Computer Sciences Commons^™

Data Driven Low-Bandwidth Intelligent Control Of A Jet Engine Combustor, Nathan L. Toner

Open Access Dissertations

This thesis introduces a low-bandwidth control architecture for navigating the input space of an un-modeled combustor system between desired operating conditions while avoiding regions of instability and blow-out. An experimental procedure is discussed for identifying regions of instability and gathering sufficient data to build a data-driven model of the system's operating modes. Regions of instability and blow-out are identified experimentally and a data-driven operating point classifier is designed. This classifier acts as a map of the operating space of the combustor, indicating regions in which the flame is in a "good" or "bad" operating mode. A data-driven predictor is also …

Packet Filter Performance Monitor (Anti-Ddos Algorithm For Hybrid Topologies), Ibrahim M. Waziri

Open Access Dissertations

DDoS attacks are increasingly becoming a major problem. According to Arbor Networks, the largest DDoS attack reported by a respondent in 2015 was 500 Gbps. Hacker News stated that the largest DDoS attack as of March 2016 was over 600 Gbps, and the attack targeted the entire BBC website.

With this increasing frequency and threat, and the average DDoS attack duration at about 16 hours, we know for certain that DDoS attacks will not be going away anytime soon. Commercial companies are not effectively providing mitigation techniques against these attacks, considering that major corporations face the same challenges. Current security …

Improving The Eco-System Of Passwords, Weining Yang

Open Access Dissertations

Password-based authentication is perhaps the most widely used method for user authentication. Passwords are both easy to understand and use, and easy to implement. With these advantages, password-based authentication is likely to stay as an important part of security in the foreseeable future. One major weakness of password-based authentication is that many users tend to choose weak passwords that are easy to guess. In this dissertation, we address the challenge and improve the eco-system of passwords in multiple aspects. Firstly, we provide methodologies that help password research. To be more specific, we propose Probability Threshold Graphs, which is superior to …

Learning Program Specifications From Sample Runs, He Zhu

Open Access Dissertations

With science fiction of yore being reality recently with self-driving cars, wearable computers and autonomous robots, software reliability is growing increasingly important. A critical pre-requisite to ensure the software that controls such systems is correct is the availability of precise specifications that describe a program's intended behaviors. Generating these specifications manually is a challenging, often unsuccessful, exercise; unfortunately, existing static analysis techniques often produce poor quality specifications that are ineffective in aiding program verification tasks.

In this dissertation, we present a recent line of work on automated synthesis of specifications that overcome many of the deficiencies that plague existing specification …

Protein Residue-Residue Contact Prediction Using Stacked Denoising Autoencoders, Joseph Bailey Luttrell Iv

Honors Theses

Protein residue-residue contact prediction is one of many areas of bioinformatics research that aims to assist researchers in the discovery of structural features of proteins. Predicting the existence of such structural features can provide a starting point for studying the tertiary structures of proteins. This has the potential to be useful in applications such as drug design where tertiary structure predictions may play an important role in approximating the interactions between drugs and their targets without expending the monetary resources necessary for preliminary experimentation. Here, four different methods involving deep learning, support vector machines (SVMs), and direct coupling analysis were …

An Extendable Visualization And User Interface Design For Time-Varying Multivariate Geoscience Data, Yanfu Zhou

School of Computing: Dissertations, Theses, and Student Research

Geoscience data has unique and complex data structures, and its visualization has been challenging due to a lack of effective data models and visual representations to tackle the heterogeneity of geoscience data. In today’s big data era, the needs of visualizing geoscience data become urgent, especially driven by its potential value to human societies, such as environmental disaster prediction, urban growth simulation, and so on. In this thesis, I created a novel geoscience data visualization framework and applied interface automata theory to geoscience data visualization tasks. The framework can support heterogeneous geoscience data and facilitate data operations. The interface automata …

A Study Of Norm Formation Dynamics In Online Crowds, Nargess Tahmasbi

Student Work

In extreme events such as the Egyptian 2011 uprising, online social media technology enables many people from heterogeneous backgrounds to interact in response to the crisis. This form of collectivity (an online crowd) is usually formed spontaneously with minimum constraints concerning the relationships among the members. Theories of collective behavior suggest that the patterns of behavior in a crowd are not just a set of random acts. Instead they evolve toward a normative stage. Because of the uncertainty of the situations people are more likely to search for norms.

Understanding the process of norm formation in online social media is …

Biomarkers For Radiation Pneumonitis Using Noninvasive Molecular Imaging, Meetha Medhora, Steven Haworth, Yu Liu, Jayashree Narayanan, Feng Gao, Ming Zhao, Said H. Audi, Elizabeth R. Jacobs, Brian L. Fish, Anne V. Clough

Mathematics, Statistics and Computer Science Faculty Research and Publications

Our goal is to develop minimally invasive biomarkers for predicting radiation-induced lung injury before symptoms develop. Currently, there are no biomarkers that can predict radiation pneumonitis. Radiation damage to the whole lung is a serious risk in nuclear accidents or in radiologic terrorism. Our previous studies have shown that a single dose of 15 Gy of x-rays to the thorax causes severe pneumonitis in rats by 6–8 wk. We have also developed a mitigator for radiation pneumonitis and fibrosis that can be started as late as 5 wk after radiation. Methods: We used 2 functional SPECT probes in vivo in …

Characterizations Of Pareto, Weibull And Power Function Distributions Based On Generalized Order Statistics, M. Ahsanullah, Gholamhossein Hamedani

Mathematics, Statistics and Computer Science Faculty Research and Publications

Characterizations of probability distributions by different regression conditions on generalized order statistics has attracted the attention of many researchers. We present here, characterization of Pareto and Weibull distributions based on the conditional expectation of generalized order statistics extending the characterization results reported by Jin and Lee (2014). We also present a characterization of the power function distribution based on the conditional expectation of lower generalized order statistics.

Addsmart: Address Digitization And Smart Mailbox With Rfid Technology, Jonathon Ross Tew

Theses and Dissertations

ADDSMART is a research project focused on digitizing addresses of locations and building a smart mailbox by combining wireless sensors, cameras, locks, and RFID readers and tags into a system controlled by an Arduino board. The aim of the project is to explore the idea of address digitization (using RFID tags to store addresses) and incorporate it into a mailbox that can communicate wirelessly with the homeowner to provide mail status updates and home security footage through digital photographs. This paper demonstrates the proposed ideas, describes the design of a smart mailbox, the technology that has been used, and the …

Analysis Of Artificial Neural Networks In The Diagnosing Of Breast Cancer Using Fine Needle Aspirates, Janette Vazquez

Theses and Dissertations

This thesis examines how Artificial Neural Networks can be used to classify a set of samples from a fine needle aspirate dataset. The dataset is composed of various different attributes, each of which are used to come to the conclusion as to whether a sample is benign or malignant. To automate the process of analyzing the various attributes and coming to a correct prediction, a neural network was implemented. First, a Feedforward Neural Network was trained with the dataset using a Backpropagation training method and an activation sigmoid function with one hidden layer in the architecture of the network. After …

Towards Building A Computer-Aided Accreditation System, Emmanuel Alejandro Santillana Fayett

Theses and Dissertations

Accreditation is a big subject. What is accreditation? Why should it matter to us? How many types of accreditation can an institution have? Is the government involved? What issues are present? How can we improve the accreditation process? All these questions will be covered in this paper. In addition, I will build towards a software that will apply the most important points in this paper, like applying the mission, objectives, and outcomes expected from the students in the form of a syllabus. This will help the faculty with the accreditation process and will help the students know what is expected …

Randomness, Information Encoding, And Shape Replication In Various Models Of Dna-Inspired Self-Assembly, Eric M. Martinez

Theses and Dissertations

Self-assembly is the process by which simple, unorganized components autonomously combine to form larger, more complex structures. Researchers are turning to self-assembly technology for the design of ever smaller, more complex, and precise nanoscale devices, and as an emerging fundamental tool for nanotechnology.

We introduce the robust random number generation problem, the problem of encoding a target string of bits in the form of a bit string pad, and the problem of shape replication in various models of tile-based self-assembly. Also included are preliminary results in each of these directions with discussion of possible future work directions.

Social Sentiment And Stock Trading Via Mobile Phones, Kwansoo Kim, Sang Yong Lee, Robert John Kauffman

Research Collection School Of Computing and Information Systems

What happens when uninformed investors trade stocks via mobile phones? Do they react to social sentiment differently than more informed traders in traditional trading? Based on 16,817 data observations and econometric analysis for the trading of 251 equities in Korea over 39 days, we present evidence of herding behavior among uninformed traders in the mobile channel. The results indicate that mobile traders seem more easily swayed by changing social sentiment. In addition, stock trading in the traditional channel probably influences sentiment formation in the market overall. Mobile traders follow signals in social media suggesting that they engage in less beneficial …

Accelerating Object Extraction And Detection Using A Hierarchical Approach With Shape Descriptors, Bassam Syed Arshad

Theses and Dissertations

Automatic object recognition is a fundamental problem in the fields of computer vision and machine learning, that has received a lot of research attention lately. Miniaturization and affordability, of both, high resolution digital cameras and advanced computing hardware, have further advanced the scope and applications of object recognition methods. While there are different methods, that build upon various low level features to construct object models, this work explores and implements the use of closed-contours as formidable object features. A hierarchical technique is employed to extract the contours, exploiting the inherent spatial relationships between the parent and child contours of an …

Incremental Phylogenetics By Repeated Insertions: An Evolutionary Tree Algorithm, Peter Revesz, Zhiqiang Li

School of Computing: Faculty Publications

We introduce the idea of constructing hypothetical evolutionary trees using an incremental algorithm that inserts species one-by-one into the current evolutionary tree. The method of incremental phylogenetics by repeated insertions lead to an algorithm that can be used on DNA, RNA and amino acid sequences. According to experimental results on both synthetic and biological data, the new algorithm generates more accurate evolutionary trees than the UPGMA and the Neighbor Joining algorithms.

Unsupervised Multi-Graph Cross-Modal Hashing For Large-Scale Multimedia Retrieval, Liang Xie, Lei Zhu, Guoqi Chen

Research Collection School Of Computing and Information Systems

With the advance of internet and multimedia technologies, large-scale multi-modal representation techniques such as cross-modal hashing, are increasingly demanded for multimedia retrieval. In cross-modal hashing, three essential problems should be seriously considered. The first is that effective cross-modal relationship should be learned from training data with scarce label information. The second is that appropriate weights should be assigned for different modalities to reflect their importance. The last is the scalability of training process which is usually ignored by previous methods. In this paper, we propose Multi-graph Cross-modal Hashing (MGCMH) by comprehensively considering these three points. MGCMH is unsupervised method which …

Safegpu: Contract- And Library-Based Gpgpu For Object-Oriented Languages, Alexey Kolesnichenko, Christopher M. Poskitt, Sebastian Nanz

Research Collection School Of Computing and Information Systems

Using GPUs as general-purpose processors has revolutionized parallel computing by providing, for a large and growing set of algorithms, massive data-parallelization on desktop machines. An obstacle to their widespread adoption, however, is the difficulty of programming them and the low-level control of the hardware required to achieve good performance. This paper proposes a programming approach, SafeGPU, that aims to make GPU data-parallel operations accessible through high-level libraries for object-oriented languages, while maintaining the performance benefits of lower-level code. The approach provides data-parallel operations for collections that can be chained and combined to express compound computations, with data synchronization and device …

User Identity Linkage By Latent User Space Modelling, Xin Mu, Feida Zhu, Ee-Peng Lim, Jing Xiao, Jianzong Wang, Zhi-Hua Zhou

Research Collection School Of Computing and Information Systems

User identity linkage across social platforms is an important problem of great research challenge and practical value. In real applications, the task often assumes an extra degree of difficulty by requiring linkage across multiple platforms. While pair-wise user linkage between two platforms, which has been the focus of most existing solutions, provides reasonably convincing linkage, the result depends by nature on the order of platform pairs in execution with no theoretical guarantee on its stability. In this paper, we explore a new concept of “Latent User Space” to more naturally model the relationship between the underlying real users and their …

Probabilistic Robust Route Recovery With Spatio-Temporal Dynamics, Hao Wu, Jiangyun Mao, Weiwei Sun, Baihua Zheng, Hanyuan Zhang, Ziyang Chen, Wei Wang

Research Collection School Of Computing and Information Systems

Vehicle trajectories are one of the most important data in location-based services. The quality of trajectories directly affects the services. However, in the real applications, trajectory data are not always sampled densely. In this paper, we study the problem of recovering the entire route between two distant consecutive locations in a trajectory. Most existing works solve the problem without using those informative historical data or solve it in an empirical way. We claim that a data-driven and probabilistic approach is actually more suitable as long as data sparsity can be well handled. We propose a novel route recovery system in …

A Fast Algorithm For Personalized Travel Planning Recommendation, Aldy Gunawan, Hoong Chuin Lau, Kun Lu

Research Collection School Of Computing and Information Systems

With the pervasive use of recommender systems and web/mobile applications such as TripAdvisor and Booking.com, an emerging interest is to generate personalized tourist routes based on a tourist’s preferences and time budget constraints, often in real-time. The problem is generally known as the Tourist Trip Design Problem (TTDP) which is a route-planning problem on multiple Points of Interest (POIs). TTDP can be considered as an extension of the classical problem of Team Orienteering Problem with Time Windows (TOPTW). The objective of the TOPTW is to determine a fixed number of routes that maximize the total collected score. The TOPTW also …

Enhancing Local Search With Adaptive Operator Ordering And Its Application To The Time Dependent Orienteering Problem, Aldy Gunawan, Hoong Chuin Lau, Kun Lu

Research Collection School Of Computing and Information Systems

No abstract provided.

Intermediaries Vs Peer-To-Peer: A Study Of Lenders’ Incentive On A Donation-Based Crowdfunding Platform, Ling Ge, Zhiling Guo, Xuechen Luo

Research Collection School Of Computing and Information Systems

Donation-based crowdfunding platform Kiva seems to hold the promise of peer-to-peer lending with zero interest rate to help the poor. However, it is actually intermediated by microfinance institutions, which raise funds from Kiva lenders, disburse the funds to borrowers and collect high interest. Later Kiva launched another platform Kiva Zip that implements interest-free loans directly from lenders to borrowers. This unique setup enables us to examine how lenders choose between Kiva and Kiva Zip, i.e. a platform with intermediaries and a real P2P platform. We develop a theoretical model and explicate that the lenders trade-off is between the sustainability of …

Api Recommendation System For Software Development, Ferdian Thung

Research Collection School Of Computing and Information Systems

Nowadays, software developers often utilize existing third party libraries and make use of Application Programming Interface (API) to develop a software. However, it is not always obvious which library to use or whether the chosen library will play well with other libraries in the system. Furthermore, developers need to spend some time to understand the API to the point that they can freely use the API methods and putting the right parameters inside them. In this work, I plan to automatically recommend relevant APIs to developers. This API recommendation can be divided into multiple stages. First, we can recommend relevant …

Accuracy And Precision Of Occlusal Contacts Of Stereolithographic Casts Mounted By Digital Interocclusal Registrations, Jason T. Krahenbuhl, Seok-Hwan Cho, Jon Patrick Irelan, Naveen K. Bansal

Mathematics, Statistics and Computer Science Faculty Research and Publications

Statement of problem

Little peer-reviewed information is available regarding the accuracy and precision of the occlusal contact reproduction of digitally mounted stereolithographic casts.

Purpose

The purpose of this in vitro study was to evaluate the accuracy and precision of occlusal contacts among stereolithographic casts mounted by digital occlusal registrations.

Material and methods

Four complete anatomic dentoforms were arbitrarily mounted on a semi-adjustable articulator in maximal intercuspal position and served as the 4 different simulated patients (SP). A total of 60 digital impressions and digital interocclusal registrations were made with a digital intraoral scanner to fabricate 15 sets of mounted stereolithographic …

An Algorithm For The Machine Calculation Of Minimal Paths, Robert Whitinger

Electronic Theses and Dissertations

Problems involving the minimization of functionals date back to antiquity. The mathematics of the calculus of variations has provided a framework for the analytical solution of a limited class of such problems. This paper describes a numerical approximation technique for obtaining machine solutions to minimal path problems. It is shown that this technique is applicable not only to the common case of finding geodesics on parameterized surfaces in R³, but also to the general case of finding minimal functionals on hypersurfaces in Rⁿ associated with an arbitrary metric.

Metrics Dashboard Services: A Framework For Analyzing Free/Open Source Team Repositories, Shilpika Shilpika, George K. Thiruvathukal, Nicholas Hayward, Konstantin Läufer

Computer Science: Faculty Publications and Other Works

No abstract provided.

Does A Taste Of Computing Increase Computer Science Enrollment?, Steven Mcgee, Randi Mcgee-Tekula, Jennifer Duck, Taylor White, Ronald I. Greenberg, Lucia Dettori, Dale F. Reed, Brenda Wilkerson, Don Yanek, Andrew Rasmussen, Gail Chapman

Computer Science: Faculty Publications and Other Works

This study investigated the impact of the Exploring Computer Science (ECS) program on the likelihood that students of all races and gender would pursue further computer science coursework in high school. ECS is designed to foster deep engagement through equitable inquiry around computer science concepts. If the course provides a meaningful and relevant experience, it will increase students' expectancies of success as well as increase their perceived value for the field of computer science. Using survey research, we sought to measure whether the relevance of students' course experiences influenced their expectancies and value and whether those attitudes predicted whether students …

Privacy-Aware Relevant Data Access With Semantically Enriched Search Queries For Untrusted Cloud Storage Services, Zeeshan Pervez, Mahmood Ahmad, Asad Masood Khattak, Sungyoung Lee, Tae Choong Chung

All Works

© 2016 Pervez et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Privacy-aware search of outsourced data ensures relevant data access in the untrusted domain of a public cloud service provider. Subscriber of a public cloud storage service can determine the presence or absence of a particular keyword by submitting search query in the form of a trapdoor. However, these trapdoor-based search queries are limited in functionality and cannot be used to identify …

Cufa: A More Formal Definition For Digital Forensic Artifacts, Vikram S. Harichandran, Daniel Walnycky, Ibrahim Baggili, Frank Breitinger

Electrical & Computer Engineering and Computer Science Faculty Publications

The term “artifact” currently does not have a formal definition within the domain of cyber/ digital forensics, resulting in a lack of standardized reporting, linguistic understanding between professionals, and efficiency. In this paper we propose a new definition based on a survey we conducted, literature usage, prior definitions of the word itself, and similarities with archival science. This definition includes required fields that all artifacts must have and encompasses the notion of curation. Thus, we propose using a new term e curated forensic artifact (CuFA) e to address items which have been cleared for entry into a CuFA database (one …