Analyzing the difference evolution of provincial energy consumption in China using the functional data analysis method

2021 ◽  
pp. 105753
Author(s):  
You Wang ◽  
Xu Gong
Keyword(s):  
Energy Consumption ◽  
Data Analysis ◽  
Functional Data Analysis ◽  
Functional Data ◽  
Analysis Method ◽  
Data Analysis Method ◽  
The Difference

A Key Parameters Analysis Method of the Quality Control in the Semiconductor Multiple Manufacturing Processes Based on Functional Data Analysis Method

2010 ◽  
Vol 139-141 ◽  
pp. 1660-1665
Author(s):  
Yang Liu ◽  
Zhi Sheng Zhang ◽  
Jin Fei Shi
Keyword(s):  
Quality Control ◽  
Data Analysis ◽  
Functional Data Analysis ◽  
Functional Data ◽  
Test Method ◽  
Quality Characteristic ◽  
Manufacturing Processes ◽  
Analysis Method ◽  
Product Lines ◽  
Data Analysis Method

The quality of the semiconductor products is defined by a series of the key performance parameters which have some certain relations to the electronic test parameters generated among the multiple manufacturing processes. Aimed at the quality control problem of the multiple manufacturing processes, a FDA (functional data analysis) method has been used and got the mapping relationship between the process parameters of the product lines and the product quality characteristic. A simple Change-Point hypothesis has been tested to analyze the data curves generated by the FDA method, and the key process variables have been found. Then, the equalization between the new test result and the old one has been verified by the Kolmogorov-Smirnov 2-sample test method. Some multiple manufacturing processes test data, which was collected from a semiconductor product workshop, has been modeled and analyzed. And the analysis results can illustrate the key factors of the process quality control in the multiple manufacturing processes and approach the reduction of the test times and the improvement of the efficiency and effectiveness of the equipment.

LIBS quantitative analysis method for samples with changing temperature via functional data analysis

2021 ◽  
Author(s):  
Fu Chang ◽  
Jianhong Yang ◽  
Huili Lu ◽  
Haixia Li
Keyword(s):  
Data Analysis ◽  
Quantitative Analysis ◽  
Functional Data Analysis ◽  
Functional Data ◽  
Laser Induced Breakdown Spectroscopy ◽  
Calibration Model ◽  
Analysis Method ◽  
Breakdown Spectroscopy ◽  
Laser Induced Breakdown ◽  
Quantitative Analysis Method

The quantitative analysis accuracy of laser-induced breakdown spectroscopy (LIBS) will decrease if the temperatures of testing samples are different from the temperature under which the calibration model is established. For...

scholarly journals Penanda Jamak Bahasa Indonesia dan Bahasa Arab pada Aspek Sintaksis (Analisis Kontrastif) [The Markers of the Plural Meaning of Indonesian and Arabian Language on Syntactical Aspects (Contrastive Analysis)]

JALABAHASA ◽  
2021 ◽  
Vol 17 (1) ◽  
pp. 42-55
Author(s):  
Sofia Nur Khasanah ◽  
Imam Baehaqie
Keyword(s):  
Data Analysis ◽  
Data Collection ◽  
Analysis Method ◽  
Contrastive Analysis ◽  
Data Analysis Method ◽  
Similarities And Differences ◽  
The Difference ◽  
Observation Method ◽  
Bahasa Indonesia

Analisis kontrastif antara dua bahasa atau lebih dimaksudkan untuk memberikan penjelasan yang objektif tentang perbedaan kaidah antara dua bahasa atau lebih yang diperbandingkan. Penelitian ini mengidentifikasi pembentukan makna jamak secara sintaksis dalam bahasa Indonesia dan bahasa Arab, kemudian membandingkannya. Tujuan penelitian ini adalah mengetahui persamaan dan perbedaan penanda makna jamak bahasa Indonesia dan bahasa Arab. Pengumpulan data dilakukan dengan menggunakan metode simak dengan teknik simak bebas libat cakap. Analisis data dilakukan dengan metode agih dan padan. Hasil penelitian ini menunjukkan makna jamak secara sintaksis dalam bahasa Indonesia dan bahasa Arab dibentuk dengan adanya kata sandang, numeralia, adverbia, dan kata yang bermakna jamak secara leksikal tanpa penanda. Keempat penanda tersebut ditemukan dalam kaidah pembentukan jamak bahasa Indonesia, tetapi dalam bahasa Arab hanya ditemukan penanda berupa numeralia dan kata yang bermakna jamak secara leksikal. Contrastive analysis between two or more languages is intended to provide an objective explanation of the difference law between two or more languages being compared. This study identifies the formation of plural meanings syntactically in Indonesian and Arabic. The purpose of this study was to determine the similarities and differences in the plural meaning markers of Indonesian and Arabic. The methods of data collection used was the observation method with the simak bebas libat cakap technique. The data analysis method used agih and padan methods respectively. The results of this study show that the syntactic plural meaning in Indonesian and Arabic is formed by the presence of the article, numeralia, adverbial, and words that have the lexical plural meaning without a marker. The four markers are found in the rules for the formation of the Indonesian plural, but in Arabic, only a marker is found in the form of a numeralia and a word that has a lexical plural meaning.

scholarly journals Equilibrio competitivo en Liga española de futbol de Primera División: Un test de Montecarlo basado en datos funcionales

2020 ◽  
Vol 30 (2) ◽  
pp. 513
Author(s):  
Francisco Montes ◽  
Ramón Sala
Keyword(s):  
Monte Carlo ◽  
Data Analysis ◽  
Functional Data Analysis ◽  
Functional Data ◽  
Common Factor ◽  
The Other ◽  
Monte Carlo Test ◽  
Uniform Probability Distribution ◽  
European Football ◽  
The Difference

The supremacy of a few teams over the other participants is a common factor in the major European football leagues. The Spanish First Division league is not an exception. In order to demonstrate this fact, functional data analysis is used to analyze football league classifications for last ten seasons, 2002-03 to 2011-12. Not only the use of these techniques distinguish this work from similar, another distinctive feature is the use of a non-uniform probability distribution on the three possible outcomes of a match, obtained from the results of the 3800 matches of the 10 seasons taking into account the difference between the categories of the teams in the match. A Monte Carlo test allows to test the hypotheses of uniformity and non-uniformity in the results.

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