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Articles 3151 - 3180 of 4524
Full-Text Articles in Computer Sciences
An Anns Based Failure Detection Method For Onos Sdon Controller, Shideh Yavary Mehr
An Anns Based Failure Detection Method For Onos Sdon Controller, Shideh Yavary Mehr
School of Computing: Dissertations, Theses, and Student Research
Network reachability is an important factor of an optical telecommunication network. In a wavelength-division-muliplexing (WDM) optical network, any failure can cause a large amount of loss and disruptions in network. Failures can occur in network elements, link, and component inside a node or etc. Since major network disruptions can caused network performance degradations, it is necessary that operators have solutions to prevent such those failures. This work examines a prediction model in optical networks and propose a protection plan using a Machine Learning (ML) algorithm called Artificial Neural Networks (ANN) using Mininet emulator. ANN is one of the best method …
Csc 511: Special Topics In Advanced Web Development (Syllabus), Shane Afsar, Nyc Tech-In-Residence Corps
Csc 511: Special Topics In Advanced Web Development (Syllabus), Shane Afsar, Nyc Tech-In-Residence Corps
Open Educational Resources
Syllabus for the course: CSC 511: "Advanced Web Development" delivered at the College of Staten Island in Fall 2019 by Shane Afsar as part of the Tech-in-Residence Corps program.
Cyber Security In The Healthcare Industry, Giovanni Ordonez 20
Cyber Security In The Healthcare Industry, Giovanni Ordonez 20
Honor Scholar Theses
No abstract provided.
Text Anomaly Detection With Arae-Anogan, Tec Yan Yap
Text Anomaly Detection With Arae-Anogan, Tec Yan Yap
Honors Projects
Generative adversarial networks (GANs) are now one of the key techniques for detecting anomalies in images, yielding remarkable results. Applying similar methods to discrete structures, such as text sequences, is still largely an unknown. In this work, we introduce a new GAN-based text anomaly detection method, called ARAE-AnoGAN, that trains an adversarially regularized autoencoder (ARAE) to reconstruct normal sentences and detects anomalies via a combined anomaly score based on the building blocks of ARAE. Finally, we present experimental results demonstrating the effectiveness of ARAE-AnoGAN and other deep learning methods in text anomaly detection.
Csci 49378: Lecture 5: Distributed Web-Based Applications, Bonan Liu, Nyc Tech-In-Residence Corps
Csci 49378: Lecture 5: Distributed Web-Based Applications, Bonan Liu, Nyc Tech-In-Residence Corps
Open Educational Resources
Lecture for the course: CSCI 49378: Intro to Distributed Systems and Cloud Computing - "Distributed Web-based Applications" (Week five) delivered at Hunter College in Spring 2020 by Bonan Liu as part of the Tech-in-Residence Corps program.
Csci 49378: Lecture 11: Logging, Monitoring, And Advanced Topics, Bonan Liu, Nyc Tech-In-Residence Corps
Csci 49378: Lecture 11: Logging, Monitoring, And Advanced Topics, Bonan Liu, Nyc Tech-In-Residence Corps
Open Educational Resources
Lecture for the course: CSCI 49378: Intro to Distributed Systems and Cloud Computing - "Logging, Monitoring, and Advanced Topics" (Week Eleven) delivered at Hunter College in Spring 2020 by Bonan Liu as part of the Tech-in-Residence Corps program.
Csci 49378: Lecture 7: Cloud Systems And Infrastructures I, Bonan Liu, Nyc Tech-In-Residence Corps
Csci 49378: Lecture 7: Cloud Systems And Infrastructures I, Bonan Liu, Nyc Tech-In-Residence Corps
Open Educational Resources
Lecture for the course: CSCI 49378: Intro to Distributed Systems and Cloud Computing - "Cloud Systems and Infrastructures I" (Week Seven) delivered at Hunter College in Spring 2020 by Bonan Liu as part of the Tech-in-Residence Corps program.
Csci 49378: Lecture 2: Distributed Systems - Key Concepts & Techniques, Bonan Liu, Nyc Tech-In-Residence Corps
Csci 49378: Lecture 2: Distributed Systems - Key Concepts & Techniques, Bonan Liu, Nyc Tech-In-Residence Corps
Open Educational Resources
Lecture for the course: CSCI 49378: Intro to Distributed Systems and Cloud Computing - "Distributed Systems - Key Concepts & Techniques" (Week Two) delivered at Hunter College in Spring 2020 by Bonan Liu as part of the Tech-in-Residence Corps program.
Csci 49378: Lecture 1: Overview, Bonan Liu, Nyc Tech-In-Residence Corps
Csci 49378: Lecture 1: Overview, Bonan Liu, Nyc Tech-In-Residence Corps
Open Educational Resources
Lecture for the course: CSCI 49378: Intro to Distributed Systems and Cloud Computing - "Overview" (Week One) delivered at Hunter College in Spring 2020 by Bonan Liu as part of the Tech-in-Residence Corps program.
Csci 49378: Lecture 3: Synchronization, Consistency And Replication, Bonan Liu, Nyc Tech-In-Residence Corps
Csci 49378: Lecture 3: Synchronization, Consistency And Replication, Bonan Liu, Nyc Tech-In-Residence Corps
Open Educational Resources
Lecture for the course: CSCI 49378: Intro to Distributed Systems and Cloud Computing - "Synchronization, Consistency and Replication" (Week Three) delivered at Hunter College in Spring 2020 by Bonan Liu as part of the Tech-in-Residence Corps program.
Csci 49378: Lecture 9: Cloud Storage And Databases I, Bonan Liu, Nyc Tech-In-Residence Corps
Csci 49378: Lecture 9: Cloud Storage And Databases I, Bonan Liu, Nyc Tech-In-Residence Corps
Open Educational Resources
Lecture for the course: CSCI 49378: Intro to Distributed Systems and Cloud Computing - "Cloud Storage and Databases I" (Week Nine) delivered at Hunter College in Spring 2020 by Bonan Liu as part of the Tech-in-Residence Corps program.
Csci 49378: Lecture 4: Distributed File Systems, Bonan Liu, Nyc Tech-In-Residence Corps
Csci 49378: Lecture 4: Distributed File Systems, Bonan Liu, Nyc Tech-In-Residence Corps
Open Educational Resources
Lecture for the course: CSCI 49378: Intro to Distributed Systems and Cloud Computing - "Distributed File Systems" (Week Four) delivered at Hunter College in Spring 2020 by Bonan Liu as part of the Tech-in-Residence Corps program.
Csci 49378: Lecture 6: Cloud Computing Concepts, Bonan Liu, Nyc Tech-In-Residence Corps
Csci 49378: Lecture 6: Cloud Computing Concepts, Bonan Liu, Nyc Tech-In-Residence Corps
Open Educational Resources
Lecture for the course: CSCI 49378: Intro to Distributed Systems and Cloud Computing - "Cloud Computing Concepts" (Week Six) delivered at Hunter College in Spring 2020 by Bonan Liu as part of the Tech-in-Residence Corps program.
Cybersecurity (Cs 3550): Lecture 1: Introduction & State Of Cybersecurity, Michael Whiteman, Nyc Tech-In-Residence Corps
Cybersecurity (Cs 3550): Lecture 1: Introduction & State Of Cybersecurity, Michael Whiteman, Nyc Tech-In-Residence Corps
Open Educational Resources
Lecture for the course: CIS 3550: Cybersecurity - "1: Introduction & State of Cybersecurity" delivered at Baruch College in Spring 2020 by Michael Whiteman as part of the Tech-in-Residence Corps program.
Cybersecurity (Cs 3550): Lecture 2: Cybersecurity Fundamentals, Michael Whiteman, Nyc Tech-In-Residence Corps
Cybersecurity (Cs 3550): Lecture 2: Cybersecurity Fundamentals, Michael Whiteman, Nyc Tech-In-Residence Corps
Open Educational Resources
Lecture for the course: CIS 3550: Cybersecurity - "2: Cybersecurity Fundamentals" delivered at Baruch College in Spring 2020 by Michael Whiteman as part of the Tech-in-Residence Corps program.
Cybersecurity (Cs 3550): Lecture 5: Intro To Web Applications I, Michael Whiteman, Nyc Tech-In-Residence Corps
Cybersecurity (Cs 3550): Lecture 5: Intro To Web Applications I, Michael Whiteman, Nyc Tech-In-Residence Corps
Open Educational Resources
Lecture for the course: CIS 3550: Cybersecurity - "5: Intro to Web Applications I" delivered at Baruch College in Spring 2020 by Michael Whiteman as part of the Tech-in-Residence Corps program.
Cis 4400 Data Warehousing: Lecture 1 - "Overview", Royce Kok, B Madhusudan, Nyc Tech-In-Residence Corps
Cis 4400 Data Warehousing: Lecture 1 - "Overview", Royce Kok, B Madhusudan, Nyc Tech-In-Residence Corps
Open Educational Resources
Lecture #1 for the course: CIS 4400: Data Warehousing for Analytics - "Overview" delivered at Baruch College in Spring 2020 by Royce Kok and B. Madhusudan as part of the NYC Tech-in-Residence Corps program.
Cybersecurity (Cs 3550): Lecture 9-10: Data Protection & Cryptography, Michael Whiteman, Nyc Tech-In-Residence Corps
Cybersecurity (Cs 3550): Lecture 9-10: Data Protection & Cryptography, Michael Whiteman, Nyc Tech-In-Residence Corps
Open Educational Resources
Lecture for the course: CIS 3550: Cybersecurity - "9-10: Data Protection & Cryptography" delivered at Baruch College in Spring 2020 by Michael Whiteman as part of the Tech-in-Residence Corps program.
Cybersecurity (Cs 3550): Lecture 15: Application Security, Michael Whiteman, Nyc Tech-In-Residence Corps
Cybersecurity (Cs 3550): Lecture 15: Application Security, Michael Whiteman, Nyc Tech-In-Residence Corps
Open Educational Resources
Lecture for the course: CIS 3550: Cybersecurity - "15: Application Security" delivered at Baruch College in Spring 2020 by Michael Whiteman as part of the Tech-in-Residence Corps program.
Cybersecurity (Cs 3550): Lecture 14: Business Continuity & Disaster Recovery, Michael Whiteman, Nyc Tech-In-Residence Corps
Cybersecurity (Cs 3550): Lecture 14: Business Continuity & Disaster Recovery, Michael Whiteman, Nyc Tech-In-Residence Corps
Open Educational Resources
Lecture for the course: CIS 3550: Cybersecurity - "14: Business Continuity & Disaster Recovery" delivered at Baruch College in Spring 2020 by Michael Whiteman as part of the Tech-in-Residence Corps program.
Cybersecurity (Cs 3550): Lecture 12: Network & Endpoint Security, Michael Whiteman, Nyc Tech-In-Residence Corps
Cybersecurity (Cs 3550): Lecture 12: Network & Endpoint Security, Michael Whiteman, Nyc Tech-In-Residence Corps
Open Educational Resources
Lecture for the course: CIS 3550: Cybersecurity - "12: Network & Endpoint Security" delivered at Baruch College in Spring 2020 by Michael Whiteman as part of the Tech-in-Residence Corps program.
Cybersecurity (Cs 3550): Lecture 7-8: Risk Management, Michael Whiteman, Nyc Tech-In-Residence Corps
Cybersecurity (Cs 3550): Lecture 7-8: Risk Management, Michael Whiteman, Nyc Tech-In-Residence Corps
Open Educational Resources
Lecture for the course: CIS 3550: Cybersecurity - "7-8: Risk Management" delivered at Baruch College in Spring 2020 by Michael Whiteman as part of the Tech-in-Residence Corps program.
Cybersecurity (Cs 3550): Lecture 3-4: Networking Fundamentals, Michael Whiteman, Nyc Tech-In-Residence Corps
Cybersecurity (Cs 3550): Lecture 3-4: Networking Fundamentals, Michael Whiteman, Nyc Tech-In-Residence Corps
Open Educational Resources
Lecture for the course: CIS 3550: Cybersecurity - "3-4: Networking Fundamentals" delivered at Baruch College in Spring 2020 by Michael Whiteman as part of the Tech-in-Residence Corps program.
Cybersecurity (Cs 3550): Lecture 21: Hacking Democracy: Election Security, Michael Whiteman, Nyc Tech-In-Residence Corps
Cybersecurity (Cs 3550): Lecture 21: Hacking Democracy: Election Security, Michael Whiteman, Nyc Tech-In-Residence Corps
Open Educational Resources
Lecture for the course: CIS 3550: Cybersecurity - "21: Hacking Democracy: Election Security" delivered at Baruch College in Spring 2020 by Michael Whiteman as part of the Tech-in-Residence Corps program.
Cybersecurity (Cs 3550): Lecture 18-19: Anatomy Of A Breach, Michael Whiteman, Nyc Tech-In-Residence Corps
Cybersecurity (Cs 3550): Lecture 18-19: Anatomy Of A Breach, Michael Whiteman, Nyc Tech-In-Residence Corps
Open Educational Resources
Lecture for the course: CIS 3550: Cybersecurity - "18-19: Anatomy of a Breach" delivered at Baruch College in Spring 2020 by Michael Whiteman as part of the Tech-in-Residence Corps program.
Cybersecurity (Cs 3550): Lecture 13: Patching & Vulnerability Management, Michael Whiteman, Nyc Tech-In-Residence Corps
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.
Using Alteryx Designer In Audit, Nolan Asiala
Using Alteryx Designer In Audit, Nolan Asiala
Honors Projects
My senior project was built around data analysis and how it relates to the auditing profession. Initially, I was planning on attending a data analytics competition, but that was canceled due to the events of COVID-19. This project utilized the Alteryx Designer program to demonstrate how it can be used during an audit engagement. By creating a workflow in Alteryx Designer, a report from a client can be cleaned and reformatted into a working dataset. My project includes two Excel files, a Microsoft Word document that serves as a brief introduction to the program, and a video describing the workflow …
Does Applying Deep Learning In Financial Sentiment Analysis Lead To Better Classification Performance?, Tao Wang, Changhe Yuan, Cuiyuan Wang
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 …
Developing Agent-Based Models To Study Financial Markets, Saurav Chakraborty
Developing Agent-Based Models To Study Financial Markets, Saurav Chakraborty
USF Tampa Graduate Theses and Dissertations
This dissertation presents research that employs agent-based modelling to provide a framework to support simulation as a complement to traditional economic models for policy evaluation. It consists of three studies. The first study employs cluster analysis to capture the different types of banks and the associated business models that define their decision-making. The results from study one will help us get an understanding of how different banks behave and provide an insight into their lending practices. Hence, it would be very helpful in evaluating and analyzing the impact of future policies. Study two develops a fine-grained interbank lending model based …
Multi-Label Model For Toxicity Prediction, Xiu Huan Yap, Michael L. Raymer
Multi-Label Model For Toxicity Prediction, Xiu Huan Yap, Michael L. Raymer
Celebration of Undergraduate & Graduate Research, Scholarship, and Creative Activities Materials
Most computational predictive models are specifically trained for a single toxicity endpoint. Since more than 1300 toxicity assays have been reported in the TOXCAST dashboard, achieving high coverage over this growing number of toxicity endpoints remains challenging. Furthermore, single-endpoint models lack the ability to learn dependencies between endpoints, such as those targeting similar biological pathways, which may be used to boost model performance. In this study, we characterize the performance of 3 multi-label classification (MLC) models, namely Classifier Chains (CC), Label Powersets (LP) and Stacking (SBR), on Tox21 challenge data. These MLC models employ the Problem Transformation approach, which is …