• Journal of Ship and Ocean Technology
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• v.11 no.1
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• pp.36-46
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• 2007

The maintenance of a ship is essential for safe navigation and hence regular surveys are prescribed according to the rule of classification societies. A hull inspection is generally performed by professional divers, but it takes a long time and the efficiency is low in terms of time and cost. In this research, a ROV(Remotely Operated Vehicle) named as SNU-ROV(Seoul National University-ROV) is developed to replace the conventional inspection method. In this system, the ROV is intended to be used for inspecting ship and harbor because harbor inspection is merging as a safety measure against any possible terror actions. In order to increase the efficiency of inspection, the ROV must be able to measure the exact position of damages. SNU-ROV has a positioning system based on LBL(Long Base Line). In shallow water such as harbor, however, LBL has bad DOP(Dilution of Precision) in the depth direction due to the limited depth. Thus LBL only can not locate the exact depth position. To solve the DOP problem, a pressure sensor is introduced to LBL and a complementary filter is attached by using indirect feedback Kalman filter. Thus developed positioning system is verified by simulation and experiment in towing tank.

• Proceedings of the Korea Committee for Ocean Resources and Engineering Conference
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• 2003.05a
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• pp.27-31
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• 2003

Underwater acoustic navigation systems are classified into three systems: ultra-short baseline (USBL), short baseline (SBL), and long baseline (LBL). Because the USBL system estimates the angle of a submersible, the estimation error becomes large if the submersible is far from the USBL transducer array mounted under a support vessel. SBL and LBL systems estimate submersible's location more accurately because they have wider distribution of measuring sensors. Especially LBL systems are widely used as a navigation system for deep ocean applications. Although it is most accurate system it still has estimation errors because of noise, measurement error, refraction and multi-path of acoustic signal, or wrong information of the distributed transponders. In this paper the estimation error of the LBL system are analyzed from a point of sensitivity. It is assumed that the error exists only in the distance between a submersible and the transponders. For this purpose sensitivity of the estimated position with respect to relative distances between them is analyzed. The result says that estimation error is small if the submersible is close to transponders but not near the ocean bottom.

• Membrane and Water Treatment
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• v.10 no.3
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• pp.245-250
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• 2019

Prussian blue (PB) is well known for its excellent $Cs^+$ ions adsorption capacity. Due to the high dispersibility of PB in aqueous phase, composite materials imbedding PB in supporting materials have been introduced as a solution. However, building PB particles inside porous supporting materials is still difficult, as PB particles are not fully formed and elute out to water. In this study, we suggest layer-by-layer (LBL) assembly to provide better immobilization of PB on supporting materials of poly vinyl alcohol sponge (PVA) and cellulose filter (CF). Three different PB attachment methods, ex-situ/in-situ/LBL assembly, were evaluated using PB leaching test as well as $Cs^+$ adsorption test. Changes of surface functionality and morphology during PB composite preparation protocols were monitored through Fourier transform infrared spectroscopy and scanning electron microscopy. The results indicate that LBL assembly led to better PB attachment on supporting materials, bringing less eluting PB particles in aqueous phase compared to other synthesis methodologies, such as ex-situ and in-situ synthesis. By enhancing the stability of the adsorbent, adsorption capacity of PVA-PB with LBL improved nine times and that of CF-PB improved over 20 times. Therefore, the results suggest that LBL assembly offers a better orientation for growing PB particles on porous supporting materials.

• Plant Resources
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• v.5 no.3
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• pp.214-223
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• 2002

The objective of this study was to understand the conservation of gene resources and provide information for mass selection' of winter bud characters among the selected populations of Kalopanax septemlobus Koidz using analysis of variance(ANOVA) tests. The obtained results are shown below; 1. Ten populations of K. septemlobus were selected for the study of the variation of winter bud characters in Korea. The results of the analysis of variance(ANOVA) tests shows that there were statistically significant differences in all of the winter bud characters among those populations. 2. Correlation analysis shows that width between Height and DBH(Diameter at breast height) characters have negative relationship with all of the characters, as ABL(Apical branch length), ABW(Apical branch width), AWBL(Apical branch winter bud length), AWBW(Apical branch winter bud width), ABT(Apical branch No. of thorns), ABLB(Apical branch No. of lateral bud) and LBL(Lateral branch length), LBW(Lateral branch width), LBT(Lateral branch No. of thorns), LBLB(Lateral branch No. of lateral bud). 3. The result of principal component analysis(PCA) for winter buds showed that the first principal components(PC' s) to the fourth principal component explains about 78% of the total variation. The first principal component(PC) was correlated with AWBW, LWBW, and LBL and the ratio of ABL/ABW and LBL/LBW out of 16 winter bud characters. The second principal component correlated with ABL, ABW, ABLB, LWBL(Lateral branch winter bud length), and LBW and the ratio of AWBL/AWBW. The third principal component correlated with ABL, ABW, LWBL, LBL, and the ratio of LBL/LBW. The fourth principal component correlated with LBL and the ratio of LWBL/LWBW(Lateral branch winter bud width), LBL/LBW. Therefore, these characters were important to analysis of the variation for winter bud characters among selected populations of K. septemlobus in Korea. 4. Cluster analysis using the average linkage method based on 10 selected populations for the 16 winter bud characters of K. septemlobus in Korea showed a clustering into two groups by level of distance 1.1(Fig. 3). As can be seen in Fig. 3, Group I consisted of three areas(Mt. Sori, Mt. Balwang and Mt. Worak) and Group Ⅱ contisted of seven areas(Suwon, Mt. Chuwang, Mt. Kyeryong, Mt. Kaji, Mt. Jiri, Muan, and Mt. Halla). The result of cluster analysis for winter bud characters corresponded well with principal component analysis, as is shown in Fig. 2.

• Proceedings of the Materials Research Society of Korea Conference
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• 2011.05a
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• pp.40.2-40.2
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• 2011

As the old saying 'nothing is complete unless you put it in final shape', although nanosheets (NSs) are a promising functional building block for various electrochemical applications, their true value cannot be realized until they are well woven into electrical conducting materials. As an effort to determine their ideal shape, in this study, a unique manufacturing route to build a layer-by-layer (LBL) structure of two-dimensionally ordered, free-standing ${\beta}$-nickel hydroxide nanosheets (${\beta}$-NHNSs) that are fully electrically addressed with single-wall carbon nanotube fabrics was demonstrated, and its capabilities were verified through a comparative study on the differences between a simple bulky and LBL-structured electrochemical cathode, representing two extreme cases. The LBL-structured cathode showed a discharging current peak that was 25 times larger than the bulky structured one measured in cyclic voltammetry, which implies that the LBL structure is near an ideal electrode configuration for NS-based electrochemical applications.

• Proceedings of the Korea Contents Association Conference
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• 2005.11a
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• pp.364-370
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• 2005

LBL(Layer-By-Layer) algorithms have been proposed to accelerate the training speed of MLPs(Multilayer Perceptrons). In this LBL algorithms, each layer needs a error function for optimization. Especially, error function for hidden layer has a great effect to achieve good performance. In this sense, this paper proposes a new hidden layer error function for improving the performance of LBL algorithm for MLPs. The hidden layer error function is derived from the mean squared error of output layer. Effectiveness of the proposed error function was demonstrated for a handwritten digit recognition and an isolated-word recognition tasks and very fast learning convergence was obtained.

• Journal of Oral Medicine and Pain
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• v.30 no.1
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• pp.35-44
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• 2005

Purpose: The aim of this preliminary study was to evaluate the effect of Problem-Based Learning (PBL) curriculum on development of comprehension of basic medical knowledge and quality of semi-structured problem solving including scientific reasoning skill. This scientific reasoning contained five components including: size of simple, design of research cause-effect, construction of risk factor, analysis statistic of data, interpretation of result. Materials and Methods: Seoul National University Dental students (100) participated in this experience during two weeks, 2004. Forty eight multiple-choice questions (MCQ) concerned "Infection Control and Prevention" were asked before and after two sections of Lecture-Based Learning (LBL) and PBL (pretest-posttest control group design). A semi-structured problem in epidemiological research was asked to these students after two sections (posttest-only control group design). Data (mean and SD) were analysed using the t Test for two independent samples (p<.05), comparing PBL versus LBL. Results: Our analyse of scores show no difference between LBL and PBL in the development of comprehension of "Infection Control and Prevention". The quality problem solving (epidemiological research) was significantly different between the two groups (p=.029); specially, two components' scores of reflection on scientific reasoning cause-effect (p=.000) and interpretation of result (p=.001) were significantly better for PBL than for LBL. Conclusion: Theses results indicate that comparing LBL and PBL, PBL curriculum have not been disadvantaged in comprehension of basic knowledge, and have contributed to develop the scientific reasoning in problem solving.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.64.4-64
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• 2001

Localization is the key role in controlling the Mobile Robot. In this papers, a development of the sensor fusion algorithm for controling UTV(Unmanned Tracked Vehicle) is presented. The multi-sensocial dead-rocking subsystem is established based on the optimal filtering by first fusing heading angle reading from a magnetic compass, a rate-gyro and two encoders mouned on the robot wheels, thereby computing the deat-reckoned location. These data and the position data provoded by LBL system are fused together by means of an extended Kalman filter. This algorithm is proved by simulation studies.

• Corrosion Science and Technology
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• v.15 no.5
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• pp.209-216
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• 2016

In the present study, chitosan based self-healing anticorrosion coatings were prepared by layer by layer (lbl) addition of chitosan (Ch) and polyvinyl butyral (PVB) on mild carbon steel substrate. Chitosan coatings exhibited enhanced coating stability and corrosion resistance in aggressive environments by the application of a PVB top layer. Chitosan layer in the lbl coatings have been modified by using glutaraldehyde (Glu) and silica ($SiO_2$). Performance of different coatings was tested using electrochemical impedance spectroscopy and immersion test. The best anticorrosion performance was observed in case of 10 % Ch_$SiO_2$_PVB coatings, which withstand immersion test over 25 days in 0.5 M salt solution without visible corrosion. 10 % Ch_$SiO_2$ coatings without the PVB top layer didn't last more than 3days. Application of PVB top layer sealed the defects in the chitosan pre-layer and improved its hydrophobic nature as well. Raman spectra and SEM of steel surfaces after corrosion study and removal of PVB_Ch/Glu_PVB coatings showed a passive layer of iron oxide, attributing to the self-healing nature of these coatings. Conducting particle like graphene reinforcement of chitosan in the lbl coatings enhanced corrosion resistance of chitosan coatings.

• The Journal of the Korea Contents Association
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• v.5 no.6
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• pp.57-64
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• 2005

LBL(Layer-By-Layer) algorithms have been proposed to accelerate the training speed of MLPs(Multilayer Perceptrons). In this LBL algorithms, each layer needs a error function for optimization. Especially, error function for hidden layer has a great effect to achieve good performance. In this sense, this paper proposes a new hidden layer error function for improving the performance of LBL algorithm for MLPs. The hidden layer error function is derived from the mean squared error of output layer. Effectiveness of the proposed error function was demonstrated for a handwritten digit recognition and an isolated-word recognition tasks and very fast learning convergence was obtained.