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- W2780996860 abstract "Soil digging is an event which is very crucial problem in the forest; the soil digging identification is very difficult in the presence of forest clutter including flowing streams, strong wind storms, and rain. Acoustic signals were collected using a microphone. The signal is processed by a mote. Digging distance is changed to obtain different signal strengths. Digging was done in different types of soils and in different soil conditions (wet and dry grounds). The recorded signals were analyzed in time and frequency domains. After analysis of signals, 10 dominant parameters were calculated (identified) in order to recognize the event. Three algorithms—K means clustering, linear discriminant analysis (LDA), and distance-based approach—were used for identification of signal. The algorithms were also tested with similar type of acoustic signals such as wood cutting by axe and hammering on soft wood in order to reduce false results." @default.
- W2780996860 created "2018-01-05" @default.
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- W2780996860 date "2017-12-29" @default.
- W2780996860 modified "2023-10-01" @default.
- W2780996860 title "Identification of Soil Digging Using Acoustic Pattern Recognition" @default.
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- W2780996860 doi "https://doi.org/10.1007/978-981-10-7122-5_5" @default.
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