Design and implementation of a multisite data repository for pediatric epilepsy

This dissertation established a software-hardware integrated design for a multisite data repository in pediatric epilepsy. A total of 16 institutions formed a consortium for this web-based application. This innovative fully operational web application allows users to upload and retrieve information through a unique human-computer graphical interface that is remotely accessible to all users of the consortium. A solution based on a Linux platform with My-SQL and Personal Home Page scripts (PHP) has been selected. Research was conducted to evaluate mechanisms to electronically transfer diverse datasets from different hospitals and collect the clinical data in concert with their related functional magnetic resonance imaging (fMRI). What was unique in the approach considered is that all pertinent clinical information about patients is synthesized with input from clinical experts into 4 different forms, which were: Clinical, fMRI scoring, Image information, and Neuropsychological data entry forms. A first contribution of this dissertation was in proposing an integrated processing platform that was site and scanner independent in order to uniformly process the varied fMRI datasets and to generate comparative brain activation patterns. The data collection from the consortium complied with the IRB requirements and provides all the safeguards for security and confidentiality requirements. An 1-MR1-based software library was used to perform data processing and statistical analysis to obtain the brain activation maps. Lateralization Index (LI) of healthy control (HC) subjects in contrast to localization-related epilepsy (LRE) subjects were evaluated. Over 110 activation maps were generated, and their respective LIs were computed yielding the following groups: (a) strong right lateralization: (HC=0%, LRE=18%), (b) right lateralization: (HC=2%, LRE=10%), (c) bilateral: (HC=20%, LRE=15%), (d) left lateralization: (HC=42%, LRE=26%), e) strong left lateralization: (HC=36%, LRE=31%). Moreover, nonlinear-multidimensional decision functions were used to seek an optimal separation between typical and atypical brain activations on the basis of the demographics as well as the extent and intensity of these brain activations. The intent was not to seek the highest output measures given the inherent overlap of the data, but rather to assess which of the many dimensions were critical in the overall assessment of typical and atypical language activations with the freedom to select any number of dimensions and impose any degree of complexity in the nonlinearity of the decision space.

Generating an Online Bottom Line

E-commerce is an approach to achieving business goals through information technology and is quickly changing the way hospitality business is planned, monitored, and conducted. No longer do buyers and sellers need to engage in interpersonal communications for transactions to occur. The future of transaction processing, which includes cyber cash and digital checking, are directly attributable to e-commerce which provides and efficient, reliable, secure, and effective platform for conducting hospitality business on the web.

A Review of the Effects of Altered Hydrology and Salinity on Vertebrate Fauna and Their Habitats in Northeastern Florida Bay

Estuarine productivity is highly dependent on the freshwater sources of the estuary. In Florida Bay, Taylor Slough was historically the main source of fresh water. Beginning in about 1960, and culminating with the completion of the South Dade Conveyance System in 1984, water management practice began to change the quantity and distribution of flow from Taylor Slough into Northeastern Florida Bay. These practices altered salinity and hydrologic parameters that had measurable negative impacts on vertebrate fauna and their habitats. Here, I review those impacts from published and unpublished literature and anecdotal observations. Almost all vertebrates covered in this review have shown some form of population decline since 1984; most of the studies implicate declines in food resources as the main stressor on their populations. My conclusion is that the diversion of fresh water resulted in an ecological cascade starting with hydrologic stresses on primary then secondary producers culminating in population declines at the top of the food web.

Everglades R-EMAP 2005

The Everglades R-EMAP project for year 2005 produced large quantities of data collected at 232 sampling sites. Data collection and analysis is an on-going long-term activity conducted by scientists of different disciplines at irregular intervals of several years. The data sets collected for 2005 include bio-geo-chemical (including mercury and hydro period), fish, invertebrate, periphyton, and plant data. Each sampling site is associated with a location, a description of the site to provide a general overview and photographs to provide a pictorial impression. The Geographic Information Systems and Remote Sensing Center(GISRSC) at Florida International University (FIU) has designed and implemented an enterprise database for long-term storage of the project�s data in a central repository, providing the framework of data storage for the continuity of future sampling campaigns and allowing integration of new sample data as it becomes available. In addition GISRSC provides this interactive web application for easy, quick and effective retrieval and visualization of that data.

The influence of processing instructions at encoding and retrieval on face recognition accuracy

Whereas previous research has demonstrated that trait ratings of faces at encoding leads to enhanced recognition accuracy as compared to feature ratings, this set of experiments examines whether ratings given after encoding and just prior to recognition influence face recognition accuracy. In Experiment 1 subjects who made feature ratings just prior to recognition were significantly less accurate than subjects who made no ratings or trait ratings. In Experiment 2 ratings were manipulated at both encoding and retrieval. The retrieval effect was smaller and nonsignificant, but a combined probability analysis showed that it was significant when results from both experiments are considered jointly. In a third experiment exposure duration at retrieval, a potentially confounding factor in Experiments 1 and 2, had a nonsignificant effect on recognition accuracy, suggesting that it probably does not explain the results from Experiments 1 and 2. These experiments demonstrate that face recognition accuracy can be influenced by processing instructions at retrieval.

An integrative approach to face and expression recognition from 3D scans

Biometrics is afield of study which pursues the association of a person's identity with his/her physiological or behavioral characteristics.^ As one aspect of biometrics, face recognition has attracted special attention because it is a natural and noninvasive means to identify individuals. Most of the previous studies in face recognition are based on two-dimensional (2D) intensity images. Face recognition based on 2D intensity images, however, is sensitive to environment illumination and subject orientation changes, affecting the recognition results. With the development of three-dimensional (3D) scanners, 3D face recognition is being explored as an alternative to the traditional 2D methods for face recognition.^ This dissertation proposes a method in which the expression and the identity of a face are determined in an integrated fashion from 3D scans. In this framework, there is a front end expression recognition module which sorts the incoming 3D face according to the expression detected in the 3D scans. Then, scans with neutral expressions are processed by a corresponding 3D neutral face recognition module. Alternatively, if a scan displays a non-neutral expression, e.g., a smiling expression, it will be routed to an appropriate specialized recognition module for smiling face recognition.^ The expression recognition method proposed in this dissertation is innovative in that it uses information from 3D scans to perform the classification task. A smiling face recognition module was developed, based on the statistical modeling of the variance between faces with neutral expression and faces with a smiling expression.^ The proposed expression and face recognition framework was tested with a database containing 120 3D scans from 30 subjects (Half are neutral faces and half are smiling faces). It is shown that the proposed framework achieves a recognition rate 10% higher than attempting the identification with only the neutral face recognition module.^

Development of face recognition: Infancy to early childhood

Perception and recognition of faces are fundamental cognitive abilities that form a basis for our social interactions. Research has investigated face perception using a variety of methodologies across the lifespan. Habituation, novelty preference, and visual paired comparison paradigms are typically used to investigate face perception in young infants. Storybook recognition tasks and eyewitness lineup paradigms are generally used to investigate face perception in young children. These methodologies have introduced systematic differences including the use of linguistic information for children but not infants, greater memory load for children than infants, and longer exposure times to faces for infants than for older children, making comparisons across age difficult. Thus, research investigating infant and child perception of faces using common methods, measures, and stimuli is needed to better understand how face perception develops. According to predictions of the Intersensory Redundancy Hypothesis (IRH; Bahrick & Lickliter, 2000, 2002), in early development, perception of faces is enhanced in unimodal visual (i.e., silent dynamic face) rather than bimodal audiovisual (i.e., dynamic face with synchronous speech) stimulation. The current study investigated the development of face recognition across children of three ages: 5 – 6 months, 18 – 24 months, and 3.5 – 4 years, using the novelty preference paradigm and the same stimuli for all age groups. It also assessed the role of modality (unimodal visual versus bimodal audiovisual) and memory load (low versus high) on face recognition. It was hypothesized that face recognition would improve across age and would be enhanced in unimodal visual stimulation with a low memory load. Results demonstrated a developmental trend (F(2, 90) = 5.00, p = 0.009) with older children showing significantly better recognition of faces than younger children. In contrast to predictions, no differences were found as a function of modality of presentation (bimodal audiovisual versus unimodal visual) or memory load (low versus high). This study was the first to demonstrate a developmental improvement in face recognition from infancy through childhood using common methods, measures and stimuli consistent across age.

An incremental multilinear system for human face learning and recognition

This dissertation establishes a novel system for human face learning and recognition based on incremental multilinear Principal Component Analysis (PCA). Most of the existing face recognition systems need training data during the learning process. The system as proposed in this dissertation utilizes an unsupervised or weakly supervised learning approach, in which the learning phase requires a minimal amount of training data. It also overcomes the inability of traditional systems to adapt to the testing phase as the decision process for the newly acquired images continues to rely on that same old training data set. Consequently when a new training set is to be used, the traditional approach will require that the entire eigensystem will have to be generated again. However, as a means to speed up this computational process, the proposed method uses the eigensystem generated from the old training set together with the new images to generate more effectively the new eigensystem in a so-called incremental learning process. In the empirical evaluation phase, there are two key factors that are essential in evaluating the performance of the proposed method: (1) recognition accuracy and (2) computational complexity. In order to establish the most suitable algorithm for this research, a comparative analysis of the best performing methods has been carried out first. The results of the comparative analysis advocated for the initial utilization of the multilinear PCA in our research. As for the consideration of the issue of computational complexity for the subspace update procedure, a novel incremental algorithm, which combines the traditional sequential Karhunen-Loeve (SKL) algorithm with the newly developed incremental modified fast PCA algorithm, was established. In order to utilize the multilinear PCA in the incremental process, a new unfolding method was developed to affix the newly added data at the end of the previous data. The results of the incremental process based on these two methods were obtained to bear out these new theoretical improvements. Some object tracking results using video images are also provided as another challenging task to prove the soundness of this incremental multilinear learning method.

Class in Classrooms: The Challenges Public Librarians Face as Border Crossing Educators

In border crossing pedagogy, educators help students negotiate identity and cultural issues. Public librarians help special populations of patrons improve on class issues through education. This study explored the issues public librarians face when they teach and border cross across social classes.

The Other Face of Cuban Medical Diplomacy: Domestic Impact

Since 1963 Cuba has provided medical assistance to third world countries while gaining international, political and economic support from its participating liaisons. But what exactly have been Cuba’s domestic consequences of such medical diplomacy? While the Cuban government sends many of its medical professionals and supplies abroad, the country suffers from extreme scarcity and a deterioration of its healthcare system. The purpose of my research is to enquire more on the consequences of such medical diplomacy on the Cuban healthcare system and how it has affected domestic medical infrastructure, health professionals working on the island as well as the quality of service. In carrying out this examination, I will rely on the use of information from books written by Cuban medical professionals on their personal experiences within the medical system, and patients treated on the island. I will also make active use of academic journals and articles on the Cuban healthcare system. Most of what has been written on Cuban medical diplomacy and internationalist missions are favorable critiques praising the Cuban government. Nevertheless, personal testimonies found in Dr. Dessy Mendoza Rivero’s Dengue: La Epidemia Secreta de Fidel Castro and in Dr. Jose Luis Comas and Dr. Luis Ovidio Gonzales’ Cuba: Medicina y Revolucion reveal a different side to this seemingly pleasant and good natured international exchange. As a Cuban who lived on the island, I personally suffered the consequences of such medical diplomacy and believe others will find benefit in arming themselves with knowledge on the issue.

Water Demand and Allocation in the Mara River Basin, Kenya/Tanzania in the Face of Land Use Dynamics and Climate Variability

The Mara River Basin (MRB) is endowed with pristine biodiversity, socio-cultural heritage and natural resources. The purpose of my study is to develop and apply an integrated water resource allocation framework for the MRB based on the hydrological processes, water demand and economic factors. The basin was partitioned into twelve sub-basins and the rainfall runoff processes was modeled using the Soil and Water Assessment Tool (SWAT) after satisfactory Nash-Sutcliff efficiency of 0.68 for calibration and 0.43 for validation at Mara Mines station. The impact and uncertainty of climate change on the hydrology of the MRB was assessed using SWAT and three scenarios of statistically downscaled outputs from twenty Global Circulation Models. Results predicted the wet season getting more wet and the dry season getting drier, with a general increasing trend of annual rainfall through 2050. Three blocks of water demand (environmental, normal and flood) were estimated from consumptive water use by human, wildlife, livestock, tourism, irrigation and industry. Water demand projections suggest human consumption is expected to surpass irrigation as the highest water demand sector by 2030. Monthly volume of water was estimated in three blocks of current minimum reliability, reserve (>95%), normal (80–95%) and flood (40%) for more than 5 months in a year. The assessment of water price and marginal productivity showed that current water use hardly responds to a change in price or productivity of water. Finally, a water allocation model was developed and applied to investigate the optimum monthly allocation among sectors and sub-basins by maximizing the use value and hydrological reliability of water. Model results demonstrated that the status on reserve and normal volumes can be improved to ‘low’ or ‘moderate’ by updating the existing reliability to meet prevailing demand. Flow volumes and rates for four scenarios of reliability were presented. Results showed that the water allocation framework can be used as comprehensive tool in the management of MRB, and possibly be extended similar watersheds.