scholarly journals The SME performance recommendation system facing the 4.0 industrial revolution uses the Fuzzy ANP method

2021 ◽  
Vol 1836 (1) ◽  
pp. 012036
Author(s):  
Y Kustiyahningsih ◽  
D R Anamisa ◽  
F A Mufarroha
Keyword(s):  
Recommendation System ◽  
Industrial Revolution ◽  
Fuzzy Anp

Awareness and Readiness of Malaysian University Students for Emotion Recognition System

2021 ◽  
Vol 13 (6) ◽  
Author(s):  
Nor Azlina Ab. Aziz ◽  
◽  
Nor Hidayati Abdul Aziz ◽  
Sharifah Noor Masidayu Sayed Ismail ◽  
Chy Tawsif Khan ◽  
...  
Keyword(s):  
University Students ◽  
Emotion Recognition ◽  
Smart Home ◽  
Recommendation System ◽  
Industrial Revolution ◽  
Recognition System ◽  
Facial Expression Analysis ◽  
Driving Assistance ◽  
Electrocardiogram Ecg ◽  
Electroencephalogram Eeg

Emotion Recognition System (ERS) identifies human emotion like happiness, sadness, anger, disgust and fear. These emotions can be detected via various modalities such as facial expression analysis, voice intonation, and physiological signals like the brain’s electroencephalogram (EEG) and heart’s electrocardiogram (ECG). The emotion recognition system allows machines to recognized human emotions and reacts to it. It offers broad areas of application, from smart home automation to entertainment recommendation system to driving assistance and to automated security system. It is a promising and interesting field to be explored especially as we are moving towards industrial revolution 5.0. Therefore, a survey was conducted on the awareness and readiness of the usage of emotion recognition system among Malaysian youths, specifically among university students. The findings are presented here. Overall, positive orientation towards the technology is observed among the participants and they are ready for its adoption

Energy, transport, and consumption in the Industrial Revolution

2019 ◽  
Vol 42 ◽  
Author(s):  
Joseph A. Tainter ◽  
Temis G. Taylor
Keyword(s):  
Mass Production ◽  
Industrial Revolution ◽  
Energy Transport ◽  
Underlying Assumption

Abstract We question Baumard's underlying assumption that humans have a propensity to innovate. Affordable transportation and energy underpinned the Industrial Revolution, making mass production/consumption possible. Although we cannot accept Baumard's thesis on the Industrial Revolution, it may help explain why complexity and innovation increase rapidly in the context of abundant energy.

The Industrial Revolution in Japan

1896 ◽  
Vol 41 (1054supp) ◽  
pp. 16840-16842
Author(s):  
William Eleroy Curtis
Keyword(s):  
Industrial Revolution

Analysis on Research Paper Publication Recommendation System with Composition of Papers and Conferences Matrices

2020 ◽  
pp. 120-127
Author(s):  
Htay Htay Win ◽  
Aye Thida Myint ◽  
Mi Cho Cho
Keyword(s):  
Social Network ◽  
Dimensionality Reduction ◽  
Correspondence Analysis ◽  
Recommendation System ◽  
Research Paper ◽  
Topic Modelling ◽  
Research Papers ◽  
The Right ◽  
Publication Recommendation

For years, achievements and discoveries made by researcher are made aware through research papers published in appropriate journals or conferences. Many a time, established s researcher and mainly new user are caught up in the predicament of choosing an appropriate conference to get their work all the time. Every scienti?c conference and journal is inclined towards a particular ?eld of research and there is a extensive group of them for any particular ?eld. Choosing an appropriate venue is needed as it helps in reaching out to the right listener and also to further one’s chance of getting their paper published. In this work, we address the problem of recommending appropriate conferences to the authors to increase their chances of receipt. We present three di?erent approaches for the same involving the use of social network of the authors and the content of the paper in the settings of dimensionality reduction and topic modelling. In all these approaches, we apply Correspondence Analysis (CA) to obtain appropriate relationships between the entities in question, such as conferences and papers. Our models show hopeful results when compared with existing methods such as content-based ?ltering, collaborative ?ltering and hybrid ?ltering.

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