Accessibility and Usability of User-centric Web Interaction with a Unified-Ubiquitous Name-based Directory Service

Web-based information services should be evaluated for accessibility and usability with various types of Internet Web-browsing devices, interacting with web information servers including directory server. A ubiquitous name-based directory server, accessible and usable with a variety of Web-browsing devices (e.g. Internet-capable mobile phones), could be a unified center for human-centric Web interaction services as well as for business models based on personalized services. We studied the accessibility and usability in user-centric Web interaction with a unified-ubiquitous name-based directory service, as metric metadata for real-time estimation. We studied the real-time metrics in synthetic approach for comparison among different services. We show empirical results based on implementation and experiments in Korea, Japan and China.     

Two versions of architectures for dynamic implied addressing mode

The complexity of today’s embedded applications increases with various requirements such as execution time, code size or power consumption. To satisfy these requirements for performance, efficient instruction set design is one of the important issues because an instruction customized for specific applications can make better performance than multiple instructions in aspect of fast execution time, decrease of code size, and low power consumption. Limited encoding space, however, does not allow adding application specific and complex instructions freely to the instruction set architecture. To resolve this problem, conventional architectures increases free space for encoding by trimming excessive bits required beyond the fixed word length. This approach however shows severe weakness in terms of the complexity of compiler, code size and execution time. In this paper, we propose a new instruction encoding scheme based on the dynamic implied addressing mode (DIAM) to resolve limited encoding space and side-effect by trimming. We report our two versions of architectures to support our DIAM-based approach. In the first version, we use a special on-chip memory to store extra encoding information. In the second version, we replace the memory by a small on-chip buffer along with a special instruction. We also suggest a code generation algorithm to fully utilize DIAM. In our experiment, the architecture augmented with DIAM shows about 8% code size reduction and 18% speed up on average, as compared to the basic architecture without DIAM.     

Optimization of silicon solar cell fabrication based on neural network and genetic programming modeling

This study describes techniques for the cascade modeling and the optimization that are required to conduct the simulator-based process optimization of solar cell fabrication. Two modeling approaches, neural networks and genetic programming, are employed to model the crucial relation for the consecutively connected two processes in solar cell fabrication. One model (Model 1) is used to map the five inputs (time, amount of nitrogen and DI water in surface texturing and temperature and time in emitter diffusion) to the two outputs (reflectance and sheet resistance) of the first process. The other model (Model 2) is used to connect the two inputs (reflectance and sheet resistance) to the one output (efficiency) of the second process. After modeling of the two processes, genetic algorithms and particle swarm optimization were applied to search for the optimal recipe. In the first optimization stage, we searched for the optimal reflectance and sheet resistance that can provide the best efficiency in the fabrication process. The optimized reflectance and sheet resistance found by the particle swarm optimization were better than those found by the genetic algorithm. In the second optimization stage, the five input parameters were searched by using the reflectance and sheet resistance values obtained in the first stage. The found five variables such as the texturing time, amount of nitrogen, DI water, diffusion time, and temperature are used as a recipe for the solar cell fabrication. The amount of nitrogen, DI water, and diffusion time in the optimized recipes showed considerable differences according to the modeling approaches. More importantly, repeated applications of particle swarm optimization yielded process conditions with smaller variations, implying greater consistency in recipe generation.     

Motion teaching method for complex robot links using motor current

Conventional robot motion teaching methods use a teaching pendant or a motion capture device and are not the most convenient or intuitive ways to teach a robot sophisticated and fluid movements such as martial arts motions. Ideally, a robot could be set up as if it were a clothing mannequin that has light limbs and flexible yet frictional joints which can be positioned at desirable shape and hold all the positions. To do the same with a robot, an operator could pull or push the links with minor forces until the desired robot posture is attained. For this, a robot should measure the applied external force by using torque sensors at the robot joints. However, torque sensors are bulky and expensive to install in every DOF joints while keeping a compact design, which is essential to humanoid robots. In this paper, we use only motor current readings to acquire joint torques. The equations used to compensate for the effect of gravity on the joint torques and the self-calibration method to earn link parameters are presented. Additionally, kinematic restrictions can be imposed on the robot’s arms to simplify the motion teaching. Here, we teach the Kendo training robot with this method and the robot’s learnt martial art motions are demonstrated.     

Trajectory generation and control for a biped robot walking upstairs

This paper presents an effective and systematic trajectory generation method, together with a control method for enabling a biped robot to walk upstairs. The COG (center of gravity) trajectory is generated by the VHIPM (virtual height inverted pendulum mode) for the horizontal motion and by a 6th order polynomial for the vertical motion; an ankle compliance control (ACC) is also added into the robot control. The proposed methods are evaluated by simulations as well as being implemented in a robot for the performance verification. The results show that the proposed methods can generate stable motions when walking upstairs, and these can significantly reduce the zero moment point (ZMP) errors compared with other methods, enabling the robot to walk up steeper stairs.     

Performance comparison of tracking filters in terms of predicted hitting point

This article describes the performance comparison of several tracking filters from the viewpoint of gun fire control. It is common that filter performance can be represented by the RMSE of the current state. However, for the design of a gun fire control system, the performance of the tracking filter in terms of prediction is more important since the current state proceeds with a designed dynamic model to a certain future which is used for the final gun order. It is shown that the predicted results amplify the current state RMSE and can be a good measure.     

Vehicle license plate tilt correction based on the straight line fitting method and minimizing variance of coordinates of projection points

Tilt correction is a very crucial and inevitable task in the automatic recognition of the vehicle license plate (VLP). In this paper, according to the least square fitting with perpendicular offsets (LSFPO), the VLP region is fitted to a straight line. After the line slope is obtained, rotation angle of the VLP is estimated. Then the whole image is rotated for tilt correction in horizontal direction by this angle. Tilt correction in vertical direction by minimizing the variance of coordinates of the projection points is proposed. Character segmentation is performed after horizontal correction and character points are projected along the vertical direction after shear transform. Despite the success of VLP detection approaches in the past decades, a few of them can effectively locate license plate (LP), even when vehicle bodies and LPs have similar color. A common drawback of color-based VLP detection is the failure to detect the boundaries or border of LPs. In this paper, we propose a modified recursive labeling algorithm for solving this problem and detecting candidate regions. According to different colored LP, these candidate regions may include LP regions. Geometrical properties of the LP such as area, bounding box and aspect-ratio are then used for classification. Various LP images were used with a variety of conditions to test the proposed method and results are presented to prove its effectiveness.     

Non-symmetric unscented transformation with application to in-flight alignment

To overcome the extended Kalman Filter (EKF) limitation, the unscented transformation (UT) was developed as a method to propagate mean and covariance information through nonlinear transformation. However, the ordinary UT has both local and global sampling problems. In this paper, non-symmetric unscented transformation (NSUT) is proposed to solve these problems. The sigma point sets of the NSUT are non-symmetrically located with respect to the zeroth sigma point set which is equal to the prior mean. Then, the weights of the sigma points are derived by using some conditions for mean and covariance. The non-symmetric unscented Kalman filter (NSUKF) based on the sigma points and weights of the NSUT are applied to the in-flight alignment (IFA) with a large heading error. With a low cost MEMS IMU, the simulations are carried out at an S-type trajectory to analyze the performance of the proposed method.     

Fire detection based on hidden Markov models

In this paper, a novel method of real-time fire detection based on HMMs is presented. First, we present an analysis of fire characteristics that provides evidence supporting the use of HMMs to detect fire; second, we propose an algorithm for detecting candidate fire pixels that entails the detection of moving pixels, fire-color inspection, and pixels clustering. The main contribution of this paper is the establishment and application of a hidden Markov fire model by combining the state transition between fire and non-fire with fire motion information to reduce data redundancy. The final decision is based on this model which includes training and application; the training provides parameters for the HMM application. The experimental results show that the method provides both a high detection rate and a low false alarm rate. Furthermore, real-time detection has been effectively realized via the learned parameters of the HMM, since the most time-consuming components such as HMM training are performed off-line.     

Modeling and simulation of powered hip orthosis by pneumatic actuators

In this study, a simulation model for a powered hip orthosis (PHO) with air muscles to predict the gait of paraplegics is presented which can be used as a design tool for hip orthoses. Before simulation, mathematical models for a human dummy with an orthosis and a pneumatic muscle actuator were generated. For the air muscle, coefficients required were obtained by static and dynamic experiments of the air muscle and experiments for the valve controlling the air pressure. The computation was conducted on the ADAMS package together with MATLAB. Computer simulation of the flexion of hip joints by the pneumatic muscle results in similar values to those from gait analysis. With the development of a simulation model for a PHO, the gait simulation model using pneumatic muscles can be used to analyze and evaluate the characteristics and efficiency of a PHO by setting the input and boundary conditions.