Abstract: This study investigates how AlGaAs/GaAs thin film
solar cells perform under varying global solar spectrum due to the
changes of environmental parameters such as the air mass and the
atmospheric turbidity. The solar irradiance striking the solar cell is
simulated using the spectral irradiance model SMARTS2 (Simple
Model of the Atmospheric Radiative Transfer of Sunshine) for clear
skies on the site of Setif (Algeria). The results show a reduction in the
short circuit current due to increasing atmospheric turbidity, it is
63.09% under global radiation. However increasing air mass leads to
a reduction in the short circuit current of 81.73%. The efficiency
decreases with increasing atmospheric turbidity and air mass.
Abstract: Real time non-invasive Brain Computer Interfaces have a significant progressive role in restoring or maintaining a quality life for medically challenged people. This manuscript provides a comprehensive review of emerging research in the field of cognitive/affective computing in context of human neural responses. The perspectives of different emotion assessment modalities like face expressions, speech, text, gestures, and human physiological responses have also been discussed. Focus has been paid to explore the ability of EEG (Electroencephalogram) signals to portray thoughts, feelings, and unspoken words. An automated workflow-based protocol to design an EEG-based real time Brain Computer Interface system for analysis and classification of human emotions elicited by external audio/visual stimuli has been proposed. The front end hardware includes a cost effective and portable Emotiv EEG Neuroheadset unit, a personal computer and a set of external stimulators. Primary signal analysis and processing of real time acquired EEG shall be performed using MATLAB based advanced brain mapping toolbox EEGLab/BCILab. This shall be followed by the development of MATLAB based self-defined algorithm to capture and characterize temporal and spectral variations in EEG under emotional stimulations. The extracted hybrid feature set shall be used to classify emotional states using artificial intelligence tools like Artificial Neural Network. The final system would result in an inexpensive, portable and more intuitive Brain Computer Interface in real time scenario to control prosthetic devices by translating different brain states into operative control signals.