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    ํ† ๋งˆํ†  ์Šค๋งˆํŠธ ์˜จ์‹ค์—์„œ ๊ฝƒ๋…ธ๋ž‘์ด์ฑ„๋ฒŒ๋ ˆ์™€ ๋‹ด๋ฐฐ๊ฐ€๋ฃจ์ด์˜ ์นœํ™˜๊ฒฝ ๊ด€๋ฆฌ ์ „๋žต

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    ํ•™์œ„๋…ผ๋ฌธ (๋ฐ•์‚ฌ) -- ์„œ์šธ๋Œ€ํ•™๊ต ๋Œ€ํ•™์› : ๋†์—…์ƒ๋ช…๊ณผํ•™๋Œ€ํ•™ ๋†์ƒ๋ฌผํ•™๊ณผ(๊ณค์ถฉํ•™์ „๊ณต), 2020. 8. ์ด์ค€ํ˜ธ.The smart greenhouse refers to a greenhouse in which the crop growth environment can be managed remotely by incorporating ICT, and is a system that enables labor reduction and high efficiency production through automatic environmental control and environmental optimization by computers. In Korea, tomato is a major plant in smart greenhouses, and Frankliniella occidentalis and Bemisia tabaci are major insect pests in tomato greenhouses. Chemical control has been the most frequently used method for insect pest control in greenhouses. However, in addition to environmental and health problems due to excessive use of chemicals, its control efficacy has been also hampered by insecticide resistance development in insect pests including F. occidentalis and B. tabaci. Thus, strategies enhancing eco-friendly pest management such as cultural and biological control methods have been increasingly considered. To explore the eco-friendly management strategy for F. occidentalis and B. tabaci in tomato smart greenhouses, following studies were conducted. I examined relationship between occurrence of thrips and whitefly and environmental conditions in tomato smart greenhouses to determine which factors should be considered to manage populations of these two pests. F. occidentalis was the dominant thrips species, and B. tabaci was the dominant whitefly species in investigated greenhouses. For thrips, its population density in the greenhouse was highly related with its outside population, indicating prohibition of inflow of thrips from outside of the greenhouse is important. Also, its population was correlated with variation of temperature and humidity in greenhouses. On the contrary, whitefly density in the greenhouse was not significantly correlated with greenhouse environmental conditions, but was also related with its outside population. The life history characteristics of F. occidentalis were investigated at control temperature and humidity (27.3 ยฑ 0.54 โ„ƒ, 79.9 ยฑ 2.79% RH) (mean ยฑ SD), a 10 โ„ƒ-range fluctuation in temperature (27.1 ยฑ 5.28 โ„ƒ, 81.5 ยฑ 4.03% RH), a 20 โ„ƒ-range fluctuation in temperature (26.5 ยฑ 10.09 โ„ƒ, 80.4 ยฑ 5.76% RH), a 20%-range fluctuation in humidity (26.8 ยฑ 0.37 โ„ƒ, 80.7 ยฑ 9.55% RH) and a 30%-range fluctuation in humidity (27.3 ยฑ 0.41 โ„ƒ, 76.3 ยฑ 15.28% RH). Overall, the life history traits of F. occidentalis were more negatively affected by fluctuating environmental conditions. The impact of temperature fluctuation was more severe than that of humidity fluctuation. Additionally, the degree of impact increased as the fluctuation range of the temperature increased, while the reverse trend was observed with humidity fluctuations. With the 20 โ„ƒ-range fluctuation in temperature, F. occidentalis died at the 1st instar larval stage. The offsprings sex ratio was significantly higher at the 20%- and 30%-range fluctuations in humidity (0.47 and 0.49, respectively). From the fertility life table analysis, the intrinsic rate of increase (r) was higher at the 30%-range fluctuation in humidity and control conditions as 0.218 and 0.205, respectively. At the 10 โ„ƒ-range fluctuation in temperature conditions, r was significantly lower as 0.169 than other conditions. High fluctuations in temperature and low fluctuations in humidity appear to be the best conditions for controlling F. occidentalis populations in greenhouses. Nesidiocoris tenuis is a biological control agent for controlling B. tabaci. Successful establishment of a biological control agent and its spatial coherence with pest in the target area is essential for effective biological control. To explore effective wavelength which can be used for enhancing spatial coherence of B. tabaci and N. tenuis, Y-tube test was conducted for various wavelengths. The 385 nm wavelength was found to be best. The incubator test was conducted to verify effect of 385 nm wavelength on N. tenuis, and enhanced establishment rate of N. tenuis was observed at 385 nm wavelength treatment. The 385 nm wavelength LED light significantly affected population dynamics of N. tenuis and B. tabaci in greenhouses. In the plots of 385 nm wavelength LED with release of N. tenuis and B. tabaci, the 385 nm wavelength appeared to enhance establishment of N. tenuis and control of B. tabaci. In conclusion, control of F. occidentalis might be enhanced by humidity control in smart greenhouses. Enhanced establishment rate of N. tenuis by 385 nm wavelength would help to control the B. tabaci population in smart greenhouses.์Šค๋งˆํŠธ์˜จ์‹ค์ด๋ž€ ICT๋ฅผ ๋†๊ฐ€์— ์ ‘๋ชฉํ•ด ๋†์ž‘๋ฌผ์˜ ์„ฑ์žฅํ™˜๊ฒฝ์„ ์›๊ฒฉ์œผ๋กœ ์œ ์ง€ยท๊ด€๋ฆฌํ•  ์ˆ˜ ์žˆ๋Š” ๋†์žฅ์„ ๋งํ•˜๋ฉฐ, ์ปดํ“จํ„ฐ์— ์˜ํ•œ ์ž๋™ ํ™˜๊ฒฝ ์ œ์–ด์™€ ํ™˜๊ฒฝ ์ตœ์ ํ™”๋ฅผ ํ†ตํ•ด ๋…ธ๋™๋ ฅ ๊ฐ์†Œ์™€ ๊ณ ํšจ์œจ ์ƒ์‚ฐ์ด ๊ฐ€๋Šฅํ•œ ์‹œ์Šคํ…œ์ด๋‹ค. ๊ฐˆ์ˆ˜๋ก ์ปค์ง€๋Š” ๋†๊ฒฝ์ง€์™€ ๋…ธ๋™ ๊ณ ๋ นํ™” ๋ฌธ์ œ๋ฅผ ํ•ด๊ฒฐํ•  ๋Œ€์•ˆ์œผ๋กœ ์ •๋ฐ€๋†์—…๊ณผ ์ž๋™์ƒ์‚ฐ ๋“ฑ์ด ๋– ์˜ค๋ฅด๊ณ  ์žˆ๋‹ค. ํ† ๋งˆํ† ๋Š” ํ•œ๊ตญ์˜ ์Šค๋งˆํŠธ ์˜จ์‹ค์˜ ์ฃผ์š” ์ž‘๋ฌผ์ด๋ฉฐ, ํ† ๋งˆํ† ์˜ ์ฃผ์š” ํ•ด์ถฉ์œผ๋กœ๋Š” ๋‹ด๋ฐฐ๊ฐ€๋ฃจ์ด์™€ ๊ฝƒ๋…ธ๋ž‘์ด์ฑ„๋ฒŒ๋ ˆ๊ฐ€ ์žˆ๋‹ค. ํ™”ํ•™ ์‚ด์ถฉ์ œ๋ฅผ ์‚ฌ์šฉํ•œ ํ•ด์ถฉ ๋ฐฉ์ œ๋Š” ๋งค์šฐ ์œ ์šฉํ•œ ๋ฐฉ๋ฒ•์ด์ง€๋งŒ, ๊ณผ์‚ฌ์šฉ์‹œ ํ™˜๊ฒฝ ์˜ค์—ผ์ด๋‚˜ ๋†์•ฝ ์ค‘๋…๊ณผ ๊ฐ™์€ ๋ฌธ์ œ๋ฅผ ์ผ์œผํ‚ฌ ์ˆ˜ ์žˆ๋‹ค. ๋˜ํ•œ, ํ™”ํ•™์‚ด์ถฉ์ œ์˜ ๊ณผ์‚ฌ์šฉ์€ ์ด์ฑ„๋ฒŒ๋ ˆ๋‚˜ ๊ฐ€๋ฃจ์ด๋ฅ˜์™€ ๊ฐ™์€ ์˜จ์‹ค ํ•ด์ถฉ๋“ค์—๊ฒŒ ์‚ด์ถฉ์ œ ์ €ํ•ญ์„ฑ์„ ์œ ๋ฐœ์‹œํ‚ฌ ์ˆ˜ ์žˆ๋‹ค. ๊ทธ๋Ÿฌ๋ฏ€๋กœ, ๊ฒฝ์ข…์  ๋ฐฉ์ œ๋ฒ•์ด๋‚˜ ์ƒ๋ฌผํ•™์  ๋ฐฉ์ œ๋ฒ• ๊ฐ™์€ ์นœํ™˜๊ฒฝ ํ•ด์ถฉ ๊ด€๋ฆฌ ๋ฐฉ๋ฒ•์— ๋Œ€ํ•œ ์—ฐ๊ตฌ๋Š” ํ•„์š”ํ•˜๋‹ค. ๊ฝƒ๋…ธ๋ž‘์ด์ฑ„๋ฒŒ๋ ˆ์™€ ๋‹ด๋ฐฐ๊ฐ€๋ฃจ์ด์˜ ์Šค๋งˆํŠธ ์˜จ์‹ค์—์„œ์˜ ์นœํ™˜๊ฒฝ ๋ฐฉ์ œ ์ „๋žต์„ ์ˆ˜๋ฆฝํ•˜๊ธฐ ์œ„ํ•ด ์—ฐ๊ตฌ๋“ค์ด ์ˆ˜ํ–‰๋˜์—ˆ๋‹ค. ํ† ๋งˆํ†  ์Šค๋งˆํŠธ ์˜จ์‹ค์—์„œ ์–ด๋–ค ํ™˜๊ฒฝ ๋ณ€์ˆ˜๊ฐ€ ์ด์ฑ„๋ฒŒ๋ ˆ๋ฅ˜์™€ ๊ฐ€๋ฃจ์ด๋ฅ˜์˜ ๋ฐœ์ƒ์— ์œ ์˜๋ฏธํ•œ ์˜ํ–ฅ์„ ๋ฏธ์น˜๋Š”์ง€ ํ™•์ธํ•˜๊ธฐ ์œ„ํ•ด, ์˜จ์‹ค ๋‚ด๋ถ€ ํ™˜๊ฒฝ์กฐ๊ฑด๋“ค๊ณผ ํ•ด์ถฉ ๋ฐœ์ƒ์— ๋Œ€ํ•œ ์ƒ๊ด€๊ด€๊ณ„๋ฅผ ์กฐ์‚ฌํ–ˆ๋‹ค. ์กฐ์‚ฌ๋œ ์˜จ์‹ค์—์„œ ์ด์ฑ„๋ฒŒ๋ ˆ๋ฅ˜๋Š” ๊ฝƒ๋…ธ๋ž‘์ด์ฑ„๋ฒŒ๋ ˆ๊ฐ€ ์šฐ์ ์ข…์ด์—ˆ๊ณ , ๊ฐ€๋ฃจ์ด๋ฅ˜๋Š” ๋‹ด๋ฐฐ๊ฐ€๋ฃจ์ด๊ฐ€ ์šฐ์ ์ข…์ด์—ˆ๋‹ค. ์ด์ฑ„๋ฒŒ๋ ˆ๋ฅ˜๋Š” ์˜จ์‹ค ์™ธ๋ถ€ ๋ฐ€๋„์™€ ๋†’์€ ์ƒ๊ด€๊ด€๊ณ„๋ฅผ ๋ณด์—ฌ ์™ธ๋ถ€๋กœ๋ถ€ํ„ฐ ์œ ์ž…์„ ์ค„์ด๋Š” ๊ฒƒ์ด ์ค‘์š”ํ•ด ๋ณด์˜€๋‹ค. ๋˜ํ•œ, ์ด์ฑ„๋ฒŒ๋ ˆ๋ฅ˜๋Š” ์˜จ์‹ค ๋‚ด๋ถ€ ์˜จ๋„์™€ ์Šต๋„์™€ ์ƒ๊ด€๊ด€๊ณ„๋ฅผ ๋ณด์˜€๋‹ค. ์ด์™€ ๋ฐ˜๋Œ€๋กœ, ๊ฐ€๋ฃจ์ด๋ฅ˜๋Š” ์˜จ์‹ค ๋‚ด๋ถ€ ํ™˜๊ฒฝ๋ณ€์ˆ˜๋“ค๊ณผ ์œ ์˜๋ฏธํ•œ ์ƒ๊ด€๊ด€๊ณ„๋ฅผ ๋ณด์ด์ง€ ์•Š์•˜๊ณ , ์™ธ๋ถ€ ๋ฐ€๋„์™€ ๋†’์€ ์ƒ๊ด€์„ฑ์„ ๋ณด์˜€๋‹ค. ์ •์˜จ/์ •์Šต ์กฐ๊ฑด๊ณผ ๋ณ€์˜จ, ๋ณ€์Šต ์กฐ๊ฑด์—์„œ ๊ฝƒ๋…ธ๋ž‘์ด์ฑ„๋ฒŒ๋ ˆ์˜ ์ƒํ™œ์‚ฌ์  ํŠน์ง•์ด ์—ฐ๊ตฌ๋˜์—ˆ๋‹ค. ์ „๋ฐ˜์ ์œผ๋กœ, ๊ฝƒ๋…ธ๋ž‘์ด์ฑ„๋ฒŒ๋ ˆ์˜ ์ƒํ™œ์‚ฌ์  ํŠน์ง•์€ ๋ณ€๋™ํ•˜๋Š” ํ™˜๊ฒฝ์กฐ๊ฑด์—์„œ ๋ถ€์ •์ ์ธ ์˜ํ–ฅ์„ ๋ฐ›๋Š” ๊ฒƒ์œผ๋กœ ๋‚˜ํƒ€๋‚ฌ๋‹ค. ์˜จ๋„์˜ ํŽธ์ฐจ๊ฐ€ ํฐ ์กฐ๊ฑด์ด ์Šต๋„์˜ ํŽธ์ฐจ๊ฐ€ ํฐ ์กฐ๊ฑด๋ณด๋‹ค ๋” ํฐ ์˜ํ–ฅ์„ ๋ฏธ์ณค๋‹ค. ๊ทธ๋ฆฌ๊ณ , ์˜จ๋„์˜ ํŽธ์ฐจ๊ฐ€ ์ปค์งˆ ์ˆ˜๋ก ๋” ์‹ฌํ•œ ์˜ํ–ฅ์„ ๋ฏธ์ณค๊ณ , ์Šต๋„๋Š” ์ด์™€ ๋ฐ˜๋Œ€์˜ ๊ฒฝํ–ฅ์„ ๋ณด์˜€๋‹ค. ์ž์‹ ์„ธ๋Œ€์˜ ์„ฑ๋น„๋Š” 20% ๋ฒ”์œ„(0.47), 30% ๋ฒ”์œ„(0.49)์˜ ์Šต๋„ ํŽธ์ฐจ ์กฐ๊ฑด์—์„œ ์œ ์˜๋ฏธํ•˜๊ฒŒ ๋†’๊ฒŒ ๋‚˜ํƒ€๋‚ฌ๋‹ค. Fertility life table ๋ถ„์„ ๊ฒฐ๊ณผ, 30% ๋ฒ”์œ„์˜ ์Šต๋„ ํŽธ์ฐจ ์กฐ๊ฑด์—์„œ 0.218์˜ ๋‚ด์  ์ž์—ฐ์ฆ๊ฐ€์œจ์„ ๋ณด์˜€๊ณ , ์ •์˜จ/์ •์Šต ์กฐ๊ฑด์—์„œ 0.205๋กœ ๋’ค๋ฅผ ์ด์—ˆ๋‹ค. ์Šค๋งˆํŠธ์˜จ์‹ค๋‚ด์—์„œ ๊ฝƒ๋…ธ๋ž‘์ด์ฑ„๋ฒŒ๋ ˆ์˜ ๋ฐ€๋„ ์กฐ์ ˆ์„ ์œ„ํ•ด์„œ๋Š” ์˜จ๋„ ํŽธ์ฐจ๊ฐ€ ํฌ๊ณ , ์Šต๋„ ํŽธ์ฐจ๊ฐ€ ์ž‘์€ ์กฐ๊ฑด์ด ์œ ๋ฆฌํ•  ๊ฒƒ์ด๋ผ ์ƒ๊ฐ๋œ๋‹ค. ๋‹ด๋ฐฐ์žฅ๋‹˜๋…ธ๋ฆฐ์žฌ๋Š” ๋‹ด๋ฐฐ๊ฐ€๋ฃจ์ด์˜ ์ฒœ์ ์ด๋‹ค. ๋ฐฉ์ œ ๋Œ€์ƒ์ง€์—ญ ์—์„œ ์ฒœ์ ์˜ ์„ฑ๊ณต์ ์ธ ์ •์ฐฉ๊ณผ ๋Œ€์ƒ ํ•ด์ถฉ๊ณผ์˜ ๊ณต๊ฐ„์  ์ผ๊ด€์„ฑ์€ ํšจ๊ณผ์ ์ธ ์ƒ๋ฌผํ•™์  ๋ฐฉ์ œ๋ฅผ ์œ„ํ•ด ํ•„์ˆ˜์ ์ด๋‹ค. Y-tube ์‹คํ—˜์„ ํ†ตํ•ด 385 nm LED๊ฐ€ ์„ ๋ฐœ๋˜์—ˆ๊ณ , ์ด ํŒŒ์žฅ์„ ์˜จ์‹ค ๋‚ด์—์„œ ๊ฒ€์ฆํ•˜๊ธฐ ์ „์— ํ•ญ์˜จ๊ธฐ ๋‚ด์—์„œ ์‹คํ—˜์„ ์ง„ํ–‰ํ•˜์˜€๋‹ค. ๊ทธ ๊ฒฐ๊ณผ 385 nm LED ์ฒ˜๋ฆฌ๊ตฌ์—์„œ ๋‹ด๋ฐฐ์žฅ๋‹˜๋…ธ๋ฆฐ์žฌ์˜ ์ •์ฐฉ๋ฅ ์ด ๋†’์•„์ง€๋Š” ๊ฒƒ์„ ํ™•์ธํ•˜์˜€๋‹ค. 385 nm LED๋Š” ์˜จ์‹ค๋‚ด ๋‹ด๋ฐฐ์žฅ๋‹˜๋…ธ๋ฆฐ์žฌ์™€ ๋‹ด๋ฐฐ๊ฐ€๋ฃจ์ด์˜ ๊ฐœ์ฒด๊ตฐ ๋™ํƒœ์— ์œ ์˜๋ฏธํ•œ ์˜ํ–ฅ์„ ๋ฏธ์ณค๋‹ค. 385 nm LED์™€ ํ•จ๊ป˜ ๋‹ด๋ฐฐ์žฅ๋‹˜๋…ธ๋ฆฐ์žฌ, ๋‹ด๋ฐฐ๊ฐ€๋ฃจ์ด๋ฅผ ๋ฐฉ์‚ฌํ•œ ์‹คํ—˜๊ตฌ์—์„œ 385 nm LED๋Š” ์„ฑ๊ณต์ ์œผ๋กœ ๋‹ด๋ฐฐ์žฅ๋‹˜๋…ธ๋ฆฐ์žฌ์˜ ์ •์ฐฉ๋ฅ ์„ ๋†’์˜€๊ณ , ์ด๋Š” ์„ฑ๊ณต์ ์œผ๋กœ ๋‹ด๋ฐฐ๊ฐ€๋ฃจ์ด์˜ ๋ฐ€๋„๋ฅผ ๋‚ฎ์ท„๋‹ค. ์ด ๊ฒฐ๊ณผ๋Š” ๋Œ€์กฐ๊ตฌ์™€ ๋น„๊ตํ–ˆ์„ ๋•Œ ์œ ์˜๋ฏธํ•œ ๊ฒฐ๊ณผ์˜€๋‹ค. 385 nm LED๋Š” ๋‹ด๋ฐฐ๊ฐ€๋ฃจ์ด์™€ ๋‹ด๋ฐฐ์žฅ๋‹˜๋…ธ๋ฆฐ์žฌ ๋ชจ๋‘๋ฅผ ์œ ์ธํ–ˆ๋‹ค. ๊ทธ๋ฆฌ๊ณ , ๋‹ด๋ฐฐ์žฅ๋‹˜๋…ธ๋ฆฐ์žฌ์˜ ์ •์ฐฉ๋ฅ ์„ ํ–ฅ์ƒ ์‹œํ‚ด๊ณผ ํ•จ๊ป˜, ๋‹ด๋ฐฐ๊ฐ€๋ฃจ์ด์™€์˜ ๊ณต๊ฐ„์  ์ผ๊ด€์„ฑ์„ ํ†ตํ•ด ๋ฐฉ์ œ์œจ์„ ๋†’์ผ ์ˆ˜ ์žˆ์—ˆ๋‹ค. ๊ฒฐ๋ก ์ ์œผ๋กœ, ์˜จ์‹ค๋‚ด ์ด์ฑ„๋ฒŒ๋ ˆ๋ฅ˜ ๋ฐ€๋„์กฐ์ ˆ์„ ์œ„ํ•œ ๊ฒฝ์ข…์ ๋ฐฉ์ œ๋ฒ•์€ ์Šต๋„ ํŽธ์ฐจ์˜ ์กฐ์ ˆ์„ ํ†ตํ•ด ๊ฐ€๋Šฅํ•  ๊ฒƒ์œผ๋กœ ๋ณด์ธ๋‹ค. ๋˜ํ•œ, 385 nm LED๋ฅผ ์‚ฌ์šฉํ•˜๋ฉด ๋‹ด๋ฐฐ๊ฐ€๋ฃจ์ด์˜ ์ฒœ์ ์ธ ๋‹ด๋ฐฐ์žฅ๋‹˜๋…ธ๋ฆฐ์žฌ์˜ ์ •์ฐฉ๋ฅ ์„ ๋†’์ผ ์ˆ˜ ์žˆ๊ณ , ์ด๋ฅผ ํ†ตํ•ด ๋‹ด๋ฐฐ๊ฐ€๋ฃจ์ด์˜ ํšจ๊ณผ์ ์ธ ๋ฐฉ์ œ๊ฐ€ ๊ฐ€๋Šฅํ•  ๊ฒƒ์ด๋‹ค.General introduction 1 Chapter I. Correlation analysis between environmental factors and insect pest density in the smart greenhouse 7 Abstract 9 1.1. Introduction 10 1.2. Materials and Methods 13 1.2.1. Data collection 13 1.2.2. Data analysis 20 1.3. Results 21 1.3.1. Whitefly and thrips density in greenhouses 21 1.3.2. Correlation analysis 46 1.4. Discussion 48 Chapter II. Cultural control method (Environmental control) Thrips, Life history characteristics of the western flower thrips, Frankliniella occidentalis (Pergande) (Thysanoptera: Thripidae), under fluctuating conditions of temperature or relative humidity 53 Abstract 55 2.1. Introduction 57 2.2. Materials and Methods 60 2.2.1. Rearing of F. occidentalis 60 2.2.2. Life table experiments 61 2.2.3. Statistical analysis 65 2.2.4. Life table analysis 66 2.3. Results 69 2.3.1. Immature development 70 2.3.2. Adult data 72 2.3.3. Survivorship and Sex ratio 74 2.3.4. Life table 76 2.4. Discussion 80 Chapter III. Biological control method Whitefly, Increase of control efficacy of Nesidiocoris tenuis (Hemiptera: Miridae) in the greenhouse by enhancing its establishment using UV-LED 85 Abstract 87 3.1. Introduction 88 3.2. Materials and methods 92 3.2.1. Test insects 92 3.2.2. Y-tube experiment 93 3.2.3. Preliminary test in greenhouse 95 3.2.4. Incubator experiment 96 3.2.5. Life table experiment 100 3.2.6. Greenhouse experiment 106 3.3. Results 114 3.3.1. Y-tube experiment 114 3.3.2. Preliminary test in greenhouse 117 3.3.3. Incubator experiment 119 3.3.4. Life table 124 3.3.5. Greenhouse experiment 133 3.4. Discussion 141 General conclusion 153 Literature Cited 160 Appendix 190 ๊ตญ๋ฌธ ์ดˆ๋ก 192 ๊ฐ์‚ฌ์˜ ๊ธ€ 197Docto

    ๊ธฐ์ˆ ์— ๋Œ€ํ•œ ํ˜„์ƒํ•™์  ๊ณ ์ฐฐ : Don Ihde๋ฅผ ์ค‘์‹ฌ์œผ๋กœ

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    ํ•™์œ„๋…ผ๋ฌธ(์„์‚ฌ)--์„œ์šธ๋Œ€ํ•™๊ต ๋Œ€ํ•™์› :์ฒ ํ•™๊ณผ ์„œ์–‘์ฒ ํ•™์ „๊ณต,2000.Maste

    ๊ธด๊ผฌ๋ฆฌ์ด๋ฆฌ์‘์• (์ง„๋“œ๊ธฐ์•„๊ฐ•: ์ด๋ฆฌ์‘์• ๊ณผ)์˜ ๋ฐœ์œก๊ณผ ์‚ฐ๋ž€ ๋ชจํ˜•, ์ƒ๋ช…ํ‘œ ๋ฐ ๊ธฐ๋Šฅ ๋ฐ˜์‘์— ๊ด€ํ•œ ์—ฐ๊ตฌ

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    ํ•™์œ„๋…ผ๋ฌธ (์„์‚ฌ)-- ์„œ์šธ๋Œ€ํ•™๊ต ๋Œ€ํ•™์› : ๋†์ƒ๋ช…๊ณตํ•™๋ถ€, 2017. 2. ์ด์ค€ํ˜ธ.๋งŽ์€ ์ด๋ฆฌ์‘์• ๋“ค์€ ์ƒ์—…ํ™”๋˜์–ด ๋†๊ฒฝ์ง€ ๋‚ด์—์„œ ์‘์• , ์ด์ฑ„๋ฒŒ๋ ˆ, ๊ฐ€๋ฃจ์ด ๋ฐฉ์ œ๋ฅผ ์œ„ํ•ด ์ด์šฉ๋˜๊ณ  ์žˆ๋‹ค. ๊ธด๊ผฌ๋ฆฌ์ด๋ฆฌ์‘์• ๋Š” ๊ตญ๋‚ด ํ† ์ฐฉ ์ด๋ฆฌ์‘์• ๋กœ, ์‚ฌ๊ณผ์› ๋‚ด ์žŽ์‘์• ๋ฅ˜์˜ ์ดˆ๊ธฐ๋ฐฉ์ œ์›์œผ๋กœ ์•Œ๋ ค์ ธ ์™”๋‹ค. ์ฒœ์ ์œผ๋กœ์„œ ๊ธด๊ผฌ๋ฆฌ์ด๋ฆฌ์‘์• ์˜ ์ž ์žฌ์„ฑ ํ‰๊ฐ€๋ฅผ ์œ„ํ•ด, ์ ๋ฐ•์ด์‘์• ๋ฅผ ๋จน์ด๋กœ ํ•˜์—ฌ ๊ธด๊ผฌ๋ฆฌ์ด๋ฆฌ์‘์• ์˜ ์ƒํƒœ์  ํŠน์„ฑ์— ๊ด€ํ•œ ์—ฐ๊ตฌ๊ฐ€ ์ง„ํ–‰๋˜์—ˆ๋‹ค. ๋จผ์ €, ์˜จ๋„ ๋ณ„ ๊ธด๊ผฌ๋ฆฌ์ด๋ฆฌ์‘์• ์˜ ๋ฐœ์œก๊ณผ ์‚ฐ๋ž€์— ๊ด€ํ•œ ์—ฐ๊ตฌ์™€ ๊ทธ๊ฒƒ์„ ์ด์šฉํ•˜์—ฌ ๋ฐœ์œก๊ณผ ์‚ฐ๋ž€ ๋ชจํ˜•์ด ๋งŒ๋“ค์–ด์กŒ๋‹ค. ๋‘๋ฒˆ์งธ๋กœ, ์—ฌ๋Ÿฌ ์˜จ๋„ ์กฐ๊ฑด์—์„œ ๊ธด๊ผฌ๋ฆฌ์ด๋ฆฌ์‘์• ์˜ ๊ฐœ์ฒด๊ตฐ ์„ฑ์žฅ ํŠน์„ฑ์„ ๋ถ„์„ํ•˜๊ธฐ์œ„ํ•ด ์ƒ๋ช…ํ‘œ๊ฐ€ ์ž‘์„ฑ๋˜์—ˆ๋‹ค. ์„ธ๋ฒˆ์งธ๋กœ, ์ ๋ฐ•์ด์‘์•  ์œ ์ถฉ์„ ์ด์šฉํ•˜์—ฌ ๊ธด๊ผฌ๋ฆฌ์ด๋ฆฌ์‘์• ์˜ ๊ธฐ๋Šฅ ๋ฐ˜์‘ ์—ฐ๊ตฌ๊ฐ€ ์ง„ํ–‰๋˜์—ˆ๋‹ค. ๊ธด๊ผฌ๋ฆฌ์ด๋ฆฌ์‘์• ์˜ ๋ฐœ์œก ์‹คํ—˜์€ 11๊ฐœ ์˜จ๋„(18.0, 20.1, 21.6, 24.0, 24.1, 27.4, 28.6, 30.2, 32.0, 33.2, 35.9 ยฐC)์—์„œ ์ง„ํ–‰๋˜์—ˆ๊ณ , ์‚ฐ๋ž€ ์‹คํ—˜์€ 6๊ฐœ ์˜จ๋„(18.0, 21.6, 24.1, 27.4, 30.2, 33.2 ยฐC)์—์„œ ์ง„ํ–‰๋˜์—ˆ๋‹ค. ๋ฐœ์œก ๋ชจํ˜•์€ Briere1 ์‹์„ ์ด์šฉํ•˜์—ฌ ํ‘œํ˜„๋˜์—ˆ๋‹ค. ๋ฏธ์„ฑ์ˆ™๊ธฐ ๋ฐœ์œก ๋ชจํ˜•์˜ ๋ฐœ์œก์˜์ ์˜จ๋„, ์ ์ •์˜จ๋„, ๋ฐœ์œกํ•œ๊ณ„์˜จ๋„, B80์€ ๊ฐ๊ฐ 13.2, 30.6, 35.9, 25.5 ~ 34.0 ยฐC ์˜€๋‹ค. ๋ฏธ์„ฑ์ˆ™๊ธฐ์˜ ๋ฐœ์œก ์™„๋ฃŒ ๋ชจํ˜•์€ Weibull ์‹์„ ์‚ฌ์šฉํ•˜์—ฌ ํ‘œํ˜„๋˜์—ˆ๋‹ค. ์‚ฐ๋ž€ ์ˆ˜ ๋ชจํ˜•์€ Extreme Value ์‹์„ ์ด์šฉํ•˜์—ฌ ํ‘œํ˜„๋˜์—ˆ๋‹ค. ์‚ฐ๋ž€์— ๋Œ€ํ•œ ์ ์ •์˜จ๋„, B80์€ ๊ฐ๊ฐ 24.3, 20.5 ~ 27.4 ยฐC ์˜€๋‹ค. ์„ฑ์ถฉ์˜ ๋ฐœ์œก ๋ชจํ˜•, ๋ˆ„์  ์‚ฐ๋ž€ ๋ชจํ˜•, ๋‚˜์ด์— ๋”ฐ๋ฅธ ์ƒ์กด์œจ ๋ชจํ˜•์€ ๊ฐ๊ฐ TableCurve 2D์˜ ๋ชฉ๋ก์— ์žˆ๋Š” ์‹๊ณผ Weibull ์‹, reverse sigmoid ์‹์„ ์ด์šฉํ•˜์—ฌ ํ‘œํ˜„๋˜์—ˆ๋‹ค. ๊ธด๊ผฌ๋ฆฌ์ด๋ฆฌ์‘์• ์˜ ์ƒ๋ช…ํ‘œ ๋ถ„์„์€ 6๊ฐœ ์˜จ๋„ (18.0, 21.6, 24.1, 27.4, 30.2, 33.2 ยฐC) ๊ทธ๋ฆฌ๊ณ  Age-stage, two-sex life table ์ด๋ก ์— ๋”ฐ๋ผ์„œ ๋ถ„์„๋˜์—ˆ๋‹ค. ์—ฐ๋ น - ๋ฐœ์œก ๋‹จ๊ณ„ ๋ณ„ ์ƒ์กด์œจ, ์—ฐ๋ น โ€“ ๋ฐœ์œก ๋‹จ๊ณ„ ๋ณ„ ์‚ฐ๋ž€ ์ˆ˜, ์—ฐ๋ น โ€“ ๋ฐœ์œก ๋‹จ๊ณ„ ๋ณ„ ๋ฒˆ์‹๊ฐ€, ์—ฐ๋ น ๋ณ„ ์ƒ์กด์œจ, ์—ฐ๋ น ๋ณ„ ์‚ฐ๋ž€ ์ˆ˜ ๊ทธ๋ฆฌ๊ณ  ๊ฐœ์ฒด๊ตฐ ์ฆ๊ฐ€์œจ ์˜ˆ์ธก์ด ์ธก์ •๋˜์—ˆ๋‹ค. ๋‚ด์  ์ž์—ฐ ์ฆ๊ฐ€์œจ์€ 0.2619๋กœ 27.4 ยฐC ์—์„œ ๊ฐ€์žฅ ๋†’๊ฒŒ ๋‚˜ํƒ€๋‚ฌ๋‹ค. ํ‰๊ท  ์„ธ๋Œ€ ๊ธฐ๊ฐ„์€ 18.0 ยฐC ์—์„œ 26.9์ผ๋กœ ๊ฐ€์žฅ ๊ธธ์—ˆ๊ณ , 30.2 ยฐC ์—์„œ 10.5์ผ๋กœ ๊ฐ€์žฅ ์งง์•˜๋‹ค. ๊ธด๊ผฌ๋ฆฌ์ด๋ฆฌ์‘์• ์˜ ๊ธฐ๋Šฅ ๋ฐ˜์‘ ์‹คํ—˜์€ ์ ๋ฐ•์ด์‘์•  ์œ ์ถฉ 10, 30, 50, 70, 130๋งˆ๋ฆฌ์—์„œ ์ง„ํ–‰๋˜์—ˆ๋‹ค. ๊ธด๊ผฌ๋ฆฌ์ด๋ฆฌ์‘์• ๋Š” 2ํ˜• ๊ธฐ๋Šฅ ๋ฐ˜์‘์„ ๋‚˜ํƒ€๋ƒˆ๋‹ค. ๊ณต๊ฒฉ์œจ์€ ์•”์ปท์€ 0.109 ์˜€๊ณ , ์ˆ˜์ปท์€ 0.019 ์˜€๋‹ค. ์ฒ˜๋ฆฌ ์‹œ๊ฐ„์˜ ๊ฒฝ์šฐ ์•”์ปท์€ 0.164 h ๊ทธ๋ฆฌ๊ณ  ์ˆ˜์ปท์€ 0.234 h ์˜€๋‹ค. ๊ณต๊ฒฉ์œจ์˜ ๊ฒฝ์šฐ ์•”์ปท๊ณผ ์ˆ˜์ปท์ด 95% ์‹ ๋ขฐ ๊ตฌ๊ฐ„์—์„œ ํ†ต๊ณ„์ ์œผ๋กœ ์œ ์˜๋ฏธํ•œ ์ฐจ์ด๋ฅผ ๋ณด์˜€์ง€๋งŒ, ์ฒ˜๋ฆฌ ์‹œ๊ฐ„์˜ ๊ฒฝ์šฐ ์œ ์˜๋ฏธํ•œ ์ฐจ์ด๋ฅผ ๋ณด์ด์ง€ ์•Š์•˜๋‹ค.Many species of Phytoseiidae have been used to control the pest such as mites, thrips and white flies in agricultural crop systems. Amblyseius eharai is a native Phytoseiidae in Korea and known for a biological control agent of spider mites in the early season in apple orchards. To evaluate the potential of A. eharai as a biological control agent, ecological characteristics of A. eharai were studied by using Tetranychus urticae (Koch) (Acari: Tetranychidae) as prey. First, development and fecundity of A. eharai were studied at different temperatures and its temperature-dependent development and oviposition models were developed. Second, life table of A. eharai was constructed at various temperatures to analyze its population growth characteristics. Third, functional response of A. eharai was studied against larvae of T. urticae. Development of A. eharai was examined at 11 constant temperatures (18.0, 20.1, 21.6, 24.0, 24.1, 27.4, 28.6, 30.2, 32.0, 33.2 and 35.9 ยฐC) and oviposition of A. eharai was examined at six constant temperatures (18.0, 21.6, 24.1, 27.4, 30.2 and 33.2 ยฐC). Development of A. eharai was well described by the Briere 1 function. Lower threshold, optimal, and upper threshold temperatures of development of total immature stage were 13.2, 30.6, and 35.9 ยฐC, respectively. Developmental variation of immature stages was well described by the two-parameter Weibull function. Fecundity was well described by the Extreme Value function. Optimal and B80 temperatures of fecundity were 24.3 and 20.5 ~ 27.4 ยฐC, respectively. Adult developmental rate model, cumulative oviposition model and age-specific survival rate model were well described by the equation from the TableCurve 2D library, Weibull function and reverse sigmoid function, respectively. Life table analysis of A. eharai was conducted at six constant temperatures (18.0, 21.6, 24.1, 27.4, 30.2 and 33.2 ยฐC) according to the age-stage, two-sex life table theory. Age-stage specific survival rate, age-stage specific fecundity, age-stage specific reproductive value, age-specific survival rate, age-specific fecundity and population projection were estimated. The intrinsic rate of increase was the highest at 27.4 ยฐC as 0.2619. Mean generation time was longest at 18.0 ยฐC as 26.9 days, and shortest at 30.2 ยฐC as 10.5 days. Functional response of A. eharai was conducted at 10, 30, 50, 70 and 130 larvae of T. urticae. Functional response of A. eharai was the Type 2. The attack rate of female and male A. eharai was 0.109 and 0.019, respectively. The handling time of female and male was 0.164 h and 0.234 h, respectively. The attack rate was significantly different between males and females at 95% confidence interval. However, handling time was not statistically different.1. General introduction 1 2. Temperature-dependent development and oviposition models of Amblyseius eharai (Amitai et Swirski) (Acari: Phytoseiidae) 4 2-1. Introduction 4 2-2. Materials and Methods 6 2-2-1. Mite culture 6 2-2-2. Development 7 2-2-3. Oviposition 8 2-2-4. Development and oviposition models 9 2-3. Results 16 2-3-1. Development model 16 2-3-2. Oviposition model 27 2-4. Discussion 36 3. Age-stage, two-sex life table of Amblyseius eharai (Amitai et Swirski) (Acari: Phytoseiidae) 38 3-1. Introduction 38 3-2. Materials and Methods 40 3-2-1. Data 40 3-2-2. Life table analysis 41 3-2-3. Population parameters 41 3-3. Results 44 3-4. Discussion 51 4. Functional response of Amblyseius eharai (Amitai et Swirski) (Acari: Phytoseiidae) to larval Tetranychus urticae (Koch) (Acari: Tetranychidae) 54 4-1. Introduction 54 4-2. Materials and Methods 56 4-2-1. Experiments 56 4-2-2. Data analysis 58 4-3. Results 60 4-4. Discussion 69 Literature Cited 73 ์ดˆ๋ก 85Maste

    ๋‹ˆ๋“ค ๊ฐ€์ด๋“œ ์žฅ์น˜ ๋ฐ ์ด๋ฅผ ํฌํ•จํ•˜๋Š” ์‹œ์Šคํ…œ

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    ์ดํ•˜, ์‹ค์‹œ์˜ˆ๋“ค์€ ๋‹ˆ๋“ค ๊ฐ€์ด๋“œ ์žฅ์น˜ ๋ฐ ์ด๋ฅผ ํฌํ•จํ•˜๋Š” ์‹œ์Šคํ…œ์— ๊ด€ํ•œ ๊ฒƒ์ด๋‹ค. ์ผ ์‹ค์‹œ์˜ˆ์— ๋”ฐ๋ฅธ ๋‹ˆ๋“ค ๊ฐ€์ด๋“œ ์žฅ์น˜๋Š”, ์ œ1 ๋น” ๋ฐ ์ƒ๊ธฐ ์ œ1 ๋น”์— ํ‰ํ–‰ํ•˜๊ฒŒ ๋ฐฐ์น˜๋˜๊ณ  ์ƒ๊ธฐ ์ œ1 ๋น”์˜ ๊ธธ์ด ๋ฐฉํ–ฅ์˜ ์ถ•์„ ๋”ฐ๋ผ ์ด๋™ ๊ฐ€๋Šฅํ•œ ์ œ2 ๋น”์„ ํฌํ•จํ•˜๊ณ , ์ผ ๋‹จ๋ถ€์— ๋‹ˆ๋“ค์ด ์žฅ์ฐฉ๋˜๋Š” ๋“œ๋ฆด์ด ์ƒ๊ธฐ ์ œ1 ๋น”์˜ ์ผ ๋‹จ๋ถ€ ๋ฐ ์ƒ๊ธฐ ์ œ2 ๋น”์˜ ์ผ ๋‹จ๋ถ€์— ๊ฐ๊ฐ ์—ฐ๊ฒฐ๋˜๊ณ , ์ƒ๊ธฐ ๋“œ๋ฆด์€ ์ƒ๊ธฐ ์ œ1 ๋น”์˜ ๊ธธ์ด ๋ฐฉํ–ฅ์˜ ์ถ• ๋ฐ ์ƒ๊ธฐ ์ œ1 ๋น”์˜ ๊ธธ์ด ๋ฐฉํ–ฅ์˜ ์ถ•์— ๊ต์ฐจํ•˜๋Š” ์ถ•์— ๋Œ€ํ•˜์—ฌ ํšŒ์ „ ๊ฐ€๋Šฅํ•˜๋‹ค

    An Efficient Software Update Technique with Code-Banking & Delta-Image for Wireless Sensor Networks

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    Software update has been regarded as one of fundamental functions in wireless sensor networks. It can disseminate a delta-image between a current software image operating on a sensor node and its new image in order to reduce an update image(transmission data) size, resultantly saving energy. In addition, code-banking capability of micro-controllers can decrease the update image size. In order to maximize the efficiency of the software update, the proposed scheme exploits both the delta-image and the code-banking at the same time. Besides, it additionally delivers a recovery delta-image to properly handle abnormal conditions, such as message corruptions and unexpected power-off during the update.2

    Method and apparatus for controlling movement of plural robots based on wireless network

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    ๋ณธ ๋ช…์„ธ์„œ์—์„œ๋Š” ๋ฌด์„  ๋„คํŠธ์›Œํฌ์— ๊ธฐ๋ฐ˜ํ•˜์—ฌ ๋‹ค์ˆ˜์˜ ๋กœ๋ด‡์˜ ์ด๋™์„ ์ œ์–ดํ•˜๋Š” ๋ฐฉ๋ฒ•๊ณผ ์žฅ์น˜๋ฅผ ์ œ๊ณตํ•œ๋‹ค ๋ณธ ๋ช…์„ธ์„œ์˜ ์ผ ์‹ค์‹œ ์˜ˆ์— ๋”ฐ๋ฅธ ๋ฌด์„  ๋„คํŠธ์›Œํฌ์— ๊ธฐ๋ฐ˜ํ•˜์—ฌ ๋‹ค์ˆ˜์˜ ๋กœ๋ด‡์˜ ์ด๋™์„ ์ œ์–ดํ•˜๋Š” ์žฅ์น˜๋Š” ๋กœ๋ด‡์˜ ์ด๋™์„ ์ œ์–ดํ•˜๋Š” ๋ช…๋ น์„ ์ƒ์„ฑํ•˜๋Š” ์›๊ฒฉ ์ œ์–ด ๋ช…๋ น ์ƒ์„ฑ๋ถ€, ์ƒ๊ธฐ ์ƒ์„ฑ๋œ ๋ช…๋ น์„ ๋ฌด์„  ๋„คํŠธ์›Œํฌ ํ†ต์‹  ๋ฐ์ดํ„ฐ๋กœ ๋ณ€ํ™˜ํ•˜๋Š” ๋„คํŠธ์›Œํฌ ์ œ์–ด๋ถ€, ์ƒ๊ธฐ ๋„คํŠธ์›Œํฌ ์ œ์–ด๋ถ€์—์„œ ๋ณ€ํ™˜ํ•œ ๋ฌด์„  ๋„คํŠธ์›Œํฌ ํ†ต์‹  ๋ฐ์ดํ„ฐ๋ฅผ ๋กœ๋ด‡์— ์†ก์‹ ํ•˜๊ณ , ์†ก์‹ ๋œ ๋ฌด์„  ๋„คํŠธ์›Œํฌ ํ†ต์‹  ๋ฐ์ดํ„ฐ์˜ ์‹คํ–‰ ๊ฒฐ๊ณผ๋ฅผ ๋กœ๋ด‡์œผ๋กœ๋ถ€ํ„ฐ ์ˆ˜์‹ ํ•˜๋Š” ์†ก์ˆ˜์‹ ๋ถ€, ๋ฐ ์ƒ๊ธฐ ์›๊ฒฉ ์ œ์–ด ๋ช…๋ น ์ƒ์„ฑ๋ถ€ ๋ฐ ์†ก์ˆ˜์‹ ๋ถ€์— ์†Œ์ •์˜ ๋ช…๋ น์„ ์ง€์‹œํ•˜๊ฑฐ๋‚˜ ๋˜๋Š” ๊ฒฐ๊ณผ๋ฅผ ํ‘œ์‹œํ•˜๋Š” ์‚ฌ์šฉ์ž ์ธํ„ฐํŽ˜์ด์Šค๋ถ€๋ฅผ ํฌํ•จํ•œ๋‹ค.์Šฌ๋ ˆ์ด๋ธŒ ๋กœ๋ด‡์˜ ์ด๋™์„ ์ œ์–ดํ•˜๋Š” ๋ช…๋ น์„ ๋ฌด์„  ๋„คํŠธ์›Œํฌ ํ†ต์‹  ๋ฐ์ดํ„ฐ๋กœ ์ˆ˜์‹ ํ•˜๋Š” ์†ก์ˆ˜์‹ ๋ถ€;์ƒ๊ธฐ ์ˆ˜์‹ ํ•œ ๋ฌด์„  ๋„คํŠธ์›Œํฌ ํ†ต์‹  ๋ฐ์ดํ„ฐ๋ฅผ ๋ณตํ˜ธํ™”ํ•˜๋Š” ๋„คํŠธ์›Œํฌ ์ œ์–ด๋ถ€; ์ƒ๊ธฐ ๋ณตํ˜ธํ™”ํ•œ ๋ฌด์„  ๋„คํŠธ์›Œํฌ ํ†ต์‹  ๋ฐ์ดํ„ฐ์—์„œ ๋ช…๋ น์„ ์ถ”์ถœํ•˜๋Š” ๋ช…๋ น ์ „์ฒ˜๋ฆฌ๋ถ€;์ƒ๊ธฐ ์ถ”์ถœํ•œ ๋ช…๋ น์— ๋”ฐ๋ผ ๋กœ๋ด‡์˜ ์ด๋™์„ ์ œ์–ดํ•˜๋Š” ์ด๋™ ์ œ์–ด๋ถ€๋ฅผ ํฌํ•จํ•˜๋ฉฐ, ์ƒ๊ธฐ ๋ช…๋ น์ด ์˜คํ†  ์ŠคํŽ˜์ด์‹ฑ์ธ ๊ฒฝ์šฐ, ์ƒ๊ธฐ ์†ก์ˆ˜์‹ ๋ถ€๋Š” ๋งˆ์Šคํ„ฐ ๋กœ๋ด‡์œผ๋กœ๋ถ€ํ„ฐ ๊ฑฐ๋ฆฌ ์ •๋ณด๋ฅผ ์ˆ˜์‹ ํ•˜๋ฉฐ;์ƒ๊ธฐ ์ˆ˜์‹ ํ•œ ๊ฑฐ๋ฆฌ ์ •๋ณด๊ฐ€ ์˜คํ†  ์ŠคํŽ˜์ด์‹ฑ ์„ค์ • ๋ณด๋‹ค ํฐ ๊ฒฝ์šฐ ์ƒ๊ธฐ ์ด๋™ ์ œ์–ด๋ถ€๋Š” ์ด๋™ ๋ช…๋ น์„ ์‹คํ–‰ํ•˜๋Š” ๊ฒƒ์„ ํŠน์ง•์œผ๋กœ ํ•˜๋Š”, ๋ฌด์„  ๋„คํŠธ์›Œํฌ์— ๊ธฐ๋ฐ˜ํ•˜์—ฌ ์ด๋™ํ•˜๋Š” ์žฅ์น˜

    Environment-Based Ranging Error Correction Technique Using IEEE 802.15.4a CSS PHY

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    Precise localization heavily relies on the accuracy of its underlying ranging technique. It has been known that the Chirp Spread Spectrum (CSS) defined in the IEEE 802.15.4a provides more dependable ranging accuracy than the Received Signal Strength Indicator (RSSI) in the IEEE 802.15.4. This paper examines the accuracy of the CSS-based ranging technique in the indoor/outdoor environments and discovers its consistent inaccuracy in different environments. Next, it proposes an error-correction architecture for the CSS-based ranging technique that exploits the per-environment consistent inaccuracy information and user visiting patterns (represented by weights for each environment).2
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