• Journal of Computational Design and Engineering
• /
• v.1 no.2
• /
• pp.103-115
• /
• 2014

The engineering design process is a creative process, and the designers must repeatedly apply Undo/Redo operations to modify CAD models to explore new solutions. Undo/Redo has become one of most important functions in interactive graphics and CAD systems. Undo/Redo in a collaborative CAD system is also very helpful for collaborative awareness among a group of cooperative designers to eliminate misunderstanding and to recover from design error. However, Undo/Redo in a collaborative CAD system is much more complicated. This is because a single erroneous operation is propagated to other remote sites, and operations are interleaved at different sites. This paper presents a multi-user selective Undo/Redo approach in full distributed collaborative CAD systems. We use site ID and State Vectors to locate the Undo/Redo target at each site. By analyzing the composition of the complex CAD model, a tree-like structure called Feature Combination Hierarchy is presented to describe the decomposition of a CAD model. Based on this structure, the dependency relationship among features is clarified. B-Rep re-evaluation is simplified with the assistance of the Feature Combination Hierarchy. It can be proven that the proposed Undo/Redo approach satisfies the intention preservation and consistency maintenance correctness criteria for collaborative systems.

• Journal of the Korea Society of Computer and Information
• /
• v.25 no.11
• /
• pp.41-50
• /
• 2020

Sentimental analysis begins with the search for words that determine the sentimentality inherent in data. Managers can understand market sentimentality by analyzing a number of relevant sentiment words which consumers usually tend to use. In this study, we propose exploring performance of feature selection methods embedded with Particle Swarm Optimization Multi Objectives Evolutionary Algorithms. The performance of the feature selection methods was benchmarked with machine learning classifiers such as Decision Tree, Naive Bayesian Network, Support Vector Machine, Random Forest, Bagging, Random Subspace, and Rotation Forest. Our empirical results of opinion mining revealed that the number of features was significantly reduced and the performance was not hurt. In specific, the Support Vector Machine showed the highest accuracy. Random subspace produced the best AUC results.

• KSCE Journal of Civil and Environmental Engineering Research
• /
• v.35 no.2
• /
• pp.327-340
• /
• 2015

General Circulation Models (GCMs) are the basic tool used for modelling climate. However, the spatio-temporal discrepancy between GCM and observed value, therefore, the models deliver output that are generally required calibration for applied studies. Which is generally done by Multi-Model Ensemble (MME) approach. Stochastic downscaling methods have been used extensively to generate long-term weather sequences from finite observed records. A primary objective of this study is to develop a forecasting scheme which is able to make use of a MME of different GCMs. This study employed a Nonstationary Hidden Markov Chain Model (NHMM) as a main tool for downscaling seasonal ensemble forecasts over 3 month period, providing daily forecasts. Our results showed that the proposed downscaling scheme can provide the skillful forecasts as inputs for hydrologic modeling, which in turn may improve water resources management. An application to the Nakdong watershed in South Korea illustrates how the proposed approach can lead to potentially reliable information for water resources management.

• Journal of the Korean Association of Geographic Information Studies
• /
• v.18 no.2
• /
• pp.59-74
• /
• 2015

The purpose of this study is to analyze reasonable green area ratios for mitigating urban heat island considering various land use types. Land uses of 5 types such as single residential, multi residential, commercial area, public facility, and industrial area were considered. Green areas were extracted from the tree attribution of land cover. Effect of urban heat island was analysed by the surface temperature of ASTER thermal infrared radiance scanned daytime and nighttime. Mitigation effect of green area at daytime was higher than nighttime. Surface temperature of green area was low in single residential at daytime. But the difference of surface temperature by each land use type was small. The effect of surface temperature mitigation of green area was lower in industrial area. The results of reasonable green area ratios for mitigating urban heat island indicate that surface temperature was the lowest with green area ratio of 40~50% in single residential, multi residential, and commercial area at daytime. Surface temperature of nighttime was not changed much by green area ratios. Therefore, the results of this study will be suggested in urban development planning to construct effectively green area for mitigating urban heat island.

• Journal of Information Science Theory and Practice
• /
• v.7 no.4
• /
• pp.56-64
• /
• 2019

Planting intercropping in rubber plantations is another alternative for generating more income for farmers. However, farmers still lack the knowledge of choosing plants. In addition, information for decision making comes from many sources and is knowledge accumulated by the expert. Therefore, this research aims to create a decision support system for growing rubber trees for individual farmers. It aims to get the highest income and the lowest cost by using semantic web technology so that farmers can access knowledge at all times and reduce the risk of growing crops, and also support the decision supporting system (DSS) to be more intelligent. The integrated intercropping ontology and rule are a part of the decision-making process for selecting plants that is suitable for individual rubber plots. A list of suitable plants is important for decision variables in the allocation of planting areas for each type of plant for multiple purposes. This article presents designing and developing the intercropping ontology for DSS which defines a class based on the principle of intercropping in rubber plantations. It is grouped according to the characteristics and condition of the area of the farmer as a concept of the rubber plantation. It consists of the age of rubber tree, spacing between rows of rubber trees, and water sources for use in agriculture and soil group, including slope, drainage, depth of soil, etc. The use of ontology for recommended plants suitable for individual farmers makes a contribution to the knowledge management field. Besides being useful in DSS by offering options with accuracy, it also reduces the complexity of the problem by reducing decision variables and condition variables in the multi-objective optimization model of DSS.

• Korean Journal of Environment and Ecology
• /
• v.26 no.3
• /
• pp.463-471
• /
• 2012

Objective of this study is to provide basic information for developing more differentiated and targeted forest healing policy and Korean medical healing programs grounded on consumer preference for forest based Korean medical healing tourism products. The internet survey(CAWI) by percentage quota sampling with 400 Seoulite ages over 30 by the age, area, and gender was conducted, and 317 samples were used for a final analysis. 61.5% of the Seoulite associated 'forest bath/walking in the woods/tree' with an image of a forest based Korean medical healing tourism product, and preference for the product and the intention to use were positive at the percentages of 72.9% and 67.5%, respectively. Preferred areas were Seoul/Gyeonggi-do(53.5%) and Gangwon-do(38.8%). 'Stress solving and refreshment', 'taking a forest bath and a walk', and 'maintaining and promoting health' were the main purposes of the use. As for a therapy, 'walking therapy' was most preferred, and 'ergotherapy' was the next. First priority as for a use facility was 'healing trail', and 'professional medical facility' ranked second. Although important decision attributes were ' cost of use', 'food', and 'friendliness of medical staff', all the other sets of attributes related to use convenience, quality of medical service and tourism activities also recorded high, which forecasts higher consumer expectation for the product. As the result showing differences in consumer preference by the demographic segmentation, differentiated and segmented consumer needs should be considered when planing and managing a product. The scope of the study is limited to a demographic segmentation which is a basic stage of understanding consumer preference, therefore more detailed future researches on complicated and multi-dimensional consumer needs are required.

• Journal of the Korean Institute of Landscape Architecture
• /
• v.30 no.2
• /
• pp.70-78
• /
• 2002

The landscape disign of Gamcheon wholesale fish Market was designed around a turnkey base to promote the economy of Busan Metropolitan City, to establish a fishery marketing center and to modernize existing facilities. The objectives of the project were to promote the mood of an old market, while preserving its functions and efficiency as a market, to design outdoor spaces with natural resources and amenities in balance, and to create attractive tourist spots in connection with the wide area development plan. The project was oriented, fast, to enhance the functions of the market. For this purpose, a multi-dimensional space layout was designed in consideration of functions as a wholesale market. The safety of pedestrians was secured by separating lathes for vehicles and for pedestrians. Tree planting with various functions such as sheltering, wind breaking and guiding was planned. Secondly, nature-friendly and human-friendly landscaping design was attempted. For this, the beautiful natural resources of Amnam Park were utilized, and green spaces such as green bridges linking buildings in the wholesale market, and rooftop gardens were to be arranged. In addition, environment-friendly facilities such as roads paved with natural materials(i.e. gravel, shells) and program parking lots were to be planned. Thirdly, landscape design was considered to create attractive tourist spots. For example, a fish farm was created as a theme street for pedestrians and various water-friendly spaces such as pedestrian ramps, observatories and seaside streets were to be secured. The main contents are as follows. First, a green bridge to Ahnnam Park was introduced for a tour source and flower garden, an event plan and viewing deck open to the sea were planned on the bridge's axis. Secondly, for the effective land use plan concerning open space and convenience to visitors, a promenade was planned, which is connected with the theme plaza and small plazas by environmental sculptures in front of the market hall and at the gate. As well, an observatory and a roof garden help create three dimensional multi leveled space, with a good view of the natural landscape of the sea, sky and park Thirdly, landscape materials, such as trees and those for facilities, strengthened for protection against the seawind and salt damage were selected. The commercial market area was intended to be transformed a traditional functional area of efficiency and economy into an attractive marine leisure area where both tourists and neighbors can make use of it.

• Journal of Intelligence and Information Systems
• /
• v.19 no.2
• /
• pp.39-54
• /
• 2013

Recent explosive increase of electronic commerce provides many advantageous purchase opportunities to customers. In this situation, customers who do not have enough knowledge about their purchases, may accept product recommendations. Product recommender systems automatically reflect user's preference and provide recommendation list to the users. Thus, product recommender system in online shopping store has been known as one of the most popular tools for one-to-one marketing. However, recommender systems which do not properly reflect user's preference cause user's disappointment and waste of time. In this study, we propose a novel recommender system which uses data mining and multi-model ensemble techniques to enhance the recommendation performance through reflecting the precise user's preference. The research data is collected from the real-world online shopping store, which deals products from famous art galleries and museums in Korea. The data initially contain 5759 transaction data, but finally remain 3167 transaction data after deletion of null data. In this study, we transform the categorical variables into dummy variables and exclude outlier data. The proposed model consists of two steps. The first step predicts customers who have high likelihood to purchase products in the online shopping store. In this step, we first use logistic regression, decision trees, and artificial neural networks to predict customers who have high likelihood to purchase products in each product group. We perform above data mining techniques using SAS E-Miner software. In this study, we partition datasets into two sets as modeling and validation sets for the logistic regression and decision trees. We also partition datasets into three sets as training, test, and validation sets for the artificial neural network model. The validation dataset is equal for the all experiments. Then we composite the results of each predictor using the multi-model ensemble techniques such as bagging and bumping. Bagging is the abbreviation of "Bootstrap Aggregation" and it composite outputs from several machine learning techniques for raising the performance and stability of prediction or classification. This technique is special form of the averaging method. Bumping is the abbreviation of "Bootstrap Umbrella of Model Parameter," and it only considers the model which has the lowest error value. The results show that bumping outperforms bagging and the other predictors except for "Poster" product group. For the "Poster" product group, artificial neural network model performs better than the other models. In the second step, we use the market basket analysis to extract association rules for co-purchased products. We can extract thirty one association rules according to values of Lift, Support, and Confidence measure. We set the minimum transaction frequency to support associations as 5%, maximum number of items in an association as 4, and minimum confidence for rule generation as 10%. This study also excludes the extracted association rules below 1 of lift value. We finally get fifteen association rules by excluding duplicate rules. Among the fifteen association rules, eleven rules contain association between products in "Office Supplies" product group, one rules include the association between "Office Supplies" and "Fashion" product groups, and other three rules contain association between "Office Supplies" and "Home Decoration" product groups. Finally, the proposed product recommender systems provides list of recommendations to the proper customers. We test the usability of the proposed system by using prototype and real-world transaction and profile data. For this end, we construct the prototype system by using the ASP, Java Script and Microsoft Access. In addition, we survey about user satisfaction for the recommended product list from the proposed system and the randomly selected product lists. The participants for the survey are 173 persons who use MSN Messenger, Daum Caf$\acute{e}$, and P2P services. We evaluate the user satisfaction using five-scale Likert measure. This study also performs "Paired Sample T-test" for the results of the survey. The results show that the proposed model outperforms the random selection model with 1% statistical significance level. It means that the users satisfied the recommended product list significantly. The results also show that the proposed system may be useful in real-world online shopping store.

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

• The KIPS Transactions:PartD
• /
• v.16D no.4
• /
• pp.487-496
• /
• 2009

This paper addresses an indexing scheme capable of efficiently processing range queries in a large-scale trajectory database. After discussing the drawbacks of previous indexing schemes, we propose a new scheme that divides the temporal dimension into multiple time intervals and then, by this interval, builds an index for the line segments. Additionally, a supplementary index is built for the line segments within each time interval. This scheme can make a dramatic improvement in the performance of insert and search operations using a main memory index, particularly for the time interval consisting of the segments taken by those objects which are currently moving or have just completed their movements, as contrast to the previous schemes that store the index totally on the disk. Each time interval index is built as follows: First, the extent of the spatial dimension is divided onto multiple spatial cells to which the line segments are assigned evenly. We use a 2D-tree to maintain information on those cells. Then, for each cell, an additional 3D $R^*$-tree is created on the spatio-temporal space (x, y, t). Such a multi-level indexing strategy can cure the shortcomings of the legacy schemes. Performance results obtained from intensive experiments show that our scheme enhances the performance of retrieve operations by 3$\sim$10 times, with much less storage space.