Computer Science Masters Papers

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Adaptive Mesh Refinment Applications for Adviction-Diffusion Problems Using Amrex
(North Dakota State University, 2020) Kanumuru, Venkata
In this paper we implemented an adaptive mesh refinement in high performance computing environment to study a wide range of problems in engineering. They are nonlinear Fisher-Kolmogorov equation, heat equation, advection equation and poisons equation using traditional message passing interface (MPI). We used adaptive mesh refinement library called AMReX for computation. AMReX is a numerical library containing the functionality to write massively parallel, block-structured adaptive mesh refinement (AMR) applications. Our study includes examples to solve poisons equation in traditional MPI approach and compared the performance between the two methods.
Advanced Computational Ratings for College Football Teams
(North Dakota State University, 2010) Hensley, Joel Michael
This paper explores the subject of rating systems applied to the world of college football. Current rating system methodologies are examined, and four rating systems are developed and evaluated in a program. The Hensley Rating system is introduced as a new method. The details of each of these systems are discussed, and the results are analyzed and evaluated using data from the college football seasons of 2000 - 2009.
Agent Based Modeling for Simulation of Microbial Community
(North Dakota State University, 2018) Tekeste, Noah Daniel
Agent based modeling uses interacting agents and a governing rule to understand a complex phenomenon. It is an important mode of inquiry in the field of life sciences. For this paper a Haploid Evolutionary Constructor (HEC) tool was used for modeling and simulation of two sample models. The model samples were analyzed under the same and varying level of specific and non-specific substrates. In the first part of each experiment, the survival rate of the models was examined based on the model’s inputs and outputs. However, since close association of microbes enhances the probability of Horizontal Gene Transfer (HGT) between organisms, HGT behavior was introduced within the populations in the second sets of experiments. This enabled them to adapt to dwindling resources in their environment and creation of new populations that are better suited for the ecosystem. Based on the obtained results, the behavior of the dominant population(s) is assessed.
Agent-Based Modeling to Simulate the Movement of a Flock of Birds
(North Dakota State University, 2013) Byrisetty, Naga Chaitanya
The most beautiful, mysterious movements of bird flocks have always amused the human and led his thinking towards what makes these complex movements possible. This paper discusses the simulation of such bird behavior based on Craig W. Reynolds’s work on bird flocking, satisfying three main objectives and trying to mimic the natural behavioral characteristics of the flock in various circumstances using Netlogo5.1.  Objective One: To develop working software that simulates movement for a flock of birds using agent-based modeling in a two-dimensional world.  Objective Two: To direct the flock towards forage grounds while sustaining the wind and obstacles affecting the flock’s propagation.  Objective Three: To introduce a predator into the world, study, and simulate the flock’s escape behavior.
Algorithms for Coverage Improvement in a Sensor Network
(North Dakota State University, 2011) Maddi, Sunil Reddy
Sensors are devices which have the ability to receive and respond to a signal. These sensors, when used as a group, form a sensor network. Sensors in a sensor network can communicate and transmit data. In the early stages of research on sensor networks, only static sensors were used to form a sensor network. As research advanced, a combination of static and mobile sensors was used to form a wireless sensor network instead of just static sensors. The primary advantage of this type of sensor network over a sensor network with static sensors is the ability of mobile sensors to move to a new location in the network to increase the overall area covered by the sensors. Some concerns in a wireless sensor network are coverage area, energy consumption of the sensors, the ratio of static and mobile sensors to be used in sensor network, and the deployment of sensors in a network. Major research in sensor networks is focused on addressing the issue of coverage area. The objective of this paper is to design, implement and analyze Most Overlapped First and Highest Coverage Gain algorithms that address the issue of coverage area in a wireless sensor network. Local Spiral Search was used as the base to develop these two algorithms in combination with the Utility Function. Both algorithms were tested, and the results were analyzed with coverage area and change in overlap area as the metrics. Results showed a significant gain in coverage area using both the algorithms, and there was a consistent change in overlap area for a varying number of sensors.
Alternative Clustering Algorithms in Sensor Networks
(North Dakota State University, 2010) Gupta, Divya
A wireless sensor network is composed of a large number of tiny sensor nodes that can be deployed in a variety of environments like battle fields, water, large fields, and the like, and can transmit data to a Base station (BS). In a clusterbased network organization, sensor nodes are organized into clusters and one sensor node is selected as a sensor head (SH) in each cluster. Each SH denotes a facility and sends useful information to the Base Station (BS) through other SHs via the shortest path. In this paper, we study two clustering techniques, namely kmedian clustering and k-center clustering for a wireless sensor network. All the sensor nodes are static and homogeneous (having the same specifications) and SHs are assumed to be heterogeneous with respect to other sensor nodes in their respective clusters (but homogeneous to other SHs once they are located). The focus of this paper is to compare the k-median and k-center clustering techniques based on shortest path and total intra-cluster distance. We have implemented the two clustering techniques using the Java language and necessary experimental and statistical results are provided.
Analysis of Security Vulnerabilities in Web Applications using Threat Modeling
(North Dakota State University, 2011) Kondamarri, Samuel Sudhakar
Software security issues have been a major concern to the cyberspace community; therefore, a great deal of research on security testing has been performed, and various security testing techniques have been developed. A security process that is integrated into the application development cycle is required for creating a secure system. A part of this process is to create a threat profile for an application. The present project explains this process as a case study for analyzing a web application using Threat Modeling. This analysis can be used in the security testing approach that derives test cases from design level artifacts.
Analyzing Access Logs Data using Stream Based Architecture
(North Dakota State University, 2018) Gautam, Nitendra
Within the past decades, the enterprise-level IT infrastructure in many businesses have grown from a few to thousands of servers, increasing the digital footprints they produce. These digital footprints include access logs that contain information about different events such as activity related to usage patterns, networks and any hostile activity affecting the network. Apache Hadoop has been one of the most standardized frameworks and is used by many Information Technology (IT) companies for analyzing these log files in distributed batch mode using MapReduce programming model. As these access logs include important information related to security and usage patterns, companies are now looking for an architecture that allows analyzing these logs in real time. To overcome the limitations of the MapReduce based architecture of Hadoop, this paper proposes a new and more efficient data processing architecture using Apache Spark, Kafka and other technologies that can handle both real-time and batch-based data.
Analyzing Student Learning Outcomes in Programming Course Using Individual Study Vs. Pair Programming
(North Dakota State University, 2014) Abeyratne, Keith
Pair programming has been common practice in the programming industry during last three decades, but only recently did it start to draw the attention as a teaching strategy. This paper investigates whether we should introduce pair programming at the beginning of the semester, instead later in the semester. To perform this investigation, we performed a control group empirical study wherein pair programming was used in the first half of the semester (in one section of introductory CS course). The control group (the other section of the same course) introduced pair programming in the second half of the semester. This study supported the implementation of specific assessment strategies to assess individual programming abilities during pair programming situations. Results found that students perceive pair programming as being beneficial and all of the subjects who used pair programming indicated that they would prefer using it again as opposed to working individually.
Analyzing Three Different Tuning Strategies for Random Forest Hyperparameters for Fraud Detection
(North Dakota State University, 2021) Sarao, Kulwinder Kaur
Technology is advancing rapidly, and more tasks are becoming online than ever. Along with the benefits comes the disadvantages of this great advancement. While online services relieve from the struggle of in person activities, it also puts you on the risk of getting deceived by the fraudsters. This paper aims to detect the fraudulent transactions made online from a bank using a synthetically produced dataset. A random forest model has been trained to predict the fraudulent transactions. To achieve the best performance, the hyperparameters of the model have been tuned using three different tuning methods. As it turns out, grid search proved to be the best tuning strategy in terms of the mean cv score, precision, recall, f1-score and accuracy. It only lacked in providing the best run time, where Bayesian Optimization scored well than the others.
Application for Capturing Potential Tardiness in Operating Room Suites
(North Dakota State University, 2012) Gronneberg, Bethlehem Abera
This paper describes the design, architecture and implementation of a Dashboard Application, a tool developed to capture the potential tardiness in Operating Room (OR) Suites. The paper is focused on developing an automated application which is intended to monitor and display the progress of multiple out-patients on the day of their elective surgery as they advance from admission to the pre-operative stages leading up to their final destination of the operating room. The application will display OR patients’ real-time location, the time they entered at that location and the time remaining for their scheduled surgery once they arrive at the admission office. The objective of this paper is to implement an automated application using real-time locating technology to provide timely and accurate information regarding patient preparedness for surgery. This information otherwise would have taken the traditional modes of communication (face-to-face and telephone) to check for patient preparedness.
An Application of Association Rule Mining to Unit Test Selection
(North Dakota State University, 2013) Gunderson, Karl Nils
Appropriate selection of unit tests during the software development process is vital when many unit tests exist. The developer may be unfamiliar with some tests and non-obvious relationships between application code and test code may exist. Poor test selection may lead to defects. This is especially true when the application is large and many developers are involved. By the application of association rule mining to the unit test selection process and by comparison with extant selection techniques, we will provide a quantitative analysis of the benefits of heuristic and its limit to development where process patterns are stable.
Application of the Kusumoto Cost-Metric to Evaluate the Cost-Effectiveness of Software Inspections
(North Dakota State University, 2012) Mandala, Narendar Reddy
Inspection and testing are two widely recommended techniques for software quality improvement with a common goal of defect detection and removal in software products. While testing cannot be conducted until software is implemented, inspections can be applied in early stages of software development. In this way inspection enables saving of testing cost and time. To manage the quality of their software, project managers need objective information to make a trade-off between the testing costs saved by performing inspections against the testing cost that would otherwise be spent if no inspections were performed. Project managers also need to decide on the number of inspectors that would make it a cost-effective inspection process. To accomplish these research goals, we have analyzed the cost invested in the inspection process against the cost saved from the inspection process by applying the Kusumoto cost-metrics on an inspection data set with varying number of inspection team size.
Applied Nonparametric Statistical Tests to Compare Evolutionary and Swarm Intelligence Approaches
(North Dakota State University, 2014) Amanchi, Srinivas Adithya
Recently, in many experimental studies, the statistical analysis of nonparametric comparisons has grown in the area of computational intelligence. The research refers to application of different techniques that are used to show comparison among the algorithms in an experimental study. Pairwise statistical technique perform individual comparison between two algorithms and multiple statistical technique perform comparison between more than two algorithms. Techniques include the Sign test, Wilcoxon signed ranks test, the multiple sign test, the Friedman test, the Friedman aligned ranks test and the Quade test. In this paper, we used these tests to analyze the results obtained in an experimental study comparing well-known algorithms and optimization functions. The analyses showed that the application of statistical tests helps to identify the algorithm that is significantly different than the remaining algorithms in a comparison. Different statistical analyses were conducted on the results of an experimental study obtained with varying dimension size.
An Automated Testing Framework for the Virtual Cell Game
(North Dakota State University, 2013) Dandey, Santosh Raj
The NDSU Virtual Cell game is a role-based, multi-user computer game developed to aid in learning cellular concepts in biology. It is developed using client/server architecture with Lambda-Moo as a server and web-based Java swing applet as a client. The Lambda-Moo (Legacy) Virtual Cell has several limitations, including development environment, performance, and maintenance. Therefore, a new virtual-cell system was developed using the Java-Moo framework to overcome the limitations of the legacy systems. The focus of this paper is to propose, design, and implement two strategies to perform functional conformance testing between the legacy and new Virtual Cell gaming system. The Automated Testing Strategy performs simulation-based testing by automating the game play using XML test cases as an input. The Record and Replay Test strategy captures the test cases of the Virtual Cell (Lambda-Moo) in an XML document and executes them in the newer version (Java Moo).
Automated Tool for Software Requirements Inspection
(North Dakota State University, 2011) Amaran, Pradeep
The software inspection process is a very cost effective method of identifying defects in documents produced during the software life cycle, leading to higher quality software with lower field failures. Manual inspections are labor intensive and dependent on human factors (e.g., preparation, moderation, and cooperation among development and quality assurance teams). An automated software inspection tool replaces a labor intensive manual approach of performing the inspection process. An automated inspection tool will offer greater efficiencies than any techniques involving manual inspections. Automation allows stakeholders (e.g., authors, inspectors) to closely work in coordination using the tool. Authors can host documents, view comments posted by inspectors, assign users and delete them. Inspectors can participate in the inspection process by validating against a set of guidelines and detect faults in a specific frame of time using different fault and error based inspection techniques. It is human to err, and as a result some of the faults may be overlooked. Hence, provisions are made for iterative inspection cycles to maximize the number of defects found and minimize the number of overlooked ones.
Automatic Evaluation of Mobile Web Pages
(North Dakota State University, 2010) Sehgal, Ankita
The use of mobile devices to access the information on the World Wide Web is growing rapidly. The growth has created a surge in the number of webpages being designed for mobile devices. In order to support efficient mobile browsing, some markup languages (e.g., WML and XHTML Mobile Profile) and standards (Mobile Web Best Practices) have been developed to specifically support the rendering of information on mobile devices. Evaluating the mobile webpages manually against the guidelines requires a tremendous amount of work. This research paper focuses on automatic evaluation of mobile webpages, a process which offers many advantages in terms of saving time, reducing costs and many others. In this paper, an extensive inspection of the 46 most popular mobile websites, according to Mobile Web Best Practices using MobileOK checker [WMC09], has been conducted. The results have been provided and analyzed to make specific and general suggestions to improve the design and development of mobile websites. We believe that the analysis will help developers produce more user-friendly mobile websites while considering the Mobile Web Best Practices. Furthermore, the paper also presents a generic approach to represent the W3C Mobile Web Guidelines as an XML schema, which provides flexibility to design rule schemas in an open format; the schemas can be added to an automated tool that is used to evaluate the mobile webpages. The XML schema can also be used to redesign the rule if there is a change in the guidelines.
Automatic Method for Testing Struts-Based Application
(North Dakota State University, 2013) Tiwari, Shweta
Model based testing is a very popular and widely used in industry and academia. There are many tools developed to support model based development and testing, however, the benefits of model based testing requires tools that can automate the testing process. The paper propose an automatic method for model-based testing to test the web application created using Strut based frameworks and an effort to further reduce the level of human intervention require to create a state based model and test the application taking into account that all the test coverage criteria are met. A methodology is implemented to test applications developed with strut based framework by creating a real-time online shopping web application and using the test coverage criteria along with automated testing tool. This implementation will demonstrate feasibility of the proposed method.
Basic Cybersecurity Awareness Through Gaming
(North Dakota State University, 2019) Kulkarni, Vikas Krishnarao
The goal of this paper is to bring the basic awareness of cybersecurity among students so that they do not become a victim of cybercrime. Studies show that cybersecurity serious games support multiple well-established perspectives of learning and have the potential to motivate individuals to learn by keeping them in a state of flow. Educators use the Bloom’s revised taxonomy, as it provides an effective method for the students who are learning a topic. Bloom's revised taxonomy identifies six cognitive levels, starting from basic steps in learning to the more advances steps. This paper includes developing a game called DodgeTheThreats that provides some useful tips on basic cybersecurity. By making use of a serious game that incorporates Bloom’s taxonomy of learning, it is possible to have a very effective learning tool for the students and thereby raise the awareness of cybersecurity.
Bayesian Approach for Detection Classification
(North Dakota State University, 2011) Annapureddy, Anupama Reddy
The objective of this paper is to develop and test a software system that uses incomplete information from a collection of sensors to classify different objects present in a particular area with a pre-specified probability. The objects in the study are referred to as vehicles called the Bus and the Truck. Intruding vehicles move across a designated geographical area. Sensors that have been placed in that area detect vehicles and calculate probabilities that a vehicle is of a specific type conditioned on the type of vehicle that is actually detected. The goal is to determine unconditional probabilities that a given detection is of a particular type. The main idea is to find which vehicle is located at a geographical point in a designated area using the Bayesian approach to calculate the probabilities for this detection classification problem. Each sensor tries to detect the vehicle based on its sensing radius, which is nothing but the distance between the sensor and the vehicle. To test the methodology, I assumed that the probabilities vary depending on the color of the vehicles. For example, if a vehicle is red in color, it is assumed to be easier for the sensors to classify than if it is blue. The framework uses Bayesian inference to calculate the probabilities and to distinguish two types of moving vehicles. Experiments are conducted to find the number of sensors that successfully distinguish two types of moving objects with a given probability threshold. In the future the Detection Classification Model can be used to distinguish any number of objects with the mobile sensors and also some obstacles included in a designated geographical area.

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