Abstract: In this paper, we analyze major components of activity recognition (AR) in wearable device with 9-axis sensors and sensor fusion filters. 9-axis sensors commonly include 3-axis accelerometer, 3-axis gyroscope and 3-axis magnetometer. We chose sensor fusion filters as Kalman filter and Direction Cosine Matrix (DCM) filter. We also construct sensor fusion data from each activity sensor data and perform classification by accuracy of AR using Naïve Bayes and SVM. According to the classification results, we observed that the DCM filter and the specific combination of the sensing axes are more effective for AR in wearable devices while classifying walking, running, ascending and descending.
Abstract: The conventional ceramic route was utilized to
prepare a hard magnetic powder (M-type strontium ferrite,
SrFe12O19). The stoichiometric mixture of iron oxide and strontium
carbonate were calcined at 1000oC and then fired at various
temperatures. The influence of various reaction parameters such as
mixing ratio, calcination temperature, firing temperature and firing
time on the magnetic behaviors of the synthesized magnetic powder
were investigated. The magnetic properties including Coercivity
(Hc), Magnetic saturation (Ms), and Magnetic remnance (Mr) were
measured by vibrating sample magnetometer. Morphologically the
produced magnetic powder has a dense hexagonal grain shape
structure.