The National Environmental Specimen Bank (NESB) has been sampling and cryogenically preserving various wildlife specimens to monitor bio-accumulations of chemical pollutants since 2010. Recently, the NESB set up a plan to develop reference materials at their facility to assure the analytical quality of and validate the analytical methods for their monitoring samples. One of the crucial characteristics of reference materials is intra- and inter-bottle homogeneity. In this study, we used ANOVA for total mercury concentrations in some samples to validate their homogeneities after milling and homogenization. We examined the intra- and inter-bottle homogeneities of two cryogenically-milled samples (Korean mussel (Mytilus coruscus) and black-tailed gull’s egg (Larus crassirostris). The variations in the total mercury concentrations were not significantly different intra- and inter-bottle (mussel: F=0.74, p=0.67; gull egg: F=1.96, p=0.10). Additionally, the relative standard deviations of the total mercury concentrations showed low values (mussel: 2.02%, gull egg: 1.78%). Therefore, the cryogenic-milling process statistically proves the homogeneity of the materials of mussels and sea gull eggs for chemical analysis for total mercury.

Due to the low localization accuracy and the requirement of special infrastructure, current LBS(Localization Based Service) is limited to show P.O.I.(Point of Interest) nearby. Improvement of IMU(Inertial Measurement Unit) based deadreckoning is presented in this paper. Additional sensors such as the magnetic compass and magnetic flux sensors are used as well as the accelerometer and the gyro for getting more information of movement. Based on the pedestrian movement, appropriate sensor information is selected and the complementary filter is used in order to enhance the accuracy of the localization.

This paper presents the use of 3 axis accelerometer for getting the gait information including the number of gaits, stride and walking distance. Travel distance is usually calculated from the double integration of the accelerometer output with respect to time; however, the accumulated errors due to the drift are inevitable. The orientation change of the accelerometer also causes error because the gravity is added to the measured acceleration. Unless three axis orientations are completely identified, the accelerometer alone does not provide correct acceleration for estimating the travel distance. We proposed a way of minimizing the error due to the change of the orientation. Pedestrian localization is implemented with the heading angle and the travel distance. Heading angle is estimated from the rate gyro and the magnetic compass measurements. The performance of the localization is presented with experimental data.

To achieve autonomous mobile robot navigation, accurate localization technique is the fundamental issue that should be addressed. In augmented reality, the position of a user is required for location-based services. This paper presents indoor localization using infrared reflective artificial landmarks. In order to minimize the disturbance to the user and to provide the ease of installation, the passive landmarks are used. The landmarks are made of coated film which reflects the infrared light efficiently. Infrared light is not visible, but the camera can capture the reflected infrared light. Once the artificial landmark is identified, the camera’s relative position/orientation is estimated with respect to the landmark. In order to reduce the number of the required artificial landmarks for a given environment, the pan/tilt mechanism is developed together with the distortion correction algorithm.

The Mobile robots are increasingly being used to perform tasks in unknown environments. The potential of robots to undertake such tasks lies in their ability to intelligently and efficiently search in an environment. An algorithm has been developed for robots which explore the environment to measure the physical properties (dust in this paper). While the robot is moving, it measures the amount of dust and registers the value in the corresponding grid cell. The robot moves from local maximum to local minimum, then to another local maximum, and repeats. To reach the local maximum or minimum, simple gradient following is used. Robust estimation of the gradient using perturbation/correlation, which is very effective when analytical solution is not available, is described. By introducing the probability of each grid cell, and considering the probability distribution, the robot doesn’t have to visit all the grid cells in the environment still providing fast and efficient sensing. The extended algorithm to coordinate multiple robots is presented with simulation results.