Routing with locality in partitioned-bus meshes

We show that adding partitioned-buses (as opposed to long buses that span an entire row or column) to ordinary meshes can reduce the routing time by approximately one-third for permutation routing with locality. A matching time lower bound is also proved. The result can be generalized to multi-packet routing.published_or_final_versio

Efficient computations on meshes with express links

At head of title: Computer science publication.Cover title.Includes bibliographical references (p. 10-12).published_or_final_versio

Hierarchical motion estimation based on visual patterns for video coding

Block matching algorithms(BMAs) are often employed for motion estimation(ME) in video coding. Most conventional fast BMAs treat the ME problem as an optimization problem and suffer heavily from the problem of being trapped at local minima. The full search algorithm(FS), on the other hand, is very time-consuming. Few of them makes use of the information inherent in the images explicitly. We propose a new ME algorithm which can reduce the search range while guaranteeing global optimality in most cases, making use of the edge features. Microblock visual patterns are designed to extract edge information to guide block matching: searching is only carried out at places where the real match most likely happens. The motion field subsampling technique is further employed to get a hierarchical algorithm, which can further double the speed. The proposed algorithms obtain speeds about ten times faster than that of FS with comparable prediction quality.published_or_final_versio

Emotional Labor and Occupational Well-Being: Latent Profile Transition Analysis Approach

This study used the latent profile transition analysis (LPTA) to analyze whether emotional labor profiles change across time and how these profiles relate to occupational well-being (i.e., job satisfaction, quality of work life, psychological distress, and work–family conflict). A total of 155 full-time Chinese employees completed the questionnaire survey at two time points. Three latent profiles were identified at Time 1 and the same profiles were replicated at Time 2. We determined that the majority of the participants retained the original profiles. Lastly, occupational well-being differed significantly across the identified profiles. The limitations and implications of this study were also provided

Validation of the reasons for gambling questionnaire (RGQ) in a British population survey

Introduction. The aim of the study is to validate the five-dimensional structure of the Reasons for Gambling Questionnaire (RGQ) and to test the differences between different types of gamblers (i.e., offline gamblers who gambled in-person only vs.mixed-mode gamblers who gambled both online and offline) on the five dimensions of the RGQ. Methods. Data from the 2010 British Gambling Prevalence Survey (BGPS) were used. The analysed data comprised 5,677 individuals (52.7% female; mean age=47.64 years; SD=17.82). Confirmatory factor analysis and independent-samples t-tests were applied. Results. The five-dimensional structure of the RGQ wasconfirmed in the general sample and among gender and age subgroups. Furthermore, mixed-mode gamblers (MMGs) who gambled both online and offline had higher scores for enhancement, recreation and money motives than offline gamblers that gambled in-person only (IPGs). In addition among males, there was a significant difference in the scores for enhancement and recreation motives across MMGs and IPGs. Among past-year gamblers aged 16-34 years, MMGs had higher scores for enhancement, recreational and monetary motives than IPGs whilst among past-year gamblers aged 35-55years, MMGs had higher scores for enhancement and recreational motives than IPGs. Conclusions. The results are consistent with a previous test of the RGQ and the findings indicate that the RGQis a valid instrument to assess gambling motives among the general population

On maximum-likelihood estimation of the differencing parameter of fractionally integrated noise with unknown mean

There are two approaches to maximum likelihood (ML) estimation of the parameter of fractionally-integrated noise: approximate frequency-domain ML (Fox and Taqqwu, 1986) and exact time-domain ML (Solwell, 1990a). If the mean of the process is known, then a clear finite-sample mean-squared error (MSE) ranking of the estimators emerges: the exact time-domain estimator has smaller MSE. We show in this paper, however, that the finite-sample efficiency of approximate frequency-domain ML relative to exact time-domain ML rises dramatically when the mean result is unknown and instead must be estimated. The intuition for our result is straightforward: The frequency-domain ML estimator is invariant to the true but unknown mean of the process, while the time-domain ML estimator is not. Feasible time-domain estimation must therefore be based upon de-meaned data, but the long memory associated with fractional integration makes precise estimation of the mean difficult. We conclude that the frequency-domain estimator is an attractive and efficient alternative for situations in which large sample sizes render time-domain estimation impractical.Time-series analysis

A technique for process preemption in the transputer

Includes bibliographical references (p. 14-15).Cover title.At head of title: Computer science publication.published_or_final_versio