Physical Sciences and Mathematics Commons^™

A Dynamic Online Dashboard For Tracking The Performance Of Division 1 Basketball Athletic Performance, Erica Juliano, Chelsea Thakkar, Christopher B. Taber, Mehul S. Raval, Kaya Tolga, Samah Senbel

School of Computer Science & Engineering Undergraduate Publications

Using Data Analytics is a vital part of sport performance enhancement. We collect data from the Division 1 'Women's basketball athletes and coaches at our university, for use in analysis and prediction. Several data sources are used daily and weekly: WHOOP straps, weekly surveys, polar straps, jump analysis, and training session information. In this paper, we present an online dashboard to visually present the data to the athletes and coaches. R shiny was used to develop the platform, with the data stored on the cloud for instant updates of the dashboard as the data becomes available. The performance of athletes …

When Ai Moves Downstream, Frances S. Grodzinsky, Keith W. Miller, Marty J. Wolf

School of Computer Science & Engineering Faculty Publications

After computing professionals design, develop, and deploy software, what is their responsibility for subsequent uses of that software “downstream” by others? Furthermore, does it matter ethically if the software in question is considered to be artificial intelligent (AI)? The authors have previously developed a model to explore downstream accountability, called the Software Responsibility Attribution System (SRAS). In this paper, we explore three recent publications relevant to downstream accountability, and focus particularly on examples of AI software. Based on our understanding of the three papers, we suggest refinements of SRAS.

Thinking Local With Original Data In Ai And Machine Learning Research, David G. Taylor, Robert Mccloud

WCBT Working Papers

Sacred Heart University spent significant funds to establish an AI lab. Initially there is no ongoing research and no real plan for a research agenda. This paper details how the Jack Welch College of Business and Technology created and implemented an active meaningful research plan. It involves two key elements: thinking local and using business connections to foster active, impactful research. Surrounding communities, business connections, area environment, and other Sacred Heart University departments all played a part. The research plan also identifies a specific issue in working with local and business contact sources: the AI researcher almost never gets data …

E-Learning Course Recommender System Using Collaborative Filtering Models, Kalyan Kumar Jena, Sourav Kumar Bhoi, Tushar Kanta Malik, Kshira Sagar Sahoo, N. Z. Jhanjhi, Sajal Bhatia, Fathi Amsaad

School of Computer Science & Engineering Faculty Publications

e-Learning is a sought-after option for learners during pandemic situations. In e-Learning platforms, there are many courses available, and the user needs to select the best option for them. Thus, recommender systems play an important role to provide better automation services to users in making course choices. It makes recommendations for users in selecting the desired option based on their preferences. This system can use machine intelligence (MI)-based techniques to carry out the recommendation mechanism. Based on the preferences and history, this system is able to know what the users like most. In this work, a recommender system is proposed …

A Survey And Evaluation Of Android-Based Malware Evasion Techniques And Detection Frameworks, Parvez Faruki, Rhati Bhan, Vinesh Jain, Sajal Bhatia, Nour El Madhoun, Rajendra Pamula

School of Computer Science & Engineering Faculty Publications

Android platform security is an active area of research where malware detection techniques continuously evolve to identify novel malware and improve the timely and accurate detection of existing malware. Adversaries are constantly in charge of employing innovative techniques to avoid or prolong malware detection effectively. Past studies have shown that malware detection systems are susceptible to evasion attacks where adversaries can successfully bypass the existing security defenses and deliver the malware to the target system without being detected. The evolution of escape-resistant systems is an open research problem. This paper presents a detailed taxonomy and evaluation of Android-based malware evasion …

A Survey And Evaluation Of Android-Based Malware Evasion Techniques And Detection Frameworks, Parvez Faruki, Rhati Bhan, Vinesh Jain, Sajal Bhatia, Nour El Madhoun, Rajendra Pamula

School of Computer Science & Engineering Faculty Publications

Android platform security is an active area of research where malware detection techniques continuously evolve to identify novel malware and improve the timely and accurate detection of existing malware. Adversaries are constantly in charge of employing innovative techniques to avoid or prolong malware detection effectively. Past studies have shown that malware detection systems are susceptible to evasion attacks where adversaries can successfully bypass the existing security defenses and deliver the malware to the target system without being detected. The evolution of escape-resistant systems is an open research problem. This paper presents a detailed taxonomy and evaluation of Android-based malware evasion …

Discovering Ways To Increase Inclusivity For Dyslexic Students In Computing Education, Felicia Hellems, Sajal Bhatia

School of Computer Science & Engineering Faculty Publications

The years accompanying entrance into the university system are often characterized by a period of great transformation. These years can also be wrought with difficulties for many students, difficulties which are often compounded in students with disabilities (SWD). Reports from the U.S. Department of Education show that as recently as 2015--16, 19% of undergraduate students experienced some form of disability1. Additionally, statistics show that SWD tend to have lower post secondary completion rates than their counterparts [3]. A review of pertinent literature has shown that there still exist gaps within the field of computing education (CE) for teaching cybersecurity concepts …

Removing The Veil: Shining Light On The Lack Of Inclusivity In Cybersecurity Education For Students With Disabilities, Felicia Hellems, Sajal Bhatia

School of Computer Science & Engineering Faculty Publications

There are currently over one billion people living with some form of disability worldwide. The continuous increase in new technologies in today's society comes with an increased risk in security. A fundamental knowledge of cybersecurity should be a basic right available to all users of technology. A review of literature in the fields of cybersecurity, STEM, and computer science (CS) has revealed existent gaps regarding educational methods for teaching cybersecurity to students with disabilities (SWD's). To date, SWD's are largely left without equitable access to cybersecurity education. Our goal is to identify current educational methods being used to teach SWD's …

Cybersecurity Logging & Monitoring Security Program, Thai H. Nguyễn

School of Computer Science & Engineering Undergraduate Publications

With ubiquitous computing becoming pervasive in every aspect of societies around the world and the exponential rise in cyber-based attacks, cybersecurity teams within global organizations are spending a massive amount of human and financial capital on their logging and monitoring security programs. As a critical part of global organizational security risk management processes, it is important that log information is aggregated in a timely, accurate, and relevant manner. It is also important that global organizational security operations centers are properly monitoring and investigating the security use-case alerting based on their log data. In this paper, the author proposes a model …

C2 Microservices Api: Ch4rl3sch4l3m4gn3, Thai H. Nguyễn

School of Computer Science & Engineering Undergraduate Publications

In the 21^st century, cyber-based attackers such as advance persistent threats are leveraging bots in the form of botnets to conduct a plethora of cyber-attacks. While there are several social engineering techniques used to get targets to unknowingly download these bots, it is the command-and-control techniques advance persistent threats use to control their bots that is of critical interest to the author. In this research paper, the author aims to develop a command-and-control microservice application programming interface infrastructure to facilitate botnet command-and-control attack simulations. To achieve this the author will develop a simple bot skeletal framework, utilize the latest …

Religious Violence And Twitter: Networks Of Knowledge, Empathy And Fascination, Samah Senbel, Carly Seigel, Emily Bryan

School of Computer Science & Engineering Faculty Publications

Twitter analysis through data mining, text analysis, and visualization, coupled with the application of actor-network-theory, reveals a coalition of heterogenous religious affiliations around grief and fascination. While religious violence has always existed, the prevalence of social media has led to an increase in the magnitude of discussions around the topic. This paper examines the different reactions on Twitter to violence targeting three religious communities: the 2015 Charleston Church shooting, the 2018 Pittsburgh Synagogue shooting, and the 2019 Christchurch Mosque shootings. The attacks were all perpetrated by white nationalists with firearms. By analyzing large Twitter datasets in response to the attacks, …

Impact Of Sleep And Training On Game Performance And Injury In Division-1 Women’S Basketball Amidst The Pandemic, Samah Senbel, S. Sharma, S. M. Raval, Christopher B. Taber, Julie K. Nolan, N. S. Artan, Diala Ezzeddine, Kaya Tolga

School of Computer Science & Engineering Faculty Publications

We investigated the impact of sleep and training load of Division - 1 women’s basketball players on their game performance and injury prediction using machine learning algorithms. The data was collected during a pandemic-condensed season with unpredictable interruptions to the games and athletic training schedules. We collected data from sleep monitoring devices, training data from coaches, injury reports from medical staff, and weekly survey data from athletes for 22 weeks.With proper data imputation, interpretable feature set, data balancing, and classifiers, we showed that we could predict game performance and injuries with more than 90% accuracy. More importantly, our F1 and …

Agent-Based Semantic Role Mining For Intelligent Access Control In Multi-Domain Collaborative Applications Of Smart Cities, Rubina Ghazal, Ahmad Kamran Malik, Basit Raza, Nauman Qadeer, Nafees Qamar, Sajal Bhatia

School of Computer Science & Engineering Faculty Publications

Significance and popularity of Role-Based Access Control (RBAC) is inevitable; however, its application is highly challenging in multi-domain collaborative smart city environments. The reason is its limitations in adapting the dynamically changing information of users, tasks, access policies and resources in such applications. It also does not incorporate semantically meaningful business roles, which could have a diverse impact upon access decisions in such multi-domain collaborative business environments. We propose an Intelligent Role-based Access Control (I-RBAC) model that uses intelligent software agents for achieving intelligent access control in such highly dynamic multi-domain environments. The novelty of this model lies in using …

Autonomous Aerial Vehicle Vision And Sensor Guided Landing, Gabriel Bitencourt, Elijah J. Brown, Cedric Bleimling, Gilbert Lai, Arman Molki, Tolga Kaya

School of Computer Science & Engineering Faculty Publications

The use of autonomous landing of aerial vehicles is increasing in demand. Applications of this ability can range from simple drone delivery to unmanned military missions. To be able to land at a spot identified by local information, such as a visual marker, creates an efficient and versatile solution. This allows for a more user/consumer friendly device overall. To achieve this goal the use of computer vision and an array of ranging sensors will be explored. In our approach we utilized an April Tag as our location identifier and point of reference. MATLAB/Simulink interface was used to develop the platform …

Cybersecurity Analysis Of Load Frequency Control In Power Systems: A Survey, Sahaj Saxena, Sajal Bhatia, Rahul Gupta

School of Computer Science & Engineering Faculty Publications

Today, power systems have transformed considerably and taken a new shape of geographically distributed systems from the locally centralized systems thereby leading to a new infrastructure in the framework of networked control cyber-physical system (CPS). Among the different important operations to be performed for smooth generation, transmission, and distribution of power, maintaining the scheduled frequency, against any perturbations, is an important one. The load frequency control (LFC) operation actually governs this frequency regulation activity after the primary control. Due to CPS nature, the LFC operation is vulnerable to attacks, both from physical and cyber standpoints. The cyber-attack strategies ranges from …

Automated Waterloo Rubric For Concept Map Grading, Shresht Bhatia, Sajal Bhatia, Irfan Ahmed

School of Computer Science & Engineering Faculty Publications

Concept mapping is a well-known pedagogical tool to help students organize, represent, and develop an understanding of a topic. The grading of concept maps is typically manual, time-consuming, and tedious, especially for a large class. Existing research mostly focuses on topological scoring based-on structural features of concept maps. However, the scoring does not achieve comparable accuracy to well-defined rubrics for manual analysis on the quality of content in a concept map. This paper presents Kastor, a new method to automate the Waterloo Rubric of scoring concept maps by quantifying the rubric’s quality assessment parameters. The evaluation is performed on a …

Fast And Memory-Efficient Tfidf Calculation For Text Analysis Of Large Datasets, Samah Senbel

School of Computer Science & Engineering Faculty Publications

Term frequency – Inverse Document Frequency (TFIDF) is a vital first step in text analytics for information retrieval and machine learning applications. It is a memory-intensive and complex task due to the need to create and process a large sparse matrix of term frequencies, with the documents as rows and the term as columns and populate it with the term frequency of each word in each document.

The standard method of storing the sparse array is the “Compressed Sparse Row” (CSR), which stores the sparse array as three one-dimensional arrays for the row id, column id, and term frequencies. We …

Leading Through Change: 2020, Domenick Pinto

School of Computer Science & Engineering Faculty Publications

Having served as department chair and school director for 31 years, I have witnessed a tremendous evolution in the role of chair as economic, social and student climates have changed. My session will summarize collected data from chairs of departments of various sizes and types in order to discuss and understand better our ever changing role as we see responsibilities of delegating, leading change, creative budgeting and fundraising, grant writing and managing conflict become vital to our positions.

Introducing Parallelism To First-Year Cs Majors, Barbara M. Anthony, D. Cenk Erdil, Olga Glebova, Robert Montante

School of Computer Science & Engineering Faculty Publications

We propose to strengthen the computer science (CS) curriculum by embedding parallel concepts in a required first-semester seminar taken by all incoming declared CS majors. We introduce students to parallel computing concepts through a series of unplugged activities so that students see parallel approaches as a natural form of solution to a task. We describe a pilot offering of the class and activities, with measurements and analysis of what students self-report and their performance on assessments.

On Using Model For Downstream Responsibility, Frances S. Grodzinsky, Marty J. Wolf, Keith W. Miller

School of Computer Science & Engineering Faculty Publications

The authors identify features of software and the software development process that may contribute to the differences in the level of responsibility assigned to the software developers when they make their software available for others to use as a tool in building a second piece of software. They call this second use of the software "downstream use."

Rcrab: An R Analytics Tool To Visualize And Analyze The Movement Of Horseshoe Crabs In Long Island Sound, Ismael Youssef, Samah Senbel, Jo-Marie Kasinak, Jennifer Mattei

School of Computer Science & Engineering Faculty Publications

Mark-recapture programs are important for studying the ecology and population dynamics of wildlife. An R shiny analytics tool was developed to track the movement of horseshoe crabs in Long Island Sound based on tag and resight data. The crabs were tagged and recaptured by volunteers of Project Limulus, a community-based research program. The dataset contains tag and recapture location information for 14,065 horseshoe crabs over 18 years. The dataset was initially cleaned by removing records with missing, duplicate or incorrect data. A new data structure was developed to save the data and simplify processing: Three dimensions were used, one for …

Securing The Human: Broadening Diversity In Cybersecurity, Mohammad Azhar, Sajal Bhatia, Greg Gagne, Chadi Kari, Joseph Maguire, Xenia Montrouidou, Liviana Tudor, David Vosen, Timothy T. Yuen

School of Computer Science & Engineering Faculty Publications

Recent global demand for cybersecurity professionals is promising, with the U.S. job growth rate at 28%, three times the national average [1]. Lacking qualified applicants, many organizations struggle to fill open positions [2]. In a global survey, 2,300 security managers reported that 59% of their security positions were unfilled, although 82% anticipated cyberattacks to their systems [3]. At the same time, the cybersecurity field is broadening, not only in technical concepts but also in human factors, business processes, and international law. The field has not become culturally diversified, however. Professionals hired in 2018 included only 24.9% women, 12.3% African Americans, …

Teaching Self-Balancing Trees Using A Beauty Contest, Samah Senbel

School of Computer Science & Engineering Faculty Publications

Trees data structures and their performance is one of the main topics to teach in a data structures course. Appreciating the importance of tree structure and tree height in software performance is an important concept to teach. In this paper, a simple and amusing activity is presented. It demonstrates to students the importance of a well-balanced tree by comparing the height of a binary search tree to a balanced (AVL) tree build upon some personal data to find the “prettiest” tree (minimum height). The activity highlights the fact that, irrelevant of your data sequence, a balanced tree guarantees a height …

On The Responsibility For Uses Of Downstream Software, Marty J. Wolf, Keith W. Miller, Frances Grodzinsky, Ed.

School of Computer Science & Engineering Faculty Publications

In this paper we explore an issue that is different from whether developers are responsible for the direct impact of the software they write. We examine, instead, in what ways, and to what degree, developers are responsible for the way their software is used “downstream.” We review some key scholarship analyzing responsibility in computing ethics, including some recent work by Floridi. We use an adaptation of a mechanism developed by Floridi to argue that there are features of software that can be used as guides to better distinguish situations where a software developer might share in responsibility for the software’s …

Responding To Some Challenges Posed By The Re-Identification Of Anonymized Personal Data, Herman T. Tavani, Frances Grodzinsky, Ed.

School of Computer Science & Engineering Faculty Publications

In this paper, we examine a cluster of ethical controversies generated by the reidentification of anonymized personal data in the context of big data analytics, with particular attention to the implications for personal privacy. Our paper is organized into two main parts. Part One examines some ethical problems involving re-identification of personally identifiable information (PII) in large data sets. Part Two begins with a brief description of Moor and Weckert’s Dynamic Ethics (DE) and Nissenbaum’s Contextual Integrity (CI) Frameworks. We then investigate whether these frameworks, used together, can provide us with a more robust scheme for analyzing privacy concerns that …

An Artificial Sweating System For Sweat Sensor Testing Applications, Andrew Brueck, Kyle Bates, Trent Wood, William House, Zachary Martinez, Shannon Peters, Blain Root, Kumar Yelamarthi, Tolga Kaya

School of Computer Science & Engineering Faculty Publications

This research proposes a completely automated, computer-controlled fluid mixing and dispensing system, which is suitable for testing sweat sensing devices, as an alternative to requiring human trials during the development phase of a sweat sensor device. An arm mold was designed and implemented with dragon skin and pores to simulate sweating action. The relay controlled mixing tanks allow for the different concentration of fluid solutions at various rates of fluid dispensing through pores. The onboard single board computer controls a dozen electronic relays and it switches and presents an easy to use graphical user interface to allow end users to …

Applying Machine Learning To Anomaly-Based Intrusion Detection Systems, Fekadu Yihunie, Eman Abdelfattah, Amish Regmi

School of Computer Science & Engineering Faculty Publications

The enormous growth of Internet-based traffic exposes corporate networks with a wide variety of vulnerabilities. Intrusive traffics are affecting the normal functionality of network's operation by consuming corporate resources and time. Efficient ways of identifying, protecting, and mitigating from intrusive incidents enhance productivity. As Intrusion Detection System (IDS) is hosted in the network and at the user machine level to oversee the malicious traffic in the network and at the individual computer, it is one of the critical components of a network and host security. Unsupervised anomaly traffic detection techniques are improving over time. This research aims to find an …

The Ethics Of An Unlicensed Medical Practitioner, Charles C. Escott

Writing Across the Curriculum

For option A of this assignment, the prompt is that Harry, a manufacturer of medical equipment and an avid reader of medical textbooks, has developed a program that will allow its users to self-diagnose and self-treat their ailments, without a doctor’s help. Harry wants to sell his program to “ordinary folk” as a replacement for consulting licensed medical practitioners. An important point here is that Harry is not licensed to practice medicine and has only read books on the subject. The posed question is whether or not his program should be published (from an ethical standpoint—not necessarily a profit-driven one). …

Electrochemical Amperometric Biosensor Applications Of Nanostructured Metal Oxides: A Review, Bünyamin Sahin, Tolga Kaya

School of Computer Science & Engineering Faculty Publications

Biological sensors have been extensively investigated during the last few decades. Among the diverse facets of biosensing research, nanostructured metal oxides (NMOs) offer a plethora of potential benefits. In this article, we provide a thorough review on the sensor applications of NMOs such as glucose, cholesterol, urea, and uric acid. A detailed analysis of the literature is presented with organized tables elaborating the fundamental characteristics of sensors including the sensitivity, limit of detection, detection range, and stability parameters such as duration, relative standard deviation, and retention. Further analysis was provided through an innovative way of displaying the sensitivity and linear …

Evaluation Of Routing Protocols With Ftp And P2p, Tyler Wilson, Eman Abdelfattah, Samir Hamada

School of Computer Science & Engineering Faculty Publications

One of the decisions that need to be made when designing and configuring a computer network in which routing protocol should be used. This paper presents a simulation of a high load File Transfer Protocol (FTP) Application and a high load Peer to Peer (P2P) Application using Riverbed Academic Modeler 17.5. The simulation is configured and run in a World environment to replicate a global network. Each simulation employs either RIP, OSPF, or EIGRP routing protocol. The queuing delay, throughput, link utilization, and IP packets dropped are used as performance parameters to determine which routing protocol is the most efficient …