We propose novel vehicle detection and classification methods based on images from visible light and thermal cameras. These methods can be used in real-time smart surveillance systems. To classify vehicles by type, we extract the headlight and grill areas from the visible light and thermal images. We then extract texture characteristics from the images and use these as features for classifying different types of moving vehicles. We also extract several features from images obtained at night and during the day, which are the contrast, homogeneity, entropy, and energy. We validated our method experimentally and achieved that the accuracy of our visible image classifier was 92.7% and the accuracy of our thermal image classifier was 65.8% when vehicles were classified into six types such as SUV type, sedan type, RV type.

Smartphones and tablets are widely used in medical fields, which can improve healthcare and reduce healthcare costs. Many medical applications for smartphones and tablets have already been developed and widely used by both health professionals and patients. Specifically, video recordings of fingertips made using a smartphone camera contain a pulsatile component caused by the cardiac pulse equivalent to that present in a photoplethysmographic signal. By performing peak detection on the pulsatile signal, it is possible to estimate a continuous heart rate and a respiratory rate. To estimate the heart rate and respiratory rate accurately, which pixel regions of the color bands give the most optimal signal quality should be investigated. In this paper, we investigate signal quality to determine the best signal quality by the largest amplitude values for three different smartphones under different conditions. We conducted several experiments to obtain reliable PPG signals and compared the PPG signal strength in the three color bands when the flashlight was both on and off. We also evaluated the intensity changes of PPG signals obtained from the smartphones with motion artifacts and fingertip pressure force. Furthermore, we have compared the PSNR of PPG signals of the full-size images with that of the region of interests (ROIs).

This research presents the process of developing the 'Sanneoul' Eco-village, located in South Korea, and describes community life in the village. Sanneoul village was created to welcome urban dwellers who choose to return to rural life and to prevent the exodus of the population in rural areas. The village features eco-friendly architecture and utility systems within which the residents live as a community. Nearly fifty community meetings were held by the residents of the village from the beginning to the end of the construction process. They received public funds to cover most of the basic costs for the village construction, and the households moving in as residents covered only the costs of the property, land, and buildings. This advantage is one of the important factors that attract city dwellers to return to rural areas. The ecological systems installed within the village include rainwater recycling, grass blocks, rooftop gardens, and an ecological sewage disposal plant. The ecological elements of the architecture are the sunlight and solar heat system, pellet boiler, fireplace, and 'ondol' floor heating. The residents actively participate in recycling garbage, food waste, and feces. The village residents are contented with the eco-friendly aspects of the village and have been active participants of the system.

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