• International Journal of Contents
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• v.3 no.2
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• pp.18-24
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• 2007

Biological sequences such as DNA and amino acid sequences typically contain a large number of items. They have contiguous sequences that ordinarily consist of more than hundreds of frequent items. In biological sequences analysis(BSA), a frequent contiguous sequence search is one of the most important operations. Many studies have been done for mining sequential patterns efficiently. Most of the existing methods for mining sequential patterns are based on the Apriori algorithm. In particular, the prefixSpan algorithm is one of the most efficient sequential pattern mining schemes based on the Apriori algorithm. However, since the algorithm expands the sequential patterns from frequent patterns with length-1, it is not suitable for biological datasets with long frequent contiguous sequences. In recent years, the MacosVSpan algorithm was proposed based on the idea of the prefixSpan algorithm to significantly reduce its recursive process. However, the algorithm is still inefficient for mining frequent contiguous sequences from long biological data sequences. In this paper, we propose an efficient method to mine maximal frequent contiguous sequences in large biological data sequences by constructing the spanning tree with a fixed length. To verify the superiority of the proposed method, we perform experiments in various environments. The experiments show that the proposed method is much more efficient than MacosVSpan in terms of retrieval performance.

• Communications for Statistical Applications and Methods
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• v.25 no.5
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• pp.501-512
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• 2018

We propose Sequential Patient Recruitment Monitoring (SPRM), a new monitoring procedure for patient recruitment in a clinical trial. Based on the sequential probability ratio test using improved stopping boundaries by Woodroofe, the method allows for continuous monitoring of the rate of enrollment. It gives an early warning when the recruitment is unlikely to achieve the target enrollment. The packet data approach combined with the Central Limit Theorem makes the method robust to the distribution of the recruitment entry pattern. A straightforward application of the counting process framework can be used to estimate the probability to achieve the target enrollment under the assumption that the current trend continues. The required extension of the recruitment period can also be derived for a given confidence level. SPRM is a new, continuous patient recruitment monitoring tool that provides an opportunity for corrective action in a timely manner. It is suitable for the modern, centralized data management environment and requires minimal effort to maintain. We illustrate this method using real data from two well-known, multicenter, phase III clinical trials.

• Phonetics and Speech Sciences
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• v.2 no.2
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• pp.63-68
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• 2010

A new version of sequential probability ratio test (SPRT) which has been investigated in utterance-length control is proposed to obtain uniform response results in speaker verification (SV). Although SPRTs can obtain fast responses in SV tests, differences in the performance may occur depending on the compositions of consonants and vowels in the sentences used. In this paper, a fast sequential probability ratio test (FSPRT) method that shows consistent performances at all times regardless of the compositions of vocalized sentences for SV will be proposed. In generating frames, the FSPRT will first conduct SV test processes with only generated frames without any overlapping and if the results do not satisfy discrimination criteria, the FSPRT will sequentially use frames applied with overlapping. With the progress of processes as such, the test will not be affected by the compositions of sentences for SV and thus fast response outcomes and even consistent performances can be obtained. Experimental results show that the FSPRT has better performance to the SPRT method while requiring less complexity with equal error rates (EER).

• The Korean Journal of Applied Statistics
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• v.21 no.2
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• pp.275-290
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• 2008

The size of microarray gene expression data is very big and its observation process is also very complex. Thus missing values are frequently occurred. In this paper we propose the sequential partial least squares(SPLS) regression fitting method to estimate missing values for time course gene expression data that has correlations among observations over time points. The SPLS method is to combine the sequential technique with the partial least squares(PLS) regression fitting method. The usefulness of method proposed is evaluated through some simulation study for three yeast time course data.

• Journal of rehabilitation welfare engineering & assistive technology
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• v.5 no.1
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• pp.59-64
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• 2011

In this paper, the lumped element model parameter estimation method and its implemented estimation software for fabricated floating mass transducers of IMEHDs have been presented so that the estimated parameter values could be compared with the designed ones and applied to predict the output performance when the transducers were implanted into human ears. The presented method is based on the sequential quadratic programming (SQP) for estimating parameters in the transducer's lumped model and has been implemented by the use of LabVIEW graphical language. Using the implemented estimation software, the accuracy of parameter estimation has been verified and our implemented estimation method has been evaluated by the comparison of the estimated transducer parameter values with the designed ones for a practically fabricated floating mass transducer for IMEHDs.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.10 no.4
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• pp.628-635
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• 1999

At center frequency of 11.85 GHz, wideband left-handed circularly polarized microstrip array antenna is designed with the method of sequential ratation based on $2\times2$ radiation elements($0^{\circ}$, $45^{\circ}$, $90^{\circ}$, $135^{\circ}$ phase delay). Its return loss, axial ratio bandwidth, radration pattern, and gain are compared with those adopting sequential rotation based on $1\times2$ radiation elements($0^{\circ}$, $90^{\circ}$, $180^{\circ}$, $270^{\circ}$phase delay). The $8\times8$ array is manufactured and measured. The results show that 10 dB return loss bandwidth is 10.51~12.74GHz(18.82%) which is 1.57 times wider than the case using $1\times2$ sequential rotation method, 3 dB axial ratio bandwidth is 11.43~12.5 GHz(9.03%) which is 1.25 times as wide as that using $1\times2$ sequential rotation method and the antennal gain is 25.4 dB. The results of mesurements are almost similar to those of simulation.

• The KIPS Transactions:PartB
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• v.11B no.3
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• pp.353-360
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• 2004

The study on scene change detection in the compressed MPEG videos has been done by various approaches. However, most of these approacher accomplished scene change detection by carrying out decoding processes and then by comparing pixels with pixels. This approach it not suitable for real time applications owing to much computing time of decoding processes. Recently, the study on scene change detection algorithms using only information of compressed domain is becoming Increasingly important. In this paper, we propose a sequential access method as an efficient scene change detection algorithm in the compressed domain. According to the type of pictures in the compressed MPEG video streams (divided in I-blocks and each I-block into P-blocks), the proposed algorithm provides effective scene change detection by applying sequential access and block by block mechanism. The proposed sequential access method provides fast and accurate detection operation by reducing checking procedures of unnecessary pictures due to molt of operations in compressed domain and checking by block units. Also, this approach uses optimal algorithm to provide fast and accurate detection operation.

• Proceedings of the Korean Vacuum Society Conference
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• 2016.02a
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• pp.415.1-415.1
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• 2016

2009년도에 Perovskite가 태양전지에 처음 적용된 이후, Perovskite를 기반으로 하는 태양전지는 급속한 발전을 이루고 있으나, 향후 상용화를 위해서는 추가적인 공정개선 및 제조 단가를 낮추는 노력이 필수적이다. 초창기 Perovskite의 증착 공정은 One step deposition 방법이 사용되었으나, Layer의 thickness, uniformity 등을 조절하기 어려워 Sequential deposition 방법으로 개선되었다. 하지만 결과적으로 초기방법 대비 추가공정이 발생함에 따라 시간 및 비용의 증가가 불가피하였다. 제조단가 측면에서는 Perovskite 태양전지를 구성하는 재료 중 HTM(정공수송물질)을 구성하는 Spiro-MeOTAD의 비용이 가장 비싸다. 따라서 저비용 태양전지를 위해서는 HTM이 없는 구조가 필요하다. 이 페이퍼에서는 Perovskite 물질이 고흡광 능력 외에 충분한 전하수송능력을 보유한다는 점에 착안하여, Gas Pressure Assisted Modified One Step Deposition을 이용한 HTM Free Perovskite를 제작하고 기존의 Sequential Deposition Method 통해 만들어진 Perovskite 태양전지와 비교/분석하였다.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.32 no.3
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• pp.258-266
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• 2008

The conventional approximate optimization method, which uses the statistical design of experiments(DOE) and response surface method(RSM), can derive an approximated optimum results through the iterative process by a trial and error. The quality of results depends seriously on the factors and levels assigned by a designer. The purpose of this study is to propose a new technique, which is called a sequential design of experiments(SDOE), to reduce a trial and error procedure and to find an appropriate condition for using artificial neural network(ANN) systematically. An appropriate condition is determined from the iterative process based on the analysis of means. With this new technique and ANN, it is possible to find an optimum design accurately and efficiently. The suggested algorithm has been applied to various mathematical examples and a structural problem.

• Journal of Multimedia Information System
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• v.6 no.4
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• pp.185-190
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• 2019

For future autonomous cars, it is necessary to recognize various surrounding environments such as lanes, traffic lights, and vehicles. This paper presents a method of speed sign recognition from a single image in automatic driving assistance systems. The detection step with the proposed method emphasizes the color attributes in modified YUV color space because speed sign area is affected by color. The proposed method is further improved by extracting the digits from the highlighted circle region. A sequential cascade AdaBoost classifier is then used in the recognition step for real-time processing. Experimental results show the performance of the proposed algorithm is superior to that of conventional algorithms for various speed signs and real-world conditions.