• Journal of Information Processing Systems
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• 제7권1호
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• pp.173-186
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• 2011

Due to the disadvantages of signature-based computer virus detection techniques, behavior-based detection methods have developed rapidly in recent years. However, current popular behavior-based detection methods only take API call sequences as program behavior features and the difference between API calls in the detection is not taken into consideration. This paper divides virus behaviors into separate function modules by introducing DLLs into detection. APIs in different modules have different importance. DLLs and APIs are both considered program calling resources. Based on the calling relationships between DLLs and APIs, program calling resources can be pictured as a tree named program behavior resource tree. Important block structures are selected from the tree as program behavior features. Finally, a virus detection model based on behavior the resource tree is proposed and verified by experiment which provides a helpful reference to virus detection.

• Industrial Engineering and Management Systems
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• 제4권1호
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• pp.102-108
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• 2005

This paper studies medical data classification methods, comparing decision tree and system reconstruction analysis as applied to heart disease medical data mining. The data we study is collected from patients with coronary heart disease. It has 1,723 records of 71 attributes each. We use the system-reconstruction method to weight it. We use decision tree algorithms, such as induction of decision trees (ID3), classification and regression tree (C4.5), classification and regression tree (CART), Chi-square automatic interaction detector (CHAID), and exhausted CHAID. We use the results to compare the correction rate, leaf number, and tree depth of different decision-tree algorithms. According to the experiments, we know that weighted data can improve the correction rate of coronary heart disease data but has little effect on the tree depth and leaf number.

• 신재생에너지
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• 제9권2호
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• pp.40-50
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• 2013

Government spending on research and development increased continuously is much more important to decision-making methodology for rational investment. Rely on a group of minority experts in the application of a general methodology, a tipping effect occur in specific technology field or difficult balanced procedure and objective control to maintain. This paper presents a qualitative-quantitative methodology to avoid such risks by utilizing Technology-Tree pertaining to energy R&D planning of the government Energy Technology Development program. Especially Energy Technology Development program "energy storage system" is applied to the analysis of Technology-Tree, mapping and analysis of existing government-supported projects during the recent 5 years, is derived essential missing elements of the technology value chain. This study suggests that significant evidence is utilized for improving efficiency of government R&D budget considering the importance of technology, domestic research-based and so forth, could be used to implement the R&D project planning.

• 한국환경복원기술학회지
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• 제6권6호
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• pp.86-95
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• 2003

The object of this paper is to correct check the tree situation and quantity around highway. Also, those data utilize in order to establish plan about how to the long and short term landscape construction and maintain program. The result of this study can be summarized as follows; 1. Tree decrease rates for 8 branch offices were Jongbu(5.62%), Gangwon(4.32%), Chungcheong (3.35%), Honam(5.62%), Gyeongbuk(3.06%), Gyeongnam(5.60%), Seorak training center(0.31%), Headquarter(1.54%). Also decrease causes were traffic accidents(1.8%), air po11ution(4.7%), humid damage(0.9%), insect and disease(1.2%), wind and rainfall(3.4%), dry damage(3.5%), cold damage (1.0%), fire(3.1%), damage of the man and anima1(4.1%), remove bad tree(13.1%), bad rooting(9.5%) and etc.(53.7%). 2. Improve methods of tree death problems were regulation management(ferti1ize, irrigation and pesticide work), improvement of draining system, Pull out the weeds, Plant native plants, utilize organic matter fertilize and plant environment trees.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2004년도 ICEIC The International Conference on Electronics Informations and Communications
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• pp.382-386
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• 2004

Recently, with the machine learning trend, most of the machine translation systems on over the world use two syntax tree sets of two relevant languages to learn syntactic tree transfer rules. However, for the English-Vietnamese language pair, this approach is impossible because until now we have not had a Vietnamese syntactic tree set which is correspondent to English one. Building of a very large correspondent Vietnamese syntactic tree set (thousands of trees) requires so much work and take the investment of specialists in linguistics. To take advantage from our available English-Vietnamese Corpus (EVC) which was tagged in word alignment, we choose the SITG (Stochastic Inversion Transduction Grammar) model to construct English- Vietnamese syntactic tree sets automatically. This model is used to parse two languages at the same time and then carry out the syntactic tree transfer. This English-Vietnamese bilingual syntactic tree set is the basic training data to carry out transferring automatically from English syntactic trees to Vietnamese ones by machine learning models. We tested the syntax analysis by comparing over 10,000 sentences in the amount of 500,000 sentences of our English-Vietnamese bilingual corpus and first stage got encouraging result $(analyzed\;about\;80\%)[5].$ We have made use the TBL algorithm (Transformation Based Learning) to carry out automatic transformations from English syntactic trees to Vietnamese ones based on that parallel syntactic tree transfer set[6].

• 상하수도학회지
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• 제29권6호
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• pp.693-702
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• 2015

The objective of this study is to investigate and evaluate that a roadside tree root intrudes sewer network systems. Two approaches were performed to assess the characteristics of tree root intrusion. First, the characteristics of tree roots that had invaded sewers were directly observed by means of closed-circuit television inspection robot. Second, the intrusion proportions of tree root into rain gutters in the sampling area were investigated. As tree species of low intrusion proportions, the results indicated that Ginkgo biloba Linn. and Acer buergerianum Miq. were 1.7% and 4.3%. On the other hand, tree species of high intrusion proportions were Metasequoia glyptostroboides Hu et Cheng, Ulmus davidiana var. japonica Nakai and Zelkova serrata Makino as 22.2%, 20.4%, and 17.6% respectively. In particular, sewers and gutters around Zelkova species should be the focus of maintenance work because of the high proportion of these trees on roadsides.

• Wind and Structures
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• 제18권1호
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• pp.69-82
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• 2014

Flow around a small white fir tree was investigated with varying the length of the bottom trunk (hereafter referred to as bottom gap). The velocity fields around the tree, which was placed in a closed-type wind tunnel test section, were quantitatively measured using particle image velocimetry (PIV) technique. Three different flow regions are observed behind the tree due to the bottom gap effect. Each flow region exhibits a different flow structure as a function of the bottom gap ratio. Depending on the gap ratio, the aerodynamic porosity of the tree changes and the different turbulence structure is induced. As the gap ratio increases, the maximum turbulence intensity is increased as well. However, the location of the local maximum turbulence intensity is nearly invariant. These changes in the flow and turbulence structures around a tree due to the bottom gap variation significantly affect the shelter effect of the tree. The wind-speed reduction is increased and the height of the maximum wind-speed reduction is decreased, as the gap ratio decreases.

• JSTS:Journal of Semiconductor Technology and Science
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• 제17권1호
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• pp.86-93
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• 2017

In this paper, we propose a novel defect detection method using component tree representations of scanning electron microscopy (SEM) images. The component tree contains rich information about the topological structure of images such as the stiffness of intensity changes, area, and volume of the lobes. This information can be used effectively in detecting suspicious defect areas. A quasi-linear algorithm is available for constructing the component tree and computing these attributes. In this paper, we modify the original component tree algorithm to be suitable for our defect detection application. First, we exclude pixels that are near the ground level during the initial stage of component tree construction. Next, we detect significant lobes based on multiple attributes and edge information. Our experiments performed with actual SEM wafer images show promising results. For a $1000{\times}1000$ image, the proposed algorithm performed the whole process in 1.36 seconds.

• Journal of the Korean Wood Science and Technology
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• 제47권6호
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• pp.700-708
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• 2019

To verify the possibility of using resistograph to estimate the age of big old living trees, we selected three Zelkova serrata and seven Pinus densiflora in Goesan. The mean diameters at breast height of Z. serrata and P. densiflora were 102 (92-116) cm and 80 (65-110) cm, respectively. The heights measured from the ground using a resistograph ranged at 1.2-4.3 m and 0.6-1.1 m for Z. serrata and P. Densiflora, respectively. The most appropriate needle speed to determine tree-ring boundaries for measuring ring width was 1500 r/min for both tree species. Alternatively, the suitable feed speeds for Z. serrata and P. densiflora were 50 cm/min and 150 cm/min, respectively. From the measured data, the mean numbers of tree rings of Z. serrata and P. densiflora were 57 (43-68) and 104 (93-124), respectively, and the mean tree-ring widths were 4.27 mm (3.18-5.09 mm) and 2.93 mm (2.32-3.34 mm), respectively. A comparison between the time series of tree-ring widths by resistograph and that from the local master chronologies tallied for the heartwood part. Finally, this study showed that resistograph can be used to estimate tree ages when a local master chronology is available.

• Journal of Information Processing Systems
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• 제19권5호
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• pp.652-662
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• 2023

Identifying highly discriminating genes is a critical step in tumor recognition tasks based on microarray gene expression profile data and machine learning. Gene selection based on tree models has been the subject of several studies. However, these methods are based on a single-tree model, often not robust to ultra-highdimensional microarray datasets, resulting in the loss of useful information and unsatisfactory classification accuracy. Motivated by the limitations of single-tree-based gene selection, in this study, ensemble gene selection methods based on multiple-tree models were studied to improve the classification performance of tumor identification. Specifically, we selected the three most representative tree models: ID3, random forest, and gradient boosting decision tree. Each tree model selects top-n genes from the microarray dataset based on its intrinsic mechanism. Subsequently, three ensemble gene selection methods were investigated, namely multipletree model intersection, multiple-tree module union, and multiple-tree module cross-union, were investigated. Experimental results on five benchmark public microarray gene expression datasets proved that the multiple tree module union is significantly superior to gene selection based on a single tree model and other competitive gene selection methods in classification accuracy.