• Asian Pacific Journal of Cancer Prevention
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• v.16 no.13
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• pp.5401-5406
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• 2015

Background: Brain metastases are the most common intra-cranial neoplasms. The incidence is on a rise due to advanced imaging techniques. Aims: The objective of the study was to analyse the clinical and demographic profile of patients with brain metastases from primary solid tumors. Materials and Methods: This is a retrospective single institutional study covering 130 consecutive patients with brain metastases from January 2007 to August 2014. Results: Some 64.6% of the patients were females. The majority were in the sixth decade of life. The site of the primary tumor was the lungs in 50.8% of the cases. The overall median time from the diagnosis of the primary malignancy to detection of brain metastases was 21.4 months. Survival was found to be significantly improved in patients with solitary brain lesions when compared to patients with multiple brain metastases, and in patients undergoing surgical excision with or without cranial irradiation when compared to whole brain irradiation alone. The majority of the cases belonged to the recursive partitioning analysis class II group. Whole brain radiation therapy was delivered to 79% of the patients. Conclusions: Most of the patients with brain metastases in the study belonged to recursive partitioning analysis classes II or III, and hence had poor prognosis. Most of the patients in the Indian context either do not satisfy the indications for surgical excision or are incapable of bearing the high cost associated with stereotactic radiosurgery. Treatment should be tailored on an individual basis to all these patients.

• Journal of the Institute of Convergence Signal Processing
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• v.4 no.4
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• pp.7-14
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• 2003

A number of embedded wavelet image coding methods have been proposed since the introduction of EZW(Embedded Zerotree Wavelet) algorithm. A common characteristic of these methods is that they use fundamental ideas found in the EZW algorithm. Especially, one of these methods is the SPIHT(Set Partitioning in Hierarchy Trees) algorithm, which became very popular since it was able to achieve equal or better performance than EZW without having to use an arithmetic encoder. In this paper We propose a recursive set partitioning in hierarchy trees(RSPIHT) algorithm for embedded image coding and evaluate it's effectiveness experimentally. The proposed RSPIHT algorithm takes the simple and regular form and the worst case time complexity of O(n). From the viewpoint of processing time, the RSPIHT algorithm takes about 16.4% improvement in average than the SPIHT algorithm at T-layer over 4 of experimental images. Also from the viewpoint of coding rate, the RSPIHT algorithm takes similar results at T-layer under 7 but the improved results at other T-layer of experimental images.

• School Mathematics
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• v.18 no.3
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• pp.625-645
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• 2016

This study clarified the big ideas related to teaching addition and subtraction of fractions with different denominators based on quantitative reasoning with unit and recursive partitioning. An analysis of this study urged us to re-consider the content related to the addition and subtraction of fraction. As such, this study analyzed textbooks and teachers' manuals developed from the fourth national mathematics curriculum to the most recent 2009 curriculum. In addition and subtraction of fractions with different denominators, it must be emphasized the followings: three-levels unit structure, fixed whole unit, necessity of common measure and recursive partitioning. An analysis of this study showed that textbooks and teachers' manuals dealt with the fact of maintaining a fixed whole unit only as being implicit. The textbooks described the reason why we need to create a common denominator in connection with the addition of similar fractions. The textbooks displayed a common denominator numerically rather than using a recursive partitioning method. Given this, it is difficult for students to connect the models and algorithms. Building on these results, this study is expected to suggest specific implications which may be taken into account in developing new instructional materials in process.

• Journal of the Korean School Mathematics Society
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• v.14 no.4
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• pp.477-490
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• 2011

The concept of pedagogical content knowledge (PCK) has been developed and expanded to identify essential components of mathematical knowledge for teaching (MKT) by Ball and her colleagues (2008). This study proposes an alternative perspective to view MKT focusing on key developmental understandings (KDUs) that carry through an instructional sequence, that are foundational for learning other ideas. In this study we provide constructive components of KDUs in fraction multiplication by focusing on the constructs of 'three-level-of-units structure' and 'recursive partitioning operation'. Expecially, our participating preservice elementary teacher, Jane, demonstrated that recursive partitioning operations with her length model played a significant role as a KDU in fraction multiplication.

• Bulletin of the Korean Chemical Society
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• v.33 no.4
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• pp.1123-1127
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• 2012

P-gp (P-glycoprotein) is a member of the ATP binding cassette (ABC) family of transporters. It transports many kinds of anticancer drugs out of the cell. It plays a major role as a cause of multidrug resistance (MDR). MDR function may be a cause of the failure of chemotherapy in cancer and influence pharmacokinetic properties of many drugs. Hence classification of candidate drugs as substrates or nonsubstrate of the P-gp is important in drug development. Therefore to identify whether a compound is a P-gp substrate or not, in silico method is promising. Recursive Partitioning (RP) method was explored for prediction of P-gp substrate. A set of 261 compounds, including 146 substrates and 115 nonsubstrates of P-gp, was used to training and validation. Using molecular descriptors that we can interpret their own meaning, we have established two models for prediction of P-gp substrates. In the first model, we chose only 6 descriptors which have simple physical meaning. In the training set, the overall predictability of our model is 78.95%. In case of test set, overall predictability is 69.23%. Second model with 2D and 3D descriptors shows a little better predictability (overall predictability of training set is 79.29%, test set is 79.37%), the second model with 2D and 3D descriptors shows better discriminating power than first model with only 2D descriptors. This approach will be used to reduce the number of compounds required to be run in the P-gp efflux assay.

• Proceedings of the Korean Statistical Society Conference
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• 2005.05a
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• pp.49-51
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• 2005

본 연구는 반복분할(recursive partitioning)에 의한 군집화 방법을 제안하고 활용 예를 제시한다. 이 방법은 나무 형태의 해석하기 쉬운 단순한 규칙을 제공하면서 동시에 변수선택기능을 제공한다.

• Bulletin of the Korean Chemical Society
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• v.29 no.1
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• pp.111-116
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• 2008

A piperazinylalkylisoxazole library containing 86 compounds was constructed and evaluated for the binding affinities to dopamine (D3) and serotonin (5-HT2A/2C) receptor to develop antipsychotics. Dopamine antagonists (DA) showing selectivity for D3 receptor over the D2 receptor, serotonin antagonists (SA), and serotonin-dopamine dual antagonists (SDA) were identified based on their binding affinity and selectivity. The analogues were divided into three groups of 7 DAs (D3), 33 SAs (5-HT2A/2C), and 46 SDAs (D3 and 5-HT2A/2C). A classification model was generated for identifying structural characteristics of those antagonists with different affinity profiles. On the basis of the results from our previous study, we conducted the generation of the decision trees by the recursive-partitioning (RP) method using Cerius2 2D descriptors, and identified and interpreted the descriptors that discriminate in-house antipsychotic compounds.

• Journal of KIISE:Software and Applications
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• v.31 no.4
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• pp.478-487
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• 2004

We had proposed the RPA(Recursive Partition Averaging) method in order to improve the storage requirement and classification rate of the Memory Based Reasoning. That algorithm worked not bad in many area, however, the major drawbacks of RPA are it's partitioning condition and the way of extracting major patterns. We propose an adaptive RPA algorithm which uses the FPD(feature-based population densimeter) to stop the ARPA partitioning process and produce, instead of RPA's averaged major pattern, optimizing resulting hyperrectangles. The proposed algorithm required only approximately 40% of memory space that is needed in k-NN classifier, and showed a superior classification performance to the RPA. Also, by reducing the number of stored patterns, it showed an excellent results in terms of classification when we compare it to the k-NN.

• The Korean Journal of Applied Statistics
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• v.18 no.3
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• pp.661-671
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• 2005

The aim of this study is to propose a clustering method, called tree-structured clustering, by recursively partitioning continuous multivariate dat a based on overall $R^2$ criterion with a practical node-splitting decision rule. The clustering method produces easily interpretable clustering rules of tree types with the variable selection function. In numerical examples (Fisher's iris data and a Telecom case), we note several differences between tree-structured clustering and K-means clustering.

• International Journal of Control, Automation, and Systems
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• v.4 no.4
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• pp.456-465
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• 2006

The problem of recursive filtering far linear discrete-time systems with uncertainties is considered. A new suboptimal filtering algorithm is herein proposed. It is based on the fusion formula, which represents an optimal mean-square linear combination of local Kalman estimates with weights depending on cross-covariances between local filtering errors. In contrast to the optimal weights, the suboptimal weights do not depend on current measurements, and thus the proposed algorithm can easily be implemented in real-time. High accuracy and efficiency of the suboptimal filtering algorithm are demonstrated on the following examples: damper harmonic oscillator motion and vehicle motion constrained to a plane.