Classification of Flying Insects with high performance using improved DTW algorithm based on hidden Markov model

ABSTRACT Insects play significant role in the human life. And insects pollinate major food crops consumed in the world. Insect pests consume and destroy major crops in the world. Hence to have control over the disease and pests, researches are going on in the area of entomology using chemical, biological and mechanical approaches. The data relevant to the flying insects often changes over time, and classification of such data is a central issue. And such time series mining tasks along with classification is critical nowadays. Most time series data mining algorithms use similarity search and hence time taken for similarity search is the bottleneck and it does not produce accurate results and also produces very poor performance. In this paper, a novel classification method that is based on the dynamic time warping (DTW) algorithm is proposed. The dynamic time warping algorithm is deterministic and lacks in modeling stochastic signals. The dynamic time warping (DTW) algorithm is improved by implementing a nonlinear median filtering (NMF). Recognition accuracy of conventional DTW algorithms is less than that of the hidden Markov model (HMM) by same voice activity detection (VAD) and noise-reduction. With running spectrum filtering (RSF) and dynamic range adjustment (DRA). NMF seek the median distance of every reference of time series data and the recognition accuracy is much improved. In this research work, optical sensors are used to record the sound of insect flight, with invariance to interference from ambient sounds. The implementation of our tool includes two parts, an optical sensor to record the "sound" of insect flight, and a software that leverages on the sensor information, to automatically detect and identify flying insects.

Usefulness of a developed four-channel EGG system with running spectrum analysis

Electrogastrography (EGG) is a method of measuring action potentials on the abdomen. It is noninvasive, inexpensive and easy to measure. However, the EGG signal has a very low frequency (0.05 Hz) and an extremely low amplitude (10-100 microV). Consequently, its measured waveform is difficult to analyze and it is not yet completely understood. In this study, a four-channel EGG measurement system was built to measure the action potential of the stomach. This system was compared with the commercially available one-channel Digitrapper EGG. The 3 cpm percentages were compared between the best channel of the four-channel system and channel 1, whose electrode position was similar to the commercially available one-channel system for normal subjects. The average 3 cpm percentage of the best channel and channel 1 for preprandial measurement was 89.5% and 83.2%, respectively, and this was statistically significant (p < 0.001). Also the average 3 cpm percentage of the best channel and channel 1 for postprandial measurement was 90.4% and 76.5%, respectively, and this was statistically significant (p = 0.003). From these results, it can be concluded that a multi-channel EGG system is required for better EGG measurement.