Computer Sciences Commons^™

Introduction To Information Systems (Gsu), Teresa Adams, Illiad Connally

Computer Science and Information Technology Grants Collections

This Grants Collection for Introduction to Information Systems was created under an ALG Round Eight Textbook Transformation Grant.

Affordable Learning Georgia Grants Collections are intended to provide faculty with the frameworks to quickly implement or revise the same materials as a Textbook Transformation Grants team, along with the aims and lessons learned from project teams during the implementation process.

Documents are in .pdf format, with a separate .docx (Word) version available for download. Each collection contains the following materials:

• Linked Syllabus
• Initial Proposal
• Final Report

Foundations Of Health Information Technology (Undergraduate) Course Materials, Chi Zhang

Computer Science and Information Technology Ancillary Materials

This is a collection of all materials used in Health Information Technology by Dr. Chi Zhang at Kennesaw State University, including lecture slides, assignments, and assessments, including a question bank.

Topics covered include:

• Clinical Financial Records
• Evidence-Based Medicine
• e-Prescribing
• Patient Bedside Systems
• Telemedicine
• Health Information Networks
• Cryptography
• Accreditation
• HIPAA Privacy and Security

Ethical Hacking For Effective Defense, Lei Li, Zhigang Li, Hossain Shahriar, Rebecca H. Rutherfoord, Svetana Peltsverger, Dawn Tatum

Computer Science and Information Technology Grants Collections

This Grants Collection for Ethical Hacking for Effective Defense was created under a Round Eight ALG Textbook Transformation Grant.

Affordable Learning Georgia Grants Collections are intended to provide faculty with the frameworks to quickly implement or revise the same materials as a Textbook Transformation Grants team, along with the aims and lessons learned from project teams during the implementation process.

Documents are in .pdf format, with a separate .docx (Word) version available for download. Each collection contains the following materials:

• Linked Syllabus
• Initial Proposal
• Final Report

Technological Evolution In Software Engineering, Cody Miller

Engineering and Technology Management Student Projects

In all software development processes, the software must evolve in response to its environment or user needs to maintain satisfactory performance. If software doesn’t support change, it gradually becomes useless. With many organizations today, being software-centric organizations, this has huge implications for their business: evolve your software, or risk your software becoming gradually useless, and therefore, your entire business.

Technology Evolution is a highly relevant subject, Intel’s business model for the last 50 years, has been that of Moore’s Law, a hardware centric Technology Evolution model. As a Software Engineer at Intel, our business group faces a similar issue, we …

A Resource View Of Information Security Incident Response, Mark-David J. Mclaughlin

2018

This dissertation investigates managerial and strategic aspects of InfoSec incident preparation and response. This dissertation is presented in four chapters:

Chapter 1: an introduction

Chapter 2: a systematic literature review

Chapter 3: two field-based case studies of InfoSec incident response processes

Chapter 4: a repertory grid study identifying characteristics of effective individual incident responders.

Together these chapters demonstrate that the lenses of the Resource Based View, Theory of Complementary Resources, and Accounting Control Theory, can be combined to classify and analyze the resources organizations use during incident response. I find that incident response is maturing as a discipline and organizations …

Security And Privacy In Ubiquitous Sensor Networks, Alfredo J. Perez, Sherali Zeadally, Nafaa Jabeur

Computer Science Faculty Publications

The availability of powerful and sensor-enabled mobile and Internet-connected devices have enabled the advent of the ubiquitous sensor network (USN) paradigm. USN provides various types of solutions to the general public in multiple sectors, including environmental monitoring, entertainment, transportation, security, and healthcare. Here, we explore and compare the features of wireless sensor networks and USN. Based on our extensive study, we classify the security- and privacy-related challenges of USNs. We identify and discuss solutions available to address these challenges. Finally, we briefly discuss open challenges for designing more secure and privacy-preserving approaches in next-generation USNs.

Understanding Natural Keyboard Typing Using Convolutional Neural Networks On Mobile Sensor Data, Travis Siems

Computer Science and Engineering Theses and Dissertations

Mobile phones and other devices with embedded sensors are becoming increasingly ubiquitous. Audio and motion sensor data may be able to detect information that we did not think possible. Some researchers have created models that can predict computer keyboard typing from a nearby mobile device; however, certain limitations to their experiment setup and methods compelled us to be skeptical of the models’ realistic prediction capability. We investigate the possibility of understanding natural keyboard typing from mobile phones by performing a well-designed data collection experiment that encourages natural typing and interactions. This data collection helps capture realistic vulnerabilities of the security …

An Investigation Of Low Frequency Noise In Server Rooms, Ahmed Al Naami

Theses

Noise in a server room can have a major impact on the performance and well-being of the occupants. Sound level and low frequency noise are considered factors that influence the hearing ability of workers. This thesis is an investigation of low-frequency noise in server rooms. We conducted the field study in a server room for a large financial institution. Some employees in this study indicated that they experienced headaches from the noise and requested an analysis of the sound to determine if there were any potential adverse health effects. Attributes of the noise were investigated by evaluating the sound pressure …

A Utp Semantics For Communicating Processes With Shared Variables And Its Formal Encoding In Pvs, Ling Shi, Yongxin Zhao, Yang Liu, Jun Sun, Jin Song Dong, Shengchao Qin

Research Collection School Of Computing and Information Systems

CSP# (communicating sequential programs) is a modelling language designed for specifying concurrent systems by integrating CSP-like compositional operators with sequential programs updating shared variables. In this work, we define an observation-oriented denotational semantics in an open environment for the CSP# language based on the UTP framework. To deal with shared variables, we lift traditional event-based traces into mixed traces which consist of state-event pairs for recording process behaviours. To capture all possible concurrency behaviours between action/channel-based communications and global shared variables, we construct a comprehensive set of rules on merging traces from processes which run in parallel/interleaving. We also define …

Evaluating Reproducibility In Computational Biology Research, Morgan Oneka

Honors Projects

For my Honors Senior Project, I read five research papers in the field of computational biology and attempted to reproduce the results. However, for the most part, this proved a challenge, as many details vital to utilizing relevant software and data had been excluded. Using Geir Kjetil Sandve's paper "Ten Simple Rules for Reproducible Computational Research" as a guide, I discuss how authors of these five papers did and did not obey these rules of reproducibility and how this affected my ability to reproduce their results.

Prioritized Task Scheduling In Fog Computing, Tejaswini Choudhari

Master's Projects

Cloud computing is an environment where virtual resources are shared among the many users over network. A user of Cloud services is billed according to pay-per-use model associated with this environment. To keep this bill to a minimum, efficient resource allocation is of great importance. To handle the many requests sent to Cloud by the clients, the tasks need to be processed according to the SLAs defined by the client. The increase in the usage of Cloud services on a daily basis has introduced delays in the transmission of requests. These delays can cause clients to wait for the response …

Vgm-Rnn: Recurrent Neural Networks For Video Game Music Generation, Nicolas Mauthes

Master's Projects

The recent explosion of interest in deep neural networks has affected and in some cases reinvigorated work in fields as diverse as natural language processing, image recognition, speech recognition and many more. For sequence learning tasks, recurrent neural networks and in particular LSTM-based networks have shown promising results. Recently there has been interest – for example in the research by Google’s Magenta team – in applying so-called “language modeling” recurrent neural networks to musical tasks, including for the automatic generation of original music. In this work we demonstrate our own LSTM-based music language modeling recurrent network. We show that it …

Android De-Shredder App, Vasudha Venkatesh

Master's Projects

Sensitive documents are usually shredded into strips before discarding them. Shredders are used to cut the pages of a document into thin strips of uniform thickness. Each shredded piece in the collection bin could belong to any of the pages in a document. The task of document reconstruction involves two steps: Identifying the page to which each shred belongs and rearranging the shreds within the page to their original position. The difficulty of the reconstruction process depends on the thickness of the shred and type of cut (horizontal or vertical). The thickness of the shred is directly proportional to the …

Improved Hands-Free Text Entry System, Gaurav Gupta

Master's Projects

An input device is a hardware device which is used to send input data to a computer or which is used to control and interact with a computer system. Contemporary input mechanisms can be categorized by the input medium: Keyboards and mice are hand-operated, Siri and Alexa are voice-based, etc. The objective of this project was to come up with a head movement based input system that improves upon earlier such systems. Input entry based on head movements may help people with disabilities to interact with computers more easily. The system developed provides the flexibility to capture rigid and non- …

Approaches To Shared State In Concurrent Programs, Sidharth Mishra

Master's Projects

We are in the multicore machine era, but our programs have yet to utilize the increased computing power offered by these machines. At present, lock-based multithreaded programming is the most common programming model used for writing concurrent programs. However, due to the nuances of shared state (and memory) in multithreaded programs and the cognitive load introduced due to locks, concurrent programming remains difficult. One way to deal with shared state in concurrent programs is to get rid of it altogether and use message passing. The other way would be to isolate shared state and store it in a state store, …

Image Segmentation And Classification Of Marine Organisms, Krishna Teja Vojjila

Master's Projects

To automate the arduous task of identifying and classifying images through their domain expertise, pioneers in the field of machine learning and computer vision invented many algorithms and pre-processing techniques. The process of classification is flexible with many user and domain specific alterations. These techniques are now being used to classify marine organisms to study and monitor their populations. Despite advancements in the field of programming languages and machine learning, image segmentation and classification for unlabeled data still needs improvement. The purpose of this project is to explore the various pre-processing techniques and classification algorithms that help cluster and classify …

Distinguishing Earthquakes And Noise Using Random Forest Algorithm, Nishita Narvekar

Master's Projects

Earthquakes are a major cause of life and property destruction. It is known that earthquakes radiate energy in the form of surface and body seismic waves. P-wave and S-waves are types of body waves. Both waves can be detected and recorded at an earthquake station. These waves can be analyzed to detect earthquakes. Most of the earthquake prediction techniques today are a combination of geophysics and signal processing, which are relatively complex. Machine learning can be used to learn the behavior of seismic waves and help in early detection. Machine learning can also be employed to process massive amounts of …

Agent-Based Computing In Java, Michael Symonds

Master's Projects

Agents are powerful, autonomous entities capable of performing simple, or vastly complex, operations individually or in groups of agent systems. Their capabilities extend significantly as mobile agents distributed across a network. Agent-based computing is a widely used technology with a broad range of applications, particularly in distributed computing and agent-based modeling. Many types of systems can be designed using the different architectures that define how they act, communicate, migrate, and more. This paper surveys agent-based computing, their architectures, and efforts at the standardization of certain aspects of the technology. It explores an existing framework called Jade through the lens of …

Music Similarity Estimation, Anusha Sridharan

Master's Projects

Music is a complicated form of communication, where creators and culture communicate and expose their individuality. After music digitalization took place, recommendation systems and other online services have become indispensable in the field of Music Information Retrieval (MIR). To build these systems and recommend the right choice of song to the user, classification of songs is required. In this paper, we propose an approach for finding similarity between music based on mid-level attributes like pitch, midi value corresponding to pitch, interval, contour and duration and applying text based classification techniques. Our system predicts jazz, metal and ragtime for western music. …

Micro-Expression Recognition Using Spatiotemporal Texture Map And Motion Magnification, Shashank Shivaji Pawar

Master's Projects

Micro-expressions are short-lived, rapid facial expressions that are exhibited by individuals when they are in high stakes situations. Studying these micro-expressions is important as these cannot be modified by an individual and hence offer us a peek into what the individual is actually feeling and thinking as opposed to what he/she is trying to portray. The spotting and recognition of micro-expressions has applications in the fields of criminal investigation, psychotherapy, education etc. However due to micro-expressions’ short-lived and rapid nature; spotting, recognizing and classifying them is a major challenge. In this paper, we design a hybrid approach for spotting and …

Fine-Grained Object Detection, Rahul Dalal

Master's Projects

Object detection plays a vital role in many real-world computer vision applications such as selfdriving cars, human-less stores and general purpose robotic systems. Convolutional Neural Network(CNN) based Deep Learning has evolved to become the backbone of most computer vision algorithms, including object detection. Most of the research has focused on detecting objects that differ significantly e.g. a car, a person, and a bird. Achieving fine-grained object detection to detect different types within one class of objects from general object detection can be the next step. Fine-grained object detection is crucial to tasks like automated retail checkout. This research has developed …

Using Filters In Time-Based Movie Recommender Systems, Ravee Khandagale

Master's Projects

On a very high level, a movie recommendation system is one which uses data about the user, data about the movie and the ratings given by a user in order to generate predictions for the movies that the user will like. This prediction is further presented to the user as a recommendation. For example, Netflix uses a recommendation system to predict movies and generate favorable recommendations for users based on their profiles and the profiles of users similar to them. In user-based collaborative filtering algorithm, the movies rated highly by the similar users of a particular user are considered as …

Compression Of Wearable Body Sensor Network Data Using Improved Two-Threshold-Two-Divisor Data Chunking Algorithm, Robinson Raju

Master's Projects

Compression plays a significant role in Body Sensor Networks (BSN) data since the sensors in BSNs have limited battery power and memory. Also, data needs to be transmitted fast and in a lossless manner to provide near real-time feedback. The paper evaluates lossless data compression algorithms like Run Length Encoding (RLE), Lempel Zev Welch (LZW) and Huffman on data from wearable devices and compares them in terms of Compression Ratio, Compression Factor, Savings Percentage and Compression Time. It also evaluates a data deduplication technique used for Low Bandwidth File Systems (LBFS) named Two Thresholds Two Divisors (TTTD) algorithm to determine …

A Medical Price Prediction System, Anuja Tike

Master's Projects

The health care costs constitute a significant fraction of the U.S. economy. Nearly 20% of the Gross Domestic Product (GDP) is spent on health care. The health spending in the US is the highest among all developed nations in absolute numbers as well as a percentage of the economy. The U.S. government bears a large portion of seniors’ health expenditure through its Medicare program. The growing health related expenses combined with the fact that the baby-boomer generation is retiring, and hence they will be eligible for Medicare, puts a great burden on the U.S. exchequer. Therefore, it is essential to …

Analyzing Android Adware, Supraja Suresh

Master's Projects

Most Android smartphone apps are free; in order to generate revenue, the app developers embed ad libraries so that advertisements are displayed when the app is being used. Billions of dollars are lost annually due to ad fraud. In this research, we propose a machine learning based scheme to detect Android adware based on static and dynamic features. We collect static features from the manifest file, while dynamic features are obtained from network traffic. Using these features, we initially classify Android applications into broad categories (e.g., adware and benign) and then further classify each application into a more specific family. …

A Convolutional Neural Network Based Approach For Visual Question Answering, Lavanya Abhinaya Koduri

Master's Projects

Computer Vision is a scientific discipline which involves the development of an algorithmic basis for the construction of intelligent systems that aim at analysis, understanding and extraction of useful information from visual data. This visual data can be plain images, video sequences, views from multiple cameras, etc. Natural Language Processing (NLP), is the ability of machines to read and understand human languages. Visual Question Answering (VQA), is a multi-discipline Artificial Intelligence (AI) research problem, which is a combination of Natural Language Processing (NLP), Computer Vision (CV), and Knowledge Reasoning (KR). Given an image and a question related to the image …

Image Robust Hashing For Malware Detection, Wei-Chung Huang

Master's Projects

This research is focused on a novel approach to detect malware based on static analysis of executable files. Specifically, we treat each executable file as a twodimensional image and use robust hashing techniques to identify whether a given executable belongs to a particular family or not. The hashing stage comprises two steps, namely, feature extraction, and compression. We compare our robust hashing approach to other machine learning-based techniques.

Pe Header Analysis For Malware Detection, Samuel Kim

Master's Projects

Recent research indicates that effective malware detection can be implemented based on analyzing portable executable (PE) file headers. Such research typically relies on prior knowledge of the header to extract relevant features. However, it is also possible to consider the entire header as a whole, and use this directly to determine whether the file is malware. In this research, we collect a large and diverse malware data set. We then analyze the effectiveness of various machine learning techniques based on PE headers to classify the malware samples. We compare the accuracy and efficiency of each technique considered.

Automated Lyrical Narrative Writing, Divya Singh

Master's Projects

Computational Creativity studies the potential of computers to act as autonomous creators and co-creators in addition to tools helping people. Creativity is evident in music, visual art, problem solving and languages. Significant work has been conducted in the area of linguistic creation mainly in the generation of stories, puns, rhymes, jokes, similes, and poetry. One of the major challenges of computational creativity is to generate lyrics that exhibit human-level creativity. On one hand, the lyrics generated should be meaningful and coherent, while on the other hand, they should satisfy poetry constraints such as rhyme scheme, rhyme type, and the number …

Modeling Human Migration Dynamics In Netlogo, Vikram Deshmukh

Master's Projects

Human Migration has often been the catalyst for the rise and fall of civilizations. It is imperative to study human migration dynamics if one is to gain insights into migratory behavior among human beings and how migration affects societies. There has been considerable research to study migration. This has given rise to some popular migration theories like the neoclassical approach, network migration, pull-push migration, etc. These theories shed light on some peculiar behaviors that influence the migration decision of an individual or a group, while also trying to predict the outcome of such actions. The goal of this project is …