Estimation of the relationship between the sacral hiatus and other dorsal sacral parameters using principle component analysis

2021 ◽  
Author(s):  
Binita Chaudhary ◽  
Adil Asghar ◽  
Shagufta Naaz ◽  
Abhigyan Satyam
Keyword(s):  
Principle Component Analysis ◽  
Component Analysis ◽  
Principle Component ◽  
Sacral Hiatus ◽  
The Relationship

scholarly journals HUBUNGAN ANTARA SEDIMEN DENGAN LOGAM BERAT DAN MAKROZOOBENTOS DI SUNGAI SIANGKER, SEMARANG

2016 ◽  
Vol 5 (4) ◽  
pp. 337-344
Author(s):  
Arini Indah Lestari ◽  
Mustofa Niti Supardjo ◽  
Boedi Hendrarto
Keyword(s):  
Heavy Metals ◽  
Principle Component Analysis ◽  
Random Sampling ◽  
Pearson Correlation ◽  
Drainage System ◽  
Component Analysis ◽  
Sediment Characteristics ◽  
The West ◽  
Principle Component ◽  
The Relationship

ABSTRAK Sungai Siangker merupakan salah satu sub sistem dari sistem drainase Semarang Barat yang mengalami pendangkalan.Limbah yang berasal dari pabrik diduga mengandung logam berat Pb dan Cd. Oleh karena itu, penelitian ini diadakan untuk mengetahui kadar logam berat Pb dan Cd dan hubungan antara sedimen serta kandungan logam berat Pb dan Cd dengan komunitas makrozoobentos. Pengambilan sampel dilakukan secara random  sampling. PCA (Principle Component Analysis) digunakan untuk mengetahui kedekatan hubungan antara makrozoobentos, nilai bahan organik dan karakteristik sedimen.Perbedaan variabel tiap stasiunnya diuji dengan Uji Kruskal-Wallis. Korelasi Pearson digunakan untuk menganalisis hubungan antara variabel kelimpahan, keanekaragaman, kadar logam berat dan karakteristik sedimen di tiap stasiunnya. Hasil rerata yang diperoleh dari analisa kadar logam berat (Pb) di muara dan sungai Siangker adalah 1,10 – 1,64 mg/l,  sedangkan untuk rerata (Cd) sebesar 0,13 – 0,43 mg/l. Kadar debu mempunyai korelasi positif yang erat (p < 0,05) dengan keanekaragaman dan kelimpahan makrozoobentos. Kadar logam berat berpengaruh nyata (p < 0,05) terhadap keanekaragaman maupun kelimpahan makrozoobentos. Kata Kunci : Sungai, logam berat, karakteristik sedimen, makrozoobentos  ABSTRACTSiangker river is one of the sub-systems of the West Semarang drainage system that experiencing siltation. Waste from the factories is suspected to contain heavy metals (Pb) and (Cd). This study was conducted to understand concentration of Pb and Cd and the relationship between characteristics of the sediments containing heavy metals (Pb) and (Cd) as well as macrozoobenthos community. Sampling was done by random sampling. PCA (Principle Component Analysis) was used to determine proximity of the relationships between macrozoobenthos and the value of organic matter as well as sediment characteristics. Meanwhile, the differences in the station of each variable was tested using Kruskal-Wallis test. Pearson correlation was used to analyze the relationship between abundance variables, diversity, the levels of heavy metals and sediment characteristics in each station. The results showed that the levels of heavy metals (Pb) in the estuary and  river Siangker were  1,10 to 1,64 mg / l, while concentration of  (Cd) is 0,13 to 0,43 mg / l. Dust levels were closely positively correlated (p < 0,05) with the diversity and abundance of macrozoobenthos. Levels of heavy metals was significant (p < 0,05) for the diversity and abundance of macrozoobenthos.     Keywords : River, heavy metal, sediment characteristic, macrozoobenthos

ANALYSIS OF VOICE CUES IN RECOGNITION OF SARCASM

2019 ◽  
Vol 12 ◽  
Author(s):  
Basavaraj N Hiremath ◽  
Malini M Patilb
Keyword(s):  
Feature Extraction ◽  
Computer Program ◽  
Principle Component Analysis ◽  
Voice Recognition ◽  
Component Analysis ◽  
Recognition System ◽  
Principle Component ◽  
Whole Process ◽  
The Voice

The voice recognition system is about cognizing the signals, by feature extraction and identification of related parameters. The whole process is referred to as voice analytics. The paper aims at analysing and synthesizing the phonetics of voice using a computer program called “PRAAT”. The work carried out in the paper also supports the analysis of voice segmentation labelling, analyse the unique features of voice cues, understanding physics of voice, further the process is carried out to recognize sarcasm. Different unique features identified in the work are, intensity, pitch, formants related to read, speak, interactive and declarative sentences by using principle component analysis.

Four challenges for cognitive neuroscience and the cortico-hippocampal division of memory

2003 ◽  
Vol 26 (6) ◽  
pp. 681-682
Author(s):  
Harry Howard
Keyword(s):  
Independent Component Analysis ◽  
Recent Work ◽  
Cognitive Neuroscience ◽  
Principle Component Analysis ◽  
Pattern Analysis ◽  
Component Analysis ◽  
Independent Component ◽  
Principle Component ◽  
Complementary Methods ◽  
Current State

Jackendoff's criticisms of the current state of theorization in cognitive neuroscience are defused by recent work on the computational complementarity of the hippocampus and neocortex. Such considerations lead to a grounding of Jackendoff's processing model in the complementary methods of pattern analysis effected by independent component analysis (ICA) and principle component analysis (PCA).

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