• Journal of Magnetics
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• v.11 no.4
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• pp.160-163
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• 2006

We have prepared crystalline Ag nanoparticles with an average size of 4 nm in diameter by using an inductively coupled plasma reactor equipped with the liquid nitrogen cooling system. Our magnetic data show that the nano-sized effect of Ag nanoparticles on the magnetic properties is ferromagnetic, instead of a diamagnetic component of the Ag bulk and a superparamagnetic component of magnetic nanoparticles. We have also studied the magnetic properties of Ag-Cu nanocomposites with an opposite concentration profile between surface and core. These comparisons indicate that the ferromagnetic component strongly depends on the surface of Ag nanoparticles, while the paramagnetic component is strongly affected by the outer oxide layer, with the background of a diamagnetic component from the core of Ag.

• Proceedings of the KIEE Conference
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• 2006.10d
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• pp.34-36
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• 2006

In this paper, we will treat the diagnosis problem to accurately determine fault types. The judgement of fault types is accomplished by observing the cluster newly formed with faults and clustering the input current waveforms to intrinsically show the conditions with the dignet that is a clustering algorithm. The types of input current waveforms are, however, constrained during normal operation, though it considers the load character. In case of faults. new clusters are generated outside the clusters. which appear during normal operation, because the input current waveforms of the induction motor are generated by the type which is not observed in case of faults. The diagnosis about the types of faults is essential to building a fault tree about the induction motor, and it removes the causes of the faults using a fuzzy logic. We, first, constitute a fault tree, which connects with the parts and the entire system of the induction motor, and investigate fault modes which can be generated from the fault tree and the relationship of the cause and the effect of each part (of the motor). Also, we distinguish the faults of each part by means of inducing the said of fuzzy relation equations encapsulating the relationship of the fault modes and each part.

• The Transactions of the Korea Information Processing Society
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• v.7 no.7
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• pp.2246-2253
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• 2000

In this paper, we show that one can enhance the performance of blind segmentation of phoneme boundaries by adopting the knowledge of Korean syllabic structure and the regions of voiced/unvoiced sounds. eh proposed method consists of three processes : the process to extract candidate phoneme boundaries, the process to detect boundaries of voiced/unvoiced sounds, and the process to select final phoneme boundaries. The candidate phoneme boudaries are extracted by clustering method based on similarity between two adjacent clusters. The employed similarity measure in this a process is the ratio of the probability density of adjacent clusters. To detect he boundaries of voiced/unvoiced sounds, we first compute the power density spectrum of speech signal in 0∼400 Hz frequency band. Then the points where this paper density spectrum variation is greater than the threshold are chosen as the boundaries of voiced/unvoiced sounds. The final phoneme boundaries consist of all the candidate phoneme boundaries in voiced region and limited number of candidate phoneme boundaries in unvoiced region. The experimental result showed about 40% decrease of insertion rate compared to the blind segmentation method we adopted.

• Journal of Navigation and Port Research
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• v.27 no.3
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• pp.315-320
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• 2003

Since the beginning of open-door policy, China has been making rapid annual growth with an average 10% economic development. And due to this rapid growth, cargo volumes via ports have been also rapidly increased, and accordingly, current China government has intensively invested in port development. Further, this development project is significantly big scale, compared with those project which Korea and Japan have. Thus, China is beginning to threaten Korean ports, especially Busan port which try to be a hub port in Northeast Asia. For this reason, it has been very important issue for Korea and Busan port to investigate or analyze Chinese ports based on empirical data. Especially, although various studies related to Shanghai and Hong Kong have been conducted, the competitiveness of overall Chinese major ports has been little studied. In this paper, we analyzed competitiveness level of eight Chinese ports with capabilities as container terminal, based on reliable sources. From data analysis, eight Chinese ports were classified into four groups according to competitiveness level. Rankings among four clusters based on competitiveness level are cluster(Hone Kong), cluster C(Shanghai), cluster A(Qingdao, Tianjin, and Yantian) and cluster D(Dalian, Shekou, and Xiamen).

• Journal of Korean Society for Atmospheric Environment
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• v.24 no.5
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• pp.584-593
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• 2008

The surface $O_3,\;CO,\;NO_x,\;and\;SO_2$ were measured at Gosan in Jeju Island from May 2004 to April 2005. Over this period, the mean concentrations $({\pm}s.d.)$ of each gas was 40.06 $({\pm}16.01)$ ppbv for $O_3,\;264.92({\pm}115.73)ppbv\;for\;CO,\;1.98({\pm}2.73)ppbv\;for\;SO)_2,\;and\;4.64 ({\pm}3.24) ppbv\;for\;NO_x$. The monthly variations and the diurnal variations of these gases show that the Gosan site is situated in a relatively clean region. However, there were episodic simultaneous peaks in CO and $SO_2$, especially in winter and early spring. Using cluster analysis with air mass back- ward trajectory analysis, we suggest that these episodes are due to the influence of transportation of polluted air mass from polluted regions. In the cluster, which was under the dominant influence of clean maritime air mass, low levels of $O_3,\;CO,\;and\;SO_2$ were observed. The levels of these species were elevated in the other two clusters which had the air mass influenced by polluted continental regions. In addition, ratios of the chemical species such as $CO/NO_x,\;SO_2/NO_x,\;and\;CO/SO_2$ revealed the somewhat different characteristics of emission sources influencing each cluster. The differences in concentration of trace gases among clusters with different origin and transport pathways imply that Gosan is under the effect of pollution transported from other regions.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2017.05a
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• pp.649-651
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• 2017

A clustering problem is one of the organizational problems to improve the network lifetime and scalability in wireless ad-hoc networks. This problem is a difficult combinatorial optimization problem associated with the design and operation of these networks. In this paper, we propose an efficient clustering algorithm to maximize the network lifetime and consider scalability in wireless ad-hoc networks. The clustering problem is known to be NP-hard. We thus solve the problem by using optimization approaches that are able to efficiently obtain high quality solutions within a reasonable time for a large size network. The proposed algorithm selects clusterheads and configures clusters by considering both nodes' power and the clustering cost. We evaluate this performance through some experiments in terms of nodes' transmission energy. Simulation results indicate that the proposed algorithm performs much better than the existing algorithms.

• Journal of Navigation and Port Research
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• v.43 no.2
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• pp.110-121
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• 2019

Ports play a key role in international trade, as integral hubs where passengers and cargoes are loaded, discharged, and transshipped. However, the function of ports is becoming more diversified, expanding on roles as industrial clusters, as well as logistical centers. Such roles combined, reap numerous and significant benefits, mainly with growth of jobs and wealth creation, for the local population living in the city, and beyond. Citizens' awareness of the function and value of ports may not be positive, because of a range of negative factors such as emissions, noise, and road congestion, which can influence their perception. This study's contribution focuses on empirically evaluating the perception of Busan citizens of the local port, by applying Q methodology. The links connecting the port-city and local population, are assessed by identifying: 1) The level of awareness of the Busan citizens of the port; 2) Factors perceived as positive as well as factors perceived as negative by Busan citizens. There are four main factors, derived from the analysis: 1) Port functional knowledge; 2) Lack of social connectedness port-city; 3) Environmentally concerned and; 4) Absent port's ripple's effect. Policy recommendations suggest focusing on improving citizens' perception of the port, for each of the four main factors derived from the analysis.

• Journal of the Society of Naval Architects of Korea
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• v.59 no.6
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• pp.393-399
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• 2022

During the ship hull design process, resistance performance estimation is generally calculated by simulation using computational fluid dynamics. Since such hull resistance performance simulation requires a lot of time and computation resources, the time taken for simulation is reduced by CPU clusters having more than tens of cores in order to complete the hull design within the required deadline of the ship owner. In this paper, we propose a method for estimating resistance performance of ship hull by simulation using a graph neural network. This method converts the 3D geometric information of the hull mesh and the physical quantity of the surface into a mathematical graph, and is implemented as a deep learning model that predicts the future simulation state from the input state. The method proposed in the resistance performance experiment of simple hull showed an average error of about 3.5 % throughout the simulation.

• Journal of the Korean Society of Marine Environment & Safety
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• v.27 no.4
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• pp.483-491
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• 2021

The identification of regional collision risks in water areas is significant for the safety of navigation. This paper introduces a new method of collision risk assessment that incorporates a clustering method based on the distance factor - hierarchical clustering - and uses real-time data in case of several surrounding vessels, group methodology and preliminary assessment to classify vessels and evaluate the basis of collision risk evaluation (called HCAAP processing). The vessels are clustered using the hierarchical program to obtain clusters of encounter vessels and are combined with the preliminary assessment to filter relatively safe vessels. Subsequently, the distance at the closest point of approach (DCPA) and time to the closest point of approach (TCPA) between encounter vessels within each cluster are calculated to obtain the relation and comparison with the collision risk index (CRI). The mathematical relationship of CRI for each cluster of encounter vessels with DCPA and TCPA is constructed using a negative exponential function. Operators can easily evaluate the safety of all vessels navigating in the defined area using the calculated CRI. Therefore, this framework can improve the safety and security of vessel traffic transportation and reduce the loss of life and property. To illustrate the effectiveness of the framework proposed, an experimental case study was conducted within the coastal waters of Mokpo, Korea. The results demonstrated that the framework was effective and efficient in detecting and ranking collision risk indexes between encounter vessels within each cluster, which allowed an automatic risk prioritization of encounter vessels for further investigation by operators.

• Korean Journal of Remote Sensing
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• v.39 no.6_1
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• pp.1235-1243
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• 2023

This study proposes the detection algorithm for the cold water mass (CWM) along the eastern coast of the Korean Peninsula using sea surface temperature (SST) data provided by the Korea Institute of Ocean Science and Technology (KIOST). Considering the occurrence and distribution of the CWM, the eastern coast of the Korean Peninsula is classified into 3 regions("Goseong-Uljin", "Samcheok-Guryongpo", "Pohang-Gijang"), and the K-means clustering is first applied to SST field of each region. Three groups, K-means clusters are used to determine CWM through applying a double threshold filter predetermined using the standard deviation and the difference of average SST for the 3 groups. The estimated sea area is judged by the CWM if the standard deviation in the sea area is 0.6℃ or higher and the average water temperature difference is 2℃ or higher. As a result of the CWM detection in 2022, the number of CWM occurrences in "Pohang-Gijang" was the most frequent on 77 days and performance indicators of the confusion matrix were calculated for quantitative evaluation. The accuracy of the three regions was 0.83 or higher, and the F1 score recorded a maximum of 0.95 in "Pohang-Gijang". The detection algorithm proposed in this study has been applied to the KIOST SST system providing a CWM map by email.