Computer Engineering Commons^™

A Data-Centric Analysis On Stem Majoring And Success: Attitude And Readiness, Xin James He, Myron Sheu, Jie Tao

Journal of International Technology and Information Management

This research studies attitude and readiness of STEM majoring and success with

the data from a survey with a total of 501 viable responses, with respect to STEM

(science, technology, engineering, and mathematics) related majors that are

essential and fundamental to skills relevant to big data business analytics.

Recruiting and keeping students in STEM areas have attracted a large body of

attention in pedagogical studies. An effective way of achieving such a goal is to

show them how rewarding and self-fulfilling STEM careers can be toward

perspective students. One example of the abundance of STEM careers is the rapid

growth …

Prediction And Recommendations On The It Leaners' Learning Path As A Collective Intelligence Using A Data Mining Technique, Seong-Yong Hong, Juyun Cho, Yonghyun Hwang

Journal of International Technology and Information Management

With the recent advances in computer technology along with pervasive internet accesses, data analytics is getting more attention than ever before. In addition, research areas on data analysis are diverging and integrating lots of different fields such as a business and social sector. Especially, recent researches focus on the data analysis for a better intelligent decision making and prediction system. This paper analyzes data collected from current IT learners who have already studied various IT subjects to find the IT learners’ learning patterns. The most popular learning patterns are identified through an association rule data mining using an arules package …

Computer Software Release: Open Photo Roster, Szymon Machajewski

Open Teaching Tools

Learning student names in a classroom course is important to creating an inclusive learning environment. Some Learning Management Systems, like Blackboard Learn, provide tools for student images, but such tools are insufficient. This software project creates a consistent and reliable way of identifying students for the needs of proctored exams as well as for learning student names.

Violating Of Individual Privacy: Moroccan Perceptions Of The Ban Of Voip Services, Tyler Delhees

Independent Study Project (ISP) Collection

On January 6, 2016, the Moroccan telecommunications regulatory agency, the ANRT, announced a ban onVoice Over Internet Protocol(VoIP) calling services such as Skype, WhatsApp, and Viber. The ban triggered sweeping opposition among the Moroccan public, opening discussion of digital rights, censorship, and Internet governance. Considering liberal democratic rights in the 2011 Moroccan Constitution and a history of censorship, this study analyzes the official justification of the ANRT alongside additional explanations involving business interests and the security services. The purpose of this study is to gauge the perceptions of Moroccans on the decision of the ANRT and provide a holistic explanation. …

Region-Based Approach For Single Image Super-Resolution, Min Zhang

Electrical & Computer Engineering Theses & Dissertations

Single image super-resolution (SR) is a technique that generates a high- resolution image from a single low-resolution image [1,2,10,11]. Single image super- resolution can be generally classified into two groups: example-based and self-similarity based SR algorithms. The performance of the example-based SR algorithm depends on the similarity between testing data and the database. Usually, a large database is needed for better performance in general. This would result in heavy computational cost. The self-similarity based SR algorithm can generate a high-resolution (HR) image with sharper edges and fewer ringing artifacts if there is sufficient recurrence within or across scales of the …

Special Issue On Cyberharassment Investigation: Advances And Trends, Joanne Bryce, Virginia N. L. Franqueira, Andrew Marrington

Journal of Digital Forensics, Security and Law

Empirical and anecdotal evidence indicates that cyberharassment is more prevalent as the use of social media becomes increasingly widespread, making geography and physical proximity irrelevant. Cyberharassment can take different forms (e.g., cyberbullying, cyberstalking, cybertrolling), and be motivated by the objectives of inflicting distress, exercising control, impersonation, and defamation. Little is currently known about the modus operandi of offenders and their psychological characteristics. Investigation of these behaviours is particularly challenging because it involves digital evidence distributed across the devices of both alleged offenders and victims, as well as online service providers, sometimes over an extended period of time. This special issue …

The Impact Of Low Self-Control On Online Harassment: Interaction With Opportunity., Hyunin Baek, Michael M. Losavio, George E. Higgins

Journal of Digital Forensics, Security and Law

Developing Internet technology has increased the rates of youth online harassment. This study examines online harassment from adolescents with low self-control and the moderating effect of opportunity. The data used in this study were collected by the Korea Institute of Criminology in 2009. The total sample size was 1,091. The results indicated that low self-control, opportunity, and gender have a significant influence on online harassment. However, these results differed according to gender; for males, low self-control significantly impacted online harassment; for females, however, only low self-control significantly impacted online harassment. Furthermore, the interaction between low self-control and opportunity did not …

Table Of Contents

Journal of Digital Forensics, Security and Law

No abstract provided.

A Legal Examination Of Revenge Pornography And Cyber-Harassment, Thomas Lonardo, Tricia Martland, Doug White

Journal of Digital Forensics, Security and Law

This paper examines the current state of the statutes in the United States as they relate to cyber-harassment in the context of "revenge porn". Revenge porn refers to websites which cater to those wishing to exploit, harass, or otherwise antagonize their ex partners using pornographic images and videos which were obtained during their relationships. The paper provide examples and illustrations as well as a summary of current statute in the United States. The paper additionally explores some of the various legal remedies available to victims of revenge pornography.

Differentiating Cyberbullies And Internet Trolls By Personality Characteristics And Self-Esteem, Lauren A. Zezulka, Kathryn C. Seigfried-Spellar

Journal of Digital Forensics, Security and Law

Cyberbullying and internet trolling are both forms of online aggression or cyberharassment; however, research has yet to assess the prevalence of these behaviors in relationship to one another. In addition, the current study was the first to investigate whether individual differences and self-esteem discerned between self-reported cyberbullies and/or internet trolls (i.e., Never engaged in either, Cyberbully-only, Troll-only, Both Cyberbully and Troll). Of 308 respondents solicited from Mechanical Turk, 70 engaged in cyberbullying behaviors, 20 engaged in only trolling behaviors, 129 self-reported both behaviors, and 89 self-reported neither behavior. Results yielded low self-esteem, low conscientiousness, and low internal moral values for …

Toward Online Linguistic Surveillance Of Threatening Messages, Brian H. Spitzberg, Jean Mark Gawron

Journal of Digital Forensics, Security and Law

Threats are communicative acts, but it is not always obvious what they communicate or when they communicate imminent credible and serious risk. This paper proposes a research- and theory-based set of over 20 potential linguistic risk indicators that may discriminate credible from non-credible threats within online threat message corpora. Two prongs are proposed: (1) Using expert and layperson ratings to validate subjective scales in relation to annotated known risk messages, and (2) Using the resulting annotated corpora for automated machine learning with computational linguistic analyses to classify non-threats, false threats, and credible threats. Rating scales are proposed, existing threat corpora …

After The Avalanche: The Post-Snowden Intelligence Politics Between The United States, The United Kingdom, And Germany, Jobel Kyle P. Vecino

Claremont-UC Undergraduate Research Conference on the European Union

The revelations of PRISM and XKeyscore by ex-National Security Agency (NSA) analyst Edward Snowden resulted in arguably the largest intelligence leak so far in the 21^st century. The leak revealed that the NSA was working with the British Government Communications Headquarters (GCHQ) on surveillance and data collection of individuals throughout Europe. Similarly, the NSA also colluded with the German Federal Intelligence Service (BND) on similar data collection and surveillance activities. Whereas the British government reacted relatively benignly to the revelations despite cries of government abuse, the German government reacted negatively to the revelations, eventually opening a rift between Washington …

Activist: A New Framework For Dataset Labelling, Jack O'Neill, Sarah Jane Delany, Brian Mac Namee

Conference papers

Acquiring labels for large datasets can be a costly and time-consuming process. This has motivated the development of the semi-supervised learning problem domain, which makes use of unlabelled data — in conjunction with a small amount of labelled data — to infer the correct labels of a partially labelled dataset. Active Learning is one of the most successful approaches to semi-supervised learning, and has been shown to reduce the cost and time taken to produce a fully labelled dataset. In this paper we present Activist; a free, online, state-of-the-art platform which leverages active learning techniques to improve the efficiency of …

Empirical Comparative Analysis Of 1-Of-K Coding And K-Prototypes In Categorical Clustering, Fei Wang, Hector Franco, John Pugh, Robert J. Ross

Conference papers

Clustering is a fundamental machine learning application, which partitions data into homogeneous groups. K-means and its variants are the most widely used class of clustering algorithms today. However, the original k-means algorithm can only be applied to numeric data. For categorical data, the data has to be converted into numeric data through 1-of-K coding which itself causes many problems. K-prototypes, another clustering algorithm that originates from the k-means algorithm, can handle categorical data by adopting a different notion of distance. In this paper, we systematically compare these two methods through an experimental analysis. Our analysis shows that K-prototypes is more …

Landmark Detection With Surprise Saliency Using Convolutional Neural Networks, Feng Tang, Damian Lyons, Daniel Leeds

Faculty Publications

Abstract—Landmarks can be used as reference to enable people or robots to localize themselves or to navigate in their environment. Automatic definition and extraction of appropriate landmarks from the environment has proven to be a challenging task when pre-defined landmarks are not present. We propose a novel computational model of automatic landmark detection from a single image without any pre-defined landmark database. The hypothesis is that if an object looks abnormal due to its atypical scene context (what we call surprise saliency), it then may be considered as a good landmark because it is unique and easy to spot by …

Support Vector Machines And Artificial Neural Networks: Assessing The Validity Of Using Technical Features For Security Forecasting, James Di Padua

Dissertations

Stock forecasting is an enticing and well studied problem in both finance and machine learning literature with linear based models such as ARIMA and ARCH to nonlinear Artificial Neural Networks (ANN) and Support Vector Machines (SVM). However, these forecasting techniques also use very different input features, some of which are seen by economists as irrational and theoretically unjustified. In this comparative study using ANNs and SVMs for 12 publicly traded companies, derivative price “technicals” are evaluated against macro and microeconomic fundamentals to evaluate the efficacy of model performance. Despite the efficient market hypothesis positing the ill suitability of technicals as …

A Regression Study Of Salary Determinants In Indian Job Markets For Entry Level Engineering Graduates, Rajveer Singh

Dissertations

The economic liberalisation of Indian markets in early 90s boosted the economic growth of the nation in various sectors over the next two decades. One such sector that has seen a massive growth in this time is Information Technology (IT). The IT industry has played a very crucial role in transforming India from a slow moving economy to one of the largest exporters of IT services. This growth created a huge demand in the labour markets for skilled labour, which in turn made engineering one of the top choices of study after high school over the years. In addition, the …

Panoramic Stereovision And Scene Reconstruction, Ashish Nair

Computer Science and Engineering Master's Theses

With advancement of research in robotics and computer vision, an increasingly high number of applications require the understanding of a scene in three dimensions. A variety of systems are deployed to do the same. This thesis explores a novel 3D imaging technique. This involves the use of catadioptric cameras in a stereoscopic arrangement. A secondary system aims to stabilize the system in the event that the cameras are misaligned during operation. The system provides a stark advantage due to it being a cost effective alternative to present day standard state-of-the-art systems that achieve the same goal of 3D imaging. The …

Using Spatialisation To Support Exploratory Search Behaviour, Clement Roux

Dissertations

Information-seekers traditionally interact with digital content through keyword-based search interfaces displaying results in list views. Well-defined lookup search tasks are performed brilliantly with these interfaces, enabling users to find relevant information and develop a relative understanding of the underlying information space. However, it is feasible to suggest that ill-defined and abstract search tasks could be better supported with a different interface that could allow the user to explore a library’s content and develop an appropriate mental model of the information space. One such approach is based on the use of visualisation, an approach to data analysis that aims to reduce …

Investigating The Impact Of Unsupervised Feature-Extraction From Multi-Wavelength Image Data For Photometric Classification Of Stars, Galaxies And Qsos, Annika Lindh

Dissertations

This thesis reviews the current state of photometric classification in Astronomy and identifies two main gaps: a dependence on handcrafted rules, and a lack of interpretability in the more successful classifiers. To address this, Deep Learning and Computer Vision were used to create a more interpretable model, using unsupervised training to reduce human bias.

The main contribution is the investigation into the impact of using unsupervised feature-extraction from multi-wavelength image data for the classification task. The feature-extraction is achieved by implementing an unsupervised Deep Belief Network to extract lower-dimensionality features from the multi-wavelength image data captured by the Sloan Digital …

Routing Algorithm With Uneven Clustering For Energy Heterogeneous Wireless Sensor Networks, Ying Zhang, Wei Xiong, Dezhi Han, Wei Chen, Jun Wang

Computer Science Faculty Research

Aiming at the “hotspots” problem in energy heterogeneous wireless sensor networks, a routing algorithm of heterogeneous sensor network with multilevel energies based on uneven clustering is proposed. In this algorithm, the energy heterogeneity of the nodes is fully reflected in the mechanism of cluster-heads’ election. It optimizes the competition radius of the cluster-heads according to the residual energy of the nodes. This kind of uneven clustering prolongs the lifetime of the cluster-heads with lower residual energies or near the sink nodes. In data transmission stage, the hybrid multihop transmission mode is adopted, and the next-hop routing election fully takes account …

An On-Line Diagnostic Method For Open-Circuit Switch Faults In Npc Multilevel Converters, Jiangbiao He, Nabeel Demerdash

Electrical and Computer Engineering Faculty Research and Publications

On-line condition monitoring is of paramount importance for multilevel converters used in safety-critical applications. A novel on-line diagnostic method for detecting open-circuit switch faults in neutral-point-clamped (NPC) multilevel converters is introduced in this paper. The principle of this method is based on monitoring the abnormal variation of the dc-bus neutral-point current in combination with the existing information on instantaneous switching states and phase currents. Advantages of this method include simpler implementation and faster detection speed compared to other existing diagnostic methods in the literature. In this method, only one additional current sensor is required for measuring the dc-bus neutral-point current, …

A Fault-Tolerant T-Type Multilevel Inverter Topology With Soft-Switching Capability Based On Si And Sic Hybrid Phase Legs, Jiangbiao He, Nathan Weise, Ramin Katebi, Lixiang Wei, Nabeel Demerdash

Electrical and Computer Engineering Faculty Research and Publications

The performance of a novel three-phase four-leg fault-tolerant T-Type inverter topology is presented in this paper, which significantly improves the inverter's fault-tolerant capability regarding device switch faults. In this new modular inverter topology, only the redundant leg is composed of Silicon Carbide (SiC) power devices and all other phase legs are constituted by Silicon (Si) devices. The addition of the redundant leg, not only provides fault-tolerant solution to switch faults that could occur in the T-Type inverter, but also can share load current with other phase legs. Moreover, quasi zero-voltage switching (ZVS) and zero-current switching (ZCS) in the Si Insulated-Gate …

An Exploration Of The Impact Of Animal Agriculture On Human Sustainable Development Index And The Child Health Indicator, Hithesan Pandian

Dissertations

Several studies have shown that animal agriculture is one of the major contributors to climate change due to greenhouse gas emissions, deforestation, land degradation, freshwater shortages, general environmental pollution and world hunger. Apart from this, meat consumption is strongly associated with certain fatal health conditions such as cancer, cardiovascular disease and diabetes (Wu, 2014). Although meat production and export could be economically beneficial in the short run, it could lead to over-exploitation of natural resources and in turn the destruction of the environment in the long run. Hence, it is essential for the leaders of a nation to make smart …

Mechanical Design And Optimization Of An Interactive Animatronic Bald Eagle, Eric Burns

Phi Kappa Phi Research Symposium (Archived)

Animatronics is a specialized sub-category of mechatronics, a fusion of mechanical and electrical engineering. The field has grown from small, individual projects into a major industry. As animatronics progress, mechanical engineers are pushed to design internal structures which occupy ever-decreasing spaces and to ensure designs can undergo maintenance and modifications smoothly. This research investigates methods of reducing space required for mechanisms and several other beneficial methods of development as well as varying satisfactions for audiences when exposed to actor-controlled systems rather than pre-scripted functions. The mechanical systems are designed using CAD software available at Georgia Southern. On-campus, resources are used …

Model-Free And Model-Based Active Learning For Regression, Jack O'Neill, Sarah Jane Delany, Brian Macnamee

Conference papers

Training machine learning models often requires large labelled datasets, which can be both expensive and time-consuming to obtain. Active learning aims to selectively choose which data is labelled in order to minimize the total number of labels required to train an effective model. This paper compares model-free and model-based approaches to active learning for regression, finding that model-free approaches, in addition to being less computationally intensive to implement, are more effective in improving the performance of linear regressions than model-based alternatives.

Keeping It Physical: Convergence On A Physicality Requirement For Patentability Of Software-Related Inventions Under The European Patent Convention And United States Law, Kevin Afghani, Duke W. Yee

Georgia Journal of Law & Technology

No abstract provided.

Project Daedalus: An Additive Manufacturing Vending Machine, Paul A. Galarnyk, Roxanna Stein, Priscilla Mcdonald, Sky Comarsh White, Matthew Caixeiro, Alexander Seifans, Chris Hays, Benjamin Sallick, Katherine Mcbrayer, Skyler Singleton, Scott Wt Kent

Student Works

The project was a research endeavor focused on designing and building a vending machine for 3D-printed parts. It also had the secondary objective of catalyzing leadership qualities among its membership by emphasizing individual responsibility and forward thinking. The project began in the spring of 2015, when the topic of autonomous 3D-printing was chosen, funding was secured, and the majority of the leadership was brought on. Over the summer and into the fall semester the team developed project requirements and infrastructure, and gathered members from the parent organization. By December of 2015 most of the machine design had been completed, and …

Improving Gold/Gold Microcontact Performance And Reliability Under Low-Frequency Ac Through Circuit Loading, T. Laurvick, Ronald A. Coutu Jr.

Electrical and Computer Engineering Faculty Research and Publications

This paper investigates the performance and reliability of microcontacts under low-frequency and low-amplitude ac test conditions. Current microcontact theory is based on dc tests adapted to RF applications. To help better apply dc theory to RF applications, frequencies between 100 Hz to 100 kHz were experimentally investigated. Microcontacts designed to conduct performance and reliability measurements were used, which in prior dc testing typically lasted for 100 million cycles or more. Under ac loads, at similar power levels, eight devices were tested under cold-switching conditions, and only one was still operational at 10 million cycles. The effect of external circuitry on …

Fall 2016

In The Loop

Dean David Miller and CDM Through the Years; The New ABCs of Digital Literacy; The Younger Generation: Computer Scientists of the Future; The Final Hurdle: Thesis Talk; Telling Stories in Cuba with Abbas Kiarostami with James Choi; Collegiate Cyber Defense Competition; TEDxDePaulUniversity Conference; Tim Nedow, Olympian; Omnibus Crowdfunded Game; News Briefs; The Social Technocrat: Andrew Ruginis; When Computing and Biology Collide; Tori Meschino: Campus Leader and All-Around Superstar; Degrees Offered at CDM