• Proceedings of the IEEK Conference
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• 2002.06d
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• pp.195-198
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• 2002

We propose an efficient mixture Gaussian synthesis method for decision tree based state tying that produces better context-dependent models in a short period of training time. This method makes it possible to handle mixture Gaussian HMMs in decision tree based state tying algorithm, and provides higher recognition performance compared to the conventional HMM training procedure using decision tree based state tying on single Gaussian GMMs. This method also reduces the steps of HMM training procedure. We applied this method to training of PBS, and we expect to achieve a little point improvement in phoneme accuarcy and reduction in training time.

• Advances in concrete construction
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• v.14 no.1
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• pp.15-34
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• 2022

The use of waste rubber in concrete can reduce natural aggregate consumption and improve some technical properties of concrete. Although there are several equations for estimating the mechanical properties of concrete containing waste rubber, limited numbers of machine learning-based models have been proposed to predict the mechanical properties of rubbercrete. In this study, an extensive database of the mechanical properties of rubbercrete was gathered from a comprehensive survey of the literature. To model the mechanical properties of rubbercrete, M5P tree and linear gene expression programming (LGEP) methods as two machine learning techniques were employed to achieve reliable mathematical equations. Two procedures of input variable selection were considered in this study. The crucial component ratios of rubbercrete and concrete age were assumed as the input variables in the first procedure. In contrast, the volumes of the coarse and fine waste rubber and the compressive strength of concrete without waste rubber were considered the second procedure of the input variables. The results show that the models obtained by LGEP are more accurate than those achieved by the M5P model tree and existing traditional equations. Besides, the volumes of the coarse and fine waste rubber and the compressive strength of concrete without waste rubber are better predictors of the mechanical properties of rubbercrete compared to the first procedure of input variable selection.

• Communications for Statistical Applications and Methods
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• v.6 no.1
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• pp.159-168
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• 1999

We introduce a new conditional signed-rank test for the tree alternatives comparing several treatments with a control in the randomized block design. We demonstrate its performance by comparing with 3 classes of signed-rank tests proposed by Park et al.(1991) in some general situations. In most cases the proposed procedure is simpler to compute and has better power than others.

• Journal of applied mathematics & informatics
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• v.16 no.1_2
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• pp.115-123
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• 2004

A recursive tree is constructed by starting with a root node and repeatedly adjoining new nodes to one node of the tree already constructed. Such a tree can represent, for example, the heirarchy of a workforce of a company that grows via recruiting. At times of economic depression, the company may decide to layoff participants, and in some cases it is a fair policy to relieve the last senior worker (most recent entry in the tree). If we remove an edge from such a tree then it falls into two subtrees one of which contains the most recent entry. If we continue to remove edges from the successively smaller subtrees that contain the most recent entry, we eventually isolate the most recent entry. We consider how many randomly selected edges must be removed in average before isolating the most recent entry by this procedure.

• IE interfaces
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• v.6 no.2
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• pp.67-78
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• 1993

In this paper, we deal with the application of the fuzzy sets theory to evaluate and estimate the system reliability under the fault tree analysis. We formulate the uncertainty of component reliability to fuzzy sets, and propose a procedure for obtaining the system reliability in case the system structure is described by fault tree. An importance measure of each component is proposed. Computer program for fuzzy fault tree analysis(FFTA) is developed using C language to obtain the system reliability and the component‘s fuzzy importance.

• Journal of KIISE:Databases
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• v.27 no.2
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• pp.216-226
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• 2000

This paper suggests a new access path, hashed B-tree which is an efficient access method for integrity checking. Hashed B-tree is based on the observation that most query patterns in enforcing integrity constraints are point queries. Hashed B-tree compresses the key by hashing procedure, which reduces the height of tree and results in fast node search. This method has the advantages such as it can be implemented easily and use the B-tree concurrency control and recovery algorithm with minor modifications.

• Communications for Statistical Applications and Methods
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• v.10 no.3
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• pp.971-980
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• 2003

The tree method can be extended to multivariate responses, such as repeated measure and longitudinal data, by modifying the split function so as to accommodate multiple responses. Recently, some decision trees for multiple responses have been constructed by Segal (1992) and Zhang (1998). Segal suggested a tree can analyze continuous longitudinal response using Mahalanobis distance for within node homogeneity measures and Zhang suggested a tree can analyze multiple binary responses using generalized entropy criterion which is proportional to maximum likelihood of joint distribution of multiple binary responses. In this paper, we will modify CART procedure and suggest a new tree-based method that can analyze multiple binary responses using similarity measures.

• Journal of the Korean Data and Information Science Society
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• v.26 no.3
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• pp.639-652
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• 2015

In today's manufacturing environment, the process data can be easily measured and transferred to a computer for analysis in a real-time mode. As a result, it is possible to monitor several correlated quality variables simultaneously. Various multivariate statistical process control (MSPC) procedures have been presented to detect an out-of-control event. Although the classical MSPC procedures give the out-of-control signal, it is difficult to determine which variable has caused the signal. In order to solve this problem, data mining and machine learning techniques can be considered. In this paper, we applied the technique of decision tree learning to the MSPC, and we did simulation for MSPC procedures to monitor the bivariate normal process means. The results of simulation show that the overall performance of the MSPC procedure using decision tree learning technique is similar for several values of correlation coefficient, and the accurate classification rates for out-of-control are different depending on the values of correlation coefficient and the shift magnitude. The introduced procedure has the advantage that it provides the information about assignable causes, which can be required by practitioners.

• The Journal of the Korean dental association
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• v.50 no.12
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• pp.755-762
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• 2012

Objective : The aim of this study was to investigate risk factor, precaution and treatment of aspirated foreign body during dental procedure. Material and Methods : Twenty cases of accidental aspiration of the foreign body, which removed by bronchoscopy at the Asan Medical Center between 2008 and 2012, were analyzed retrospectively. Results : Ten cases of accidental aspiration were occurred during dental procedure. Symtoms include cough(65%), dyspnea(50%), sputum(25%) and wheezing(25%). The most common location of foreign body was right bronchial tree(50%), left bronchial tree(45%) and carina(5%). Patients risk factors were chronic obstructive pulmonary disease, lung cancer, pulmonary tuberculosis, esophageal cancer and vegetative state. Conclusion : Accidental aspiration or swallowing of dental instrument or material is not uncommon accidents in dental practice. Most foreign bodies enter into gastrointestinal tract spontaneously. But aspiration into broncho-trachea can be more serious events and must be treated as an emergency situation. Prompt emergency treatment and removal of the foreign body is necessary to avoid complication. Dentists must have knowledge about the precaution and be ready to deal with foreign body aspiration during dental procedures.

• Korean Journal of Remote Sensing
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• v.27 no.3
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• pp.389-401
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• 2011

Most nations around the world have expressed significant concern in the climate change due to a rapid increase in green-house gases and thus reach an international agreement to control total amount of these gases for the mitigation of global warming. As the most important absorber of carbon dioxide, one of major green-house gases, forest resources should be more tightly managed with a means to measure their total amount, forest biomass, efficiently and accurately. Forest biomass has close relations with forest areas and tree height. Airborne LiDAR data helps extract biophysical properties on forest resources such as tree height more efficiently by providing detailed spatial information about the wide-range ground surface. Many researchers have thus developed various methods to estimate tree height using LiDAR data, which retain different performance and characteristics depending on forest environment and data characteristics. In this study, we attempted to investigate such various techniques to estimate tree height, elaborate their advantages and limitations, and suggest future research directions. We first examined the characteristics of LiDAR data applied to forest studies and then analyzed methods on filtering, a precedent procedure for tree height estimation. Regarding the methods for tree height estimation, we classified them into two categories: individual tree-based and regression-based method and described the representative methods under each category with a summary of their analysis results. Finally, we reviewed techniques regarding data fusion between LiDAR and other remote sensing data for future work.