Engineering Commons^™

Pollutant Forecasting Using Neural Network-Based Temporal Models, Richard Pike

Masters Theses & Specialist Projects

The Jing-Jin-Ji region of China is a highly industrialized and populated area of the country. Its periodic high pollution and smog includes particles smaller than 2.5 μm, known as PM2.5, linked to many respiratory and cardiovascular illnesses. PM2.5 concentration around Jing-Jin-Ji has exceeded China’s urban air quality safety threshold for over 20% of all days in 2017 through 2020.

The quantity of ground weather stations that measure the concentrations of these pollutants, and their valuable data, is unfortunately small. By employing many machine learning strategies, many researchers have focused on interpolating finer spatial grids of PM2.5, or hindcasting PM2.5. However, …

Source Code Plagiarism Detection Using Jplag & Stack Overflow Data, Sudheer Yetthapu

Masters Theses & Specialist Projects

Advancements in computer technology and internet services have led to the availability of vast amounts of information like videos, articles, research papers, and code samples. Free online information will increase the possibility of plagiarism and collusion among students. People can commit plagiarism in both text and code [1], as tools used to detect plagiarism between texts and between codes are distinct. Traditionally plagiarism in code is detected using manual inspection, which is a tedious process and misses to compare code from previous submissions and external sources. To overcome this issue, systems that can automatically detect plagiarism in code were developed …

Bibliography, Huanjing Wang

Faculty/Staff Personal Papers

Bibliography of publications by Huanjing Wang.

Robust Sensor Design For The Novel Reduced Models Of The Mead-Marcus Sandwich Beam Equation, Ahmet Aydin

Masters Theses & Specialist Projects

Novel space-discretized Finite Differences-based model reductions are proposed for the partial differential equations (PDE) model of a multi-layer Mead-Marcus-type beam with (i) hinged-hinged and (ii) clamped-free boundary conditions. The PDE model describes transverse vibrations for a sandwich beam whose alternating outer elastic layers constrain viscoelastic core layers, which allow transverse shear. The major goal of this project is to design a single boundary sensor, placed at the tip of the beam, to control the overall dynamics on the beam.

For (i), it is first shown that the PDE model is exactly observable by the so-called nonharmonic Fourier series approach. However, …

K-Means Clustering Using Gravity Distance, Ajinkya Vishwas Indulkar

Masters Theses & Specialist Projects

Clustering is an important topic in data modeling. K-means Clustering is a well-known partitional clustering algorithm, where a dataset is separated into groups sharing similar properties. Clustering an unbalanced dataset is a challenging problem in data modeling, where some group has a much larger number of data points than others. When a K-means clustering algorithm with Euclidean distance is applied to such data, the algorithm fails to form good clusters. The standard K-means tends to split data into smaller clusters during a clustering process evenly.

We propose a new K-means clustering algorithm to overcome the disadvantage by introducing a different …

Simplification Of Robotics Through Autonomous Navigation, Grant Turner

Mahurin Honors College Capstone Experience/Thesis Projects

With self-driving vehicles, college campus food delivery, or even automated home vacuuming systems, robotics is undoubtedly becoming more prevalent in everyday society and it can be expected to continue with time. While many people are owners, users, or even just spectators of theses robotic products or services, there seems to be a negative perception of robotics that poses an intimidation factor regarding the attempt to understand the ideas driving technology. This perception tends to view robotics as machines that require rich education to understand the complexity and interworkings of, thus attempts understand the field are neglected.

To combat this line …

Development Of An Autonomous Aerial Toolset For Agricultural Applications, Terrance Life

Mahurin Honors College Capstone Experience/Thesis Projects

According to the United Nations, the world population is expected to grow from its current 7 billion to 9.7 billion by the year 2050. During this time, global food demand is also expected to increase by between 59% and 98% due to the population increase, accompanied by an increasing demand for protein due to a rising standard of living throughout developing countries. [1] Meeting this increase in required food production using present agricultural practices would necessitate a similar increase in farmland; a resource which does not exist in abundance. Therefore, in order to meet growing food demands, new methods will …

A Comparative Study Of Recommendation Systems, Ashwini Lokesh

Masters Theses & Specialist Projects

Recommendation Systems or Recommender Systems have become widely popular due to surge of information at present time and consumer centric environment. Researchers have looked into a wide range of recommendation systems leveraging a wide range of algorithms. This study investigates three popular recommendation systems in existence, Collaborative Filtering, Content-Based Filtering, and Hybrid recommendation system. The famous MovieLens dataset was utilized for the purpose of this study. The evaluation looked into both quantitative and qualitative aspects of the recommendation systems. We found that from both the perspectives, the hybrid recommendation system performs comparatively better than standalone Collaborative Filtering or Content-Based Filtering …

Exploring The Effect Of Different Numbers Of Convolutional Filters And Training Loops On The Performance Of Alphazero, Jared Prince

Masters Theses & Specialist Projects

In this work, the algorithm used by AlphaZero is adapted for dots and boxes, a two-player game. This algorithm is explored using different numbers of convolutional filters and training loops, in order to better understand the effect these parameters have on the learning of the player. Different board sizes are also tested to compare these parameters in relation to game complexity. AlphaZero originated as a Go player using an algorithm which combines Monte Carlo tree search and convolutional neural networks. This novel approach, integrating a reinforcement learning method previously applied to Go (MCTS) with a supervised learning method (neural networks) …

Application Of Huffman Data Compression Algorithm In Hashing Computation, Lakshmi Narasimha Devulapalli Venkata,

Masters Theses & Specialist Projects

Cryptography is the art of protecting information by encrypting the original message into an unreadable format. A cryptographic hash function is a hash function which takes an arbitrary length of the text message as input and converts that text into a fixed length of encrypted characters which is infeasible to invert. The values returned by the hash function are called as the message digest or simply hash values. Because of its versatility, hash functions are used in many applications such as message authentication, digital signatures, and password hashing [Thomsen and Knudsen, 2005].

The purpose of this study is to apply …

Vertical Implementation Of Cloud For Education (V.I.C.E.), Travis S. Brummett

Masters Theses & Specialist Projects

There are several different implementations of open source cloud software that organizations can utilize when deploying their own private cloud. Some possible solutions are OpenNebula, Nimbus, and Eucalyptus. These are Infrastructure-as-a-Service (IaaS) cloud implementations that ultimately gives users virtual machines to undefined job types. A typical IaaS cloud is composed of a front-end cloud controller node, a cluster controller node for controlling compute nodes, a virtual machine image repository node, and many persistent storage nodes and compute nodes. These architectures are built for ease of scalability and availability.

Interestingly, the potential of such architectures could have in the educational field …

In The Face Of Anticipation: Decision Making Under Visible Uncertainty As Present In The Safest-With-Sight Problem, Bryan A. Knowles

Masters Theses & Specialist Projects

Pathfinding, as a process of selecting a fixed route, has long been studied in

Computer Science and Mathematics. Decision making, as a similar, but intrinsically different, process of determining a control policy, is much less studied. Here, I propose a problem that appears to be of the first class, which would suggest that it is easily solvable with a modern machine, but that would be too easy, it turns out. By allowing a pathfinding to anticipate and respond to information, without setting restrictions

on the \structure" of this anticipation, selecting the \best step" appears to be an intractable problem.

After …

Pedestrian Detection Using Basic Polyline: A Geometric Framework For Pedestrian Detection, Liang Gongbo

Masters Theses & Specialist Projects

Pedestrian detection has been an active research area for computer vision in recently years. It has many applications that could improve our lives, such as video surveillance security, auto-driving assistance systems, etc. The approaches of pedestrian detection could be roughly categorized into two categories, shape-based approaches and appearance-based approaches. In the literature, most of approaches are appearance-based. Shape-based approaches are usually integrated with an appearance-based approach to speed up a detection process.

In this thesis, I propose a shape-based pedestrian detection framework using the geometric features of human to detect pedestrians. This framework includes three main steps. Give a static …

Distributed Approach For Peptide Identification, Naga V K Abhinav Vedanbhatla

Masters Theses & Specialist Projects

A crucial step in protein identification is peptide identification. The Peptide Spectrum Match (PSM) information set is enormous. Hence, it is a time-consuming procedure to work on a single machine. PSMs are situated by a cross connection, a factual score, or a probability that the match between the trial and speculative is right and original. This procedure takes quite a while to execute. So, there is demand for enhancement of the performance to handle extensive peptide information sets. Development of appropriate distributed frameworks are expected to lessen the processing time.

The designed framework uses a peptide handling algorithm named C-Ranker, …

The Cadet Training Program Versus The Student Certification Program: A Study Of It- Support Training Programs At Western Kentucky University, Michael Courtney Moore

Masters Theses & Specialist Projects

Technology is a critical component of modern-day success. Advancements in technology have improved communication between individuals and companies. Technological advancements have allowed students to earn college degrees online. People who habitually use technology expect a high level of performance and support. As new technologies are implemented, such as complex web services or new operating systems, the dependence for information technology (IT) support grows in demand. Even learning curves can be cumbersome without proper assistance from IT professionals. Companies and institutions must accommodate user needs by implementing fast, efficient, and friendly support. In order to offer optimal customer support, representatives must …

A Novel Dataset-Similarity-Aware Approach For Evaluating Stability Of Software Metric Selection Techniques, Taghi M. Khoshgoftaar, Huanjing Wang, Randall Wald, Amri Napolitano

Computer Science Faculty Publications

Software metric (feature) selection is an important preprocessing step before building software defect prediction models. Although much research has been done analyzing the classification performance of feature selection methods, fewer works have focused on their stability (robustness). Stability is important because feature selection methods which reliably produce the same results despite changes to the data are more trustworthy. Of the papers studying stability, most either compare the features chosen from different random subsamples of the dataset or compare each random subsample with the original dataset. These either result in an unknown degree of overlap between the subsamples, or comparing datasets …

Stability And Classification Performance Of Feature Selection Techniques, Huanjing Wang, Taghi Khoshgoftaar, Qianhui Liang

Computer Science Faculty Publications

Feature selection techniques can be evaluated based on either model performance or the stability (robustness) of the technique. The ideal situation is to choose a feature selec- tion technique that is robust to change, while also ensuring that models built with the selected features perform well. One domain where feature selection is especially important is software defect prediction, where large numbers of met- rics collected from previous software projects are used to help engineers focus their efforts on the most faulty mod- ules. This study presents a comprehensive empirical ex- amination of seven filter-based feature ranking techniques (rankers) applied to …

Measuring Stability Of Threshold-Based Feature Selection Techniques, Huanjing Wang, Taghi Khoshgoftaar

Computer Science Faculty Publications

Feature selection has been applied in many domains, such as text mining and software engineering. Ideally a feature selection technique should produce consistent out- puts regardless of minor variations in the input data. Re- searchers have recently begun to examine the stability (robustness) of feature selection techniques. The stability of a feature selection method is defined as the degree of agreement between its outputs to randomly-selected subsets of the same input data. This study evaluated the stability of 11 threshold-based feature ranking techniques (rankers) when applied to 16 real-world software measurement datasets of different sizes. Experimental results demonstrate that AUC …

Measuring Robustness Of Feature Selection Techniques On Software Engineering Datasets, Huanjing Wang, Taghi Khoshgoftaar, Randall Wald

Computer Science Faculty Publications

Feature Selection is a process which identifies irrelevant and redundant features from a high-dimensional dataset (that is, a dataset with many features), and removes these before further analysis is performed. Recently, the robustness (e.g., stability) of feature selection techniques has been studied, to examine the sensitivity of these techniques to changes in their input data. In this study, we investigate the robustness of six commonly used feature selection techniques as the magnitude of change to the datasets and the size of the selected feature subsets are varied. All experiments were conducted on 16 datasets from three real-world software projects. The …

Ua3/9/2 I.T. Division Annual Report + Tactical Plan, Wku Information Technology

WKU Archives Records

Annual report of WKU Information Technology Division submitted to WKU President Gary Ransdell. Report is housed in UA3/9/2 Subject Files.

Back-Up Server For Computer Science Department, Victoria Gaylord

Mahurin Honors College Capstone Experience/Thesis Projects

Because Western Kentucky University does not maintain a back-up system for its departments, the Computer Science Department has implemented its own. Using Bacula software on a Unix server, files from faculty desktop computers and servers are backed up to a tape drive on a daily basis. The server is protected from outside threats with a carefully configured firewall script. This paper explains how both the firewall and the back-up software were implemented and how successful that implementation has been.

Ua66 2007 Student Awards Ceremony, Wku Ogden College Of Science & Engineering

WKU Archives Records

Program recognizing Ogden College students with brief list of activities for each student.

Ua1b2/1/5 Oral History, Paula Trafton, Charles Anderson

WKU Archives Records

Interview conducted by Paula Trafton with Charles Anderson, retired Vice President for Information Technology.