• The Journal of Korean Institute of Communications and Information Sciences
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• v.37B no.12
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• pp.1160-1167
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• 2012

Identifying traffic is an important issue for many networking applications including quality of service, firewall enforcement, and network security. Once we know the purpose of using the traffic in the firewall, we can allow or deny it and provide quality of service, and effective operation in terms of security. However, a number of applications encrypts traffics in order to enhance security or privacy. As a result, effective traffic monitoring is getting more difficult. In this paper, we analyse SSH encrypted traffic and identify differences among SSH tunneling, SFTP, and normal SSH traffics. By using EM clustering, we identify traffics and validate experiment results.

• Korean Journal of Plant Taxonomy
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• v.48 no.3
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• pp.153-162
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• 2018

Lespedeza maximowiczii C. K. Schneid. (Fabaceae) is a deciduous shrub which is known to be distributed in the temperate forests of China, Korea and on Tsushima Island of Japan. Due to severe morphological variations within species, numerous examinations have been conducted for Korean L. maximowiczii. However, the morphology of Chinese plants has not been studied as thoroughly, despite doubts about their taxonomy. To clarify this taxonomic issue, we investigated morphological characters and undertook a Bayesian clustering analysis with microsatellite markers. The morphological and genetic traits of Chinese individuals varied considerably from those of typical L. maximowiczii growing in Korea. For example, petals of the former had a different shape and bore long claws, while the calyx lobes were diverged above the middle and the upper surface of the leaflet was pubescent. Their terete buds and spirally arranged bud scales were distinct from those within the series/section Heterolespedeza, which includes L. maximowiczii. Our Bayesian clustering analysis additionally included L. buergeri as an outgroup. Those results indicated that the Chinese samples clustered into a lineage separated from L. maximowiczii (optimum cluster, K = 2), despite the fact that the latter is grouped into the same lineage with L. buergeri. Therefore, we treat those Chinese plants as a new species with the name L. pseudomaximowiczii.

• Nuclear Engineering and Technology
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• v.49 no.6
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• pp.1157-1164
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• 2017

The Monte Carlo criticality simulation of decoupled systems, as for instance in large reactor cores, has been a challenging issue for a long time. In particular, due to limited computer time resources, the number of neutrons simulated per generation is still many order of magnitudes below realistic statistics, even during the start-up phases of reactors. This limited number of neutrons triggers a strong clustering effect of the neutron population that affects Monte Carlo tallies. Below a certain threshold, not only is the variance affected but also the estimation of the eigenvectors. In this paper we will build a time-dependent diffusion equation that takes into account both spatial correlations and population control (fixed number of neutrons along generations). We will show that its solution obeys a traveling wave dynamic, and we will discuss the mechanism that explains this biasing of local tallies whenever leakage boundary conditions are applied to the system.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.3
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• pp.813-829
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• 2022

In multi-view subspace clustering, how to integrate the complementary information between perspectives to construct a unified representation is a critical problem. In the existing works, the unified representation is usually constructed in the original data space. However, when the data representation in each view is very diverse, the unified representation derived directly in the original data domain may lead to a huge information loss. To address this issue, different to the existing works, inspired by the latest revelation that the data across all perspectives have a very similar or close spectral block structure, we try to construct the unified representation in the spectral embedding domain. In this way, the complementary information across all perspectives can be fused into a unified representation with little information loss, since the spectral block structure from all views shares high consistency. In addition, to capture the global structure of data on each view with high accuracy and robustness both, we propose a novel low-rank approximation via the tight lower bound on the rank function. Finally, experimental results prove that, the proposed method has the effectiveness and robustness at the same time, compared with the state-of-art approaches.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.10
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• pp.4781-4803
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• 2017

Environmental monitoring systems using Wireless Sensor Networks (WSNs) face the challenge of high power consumption, due to the high levels of multi-hop data communication involved. In order to overcome the issue of fast energy depletion, a proof-of-concept implementation proves that adopting a clustering algorithm in environmental monitoring applications will significantly reduce the total power consumption for environment sensor nodes. In this paper, an energy-efficient WSN-based environmental monitoring system is proposed and implemented, using eight sensor nodes deployed over an area of $1km^2$, which took place in the city of Tabuk in Saudi Arabia. The effectiveness of the proposed environmental monitoring system has been demonstrated through adopting a number of real experimental studies.

• Proceedings of the Society of Korea Industrial and System Engineering Conference
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• 2002.05a
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• pp.455-460
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• 2002

As the transmission of 3D shape models through Internet becomes more important, the compression issue of shape models gets more critical. The issues for normal vectors have not yet been explored as much as it deserves, even though the size of the data for normal vectors can be significantly larger than its counterparts of topology and geometry. Presented in this paper is an approach to compress the normal vectors of a shape model represented in a mesh using the concept of clustering. It turns out that the proposed approach has a significant compression ratio without a serious sacrifice of the visual quality of the model.

• International Journal of Contents
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• v.9 no.1
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• pp.6-10
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• 2013

Foreground estimation in object segmentation has been an important issue for last few decades. In this paper we propose a GrabCut based automatic foreground estimation method using block clustering. GrabCut is one of popular algorithms for image segmentation in 2D image. However GrabCut is semi-automatic algorithm. So it requires the user input a rough boundary for foreground and background. Typically, the user draws a rectangle around the object of interest manually. The goal of proposed method is to generate an initial rectangle automatically. In order to create initial rectangle, we use Gabor filter and Saliency map and then we use 4 features (amount of area, variance, amount of class with boundary area, amount of class with saliency map) to categorize foreground and background. From the experimental results, our proposed algorithm can achieve satisfactory accuracy in object segmentation without any prior information by the user.

• IE interfaces
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• v.21 no.2
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• pp.237-246
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• 2008

In today's competitive global environment, technological innovation is an important issue. Many countries are devising national level strategies to further strengthen industrial capacity in support of innovative companies. South Korea is no exception, and multiple strategies are in place to aid innovative development in the private sector. This study postulates that such national level strategies are applied differently depending on the innovation goal pursued by the service sector in Korea. We use data mining methods to test such research hypothesis. Factor analysis is used for clustering of various service companies, while association rule is used in finding the relationship per each cluster. The results show that national level strategies are underutilized and unequally distributed. This may be attributed to the disparity between the demand and needs of the private sector and the opinion of the government, which lead to underutilized and indistinguishable strategies.

• Proceedings of the Korea Information Processing Society Conference
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• 2005.05a
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• pp.1461-1464
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• 2005

In contrast with conventional networks, mobile ad hoc networks usually do not provide online access to trusted authorities or to centralized servers, and they exhibit frequent partitioning due to link and node failures and node mobility. For these reasons, traditional security solutions that require online trusted authorities or certificate repositories, but those are not well-suited for securing ad hoc networks. Moreover, a fundamental issue of securing mobile ad hoc networks is to ensure mobile nodes can authenticate each other. Because of its strength and efficiency, public key and digital signature is an ideal mechanism to construct the authentication service. Although this is already mature in the internet application, providing public key based authentication is still very challenging in mobile ad hoc networks. In this paper I propose a secure public key authentication service based on clustering model and trust model to protect nodes from getting false public keys of the others efficiently when there are malicious nodes in the network.

• Journal of the Korea Society of Computer and Information
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• v.22 no.5
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• pp.65-72
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• 2017

Premature Ventricular Contraction(PVC) arrhythmia is most common abnormal-heart rhythm that may increase mortal risk of a cardiac patient. Thus, it is very important issue to identify the specular portraits of PVC pattern especially from the patient. In this paper, we propose a new method to extract the characteristics of PVC pattern by applying K-means machine learning algorithm on Heart Rate Variability depicted in Poinecare plot. For the quantitative analysis to distinguish the trend of cluster patterns between normal sinus rhythm and PVC beat, the Euclidean distance measure was sought between the clusters. Experimental simulations on MIT-BIH arrhythmia database draw the fact that the distance measure on the cluster is valid for differentiating the pattern-traits of PVC beats. Therefore, we proposed a method that can offer the simple remedy to identify the attributes of PVC beats in terms of K-means clusters especially in the long-period Electrocardiogram(ECG).