On the decay rates of buffers in continuous flow lines

Consider a tandem system of machines separated by infinitely large buffers. The machines process a continuous flow of products, possibly at different speeds. The life and repair times of the machines are assumed to be exponential. We claim that the overflow probability of each buffer has an exponential decay, and provide an algorithm to determine the exact decay rates in terms of the speeds and the failure and repair rates of the machines. These decay rates provide useful qualitative insight into the behavior of the flow line. In the derivation of the algorithm we use the theory of Large Deviations.

A portable load cell for in-situ ore impact breakage testing

This paper discusses the design and characterisation of a short, and hence portable impact load cell for in-situ quantification of ore breakage properties under impact loading conditions. Much literature has been published in the past two decades about impact load cells for ore breakage testing. It has been conclusively shown that such machines yield significant quantitative energy-fragmentation information about industrial ores. However, documented load cells are all laboratory systems that are not adapted for in-situ testing due to their dimensions and operating requirements. The authors report on a new portable impact load cell designed specifically for in-situ testing. The load cell is 1.5 m in height and weighs 30 kg. Its physical and operating characteristics are detailed in the paper. This includes physical dimensions, calibration and signal deconvolution. Emphasis is placed on the deconvolution issue, which is significant for such a short load cell. Finally, it is conclusively shown that the short load cell is quantitatively as accurate as its larger laboratory analogues. (C) 2062 Elsevier Science B.V. All rights reserved.

Checklist of health promotion environments at worksites (CHEW): Development and measurement characteristics

Purpose. Health promotion policy frameworks, recent theorizing, and research all emphasize understanding and mobilizing environmental influences to change particular health-related behaviors in specific settings. The workplace is a key environmental setting. The Checklist of Health Promotion Environments at Worksites (CHEW) was designed as a direct observation instrument to assess characteristics of worksite environments that are known to influence health-related behaviors. Methods. The CHEW is a 112-item checklist of workplace environment features hypothesized to be associated, both positively and negatively, with physical activity, healthy eating, alcohol consumption, and smoking. The three environmental domains assessed are (1) physical characteristics of the worksite, (2) features of the information environment, and (3) characteristics of the immediate neighborhood around the workplace. The conceptual rationale and development studies for the CHEW are described, and data from observational studies of 20 worksites are reported. Results. The data on CHEW-derived environmental attributes showed generally good reliability and identified meaningful sets of variables that plausibly may influence health-related behaviors. With the exception of one information environment attribute, intraclass correlation coefficients ranged from 0.80 to 1.00. Descriptive statistics on selected physical and information environment characteristics indicated that vending machines, showers, bulletin boards, and signs prohibiting smoking were common across worksites. Bicycle racks, visible stairways, and signs related to alcohol consumption, nutrition, and health. promotion were relatively uncommon. Conclusions. These findings illustrate the types of data on environmental attributes that can be derived, their relevance for program planning, and how they can characterize variability across worksites. The CHEW is a promising observational measure that has the potential to assess environmental influences on health behaviors and to evaluate workplace health promotion programs.

Randomized comparison of the quality of realtime fetal ultrasound images transmitted by ISDN and by IP videoconferencing

We compared the quality of realtime fetal ultrasound images transmitted using ISDN and IP networks. Four experienced obstetric ultrasound specialists viewed standard recordings in a randomized trial and rated the appearance of 30 fetal anatomical landmarks, each on a seven-point scale. A total of 12 evaluations were performed for various combinations of bandwidths (128, 384 or 768 kbit/s) and networks (ISDN or IF). The intraobserver coefficient of variation was 2.9%, 5.0%, 12.7% and 14.7% for the four observers. The mean overall ratings by each of the four observers were 4.6, 4.8, 5.0 and 5.3, respectively (a rating of 4 indicated satisfactory visualization and 7 indicated as good as the original recording). Analysis of variance showed that there were no significant interobserver variations nor significant differences in the mean scores for the different types of videoconferencing machines used. The most significant variable affecting the mean score was the bandwidth used. For ISDN, the mean score was 3.7 at 128 kbit/s, which was significantly worse than the mean score of 4.9 at 384 kbit/s, which was in turn significantly worse than the mean score of 5.9 at 768 kbit/s. The mean score for transmission using IP was about 0.5 points lower than that using ISDN across all the different bandwidths, but the differences were not significant. It appears that IP transmission in a private (non-shared) network is an acceptable alternative to ISDN for fetal tele-ultrasound and one deserving further study.

Learning the dynamics of embedded clauses

Recent work by Siegelmann has shown that the computational power of recurrent neural networks matches that of Turing Machines. One important implication is that complex language classes (infinite languages with embedded clauses) can be represented in neural networks. Proofs are based on a fractal encoding of states to simulate the memory and operations of stacks. In the present work, it is shown that similar stack-like dynamics can be learned in recurrent neural networks from simple sequence prediction tasks. Two main types of network solutions are found and described qualitatively as dynamical systems: damped oscillation and entangled spiraling around fixed points. The potential and limitations of each solution type are established in terms of generalization on two different context-free languages. Both solution types constitute novel stack implementations - generally in line with Siegelmann's theoretical work - which supply insights into how embedded structures of languages can be handled in analog hardware.