92 resultados para Sensor noise


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While building provides shelter for human being, the previous models for assessing the intelligence of a building seldom consider the responses of occupants. In addition, the assessment is usually conducted by an authority organization on a yearly basis, thus can seldom provide timely assistance for facility manager to improve his daily facility maintenance performance. By the extending the law of entropy into the area of intelligent building, this paper demonstrate that both energy consumption and the response of occupants are important when partially assessing the intelligence of a building. This study then develops a sensor based real time building intelligence (BI) assessment model. An experimental case study demonstrates how the model can be implemented. The developed model can address the two demerits of the previous BI assessment model.

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Background: Inadvertent drilling on the ossicular chain is one of the causes of sensorineural hearing loss (HL) that may follow tympanomastoid surgery. A high-frequency HL is most frequently observed. It is speculated that the HL is a result of vibration of the ossicular chain resembling acoustic noise trauma. It is generally considered that using a large cutting burr is more likely to cause damage than a small diamond burr. Aim: The aim was to investigate the equivalent noise level and its frequency characteristics generated by drilling onto the short process of the incus in fresh human temporal bones. Methods and Materials: Five fresh cadaveric temporal bones were used. Stapes displacement was measured using laser Doppler vibrometry during short drilling episodes. Diamond. and cutting burrs of different diameters were used. The effect of the drilling on stapes footplate displacement was compared with that generated by an acoustic signal. The equivalent noise level (dB sound pressure level equivalent [SPL eq]) was thus calculated. Results: The equivalent noise levels generated ranged from 93 to 125 dB SPL eq. For a 1-mm cutting burr, the highest equivalent noise level was 108 dB SPL eq, whereas a 2.3-mm cutting burr produced a maximal level of 125 dB SPL eq. Diamond burrs generated less noise than their cutting counterparts, with a 2.3-mm diamond burr producing a highest equivalent noise level of 102, dB SPL eq. The energy of the noise increased at the higher end of the frequency spectrum, with a 2.3-mm cutting burr producing a noise level of 105 dB SPL eq at 1 kHz and 125 dB SPL eq at 8 kHz. In contrast, the same sized diamond burr produced 96 dB SPL eq at 1 kHz and 99 dB at 8 kHz. Conclusion:This study suggests that drilling on the ossicular chain can produce vibratory force that is analogous with noise levels known to produce acoustic trauma. For the same type of burr, the larger the diameter, the greater the vibratory force, and for the same size of burr, the cutting burr creates more vibratory force than the diamond burr. The cutting burr produces greater high-frequency than lower-frequency vibratory energy.

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This article presents a prototype model based on a wireless sensor actuator network (WSAN) aimed at optimizing both energy consumption of environmental systems and well-being of occupants in buildings. The model is a system consisting of the following components: a wireless sensor network, `sense diaries', environmental systems such as heating, ventilation and air-conditioning systems, and a central computer. A multi-agent system (MAS) is used to derive and act on the preferences of the occupants. Each occupant is represented by a personal agent in the MAS. The sense diary is a new device designed to elicit feedback from occupants about their satisfaction with the environment. The roles of the components are: the WSAN collects data about physical parameters such as temperature and humidity from an indoor environment; the central computer processes the collected data; the sense diaries leverage trade-offs between energy consumption and well-being, in conjunction with the agent system; and the environmental systems control the indoor environment.

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Perceptual effects of room reverberation on a "sir" or "stir" test-word can be observed when the level of reverberation in the word is increased, while the reverberation in a surrounding 'context I utterance remains at a minimal level. The result is that listeners make more "sit" identifications. When the context's reverberation is also increased, to approach the level in the test word, extrinsic perceptual compensation is observed, so that the number of listeners' "sir" identifications reduces to a value similar to that found with minimal reverberation. Thus far, compensation effects have only been observed with speech or speech-like contexts in which the short-term spectrum changes as the speaker's articulators move. The results reported here show that some noise contexts with static short-term spectra can also give rise to compensation. From these experiments it would appear that compensation requires a context with a temporal envelope that fluctuates to some extent, so that parts of it resemble offsets. These findings are consistent with a rather general kind of perceptual compensation mechanism; one that is informed by the 'tails' that reverberation adds at offsets. Other results reported here show that narrow-band contexts do not bring about compensation, even when their temporal-envelopes are the same as those of the more effective wideband contexts. These results suggest that compensation is confined to the frequency range occupied by the context, and that in a wideband sound it might operate in a 'band by band' manner.

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The 'irrelevant sound effect' in short-term memory is commonly believed to entail a number of direct consequences for cognitive performance in the office and other workplaces (e.g. S. P. Banbury, S. Tremblay, W. J. Macken, & D. M. Jones, 2001). It may also help to identify what types of sound are most suitable as auditory warning signals. However, the conclusions drawn are based primarily upon evidence from a single task (serial recall) and a single population (young adults). This evidence is reconsidered from the standpoint of different worker populations confronted with common workplace tasks and auditory environments. Recommendations are put forward for factors to be considered when assessing the impact of auditory distraction in the workplace. Copyright (c) 2005 John Wiley & Sons, Ltd.

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A field study assessed subjective reports of distraction from various office sounds among 88 employees at two sites. In addition, the study examined the amount of exposure the workers had to the noise in order to determine any evidence for habituation. Finally, respondents were asked how they would improve their environment ( with respect to noise), and to rate examples of improvements with regards to their job satisfaction and performance. Out of the sample, 99% reported that their concentration was impaired by various components of office noise, especially telephones left ringing at vacant desks and people talking in the background. No evidence for habituation to these sounds was found. These results are interpreted in the light of previous research regarding the effects of noise in offices and the 'irrelevant sound effect'.

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This paper proposes a new iterative algorithm for OFDM joint data detection and phase noise (PHN) cancellation based on minimum mean square prediction error. We particularly highlight the problem of "overfitting" such that the iterative approach may converge to a trivial solution. Although it is essential for this joint approach, the overfitting problem was relatively less studied in existing algorithms. In this paper, specifically, we apply a hard decision procedure at every iterative step to overcome the overfitting. Moreover, compared with existing algorithms, a more accurate Pade approximation is used to represent the phase noise, and finally a more robust and compact fast process based on Givens rotation is proposed to reduce the complexity to a practical level. Numerical simulations are also given to verify the proposed algorithm.

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This paper provides an introduction to Wireless Sensor Networks (WSN), their applications in the field of control engineering and elsewhere and gives pointers to future research needs. WSN are collections of stand-alone devices which, typically, have one or more sensors (e.g. temperature, light level), some limited processing capability and a wireless interface allowing communication with a base station. As they are usually battery powered, the biggest challenge is to achieve the necessary monitoring whilst using the least amount of power.

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The results from applying a sensor fusion process to an adaptive controller used to balance all inverted pendulum axe presented. The goal of the sensor fusion process was to replace some of the four mechanical measurements, which are known to be sufficient inputs for a linear state feedback controller to balance the system, with optic flow variables. Results from research into the psychology of the sense of balance in humans were the motivation for the investigation of this new type of controller input. The simulated model of the inverted pendulum and the virtual reality environments used to provide the optical input are described. The successful introduction of optical information is found to require the preservation of at least two of the traditional input types and entail increased training till-le for the adaptive controller and reduced performance (measured as the time the pendulum remains upright)

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Wireless sensor networks (WSNs) have been widely used in pervasive systems such as intelligent buildings. As a vital factor of product cost, energy consuming in WSN has been focused upon, but only via energy harvesting can the problem be overcome radically. This article presents a new approach to harvesting electromagnetic energy for WSN from useless radio frequency (RF) signals transmitted in WSN, with a quantitative analysis showing its feasibility.

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As a vital factor affecting system cost and lifetime, energy consumption in wireless sensor networks (WSNs) has been paid much attention to. This article presents a new approach to making use of electromagnetic energy from useless radio frequency (RF) signals transmitted in WSNs, with a quantitative analysis showing its feasibility. A mechanism to harvest the energy either passively or actively is proposed.

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The two major applications of microwave remote sensors are radiometer and radar. Because of its importance and the nature of the application, much research has been made on the various aspects of the radar. This paper will focus on the various aspects of the radiometer from a design point of view and the Low Noise Amplifier will be designed and implemented. The paper is based on a study in radio Frequency Communications engineering and understanding of electronic and RF circuits. Some research study about the radiometer and practical implementation of Low Noise Amplifier for Radiometer will be the main focus of this paper. Basically the paper is divided into two parts. In the first part some background study about the radiometer will be carried out and commonly used types of radiometer will be discussed. In the second part LNA for the radiometer will be designed.