Application of the Strain Index in multiple task jobs

Six different methods to calculate the Strain Index (SI) scores for jobs with multiple forces/tasks were developed. Exposure data of 733 subjects from 12 different worksites were used to calculate these SI scores. Results show that using different SI computation methods could result in different SI scores, hence different risk level classifications. However, some simpler methods generated SI scores were comparable to the more complicated composite SI method. Despite differences in the scores between the six different SI computation methods, Spearman rank-order correlation coefficients of 0.61-0.97 were found between the methods. With some confidence, ergonomic practitioners may use simpler methods, depending on their specificity requirement in job evaluations and available resources. Some SI computation methods may tend to over-estimate job risk levels, while others may tend to under-estimate job risk levels, due to different ways used in obtaining the various SI parameters and computations.     

Robust resource allocation in a cluster based imaging system

Recently there has been an increased demand for imaging systems in support of high-speed digital printing. The required increase in performance in support of such systems can be accomplished through an effective parallel execution of image processing applications in a distributed cluster computing environment. The output of the system must be presented to a raster based display at regular intervals, effectively establishing a hard deadline for the production of each image. Failure to complete a rasterization task before its deadline will result in an interruption of service that is unacceptable. The goal of this research was to derive a metric for measuring robustness in this environment and to design a resource allocation heuristic capable of completing each rasterization task before its assigned deadline, thus, preventing any service interruptions. We present a mathematical model of such a cluster based raster imaging system, derive a robustness metric for evaluating heuristics in this environment, and demonstrate using the metric to make resource allocation decisions. The heuristics are evaluated within a simulation of the studied raster imaging system. We clearly demonstrate the effectiveness of the heuristics by comparing their results with the results of a resource allocation heuristic commonly used in this type of system.     

An intelligent terrain-based navigation system for planetary rovers

A fuzzy logic framework for onboard terrain analysis and guidance towards traversable regions. An onboard terrain-based navigation system for mobile robots operating on natural terrain is presented. This system utilizes a fuzzy-logic framework for onboard analysis of the terrain and develops a set of fuzzy navigation rules that guide the rover toward the safest and the most traversable regions. The overall navigation strategy deals with uncertain knowledge about the environment and uses the onboard terrain analysis to enable the rover to select easy-to-traverse paths to the goal autonomously. The navigation system is tested and validated with a set of physical rover experiments and demonstrates the autonomous capability of the system     

Two posture analysis approaches and their application in a modified rapid upper limb assessment evaluation

This paper presents two posture risk quantification methods: first, an event-based method where the most common and the worst postures are estimated in a task; second, a time-based method where posture distributions are calculated from random samples of observed postures in the task. A 'click-on-screen' posture data entry method was developed for the time-based posture analysis method to make the observation process easier and to reduce possible posture categorization bias. Both methods were used to quantify various work posture parameters among a study cohort of 733 subjects from a prospective epidemiological study of upper extremity musculoskeletal disorders. Composite posture indices using a modified Rapid Upper Limb Assessment (RULA) method were also computed using data obtained by the two posture analysis methods. Results showed that both methods were able to distinguish jobs with large differences in certain posture measures. However, they did not produce the same results and could not be used interchangeably. Risk evaluation criteria should be developed, either for specific posture parameters or as a composite index, with a well-defined postural analysis method, so that users can follow exact procedures and obtain comparable results. The event-based method is easy to use and may suit practitioners better, while the time-based method adds more information to the measurement and may suit users who want more detailed information about posture exposure.     

Flexible Image-Based Photometric Reconstruction using Virtual Light Sources

Photometric reconstruction is the process of estimating the illumination and surface reflectance properties of an environment, given a geometric model of the scene and a set of photographs of its surfaces. For mixed-reality applications, such data is required if synthetic objects are to be correctly illuminated or if synthetic light sources are to be used to re-light the scene. Current methods of estimating such data are limited in the practical situations in which they can be applied, due to the fact that the geometric and radiometric models of the scene which are provided by the user must be complete, and that the position (and in some cases, intensity) of the light sources must also be specified a-priori. In this paper, a novel algorithm is presented which overcomes these constraints, and allows photometric data to be reconstructed in less restricted situations. This is achieved through the use of virtual light sources which mimic the effect of direct illumination from unknown luminaires, and indirect illumination reflected off unknown geometry. The intensity of these virtual light sources and the surface material properties are estimated using an iterative algorithm which attempts to match calculated radiance values to those observed in photographs. Results are presented for both synthetic and real scenes that show the quality of the reconstructed data and its use in off-line mixed-reality applications.     

Free radicals in γ-irradiated PETN

An EPR investigation of-irradiated PETN (Pentaerythritol Tetranitrate) was conducted. Low temperature irradiation accumulates at least two different radicals. The more stable radical is the NO₂ radical presumably produced by photon cleavage of the NO₂ groups and/or by radical reactions in excited states resulting in detached NO₂. The spectrum of the more reactive radical is obtained by computer substraction. Decay kinetics are proposed for the NO₂ and the unknown highly reactive radical.     

Groundwater temperature and degassing in the Mad River subwatershed of Lake Huron

Groundwater was measured 70 times in two years at 10 sites as it flowed 50 m over an accumulation of travertine (CaCO₃) before reaching the Mad River. At source, the groundwater was relatively cool (6.77 ± 2.89 °C), slightly acidic ( pH 6.86 ± 0.22), and had a moderately high specific conductivity (606 ± 51 μS). Degassing was assessed from increases in pH, and CaCO₃ deposition was assessed from decreasing conductivity. After flowing over the experimental site, degassing had increased pH to 8.04 ± 0.16 (P < 0.001), which was similar to river water (pH 8.07 ± 0.30). Concurrently, CaCO₃ deposition decreased conductivity to 577 ± 43 μS (P < 0.001) but this was still higher (P < 0.001) than river water (494 ± 72). Seasonal changes in air temperature affected the rate of degassing. The pH was correlated with air temperature (r = 0.15, P < 0.001) while conductivity was correlated with pH (r = − 0.27, P < 0.001), but no direct relationship of air temperature with conductivity was detected. Groundwater entering the river after atmospheric exposure had a fairly constant temperature (7.05 ± 1.22 °C) despite seasonal changes in air temperature, thus warming the river in winter (up to day 100 and after day 300) and cooling it in summer (from days 140 to 260). Degassing and CaCO₃ deposition in springs without travertine was similar to that observed in the study stream over travertine. These groundwater inflows provide favorable pH and temperature conditions for brook trout.     

Probabilistic resource allocation in heterogeneous distributed systems with random failures

The problem of finding efficient workload distribution techniques is becoming increasingly important today for heterogeneous distributed systems where the availability of compute nodes may change spontaneously over time. Resource-allocation policies designed for such systems should maximize the performance and, at the same time, be robust against failure and recovery of compute nodes. Such a policy, based on the concepts of the Derman–Lieberman–Ross theorem, is proposed in this work, and is applied to a simulated model of a dedicated system composed of a set of heterogeneous image processing servers. Assuming that each image results in a “reward” if its processing is completed before a certain deadline, the goal for the resource allocation policy is to maximize the expected cumulative reward. An extensive analysis was done to study the performance of the proposed policy and compare it with the performance of some existing policies adapted to this environment. Our experiments conducted for various types of task-machine heterogeneity illustrate the potential of our method for solving resource allocation problems in a broad spectrum of distributed systems that experience high failure rates.     

Model checking agent programming languages

In this paper we describe a verification system for multi-agent programs. This is the first comprehensive approach to the verification of programs developed using programming languages based on the BDI (belief-desire-intention) model of agency. In particular, we have developed a specific layer of abstraction, sitting between the underlying verification system and the agent programming language, that maps the semantics of agent programs into the relevant model-checking framework. Crucially, this abstraction layer is both flexible and extensible; not only can a variety of different agent programming languages be implemented and verified, but even heterogeneous multi-agent programs can be captured semantically. In addition to describing this layer, and the semantic mapping inherent within it, we describe how the underlying model-checker is driven and how agent properties are checked. We also present several examples showing how the system can be used. As this is the first system of its kind, it is relatively slow, so we also indicate further work that needs to be tackled to improve performance.