Other Computer Sciences Commons^™

Self-Assembly Of Tiles: Theoretical Models, The Power Of Signals, And Local Computing, Amirhossein Simjour

Electronic Thesis and Dissertation Repository

DNA-based self-assembly is an autonomous process whereby a disordered system of DNA sequences forms an organized structure or pattern as a consequence of Watson-Crick complementarity of DNA sequences, without external direction.

Here, we propose self-assembly (SA) hypergraph automata as an automata-theoretic model for patterned self-assembly. We investigate the computational power of SA-hypergraph automata and show that for every recognizable picture language, there exists an SA-hypergraph automaton that accepts this language. Conversely, we prove that for any restricted SA-hypergraph automaton, there exists a Wang Tile System, a model for recognizable picture languages, that accepts the same language.

Moreover, we investigate the …

Web Application For Graduate Course Advising System, Sanjay Karrolla

Electronic Theses, Projects, and Dissertations

The main aim of the course recommendation system is to build a course recommendation path for students to help them plan courses to successfully graduate on time. The Model-View-Controller (MVC) architecture is used to isolate the user interface (UI) design from the business logic. The front-end of the application develops the UI using AngularJS. The front-end design is done by gathering the functionality system requirements -- input controls, navigational components, informational components and containers and usability testing. The back-end of the application involves setting up the database and server-side routing. Server-side routing is done using Express JS.

Design And Implementation Of A Stand-Alone Tool For Metabolic Simulations, Milad Ghiasi Rad

Department of Computer Science and Engineering: Dissertations, Theses, and Student Research

In this thesis, we present the design and implementation of a stand-alone tool for metabolic simulations. This system is able to integrate custom-built SBML models along with external user’s input information and produces the estimation of any reactants participating in the chain of the reactions in the provided model, e.g., ATP, Glucose, Insulin, for the given duration using numerical analysis and simulations. This tool offers the food intake arguments in the calculations to consider the personalized metabolic characteristics in the simulations. The tool has also been generalized to take into consideration of temporal genomic information and be flexible for simulation …

Morphogenesis And Growth Driven By Selection Of Dynamical Properties, Yuri Cantor

Dissertations, Theses, and Capstone Projects

Organisms are understood to be complex adaptive systems that evolved to thrive in hostile environments. Though widely studied, the phenomena of organism development and growth, and their relationship to organism dynamics is not well understood. Indeed, the large number of components, their interconnectivity, and complex system interactions all obscure our ability to see, describe, and understand the functioning of biological organisms.

Here we take a synthetic and computational approach to the problem, abstracting the organism as a cellular automaton. Such systems are discrete digital models of real-world environments, making them more accessible and easier to study then their physical world …

Ancr—An Adaptive Network Coding Routing Scheme For Wsns With Different-Success-Rate Links †, Xiang Ji, Anwen Wang, Chunyu Li, Chun Ma, Yao Peng, Dajin Wang, Qingyi Hua, Feng Chen, Dingyi Fang

Department of Computer Science Faculty Scholarship and Creative Works

As the underlying infrastructure of the Internet of Things (IoT), wireless sensor networks (WSNs) have been widely used in many applications. Network coding is a technique in WSNs to combine multiple channels of data in one transmission, wherever possible, to save node’s energy as well as increase the network throughput. So far most works on network coding are based on two assumptions to determine coding opportunities: (1) All the links in the network have the same transmission success rate; (2) Each link is bidirectional, and has the same transmission success rate on both ways. However, these assumptions may not be …

Parallelization Of Molecular Docking Algorithms Using Cuda For Use In Drug Discovery, Brandon Stewart, Jonathan Fine, Gaurav Chopra Phd

The Summer Undergraduate Research Fellowship (SURF) Symposium

Traditional drug discovery methodology uses a multitude of software packages to design and evaluate new drug-like compounds. While software packages implement a wide variety of methods, the serial (i.e. single core) implementation for many of these algorithms, prohibit large scale docking, such as proteome-wide docking (i.e. thousands of compounds with thousands of proteins). Several docking algorithms can be parallelized, significantly reducing the runtime of the calculations, thus enabling large-scale docking. Implementing algorithms that take advantage of the distributed nature of graphical processing units (GPUs) via the Compute Unified Device Architecture (CUDA) enables us to efficiently implement massively parallel algorithms. Two …

A Gpu Implementation Of Distance-Driven Computed Tomography, Ryan D. Wagner

Masters Theses

Computed tomography (CT) is used to produce cross-sectional images of an object via noninvasive X-ray scanning of the object. These images have a wide range of uses including threat detection in checked baggage at airports. The projection data collected by the CT scanner must be reconstructed before the image may be viewed. In comparison to filtered backprojection methods of reconstruction, iterative reconstruction algorithms have been shown to increase overall image quality by incorporating a more complete model of the underlying physics. Unfortunately, iterative algorithms are generally too slow to meet the high throughput demands of this application. It is therefore …

An Analysis Of The Application Of Simplified Silhouette To The Evaluation Of K-Means Clustering Validity, Fei Wang, Hector-Hugo Franco-Penya, John D. Kelleher, John Pugh, Robert J. Ross

Conference papers

Silhouette is one of the most popular and effective internal measures for the evaluation of clustering validity. Simplified Silhouette is a computationally simplified version of Silhouette. However, to date Simplified Silhouette has not been systematically analysed in a specific clustering algorithm. This paper analyses the application of Simplified Silhouette to the evaluation of k-means clustering validity and compares it with the k-means Cost Function and the original Silhouette from both theoretical and empirical perspectives. The theoretical analysis shows that Simplified Silhouette has a mathematical relationship with both the k-means Cost Function and the original Silhouette, while empirically, we show that …

Educational Magic Tricks Based On Error-Detection Schemes, Ronald I. Greenberg

Computer Science: Faculty Publications and Other Works

Magic tricks based on computer science concepts help grab student attention and can motivate them to delve more deeply. Error detection ideas long used by computer scientists provide a rich basis for working magic; probably the most well known trick of this type is one included in the CS Unplugged activities. This paper shows that much more powerful variations of the trick can be performed, some in an unplugged environment and some with computer assistance. Some of the tricks also show off additional concepts in computer science and discrete mathematics.

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 …

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 …

Efficient Simulation Of A Simple Evolutionary System, Mahendra Duwal Shrestha

Masters Theses

An infinite population model is considered for diploid evolution under the influence of crossing over and mutation. The evolution equations show how Vose’s haploid model for Genetic Algorithms extends to the diploid case, thereby making feasible simulations which otherwise would require excessive resources. This is illustrated through computations confirming the convergence of finite diploid population short-term behaviour to the behaviour predicted by the infinite diploid model. The results show the distance between finite and infinite population evolutionary trajectories can decrease in practice like the reciprocal of the square root of population size.

Under necessary and sufficient conditions (NS) concerning mutation …

Data Mining By Grid Computing In The Search For Extrasolar Planets, Oisin Creaner [Thesis]

Doctoral

A system is presented here to provide improved precision in ensemble differential photometry. This is achieved by using the power of grid computing to analyse astronomical catalogues. This produces new catalogues of optimised pointings for each star, which maximise the number and quality of reference stars available. Astronomical phenomena such as exoplanet transits and small-scale structure within quasars may be observed by means of millimagnitude photometric variability on the timescale of minutes to hours. Because of atmospheric distortion, ground-based observations of these phenomena require the use of differential photometry whereby the target is compared with one or more reference stars. …

An Introduction To The Theory And Applications Of Bayesian Networks, Anant Jaitha

CMC Senior Theses

Bayesian networks are a means to study data. A Bayesian network gives structure to data by creating a graphical system to model the data. It then develops probability distributions over these variables. It explores variables in the problem space and examines the probability distributions related to those variables. It conducts statistical inference over those probability distributions to draw meaning from them. They are good means to explore a large set of data efficiently to make inferences. There are a number of real world applications that already exist and are being actively researched. This paper discusses the theory and applications of …

Network Analytics For The Mirna Regulome And Mirna-Disease Interactions, Joseph Jayakar Nalluri

Theses and Dissertations

miRNAs are non-coding RNAs of approx. 22 nucleotides in length that inhibit gene expression at the post-transcriptional level. By virtue of this gene regulation mechanism, miRNAs play a critical role in several biological processes and patho-physiological conditions, including cancers. miRNA behavior is a result of a multi-level complex interaction network involving miRNA-mRNA, TF-miRNA-gene, and miRNA-chemical interactions; hence the precise patterns through which a miRNA regulates a certain disease(s) are still elusive. Herein, I have developed an integrative genomics methods/pipeline to (i) build a miRNA regulomics and data analytics repository, (ii) create/model these interactions into networks and use optimization techniques, motif …

Special Issue: Neutrosophic Theories Applied In Engineering, Florentin Smarandache, Jun Ye

Branch Mathematics and Statistics Faculty and Staff Publications

Neutrosophic sets and logic are generalizations of fuzzy and intuitionistic fuzzy sets and logic. Neutrosophic sets and logic are gaining significant attention in solving many real life decision making problems that involve uncertainty, impreciseness, vagueness, incompleteness, inconsistent, and indeterminacy. They have been applied in computational intelligence, multiple criteria decision making, image processing, medical diagnoses, etc. This Special Issue presents original research papers that report on state-of-the-art and recent advancements in neutrosophic sets and logic in soft computing, artificial intelligence, big and small data mining, decision making problems, and practical achievements.