• Proceedings of the Korea Information Processing Society Conference
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• 2008.11a
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• pp.1307-1310
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• 2008

EM(Expectation Maximization)은 불확실한 데이터들을 가지고 분포를 모델링하는, 널리 알려진 군집화 알고리즘이다. EM 알고리즘에서, 정규 분포는 기대(Expectation)-최대화(Maximization)과정을 반복하는 과정에서 그 윤곽을 다져간다. 이 때 이 과정은 EM 알고리즘의 다양한 확률 초기화에 따라 다른 결과를 내게 된다, 본 논문에서는 이 확률 초기화 값의 조정을 통하여 HAPS(High Altitude Platform Station) 기반 네트워크에서 이동 기지국의 위치를 실시간으로 결정하고자 하는 문제를 풀기 위한 조건을 몇 가지 반영시켜 확률 초기 값을 결정해 보고, 그 결과를 제시한다. 이에 더불어, ITU에서 제한하고 있는 이동 기지국의 서비스 반경을 고려하는 방법을 제시한다.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.7
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• pp.740-748
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• 2016

IT and communication technologies has contributed significantly to the convenience of passengers and the financial management of stations in accordance with the task automation in the field of the urban railway system. The foundation of the above development is based on the large amounts of data from various sensors installed in railways, trains, and stations. In particular, the sensor network that is installed in the station and train has played an important role in the railway information system. The performance of AP is affected by the number of APs and their locations installed in the station. In the installation of APs in stations, the intensity of the radio wave of the AP on its underlying position is considered to determine the number and position of APs. This paper proposes a method to estimate the number of APs and their position based on the structure of the underlying station and implemented a simulator to simulate the performance of the proposed method. The implemented simulator was applied to the decision of AP installation at Busan Seomyeon station to evaluate its performance.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.49 no.1
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• pp.39-45
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• 2012

In this paper, a distributed 2-hop routing algorithm is proposed. The main purpose of the proposed algorithm is to reduce the overall power consumption of each sensor node so that the lifetime of WSN(wireless sensor network) is prolonged. At the beginning of each round, the base station transmits a synchronization signal that contains information on the priority table that is used to decide whether each sensor node is elected as a cluster head or not. The priority table is constructed so that sensor nodes closer to half energy distance from the base station get the higher priority. 2-hop routing is done as follows. Cluster heads inside half energy distance from the base station communicate with the base station directly. Those outside half energy distance have to decide whether they choose 2-hop routing or 1-hop routing. To do this, each cluster head outside half energy distance calculates the energy consumption needed to communicate with the base station via 1-level cluster head or directly. If less energy is needed when passing through the 1-level cluster head, 2-hop routing is chosen and if not, 1-hop routing is chosen. After routing is done each sensor nodes start sensing data.

• Journal of Korea Water Resources Association
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• v.34 no.6
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• pp.577-586
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• 2001

This study proposes a theoretical methodology for deriving a rainfall intensity-duration- frequency (I-D-F) curve using a simple rectangular pulses Poisson process model. As the I-D-F curve derived by considering the model structure is dependent on the rainfall model parameters estimated using the observed first and second order statistics, it becomes less sensitive to the unusual rainfall events than that derided using the annual maxima rainfall series. This study has been applied to the rainfall data at Seoul and Inchon stations to check its applicability by comparing the two I-D-F carves from the model and the data. The results obtained are as followed. (1) As the duration becomes longer, the overlap probability increases significantly. However, its contribution to the rainfall intensity decreases a little. (2) When considering the overlap of each rainfall event, especially for large duration and return period, we could see obvious increases of rainfall intensity. This result is normal as the rainfall intensity is calculated by considering both the overlap probability and return period. Also, the overlap effect for Seoul station is fecund much higher than that for Inchon station, which is mainly due to the different overlap probabilities calculated using different rainfall model parameter sets. (3) As the rectangular pulses Poisson processes model used in this study cannot consider the clustering characteristics of rainfall, the derived I-D-F curves show less rainfall intensities than those from the annual maxima series. However, overall pattern of both I-D-F curves are found very similar, and the difference is believed to be overcome by use of a rainfall model with the clustering consideration.

• Journal of KIISE:Computing Practices and Letters
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• v.15 no.12
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• pp.938-942
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• 2009

In this paper, we propose a novel filtering method for processing continuous skyline queries on wireless sensor network environments. The existing filtering methods use the filter based on router paths. However, because these filters are applied not to a whole area but to a partial area, these methods send almost data of sensor nodes to transmit to the base station and have no sufficient effect in terms of energy efficiency. Therefore, we propose an efficient method to dramatically reduce the transmission data of sensors through applying a low-cost and effective filter to all sensor nodes. The proposed effective filter is generated by using characteristics such as the data locality and the clustering of sensors. An extensive performance study verifies the merits of our new method.

• Journal of Environmental Science International
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• v.20 no.6
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• pp.737-753
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• 2011

The typical characteristics of seasonal winds were studied around the Pohang using two-stage (average linkage then k-means) clustering technique based on u- and v-component wind at 850 hpa from 2004 to 2006 (obtained the Pohang station) and a high-resolution (0.5 km grid for the finest domain) WRF-UCM model along with an up-to-date detailed land use data during the most predominant pattern in each season. The clustering analysis identified statistically distinct wind patterns (7, 4, 5, and 3 clusters) representing each spring, summer, fall, and winter. During the spring, the prevailed pattern (80 days) showed weak upper northwesterly flow and late sea-breeze. Especially at night, land-breeze developed along the shoreline was converged around Yeongil Bay. The representative pattern (92 days) in summer was weak upper southerly flow and intensified sea-breeze combined with sea surface wind. In addition, convergence zone between the large scale background flow and well-developed land-breeze was transported around inland (industrial and residential areas). The predominant wind distribution (94 days) in fall was similar to that of spring showing weak upper-level flow and distinct sea-land breeze circulation. On the other hand, the wind pattern (117 days) of high frequency in winter showed upper northwesterly and surface westerly flows, which was no change in daily wind direction.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.46 no.4
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• pp.334-340
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• 2001

Two different types of molecular markers, simple sequence repeat (SSR) and single nucleotide polymorphism (SNP), were used to measure genetic diversity among five Korean, eight Thai, and three wild soybeans. For SSR analysis, a total of 20 markers were surveyed to detect polymorphisms. For SNP analysis, four primers were designed from consensus sequence regions on disease resistance protein homolog genes, and used to amplify the genomic region. The PCR products were sequenced. A number of polymorphic SSR and SNP bands were scored on all genotypes and their genetic similarity was measured. Clustering analysis was performed independently on both types of markers. Clustering based on SSR markers separated the genotypes into three main groups originated from Korea, Thailand, and wild soybeans. On the other hand, two main groups were classified using SNP analysis. It seemed that SSR was more informative than SNP in this study. This may be due to the fact that SNP was surveyed on the smaller genomic region than SSR. Grouping based on the combined data of both markers revealed similar results to that of SNP rather than that of SSR. This might be due to the fact that more loci from SNP were considered to measure genetic relatedness than those from the SSR.

• Convergence Security Journal
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• v.7 no.2
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• pp.107-118
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• 2007

Distributed wireless sensor network in various environment have characteristic that is surveillance of environment-element and offering usefully military information but there is shortcoming that have some secure risks. Therefore secure service must be required for this sensor network safety. More safe and effective techniques of node administration are required for safe communication between each node. This paper proposes effective cluster-header and clustering techniques in suitable administration techniques of group-key on sensor network. In this paper, first each node transmit residual electric power and authentication message to BS (Base-Station). BS reflects "Validity Authentication Rate" and residual electric power. And it selects node that is more than these regularity values by cluster header. After BS broadcasts information about cluster header in safety and it transmits making a list of information about cluster member node to cluster header. Also, Every rounds it reflects and accumulates "Validity Authentication Rate" of former round. Finally, BS can select more secure cluster header.

• Journal of the Korea Society of Computer and Information
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• v.12 no.1 s.45
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• pp.73-82
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• 2007

This paper proposes how to reduce the amount of data transmitted in each sensor and cluster head in order to lengthen the lifetime of sensor network by data aggregation of the continuous queries. The most important factor of refuting the sensor's energy dissipation is to reduce the amount of messages transmitted. The method proposed is basically to combine clustering, in-network data aggregation and hierarchical filtering. Hierarchical filtering is to divide sensor network by two tiers when filtering it. First tier performs filtering when transmitting the data from cluster member to cluster head, and second tier performs filtering when transmitting the data from cluster head to base station. This method is much more efficient and effective than the previous work. We show through various experiments that our scheme reduces the network traffic significantly and increases the network's lifetime than existing methods.

• Journal of the Korea Society of Computer and Information
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• v.13 no.5
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• pp.219-227
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• 2008

As found in research on constraint satisfaction problems, the choice of variable ordering heuristics is crucial for effective solving of constraint optimization problems. For the special problems such as energy-efficient clustering in heterogeneous wireless sensor networks, in which cluster heads have an inclination to be near a base station, we propose a new approach based on the static preferences variable orderings and provide a pnode heuristic algorithm for a specific application. The pnode algorithm selects the next variable with the highest Preference. In our problem, the preference becomes higher when the cluster heads are closer to the optimal region, which can be obtained a Priori due to the characteristic of the problem. Since cluster heads are the most dominant sources of Power consumption in the cluster-based sensor networks, we seek to minimize energy consumption by minimizing the maximum energy dissipation at each cluster heads as well as sensor nodes. Simulation results indicate that the proposed approach is more efficient than other methods for solving constraint optimization problems with static preferences.