TensorFlow Enabled Genetic Programming

Genetic Programming, a kind of evolutionary computation and machine learning algorithm, is shown to benefit significantly from the application of vectorized data and the TensorFlow numerical computation library on both CPU and GPU architectures. The open source, Python Karoo GP is employed for a series of 190 tests across 6 platforms, with real-world datasets ranging from 18 to 5.5M data points. This body of tests demonstrates that datasets measured in tens and hundreds of data points see 2-15x improvement when moving from the scalar/SymPy configuration to the vector/TensorFlow configuration, with a single core performing on par or better than multiple CPU cores and GPUs. A dataset composed of 90,000 data points demonstrates a single vector/TensorFlow CPU core performing 875x better than 40 scalar/Sympy CPU cores. And a dataset containing 5.5M data points sees GPU configurations out-performing CPU configurations on average by 1.3x.Comment: 8 pages, 5 figures; presented at GECCO 2017, Berlin, German

Dosimetry, Personal Monitoring Film

The article focuses on radiation dosimetry, which made use of the photographic film known as Type 2 Monitoring Film (Kodak) to detect and measure harmful ionizing radiation. It explores the implications of the demise of this technology in relation to Henri Van Lier's critique of photographic indexicality in his paper "Towards a Philosophy Instigated by Photography". It notes that the demise of indexical theories of photographic film can be aligned to the demise of the personal monitoring film. It states that dosimetry reveals the limitation of energetic effects in a superabundant field

Multiscale computational analysis of the bioelectric consequences of myocardial ischaemia and infarction

[EN] Ischaemic heart disease is considered as the single most frequent cause of death, provoking more than 7 000 000 deaths every year worldwide. A high percentage of patients experience sudden cardiac death, caused in most cases by tachyarrhythmic mechanisms associated to myocardial ischaemia and infarction. These diseases are difficult to study using solely experimental means due to their complex dynamics and unstable nature. In the past decades, integrative computational simulation techniques have become a powerful tool to complement experimental and clinical research when trying to elucidate the intimate mechanisms of ischaemic electrophysiological processes and to aid the clinician in the improvement and optimization of therapeutic procedures. The purpose of this paper is to briefly review some of the multiscale computational models of myocardial ischaemia and infarction developed in the past 20 years, ranging from the cellular level to whole-heart simulations.This work was partially supported by the 'VI Plan Nacional de Investigacion Cientifica, Desarrollo e Innovacion Tecnologica' from the Ministerio de Economia y Competitividad of Spain (grant number TIN2012-37546-C03-01) and the European Commission (European Regional Development Funds-ERDF-FEDER), and by the Direccion General de Politica Cientifica de la Generalitat Valenciana (grant number GV/2013/119).Ferrero De Loma-Osorio, JM.; Trénor Gomis, BA.; Romero Pérez, L. (2014). Multiscale computational analysis of the bioelectric consequences of myocardial ischaemia and infarction. EP-Europace. 16(3):405-415. https://doi.org/10.1093/europace/eut405S40541516