Computer Sciences Commons^™

H-Workload 2019: 3rd International Symposium On Human Mental Workload: Models And Applications (Works In Progress), Luca Longo, Maria Chiara Leva

H-Workload 2019: Models & Applications: Works in Progress

No abstract provided.

Universal Quantum Computation, Junya Kasahara

Theses, Dissertations and Capstones

We study quantum computers and their impact on computability. First, we summarize the history of computer science. Only a few articles have determined the direction of computer science and industry despite the fact that many works have been dedicated to the present success. We choose articles by A. M. Turing and D. Deutsch, because A. M. Turing proposed the basic architecture of modern computers while D. Deutsch proposed an architecture for the next generation of computers called quantum computers. Second, we study the architecture of modern computers using Turing machines. The Turing machine has the basic design of modern computers …

A Machine Learning Recommender Model For Ride Sharing Based On Rider Characteristics And User Threshold Time, Govind Pramod Yatnalkar

Theses, Dissertations and Capstones

In the present age, human life is prospering incredibly due to the 4^th Industrial Revolution or The Age of Digitization and Computing. The ubiquitous availability of the Internet and advanced computing systems have resulted in the rapid development of smart cities. From connected devices to live vehicle tracking, technology is taking the field of transportation to a new level. An essential part of the transportation domain in smart cities is Ride Sharing. It is an excellent solution to issues like pollution, traffic, and the rapid consumption of fuel. Even though Ride Sharing has several benefits, the current usage is …

What People Complain About Drone Apps? A Large-Scale Empirical Study Of Google Play Store Reviews, Kanimozhi Kalaichelvan

Theses, Dissertations and Capstones

Within the past few years, there has been a tremendous increase in the number of UAVs (Unmanned Aerial Vehicle) or drones manufacture and purchase. It is expected to proliferate further, penetrating into every stream of life, thus making its usage inevitable. The UAV’s major components are its physical hardware and programming software, which controls its navigation or performs various tasks based on the field of concern. The drone manufacturers launch the controlling app for the drones in mobile app stores. A few drone manufacturers also release development kits to aid drone enthusiasts in developing customized or more creative apps. Thus, …

Cyber Security Awareness Among College Students, Abbas Moallem

Faculty Publications

This study reports the early results of a study aimed to investigate student awareness and attitudes toward cyber security and the resulting risks in the most advanced technology environment: the Silicon Valley in California, USA. The composition of students in Silicon Valley is very ethnically diverse. The objective was to see how much the students in such a tech-savvy environment are aware of cyber-attacks and how they protect themselves against them. The early statistical analysis suggested that college students, despite their belief that they are observed when using the Internet and that their data is not secure even on university …

A Semester Long Classroom Course Mimicking A Software Company And A New Hire Experience For Computer Science Students Preparing To Enter The Software Industry, David A. Chamberlain

Master’s Theses and Projects

Students in a Computer Science degree programs must learn to code before they can be taught Software Engineering skills. This core skill set is how to program and consists of the constructs of various languages, how to create short programs or applications, independent assignments, and arrive at solutions that utilize the skills being covered in the language for that course (Chatley & Field, 2017). As an upperclassman, students will often be allowed to apply these skills in newer ways and have the opportunity to work on longer, more involved assignments although frequently still independent or in small groups of two …

Xr-Based Workforce Develop In The Southwestern Region Of Ohio, Thomas Wischgoll

Computer Science and Engineering Faculty Publications

No abstract provided.

A Usability Study On Shape Shape Hooray: An Adaptive Educational Game Associating 3d Geometric Shapes To Daily Objects, Winna Mia Victoria D. Buenviaje, Ma. Anniela B. Dela Cruz, Ingrid Marie Therese P. Fadriquela

Goal 4: Quality Education

Situated learning theory argues that learning is embedded within an activity, context, and culture. It posits that students are more likely to learn if they have an exposure to the authentic context of the learning environment. Based loosely on this theory, Shape Shape Hooray is an adaptive educational game that aims to teach basic 3D geometric shapes by allowing basic education students associate 3D shapes to daily objects. As an adaptive game, this paper discusses the paths developed for different kinds of players (no prior/low prior, average, and high prior knowledge). A usability test was conducted to which a generally …

A Novel Cooperative Distributed Secondary Controller For Vsi And Pq Inverters Of Ac Microgrids, F. Doost Mohammadi, H. Keshtkar, A. Dehghan Banadaki, A. Feliachi

Faculty & Staff Scholarship

This paper proposes a novel cooperative secondary control strategy for microgrids which is fully distributed. There is a two-layered coordination, which exists between inverter based DGs of both types, i.e. Voltage Source Inverter (VSI) and Current Source Inverter (CSI), also called PQ inverter. In first layer of the proposed two-layered cooperative control strategy, VSIs will take care of the primary average voltage regulation by implementing the average consensus algorithm (ACA); then in the second layer of control, the PQ inverters will improve the voltage quality of the microgrid while maintaining the average voltage of buses at the same desired level. …

Analyzing Public View Towards Vaccination Using Twitter, Mahajan Rutuja

Browse all Theses and Dissertations

Educating people about vaccination tends to target vaccine acceptance and reduction of hesitancy. Social media provides a promising platform for studying public perception regarding vaccination. In this study, we harvested tweets over a year related to vaccines from February 2018 to January 2019. We present a two-stage classifier to: (1) classify the tweets as relevant or non-relevant and (2) categorize them in terms of pro-vaccination, anti-vaccination, or neutral outlook. We found that the classifier was able to distinguish clearly between anti-vaccination and pro-vaccination tweets, but also misclassified many of these as neutral. Using Latent Dirichlet Allocation, we found that two …

Driving And Effective Data-Ready Culture: How Companies Can Take On A Datadriven Approach To 11 Business, Johnson Poh

MITB Thought Leadership Series

TECHNOLOGY has turned the tables in favour of consumers, enabling them to find goods and services faster and access more choices. Companies now compete more intensely to capture consumers’ mindshare and scour for ways to keep their products relevant. But every coin has two sides. While technology has empowered consumers with choice, it has also offered companies a plethora of data to understand consumers better. This puts the odds in favour of companies that can leverage on data to gain consumer insights and meet their business objectives.

Exploiting Mobile Social Networks From Temporal Perspective: A Survey, Huan Zhou, Hui Wang, Ning Wang, Dawei Li, Yue Cao, Xiuhua Li, Jie Wu

College of Science & Mathematics Departmental Research

With the popularity of smart mobile devices, information exchange between users has become more and more frequent, and Mobile Social Networks (MSNs) have attracted significant attention in many research areas. Nowadays, discovering social relationships among people, as well as detecting the evolution of community have become hotly discussed topics in MSNs. One of the major features of MSNs is that the network topology changes over time. Therefore, it is not accurate to depict the social relationships of people based on a static network. In this paper, we present a survey of this emerging field from a temporal perspective. The state-of-the-art …

An Investigation Into The Predictive Capability Of Customer Spending In Modelling Mortgage Default, Donal Finn [Thesis]

Dissertations

The mortgage arrears crisis in Ireland was and is among the most severe experienced on record and although there has been a decreasing trend in the number of mortgages in default in the past four years, it still continues to cause distress to borrowers and vulnerabilities to lenders. There are indications that one of the main factors associated with mortgage default is loan affordability, of which the level of disposable income is a driver. Additionally, guidelines set out by the European Central Bank instructed financial institutions to adopt measures to further reduce and prevent loans defaulting, including the implementation and …

Audio Mixing Using Image Neural Style Transfer Networks, Susan Mckeever, Xuehao Liu, Sarah Jane Delany

Conference papers

Image style transfer networks are used to blend images, producing images that are a mix of source images. The process is based on controlled extraction of style and content aspects of images, using pre-trained Convolutional Neural Networks (CNNs). Our interest lies in adopting these image style transfer networks for the purpose of transforming sounds. Audio signals can be presented as grey-scale images of audio spectrograms. The purpose of our work is to investigate whether audio spectrogram inputs can be used with image neural transfer networks to produce new sounds. Using musical instrument sounds as source sounds, we apply and compare …

Activity - Python Functions - Drawing With Turtle, Robert J. Domanski

Open Educational Resources

A Python Functions activity - "Drawing with Turtle" - for CS0 students. Part of the CUNY CS04All project.

Music Retrieval System Using Dynamic Time Warping, Emeka Jude Okafor

Theses

With the growth of digital audio data, various and fast access to music data is strongly desired, especially for large music databases. A more natural way to retrieve a song from a database will be to hum to the tune. To relate and compare musical pieces is a very complex task. Musical compositions usually collapse multiple information sources and complex, multifaceted interactions established between parts. Despite such degrees of complexity, humans are outstandingly good at performing individual musical judgments with little conscious effort, while a computer cannot efficiently achieve this task. In this work, we focus on one such task: …

Reimagining Medical Education In The Age Of Ai, Steven A. Wartman, C. Donald Combs

Computational Modeling & Simulation Engineering Faculty Publications

Available medical knowledge exceeds the organizing capacity of the human mind, yet medical education remains based on information acquisition and application. Complicating this information overload crisis among learners is the fact that physicians' skill sets now must include collaborating with and managing artificial intelligence (AI) applications that aggregate big data, generate diagnostic and treatment recommendations, and assign confidence ratings to those recommendations. Thus, an overhaul of medical school curricula is due and should focus on knowledge management (rather than information acquisition), effective use of AI, improved communication, and empathy cultivation.

Emerging Roles Of Virtual Patients In The Age Of Ai, C. Donald Combs, P. Ford Combs

Computational Modeling & Simulation Engineering Faculty Publications

Today's web-enabled and virtual approach to medical education is different from the 20th century's Flexner-dominated approach. Now, lectures get less emphasis and more emphasis is placed on learning via early clinical exposure, standardized patients, and other simulations. This article reviews literature on virtual patients (VPs) and their underlying virtual reality technology, examines VPs' potential through the example of psychiatric intake teaching, and identifies promises and perils posed by VP use in medical education.

Using Long Short-Term Memory (Lstm) Recurrent Neural Network (Rnn) To Classify Network Attacks, Pramita Sree Muhuri

Theses

Cyber-attacks have increased greatly in recent years. Therefore, the identification of various network attacks has been an important research area. An Intrusion Detection System (IDS), can identify an ongoing invasion or an intrusion which has already occurred. Intrusion Detection is a classification problem. It identifies whether the network traffic behavior is normal or anomalous or identifies the attack types. Various approaches have been proposed to improve the accuracy of classifiers for identifying the intrusion types. Recently, deep learning has emerged as a successful approach in IDSs having a high accuracy rate with its distinctive learning mechanism. In this research, Long …

Multi-Sensory Deep Learning Architectures For Slam Dunk Scene Classification, Paul Minogue

Dissertations

Basketball teams at all levels of the game invest a considerable amount of time and effort into collecting, segmenting, and analysing footage from their upcoming opponents previous games. This analysis helps teams identify and exploit the potential weaknesses of their opponents and is commonly cited as one of the key elements required to achieve success in the modern game. The growing importance of this type of analysis has prompted research into the application of computer vision and audio classification techniques to help teams classify scoring sequences and key events using game footage. However, this research tends to focus on classifying …

A New Network Model For Cyber Threat Intelligence Sharing Using Blockchain Technology, Daire Homan, Ian Shiel, Christina Thorpe

Conference Papers

The aim of this research is to propose a new blockchain network model that facilitates the secure dissemination of Cyber Threat Intelligence (CTI) data. The primary motivations for this study are based around the recent changes to information security legislation in the European Union and the challenges that Computer Security and Incident Response Teams (CSIRT) face when trying to share actionable and highly sensitive data within systems where participants do not always share the same interests or motivations. We discuss the common problems within the domain of CTI sharing and we propose a new model, that leverages the security properties …

Abso2luteu-Net: Tissue Oxygenation Calculation Using Photoacoustic Imaging And Convolutional Neural Networks, Kevin Hoffer-Hawlik, Geoffrey P. Luke

ENGS 88 Honors Thesis (AB Students)

Photoacoustic (PA) imaging uses incident light to generate ultrasound signals within tissues. Using PA imaging to accurately measure hemoglobin concentration and calculate oxygenation (sO₂) requires prior tissue knowledge and costly computational methods. However, this thesis shows that machine learning algorithms can accurately and quickly estimate sO₂. absO₂luteU-Net, a convolutional neural network, was trained on Monte Carlo simulated multispectral PA data and predicted sO₂ with higher accuracy compared to simple linear unmixing, suggesting machine learning can solve the fluence estimation problem. This project was funded by the Kaminsky Family Fund and the Neukom Institute.

Augustana Stories, Maegan Patterson

Honors Program: Student Scholarship & Creative Works

This is an Android app that describes the history and urban legends of Augustana’s campus. There are several stories that can be accessed from a list or from a map feature that shows where the buildings are on campus. The map is also capable of giving an order in which to visit the buildings if the user decides to take a tour of the campus. The app is written in Java and the stories are housed in webpages.

An Evaluation Of Learning Employing Natural Language Processing And Cognitive Load Assessment, Mrunal Tipari

Dissertations

One of the key goals of Pedagogy is to assess learning. Various paradigms exist and one of this is Cognitivism. It essentially sees a human learner as an information processor and the mind as a black box with limited capacity that should be understood and studied. With respect to this, an approach is to employ the construct of cognitive load to assess a learner's experience and in turn design instructions better aligned to the human mind. However, cognitive load assessment is not an easy activity, especially in a traditional classroom setting. This research proposes a novel method for evaluating learning …

Towards A More Efficient Representation Of Functions In Quantum And Reversible Computing, Oscar Galindo, Laxman Bokati, Vladik Kreinovich

Departmental Technical Reports (CS)

Many practical problem necessitate faster computations. Simple physical estimates show that the only way to achieve a drastic computation speedup is to use quantum -- or, more generally, reversible -- computing. Thus, we need to be able to transform the existing algorithms into reversible form. Such transformation schemes exist. However, such schemes are not very efficient. Indeed, in general, when we write an algorithm, we composed it of several pre-existing modules. It would be nice to be able to similarly compose a reversible version of our algorithm from reversible version of these moduli -- but the existing transformation schemes cannot …

Using Neural Networks To Classify Discrete Circular Probability Distributions, Madelyn Gaumer

HMC Senior Theses

Given the rise in the application of neural networks to all sorts of interesting problems, it seems natural to apply them to statistical tests. This senior thesis studies whether neural networks built to classify discrete circular probability distributions can outperform a class of well-known statistical tests for uniformity for discrete circular data that includes the Rayleigh Test¹, the Watson Test², and the Ajne Test³. Each neural network used is relatively small with no more than 3 layers: an input layer taking in discrete data sets on a circle, a hidden layer, and an output …

Evaluating Software Testing Techniques: A Systematic Mapping Study, Mitchell Mayeda

Electronic Theses and Dissertations

Software testing techniques are crucial for detecting faults in software and reducing the risk of using it. As such, it is important that we have a good understanding of how to evaluate these techniques for their efficiency, scalability, applicability, and effectiveness at finding faults. This thesis enhances our understanding of testing technique evaluations by providing an overview of the state of the art in research. To accomplish this we utilize a systematic mapping study; structuring the field and identifying research gaps and publication trends. We then present a small case study demonstrating how our mapping study can be used to …

Applied Machine Learning For Classification Of Musculoskeletal Inference Using Neural Networks And Component Analysis, Shaswat Sharma

Electronic Theses and Dissertations

Artificial Intelligence (AI) is acquiring more recognition than ever by researchers and machine learning practitioners. AI has found significance in many applications like biomedical research for cancer diagnosis using image analysis, pharmaceutical research, and, diagnosis and prognosis of diseases based on knowledge about patients' previous conditions. Due to the increased computational power of modern computers implementing AI, there has been an increase in the feasibility of performing more complex research.

Within the field of orthopedic biomechanics, this research considers complex time-series dataset of the "sit-to-stand" motion of 48 Total Hip Arthroplasty (THA) patients that was collected by the Human Dynamics …

A Policy Mechanism For Federal Recommendation Of Security Standards For Mobile Devices That Conduct Transactions, Ariel Huckabay

Electronic Theses and Dissertations

The proliferation of mobile devices in the BRIC countries has prompted them to develop policies to manage the security of these devices. In China, mobile devices are a primary tool for payments. As a result, China instituted in 2017 a cyber security policy that applies to mobile devices giving China broad authority to manage cyber threats. The United States has a similar need for a cyber policy. Mobile devices are likely to become a primary payment tool in the United States soon. DHS has also identified a need for more effective security policy in mobile devices for government operations. This …

Detecting Malicious Behavior In Openwrt With Qemu Tracing, Jeremy Porter

Browse all Theses and Dissertations

In recent years embedded devices have become more ubiquitous than ever before and are expected to continue this trend. Embedded devices typically have a singular or more focused purpose, a smaller footprint, and often interact with the physical world. Some examples include routers, wearable heart rate monitors, and thermometers. These devices are excellent at providing real time data or completing a specific task quickly, but they lack many features that make security issues more obvious. Generally, Embedded devices are not easily secured. Malware or rootkits in the firmware of an embedded system are difficult to detect because embedded devices do …