Other Computer Engineering Commons^™

Streaming Mysql Database Activity To Aws Kinesis, Chris I. Voncina

Computer Engineering

Connecting Amazon RDS MySQL engine with AWS Kinesis is a feature that RDS customers have often requested. A good example indicating customer demand is demonstrated on AWS’ forum post at https://forums.aws.amazon.com/thread.jspa?messageID=697516.

Upon completion, my project will enable Amazon RDS to pick up the MySQL open source project, integrate the MySQL plugin with Amazon RDS MySQL and deliver this feature to Amazon RDS MySQL customers. Other open source engine projects can follow and build upon my project.

Amazon Aurora delivered similar capability to the project. See details at https://aws.amazon.com/about-aws/whats-new/2016/10/amazon-aurora-new-features-aws-lambda-integration-and-data-load-from-amazon-s3-to-aurora-tables/

Real Time And High Fidelity Quadcopter Tracking System, Tyler Mckay Hall

Computer Engineering

This project was conceived as a desired to have an affordable, flexible and physically compact tracking system for high accuracy spatial and orientation tracking. Specifically, this implementation is focused on providing a low cost motion capture system for future research. It is a tool to enable the further creation of systems that would require the use of accurate placement of landing pads, payload acquires and delivery. This system will provide the quadcopter platform a coordinate system that can be used in addition to GPS.

Field research with quadcopter manufacturers, photographers, agriculture and research organizations were contact and interviewed for information …

Demand Side Management In Smart Grid Using Big Data Analytics, Sidhant Chatterjee

All Graduate Plan B and other Reports, Spring 1920 to Spring 2023

Smart Grids are the next generation electrical grid system that utilizes smart meter-ing devices and sensors to manage the grid operations. Grid management includes the prediction of load and and classification of the load patterns and consumer usage behav-iors. These predictions can be performed using machine learning methods which are often supervised. Supervised machine learning signifies that the algorithm trains the model to efficiently predict decisions based on the previously available data.

Smart grids are employed with numerous smart meters that send user statistics to a central server. The data can be accumulated and processed using data mining and machine …

A Data Hiding Scheme Based On Chaotic Map And Pixel Pairs, Sengul Dogan Sd

Journal of Digital Forensics, Security and Law

Information security is one of the most common areas of study today. In the literature, there are many algorithms developed in the information security. The Least Significant Bit (LSB) method is the most known of these algorithms. LSB method is easy to apply however it is not effective on providing data privacy and robustness. In spite of all its disadvantages, LSB is the most frequently used algorithm in literature due to providing high visual quality. In this study, an effective data hiding scheme alternative to LSB, 2LSBs, 3LSBs and 4LSBs algorithms (known as xLSBs), is proposed. In this method, random …

Pubwc Bathroom Review App, Clay Jacobs

Computer Science and Software Engineering

For my senior project, I developed an iOS application to allow users to find, rate, and review nearby public restrooms. The app takes advantage of crowdsourced data to collect bathroom and review information. I also created a REST API to interface with the backend database that could be used to port the application to other platforms.

Cloudskulk: Design Of A Nested Virtual Machine Based Rootkit-In-The-Middle Attack, Joseph Anthony Connelly

Boise State University Theses and Dissertations

Virtualized cloud computing services are a crucial facet in the software industry today, with clear evidence of its usage quickly accelerating. Market research forecasts an increase in cloud workloads by more than triple, 3.3-fold, from 2014 to 2019 [33]. Integrating system security is then an intrinsic concern of cloud platform system administrators that with the growth of cloud usage, is becoming increasingly relevant. People working in the cloud demand security more than ever. In this paper, we take an offensive, malicious approach at targeting such cloud environments as we hope both cloud platform system administrators and software developers of these …

Development Of Some Scalable Pattern Recognition Algorithms For Real Life Data Analysis, Partha Garai

Doctoral Theses

A huge amount of data is being generated continuously as a result of recent advancement and wide use of high-throughput technologies. With the rapid increase in size of data distributed worldwide, understanding the data has become critical. In this regard, dimensionality reduction and clustering have become the necessary preprocessing steps of multiple research areas and applications. One of the important problems of real life large data sets is uncertainty. Some of the sources of this uncertainty include imprecision in computation and vagueness in class denitions. The uncertainty may also be present in the denition of class membership function. In this …

Applied Deep Learning: Automated Segmentation Of White Matter Hyperintensities (Wmh) On Brain Mr Images, Matt Berseth

DHI Digital Projects Showcase

Small vessel disease plays a crucial role in stroke, dementia, and ageing. White matter hyperintensities (WMH) of vascular origin are one of the main consequences of small vessel disease and well visible on brain MR images. Quantification of WMH volume, location, and shape is of key importance in clinical research studies and likely to find its way into clinical practice; supporting diagnosis, prognosis, and monitoring of treatment for dementia and other neurodegenerative diseases. It has been noted that visual rating of WMH has important limitations and hence a more detailed segmentation of WMH is preferred. Various automated WMH segmentation techniques …

2fly With Rpi - Evaluating The Raspberry Pi For Glass Cockpit Applications, Donald R. Morris

ASA Multidisciplinary Research Symposium

Evaluating the capabilities of Raspberry Pi computers to be used in embedded glass cockpit applications for experimental aircraft. This includes details of what is required for these applications as well as how well the Raspberry Pi 3B can perform in this role.

Simple Implementation Of An Elgamal Digital Signature And A Brute Force Attack On It, Valeriia Laryoshyna

Student Works

This study is an attempt to show a basic mathematical usage of the concepts behind digital signatures and to provide a simple approach and understanding to cracking basic digital signatures. The approach takes on simple C programming of the ElGamal digital signature to identify some limits that can be encountered and provide considerations for making more complex code. Additionally, there is a literature review of the ElGamal digital signature and the brute force attack.

The research component of this project provides a list of possible ways to crack the basic implementations and classifies the different approaches that could be taken …

In Search Of Homo Sociologicus, Yunqi Xue

Dissertations, Theses, and Capstone Projects

The subject of this dissertation is to build an epistemic logic system that is able to show the spreading of knowledge and beliefs in a social network that contains multiple subgroups. Epistemic logic is the study of logical systems that express mathematical properties of knowledge and belief. In recent years, there have been increasing number of new epistemic logic systems that are focused on community properties such as knowledge and belief adoption among friends.

We are interested in revisable and actionable social knowledge/belief that leads to a large group action. Instead of centralized coordination, bottom-up approach is our focus. We …

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 …

Research On Improving Navigation Safety Based On Big Data And Cloud Computing Technology For Qiongzhou Strait, Rui Wang

Maritime Safety & Environment Management Dissertations (Dalian)

No abstract provided.

Data-Driven Abstraction, Vivian Mankau Ho

LSU Master's Theses

Given a program analysis problem that consists of a program and a property of interest, we use a data-driven approach to automatically construct a sequence of abstractions that approach an ideal abstraction suitable for solving that problem. This process begins with an infinite concrete domain that maps to a finite abstract domain defined by statistical procedures resulting in a clustering mixture model. Given a set of properties expressed as formulas in a restricted and bounded variant of CTL, we can test the success of the abstraction with respect to a predefined performance level. In addition, we can perform iterative abstraction-refinement …

Improving Disciplinary Literacy In An Electronics Course, Ohbong Kwon, Juanita C. But, Sunghoon Jang

Publications and Research

Electronics (EMT1255) is a required course for the Associate Degree in Applied Science (AAS) in Electromechanical Engineering Technology (EMT) at New York City College of Technology. EMT1255 introduces semiconductor devices and their applications in electronic-circuits. Students are expected to understand the structures and principles of semiconductor devices and the configuration and principles of basic electronic circuits. They also learn to analyze and design electronic circuits. In the lab setting, they acquire troubleshooting knowledge and hands-on technical skills. In this reading intensive course, students need to read the lab manual and a textbook of over 700 pages. Therefore, reading and understanding …

Compiler And Runtime Optimization Techniques For Implementation Scalable Parallel Applications, Zahra Khatami

LSU Doctoral Dissertations

The compiler is able to detect the data dependencies in an application and is able to analyze the specific sections of code for parallelization potential. However, all of these techniques provided by a compiler are usually applied at compile time, so they rely on static analysis, which is insufficient for achieving maximum parallelism and desired application scalability. These compiler techniques should consider both the static information gathered at compile time and dynamic analysis captured at runtime about the system to generate a safe parallel application. On the other hand, runtime information is often speculative. Solely relying on it doesn't guarantee …

Dynamic Adversarial Mining - Effectively Applying Machine Learning In Adversarial Non-Stationary Environments., Tegjyot Singh Sethi

Electronic Theses and Dissertations

While understanding of machine learning and data mining is still in its budding stages, the engineering applications of the same has found immense acceptance and success. Cybersecurity applications such as intrusion detection systems, spam filtering, and CAPTCHA authentication, have all begun adopting machine learning as a viable technique to deal with large scale adversarial activity. However, the naive usage of machine learning in an adversarial setting is prone to reverse engineering and evasion attacks, as most of these techniques were designed primarily for a static setting. The security domain is a dynamic landscape, with an ongoing never ending arms race …

Computer-Aided Detection Of Pathologically Enlarged Lymph Nodes On Non-Contrast Ct In Cervical Cancer Patients For Low-Resource Settings, Brian M. Anderson, Laurence E. Court, Ann Klopp, Stephen F. Kry, Jennifer Johnson, Erik Cressman, Arvind Rao, Jinzhong Yang

Dissertations and Theses (Open Access)

The mortality rate of cervical cancer is approximately 266,000 people each year, and 70% of the burden occurs in Low- and Middle- Income Countries (LMICs). Radiation therapy is the primary modality for treatment of locally advanced cervical cancer cases. In the absence of high quality diagnostic imaging needed to identify nodal metastasis, many LMIC sites treat standard pelvic fields, failing to include node metastasis outside of the field and/or to boost lymph nodes in the abdomen and pelvis. The first goal of this project was to create a program which automatically identifies positive cervical cancer lymph nodes on non-contrast daily …

Prediction Of Graduation Delay Based On Student Characterisitics And Performance, Tushar Ojha

Electrical and Computer Engineering ETDs

A college student's success depends on many factors including pre-university characteristics and university student support services. Student graduation rates are often used as an objective metric to measure institutional effectiveness. This work studies the impact of such factors on graduation rates, with a particular focus on delay in graduation. In this work, we used feature selection methods to identify a subset of the pre-institutional features with the highest discriminative power. In particular, Forward Selection with Linear Regression, Backward Elimination with Linear Regression, and Lasso Regression were applied. The feature sets were selected in a multivariate fashion. High school GPA, ACT …

Distributed Knowledge Discovery For Diverse Data, Hossein Hamooni

Computer Science ETDs

In the era of new technologies, computer scientists deal with massive data of size hundreds of terabytes. Smart cities, social networks, health care systems, large sensor networks, etc. are constantly generating new data. It is non-trivial to extract knowledge from big datasets because traditional data mining algorithms run impractically on such big datasets. However, distributed systems have come to aid this problem while introducing new challenges in designing scalable algorithms. The transition from traditional algorithms to the ones that can be run on a distributed platform should be done carefully. Researchers should design the modern distributed algorithms based on the …