Physical Sciences and Mathematics Commons^™

Computer Ethics In Curriculum, Tiya Williams

Publications and Research

Ethics specifically in Computer Curriculum is a growing problem that has yet to be widely addressed. Although, start of computer ethics being taught has been traced back to the early 1940’s it has not been standardized or implemented in all computer curriculum. The objective of this research is to diagnose the reasons why ethics is so crucial in computer curriculum at all levels. I used surveys to investigate whether students were taught ethics in their computer curriculum. I also conducted surveys for professors at universities and colleges if they were taught ethics while obtaining their degree, as well as if …

Plasmon Damping Rates In Coulomb-Coupled 2d Layers In A Heterostructure, Dipendra Dahal, Godfrey Gumbs, Andrii Iurov, Chin-Sen Ting

Publications and Research

The Coulomb excitations of charge density oscillation are calculated for a double-layer heterostructure. Specifically, we consider two-dimensional (2D) layers of silicene and graphene on a substrate. From the obtained surface response function, we calculated the plasmon dispersion relations, which demonstrate how the Coulomb interaction renormalizes the plasmon frequencies. Most importantly, we have conducted a thorough investigation of how the decay rates of the plasmons in these heterostructures are affected by the Coulomb coupling between different types of two- dimensional materials whose separations could be varied. A novel effect of nullification of the silicene band gap is noticed when graphene is …

Algorithmic Rationality, Rohit J. Parikh

Publications and Research

The notion of rationality is much discussed by both Economists and Philosophers. Perhaps you are rational if you accept certain axioms of rationality. If you prefer A to B and B to C then you must prefer A to C. Or you can define rationality in terms of the net results of your behavior. We examine a notion of algorithmic rationality. Even animals upwards from the humble tick carry out algorithms. Are they rational? And can we use this theory to define the IQ of animals?

Artificial Intelligence And The Situational Rationality Of Diagnosis: Human Problem-Solving And The Artifacts Of Health And Medicine, Michael W. Raphael

Publications and Research

What is the problem-solving capacity of artificial intelligence (AI) for health and medicine? This paper draws out the cognitive sociological context of diagnostic problem-solving for medical sociology regarding the limits of automation for decision-based medical tasks. Specifically, it presents a practical way of evaluating the artificiality of symptoms and signs in medical encounters, with an emphasis on the visualization of the problem-solving process in doctor-patient relationships. In doing so, the paper details the logical differences underlying diagnostic task performance between man and machine problem-solving: its principle of rationality, the priorities of its means of adaptation to abstraction, and the effects …

Small Molecule Modulation Of Microbiota: A Systems Pharmacology Perspective, Qiao Liu, Bohyun Lee, Lei Xie

Publications and Research

Background

Microbes are associated with many human diseases and influence drug efficacy. Small-molecule drugs may revolutionize biomedicine by fine-tuning the microbiota on the basis of individual patient microbiome signatures. However, emerging endeavors in small-molecule microbiome drug discovery continue to follow a conventional “one-drug-one-target-one-disease” process. A systematic pharmacology approach that would suppress multiple interacting pathogenic species in the microbiome, could offer an attractive alternative solution.

Results

We construct a disease-centric signed microbe–microbe interaction network using curated microbe metabolite information and their effects on host. We develop a Signed Random Walk with Restart algorithm for the accurate prediction of effect of microbes …

Web Design, Kwame A. Baffour

Open Educational Resources

No abstract provided.

How Many Mutex Bugs Can A Simple Analysis Find In Go Programs?, Fumi Takeuchi, Hidehiko Masuhara, Raffi T. Khatchadourian, Youyou Cong, Keisuke Ishibashi

Publications and Research

In open-source software, it is known that there are many concurrency bugs. A previous study in Go revealed that a considerable number of such bugs are simple (for example, 9% of the bugs are the ones that forget to unlock a mutex,) through a manual program investigation. This paper tries to detect such bugs by applying a simple analysis to see how far such a tool can match the manual analysis. We built a simple intraprocedural control flow analysis in Go, and evaluated its performance concerning the open source programs with concurrency bugs reported in the previous study. Consequently, as …

Asian Hate Speech Detection On Twitter During Covid-19, Amir Toliyat, Sarah Ita Levitan, Zeng Peng, Ronak Etemadpour

Publications and Research

Coronavirus disease 2019 (COVID-19) started in Wuhan, China, in late 2019, and after being utterly contagious in Asian countries, it rapidly spread to other countries. This disease caused governments worldwide to declare a public health crisis with severe measures taken to reduce the speed of the spread of the disease. This pandemic affected the lives of millions of people. Many citizens that lost their loved ones and jobs experienced a wide range of emotions, such as disbelief, shock, concerns about health, fear about food supplies, anxiety, and panic. All of the aforementioned phenomena led to the spread of racism and …

(2022 Revision) Chapter 3: Essential Aspects Of Physical Design And Implementation Of Relational Databases, Tatiana Malyuta, Ashwin Satyanarayana

Open Educational Resources

No abstract provided.

(2022 Revision) Chapter 5: Essential Aspects Of Physical Design And Implementation Of Relational Databases, Tatiana Malyuta, Ashwin Satyanarayana

Open Educational Resources

No abstract provided.

(2022 Revision) Chapter 1: Essential Aspects Of Physical Design And Implementation Of Relational Databases, Tatiana Malyuta, Ashwin Satyanarayana

Open Educational Resources

No abstract provided.

(2022 Revision) Chapter 2: Essential Aspects Of Physical Design And Implementation Of Relational Databases, Tatiana Malyuta, Ashwin Satyanarayana

Open Educational Resources

No abstract provided.

(2022 Revision) Chapter 4: Essential Aspects Of Physical Design And Implementation Of Relational Databases, Tatiana Malyuta, Ashwin Satyanarayana

Open Educational Resources

No abstract provided.

(2022 Revision) Chapter 6: Essential Aspects Of Physical Design And Implementation Of Relational Databases, Tatiana Malyuta, Ashwin Satyanarayana

Open Educational Resources

No abstract provided.

(2022 Revision) Chapter 7: Essential Aspects Of Physical Design And Implementation Of Relational Databases, Tatiana Malyuta, Ashwin Satyanarayana

Open Educational Resources

No abstract provided.

(2022 Revision) Appendix: Essential Aspects Of Physical Design And Implementation Of Relational Databases, Tatiana Malyuta, Ashwin Satyanarayana

Open Educational Resources

No abstract provided.

Quertci: A Tool Integrating Github Issue Querying With Comment Classification, Ye Paing, Tatiana Castro Vélez, Raffi T. Khatchadourian

Publications and Research

Empirical Software Engineering (ESE) researchers study (open-source) project issues and the comments and threads within to discover—among others—challenges developers face when incorporating new technologies, platforms, and programming language constructs. However, such threads accumulate, becoming unwieldy and hindering any insight researchers may gain. While existing approaches alleviate this burden by classifying issue thread comments, there is a gap between searching popular open-source software repositories (e.g., those on GitHub) for issues containing particular keywords and feeding the results into a classification model. This paper demonstrates a research infrastructure tool called QuerTCI that bridges this gap by integrating the GitHub issue comment search …

Computer-Aided Response-To-Intervention For Reading Comprehension Based On Recommender System, Ming-Chi Liu, Wei-Yang Lin, Chia-Ling Tsai

Publications and Research

In 2019, New York State Education Department announced 54.6% of all students in grades 3 to 8 not meeting the standard of reading proficiency. Motivated by the need for a more efficient intervention model, we propose a recommender system to leverage the technology in machine learning to recommend suitable reading materials for effective intervention. The recommendation is based on the student's prior reading comprehension assessments and also assessments of other students at the same grade level using collaborative filtering. No other prior academic or demographic information of students is available. Two main challenges are lack of explicit ratings of reading …

Positive Rate-Dependent Action Potential Prolongation By Modulating Potassium Ion Channels, Candido Cabo

Publications and Research

Pharmacological agents that prolong action potential duration (APD) to a larger extent at slow rates than at the fast excitation rates typical of ventricular tachycardia exhibit reverse rate dependence. Reverse rate dependence has been linked to the lack of efficacy of class III agents at preventing arrhythmias because the doses required to have an anti-arrhythmic effect at fast rates may have pro-arrhythmic effects at slow rates due to an excessive APD prolongation. In this report we show that, in computer models of the ventricular action potential, APD prolongation by accelerating phase 2 repolarization (by increasing I_Ks) and decelerating …

Spotlight Report #6: Proffering Machine-Readable Personal Privacy Research Agreements: Pilot Project Findings For Ieee P7012 Wg, Noreen Y. Whysel, Lisa Levasseur

Publications and Research

What if people had the ability to assert their own legally binding permissions for data collection, use, sharing, and retention by the technologies they use? The IEEE P7012 has been working on an interoperability specification for machine-readable personal privacy terms to support this ability since 2018. The premise behind the work of IEEE P7012 is that people need technology that works on their behalf—i.e. software agents that assert the individual’s permissions and preferences in a machine-readable format.

Thanks to a grant from the IEEE Technical Activities Board Committee on Standards (TAB CoS), we were able to explore the attitudes of …

Challenges In Migrating Imperative Deep Learning Programs To Graph Execution: An Empirical Study, Tatiana Castro Vélez, Raffi T. Khatchadourian, Mehdi Bagherzadeh, Anita Raja

Publications and Research

Efficiency is essential to support responsiveness w.r.t. ever-growing datasets, especially for Deep Learning (DL) systems. DL frameworks have traditionally embraced deferred execution-style DL code that supports symbolic, graph-based Deep Neural Network (DNN) computation. While scalable, such development tends to produce DL code that is error-prone, non-intuitive, and difficult to debug. Consequently, more natural, less error-prone imperative DL frameworks encouraging eager execution have emerged at the expense of run-time performance. While hybrid approaches aim for the "best of both worlds," the challenges in applying them in the real world are largely unknown. We conduct a data-driven analysis of challenges—and resultant bugs—involved …

A Tool For Rejuvenating Feature Logging Levels Via Git Histories And Degree Of Interest, Yiming Tang, Allan Spektor, Raffi T. Khatchadourian, Mehdi Bagherzadeh

Publications and Research

Logging is a significant programming practice. Due to the highly transactional nature of modern software applications, a massive amount of logs are generated every day, which may overwhelm developers. Logging information overload can be dangerous to software applications. Using log levels, developers can print the useful information while hiding the verbose logs during software runtime. As software evolves, the log levels of logging statements associated with the surrounding software feature implementation may also need to be altered. Maintaining log levels necessitates a significant amount of manual effort. In this paper, we demonstrate an automated approach that can rejuvenate feature log …

Exploration Of Chemical Space With Partial Labeled Noisy Student Self‑Training And Self‑Supervised Graph Embedding, Yang Liu, Hansaim Lim, Lei Xie

Publications and Research

Background Drug discovery is time-consuming and costly. Machine learning, especially deep learning, shows great potential in quantitative structure–activity relationship (QSAR) modeling to accelerate drug discovery process and reduce its cost. A big challenge in developing robust and generalizable deep learning models for QSAR is the lack of a large amount of data with high-quality and balanced labels. To address this challenge, we developed a self-training method, Partially LAbeled Noisy Student (PLANS), and a novel self-supervised graph embedding, Graph-Isomorphism-Network Fingerprint (GINFP), for chemical compounds representations with substructure information using unlabeled data. The representations can be used for predicting chemical properties such …

Designing Respectful Tech: What Is Your Relationship With Technology?, Noreen Y. Whysel

Publications and Research

According to research at the Me2B Alliance, people feel they have a relationship with technology. It’s emotional. It’s embodied. And it’s very personal. We are studying digital relationships to answer questions like “Do people have a relationship with technology?” “What does that relationship feel like?” And “Do people understand the commitments that they are making when they explore, enter into and dissolve these relationships?” There are parallels between messy human relationships and the kinds of relationships that people develop with technology. As with human relationships, we move through states of discovery, commitment and breakup with digital applications as well. Technology …

Diagnosis Of Polypoidal Choroidal Vasculopathy From Fluorescein Angiography Using Deep Learning, Yu-Yeh Tsai, Wei-Yang Ling, Shih-Jen Chen, Paisan Ruamviboonsuk, Cheng-Ho King, Chia-Ling Tsai

Publications and Research

Purpose: To differentiate polypoidal choroidal vasculopathy (PCV) from choroidal neovascularization (CNV) and to determine the extent of PCV from fluorescein angiography (FA) using attention-based deep learning networks.

Methods: We build two deep learning networks for diagnosis of PCV using FA, one for detection and one for segmentation. Attention-gated convolutional neural network (AG-CNN) differentiates PCV from other types of wet age-related macular degeneration. Gradient-weighted class activation map (Grad-CAM) is generated to highlight important regions in the image for making the prediction, which offers explainability of the network. Attention-gated recurrent neural network (AG-PCVNet) for spatiotemporal prediction is applied for segmentation …

Diagnosis Of Polypoidal Choroidal Vasculopathy From Fluorescein Angiography Using Deep Learning, Yu-Yeh Tsai, Wei-Yang Lin, Shih-Jen Chen, Paisan Ruamviboonsuk, Cheng-Ho King, Chia-Ling Tsai

Publications and Research

Purpose: To differentiate polypoidal choroidal vasculopathy (PCV) from choroidal neovascularization (CNV) and to determine the extent of PCV from fluorescein angiography (FA) using attention-based deep learning networks.

Methods: We build two deep learning networks for diagnosis of PCV using FA, one for detection and one for segmentation. Attention-gated convolutional neural network (AG-CNN) differentiates PCV from other types of wet age-related macular degeneration. Gradient-weighted class activation map (Grad-CAM) is generated to highlight important regions in the image for making the prediction, which offers explainability of the network. Attention-gated recurrent neural network (AG-PCVNet) for spatiotemporal prediction is applied for segmentation of PCV. …

Emotion Recognition With Audio, Video, Eeg, And Emg: A Dataset And Baseline Approaches, Jin Chen, Tony Ro, Zhigang Zhu

Publications and Research

This paper describes a new posed multimodal emotional dataset and compares human emotion classification based on four different modalities - audio, video, electromyography (EMG), and electroencephalography (EEG). The results are reported with several baseline approaches using various feature extraction techniques and machine-learning algorithms. First, we collected a dataset from 11 human subjects expressing six basic emotions and one neutral emotion. We then extracted features from each modality using principal component analysis, autoencoder, convolution network, and mel-frequency cepstral coefficient (MFCC), some unique to individual modalities. A number of baseline models have been applied to compare the classification performance in emotion recognition, …

Me2b Alliance Validation Testing Report: Consumer Perception Of Legal Policies In Digital Technology, Noreen Y. Whysel, Karina Alexanyan, Shaun Spaulting, Julia Little

Publications and Research

Our relationship with technology involves legal agreements that we either review or enter into when using a technology, namely privacy policies and terms of service or terms of use (“TOS/TOU”). We initiated this research to understand if providing a formal rating of the legal policies (privacy policies and TOS/TOUs) would be valuable to consumers (or Me-s). From our early qualitative discussions, we noticed that people were unclear on whether these policies were legally binding contracts or not. Thus, a secondary objective emerged to quantitatively explore whether people knew who these policies protected (if anyone), and if the policies were perceived …

Eclipse, Osgi, And The Java Model, Raffi T. Khatchadourian

Open Educational Resources

No abstract provided.

Abstract Syntax Trees (Asts) And The Visitor Pattern, Raffi T. Khatchadourian

Open Educational Resources

No abstract provided.