Fuzzy logic approach for detecting drivers’ drowsiness based on image processing and Video streaming

<p>The driver's face is detected and extracted extra features of the eyes and mouth areas. Start the analysis process to determine the status of these parameters. Second, the Kalman filter method is used to track and manipulate the difference in the size and orientation of the captured features. The technique checks all image states such as brightness, shadows, and clarity. Third, the blur control system provides different alert sounds based on the information tracked from the face, eyes, and mouth. The proposed method uses real-time data recorded by a webcam tool in the MatlabR2016a environment. The data sample contains videos of different users of different races, whether they wear glasses, gender, and various lighting backgrounds. The proposed system achieved an accuracy of up to 94.5% in the detection driver status.</p>

Fuzzy logic approach for detecting drivers’ drowsiness based on image processing and Video streaming

<p>The driver's face is detected and extracted extra features of the eyes and mouth areas. Start the analysis process to determine the status of these parameters. Second, the Kalman filter method is used to track and manipulate the difference in the size and orientation of the captured features. The technique checks all image states such as brightness, shadows, and clarity. Third, the blur control system provides different alert sounds based on the information tracked from the face, eyes, and mouth. The proposed method uses real-time data recorded by a webcam tool in the MatlabR2016a environment. The data sample contains videos of different users of different races, whether they wear glasses, gender, and various lighting backgrounds. The proposed system achieved an accuracy of up to 94.5% in the detection driver status.</p>

Fuzzy logic approach for detecting drivers’ drowsiness based on image processing and Video streaming

<p>The driver's face is detected and extracted extra features of the eyes and mouth areas. Start the analysis process to determine the status of these parameters. Second, the Kalman filter method is used to track and manipulate the difference in the size and orientation of the captured features. The technique checks all image states such as brightness, shadows, and clarity. Third, the blur control system provides different alert sounds based on the information tracked from the face, eyes, and mouth. The proposed method uses real-time data recorded by a webcam tool in the MatlabR2016a environment. The data sample contains videos of different users of different races, whether they wear glasses, gender, and various lighting backgrounds. The proposed system achieved an accuracy of up to 94.5% in the detection driver status.</p>

Influence of exposure to high muscularity bodies on muscularity preferences and body satisfaction in young men.

The visual diet hypothesis suggests that exposure to a certain body type increases our preference for that type of body, and exposure to ideal bodies is proposed to lead to body dissatisfaction. Here we examined the effect of exposure to high/low muscularity bodies on muscularity preferences and, subsequently, on body satisfaction in men, as well as exploring how men’s pre-existing cognitions around their bodies might moderate susceptibility to these effects. Study 1 participants (80 women, 84 men) viewed high or low muscularity images of real and CGI male bodies and reported their preferences for pairs of bodies varying in muscularity before and after. They additionally completed the Sociocultural Attitudes Towards Appearance Questionnaire 4. Data replicated previous results showing that viewing low muscularity images reduces preferences for muscularity in participants. This was significantly moderated by SATAQ in men, such that those with higher internalisation of cultural body ideals (higher SATAQ scores) showed this effect more strongly. In Study 2, participants (81 Men) completed the same task, with the change that some viewed the CGI bodies, and some the real bodies, during the manipulation, and also completed the Drive for Muscularity Scale at pre-test and the Body Image States Scale at pre- and post-test. Results again showed that exposure to low muscularity bodies reduces muscularity preferences but there was no moderating effect of SATAQ or of drive for muscularity. There was also no impact of viewing the images on body satisfaction.

PURCHASE DECISION BETWEEN CONSUMER LOYALTY AND BRAND IMAGE

This study aims to determine and analyze the effect of consumer loyalty and brand image onseafood food purchasing decisions. The analytical tool used in this study is multiple linearregression analysis, T-Test and F-Test and Determination Coefficient. With SPSS The resultsof the research show that partially consumer loyalty and brand image influence the decisionto buy seafood. Likewise, the results of other hypothesis tests indicate that simultaneously theindependent variable of consumer loyalty and brand image influences buying decisions. Thusthe results of this hypothesis test are in line with several previous studies. Consumer loyalty isthe commitment of customers to a brand, store, or supplier based on the very positive natureof long-term purchases, whereas brand image states that a brand has strong roots when thebrand is associated with values that represent or are desired by consumers.