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RISS 인기검색어
- 검색키워드
- 저자 : ( Thi Nha Ngo ) (검색결과 4 건)
- 무료
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Assessment of Pesticide Effect on Honey Bees Behavior using a Real-time Imaging System
( Thi Nha Ngo ),( Kung-chin Wu ),( En-cheng Yang ),( Ta-te Lin ) 한국농업기계학회 2018 한국농업기계학회 학술발표논문집 Vol.23 No.1
Honey bees (Apis mellifera) are ecologically and economically important insects. However, massive deaths of honey bees have been reported all around the world. There is much evidence linking the decline of their population to pesticides. However, the impact of lethal doses of pesticide on honey bees is still under debate. Monitoring honey bees passing frequencies at hive entrance is an efficient method to verify the health condition of a beehive. In this study, a real-time imaging system based on a GPU processor for automatic tracking of in-and-out frequencies is presented. The imaging system includes: (1) a dark acrylic box with a transparent pathway. This restricts bees to pass into the image capturing area, (2) an LED light source, (3) a webcam, and (4) an embedded system with GPUs (NVIDIA Jetson TX2) for real-time image acquisition and processing. Background subtraction is applied to remove unnecessary objects from the video. In order to track the in-and-out frequencies of multiple honey bees, and integrated Kalman Filter (KF) and Hungarian algorithm is implemented. KF is used to estimate the object position on each frame. Meanwhile, the Hungarian algorithm is used for the detection of multiple honey bees. Based on the honey bees’ trajectories, a counting algorithm is used to determine their in-and-out activities. The detection algorithms and real-time automatic tracking accuracy rates were evaluated and the system performance was tested with field experiments. The imaging system was further applied to assess the effect of pesticides on honey bee colonies. Five healthy honey bee colonies were treated with different levels of pesticide concentration in contaminated food. The experimental results, which demonstrate the feasibility of our monitoring and tracking system to determine honey bee frequencies, are useful for assessing the pesticide effect on honey bee colonies.
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Nguyen Thi Mai Tho,Bui The Huy,Dang Nguyen Nha Khanh,Ho Nguyen Nhat Ha,Vu Quang Huy,Ngo Thi Tuong Vy,Do Manh Huy,Duong Phuoc Dat,Nguyen Thi Kim Phuong 한국화학공학회 2018 Korean Journal of Chemical Engineering Vol.35 No.12
Novel highly active visible-light photocatalysts in the form of zinc bismuth oxide (ZnBi2O4) and graphite hybrid composites were prepared by coupling via a co-precipitation method followed by calcination at 450 oC. The asprepared ZnBi2O4-graphite hybrid composites were tested for the degradation of rhodamine B (RhB) solutions under visible-light irradiation. The existence of strong electronic coupling between the two components within the ZnBi2O4- graphite heterostructure suppressed the photogenerated recombination of electrons and holes to a remarkable extent. The prepared composite exhibited excellent photocatalytic activity, leading to more than 93% of RhB degradation at an initial concentration of 50mg·L1 with 1.0 g catalyst per liter in 150min. The excellent visible-light photocatalytic mineralization of ZnBi2O4-1.0graphite in comparison with pristine ZnBi2O4 could be attributed to synergetic effects, charge transfer between ZnBi2O4 and graphite, and the separation efficiency of the photogenerated electrons and holes. The photo-induced h+ and the superoxide anion were the major active species responsible for the photodegradation process. The results demonstrate the feasibility of ZnBi2O4-1.0graphite as a potential heterogeneous photocatalyst for environmental remediation.
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Assessing Pesticide Effects on Honeybee Movement Behavior using an In-hive Imaging System
( Kung-chin Wu ),( Jun-jee Chao ),( Thi Nha Ngo ),( En-cheng Yang ),( Ta-te Lin ) 한국농업기계학회 2018 한국농업기계학회 학술발표논문집 Vol.23 No.1
Food and cash crops in the world naturally depend on honeybees for delivering pollen. In recent years, the occurrence of the honeybee colony collapse disorder (CCD) caused a large number of honeybee populations to disappear. This phenomenon is causing a significant impact on agricultural production. Therefore, this study aims to monitor the behavior of honeybees and establish effective analysis tools to understand the causes of CCD. Honeybee interaction behavior inside the beehives offers important behavioral information. In order to analyze honeybee behavior, each individual honeybee was affixed with waterproof text labels for observation. Using image processing techniques, such as label recognition and tracking, the movement of the honeybee inside the hive are recorded. By using label tags, the honeybee can be labeled by groups, and the trajectories can be used to classify them into different groups. After obtaining the honeybee trajectories, the states and transformation conditions were determined and used to create a finite state machine (FSM) model. The FSM model was used to analyze the trajectories of the honeybee: it was divided into multiple secondary trajectories by different conditions and state transitions. The model could also be used to transform the trajectories into patterns of behavior and were combined into a sequence of behavioral patterns. Using the data obtained, it was found that in-hive and foraging bees have different trajectory and behavioral patterns. It was also found that the behavioral pattern sequences and trajectories can be used to train models using machine learning and deep learning techniques to classify and recognize different groups of honeybees. Experiments were performed using the imaging system to record and analyze long-term observation of honeybee movement behavior after treatment with pesticide in contaminated food. We further demonstrated this technique in assessing the effect of pesticide on the change of movement behaviors of honeybees.
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