Comparative study on multibody vehicle dynamics models based on subsystem synthesis method using Cartesian and joint coordinates

The subsystem synthesis method has been developed in order to improve computational efficiency for a multibody vehicle dynamics model. Using the subsystem synthesis method, equations of motion of the base body and each subsystem can be solved separately. In the subsystem synthesis method, various coordinate systems can be used and various integration methods can be applied in each subsystem, as long as the effective mass matrix and the effective force vector are properly produced. In this paper, comparative study has been carried out for the subsystem synthesis method with Cartesian coordinates and with joint relative coordinates. Two different integration methods such as an explicit integrator and an explicit implicit integrator are employed. In order to see the accuracy and computational efficiency from the different models based on the different coordinate systems and different integration methods, a rough terrain run simulations has been carried out with a 6 × 6 off-road multibody vehicle model.

Development of a Concentration Measurement Technique for Steady State Solid-liquid Mixing using a Neural Network

A measurement technique that can measure the concentration of the solid particles in liquid flow was developed.The measurement system consists of a color camera and three LCD displays.The solid particles were put at the bottom of a cylindrical mixing tank in which JetA1 oil was filled.Transient mixing of the solid particles was performed by rotating a propeller type agitator with three different rotation speed(500,600,700 r/min).Mixing state was visualized by the LCD displays and a color camcorder.The color intensity of the glass particles changes with their concentration.The color information was decoded into three principle colors R,G,and B so that,the calibration curve of color-to-concentration was performed using these information.A neural network was used for this calibration.The transient concentration field of the solid particles was quantitatively visualized.

Towards a respondent-preferred k_i-anonymity model

Recently, privacy concerns about data collection have received an increasing amount of attention. In data collection process, a data collector （an agency） assumed that all respondents would be comfortable with submitting their data if the published data was anonymous. We believe that this assumption is not realistic because the increase in privacy concerns causes some re- spondents to refuse participation or to submit inaccurate data to such agencies. If respondents submit inaccurate data, then the usefulness of the results from analysis of the collected data cannot be guaranteed. Furthermore, we note that the level of anonymity （i.e., k-anonymity） guaranteed by an agency cannot be verified by respondents since they generally do not have access to all of the data that is released. Therefore, we introduce the notion of ki-anonymity, where ki is the level of anonymity preferred by each respondent i. Instead of placing full trust in an agency, our solution increases respondent confidence by allowing each to decide the preferred level of protection. As such, our protocol ensures that respondents achieve their preferred kranonymity during data collection and guarantees that the collected records are genuine and useful for data analysis.