Robust finite-time boundedness of multi-agent systems subject to parametric uncertainties and disturbances

In this paper, we consider finite-time control problems for linear multi-agent systems subject to exogenous constant disturbances and impulses. Some sufficient conditions are obtained to ensure the finite-time boundedness of the multi-agent systems, which could be then reduced to a feasibility problem involving linear matrix inequalities. Numerical examples are given to illustrate the results.     

Economic lot sizing in a production system with random demand

An extended economic production quantity model that copes with random demand is developed in this paper. A unique feature of the proposed study is the consideration of transient shortage during the production stage, which has not been explicitly analysed in existing literature. The considered costs include set-up cost for the batch production, inventory carrying cost during the production and depletion stages in one replenishment cycle, and shortage cost when demand cannot be satisfied from the shop floor immediately. Based on renewal reward process, a per-unit-time expected cost model is developed and analysed. Under some mild condition, it can be shown that the approximate cost function is convex. Computational experiments have demonstrated that the average reduction in total cost is significant when the proposed lot sizing policy is compared with those with deterministic demand.     

Geostatistical downscaling of AMSR2 precipitation with COMS infrared observations

This article presents a geostatistical approach for downscaling precipitation products from passive microwave satellites with geostationary Meteorological Satellite observations. More precisely, the Advanced Microwave Scanning Radiometer 2 (AMSR2) precipitation (daily level 3 product) with 0.25° spatial resolution and the Communication, Ocean and Meteorological Satellite (COMS) infrared (IR) data with 5 km spatial resolution were used for the downscaling experiment over the Korean peninsula. Brightness temperature data observed at COMS IR 1 and water vapour channels were incorporated for downscaling via area-to-point residual Kriging with non-linear regression. The evaluation results with densely sampled Automatic Weather Station data revealed that incorporating the COMS IR observations with the AMSR2 precipitation showed similar error statistics to those of the AMSR2 precipitation because of the limitations of IR observations themselves and the inherent errors of the AMSR2 precipitation product over land. However, the area-based evaluation using information entropy indicated that incorporating the COMS observations resulted in more detailed spatial variation in the final product than direct downscaling of the AMSR2 precipitation. In addition, local precipitation patterns could be captured when there were regions with missing precipitation values in the AMSR2 product. Consequently, the downscaling result is useful for understanding the local precipitation patterns with an accuracy similar to that provided by microwave satellite observations. It is also suggested that the spatial variability in the downscaling result and errors in input low-resolution data should be considered when downscaling coarse resolution data using fine resolution auxiliary variables.     

The role of goal awareness and information technology self-efficacy on job satisfaction of healthcare system users

This paper investigates the influence of goal awareness and IT self-efficacy on job satisfaction based on the motivation sequence model, goal-setting theory, and social cognitive theory. Using a large-scale field survey of healthcare enterprise resource planning (ERP) system users (n?=?352), this study investigates these relationships and provides important insight to healthcare ERP system researchers and managers. Both goal awareness and IT self-efficacy influence positive job satisfaction of healthcare ERP system users, as expected. Furthermore, the influence of goal awareness is stronger when the role of ERP systems is highly perceived for decision-making of the job. There was no interaction effect between goal awareness and IT self-efficacy in the post hoc analysis. The model is significantly supported by the empirical test with the large number of field data from healthcare ERP system users in the healthcare company. Practical and academic implications are discussed in the paper.     

Consistent color and detail transfer from multiple source images for video and images

In this paper, we propose a method to jointly transfer the color and detail of multiple source images to a target video or image. Our method is based on a probabilistic segmentation scheme using Gaussian mixture model (GMM) to divide each source image as well as the target video frames or image into soft regions and determine the relevant source regions for each target region. For detail transfer, we first decompose each image as well as the target video frames or image into base and detail components. Then histogram matching is performed for detail components to transfer the detail of matching regions from source images to the target. We propose a unified framework to perform both color and detail transforms in an integrated manner. We also propose a method to maintain consistency for video targets, by enforcing consistent region segmentations for consecutive video frames using GMM-based parameter propagation and adaptive scene change detection. Experimental results demonstrate that our method automatically produces consistent color and detail transferred videos and images from a set of source images.     

Scale‐aware Structure‐Preserving Texture Filtering

This paper presents a novel method to enhance the performance of structure‐preserving image and texture filtering. With conventional edge‐aware filters, it is often challenging to handle images of high complexity where features of multiple scales coexist. In particular, it is not always easy to find the right balance between removing unimportant details and protecting important features when they come in multiple sizes, shapes, and contrasts. Unlike previous approaches, we address this issue from the perspective of adaptive kernel scales. Relying on patch‐based statistics, our method identifies texture from structure and also finds an optimal per‐pixel smoothing scale. We show that the proposed mechanism helps achieve enhanced image/texture filtering performance in terms of protecting the prominent geometric structures in the image, such as edges and corners, and keeping them sharp even after significant smoothing of the original signal.     

Humanoid Posture Selection for Reaching Motion and a Cooperative Balancing Controller

Our goal in this research was to develop a motion planning algorithm for a humanoid to enable it to remove an object that is blocking its path. To remove an object in its path, a humanoid must be able to reach it. Simply stretching its arms, which in a humanoid are shorter than its body and legs, is not sufficient to reach an object located at some distance away or on the ground. Therefore, reachability has to be ensured by a combination of motions that include kneeling and orienting the pelvis. However, many posture selection options exist because of the redundancy of a humanoid. In this research, we focused on the optimization of the posture of a humanoid that is reaching toward a point. The posture selected depends on the initial posture, the location of the point, and the desired manipulability of the humanoid’s arms. A cooperative balancing controller ensures the stability of the reaching motion. In this paper, we propose an algorithm for reaching posture selection and a balancing controller for humanoids, and we present the results of several experiments that confirm the effectiveness of the proposed algorithm and controller.     

Balancing of humanoid robot using contact force/moment control by task-oriented whole body control framework

Balancing control of humanoid robots is of great importance since it is a necessary functionality not only for maintaining a certain position without falling, but also for walking and running. For position controlled robots, the for-ce/torque sensors at each foot are utilized to measure the contact forces and moments, and these values are used to compute the joint angles to be commanded for balancing. The proposed approach in this paper is to maintain balance of torque-controlled robots by controlling contact force and moment using whole-body control framework with hierarchical structure. The control of contact force and moment is achieved by exploiting the full dynamics of the robot and the null-space motion in this control framework. This control approach enables compliant balancing behavior. In addition, in the case of double support phase, required contact force and moment are controlled using the redundancy in the contact force and moment space. These algorithms are implemented on a humanoid legged robot and the experimental results demonstrate the effectiveness of them.