• Journal of the Korea Convergence Society
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• v.9 no.8
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• pp.1-8
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• 2018

In the field of biometric security such as face and iris recognition, it is essential to extract facial features such as eyes and lips. In this paper, we have studied a method of detecting eye and lip region in face image using faster R-CNN. The faster R-CNN is an object detection method using deep running and is well known to have superior performance compared to the conventional feature-based method. In this paper, feature maps are extracted by applying convolution, linear rectification process, and max pooling process to facial images in order. The RPN(region proposal network) is learned using the feature map to detect the region proposal. Then, eye and lip detector are learned by using the region proposal and feature map. In order to examine the performance of the proposed method, we experimented with 800 face images of Korean men and women. We used 480 images for the learning phase and 320 images for the test one. Computer simulation showed that the average precision of eye and lip region detection for 50 epoch cases is 97.7% and 91.0%, respectively.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.21 no.3
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• pp.607-612
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• 2017

IT convergence with agriculture and livestock farming are expected to bring more efficiency and quality improvement in producing, distributing, consuming of agricultural products with the aid of information processing and autonomous control technologies of the IT area. The standardization work for smart farming and livestock farming based on networks is just at the beginning stage. And also, it is capable of coping with environment and technical problems with the actualized IT convergence case for agriculture. Hence, more studies on each point are required to finish the works including amendments and enhancements. More interests are expected to attain the successful results that ultimately contribute to innovate in the lifestyle. In this paper, it is analyzed strategy item and consider the actualized IT convergence case for agriculture and livestock, namely Smart Farming and Smart livestock Farming as a solution to cope the presented problems. In addition, suggest to ICT standardization road map for future planning.

• Journal of Convergence for Information Technology
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• v.11 no.11
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• pp.335-344
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• 2021

The purpose of this paper is the development of course data models and learning achievement computation algorithms for enabling the course-embedded assessment(CEA), which is essential of competency-based education in higher education. The previous works related CEA have weakness in the development of the systematic solution for CEA computation. In this paper, we propose data models and algorithms to implement competency-based assessment system. Our data models are composed of a layered architecture of learning outcomes, learning modules and activities, and an associative matrix of learning outcomes and activities. The proposed methods can be applied to the development of the course-embedded assessment system as core modules. We evaluated the effectiveness of our proposed models through applying the models to a practical course, Java Programing. From the result of the experiments we found that our models can be used in the assessment system as a core module.

• The Journal of the Convergence on Culture Technology
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• v.8 no.3
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• pp.427-434
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• 2022

This study aims to develop design elements for cultural convergence between rehabilitation for individuals with developmental disabilities and lifelong education for individuals with disabilities, which is a key area in the practical support system for independent life support for individuals with developmental disabilities. As for the research method, a procedure for conducting FGI by forming two teams for professors majoring in special education and rehabilitation science was formed. The research was presented in three upper categories (universal cultural convergence elements, field-centered cultural convergence elements, and policy-centered cultural convergence elements) that should be designed for cultural convergence between rehabilitation for individuals with developmental disabilities and lifelong education for individuals with disabilities. In addition, subcategories were specifically composed for each upper category. First, as a universal cultural element, "open creative convergence" was presented in principle, which can be explained as a principle of exploring and practicing the validity of convergence between related fields for rehabilitation for individuals with developmental disabilities and lifelong education for individuals with disabilities. Second, field-centered cultural factors included development of joint practice model between fields of rehabilitation science and special education, subject matter education knowledge and skills, teaching and learning methods, learning career roadmaps, employment and job career development roadmaps, and the formation of an independent life development history certification system. Third, as policy-centered cultural elements, the formation of a curriculum integration composition system between local related institutions, the establishment of a qualification development path for coordinator-professional teacher-type personnel, and the organizational systematization between school-center types were presented. The study concluded that independent life support for individuals with developmental disabilities should not only be guaranteed for the entire life of adulthood, but also a lifelong education for individuals with disabilities based rehabilitation support system for individuals with developmental disabilities should be established through cultural convergence.

• Journal of Cadastre & Land InformatiX
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• v.47 no.2
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• pp.49-60
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• 2017

Recently, the use of mashup that integrates real-time data with spatial data such as tiled map and satellite imagery has been increased significantly. As the use of mashup has been extended to various fields of O2O, LBS, Smart City, and Autonomous Driving, the performance of mashup has become more important. Therefore, this study aims to compare and analyze the performance of various map platforms, when large amounts of real-time data are integrated with spatial data. Specifically, we compare the performance of most popular map platforms available in Korea, such as Google Maps, OpenStreetMap, Daum Map, Naver Map, olleh Map, and VWorld. We also compare the performance using most common web browsers of Chrome, Firefox and Internet Explorer. In the performance analysis, we measured and compared the initialization time of basic map and the mashup time of real-time data for the above map platforms. From analysis results, we could find that Google Maps, OpenStreetMap, VWorld, and olleh Map platforms showed a better performance than the others.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.4
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• pp.34-40
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• 2018

This paper presents a new method to estimate the pose of a moving object accurately using a monocular camera and a low-end GPS+IMU sensor system. For this goal, we adopted a deep neural network for the semantic segmentation of input images and compared the results with a semantic map of a neighborhood. In this map matching, we use weight tables to deal with label inconsistency effectively. Signals from a low-end GPS+IMU sensor system are used to limit search spaces and minimize the proposed function. For the evaluation, we added noise to the signals from a high-end GPS-IMU system. The results show that the pose can be recovered from the noisy signals. We also show that the proposed method is effective in handling non-open-sky situations.

• Journal of Industrial Convergence
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• v.18 no.1
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• pp.79-85
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• 2020

Recently, the RPAS(Remote Piloted Aircraft System), by remote control and autonomous navigation, has been increasing in interest and utilization in various industries and public organizations along with delivery drones, fire drones, ambulances, agricultural drones, and others. The problems of the stability of unmanned drones, which can be self-controlled, are also the biggest challenge to be solved along the development of the drone industry. drones should be able to fly in the specified path the autonomous flight control system sets, and perform automatically an accurate landing at the destination. This study proposes a technique to check arrival by landing point images and control landing at the correct point, compensating for errors in location data of the drone sensors and GPS. Receiving from the Google Map API and learning from the destination video, taking images of the landing point with a drone equipped with a NAVIO2 and Raspberry Pi, camera, sending them to the server, adjusting the location of the drone in line with threshold, Drones can automatically land at the landing point.

• Journal of the Korea Society of Computer and Information
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• v.19 no.2
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• pp.233-241
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• 2014

In this paper, it predicts green technology in the future with "Co-word" which is patent analysis, "technology road-map, life cycle graph of patent activation and trend analysis. Analysis result shows that it would help environment preservation because development of ITS green technology makes carbon emission effectiveness and ITS green technology is especially expected to develop in fuel saving field. In addition, fuel saving field is predicted to be advance more practically technology field with convergence with IT.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2019.05a
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• pp.403-405
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• 2019

The risk mitigation service based on network provides monitoring of the risk event data to be inputted and analyses its big data to be stored in real time. Furthermore, it performs the analysis of the plant disease risk such as a red tide, and livestock disease risk such a food-and-mouth disease, avian influenza, and rinderpest, and provides the mitigation service. The standardization road map for risk mitigation is the real time acquisition monitoring of risk events, and mitigation service for the risks.

• Proceedings of the Korea Information Processing Society Conference
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• 2010.11a
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• pp.215-217
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• 2010

IT융합의 중요성이 강조되고 있는 IT 지식정보화 사회에 지능형 로봇의 발전은 끝없이 연구되고 있다. 미래 인간사회에 로봇이 미치는 영향은 아주 클 것으로 예상하고 있으며, 인간의 실생활과 로봇의 가상공간 세계는 점점 일체화 되어 갈 것으로 예측된다. 따라서 인간은 로봇의 활동과 행동을 좀 더 구체적이고 자세하게 제어할 필요가 있다. 최근 현실세계를 가상공간의 세계로 표현하고자 하는 연구가 활발히 진행되고 있으며, 가상공간을 활용한 미래의 세상 환경은 점점 많아 질 것으로 예상한다. 따라서 본 논문에서는 지능로봇 시뮬레이션 맵 자동생성을 위한 제어 동기화 설계를 연구하였다. 현실세계의 실제 로봇과 가상공간의 시뮬레이션 로봇을 동기화하여 하드웨어 로봇의 움직임에 따라 가상공간의 로봇이 맵을 자동으로 생성시킬 수 있는 방법을 연구하고 설계하여 실험하였다. 실제 로봇의 움직임을 3차원 가상공간으로 자동 생성하게 함으로서, 로봇의 제어를 좀 더 지능화 시킬 수 있을 뿐아니라, 여러 다양한 시뮬레이션 테스트 환경으로 응용할 수 있는 큰 장점이 있다. 또한 로봇을 활용한 가상공간 세계의 시뮬레이션은 미래 인간과 로봇이 함께하는 공존세계에 큰 역할을 할 수 있을 것으로 기대한다.