• KSCE Journal of Civil and Environmental Engineering Research
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• v.39 no.1
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• pp.93-103
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• 2019

In metropolitan cities have been reorganizing the routes of the city buses periodically due to changes in the spatial structure and traffic pattern and the lack of supply due to new developments. However, there is a lack of system to comprehensively evaluate the routes. Even if the evaluation index is not clearly defined, it may not be reasonable. Therefore, it is difficult to set the improvement direction when the bus route is reorganized. In this study, the existing evaluation indexes were reviewed and further investigation was conducted on the problematic indexes. In particular, the degree of curvature has been used as a very important index in the evaluation of the route system, but the existing curvature based curvature has a limitation in considering the traffic characteristics of individual users. For this purpose, a virtual city bus network was set up and the degree of curvature was calculated and compared based on the point - based curvature and stopping point based on individual user O/D. In this study, it is considered that more efficient and practical analysis and evaluation are possible in the evaluation of the city bus route system through the curvature considering the individual user O/D based on the stopping point. It is expected that it will be used at the time of reorganization of city bus route performed by individual local governments in the future.

• Journal of the Korean Association of Geographic Information Studies
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• v.21 no.4
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• pp.14-25
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• 2018

The operation of high-speed rail (HSR) has an effect on the agglomeration economies, and the impact is shown as a relocation of individual firm and worker to where business activity can be maximized. The proximity to the HSR station could be considered as a core district to maximize the industrial benefit through the HSR network. From this perspective, this study considers the agglomeration effect of HSR within the HSR station-area and analyzed the agglomerated spatial pattern through hotspot analysis by service industry in the cases of Korea and Japan using GIS. This study analyzed the service industry within 1km distance from 8 HSR stations of Korea and 4 Kyushu Shinkansen stations of Japan. The results suggest that the hotspot patterns are observed in the service industry within 1km distance from the HSR station of Korea and Japan, except for two HSR stations of Gupo station and Kagoshima-Chuo station. Leisure, amusement, association, and other specific service industries could be affected by HSR passengers and knowledge-spillovers through HSR station. Therefore, the observed hotspot districts near the HSR station-area could explain an agglomeration pattern of the service industry through a closeness to the HSR station. Further, we could expect that the impact of HSR affects the service industry, and the impact could attract business activities of the service-area to maximize their benefit from HSR travelers. With the result, it is required to build up a supportive policy to maximize the HSR's impact on the service industry when considering the HSR station-area development.

• Korean Journal of Heritage: History & Science
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• v.48 no.4
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• pp.74-93
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• 2015

Geophysical survey of Korea was introduced in Nara National Research Institute of Cultural Heritage in 1995. At that time, it has been activated geophysical survey of architecture and civil engineering in Korea. But there was no exploration experts to be combined the archaeology. For this reason, National Research Institute of Cultural Heritage has introduced the physical exploration. Through the expert exchanges South Korea and Japan carried out joint exploration. And it has increased the reliability of the exploration method and exploration results. It is GPR the most method commonly in geophysical exploration. There are many usability before excavation because of good resolution. However, the shallow GPR penetration depth has limitations in large mounds. We were able to take advantage of the resistivity analysis program to study the underground structure to deep through the experts exchange. We was able to get a good result that overcomes the limitations of GPR exploration in a number of burial mounds including Naju bokamri by the resistivity analysis program. In particular, we confirmed the location of the burial main body by compares the results of exploration and excavation results. In the future we will perform a convergence research of exploration and archaeology through a variety of joint research. In addition we will have to build a new network of archaeological science.

• Korean Journal of Environment and Ecology
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• v.35 no.5
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• pp.569-575
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• 2021

This study analyzed the effect of forests on reducing particulate matter by investigating the particulate matter concentration and influencing factors between urban forest and traffic forest. The concentrations of particulate matter in Hongreung Experimental Forest (urban forest) and a forest (traffic forest) formed at the intersection of Cheongryangri Station in Dongdaemun-gu, Seoul were measured with the light scattering method instrument from January to November 2018. During the study period, the average PM₁₀ concentrations in the urban forest and the traffic forest were 12.5㎍/m³ and 15.7 ㎍/m³, respectively, and the average PM_2.5 concentrations were 16.6㎍/m³and 6.9 ㎍/m³, respectively. Comparing the concentration by the urban atmospheric measurement network of the Ministry of Environment and the concentration in urban forests showed that the reduction rate of PM₁₀ was 66.9±28.6% in urbanforest and 58.6±44.1% in traffic forest and that of PM_2.5 was 71.3±23.0% and 64.9±31.3%. The difference in the reduction rate of particulate matter is likely related to the size and structure of the urban forest, and the wind velocity is considered the reduction factor.

• Korean journal of applied entomology
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• v.60 no.1
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• pp.79-90
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• 2021

Landscape composition and structure are important factors determining biological diversity including pests and natural enemires in agricultural ecosystem. This study was conducted to indentify effect of landscape composition on occurrence of lepidopteran pest population in Geochang, Gyoungdnam. For this, orchard characteristics and management practices were surveyed in 80 conventional apple orchards in Geochang, Korea, along with the monitoring of pest population densities. The landscape features of each surveyed orchard also obtained by extracting information from the public-service map. Grapholita molesta was the most dominat and damaging pest followed by Phyllonorycter ringoniella and Carposina sasakii in trap catches. Adoxophyes paraorana occurrences were low. Farmers spray insecticides and fungicides ap. 12.4 times per year respectively while acaricides were sprayed 2.4 times. Major landscape features such as surrounding apple orchard or paddy field did not influence the pest populations but presence of plum, peach, wild peach, graph, and even abandoned orchards significantly resulted in higher pest population mostly on G. molesta. C. sasakii population was higher in orchards with grape, peach, and P. ringoniella with peach, grape, abandoned orchards and jujube. Results highlight the need of landscape management not only for the rural amenity but also for increasing functional diversity of agroecosystem as well as reducing pest population.

• KIPS Transactions on Software and Data Engineering
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• v.10 no.1
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• pp.1-8
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• 2021

In the political field of news articles, there are polarized and biased characteristics such as conservative and liberal, which is called political bias. We constructed keyword-based dataset to classify bias of news articles. Most embedding researches represent a sentence with sequence of morphemes. In our work, we expect that the number of unknown tokens will be reduced if the sentences are constituted by subwords that are segmented by the language model. We propose a document embedding model with subword tokenization and apply this model to SVM and feedforward neural network structure to classify the political bias. As a result of comparing the performance of the document embedding model with morphological analysis, the document embedding model with subwords showed the highest accuracy at 78.22%. It was confirmed that the number of unknown tokens was reduced by subword tokenization. Using the best performance embedding model in our bias classification task, we extract the keywords based on politicians. The bias of keywords was verified by the average similarity with the vector of politicians from each political tendency.

• The Journal of Korean Institute of Next Generation Computing
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• v.14 no.5
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• pp.31-39
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• 2018

Recently, there has been active studies to provide a user-friendly interface in a virtual reality environment by recognizing user hand gestures based on deep learning. However, most studies use separate sensors to obtain hand information or go through pre-process for efficient learning. It also fails to take into account changes in the external environment, such as changes in lighting or some of its hands being obscured. This paper proposes a hand gesture recognition method based on deep learning that is strong in external environments without the need for pre-process of RGB images obtained from general webcam. In this paper we improve the VGGNet and the GoogLeNet structures and compared the performance of each structure. The VGGNet and the GoogLeNet structures presented in this paper showed a recognition rate of 93.88% and 93.75%, respectively, based on data containing dim, partially obscured, or partially out-of-sight hand images. In terms of memory and speed, the GoogLeNet used about 3 times less memory than the VGGNet, and its processing speed was 10 times better. The results of this paper can be processed in real-time and used as a hand gesture interface in various areas such as games, education, and medical services in a virtual reality environment.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.20 no.2
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• pp.43-55
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• 2010

${\mu}TESLA$ broadcast authentication protocol have been developed by many researchers for providing authenticated broadcasting message between receiver and sender in sensor networks. Those cause authentication delay Tree-based ${\mu}TESLA$[3] solves the problem of authentication delay. But, it has new problems from Merkel hash tree certificate structure. Such as an increase in quantity of data transmission and computation according to the number of sender or parameter of ${\mu}TESLA$ chain. ${\mu}TPCT$-based ${\mu}TESLA$[4] has an advantages, such as a fixed computation cost by altered Low-level Merkel has tree to hash chain. However, it only use the sequential values of Hash chain to authenticate ${\mu}TESLA$ parameters. So, It can't ensure the success of authentication in lossy sensor network. This paper is to propose the improved method for Tree-based ${\mu}TESLA$ by using XOR-based chain. The proposed scheme provide advantages such as a fixed computation cost with ${\mu}$TPCT-based ${\mu}TESLA$ and a message loss-tolerant with Tree-based ${\mu}TESLA$.

• Economic and Environmental Geology
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• v.54 no.3
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• pp.353-364
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• 2021

Since the mid-twentieth century, geology has gradually evolved as an interdisciplinary context in South Korea. The journal of Economic and Environmental Geology (EEG) has a long history of over 52 years and published interdisciplinary articles based on geology. In this study, we performed a literature review using topic modeling based on Latent Dirichlet Allocation (LDA), an unsupervised machine learning model, to identify geological topics, historical trends (classic topics and emerging topics), and association by analyzing titles, keywords, and abstracts of 2,571 publications in EEG during 1968-2020. The results showed that 8 topics ('petrology and geochemistry', 'hydrology and hydrogeology', 'economic geology', 'volcanology', 'soil contaminant and remediation', 'general and structural geology', 'geophysics and geophysical exploration', and 'clay mineral') were identified in the EEG. Before 1994, classic topics ('economic geology', 'volcanology', and 'general and structure geology') were dominant research trends. After 1994, emerging topics ('hydrology and hydrogeology', 'soil contaminant and remediation', 'clay mineral') have arisen, and its portion has gradually increased. The result of association analysis showed that EEG tends to be more comprehensive based on 'economic geology'. Our results provide understanding of how geological research topics branch out and merge with other fields using a useful literature review tool for geological research in South Korea.

• Journal of Ginseng Research
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• v.45 no.3
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• pp.390-400
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• 2021

Background: We recently showed that gintonin, an active ginseng ingredient, exhibits antibrain neurodegenerative disease effects including multiple target mechanisms such as antioxidative stress and antiinflammation via the lysophosphatidic acid (LPA) receptors. Amyotrophic lateral sclerosis (ALS) is a spinal disease characterized by neurodegenerative changes in motor neurons with subsequent skeletal muscle paralysis and death. However, pathophysiological mechanisms of ALS are still elusive, and therapeutic drugs have not yet been developed. We investigate the putative alleviating effects of gintonin in ALS. Methods: The G93A-SOD1 transgenic mouse ALS model was used. Gintonin (50 or 100 mg/kg/day, p.o.) administration started from week seven. We performed histological analyses, immunoblot assays, and behavioral tests. Results: Gintonin extended mouse survival and relieved motor dysfunctions. Histological analyses of spinal cords revealed that gintonin increased the survival of motor neurons, expression of brain-derived neurotrophic factors, choline acetyltransferase, NeuN, and Nissl bodies compared with the vehicle control. Gintonin attenuated elevated spinal NAD(P) quinone oxidoreductase 1 expression and decreased oxidative stress-related ferritin, ionized calcium-binding adapter molecule 1-immunoreactive microglia, S100β-immunoreactive astrocyte, and Olig2-immunoreactive oligodendrocytes compared with the control vehicle. Interestingly, we found that the spinal LPA1 receptor level was decreased, whereas gintonin treatment restored decreased LPA1 receptor expression levels in the G93A-SOD1 transgenic mouse, thereby attenuating neurological symptoms and histological deficits. Conclusion: Gintonin-mediated symptomatic improvements of ALS might be associated with the attenuations of neuronal loss and oxidative stress via the spinal LPA1 receptor regulations. The present results suggest that the spinal LPA1 receptor is engaged in ALS, and gintonin may be useful for relieving ALS symptoms.