• Journal of the Korean Association of Oral and Maxillofacial Surgeons
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• v.37 no.5
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• pp.343-348
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• 2011

Introduction: Third molar extraction is one of the most common procedures in oral and maxillofacial surgery. The impacted third molar causes many pathological conditions, such as pericoronitis, caries, periodontitis, resorption of adjacent teeth, and cyst or tumors associated with impacted teeth. Extraction is often considered the treatment of choice for impacted lower third molars. On the other hand, imprudent extraction of deeply impacted third molars can cause permanent complications, such as inferior alveolar nerve damage. Therefore, guidelines for the extraction of lower third molars should be set to prevent embarrassing complications. This study examined the indication and current trends of the extracted lower third molars in the dental hospital of a dental college. Materials and Methods: 557 extracted third molars were evaluated at the department of oral and maxillofacial surgery of Yonsei University. The chief complaint, diagnosis, age and degree of impaction were analyzed to determine the tendency for the extraction of asymptomatic lower third molars. Results: The percentage of asymptomatic third molars was 40.8%. In cases of full impacted tooth or full erupted tooth, the percentage of asymptomatic teeth was more than 50% (52.4% and 54.3, respectively). Among those partially impacted teeth, 73.1% of them showed symptoms, such as pain, tenderness and swelling. In terms of age, pericoronitis was evident at a younger age, and dental caries/periodontitis was the main cause of removal in those aged over 50. Twenty nine cases (1.6%) had teeth associated with pathological changes Conclusion: The incidence of pathological changes to the lower third molar was relatively low. Surgical extraction is recommended in cases of partially impacted teeth. In Korea, the incidence of asymptomatic third molar extraction was relatively higher than in European countries. More careful attention would be desirable to consider the risks and benefits of lower third molar extraction.

• Journal of Korean Society of Forest Science
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• v.102 no.2
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• pp.229-238
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• 2013

This study was conducted to analyze on the operational cost of logging operations in the whole-tree logging operation system by tower-yarder and swing-yarder, and in the cut-to-length logging operation system by excavator with grapple in order to spread efficient logging operation technique and to establish the logging operation system. In the results of the analysis of operation cost, in case of the whole-tree logging operation system, the operation cost was 2,099 won/$m^3$ in felling by chain saw, 28,286 won/$m^3$ in yarding by tower-yarder, 18,265 won/$m^3$ in yarding by swing-yarder, 18,939 won/$m^3$ in bucking by excavator with grapple and chain saw, 20,484 won/$m^3$ in forwarding and accumulation by wheel type mini-forwarder, 12,701 won/$m^3$ in forwarding and accumulation by excavator with grapple and small forwarding vehicle. In case of the cut-to-length logging operation system, the operation cost was 10,160 won/$m^3$ in felling and bucking by chain saw, 7,567 won/$m^3$ in cut-to-length extraction by excavator with grapple, 6,982 won/$m^3$ in branches and leaves extraction by excavator with grapple, 3,040 won/$m^3$ in the operation road construction by excavator with grapple, 20,484 won/$m^3$ in forwarding and accumulation by wheel type mini-forwarder, 12,701 won/$m^3$ in forwarding and accumulation by excavator with grapple and small forwarding vehicle.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.42 no.4 s.304
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• pp.95-102
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• 2005

In this paper, we propose a user friendly object-based image retrieval system using the interaction between cortex and hippocampus. Most existing ways of queries in content-based image retrieval rely on query by example or query by sketch. But these methods of queries are not adequate to needs of people's various queries because they are not easy for people to use and restrict. We propose a method of automatic color object extraction using CSB tree map(Color and Spatial based Binary をn map). Extracted objects were transformed to bit stream representing information such as color, size and location by region labelling algorithm and they are learned by the hippocampal neural network using the interplay between cortex and hippocampus. The cells of exciting at peculiar features in brain generate the special sign when people recognize some patterns. The existing neural networks treat each attribute of features evenly. Proposed hippocampal neural network makes an adaptive fast content-based image retrieval system using excitatory learning method that forwards important features to long-term memories and inhibitory teaming method that forwards unimportant features to short-term memories controlled by impression.

• Journal of Internet Computing and Services
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• v.10 no.5
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• pp.65-78
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• 2009

The most commonly adopted approach to find valuable information from tree data is to extract frequently occurring subtree patterns from them. Because mining frequent tree patterns has a wide range of applications such as xml mining, web usage mining, bioinformatics, and network multicast routing, many algorithms have been recently proposed to find the patterns. However, existing tree mining algorithms suffer from several serious pitfalls in finding frequent tree patterns from massive tree datasets. Some of the major problems are due to (1) modeling data as hierarchical tree structure, (2) the computationally high cost of the candidate maintenance, (3) the repetitious input dataset scans, and (4) the high memory dependency. These problems stem from that most of these algorithms are based on the well-known apriori algorithm and have used anti-monotone property for candidate generation and frequency counting in their algorithms. To solve the problems, we base a pattern-growth approach rather than the apriori approach, and choose to extract maximal frequent subtree patterns instead of frequent subtree patterns. The proposed method not only gets rid of the process for infrequent subtrees pruning, but also totally eliminates the problem of generating candidate subtrees. Hence, it significantly improves the whole mining process.

• Korean Journal of Remote Sensing
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• v.39 no.5_4
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• pp.1155-1164
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• 2023

Currently, the National Forest Inventory (NFI) collects tree information by human, so the range and time of the survey are limited. Research is actively being conducted to extract tree information from a large area using aerial Light Detection And Ranging (LiDAR) and aerial photographs, but it does not reflect the characteristics of forest areas in Korea because it is conducted in areas with wide tree spacing or evenly spaced trees. Therefore, this study proposed a methodology for generating Digital Surface Model (DSM), Digital Elevation Model (DEM), and Canopy Height Model (CHM) images using aerial LiDAR, extracting the tree height through the local Maxima, and calculating the Diameter at Breath Height (DBH) through the DBH-tree height formula. The detection accuracy of trees extracted through the proposed methodology was 88.46%, 86.14%, and 84.31%, respectively, and the Root Mean Squared Error (RMSE) of DBH calculated based on the tree height formula was around 5cm, confirming the possibility of using the proposed methodology. It is believed that if standardized research on various types of forests is conducted in the future, the scope of automation application of the manual national forest resource survey can be expanded.

• KSBB Journal
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• v.32 no.2
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• pp.117-123
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• 2017

Maple tree is a useful medical plant for obtaining bioactive materials such as pharmaceutics, cosmetics, food additive, etc., and there are 16 species of native maple trees in Korea. In this study, we evaluated the antioxidant activity of sap and crude extracts of Acer mono Max, a representative maple species. The crude extracts were obtained by solvent extraction (water, ethanol, and ethyl acetate) from its branches (bark and xylem). The phenolic contents and radical scavenging capacities of the extracts and the sap were evaluated in terms of half maximal effective concentration ($EC_{50}$) and kinetics by 2,2-diphenyl-1-picrylhydrazyl (DPPH) assay. The ethanol extracts showed the highest extraction yield, phenolic contents and antioxidant activity, and bark extracts showed better antioxidant activity than xylem extracts. The antioxidant activity of the sap was very low, but the $EC_{50}$ of ethanol and ethyl acetate extracts ranged from 68 to $79{\mu}g/mL$, similar to that ($60{\mu}g/mL$) of the control, butylated hydroxytoluene (BHT). The DPPH radical scavenging rate ($220{\sim}760{\mu}M/min$) and the second-order reaction rate constant ($6.48{\sim}7.04L/g{\cdot}min$) of these extracts were better than those of BHT ($55{\sim}370{\mu}M/min$ and $3.60L/g{\cdot}min$). These results suggest that A. mono Max. is one of the useful bioresources for obtaining antioxidant biologically active substances, and it is possible to obtain physiologically active substances from by-product of its pruning while minimizing the effect on the growth of the tree.

• Journal of Internet Computing and Services
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• v.12 no.5
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• pp.73-85
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• 2011

Lots of valuable textual information is used to extract relations between named entities from literature. Composite kernel approach is proposed in this paper. The composite kernel approach calculates similarities based on the following information:(1) Phrase structure in convolution parse tree kernel that has shown encouraging results. (2) Predicate-argument structure patterns. In other words, the approach deals with syntactic structure as well as semantic structure using a reciprocal method. The proposed approach was evaluated using various types of test collections and it showed the better performance compared with those of previous approach using only information from syntactic structures. In addition, it showed the better performance than those of the state of the art approach.

• The KIPS Transactions:PartD
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• v.19D no.4
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• pp.263-270
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• 2012

With the current development of high speed Internet and massive database technology, the amount of web documents increases rapidly, and thus, classifying those documents automatically is getting important. In this study, we propose an effective method to extract document features based on Hangeul morpheme and keyword analyses, and to classify non-structured documents automatically by predicting subjects of those documents. To extract document features, first, we select terms using a morpheme analyzer, form the keyword set based on term frequency and subject-discriminating power, and perform the scoring for each keyword using the discriminating power. Then, we generate the classification model by utilizing the commercial software that implements the decision tree, neural network, and SVM(support vector machine). Experimental results show that the proposed feature extraction method has achieved considerable performance, i.e., average precision 0.90 and recall 0.84 in case of the decision tree, in classifying the web documents by subjects.

• Information Systems Review
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• v.26 no.2
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• pp.83-93
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• 2024

This study proposes a preprocessing methodology based on Dynamic Time Warping (DTW) and k-Nearest Neighbors (kNN) to effectively represent time series data for predicting the completion quality of electroplating baths. The proposed DTW-based kNN preprocessing approach was applied to various regression models and compared. The results demonstrated a performance improvement of up to 43% in maximum RMSE and 24% in MAE compared to traditional decision tree models. Notably, when integrated with neural network-based regression models, the performance improvements were pronounced. The combined structure of the proposed preprocessing method and regression models appears suitable for situations with long time series data and limited data samples, reducing the risk of overfitting and enabling reasonable predictions even with scarce data. However, as the number of data samples increases, the computational load of the DTW and kNN algorithms also increases, indicating a need for future research to improve computational efficiency.

• Proceedings of the Korean Society of Crop Science Conference
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• 2017.06a
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• pp.182-182
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• 2017

The objective of this research was to determine controlling effects on rice blast (Pyricularia oryzae) in rice plants by using plant extracts from different extraction methods (water, boiling water, fermentation, and ethanol) from 38 agricultural materials of traditional agriculture. Rice blast was completely suppressed by 3% ethanol extracts in Rheum palmatum roots, and suppressed 97% and 77% by 10% ethanol extracts in onion bulb and pine tree leaves, respectively in a laboratory test. However, other agricultural materials showed low effect on suppression of rice blast. Additionally, in a seedling test, rice injury of two cultivars (Ilmibyeo and Hopyoungbyeo) against rice blast was reduced 40-71%, 29-63%, and 23-63% by 5 and 10% ethanol extracts in Rheum palmatum roots, onion bulb, and pine tree leaves, respectively, compared with non-treated controls. Rice injury of two cultivars (Ilmibyeo and Hopyoungbyeo) against rice blast was reduced by 21-55%, 23-46%, and 5-39% in response to Rheum palmatum roots, onion bulb, and pine tree leaf applications at 100, 200 and $400g/m^2$ at 0 day after seeding, respectively, compared with non-treated controls. Rice plants did not show any leaf injuries and growth reduction after treatments of the Rheum palmatum roots, onion bulb, and pine tree leaf extracts or soil application. Thus, the above materials may be used for controlling rice blast in organically produced rice fields.