Computer Sciences Commons^™

Inflammatory Bowel Disease Diagnosis Using Metagenomic Classification, Michael Riggle

Masters Theses & Specialist Projects

Inflammatory bowel disease (IBD) is a set of disorders that involve chronic inflammation of digestive tracts, e.g., Crohn's disease (CD) and ulcerative colitis (UC). Millions of people around the world have inflammatory bowel disease. However, it is still difficult to treat IBD due to its unknown cause. In fact, accurately diagnosing inflammatory bowel disease (IBD) can be very challenging too since some of IBD symptoms can mimic those of other conditions. In this work, we apply classification methods to help improve the success rate of diagnosis. We study four formulations of IBD classification: i) IBD and non-IBD (binary classification), ii) …

Finding Critical And Gradient-Flat Points Of Deep Neural Network Loss Functions, Charles Gearhart Frye '09

Doctoral Dissertations

Despite the fact that the loss functions of deep neural networks are highly non-convex, gradient-based optimization algorithms converge to approximately the same performance from many random initial points. This makes neural networks easy to train, which, combined with their high representational capacity and implicit and explicit regularization strategies, leads to machine-learned algorithms of high quality with reasonable computational cost in a wide variety of domains.

One thread of work has focused on explaining this phenomenon by numerically characterizing the local curvature at critical points of the loss function, where gradients are zero. Such studies have reported that the loss functions …

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 …

Searchbreaches.Me, Ajay Shah, Harshal Patel, Eric Gargiulo

Petersheim Academic Exposition

No abstract provided.

Autism Searches: A Modern Search Engine For Asd Related Topics, Joshua Schappel, Jonathan Simone Bar-Eli, Sachin Mahashabde, Jeremy Suero

Petersheim Academic Exposition

No abstract provided.

Data Science Meets Compliance, Christian Clarke

Petersheim Academic Exposition

No abstract provided.

Equations For Which Newton's Method Never Works: Pedagogical Examples, Leobardo Valera, Martine Ceberio, Olga Kosheleva, Vladik Kreinovich

Departmental Technical Reports (CS)

One of the most widely used methods for solving equations is the classical Newton's method. While this method often works -- and is used in computers for computations ranging from square root to division -- sometimes, this method does not work. Usual textbook examples describe situations when Newton's method works for some initial values but not for others. A natural question that students often ask is whether there exist functions for which Newton's method never works -- unless, of course, the initial approximation is already the desired solution. In this paper, we provide simple examples of such functions.

Why Class-D Audio Amplifiers Work Well: A Theoretical Explanation, Kevin Alvarez, Julio Urenda, Vladik Kreinovich

Departmental Technical Reports (CS)

Most current high-quality electronic audio systems use class-D audio amplifiers (D-amps, for short), in which a signal is represented by a sequence of pulses of fixed height, pulses whose duration at any given moment of time linearly depends on the amplitude of the input signal at this moment of time. In this paper, we explain the efficiency of this signal representation by showing that this representation is the least vulnerable to additive noise (that affect measuring the signal itself) and to measurement errors corresponding to measuring time.

How To Explain The Anchoring Formula In Behavioral Economics, Laxman Bokati, Vladik Kreinovich, Chon Van Le

Departmental Technical Reports (CS)

According to the traditional economics, the price that a person is willing to pay for an item should be uniquely determined by the value that this person will get from this item, it should not depend, e.g., on the asking price proposed by the seller. In reality, the price that a person is willing to pay does depend on the asking price; this is known as the anchoring effect. In this paper, we provide a natural justification for the empirical formula that describes this effect.

A "Fuzzy" Like Button Can Decrease Echo Chamber Effect, Olga Kosheleva, Vladik Kreinovich

Departmental Technical Reports (CS)

One of the big problems of the US political life is the echo chamber effect -- in spite of the abundance of materials on the web, many people only read materials confirming their own opinions. The resulting polarization often deadlocks the political situation and prevents politicians from reaching compromises needed to make needed changes. In this paper, we show, on a simplified model, that the echo chamber effect can be decreased if we simply replace the currently prevalent binary (yes-no) Like button on webpages with a more gradual ("fuzzy") one -- a button that will capture the relative degree of …

Devops: Lecture 1 - "Overview", Jeremy Andrews, Nyc Tech-In-Residence Corps

Open Educational Resources

Overview lecture for the "DevOps" course delivered at the City College of New York in Spring 2020 by Jeremy Andrews as part of the Tech-in-Residence Corps program.

Topics In Artifical Intelligence, Hunter Mcnichols, Nyc Tech-In-Residence Corps

Open Educational Resources

Syllabus for the course "CSC 59974: Special Topics in Artificial Intelligence" delivered at the City College of New York in Spring 2020 by Hunter McNichols as part of the Tech-in-Residence Corps program.

Weighted Random Search For Cnn Hyperparameter Optimization, Rǎzvan Andonie, Adrian-Cǎtǎlin Florea

All Faculty Scholarship for the College of the Sciences

Nearly all model algorithms used in machine learning use two different sets of parameters: the training parameters and the meta-parameters (hyperparameters). While the training parameters are learned during the training phase, the values of the hyperparameters have to be specified before learning starts. For a given dataset, we would like to find the optimal combination of hyperparameter values, in a reasonable amount of time. This is a challenging task because of its computational complexity. In previous work, we introduced the Weighted Random Search (WRS) method, a combination of Random Search (RS) and probabilistic greedy heuristic. In the current paper, we …

Digital Forensic Readiness: An Examination Of Law Enforcement Agencies In The State Of Maryland, James B. Mcnicholas Iii

Masters Theses & Doctoral Dissertations

Digital forensic readiness within the law enforcement community, especially at the local level, has gone mostly unexplored. As a result, a current lack of data exists that examines the digital forensic readiness of individual agencies, the possibility of proximity relationships, and correlations between readiness and backlogs. This quantitative, crosssectional research study sought to explore these issues by focusing on the state of Maryland. The study resulted in the creation of a digital forensic readiness scoring model that was then used to assign digital forensic readiness scores to thirty (30) of the one-hundred-forty-one (141) law enforcement agencies throughout Maryland. It was …

Byod-Insure: A Security Assessment Model For Enterprise Byod, Melva Ratchford

Masters Theses & Doctoral Dissertations

As organizations continue allowing employees to use their personal mobile devices to access the organizations’ networks and the corporate data, a phenomenon called ‘Bring Your Own Device’ or BYOD, proper security controls need to be adopted not only to secure the corporate data but also to protect the organizations against possible litigation problems. Until recently, current literature and research have been focused on specific areas or solutions regarding BYOD. The information associated with BYOD security issues in the areas of Management, IT, Users and Mobile Device Solutions is fragmented. This research is based on a need to provide a holistic …

E-Archive, Florian Hyseni

Theses and Dissertations

Pasi që jemi konsultuar me prof.Ramiz Hoxha dhe prof.Murat Retkoceri kemi vënë re që një sistem i cili do të kryente menaxhimin e të gjithë dokumentave në menyrë të automatizuar dhe digjitalizuar nuk ekziston në rajonin tonë. Sistem i cili do të përshpetoj të gjitha punët të cilët kanë të bëjnë me dokumenta fizike, dhe kemi vendosur që ta marim përsipër këtë sistem si projekt zhvillues për temë diplome un Festim Shabani dhe Florian Hyseni në mbikqyrje të prof.Ramiz Hoxha dhe prof.Murat Retkoceri. Si kërkesa bazike të sistemit tonë janë ruajtja dhe kërkimi i dokumenteve në menyrë të automatizuar dhe …

Analiza E Migrimit Të Data Warehouse Nga Ibm Datastage Në Odi 11g, Leutrim Sylkaj

Theses and Dissertations

Migrimi i të dhënave është procesi i zgjedhjes, përgatitjes, nxjerrjes, transformimit të të dhënave dhe transferimit të përhershëm të tyre nga një sistem/aplikacion kompjuterik në të cilin janë të ruajtura të dhënat në një sistem/aplikacion tjetër kompjuterik.

Në kompanitë e mëdha në ditët e sotme luan rol të rëndësishëm performanca dhe kualiteti i të dhënave gjatë procesit ETL(Ekstraktimit, Transformimit dhe Transferimit) të të dhënave në Data Warehouse.Pas hulumtimeve kemi arritur në përfundim që problem për disa nga kompanitë e mëdha të cilat si aplikacion bazë për transferimin e të dhënave nga burimet e ndryshme të të dhënave në Data Warehouse …

Iot Security With Blockchain Solution, Arber Murati

Theses and Dissertations

IoT është një teknologji me një potencial, impakt dhe rritje të jashtzakonshme. Sot, prodhimi momental i të dhënave nga paisjet teknologjike llogaritet të jetë rreth 2.5 quintillion bytes gjdo ditë. Për të pasur një kuptim më figurativ, 2.5 quntillion cent në monedha do të mbulonin sipërfaqën e globit për rreth 5 herë nëse token do ta përcaktonim si të sheshtë. Sipas hulumtimeve të fundit, deri në vitin 2025 diku rreth 41.6-miliard paisje IoT do të jenë online si dhe 30 % e të gjitha të dhënave do të duhen të procesohen në real-time. Hakerët shpesh fitojnë qasje në pajisje fundore …

Analiza Dhe Performanca E Rrjetit Kompjuterik Në Komunën E Lipjanit, Daut Azemi

Theses and Dissertations

Ne jetojmë në një botë të zhvillimit të hovshëm të teknologjisë, një botë në të cilën njerëzit janë të rrethuar nga pajisjet teknologjike, të cilat mund t’i hasim në çdo ambient kudo që ndodhemi, si për shembull: shtëpi, shkolla, lokale apo edhe nëpër ndërmarrje dhe biznese të ndryshme.

Sot “teknologjia po na magjeps”, ne kërkojmë që ajo të sjellë ndryshime në jetën tonë dhe sidomos në arsim, në ditët e sodit nuk ka shkollë, që nuk ka internet e në të cilën nuk ka nevojë për Rrjeta Kompjuterike brenda shkollës. Sot në Komunat e Kosovës kanë filluar të përdoren disa …

An Examination Of The Work Practices Of Crowdfarms, Yihong Wang, Konstantinos Papangelis, Michael Saker, Ioanna Lykourentzou, Vassilis-Javed Khan, Alan Chamberlain, Jonathan Grudin

Presentations and other scholarship

Crowdsourcing is a new value creation business model. Annual revenue of the Chinese market alone is hundreds of millions of dollars, yet few studies have focused on the practices of the Chinese crowdsourcing workforce, and those that do mainly focus on solo crowdworkers. We have extended our study of solo crowdworker practices to include crowdfarms, a relatively new entry to the gig economy: small companies that carry out crowdwork as a key part of their business. We report here on interviews of people who work in53 crowdfarms. We describe how crowdfarms procure jobs, carry out macrotasks and microtasks, manage their …

The Influence Of Peer And Parental Norms On First-Generation College Students’ Binge Drinking Trajectories, Graham T. Diguiseppi, Jordan P. Davis, Matthew K. Meisel, Melissa A. Clark, Mya L. Roberson, Miles Q. Ott, Nancy P. Barnett

Statistical and Data Sciences: Faculty Publications

Introduction: First-generation college students are those whose parents have not completed a four-year college degree. The current study addressed the lack of research on first-generation college students’ alcohol use by comparing the binge drinking trajectories of first-generation and continuing-generation students over their first three semesters. The dynamic influence of peer and parental social norms on students’ binge drinking frequencies were also examined. Methods: 1342 college students (n = 225 first-generation) at one private University completed online surveys. Group differences were examined at Time 1, and latent growth-curve models tested the association between first-generation status and social norms (peer descriptive, peer …

Devops: Architecting Your Infrastructure (Syllabus), Jeremy Andrews, Nyc Tech-In-Residence Corps

Open Educational Resources

Syllabus for the "DevOps" course delivered at the City College of New York in Spring 2020 by Jeremy Andrews as part of the Tech-in-Residence Corps program.

Cs 485 Computer Architecture, Danyang Zhang

Open Educational Resources

This course will present the basic concepts and technologies in computer organization and architecture. For example, logical devices and digital circuits, data representation, register transfer, central processor organization, microprogram control and organization, parallel computing. Although there could be multiple perspectives in studying computer architecture, our focus would be to better understand computer organization in order to design more efficient and reliable application software. The OER (Open Educational Resources) session of this course will have no textbook required (ZTC: Zero Textbook Cost), conduct lectures based on online resources and other open educational resources, and have students involved in active learning including …

Two Can Play That Game: An Adversarial Evaluation Of A Cyber-Alert Inspection System, Ankit Shah, Arunesh Sinha, Rajesh Ganesan, Sushil Jajodia, Hasan Cam

Research Collection School Of Computing and Information Systems

Cyber-security is an important societal concern. Cyber-attacks have increased in numbers as well as in the extent of damage caused in every attack. Large organizations operate a Cyber Security Operation Center (CSOC), which forms the first line of cyber-defense. The inspection of cyber-alerts is a critical part of CSOC operations (defender or blue team). Recent work proposed a reinforcement learning (RL) based approach for the defender’s decision-making to prevent the cyber-alert queue length from growing large and overwhelming the defender. In this article, we perform a red team (adversarial) evaluation of this approach. With the recent attacks on learning-based decision-making …

Techniques To Visualize Occluded Graph Elements For 2.5d Map Editing, Kazuyuki Fujita, Daigo Hayashi, Kotaro Hara, Kazuki Takashima, Yoshifumi Kitamura

Research Collection School Of Computing and Information Systems

We propose an interface with two novel techniques to visualize occluded graph nodes and edges that help the user edit map data with a 2.5D geographical structure (e.g., multi-floor indoor maps). We first design a visualization technique —Repel Signification— that employs micro-animation to signify the graph elements that are overlapping with each other (and potentially erroneous). We also design a technique that enables the user to edit the occluded components with Expansion Interaction, which simultaneously visualizes both in-floor and across-floor occluded connections between the map elements. The combination of the two methods would enable the map editors (non-experts) to effectively …

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 …

Cybersecurity (Cs 3550): Lecture 11: Identity & Access Management, Michael Whiteman, Nyc Tech-In-Residence Corps

Open Educational Resources

Lecture for the course: CIS 3550: Cybersecurity - "11: Identity & Access Management" delivered at Baruch College in Spring 2020 by Michael Whiteman as part of the Tech-in-Residence Corps program.

Cis 4400 Data Warehousing - Lecture 2, Royce Kok, B Madhusudan, Nyc Tech-In-Residence Corps

Open Educational Resources

Lecture 2 for CIS 4400: Data Warehousing (Spring 2020)

Deep Cellular Recurrent Neural Architecture For Efficient Multidimensional Time-Series Data Processing, Lasitha S. Vidyaratne

Electrical & Computer Engineering Theses & Dissertations

Efficient processing of time series data is a fundamental yet challenging problem in pattern recognition. Though recent developments in machine learning and deep learning have enabled remarkable improvements in processing large scale datasets in many application domains, most are designed and regulated to handle inputs that are static in time. Many real-world data, such as in biomedical, surveillance and security, financial, manufacturing and engineering applications, are rarely static in time, and demand models able to recognize patterns in both space and time. Current machine learning (ML) and deep learning (DL) models adapted for time series processing tend to grow in …

Account Recovery Methods For Two-Factor Authentication (2fa): An Exploratory Study, Lauren Nicole Tiller

Psychology Theses & Dissertations

System administrators have started to adopt two-factor authentication (2FA) to increase user account resistance to cyber-attacks. Systems with 2FA require users to verify their identity using a password and a second-factor authentication device to gain account access. This research found that 60% of users only enroll one second-factor device to their account. If a user’s second factor becomes unavailable, systems are using different procedures to ensure its authorized owner recovers the account. Account recovery is essentially a bypass of the system’s main security protocols and needs to be handled as an alternative authentication process (Loveless, 2018). The current research aimed …