• Title/Summary/Keyword: 반자연적 조건

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Temporal Pattern of Within-harborage Time and Visiting Frequency in Two Strains of the german Cockroach, Blatella germanica, in Semi-natural Conditions (반자연적인 조건에서 두 계통 바퀴(Blattella germanica)의 휴식처 체제 시간 및 방문빈도에 대한 시간적 유형)

  • ;;Mary H. Ross
    • Korean journal of applied entomology
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    • v.36 no.4
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    • pp.299-310
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    • 1997
  • A mutant, or(orange body), and the KNIH(Korea National Institute of Health) strain of the German cockroach, Blattella germanica(L.) (Orthoptera: Blattellidae), were observed continuously in semi-natural conditions through video taping and data processing by computers. Male adults were individually observed for 4-5 days in a rectangular-shaped rearing cage with four different microhabitats, allowing observations of behavior such as resting, feeding, drinking and communicating with other individuals. The frequencies of visits to and times spent within harborage were determined. Although there were relatively large variations among individuals, the average stays withing harborage ranged from 47-61% of the total observation time. The duration of within-harborage time was significantly different between maternal origins, while not distinctively different between the strains. Diel differences were observed in body strains. The time spent within harborage was longer in photophase than in scotophase. visiting frequency, which represented local activity around harborage, appeared slightly higher in the or strain than in the KNIH strain, and was significant in the or strain while it was not significant in the KNIH strain. Although there were variations among individuals, similar temporal patterns in some progenies from the same maternal origins were observed in time spent within harborage and in visiting frequency.

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Analysis and Recognition of Behavioral Response of Selected Insects in Toxic Chemicals for Water Quality Monitoring (수질 모니터링을 위한 유해 물질 유입에 따른 생물체의 행동 반응 분석 및 인식)

  • Kim, Cheol-Ki;Cha, Eui-Young
    • The KIPS Transactions:PartB
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    • v.9B no.5
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    • pp.663-672
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    • 2002
  • In this paper, Using an automatic tracking system, behavior of an aquatic insect, Chironomus sp. (Chironomidae), was observed in semi-natural conditions in response to sub-lethal treament of a carbamate insecticide, carbofuran. The fourth instar larvae were placed in an observation cage $(6cm\times{7cm}\times{2.5cm)}$ at temperature of $18^\circ{C}$ and the light condition of 10 time (light) : 14 time (dark). The tracking system was devised to detect the instant, partial movement of the insect body. Individual movement was traced after the treatment of carbofuran (0.1ppm) for four days 2days : before treatment, 2 days : after treatment). Along with the other irregular behaviors, "ventilation activity", appearing as a shape of "compressed zig-zag", was more frequently observed after the treatment of the insecticide. The activity of the test individuals was also generally depressed after the chemical treatment. In order to detect behavioral changes of the treated specimens, wavelet analysis was implemented to characterize different movement patterns. The extracted parameters based on Discrete Wavelet Transforms (DWT) were subsequently provided to artificial neural networks to be trained to represent different patterns of the movement tracks before and after treatments of the insecticide. This combined model of wavelets and artificial neural networks was able to point out the occurrence of characteristic movement patterns, and could be an alternative tool for automatically detecting presences of toxic chemicals for water quality monitoring. quality monitoring.

Analysis and Recognition of Behavior of Medaka in Response to Toxic Chemical Inputs by using Multi-Layer Perceptron (다층 퍼셉트론을 이용한 유해물질 유입에 따른 송사리의 행동 반응 분석 및 인식)

  • 김철기;김광백;차의영
    • Journal of Korea Multimedia Society
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    • v.6 no.6
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    • pp.1062-1070
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    • 2003
  • In this paper, we observe one of the aquatic insect, fish(Medaka)'s behavior which reacts to giving toxic chemicals until lethal conditions using automatic tracking sl$.$stem. For the result, we define the Pattern A is a normal movement of fish and Pattern B is after giving the chemicals. In order to detect the movement of fish automatically, these patterns are selected for the training data of the artificial neural networks. The average recognition rates of the pattern B are remarkably increased after inputs of toxic chemical(diazinon) while the Pattern A is decreased distinctively. This study demonstrates that artificial neural networks are useful method for detecting presence of toxicoid in environment as for an alternative of in-situ behavioral monitoring tool.

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