Successful Aging of Korean Older Adults Engaging in Sports Regularly: Health Beliefs, Exercise Adherence Intention, and Health Promotion Behavior.

The population of older adults is increasing more rapidly in Korea than in any other country, making successful aging a salient need in Korean society. For successful aging, older adults must engage in sports activities regularly. This study determined the relationships among health beliefs, exercise adherence intention, health promotion behavior, and successful aging among older adults who engage in sports activities regularly. The participants were 287 adults aged 65 years or older who live in Korea and exercise regularly. Data were collected through a survey and analyzed using descriptive statistics, correlation analysis, and structural equation modeling. The integrated model lacked explanatory power in terms of goodness of fit, but the alternative model had sufficient explanatory power. The alternative model showed that health beliefs, exercise adherence intention, and health promotion behavior are significantly related and that health promotion behavior positively predicts successful aging. It also showed that health beliefs affect successful aging through the mediation of exercise adherence intention and health promotion behavior. This study is meaningful because it verifies the structural and theoretical relationships among health beliefs, exercise adherence intention, health promotion behavior, and successful aging. As a result, it provides information that can improve the welfare of older adults in Korean society.

Examining the Role of Life Skills in Mediating the Relationship between the Basic Psychological Needs and Subjective Well-Being of Taekwondo Student-Athletes.

Various theories in the field of positive youth development (PYD) through sport argue that student athletes' satisfaction with basic psychological needs, life skills development, and well-being are closely related to each other. This study identified the structural relationship among three basic psychological needs, life skills, and subjective well-being. Korean Taekwondo student athletes (N = 302, Mage = 17.67, range = 17-19) completed a survey evaluating basic psychological needs (autonomy, competence, and relatedness), life skills (teamwork, goal setting, social skills, time management, and leadership), and subjective well-being (life satisfaction, positive/negative affect). Data were analyzed by using descriptive statistics, correlation, and the Structural Equation Model (SEM). The model's goodness of fit was Ï°2/df = 2.78, TLI = 0.90, CFI = 0.90, RMSEA = 0.077 (95% CI = 0.70, 0.80), and SRMR = 0.085. The three basic psychological needs were positively related to life skills and subjective well-being. In addition, life skills had a mediation effect between the three basic psychological needs and subjective well-being. The interpretation of the results indicated that life skills development and well-being depend on basic psychological needs. Thus, coaches should encourage a PYD climate to satisfy their athletes' psychological needs.

Critical Image Identification via Incident-Type Definition Using Smartphone Data during an Emergency: A Case Study of the 2020 Heavy Rainfall Event in Korea.

In unpredictable disaster scenarios, it is important to recognize the situation promptly and take appropriate response actions. This study proposes a cloud computing-based data collection, processing, and analysis process that employs a crowd-sensing application. Clustering algorithms are used to define the major damage types, and hotspot analysis is applied to effectively filter critical data from crowdsourced data. To verify the utility of the proposed process, it is applied to Icheon-si and Anseong-si, both in Gyeonggi-do, which were affected by heavy rainfall in 2020. The results show that the types of incident at the damaged site were effectively detected, and images reflecting the damage situation could be classified using the application of the geospatial analysis technique. For 5 August 2020, which was close to the date of the event, the images were classified with a precision of 100% at a threshold of 0.4. For 24-25 August 2020, the image classification precision exceeded 95% at a threshold of 0.5, except for the mudslide mudflow in the Yul area. The location distribution of the classified images showed a distribution similar to that of damaged regions in unmanned aerial vehicle images.

Object Distance Estimation Using a Single Image Taken from a Moving Rolling Shutter Camera.

This paper proposes a technique to estimate the distance between an object and a rolling shutter camera using a single image. The implementation of this technique uses the principle of the rolling shutter effect (RSE), a distortion within the rolling-shutter-type camera. The proposed technique has a mathematical strength compared to other single photo-based distance estimation methods that do not consider the geometric arrangement. The relationship between the distance and RSE angle was derived using the camera parameters (focal length, shutter speed, image size, etc.). Mathematical equations were derived for three different scenarios. The mathematical model was verified through experiments using a Nikon D750 and Nikkor 50 mm lens mounted on a car with varying speeds, object distances, and camera parameters. The results show that the mathematical model provides an accurate distance estimation of an object. The distance estimation error using the RSE due to the change in speed remained stable at approximately 10 cm. However, when the distance between the object and camera was more than 10 m, the estimated distance was sensitive to the RSE and the error increased dramatically.

Automated Algorithm for Removing Clutter Objects in Mms Point Cloud for 3D Road Mapping.

Road information high definition maps (HD map) contain information about the facilities around the roads and are often constructed through a mobile mapping system (MMS). Although constructing an HD map is essential for road maintenance and the application of autonomous driving in the future, it is problematic to acquire the data of objects other than the facilities in an unstructured form while operating the MMS. In this study, the researchers define this object data as clutter objects and present a method of automatic removal using characteristics of the MMS and image segmentation techniques. By applying the method to 10 KITTI (Karlsruhe Institute of Technology and Toyota Technological Institute at Chicago) datasets, clutter objects were removed with an average overall accuracy of 91% with 0% (0.448%) error of commission for the complete point cloud map.