• (The)Korea Educational Review
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• v.23 no.1
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• pp.231-260
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• 2017

The Fourth Industrial Revolution foreshadows radical changes in our lives. In the era of the fourth industrial revolution called the digital revolution, individualized learning based on ubiquitous learning is emphasized. The contents of learning will be centered on procedural knowledge rather than narrative knowledge, and fusion education in which boundaries between learning domains are broken down will be achieved. First of all, learners in the fourth industrial revolution era should have critical thinking and problem solving abilities. Metacognition based on self-control and cognitive flexibility is important for effective self-directed and active learning. Creativity-based collaborative activities, social vision skills, and social and emotional skills are also important competencies. Therefore, in order to provide individualized learning contents to learners in the fourth industrial revolution era, they should be transformed into learning paradigm based on personal characteristics such as learners' self-efficacy, interest, curiosity and creativity. In addition to this, evaluation forms should be diversified according to changing teaching and learning methods. In order to cultivate teachers to lead such educational innovation, it is necessary to reconsider the teaching capacity. Teachers should be able to construct creative lessons by skillfully exploiting technology in future learning environments. In addition to this, it should also have the ability to collaborate and cognitive flexibility to converge with other academic disciplines. Along with these discussions, we proposed the need for policy intervention along with changes in education.

• Asian-Australasian Journal of Animal Sciences
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• v.23 no.1
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• pp.116-121
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• 2010

Long-chain polyunsaturated fatty acids (LC-PUFA) promote the development of brain and vision of the fetus, relieve inflammation, inhibit oral dysplasia of rumor cell, decrease the incidence of cardiovascular disease and regulate arrhythmia. ${\Delta}-6$ desaturase is the rate-limited enzyme in the desaturation process. This study reports the cloning, characterization and tissue expression of a ${\Delta}-6$ desaturase gene in the chicken. PCR primers were designed based on the predicted sequence of chicken ${\Delta}-6$ desaturase (accession number: XM421053) and used to isolate a cDNA fragment of 1,323 bp from chicken liver. Based on the 1,323 bp fragment an EST (BI390105) was obtained by BLAST. The EST and 5'nd of the 1,323 bp fragment were partially overlapped. Gene specific primers derived from the EST were used for amplification of the 5'nd. Another gene-specific primer derived from the 1,323 bp fragment was used for amplification of the 3'nd by 3'ACE. Then the three overlapping cDNA sequences obtained were assembled with DNAMAN software and a full-length ${\Delta}-6$ desaturase of 2,153 bp was obtained. The full-length cDNA contained an ORF of 1,335 bp with a 5'ntranslated region of 147 nucleotides followed by an ATG initiation codon. Stop codon TGA was at position 1,481-1,483 bp. The deduced amino acids shared an homology above 77% with bovine, mice, orangutan, rat and human. The protein sequence had three histidine-rich regions HDFGH (HisI region), HFQHH (HisII region) and HH (HisIII region), a cytochrome $b_{5}$-like domain containing a heme-binding motif and two transmembrane domains. Sequence analysis of the chicken genomic DNA revealed that the coding sequence of chicken ${\Delta}-6$ desaturase included 12 exons and 11 introns. Semi-quantitative RT-PCR showed that the ${\Delta}-6$ desaturase expression levels were in turn liver, spleen, pancreas, lung, breast muscle, heart, and abdominal fat. The expression of ${\Delta}-6$ desaturase in liver was significantly higher than that in breast muscle (p<0.01). The expression of ${\Delta}-6$ desaturase in lung was significantly higher than that in abdominal fat (p<0.01). This is the first clone of chicken ${\Delta}-6$ desaturase.

• Journal of rehabilitation welfare engineering & assistive technology
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• v.9 no.1
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• pp.17-21
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• 2015

There have been sustained developments of advanced technologies using traffic safety facilities recently and techniques for identifying failure modes and devices which could result in fatal outcomes. The purpose of this research is aimed at improving the driving conditions in advance through analyzing the IT convergence, driving education, researches for vehicles, field of construction and robotics. The researchers evaluate on usability tests of the driving with 26 candidates through focusing on safety, convenience, efficiency, effectiveness. Using specialized LED panel to enhance driving performances of disabled people are for cautious road conditions like foggy weather or heavy rain. As a result, there were improvements in the driving conditions, and candidates reported this system was helpful. It allows them for maintaining proper driving all times and was especially informative for people with low vision or visually impaired. This system plays a pivotal role as a prevention mechanism not only for regular drivers but also for further delict of traffic violations or accident offenders who already have former record on tort.

• Journal of Advanced Marine Engineering and Technology
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• v.38 no.10
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• pp.1217-1224
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• 2014

This paper provides a practical scaling method to solve an old problem for scaling and developing the speed and resistance of a model to full-scale submarine in fully submerged underwater test. In every experimental test in towing tank, water tunnel and wind tunnel, in the first step, the speed of a model should be scaled to the full-scale vessel (ship or submarine). In the second step, the obtained resistance of the model should be developed. For submarine, there are two modes of movement: surface and submerged mode. There is no matter in surface mode because, according to Froude's law, the ratio of speed of the model to the full-scale vessel is proportional to the square root of lengths (length of the model on the length of the vessel). This leads to a reasonable speed and is not so much for the model that is applicable in the laboratory. The main problem is in submerged mode (fully submerged) that there isn't surface wave effect and therefore, Froude's law couldn't be used. Reynold's similarity is actually impossible to implement because it leads to very high speeds of the model that is impossible in a laboratory and inside the water. According to Reynold's similarity, the ratio of speed of the model to the full-scale vessel is proportional to the ratio of the full-scale length to the model length that leads to a too high speed. This paper proves that there is no need for exact Reynold's similarity because after a special Reynolds, resistance coefficient remains constant. Therefore, there is not compulsion for high speeds of the model. For proving this finding, three groups of results are presented: two cases are based on CFD method, and one case is based on the model test in towing tank. All these three results are presented for three different shapes that can show; this finding is independent of the shapes and geometries. For CFD method, Flow Vision software has been used.

• Journal of Digital Convergence
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• v.16 no.12
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• pp.283-292
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• 2018

UHD (Ultra High Definition) broadcasting technology, and UWV (Ultra Wide Vision) which is the high quality panoramic video of wide view angle based on UHD, were commercialized in Korea for the first time in the world, and those are representative realistic video technologies that maximize the user's sense of presence. By comparing the user's subjective reaction of UHD and UWV, the purpose of this study is to systematically establish the user's subjective video quality evaluation. For this purpose, a large screen projection experiment is designed by setting the screen size (4k x 2k, 8k x 2k) and content types (sports, landscape, concert) as variables to measure the user's subjective video quality evaluation and satisfaction. As a result of the study, the users' evaluation of UWV was higher than UHD in all items of subjective video quality, and satisfaction. Moreover, the results showed the significant differences depending on the video contents. Based on the results of the research, the study proposed the points necessary for the development and commercialization of UWV panoramic technology, and suggestions for the future research.

• Journal of the Society of Disaster Information
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• v.18 no.2
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• pp.269-279
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• 2022

Purpose: The purpose of this study is to develop a deep learning-based personal protective equipment detection model for disaster prevention at construction sites, and to apply it to actual construction sites and to analyze the results. Method: In the method of conducting this study, the dataset on the real environment was constructed and the developed personal protective equipment(PPE) detection model was applied. The PPE detection model mainly consists of worker detection and PPE classification model.The worker detection model uses a deep learning-based algorithm to build a dataset obtained from the actual field to learn and detect workers, and the PPE classification model applies the PPE detection algorithm learned from the worker detection area extracted from the work detection model. For verification of the proposed model, experimental results were derived from data obtained from three construction sites. Results: The application of the PPE recognition model to construction site brings up the problems related to mis-recognition and non-recognition. Conclusions: The analysis outcomes were produced to apply the object recognition technology to a construction site, and the need for follow-up research was suggested through representative cases of worker recognition and non-recognition, and mis-recognition of personal protective equipment.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.21 no.5
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• pp.171-182
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• 2022

The safe use of a structure requires it to be maintained in an undamaged state. Thus, a typical factor that determines the safety of a structure is a crack in it. In addition, cracks are caused by various reasons, damage the structure in various ways, and exist in different shapes. Making matters worse, if these cracks are unattended, the risk of structural failure increases and proceeds to a catastrophe. Hence, recently, methods of checking structural damage using deep learning and computer vision technology have been introduced. These methods usually have the premise that there should be a large amount of training image data. However, the amount of training image data is always insufficient. Particularly, this insufficiency negatively affects the performance of deep learning crack detection algorithms. Hence, in this study, a method of augmenting crack image data based on the image translation technique was developed. In particular, this method obtained the crack image data for training a deep learning neural network model by transforming a specific case of a asphalt crack image into a concrete crack image or vice versa . Eventually, this method expected that a robust crack detection algorithm could be developed by increasing the diversity of its training data.

• Journal of Intelligence and Information Systems
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• v.25 no.1
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• pp.1-19
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• 2019

Artificial intelligence (AI) is one of the main driving forces leading the Fourth Industrial Revolution. The technologies associated with AI have already shown superior abilities that are equal to or better than people in many fields including image and speech recognition. Particularly, many efforts have been actively given to identify the current technology trends and analyze development directions of it, because AI technologies can be utilized in a wide range of fields including medical, financial, manufacturing, service, and education fields. Major platforms that can develop complex AI algorithms for learning, reasoning, and recognition have been open to the public as open source projects. As a result, technologies and services that utilize them have increased rapidly. It has been confirmed as one of the major reasons for the fast development of AI technologies. Additionally, the spread of the technology is greatly in debt to open source software, developed by major global companies, supporting natural language recognition, speech recognition, and image recognition. Therefore, this study aimed to identify the practical trend of AI technology development by analyzing OSS projects associated with AI, which have been developed by the online collaboration of many parties. This study searched and collected a list of major projects related to AI, which were generated from 2000 to July 2018 on Github. This study confirmed the development trends of major technologies in detail by applying text mining technique targeting topic information, which indicates the characteristics of the collected projects and technical fields. The results of the analysis showed that the number of software development projects by year was less than 100 projects per year until 2013. However, it increased to 229 projects in 2014 and 597 projects in 2015. Particularly, the number of open source projects related to AI increased rapidly in 2016 (2,559 OSS projects). It was confirmed that the number of projects initiated in 2017 was 14,213, which is almost four-folds of the number of total projects generated from 2009 to 2016 (3,555 projects). The number of projects initiated from Jan to Jul 2018 was 8,737. The development trend of AI-related technologies was evaluated by dividing the study period into three phases. The appearance frequency of topics indicate the technology trends of AI-related OSS projects. The results showed that the natural language processing technology has continued to be at the top in all years. It implied that OSS had been developed continuously. Until 2015, Python, C ++, and Java, programming languages, were listed as the top ten frequently appeared topics. However, after 2016, programming languages other than Python disappeared from the top ten topics. Instead of them, platforms supporting the development of AI algorithms, such as TensorFlow and Keras, are showing high appearance frequency. Additionally, reinforcement learning algorithms and convolutional neural networks, which have been used in various fields, were frequently appeared topics. The results of topic network analysis showed that the most important topics of degree centrality were similar to those of appearance frequency. The main difference was that visualization and medical imaging topics were found at the top of the list, although they were not in the top of the list from 2009 to 2012. The results indicated that OSS was developed in the medical field in order to utilize the AI technology. Moreover, although the computer vision was in the top 10 of the appearance frequency list from 2013 to 2015, they were not in the top 10 of the degree centrality. The topics at the top of the degree centrality list were similar to those at the top of the appearance frequency list. It was found that the ranks of the composite neural network and reinforcement learning were changed slightly. The trend of technology development was examined using the appearance frequency of topics and degree centrality. The results showed that machine learning revealed the highest frequency and the highest degree centrality in all years. Moreover, it is noteworthy that, although the deep learning topic showed a low frequency and a low degree centrality between 2009 and 2012, their ranks abruptly increased between 2013 and 2015. It was confirmed that in recent years both technologies had high appearance frequency and degree centrality. TensorFlow first appeared during the phase of 2013-2015, and the appearance frequency and degree centrality of it soared between 2016 and 2018 to be at the top of the lists after deep learning, python. Computer vision and reinforcement learning did not show an abrupt increase or decrease, and they had relatively low appearance frequency and degree centrality compared with the above-mentioned topics. Based on these analysis results, it is possible to identify the fields in which AI technologies are actively developed. The results of this study can be used as a baseline dataset for more empirical analysis on future technology trends that can be converged.

• Journal of Korea Technology Innovation Society
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• v.11 no.3
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• pp.352-375
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• 2008

Recently policy coordination and integration have emerged as core challenges as complexity and uncertainty of policy. Especially as innovation and environment policy is expanding and its position is being further elevated within policy hierarchy, policy integration has emerged as core governance challenges for nation states. OECD countries emphasized the need of coordination and integration of policy by introducing concepts such as 'Environmental Policy Integration', 'the Third generation innovation policy', 'integrated innovation policy'. This study analysed the background, concepts, objects, mechanisms, and major issues of integrated innovation policy and various attempts for integrate innovation policy by policy level and cycle. Developing integrated innovation policies has become increasingly important for the EU and OECD countries in recent years. OECD countries including Finland have developed broader policy agendas for balancing policy objectives and aims of other policy sectors and horizontal relationships with other policy sectors. Policy integration helps to reorient policies where related policies are in conflict and to ensure coherence across different policy areas. Policy integration emphasizes long-term policy adjustment and adaptation based on social agreement and common vision.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.26 no.6
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• pp.599-609
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• 2008

Development of computer and electronic technology leads innovative progress in spatial informatics and successful commercialization. Geospatial information technology plays an important role in decision making in various applications. However, information display media are two-dimensional plane that limits visual perception. Understanding human visual processing mechanism to percept stereo vision makes possible to implement three-dimensional stereo image display. This paper proposes on-the-fly stereo image generation methods that are involved with various exterior and camera parameters including exposure station, viewing direction, image size, overlap and focal length. Collinearity equations and parameters related with stereo viewing conditions were solved to generate realisitc stereo imagery. In addition stereo flying simulation scenery was generated with different viewing locations and directions. The stereo viewing is based on the parallax principle of two veiwing locations. This study implemented anaglyphic stereogram, polarization and lenticular stereo display methods. Existing display technology has limitation to provide visual information of three-dimensional and dynamic nature of the real world because the 3D spatial information is projected into 2D plane. Therefore, stereo display methods developed in this study improves geospatial information and applications of GIS by realistic stereo visualization.