• Korean journal of applied entomology
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• v.48 no.3
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• pp.301-310
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• 2009

For the comparing of mortality of the resistance and susceptible population of Myzus persicae, etofenprox was treated in the recommended concentration of 200ppm. Mortalities of resistance population were 16.7 and 36.7%, and susceptible population were 86.7 and 86.7% after 24 and 48 hours treatment, respectively. For the detect of cross resistance to other pyrethroids, 6 pyrethroids were examined. Mortalities of susceptible and resistance populations were 90 and 31% to deltamethrin, 92 and 23% to lambda cyhalothrin, 81 and 14% to cypermethrin, 70 and 20% to $\alpha$-cypermethrin, 29 and 28% to fenpropathrin, 84 and 29% to fenvalerate, respectively. It was showed that resistance populations were generally resistive to other pyrethroids. On the other hands, for recognized ecological characteristic of M. persicae susceptible and resistance populations life table was tested on the pepper leaves in the petri dish and on the plant in the pot. This results were showed that intrinsic rate of increase ($r_m$), net reproduction number ($R_0$) and generation time in day ($T_c$) were significantly different between two population in both tested. However, life span and reproduction period were slightly different between them. Otherwise, feeding behaviors were tested using EPG technique with non- and treated etofenprox. First potential drop time of susceptible and resistance population was 73.5 and 257.9 sec with non-treated and 93.3 and 1076.2 sec after treated, respectively. Electrical probing signals were 8.2 and 48.8 times with susceptible and resistance individuals after treated etofenprox, respectively. It was supposed that the resistance is more probings than susceptible population. After treated, total feeding time have more 6,728.9 sec on resistance than 965.5 sec on susceptible population. So, total non penetration time of susceptible population was 3,000 sec longer than resistance population.

• Korean journal of applied entomology
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• v.59 no.2
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• pp.153-163
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• 2020

This study was conducted to evaluate the fitness of Tetranychus kanzawai Kishida on different host plants: young and old leaves of the mandarin orange 'shiranuhi' ((Citrus unshiu × C. sinensis) × C. reticulata), Japanese violet (Viola japonica Langsd.) and kidney bean (Phaseolus vulgaris L.). The development and oviposition experiments were conducted at constant temperatures (20, 25 and 30℃) and a life table parameters were estimated. T. kanzawai could complete it's development on 'shiranuhi' young leaves, japanese violet and kidney bean, while all died during the immature period on 'shiranuhi' old leaves. The total developmental period of T. kanzawai feeding on 'shiranuhi' young leaves was 17.4, 13.4 and 10.2 days at each temperature, respectively, which was longer than 16.1, 9.5 and 7.0 days of kidney bean. The female longevity of T. kanzawai on young leaves of 'shiranuhi' were 19.1, 15.0 and 12.3 days at each temperature, respectively, and there was no significant difference from 22.1, 14.1 and 10.9 days investigated from kidney bean. The fecundity was 18.1, 23.9 and 17.8 eggs per female, which was less than them of japanese violet and kidney bean at each temperature, respectively. As a result of estimating the life table parameters based on the experimental data, intrinsic rate of increase (r_m) were significantly different from each other, and appeared in the following order: kidney (0.1542, 0.2563 and 0.3251), japanese violet (0.1087, 0.2007 and 0.2673) and 'shiranuhi' young leaves (0.0868, 0.1002 and 0.1217) at each temperature, respectively. Finally, the management strategy against T. kanzawai in citrus orchards was discussed based on the results.

• Korean journal of applied entomology
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• v.53 no.2
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• pp.193-197
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• 2014

Transgenic crops that produce insecticidal toxins have a great potential for controlling target pest insects, but there is a growing concern about unintended influences on non-target species. In the present study, the preferences and performance of non-target green peach aphid, Myzus persicae (Sulzer), on transgenic cabbages (Brassica oleracea) that produce Bt toxin (Cry1Ac1) and untransformed control plants were investigated as a part of risk assessment. In a free-choice situation, the number of nymphs larviposited by 10 winged adults over 3 days was $21.9{\pm}1.8$ and $22.5{\pm}2.2$ on transgenic and the control plants, respectively, indicating that the aphids did not discriminate between the two types of plants. In a performance assay, the development time (D) and intrinsic rate of increase (rm) of wingless aphids reared on transgenic and control plants were also similar (D, $5.8{\pm}0.2$ and $5.9{\pm}0.1$ (days) and rm, $0.7{\pm}0.1$ and $0.8{\pm}0.1$, for transgenic and control plants, respectively). These results suggest that M. persicae is not significantly affected by transgenic Bt cabbage.

• Journal of Intelligence and Information Systems
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• v.25 no.1
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• pp.63-83
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• 2019

Investors prefer to look for trading points based on the graph shown in the chart rather than complex analysis, such as corporate intrinsic value analysis and technical auxiliary index analysis. However, the pattern analysis technique is difficult and computerized less than the needs of users. In recent years, there have been many cases of studying stock price patterns using various machine learning techniques including neural networks in the field of artificial intelligence(AI). In particular, the development of IT technology has made it easier to analyze a huge number of chart data to find patterns that can predict stock prices. Although short-term forecasting power of prices has increased in terms of performance so far, long-term forecasting power is limited and is used in short-term trading rather than long-term investment. Other studies have focused on mechanically and accurately identifying patterns that were not recognized by past technology, but it can be vulnerable in practical areas because it is a separate matter whether the patterns found are suitable for trading. When they find a meaningful pattern, they find a point that matches the pattern. They then measure their performance after n days, assuming that they have bought at that point in time. Since this approach is to calculate virtual revenues, there can be many disparities with reality. The existing research method tries to find a pattern with stock price prediction power, but this study proposes to define the patterns first and to trade when the pattern with high success probability appears. The M & W wave pattern published by Merrill(1980) is simple because we can distinguish it by five turning points. Despite the report that some patterns have price predictability, there were no performance reports used in the actual market. The simplicity of a pattern consisting of five turning points has the advantage of reducing the cost of increasing pattern recognition accuracy. In this study, 16 patterns of up conversion and 16 patterns of down conversion are reclassified into ten groups so that they can be easily implemented by the system. Only one pattern with high success rate per group is selected for trading. Patterns that had a high probability of success in the past are likely to succeed in the future. So we trade when such a pattern occurs. It is a real situation because it is measured assuming that both the buy and sell have been executed. We tested three ways to calculate the turning point. The first method, the minimum change rate zig-zag method, removes price movements below a certain percentage and calculates the vertex. In the second method, high-low line zig-zag, the high price that meets the n-day high price line is calculated at the peak price, and the low price that meets the n-day low price line is calculated at the valley price. In the third method, the swing wave method, the high price in the center higher than n high prices on the left and right is calculated as the peak price. If the central low price is lower than the n low price on the left and right, it is calculated as valley price. The swing wave method was superior to the other methods in the test results. It is interpreted that the transaction after checking the completion of the pattern is more effective than the transaction in the unfinished state of the pattern. Genetic algorithms(GA) were the most suitable solution, although it was virtually impossible to find patterns with high success rates because the number of cases was too large in this simulation. We also performed the simulation using the Walk-forward Analysis(WFA) method, which tests the test section and the application section separately. So we were able to respond appropriately to market changes. In this study, we optimize the stock portfolio because there is a risk of over-optimized if we implement the variable optimality for each individual stock. Therefore, we selected the number of constituent stocks as 20 to increase the effect of diversified investment while avoiding optimization. We tested the KOSPI market by dividing it into six categories. In the results, the portfolio of small cap stock was the most successful and the high vol stock portfolio was the second best. This shows that patterns need to have some price volatility in order for patterns to be shaped, but volatility is not the best.