• Journal of Korean Society of Transportation
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• v.26 no.1
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• pp.127-135
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• 2008

Generally, optimum shortest path algorithms adopt single attribute objective among several attributes such as travel time, travel cost, travel fare and travel distance. On the other hand, multi-objective shortest path algorithms find the shortest paths in consideration with multi-objectives. Up to recently, the most of all researches about multi-objective shortest paths are proceeded only in single transportation mode networks. Although, there are some papers about multi-objective shortest paths with multi-modal transportation networks, they did not consider transfer problems in the optimal solution level. In particular, dynamic programming method was not dealt in multi-objective shortest path problems in multi-modal transportation networks. In this study, we propose a multi-objective shortest path algorithm including dynamic programming in order to find optimal solution in multi-modal transportation networks. That algorithm is based on two-objective node-based label correcting algorithm proposed by Skriver and Andersen in 2000 and transfer can be reflected without network expansion in this paper. In addition, we use non-dominated paths and tree sets as labels in order to improve effectiveness of searching non-dominated paths. We also classifies path finding attributes into transfer and link travel attribute in limited transit networks. Lastly, the calculation process of proposed algorithm is checked by computer programming in a small-scaled multi-modal transportation network.

• Journal of Forest and Environmental Science
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• v.15 no.1
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• pp.1-9
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• 1999

Noticing the intrinsic growing habit variations of hardwood species which is indigenous to the natural deciduous forest, eighteen tree species in overstory were selected for comparative evaluating tree form so as to develop the tree form index (TFI). Selected six tree form attributes were arbitrarily divided four assessment criteria and given appropriate scores. Eighteen tree species were undergone corresponding scores, converted to percentage base, and estimated TFI by the summation of the six scoring values. Cluster analysis was carried out to review which attribute would have been shared among species based on dissimilarity of scores for each pair of species in $18{\times}6$ data matrix. The result showed that Populus davidiana had the highest TFI value of 80.8 and Carpinus cordata had the lowest TFI va1ue of 46.3. The species which received more than 70 of TFI are Populus davidiana, Betula costata, Fraxinus mandshurica, and Ulmus davidiana var. japonica, characterized by the advantage of straight and longer bole, the narrower crown, and the thinner branch. On the contrary, such species as Sorbus alnifolia. Prunus sargentii, Acer mandshuricum, Juglans mandshurica, and Carpinus cordata received less than 60 of TFI, characterized by the disadvantage of the crooked or forked stem. the wider or deeper crown. and the thicker branch. In the dendrogram produced by cluster analysis, arbitrary value of Euclidean distance 10 divided eighteen species into four distinctive groups. and the typical characteristics of each group were discussed.

• Journal of Korea Multimedia Society
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• v.9 no.7
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• pp.927-937
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• 2006

Auto-playing programs are often used in behalf of human players in MMORPG(Massively Multi-player Online Role Playing Game). By playing automatically and continuously, it helps to speed up the game character's level-up process. However, the auto-playing programs, either software or hardware, do harm to games servers in various ways including abuse of resources. In this paper, we propose a way of detecting the auto programs by analyzing the window event sequences produced by the game players. In our proposed method, the event sequences are transformed into a set of attributes, and the Decision Tree learning is applied to classify the data represented by the set of attribute values into human or auto player. The results from experiments with several MMORPG show that the Decision Tree learning with proposed method can identify the auto-playing programs with high accuracy.

• Journal of Korean Society for Geospatial Information Science
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• v.20 no.2
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• pp.55-61
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• 2012

The primary factors of the LOS(Line-of-Sight) analysis process are terrain height, camera capacity, and canopy cover. The canopy cover rate differs depending on the changing season, and its value is influenced by the tree density, tree height, and etc. This study generated the canopy cover value based on relationship between NDVI(Normalized Difference Vegetation Index) and DMT(Density Measure % of Tree/Canopy Cover), which is a digital map attribute, and then performed the LOS analysis on six station of test sites. As results, It was found that NDVI and DMT are correlated with each other through the experiments. Based on this finding, new DMT map can be generated using NDVI. Also, There is a difference between the result of visibility analysis using the present DMT and one using a new DMT. Especially, the spatial distributions of the detected visible areas are significantly different between the two visibility analysis results.

• Journal of Information Processing Systems
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• v.16 no.5
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• pp.1113-1128
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• 2020

Ad hoc networks play an important role in mobile communications, and the performance of nodes has a significant impact on the choice of communication links. To ensure efficient and secure data forwarding and delivery, an intelligent routing protocol (IAODV) based on learning method is constructed. Five attributes of node energy, rate, credit value, computing power and transmission distance are taken as the basis of segmentation. By learning the selected samples and calculating the information gain of each attribute, the decision tree of routing node is constructed, and the rules of routing node selection are determined. IAODV algorithm realizes the adaptive evaluation and classification of network nodes, so as to determine the optimal transmission path from the source node to the destination node. The simulation results verify the feasibility, effectiveness and security of IAODV.

• The Transactions of the Korea Information Processing Society
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• v.3 no.6
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• pp.1542-1552
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• 1996

This paper presents a design and implementation of an extended directory system in manage and provide an effective search operation of the DFR(Document Filing and Retrieval) Object's attributes. For this, the design and implementation of a configuration model for interworking between the DFR and directory systems, an association mechanisms between two application's operation, extended directory schema and extended DIT(Directory Information Tree) are described. In a distributed environment, the interworking between the DFR and directory system implemented by using QUIPU 8.0 of ISODE(ISO Development Environment) directory system is tested. based on the result of this paper, an extended model of the directory system is proposed for proving search operation of various application's objects.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.4
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• pp.1975-1988
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• 2019

Short-term traffic flow prediction plays an important role in intelligent transportation systems (ITS) in areas such as transportation management, traffic control and guidance. For short-term traffic flow regression predictions, the main challenge stems from the non-stationary property of traffic flow data. In this paper, we design an ensemble cascading prediction framework based on extremely randomized trees (extra-trees) using a boosting technique called EET to predict the short-term traffic flow under non-stationary environments. Extra-trees is a tree-based ensemble method. It essentially consists of strongly randomizing both the attribute and cut-point choices while splitting a tree node. This mechanism reduces the variance of the model and is, therefore, more suitable for traffic flow regression prediction in non-stationary environments. Moreover, the extra-trees algorithm uses boosting ensemble technique averaging to improve the predictive accuracy and control overfitting. To the best of our knowledge, this is the first time that extra-trees have been used as fundamental building blocks in boosting committee machines. The proposed approach involves predicting 5 min in advance using real-time traffic flow data in the context of inherently considering temporal and spatial correlations. Experiments demonstrate that the proposed method achieves higher accuracy and lower variance and computational complexity when compared to the existing methods.

• Journal of the Korean Institute of Landscape Architecture
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• v.24 no.4
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• pp.1-22
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• 1997

This paper was focused on the efficient management of landscape woody plants, and concerned itself with their important role in the urban environment. Based on the philosophy that there is nothing that can be done without an inventory, the purpose of this study was to develop an inventory system and iris proper application to a site for establishing a management plan Two different approaches were used, The first was to make a newly structured inventory system through collecting, analyzing, and evaluating various types of inventories used in Korea, the U. S. A., and Japan. The second approach was to apply a newly designed inventory system to the case study area. using GIS 'as a tool of spacial analysis and statistics for making decisions. The results could be summarized as follows; 1. In Korea, most of the Landscape Woozy Plants Inventories had datas which represented possession of trees, and only the work which they had done according to their traditional ways, There was no data related to the conditions, management needs, and site conditions of individual trees, This is essential information for organizing an inventory system . 2. There needs to be data which is balanced, containing tree characteristics and site characteristics. Through such information the management needs could be adjusted properly. The inventory list described in this paper was determined by botanical identity, placement condition, condition of tree, and types of work for maintaining as well as improving the condition of each tree One of the most important things was to determine the location data of each tree so as to compare data with other trees. The data gained from the field survey still had some problems because of lack of scientific method for supporting objective views, and because of actual situations, especially in the field of evaluating site conditions and management needs. All data should be revised to fit a computer data management system , if possible 3. The GIS(Geographic Information System) application showed good performance in handling inventory data for decision making. All the data used for the GIS application was divided into location and non-spatial data. Using the location data, it was easy to find the exact location of each tree on the monitor and on the maps generated by the computer even in the actual managed trite, along with various attribute data. Therefore it could be said that the entire management plan should start from data of individual trees with their exact locations, for making concrete management goals through actual budget planning.

• Journal of KIISE:Databases
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• v.37 no.4
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• pp.177-184
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• 2010

In these day, many data including sensor, delivery, credit and stock data are generated continuously in massive quantity. It is difficult to learn from these data because they are large in volume and changing fast in their concepts. To handle these problems, learning methods based in sliding window methods over time have been used. But these approaches have a problem of rebuilding models every time new data arrive, which requires a lot of time and cost. Therefore we need very simple incremental learning methods. Bayesian method is an example of these methods but it has a disadvantage which it requries the prior knowledge(probabiltiy) of data. In this study, we propose a learning method based on attribute values. In the proposed method, even though we don't know the prior knowledge(probability) of data, we can apply our new method to data. The main concept of this method is that each attribute value is regarded as an expert learner, summing up the expert learners lead to better results. Experimental results show our learning method learns from data very fast and performs well when compared to current learning methods(decision tree and bayesian).

• Journal of the Korean Society of Environmental Restoration Technology
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• v.2 no.2
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• pp.78-87
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• 1999

This study was aimed to establish the method and process of the Biotope Mapping System.(B.M.S.) The main aspects of research for biotope were divided by 4 schemes such as biosphere, geosphere, antroposphere and evaluation informations. The cartographic function of GIS(geographic information system) was also used to mapping them. The B.M.S. had been progressed with 5 steps : (1) making research goals, (2) constructing the graphic and attribute databases, (3) classifying 3 types of biotope such as tree/shrub biotop, grass biotop and wetland biotop. (4) cross-analyzing biotope types against land use, habitat characters, relief characters and danger/disturbance elements, (5) evaluating the biotope's potentialities. Only 3 steps of them were done in this study. The results of applicating the B.M.S on the research site as followings : 1. The interdisciplinary researches were needed to develop the B.M.S in Korea since ecological habitat conditions of Germany, England are differed from them of Korea. 2. The distributions of the land uses in Maejuri, Seunghwan eup in Chonan city were mainly recorded by forest(29.82%), orchard(14.11%) and landscaping around building site(9.05%). 3. The percentages of the Tree/Shrub Biotope type were ranged by the orchard type(23.8%), natural and artificial deciduous type with natural coniferous(23.6%) and etc. 4. The Grass Biotope type was mainly recorded by the wild grassland type(27.99%), garden type(14.21%) and peddy field with wild grassland(13.24%). 5. The distributions of the wetland were pointed high at the wetland type with reed marsh and edge vegetation around wetland(54.79%) and etc.