• Ocean Systems Engineering
• /
• 제8권4호
• /
• pp.409-426
• /
• 2018

This paper presents the strengthening of tubular joint by wrapping Carbon fiber reinforced polymer (CFRP) and glass fiber reinforced polymer (GFRP). In this study, total number of layers, stacking sequence and length of wrapping are the different parameters involved when fiber reinforced polymers (FRP) composites are used for strengthening. For this, parameters where varied and results were compared with the reference joint. The best stacking sequence was identified which has the highest value in ultimate load with lesser deflections. For determining the best stacking sequence, numerical investigation was performed on CFRP composites; length of wrapping and number of layers were fixed. Later, the studies were focused on CFRP and GFRP strengthened joint by varying the total number of layers and length of wrapping. An attempt was done to propose a parametric equation from multiple regression analysis, which can be used for CFRP strengthened joints. Hashin failure criteria was used to check the failure of composites. Results revealed that FRP was having a greater influence in the load bearing capacity of joints, and in reducing the deflections and stresses of joint under axial compressive loads. It was also seen that, CFRP was far better than GFRP in reducing the stresses and deflection.

• 대한전자공학회논문지SD
• /
• 제41권7호
• /
• pp.71-79
• /
• 2004

패킷형 데이터전송은 다량의 데이터가 연속적으로 전달되는 특성이 있다. 이와 같은 데이터를 버스를 통하여 전송할 패에 데이터의 전송순서는 버스의 전력소모에 영향을 주는 하나의 요소로서 작용한다. 본 논문에서는 패킷형 데이터를 전송할 때 데이터의 전송순서를 변화시켜 버스의 전이횟수를 줄임으로써 버스의 소비전력을 감소시키는 순서변환코딩 (Sequence-Switch Coding, SSC)을 제안하였다. 또한 SSC를 구현하는 알고리즘을 개발하였으며, 실험을 통하여 이들 알고리즘으로 기존의 널리 알려진 Bus-Invert Coding보다 우수한 성능을 얻을 수 있음을 보였다. SSC는 버스의 소비전력을 줄이는 하나의 방법이며, 이를 실현하는 알고리즘은 무수히 많다. 알고리즘의 다양성은 SSC가 갖는 하나의 장점으로써 회로설계자에게 버스의 소비전력과 회로의 구현부담 사이에서 넓은 범위에 걸쳐 절충할 수 있는 자유를 제공해 준다.

• Journal of Power Electronics
• /
• 제14권5호
• /
• pp.946-956
• /
• 2014

Cascaded H-Bridge (CHB) converters can be directly connected to medium-voltage grids without using transformers and they possess the advantages of large capacity and low harmonics. They are significant tools for providing grid connections in large-capacity renewable energy systems. However, the reliability of a grid-connected CHB converter can be seriously influenced by the number of power switching devices that exist in the structure. This paper proposes a fault-tolerant control strategy based on double zero-sequence voltage injection and DC voltage optimization to improve the reliability of star-connected CHB converters after one or more power units have been bypassed. By injecting double zero-sequence voltages into each phase cluster, the DC voltages of the healthy units can be rapidly balanced after the faulty units are bypassed. In addition, optimizing the DC voltage increases the number of faulty units that can be tolerated and improves the reliability of the converter. Simulations and experimental results are shown for a seven-level three-phase CHB converter to validate the efficiency and feasibility of this strategy.

• 한국컴퓨터정보학회논문지
• /
• 제13권2호
• /
• pp.113-119
• /
• 2008

월드 와이드 웹에는 거대한 양의 하이퍼링크들과 웹 사용 정보들을 포함하고 있는 동적인 페이지들이 모여 있다. 이러한 구조화되어 있지 않은 웹 데이터들과 온라인 정보들의 폭발적인 증가로 인해 효율적인 웹 데이터 마이닝 툴이 필요로 하게 되었다. 최근에는 웹 사용자들의 특성을 자동적으로 발견하기 위한 Web usage mining 분야에서 많은 연구가 진행되고 있다. 본 연구에서는 웹 사용자들의 방문 기록, 단백질 시퀀스, 소매점 거래 데이터 등과 같은 시퀀스 데이터를 분석하는 방법에 대하여 연구한다. 러프 셋 이론을 이용하여 시퀀스 데이터들을 클러스터링 하는 방법을 제안하고, 간단한 예제를 통하여 제안하는 절차를 소개하고 splice 데이터셋과 합성 데이터셋을 통한 실험 결과를 제시한다.

• 제어로봇시스템학회:학술대회논문집
• /
• 제어로봇시스템학회 1997년도 한국자동제어학술회의논문집; 한국전력공사 서울연수원; 17-18 Oct. 1997
• /
• pp.1267-1270
• /
• 1997

An assembly sequence is considered to be optimal when it minimizes assembly cost while satisfying assembly constraints. to generate such sequences for robotic assembly, this paper proposes a method using a genetic algorithm (GA). This method denotes an assembly sequence as an individual, which is assigned a fitness related to the assembly cost. Then, a population consisting of a number of individuals evolves to the next generation through genetic operations of crossover and mutation based upon the fitness of the individuals. The population continues to repetitively evolve, and finally the fittest individual and its corresponding assembly sequence is found. Through case study for an electrical relay, the effectiveness of the proposed method is demonstrated. Also, the performance is evaluated by-comparing with those of previously presented approaches such as a neural-netowork-based method and a simulated annealing method.

• 제어로봇시스템학회:학술대회논문집
• /
• 제어로봇시스템학회 1993년도 한국자동제어학술회의논문집(국제학술편); Seoul National University, Seoul; 20-22 Oct. 1993
• /
• pp.24-29
• /
• 1993

In this paper, the estimation of the structure of a logic circuit under test is made from the observation of the input-output correlation function by use of M-sequence, from which we can estimate whether or not any fault exist in the logic circuit. Especially, investigation was made in case of the 2_stage logic circuit. We checked theoretically the sequence of correlation function, and we have shown that the correlation function is a function of period of M-sequence only, land the appearing number of correlation function in a period is a constant value depending on the logic circuit only. And by computer simulations we have shown that the structure of the circuit under test can be estimated from the observation of sequence of correlation function.

• Communications for Statistical Applications and Methods
• /
• 제12권1호
• /
• pp.139-147
• /
• 2005

It is interesting to locate homogeneous segments within a DNA sequence. Suppose that the DNA sequence has segments within which the observations follow the same residue frequency distribution, and between which observations have different distributions. In this setting, change points correspond to the end points of these segments. This article explores the use of a binary segmentation procedure in detecting the change points in the DNA sequence. The change points are determined using a sequence of nested hypothesis tests of whether a change point exists. At each test, we compare no change-point model with a single change-point model by using the Bayesian information criterion. Thus, the method circumvents the computational complexity one would normally face in problems with an unknown number of change points. We illustrate the procedure by analyzing the genome of the bacteriophage lambda.

• 대한전자공학회논문지
• /
• 제21권6호
• /
• pp.56-63
• /
• 1984

본 논문에서는 GRAFCET로 기술된 병렬 sequence를 갖는 순서 논리 시스템을 Programmed logic에 의해 실현하는 방법을 제안한다 이를 위해 먼저 병렬 sequence를 갖는 GRAFCET를 그 본래의 물리적 의미를 변형치 않고 다수의 state graph로 재구성하는 알고리즘을 제안했으며 이 제안된 알고리즘은 모든 형태의 GRAFCET에 적용 가능하며 특히 sub-system으로의 분해 및 그 역과정을 손쉽게 한다. 다음 이와같이 재구성된 state graph를 ROM을 사용한 microproerammed logic에 의해 구성하는 조직적인 방법을 제시했으며 이 제시된 구성 방법은 선택 sequence의 수를 임의로 확장할 수 있다.

• 대한전자공학회:학술대회논문집
• /
• 대한전자공학회 2006년도 하계종합학술대회
• /
• pp.15-16
• /
• 2006

In this paper, we propose an adaptive SLM scheme based on peak observation for PAPR reduction of OFDM signals. The proposed scheme is composed of three steps: peak scaling, sequence selection, and SLM procedures. In the first step, the peak signal samples in the IFFT outputs of the original input sequence are scaled down. In the second step, the sub-carrier positions where power difference between the original input sequence and the FFT outputs of the scaled signal is large, are identified. Then, the phase sequences which have the maximum number of phase-reversed sequence words only for these positions, are selected. Finally, only using the selected phase sequences, the generic SLM procedure is performed for the original input sequence. Simulation results reveal that the proposed adaptive SLM remarkably reduces the complexity in terms of IFFT and PAPR calculations than the conventional SLM, while maintaining the PAPR reduction performance.

• International Journal of Fuzzy Logic and Intelligent Systems
• /
• 제15권3호
• /
• pp.145-152
• /
• 2015

We consider an online selective-sample learning problem for sequence classification, where the goal is to learn a predictive model using a stream of data samples whose class labels can be selectively queried by the algorithm. Given that there is a limit to the total number of queries permitted, the key issue is choosing the most informative and salient samples for their class labels to be queried. Recently, several aggressive selective-sample algorithms have been proposed under a linear model for static (non-sequential) binary classification. We extend the idea to hidden Markov models for multi-class sequence classification by introducing reasonable measures for the novelty and prediction confidence of the incoming sample with respect to the current model, on which the query decision is based. For several sequence classification datasets/tasks in online learning setups, we demonstrate the effectiveness of the proposed approach.