scholarly journals Factors Underlie Selfie Addiction: Developing and Validating a Scale

2020 ◽  
Vol 7 (1) ◽  
pp. 82
Author(s):  
Khalid Ismail Mustafa ◽  
Zhwan Dalshad Abdullah ◽  
Renas Osman Abdulrahman ◽  
Azad Ali Ismail
Keyword(s):  
Social Media ◽  
Gender Difference ◽  
University Students ◽  
Principle Component Analysis ◽  
Component Analysis ◽  
Principle Component ◽  
Self Acceptance

This study aimed at investigating the underlying factors of selfie addiction among university students. It further attempted to find out the role of gender difference in selfie addiction. A 19-item self-developed questionnaire used to measure selfie addiction. The questionnaire was validated using a sample of 269 randomly selected university students. Principle Component Analysis (PCA) was conducted to test the validity of the questionnaire. The results revealed three underlined factors which were: Intention, Self-Obsessed, and Self-Acceptance. The results also indicated that females are more addicted with respect to selfies on social media than their males.

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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