Partial consensus of identical feedforward dynamic systems with input saturations

This paper studies the partial consensus problem for identical feedforward dynamic systems with input saturations. We construct two consensus protocols using the partial‐state information and full‐state information, respectively. Applying a change of coordinates, feedforward system is transformed into the block diagonal form. Then, by utilizing the bounded real lemma and small gain theorem, we solve the partial consensus problem, and the existence of each protocol is derived. Copyright © 2015 John Wiley & Sons, Ltd.     

User Satisfaction with Tablet PC Features

Previous studies of tablet personal computers have concentrated on their use in education and healthcare. The current study focused instead on personal usage, investigating how satisfied users are with their own tablets after having used them in their daily lives. The objective was to identify the major features for tablets and to investigate how form factors affect the preference of functions by performing a comparison of iPad1 and Galaxy Tab. Also, gender and ethnicity were analyzed to determine whether they influence satisfaction with the devices. For e‐mail and web browsing functions, users’ ratings showed more satisfaction with the iPad1 since it has a larger display; for the e‐book reader function, users indicated higher satisfaction with the Galaxy Tab. Male users evaluated their devices by the function itself, whereas female users were mainly concerned with aesthetic aspects. Koreans indicated that they were less satisfied with their tablets than were other ethnic groups.     

Band selection for hyperspectral images using probabilistic memetic algorithm

Band selection plays an important role in identifying the most useful and valuable information contained in the hyperspectral images for further data analysis such as classification, clustering, etc. Memetic algorithm (MA), among other metaheuristic search methods, has been shown to achieve competitive performances in solving the NP-hard band selection problem. In this paper, we propose a formal probabilistic memetic algorithm for band selection, which is able to adaptively control the degree of global exploration against local exploitation as the search progresses. To verify the effectiveness of the proposed probabilistic mechanism, empirical studies conducted on five well-known hyperspectral images against two recently proposed state-of-the-art MAs for band selection are presented.     

Evaluating the Wisdom of Strangers: The Perceived Credibility of Online Consumer Reviews on Yelp

This study examined the effects of review valence, the reviewer profile, and the receiver's familiarity with the platform (user/nonuser) on the perceived credibility of a review on Yelp.com and on the receiver's attitude toward the reviewed object. The results demonstrated a difference in cue‐taking between users and nonusers. For users, there was an interaction effect of 2 profile cues (number of friends and number of reviews) on competence. Users interpreted the cues in combination, whereas non‐users were not influenced by them. The friends × reviews × platform familiarity interaction indirectly affected attitude through competence. Further, review valence was positively associated with perceived credibility and attitude. The findings support and extend the social information processing theory and cue combination literature.     

An interactive lung field segmentation scheme with automated capability

Feasible clinical application of any automated segmenting methodology demands more than just accuracy. Amendment to the automated delineation is necessary when the algorithm fails, however, integrated solution to such a scenario is largely absent in literature. Hence in this survey we devised an architecture that does both the automated and interactive lung field localizations using a single segmenting engine—random walker algorithm—so that intuitive amendment is only necessary when the automated generated delineation is unsatisfactory. The algorithm proceeds by first extracting 18 intensity profiles running horizontally, each of them equally spacing apart, and in each intensity profile three extreme points denoting the two lungs and the esophagus are determined through profile matching. This done, the algorithm removes profiles that do not intersect with the lung, and the rest of the extreme points are plugged into random walker algorithm to perform segmentation. The achieved accuracy in localization by the above was 0.8875 in terms of overlap measure (the maximum value for this parameter is 1) over 341 images. In the case where unsatisfactory delineation prompts amendment necessary, the user can interactively segment the lung by just a shift on some of the previous-determined points to the desired locations, and random walker algorithm is run again with the amended input. By such a fusion, the benefits of both the automated and interactive segmentation are shared in a single architecture.     

Measurement feedback control for a class of feedforward nonlinear systems

We propose a measurement feedback controller for a class of feedforward nonlinear systems under sensor noise. The sensor noise has unknown magnitude, frequency, and phase. Our proposed controller is coupled with a low‐pass filter in such a way that the sensor noise is attenuated. We show that the controlled system results in bounded states whose ultimate bounds are inversely proportional to the minimum frequency of the sensor noise. Our result is further generalized to work in a case where the sensor noise is only required to have a Fourier transform with finite energy. Moreover, if the sensor noise enters only at partial states, depending on the location of the sensor noise, the ultimate bounds of the particular states can be made arbitrarily small via the gain factor of the controller. Copyright © 2012 John Wiley & Sons, Ltd.     

Semi-online scheduling problems on a small number of machines

We consider the semi-online parallel machine scheduling problem of minimizing the makespan given a priori information: the total processing time, the largest processing time, the combination of the previous two or the optimal makespan. We propose a new algorithm that can be applied to the problem with the known total or largest processing time and prove that it has improved competitive ratios for the cases with a small number of machines. Improved lower bounds of the competitive ratio are also provided by presenting adversary lower bound examples.