Computer Sciences Commons^™

Influence Detection And Spread Estimation In Social Networks, Madhura Kaple

Master's Projects

A social network is an online platform, where people communicate and share information with each other. Popular social network features, which make them di erent from traditional communication platforms, are: following a user, re-tweeting a post, liking and commenting on a post etc. Many companies use various social networking platforms extensively as a medium for marketing their products. A xed amount of budget is alloted by the companies to maximize the positive in uence of their product. Every social network consists of a set of users (people) with connections between them. Each user has the potential to extend its in …

Comparing Authentic And Cryptic 5’ Splice Sites Using Hidden Markov Models And Decision Trees, Pratikshya Mishra

Master's Projects

Splicing is the editing of the precursor mRNA produced during transcription. The mRNA contains a large number of nucleotides in the introns and exons which are spliced to remove the introns and bind the exons to produce the mature mRNA which is translated to generate proteins. Hence accurate splicing at 5’ and 3’ splice sites (authentic splice sites (AuthSS)) is of foremost importance. The 5’ and 3’ splice sites are characterized by consensus sequences. Eukaryotic genome also contains splice sites known as Cryptic Splice Sites (CSS) that match the consensus. But the CSS are activated only when there is a …

Application Of Computational Methods To Study The Selection Of Authentic And Cryptic Splice Sites, Tapomay Dey

Master's Projects

Proteins are building blocks of the bodies of eukaryotes, and the process of synthesizing proteins from DNA is crucial for the good health of an organism [13]. However, some mutations in the DNA may disrupt the selection of 5’ or 3’ splice sites by a spliceosome. An important research question is whether the disruptions have a stochastic relation to the position of nucleotides in the vicinity of the known authentic and cryptic splice sites. This can be achieved by proving that the authentic and cryptic splice sites are intrinsically different. However, the behavior of the spliceosome is not accurately known. …

Scoring Scene Symmetry, Morteza Rezanejad, John D. Wilder, Sven Dickinson, Allan Jepson, Dirk B. Walther, Kaleem Siddiqi

MODVIS Workshop

No abstract provided.

Case Study: A New Method For Investigating Crimes Against Children, Hallstein Asheim Hansen, Stig Andersen, Stefan Axelsson, Svein Hopland

Annual ADFSL Conference on Digital Forensics, Security and Law

Investigations of crimes against children are often complex, both in terms of the varied and large amount of digital technology encountered and the offensive nature of the crimes. Such cases are numerous, large, and prioritised, requiring digital forensics competence. Earlier digital forensics was considered and treated as a typical forensic science like fingerprint analysis, performed in a laboratory isolated from the investigative team. This decoupled way of working has proved to be both inefficient and error prone.

At the Digital Forensic Unit of Oslo Police District we have developed a new way of working that addresses many of the problems …

Development Of A Professional Code Of Ethics In Digital Forensics, Kathryn C. Seigfried-Spellar, Marcus Rogers, Danielle M. Crimmins 2184089

Annual ADFSL Conference on Digital Forensics, Security and Law

Academics, government officials, and practitioners suggest the field of digital forensics is in need of a professional code of ethics. In response to this need, the authors developed and proposed a professional code of ethics in digital forensics. The current paper will discuss the process of developing the professional code of ethics, which included four sets of revisions based on feedback and suggestions provided by members of the digital forensic community. The final version of the Professional Code of Ethics in Digital Forensics includes eight statements, and we hope this is a step toward unifying the field of digital forensics …

Defining A Cyber Jurisprudence, Peter R. Stephenson Phd

Annual ADFSL Conference on Digital Forensics, Security and Law

Jurisprudence is the science and philosophy or theory of the law. Cyber law is a very new concept and has had, compared with other, older, branches of the law, little structured study. However, we have entered the cyber age and the law - on all fronts - is struggling to keep pace with technological advances in cyberspace. This research explores a possible theory and philosophy of cyber law, and, indeed, whether it is feasible to develop and interpret a body of law that addresses current and emerging challenges in cyber space.

While there is an expanding discussion of the nature …

An Accidental Discovery Of Iot Botnets And A Method For Investigating Them With A Custom Lua Dissector, Max Gannon, Gary Warner, Arsh Arora

Annual ADFSL Conference on Digital Forensics, Security and Law

This paper presents a case study that occurred while observing peer-to-peer network communications on a botnet monitoring station and shares how tools were developed to discover what ultimately was identified as Mirai and many related IoT DDOS Botnets. The paper explains how researchers developed a customized protocol dissector in Wireshark using the Lua coding language, and how this enabled them to quickly identify new DDOS variants over a five month period of study.

Kelihos Botnet: A Never-Ending Saga, Arsh Arora, Max Gannon, Gary Warner

Annual ADFSL Conference on Digital Forensics, Security and Law

This paper investigates the recent behavior of the Kelihos botnet, a spam-sending botnet that accounts for many millions of emails sent each day. The paper demonstrates how a team of students are able to perform a longitudinal malware study, making significant observations and contributions to the understanding of a major botnet using tools and techniques taught in the classroom. From this perspective the paper has two objectives: encouragement and observation. First, by providing insight into the methodology and tools used by student researchers to document and understand a botnet, the paper strives to embolden other academic programs to follow a …

Unsupervised Machine Learning In Agent-Based Modeling, Luke D. Robinson

Celebration of Learning

Agent-based models (ABMs) are used by researchers in a variety of fields to model natural phenomena. In an ABM, a wide range of behaviors and outcomes can be observed based on the parameters of the model. In many cases, these behaviors can be categorized into discrete outcomes identifiable by human observers. Our goal was to use clustering algorithms to identify those outcomes from model output data. For this project, we used data from the NetLogo Wolf Sheep Predation model to explore and evaluate three clustering algorithms from Python's scikit-learn package. If this task can be completed reliably by a computer, …

Investigating Trust And Trust Recovery In Human-Robot Interactions, Abigail L. Thomson

Celebration of Learning

As artificial intelligence and robotics continue to advance and be used in increasingly different functions and situations, it is important to look at how these new technologies will be used. An important factor in how a new resource will be used is how much it is trusted. This experiment was conducted to examine people’s trust in a robotic assistant when completing a task, how mistakes affect this trust, and if the levels of trust exhibited with a robot assistant were significantly different than if the assistant were human. The task was to watch a computer simulation of the three-cup monte …

Optimized Forecasting Of Dominant U.S. Stock Market Equities Using Univariate And Multivariate Time Series Analysis Methods, Michael Schwartz

Computational and Data Sciences Theses

This dissertation documents an investigation into forecasting U.S. stock market equities via two very different time series analysis techniques: 1) autoregressive integrated moving average (ARIMA), and 2) singular spectrum analysis (SSA). Approximately 40% of the S&P 500 stocks are analyzed. Forecasts are generated for one and five days ahead using daily closing prices. Univariate and multivariate structures are applied and results are compared. One objective is to explore the hypothesis that a multivariate model produces superior performance over a univariate configuration. Another objective is to compare the forecasting performance of ARIMA to SSA, as SSA is a relatively recent development …

Simulating Foodborne Pathogens In Poultry Production And Processing To Defend Against Intentional Contamination, Silas B. Lankford

Computer Science and Computer Engineering Undergraduate Honors Theses

There is a lack of data in recent history of food terrorism attacks, and as such, it is difficult to predict its impact. The food supply industry is one of the most vulnerable industries for terrorist threats while the poultry industry is one of the largest food industries in the United States. A small food terrorism attack against just a single poultry processing center has the potential to affect a much larger population than its immediate consumers. In this work, the spread of foodborne pathogens is simulated in a poultry production and processing system to defend against intentional contamination. An …

Hybridguard: A Principal-Based Permission And Fine-Grained Policy Enforcement Framework For Web-Based Mobile Applications, Phu Huu Phung, Abhinav Mohanty, Rahul Rachapalli, Meera Sridhar

Computer Science Faculty Publications

Web-based or hybrid mobile applications (apps) are widely used and supported by various modern hybrid app development frameworks. In this architecture, any JavaScript code, local or remote, can access available APIs, including JavaScript bridges provided by the hybrid framework, to access device resources. This JavaScript inclusion capability is dangerous, since there is no mechanism to determine the origin of the code to control access, and any JavaScript code running in the mobile app can access the device resources through the exposed APIs. Previous solutions are either limited to a particular platform (e.g., Android) or a specific hybrid framework (e.g., Cordova) …

Image Segmentation Using De-Textured Images, Yaswanth Kodavali

All Graduate Plan B and other Reports, Spring 1920 to Spring 2023

Image segmentation is one of the fundamental problems in computer vision. The outputs of segmentation are used to extract regions of interest and carry out identification or classification tasks. For these tasks to be reliable, segmentation has to be made more reliable. Although there are exceptionally well-built algorithms available today, they perform poorly in many instances by producing over-merged (combining many unrelated objects) or under-merged (one object appeared as many) results. This leads to far fewer or more segments than expected. Such problems primarily arise due to varying textures within a single object and/or common textures near borders of adjacent …

Relation Algebras, Idempotent Semirings And Generalized Bunched Implication Algebras, Peter Jipsen

Mathematics, Physics, and Computer Science Faculty Articles and Research

This paper investigates connections between algebraic structures that are common in theoretical computer science and algebraic logic. Idempotent semirings are the basis of Kleene algebras, relation algebras, residuated lattices and bunched implication algebras. Extending a result of Chajda and Länger, we show that involutive residuated lattices are determined by a pair of dually isomorphic idempotent semirings on the same set, and this result also applies to relation algebras. Generalized bunched implication algebras (GBI-algebras for short) are residuated lattices expanded with a Heyting implication. We construct bounded cyclic involutive GBI-algebras from so-called weakening relations, and prove that the class of weakening …

The Chess Puzzle Lock Screen, Ryan J. Hayes

Student Scholar Showcase

The Chess Puzzle Lock Screen

Many times each day, owners of cellphones use their phone’s lock screen in order to access their device. The goal of this project has been to take advantage of the action of unlocking one’s device by incorporating an element of self-help into the process. Every time a user who is interested in learning a new field attempts to access their device, that user is faced with a problem pertaining to a subject they are interested in learning more about. After many repetitions of this scenario, the user will have increased their understanding of this field. …

Toward An Iot-Based Expert System For Heart Disease Diagnosis, Do Thanh Thai, Quang Tran Minh, Phu Huu Phung

Computer Science Faculty Publications

IoT technology has been recently adopted in the healthcare system to collect Electrocardiogram (ECG) signals for heart disease diagnosis and prediction. However, noises in collected ECG signals make the diagnosis and prediction system unreliable and imprecise. In this work, we have proposed a new lightweight approach to removing noises in collected ECG signals to perform precise diagnosis and prediction. First, we have used a revised Sequential Recursive (SR) algorithm to transform the signals into digital format. Then, the digital data is proceeded using a revised Discrete Wavelet Transform (DWT) algorithm to detect peaks in the data to remove noises. Finally, …

Multi-Plc Exercise Environments For Training Ics First Responders, Joseph K. Daoud

Theses and Dissertations

When systems are targeted by cyber attacks, cyber first responders must be able to react effectively, especially when dealing with critical infrastructure. Training for cyber first responders is lacking and most existing exercise platforms are expensive, inaccessible or ineffective. This paper presents a mobile training platform which incorporates a variety of programmable logic controllers into a single system which facilitates the development of the unique skills required of cyber first responders operating in the realm of industrial control systems. The platform is modeled after a jail in the northeastern United States and was developed to maximize realism. Example training scenarios …

Iota Pi Application For Ios, Deborah Newberry

Computer Science and Software Engineering

Kappa Kappa Psi is a national honorary fraternity for college band members. They meet every Sunday night, and during these meetings they plan events (both internal and external) that aim to meet our goal of making sure that the Cal Poly band programs have their social, financial, material, and educational needs satisfied. This paper details the steps I took to create an application for them to use internally to help ease organizational processes.

Gpumap: A Transparently Gpu-Accelerated Map Function, Ivan Pachev

Master's Theses

As GPGPU computing becomes more popular, it will be used to tackle a wider range of problems. However, due to the current state of GPGPU programming, programmers are typically required to be familiar with the architecture of the GPU in order to effectively program it. Fortunately, there are software packages that attempt to simplify GPGPU programming in higher-level languages such as Java and Python. However, these software packages do not attempt to abstract the GPU-acceleration process completely. Instead, they require programmers to be somewhat familiar with the traditional GPGPU programming model which involves some understanding of GPU threads and kernels. …

Mixed-Initiative Personal Assistants, Joshua W. Buck, Saverio Perugini

Computer Science Faculty Publications

Specification and implementation of flexible human-computer dialogs is challenging because of the complexity involved in rendering the dialog responsive to a vast number of varied paths through which users might desire to complete the dialog. To address this problem, we developed a toolkit for modeling and implementing task-based, mixed-initiative dialogs based on metaphors from lambda calculus. Our toolkit can automatically operationalize a dialog that involves multiple prompts and/or sub-dialogs, given a high-level dialog specification of it. Our current research entails incorporating the use of natural language to make the flexibility in communicating user utterances commensurate with that in dialog completion …

Tandem 2.0: Image And Text Data Generation Application, Christopher J. Vitale

Dissertations, Theses, and Capstone Projects

First created as part of the Digital Humanities Praxis course in the spring of 2012 at the CUNY Graduate Center, Tandem explores the generation of datasets comprised of text and image data by leveraging Optical Character Recognition (OCR), Natural Language Processing (NLP) and Computer Vision (CV). This project builds upon that earlier work in a new programming framework. While other developers and digital humanities scholars have created similar tools specifically geared toward NLP (e.g. Voyant-Tools), as well as algorithms for image processing and feature extraction on the CV side, Tandem explores the process of developing a more robust and user-friendly …

The Proscriptive Principle And Logics Of Analytic Implication, Thomas M. Ferguson

Dissertations, Theses, and Capstone Projects

The analogy between inference and mereological containment goes at least back to Aristotle, whose discussion in the Prior Analytics motivates the validity of the syllogism by way of talk of parts and wholes. On this picture, the application of syllogistic is merely the analysis of concepts, a term that presupposes—through the root ἀνά + λύω —a mereological background.

In the 1930s, such considerations led William T. Parry to attempt to codify this notion of logical containment in his system of analytic implication AI. Parry’s original system AI was later expanded to the system PAI. The hallmark of Parry’s systems—and of …

Static Human Detection And Scenario Recognition Via Wearable Thermal Sensing System, Qingquan Sun, Ju Shen, Haiyan Qiao, Xinlin Huang, Chen Chen, Fei Hu

Computer Science Faculty Publications

Conventional wearable sensors are mainly used to detect the physiological and activity information of individuals who wear them, but fail to perceive the information of the surrounding environment. This paper presents a wearable thermal sensing system to detect and perceive the information of surrounding human subjects. The proposed system is developed based on a pyroelectric infrared sensor. Such a sensor system aims to provide surrounding information to blind people and people with weak visual capability to help them adapt to the environment and avoid collision. In order to achieve this goal, a low-cost, low-data-throughput binary sampling and analyzing scheme is …

Computational Analysis Of Residue Interaction Networks And Coevolutionary Relationships In The Hsp70 Chaperones: A Community- Hopping Model Of Allosteric Regulation And Communication, Gabrielle Stetz, Gennady M. Verkhivker

Mathematics, Physics, and Computer Science Faculty Articles and Research

Allosteric interactions in the Hsp70 proteins are linked with their regulatory mechanisms and cellular functions. Despite significant progress in structural and functional characterization of the Hsp70 proteins fundamental questions concerning modularity of the allosteric interaction networks and hierarchy of signaling pathways in the Hsp70 chaperones remained largely unexplored and poorly understood. In this work, we proposed an integrated computational strategy that combined atomistic and coarse-grained simulations with coevolutionary analysis and network modeling of the residue interactions. A novel aspect of this work is the incorporation of dynamic residue correlations and coevolutionary residue dependencies in the construction of allosteric interaction networks …

Visualizing Incongruity: Visual Data Mining Strategies For Modeling Humor In Text, Andrew Smigaj

All Graduate Projects

The goal of this project is to investigate the use of visual data mining to model verbal humor. We explored various means of text visualization to identify key featrues of garden path jokes as compared with non jokes. With garden path jokes one interpretation is established in the setup but new information indicating some alternative interpretation triggers some resolution process leading to a new interpretation. For this project we visualize text in three novel ways, assisted by some web mining to build an informal ontology, that allow us to see the differences between garden path jokes and non jokes of …

On Barrier Graphs Of Sensor Networks, Kirk Anthony Boyer

Electronic Theses and Dissertations

The study of sensor networks begins with a model, which usually has a geometric component. This thesis focuses on networks of sensors modeled as collections of rays in the plane whose use is to detect intruders, and in particular a graph derived from this geometry, called the barrier graph of the network, which captures information about the network's coverage. Every such ray-barrier sensor network corresponds to a barrier graph, but not every graph is the barrier graph of some network.

We show that any barrier graph is not just tripartite, but perfect. We describe how to find networks which have …

Parsing Metamap Files In Hadoop, Amy Olex, Alberto Cano, Bridget T. Mcinnes

Computer Science Publications

The UMLS::Association CUICollector module identifies UMLS Concept Unique Identifier bigrams and their frequencies in a biomedical text corpus. CUICollector was re-implemented in Hadoop MapReduce to improve algorithm speed, flexibility, and scalability. Evaluation of the Hadoop implementation compared to the serial module produced equivalent results and achieved a 28x speedup on a single-node Hadoop system.

Using Consumer Accessible Mobile Devices To Collect Vehicle Emissions Compliance Data, Joshua N. Jensen

Regis University Student Publications (comprehensive collection)

The emissions inspection procedure has been largely stagnate for the last 20 years. Vehicle owners in the United States spend approximately 1.7 billion dollars annually for a technician to perform the simple task of plugging an emissions inspection computer into their car’s computer. Smart Emissions was developed as an Android application to provide a new procedure for emissions inspection utilizing consumer-accessible mobile devices and an ELM327 Bluetooth adapter. With Smart Emissions, vehicle owners utilize the Android devices they already own to connect to a Bluetooth adapter inserted into the diagnostic link connector port of their vehicle. The adapter communicates with …