverty and powerlessness. Grounded in principles of decolonization and participatory action, this project addresses the root causes of marginalization by empowering residents of Kokal Village to become active agents of change. Through a robust mixed-methods research approach, the project identifies systemic challenges and leverages existing social networks to build a sustainable, locally-owned model for development. The Power Centre implements a three-pronged strategy, focusing on increasing community participation, strengthening existing groups, and fostering collaborative networks to weave a robust support system. By addressing …

Power Centres: A Collaborative Development Proposal For Addressing Poverty And Related Challenges In Rural Communities In Kenya, Kennedy Okello Miruka, Kennedy Okello Miruka

Regis University Student Publications (comprehensive collection)

In Homa Bay County, Kenya, a community-led development initiative called the Power Centre is transforming the fight against poverty and powerlessness. Grounded in principles of decolonization and participatory action, this project addresses the root causes of marginalization by empowering residents of Kokal Village to become active agents of change. Through a robust mixed-methods research approach, the project identifies systemic challenges and leverages existing social networks to build a sustainable, locally-owned model for development. The Power Centre implements a three-pronged strategy, focusing on increasing community participation, strengthening existing groups, and fostering collaborative networks to weave a robust support system. By addressing …

Winona State University Improving Our World Blog: 2013-2022, Winona State University

Winona State University Blogs

The Winona State University (WSU) Improving Our World Blog articles and entries from September 2013-February 2022. Note: there may be format coding in the document.

Winona State University Rochester Blog:2014-2023, Winona State University

Winona State University Blogs

The Winona State University (WSU) Rochester Blog includes articles and entries from May 2014-March 2023. Note: there may be format coding in the document.

Winona State University Campus Life Blog: 2013-2022, Winona State University

Winona State University Blogs

The Winona State University (WSU) Campus Life Blog includes articles and entries from October 2013- October 2022. Note: there may be format coding in the document.

Winona State University Wellness Blog: 2013-2023, Winona State University

Winona State University Blogs

The Winona State University (WSU) Wellness blog includes articles and entries from February 2013-February 2023. Note: there may be format coding in the document.

Bert-Based Detection Of Ai-Generated Text For Content Verification, Soham Biren Katlariwala

2024 REYES Proceedings

With advancements in AI-driven natural language generation, distinguishing between AI-generated and human-written text has become imperative for ensuring content authenticity across industries. This study explores the effectiveness of Bidirectional Encoder Representations from Transformers (BERT) in addressing this classification challenge. Utilizing a diverse dataset and robust preprocessing techniques, BERT achieved a peak F1-score of 0.94364, outperforming traditional models such as Logistic Regression and Support Vector Machines. The results underscore the potential of transformer-based models in addressing real-world con- tent verification problems. Future enhancements include fine-tuning and expanding datasets for greater generalizability.

Research Trends And Impact Report On Aggregation-Induced Emission (Aie), 2001-2021, Elsevier Analytical Services

Public Reports

Since the concept of AIE was first proposed in China in 2001, it has gradually grown to a field of science that attracts dedicated researchers from around the world. Elsevier's data analytics team used AIE experts' interpretation of current theoretical, technological, and industrial development trends in the field for reference to collect AIE-related global scientific publications (from the Scopus database) to serve as a publication set in the field of AIE. This was undertaken to present, accurately and objectively, the development of AIE research over the past two decades and the latest scientific advancements in the field; to facilitate the …

Predicting Compressive Strength Of Concrete Incorporating Fly Ash, Blast Furnace Slag, And Superplasticizer Using Machine Learning Techniques, Muhammad Faisal Yaqub

2024 REYES Proceedings

Concrete is the second most essential element in the construction industry, and its strength requirements vary based on the specific conditions of each project. However, determining the compressive strength of concrete involves laboratory tests, which wastes a lot of time and money. Researchers have developed machine learning models that predict the compressive strength of cement-based concrete having various mixes. In this research, the compressive strength of concrete incorporating fly ash, blast furnace slag, and superplasticizer is predicted using different machine learning models, namely, Linear Regression, Random Forest Regression, Decision Tree Regression, Extreme Gradient Boosting, Light Gradient Boosting, AdaBoost, and CatBoost …

Enhancing Robustness Of Graph Neural Network Against Adversarial Attacks By Balancing Local And Global Perspectives, Bibek Raj Joshi

Browse all Theses and Dissertations

Graph Neural Networks (GNNs) have increasingly gained popularity as tools for analyzing graph data in areas like biology, knowledge-graphs, social networks, biology, and recommendation systems. However, their vulnerability to adversarial attacks - small, targeted manipulations of graph structures or node features - raises serious concerns about their reliability in real-world applications. Existing defense strategies, such as adversarial training, edge filtering, low-rank approximations, and randomization-based methods, often suffer from high computational costs, scalability issues, or reduced clean-data performance. Unlike these methods, the proposed approach integrates multi-hop relationships, applies adaptive regularization, and maintains a balance between feature-based and structural embeddings, ensuring improved …

Meta-Learning-Based Model Stacking Framework For Hardware Trojan Detection In Fpga Systems, Mani Rupak Gurram

Browse all Theses and Dissertations

In today's technological landscape, hardware devices are integral to critical applications such as industrial automation, autonomous vehicles, and medical equipment, relying on advanced platforms like FPGAs for core functionalities. However, the multi-stage manufacturing process, often distributed across various foundries, introduces substantial security risks, notably the potential for hardware Trojan insertion. These malicious modifications compromise the reliability and safety of hardware systems. This research addresses the detection of hardware Trojans through side-channel analysis, utilizing power and electromagnetic signal data, combined with meta-learning techniques, specifically model stacking. By employing diverse base models and a meta-model to consolidate predictions, this non-invasive approach effectively …

Deep Transfer Learning For Detection Of Upper And Lower Body Movements: Transformer With Convolutional Neural Network, Kyle Lacroix, Davoud Gholamiangonabadi, Ana Luisa Trejos, Katarina Grolinger

Electrical and Computer Engineering Publications

When humans repeat the same motion, the tendons, muscles, and nerves can be damaged, causing Repetitive Stress Injuries (RSI). If the repetitive motions that lead to RSI are recognized early, actions can be taken to prevent these injuries. As Human Activity Recognition (HAR) aims to identify activities employing wearable or environment sensors, HAR is the first step toward identifying repetitive motions. Deep learning models, such as Convolutional Neural Networks (CNNs), have seen great success in recognizing activities for participants whose data are used in the model training; however, their accuracy drops for new participants as people move in different ways. …

Federated Learning For Sentiment Analysis In Presence Of Non-Iid Data: Sensitivity Of Deep Learning Models, Davoud Gholamiangonabadi, Katarina Grolinger

Electrical and Computer Engineering Publications

In sentiment analysis, data are commonly distributed across many devices, and traditional machine learning requires transferring these data to a central location exposing data to security and privacy risks. Federated Learning (FL) avoids this transfer by training a model without requiring the clients/devices to share their local data; however, FL performance drops when data are not Independent and Identically Distributed (non-IID), such as when label distribution or data size vary across clients. Although techniques for non-IID data have been proposed primarily in the image domain, the sensitivity of various deep learning models to non-IID data needs to be examined. Consequently, …

Cav-Ad: A Robust Framework For Detection Of Anomalous Data And Malicious Sensors In Cav Networks, Md Sazedur Rahman, Mohamed Elmahallawy, Sanjay Madria, Samuel Frimpong

Computer Science Faculty Research & Creative Works

The adoption of connected and automated vehicles (CAVs) has sparked considerable interest across diverse industries, including public transportation, underground mining, and agriculture sectors. However, CAVs' reliance on sensor readings makes them vulnerable to significant threats. Manipulating these readings can compromise CAV network security, posing serious risks for malicious activities. Although several anomaly detection (AD) approaches for CAV networks are proposed, they often fail to: i) detect multiple anomalies in specific sensor(s) with high accuracy or F1 score, and ii) identify the specific sensor being attacked. In response, this paper proposes a novel framework tailored to CAV networks, called CAV-AD, for …

การจัดลำดับความสำคัญของบทวิจารณ์ของผู้ใช้ซอฟต์แวร์โดยคำนึงถึงประสบการณ์ผู้ใช้โดยใช้การเรียนรู้ของเครื่อง, ลักษณ์สิปาง สาครวิจิตรี

Chulalongkorn University Theses and Dissertations (Chula ETD)

ปัจจุบันตลาดโมไบล์แอปพลิเคชันมีการแข่งขันสูง นักพัฒนาจึงจำเป็นต้องให้ความสำคัญกับบทวิจารณ์ของผู้ใช้ซึ่งบ่งบอกถึงความคิดเห็นและประสบการณ์ของผู้ใช้งานจริง เพื่อนำไปสู่การปรับปรุงและพัฒนาฟังก์ชันการทำงานให้ตรงตามความต้องการของผู้ใช้มากยิ่งขึ้น อย่างไรก็ตาม แอปพลิเคชันยอดนิยมมักมีบทวิจารณ์จำนวนมาก ทำให้เกิดข้อจำกัดในการที่นักพัฒนาจะสามารถอ่านและวิเคราะห์บทวิจารณ์ทั้งหมดได้อย่างมีประสิทธิภาพ เพื่อจัดการกับปัญหาดังกล่าว งานวิจัยฉบับนี้จึงนำเทคโนโลยีการเรียนรู้ของเครื่องเข้ามาช่วยในการจำแนกประเภทของบทวิจารณ์ โดยพิจารณาจากเนื้อหาในบทวิจารณ์ของผู้ใช้ซึ่งอาจสะท้อนถึงปัญหา ข้อบกพร่อง หรือข้อเสนอในการพัฒนาฟังก์ชันใหม่ ข้อมูลที่ได้จะถูกนำไปใช้จัดลำดับความสำคัญของการแก้ไขปรับปรุงตามผลกระทบที่มีต่อประสบการณ์ของผู้ใช้ งานวิจัยนี้ได้กำหนดหมวดหมู่ของบทวิจารณ์ไว้ทั้งหมด 5 ประเภท ได้แก่ ปัญหาด้านความจำเป็นพื้นฐาน, ปัญหาด้านการปฏิบัติ, ปัญหาด้านความเพลิดเพลิน, ปัญหาด้านความแปลกใหม่ และปัญหาอื่น ๆ ซึ่งสะท้อนลำดับความสำคัญของปัญหาจากมุมมองของผู้ใช้ ในการพัฒนาโมเดลการเรียนรู้ของเครื่องพบว่าโมเดลเบิร์ตมีประสิทธิภาพสูงกว่าโมเดลเอสวีเอ็ม แรนดอมฟอเรสต์ และโลจิสติกรีเกรสชัน โดยมีค่าความเที่ยงเป็น 0.72 ค่าเรียกกลับเป็น 0.719 ค่าเอฟวันเป็น 0.719 และค่าความแม่นเป็น 0.722 นอกจากนี้ งานวิจัยยังได้พัฒนาเว็บแอปพลิเคชันต้นแบบที่ใช้โมเดลเบิร์ตที่สร้างขึ้น เพื่อช่วยให้นักพัฒนาสามารถนำไปใช้วิเคราะห์และจัดลำดับความสำคัญของงานการบำรุงรักษาโมไบล์แอปพลิเคชัน โดยเว็บแอปพลิเคชันจะช่วยลดภาระในการอ่านบทวิจารณ์จำนวนมาก พร้อมทั้งสกัดข้อมูลที่สำคัญออกมาให้เห็นภาพรวมของความต้องการของผู้ใช้