Computer Sciences Commons^™

Algorithmic Music Generation For Pedagogy Of Sight Reading, Ryan Stephen Davis

Electronic Theses and Dissertations

Autodeus is the name of the program that has been developed and was designed to aid guitar students in the attainment and betterment of musical notation sight reading skills. Its primary goal is to provide a very flexible tool that has the ability to generate virtually endless types of sight reading exercises at many various skill levels.

A complimentary 2 year-long comprehensive guitar sight-reading course syllabus can be implemented via Autodeus as it is capable of generating all the necessary exercises. It is able to generate these exercises quickly and efficiently through the use of a back tracking algorithm that …

Providing Protection To Programmers' Works: Disregard The Merger Doctrine And Adopt The Application Approach, Akshay Jain

Catholic University Journal of Law and Technology

In today’s technological landscape, computer programs are one of the most highly complex and popular inventions. However, they still receive little or sometimes no legal protection. As a consequence, programmers are reluctant to create new programs, discouraging innovation and preventing the public to benefit from using these inventions. If the court does afford them copyright protection, they may still not receive legal damages for copyright infringement because the court would not consider their program registered under the Copyright Act of 1976.

This Comment argues for greater copyright protection for programs by disregarding the merger doctrine, which does not provide protection …

Recommender Systems For Large-Scale Social Networks: A Review Of Challenges And Solutions, Magdalini Eirinaki, Jerry Gao, Iraklis Varlamis, Konstantinos Tserpes

Faculty Publications

Social networks have become very important for networking, communications, and content sharing. Social networking applications generate a huge amount of data on a daily basis and social networks constitute a growing field of research, because of the heterogeneity of data and structures formed in them, and their size and dynamics. When this wealth of data is leveraged by recommender systems, the resulting coupling can help address interesting problems related to social engagement, member recruitment, and friend recommendations.In this work we review the various facets of large-scale social recommender systems, summarizing the challenges and interesting problems and discussing some of the …

Support Vector Machines For Image Spam Analysis, Aneri Chavda, Katerina Potika, Fabio Di Troia, Mark Stamp

Faculty Publications, Computer Science

Email is one of the most common forms of digital communication. Spam is unsolicited bulk email, while image spam consists of spam text embedded inside an image. Image spam is used as a means to evade text-based spam filters, and hence image spam poses a threat to email-based communication. In this research, we analyze image spam detection using support vector machines (SVMs), which we train on a wide variety of image features. We use a linear SVM to quantify the relative importance of the features under consideration. We also develop and analyze a realistic “challenge” dataset that illustrates the limitations …

Data Warehousing Class Project Report, Gaya Haciane, Chuan Chieh Lu, Rassaniya Lerdphayakkarat, Rudraxi Mitra

Engineering and Technology Management Student Projects

Data mining is widely described or defined as the discipline of: “making sense of the data”. In today’s day and age, the rise of ubiquity of information calls for more advanced and developed techniques to mine the data and come up with insights. Data mining finds applications in many different fields and industries: Whether it is in Embryology, Crops, Elections, or Business Marketing...etc. It is not a wild assumption to consider that every organization in the world has some data mining capabilities or its main activity necessitates it and they have some third party organization doing that for them. One …

Smu Master Of It In Business Launches New Artificial Intelligence Track, Singapore Management University

SMU Press Releases and News

The Singapore Management University’s School of Information Systems (SIS) has launched a new Artificial Intelligence (AI) track under its Master of IT in Business (MITB) programme. Geared towards nurturing graduates who are ready for the revolutionary change from AI in data science, the AI track equips a new generation of IT business leaders in careers that bridge AI with business.

Investigating Query Formulation Assistance For Children, Oghenemaro Anuyah, Maria Soledad Pera, Jerry Alan Fails

Computer Science Faculty Publications and Presentations

Popular tools used to search for online resources are tuned to satisfy a broad category of users—primarily adults. Because children have specific needs, these tools may not always be successful in offering the right level of support in their quest for information. While search tools often provide query assistance, children still face many difficulties expressing their information needs in the form of a query. In this paper, we share results from our ongoing research work focused on understanding children's interactions with query suggestions and their preferences with respect to suggestions offered by a general-purpose strategy versus a counterpart designed exclusively …

Exploring Author Gender In Book Rating And Recommendation, Michael D. Ekstrand, Mucun Tian, Mohammed R. Imran Kazi, Hoda Mehrpouyan, Daniel Kluver

Computer Science Faculty Publications and Presentations

Collaborative filtering algorithms find useful patterns in rating and consumption data and exploit these patterns to guide users to good items. Many of the patterns in rating datasets reflect important real-world differences between the various users and items in the data; other patterns may be irrelevant or possibly undesirable for social or ethical reasons, particularly if they reflect undesired discrimination, such as gender or ethnic discrimination in publishing. In this work, we examine the response of collaborative filtering recommender algorithms to the distribution of their input data with respect to a dimension of social concern, namely content creator gender. Using …

Survivability Strategies For Emerging Wireless Networks With Data Mining Techniques: A Case Study With Netlogo And Rapidminer, Ivan Garcia-Magarino, Geraldine Gray, Raquel Lacuesta, Jaime Lloret

Articles

Emerging wireless networks have brought Internet and communications to more users and areas. Some of the most relevant emerging wireless technologies are Worldwide Interoperability for Microwave Access, Long-Term Evolution Advanced, and ad hoc and mesh networks. An open challenge is to ensure the reliability and robustness of these networks when individual components fail. The survivability and performance of these networks can be especially relevant when emergencies arise in rural areas, for example supporting communications during a medical emergency. This can be done by anticipating failures and finding alternative solutions. This paper proposes using big data analytics techniques, such as decision …

On The Effectiveness Of Generic Malware Models, Naman Bagga, Fabio Di Troia, Mark Stamp

Faculty Publications, Computer Science

Malware detection based on machine learning typically involves training and testing models for each malware family under consideration. While such an approach can generally achieve good accuracy, it requires many classification steps, resulting in a slow, inefficient, and potentially impractical process. In contrast, classifying samples as malware or benign based on more generic “families” would be far more efficient. However, extracting common features from extremely general malware families will likely result in a model that is too generic to be useful. In this research, we perform controlled experiments to determine the tradeoff between generality and accuracy—over a variety of machine …

Rnn-Based Generation Of Polyphonic Music And Jazz Improvisation, Andrew Hannum

Electronic Theses and Dissertations

This paper presents techniques developed for algorithmic composition of both polyphonic music, and of simulated jazz improvisation, using multiple novel data sources and the character-based recurrent neural network architecture char-rnn. In addition, techniques and tooling are presented aimed at using the results of the algorithmic composition to create exercises for musical pedagogy.

Preparing Millennials As Digital Citizens And Socially And Environmentally Responsible Business Professionals In A Socially Irresponsible Climate, Barbara Burgess-Wilkerson, Clovia Hamilton, Chlotia Garrison, Keith Robbins

Winthrop Faculty and Staff Publications

No abstract provided.

Remote Sensing Of Energy Efficient Windows, Isaac Chen, Randall Brouwer, Yoon Kim

Summer Research

Windows gained popularity in modern architecture for their aesthetic appearance and ability to provide natural sunlight. But in terms of energy efficiency, windows are less desirable due to their lack of insulation and their vulnerability to sun radiation. Mackinac Technology Company invented a coating solution to help depreciate solar radiation through windows, thus saving energy from cooling windowed infrastructures. The goal of research is to implement test boxes (Sunbox) to evaluate window’s thermal resistance. The Sunboxes will be placed in remote locations and must be remotely monitored and controlled by designated computers

Content-Based Clustering And Visualization Of Social Media Text Messages, Sydney A. Barnard

Browse all Theses and Dissertations

Although Twitter has been around for more than ten years, crisis management agencies and first response personnel are not able to fully use the information this type of data provides during a crisis or natural disaster. This thesis addresses clustering and visualizing social media data by textual similarity, rather than by only time and location, as a tool for first responders. This thesis presents a tool that automatically clusters geotagged text data based on their content and displays the clusters and their locations on the map. It allows at-a-glance information to be displayed throughout the evolution of a crisis. For …

Knowledge-Enabled Personalized Dashboard For Asthma Management In Children, Vaikunth Sridharan, Revathy Venkataramanan, Dipesh Kadariya, Krishnaprasad Thirunarayan, Amit Sheth, Maninder Kalra

Kno.e.sis Publications

Introduction: Childhood Asthma is a significant public health concern worldwide. Effective management of childhood asthma requires close monitoring of disease triggers, medication compliance and symptom control. The recent growth of the Internet of Things (IoT) based devices has enabled continuous monitoring of patients. kHealth-Asthma is a knowledge-enabled semantic framework consisting of IoT enabled sensors to record patient symptoms, medication usage and their environment. For each patient, 29 diverse parameters with 1852 data points are collected daily. kHealthDash platform enables real-time visual analysis at an individual and cohort level over such high volume, high variety data.

Methods: The kHealth kit was …

Khealth: A Personalized Healthcare Approach For Pediatric Asthma, Utkarshani Jaimini, Hong Y. Yip, Revathy Venkataramanan, Dipesh Kadariya, Vaikunth Sridharan, Tanvi Banerjee, Krishnaprasad Thirunarayan, Maninder Kalra, Amit Sheth

Kno.e.sis Publications

Can we assess the asthma control level, determine vulnerability, and medication compliance for a patient? Can we understand the causal relationship between the asthma symptom and possible factors responsible for it? Can we reduce the number of asthma attacks through continuous monitoring of the patient’s health condition?

Poster: Image Disguising For Privacy-Preserving Deep Learning, Sagar Sharma, Keke Chen

Kno.e.sis Publications

No abstract provided.

Towards Using A Physio-Cognitive Model In Tutoring For Psychomotor Tasks., Jong W. Kim, Chris Dancy, Robert A. Sottilare

Faculty Conference Papers and Presentations

We report our exploratory research of psychomotor task training in intelligent tutoring systems (ITSs) that are generally limited to tutoring in the desktop learning environment where the learner acquires cognitively oriented knowledge and skills. It is necessary to support computer-guided training in a psychomotor task domain that is beyond the desktop environment. In this study, we seek to extend the current capability of GIFT (Generalized Intelligent Frame-work for Tutoring) to address these psychomotor task training needs. Our ap-proach is to utilize heterogeneous sensor data to identify physical motions through acceleration data from a smartphone and to monitor respiratory activity through …

Knowing And Designing: Understanding Information Use In Open Source Design Through The Lens Of Information Archetypes, Kevin Lumbard, Ammar Abid, Christine Toh, Matt Germonprez

Interdisciplinary Informatics Faculty Proceedings & Presentations

The early phases of the product design process are crucial to the success of design outcomes. While information utilized during idea development has tremendous potential to impact the final design, there is a lack of understanding about the types of information utilized in industry, making it challenging to develop and teach methodologies that support the design of competitive products. As a first step in understanding this process, this study focuses on developing a framework of Information Archetypes utilized by designers in industry. This was accomplished through in-depth analysis of qualitative interviews with large software engineering companies. The results reveal two …

Ua8 It Security Bulletins, Wku Information Technology

WKU Administration Documents

IT Security Bulletins issued in 2018 to faculty and staff via email.

• Ciampa, Mark. Protecting Your Critical Email Password
• Alteryx Data Breach
• Securing the Human
• New to WKU?
• Spam
• University Policy
• Personnel Changes
• Password Extortion
• Facebook Messenger Scam
• Privacy
• Phishing

Exploring How Integrating Art & Animation In Teaching Text-Based Programming Affects High School Students' Interest In Computer Science, Hadeel Mohammed Jawad

Master's Theses and Doctoral Dissertations

As oil is the fuel of the industrial society, software is the fuel of our current information society. According to the Bureau of Labor Statistics, there will be more demand for computing jobs in the future. By 2024, more than one million computing jobs will be available. Statistics show that there is more demand for computing jobs than there is a supply of qualified graduates from universities. In this experimental study, three groups of high school students were targeted to explore how integrating art, animation, and code sharing into programming affects their interest in pursuing a degree in computer science …

Access Granted: A Study Of The Factors Affecting The Development Of Technology Literacy In Black Males, Carlton Bernard Bell

Master's Theses and Doctoral Dissertations

One of the most urgent challenges of the digital divide is the need to expand technology literacy. Access to technology was believed to be one of the causes for the discrepancy that exists, but there is a deeper divide: the divide that exists between technology literacy, and career readiness. Although access to technology has improved over time, the educational outcomes for Black males in related fields have not. A critical area of concern is the lack of a Black male professional presence in technology fields, which has serious implications for the future of our society. These implications include a less …

Examining The Influence Of Technology Acceptance, Self-Efficacy, And Locus Of Control On Information Security Behavior Of Social Media Users, Abdullah Almuqrin

Master's Theses and Doctoral Dissertations

Due to recent advances in online communication technology, social networks have become a vital avenue for human interaction. At the same time, they have been exploited as a target for viruses, attacks, and security threats. The first line of defense against such attacks and threats— as well as their primary cause—are social media users themselves. This study investigated the relationship between certain personality factors among social media users—i.e., technology acceptance of security protection technologies, self-efficacy of information security, and locus of control—and their information security behavior. Quantitative methods were used to examine this relationship. The population consisted of all students …

Graduate Admissions Recruitment Project, Kevin Anderson, Chiemela Dike, Yixin Du, Arvinder Kaur, Amanda Popp, Huizhong Yang

School of Professional Studies

In this project, several comparison schools were interviewed and disclosed to have used search lists to find candidates. The organizations that have valuable search lists which may be of good use for the School of Professional Studies include Educational Testing Service (ETS) and the Graduate Management Admission Council (GMAC). By choosing criteria such as demographics, location, academic performance, educational history provided by search lists, we believe there are many quality candidates for SPS programs. However, as we further investigated the functionality and cost-efficiency or return of investment of GRE search list, we spotted many uncertainties and few solid and successful …

Verifying Data-Oriented Gadgets In Binary Programs To Build Data-Only Exploits, Zachary David Sisco

Browse all Theses and Dissertations

Data-Oriented Programming (DOP) is a data-only code-reuse exploit technique that "stitches" together sequences of instructions to alter a program's data flow to cause harm. DOP attacks are difficult to mitigate because they respect the legitimate control flow of a program and by-pass memory protection schemes such as Address Space Layout Randomization, Data Execution Prevention, and Control Flow Integrity. Techniques that describe how to build DOP payloads rely on a program's source code. This research explores the feasibility of constructing DOP exploits without source code-that is, using only binary representations of programs. The lack of semantic and type information introduces difficulties …

“How Is My Child’S Asthma?” Digital Phenotype And Actionable Insights For Pediatric Asthma, Utkarshani Jaimini, Krishnaprasad Thirunarayan, Maninder Kalra, Revathy Venkataramanan, Dipesh Kadariya, Amit Sheth

Kno.e.sis Publications

Background: In the traditional asthma management protocol, a child meets with a clinician infrequently, once in 3 to 6 months, and is assessed using the Asthma Control Test questionnaire. This information is inadequate for timely determination of asthma control, compliance, precise diagnosis of the cause, and assessing the effectiveness of the treatment plan. The continuous monitoring and improved tracking of the child’s symptoms, activities, sleep, and treatment adherence can allow precise determination of asthma triggers and a reliable assessment of medication compliance and effectiveness. Digital phenotyping refers to moment-by-moment quantification of the individual-level human phenotype in situ using data from …

A Semantically Enhanced Approach To Identify Depression-Indicative Symptoms Using Twitter Data, Ankita Saxena

Browse all Theses and Dissertations

According to the World Health Organization, more than 300 million people suffer from Major Depressive Disorder (MDD) worldwide. PHQ-9 is used to screen and diagnose MDD clinically and identify its severity. With the unprecedented growth and enthusiastic acceptance of social media such as Twitter, a large number of people have come to share their feelings and emotions on it openly. Each tweet can indicate a user's opinion, thought or feeling. A tweet can also indicate multiple symptoms related to PHQ-9. Identifying PHQ-9 symptoms indicated by a tweet can provide crucial information about a user regarding his/her depression diagnosis. The current …

Worcester Center For Crafts: A Transition To Online Sales, Monica Gow, Carly Branconnier, Srilatha Prodduturi, Ekaterina Shusharina, Alberta Yamoah

School of Professional Studies

The Clark University School of Professional Studies created a capstone team consisting of Monica Gow, Carly Branconnier, Iana Matkovskaia, Srilatha Prodduturi, Ekaterina Shusharina, and Alberta Yamoah to assist Worcester Center for Crafts (WCC) with the launch of their new online store. Worcester Center for Crafts wanted to showcase their beautiful American handmade crafts on an online platform, Shopify, in order to increase their sales and expand their market reach. The capstone team created a charter that outlined the scope of the project and what the team would deliver to WCC by the end of the project. The team agreed to …

Audubon Data Project Final Report, Askhat Beygenov, Valinur Kutlambetov, Shrikant Patel, Phoebe Roberts, Ulfat Sayyed, Shriram Sivaraman

School of Professional Studies

The Audubon Data Project was initiated as a Clark University Capstone project. The project’s client, Mass Audubon’s Shaping the Future of Your Community program, had identified a need to improve their data management methods and make better use of their data. The Capstone team, composed of Clark University graduate students, met with the client regularly to review the current state of the data and potential improvements to be made. The process began with a data review. During the review we worked with the client to explicitly define the purposes and requirements of the data, the current process for updating and …

Recurrent Neural Networks And Their Applications To Rna Secondary Structure Inference, Devin Willmott

Theses and Dissertations--Mathematics

Recurrent neural networks (RNNs) are state of the art sequential machine learning tools, but have difficulty learning sequences with long-range dependencies due to the exponential growth or decay of gradients backpropagated through the RNN. Some methods overcome this problem by modifying the standard RNN architecure to force the recurrent weight matrix W to remain orthogonal throughout training. The first half of this thesis presents a novel orthogonal RNN architecture that enforces orthogonality of W by parametrizing with a skew-symmetric matrix via the Cayley transform. We present rules for backpropagation through the Cayley transform, show how to deal with the Cayley …