Computer Sciences Commons^™

Using Forecasting To Predict Long-Term Resource Utilization For Web Services, Daniel Wayne Yoas

CCAC Theses and Dissertations

Researchers have spent years understanding resource utilization to improve scheduling, load balancing, and system management through short-term prediction of resource utilization. Early research focused primarily on single operating systems; later, interest shifted to distributed systems and, finally, into web services. In each case researchers sought to more effectively use available resources. Since schedulers are required to manage the execution of multiple programs every second, short-term prediction has focused on time frames ranging from fractions of a second to several minutes.

The recent increase in the number of research studies about web services has occurred because of the explosive growth and …

Employee Determinants To Share Knowledge In A Us Federal Government Environment, Kenneth White

CCAC Theses and Dissertations

Although the literature indicates that knowledge sharing (KS) research is prevalent in the private sector, there is scant empirical research data about KS in the public sector. Moreover, organizations lack an understanding of employee KS behavior. This study investigated two research questions: First, how does the perceived importance of five determinants of KS behavior (organizational culture, workplace trust, incentives, management support, and technology) vary based upon the variables of job function, gender, and work category? Second, what is the relative importance of the five determinants of KS behavior to U.S. federal government employees? This descriptive study employed a Web-based survey …

The Role Of Faculty In The Effectiveness Of Fully Online Programs, Sami Al Salman

CCAC Theses and Dissertations

The enormous growth of online learning creates the need to develop a set of standards and guidelines for fully online programs. While many guidelines do exist, web-based programs still fall short in the recognition, adoption, or the implementation of these standards. One consequence is the high attrition rates associated with web-based distance learning programs. This poor outcome has a negative impact on the perceived quality of these programs which in turn limits the resources that are made available to academic institutions for implementation. Faculty plays a significant role in this dilemma. While academic administrators strive to enhance their online offerings …

Developing Software Requirements For A Knowledge Management System That Coordinates Training Programs With Business Processes And Policies In Large Organizations, James Richard Kiper

CCAC Theses and Dissertations

For large organizations, updating instructional programs presents a challenge to keep abreast of constantly changing business processes and policies. Each time a process or policy changes, significant resources are required to locate and modify the training materials that convey the new content. Moreover, without the ability to track learning objects to processes and policies, training managers cannot conduct an effective training gap analysis in these areas. As a result, the corporate training picture is unclear and instructional needs cannot be accurately determined.

The research addressed these problems by recognizing the need for linkages between an organization's business processes, its policies, …

Optimized Features Selection For Gender Classification Using Optimization Algorithms, Sajid Ali Khan, Muhammad Nazir, Naveed Riaz

Turkish Journal of Electrical Engineering and Computer Sciences

Optimized feature selection is an important task in gender classification. The optimized features not only reduce the dimensions, but also reduce the error rate. In this paper, we have proposed a technique for the extraction of facial features using both appearance-based and geometric-based feature extraction methods. The extracted features are then optimized using particle swarm optimization (PSO) and the bee algorithm. The geometric-based features are optimized by PSO with ensemble classifier optimization by the genetic algorithm. Using this approach, we have obtained promising results in terms of the classification error rate and computation time minimization. Moreover, our optimized feature-based method …

Extracting Fuzzy Rules For The Diagnosis Of Breast Cancer, Ali̇ Keleş, Aytürk Keleş

Turkish Journal of Electrical Engineering and Computer Sciences

About one million women are diagnosed with breast cancer every year. Breast cancer makes up one-third of all cancer diagnoses in women. Diagnosing breast cancer early is vital for successful treatment. Among the breast cancer screening methods available today, mammography is the most effective, although the low precision rate of breast biopsy caused by mammogram interpretation results in approximately 70% unnecessary biopsies with benign outcomes. The aim of this study was to extract strong diagnostic fuzzy rules for the inference engine of an expert system to be used for the diagnosis of breast cancer. These rules have been extracted through …

Multireference Tdoa-Based Source Localization, Hamid Torbati Fard, Mahmoud Atashbar, Yaser Norouzi, Farrokh Hojjat Kashani

Turkish Journal of Electrical Engineering and Computer Sciences

Time difference of arrival (TDOA)-based methods usually achieve the most accurate source localization in passive systems. In these methods, one of the sensors is assigned as the reference and the TDOA of the others with respect to the reference is measured. The source location is estimated by processing these TDOAs. In this paper, a multireference maximum likelihood (ML)-Taylor algorithm is proposed in order to decrease the source localization error of the TDOA methods. In the proposed algorithm, TDOAs are measured assuming 2 different reference sensors, and then the ML objective function of this multireference TDOA algorithm is derived and solved …

Prism And Privacy: Will This Change Everything?, Fred H. Cate, Christopher Kuner, Christopher Millard, Dan Jerker B. Svantesson

Articles by Maurer Faculty

No abstract provided.

On The Difference In Quality Between Current Heuristic And Optimal Solutions To The Protein Structure Alignment Problem, Mauricio Arriagada, Aleksandar Poleksic

Faculty Work

The importance of pairwise protein structural comparison in biomedical research is fueling the search for algorithms capable of finding more accurate structural match of two input proteins in a timely manner. In recent years, we have witnessed rapid advances in the development of methods for approximate and optimal solutions to the protein structure matching problem. Albeit slow, these methods can be extremely useful in assessing the accuracy of more efficient, heuristic algorithms. We utilize a recently developed approximation algorithm for protein structure matching to demonstrate that a deep search of the protein superposition space leads to increased alignment accuracy with …

An Examination Of The Acceptance, Adoption, And Diffusion Of Smartphone Devices With Senior Citizens., James M. Reneau

CCAC Theses and Dissertations

This research looked at the process of the diffusion of an innovation in the context of smartphones with American senior citizens. The subject of diffusion, or spread of a technology, is a rich and varied topic with more than 60 years of research. Much of this diffusion research does not go beyond the study of the original acceptance of a new idea. An on-line and face-to-face questionnaire was used to collect data from 155 seniors on the entire process of diffusion. The questionnaire was adaptive in nature, focusing questions directly at participants based on where they were in the diffusion …

Reducing Cognitive Load Using Adaptive Uncertainty Visualization, Gregory Block

CCAC Theses and Dissertations

Uncertainty is inherent in many real-world settings; for example, in a combat situation, darkness may prevent a soldier from classifying approaching troops as friendly or hostile. In an environment plagued with uncertainty, decision-support systems, such as sensor-based networks, may make faulty assumptions about field conditions, especially when information is incomplete, or sensor operations are disrupted. Displaying the factors that contribute to uncertainty informs the decision-making process for a human operator, but at the expense of limited cognitive resources, such as attention, memory, and workload.

This research applied principles of perceptual cognition to human-computer interface design to introduce uncertainty visualizations in …

An Examination Of Internet Filtering And Safety Policy Trends And Issues In South Carolina's K-12 Public Schools, Mary E. Vicks

CCAC Theses and Dissertations

School districts have implemented filtering and safety policies in response to legislative and social mandates to protect students from the proliferation of objectionable online content. Subject related literature suggests these policies are more restrictive than legal mandates require and are adversely affecting information access and instruction. There is limited understanding of how filtering and safety policies are affecting teaching and learning because no comprehensive studies have investigated the issues and trends surrounding filtering and safety policy implementation. In order to improve existing safety policies, policymakers need research-based data identifying end user access issues that limit technology integration in the kindergarten-12th …

Lexis In Chemical Engineering Discourse: Analyzing Style In Chemical Engineering Research Articles Through A Rhetorical Lens, David Lamar Young

Masters Theses

"This study examines the style of chemical engineering research articles to discover stylistic trends that may be applicable to authors looking to publish their own research. Rhetorical stylistic analysis was used as a research method to allow for thorough analysis of all articles in the sample. Ten research articles from the two prominent chemical engineering journals were chosen using specific criteria to constitute a sample of articles that could most accurately represent the population of chemical engineering research articles. Each article was then analyzed line by line to identify markers of chemical engineering research article style, including the following: ▬Use …

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 …

Automatic Macro- And Micro-Facial Expression Spotting And Applications, Matthew Adam Shreve

USF Tampa Graduate Theses and Dissertations

Automatically determining the temporal characteristics of facial expressions has extensive application domains such as human-machine interfaces for emotion recognition, face identification, as well as medical analysis. However, many papers in the literature have not addressed the step of determining when such expressions occur. This dissertation is focused on the problem of automatically segmenting macro- and micro-expressions frames (or retrieving the expression intervals) in video sequences, without the need for training a model on a specific subset of such expressions. The proposed method exploits the non-rigid facial motion that occurs during facial expressions by modeling the strain observed during the elastic …

Consumer Acceptance Of Mobile Payments In Restaurants, Anna Shatskikh

USF Tampa Graduate Theses and Dissertations

Regardless all the advantages of MPs, it has not reach the sizable customer base. In this paper, we examined the core drivers of using mobile payments (MPs) in restaurant industry from the consumers' perspective. Based on the Technology Acceptance Model (TAM), we developed a six factor model to reveal the determinants of consumers' intention to use MPs in restaurant. Security, subjective norm, compatibility with lifestyle, and previous experience with MPs were added to the traditional two factor TAM model (usefulness and ease of use). 300 respondents were recruited from an online survey agency and 258 valid responses were included in …

An Application Developed For Simulation Of Electrical Excitation And Conduction In A 3d Human Heart, Di Yu

USF Tampa Graduate Theses and Dissertations

This thesis first reviews the history of General Purpose computing Graphic Processing Unit (GPGPU) and then introduces the fundamental problems that are suitable for GPGPU algorithm. The architecture of GPGPU is compared against modern CPU architecture, and the fundamental difference is outlined. The programming challenges faced by GPGPU and the techniques utilized to overcome these issues are evaluated and discussed.

The second part of the thesis presents an application developed with GPGPU technology to simulate the electrical excitation and conduction in a 3D human heart model based on cellular automata model. The algorithm and implementation are discussed in detail and …

Energy Efficient Context-Aware Framework In Mobile Sensing, Ozgur Yurur

USF Tampa Graduate Theses and Dissertations

The ever-increasing technological advances in embedded systems engineering, together with the proliferation of small-size sensor design and deployment, have enabled mobile devices (e.g., smartphones) to recognize daily occurring human based actions, activities and interactions. Therefore, inferring a vast variety of mobile device user based activities from a very diverse context obtained by a series of sensory observations has drawn much interest in the research area of ubiquitous sensing. The existence and awareness of the context provides the capability of being conscious of physical environments or situations around mobile device users, and this allows network services to respond proactively and intelligently …

Robotic Swarming Without Inter-Agent Communication, Daniel Jonathan Standish

USF Tampa Graduate Theses and Dissertations

Many physical and algorithmic swarms utilize inter-agent communication to achieve advanced swarming behaviors. These swarms are inspired by biological swarms that can be seen throughout nature and include bee swarms, ant colonies, fish schools, and bird flocks. These biological swarms do not utilize inter-agent communication like their physical and algorithmic counterparts. Instead, organisms in nature rely on a local awareness of other swarm members that facilitates proper swarm motion and behavior. This research aims to pursue an effective swarm algorithm using only line-of-sight proximity information and no inter-agent communication. It is expected that the swarm performance will be lower than …

Packet Coalescing And Server Substitution For Energy-Proportional Operation Of Network Links And Data Servers, Mehrgan Mostowfi

USF Tampa Graduate Theses and Dissertations

Electricity generation for Information and Communications Technology (ICT) contributes over 2% of the human-generated CO2 to the atmosphere. Energy costs are rapidly becoming the major operational expense for ICT and may soon dwarf capital expenses as software and hardware continue to drop in price. In this dissertation, three new approaches to achieving energy-proportional operation of network links and data servers are explored.

Ethernet is the dominant wireline communications technology for Internet connectivity. IEEE 802.3az Energy Efficient Ethernet (EEE) describes a Low Power Idle (LPI) mechanism for allowing Ethernet links to sleep. A method of coalescing packets to consolidate link idle …

Automatic Identification Of Points Of Interest In Global Navigation Satellite System Data: A Spatial Temporal Approach, Khoa Anh Tran

USF Tampa Graduate Theses and Dissertations

In addition to the emergence of smartphones and tablets in recent years, the rise of Global Navigation Satellite Systems (GNSS) has allowed mobile tracking applications to become popular and be put into many uses. Analyzing tracking records to identify points of interest (POIs) is useful for both prediction applications and research such as human behavior analysis, transportation planning, and especially travel surveys. Past research in travel surveys has shown that a GPS mobile phone-based survey is a useful tool for collecting information about individuals. Moreover, a passive travel survey collection is preferred to an active travel survey method by the …

Delta Encoding Based Methods To Reduce The Size Of Smartphone Application Updates, Nikolai Samteladze

USF Tampa Graduate Theses and Dissertations

In 2012 the two biggest smartphone application markets - the Google Play store and the Apple App Store - each had close to 700 thousand applications with approximately 2 billion downloads happening every month. The introduction of new features and correction of bugs and security vulnerabilities make it usual for mobile application developers to release new version of an application every month. Combined with the great smartphone popularity, it leads to approximately 400 PB annual traffic generated by app updates in the U.S. wireless networks alone. Being partially transmitted through cellular networks, mobile application updates traffic accounts to up to …

Fpca Based Human-Like Trajectory Generating, Wei Dai

USF Tampa Graduate Theses and Dissertations

This thesis presents a new human-like upper limb and hand motion generating method. The work is based on Functional Principal Component Analysis and Quadratic Programming. The human-like motion generating problem is formulated in a framework of minimizing the difference of the dynamic profile of the optimal trajectory and the known types of trajectory. Statistical analysis is applied to the pre-captured human motion records to work in a low dimensional space. A novel PCA FPCA hybrid motion recognition method is proposed. This method is implemented on human grasping data to demonstrate its advantage in human motion recognition. One human grasping hierarchy …

Real-Time Map Manipulation For Mobile Robot Navigation, Carlos Favis Ezequiel

USF Tampa Graduate Theses and Dissertations

Mobile robots are gaining increased autonomy due to advances in sensor and computing technology. In their current form however, robots still lack algorithms for rapid perception of objects in a cluttered environment and can benefit from the assistance of a human operator. Further, fully autonomous systems will continue to be computationally expensive and costly for quite some time. Humans can visually assess objects and determine whether a certain path is traversable, but need not be involved in the low-level steering around any detected obstacles as is necessary in remote-controlled systems. If only used for rapid perception tasks, the operator could …

Accelerated Fuzzy Clustering, Jonathon Karl Parker

USF Tampa Graduate Theses and Dissertations

Clustering algorithms are a primary tool in data analysis, facilitating the discovery of groups and structure in unlabeled data. They are used in a wide variety of industries and applications. Despite their ubiquity, clustering algorithms have a flaw: they take an unacceptable amount of time to run as the number of data objects increases. The need to compensate for this flaw has led to the development of a large number of techniques intended to accelerate their performance. This need grows greater every day, as collections of unlabeled data grow larger and larger. How does one increase the speed of a …

Hedge Detection Using A Rewards And Penalties Approach, Ken Stahl

Legacy Theses & Dissertations (2009 - 2024)

Semantic and syntactic features found in text can be used in combination to statistically predict linguistic devices such as hedges in online chat. Some features are better indicators than others, and there are cases when multiple features need to be considered together to be useful. Once the features are identified, it becomes an optimization problem to find the best division of data.

Nfl: The World Of Technology?: How Technology Made The Nfl The Cash Cows Of The Sports World, Jaron A. Moody

Senior Seminars

Sports coverage is highly focused on the image of the sport and how the fans experience the sport. Technology plays a huge part of that. The technology that's used to maintain the display of the game as well as the technology that holds the statistics that keeps fans fully aware about what's going on in the game. The IT department has to work with programmers to create these programs and they have to keep them up to date. Without this, the experience of watching sports on television would decrease rapidly which would send the value of the NFL to a …

The History Of Apple Inc., Dominique Turner

Senior Seminars

No abstract provided.

Compression Of Gps Trajectory Data : Benchmarking Framework And New Approach, Jonathan Muckell

Legacy Theses & Dissertations (2009 - 2024)

GPS-equipped mobile devices such as smart phones and in-car navigation units are collecting enormous amounts of spatial and temporal information that traces a moving object's path. The exponential increase in the amount of such trajectory data has caused three major problems. First, transmission of large amounts of data is expensive and time-consuming. Second, queries on large amounts of trajectory data require computationally expensive operations to extract useful patterns and information. Third, GPS trajectories often contain large amounts of redundant data that waste storage and cause increased disk I/O time. These issues can be addressed by algorithms that reduce the size …

Kernel Density Metric Learning, Yujie He, Wenlin Chen, Yixin Chen

All Computer Science and Engineering Research

This paper introduces a supervised metric learning algorithm, called kernel density metric learning (KDML), which is easy to use and provides nonlinear, probability-based distance measures. KDML constructs a direct nonlinear mapping from the original input space into a feature space based on kernel density estimation. The nonlinear mapping in KDML embodies established distance measures between probability density functions, and leads to correct classification on datasets for which linear metric learning methods would fail. Existing metric learning algorithms, such as large margin nearest neighbors (LMNN), can then be applied to the KDML features to learn a Mahalanobis distance. We also propose …