• Korean Journal of Environment and Ecology
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• v.35 no.3
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• pp.256-264
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• 2021

Rapid urbanization around the world has negatively affected wildlife habitats, including birds. Wild birds settled in the city are adapting to the changed surroundings, and are typically known to make nests using materials that are easy to find around the city. This study was conducted for the purpose of analyzing the nesting materials on the Paridae using artificial bird nests installed in cities. In this study, the researchers established a total of 33 artificial bird nests in urban parks (22) and forests (11) in Cheonan-si, Chungcheongnam-do. Then we collected 4 artificial bird nests in urban parks (18.19%) and 5 in urban forests (45.46%) to compare the characteristics of bird nest materials by the nest, species, and urban green area types. Eight nests, excluding a nest abandoned by a pair of Paridae, were used for the material analysis. The collected nests were dried, and classified into natural materials (vegetable materials, animal materials, moss, and soil) and artificial materials (cotton, paper pieces, plastics, vinyl, and synthetic fibers), and then each nest was weighed. The classification result shows that the portion of moss (50.65%) was the highest in all nests, followed by soil (21.43%), artificial material (13.95%), vegetable material (5.78%), animal material (4.57%), and others (3.59%) in that order. Artificial materials were used in all nests in urban green areas. Moreover, although the Paridae used about 5.16% more vegetable material than the Parus varius, it was not significant (t=2.17, p=0.07). Plant materials and soil were most preferred in urban forests, and moss, animal, and artificial materials were widely used in that order in urban parks. There was a significant difference in the use of vegetable materials between urban parks and urban forests (t=3.07, p<0.05^*). In the habitats like urbanized and dry areas, where artificial materials are highly accessible, artificial materials replaced some roles of natural materials. This study is a basic study for the analysis of the types of materials used in artificial bird nests to understand the habitat system of urban ecosystems. It can be used as the basic data for ecological studies and conservation of the Paridae species.

• Journal of the Korean Institute of Landscape Architecture
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• v.49 no.1
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• pp.54-69
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• 2021

In 2020, civilized society's overall lifestyle showed a distinct change from consumable analog media, such as paper, to digital media with the increased penetration of cloud computing, and from wired media to wireless media. Based on these social changes, this work examines whether the use of computer media in the field of landscape architecture is appropriately applied. This study will give directions for new computer media classes in landscape architectural education in the 4th Industrial Revolution era. Landscape architecture is a field that directly proposes the realization of a positive lifestyle and the creation of a living environment and is closely connected with social change. However, there is no clear evidence that landscape architectural education is making any visible change, while the digital infrastructure of the 4th Industrial Revolution, such as Artificial Intelligence (AI), Big Data, autonomous vehicles, cloud networks, and the Internet of Things, is changing the contemporary society in terms of technology, culture, and economy among other aspects. Therefore, it is necessary to review the current state of the use of computer technology and media in landscape architectural education, and also to examine the alternative direction of the curriculum for the new digital era. First, the basis for discussion was made by studying the trends of computational design in modern landscape architecture. Next, the changes and current status of computer media classes in domestic and overseas landscape education were analyzed based on prior research and curriculum. As a result, the number and the types of computer media classes increased significantly between the study in 1994 and the current situation in 2020 in the foreign landscape department, whereas there were no obvious changes in the domestic landscape department. This shows that the domestic landscape education is passively coping with the changes in the digital era. Lastly, based on the discussions, this study examined alternatives to the new curriculum that landscape architecture department should pursue in a new degital world.

• The Journal of the Convergence on Culture Technology
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• v.7 no.1
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• pp.264-271
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• 2021

In this paper, we intended to find the labor situations and labor rights consciousness of local juveniles and also to identify how they are treated and respond to those treatments they encounter. At the same time, another purpose of this research is to collect basic data to give the youth proper education about labor rights when they are faced with unfair labor practice. The research results are as follows: First, 262 students (50.5%) have work experience. Second, 133 students(24.9%) took the education about labor rights, which means relatively small number of students were educated about labor rights. Third, it is reported that 54.2% of those students considered 'payment' top priority, and 67.7% of them got the work through their parents, friends, and acquaintances, and 60.2% had their jobs at restaurants. Average working hours are 7 hours a day and 20 hours a week, which shows that they worked quite long hours. Fourth, 28.9% of respondents reported they wrote employment contracts, and 82.1% said their main purpose of work was 'to make money'. Fifth, 24.7% of the students reported the experience of unfair treatment while working, and the most common case was 'jobs other than expected work'(17.9%). When they were asked how they coped with the unfair treatments, the largest percentage(30.3%) of them answered they 'quit the job'. Last, when the respondants were asked to list improvements for juvenile part-time jobs, the answers were minimum wage and payment with weekly vacation allowance(25.1%), enhancing social awareness(14.3%), increasing good job opportunity(12.8%), and etc.. This demonstrates that social awareness of juvenile labor jobs is to improve urgently in local community.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.15 no.6
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• pp.95-114
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• 2020

This paper, a meta-analysis of the effect of the start-up support policy on the start-up performance was conducted to examine the effect of the start-up support policy on the start-up performance of beneficiary companies and to provide theoretical and practical implications to support organizations and practitioners. To this end, 35 papers containing the correlation coefficient, which is a positive statistical value, were selected from the previous studies in academic journals and dissertations published in Korea from 2007 to 2020. In the preceding study of the start-up support policy, the independent variables include funding, education support, facility/equipment support, network support, mentoring support, consulting support, marketing support, management support, technical support, manpower support, and finance as a dependent variable. The effect size of the impact on aptitude and non-financial performance was reviewed. The pattern of the effect size was presented as a forest plot for easy visual understanding, and outliers were verified through sensitivity analysis for small-study-effect data with publication convenience. As a result of analyzing the effect size of the government-supported policy, it was verified that the effect size was generally medium or higher, affecting the entrepreneurial performance. Among the independent variables, the factor that has the greatest effect on startup performance is manpower support, followed by technical support, marketing support, management support, facility/equipment support, education support, mentoring support, funding, network support, and consulting support. It was analyzed that the effect size was large in order. As the 「Small and Medium Business Startup Support Act」 was recently reorganized from the manufacturing industry to digital transformation and smartization on October 8, 2020, the start-up support policy should consider the start-up stage and verify the priorities to organize the budget.

• Korean Journal of Mineralogy and Petrology
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• v.35 no.2
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• pp.101-109
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• 2022

The mobility and transport of radioactive cesium are crucial factors to consider for the safety assessment of high-level radioactive waste disposal sites in granite. The retardation of radionuclides in the fractured crystalline rock is mainly controlled by the hydrochemical condition of groundwater and surface reactions with minerals present in the fractures. This paper reports the experimental results of cesium sorption to the Wonju Granite, a typical Mesozoic granite in Korea, performed in an anaerobic chamber that mimics the anoxic environment of a deep disposal site. We measured the rates and amounts of cesium (¹³³Cs) removed by crushed granite samples in different electrolyte (NaCl, KCl, and CaCl₂) solutions and a synthetic groundwater solution, with variations in the initial cesium concentration (10^-5, 5×10^-6, 10^-6, 5×10^-7 M). The cesium sorption kinetic and isotherm data were successfully simulated by the pseudo-second-order kinetic model (r²= 0.99) and the Freundlich isotherm model (r²= 0.99), respectively. The sorption distribution coefficient of granite increased almost linearly with increasing biotite content in granite samples, indicating that biotite is an effective cesium scavenger. The cesium removal was minimal in KCl solution compared to that in NaCl or CaCl₂ solution, regardless of the ionic strength and initial cesium concentration that we examined, showing that K⁺ is the most competitive ion against cesium in sorption to granite. Because it is the main source mineral of K⁺ in fracture fluids, biotite may also hinder the sorption of cesium, which warrants further research.

• Journal of Intelligence and Information Systems
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• v.28 no.2
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• pp.191-206
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• 2022

Recently, it is a de-facto approach to utilize a pre-trained language model(PLM) to achieve the state-of-the-art performance for various natural language tasks(called downstream tasks) such as sentiment analysis and question answering. However, similar to any other machine learning method, PLM tends to depend on the data distribution seen during the training phase and shows worse performance on the unseen (Out-of-Distribution) domain. Due to the aforementioned reason, there have been many efforts to develop domain-specified PLM for various fields such as medical and legal industries. In this paper, we discuss the training of a finance domain-specified PLM for the Korean language and its applications. Our finance domain-specified PLM, KB-BERT, is trained on a carefully curated financial corpus that includes domain-specific documents such as financial reports. We provide extensive performance evaluation results on three natural language tasks, topic classification, sentiment analysis, and question answering. Compared to the state-of-the-art Korean PLM models such as KoELECTRA and KLUE-RoBERTa, KB-BERT shows comparable performance on general datasets based on common corpora like Wikipedia and news articles. Moreover, KB-BERT outperforms compared models on finance domain datasets that require finance-specific knowledge to solve given problems.

• KIPS Transactions on Software and Data Engineering
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• v.11 no.1
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• pp.41-50
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• 2022

In this paper, a method to directly calculate the major elements of skin color such as melanin and hemoglobin from the RGB signal of the camera is proposed. The main elements of skin color typically measure spectral reflectance using specific equipment, and reconfigure the values at some wavelengths of the measured light. The values calculated by this method include such things as melanin index and erythema index, and require special equipment such as a spectral reflectance measuring device or a multi-spectral camera. It is difficult to find a direct calculation method for such component elements from a general digital camera, and a method of indirectly calculating the concentration of melanin and hemoglobin using independent component analysis has been proposed. This method targets a region of a certain RGB image, extracts characteristic vectors of melanin and hemoglobin, and calculates the concentration in a manner similar to that of Principal Component Analysis. The disadvantage of this method is that it is difficult to directly calculate the pixel unit because a group of pixels in a certain area is used as an input, and since the extracted feature vector is implemented by an optimization method, it tends to be calculated with a different value each time it is executed. The final calculation is determined in the form of an image representing the components of melanin and hemoglobin by converting it back to the RGB coordinate system without using the feature vector itself. In order to improve the disadvantages of this method, the proposed method is to calculate the component values of melanin and hemoglobin in a feature space rather than an RGB coordinate system using a feature vector, and calculate the spectral reflectance corresponding to the skin color using a general digital camera. Methods and methods of calculating detailed components constituting skin pigments such as melanin, oxidized hemoglobin, deoxidized hemoglobin, and carotenoid using spectral reflectance. The proposed method does not require special equipment such as a spectral reflectance measuring device or a multi-spectral camera, and unlike the existing method, direct calculation of the pixel unit is possible, and the same characteristics can be obtained even in repeated execution. The standard diviation of density for melanin and hemoglobin of proposed method was 15% compared to conventional and therefore gives 6 times stable.

• Korean Journal of Heritage: History & Science
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• v.55 no.1
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• pp.175-198
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• 2022

With the development of technology, the methods of digitally converting various forms of analog information have become common. As a result, the concept of recording, building, and reproducing data in a virtual space, such as digital heritage and digital reconstruction, has been actively used in the preservation and research of various cultural heritages. However, there are few existing research results that suggest optimal scanners for small and medium-sized relics. In addition, scanner prices are not cheap for researchers to use, so there are not many related studies. The 3D scanner specifications have a great influence on the quality of the 3D model. In particular, since the state of light reflected on the surface of the object varies depending on the type of light source used in the scanner, using a scanner suitable for the characteristics of the object is the way to increase the efficiency of the work. Therefore, this paper conducted a study on nine small and medium-sized buried cultural properties of various materials, including earthenware and porcelain, by period, to examine the differences in quality of the four types of 3D scanners. As a result of the study, optical scanners and small and medium-sized object scanners were the most suitable digital records of the small and medium-sized relics. Optical scanners are excellent in both mesh and texture but have the disadvantage of being very expensive and not portable. The handheld method had the advantage of excellent portability and speed. When considering the results compared to the price, the small and medium-sized object scanner was the best. It was the photo room measurement that was able to obtain the 3D model at the lowest cost. 3D scanning technology can be largely used to produce digital drawings of relics, restore and duplicate cultural properties, and build databases. This study is meaningful in that it contributed to the use of scanners most suitable for buried cultural properties by material and period for the active use of 3D scanning technology in cultural heritage.

• Korean Journal of Remote Sensing
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• v.38 no.6_1
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• pp.1057-1068
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• 2022

This paper compares the combination performance of feature point-based matching algorithms as a study to confirm the matching possibility between image taken by a user and a virtual texture image with the goal of developing mobile-based real-time image positioning technology. The feature based matching algorithm includes process of extracting features, calculating descriptors, matching features from both images, and finally eliminating mismatched features. At this time, for matching algorithm combination, we combined the process of extracting features and the process of calculating descriptors in the same or different matching algorithm respectively. V-World 3D desktop was used for the virtual indoor texture image. Currently, V-World 3D desktop is reinforced with details such as vertical and horizontal protrusions and dents. In addition, levels with real image textures. Using this, we constructed dataset with virtual indoor texture data as a reference image, and real image shooting at the same location as a target image. After constructing dataset, matching success rate and matching processing time were measured, and based on this, matching algorithm combination was determined for matching real image with virtual image. In this study, based on the characteristics of each matching technique, the matching algorithm was combined and applied to the constructed dataset to confirm the applicability, and performance comparison was also performed when the rotation was additionally considered. As a result of study, it was confirmed that the combination of Scale Invariant Feature Transform (SIFT)'s feature and descriptor detection had the highest matching success rate, but matching processing time was longest. And in the case of Features from Accelerated Segment Test (FAST)'s feature detector and Oriented FAST and Rotated BRIEF (ORB)'s descriptor calculation, the matching success rate was similar to that of SIFT-SIFT combination, while matching processing time was short. Furthermore, in case of FAST-ORB, it was confirmed that the matching performance was superior even when 10° rotation was applied to the dataset. Therefore, it was confirmed that the matching algorithm of FAST-ORB combination could be suitable for matching between virtual texture image and real image.

• Korean Journal of Remote Sensing
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• v.38 no.6_1
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• pp.1505-1514
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• 2022

Image matching is a crucial preprocessing step for effective utilization of multi-temporal and multi-sensor very high resolution (VHR) satellite images. Deep learning (DL) method which is attracting widespread interest has proven to be an efficient approach to measure the similarity between image pairs in quick and accurate manner by extracting complex and detailed features from satellite images. However, Image matching of VHR satellite images remains challenging due to limitations of DL models in which the results are depending on the quantity and quality of training dataset, as well as the difficulty of creating training dataset with VHR satellite images. Therefore, this study examines the feasibility of DL-based method in matching pair extraction which is the most time-consuming process during image registration. This paper also aims to analyze factors that affect the accuracy based on the configuration of training dataset, when developing training dataset from existing multi-sensor VHR image database with bias for DL-based image matching. For this purpose, the generated training dataset were composed of correct matching pairs and incorrect matching pairs by assigning true and false labels to image pairs extracted using a grid-based Scale Invariant Feature Transform (SIFT) algorithm for a total of 12 multi-temporal and multi-sensor VHR images. The Siamese convolutional neural network (SCNN), proposed for matching pair extraction on constructed training dataset, proceeds with model learning and measures similarities by passing two images in parallel to the two identical convolutional neural network structures. The results from this study confirm that data acquired from VHR satellite image database can be used as DL training dataset and indicate the potential to improve efficiency of the matching process by appropriate configuration of multi-sensor images. DL-based image matching techniques using multi-sensor VHR satellite images are expected to replace existing manual-based feature extraction methods based on its stable performance, thus further develop into an integrated DL-based image registration framework.