Feature Extraction and Random Forest to Identify Sheep Behavior from Accelerometer Data

Sensor technologies play an essential part in the agricultural community and many other scientific and commercial communities. Accelerometer signals and Machine Learning techniques can be used to identify and observe behaviours of animals without the need for an exhaustive human observation which is labour intensive and time consuming. This study employed random forest algorithm to identify grazing, walking, scratching, and inactivity (standing, resting) of 8 Hebridean ewes located in Cheshire, Shotwick in the UK. We gathered accelerometer data from a sensor device which was fitted on the collar of the animals. The selection of the algorithm was based on previous research by which random forest achieved the best results among other benchmark techniques. Therefore, in this study, more focus was given to feature engineering to improve prediction performance. Seventeen features from time and frequency domain were calculated from the accelerometer measurements and the magnitude of the acceleration. Feature elimination was utilised in which highly correlated ones were removed, and only nine out of seventeen features were selected. The algorithm achieved an overall accuracy of 99.43% and a kappa value of 98.66%. The accuracy for grazing, walking, scratching, and inactive was 99.08%, 99.13%, 99.90%, and 99.85%, respectively. The overall results showed that there is a significant improvement over previous methods and studies for all mutually exclusive behaviours. Those results are promising, and the technique could be further tested for future real-time activity recognition

Trades-offs between biomass use and soil cover. The case of rice-based cropping system in the lake Alaotra region of Madagascar.

International audienceFarmers in the Lake Alaotra region of Madagascar are currently evaluating a range of conservation agriculture (CA) cropping systems. Most of the expected agroecological functions of CA (weed control, erosion control and water retention) are related to the degree of soil cover. Under farmers' conditions, the grain and biomass productivity of these systems is highly variable and the biomass is used for several purposes. In this study,we measured biomass production of cover crops and crops in farmers' fields. Further, we derived relationships to predict the soil cover that can be generated for a particular quantity of mulch. We used these relationships to explore the variability of soil cover that can be generated in farmers' fields, and to estimate howmuch of the biomass can be removed for use as livestock feed,while retaining sufficient soil cover. Three different kinds of cropping systems were investigated in 91 farmers' fields. The first two cropping sequences were on the hillsides: (i) maize + pulse (Vigna unguiculata or Dolichos lablab)inyear1, followed by upland rice in year 2; (ii) the second crop sequence included several years of Stylosanthes guianensis followed by upland rice; (iii) the third crop sequence was in lowland paddy fields: Vicia villosa or D. lablab, which was followed by rice within the same year and repeated every year. The biomass available prior to rice sowing varied from 3.6 t ha−1 with S. guianensis to 7.3 t ha−1 with V. villosa. The relationship between the mulch quantity (M) and soil cover (C) was measured using digital imaging and was well described by the following equation: C = 1 − exp(−Am × M),where Am is an area-to-mass ratio with R2 > 0.99 in all cases. The calculated average soil cover varied from 56 to 97% for maize + V. unguiculata and V. villosa, respectively. In order to maintain 90% soil cover at rice sowing, the average amount of biomass of V. villosa that could be removed was at least 3 t ha−1 for three quarters of the fields. This quantity was less for other annual or biennial cropping systems. On average the V. villosa aboveground biomass contained 236 kg N ha−1. The study showed that for the conditions of farmers ofMalagasy, the production and conservation of biomass is not always sufficient to fulfil all the above-cited agroecological functions of mulch. Inventory of the soil cover capacity for different types of mulch may help farmers to decide how much biomass they canremove from the field

Ab initio of magnetic properties of cobalt and tetracobalt nitride Co4N

Magnetic properties and bonding analyses of perovskite structure Co4N nitride have been investigated within density functional theory using both pseudopotential and all electron methods. In the same time, the structural and magnetic stabilities of pure cobalt in hexagonal close packed (hcp), face centered cubic (fcc), and body centered cubic structures are reviewed..