نتایج جستجو برای: functional principal component analysis

تعداد نتایج: 3758525  

Journal: :desert 2012
e. fattahi k. noohi h. shiravand

as widespread deserts is located in west and southwest of iran plateau, dust storms form due to west andsouthwest systems over syria or iraq as well as arabian peninsula. these systems severely affect west and southwestregions. sometimes the fine dusts transmit to central, north east, and east regions. in this study for investigating dustysynoptical patterns, meteorological data at 5 synoptic s...

Journal: :future of medical education journal 0
masoumeh nazari chamak student research assembly, kerman university of medical science, kerman, iran khodadad sheikhzadeh regional knowledge hub and who collaborating centre for hiv surveillance, institute for futures studies in health, kerman university of medical sciences, kerman, iran ali akbar haghdoost regional knowledge hub for hiv/aids surveillance, research centre for modelling in health, institute for future studies in health, kerman university of medical sciences, kerman, iran

background: in order to check the practicality of classification of universities of medical sciences (umss) based on their infrastructures, and scientific contributions, this study explored the most appropriate indicators to measure the size and productivity of umss. methods: in the first phase, we approached a group of experts who had a deep experience in the management of umss and in the mini...

2010
Han Lin Shang

This paper uses half-hourly electricity demand data in South Australia as an empirical study of nonparametric modeling and forecasting methods for prediction from half-hour ahead to one year ahead. A notable feature of the univariate time series of electricity demand is the presence of both intraweek and intraday seasonalities. An intraday seasonal cycle is apparent from the similarity of the d...

2015
Federico Visi Esther Coorevits Rodrigo Schramm Eduardo Miranda

Body movement and embodied knowledge play an important part in how we express and understand music. The gestures of a musician playing an instrument are part of a shared knowledge that contributes to musical expressivity by building expectations and influencing perception. In this study, we investigate the extent in which the movement vocabulary of violin performance is part of the embodied kno...

2012
Kehui Chen

We introduce a new methodological framework for repeatedly observed and thus dependent functional data, aiming at situations where curves are recorded repeatedly for each subject in a sample. Our methodology covers the case where the recordings of the curves are scheduled on a regular and dense grid and also situations more typical for longitudinal studies, where the timing of recordings is oft...

Journal: :Reliability Engineering & System Safety 2021

Motivated by risk assessment of coastal flooding, we consider time-consuming simulators with a spatial output. The aim is to perform sensitivity analysis (SA), quantifying the influence input parameters on There are three main issues. First, due computational time, standard SA techniques cannot be directly applied simulator. Second, output infinite dimensional, or at least high dimensional if d...

Journal: :Front. Robotics and AI 2017
Giuseppe Averta Cosimo Della Santina Edoardo Battaglia Federica Felici Matteo Bianchi Antonio Bicchi

The rich variety of human upper limb movements requires an extraordinary coordination of different joints according to specific spatio-temporal patterns. However, unvealing these motor schemes is a challenging task. Principal components have been often used for analogous purposes, but such an approach relies on hypothesis of temporal uncorrelation of upper limb poses in time. To overcome these ...

A. K. Wadhwani Manish Dubey, Monika Saraswat

The principle of dimensionality reduction with PCA is the representation of the dataset ‘X’in terms of eigenvectors ei ∈ RN  of its covariance matrix. The eigenvectors oriented in the direction with the maximum variance of X in RN carry the most      relevant information of X. These eigenvectors are called principal components [8]. Ass...

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