• The KIPS Transactions:PartC
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• v.11C no.7 s.96
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• pp.905-916
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• 2004

Self-organizing hierarchical ad hoc network (SOHAN) is a new ad-hoc network architecture designed to improve the scalability properties of conventional 'flat' ad hoc networks. This network architecture consists of three tiers of ad-hoc nodes, i.e.. access points, forwarding nodes and mobile nodes. This paper presents a topology discovery and routing protocol for the self-organization of SOHAN. We propose a cross-layer path metric based on link quality and MAC delay which plays a key role in producing an optimal cluster-based hierarchical topology with high throughput capacity. The topology discovery protocol provides the basis for routing which takes place in layer 2.5 using MAC addresses. The routing protocol is based on AODV with appropriate modifications to take advantage of the hierarchical topology and interact with the discovery protocol. Simulation results are presented which show the improved performance as well as scalability properties of SOHAN in terms of through-put capacity, end-to-end delay, packet delivery ratio and control overhead.

• Journal of Digital Contents Society
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• v.15 no.6
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• pp.737-743
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• 2014

For single image super resolution (SR), interpolation based and example based algorithms are extensively used. The interpolation algorithms have the strength of theoretical simplicity. However, those algorithms are tending to produce high resolution images with jagged edges, because they are not able to use more priori information. Example based algorithms have been studied in the past few years. For example based SR, the nearest neighbor based algorithms are extensively considered. Among them, neighbor embedding (NE) has been inspired by manifold learning method, particularly locally linear embedding. However, the sizes of local training sets are always too small. So, NE algorithm is weak in the performance of the visuality and quantitative measure by the poor generalization of nearest neighbor estimation. An improved NE algorithm with Support Vector Regression (SVR) was proposed to solve this problem. Given a low resolution image, the pixel values in its high resolution version are estimated by the improved NE. Comparing with bicubic and NE, the improvements of 1.25 dB and 2.33 dB are achieved in PSNR. Experimental results show that proposed method is quantitatively and visually more effective than prior works using bicubic interpolation and NE.

• The KIPS Transactions:PartB
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• v.13B no.2 s.105
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• pp.121-126
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• 2006

In this paper, we propose an approach to increase the power of clustering Web images by using high-level semantic features from text information relevant to Web images as well as low-level visual features of image itself. These high-level text features can be obtained from image URLs and file names, page titles, hyperlinks, and surrounding text. As a clustering engine, self-organizing map (SOM) proposed by Kohonen is used. In the SOM-based clustering using high-level text features and low-level visual features, the 200 images from 10 categories are divided in some suitable clusters effectively. For the evaluation of clustering powers, we propose simple but novel measures indicating the degrees of scattering images from the same category, and degrees of accumulation of the same category images. From the experiment results, we find that the high-level text features are more useful in SOM-based Web image clustering.

• Journal of the Korean Society of Fisheries and Ocean Technology
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• v.31 no.2
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• pp.199-209
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• 1995

From the results of model tests, statistical regression analysis of EHP estimation based on hull form parameters is adopted in this study. From this result, the method for estimation of EHP at the initial design stage of fishing boats is developed. This method is applied to four standard fishing boats with chine lines and two standard fishing boats with round bottom. The EHP's are estimated and compared to experimental results. In the case of six fishing boats, the estimated EHP corresponds well and approximates well with experimental results through out all the range tested. From these results it can be concluded that this numerical method is very efficient in estimating EHP of fishing boats having chine line and round bottom. Therefore, by applying the proposed method to design of fishing boats, we can improve the resistance characteristics. Further, this method can contribute to reduction of design time and thus down the total expenses.

• Journal of the Korea Society of Computer and Information
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• v.20 no.1
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• pp.21-28
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• 2015

Feature normalization as a pre-processing step has been widely used to reduce the effect of different scale in each feature dimension and error rate in classification. Most of the existing normalization methods, however, do not use the class labels of data points and, as a result, do not guarantee the optimality of normalization in classification aspect. A supervised rank normalization method, combination of rank normalization and supervised learning technique, was proposed and demonstrated better result than others. In this paper, another technique, training sample selection, is introduced in supervised feature normalization to reduce classification error more. Training sample selection is a common technique for increasing classification accuracy by removing noisy samples and can be applied in supervised normalization method. Two sample selection measures based on the classes of neighboring samples and the distance to neighboring samples were proposed and both of them showed better results than previous supervised rank normalization method.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.10 no.1
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• pp.148-155
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• 2006

Portable embedded systems which mainly handle multimedia applications involve the problem that frequent accesses to fetch data from memory make running time increased. To cope with the problem, embedded processors have adopted data prefetching schemes. From a power point of view, which is a main performance indicator of embedded systems, this paper analyzed to investigate how data prefetching schemes influence on system's performance. To solve the problem, we proposed a power-consumption analysis model of a memory system with data prefetching scheme and measured the power dissipated during running application programs. As a result data prefetching schemes have application program's running time reduced but have system's power increased. Also we proposed a performance analysis model considering execution time and power consumption for embedded system with data prefetching schemes.

• Proceedings of the Korean Society for Emotion and Sensibility Conference
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• 2007.05a
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• pp.39-41
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• 2007

본 연구는 직물 기반 바이오 모니터링 스마트 의류를 개발하기 위해 의복 소재의 신축성에 따른 심전도 신호 검출 성능과 착용 성능을 평가하여 직물 기반 심전도 의복을 위한 최적 범위를 제안하고자 한다. 이를 위해, 서로 다른 신축률의 편물을 얻기 위해 면/폴리에스테르에 스판덱스 함유율을 0%, 5%, 8%로 다르게 하여 제편하였다. 이 세 가지 소재로 심전도 측정을 위해 동일한 사이즈로 의복을 제작한 후, 금속사를 이용한 자수 기법으로 심전도 전극을 설치하였다. 심장 관련 병력이 없고 평균 BMI가 $20{\sim}24$인 정상 체중의 5명을 대상으로 Biopac MP150을 사용하여 심전도 신호를 검출한 후, 설문지를 사용하여 소재의 신축성에 따른 착용성 평가를 시행하여 신축성에 대한 만족감, 동작용이성, 전반적 쾌적함 등을 Likert 7점 척도로 평가하도록 하였다. 실험 결과, 심전도 신호 검출 성능 측면에서는 8% 라이크라 함유 소재가 가장 우수하였으나, 착용성 측면에서는 5% 소재가 가장 우수한 것으로 파악되었다. 향후 그 수요가 높아질 것으로 예상되는 바이오 모니터링 의복 소재 개발을 위해 기능성과 착용성을 모두 고려한 본 연구 결과가 유용하게 활용될 것이다.

• Journal of the Korea Society for Simulation
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• v.21 no.2
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• pp.69-78
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• 2012

In this paper, a study on finding an appropriate helper node that can help increase effective frame transmission rate for cooperative communications at ad hoc networks is carried out. Those researches from reference use the reactive helper node selection mechanism which starts its role after exchanging RTS and CTS frames between source and destination nodes, and are implemented into our simulator for performance comparison. System throughput and average channel access delay are used for performance measures and all communicating nodes are assumed to move independently within the communication range. It is anticipated that this research result can be used as basic information for designing a new efficient helper node selection scheme.

• Journal of the Society of Naval Architects of Korea
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• v.36 no.2
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• pp.72-76
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• 1999

To predict the maneuverabiliy of a ship, it is most reliable to carry out the model tests for the ship. But, at the initial design stage of ships, scene other methods of predicting the overall maneuverabiliy of ships with confined data, like principal dimensions and propeller and rudder characteristics, are required. In this paper, the authors suggested new formulas for the linear derivatives of the sway force and yaw moment, based on the captive model test carried out by the Japanese researchers. These formulas can account the effects of stern frame line shape and stern profile, when assessing the maneuverability of ships. The usefulness of the formulas are discussed by comparing the simulations with the model tests.

• Journal of the Society of Naval Architects of Korea
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• v.35 no.1
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• pp.46-53
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• 1998

In this paper, we studied to improve Inoue's[1] and Kijima's[2] model used to predict ship's manoeuvrability at initial design state. To perform this work, we carried out PMM(Planar motion Mechanism) test and rudder open water test for 12 models of low-speed blunt-ship which have horn type rudders and bulbs in afterbody. As we adopted MMG(Mathematical Modelling Group) model, we could analyze hydrodynamic and MMG experimental coefficients. The regression analyses by principle parameters were carried out for hydrodynamic and MMG experimental coefficients. The regression analyses by principle parameters were carried out for hydrodynamic and MMG experimental coefficients and the equations by regression analysis wee used to search sensitivities and to estimate ship's manoeuvrability. We had simulated ship's manoeuvrability to check revised MMG.