Other Computer Engineering Commons^™

Quiz Web Application, Dipti Rathod

Electronic Theses, Projects, and Dissertations

The Quiz web application is designed to facilitate the process of quiz creation and participation. This web application mainly consists of three roles: Admin, Instructor, and Student. Each role has specific features, functionalities, and permissions. With a user-friendly interface, the admin role can handle the departments, courses, and instructors. This web application also ensures smooth quiz management, allowing the instructors to schedule the upcoming quizzes, create the questions, and manage the students with ease. Student roles have features like taking quizzes and seeing their results. Additionally, this web application includes a significant feature to prevent cheating during online tests, ensuring …

Hypothyroid Disease Analysis By Using Machine Learning, Sanjana Seelam

Electronic Theses, Projects, and Dissertations

Thyroid illness frequently manifests as hypothyroidism. It is evident that people with hypothyroidism are primarily female. Because the majority of people are unaware of the illness, it is quickly becoming more serious. It is crucial to catch it early on so that medical professionals can treat it more effectively and prevent it from getting worse. Machine learning illness prediction is a challenging task. Disease prediction is aided greatly by machine learning. Once more, unique feature selection strategies have made the process of disease assumption and prediction easier. To properly monitor and cure this illness, accurate detection is essential. In order …

Early-Warning Prediction For Machine Failures In Automated Industries Using Advanced Machine Learning Techniques, Satnam Singh

Electronic Theses, Projects, and Dissertations

This Culminating Experience Project explores the use of machine learning algorithms to detect machine failure. The research questions are: Q1) How does the quality of input data, including issues such as outliers, and noise, impact the accuracy and reliability of machine failure prediction models in industrial settings? Q2) How does the integration of SMOTE with feature engineering techniques influence the overall performance of machine learning models in detecting and preventing machine failures? Q3) What is the performance of different machine learning algorithms in predicting machine failures, and which algorithm is the most effective? The research findings are: Q1) Effective outlier …

Improving Credit Card Fraud Detection Using Transfer Learning And Data Resampling Techniques, Charmaine Eunice Mena Vinarta

Electronic Theses, Projects, and Dissertations

This Culminating Experience Project explores the use of machine learning algorithms to detect credit card fraud. The research questions are: Q1. What cross-domain techniques developed in other domains can be effectively adapted and applied to mitigate or eliminate credit card fraud, and how do these techniques compare in terms of fraud detection accuracy and efficiency? Q2. To what extent do synthetic data generation methods effectively mitigate the challenges posed by imbalanced datasets in credit card fraud detection, and how do these methods impact classification performance? Q3. To what extent can the combination of transfer learning and innovative data resampling techniques …

Lung Lesion Segmentation Using Deep Learning Approaches, Sree Snigdha Tummala

Electronic Theses, Projects, and Dissertations

The amount of data generated in the medical imaging field, especially in a modern context, is growing significantly. As the amount of data grows, it's prudent to make use of automated techniques that can leverage datasets to solve problems that are error-prone or have inconsistent solutions.

Deep learning approaches have gained traction in medical imaging tasks due to their superior performance with larger datasets and ability to discern the intricate features of 3D volumes, a task inefficient if done manually. Specifically for the task of lung nodule segmentation, several different methods have been tried before such as region growing etc. …

Automated Medical Notes Labelling And Classification Using Machine Learning, Akhil Prabhakar Thota

Electronic Theses, Projects, and Dissertations

The amount of data generated in medical records, especially in a modern context, is growing significantly. As the amount of data grows, it is very useful to classify the data into relevant classes for further interventions. Different methods that are not automated are very time-consuming and require manual effort have been tried for this before.

Recently deep learning has been used for this task but due to the complexity of the dataset, specifically due to inter-class similarities in the dataset and specific terminology having different meanings in medical contexts has caused significant problems in having a definitive approach to medical …

Classification Of Large Scale Fish Dataset By Deep Neural Networks, Priyanka Adapa

Electronic Theses, Projects, and Dissertations

The development of robust and efficient fish classification systems has become essential to preventing the rapid depletion of aquatic resources and building conservation strategies. A deep learning approach is proposed here for the automated classification of fish species from underwater images. The proposed methodology leverages state-of-the-art deep neural networks by applying the compact convolutional transformer (CCT) architecture, which is famous for faster training and lower computational cost. In CCT, data augmentation techniques are employed to enhance the variability of the training data, reducing overfitting and improving generalization. The preliminary outcomes of our proposed method demonstrate a promising accuracy level of …

Finserv Android Application, Harsh Piyushkumar Shah

Electronic Theses, Projects, and Dissertations

The FINSERV Android application is a mobile tool designed for individuals to manage and track their finances. In financially complex world, many people struggle to maintain a clear overview of their income, expenses, and financial goals. This application aims to bridge that gap by providing users with a powerful and user-friendly platform to efficiently monitor and optimize their personal finances.

With the Personal Finance Tracking Android Application, users can effortlessly track their income and expenses, categorize transactions, and gain valuable insights into their spending patterns. The application offers features such as expense categorization and real-time expense tracking.

To enhance usability …

Analyzing The Impact Of Automation On Employment In Different Us Regions: A Data-Driven Approach, Thejaas Balasubramanian

Electronic Theses, Projects, and Dissertations

Automation is transforming the US workforce with the increasing prevalence of technologies like robotics, artificial intelligence, and machine learning. As a result, it is essential to understand how this shift will impact the labor market and prepare for its effects. This culminating experience project aimed to examine the influence of computerization on jobs in the United States and answer the following research questions: Q1. What factors affect how likely different jobs will be automated? Q2. What are the possible effects of automation on the US workforce across states and industries? Q3. What are the meaningful predictors of the likelihood of …

Bridging The Gap Between Public Organizaions And Cybersecurity, Christopher Boutros

Electronic Theses, Projects, and Dissertations

Cyberattacks are a major problem for public organizations across the nation, and unfortunately for them, the frequency of these attacks is constantly growing. This project used a case study approach to explore the types of cybersecurity public organization agencies face and how those crimes can be mitigated. The goal of this paper is to understand how public organization agencies have prepared for cyberattacks and discuss additional suggestions to improve their current systems with the current research available This research provides an analysis of current cyber security systems, new technologies that can be implemented, roadblocks public agencies face before and during …

A Long-Term Funds Predictor Based On Deep Learning, Shuiyi Kuang

Electronic Theses, Projects, and Dissertations

Numerous neural network models have been created to predict the rise or fall of stocks since deep learning has gained popularity, and many of them have performed quite well. However, since the share market is hugely influenced by various policy changes or unexpected news, it is challenging for investors to use such short-term predictions as a guide. In this paper, we try to find a suitable long-term predictor for the funds market by testing different kinds of neural network models, including the Long Short-Term Memory(LSTM) model with different layers, the Gated Recurrent Units(GRU) model with different layers, and the combination …

Pillow Based Sleep Tracking Device Using Raspberry Pi, Venkatachalam Seviappan

Electronic Theses, Projects, and Dissertations

Almost half of all people have sleep interruptions at some point in their lives, making sleep disorders a common issue that affects a sizeable section of the population. Both their physical and emotional well-being may suffer as a result of this.Insomnia, which is a prevalent sleep disorder, is identified by symptoms including insufficient sleep duration and quality, trouble initiating sleep, multiple nighttime awakenings, early morning awakenings, and non-restorative sleep. It is essential to employ sleep monitoring systems to detect sleeping disorders as soon as possible for prompt diagnosis and treatment. To avoid sleep related health issues, there are plenty of …

Ott Subscriber Churn Prediction Using Machine Learning, Needhi Devan Senthil Kumar

Electronic Theses, Projects, and Dissertations

Subscriber churn is a critical issue for companies that rely on recurring revenue from subscription-based services like the OTT platform. Machine Learning algorithms can be used to predict churn and develop targeted retention strategies to address the specific needs and concerns of at-risk subscribers. The research questions are 1) What Machine Learning algorithms are used to overcome subscriber churn? 2) How to predict subscribers’ churn in the OTT platform using Machine Learning? 3) How to retain subscribers and improve customer targeting? The dataset was collected from the Kaggle repository and implemented it into the various prediction algorithms used in previous …

Max Fit Event Management With Salesforce, Akshay Dagwar

Electronic Theses, Projects, and Dissertations

MAX FIT Gym is looking for an event management software program to help manage activities very efficiently, along with attendees and environmental statistics. The event management program is developed and deployed using the Salesforce platform. MAX FIT can efficiently create, edit, and remove events and send email alerts to clients. This task operated on opportunities captured under MAX FIT, including all clients, and prepared information in the Salesforce cloud. This also includes product inventory with various varieties of protein products, and business owners can also add more products to their inventory. In the event management program, the event addresses within …

A Study Of Heart Disease Diagnosis Using Machine Learning And Data Mining, Intisar Ahmed

Electronic Theses, Projects, and Dissertations

Heart disease is the leading cause of death for people around the world today. Diagnosis for various forms of heart disease can be detected with numerous medical tests, however, predicting heart disease without such tests is very difficult. Machine learning can help process medical big data and provide hidden knowledge which otherwise would not be possible with the naked eye. The aim of this project is to explore how machine learning algorithms can be used in predicting heart disease by building an optimized model. The research questions are; 1) What Machine learning algorithms are used in the diagnosis of heart …

Lung Cancer Type Classification, Mohit Ramajibhai Ankoliya

Electronic Theses, Projects, and Dissertations

Lung cancer is the third most common cancer in the U.S. This research focuses on classifying lung cancer cells based on their tumor cell, shape, and biological traits in images automatically obtained by passing through the

convolutional layers. Additionally, I classify whether the lung cell is adenocarcinoma, large cell carcinoma, squamous cell carcinoma, or normal cell carcinoma. The benefit of this classification is an accurate prognosis, leading to patients receiving proper therapy. The Lung Cancer CT(Computed Tomography) image dataset from Kaggle has been drawn with 1000 CT images of various types of lung cancer. Two state-of-the-art convolutional neural networks (CNNs) …

Ahmedabad City App, Rushabh Picha

Electronic Theses, Projects, and Dissertations

The Ahmedabad City App is a city guide app that provides information on the city's accessible resources. The project's goal is to provide a concrete, one-stop platform for finding information on all of Ahmedabad's accessible resources. The main goal is to simplify the railway's schedule and make it easier for customers to get from one point to another swiftly and safely. Emergency connections such as the blood bank, fire department, police station, and hospitals will be included in the app. Restaurants and picnic areas are also included in the rejuvenation process.

The proposed system uses SQLite as the database and …

Towards A Fault-Tolerant, Scheduling Methodology For Safety-Critical Certified Information Systems, Jian Lin

Journal of International Technology and Information Management

Today, many critical information systems have safety-critical and non-safety-critical functions executed on the same platform in order to reduce design and implementation costs. The set of safety-critical functionality is subject to certification requirements and the rest of the functionality does not need to be certified, or is certified to a lower level. The resulting mixed-criticality systems bring challenges in designing such systems, especially when the critical tasks are required to complete with a timing constraint. This paper studies a problem of scheduling a mixed-criticality system with fault tolerance. A fault-recovery technique called checkpointing is used where a program can go …

Social Network For Software Developers, Sanket Prabhakar Jadhav

Electronic Theses, Projects, and Dissertations

This project is the design and implementation of a web-based message board for software developers. The purpose of “Social Network for Software Developers” is to connect inexperienced software developers with experienced software developers.

Organize Events Mobile Application, Thakshak Mani Chandra Reddy Gudimetla

Electronic Theses, Projects, and Dissertations

In a big organization there are many events organized every day. To know about the events, we typically need to check an events page, rely on flyers or on distributed pamphlets or through word of mouth. To register for an event a user now a days typically does this online which involves inputting user details. At the event, the user either signs a sheet of paper or enters credentials in a web page loaded on a tablet or other electronic device. Typically, this is a time-consuming process with many redundancies like entering user details every time the user wants to …

Introducing Competencies In Organizations, Henk Plessius, Anand Sheombar, Pascal Ravesteyn

Communications of the IIMA

In the fast-changing world of IT, relevant competencies are getting more important as these determine how successful you can function in practice. As a consequence, organizations are introducing competency frameworks like the European e-Competence Framework (e-CF, 2014) in their IT departments. However, for many organizations it is unclear what good practices and pitfalls are when introducing such a framework. In this paper this topic is studied by analysing 13 interviews with IT- and HR-managers who are (or recently have been) involved in a transition towards the use of competencies with their IT-staff.

Natural Language Processing Based Generator Of Testing Instruments, Qianqian Wang

Electronic Theses, Projects, and Dissertations

Natural Language Processing (NLP) is the field of study that focuses on the interactions between human language and computers. By “natural language” we mean a language that is used for everyday communication by humans. Different from programming languages, natural languages are hard to be defined with accurate rules. NLP is developing rapidly and it has been widely used in different industries. Technologies based on NLP are becoming increasingly widespread, for example, Siri or Alexa are intelligent personal assistants using NLP build in an algorithm to communicate with people. “Natural Language Processing Based Generator of Testing Instruments” is a stand-alone program …

Android Mobile Application For Hospital Executives, Vihitha Nalagatla

Electronic Theses, Projects, and Dissertations

Hospitals are the largest and most complex organizations where health care is provided. Safe and effective patient care services in hospitals depend on the efficient decisions made by hospital executives. The main task of hospital executives is to ensure the hospital can provide high quality patient care and services. “Android Mobile Application For Hospital Executives” is an Android application used for displaying hospital performance metrics on a daily basis. This application allows hospital executives to review and monitor hospital operational data with ease of access and in a portable manner. Thus, reducing the effort of the hospital executives to perform …

Coyotelab - Linux Containers For Educational Use, Michael D. Korcha

Electronic Theses, Projects, and Dissertations

CoyoteLab is an exploration in the use of Linux container technology as a means to simplify the way students in computing fields access and complete laboratory work in their educational career. This project provides two main benefits: creating a simple way for students to log in and access their coursework without anything more than their web browser, and providing course instructors a way to verify that assigned work is completed successfully. Thanks to advances in container technology and the advent of WebSockets, this becomes a middle layer between a WebSocket opened up on the client’s browser and the SSH daemon …

Estimation On Gibbs Entropy For An Ensemble, Lekhya Sai Sake

Electronic Theses, Projects, and Dissertations

In this world of growing technology, any small improvement in the present scenario would create a revolution. One of the popular revolutions in the computer science field is parallel computing. A single parallel execution is not sufficient to see its non-deterministic features, as same execution with the same data at different time would end up with a different path. In order to see how non deterministic a parallel execution can extend up to, creates the need of the ensemble of executions. This project implements a program to estimate the Gibbs Entropy for an ensemble of parallel executions. The goal is …

Developing Java Programs On Android Mobile Phones Using Speech Recognition, Santhrushna Gande

Electronic Theses, Projects, and Dissertations

Nowadays Android operating system based mobile phones and tablets are widely used and had millions of users around the world. The popularity of this operating system is due to its multi-tasking, ease of access and diverse device options. “Java Programming Speech Recognition Application” is an Android application used for handicapped individuals who are not able or have difficultation to type on a keyboard. This application allows the user to write a compute program (in Java Language) by dictating the words and without using a keyboard. The user needs to speak out the commands and symbols required for his/her program. The …

Antics: A Cross-Platform Mobile Game, Gerren D. Willis

Electronic Theses, Projects, and Dissertations

Recent technologies have made it increasingly easier for independent developers to build and deploy gaming applications for mobile devices. The focus of this master's project is to investigate one such set of technologies, which include Adobe AIR, Starling and Feathers, that allow games to be written in ActionScript and run on both Android and iOS devices. For this purpose, I chose to use these technologies to design and implement the game ANTics proposed by Whim Independent Studios, a start up game studio in San Bernardino. ANTics is written in ActionScript and runs on Adobe AIR. It can be deployed on …

Density Based Data Clustering, Rayan Albarakati

Electronic Theses, Projects, and Dissertations

Data clustering is a data analysis technique that groups data based on a measure of similarity. When data is well clustered the similarities between the objects in the same group are high, while the similarities between objects in different groups are low. The data clustering technique is widely applied in a variety of areas such as bioinformatics, image segmentation and market research.

This project conducted an in-depth study on data clustering with focus on density-based clustering methods. The latest density-based (CFSFDP) algorithm is based on the idea that cluster centers are characterized by a higher density than their neighbors and …

The I: A Client-Based Point-And-Click Puzzle Game, Aldo Lewis

Electronic Theses, Projects, and Dissertations

Given mobile devices’ weak computational power, game programmers must learn to create games with simple graphics that are engaging and easy to play. Though seldom created for phones and tablets, puzzle games are a perfect fit. In recent years, the genre has gained a following and even won some acclaim. Games like Myst, The Seventh Guest and Portal all engage gamers with challenging puzzles and then reward them with story components upon task fulfillment. Few such games have been created for mobile devices, in part due to the difficulty of developing for devices with different operating systems. Android, WebIOS and …