• Journal of electromagnetic engineering and science
• /
• 제2권1호
• /
• pp.28-33
• /
• 2002

The LHCP circularly polarized antenna operating at DBS band is developed by employing the sequential-rotation technique in which each subarray is comprised the three truncated-corner patch square element. Antenna designed with sequentially-related technique whose M=3, p=2 has the effect of improved axial-ratio bandwidth, cross-polarization etc. And it is proved that the degradation of radiation pattern can be reduced significantly by minimizing the radiation loss of feeding line structure. Antenna designed shows extremely low side lobe level of below - 25 dB in the diagonal plane and cross-polarization level of below -20 dB in the all plane. And these performances comply with the array antenna specification for DBS.

• Journal of Electrical Engineering and information Science
• /
• 제2권3호
• /
• pp.7-13
• /
• 1997

To overcome the large hardware overhead attendant in the full scan design, the concept of partial scan design has emerged with the virtue of less area and testability close to full scan. Combinational Structure has been developed to avoid the use of sequential test generator. But the patterns sifted on scan register have to be held for sequential depth period upon the aid of the dedicated HOLD circuit. In this paper, a new levelized structure is introduced aiming to exclude the need of extra HOLD circuit. The time to stimulate each scan latch is uniquely determined on this structure, hence each test pattern can e applied by scan shifting and then pulsing a system clock like the full scan but with much les scan flip-flops. Experimental results show that some sequential circuits are levelized by just scanning self-loop flip-flops.

• 전자공학회논문지CI
• /
• 제43권5호
• /
• pp.17-28
• /
• 2006

본 논문에서는 데이터베이스에 새로운 트랜잭션이 추가되었을 때 순차 패턴을 갱신하는 문제를 연구하였다. 트랜잭션이 순차적으로 증가되는 환경에서 기존에 발견된 빈발 시퀸스를 재사용하여 순차패턴을 갱신하는 효율적인 알고리즘을 제안한다. 본 논문에서 제안한 방법은 후보 집합의 개수를 효율적으로 줄임으로써 AprioriAll이나 PrefixSpan 알고리즘보다 좋은 성능을 보임을 실험으로 확인하였다.

• 한국발생생물학회지:발생과생식
• /
• 제25권1호
• /
• pp.55-57
• /
• 2021

Samples were collected from the subtidal region of Jumunjin on the eastern coast of Korea in July 2020. A total of 338 mussels of shell height (SH) 20.8-149.8 mm were used for sex ratio analysis. The sex ratio (F:M) in the same population of mussel Mytilus coruscus was approximately 1:0.7. The sex ratio according to the class of SH was different. The sex reversal pattern of M. coruscus appears to go from male → female → male → female, and as such is determined to be sequential hermaphrodites.

• 한국멀티미디어학회논문지
• /
• 제9권9호
• /
• pp.1118-1130
• /
• 2006

데이터 스트림에 대한 기존의 패턴 분석 알고리즘은 대부분 속도 향상과 효율적인 메모리 사용에 대하여 연구되어 왔다. 그러나 기존의 연구들은 새로운 패턴을 가진 데이터 스트림이 입력되었을 경우, 이 전에 분석된 패턴을 버리고 다시 패턴을 분석하여야 한다. 이러한 방법은 데이터의 실시간적인 패턴 분석을 필요로 하는 실제 환경에서는 많은 속도와 계산 비용이 소모된다. 본 논문에서는 끊임없이 입력되는 데이터 스트림의 패턴을 실시간으로 분석하는 방법을 제안한다. 이 것은 먼저 빠르게 패턴을 분석하고 그 다음부터는 이전에 분석된 패턴을 효율적으로 갱신하여 실시간적인 패턴을 얻어내는 방법이다. 데이터 스트림이 입력되면 시간 기반 윈도우로 나누어 여러 개의 순차들을 생성한다. 그리고 생성된 순차들의 정보는 해시 테이블에 입력되어 정해진 개수의 순차가 해시 테이블에 채워질 때마다 해시 테이블에서 패턴을 분석해 낸다. 이렇게 분석된 패턴은 패턴 트리를 형성하게 되고, 이 후에 새로 분석된 패턴들은 이 패턴 트리 안의 패턴 별로 갱신하여 현재 패턴을 유지하게 된다. 새로운 패턴 추가를 위해 패턴을 분석할 때 이전에 이미 발견된 패턴이 Suffix로 나올 수 있다. 그러면 패턴 트리에서 이 전 패턴으로의 포인터를 생성하여 중복되는 패턴 분석으로 인한 계산 시간의 낭비를 방지한다. 그리고 FIFO방법을 사용하여 오랫동안 입력이 안 된 패턴을 손쉽게 제거한다. 패턴이 조금씩 바뀌는 데이터 스트림 환경에서 RSP-DS가 기존의 알고리즘보다 우수하다는 것을 성능 평가를 통하여 증명하였다. 또한 패턴 분석을 수행할 데이터 순차의 개수와 자주 등장하는 데이터를 판별하는 기준을 조절하여 성능의 변화를 살펴보았다.

• Communications for Statistical Applications and Methods
• /
• 제25권5호
• /
• pp.501-512
• /
• 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.

• ETRI Journal
• /
• 제13권2호
• /
• pp.34-41
• /
• 1991

In this paper, a new distributed parallel algorithm for pattern classification based upon Self-Organizing Neural Network(SONN)[10-12] is developed. This system works without any information about the number of clusters or cluster centers. The SONN model showed good performance for finding classification information, cluster centers, the number of salient clusters and membership information. It took a considerable amount of time in the sequential version if the input data set size is very large. Therefore, design of parallel algorithm is desirous. A new distributed parallel algorithm is developed and experimental results are presented.

• 제어로봇시스템학회논문지
• /
• 제14권2호
• /
• pp.148-155
• /
• 2008

This paper proposes a method of adaptively generating a gait pattern of biped robot. The gait synthesis is based on human's gait pattern analysis. The proposed method can easily be applied to generate the natural and stable gait pattern of any biped robot. To analyze the human's gait pattern, sequential images of the human's gait on the sagittal plane are acquired from which the gait control values are extracted. The gait pattern of biped robot on the sagittal plane is adaptively generated by a genetic algorithm using the human's gait control values. However, gait trajectories of the biped robot on the sagittal plane are not enough to construct the complete gait pattern because the biped robot moves on 3-dimension space. Therefore, the gait pattern on the frontal plane, generated from Zero Moment Point (ZMP), is added to the gait one acquired on the sagittal plane. Consequently, the natural and stable walking pattern for the biped robot is obtained, as proved by the experiments.

• 대한전기학회논문지
• /
• 제33권10호
• /
• pp.381-386
• /
• 1984

This paper deals with the microcomputer realization of EMG pattern recognition system which provides identification of motion commands from the EMG signals for the on-line control of a prosthetic arm. A probabilistic model of pattern is formulated in the feature space of integral absolute value(IAV) to describe the relation between a motion command and the location of corresponding pattern. This model enables the derivation of sample density function of a command in the feature space of IAV. Classification is caried out through the multiclass sequential decision process, where the decision rule and the stopping rule of the process are designed by using the simple mathematical formulas defined as the likelihood probability and the decision measure, respectively. Some floating point algorithms such as addition, multiplication, division, square root and exponential function are developed for calculating the probability density functions and the decision measure. Only six primitive motions and one no motion are incorporated in this paper.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• 제10권3호
• /
• pp.1390-1403
• /
• 2016

Facial expression recognition (FER) plays a very significant role in computer vision, pattern recognition, and image processing applications such as human computer interaction as it provides sufficient information about emotions of people. For video-based facial expression recognition, depth cameras can be better candidates over RGB cameras as a person's face cannot be easily recognized from distance-based depth videos hence depth cameras also resolve some privacy issues that can arise using RGB faces. A good FER system is very much reliant on the extraction of robust features as well as recognition engine. In this work, an efficient novel approach is proposed to recognize some facial expressions from time-sequential depth videos. First of all, efficient Local Binary Pattern (LBP) features are obtained from the time-sequential depth faces that are further classified by Generalized Discriminant Analysis (GDA) to make the features more robust and finally, the LBP-GDA features are fed into Hidden Markov Models (HMMs) to train and recognize different facial expressions successfully. The depth information-based proposed facial expression recognition approach is compared to the conventional approaches such as Principal Component Analysis (PCA), Independent Component Analysis (ICA), and Linear Discriminant Analysis (LDA) where the proposed one outperforms others by obtaining better recognition rates.