• Journal of the Korean Institute of Traditional Landscape Architecture
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• v.38 no.1
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• pp.10-20
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• 2020

This study aims to analyze the developed characteristics of the knowledge and information of gardens through garden or flowering plant books compiled in the 15th and 19th centuries of Joseon Dynasty. Diachronically analysis of the garden or flowering plant books classified the characteristics in which knowledge and information about gardens are developed by the period, and looked at the factors. The results are as follows; First, the relationship between the authors who compiled the garden or flowering plant books had similar characteristics to the genealogy of Realist School of Confucianism(實學) in the Joseon Dynasty. Kang, Hee-An's practical features influenced later realist school of confucianism scholars. Lee, Su-Gwang has accumulated knowledge of the garden through his experience of traveling the diplomatic envoy to China. Since then, Hong Man-sun's ideology has been related to Charles, a member of the Southerners. Seo Yu-gu was also able to accept Realist School of Confucianism in an integrated way through the Jungnong school's theory and interaction with the Jungsang school. Ryu, Jung-Lim's relationship with the Jungnong school emerged as he added to the 『Jeungbosanrimgyeongje(增補山林經濟)』. Second, the 『Yanghwasorok(養花小錄)』, 『Jibongyuseol(芝峯類說)』 「Hwuimok(卉木)」, 『Hangjeongrok(閑情錄)』, 『Sanrimgyeongje(山林經濟)』 「Yanghwa(養花)」, 『Jeungbosanrimgyeongje(增補山林經濟)』 「Yanghwa(養花)」, 『Hwaamsurok(花庵隨錄)』 and 『Imwongyeongjeji(林園經濟志)』 「Yewonji(藝畹志)」 contain garden plant characteristics, cultivation methods, and management methods. The 『Imwongyeongjeji(林園經濟志)』 「Seomyongji(贍用志)」, 「Iunji(怡雲志)」, 「Sangtaekji(相宅志)」 contain details on the location selection of gardens, the layout of facilities, how to create them and materials. The description of these garden or flowering plant books was found to be the most common introduction with 55 percent, followed by methodologies(42.8%), the Lichi Theory(理氣論, 15.5%), the classification(12.4%), and the convention(1.9%). Third, based on the importance of knowledge and information on gardens, the garden or flowering plant books related to the period were classified as early period, including 『Yanghwasorok(養花小錄)』, 『Jibongyuseol(芝峯類說)』 which were compiled before the 17th century. The 18th-century compiled 『Sanrimgyeongje(山林經濟)』 and 『Jeungbosanrimgyeongje(增補山林經濟)』 were classified as middle period, and the 19th-century compilation of 『Imwongyeongjeji(林園經濟志)』 was classified as late period. The garden or flowering plant books were cited the contents of ancient Chinese books, the author's experiences and opinions contained in the preceding period in later garden books. And the reinforcement of garden knowledge was made to reflect the agricultural technology and expertise developed at the time of writing. Fourth, based on analysis of the development and acceptance of knowledge information in garden by period, In the early period was dealing with floriculture as a way to explore the logic of things. Later, in the 18th century, a vast influx of garden knowledge information came from China. Among scholars, they secured justification for garden creation as part of various knowledge-seeking activities, which expanded their expertise in gardens. In response to the trend of gardening in the 19th century, professional books were written based on knowledge and information on gardens that were collected in the past, and systems were established such as the collection and management of garden plants, construction methods, enjoying methods, and self-realization.

• Journal of the Korean Geosynthetics Society
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• v.14 no.2
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• pp.89-94
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• 2015

In this study, the mixed soil with an optimum mixed ratio was suggested in order to recycle the powdered sludge of basalt in Jeju Island as the impermeable liner materials. As the results of soil laboratory tests, the grain size of the powdered sludge of basalt is less than 0.1mm and the powdered sludge was classified into ML or CL category in accordance with the Unified Soil Classification System (USCS). Also, the grain size of natural soils is ranged from 0.1 mm to 10 mm and the soils were classified into SW category in USCS. To select the optimum mixed ratio of powdered sludge, the variable permeability test was performed to various mixed soils with different powdered sludge amount under both optimum compaction and field conditions. As the results of permeability tests, the coefficient of permeability of mixed soils was decreased with increasing the mixed ratio of powdered sludge, and the mixed soil with mixed ratio of 60% has the minimum coefficient of permeability. Therefore, the optimum mixed ratio of powdered sludge is 60% for recycling the powdered sludge of basalt as the impermeable liner materials.

• Journal of Korean Society of Forest Science
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• v.83 no.3
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• pp.322-330
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• 1994

The Universal Soil Loss Equation (USLE) has been widely used to predict long-term soil loss by incorporating several erosion factors, such as rainfall, soil, topography, and vegetation. This study is aimed to introduce the LISLE within geographic information system(GIS) environment. The Kwangneung Experimental Forest located in Kyongki Province was selected for the study area. Initially, twelve years of hourly rainfall records that were collected from 1982 to 1993 were processed to obtain the rainfall factor(R) value for the LISLE calculation. Soil survey map and topographic map of the study area were digitized and subsequent input values(K, L, S factors) were derived. The cover type and management factor (C) values were obtained from the classification of Landsat Thematic Mapper(CM) satellite imagery. All these input values were geographically registered over a common map coordinate with $25{\times}25m^2$ ground resolution. The USLE was calculated for every grid location by selecting necessary input values from the digital base maps. Once the LISLE was calculated, the resultant soil loss values(A) were represented by both numerical values and map format. Using GIS to run the LISLE, it is possible to pent out the exact locations where soil loss potential is high. In addition, this approach can be a very effective tool to monitor possible soil loss hazard under the situations of forest changes, such as conversion of forest lands to other uses, forest road construction, timber harvesting, and forest damages caused by fire, insect, and diseases.

• Journal of KIISE
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• v.43 no.10
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• pp.1085-1093
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• 2016

Community-based Question Answering system is a system which provides answers for each question from the documents uploaded on web communities. In order to enhance the capacity of question analysis, former methods have developed specific rules suitable for a target region or have applied machine learning to partial processes. However, these methods incur an excessive cost for expanding fields or lead to cases in which system is overfitted for a specific field. This paper proposes a multiple machine learning method which automates the overall process by adapting appropriate machine learning in each procedure for efficient processing of community-based Question Answering system. This system can be divided into question analysis part and answer selection part. The question analysis part consists of the question focus extractor, which analyzes the focused phrases in questions and uses conditional random fields, and the question type classifier, which classifies topics of questions and uses support vector machine. In the answer selection part, the we trains weights that are used by the similarity estimation models through an artificial neural network. Also these are a number of cases in which the results of morphological analysis are not reliable for the data uploaded on web communities. Therefore, we suggest a method that minimizes the impact of morphological analysis by using character features in the stage of question analysis. The proposed system outperforms the former system by showing a Mean Average Precision criteria of 0.765 and R-Precision criteria of 0.872.

• Journal of Digital Convergence
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• v.10 no.11
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• pp.427-432
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• 2012

The article herein suggested a compound repository and a descriptive method to develop a compound knowledge process. A data target saved in a compound knowledge repository suggested in this article includes all compound knowledge meta data and digital resources, which can be divided into the three following factors according to the purpose: user roles, functional elements, and service ranges. The three factors are basic components to describe abstract models of repository. In this article, meta data of compound knowledge are defined by being classified into the two factors. A component stands for the property about a main agent, activity unit or resource that use and create knowledge, and a context presents the context in which knowledge object are included. An agent of the compound knowledge process performs classification, registration, and pattern information management of composite knowledge, and serves as data flow and processing between compound knowledge repository and user. The agent of the compound knowledge process consists of the following functions: warning to inform data search and extraction, data collection and output for data exchange in an distributed environment, storage and registration for data, request and transmission to call for physical material wanted after search of meta data. In this article, the construction of a compound knowledge repository for recommendation system to be developed can serve a role to enhance learning productivity through real-time visualization of timely knowledge by presenting well-put various contents to users in the field of industry to occur work and learning at the same time.

• Journal of the Korean Institute of Landscape Architecture
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• v.38 no.5
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• pp.31-41
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• 2010

This research aims to present a methodological approach for repurposing small pockets of national/public lands, which can be constructed as parks, through an investigation of the present status of these areas of national/public lands that are scattered around Busan Megalopolis as well as the suitability of their construction. In order to attain this, this study looked at the present status of these small areas of national/public lands by utilizing a national land, city land list (lot number), land registration map and satellite image of Busan Megalopolis, and evaluating their suitability as parks through GIS analysis and classification. As a result, these small areas of lands with the potential to be turned into parks include 516 spots($375,934m^2$). Geographically, 39% of these areas are located on flat land and are the most scattered. 260 places met the requirements for optimal placement for conversion, while convenience included 305 places, and availability 267 places. The most optimal of the places meeting such standards include 61 spots. The characteristics of these areas of national/public lands include being below $500m^2$, with flatlands and open areas above a 5' grade occupy the highest ratio, accounting for 25.4% of the land studied. These results have offered a methodology for a GIS DB, which can visualize the data for a positive utilization be yond the simple level of the maintenance/preservation of national/public lands and provide basic data for the utilization and management of these types of areas in the future.

• Journal of KIISE:Software and Applications
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• v.29 no.7
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• pp.465-475
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• 2002

An object-oriented framework supports efficient component-based software development by providing a flexible architecture that can be decomposed into easily modifiable and composable classes. Object-oriented frameworks require thorough testing as they are intended to be reused repeatedly In developing numerous applications. Furthermore, additional testing is needed each time the framework is modified and extended for reuse. To test a framework, it must be instantiated into a complete, executable system. It is, however, practically impossible to test a framework exhaustively against all kinds of framework instantiations, as possible systems into which a framework can be configured are infinitely diverse. If we can classify possible configurations of a framework into a finite number of groups so that all configurations of a group have the same structural or behavioral characteristics, we can effectively cover all significant test cases for the framework testing by choosing a representative configuration from each group. This paper proposes a systematic method of classifying object structures of a framework hotspot and extracting structural test patterns from them. This paper also presents how we can select an instance of object structure from each extracted test pattern for use in the frameworks hotspot testing. This method is useful for selection of optimal test cases and systematic construction of executable test target.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.39 no.4
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• pp.235-243
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• 2021

River surveying is conducted to acquire basic geographic data for river master plans and various river maintenance, and it is also used to predict changes after river maintenance construction. ABL (Airborne Bathymetric LiDAR) system is a cutting-edge surveying technology that can simultaneously observe the water surface and river bed using a green laser, and has many advantages in river surveying. In order to use the ABL data for river surveying, it is prerequisite step to segment and extract the water surface and river bed points from the original point cloud data. In this study, point cloud segmentation was performed by applying the ground filtering technique, ATIN (Adaptive Triangular Irregular Network) to the ABL data and then, the water surface and riverbed point clouds were extracted sequentially. In the Gokgyocheon river area, Chungcheongnam-do, the experiment was conducted with the dataset obtained using the Leica Chiroptera 4X sensor. As a result of the study, the overall classification accuracy for the water surface and riverbed was 88.8%, and the Kappa coefficient was 0.825, confirming that the ABL data can be effectively used for river surveying.

• KIPS Transactions on Software and Data Engineering
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• v.7 no.11
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• pp.435-442
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• 2018

Outlier detection means to detect data samples that deviate significantly from the distribution of normal data. Most outlier detection methods calculate an outlier score that indicates the extent to which a data sample is out of normal state and determine it to be an outlier when its outlier score is above a given threshold. However, since the range of an outlier score is different for each data and the outliers exist at a smaller ratio than the normal data, it is very difficult to determine the threshold value for an outlier score. Further, in an actual situation, it is not easy to acquire data including a sufficient amount of outliers available for learning. In this paper, we propose a clustering-based outlier detection method by constructing a model representing a normal data region using only normal data and performing binary classification of outliers and normal data for new data samples. Then, by dividing the given normal data into chunks, and constructing a clustering model for each chunk, we expand it to the ensemble method combining the decision by the models and apply it to the streaming data with dynamic changes. Experimental results using real data and artificial data show high performance of the proposed method.

• Journal of Internet Computing and Services
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• v.19 no.6
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• pp.21-29
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• 2018

In the era of the 4-th industrial revolution, the concept of smart factory is emerging. There are efforts to predict the occurrences of facility errors which have negative effects on the utilization and productivity by using data analysis. Data composed of the situation of a facility error and the type of the error, called the facility error log, is required for the prediction. However, in many manufacturing companies, the types of facility error are not precisely defined and categorized. The worker who operates the facilities writes the type of facility error in the form with unstructured text based on his or her empirical judgement. That makes it impossible to analyze data. Therefore, this paper proposes a framework for constructing a phrase network to support the identification and classification of facility error types by using facility error logs written by operators. Specifically, phrase indicating the types are extracted from text data by using dictionary which classifies terms by their usage. Then, a phrase network is constructed by calculating the similarity between the extracted phrase. The performance of the proposed method was evaluated by using real-world facility error logs. It is expected that the proposed method will contribute to the accurate identification of error types and to the prediction of facility errors.