scholarly journals Word discovery with beta process factor analysis

2012 ◽  
Author(s):  
Niklas Vanhainen ◽  
Giampiero Salvi
Keyword(s):  
Factor Analysis ◽  
Process Factor ◽  
Beta Process

scholarly journals Gaussian-Process Factor Analysis for Low-Dimensional Single-Trial Analysis of Neural Population Activity

2009 ◽  
Vol 102 (1) ◽  
pp. 614-635 ◽  
Author(s):  
Byron M. Yu ◽  
John P. Cunningham ◽  
Gopal Santhanam ◽  
Stephen I. Ryu ◽  
Krishna V. Shenoy ◽  
...  
Keyword(s):  
Factor Analysis ◽  
Gaussian Process ◽  
Predictive Ability ◽  
Neural Population ◽  
Single Trial ◽  
Two Stage ◽  
Population Activity ◽  
Process Factor ◽  
Low Dimensional ◽  
Neural Population Activity

We consider the problem of extracting smooth, low-dimensional neural trajectories that summarize the activity recorded simultaneously from many neurons on individual experimental trials. Beyond the benefit of visualizing the high-dimensional, noisy spiking activity in a compact form, such trajectories can offer insight into the dynamics of the neural circuitry underlying the recorded activity. Current methods for extracting neural trajectories involve a two-stage process: the spike trains are first smoothed over time, then a static dimensionality-reduction technique is applied. We first describe extensions of the two-stage methods that allow the degree of smoothing to be chosen in a principled way and that account for spiking variability, which may vary both across neurons and across time. We then present a novel method for extracting neural trajectories—Gaussian-process factor analysis (GPFA)—which unifies the smoothing and dimensionality-reduction operations in a common probabilistic framework. We applied these methods to the activity of 61 neurons recorded simultaneously in macaque premotor and motor cortices during reach planning and execution. By adopting a goodness-of-fit metric that measures how well the activity of each neuron can be predicted by all other recorded neurons, we found that the proposed extensions improved the predictive ability of the two-stage methods. The predictive ability was further improved by going to GPFA. From the extracted trajectories, we directly observed a convergence in neural state during motor planning, an effect that was shown indirectly by previous studies. We then show how such methods can be a powerful tool for relating the spiking activity across a neural population to the subject's behavior on a single-trial basis. Finally, to assess how well the proposed methods characterize neural population activity when the underlying time course is known, we performed simulations that revealed that GPFA performed tens of percent better than the best two-stage method.

scholarly journals Geo-environmental analysis of the groundwater quality in the vicinity of textile industrial zone

2021 ◽  
Vol 2070 (1) ◽  
pp. 012188
Author(s):  
K Arumugam ◽  
T Karthika ◽  
M Kartic Kumar ◽  
R K. Sangeetha ◽  
T Anitha ◽  
...  
Keyword(s):  
Water Quality ◽  
Factor Analysis ◽  
Groundwater Quality ◽  
Anthropogenic Activities ◽  
Economic Behavior ◽  
Subsurface Water ◽  
Industrial Zone ◽  
Rock Interaction ◽  
Process Factor ◽  
Two Samples

Abstract The increase in inhabitants and development of advantageous economic behavior undoubtedly leads to escalating water demand for different uses. Improper planning, mismanagement, inappropriate standards and procedure for discharging the industrial effluents are prime causes for deterioration of groundwater quality in industrial zone. The study vicinity is exaggerated by subsurface water quality problem. To evaluate the water quality of aquifer, sixty two samples were collected, analyzed and the results of the data are evaluated according to the standards. Hydro-chemical facies, rock-water process, factor analysis, correlation matrix studies were carried out for assessing the associated hydro-chemical process operating in the progress of salinity concentration. The analysis reveals that water belongs to highly brackish type. In this study zone, groundwater is influenced by water-rock interaction and evaporation process. Factor analysis shows that the groundwater is greatly deteriorated by anthropogenic activities. Based on hyrochemical study, the subsurface water is not fit for domestic purposes.

scholarly journals Analisis Faktor-Faktor Yang Dipertimbangkan Konsumen Dalam Keputusan Pembelian Minyak Goreng Bimoli Di Pasar Swalayan Kabupaten Wonogiri

2018 ◽  
Vol 15 (1) ◽  
pp. 39
Author(s):  
Yenny Sundari ◽  
Mohd. Harisudin ◽  
Agustono Agustono
Keyword(s):  
Factor Analysis ◽  
Psychological Factors ◽  
Secondary Data ◽  
Primary Data ◽  
Individual Factor ◽  
Process Factor ◽  
Packing Factor ◽  
Cooking Oil ◽  
Process Factors ◽  
Product Factor

<em>The research aims to find out the considered factors and the dominant variables which considered by consumers into buying Bimoli’s cooking oil at supermarket in Wonogiri regency. The basic method in this research is analytical descriptive with survey techniques. Location research purposively determined. The sampling method used was judgment sampling and data analysis method used is factor analysis. The data used are primary data and secondary data. The results of factor analysis  showed that  there  are  7 factors  that  become  consumer  consideration  in buying Bimoli cooking oil product at supermarket in Wonogiri regency. The seven factors are based on their priorities are product factors, individual factors, promotion factors, packaging factors, process factors, place factors, and psychological factors. The  dominant  variables  considered  by  consumer  are  clarity  variable  on  product factor, variable of income level on individual factor, advertisement display variable on promotion factor, image variable and color of packaging on packing factor, service variable on process factor, comfort variable at place factor, and Confidence variable on psychological factors.</em>

Analytic Standard Errors for Exploratory Process Factor Analysis

Psychometrika ◽  
2014 ◽  
Vol 79 (3) ◽  
pp. 444-469 ◽  
Author(s):  
Guangjian Zhang ◽  
Michael W. Browne ◽  
Anthony D. Ong ◽  
Sy Miin Chow
Keyword(s):  
Factor Analysis ◽  
Standard Errors ◽  
Process Factor

Characterization of controlling hydrogeochemical processes using factor analysis in Puyang Yellow River irrigation district (China)

2016 ◽  
Vol 48 (5) ◽  
pp. 1438-1454 ◽  
Author(s):  
Wenjia Wang ◽  
Xianfang Song ◽  
Ying Ma
Keyword(s):  
Factor Analysis ◽  
Yellow River ◽  
Groundwater Chemistry ◽  
Hydrogeochemical Processes ◽  
Irrigation District ◽  
Total Variance ◽  
Data Set ◽  
Rock Interaction ◽  
Process Factor ◽  
Interaction Factor

Groundwater chemistry is diverse and complicated and is regulated by both natural hydrogeochemical and anthropogenic processes. Determining the governing processes and their influence on groundwater chemistry is very important to understand groundwater quality evolution and establish reasonable water management strategies. Main cations (Ca2+, Mg2+, Na+, K+, and Sr2+), anions (Cl−, SO2−4, HCO−3, NO−3, and F−), and SiO2 and UV254 of 50 shallow groundwater samples were treated and analyzed. Factor analysis combined with ionic ratio and correlation analysis was used to identify the major hydrogeochemical processes responsible for the variation of hydrochemical components. Approximately 76% of the total variance of the data set can be explained by the four factors identified. Composing of Sr2+, Mg2+, Ca2+, and electrical conductivity (EC), Factor 1 accounted for 25.67% of the total variances, and represented groundwater formation background and fundamental water–soil/rock interaction. Factor 2 with high loadings on NO−3, U(Cl−, SO2−4, HCO−3, NO−3, and F−), and F−)254, and F−, was related to anthropogenic activities, especially the release of domestic sewage and industrial effluents. Factor 3 composed of Na+, HCO−3 and EC was interpreted as cation exchange process. Factor 4 explained 15.75% of the total variance, and was attributed to the influence of agricultural activities, especially chemical fertilizer application.

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