A Better Looking Brain: Image Pre-Processing Approaches for fMRI Data

Researchers in the field of functional neuroimaging have faced a long standing problem in pre-processing low spatial resolution data without losing meaningful details within. Commonly, the brain function is recorded by a technique known as echo-planar imaging that represents the measure of blood flow (BOLD signal) through a particular location in the brain as an array of intensity values changing over time. This approach to record a movie of blood flow in the brain is known as fMRI. The neural activity is then studied from the temporal correlation patterns existing within the fMRI time series. However, the resulting images are noisy and contain low spatial detail, thus making it imperative to pre-process them appropriately to derive meaningful activation patterns. Two of the several standard preprocessing steps employed just before the analysis stage are denoising and normalization. Fundamentally, it is difficult to perfectly remove noise from an image without making assumptions about signal and noise distributions. A convenient and commonly used alternative is to smooth the image with a Gaussian filter, but this method suffers from various obvious drawbacks, primarily loss of spatial detail. A greater challenge arises when we attempt to derive average activation patterns from fMRI images acquired from a group of individuals. The brain of one individual differs from others in a structural sense as well as in a functional sense. Commonly, the inter-individual differences in anatomical structures are compensated for by co-registering each subject\u27s data to a common normalization space, known as spatial normalization. However, there are no existing methods to compensate for the differences in functional organization of the brain. This work presents first steps towards data-driven robust algorithms for fMRI image denoising and multi-subject image normalization by utilizing inherent information within fMRI data. In addition, a new validation approach based on spatial shape of the activation regions is presented to quantify the effects of preprocessing and also as a tool to record the differences in activation patterns between individual subjects or within two groups such as healthy controls and patients with mental illness. Qualititative and quantitative results of the proposed framework compare favorably against existing and widely used model-driven approaches such as Gaussian smoothing and structure-based spatial normalization. This work is intended to provide neuroscience researchers tools to derive more meaningful activation patterns to accurately identify imaging biomarkers for various neurodevelopmental diseases and also maximize the specificity of a diagnosis

Cache Hierarchy-Aware Query Mapping on Emerging Multicore Architectures

One of the important characteristics of emerging multicores/manycores is the existence of 'shared on-chip caches,' through which different threads/processes can share data (help each other) or displace each other's data (hurt each other). Most of current commercial multicore systems on the market have on-chip cache hierarchies with multiple layers (typically, in the form of L1, L2 and L3, the last two being either fully or partially shared). In the context of database workloads, exploiting full potential of these caches can be critical. Motivated by this observation, our main contribution in this work is to present and experimentally evaluate a cache hierarchy-aware query mapping scheme targeting workloads that consist of batch queries to be executed on emerging multicores. Our proposed scheme distributes a given batch of queries across the cores of a target multicore architecture based on the affinity relations among the queries. The primary goal behind this scheme is to maximize the utilization of the underlying on-chip cache hierarchy while keeping the load nearly balanced across domain affinities. Each domain affinity in this context corresponds to a cache structure bounded by a particular level of the cache hierarchy. A graph partitioning-based method is employed to distribute queries across cores, and an integer linear programming (ILP) formulation is used to address locality and load balancing concerns. We evaluate our scheme using the TPC-H benchmarks on an Intel Xeon based multicore. Our solution achieves up to 25 percent improvement in individual query execution times and 15-19 percent improvement in throughput over the default Linux-based process scheduler. © 1968-2012 IEEE

Seismic characterization of naturally fractured reservoirs

Many hydrocarbon reservoirs have sufficient porosity but low permeability (for example, tight gas sands and coal beds). However, such reservoirs are often naturally fractured. The fracture patterns in these reservoirs can control flow and transport properties, and therefore, play an important role in drilling production wells. On the scale of seismic wavelengths, closely spaced parallel fractures behave like an anisotropic media, which precludes the response of individual fractures in the seismic data. There are a number of fracture parameters which are needed to fully characterize a fractured reservoir. However, seismic data may reveal only certain fracture parameters and those are fracture orientation, crack density and fracture infill. Most of the widely used fracture characterization methods such as Swave splitting analysis or amplitude vs. offset and azimuth (AVOA) analysis fail to render desired results in laterally varying media. I have conducted a systematic study of the response of fractured reservoirs with laterally varying elastic and fracture properties, and I have developed a scheme to invert for the fracture parameters. I have implemented a 3D finite-difference method to generate multicomponent synthetic seismic data in general anisotropic media. I applied the finite-difference algorithm in both Standard and Rotated Staggered grids. Standard Staggered grid is used for media having symmetry up to orthorhombic (isotropic, transversely isotropic, and orthorhombic), whereas Rotated Staggered grid is implemented for monoclinic and triclinic media. I have also developed an efficient and accurate ray-bending algorithm to compute seismic traveltimes in 3D anisotropic media. AVOA analysis is equivalent to the first-order Born approximation. However, AVOA analysis can be applied only in a laterally uniform medium, whereas the Born-approximation does not pose any restriction on the subsurface structure. I have developed an inversion scheme based on a ray-Born approximation to invert for the fracture parameters. Best results are achieved when both vertical and horizontal components of the seismic data are inverted simultaneously. I have also developed an efficient positivity constraint which forbids the inverted fracture parameters to be negative in value. I have implemented the inversion scheme in the frequency domain and I show, using various numerical examples, that all frequency samples up to the Nyquist are not required to achieve desired inversion results.Geological Science

Growing grass for a green biorefinery - an option for Ireland?

Growing grass for a green biorefinery – an option for Ireland? Mind the gap: deciphering the gap between good intentions and healthy eating behaviour Halting biodiversity loss by 2020 – implications for agriculture A milk processing sector model for Irelan

Engineering Aggregation Operators for Relational In-Memory Database Systems

In this thesis we study the design and implementation of Aggregation operators in the context of relational in-memory database systems. In particular, we identify and address the following challenges: cache-efficiency, CPU-friendliness, parallelism within and across processors, robust handling of skewed data, adaptive processing, processing with constrained memory, and integration with modern database architectures. Our resulting algorithm outperforms the state-of-the-art by up to 3.7x

Albuquerque Daily Citizen, 03-26-1900

https://digitalrepository.unm.edu/abq_citizen_news/2679/thumbnail.jp

Arquitectura dirigida por modelos aplicada al desarrollo de metodologías de aprendizaje de idiomas

Hoy en día, cada vez más gente está interesada en el aprendizaje de una segunda -e incluso de una tercera- lengua extranjera. Esto es debido al fenómeno de la globalización, y está siendo facilitado por el uso extensivo de Internet. El proceso de aprendizaje de una lengua extranjera está definido por metodologías y -cada vez más- apoyado por la tecnología. El desarrollo de este tipo de aplicaciones es complejo (por la variedad de los entornos de ejecución, y por tener una gran cantidad de contenidos con frecuencia difíciles de validar), por lo que esta tesis propone un enfoque dirigido por modelos para desarrollo de software para dar soporte a la enseñanza de idiomas. El estudio y análisis de diferentes metodologías para el aprendizaje de idiomas ha permitido obtener, mediante un proceso de abstracción, los elementos comunes a todas ellas: En primer lugar (1) un conjunto/jerarquía de conceptos que se enseñan (contenidos), y (2) un conjunto de recursos (medios) para presentar los conceptos. Por otra parte, todas las metodologías definen (3) diversos tipos de ejercicios de aprendizaje (actividades) y (4) una secuencia o conjunto de secuencias que las relacionan (flujo de control/trabajo). Finalmente, definen una serie de (5) plantillas o disposiciones para la visualización de los contenidos y de las actividades (presentación). Esta tesis presenta una solución Model-Driven Architecture (MDA) que permite el desarrollo de aplicaciones para el aprendizaje de idiomas a partir de modelos. Así pues, desde una capa Computational Independent Model (CIM) hasta la capa Implementation Specific Model (ISM), se presentan los meta-modelos y los editores gráficos para los distintos lenguajes específicos de dominio, que permiten modelar todo lo necesario para el desarrollo de casi cualquier metodología de aprendizaje de idiomas. Por otra parte, en esta tesis también se definen las transformaciones necesarias, y el proceso de transformación asociado, para la generación automática del código fuente (en HTML y JavaScript) de aplicaciones de aprendizaje de idiomas. La propuesta ha sido validada a través del modelado y la generación del código fuente de los elementos de funcionalidad más importantes de la metodología Lexiway, así como de varios tipos de actividades de aprendizaje muy utilizados -y de forma muy parecida- en metodologías como Duolingo y Busuu

Patients’ satisfaction received from nursing staff in the Home Care Programme run by the Ministry of Health in Cyprus

The main purpose of this study was to investigate the home care patients’ satisfaction received from the nursing staff in the public home care program in Cyprus. Patients’ satisfaction has become an important part in evaluating the quality of health care services. Patients are the ones who can identify better than anyone else the aspects of nursing care which need improvement. Home care services are quite new and still developing in Cyprus while the need for these services is increasing rapidly. This study, utilized the QPP survey questionnaire, in depth semi-structured interviews and observations. The questionnaire was delivered to the home care patients who received long term care during the period of February 2011 to May 2011. A purposive sample was used for the interviews of the patients, the nursing staff and the management staff of the home care program and for the observations of the home care visits. The results of this study showed that the home care patients of the public home care program in Cyprus are very satisfied from the services they receive from the home care nursing staff. The quality of care, QPP index was found of the highest score in all items of the questionnaire. This study revealed high standards in the elements relating to the humane approach, the medical competence, the information and advising provided to the patients. At the same time, this study identified a deficiency in the abilities of the nursing staff to provide psychological support in difficult cases and the patients’ inadequate control of their medical care according to their desires rather than by the procedures of their home care nurse. It also identified the need of the home care patients for help in the activities of daily living (ADLs). Additionally, this study surfaced the aspects of the nursing care which the home care patients consider more important and highlighted the characteristics of an ideal home care nurse through the patients’ eyes; placing the humane approach as the most important aspect, followed by the psychological support provided and then by the nursing knowledge. A deviation was identified between the nursing and management views, with the later placing the nursing knowledge as first, followed by leadership skills and then by the humane approach. This study, also identified those problematic areas of the program which negatively influence the nursing services; these were the absence of a team of health professionals in the program, the limited operating hours, the non-implementation of the concept of prescribing nurses, the non- eligibility of the nurses to refer the patients to other health professionals, inadequate technology, insufficient financial support of the program, and the cumbersome procedures of the public sector. Home care patients’ satisfaction from the nursing staff is very high; yet there are some areas which need improvement. Recommendations emanated from the project include the enhancement of the nursing undergraduate and post graduate education in home care nursing, with courses and workshops on the psychology of home care patients, on gerontology, on leadership and communication skills. Recommendations also include individual and organizational development interventions for providing more support to the home care nurses, higher quality of care to the home care patients within a client-centred environment and feedback strategies

Some Prototype Examples for Expert Systems v.1

This report consists of the nineteen term project reports for the graduate-level course EE695G ” Expert Systems and Knowledge Engineering”, which was offered for the fall semester of 1984 in the School of Electrical Engineering. The purpose of the term project is to provide each student an opportunity of designing and implementing a prototype expert system. The application area of each of these expert systems was selected by the student(s) working on the projects. This report is published for the purpose of documenting these results for future reference by the students of the above-mentioned course and, possibly, other workers in expert systems. The nineteen reports are grouped into seven parts based on their application domains. Part 1 - Manufacturing consists of six reports, and Part II - Robotics contains three. Two reports in each of Part III - Vision and Part IV - Management, and one in each of Part V - Structural Engineering and Part VI - Automatic Programming. The last part, Part VII - Others, consists of four reports with different applications