• Journal of Crop Science and Biotechnology
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• v.11 no.2
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• pp.83-90
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• 2008

Two hundred and sixty Korean soybean landrace accessions were analyzed for polymorphism at 92 simple sequence repeat(SSR) loci. The 995 identified alleles served as raw data for estimating genetic diversity and population structure. The number of alleles at a locus ranged from three to 27 with a mean of 10.4 alleles per locus. $F_{ST}$ values estimated by analysis of molecular variance(AMOVA) using SSR data set were 0.018, 0.027, and 0.016 for usage, collection site and maturity groups, respectively, indicating little genetic differentiation. The model-based clustering analysis placed the accessions into three clusters(K=3) with 0.0503 of $F_{ST}$, indicating moderate genetic differentiation. Duncan's Multiple Range Test at K = 3 on the basis of 18 quantitative traits revealed that one cluster was mainly differentiated from the other two clusters by seed related traits and the other two clusters were differentiated from each other by biochemical traits. Genetic structure of Korean soybean landraces was differentiated by model-based clustering and supported by their phenotypic traits in part. This preliminary study could be the first step towards more efficient germplasm management and utilization of soybean landraces and helpful in association studies between genotypic and phenotypic traits in Korean soybean landraces.

• Journal of KIISE:Information Networking
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• v.34 no.3
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• pp.156-167
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• 2007

In this paper, we develop the model based prediction algorithm for Variable-Bit-Rate(VBR) video traffic with regular Group of Picture(GOP) pattern. We use multiplicative ARIMA process called GOP ARIMA (ARIMA for Group Of Pictures) as a base stochastic model. Kalman Filter based prediction algorithm consists of two process: GOP ARIMA modeling and prediction. In performance study, we produce three video traces (news, drama, sports) and we compare the accuracy of three different prediction schemes: Kalman Filter based prediction, linear prediction, and double exponential smoothing. The proposed prediction algorithm yields superior prediction accuracy than the other two. We also show that confidence interval analysis can effectively detect scene changes of the sample video sequence. The Kalman filter based prediction algorithm proposed in this work makes significant contributions to various aspects of network traffic engineering and resource allocation.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.40 no.6
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• pp.90-97
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• 2003

This paper proposes a speech recognition based on HMM(Hidden Markov Model) using FSVQ(First Section Vector Quantization) and fuzzy concept. In the proposed paper, we generate codebook of First Section, and then obtain multi-observation sequences by order of large propabilistic values based on fuzzy rule from the codebook of the first section. Thereafter, this observation sequences of first section from codebooks is trained and in case of recognition, a word that has the most highest probability of first section is selected as a recognized word by same concept. Train station names are selected as the target recognition vocabulary and LPC cepstrum coefficients are used as the feature parameters. Besides the speech recognition experiments of proposed method, we experiment the other methods under same conditions and data. Through the experiment results, it is proved that the proposed method based on HMM using FSVQ and fuzzy concept is superior to tile others in recognition rate.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.36S no.12
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• pp.76-84
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• 1999

This paper presents an integrated method for aircraft position estimation using sequential aerial images. The proposed integrated system for position estimation is composed of two parts: relative position estimation and absolute position estimation. Relative position estimation recursively computes the current position of an aircraft by accumulating relative displacement estimates extracted from two successive aerial images. Simple accumulation of parameter values decreases reliability of the extracted parameter estimates as an aircraft goes on navigating, resulting in large position error. Therefore absolute position estimation is required to compensate for the position error generated in relative position estimation. Absolute position estimation algorithms by image matching or digital elevation model (DEM) matching are presented. In image matching, a robust oriented Hausdorff measure (ROHM) is employed whereas in DEM matching an algorithm using multiple image pairs is used. Computer simulation with four real aerial image sequences shows the effectiveness of the proposed integrated position estimation algorithm.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.20 no.8
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• pp.1537-1545
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• 2016

In real time video sequence, object segmentation and tracking method are actively applied in various application tasks, such as surveillance system, mobile robots, augmented reality. This paper propose a robust object tracking method. The background models are constructed by learning the initial part of each video sequences. After that, the moving objects are detected via object segmentation by using background subtraction method. The region of detected objects are continuously tracked by using the HSV color histogram with particle filter. The proposed segmentation method is superior to average background model in term of moving object detection. In addition, the proposed tracking method provide a continuous tracking result even in the case that multiple objects are existed with similar color, and severe occlusion are occurred with multiple objects. The experiment results provided with 85.9 % of average object overlapping rate and 96.3% of average object tracking rate using two video sequences.

• Bulletin of the Society of Naval Architects of Korea
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• v.11 no.2
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• pp.15-22
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• 1974

As for the added mass moment of inertia of ships in torsional vibration, it seems that the works by T. Kumai[1,2] are the only systematic one available currently. The work[1] is for the calculation of the two dimensional correction factors with finitely-long elliptic cylinders as the mathematic model. In this work the authors recalculated the above factors, $J_{\tau}$, with the same mathematic model and the same problem formulation, and presented the numerical results in Fig. 1. The reason why the reinvestigation was done was that in Kumai's work he obtained the solutions of the Mathieu equations, which was derived from the problem formulation for the velocity potential, under the assumption that the dummy constant q involved in the equations was always far less than unity, whereas in fact it takes values within the region of $0<q{\leq}{\infty}$ in sequence. As a result the authors found two remarkable differences in general features of $J_{\tau}$(refer to Fg.3); one that the authors' numerical results are considerably higher than the results given in [2], and the other that for a given number of node those have properties of decreasing monotonically with increase of the beam-draft ratio while these rapidly decrease from a maximum value of near at B/T=2.00 with B/T becoming greater or less than ratio. It seems that the latter trend was resulted from the fact that the assumption of $q{\ll}1$ employed in [2] was more closely satisfied in the vicinity of B/T=2.00.

• Journal of KIISE:Databases
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• v.29 no.2
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• pp.138-147
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• 2002

The concept of the critical path in the workflow is important because it can be utilized In many issues in workflow systems, e.g., workflow resource management and workflow time management. However, the critical path in the contest of the workflow has not been much addressed in the past. This is because control flows in the workflow, generally including sequence, parallel, alternative, iteration and so on, are much more complex than those in the ordinary graph or network. In this paper we first describe our workflow model that has considerable work(low control constructs. They would provide the sufficient expressive power for modeling the growing complexities of today's most business processes. Then, we propose a method to systematically determine the critical path in a workflow schema built by the workflow control constructs described in our workflow model.

• Journal of Korean Society of Steel Construction
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• v.18 no.2
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• pp.161-171
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• 2006

paper presents the results of a three-dimensional study of the natural vibration of laminated composite rectangular plates with various combinations of clamped and free boundaries. The Ritz method was used to obtain the stationary values of the associated Lagrangian, with displacements approximated using mathematicaly complete, characteristic orthogonal polynomials. The correctness of the three-dimensional model was established through a convergence study of the non-dimensional frequencies, followed by a comparison of the analytical findings in the existing literature. The wide scope of additional three-dimensional frequency results explains the influence of a number of geometrical and material parameters for angle-ply and cross-ply laminated plates, namely aspect ratio (${\mathcal{a/b}}$), thickness ratio (${\mathcal{a/h}}$), orthotropy of material, number of plies (${\mathcal{N}}$), fiber orientation angle (${\theta}$), and stacking sequence.

• Tunnel and Underground Space
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• v.14 no.1
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• pp.54-68
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• 2004

In this study, scaled model tests were performed on blasting demolition of reinforced concrete structures and the experimental results were analyzed in comparison with the results of numerical analysis. The tests were designed to induce a progressive collapse, and physical properties of the scaled model were determined using scale factors obtained ken dimension analysis. The scaled model structure was made of a mixture of plaster, sand and water at the ratio determined to yield the best scaled-down strength. Lead wire was used as a substitute for reinforcing bars. The scaled length was at the ratio of 1/10. Selecting the material and scaled factors was aimed at obtaining appropriately scaled-down strength. PFC2D (Particle Flow Code 2-Dimension) employing DEM (Distinct Element Method) was used for the numerical analysis. Blasting demolition of scaled 3-D plain concrete laymen structure was filmed and compared to results of numerical simulation. Despite the limits of 2-D simulation the resulting demolition behaviors were similar to each other. Based on the above experimental results in combination with bending test results of RC beam, numerical analysis was carried out to determine the blasting sequence and delay times. Scaled model test of RC structure resulted in remarkably similar collapse with the numerical results up to 900㎳ (mili-second).

• Proceedings of the Korean Vacuum Society Conference
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• 2012.02a
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• pp.241-241
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• 2012

Semiconductor industry has been taking the advantage of improvements in process technology in order to maintain reduced device geometries and stringent performance specifications. This results in semiconductor manufacturing processes became hundreds in sequence, it is continuously expected to be increased. This may in turn reduce the yield. With a large amount of investment at stake, this motivates tighter process control and fault diagnosis. The continuous improvement in semiconductor industry demands advancements in process control and monitoring to the same degree. Any fault in the process must be detected and classified with a high degree of precision, and it is desired to be diagnosed if possible. The detected abnormality in the system is then classified to locate the source of the variation. The performance of a fault detection system is directly reflected in the yield. Therefore a highly capable fault detection system is always desirable. In this research, time series modeling of the data from an etch equipment has been investigated for the ultimate purpose of fault diagnosis. The tool data consisted of number of different parameters each being recorded at fixed time points. As the data had been collected for a number of runs, it was not synchronized due to variable delays and offsets in data acquisition system and networks. The data was then synchronized using a variant of Dynamic Time Warping (DTW) algorithm. The AutoRegressive Integrated Moving Average (ARIMA) model was then applied on the synchronized data. The ARIMA model combines both the Autoregressive model and the Moving Average model to relate the present value of the time series to its past values. As the new values of parameters are received from the equipment, the model uses them and the previous ones to provide predictions of one step ahead for each parameter. The statistical comparison of these predictions with the actual values, gives us the each parameter's probability of fault, at each time point and (once a run gets finished) for each run. This work will be extended by applying a suitable probability generating function and combining the probabilities of different parameters using Dempster-Shafer Theory (DST). DST provides a way to combine evidence that is available from different sources and gives a joint degree of belief in a hypothesis. This will give us a combined belief of fault in the process with a high precision.