• The Journal of Korean Institute of Next Generation Computing
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• v.13 no.6
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• pp.7-20
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• 2017

The advancement of cloud and big data and the considerable growth of traffic have increased the complexity and problems in the management inefficiency of existing networks. The software-defined networking (SDN) environment has been developed to solve this problem. SDN enables us to control network equipment through programming by separating the transmission and control functions of the equipment. Accordingly, several studies have been conducted to improve the performance of SDN controllers, such as the method of connecting existing legacy equipment with SDN, the packet management method for efficient data communication, and the method of distributing controller load in a centralized architecture. However, there is insufficient research on the control of SDN in terms of the quality of network-using applications. To support the establishment and change of the routing paths that meet the required network service quality, we require a mechanism to identify network requirements based on a contract for application network service quality and to collect information about the current network status and identify the violations of network service quality. This study proposes a method of identifying the quality violations of network paths through ontology to ensure the network service quality of applications and provide efficient services in an SDN environment.

• Journal of Navigation and Port Research
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• v.47 no.6
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• pp.358-366
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• 2023

This study aimed to provide a solution for improving ship collision alert of the 'accident vulnerable ship monitoring service' among the 'intelligent marine traffic information system' services of the Ministry of Oceans and Fisheries. The current ship collision alert uses a supervised learning (SL) model with survey labels based on large ship-oriented data and its operators. Consequently, the small ship data and the operator's opinion are not reflected in the current collision-supervised learning model, and the effect is insufficient because the alarm is provided from a longer distance than the small ship operator feels. In addition, the supervised learning (SL) method requires a large number of labeled data, and the labeling process requires a lot of resources and time. To overcome these limitations, in this paper, the classification model of collision alerts for small ships using unlabeled data with the semi-supervised learning (SSL) algorithms (Label Propagation and TabNet) was studied. Results of real-time experiments on small ship operators using the classification model of collision alerts showed that the satisfaction of operators increased.

• The KIPS Transactions:PartA
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• v.10A no.5
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• pp.469-478
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• 2003

Internet information search engines using web robots visit servers conneted to the Internet periodically or non-periodically. They extract and classify data collected according to their own method and construct their database, which are the basis of web information search engines. There procedure are repeated very frequently on the Web. Many search engine sites operate this processing strategically to become popular interneet portal sites which provede users ways how to information on the web. Web search engine contacts to thousands of thousands web servers and maintains its existed databases and navigates to get data about newly connected web servers. But these jobs are decided and conducted by search engines. They run web robots to collect data from web servers without knowledge on the states of web servers. Each search engine issues lots of requests and receives responses from web servers. This is one cause to increase internet traffic on the web. If each web server notify web robots about summary on its public documents and then each web robot runs collecting operations using this summary to the corresponding documents on the web servers, the unnecessary internet traffic is eliminated and also the accuracy of data on search engines will become higher. And the processing overhead concerned with web related jobs on web servers and search engines will become lower. In this paper, a monitoring system on the web server is designed and implemented, which monitors states of documents on the web server and summarizes changes of modified documents and sends the summary information to web robots which want to get documents from the web server. And an efficient web robot on the web search engine is also designed and implemented, which uses the notified summary and gets corresponding documents from the web servers and extracts index and updates its databases.

• Journal of Environmental Impact Assessment
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• v.26 no.4
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• pp.272-289
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• 2017

This study analyzed the status of the naturalized plants in islands in Jeollanamdo from an island biogeographic perspective. As a result of a floristic analysis at 47 inhabited islands and 194 uninhabited islands, 30 families and 134 species naturalized plants are reported. The most commonly occurring naturalized plant from 141 islands was Rumex crispus. The average number of naturalized plants by islands is 20.6 species (${\pm}14.22$) at the inhabited islands and 3.7 species (${\pm}3.89$) at the uninhabited islands. Presence of fifty nine naturalized species at Geumodo in Yeosu-si is the largest in number. The naturalization ratio, which is the ratio of naturalized plants to native plants, is 7.66% (${\pm}3.96$) in the inhabitable islands and 4.97% (${\pm}3.70$) in the uninhabitable islands. The naturalization ratio among islands of the West Sea in Jeollanam-do is 5.92% (${\pm}4.49$), and it is higher than 4.96% (${\pm}2.15$) in islands in the South Sea. Especially, the naturalization ratio at the inhabitable islands, i.e., 8.39% (${\pm}4.37$) at the islands of the West Sea is higher than 5.80% (${\pm}1.41$) at islands in the South Sea. The naturalization ratio of naturalized plants at the islands shows positive correlation with the size of the island (r=0.412, p<0.01), but the correlations with distance from the mainland and altitude above sea level are not significant. Eight ecosystem disturbing species designated by law are reported, and each species shows distinct distributional ranges. The regional differences in the number of naturalized plant species seem to be a result of the complex reflection of natural and human environmental factors, such as the degree of traffic between mainland and islands, degree of cultivation activities, along with the physical environmental differences. Since islands have limited habitats and resources, islands could be more vulnerable to the incoming species from outside, and environmental changes than mainland. Therefore, continuous monitoring and management against the naturalized plants in islands are needed.

• Journal of the Korean Institute of Traditional Landscape Architecture
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• v.34 no.1
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• pp.118-128
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• 2016

The purpose of this study is to present efficient methods of preserving and managing the fish shelter forest in Mulgun-ri on the southern coast of Korea on the basis of its humanistic, sociological and ecological characteristics. The study object is Korean natural monument No. 150, which is presumed to have been forested by descendants of Jeonju Lee Family who settled there, and village rituals are held every October to pray for the peace of the village. The forest is managed by Namhae-gun as a historical and cultural resource as well as its disaster-preventing, economic, and environmental and ecological functions. The linear form of the area is $23,962.6m^2$ and farmland(48.5%) and urbanization area(38.2%) are extensively located in its periphery area. Actual vegetation was sub-classified into three types of land according to use pressure and whether or not damage was done: land where its stratification was formed; land where it was restored, and the land where it was damaged. Plant communities were sub-classified into Aphananthe aspera community(I) and Zelkova serrata community(II) which had a low use pressure; Z. serrata-Chionanthus retusa-A. aspera community(III) and A. aspera-Z. serrata community(IV) which had a high use pressure; and Celtis sinensis-A. aspera community(V) whose underlayer was damaged by use. Fragmentation of the forest is under way and its inside vegetation growth is hampered due to the installation of traffic and resting facilities such as the through roads costal roads, wooden-deck walkways, parking lots, washstands, etc. As a restoration management plan for this, the following were required: an establishment of preferred restoration area; a selection of restoration vegetation species; and an appropriate restoration method. The damaged area($7,868.2m^2$) will have to be set up as the preferred restoration area; seedlings of restored vegetation species should be raised with dominant species within the forest(i.e., Z. serrata, A. aspera, C. sinensis, and C. retusa) as their 'mother trees' for the benefit of for the next-generation forest; and sub-tree and shrub layer should be complementarily planted with 5 and 115 trees(unit $100m^2$) respectively to facilitate the formation of a multi-layered vegetation structure. In addition, resting facilities scattered inside the forest should be demolished; and indiscriminate use of them should be controlled; management and monitoring should be carried out so that the area can be preserved and restored as a deciduous broad-leaved forest.

• Journal of Korean Society for Atmospheric Environment
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• v.34 no.4
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• pp.567-587
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• 2018

A severe haze event occurred in October 2015 in Gwangju, Korea. In this study, the driving chemical species and the formation mechanisms of $PM_{2.5}$ pollution were investigated to better understand the haze event. Hourly concentrations of $PM_{2.5}$, organic and elemental carbon, water-soluble ions, and elemental constituents were measured at the air quality intensive monitoring station in Gwangju. The haze event occurred was attributed to a significant contribution (72.3%) of secondary inorganic species concentration to the $PM_{2.5}$, along with the contribution of organic aerosols that were strongly attributed to traffic emissions over the study site. MODIS images, weather charts, and air mass backward trajectories supported the significant impact of long-range transportation (LTP) of aerosol particles from northeastern China on haze formation over Gwangju in October 2015. The driving factor for the haze formation was stagnant atmospheric flows around the Korean peninsula, and high relative humidity (RH) promoted the haze formation at the site. Under the high RH conditions, $SO{_4}^{2-}$ and $NO_3{^-}$ were mainly produced through the heterogenous aqueous-phase reactions of $SO_2$ and $NO_2$, respectively. Moreover, hourly $O_3$ concentration during the study period was highly elevated, with hourly peaks ranging from 79 to 95ppb, suggesting that photochemical reaction was a possible formation process of secondary aerosols. Over the $PM_{2.5}$ pollution, behavior and formation of secondary ionic species varied with the difference in the impact of LTP. Prior to October 19 when the influence of LTP was low, increasing rate in $NO_3{^-}$ was greater than that in $NO_2$, but both $SO_2$ and $SO{_4}^{2-}$ had similar increasing rates. While, after October 20 when the impact of haze by LTP was significant, $SO{_4}^{2-}$ and $NO_3{^-}$ concentrations increased significantly more than their gaseous precursors, but with greater increasing rate of $NO_3{^-}$. These results suggest the enhanced secondary transformation of $SO_2$ and $NO_2$ during the haze event. Overall, the result from the study suggests that control of anthropogenic combustion sources including vehicle emissions is needed to reduce the high levels of nitrogen oxide and $NO_3{^-}$ and the high $PM_{2.5}$ pollution occurred over fall season in Gwangju.

• Journal of Environmental Impact Assessment
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• v.28 no.2
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• pp.113-128
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• 2019

The concentration and coating thickness of black carbon (BC) were measured along with fine dust in the fall of 2018, at the Seoul Metropolitan Area Intensive Monitoring Station (SIMS). In fall, the concentration of $PM_{10}$ and $PM_{2.5}$ was $23{\pm}12.6{\mu}g/m^3$ and $12{\pm}5.8{\mu}g/m^3$, respectively, lower than that in other seasons. The BC level, measured using an Aethalometer, was $0.73{\pm}0.43{\mu}g/m^3$, while the levels of elemental carbon (EC) and refractory-BC (rBC), measured by semi-continuous carbon analyzer (SOCEC) and single particle soot photometer (SP2), were $0.34{\pm}0.18{\mu}g/m^3$ and $0.32{\pm}0.18{\mu}g/m^3$, respectively. As such, the concentration level differed according to the measurement method, but its time-series distribution and diurnal variation showed the same trends. The BC concentration at SIMS was primarily affected by automobiles with higher levels of BC during morning and evening commuting times due to increased traffic congestion. rBC, measured by SP2, had a peak concentration and coating thickness of 84 nm and 43 nm, respectively. Notably, the coating thickness had an inverse relationship with particle size.

• Korean Journal of Heritage: History & Science
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• v.43 no.1
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• pp.190-211
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• 2010

The purpose of this paper is to provide the preliminary data for maintenance of old trees of natural monuments and establishing protection projects. Accordingly, growth conditions, location circumstances, environment and protection management were analyzed for old trees at 34 sites in Gyeongsangbuk-do. Tree forms, crown, trunk and trees' health, leaves volume were analyzed in survey sites. As the results, the growth of Picrasma quassioides in Songsadong, Andong-si and Catalpa ovata in Hongwon-ri, Cheongsong-gun were not in good condition, along with other old trees of 6 cities (Quercus variabilis in Susan-ri, Uljin-gun, Juniperus chinensis in Hujeong-ri, Uljin-gun, Pyrus ussuriensis in Ssangjeon-ri, Uljin-gun, Salix glandulosa var. pilosa in Deokchon-ri, Cheongdo-gun, Pinus densiflora for. multicaulis in Hwasan-ri, Mungyeong-si, Pinus densiflora in Daeha-ri, Mungyeong-si). Accoding to these results, protection project and consistent monitoring are necessary. The analysis results of growth conditions per location circumstances showed that the old trees in the small spaces with large traffic of people were in bad condition. Therefore, it is necessary to secure sufficient space and soil improvement for such trees. The analysis results of growth conditions per species showed that Zelkova serrata, Quercus spp., Pinus densiflora are in good condition while Salix koreensis and others, i.e. a singular tree, are in poor condition. Thus, relatively smaller individuals and separately situated trees need careful management in their protection. The analysis results of trunk's growth ratio showed that Pinus densiflora, Ginkgo biloba, Zelkova serrata are in good condition whereas Juniperus chinensis, Quercus variabilis, Salix koreensis are not. It is a recent trend that tree surgeries are gradually decreasing; there are a number of damaged trees with no maintenance/management, and several sites requiring mend trunks management and cabling, bracing in protection and management projects. Hence, in the future, local government and management organizations should plan for systematic management and establish a protection plan for the natural monument trees. Also, 12 sites were found to be in need to purchase lands in order to secure the growth spaces, and since most of these areas are available for purchase, it is needed to promote a budget and purchase those areas through persuasion of the owner. These areas seems crucial in order to maximize the effect of conservation efforts and budgets for the preservation and restoration of the old trees.

• Journal of Intelligence and Information Systems
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• v.26 no.2
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• pp.131-145
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• 2020

In line with the trend of industrial innovation, IoT technology utilized in a variety of fields is emerging as a key element in creation of new business models and the provision of user-friendly services through the combination of big data. The accumulated data from devices with the Internet-of-Things (IoT) is being used in many ways to build a convenience-based smart system as it can provide customized intelligent systems through user environment and pattern analysis. Recently, it has been applied to innovation in the public domain and has been using it for smart city and smart transportation, such as solving traffic and crime problems using CCTV. In particular, it is necessary to comprehensively consider the easiness of securing real-time service data and the stability of security when planning underground services or establishing movement amount control information system to enhance citizens' or commuters' convenience in circumstances with the congestion of public transportation such as subways, urban railways, etc. However, previous studies that utilize image data have limitations in reducing the performance of object detection under private issue and abnormal conditions. The IoT device-based sensor data used in this study is free from private issue because it does not require identification for individuals, and can be effectively utilized to build intelligent public services for unspecified people. Especially, sensor data stored by the IoT device need not be identified to an individual, and can be effectively utilized for constructing intelligent public services for many and unspecified people as data free form private issue. We utilize the IoT-based infrared sensor devices for an intelligent pedestrian tracking system in metro service which many people use on a daily basis and temperature data measured by sensors are therein transmitted in real time. The experimental environment for collecting data detected in real time from sensors was established for the equally-spaced midpoints of 4×4 upper parts in the ceiling of subway entrances where the actual movement amount of passengers is high, and it measured the temperature change for objects entering and leaving the detection spots. The measured data have gone through a preprocessing in which the reference values for 16 different areas are set and the difference values between the temperatures in 16 distinct areas and their reference values per unit of time are calculated. This corresponds to the methodology that maximizes movement within the detection area. In addition, the size of the data was increased by 10 times in order to more sensitively reflect the difference in temperature by area. For example, if the temperature data collected from the sensor at a given time were 28.5℃, the data analysis was conducted by changing the value to 285. As above, the data collected from sensors have the characteristics of time series data and image data with 4×4 resolution. Reflecting the characteristics of the measured, preprocessed data, we finally propose a hybrid algorithm that combines CNN in superior performance for image classification and LSTM, especially suitable for analyzing time series data, as referred to CNN-LSTM (Convolutional Neural Network-Long Short Term Memory). In the study, the CNN-LSTM algorithm is used to predict the number of passing persons in one of 4×4 detection areas. We verified the validation of the proposed model by taking performance comparison with other artificial intelligence algorithms such as Multi-Layer Perceptron (MLP), Long Short Term Memory (LSTM) and RNN-LSTM (Recurrent Neural Network-Long Short Term Memory). As a result of the experiment, proposed CNN-LSTM hybrid model compared to MLP, LSTM and RNN-LSTM has the best predictive performance. By utilizing the proposed devices and models, it is expected various metro services will be provided with no illegal issue about the personal information such as real-time monitoring of public transport facilities and emergency situation response services on the basis of congestion. However, the data have been collected by selecting one side of the entrances as the subject of analysis, and the data collected for a short period of time have been applied to the prediction. There exists the limitation that the verification of application in other environments needs to be carried out. In the future, it is expected that more reliability will be provided for the proposed model if experimental data is sufficiently collected in various environments or if learning data is further configured by measuring data in other sensors.