Automated detection and identification of white-backed planthoppers in paddy fields using image processing

A survey of the population densities of rice planthoppers is important for forecasting decisions and efficient control. Traditional manual surveying of rice planthoppers is time-consuming, fatiguing, and subjective. A new three-layer detection method was proposed to detect and identify white-backed planthoppers(WBPHs, Sogatella furcifera(Horváth)) and their developmental stages using image processing. In the first two detection layers, we used an Ada Boost classifier that was trained on a histogram of oriented gradient(HOG) features and a support vector machine(SVM) classifier that was trained on Gabor and Local Binary Pattern(LBP) features to detect WBPHs and remove impurities. We achieved a detection rate of 85.6% and a false detection rate of 10.2%. In the third detection layer, a SVM classifier that was trained on the HOG features was used to identify the different developmental stages of the WBPHs, and we achieved an identification rate of 73.1%, a false identification rate of 23.3%, and a 5.6% false detection rate for the images without WBPHs. The proposed three-layer detection method is feasible and effective for the identification of different developmental stages of planthoppers on rice plants in paddy fields.     

NEW CLOSED-LOOP DRIVING CIRCUIT OF SILICON MICROMACHINED VIBRATORY GYROSCOPE

A new closed-loop driving scheme for the silicon micromachined vibratory gyroscope (SMVG) is proposed. The push-pull driving is adopted and in-phase AC and reverse-phase DC voltages are applied in the driving electrodes placed in both sides of the active combs, respectively. Driving performance analyses show that the frequency spectrum between driving moments and noise signals is separated. Therefore, the model of the closed-loop control is set up with the phase lock loop (PLL). The requirements for phases and gains of the sinusoidal selfdrive-oscillation are met by PLL, thus the closed-loop circuit reaches the self-drive-oscillation. Phase conditions of the sinusoidal self-drive-oscillation and the characteristic of phase discrimination of the PLL are used to eliminate the coupling between driving and sense signals, and noise signals. Finally, experimental results show that the variations of both the driving frequency and the amplitude are all under 0.02%. The precision and the reliability of the gyroscope are greatly improved.     

Automated Counting of Rice Planthoppers in Paddy Fields Based on Image Processing

A quantitative survey of rice planthoppers in paddy fields is important to assess the population density and make forecasting decisions. Manual rice planthopper survey methods in paddy fields are time-consuming, fatiguing and tedious. This paper describes a handheld device for easily capturing planthopper images on rice stems and an automatic method for counting rice planthoppers based on image processing. The handheld device consists of a digital camera with WiFi, a smartphone and an extrendable pole. The surveyor can use the smartphone to control the camera, which is fixed on the front of the pole by WiFi, and to photograph planthoppers on rice stems. For the counting of planthoppers on rice stems, we adopt three layers of detection that involve the following：（a） the first layer of detection is an AdaBoost classifier based on Haar features;（b） the second layer of detection is a support vector machine（SVM） classifier based on histogram of oriented gradient（HOG） features;（c） the third layer of detection is the threshold judgment of the three features. We use this method to detect and count whiteback planthoppers（Sogatella furcifera） on rice plant images and achieve an 85.2% detection rate and a 9.6% false detection rate. The method is easy, rapid and accurate for the assessment of the population density of rice planthoppers in paddy fields.     

Development of a Synthetic Peptide ELISA Assay for the Detection of Foot-and-Mouth Disease Virus Nonstructural Protein Antibodies

In order to develop an ELISA assay with synthetic peptides for the detection of antibody to the nonstructural proteins of foot-and-mouth disease virus, specific peptides were synthesized by a solid-phase method according to FMDV NSPs B-cell epitopes, and were conjugated to carrier protein BSA. An ELISA system was developed to detect FMDV NSPs antibody with the conjugated proteins as the coating antigen. The optimal coating concentration of the antigen was determined as 2.5 μg mL-1. The comparative study of this assay with UBI NSP ELISA kit and national commercial 3ABC ELISA kit in the detection of 199 serum samples showed that they were very coincident, and the identity rates were 96.48 and 97.48%, respectively. The development of ELISA using the synthetic peptides as coating antigen is specific, reproducible, stable, and easy, and can be used to differentiate FMDV infected pigs from immunized pigs.     

基于阈值判决的无线传感器网络混沌信号重构

考虑在传感器网络中重构混沌信号的问题.各传感器同时观测一个混沌信号.由于带宽受限,各传感器量化观测信号并将量化后的数据发送到融合中心,该中心使用无先导卡尔曼滤波算法重构观测的混沌信号.为了节省能量,只有观测信号信噪比高于某个阈值的传感器被选中并发送数据.定义代价函数关联重构性能和能量消耗,分析并仿真了代价函数和阈值之间的关系.结果表明在某些情况下部分传感器发送数据更合理.

Abstract：

The problem of reconstructing chaotic signals in wireless sensor networks is considered.All sensors observe a common chaotic signal.Because of the limited bandwidth,the observations are quantized and the quantized data are sent to a fusion center.The fusion center reconstructs the chaotic signals by using the unscented Kalman filtering(UKF)algorithm.To save energy,only the sensors for which the SNR of the observation is higher than a threshold are chosen for transmission.A cost function is defined to relate the reconstruction performance and the energy consumption.The relationship between the cost function and the threshold is analyzed and simulated.The results show that under certain conditions,it is more reasonable that only a portion of the sensors transmit data.     

基于Kalman滤波的UWB的TOA估计

提出了一种基于卡尔曼滤波的TOA估计算法,充分利用了卡尔曼滤波的预测功能,以预测值为中心对接收信号进行加窗处理,对此窗口内的接收信号作主成份分析得到测量值,然后对预测值进行修正.实验结果表明,与传统的TOA估计算法相比,该算法不仅使信噪比提高了约8～12 dB、均方误差降低了3～4个数量级,而且更便于实时实现.

Abstract：

In this paper,we propose a TOA estimation algorithm based on the Kalman filter in UWB systems.With the predictive function of the Kalman filter,this method processes the received signals in a window whose center is the predictive value.After we get the measured TOA from the received signals of this window by PCA,the estimated TOA can be revised.Extensive experiment results show that not only does the proposed algorithm increase the signal to noise ratio(SNR)by about 8-12 dB and decrease the mean square error by 3～4 orders compared with the traditional algorithms,it also is suitable for real-time implementation.     

Rapid Non-destructive Detection for Molds Colony of Paddy Rice Based on Near Infrared Spectroscopy

Near infrared spectrometer technology under a wavelength range of 918-1045 nm was used to rapidly detect paddy rice that was stored at 5℃, 15℃ and 25℃. A total of 121 paddy rice samples were collected from artificial infection with moulds to build the calibration models to calculate the total number colony of moulds based on the principal component regression method and multiple linear regression method. The results of statistical analysis indicated that multiple linear regression method was applicable to the detection of the total number colony of moulds. The correlation of calibration data set was 0.943. The correlation of prediction data set was 0.897. Therefore, the result showed that near infrared spectroscopy could be a useful instrumental method for determining the total number colony of moulds in paddy rice. The near infrared spectroscopy methodology could be applied for monitoring mould contamination in postharvest paddy rice during storage and might become a powerful tool for monitoring the safety of the grain.     

Research on the modeling method of soybean leaf’s structure simulation

Leaf is one of the most important organs of soybean.The modeling of soybean leaf structure is useful to research of leaf function.The paper discussed it from two aspects that were distilling method of leaf profile and establishing method of leaf simulation model.It put forward basic method of soybean leaf digital process,and successfully established simulation model of soybean leaf structure based on L-system.It also solved a critical problem in the process of establishing soybean growth simulation model.And the research had guiding significance to establishment of soybean plant model.     

Application of Interval Algorithm in Rural Power Network Planning

Rural power network planning is a complicated nonlinear optimized combination problem which based on load forecasting results, and its actual load is affected by many uncertain factors, which influenced optimization results of rural power network planning. To solve the problems, the interval algorithm was used to modify the initial search method of uncertainty load mathematics model in rural network planning. Meanwhile, the genetic/tabu search combination algorithm was adopted to optimize the initialized network. The sample analysis results showed that compared with the certainty planning, the improved method was suitable for urban medium-voltage distribution network planning with consideration of uncertainty load and the planning results conformed to the reality.     

Early Identification of Stable Transformation Events by Combined Use of Antibiotic Selection and Vital Detection of Green Fluorescent Protein （GFP） in Carrot （Daucus carota L.） Callus

Genetic transformation is a useful technique to complement conventional breeding in crop improvement. Although carrot has been a model organism for in vitro embryogenesis study, genetic transformation of carrot is still lengthy and labor intensive. An efficient transformation and detection system is desirable. Direct infection of Agrobacterium to carrot calli has provided an easy way for carrot genetic transformation. To improve the efficiency of antibiotic selection in this method, we report the combined use of an improved green-fluorescent protein, referred to as smGFP, to establish a versatile selection method for carrot callus transformation system. By combining antibiotic selection with the bright fluorescence observed in the callus tissue, we were able to easily identify stable transformants in early stage of the transformation process. In addition to the GFP expression of the callus cells, the transgenic nature of callus cells was confirmed with Southern and Western analysis. We found we can link the simplicity of carrot-callus-cell transformation, early detection of stable transformants with antibiotic selection, visualization of GFP fluorescence, and molecular analysis （Southern and Western） of callus tissue （non-photosynthetic tissue） to provide a more efficient way in identifying stable transformants at early stage of carrot transformation.