Efficient parallelization on GPU of an image smoothing method based on a variational model

Medical imaging is fundamental for improvements in diagnostic accuracy. However, noise frequently corrupts the images acquired, and this can lead to erroneous diagnoses. Fortunately, image preprocessing algorithms can enhance corrupted images, particularly in noise smoothing and removal. In the medical field, time is always a very critical factor, and so there is a need for implementations which are fast and, if possible, in real time. This study presents and discusses an implementation of a highly efficient algorithm for image noise smoothing based on general purpose computing on graphics processing units techniques. The use of these techniques facilitates the quick and efficient smoothing of images corrupted by noise, even when performed on large-dimensional data sets. This is particularly relevant since GPU cards are becoming more affordable, powerful and common in medical environments

Método de suavização de imagem baseado num modelo variacional paralelizado em arquitetura CUDA

O aumento constante da velocidade de cálculo dos processadores tem sido uma grande aliada no desenvolvimento de áreas da ciência que exigem processamento de alto desempenho. Associado ao aumento dos recursos computacionais, tem-se presenciado um aumento no emprego de técnicas de computação paralela, no intuito de explorar ao máximo a capacidade de processamento das arquiteturas multiprocessador. No entanto, o custo financeiro para aquisição de hardware para computação paralela não é baixo, implicando assim aa busca de alternativas. A arquitetura GPGPU (General Purpose Computing on Graphics Processing Unit), torna-se uma opção de baixo custo sem comprometer o poder de processamento necessário. Neste trabalho, esta arquitetura é empregada na paralelização de um método de suavização de imagem baseado num modelo variacional, aplicado em sequências de imagens de ultra-sonografia. Os resultados obtidos são promissores, permitindo um ganho de tempo computacional considerável

Federalism, ICT and development in the Global South

This paper builds on the ICT and development literature to answer the question on what indicators better represent ICT institutional background in the Global South, namely Central America, the Caribbean Islands, South America, Africa and South Asia. It delves into the institutional variable of federalism widely used in comparative analyzes tackling the correlation between e.g. broadband deployment and economic development, by finding granulated variables that portray a more precise scenario of institutional commensurability among countries being compared for public policy purposes. Its main underpinnings are the concept of information revolution and the methodology put forward by the Telecommunications Law Indicators for Comparative Studies (TLICS) Model. Six sets of federative indicators on revenue, fiscal transfer, regulatory jurisdiction, adjudication, planning, and media content regulation are put together to compare ICT federal environment in the Global South as a groundwork for the ICT comparative research. The empirical universe of the paper encompassed thirty-eight countries from Central and South America, the Caribbean Islands, Africa and South Asia, that form a potpourri of thirty officially unitary countries – Angola, Belize, Bolivia, Cabo Verde, Chile, Colombia, Costa Rica, Cuba, Dominican Republic, Ecuador, El Salvador, Guatemala, Guinea Bissau, Haiti, Honduras, Jamaica, Mozambique, New Zealand, Nicaragua, Panama, Papua New Guinea, Paraguay, Peru, Philippines, Sao Tome and Principe, Singapore, Suriname, Tanzania, Trinidad and Tobago, and Uruguay –, and eight federal countries – Argentina, Brazil, India, Malaysia, Mexico, Nigeria, South Africa, and Venezuela. The article is organized in three main parts. A brief description of the paper assumptions is performed in the first part. The second part applies TLICS variables to sets of the aforementioned states. The third part delves into the comparison of the states analyzed by means of categorizing the differences and commonalities revealed by more than one thousand five hundred variables collected in the legal and institutional framework of those countries and finally summarized in the ICT federal index (IFI) and ICT unitary index (IUI). We also test the association between federalism as the outcome and each of the independent (explanatory) variables proposed by the TLICS model by applying statistical tests (Fisher exact test, relative risk, and odds ratio). The only ICT variable significantly associated with a country being classified as a federal state is tax in the telecom and broadcast. As a main outcome, based on data collected from the institutional background and legal frameworks of those countries, we found clusters of federal commonalities in federal and unitary countries of the region. With that, we proposed two indices that better represent federal and unitary institutional backgrounds: The ICT Federal Index (IFI); and the ICT Unitary Index (IUI). They provide a real picture of their institutional background for ICT and development comparative purposes and gather sets of countries with similar institutional backgrounds upon which the ICT and Development literature may rely on to explain different outcomes from public policies or investments on ICT in countries that share a common institutional background, as far as the institutional variable of federalism is concerned