Computer Sciences Commons^™

Cybersecurity (Cs 3550): Lecture 13: Patching & Vulnerability Management, Michael Whiteman, Nyc Tech-In-Residence Corps

Open Educational Resources

Lecture for the course: CIS 3550: Cybersecurity - "13: Patching & Vulnerability Management" delivered at Baruch College in Spring 2020 by Michael Whiteman as part of the Tech-in-Residence Corps program.

Does Applying Deep Learning In Financial Sentiment Analysis Lead To Better Classification Performance?, Tao Wang, Changhe Yuan, Cuiyuan Wang

Publications and Research

Using a unique data set from Seeking Alpha, we compare the deep learning approach with traditional machine learning approaches in classifying financial text. We apply the long short-term memory (LSTM) as the deep learning method and Naive Bayes, SVM, Logistic Regression, XGBoost as the traditional machine learning approaches. The results suggest that the LSTM model outperforms the conventional machine learning methods on all metrics. Based on the tSNE graph, the success of the LSTM model is partially explained as the high-accuracy LSTM model distinguishes between positive and negative important sentiment words while those words are chosen based on SHAP values …

Cis 356 - Fundamentals Of Cybersecurity And Intelligence Gathering, Fahad Chowdhury, Nyc Tech-In-Residence Corps

Open Educational Resources

Syllabus for the course: CIS 356: "Fundamentals of Cybersecurity and Intelligence Gathering" delivered at Lehman College in Spring 2020 by Fahad Chowdhury as part of the Tech-in-Residence Corps program.

Cis 356: Fundamentals Of Cybersecurity And Intelligence Gathering - Case Study Assignment, Fahad Chowdhury, Nyc Tech-In-Residence Corps

Open Educational Resources

Assignment for the course: CIS 356: Fundamentals of Cybersecurity and Intelligence Gathering - "Case Study Assignment" delivered at Lehman College in Spring 2020 by Fahad Chowdhury as part of the Tech-in-Residence Corps program.

Cis 356: Fundamentals Of Cybersecurity And Intelligence Gathering - Confidentiality, Integrity, Availability, Fahad Chowdhury, Nyc Tech-In-Residence Corps

Open Educational Resources

Lecture for the course: CIS 356: Fundamentals of Cybersecurity and Intelligence Gathering - "Confidentiality, Integrity, Availability" (Week One) delivered at Lehman College in Spring 2020 by Fahad Chowdhury as part of the Tech-in-Residence Corps program.

Cis 356: Fundamentals Of Cybersecurity And Intelligence Gathering - Vulnerabilities And Exploits, Fahad Chowdhury, Nyc Tech-In-Residence Corps

Open Educational Resources

Lecture for the course: CIS 356: Fundamentals of Cybersecurity and Intelligence Gathering - "Vulnerabilities and Exploits" (Week Two) delivered at Lehman College in Spring 2020 by Fahad Chowdhury as part of the Tech-in-Residence Corps program.

Cis 356: Fundamentals Of Cybersecurity And Intelligence Gathering - Encryption And Hashing, Fahad Chowdhury, Nyc Tech-In-Residence Corps

Open Educational Resources

Lecture for the course: CIS 356: Fundamentals of Cybersecurity and Intelligence Gathering - "Encryption and Hashing" (Week Four) delivered at Lehman College in Spring 2020 by Fahad Chowdhury as part of the NYC Tech-in-Residence Corps program.

Cis 356-Zi81: Intermediate-Level Topics In Computer Applications (Spring 2020), Fahad Choudhury, Nyc Tech-In-Residence Corps

Open Educational Resources

Syllabus for CIS 356-ZI81: Intermediate-Level Topics in Computer Applications (Spring 2020)

Csci 380 - Digital Operations And Cybersecurity Management (Syllabus), Eric Spector, Nyc Tech-In-Residence Corps

Open Educational Resources

Syllabus for the course "CSCI 380 - Digital Operations and Cybersecurity Management" delivered at the John Jay COllege in Spring 2020 by Eric Spector as part of the Tech-in-Residence Corps program.

Cis 356: Fundamentals Of Cybersecurity And Intelligence Gathering - Hackers, Fahad Chowdhury, Nyc Tech-In-Residence Corps

Open Educational Resources

Lecture for the course: CIS 356: Fundamentals of Cybersecurity and Intelligence Gathering - "Hackers" (Week Three) delivered at Lehman College in Spring 2020 by Fahad Chowdhury as part of the NYC Tech-in-Residence Corps program.

Artificial Intelligence: A New Paradigm In Obstetrics And Gynecology Research And Clinical Practice, Pulwasha Iftikhar, Marcela V. Kuijpers, Azadeh Khayyat, Aqsa Iftikhar, Maribel Degouvia De Sa

Publications and Research

Artificial intelligence (AI) is growing exponentially in various fields, including medicine. This paper reviews the pertinent aspects of AI in obstetrics and gynecology (OB/GYN) and how these can be applied to improve patient outcomes and reduce the healthcare costs and workload for clinicians.

Herein, we will address current AI uses in OB/GYN, and the use of AI as a tool to interpret fetal heart rate (FHR) and cardiotocography (CTG) to aid in the detection of preterm labor, pregnancy complications, and review discrepancies in its interpretation between clinicians to reduce maternal and infant morbidity and mortality. AI systems can be used …

Robust Neural Machine Translation, Abdul Rafae Khan

Dissertations, Theses, and Capstone Projects

This thesis aims for general robust Neural Machine Translation (NMT) that is agnostic to the test domain. NMT has achieved high quality on benchmarks with closed datasets such as WMT and NIST but can fail when the translation input contains noise due to, for example, mismatched domains or spelling errors. The standard solution is to apply domain adaptation or data augmentation to build a domain-dependent system. However, in real life, the input noise varies in a wide range of domains and types, which is unknown in the training phase. This thesis introduces five general approaches to improve NMT accuracy and …

Safe Automated Refactoring For Intelligent Parallelization Of Java 8 Streams, Raffi Khatchadourian, Yiming Tang, Mehdi Bagherzadeh

Publications and Research

Streaming APIs are becoming more pervasive in mainstream Object-Oriented programming languages and platforms. For example, the Stream API introduced in Java 8 allows for functional-like, MapReduce-style operations in processing both finite, e.g., collections, and infinite data structures. However, using this API efficiently involves subtle considerations such as determining when it is best for stream operations to run in parallel, when running operations in parallel can be less efficient, and when it is safe to run in parallel due to possible lambda expression side-effects. ics-preserving fashion. The approach, based on a novel data ordering and typestate analysis, consists of preconditions and …

Needfinding, Devorah Kletenik

Open Educational Resources

This activity guides students through the process needfinding to identify areas of need for their creation of a technology for the "public good." Students will conduct contextual inquiry to identify the needs of their target audience.

Personas, Scenarios And Storyboards, Devorah Kletenik

Open Educational Resources

This activity guides students towards the creation of personas, scenarios and storyboards for a product/website that they are creating.

Public Interest Technology: Coding For The Public Good, Devorah Kletenik

Open Educational Resources

These slides are used to guide a discussion with students introducing them to the notion of public interest technology and coding for the public good. The lesson is intended to spark a discussion with students about different sorts of technology and their societal ramifications.

Accessibility: The Whys And The Hows, Devorah Kletenik

Open Educational Resources

This presentation introduces Computer Science students to the notion of accessibility: developing software for people with disabilities. This lesson provides a discussion of why accessibility is important (including the legal, societal and ethical benefits) as well as an overview of different types of impairments (visual, auditory, motor, neurological/cognitive) and how developers can make their software accessible to users with those disabilities. This lesson includes videos and links to readings and tutorials for students.

Coding For The Public Good: Front-End Website Design And Development, Devorah Kletenik

Open Educational Resources

This activity helps student design and develop a front-end of a website, from wireframes through HTML/CSS/Javascript. It includes design questions for students, including the invocation of Ben Schneiderman's eight golden rules for interface design.

Note: this activity assumes prior knowledge of web development. Since this activity is designed for an HCI course, with a focus on interface design, students are not expected to create a back-end for it. This activity can obviously be modified for a full-stack experience.

Accessibility Evaluation, Devorah Kletenik

Open Educational Resources

This activity guides students through the evaluation of a website that they have created to see if it is accessible for users with disabilities. Students will simulate a number of different disabilities (e.g. visual impairments, color blindness, auditory impairments, motor impairments) to see if their website is accessible; they will also use automated W3 and WAVE tools to evaluate their sites. Students will consider the needs of users with disabilities by creating a persona and scenario of a user with disabilities interacting with their site. Finally, students will write up recommendations to change their site and implement the changes.

Technological Challenges And Innovations In Cybersecurity And Networking Technology Program, Syed R. Zaidi, Ajaz Sana, Aparicio Carranza

Publications and Research

This era is posing a unique challenge to the Cybersecurity and related Engineering Technology areas, stimulated by the multifaceted technological boom expressed in accelerated globalization, digital transformation, the cloud, mobile access apps, and the Internet of Things (IoT)—where more and more devices are connected to the Internet every day. As the use of new Internet-based technologies increase; so does the risk of theft and misuse of sensitive information. This demands the awareness of cyber-criminality and the need for cyber hygiene in corporations, small businesses, and the government. As the need for experienced cybersecurity specialists has skyrocketed in recent years and …

Multimodal Data Integration For Real-Time Indoor Navigation Using A Smartphone, Yaohua Chang

Dissertations and Theses

We propose an integrated solution of indoor navigation using a smartphone, especially for assisting people with special needs, such as the blind and visually impaired (BVI) individuals. The system consists of three components: hybrid modeling, real-time navigation, and client-server architecture. In the hybrid modeling component, the hybrid model of a building is created region by region and is organized in a graph structure with nodes as destinations and landmarks, and edges as traversal paths between nodes. A Wi-Fi/cellular-data connectivity map, a beacon signal strength map, a 3D visual model (with destinations and landmarks annotated) are collected while a modeler walks …

V-Slam And Sensor Fusion For Ground Robots, Ejup Hoxha

Dissertations and Theses

In underground, underwater and indoor environments, a robot has to rely solely on its on-board sensors to sense and understand its surroundings. This is the main reason why SLAM gained the popularity it has today. In recent years, we have seen excellent improvement on accuracy of localization using cameras and combinations of different sensors, especially camera-IMU (VIO) fusion. Incorporating more sensors leads to improvement of accuracy,but also robustness of SLAM. However, while testing SLAM in our ground robots, we have seen a decrease in performance quality when using the same algorithms on flying vehicles.We have an additional sensor for ground …

The Privacy Preserving Framework With Virtual Ring And Identity-Based Cryptography For Smart Grid, Leonard Sutanto

Publications and Research

One of the main challenges in the smart grid is how to efficiently manage the high-volume data from smart meters and sensors and preserve the privacy from the consumption data to avoid potential attacks (e.g., identity theft) for the involved prosumers, retail electricity providers and other clusters of distributed energy resources. This poster proposes a two-layer framework with the cloud computing infrastructure. The virtual ring and identity-based cryptography are utilized in each layer to preserve privacy efficiently. The methods of the virtual ring and identity-based cryptography are introduced. The purposes and needs are discussed at the end of this poster.

A Note On Graphs With Prescribed Orbit Structure, Abbe Mowshowitz, Matthias Dehmer, Frank Emmert-Streib

Publications and Research

No abstract provided.

Csci49379: Intro To Blockchain (Syllabus), Wendy Mock, Nyc Tech-In-Residence Corps

Open Educational Resources

Syllabus for the course: CSCI 49397 - Blockchain. Delivered at Hunter College in Fall 2019 by Wendy Mock as part of the Tech-in-Residence Corps program.

Amazon Alexa + Linked Open Data: Theorizing Concerning Relationships Between (Surveillant) Smart-Home Voice Assistants And Linked Open Data, Michelle Nitto

Publications and Research

No abstract provided.

An Evolutionary Perspective On Foraging Strategies And Group Dynamics In Bio-Social Inspired Cognitive Radio Networks, Anna Wisniewska

Dissertations, Theses, and Capstone Projects

Saturation of wireless channels is inevitable as the number of wireless devices grows exponentially in an environment of limited radio spectrum capacity. Cognitive radio technology has been proposed to relieve overcrowded spectrum resources by allowing licensed channels to be opportunistically accessed by unlicensed users (cognitive radio devices) during periods of time when the license holder (primary user) is absent from its channel. Uncoordinated competition over limited resources among cognitive radio devices poses complex co-existence challenges. We propose novel bio-social inspired behavioral models and map out plausible evolutionary trajectories of co-use strategies in the cognitive radio ecosystem. By drawing parallels between …

Semi-Supervised Regression With Generative Adversarial Networks Using Minimal Labeled Data, Greg Olmschenk

Dissertations, Theses, and Capstone Projects

This work studies the generalization of semi-supervised generative adversarial networks (GANs) to regression tasks. A novel feature layer contrasting optimization function, in conjunction with a feature matching optimization, allows the adversarial network to learn from unannotated data and thereby reduce the number of labels required to train a predictive network. An analysis of simulated training conditions is performed to explore the capabilities and limitations of the method. In concert with the semi-supervised regression GANs, an improved label topology and upsampling technique for multi-target regression tasks are shown to reduce data requirements. Improvements are demonstrated on a wide variety of vision …

Do It Like A Syntactician: Using Binary Gramaticality Judgements To Train Sentence Encoders And Assess Their Sensitivity To Syntactic Structure, Pablo Gonzalez Martinez

Dissertations, Theses, and Capstone Projects

The binary nature of grammaticality judgments and their use to access the structure of syntax are a staple of modern linguistics. However, computational models of natural language rarely make use of grammaticality in their training or application. Furthermore, developments in modern neural NLP have produced a myriad of methods that push the baselines in many complex tasks, but those methods are typically not evaluated from a linguistic perspective. In this dissertation I use grammaticality judgements with artificially generated ungrammatical sentences to assess the performance of several neural encoders and propose them as a suitable training target to make models learn …

Deep Machine Learning Techniques For The Detection And Classification Of Sperm Whale Bioacoustics, Peter C. Bermant, Michael M. Bronstein, Robert J. Wood, Shane Gero, David F. Gruber

Publications and Research

We implemented Machine Learning (ML) techniques to advance the study of sperm whale (Physeter macrocephalus) bioacoustics. This entailed employing Convolutional Neural Networks (CNNs) to construct an echolocation click detector designed to classify spectrograms generated from sperm whale acoustic data according to the presence or absence of a click. The click detector achieved 99.5% accuracy in classifying 650 spectrograms. The successful application of CNNs to clicks reveals the potential of future studies to train CNN-based architectures to extract finer-scale details from cetacean spectrograms. Long short-term memory and gated recurrent unit recurrent neural networks were trained to perform classification tasks, including (1) …