• Communications for Statistical Applications and Methods
• /
• v.29 no.4
• /
• pp.421-439
• /
• 2022

Phase I dose-finding trials are essential in drug development. By finding the maximum tolerated dose (MTD) of a new drug or treatment, a Phase I trial establishes the recommended doses for later-phase testing. The primary toxicity endpoint of interest is often a binary variable, which describes an event of a patient who experiences dose-limiting toxicity. However, there is a growing interest in dose-finding studies regarding non-binary outcomes, defined by either the weighted sum of rates of various toxicity grades or a continuous outcome. Although several novel methods have been proposed in the literature, accessible software is still lacking to implement these methods. This study introduces a newly developed R package, UnifiedDoseFinding, which implements three phase I dose-finding methods with non-binary outcomes (Quasi- and Robust Quasi-CRM designs by Yuan et al. (2007) and Pan et al. (2014), gBOIN design by Mu et al. (2019), and by a method by Ivanova and Kim (2009)). For each of the methods, UnifiedDoseFinding provides corresponding functions that begin with next that determines the dose for the next cohort of patients, select, which selects the MTD defined by the non-binary toxicity endpoint when the trial is completed, and get oc, which obtains the operating characteristics. Three real examples are provided to help practitioners use these methods. The R package UnifiedDoseFinding, which is accessible in R CRAN, provides a user-friendly tool to facilitate the implementation of innovative dose-finding studies with nonbinary outcomes.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.9 no.6
• /
• pp.2302-2316
• /
• 2015

We propose an efficient method of extracting targets within a region of interest in non-homogeneous infrared images by using a principal component analysis (PCA) plane and adaptive Gaussian kernel. Existing approaches for extracting targets have been limited to using only the intensity values of the pixels in a target region. However, it is difficult to extract the target regions effectively because the intensity values of the target region are mixed with the background intensity values. To overcome this problem, we propose a novel PCA based approach consisting of three steps. In the first step, we apply a PCA technique minimizing the total least-square errors of an IR image. In the second step, we generate a binary image that consists of pixels with higher values than the plane, and then calculate the second derivative of the sum of the square errors (SDSSE). In the final step, an iteration is performed until the convergence criteria is met, including the SDSSE, angle and labeling value. Therefore, a Gaussian kernel is weighted in addition to the PCA plane with the non-removed data from the previous step. Experimental results show that the proposed method achieves better segmentation performance than the existing method.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.39A no.2
• /
• pp.92-99
• /
• 2014

This paper proposes the method of facial expression recognition based on decision tree structure. In the image of facial expression, ASM(Active Shape Model) and LBP(Local Binary Pattern) make the local features of a facial expressions extracted. The discriminant features gotten from local features make the two facial expressions of all combination classified. Through the sum of true related to classification, the combination of facial expression and local region are decided. The integration of branch classifications generates decision tree. The facial expression recognition based on decision tree shows better recognition performance than the method which doesn't use that.

• Journal of the Institute of Electronics Engineers of Korea TC
• /
• v.44 no.11
• /
• pp.25-32
• /
• 2007

In this paper, we propose the Group Separation Algorithm for RFID Tag Anti-Collision. We study the RFID Tag anti-collision technique of ALOHA and the anti-collision algorithm of binary search. The existing technique is several problems; the transmitted data rate included of data, the recognition time and energy efficiency. For distinction of all tags, the Group Separation algorithm identify each Tag_ID bit#s sum of bit #1#. In other words, Group Separation algorithm had standard of selection by collision table, the algorithm can reduce unnecessary number of search even than the exisiting algorithm. The Group Separation algorithm had performance test that criterions were reader#s number of repetition and number of transmitted bits for understanding tag. We showed the good performance of Group Separation algorithm better than exisiting algorithm.

• Journal of the Institute of Electronics Engineers of Korea TC
• /
• v.44 no.4
• /
• pp.1-9
• /
• 2007

in this paper, we propose the Adaptive Decision Algorithm for RFID Tag Anti-Collision. We study the RFID Tag anti-collision technique of ALOHA and the anti-collision algorithm of binary search. The existing technique is several problems; the transmitted data rate included of data, the recognition time and energy efficiency. For distinction of all tags, the Adaptive Decision algorithm identify smaller one ,each Tag_ID bit's sum of bit '1'. In other words, Adaptive Decision algorithm had standard of selection by actively, the algorithm can reduce unnecessary number of search even than the exisiting algorithm. The Adaptive Decision algorithm had performance test that criterions were reader's number of repetition and number of transmitted bits for understanding tag. We showed the good performance of Adaptive Decision algorithm better than exisiting algorithm.

• Journal of Korean Society of Industrial and Systems Engineering
• /
• v.32 no.4
• /
• pp.53-62
• /
• 2009

Lee[15] examined quantity discount contracts between a manufacturer and a retailer in a stochastic, two-period inventory model where quantity discounts are provided based on the previous order size. During the two periods, the retailer faces stochastic (truncated Poisson distributed) demands and he/she places orders to meet the demands. The manufacturer provides for the retailer a price discount for the second period order if its quantity exceeds the first period order quantity. In this paper we extend the above two-period model to a k-period one (where k < 2) and propose a stochastic nonlinear mixed binary integer program for it. In order to make the program tractable, the nonlinear term involving the sum of truncated Poisson cumulative probability function values over a certain range of demand is approximated by an i-interval piecewise linear function. With the value of i selected and fixed, the piecewise linear function is determined using an evolutionary algorithm where its fitness to the original nonlinear term is maximized. The resulting piecewise linear mixed binary integer program is then transformed to a mixed binary integer linear program. With the k-period model developed, we suggest a solution procedure of receding horizon control style to solve n-period (n < k) order decision problems. We implement Lee's two-period model and the proposed k-period model for the use in receding horizon control style to solve n-period order decision problems, and compare between the two models in terms of the pattern of order quantities and the total profits. Our computational study shows that the proposed model is superior to the two-period model with respect to the total profits, and that order quantities from the proposed model have higher fluctuations over periods.

• Journal of the Institute of Electronics and Information Engineers
• /
• v.51 no.6
• /
• pp.201-208
• /
• 2014

In this paper, we propose the classifier structure design algorithm using DTW. Proposed algorithm uses DTW result to design the binary tree architecture based on the SVM which classify the multi-class data. Design the binary tree architecture for Support Vector Machine(SVM-BTA) using the threshold criterion calculated by the sum columns in square matrix which components are the reference data from each class. For comparison the performance of the proposed algorithm, compare the results of classifiers which binary tree structure are designed based on database and k-means algorithm. The data used for classification is 333 signals from 18 classes of underwater transient noise. The proposed classifier has been improved classification performance compared with classifier designed by database system, and probability of detection for non-biological transient signal has improved compare with classifiers using k-means algorithm. The proposed SVM-BTA classified 68.77% of biological sound(BO), 92.86% chain(CHAN) the mechanical sound, and 100% of the 6 kinds of the other classes.

• Journal of the Korean Mathematical Society
• /
• v.54 no.4
• /
• pp.1317-1329
• /
• 2017

A Boolean rank one matrix can be factored as $\text{uv}^t$ for vectors u and v of appropriate orders. The perimeter of this Boolean rank one matrix is the number of nonzero entries in u plus the number of nonzero entries in v. A Boolean matrix of Boolean rank k is the sum of k Boolean rank one matrices, a rank one decomposition. The perimeter of a Boolean matrix A of Boolean rank k is the minimum over all Boolean rank one decompositions of A of the sums of perimeters of the Boolean rank one matrices. The arctic rank of a Boolean matrix is one half the perimeter. In this article we characterize the linear operators that preserve the symmetric arctic rank of symmetric Boolean matrices.

• Journal of Global Scholars of Marketing Science
• /
• v.17 no.4
• /
• pp.91-111
• /
• 2007

Marketing is said to be a zero sum game i.e. each gain of customer for a firm is always at the expense of some other firm's customers. Therefore in a marketplace churn is a natural occurrence. Churn in Indian telecom market is among the highest in growing telecom markets. By using binary logistics regression analysis based models based covering a sample of 822 Indian telecom subscribers; this paper attempts to examine the determinants of churn. The future churn is found to be dependent on satisfaction level of the customer with the service provider, attitude and loyalty of the customer variables, intended churn (i.e. intention to churn) and current loyalty (defined as intention to recommend) and distraction (i.e. intention to experiment).

• Journal of applied mathematics & informatics
• /
• v.26 no.5_6
• /
• pp.973-981
• /
• 2008

In this paper we focus on a type of Unimodular polynomial pair used for digital systems and present some new properties of them which lead us to estimation of their autocorrelation coefficients and the moments of a Rudin-Shapiro polynomial product. Some new results on the Rudin-shapiro sequences will be presented in the last section. Main Facts: For positive integers M and n with $M\;<\;2^n$ - 1, consider the $2^n$ - M numbers ${\epsilon}_k$ ($M\;{\leq}\;k\;{\leq}\;2^n$ - 1) which form a collection of Rudin-Shapiro coefficients. We verify that $|{\sum}_{k=M}^{2^{n-1}}\;{{\epsilon}_k}e^{ikt}|$ is dominated by $(2+\sqrt{2})\;\sqrt {2^n-M}-{\sqrt{2}}$.