• Journal of Software Assessment and Valuation
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• v.17 no.1
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• pp.75-82
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• 2021

Mastitis in cows is a major factor that hinders dairy productivity of farms, and many attempts have been made to solve it. However, research on mastitis has been limited to diagnosis rather than prediction, and even this is mostly using a single sensor. In this study, a predictive model was developed using multivariate data including biometric data and environmental data. The data used for the analysis were collected from robot milking machines and sensors installed in farmhouses in Chungcheongnam-do, South Korea. The recurrent neural network model using three weeks of data predicts whether or not mastitis is diagnosed the next day. As a result, mastitis was predicted with an accuracy of 82.9%. The superiority of the model was confirmed by comparing the performance of various data collection periods and various models.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.8 no.1
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• pp.1-11
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• 2013

The femto fusion technology refers to not only the technology for femtosecond($10^{-15}$ second) laser and but also the fusion technology of its application. This technology is comparable to the nano technology, the extreme technology on the space, and is of extreme time-domain technology. Now, we need to develop the hyperfine and high-precision femto fusion process technology which allows to miniaturize and highly integrate the products of mobile, semiconductor and display industries, the national main focusing growth industries. However, The femtosecond laser fabrication technology is essential in the development of fusion technology, but only a few of domestic researchers can handle the former. Under this condition, our government plans to develop the "femto fusion technology infrastructure project" as one of the ICT research infrastructure. So the purpose of this study is to analyze the feasibility of this project. We applied AHP(analytic hierarchy process) for this study. The final result shows that all the repondent's score is over 0.55 and the aggregated score is 0.846. And as a consequence, we can conclude that to do this project is feasible.

• Science of Emotion and Sensibility
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• v.20 no.4
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• pp.89-100
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• 2017

Since smart devices are able to efficiently provide information without barriers of time and location, they are widely utilized with advent of the hyper-connected society. Especially, the smart devices have been developed in the form of wearable devices for mutual interaction between human and objects. Smart clothing, which embeds smart devices within clothes, measures and obtains a variety of bio-signals as it is in close contact with the human bodies. Conventional smart clothing generated wearers' discomfort because they were developed by simple attachment of electronic devices to clothes. Therefore, it is highly recommended to develop novel smart clothing based on smart textiles which integrate electronic devices as parts of textiles. As smart watches are currently the most available wearable devices in the market, smart watch users were selected in this study, for the purpose of investigating core needs of wearable smart device users based on the user experience and user's sensibility. Qualitative research was performed through semi-structured interview in order to obtain detailed answers about user sensibility based on smart watch user experience. After the in-depth interview, the user's sensibility was categorized into four aspects; functional, aesthetic, social, and empirical. Sensibility adjectives and key words were assigned to each aspect and their frequency was analyzed. It was the functional aspect of sensibility that the wearable device users require the most. The results of this study will be utilized as a fundamental data to develop the smart textiles required for the next generation of smart clothing which is attracting as a future wearable device.

• The Journal of Engineering Geology
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• v.24 no.3
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• pp.431-440
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• 2014

Since the establishment of the Groundwater Act in Korea in 1993, the national policy on groundwater has focused on the preservation and management of groundwater, which should be used only as a subsidiary water resource. However, population growth, increased water demand, climate change, and the need for uniform water distribution have brought changes to groundwater policy, and have led to the prioritization of development projects such as groundwater dams and river bank filtration. Population growth, changes to the water environment, and increased water risks have all played a role in triggering rapid growth within the water industry; the size of the investment in water resources will also continue to increase worldwide. Until now, private wells and bottled mineral water have led the groundwater industry in South Korea. However, a new area of the groundwater industry, which includes the health and medical sciences, employs groundwater properties derived from regional geology, and is growing. This requires the advancement of groundwater research and technical development connected with ICT (Information and Communication Technology) and medical science, and that the public development of groundwater and its various applications is expanded through locating groundwater in the core of the water industry cluster.

• Journal of Bio-Environment Control
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• v.27 no.1
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• pp.27-33
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• 2018

This study was performed to review the domestic and international smart farm service model based on the convergence of agriculture and information & communication technology and derived various factors needed to improve the Korean smart greenhouse. Studies on modelling of crop growth environment in domestic smart farms were limited. And it took a lot of time to build research infrastructure. The cloud-based research platform as an alternative is needed. This platform can provide an infrastructure for comprehensive data storage and analysis as it manages the growth model of cloud-based integrated data, growth environment model, actuators control model, and farm management as well as knowledge-based expert systems and farm dashboard. Therefore, the cloud-based research platform can be applied as to quantify the relationships among various factors, such as the growth environment of crops, productivity, and actuators control. In addition, it will enable researchers to analyze quantitatively the growth environment model of crops, plants, and growth by utilizing big data, machine learning, and artificial intelligences.

• Journal of Intelligence and Information Systems
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• v.28 no.1
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• pp.89-106
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• 2022

Recently, the amount of video data collected from smartphones, CCTVs, black boxes, and high-definition cameras has increased rapidly. According to the increasing video data, the requirements for analysis and utilization are increasing. Due to the lack of skilled manpower to analyze videos in many industries, machine learning and artificial intelligence are actively used to assist manpower. In this situation, the demand for various computer vision technologies such as object detection and tracking, action detection, emotion detection, and Re-ID also increased rapidly. However, the object detection and tracking technology has many difficulties that degrade performance, such as re-appearance after the object's departure from the video recording location, and occlusion. Accordingly, action and emotion detection models based on object detection and tracking models also have difficulties in extracting data for each object. In addition, deep learning architectures consist of various models suffer from performance degradation due to bottlenects and lack of optimization. In this study, we propose an video analysis system consists of YOLOv5 based DeepSORT object tracking model, SlowFast based action recognition model, Torchreid based Re-ID model, and AWS Rekognition which is emotion recognition service. Proposed model uses single-linkage hierarchical clustering based Re-ID and some processing method which maximize hardware throughput. It has higher accuracy than the performance of the re-identification model using simple metrics, near real-time processing performance, and prevents tracking failure due to object departure and re-emergence, occlusion, etc. By continuously linking the action and facial emotion detection results of each object to the same object, it is possible to efficiently analyze videos. The re-identification model extracts a feature vector from the bounding box of object image detected by the object tracking model for each frame, and applies the single-linkage hierarchical clustering from the past frame using the extracted feature vectors to identify the same object that failed to track. Through the above process, it is possible to re-track the same object that has failed to tracking in the case of re-appearance or occlusion after leaving the video location. As a result, action and facial emotion detection results of the newly recognized object due to the tracking fails can be linked to those of the object that appeared in the past. On the other hand, as a way to improve processing performance, we introduce Bounding Box Queue by Object and Feature Queue method that can reduce RAM memory requirements while maximizing GPU memory throughput. Also we introduce the IoF(Intersection over Face) algorithm that allows facial emotion recognized through AWS Rekognition to be linked with object tracking information. The academic significance of this study is that the two-stage re-identification model can have real-time performance even in a high-cost environment that performs action and facial emotion detection according to processing techniques without reducing the accuracy by using simple metrics to achieve real-time performance. The practical implication of this study is that in various industrial fields that require action and facial emotion detection but have many difficulties due to the fails in object tracking can analyze videos effectively through proposed model. Proposed model which has high accuracy of retrace and processing performance can be used in various fields such as intelligent monitoring, observation services and behavioral or psychological analysis services where the integration of tracking information and extracted metadata creates greate industrial and business value. In the future, in order to measure the object tracking performance more precisely, there is a need to conduct an experiment using the MOT Challenge dataset, which is data used by many international conferences. We will investigate the problem that the IoF algorithm cannot solve to develop an additional complementary algorithm. In addition, we plan to conduct additional research to apply this model to various fields' dataset related to intelligent video analysis.

• Journal of The Korean Association For Science Education
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• v.39 no.2
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• pp.279-293
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• 2019

This study investigated the effects of national science leading school programs on students' positive experiences about science (PES) and teachers' perceptions of curriculum implementation factors affecting students' PES. For this study, Test for Indicators of Positive Experiences about Science (TIPES) was administered to a total of 11,488 students from 117 national science leading schools and 1,315 students from 50 normal counterpart schools. In addition, a total of 105 teachers were given a survey asking their curriculum implementation levels and perceptions on importance and performance levels of each identified factor that was known to influence students' PES. Students' total PES scores and scores in five sub-components of PES were widely varied across science leading school program types. In general, participating teachers reported common curriculum implementation factors that most positively affected students' PES including 'science-related activities out of school,' 'student-centered research projects,' 'ICT-related materials' and 'performance assessment.' Based on these results, implications for science education were discussed.

• Journal of Internet Computing and Services
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• v.16 no.6
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• pp.123-131
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• 2015

Recently the development of ICT has a big impact on education field, and diffusion of smart devices has brought new education paradigm. Since people has an opportunity to use various contents anytime and communicate in an interactive way, the method of learning has changing. In 2011, Korean government has established the smart education promotion plan to be a first mover in the paradigm shift from e-learning to smart learning. Especially, government aimed to improve the quality of learning materials and method in public schools, and also to decrease the high expenditure on private education. However, the achievement of smart education policy has not emerged yet, and the refinement of smart learning policy and strategy is essential at this moment. Therefore, the purpose of this study is to propose the successful strategies for smart learning in public education. First, this study explores the status of public education and smart learning environment in Korea. Then, it derives the key success factors through SWOT(Strength, Weakness, Opportunity, Threat) analysis, and suggests strategic priorities through AHP(Analytic Hierarchy Priority) method. The interview and survey were conducted with total 20 teachers, who works in public schools. As a results, focusing on weakness-threat(WT) strategy is the most prior goal for public education, to activate the smart learning. As sub-factors, promoting the education programs for teachers($W_2$), which is still a weakness, appeared as the most important factor to be improved. The second sub-factor with high priority was an efficient optimizing the capability of new learning method($S_4$), which is a strength of systematic public education environment. The third sub-factor with high priority was the extension of limited government support($T_4$), which could be a threat to other public schools with no financial support. In other words, the results implicate that government institution factors should be considered with high priority to make invisible achievement in smart learning. This study is significant as an initial approach with strategic perspective for public education. While the limitation of this study is that survey and interview were conducted with only teachers. Accordingly, the future study needs to be analyzed in effectiveness and feasibility, by considering perspectives from field experts and policy makers.

• The Journal of the Korea Contents Association
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• v.18 no.6
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• pp.353-363
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• 2018

According to the Digi Capital forecast, the global augmented reality market is expected to grow rapidly by 2020 to reach 150 billion dollars. In particular, high value added effects are expected in education. As ICT advances, digital textbooks are also leading innovative education by adding interactive functions. Advanced countries, including the U.S., are already using digital textbooks that use augmented reality technology in their classes. In line with this technological outlook, the ministry proposed a design plan that applies augmented reality technology to middle school science 1 digital textbooks. A study on middle school science 1 digital textbooks showed that each unit provided short videos. In addition, an investigation into the augmented reality class case showed that it was difficult to establish experimental equipment, lack of equipment (devices), and 3D design contents that did not continue despite the excellence of learning effects. Based on this demand, we designed an augmented reality scenario and system configuration to be applied to the instrument-specific experiments of middle school science 1 digital textbooks to explore and explore the contents of augmented reality by students. This research will replace the dangerous experiments and time consuming experiments for teachers and students by applying augmented reality to science subjects that are essential for the development of digital textbooks.

• Journal of Digital Convergence
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• v.15 no.5
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• pp.13-25
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• 2017

The purpose of this study is to suggest the direction of O2O industry policy for solving the conflict problems with the traditional industry stakeholder and for enhancing the regulations as new industry development is inevitable. We make use of TAIDA that is one of scenario methods to accomplish the purpose and suggest the direction of policy. First, it is needed to prepare directly by government the environment that new business models are able to emerge easily with various consulting services and information supports like public system servers and IT infra, it is practical support policy. Second, positive legal application for new business and making the law for new business are needed in legal issues situation as soon as possible. Third, the conflicts with old and new industry would be managed to the direction of "predictable" progressively. Incongruity among laws, safety and security problems, and the conflict of stakeholder are urgent. Because of the limit in this study, it is expected that O2O industry is categorized in detail aligned to the characteristics and that new policies along to the separate industry areas are developed by the following study.