• The Korean Journal of Pesticide Science
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• v.19 no.4
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• pp.440-449
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• 2015

Pine wood nematode (PWN), Bursaphelenchus xylophilus is one of the most serious pests of pine tree. Trunk injection of some nematicides in tree is well known as an effective control method. However there are some limitating factors which hindering the efficacy of trunk injection in field or potted tree. In this study we suggested easy and useful alternative screening methods of nematicides against PWN. Reproduction of PWN was influenced by tree twig moisture (high reproduction in high moisture trig) and paraffin coating was 78.6% reduced moisture loss in tested twig. There were no reproduction different in up and down site from infection site of twig at 1 month after inoculation of PWN and also distance (5 and 10 cm) from inoculation site of PWN did not influence the reproduction of PWN. Numbers of reproduced PWN were higher with decreasing diameter of twig. Numbers of reproduced PWN were similar to P. thunbergii and P. densiflora. However reproduction was increased depending on high inoculation density and longer propagation period. When inoculation of PWN on cut twig injected with emamectin benzoate 2.15% EC and morantel tartrate 8% SL in trunk of Pinus thunbergii in the field, PWN number were significantly reduced than untreated control. We suggest this screening method for PWN control agents.

• The Transactions of the Korea Information Processing Society
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• v.5 no.6
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• pp.1610-1619
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• 1998

The ABR service class provides feedback based traffic control to transport bursty data traffic efficiently. Feedback based congestion control has first been studied to be applied to unicast connections. Recently. several congestion control algorithms for multicast connections have also been proposed as the number of ABR applications requiring multicast increases. With feedback based congestion control, the effectiveness of a traffic control scheme diminishes as propagation delay increases. Especially for a multicast connection, a remote destination may suffer unfair service compared to a local destination due to the delayed feedback. Amelioration of the disadvantages caused by feedback delay is therefore more important for remote destinations in multicast connections. This paper proposes a new switch behavior to provide effective feedback based mathc control for rentoh destinations. The proposed switches adjust the service rate dynamically in accordance woth the state of the downstream, that is, the congestion of the destinaion is immediately controlled by the nearest apstream switch before the source to ramp down the transmission rate of the connection. The proposed switch has an implementation overhead to have a separate buffer for each VC to adjust the service rate in accordance with a backward Rm cell of each VC. The buffer requirement id also increased at intermediate switches. Simulation results show that the proposed switch reduces the cell loss rate in both the local and the remote destinations and slso amelioratd the between the two destinations.

• Journal of the Korean Society for Railway
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• v.12 no.1
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• pp.9-15
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• 2009

In this study, the l/35 reduced-scale model experiment were conducted to investigate designed ventilation system performance at rescue station in tunnel fire. A model tunnel with 2 mm thick of steel, 10 m long, 0.19 m high and 0.26m was made by using Froude number scaling law. The cross-passages installing escape door at the center. were connected between accident tunnel and rescue tunnel. The n-heptane pool fire, $4cm\times4cm$, with heat release rate 698.97W were used as fire source. The fire source was located in the center and portal of accident tunnel as Worst case.. An operating ventilation system extracted smoke amount of 0.015 cms. The smoke temperature and carbon monoxide. concentration in cross-passage were measured to verify designed ventilation system. The results showed that, in center fire case without ventilation in accident tunnel, smoke did not propagated to rescue station. In portal tire case, smoke spreaded to rescue station without ventilation. But smoke did not propagated to rescue station with designed ventilation.

• Korean Journal of Plant Resources
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• v.24 no.5
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• pp.628-635
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• 2011

This study was conducted to establish the tissue culture system for Korean domestic Miscanthus sinensis, which is used in various purposes such as forage, and bio-energy resources. With the mature seed of Miscanthus, optimum concentrations of plant growth regulators were identified for an efficient callus induction and regeneration. Among the treatments of 1~10 $mg{\cdot}L^{-1}$ 2,4-D, IBA, or NAA, callus induction rate was highest (85.3%) on MS medium containing 5 $mg{\cdot}L^{-1}$ 2,4-D. Under the condition, the callus were efficiently induced and proliferated with comparably lower frequencies of callus browning. In shoot regeneration, the treatment of NAA combined with BAP seemed to contribute more efficient conditions to shoot regeneration than those of NAA with Kinetin or 2-iP. Especially, regeneration efficiency and number of regenerated plants were 83.7% and 5.5 in 3 $mg{\cdot}L^{-1}$ NAA with 5 $mg{\cdot}L^{-1}$ BAP, respectively, which were higher frequencies than those in NAA with Kinetin or 2-iP. In results, 5 $mg{\cdot}L^{-1}$ 2,4-D and 3 $mg{\cdot}L^{-1}$ NAA combined with 5 $mg{\cdot}L^{-1}$ BAP were efficient for embryogenic callus induction and regeneration of Miscanthus. This system would be useful for mass-propagation and developing new cultivars via tissue culture of Miscanthus sinensis.

• Korean Journal of Medicinal Crop Science
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• v.3 no.3
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• pp.246-250
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• 1995

Scions from the one- and two-years old and the nodes of Ligusticum chuanxiong stem were used to study the rooting ability with the treatment of plant growth regulators planted to different bed soils as the alternative propagation for the present method by rhizome. The rooting ratio in the scion from the one- and the two-years old plants showed any difference, but that was ranged from 94% to 100% in the first node and from 56% to 64% in the second node from the bottom of the stem. The scion of first node from both the plants showed more than 90% in the root ratio and 16 in the number of rooting and growed more than 31cm in the root length. The Rootone-F and 250ppm of NAA were most effective for the promotion of rooting. Rooting ratios in the sand and in the mixture of vermiculite and perlite as bed soils were about 18%, but that in the cultured soil considerably decreased.

• Journal of the Korean Institute of Intelligent Systems
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• v.10 no.5
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• pp.487-496
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• 2000

In this paper, the Multi-FNN(Fuzzy-Neural Networks) model is identified and optimized using HCM(Hard C-Means) clustering method and genetic algorithms. The proposed Multi-FNN is based on Yamakawa's FNN and uses simplified inference as fuzzy inference method and error back propagation algorithm as learning rules. We use a HCM clustering and Genetic Algorithms(GAs) to identify both the structure and the parameters of a Multi-FNN model. Here, HCM clustering method, which is carried out for the process data preprocessing of system modeling, is utilized to determine the structure of Multi-FNN according to the divisions of input-output space using I/O process data. Also, the parameters of Multi-FNN model such as apexes of membership function, learning rates and momentum coefficients are adjusted using genetic algorithms. A aggregate performance index with a weighting factor is used to achieve a sound balance between approximation and generalization abilities of the model. The aggregate performance index stands for an aggregate objective function with a weighting factor to consider a mutual balance and dependency between approximation and predictive abilities. According to the selection and adjustment of a weighting factor of this aggregate abjective function which depends on the number of data and a certain degree of nonlinearity, we show that it is available and effective to design an optimal Multi-FNN model. To evaluate the performance of the proposed model, we use the time series data for gas furnace and the numerical data of nonlinear function.

• The KIPS Transactions:PartC
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• v.12C no.7 s.103
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• pp.989-998
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• 2005

Information systems are today becoming larger and mostly broadband-networked. This exposes them at a higher risk of intrusions and hacking than ever before. Of the technologies developed to meet information system security needs, risk analysis is currently one of the most actively researched areas. Meanwhile, due to the extreme diversity of assets and complexity of network structure, there is a limit to the level of accuracy which can be achieved by an analysis tool in the assessment of risk run by an information system. Also, the results of a risk assessment are most oftennot up-to-date due to the changing nature of security threats. By the time an evaluation and associated set of solutions are ready, the nature and level of vulnerabilities and threats have evolved and increased, making them obsolete. Accordingly, what is needed is a risk analysis tool capable of assessing threats and propagation of damage, at the same time as security solutions are being identified. To do that, the information system must be simplified, and intrusion data must be diagrammed using a modeling technique this paper, we propose a modeling technique information systems to enable security risk analysis, using SPICE and Petri-net, and conduct simulations of risk analysis on a number of case studies.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.46 no.5
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• pp.56-63
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• 2009

The IEEE 802.11 standard has been used for wireless data networks such as wireless LAN, ad-hoc network, and vehicular ad-hoc network. Thus, the performance analysis of the IEEE 802.11 specification has been one of the hottest issues for network optimization and resource management. Most of the analysis studies were performed in a data plane of the IEEE 802.11 unicast. However, IEEE 802.11 broadcast is widely used for topology management, path management, and data dissemination. Thus, it is important to understand the performance of the broadcast scheme for the design of efficient wireless data network. In this contort, we analyze the IEEE 802.11 broadcast scheme in terms of the broadcast frame reception probability according to the distance from a sending node. Unlike the other works, our analysis framework includes not only the system parameters of the IEEE 802.11 specification such as transmission range, data rate, minimum contention window but also the networking environments such as the number of nodes, network load, and the radio propagation environments. Therefore, our analysis framework is expected to be used for the development of protocols and algorithms in a dynamic wireless data network.

• Journal of Bio-Environment Control
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• v.16 no.4
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• pp.388-394
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• 2007

To product the edible fresh shoots of Sedum sarmentosum in summer season, 4 local strains were cultivated with cutting propagation under 0, 30, 50, 70, 90% shading. Effect of shading on shoot growth, leaf chroma value, SPAD value, and bitterness were investigated at 35 days after cutting. Plant height, the number of node and leaf stem diameter in $30{\sim}90%$ shading were increased than in the control, and Pohang local strain had little-overgrowth shoot, thicker stem, a few brenches per shoot, and larger leaf compared to the other local strains. Fresh and dry weight under shading were increased than in the control, dry weight of pohang local strain was highest in 50% shading. Hunter L and b values were decreased out of proportion to higher shading rate. SPAD value in $50{\sim}90%$ shading was significantly lower than in the control. The bitterness of fresh shoot was decreased out of proportion to higher shading rate. In Summer season, producing the fresh shoot of S. sarmentosum was excellent in 50% shading, and Pohang local strain among 4 local strains was more stable and good in yield and quality under shading.

• Computers and Concrete
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• v.19 no.5
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• pp.457-465
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• 2017

The Taiwanese liquid crystal display (LCD) industry has traditionally produced a huge amount of waste glass that is placed in landfills. Waste glass recycling can reduce the material costs of concrete and promote sustainable environmental protection activities. Concrete is always utilized as structural material; thus, the concrete compressive strength with a variety of mixtures must be studied using predictive models to achieve more precise results. To create an efficient waste LCD glass concrete (WLGC) design proportion, the related studies utilized a multivariable regression analysis to develop a compressive strength waste LCD glass concrete equation. The mix design proportion for waste LCD glass and the compressive strength relationship is complex and nonlinear. This results in a prediction weakness for the multivariable regression model during the initial growing phase of the compressive strength of waste LCD glass concrete. Thus, the R ratio for the predictive multivariable regression model is 0.96. Neural networks (NN) have a superior ability to handle nonlinear relationships between multiple variables by incorporating supervised learning. This study developed a multivariable prediction model for the determination of waste LCD glass concrete compressive strength by analyzing a series of laboratory test results and utilizing a neural network algorithm that was obtained in a related prior study. The current study also trained the prediction model for the compressive strength of waste LCD glass by calculating the effects of several types of factor combinations, such as the different number of input variables and the relevant filter for input variables. These types of factor combinations have been adjusted to enhance the predictive ability based on the training mechanism of the NN and the characteristics of waste LCD glass concrete. The selection priority of the input variable strategy is that evaluating relevance is better than adding dimensions for the NN prediction of the compressive strength of WLGC. The prediction ability of the model is examined using test results from the same data pool. The R ratio was determined to be approximately 0.996. Using the appropriate input variables from neural networks, the model validation results indicated that the model prediction attains greater accuracy than the multivariable regression model during the initial growing phase of compressive strength. Therefore, the neural-based predictive model for compressive strength promotes the application of waste LCD glass concrete.