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Background/objectives: Due to the increase in mobility handicapped, related measures that reflect the needs of vulnerable people have been proposed in various fields. In particular, when entering an aging society, it is necessary to prepare for an overall social system. As the opportunities and demands for social participation of the elderly and the disabled are increasing, the need for research on the environment and mobility support for the mobility handicapped is increasing. Method/Statistical analysis: In the case of elderly people, the right to move has a close relationship with the economy when the guarantee for retirement life is insufficient. For the disabled, it is necessary to support movement to welfare facilities and medical support facilities, such as participation in rehabilitation and social education. System improvement and legislation are being made to guarantee the right to move for people with reduced mobility, but there are limitations in actual mobility support. Therefore, in this thesis, we intend to present a plan and a prospect of using ICT environment to support mobility of the mobility handicapped. Findings: By providing mobility support services in an ICT environment tailored to the types and characteristics of mobility handicapped, reflecting the mobility characteristics and requirements of mobility handicapped, we will improve the mobility autonomy of vulnerable people and provide welfare services and opportunities for social participation. Improvements/Application: Analyzing case studies on various mobility support using the ICT environment, we propose a plan to guarantee the right to move for the mobility handicapped.

Background/Objectives Deep learning which main technology in AI has high growth with being applied to field of speech recognition and Image classification. Especially, Deep learning technology in the field of Image classification is being applied as a core technology to Self-driving and crime prevention monitoring system that is recently emerging as the future industry. Methods/Statistical analysis: Various algorithm which is improved and developed CNN being able to do image process is suggested as Deep learning model in image recognition field. In this paper, we introduce various object detection algorithm including CNN. And explore most representative algorithms just R-CNN, Fast R-CNN, Faster R-CNN and difference between versions of YOLO devised to detect and track in real time. Findings: This paper evaluates deep learning algorithm’s performance by comparative analysis about mAP (mean average precision) and FPS (frames per second). In result of performance evaluation, YOLO algorithm is confirmed as that It shows excellent result in speed that detects and recognizes object and accuracy in real time system environment. Finally, we search cases in field of autonomous driving and access control system and home anti-crime system. Improvements/Applications: In this research, we can understand object detection algorithm among speech recognition technologies and proper field in each algorithm, apply security service based on image, recommend proper algorithm in various environment just like autonomous driving and security work, etc.

Background/Objectives: Under the background of educational informatization, the realization of education modernization and information education is the inevitable trend of future education development. As the backbone of the future teacher team, the level of information technology application ability of normal university students is the key to the modernization of future education. Therefore, the ministry of education proposed to strengthen the cultivation of information literacy of normal university students. Methods/Statistical analysis: As the cradle of basic education teachers in yanbian prefecture, yanbian university should strengthen the cultivation of information technology application ability of normal university students and study the current situation of the cultivation. In this paper, two questionnaires were conducted before and after the training of normal university students in yanbian university. Findings: Through the comparison and analysis of the two data by SPSS software, it is found that there is no specific training for normal university students in the training of information technology application ability of normal university students in yanbian university. Teaching less theoretical knowledge; Students have fewer opportunities to practice the problem. Improvements/Applications: Finally, the author puts forward some strategies for the future cultivation of information technology application ability of normal university students in yanbian university. For the training of excellent information teachers to contribute.

Background/Objectives: In this study, by analyzing foreign tourists entering the country by country, we tried to study the changes in the inflow of foreign tourists according to the monthly pattern. Methods/Statistical analysis: For the purpose of using statistical data on foreign tourists entering the country for the purpose of using it as basic data for establishing tourism policy and marketing strategy by the Korea Tourism Organization, data on monthly foreign tourist statistics are collected, and pandas and matplotlib technologies provided by Python are used. Thus, data preprocessing and time series data were analyzed. Findings: The number of foreign tourists steadily increased from 2010 to 2016, but the number of tourists decreased sharply in early 2017. It was analyzed that the number of tourists gradually increased from mid-2017. Every summer, the influx of tourists was analyzed to be very high, and especially in the summer of 2015, the number of tourists was analyzed to have decreased significantly. Improvements/Application: In this study, the trend of monthly tourists by country was analyzed, and if the relationship between social issues in the section in which the change trend curve rapidly decreases, it is likely to be possible to analyze the factors that influence the change of tourists.