Computer Sciences Commons^™

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 …

A Feel For The Game: Ai, Computer Games And Perceiving Perception, Marc A. Ouellette, Steven Conway

English Faculty Publications

I walk into the room and the smell of burning wood hits me immediately. The warmth from the fireplace grows as I step nearer to it. The fire needs to heat the little cottage through the night so I add a log to the fire. There are a few sparks and embers. I throw a bigger log onto the fire and it drops with a thud. Again, there are barely any sparks or embers. The heat and the smell stay the same. They don’t change and I do not become habituated to it. Rather, they are just a steady stream, …

Infrared And Visible Image Fusion Based On Oversampled Graph Filter Banks, Chunyan Song, Xueying Gao, Yu-Long Qiao, Kaige Zhang

Computer Science Student Research

The infrared image (RI) and visible image (VI) fusion method merges complementary information from the infrared and visible imaging sensors to provide an effective way for understanding the scene. The graph filter bank-based graph wavelet transform possesses the advantages of the classic wavelet filter bank and graph representation of a signal. Therefore, we propose an RI and VI fusion method based on oversampled graph filter banks. Specifically, we consider the source images as signals on the regular graph and decompose them into the multiscale representations with M-channel oversampled graph filter banks. Then, the fusion rule for the low-frequency subband is …

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.

Incorporating A Reverse Logistics Scheme In A Vehicle Routing Problem With Cross-Docking Network: A Modelling Approach, Audrey Tedja Widjaja, Aldy Gunawan, Panca Jodiawan, Vincent F. Yu

Research Collection School Of Computing and Information Systems

Reverse logistics has been implemented by various companies because of its ability to gain more profit and maintain the competitiveness of the company. However, extensive studies on the vehicle routing problem with cross-docking (VRPCD) only considered the forward flow instead of the reverse flow. Motivated by the ability of a VRPCD network to minimize the distribution cost in the forward flow, this research incorporates the reverse logistics scheme in a VRPCD network, namely the VRP with reverse cross-docking (VRP-RCD). We propose a VRP-RCD mathematical model for a four-level supply chain network that involves suppliers, cross-dock, customers, and outlets. The main …

Text Analytics, Nlp, And Accounting Research, Richard M. Crowley

Research Collection School Of Accountancy

The presentation covered: What is text analytics and NLP?; How text analytics has evolved in the accounting literature since the 1980s; What current (as of 2020) methods are used in the literature; What methods are on the horizon.

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)

Computer Simulations Of Muscle Driven Undulatory Locomotion, Ye Luo

Dissertations

A novel muscle driven method is developed to mimic contracting and expanding of muscles, in a fish-like swimming body, which cause its body flapping in the transversal direction and create thrust force to push its body to cruise in the longitudinal direction. The muscle deformation is realized by using the RATTLE constraint algorithm. The turbulent fluids are treated by a multi-relaxation time lattice Boltzmann method with a large eddy simulation. The fish body is dealt with a lattice spring model and interactions between fluids and solid structures are handled by a direct-forcing immersed boundary method. Validations are conducted by comparing …

Explainable Deep Learning For Medical Image Analysis, Brennan Rhoadarmer

UCARE: Research Products

Explainable Deep Learning for Medical Image Analysis is a project focused on improving the ability for deep learning models to explain the reasoning behind their classification in order to improve their viability in the medical field, where explanations of decisions is critical for the care of patients. In order to explore this topic, we work to implement GradCAM, which is a new method of determining the cause classification in models by tracing back through the model layers to the input.

A New Intra-Cluster Scheduling Scheme For Real-Time Flows In Wireless Sensor Networks, Gohar Ali, Fernando Moreira, Omar Alfandi, Babar Shah, Mohammed Ilyas

All Works

© 2020 by the authors. Licensee MDPI, Basel, Switzerland. Real-time flows using time division multiple access (TDMA) scheduling in cluster-based wireless sensor networks try to schedule more flows per time frame to minimize the schedule length to meet the deadline. The problem with the previously used cluster-based scheduling algorithm is that intra-cluster scheduling does not consider that the clusters may have internal or outgoing flows. Thus, intra-cluster scheduling algorithms do not utilize their empty time-slots and thus increase schedule length. In this paper, we propose a new intra-cluster scheduling algorithm by considering that clusters may have having internal or outgoing …

Pilot Study Protocol Of A Mhealth Self‐Management Intervention For Family Members Of Pediatric Transplant Recipients, Stacee M. Lerret, Rosemary White-Traut, Barbara Medoff-Cooper, Pippa Simpson, Riddhiman Adib, Sheikh Iqbal Ahamed, Rachel Schiffman

Computer Science Faculty Research and Publications

Solid‐organ transplantation is the treatment of choice for end‐stage organ failure. Parents of pediatric transplant recipients who reported a lack of readiness for discharge had more difficulty coping and managing their child's medically complex care at home. In this paper, we describe the protocol for the pilot study of a mHealth intervention (myFAMI). The myFAMI intervention is based on the Individual and Family Self‐Management Theory and focuses on family self‐management of pediatric transplant recipients at home. The purpose of the pilot study is to test the feasibility of the myFAMI intervention with family members of pediatric transplant recipients …

Machine Learning And Data Mining-Based Methods To Estimate Parity Status And Age Of Wild Mosquito Vectors Of Infectious Diseases From Near-Infrared Spectra, Masabho Peter Milali

Dissertations (1934 -)

Previous studies show that a trained partial least square regresser [sic] (PLSR) from near-infrared spectra classify laboratory and semi-field raised mosquitoes into less than or ≥ to seven days old with an average accuracy of 80%. This dissertation demonstrates that training models on near-infrared spectra (NIRS) using artificial neural network (ANN) as an architecture yields models with higher accuracies than training models using partial least squares (PLS) as an architecture. In addition, irrespective of the model architecture used, direct training of a binary classifier scores higher accuracy than training a regresser and interpreting it as a binary classifier. Furthermore, for …

Dependable And Scalable Public Ledger For Policy Compliance, A Blockchain Based Approach, Zhou Wu

Dissertations (1934 -)

Policies and regulations, such as the European Union General Data Protection Regulation (EU GDPR), have been enforced to protect personal data from abuse during storage and processing. We design and implement a prototype scheme that could 1) provide a public ledger of policy compliance to help the public make informative decisions when choosing data services; 2) provide support to the organizations for identifying violations and improve their ability of compliance. Honest organizations could then benefit from their positive records on the public ledger. To address the scalability problem inherent in the Blockchain-based systems, we develop algorithms and leverage state channels …

Gradual Program Analysis, Samuel Estep

Senior Honors Theses

Dataflow analysis and gradual typing are both well-studied methods to gain information about computer programs in a finite amount of time. The gradual program analysis project seeks to combine those two techniques in order to gain the benefits of both. This thesis explores the background information necessary to understand gradual program analysis, and then briefly discusses the research itself, with reference to publication of work done so far. The background topics include essential aspects of programming language theory, such as syntax, semantics, and static typing; dataflow analysis concepts, such as abstract interpretation, semilattices, and fixpoint computations; and gradual typing theory, …

A Semi-Automatic Integrated Framework For Non-English Sentiment Lexicons, Abdullah Kaity Mohammed Salem

Student Works (2020-2029)

There has been significant growth in social media networks in the last few years. Posting opinions and messages on social networking websites has become a popular activity on the Internet. The data sources are necessary for business intelligence and market analytics, as human opinions form a major indicator of human desires and behaviour. This has resulted in the development of a new study field called sentiment analysis. This includes the analysis, evaluation and interpretation of the opinions with the help of text mining and Natural Language Processing (NLP) processes, for identifying the text polarity, as positive, neutral or negative. It …

Multi-Tier Classification Based On Sentiment, Type, Emotion And Purpose For Online Diabetes Community, Ratan Singh Wandeep Kaur

Student Works (2020-2029)

The evolution of social media platforms has created a niche for users to increasingly turn to such sites in order to share and exchange health related information. Facebook being one of the largest social networking sites has only encouraged such exchange thus mounting to a sheer amount of data that is hidden within unstructured text. The aim of this research is to propose a multi-tier classification based on sentiment, type, emotion and purpose (STEP) to classify data collected from diabetes community within Facebook. There are three tiers within the proposed STEP framework namely type, purpose and sentiment (and emotion within …

Raising Funds In The Era Of Digital Economy, Deserina Sulaeman

Dissertations and Theses Collection (Open Access)

The rapid advancement in technology and internet penetration have substantially increased the number of economic transactions conducted online. Platforms that connect economic agents play an important role in this digital economy. The unbridled proliferation of digital platforms calls for a closer examination of the factors that could affect the welfare of the increasing number of economic agents who participate in them.

This dissertation examines the factors that could affect the welfare of agents using the setting of a crowdfunding platform where fundraisers develop campaigns to solicit funding from potential donors. These factors can be broadly categorized into three distinct groups: …

Computer Science Without Computers: A Guide To Teaching Concepts Of Computer Science Without Access To Computers Or Other Technological Devices, Anna Nagy 20

Honor Scholar Theses

No abstract provided.

A Survey Of Feature Extraction And Fusion Of Deep Learning For Detection Of Abnormalities In Video Endoscopy Of Gastrointestinal-Tract, Hussam Ali, Muhammad Sharif, Mussarat Yasmin, Mubashir Husain Rehmani, Farhan Riaz

Publications

A standard screening procedure involves video endoscopy of the Gastrointestinal tract. It is a less invasive method which is practiced for early diagnosis of gastric diseases. Manual inspection of a large number of gastric frames is an exhaustive, time-consuming task, and requires expertise. Conversely, several computer-aided diagnosis systems have been proposed by researchers to cope with the dilemma of manual inspection of the massive volume of frames. This article gives an overview of different available alternatives for automated inspection, detection, and classification of various GI abnormalities. Also, this work elaborates techniques associated with content-based image retrieval and automated systems for …

Are These Comments Triggering? Predicting Triggers Of Toxicity In Online Discussions, Hind Almerekhi, Haewoon Kwak, Joni Salminen, Bernard J. Jansen

Research Collection School Of Computing and Information Systems

Understanding the causes or triggers of toxicity adds a new dimension to the prevention of toxic behavior in online discussions. In this research, we define toxicity triggers in online discussions as a non-toxic comment that lead to toxic replies. Then, we build a neural network-based prediction model for toxicity trigger. The prediction model incorporates text-based features and derived features from previous studies that pertain to shifts in sentiment, topic flow, and discussion context. Our findings show that triggers of toxicity contain identifiable features and that incorporating shift features with the discussion context can be detected with a ROC-AUC score of …

Statistical Modeling Of Harassment Against Reddit Moderators, Hamad Bin Khalifa University, Haewoon Kwak

Research Collection School Of Computing and Information Systems

Despite the dedication that some volunteer moderators of online communities display when performing their moderation duties, they become targets of hate and harassment by other users. To understand what causes the change in moderator role from heroes to victims, we analyze the responses of 1,818 moderators on Reddit to an online survey about moderation practices and harassment. We built a statistical model and found 6 significant independent variables that affect harassment on moderators, such as the knowledge of community norms, which increases harassment on moderators the most. Our findings imply that vulnerable moderators in toxic communities need countermeasures against harassment.

On The Robustness Of Cascade Diffusion Under Node Attacks, Alvis Logins, Yuchen Li, Panagiotis Karras

Research Collection School Of Computing and Information Systems

How can we assess a network's ability to maintain its functionality under attacks? Network robustness has been studied extensively in the case of deterministic networks. However, applications such as online information diffusion and the behavior of networked public raise a question of robustness in probabilistic networks. We propose three novel robustness measures for networks hosting a diffusion under the Independent Cascade (IC) model, susceptible to node attacks. The outcome of such a process depends on the selection of its initiators, or seeds, by the seeder, as well as on two factors outside the seeder's discretion: the attack strategy and the …

Attribute-Based Cloud Data Integrity Auditing For Secure Outsourced Storage, Yong Yu, Yannan Li, Bo Yang, Willy Susilo, Guomin Yang, Jian Bai

Research Collection School Of Computing and Information Systems

Outsourced storage such as cloud storage can significantly reduce the burden of data management of data owners. Despite of a long list of merits of cloud storage, it triggers many security risks at the same time. Data integrity, one of the most burning challenges in secure cloud storage, is a fundamental and pivotal element in outsourcing services. Outsourced data auditing protocols enable a verifier to efficiently check the integrity of the outsourced files without downloading the entire file from the cloud, which can dramatically reduce the communication overhead between the cloud server and the verifier. Existing protocols are mostly based …

Applications Of Machine Learning To Threat Intelligence, Intrusion Detection And Malware, Charity Barker

Senior Honors Theses

Artificial Intelligence (AI) and Machine Learning (ML) are emerging technologies with applications to many fields. This paper is a survey of use cases of ML for threat intelligence, intrusion detection, and malware analysis and detection. Threat intelligence, especially attack attribution, can benefit from the use of ML classification. False positives from rule-based intrusion detection systems can be reduced with the use of ML models. Malware analysis and classification can be made easier by developing ML frameworks to distill similarities between the malicious programs. Adversarial machine learning will also be discussed, because while ML can be used to solve problems or …

Sdhcare: Secured Distributed Healthcare System, Mohammed R. S. Al Baqari

Information Security Theses

In the healthcare sector, the move towards Electronic Health Records (EHR) systems has been accelerating in parallel with the increased adoption of IoT and smart devices. This is driven by the anticipated advantages for patients and healthcare providers. The integration of EHR and IoT makes it highly heterogeneous in terms of devices, network standards, platforms, types of data, connectivity, etc. Additionally, it introduces security, patient and data privacy, and trust challenges. To address such challenges, this thesis proposes an architecture that combines biometric-based blockchain technology with the EHR system. More specifically, this thesis describes a mechanism that uses a patient’s …