The Federal Technology Transfer Act : environmental monitoring technologies opportunities.

Mode of access: Internet.

Computer-based patient monitoring systems /

Prepared under contract no. HSM 110-70-406.

The VRTC Digital Systems Laboratory. Final report.

National Highway Traffic Safety Administration, Vehicle Research Test Center, East Liberty, Ohio

An evaluation of existing tire pressure monitoring systems.

Mode of access: Internet.

Requirements for environmental monitoring assessment, and controls for nonnuclear energy demonstration projects.

Issued May 1978.

Environmental monitoring reports from the 1982 Maine Cooperative Spruce Budworm Suppression Project.

Cover title.

Forecast Systems Laboratory, Boulder, Colorado.

Mode of access: Internet.

Proposed U.S. Army Chemical Research & Development Facility : located at Chemical Systems Laboratory, Edgewood Area, Aberdeen Proving Ground, Maryland.

Cover title.

Modelling the input-output behaviour of piezoelectric structural health monitoring systems for composite plates

This paper investigates the input-output characteristics of structural health monitoring systems for composite plates based on permanently attached piezoelectric transmitter and sensor elements. Using dynamic piezoelectricity theory and a multiple integral transform method to describe the propagating and scattered flexural waves an electro-mechanical model for simulating the voltage input-output transfer function for circular piezoelectric transmitters and sensors adhesively attached to an orthotropic composite plate is developed. The method enables the characterization of all three physical processes, i.e. wave generation, wave propagation and wave reception. The influence of transducer, plate and attached electrical circuit characteristics on the voltage output behaviour of the system is examined through numerical calculations, both in frequency and the time domain. The results show that the input-output behaviour of the system is not properly predicted by the transducers' properties alone. Coupling effects between the transducers and the tested structure have to be taken into account, and adding backing materials to the piezoelectric elements can significantly improve the sensitivity of the system. It is shown that in order to achieve maximum sensitivity, particular piezoelectric transmitters and sensors need to be designed according to the structure to be monitored and the specific frequency regime of interest.

Accuracy of SRM and power tap power monitoring systems for bicycling

Purpose: Although manufacturers of bicycle power monitoring devices SRM and Power Tap (PT) claim accuracy to within 2.5%, there are limited scientific data available in support. The purpose of this investigation was to assess the accuracy of SRM and PT under different conditions. Methods: First, 19 SRM were calibrated, raced for 11 months, and retested using a dynamic CALRIG (50-1000 W at 100 rpm). Second, using the same procedure, five PT were repeat tested on alternate days. Third, the most accurate SRM and PT were tested for the influence of cadence (60, 80, 100, 120 rpm), temperature (8 and 21degreesC) and time (1 h at similar to300 W) on accuracy. Finally, the same SRM and PT were downloaded and compared after random cadence and gear surges using the CALRIG and on a training ride. Results: The mean error scores for SRM and PT factory calibration over a range of 50-1000 W were 2.3 +/- 4.9% and -2.5 +/- 0.5%, respectively. A second set of trials provided stable results for 15 calibrated SRM after 11 months (-0.8 +/- 1.7%), and follow-up testing of all PT units confirmed these findings (-2.7 +/- 0.1%). Accuracy for SRM and PT was not largely influenced by time and cadence; however. power output readings were noticeably influenced by temperature (5.2% for SRM and 8.4% for PT). During field trials, SRM average and max power were 4.8% and 7.3% lower, respectively, compared with PT. Conclusions: When operated according to manufacturers instructions, both SRM and PT offer the coach, athlete, and sport scientist the ability to accurately monitor power output in the lab and the field. Calibration procedures matching performance tests (duration, power, cadence, and temperature) are, however, advised as the error associated with each unit may vary.

The challenge of real-time automatic mapping for environmental monitoring network management

The automatic interpolation of environmental monitoring network data such as air quality or radiation levels in real-time setting poses a number of practical and theoretical questions. Among the problems found are (i) dealing and communicating uncertainty of predictions, (ii) automatic (hyper)parameter estimation, (iii) monitoring network heterogeneity, (iv) dealing with outlying extremes, and (v) quality control. In this paper we discuss these issues, in light of the spatial interpolation comparison exercise held in 2004.

RELAX:a language to address uncertainty in self-adaptive systems requirement

Self-adaptive systems have the capability to autonomously modify their behavior at run-time in response to changes in their environment. Self-adaptation is particularly necessary for applications that must run continuously, even under adverse conditions and changing requirements; sample domains include automotive systems, telecommunications, and environmental monitoring systems. While a few techniques have been developed to support the monitoring and analysis of requirements for adaptive systems, limited attention has been paid to the actual creation and specification of requirements of self-adaptive systems. As a result, self-adaptivity is often constructed in an ad-hoc manner. In order to support the rigorous specification of adaptive systems requirements, this paper introduces RELAX, a new requirements language for self-adaptive systems that explicitly addresses uncertainty inherent in adaptive systems. We present the formal semantics for RELAX in terms of fuzzy logic, thus enabling a rigorous treatment of requirements that include uncertainty. RELAX enables developers to identify uncertainty in the requirements, thereby facilitating the design of systems that are, by definition, more flexible and amenable to adaptation in a systematic fashion. We illustrate the use of RELAX on smart home applications, including an adaptive assisted living system.

RELAX:incorporating uncertainty into the specification of self-adaptive systems

Self-adaptive systems have the capability to autonomously modify their behaviour at run-time in response to changes in their environment. Self-adaptation is particularly necessary for applications that must run continuously, even under adverse conditions and changing requirements; sample domains include automotive systems, telecommunications, and environmental monitoring systems. While a few techniques have been developed to support the monitoring and analysis of requirements for adaptive systems, limited attention has been paid to the actual creation and specification of requirements of self-adaptive systems. As a result, self-adaptivity is often constructed in an ad-hoc manner. In this paper, we argue that a more rigorous treatment of requirements explicitly relating to self-adaptivity is needed and that, in particular, requirements languages for self-adaptive systems should include explicit constructs for specifying and dealing with the uncertainty inherent in self-adaptive systems. We present RELAX, a new requirements language for selfadaptive systems and illustrate it using examples from the smart home domain. © 2009 IEEE.

Implementing biodiversity action plans within environmental management systems

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