Inertial Navigation System (INS) is one of the navigation systems widely used in various land-based, aerial, and marine applications. Among all types of INS, Microelectromechanical System (MEMS)-based INS can be widely utilized, owing to their low cost, lightweight, and small size. However, due to the manufacturing technology, MEMS-based INS suffers from deterministic and stochastic errors, which increase positioning errors over time. In this paper, a new effective noise reduction method is proposed that can provide more accurate outputs of MEMS-based inertial sensors. The intelligent method in this paper is a combined denoising method that combines Wavelet Transform (WT), Permutation Entropy (PE), Support Vector Regression (SVR), and Genetic Algorithm (GA). Firstly, WT is employed to obtain a time-frequency representation of raw data. Secondly, a four-element feature vector is formed. These four features are (1) amplitude of frequency, (2) its ratio to mean of amplitudes of all frequencies, (3) location of frequency in time-frequency representation, and (4) judgment on behaviors of frequency that is obtained by utilizing PE. Thirdly, based on the feature vector, the GA-SVR algorithm predicts amplitudes of all frequencies in the time-frequency representation of the denoised signal. Finally, by employing inverse WT the denoised signal is obtained. In this work, the outputs of the Inertial Measurement Unit (IMU) in ADIS16407 sensor, as a low-cost and MEMS-based INS, have been utilized for data collection. The proposed method has been compared with other noise reduction methods and the achieved results verify superior improvement than other methods.

Background and Aim: Acceptable noise level (ANL) is the loudest level of background noise that human can tolerate while listening a running speech. ANL test is used for the prediction that whether a hearing aid (HA) candidate can use HA successfully by determining how well the individual tolerates background noise while listening to speech. In the current review, we reviewed the basis and theories of the ANL test and the factors that identified from the studies that have conducted on ANL and the influence of this test in increasing the quality of life of hearing aid users along with a discussion of its application in clinical audiology.Recent Findings: Research showed that subjects with a higher tolerance for background noise are most probable to be the successful hearing aid users. Clinical trials demonstrated that ANL test provides reliable results and can predict HA successful use with 85% accuracy.Conclusion: Acceptable noise level is a reliable and valid test that can be used as a predictive index for the successful application of HA, and it is applicable in before/after HA fitting assessments.Thus, it is suggested that ANL can be implemented in the fitting and counseling process of HAs prescription. Further studies are required to resolve biases over the employment of this test in bilinguals.

Background and Aim: Problem with tolerating Levels of amplified background noise is one of the most complications of people with hearing loss. Acceptable noise level (ANL) test can be used as an accurate and valid test to evaluate the ability of tolerating levels of noise among peoples. The aims of this study were to develop and evaluate the reliability of acceptable noise level test in Persian language.Materials and Methods: After selecting suitable materials for multi talker babble noise and running speech signals, Material were recorded in controlled situation in professional recording studio. The test was conducted twice with one week separation on 66 normal people with mean age of 25±4.Results: Statistical analysis showed the mean Acceptable Noise Level in two repeats had no significant difference (0.05>P). The correlation coefficient between the first and second repeats of (ANL) was r=0.847 (0.001>P) and Inter Class Correlation coefficient between the first and second repeats was 0.920 (0.001>P).Conclusion: Based on the findings, the Persian version of acceptable noise level test had desired reliability in the individual with normal hearing. Implementation simplicity, non-invasive and the low cost are the benefits for the clinical use of this test.

Bazaars are among the few historical buildings that still continue to operate. The Bazaar in a city has been important not only from economic aspects but also from cultural and social aspects. Today, the empty space of such urban spaces, which can become a lasting space by creating a sense of belonging and peace, while meeting the needs of today's people, is felt very much. Sound is one of the main factors in creating memories in the human mind. In order to investigate the role of sound in the traditional architecture of Iran, a research was conducted in the Vakil Bazzar of Shiraz. The final goal of this research is to investigate the quantitative and qualitative conditions of the sound using sound meter software in the Vakil Bazzar of Shiraz. The permissible level of noise pollution in urban spaces is 60 decibels based on the resolution of the Supreme Council of Environmental Protection of Iran for commercial areas. The results of this research indicate that in the quietest conditions, the noise pollution for at least 33% of the Bazzar space is higher than the maximum allowed amount of noise pollution. How to improve the sound conditions in Vakil Bazzar, such as reducing noise by creating a masking sound source, creating a pond and a fountain, is one of the most important results of this research.

Background and Aims: Despite the recent advances in digital processing of hearing aids, a large number of users are not happy with their hearing aids. One of the major reasons for this is the lack of good recognition of speech in noisy environments. Digital noise reduction and directionality are some of the technologies that are helpful in this issue. The present study was conducted to evaluate the effects of these two technologies on listening comfort and speech recognition of individuals with moderate sensory-neural hearing loss. Materials and Methods: In the current study, we applied Acceptable Noise Level (ANL) and Farsi Auditory Recognition of Digit in Noise (FARDIN), as measures of listening comfort and speech intelligibility, respectively, on 18 participants (8 male and 10 female) who had moderate sensory neural hearing loss. We evaluated both these measures under six different hearing aid conditions: 1) Omnidirectional-DNR/off (baseline), 2) Omnidirectional-Broadband DNR, 3) Omnidirectional-Multichannel DNR, 4) Directional, 5) Directional-Broadband DNA, and 6) Directional-Multicellular DNR. Results: Both the digital noise reduction technology and the directionality improved the ANL, but the effect of directionality was more than the other. None of the digital noise reduction or directionality could improve the score in FARDIN test, but it did not make the results even worse. Conclusion: According to the results, since these two technologies improve listening comfort and do not affect speech comprehension, it is recommended that these two options be activated for adjusting the hearing aid in clinics.

Many important speech enhancement methods operate in frequency domain. In these methods, a frequency gain filter is multiplied by the noisy spectrum. In this paper, frequency methods are investigated and the gain filters are shown as functions of the Signal to Noise Ratio (SNR). Since gain filters are functions of SNR, SNR estimation methods are presented and consequently a new SNR estimation method is proposed. Moreover, we proposed a technique for controlling the level of residual noise and shaping it. In our proposed techniques, the frequency gain filters are tuned in order to have less noise reduction and as a result achieve less distortion. In addition to controlling the level of noise, in our proposed technique, the shape of residual noise is changed in order to have more pleasant residual noise. For evaluation of methods, listening tests are performed and the results are reported based of four aspects of speech signals: musical residual noise, level of background noise, echo and unnatural residual noise. Evaluation of methods shows that the proposed methods are successful from these aspects point of view.

The present study was an attempt to empirically find out if the very presence of background noise would impair L2 listening comprehension, and also to explore to what extent the nature of noise would mediate this disruption. Regarding the latter point, the effect of lexicality, meaning, and Ll/L2 dichotomy were investigated. The participants listened, within a repeated-measures design, to ten L2 passages two of which were against a quiet background and others were in the presence of either radio static (roughly representing the white noise, Le., the standard non-lexical noise), Russian (as a totally unknown language) noise, English (L2) noise, or Persian (Ll) noise. Matched t-test results showed the background noise to be substantially disruptive of L2 listening comprehension. In addition, more masking was found from white noise that from competing speech, including the lexicality reduced the amount of masking. The effect of meaning, too, did not reach significance: Meaningless background interfered with L2 listening comprehension as much as did meaningful speech. Similarly, Ll and L2~oises were statistically equal in their power to corrupt L2 listening performance.

Background and Aim: Acceptable noise level (ANL) measures the amount of accepted background noise while listening to the story. In the current study, ANL was carried out in children with learning disability (LD) and compared with the results of normal children by using examiner- and self-adjusted methods.Methods: Forty seven (25 male, 22 female) normal children with good and better educational background and 46 (27 male, 19 female) LD children ranging in age from 7-12 years old were participated. ANL was assessed using an ear-level loudspeaker in front of children. The differences of ANL, most comfortable level (MCL), and background noise level (BNL) between groups and their relationship between examiner- and self-adjusted procedures were investigated.Results: Mean ANLs of LD children either in examiner- or self-adjusted methods (8.91±4.66 and 11.00±5.38, respectively) were worse than those of normal children (7.19±3.63 and 9.61±3.41, respectively). The difference between mean ANL of normal and LD children was statistically significant only for examiner-adjusted method (p=0.05). There were also significant differences in BNL between groups for examiner- and self-adjusted method (p< 0.05). A strong positive correlation was found between examiner- and self-adjusted conditions for ANL, MCL, and BNL among groups (p<0.001).Conclusion: ANL is clinically applicable in LD children. Moreover, LD children accept lower background noise; therefore modification of their listening environment is recommended. Because of a strong positive relationship between ANL in examiner- and self-adjusted procedures, both methods can be implemented in different situations.