Articles — Recent

Event Related Potentials (ERP) have proven a valuable tool in understanding the neural base of language processing during the past decades. In this presentation, we focus on one of the most important ERP, the N400. We simulate a small experiment in class and explain the different linguistic contexts in which it appears.

Bachelor thesis on Upscaling the extracellular glucose oxidase production in Aspergillus niger var tubingensis strain Ed8 Grade: ~95% Abbreviation system included.

6.867 Machine Learning Homework 2 (fall 2015)

Colorectal cancer and phytochemicals

The research system in Germany

This report provides insight into the magnetic phenomenon of Hysteresis. Hysteresis is defined as a retardation effect where the magnetisation of a magnetic material lags behind the magnetizing force. Here we will explore the hysteresis loop for a silver steel ferromagnet and use this to discover it’s magnetic properties. The method used will be to place a ferromagnet inside a solenoid with an alternating voltage which will continually reverse the magnetic field and magnetism direction. The relation between these two quantities will be used to produce a hysteresis loop from which magnetic properties can be deduced. The results obtained were: saturation magnetisation = (8.4±0.5)(105)Am-1; remnant magnetisation = (5.9±0.5)(105)Am-1; coercive field: (4.3±0.5)(104)Am-1; energy expended per cycle per unit volume of material: (1.55±0.05)(103)Jm-3s-1; energy product: (8.7±3.0)(104)Jm-3.

Gabriel Antelo's Curriculum Vitae. Created with the ModernCV template.

The Loewner Equation and the derivative of its solution

Image reconstruction is observed to be one of the most common problem because of it's large data movement and non-trivial data dependencies. In the past, these problems were tackled by many high performance hardware such as FPGA's and GPGPU's. This also reflects the investemts to be made in these supercomputers for real time reconstruction of clinical computed tomography (CT) applications. Medical imaging systems are employing high performance computing (HPC) technology to meet their time constraints. This paper presents different optimizations to the volume reconstruction and implement it on a commodity hardware such as x86 based multicore system. This paper chooses to perform its implementaion on Intel Xeon X5365 multicore processor. We perform different levels of parallelization and analyse each of them and report their results with respect to serial implementation. The objective of this paper is to understand the constraints of volume reconstruction in multicore architecture and optimize them while preserving the quality of the reconstructed image.