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With the increased popularity of wearable devices, we are seeing head gears (such as Google glass) that provide augmented visual information. We can also extend augmented information to audible signals to guide users in finding their way, alert user to prominent danger in noisy environment, or simply creating virtual-and-augmented reality gaming platform. In this paper, we outline new approaches in combining real sonic environment and augmented virtual sound source through an open-ear headphones. Microphones are positioned in the headphones to capture the sonic information as well as the signal playback to the headphones. Active noise control (ANC) techniques have conventionally been used for noisecancellingheadphones, and this paper shows how we can apply ANC techniques in augmented reality headphones to compensate for the sonic difference between augmented and real sound objects and provide a seamless combination of the two. Some interesting new applications using the augmented reality headphones can be realized with this augmented reality headphones, and open up new possibilities for other interactive applications.
This work is the first to look at ANC on a model of adult patients in an ICU environment. Noise-cancellingheadphones are associated with a recorded mean reduction in noise ex- posure over a 24-h period of 6.8 dB and a reduction in the exposure to high intensity sound events in our model. This effect appears to be constant over the course of a typical day, and although we were unable to reduce noise levels below suggested ‘ideal’ standards, ANC may form an important contributor alongside other measures to achieve this.
considerable improvements in the implemenatation of such systems over the past decade or so have been largely due to the availability of poweful and yet relatively cheap DSP devices. Some of the alogirthms like filtered-x LMS alorithm have been tested for headphones on DSP processors [Wan 97]. Experiments have shown drastic improvement in the cancellation of noise in headphones. However for most of these algorithms, the noise cancellation parameters are taken in the absence of audio signal and hence they have to be updated in case of change of noise source or addition of another noise source. There are other alorithms like recursive least squares (RLS) algorithm, which is deterministic in the nature of the noise and hence can be used for real time cancellation of noise without the need for offline updating of its parameters, and Kalman filtering approach, which has a faster rate of convergence. However due to the computational complexity of the algorithms and the cost involved, there have not been much research on the implementation of these algoithms in noisecancellingheadphones. So it will take a few more years to implement these algorithms on the DSP processors to achieve a better improvement in the cancellation of noise in headphones.
The EAS algorithm is rather sensitive to noise. On one hand, the other artifacts (such as those due to eye blinks, movements, sweat, etc.) prevent an accurate detection of the interference peaks. On the other hand, these artifacts have a big influence on the computed average interference waveform. This is well illustrated on Figure 19. By looking at the cardiac interference estimate with the EAS method (Figure 19(d)), we can see that the position of the interfer- ence peak at the 14th second is not correctly detected because of artifact. Moreover, we see that the average interference waveform estimated by the EAS method seems to be strongly influenced by the artifact in contrast with the interference estimated by the ICA method (Figure 19(e)). This probably causes the bad corrections observed around seconds 4.5, 7.5, and 11 on Figure 19(c).
The full-duplex system ﬁrstly requires high isolation between the transmit antenna and receive antenna to reduce the self-interference signal to an acceptable level. This technique is called passive cancellation. However, this method alone cannot cancel the self-interference signal down to the noise ﬂoor level. Therefore, to entirely suppress this unwanted signal, an active cancellation technique must follow the passive technique stage for further reduction of the self-interference signal. Active cancellation can be divided into two types: Radio Frequency (RF) cancellation, and digital baseband cancellation . In this paper, a novel antenna cancellation scheme for full-duplex systems is presented to cancel the self-interference signal. Computer simulation technology (CST) microwave studio software is utilized to model the proposed scheme, which consists of three patch antennas; one receiving antenna and two transmitting antennas. The two transmitters are fed by a developed coupler, which is constructed and integrated with the antennas on one substrate. Results show that this simple structure can provide a high cancellation over a wide band of frequencies.
• If you cannot connect your device or connect a headset to each other, or the sound is played from only one earphone, you must re-enter the system to the search mode. Put the headphones to the charging case. Take headphones out the caseand they will automatically connect to each other. After that, pair the headphones with the device, as described above*.
• (HFP only) It may be difficult to hear phone conversations when the unit is used in locations with loud ambient noise or in outdoor or other locations exposed to powerful winds. In that case, change the calling location or switch the calling device to the Bluetooth ® enabled phone to continue the call. (Press the Multiple functions button on the unit twice quickly to switch.)
The provided headphones were proven to cause consid- erable attenuation of 511 keV photons of PET, thus justi- fying the manufacturer’s disapproval of using them for simultaneous PET scanning of the head. Their effects on PET quantification in phantom and patient studies were clearly evidenced in the scans. In the latter, especially the cerebellum and the temporal lobes as regions that are located right between the earcups experienced a ra- ther uniform decrease in uptake values of approximately 10 %, while more remote regions were less affected. Therefore, specifically in PET studies where absolute up- take quantification is necessary (e.g. kinetic modelling of tracer uptake in the brain), the headphones should be avoided. In cases where quantification is not of import- ance, the headphone-introduced bias may still have
• DO NOT use mobile phone adapters to connect headphones to airplane seat jacks as this could result in personal injury such as burns or property damage due to overheating. Remove and disconnect immediately if you experience warming sensation or loss of audio.
The purpose of this test is to verify whether the distor- tion produced by each equalized headphone at different reproduction levels can be perceived or not. To avoid visual and tactile biases, all the different headphone emulations and their distortions measured were simulated through the refer- ence headphone in a virtual simulation listening test. Wearing just the reference headphones, the subjects per- forming the test can have immediate access to the different headphones and the procedure of the test becomes more flex- ible, transparent, controlled, and repeatable. 12 This method- ology is desirable due to the differences in appearance, fitting, and range of qualities of the headphones employed.
corrected standard deviation of signed localization error. Further analysis of head movement to obtain judgment pro- files showed that the participants on average took 0.2 s longer to reach their final judgments and used 0.1 more head-turns, which could imply an increase in complexity of the localization process due to corrupted localization cues. In light of the findings in this study, it is recommended that care must be taken when choosing headphones for a scenario in which a listener is presented with external acoustic sources. Results for different headphone designs highlight that the use of electrostatic transducers could help maintain natural acoustical perception, however, the effect on perception is still measurable and therefore headphone transparency should not be assumed. For an alternative so- lution it is recommended that headphones be worn during HRTF measurements to allow like-for-like comparison be- tween the real and virtual sources, where in-situ HRTF measurement is possible [16, 23].
The population, in general, is exposed to noise levels ranging from 35 to 85 dBA. In a normal noise environment, below 45 dBA, no one usually experiences any annoyance, which tends to appear once the level reaches 85 dBA. Because of this, the threshold where annoyance begins for humans is located between 60 and 65 dBA for daytime noise. For example, in a library environment there is 40 dBA, a loud conversation one meter away records 70 dBA, transit on a hectic street is easily over 85 dBA on the curb, and a plane taking off at a distance of 70 meters reaches 120 dBA (Bruel and Kjaer, 1984).
The noise level near the highway depends on the number of vehicles. The noise level increases with an increase in traffic volume. Traffic volume is defined as the total number of vehicles passing a given point during a spe- cific period of time or the number of vehicles that pass over a given section of a lane or a roadway during a spe- cific period of time.
In addition to the IMO resolution there may be national legislation on noise limits in the harbour area. For example Danish legislation specifies that the whole harbour, including ships at berth, should be treated as an “industrial source” with noise guideline limits as defined by the Danish Environmental Protection Agency in . However, this legislation only applies to ship at berth and not during manoeuvring in the port. With regard to noise this is the most interesting period as the time at berth is usually significantly longer than the manoeuvring time in port. An excerpt of the guiding limits is given in Table 1. The limits are quite strict especially if the ship is at berth close to residential or recreational areas.
A study of the effects of nighttime noise exposure on the in-home sleep of residents near one military airbase, near one civil airport, and in several households with negligible nighttime aircraft noise exposure, revealed SEL as the best noise metric predicting noise-related awakenings. It also determined that out of 930 subject nights, the average spontaneous (not noise-related) awakenings per night was 2.07 compared to the average number of noise-related awakenings per night of 0.24 (Fidell, et al. 1994). Additionally, a 1995 analysis of sleep disturbance studies conducted both in the laboratory environment and in the field (in the sleeping quarters of homes) showed that when measuring awakening to noise, a 10 dB increase in SEL was associated with only an 8 percent increase in the probability of awakening in the laboratory studies, but only a 1 percent increase in the field (Pearsons, et al. 1995). Pearsons, et al. (1995), reported that even SEL values as high as 85 dB produced no awakenings or arousals in at least one study. This observation suggests a strong influence of habituation on susceptibility to noise-induced sleep disturbance. A 1984 study (Kryter 1984) indicates that an indoor SEL of 65 dB or lower should awaken less than 5 percent of exposed individuals. Nevertheless, some guidance is available in judging sleep interference. The EPA identified an indoor DNL of 45 dB as necessary to protect against sleep interference (U.S. Environmental Protection Agency 1978). Assuming a very conservative structural noise insulation of 20 dB for typical dwelling units, this corresponds to an outdoor day-night average sound level of 65 dB to minimize sleep interference.