• Korean Journal of Medicinal Crop Science
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• v.11 no.4
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• pp.259-263
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• 2003

This study was carried out to get basic information about the morphological and production characteristics of fennel populations different origin under different ecological conditions in Hungary. The Korean population can be registered as a medium high genotype and showed a more accelerated growth characters than Hungarian taxon and the two populations have a medium homogeneity $(CV\;=\;4{\sim}22%)$. In the second year plant height in Hungarian taxon was significantly higher than that of the Korean population. The shooting dynamic of individual plants might be heterogeneous in both taxa and the Korean population was not only shorter in the height but had also less shoots by 16% than the Hungarian one. The Hungarian taxon exceeded the umbel size and numbers to the Korean one (by 3.62 cm in the average) and the variability in the populations was high $(CV\;=\;29{\sim}49%)$. Seed size was proved to be also a discriminative feature between the examined taxa. With small deviations (CV < 2) the Hungarian population produced seeds longer by 38%. Homogeneity in the populations was dependent more on the vegetation years and on the characteristics measured but less on the origins, respectively.

• Proceedings of the Korean Society of Crop Science Conference
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• 2005.08a
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• pp.22-46
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• 2005

Spatial and timely information on crop and filed conditions is one of the most important basics for rational and efficient planning and management in agriculture. Remote sensing, GIS, and modeling are powerful tools for such applications. This paper presents an overview of the state of the art in remote sensing of crop and field conditions with some case studies. It is also shown that a synergistic linkage between process-based models and remote sensing signatures enables us to estimate the multiple crop/ecosystem variables at a dynamic mode. Remotely sensed information can greatly reduce the uncertainty of simulation models by compensating for insufficient availability of data or parameters. This synergistic approach allows the effective use of infrequent and multi-source remote sensing data for estimating important ecosystem variables such as biomass growth and ecosystem $CO_2$ flux. This paper also shows a geo-spatial information system that enables us to integrate, search, extract, process, transform, and calculate any part of the data based on ID#, attributes, and/or by river-basin boundary, administrative boundary, or boundaries of arbitrary shape/size all over Japan. A case study using the system demonstrates that the nitrogen load from fertilizer was closely related to nitrate concentration of groundwater. The combined use of remote sensing, GIS and modeling would have great potential for various agro-ecosystem applications.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.8
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• pp.3203-3215
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• 2015

Due to the high growth of SNS population, service scalability is one of the critical issues to be addressed. The cloud environment provides the flexible computing and storage resources for services deployment, which fits the characteristics of scalable SNS deployment. However, if the SNS related information is not properly placed, it will cause unbalance load and heavy transmission cost on the storage virtual machine (VM) and cloud data center (CDC) network. In this paper, we characterize the SNS into a graph model based on the users' associations and interest correlations. The node weight represents the degree of associations, which can be indexed by the number of friends or data sources, and the link weight denotes the correlation between users/data sources. Then, based on the SNS graph, the two-step algorithm is proposed in this paper to determine the placement of SNS related data among VMs. Two k-means based clustering schemes are proposed to allocate social data in proper VM and physical servers for pre-configured VM and dynamic VM environment, respectively. The experimental example was conducted and to illustrate and compare the performance of the proposed schemes.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.11
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• pp.5243-5263
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• 2017

Data center networks provide critical bandwidth for the continuous growth of cloud computing, multimedia storage, data analysis and other businesses. The problem of low link bandwidth utilization in data center network is gradually addressed in more hot fields. However, the current scheduling strategies applied in data center network do not adapt to the real-time dynamic change of the traffic in the network. Thus, they fail to distribute resources due to the lack of intelligent management. In this paper, we present an improved adaptive traffic scheduling strategy utilizing the simulated annealing genetic algorithm (SAGA). Inspired by the idea of software defined network, when a flow arrives, our strategy changes the bandwidth demand dynamically to filter out the flow. Then, SAGA distributes the path for the flow by considering the scheduling of the different pods as well as the same pod. It is implemented through software defined network technology. Simulation results show that the bisection bandwidth of our strategy is higher than state-of-the-art mechanisms.

• Nuclear Engineering and Technology
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• v.48 no.4
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• pp.915-924
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• 2016

After a severe accident to the nuclear reactor, the in-vessel retention strategy is a key way to prevent the leakage of radioactive material. Nanofluid is a steady suspension used to improve heat-transfer characteristics of working fluids, formed by adding solid particles with diameters below 100nm to the base fluids, and its thermal physical properties and heat-transfer characteristics are much different from the conventional working fluids. Thus, nanofluids with appropriate nanoparticle type and volume concentration can enhance the heat-transfer process. In this study, the moving particle semi-implicit method-meshless advection using flow-directional local grid method is used to simulate the bubble growth, departure, and sliding on the downward-facing heating surface in pure water and nanofluid (1.0 vol.% $Al_2O_3/H_2O$) flow boiling processes; additionally, the bubble critical departure angle and sliding characteristics and their influence are also investigated. The results indicate that the bubble in nanofluid departs from the heating surface more easily and the critical departure inclined angle of nanofluid is greater than that of pure water. In addition, the influence of nanofluid on bubble sliding is not significant compared with pure water.

• Nuclear Engineering and Technology
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• v.33 no.4
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• pp.409-422
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• 2001

The dynamic character of a system of the governing differential equations for the one- dimensional two-fluid model, where the momentum flux parameters are employed to consider the velocity and void fraction distribution in a flow channel, is investigated. In response to a perturbation in the form of a＇traveling wave, a linear stability analysis is peformed for the governing differential equations. The expression for the growth factor as a function of wave number and various flow parameters is analytically derived. It provides the necessary and sufficient conditions for the stability of the one-dimensional two-fluid model in terms of momentum flux parameters. It is demonstrated that the one-dimensional two-fluid model employing the physical momentum flux parameters for the whole range of dispersed flow regime, which are determined from the simplified velocity and void fraction profiles constructed from the available experimental data and $C_{o}$ correlation, is stable to the linear perturbations in all wave-lengths. As the basic form of the governing differential equations for the conventional one-dimensional two-fluid model is mathematically ill posed, it is suggested that the velocity and void distributions should be properly accounted for in the one-dimensional two-fluid model by use of momentum flux parameters.s.

• Journal of the Korea Society of Computer and Information
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• v.13 no.3
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• pp.123-130
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• 2008

To avoid some protection systems such as firewall, P2P applications have recently used to apply dynamic port numbers. Reliable estimates of P2P traffic require examination of packet payload, a methodological land mine from legal, privacy technical, logistic, and fiscal perspectives. Indeed, access to user payload is often rendered impossible by one of these factors, inhibiting trustworthy estimation of P2P growth and dynamics. Despite various methods such as port-based and signature-based techniques, it still dose not satisfy the method which uses both qualitative and quantitative aspects. In this paper, a method using SVM mechanism which discriminate the P2P traffic from non-P2P traffics using differences between P2P and other application traffics is suggested. This is a systematic methodology to identify P2P networks, and without relying on packet payload.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2017.05a
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• pp.249-251
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• 2017

In the past, People thought that software security was not important. but Skills of attacking software has growing up in fast, software crack fall down software industry growth and profit of copyright holder was declined. So I propose software crack prevention for changing PE Format. Hackers can analyze program in static. As we change the PE format, we can prevent static analysis. As I insert anti - debugging code the exe file, the program is protected from dynamic analysis.

• ETRI Journal
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• v.31 no.2
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• pp.173-181
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• 2009

The growth of the World Wide Web and web-based applications is creating demand for high performance web servers to offer better throughput and shorter user-perceived latency. This demand leads to widely used cluster-based web servers in the Internet infrastructure. Load balancing algorithms play an important role in boosting the performance of cluster web servers. Previous load balancing algorithms suffer a significant performance drop under dynamic and database-driven workloads. We propose an estimation-based load balancing algorithm with admission control for cluster-based web servers. Because it is difficult to accurately determine the load of web servers, we propose an approximate policy. The algorithm classifies requests based on their service times and tracks the number of outstanding requests from each class in each web server node to dynamically estimate each web server load state. The available capacity of each web server is then computed and used for the load balancing and admission control decisions. The implementation results confirm that the proposed scheme improves both the mean response time and the throughput of clusters compared to rival load balancing algorithms and prevents clusters being overloaded even when request rates are beyond the cluster capacity.

• The Bulletin of The Korean Astronomical Society
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• v.37 no.2
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• pp.117.2-117.2
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• 2012

It is generally accepted that sudden compressions of the magnetosphere cause electromagnetic ion cyclotron (EMIC) wave growth by increasing the proton temperature anisotropy. These compression-associated EMIC waves are expected to be on higher latitudes (i.e., higher-L regions close to the magnetopause). In this study we examine Pc1 pulsations, which are believed to be generated by the EMIC instability, observed at subauroral latitude near the nominal plasmapause when the magnetosphere is suddenly compressed by solar wind dynamic pressure variations, using induction magnetometer data obtained from Athabasca, Canada (geomagnetic latitude = 61.7 N, L ~ 4.5). We identified 9 compression-associated Pc1 waves with frequencies of ~0.5-2.0 Hz. The wave activity appears in the horizontal H (positive north) and D (positive eastward) components. All of events show low coherence between H and D components. This indicates that the Pc1 pulsations in H and D oscillate with a different frequency. Thus, we cannot determine the polarization state of the waves. We will discuss the occurrence location of compression-associated Pc1 pulsations, their spectral structure, and wave properties.