Computer Sciences Commons^™

Automated Color Calibration Of Display Devices, Andrew Shulman

All Computer Science and Engineering Research

If you compare two identical images on two different monitors, they will likely appear different. Every display device is supposed to adhere to a particular set of standards regulating the color and intensity of the image it outputs. However, in practice, very few do. Color calibration is the practice of modifying the signal path such that the colors produced more closely match reference standards. This is essential for graphics professionals who are mastering original content. They must ensure that the source material appears correct when viewed on a reference monitor. When viewed on a consumer panel, however, some error will …

Ewa Model With Recency Effect And Limited Memory, Hang Xie

All Computer Science and Engineering Research

Game theory is an important field in economics; it studies how people make decisions amid conflict and cooperation. Various experiments have been carried to study the way people play those games, and economists study those data for various purposes. There has been a rise of need for using artificial agents to simulate the game, since we could save the cost of hiring human subjects for the experiments, and we could gain more control over the experiment settings.

Knowledge Extraction From Survey Data Using Neural Networks, Khan Imran, Arun Kulkarni

Computer Science Faculty Publications and Presentations

Surveys are an important tool for researchers. It is increasingly important to develop powerful means for analyzing such data and to extract knowledge that could help in decision-making. Survey attributes are typically discrete data measured on a Likert scale. The process of classification becomes complex if the number of survey attributes is large. Another major issue in Likert-Scale data is the uniqueness of tuples. A large number of unique tuples may result in a large number of patterns. The main focus of this paper is to propose an efficient knowledge extraction method that can extract knowledge in terms of rules. …

The Meaning Of Music-Making For Computer Scientists With A Serious Musing-Making Avocation: A Phenomenological Case Study, Varda Shaked

Educational Studies Dissertations

This study explores the meaning of music-making in the lives of computer scientists who play classical music as their serious avocation. In particular, it investigates their tendencies and capacities to concurrently engage in two such distinct disciplines on a regular basis, by exploring the cognitive, social, and cultural aspects of their concurrent engagement. While current research literature approaches the affinities between mathematicians/scientists and musicians through the presence of mathematical properties of music and through anecdotal evidence involving known persona and their innovations, this study provides a deeper look at the individuals who combine such worlds, in order to better understand …

Core Ironclad, Peter-Michael Osera, Richard A. Eisenberg, Christian Delozier, Santosh Nagarakatte, Milo M.K. Martin, Steve Zdancewic

Computer Science Faculty Research and Scholarship

Core Ironclad is a core calculus that models the salient features of Ironclad C++, a library-augmented type-safe subset of C++. We give an overview of the language including its definition and key design points. We then prove type safety for the language and use that result to show that the pointer lifetime invariant, a key property of Ironclad C++, holds within the system.

Closed Type Families With Overlapping Equations (Extended Version), Richard A. Eisenberg, Dimitrios Vytiniotis, Simon Peyton Jones, Stephanie Weirich

Computer Science Faculty Research and Scholarship

Open, type-level functions are a recent innovation in Haskell that move Haskell towards the expressiveness of dependent types, while retaining the look and feel of a practical programming language. This paper shows how to increase expressiveness still further, by adding closed type functions whose equations may overlap, and may have non-linear patterns over an open type universe. Although practically useful and simple to implement, these features go beyond conventional dependent type theory in some respects, and have a subtle metatheory.

System Fc With Explicit Kind Equality (Extended Version), Stephanie Weirich, Justin Hsu, Richard A. Eisenberg

Computer Science Faculty Research and Scholarship

System FC, the core language of the Glasgow Haskell Compiler, is an explicitly-typed variant of System F with first-class type equality proofs called coercions. This extensible proof system forms the foundation for type system extensions such as type families (type- level functions) and Generalized Algebraic Datatypes (GADTs). Such features, in conjunction with kind polymorphism and datatype promotion, support expressive compile-time reasoning.

However, the core language lacks explicit kind equality proofs. As a result, type-level computation does not have access to kind- level functions or promoted GADTs, the type-level analogues to expression-level features that have been so useful. In this paper, …

Cultivating Intelligent Tutoring Cognizing Agents In Ill-Defined Domains Using Hybrid Approaches, Rania Hodhod

Faculty Bibliography

Cognizing agents are those systems that can perceive information from the external environment and can adapt to the changing conditions of that environment. Along the adaptation process a cognizing agent perceives information about the environment and generates reactions. An intelligent tutoring cognizing agent should deal not only with the tutoring system’s world but also with the learner-it should infer and predict new information about the learner and tailor the learning process to fit this specific learner. This paper shows how intelligent tutoring cognizing agents can be cultivated in ill-defined domains using hybrid techniques instantiated in the two example agents AEINS-CA …

Application Of Social Network Metrics To A Trust-Aware Collaborative Model For Generating Personalized User Recommendations, Iraklis Varlamis, Magdalini Eirinaki, Malamati Louta

Faculty Publications

Social network analysis has emerged as a key technique in modern sociology, but has recently gained a lot of interest in Web mining research, because of the advent and the increasing popularity of social media, such as blogs, social networks, micro-blogging, customer review sites etc. Such media often serve as platforms for information dissemination and product placement or promotion. One way to improve the quality of recommendations provided to the members of social networks is to use trustworthy resources. In this environment, community-based reputation can help estimating the trustworthiness of individual users. Consequently, influence and trust are becoming essential qualities …

Continuous Brightness Estimation (Cobe): Implementation And Its Possible Applications, G. Presti, Davide Andrea Mauro

Computer Sciences and Electrical Engineering Faculty Research

This paper presents a time-domain technique based solely on simple operations, like filtering and scaling, to continuously track a sound descriptor correlated to brightness and pitch. In opposition to existing algorithms this approach does not rely on input framing or frequencydomain transforms, ensuring a better temporal resolution and the possibility to model analog-like implementations. In the first part of the document we present the details of our approach to brightness estimation; then we will compare CoBE to the brightness estimation implemented in MIR Toolbox; we introduce and define the concept of “Equivalent Brightness Frequency” (EBF) and finally we show how …

Further Evidence Of The Contribution Of The Ear Canal To Directional Hearing: Design Of A Compensating Filter, Andrea Martelloni, Davide Andrea Mauro Phd, Antonio Mancuso

Computer Sciences and Electrical Engineering Faculty Research

It has been proven, and it is well documented in literature, that the directional response in HRTFs comes largely from the effect of the pinnae. However, few studies have analysed the contribution given by the remaining part of the external ear, particularly the ear canal. This work investigates the directionally dependent response of the modelled ear canal of a dummy head, assuming that the behaviour of the external ear is sufficiently linear to be approximated by an LTI system. In order to extract the ear canal's transfer function, two critical microphone placements (at the eardrum and at the beginning of …

Defining And Preventing Code-Injection Attacks, Donald Ray

USF Tampa Graduate Theses and Dissertations

This thesis shows that existing definitions of code-injection attacks (e.g., SQL-injection attacks) are flawed. The flaws make it possible for attackers to circumvent existing mechanisms, by supplying code-injecting inputs that are not recognized as such. The flaws also make it possible for benign inputs to be treated as attacks. After describing these flaws in conventional definitions of code-injection attacks, this thesis proposes a new definition, which is based on whether the symbols input to an application get used as (normal-form) values in the application's output. Because values are already fully evaluated, they cannot be considered ``code'' when injected. This simple …

Application Of Swarm And Reinforcement Learning Techniques To Requirements Tracing, Hakim Sultanov

Theses and Dissertations--Computer Science

Today, software has become deeply woven into the fabric of our lives. The quality of the software we depend on needs to be ensured at every phase of the Software Development Life Cycle (SDLC). An analyst uses the requirements engineering process to gather and analyze system requirements in the early stages of the SDLC. An undetected problem at the beginning of the project can carry all the way through to the deployed product.

The Requirements Traceability Matrix (RTM) serves as a tool to demonstrate how requirements are addressed by the design and implementation elements throughout the entire software development lifecycle. …

Logical Linked Data Compression, Amit Krishna Joshi, Pascal Hitzler, Guozhu Dong

Computer Science and Engineering Faculty Publications

Linked data has experienced accelerated growth in recent years. With the continuing proliferation of structured data, demand for RDF compression is becoming increasingly important. In this study, we introduce a novel lossless compression technique for RDF datasets, called Rule Based Compression (RB Compression) that compresses datasets by generating a set of new logical rules from the dataset and removing triples that can be inferred from these rules. Unlike other compression techniques, our approach not only takes advantage of syntactic verbosity and data redundancy but also utilizes semantic associations present in the RDF graph. Depending on the nature of the dataset, …

A Resolution Procedure For Description Logics With Nominal Schemas, Cong Wang, Pascal Hitzler

Computer Science and Engineering Faculty Publications

We present a polynomial resolution-based decision procedure for the recently introduced description logic ELHOV_n(⊓), which features nominal schemas as new language construct. Our algorithm is based on ordered resolution and positive superposition, together with a lifting lemma. In contrast to previous work on resolution for description logics, we have to overcome the fact that ELHOV_n(⊓) does not allow for a normalization resulting in clauses of globally limited size.

Blackops: Increasing Confidence In Variant Detection Through Mappability Filtering, Christopher R. Cabanski, Matthew D. Wilkerson, Matthew Soloway, Joel S. Parker, Jinze Liu, Jan F. Prins, J. S. Marron, Charles M. Perou, D. Neil Hayes

Computer Science Faculty Publications

Identifying variants using high-throughput sequencing data is currently a challenge because true biological variants can be indistinguishable from technical artifacts. One source of technical artifact results from incorrectly aligning experimentally observed sequences to their true genomic origin (‘mismapping’) and inferring differences in mismapped sequences to be true variants. We developed BlackOPs, an open-source tool that simulates experimental RNA-seq and DNA whole exome sequences derived from the reference genome, aligns these sequences by custom parameters, detects variants and outputs a blacklist of positions and alleles caused by mismapping. Blacklists contain thousands of artifact variants that are indistinguishable from true variants and, …

Diffsplice: The Genome-Wide Detection Of Differential Splicing Events With Rna-Seq, Yin Hu, Yan Huang, Ying Du, Christian F. Orellana, Darshan Singh, Amy R. Johnson, Anaïs Monroy, Pei-Fen Kuan, Scott M. Hammond, Liza M. Hammond, Scott H. Randell, Derek Y. Chiang, D. Neil Hayes, Corbin Jones, Yufeng Liu, Jan F. Prins, Jinze Liu

Computer Science Faculty Publications

The RNA transcriptome varies in response to cellular differentiation as well as environmental factors, and can be characterized by the diversity and abundance of transcript isoforms. Differential transcription analysis, the detection of differences between the transcriptomes of different cells, may improve understanding of cell differentiation and development and enable the identification of biomarkers that classify disease types. The availability of high-throughput short-read RNA sequencing technologies provides in-depth sampling of the transcriptome, making it possible to accurately detect the differences between transcriptomes. In this article, we present a new method for the detection and visualization of differential transcription. Our approach does …

Mexsvms: Mid-Level Features For Scalable Action Recognition, Du Tran, Lorenzo Torresani

Computer Science Technical Reports

This paper introduces MEXSVMs, a mid-level representation enabling efficient recognition of actions in videos. The entries in our descriptor are the outputs of several movement classifiers evaluated over spatial-temporal volumes of the image sequence, using space-time interest points as low-level features. Each movement classifier is a simple exemplar-SVM, i.e., an SVM trained using a single positive video and a large number of negative sequences. Our representation offers two main advantages. First, since our mid-level features are learned from individual video exemplars, they require minimal amount of supervision. Second, we show that even simple linear classification models trained on our global …

Excel Tips And Tricks Handout, Julene L. Jones

Julene L. Jones

Handout given at UK Libraries' Third Thursday: "Excel tips and tricks"

Consequence Based Procedure For Description Logics With Self Restriction, Cong Wang, Pascal Hitzler

Computer Science and Engineering Faculty Publications

We present a consequence based classification procedure for the description logics with self restriction constructor. Due to the difficulty of constructing a concept inclusion model for self restriction, we use a different proof by showing that all the completion rules can simulate all the corresponding ordered resolution inferences.