An Adaptive Pointing and Correction Algorithm Using Genetic Approach

Abstract

In this paper, we propose a new user-adaptive pointing and correction algorithm applied in the field of smart sensing. The error from the accelerometer sensor's output must be carefully managed as the sensor is more sensitive to data change compared to that of the gyroscope sensor. Thus, we minimize noise by applying the Kalman filtering to data for each axis from the accelerometer. In addition, we can also obtain effect compensating hand tremor by applying the Kalman filter to the data variation for x and y. In this study, we extract data through the Quaternion mapping process on data from the accelerometer and gyroscope. In turn, we can obtain a tilt compensation by applying the compensation algorithm with acceleration of the gravity of the extracted data. Moreover, in order to correct the inaccuracy on smart sensors due to the rapid movement of a device, we propose and integrate a genetic approach.

Social Network Visualization Method using Inherence Relationship of User Based on Cloud

“…HR; hierarchy relation) with four methods (i.e., NL [1], MAT [2], MatLink [4]) using the real social networks data [13][14][15][16]. NL denotes node-link based method, MAT denotes matrix graph based method, and MatLink denotes a hybrid method based on NL and MAT.…”