The History, Geography, and Economics of America’s Early Computer Clusters, Part 2: Explanations

2016 ◽  
Vol 51 (4) ◽  
pp. 445-478
Author(s):  
Florencia Garcia-Vicente ◽  
Daniel D. Garcia-Swartz ◽  
Martin Campbell-Kelly
Keyword(s):  
Computer Clusters ◽  
Early Computer

The Hydra of Lerna: Economic-Geography Perspectives on America's Early Computer Clusters

2014 ◽  
Author(s):  
Florencia Garcia-Vicente ◽  
Daniel D. Garcia-Swartz ◽  
Martin Campbell-Kelly
Keyword(s):  
Economic Geography ◽  
Computer Clusters ◽  
Early Computer

The History, Geography, and Economics of America’s Early Computer Clusters, Part 1: Patterns

2016 ◽  
Vol 51 (3) ◽  
pp. 299-320 ◽  
Author(s):  
Florencia Garcia-Vicente ◽  
Daniel D. Garcia-Swartz ◽  
Martin Campbell-Kelly
Keyword(s):  
Computer Clusters ◽  
Early Computer

The History, Geography, and Economics of America’s Early Computer Clusters, Part 1: Patterns

2016 ◽  
Vol 51 (3) ◽  
pp. 299-320
Author(s):  
Florencia Garcia-Vicente ◽  
Daniel D. Garcia-Swartz ◽  
Martin Campbell-Kelly
Keyword(s):  
Computer Clusters ◽  
Early Computer

The History, Geography, and Economics of America’s Early Computer Clusters, Part 2: Explanations

2016 ◽  
Vol 51 (4) ◽  
pp. 445-478
Author(s):  
Florencia Garcia-Vicente ◽  
Daniel D. Garcia-Swartz ◽  
Martin Campbell-Kelly
Keyword(s):  
Computer Clusters ◽  
Early Computer

Using computer clusters for processing spatial-temporal data streams in data acquisition systems

2018 ◽  
Vol 935 (5) ◽  
pp. 54-63
Author(s):  
A.A. Maiorov ◽  
A.V. Materuhin ◽  
I.N. Kondaurov
Keyword(s):  
Data Acquisition ◽  
Data Streams ◽  
Spatial Data ◽  
High Performance ◽  
Temporal Data ◽  
Cyberphysical Systems ◽  
Software Environment ◽  
Computer Clusters ◽  
Data Acquisition Systems ◽  
Essential Components

Geoinformation technologies are now becoming “end-to-end” technologies of the new digital economy. There is a need for solutions for efficient processing of spatial and spatio-temporal data that could be applied in various sectors of this new economy. Such solutions are necessary, for example, for cyberphysical systems. Essential components of cyberphysical systems are high-performance and easy-scalable data acquisition systems based on smart geosensor networks. This article discusses the problem of choosing a software environment for this kind of systems, provides a review and a comparative analysis of various open source software environments designed for large spatial data and spatial-temporal data streams processing in computer clusters. It is shown that the software framework STARK can be used to process spatial-temporal data streams in spatial-temporal data streams. An extension of the STARK class system based on the type system for spatial-temporal data streams developed by one of the authors of this article is proposed. The models and data representations obtained as a result of the proposed expansion can be used not only for processing spatial-temporal data streams in data acquisition systems based on smart geosensor networks, but also for processing spatial-temporal data streams in various purposes geoinformation systems that use processing data in computer clusters.

Reverse time migration in tilted transversely isotropic media

2020 ◽  
Vol 38 (2) ◽  
Author(s):  
Razec Cezar Sampaio Pinto da Silva Torres ◽  
Leandro Di Bartolo
Keyword(s):  
Seismic Anisotropy ◽  
Synthetic Data ◽  
Transversely Isotropic ◽  
Reverse Time ◽  
Reverse Time Migration ◽  
Computer Clusters ◽  
Time Migration ◽  
Transversely Isotropic Media ◽  
Isotropic Media ◽  
Tti Media

ABSTRACT. Reverse time migration (RTM) is one of the most powerful methods used to generate images of the subsurface. The RTM was proposed in the early 1980s, but only recently it has been routinely used in exploratory projects involving complex geology – Brazilian pre-salt, for example. Because the method uses the two-way wave equation, RTM is able to correctly image any kind of geological environment (simple or complex), including those with anisotropy. On the other hand, RTM is computationally expensive and requires the use of computer clusters. This paper proposes to investigate the influence of anisotropy on seismic imaging through the application of RTM for tilted transversely isotropic (TTI) media in pre-stack synthetic data. This work presents in detail how to implement RTM for TTI media, addressing the main issues and specific details, e.g., the computational resources required. A couple of simple models results are presented, including the application to a BP TTI 2007 benchmark model.Keywords: finite differences, wave numerical modeling, seismic anisotropy. Migração reversa no tempo em meios transversalmente isotrópicos inclinadosRESUMO. A migração reversa no tempo (RTM) é um dos mais poderosos métodos utilizados para gerar imagens da subsuperfície. A RTM foi proposta no início da década de 80, mas apenas recentemente tem sido rotineiramente utilizada em projetos exploratórios envolvendo geologia complexa, em especial no pré-sal brasileiro. Por ser um método que utiliza a equação completa da onda, qualquer configuração do meio geológico pode ser corretamente tratada, em especial na presença de anisotropia. Por outro lado, a RTM é dispendiosa computacionalmente e requer o uso de clusters de computadores por parte da indústria. Este artigo apresenta em detalhes uma implementação da RTM para meios transversalmente isotrópicos inclinados (TTI), abordando as principais dificuldades na sua implementação, além dos recursos computacionais exigidos. O algoritmo desenvolvido é aplicado a casos simples e a um benchmark padrão, conhecido como BP TTI 2007.Palavras-chave: diferenças finitas, modelagem numérica de ondas, anisotropia sísmica.

Border Detection in Skin Lesion Images Using an Improved Clustering Algorithm

2020 ◽  
Vol 16 (4) ◽  
pp. 15-29
Author(s):  
Jayalakshmi D. ◽  
Dheeba J.
Keyword(s):  
Skin Cancer ◽  
Skin Lesion ◽  
Clustering Algorithm ◽  
Median Filter ◽  
Second Phase ◽  
Border Detection ◽  
Early Computer ◽  
Segmentation Methods ◽  
Two Phases ◽  
Skin Cancer Detection

The incidence of skin cancer has been increasing in recent years and it can become dangerous if not detected early. Computer-aided diagnosis systems can help the dermatologists in assisting with skin cancer detection by examining the features more critically. In this article, a detailed review of pre-processing and segmentation methods is done on skin lesion images by investigating existing and prevalent segmentation methods for the diagnosis of skin cancer. The pre-processing stage is divided into two phases, in the first phase, a median filter is used to remove the artifact; and in the second phase, an improved K-means clustering with outlier removal (KMOR) algorithm is suggested. The proposed method was tested in a publicly available Danderm database. The improved cluster-based algorithm gives an accuracy of 92.8% with a sensitivity of 93% and specificity of 90% with an AUC value of 0.90435. From the experimental results, it is evident that the clustering algorithm has performed well in detecting the border of the lesion and is suitable for pre-processing dermoscopic images.

Early Computer Developments in Madrid

1982 ◽  
Vol 4 (1) ◽  
pp. 31-34
Author(s):  
Jose Garcia Santesmases
Keyword(s):  
Early Computer

scholarly journals Optimum off-line trace synchronization of computer clusters

2012 ◽  
Vol 341 ◽  
pp. 012029 ◽  
Author(s):  
Masoume Jabbarifar ◽  
Michel Dagenais ◽  
Robert Roy ◽  
Alireza Shameli Sendi
Keyword(s):  
Computer Clusters ◽  
Line Trace
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