Computer Sciences Commons^™

Prediction Of Laser Ablation In Brain: Sensitivity, Calibration, And Validation, Samuel J. Fahrenholtz

Dissertations & Theses (Open Access)

The surgical planning of MR-guided laser induced thermal therapy (MRgLITT) stands to benefit from predictive computational modeling. The dearth of physical model parameter data leads to modeling uncertainty. This work implements a well-accepted framework with three key steps for model-building: model-parameter sensitivity analysis, model calibration, and model validation.

The sensitivity study is via generalized polynomial chaos (gPC) paired with a transient finite element (FEM) model. Uniform probability distribution functions (PDFs) capture the plausible range of values suggested by the literature for five model parameters. The five PDFs are input separately into the FEM model to gain a probabilistic sensitivity response …

In Need Of A Domain-Specific Language Modeling Notation For Smartphone Applications With Portable Capability, Hamza Ghandorh, Luiz Fernando Capretz Dr., Ali Bou Nassif Dr.

Electrical and Computer Engineering Publications

The rapid growth of the smartphone market and its increasing revenue has motivated developers to target multiple platforms. Market leaders, such as Apple, Google, and Microsoft, develop their smartphone applications complying with their platform specifications. The specification of each platform makes a platform-dedicated application incompatible with other platforms due to the diversity of operating systems, programming languages, and design patterns. Conventional development methodologies are applied to smartphone applications, yet they perform less well. Smartphone applications have unique hardware and software requirements. All previous factors push smartphone developers to build less sophisticated and low-quality products when targeting multiple smartphone platforms. Model-driven …

Maintaining Consistency Between A Design Model And Its Implementation, Hector M. Chavez

Dissertations

Software design models are increasingly being used as part of the software development process as analysis and design artifacts and to automatically generate code that developers can further modify or extend, greatly expediting the software development process. This, however, has introduced the challenge of maintaining consistency between the design models and their implementation as they evolve during the development process. Traditional software testing and verification techniques have been well studied in the past, and they are an integral part of many software development projects, however, they are not well suited for consistency checking between a design model and its implementation. …

Interdisciplinary Modeling For Water-Related Issues Graduate Course, Laurel Saito, Alexander Fernald, Timothy Link

All ECSTATIC Materials

The science and management of aquatic ecosystems is inherently interdisciplinary, with issues associated with hydrology, atmospheric science, water quality, geochemistry, sociology, economics, environmental science, and ecology. Addressing water resources issues in any one discipline invariably involves effects that concern other disciplines, and attempts to address one issue often have consequences that exacerbate existing issues or concerns, or create new ones (Jørgensen et al. 1992; Lackey et al. 1975; Straskraba 1994) due to the strongly interactive nature of key processes (Christensen et al. 1996). Thus, research and management of aquatic ecosystems must be interdisciplinary to be most effective, but such truly …

Detecting, Modeling, And Predicting User Temporal Intention, Hany M. Salaheldeen

Computer Science Theses & Dissertations

The content of social media has grown exponentially in the recent years and its role has evolved from narrating life events to actually shaping them. Unfortunately, content posted and shared in social networks is vulnerable and prone to loss or change, rendering the context associated with it (a tweet, post, status, or others) meaningless. There is an inherent value in maintaining the consistency of such social records as in some cases they take over the task of being the first draft of history as collections of these social posts narrate the pulse of the street during historic events, protest, riots, …

Time Series Modeling Of Baseball Performance​, Kyle Andelin, Sam Kaplan

Scholars Week

The 162 game long Major League Baseball season provides ample time for a player’s performance to vary and trend in different directions. Managers must set daily rosters for their teams, using past performance to help make decisions. But which prior performance periods tell us the most about upcoming performance? To answer this, it's helpful to view a player’s future performance, for any given statistic, as a function of his performance in previous playing periods (e.g. previous game, previous week, previous year, etc.). In this on-going research project, we consider two approaches to predicting future performance from the past. In the …

Toward A Theory Of Multi-Method Modeling And Simulation Approach, Mariusz A. Balaban

Computational Modeling & Simulation Engineering Theses & Dissertations

The representation via simulation models can easily lead to simulation models too simple for their intended purpose, or with too much detail, making them hard to understand. This problem is related to limitations of the modeling and simulation methods. A multi-method Modeling and Simulation (M&S) approach has the potential for improved representation by taking advantage of methods' strengths and mitigating their weaknesses. Despite a high appeal for using multiple M&S methods, several related problems should be addressed first. The current level of theoretical, methodological, and pragmatic knowledge related to a multi-method M&S approach is limited. It is problematic that there …

Dependency-Topic-Affects-Sentiment-Lda Model For Sentiment Analysis, Shunshun Yin, Jun Han, Yu Huang, Kuldeep Kumar

Kuldeep Kumar

Sentiment analysis tends to use automated approaches to mine the sentiment information expressed in text, such as reviews, blogs and forum discussions. As most traditional approaches for sentiment analysis are based on supervised learning models and need many labeled corpora as their training data which are not always easily obtained, various unsupervised models based on Latent Dirichlet Allocation (LDA) have been proposed for sentiment classification. In this paper, we propose a novel probabilistic modeling framework based on LDA, called Dependency-Topic-Affects-Sentiment-LDA (DTAS) model, which drops the ”bag of words” assumption and assumes that the topics of sentences in a document form …

Modeling And Simulation Of Evacuation Plan For Hancock Stadium, Nirmal Neranjan Weerasekara

Theses and Dissertations

The goal of this study is to use Modeling and Simulation of Evacuation Plan (MSEP) to support management to execute proper evacuation plan in case of emergency at Hancock Stadium in Illinois State University. Analyses of the research literature and evacuation scenarios are used to build a simulation system that will connect a description of emergency and evacuation situation with its context. It shows how an evacuation plan actually functions. The results of the study will help safety managers to understand the current situations of evacuation according to the specific simulation scenarios. The evacuation simulation is categorized according to the …

Reverse Engineering The Human Brain: An Evolutionary Computation Approach To The Analysis Of Fmri, Nicholas Allgaier

Graduate College Dissertations and Theses

The field of neuroimaging has truly become data rich, and as such, novel analytical methods capable of gleaning meaningful information from large stores of imaging data are in high demand. Those methods that might also be applicable on the level of individual subjects, and thus potentially useful clinically, are of special interest. In this dissertation we introduce just such a method, called nonlinear functional mapping (NFM), and demonstrate its application in the analysis of resting state fMRI (functional Magnetic Resonance Imaging) from a 242-subject subset of the IMAGEN project, a European study of risk-taking behavior in adolescents that includes longitudinal …

Adaptive Network-Based Inference System Models On Multiband Patch Antenna Design, Erdem Demi̇rci̇oğlu, Murat Hüsnü Sazli, Orhan Şengül, Şehabeddi̇n Taha İmeci̇, Hakki Alparslan Ilgin

Turkish Journal of Electrical Engineering and Computer Sciences

In this study, an adaptive network-based fuzzy inference system (ANFIS) for multiband microstrip patch antenna (MMPA) modeling is proposed. The MMPA includes a single patch with inverted L-shaped stubs on the edges. The antenna production process needs iterative runs of the electromagnetic (EM) simulator, fabricating and testing the simulated antenna to find the optimum geometry. Production processes (design, simulation, fabrication, and testing) and the cost computation time add to the overall manufacturing expenses. A computer-aided modeling approach using the ANFIS is developed and trained with data acquired from the EM simulators, Sonnet Suites and AWR AXIEM, and measurement data. The …

A Predictive Modeling System: Early Identification Of Students At-Risk Enrolled In Online Learning Programs, Mary L. Fonti

CCE Theses and Dissertations

Predictive statistical modeling shows promise in accurately predicting academic performance for students enrolled in online programs. This approach has proven effective in accurately identifying students who are at-risk enabling instructors to provide instructional intervention. While the potential benefits of statistical modeling is significant, implementations have proven to be complex, costly, and difficult to maintain. To address these issues, the purpose of this study is to develop a fully integrated, automated predictive modeling system (PMS) that is flexible, easy to use, and portable to identify students who are potentially at-risk for not succeeding in a course they are currently enrolled in. …