Computer Sciences Commons^™

Engagement And Computational Thinking Through Creative Coding, Dana Hoppe

Honors Program: Senior Projects (Public)

Rising enrollments in Computer Science pose an opportunity to engage students from diverse backgrounds and interests; and a challenge to deliver on positive learning outcomes. While student engagement is the driving factor for increased learning performance and retention, it has been declining to new lows for Computer Science students in recent years. In order to further explore the potential of contextualized computing as a tool for increasing engagement in computing and developing Computational Thinking aptitude in students, we have developed an introductory computing course contextualized with Art and Design with modules centered around guiding pedagogical principles and aimed at middle …

Devops: Lecture 1 - "Overview", Jeremy Andrews, Nyc Tech-In-Residence Corps

Open Educational Resources

Overview lecture for the "DevOps" course delivered at the City College of New York in Spring 2020 by Jeremy Andrews as part of the Tech-in-Residence Corps program.

Devops: Architecting Your Infrastructure (Syllabus), Jeremy Andrews, Nyc Tech-In-Residence Corps

Open Educational Resources

Syllabus for the "DevOps" course delivered at the City College of New York in Spring 2020 by Jeremy Andrews as part of the Tech-in-Residence Corps program.

Some Advice For Psychologists Who Want To Work With Computer Scientists On Big Data, Cornelius J. König, Andrew M. Demetriou, Philipp Glock, Annemarie M. F. Hiemstra, Dragos Iliescu, Camelia Ionescu, Markus Langer, Cynthia C. S. Liem, Anja Linnenbürger, Rudolf Siegel, Ilias Vartholomaios

Personnel Assessment and Decisions

This article is based on conversations from the project “Big Data in Psychological Assessment” (BDPA) funded by the European Union, which was initiated because of the advances in data science and artificial intelligence that offer tremendous opportunities for personnel assessment practice in handling and interpreting this kind of data. We argue that psychologists and computer scientists can benefit from interdisciplinary collaboration. This article aims to inform psychologists who are interested in working with computer scientists about the potentials of interdisciplinary collaboration, as well as the challenges such as differing terminologies, foci of interest, data quality standards, approaches to data analyses, …

A Multi-Branch Separable Convolution Neural Network For Pedestrian Attribute Recognition, Imran N. Junejo, Naveed Ahmed

All Works

© 2020 The Authors Computer science; Computer Vision; Image processing; Deep learning; Pedestrian attribute recognition

Experiential Learning In The Technology Disciplines February 2020, Patricia Sendall, Christopher S. Stuetzle, Zachary A. Kissel, Tahir Hameed

Computer and Data Science Faculty Publications

Learning-by-doing has long been a tradition in the technology disciplines. It is the "hands-on" work, combined with student reflection, feedback and assessment, that reinforces theory into practice. Over the past 40 years, experiential learning (EL) in higher education has grown beyond in-class assignments to include internships, cooperative education, team-based learning, project-based learning, community engagement, service learning, international and study-away experiences, capstone projects and research opportunities. This paper provides an overview of experiential education theory and practice in the undergraduate technology disciplines, and presents examples of how experiential learning practices have evolved over time at a medium-sized institution in the Northeast …

Ms In Quantum Computing, Joanna M. Burkhardt

Library Impact Statements

No abstract provided.

Using Natural Language Processing To Categorize Fictional Literature In An Unsupervised Manner, Dalton J. Crutchfield

Electronic Theses and Dissertations

When following a plot in a story, categorization is something that humans do without even thinking; whether this is simple classification like “This is science fiction” or more complex trope recognition like recognizing a Chekhov's gun or a rags to riches storyline, humans group stories with other similar stories. Research has been done to categorize basic plots and acknowledge common story tropes on the literary side, however, there is not a formula or set way to determine these plots in a story line automatically. This paper explores multiple natural language processing techniques in an attempt to automatically compare and cluster …

Social Media Based Algorithmic Clinical Decision Support Learning From Behavioral Predispositions, Radhika V. Medury

Doctoral Dissertations

Behavioral disorders are disabilities characterized by an individual’s mood, thinking, and social interactions. The commonality of behavioral disorders amongst the United States population has increased in the last few years, with an estimated 50% of all Americans diagnosed with a behavioral disorder at some point in their lifetime. AttentionDeficit/Hyperactivity Disorder is one such behavioral disorder that is a severe public health concern because of its high prevalence, incurable nature, significant impact on domestic life, and peer relationships. Symptomatically, in theory, ADHD is characterized by inattention, hyperactivity, and impulsivity. Access to providers who can offer diagnosis and treat the disorder varies …

Prediction Of Sudden Cardiac Death Using Ensemble Classifiers, Ayman Momtaz El-Geneidy

CCAC Theses and Dissertations

Sudden Cardiac Death (SCD) is a medical problem that is responsible for over 300,000 deaths per year in the United States and millions worldwide. SCD is defined as death occurring from within one hour of the onset of acute symptoms, an unwitnessed death in the absence of pre-existing progressive circulatory failures or other causes of deaths, or death during attempted resuscitation. Sudden death due to cardiac reasons is a leading cause of death among Congestive Heart Failure (CHF) patients. The use of Electronic Medical Records (EMR) systems has made a wealth of medical data available for research and analysis. Supervised …

A Pcnn Framework For Blood Cell Image Segmentation, Carol D. Lenihan

CCAC Theses and Dissertations

This research presents novel methods for segmenting digital blood cell images under a Pulse Coupled Neural Network (PCNN) framework. A blood cell image contains different types of blood cells found in the peripheral blood stream such as red blood cells (RBCs), white blood cells (WBCs), and platelets. WBCs can be classified into five normal types – neutrophil, monocyte, lymphocyte, eosinophil, and basophil – as well as abnormal types such as lymphoblasts and others. The focus of this research is on identifying and counting RBCs, normal types of WBCs, and lymphoblasts. The total number of RBCs and WBCs, along with classification …

Ethics, Privacy And Data Collection: A Complex Intersection, Matthew S. Brown

Honors Theses

The technology around us enables incredible abilities such as high-resolution video calls and the ability to stay connected with everyone we care about through social media. This technology also comes with a hidden cost in the form of data collection.

This work explores what privacy means and how users understand what data social media companies collect and monetize. This thesis also proposes a more ethical business model that addresses privacy concerns from an individual perspective.

A Tutorial And Future Research For Building A Blockchain-Based Secure Communication Scheme For Internet Of Intelligent Things, Mohammad Wazid, Ashok Kumar Das, Sachin Shetty, Minho Jo

Computational Modeling & Simulation Engineering Faculty Publications

The Internet of Intelligent Things (IoIT) communication environment can be utilized in various types of applications (for example, intelligent battlefields, smart healthcare systems, the industrial internet, home automation, and many more). Communications that happen in such environments can have different types of security and privacy issues, which can be resolved through the utilization of blockchain. In this paper, we propose a tutorial that aims in desiging a generalized blockchain-based secure authentication key management scheme for the IoIT environment. Moreover, some issues with using blockchain for a communication environment are discussed as future research directions. The details of different types of …

Transfer Equivalency Site For The Registrar, Janelle N. Rohrbach, Alissa C. Cielecki, Jules A. Turner

Capstone Showcase

The website, arcadia-transfer-equiv.com, was drafted and created for Bill Enick, Registrar at Arcadia University. This was an expansion of a preliminary version of the website created by Caleigh Diefenthaler, Christian Charney, and Dylan Power. The site includes two transfer equivalency tools which can be used to search for course equivalencies by academic institution or by a given Arcadia course. The tools, which pull from a database maintained by the Registrar, will display courses that have transferred to the University successfully. The website also hosts two interactive forms. These forms allow Arcadia students to request approval for courses that have or …

Identifying Knowledge Gaps Using A Graph-Based Knowledge Representation, Daniel P. Schmidt

Browse all Theses and Dissertations

Knowledge integration and knowledge bases are becoming more and more prevalent in the systems we use every day. When developing these knowledge bases, it is important to ensure the correctness of the information upon entry, as well as allow queries of all sorts; for this, understanding where the gaps in knowledge can arise is critical. This thesis proposes a descriptive taxonomy of knowledge gaps, along with a framework for automated detection and resolution of some of those gaps. Additionally, the effectiveness of this framework is evaluated in terms of successful responses to queries on a knowledge base constructed from a …

An Adversarial Framework For Deep 3d Target Template Generation, Walter E. Waldow

Browse all Theses and Dissertations

This paper presents a framework for the generation of 3D models. This is an important problem for many reasons. For example, 3D models are important for systems that are involved in target recognition. These systems use 3D models to train up accuracy on identifying real world object. Traditional means of gathering 3D models have limitations that the generation of 3D models can help overcome. The framework uses a novel generative adversarial network (GAN) that learns latent representations of two dimensional views of a model to bootstrap the network’s ability to learn to generate three dimensional objects. The novel architecture is …

Examination Of Practices Used By Ap Computer Science Teachers With Higher Than Average Female Enrollment, Derek J. Miller

Graduate Research Theses & Dissertations

This dissertation examines the practices employed by AP Computer Science A teachers that can help recruit and retain female students in computer science. A survey was sent to teachers to see what practices they used in their classrooms and what practices they thought had the biggest influence on female student recruitment and retention. Of the five practice categories (recruitment, pedagogical, curricular, extracurricular, and mentoring), the survey respondents thought recruitment was the most influential and curricular was the least influential. After the survey, 12 teachers were chosen for interviews because they had a higher enrollment of female students than the rest …

The Perceptions And Lived Experiences Of Female Students In A Computer Science Program At A Community College, Terry Voldase

Walden Dissertations and Doctoral Studies

America's higher education institutions have aligned computer science curricula with today's modern technology. Despite these efforts, data have shown that there is slow growth among young women majoring in computer science and even slower growth in this area at community colleges. Higher education institutions have also acknowledged a gap between men and women entering the computer science field and a need to explore options for computer science programs to engage women in the industry. The purpose of this phenomenological study was to gain an understanding of the perceptions and lived experiences of female students enrolled in computer classes at New …

Overrepresentation Of The Underrepresented: Gender Bias In Wikipedia, Anna Marinina

Honors College Theses

The goal of our research is to determine if gender bias exists in Wikipedia. Wikipedia is a very large dataset that has been used to train artificial intelligence models. If a dataset that is being used for this purpose is biased, then the artificial intelligence model that was trained with it will be biased as well, therefore making biased decisions. For this reason, it is important to explore large datasets for any potential biases before they are used in machine learning. Since Wikipedia is ontologically structured, we used graph theory to create a network of all of the website’s categories …

Local Radiance, Scott Peter Britell

Dissertations and Theses

Recent years have seen a proliferation of web applications based on content management systems (CMS). Using a CMS, non-technical content authors are able to define custom content types to support their needs. These content type names and the attribute names in each content type are typically domain-specific and meaningful to the content authors. The ability of a CMS to support a multitude of content types allows for endless creation and customization but also leads to a large amount of heterogeneity within a single application. While this meaningful heterogeneity is beneficial, it introduces the problem of how to write reusable functionality …

Realtime Object Detection Via Deep Learning-Based Pipelines, James G. Shanahan, Liang Dai

Information Systems and Analytics Department Faculty Conference Proceedings

Ever wonder how the Tesla Autopilot system works (or why it fails)? In this tutorial we will look under the hood of self-driving cars and of other applications of computer vision and review state-of-the-art tech pipelines for object detection such as two-stage approaches (e.g., Faster R-CNN) or single-stage approaches (e.g., YOLO/SSD). This is accomplished via a series of Jupyter Notebooks that use Python, OpenCV, Keras, and Tensorflow. No prior knowledge of computer vision is assumed (although it will be help!). To this end we begin this tutorial with a review of computer vision and traditional approaches to object detection such …

Technical Report 2019-01: Pupil Labs Eye Tracking User Guide, Joan D. Gannon, Augustine Ubah, Chris Dancy

Other Faculty Research and Publications

No abstract provided.

User Syndication Using Speech Rhythm, Faisal Z H Alnahhas

Computer Science and Engineering Theses - Archive

In recent years we have seen a variety of approaches to increase security on computers and mobile devices including fingerprint, and facial recognition. Such techniques while effective are very expensive. Voice biometrics, specifically speech rhythm, is a method that has been drawing attention and growing in recent years. Unlike other methods, it requires little to no additional hardware installed on a device for it to work accurately. Speech rhythm utilizes the device's built-in microphone, and analyzes speakers based on features of their speech. In this work we leverage the existing hardware and simply add an efficient layer of software to …

Versatile Binary-Level Concolic Testing, Bo Chen

Dissertations and Theses

Computing systems are experiencing an explosive growth, both in complexities and diversities, ushered in by the proliferation of cloud computing, mobile computing, and Internet of Things. This growth has also exposed the consequences of unsafe, insecure, and unreliable computing systems. These all point to the great needs of sophisticated system validation techniques. Recent advances in research on symbolic execution has shown great promises for automated software analysis, e.g., generating test cases, finding bugs, and detecting security vulnerabilities. However, symbolic execution is mostly adopted to analyze user applications, while modern computing systems in practice consist of many components shipped by various …

Design And Experimental Evaluation Of Deepmarket: An Edge Computing Marketplace With Distributed Tensorflow Execution Capability, Soyoung Kim

Dissertations and Theses

There is a rise in demand among machine learning researchers for powerful computational resources to train complex machine learning models, e.g., deep learning models. In order to train these models in a reasonable amount of time, the training is often distributed among multiple machines; yet paying for such machines (either through renting them on cloud data centers or building a local infrastructure) is costly. DeepMarket attempts to reduce these costs by creating a marketplace that integrates multiple computational resources over a distributed TensorFlow framework. Instead of requiring users to rent expensive GPU/CPUs from a third-party cloud provider, DeepMarket allows users …

Inclusion Of Women In Computer Science, Naomi Johnson, Dr. Kevin Seppi

Journal of Undergraduate Research

Since the 1980’s, the percentage of computer science degrees awarded to women in the United States has fallen dramatically. There are growing numbers of men earning bachelor’s degrees in CS, and the numbers of women are increasing very slowly. For decades, researchers have been studying recruitment and retention of women and other minorities in CS, yet it is still not apparent what departments, professors, or students can do in order to get the numbers of women earning degrees in CS up again.

Single Image Reflection Removal Beyond Linearity, Qiang Wen, Yinjie Tan, Jing Qin, Wenxi Liu, Guoqiang Han, Shengfeng He

Research Collection School Of Computing and Information Systems

Due to the lack of paired data, the training of image reflection removal relies heavily on synthesizing reflection images. However, existing methods model reflection as a linear combination model, which cannot fully simulate the real-world scenarios. In this paper, we inject non-linearity into reflection removal from two aspects. First, instead of synthesizing reflection with a fixed combination factor or kernel, we propose to synthesize reflection images by predicting a non-linear alpha blending mask. This enables a free combination of different blurry kernels, leading to a controllable and diverse reflection synthesis. Second, we design a cascaded network for reflection removal with …

Crumpled And Abraded Encryption: Implementation And Provably Secure Construction, Scott Sherlock Griffy

Dissertations and Theses

Abraded and crumpled encryption allows communication software such as messaging platforms to ensure privacy for their users while still allowing for some investigation by law enforcement. Crumpled encryption ensures that each decryption is costly and prevents law enforcement from performing mass decryption of messages. Abrasion ensures that only large organizations like law enforcement are able to access any messages. The current abrasion construction uses public key parameters such as prime numbers which makes the abrasion scheme difficult to analyze and allows possible backdoors. In this thesis, we introduce a new abrasion construction which uses hash functions to avoid the problems …

Building Of Mira’S Ghost Cleansing Services, Ashley Vargas

Honors College Theses

In this thesis, I built a PC game called Mira’s Cleansing Services. It is a sidescroller game that follows the story of a female exorcist for-hire who is also a high school student. Using ABC Scrum, a modified version of Scrum for game development, I developed the game using Game Maker. Additionally, I created all the art and music in different software. Because of time constraints and because I was working alone, I only developed the first level of the game. However, I plan to continue developing the game after this semester to eventually complete and publish it. My ultimate …

Seeing Eye To Eye: A Machine Learning Approach To Automated Saccade Analysis, Maigh Attre

Honors Scholar Theses

Abnormal ocular motility is a common manifestation of many underlying pathologies particularly those that are neurological. Dynamics of saccades, when the eye rapidly changes its point of fixation, have been characterized for many neurological disorders including concussions, traumatic brain injuries (TBI), and Parkinson’s disease. However, widespread saccade analysis for diagnostic and research purposes requires the recognition of certain eye movement parameters. Key information such as velocity and duration must be determined from data based on a wide set of patients’ characteristics that may range in eye shapes and iris, hair and skin pigmentation [36]. Previous work on saccade analysis has …