• Journal of Digital Convergence
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• v.19 no.5
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• pp.175-186
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• 2021

The roles and functions of domestic public libraries are diversifying, but various problems have emerged due to internally biased book lending. In addition, due to the 4th Industrial Revolution, public libraries have introduced a book recommendation system focusing on popular books, but the variety of books that users can access is limited. Therefore, in this study, the public library unborrowed book recommendation system was implemented limiting its spatial scope to Duryu Library in Daegu City to enhance the satisfaction of public library users, by using the loan records data (213,093 cases), user information (35,561 people), etc. and utilizing methods like cluster analysis, topic modeling, content-based filtering recommendation algorithm, and conducted a survey on actual users' satisfaction to present the possibility and implications of the unborrowed book recommendation system. As a result of the analysis, the majority of users responded with high satisfaction, and was able to find the satisfaction was relatively high in the class classified by specific gender, age, occupation, and usual reading. Through the results of this study, it is expected that some problems such as biased book lending and reduced operational efficiency of public libraries can be improved, and limitations of the study was also presented.

• Journal of Digital Convergence
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• v.19 no.12
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• pp.281-289
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• 2021

This study aims to investigate the influence of the components of the startup ecosystem on the business performance of startups, focusing on the mediating effect of the location environment. By presenting the insight that the popularization of start-ups can be an alternative for job creation thanks to the government's start-up support policy considering the location environment, it is possible to construct an optimal configuration scenario between the components of the start-up ecosystem and the location environment. Furthermore, it is expected to contribute to the improvement of corporate management performance. To achieve this goal, we performed a survey and the subjects were domestic start-up company employees with less than 7 years of experience. The results show that the components of the start-up ecosystem had a significant effect on the business performance of start-up companies and the location environment and on the management performance of start-up companies according to the mediation of the location environment.

• The Journal of the Korea Contents Association
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• v.21 no.7
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• pp.363-373
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• 2021

The purpose of this research is to analyze the Spill-over economic effect of the cultural and creative industries(CCI) in Henan Province, China. The research object is the CCI of Henan Province, which is mainly based on five sectors out of 42 industries in the industrial association table of the Statistical Bureau of Henan Province, China in 2017 (culture, sports; recreation and research sector; experimental development and integrated technical services sector; information transmission, computer services and software sector; education sector, etc), and is analyzed through secondary integration and redefinition of the CCI of Henan Province. Through the analysis of Henan Province Industry Association Table, this paper provides some enlightenment to the future direction of the cultural and creative industries. The main analysis results are as follows. The total production inducement of the CCI in Henan province is 48,848 billion yuan, and in particular, the production inducement coefficient of the industry in Henan province is 2.72809, 2.23909 (total of columns and rows), Index of the power of dispersion is 0.26325, and the index of the sensitivity of dispersion is 0.87535. Income induction coefficient is 0.55211, production tax induction coefficient is 0.09291. Because CCI of Henan Province has full development potential, the government needs to provide active support and policy support, in addition to the need for legal provisions and supervision of market management. In order to improve the innovative development of the CCI, it is necessary to develop a new model of "CCI+X".

• Korean Chemical Engineering Research
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• v.57 no.4
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• pp.445-454
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• 2019

Layered double hydroxides (LDHs) nanoparticles have emerged as novel nanomaterials for bio-imaging applications due to its unique layered structure, physicochemical properties, and good biocompatibility. Bio-imaging is one of the most important fields for medical applications in clinical diagnostics and therapeutics of various diseases. Enhanced diagnostic techniques are needed to realize new paradigm for next-generation personalized medicine through nanoscale materials. When nanotechnology is introduced into bio-imaging system, nanoparticle probes can endow imaging techniques with enhanced ability to obtain information about biological system at the molecular level. In this review, we summarize structural features of LDH nanoparticles with current issues of bio-imaging system. LDH nanoparticle probes are also discussed through in vitro as well as in vivo studies in various bio-imaging techniques including fluorescence imaging, magnetic resonance imaging (MRI), positron emission tomography (PET), and computed X-ray tomography (CT), which will have the potential in the development of the advanced nanoparticles with high sensitivity and selectivity.

• KIPS Transactions on Software and Data Engineering
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• v.8 no.6
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• pp.243-250
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• 2019

Because of a moving UAV has a lot of potential/kinetic energy, if the UAV falls to the ground, it may have a lot of impact. Because this can lead to human casualities, in this paper, the population density area on the UAV flight path is defined as a dangerous area. The conventional UAV path flight was a passive form in which a UAV moved in accordance with a path preset by a user before the flight. Some UAVs include safety features such as a obstacle avoidance system during flight. Still, it is difficult to respond to changes in the real-time flight environment. Using public Big Data for UAV path flight can improve response to real-time flight environment changes by enabling detection of dangerous areas and avoidance of the areas. Therefore, in this paper, we propose a method to detect and avoid dangerous areas for UAVs by utilizing the Big Data collected in real-time. If the routh is designated according to the destination by the proposed method, the dangerous area is determined in real-time and the flight is made to the optimal bypass path. In further research, we will study ways to increase the quality satisfaction of the images acquired by flying under the avoidance flight plan.

• Journal of the Korean Society of Radiology
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• v.12 no.7
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• pp.879-886
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• 2018

A 3-dimensional (D) printer is a device capable of outputting a three-dimensional solid object based on data modeled in a computer. These features are utilized in the bone model X - ray phantom production etc using CT data by fusing with the radiation science field. A bone model phantom was made using data obtained by CT scan of an existing Pelvis phantom, using PLA, Wood, XT-CF20, Glow fill, Steel filaments which are materials of Fused Filament Fabrication (FFF) 3D printer.Measure Hounsfield Unit (HU) with images obtained by CT scan of the existing Pelvis phantom and five material phantoms made with 3D printer under the same conditions,SI and SNR were measured using a diagnostic X-ray generator, and each phantom was compared and analyzed.As a result, the X - ray phantom in the X - ray examination condition of the limb was found to be most suitable for the glow fill filament.The characteristics of the filament can be known to the base of this research and the practicality of X - ray phantom fabrication was confirmed.

• KIPS Transactions on Software and Data Engineering
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• v.7 no.12
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• pp.485-496
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• 2018

So far, the deep learning, a field of artificial intelligence, has achieved remarkable results in solving problems from unstructured data. However, it is difficult to comprehensively judge situations like humans, and did not reach the level of intelligence that deduced their relations and predicted the next situation. Recently, deep neural networks show that artificial intelligence can possess powerful relational reasoning that is core intellectual ability of human being. In this paper, to analyze and observe the performance of Relation Networks (RN) among the neural networks for relational reasoning, two types of RN-based deep neural network models were constructed and compared with the baseline model. One is a visual question answering RN model using Sort-of-CLEVR and the other is a text-based question answering RN model using bAbI task. In order to maximize the performance of the RN-based model, various performance improvement experiments such as hyper parameters tuning have been proposed and performed. The effectiveness of the proposed performance improvement methods has been verified by applying to the visual QA RN model and the text-based QA RN model, and the new domain model using the dialogue-based LL dataset. As a result of the various experiments, it is found that the initial learning rate is a key factor in determining the performance of the model in both types of RN models. We have observed that the optimal initial learning rate setting found by the proposed random search method can improve the performance of the model up to 99.8%.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.11
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• pp.295-302
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• 2018

Face recognition (FR) has been widely used in various applications, such as smart surveillance systems, immigration control in airports, user authentication in smart devices, and so on. FR in well-controlled conditions has been extensively studied and is relatively mature. However, in unconstrained conditions, FR performance could degrade due to undesired characteristics of the input face image (such as irregular facial pose variations). To overcome this problem, this paper proposes a new method for determining if an input image is suitable for FR. In the proposed method, for an input face image, reconstruction error is computed by using a predefined set of reference face images. Then, suitability can be determined by comparing the reconstruction error with a threshold value. In order to reduce the effect of illumination changes on the determination of suitability, a preprocessing algorithm is applied to the input and reference face images before the reconstruction. Experimental results show that the proposed method is able to accurately discriminate non-frontal and/or incorrectly aligned face images from correctly aligned frontal face images. In addition, only 3 ms is required to process a face image of $64{\times}64$ pixels, which further demonstrates the efficiency of the proposed method.

• Informatization Policy
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• v.25 no.4
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• pp.3-36
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• 2018

This article discusses the possibilities and limitations of ICT education by reviewing the previous research on its various aspects including educational goals, contents, methods, and evaluation. First, when it comes to its educational goal, the prior studies suggest that ICT education aims to nurture digital citizenship among students and to enable them to participate in different sectors of our society. ICT education characterizes the core capacities of its future learners as 'lifelong learners,' 'information producers/consumers,' and 'local/global citizens.' Second, in regard to the educational content of ICT education, researchers investigate SW education importantly: They develop the educational programs and examine the effectiveness of those programs. However, to ensure the relevancy of the educational contents to the future society, institutional support is imperative including facilitating educators' capacities and synchronizing ICT education with subject education. Third, as the educational methods, various ICTs such as flipped learning and augmented reality (AR) are being applied to actual classroom teaching. Research on the educational methods, which is the most vibrant area in the ICT education scholarship, is expected to improve the previous educational methods and to lead the qualitative development of ICT education. Fourth, the previous discussion on the educational evaluation focuses on computer-based evaluations. Educational evaluation using ICT will enable educators to assess the characteristics and achievement of an individual learner accurately and to lead them to apply a teaching-learning process effectively, which will ultimately enhance the effectiveness of educational evaluation. Along with the overall review on the possibilities of ICT education, this article discusses the limitations of the current ICT education and its implications for educational inequalities.

• Journal of Cadastre & Land InformatiX
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• v.49 no.1
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• pp.85-101
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• 2019

Recently, thank to the popularization of light-weight drone through the significant developments in computer technologies as well as the advanced automated procedures in photogrammetry, Unmanned Aircraft Systems have led to a growing interest in industry as a whole. Documentation, maintenance, and restoration projects of large scaled cultural property would required accurate 3D phenomenon modeling and efficient visual inspection methods. The object of this study verify on the accuracies achieved of 3D phenomenon reconstruction as well as on the validity of the preservation, maintenance and restoration of large scaled cultural property by UAS photogrammetry. The test object is cltural heritage(treasure 1324) that is the rock-carved standing Bodhisattva in Soraesan Mountain, Siheung, documented in Goryeo Period(918-1392). This standing Bodhisattva has of particular interests since it's size is largest stone Buddha carved in a rock wall and is wearing a lotus shaped crown that is decorated with arabesque patterns. The positioning accuracy of UAS photogrammetry were compared with non-target total station survey results on the check points after creating 3D phenomenal models in real world coordinates system from photos, and also the quantified informations documented by Culture Heritage Administration were compared with UAS on the bodhisattva image of thin lines. Especially, tests the validity of UAS photogrammetry as a alternative method of visual inspection methods. In particular, we examined the effectiveness of the two techniques as well as the relative fluctuation of rock surface for about 2 years through superposition analysis of 3D points cloud models produced by both UAS image analysis and ground laser scanning techniques. Comparison studies and experimental results prove the accuracy and efficient of UAS photogrammetry in 3D phenomenon modeling, maintenance and restoration for various large-sized Cultural Heritage.