scholarly journals CUDAICA: GPU Optimization of Infomax-ICA EEG Analysis

2012 ◽  
Vol 2012 ◽  
pp. 1-8 ◽  
Author(s):  
Federico Raimondo ◽  
Juan E. Kamienkowski ◽  
Mariano Sigman ◽  
Diego Fernandez Slezak
Keyword(s):  
Computing Time ◽  
Multiple Channels ◽  
Function Calls ◽  
Eeg Data ◽  
Video Card ◽  
Gpu Optimization ◽  
Vector Processors ◽  
Vector Matrix ◽  
Cuda Kernel ◽  
Analyze Data

In recent years, Independent Component Analysis (ICA) has become a standard to identify relevant dimensions of the data in neuroscience. ICA is a very reliable method to analyze data but it is, computationally, very costly. The use of ICA for online analysis of the data, used in brain computing interfaces, results are almost completely prohibitive. We show an increase with almost no cost (a rapid video card) of speed of ICA by about 25 fold. The EEG data, which is a repetition of many independent signals in multiple channels, is very suitable for processing using the vector processors included in the graphical units. We profiled the implementation of this algorithm and detected two main types of operations responsible of the processing bottleneck and taking almost 80% of computing time: vector-matrix and matrix-matrix multiplications. By replacing function calls to basic linear algebra functions to the standard CUBLAS routines provided by GPU manufacturers, it does not increase performance due to CUDA kernel launch overhead. Instead, we developed a GPU-based solution that, comparing with the original BLAS and CUBLAS versions, obtains a 25x increase of performance for the ICA calculation.

Calculation of structure images of crystalline defects

1978 ◽  
Vol 36 (1) ◽  
pp. 282-283
Author(s):  
M.A. O'Keefe ◽  
Sumio Iijima
Keyword(s):  
Diffuse Scattering ◽  
Computing Time ◽  
Continuous Distribution ◽  
Sampling Interval ◽  
Reciprocal Space ◽  
Objective Lens ◽  
Lattice Images ◽  
Slice Method ◽  
Space Cell ◽  
Beam Lattice

We have extended the multi-slice method of computating many-beam lattice images of perfect crystals to calculations for imperfect crystals using the artificial superlattice approach. Electron waves scattered from faulted regions of crystals are distributed continuously in reciprocal space, and all these waves interact dynamically with each other to give diffuse scattering patterns.In the computation, this continuous distribution can be sampled only at a finite number of regularly spaced points in reciprocal space, and thus finer sampling gives an improved approximation. The larger cell also allows us to defocus the objective lens further before adjacent defect images overlap, producing spurious computational Fourier images. However, smaller cells allow us to sample the direct space cell more finely; since the two-dimensional arrays in our program are limited to 128X128 and the sampling interval shoud be less than 1/2Å (and preferably only 1/4Å), superlattice sizes are limited to 40 to 60Å. Apart from finding a compromis superlattice cell size, computing time must be conserved.

A New Numerical Model for Electron-Probe Analysis at High Depth Resolution

1996 ◽  
Vol 54 ◽  
pp. 490-491
Author(s):  
P.-F. Staub ◽  
C. Bonnelle ◽  
F. Vergand ◽  
P. Jonnard
Keyword(s):  
Electron Probe ◽  
Surface Segregation ◽  
Depth Distribution ◽  
Computing Time ◽  
Depth Resolution ◽  
Physical Parameters ◽  
Electron Probe Analysis ◽  
Interface Phases ◽  
Excitation Conditions ◽  
High Depth

Characterizing dimensionally and chemically nanometric structures such as surface segregation or interface phases can be performed efficiently using electron probe (EP) techniques at very low excitation conditions, i.e. using small incident energies (0.5<E0<5 keV) and low incident overvoltages (1<U0<1.7). In such extreme conditions, classical analytical EP models are generally pushed to their validity limits in terms of accuracy and physical consistency, and Monte-Carlo simulations are not convenient solutions as routine tools, because of their cost in computing time. In this context, we have developed an intermediate procedure, called IntriX, in which the ionization depth distributions Φ(ρz) are numerically reconstructed by integration of basic macroscopic physical parameters describing the electron beam/matter interaction, all of them being available under pre-established analytical forms. IntriX’s procedure consists in dividing the ionization depth distribution into three separate contributions:

The Relation Between Aerobic Fitness and Cognitive Performance

2016 ◽  
Vol 30 (3) ◽  
pp. 102-113 ◽  
Author(s):  
Chun-Hao Wang ◽  
Chun-Ming Shih ◽  
Chia-Liang Tsai
Keyword(s):  
Cognitive Performance ◽  
Aerobic Fitness ◽  
Reaction Times ◽  
Mediation Model ◽  
Brain Potentials ◽  
Fitness Level ◽  
Eeg Data ◽  
Attention Performance ◽  
P3 Amplitude ◽  
The Relationship

Abstract. This study aimed to assess whether brain potentials have significant influences on the relationship between aerobic fitness and cognition. Behavioral and electroencephalographic (EEG) data was collected from 48 young adults when performing a Posner task. Higher aerobic fitness is related to faster reaction times (RTs) along with greater P3 amplitude and shorter P3 latency in the valid trials, after controlling for age and body mass index. Moreover, RTs were selectively related to P3 amplitude rather than P3 latency. Specifically, the bootstrap-based mediation model indicates that P3 amplitude mediates the relationship between fitness level and attention performance. Possible explanations regarding the relationships among aerobic fitness, cognitive performance, and brain potentials are discussed.

Analysis of the Multi-Channel Epileptiform EEG Using the Markov Chains Formalism

1989 ◽  
Vol 28 (03) ◽  
pp. 160-167 ◽  
Author(s):  
P. Penczek ◽  
W. Grochulski
Keyword(s):  
Dynamic Behaviour ◽  
Joint Probability ◽  
Drug Effects ◽  
Anticonvulsant Drug ◽  
Channel System ◽  
Markov Network ◽  
Eeg Data ◽  
Multi Level ◽  
Joint Probability Functions ◽  
Dependent State

Abstract:A multi-level scheme of syntactic reduction of the epileptiform EEG data is briefly discussed and the possibilities it opens up in describing the dynamic behaviour of a multi-channel system are indicated. A new algorithm for the inference of a Markov network from finite sets of sample symbol strings is introduced. Formulae for the time-dependent state occupation probabilities, as well as joint probability functions for pairs of channels, are given. An exemplary case of analysis in these terms, taken from an investigation of anticonvulsant drug effects on EEG seizure patterns, is presented.

MOTIVASI MEMEDIASI PENGARUH PELATIHAN DAN LINGKUNGAN KERJA TERHADAP KINERJA KARYAWAN PT. TELKOM WITEL YOGYAKARTA

2020 ◽  
Vol 28 (1) ◽  
pp. 71-88
Author(s):  
Tyas Tunjung Sari ◽  
Pandu Nuansa Luhur
Keyword(s):  
Work Environment ◽  
Significant Influence ◽  
Structural Equation ◽  
Employee Performance ◽  
Partial Least Square ◽  
Least Square ◽  
Primary Data ◽  
Version 2.0 ◽  
Analyze Data

This study aims to determine the motivation of work to mediate the effect of training and work environment on employee performance at PT. Telkom Witel Yogyakarta Yogyakarta. The purpose of this study is to determine and analyze 1) the effect of training on employee performance at PT. Telkom Witel Yogyakarta 2) the effect of training on employee performance through motivation at PT. Telkom Witel Yogyakarta 3) the influence of the work environment on employee performance at PT. Telkom Witel Yogyakarta 4) the influence of the work environment on employee performance through motivation at PT. Telkom Witel Yogyakarta. This study uses primary data through research on 62 respondents. Structural Equation is used to analyze data, using PLS (Partial Least Square) version 2.0. The results of this study indicate that there are 1) positive and significant influence of training on employee performance 2) positive and significant influence of work environment on employee performance 3) positive and significant effect of training on employee performance through motivation 4) positive and significant influence of work environment on employee performance through motivation.

Machine Learning Verdict of EEG Signals in Brain Computer Interface

2018 ◽  
pp. 429-441
Author(s):  
M. Jeyanthi ◽  
C. Velayutham
Keyword(s):  
Nearest Neighbor ◽  
Technology Development ◽  
Vital Role ◽  
Svm Classifier ◽  
K Nearest Neighbor ◽  
Data Mining Technique ◽  
Data Set ◽  
Eeg Data ◽  
Irrelevant Attributes

In Science and Technology Development BCI plays a vital role in the field of Research. Classification is a data mining technique used to predict group membership for data instances. Analyses of BCI data are challenging because feature extraction and classification of these data are more difficult as compared with those applied to raw data. In this paper, We extracted features using statistical Haralick features from the raw EEG data . Then the features are Normalized, Binning is used to improve the accuracy of the predictive models by reducing noise and eliminate some irrelevant attributes and then the classification is performed using different classification techniques such as Naïve Bayes, k-nearest neighbor classifier, SVM classifier using BCI dataset. Finally we propose the SVM classification algorithm for the BCI data set.

Feelings of Figures in Novel Notes Juang Fiersa Besari (Personality Ludwig Klages)

2020 ◽  
Vol 8 (3) ◽  
pp. 13
Author(s):  
Faridatus Soleha
Keyword(s):  
Qualitative Approach ◽  
Personality Structure ◽  
Personality Theory ◽  
The Novel ◽  
Research Focus ◽  
The Third ◽  
Analyze Data

This study aims to describe the feelings of the characters in the novel Juang Notes by Fiersa Bersari and researchers analyze using personality theory originated by Ludwig Klages by focusing his study on the personality structure of feelings. Feeling is a process of someone accepting or rejecting something in life. This study uses a qualitative approach by using library techniques to obtain data that will produce a description of the words or sentences in the observed study. In the analysis of this research using the hermeutics technique, in the hermeutics technique there are several stages, namely reading the research object in this study in the form of a fighting journal, the second gives a mark on the data that has been obtained from the reading results, the third provides code or coding on the data that has been found, and the fourth is to analyze data that has been obtained from the object of research in accordance with the specified research focus. Novel Notes Juang by Fiersa Besari is a novel that can be used as an inspiration for readers in living life. Based on the results of the study it was found that in the Fighting Notes novel there is a feeling that is divided into inner activities and the level of clarity, inner activities in the novel in the form of fear and guilt while viewed from the level of clarity in the form of happiness, sadness and longing.

Mechanisms of liver damage in COVID-19

2020 ◽  
Vol 1 (19) ◽  
pp. 39-46
Author(s):  
T. V. Pinchuk ◽  
N. V. Orlova ◽  
T. G. Suranova ◽  
T. I. Bonkalo
Keyword(s):  
Hepatocellular Carcinoma ◽  
Liver Transplantation ◽  
Risk Factor ◽  
Liver Disease ◽  
Liver Function ◽  
Liver Damage ◽  
The World ◽  
Coronavirus Infection ◽  
The Impact ◽  
Analyze Data

At the end of 2019, a new coronavirus (SARS-CoV-2) was discovered in China, causing the coronavirus infection COVID-19. The ongoing COVID-19 pandemic poses a major challenge to health systems around the world. There is still little information on how infection affects liver function and the significance of pre-existing liver disease as a risk factor for infection and severe COVID-19. In addition, some drugs used to treat the new coronavirus infection are hepatotoxic. In this article, we analyze data on the impact of COVID-19 on liver function, as well as on the course and outcome of COVID-19 in patients with liver disease, including hepatocellular carcinoma, or those on immunosuppressive therapy after liver transplantation.

ANALISA DATA EKSPEDISI PAKET DENGAN MENERAPKAN ALGORITMA ROUGH SET (STUDI KASUS: JNE AGEN MENTENG MEDAN)

2019 ◽  
Vol 3 (1) ◽  
Author(s):  
Hasrat Selpia Simorangkir
Keyword(s):  
Data Mining ◽  
Rough Set ◽  
Microsoft Excel ◽  
General Rules ◽  
New Knowledge ◽  
Analyze Data

In analyzing data with data mining using the Rough Set algorithm which has results in the form of rules (rules). The process of determining the rules in the Rough Set method starts from processing the Microsoft Excel database, and continues testing with the Rough Set method. Thus producing General Rules which will become new knowledge in this research.With the existence of data mining using the rough set penilus algorithm, it can analyze data and provide solutions to the weaknesses faced in the menteng Medan field agents that have occurred so that it can be used as an alternative to solving problems in packet expedition encountered so far.Keyword: Data Mining, Descision System, Equivalen Class, ,General Rules, Rough set,Reduction

Sign in / Sign up

Export Citation Format

Share Document