Environmental noise remains a complex and fragmented interplay between industrialization, population growth, technological developments, and the living environment. Next to the circulatory diseases and cancer, noise pollution has been cited as the third epidemic cause of psychological and physiological disorders internationally. A reliable and firm relationship between the cumulative health implications with the traffic annoyance and occupational noise has been established. This agenda has called for an integrated, coordinated, and participatory approach to the reliable protection of noise interference. Despite several fragmented policies, legislation and global efforts have been addressed; the noise pollution complaints have been traditionally neglected in developing countries, especially in Malaysia. This paper was undertaken to postulate an initial platform to address the dynamic pressures, gigantic challenges, and tremendous impacts of noise pollution scenario in Malaysia. The emphasis is speculated on the traffic interference and assessment of industrial and occupational noise. The fundamental importance of noise monitoring and modeling is proposed. Additionally, the confronting conservation program and control measure for noise pollution control are laconically elucidated.
The dynamic behavior of a body-in-white (BIW) structure has significant influence on the noise, vibration, and harshness (NVH) and crashworthiness of a car. Therefore, by improving the dynamic characteristics of BIW, problems and failures associated with resonance and fatigue can be prevented. The design objectives attempt to improve the existing torsion and bending modes by using structural optimization subjected to dynamic load without compromising other factors such as mass and stiffness of the structure. The natural frequency of the design was modified by identifying and reinforcing the structure at critical locations. These crucial points are first identified by topology optimization using mass and natural frequencies as the design variables. The individual components obtained from the analysis go through a size optimization step to find their target thickness of the structure. The thickness of affected regions of the components will be modified according to the analysis. The results of both optimization steps suggest several design modifications to achieve the target vibration specifications without compromising the stiffness of the structure. A method of combining both optimization approaches is proposed to improve the design modification process.
A number of techniques have been proposed during the last three decades for noise variance and signal-to-noise ratio (SNR) estimation in digital images. While some methods have shown reliability and accuracy in SNR and noise variance estimations, other methods are dependent on the nature of the images and perform well on a limited number of image types. In this article, we prove the accuracy and the efficiency of the image noise cross-correlation estimation model, vs. other existing estimators, when applied to different types of scanning electron microscope images.
Strategic noise mapping provides important information for noise impact assessment and noise abatement. However, producing reliable strategic noise mapping in a dynamic, complex working environment is difficult. This study proposes the implementation of the random walk approach as a new stochastic technique to simulate noise mapping and to predict the noise exposure level in a workplace. A stochastic simulation framework and software, namely RW-eNMS, were developed to facilitate the random walk approach in noise mapping prediction. This framework considers the randomness and complexity of machinery operation and noise emission levels. Also, it assesses the impact of noise on the workers and the surrounding environment. For data validation, three case studies were conducted to check the accuracy of the prediction data and to determine the efficiency and effectiveness of this approach. The results showed high accuracy of prediction results together with a majority of absolute differences of less than 2 dBA; also, the predicted noise doses were mostly in the range of measurement. Therefore, the random walk approach was effective in dealing with environmental noises. It could predict strategic noise mapping to facilitate noise monitoring and noise control in the workplaces.
This paper presents an acoustic noise cancelling technique using an inverse kepstrum system as an innovations-based whitening application for an adaptive finite impulse response (FIR) filter in beamforming structure. The inverse kepstrum method uses an innovations-whitened form from one acoustic path transfer function between a reference microphone sensor and a noise source so that the rear-end reference signal will then be a whitened sequence to a cascaded adaptive FIR filter in the beamforming structure. By using an inverse kepstrum filter as a whitening filter with the use of a delay filter, the cascaded adaptive FIR filter estimates only the numerator of the polynomial part from the ratio of overall combined transfer functions. The test results have shown that the adaptive FIR filter is more effective in beamforming structure than an adaptive noise cancelling (ANC) structure in terms of signal distortion in the desired signal and noise reduction in noise with nonminimum phase components. In addition, the inverse kepstrum method shows almost the same convergence level in estimate of noise statistics with the use of a smaller amount of adaptive FIR filter weights than the kepstrum method, hence it could provide better computational simplicity in processing. Furthermore, the rear-end inverse kepstrum method in beamforming structure has shown less signal distortion in the desired signal than the front-end kepstrum method and the front-end inverse kepstrum method in beamforming structure.
A new and robust parameter estimation technique, named image noise cross-correlation, is proposed to predict the signal-to-noise ratio (SNR) of scanning electron microscope images. The results of SNR and variance estimation values are tested and compared with nearest neighborhood and first-order interpolation. Overall, the proposed method is best as its estimations for the noise-free peak and SNR are most consistent and accurate to within a certain acceptable degree, compared with the others.
This paper proposes a signal-to-noise-ratio (SNR) improvement by using an external phase modulator that allowed flexible control of the spectrum amplitude by varying the modulation index for linewidth measurements. Compared with the conventional self-heterodyne detection technique, the results obtained in this study showed an SNR improvement as high as 10 dB. This 10 dB improvement in SNR could help to reduce the usage of a particular length of a single mode fibre (normally about 50 Km) when measuring a linewidth in the region of 10 kHz.
This paper presents the improvement of quality factor (Q) estimation using shift frequency method. A new method was developed based on two previous methods; peak frequency shift (PFS) method and centroid frequency shift (CFS) method. The proposed algorithm has been tested to gauge its performance using three different scenarios; Q variation, travel
time variation, and signal to noise ratio (SNR) variation. The test was performed using the Ricker wavelet with random noise included. Based on the results obtained, it can be concluded that the new proposed method was able to improve Q estimation using shift frequency method. This method can also be implemented in the low and high Q condition, shallow and deep wavelet targets and in the low and high SNR conditions of seismic data. The limitations in the PFS and CFS methods can be reduced by this method.
Subei basin is the most promising onshore oil and gas bearing basin in South China. With the deepening of exploration, subtle hydrocarbon reservoirs have gradually become the major target of exploration. Seismic record often shows low signal to noise ratio (SNR), resulting that conventional seismic records have three shortcomings in the identification of subtle reservoirs: difficult to identify small faults; difficult to show the distribution law of sand body; and difficult to find traps. In order to solve this problem, we conducted the research on signal synthesis and decomposition. The research results showed that seismic record of different frequency bands can be restored from original seismic record and both of them contain real stratigraphic information. Based on this, when a certain band or several bands in the original seismic record is affected by noise and result in the reduction of SNR of seismic record, seismic information seriously affected by noise can be abandoned, leaving only less affected seismic information to obtain seismic record with higher SNR. In the collection of actual seismic record, the low and high band seismic information is seriously affected by noise, while medium-band seismic information is less affected. Therefore, based on this, the medium-band seismic information can be restored from the original seismic record to be new record, which is called predominant frequency band seismic record. In this paper, based on the research result, the predominant frequency band seismic record was applied to the two areas of Subei basin and the result showed the research result can be used as a good instruction on well placement and the improvement of drilling success rate.
Combining Mel Frequency Cepstral Coefficient with wavelet transform for feature extraction is not new. This paper proposes a new architecture to help in increasing the accuracy of speaker recognition compared with conventional architecture. In conventional speaker model, the voice will undergo noise elimination first before feature extraction. The proposed architecture however, will extract the features and eliminate noise simultaneously. The MFCC is used to extract the voice features while wavelet de-noising technique is used to eliminate the noise contained in the speech signals. Thus, the new architecture achieves two outcomes in one single process: ex-tracting voice feature and elimination of noise.
In this paper, an improved method of reducing ambient noise in speech signals is introduced. The proposed noise canceller was developed using a computationally efficient (DFT) filter bank to decompose input signals into sub-bands. The filter bank was based on a prototype filter optimized for minimum output distortion. A variable step-size version of the (LMS) filter was used to reduce the noise in individual branches. The subband noise canceller was aimed to overcome problems associated with the use of the conventional least mean square (LMS) adaptive algorithm in noise cancellation setups. Mean square error convergence was used as a measure of performance under white and ambient interferences. Compared to conventional as well as recently developed techniques, fast initial convergence and better noise cancellation performances were obtained under actual speech and ambient noise.
A beamformer in seismology is a signal receptor with a series of geophones, in which a beam of elastic waves is formed like a light beam by adjusting signal delays at individual geophones. Recently, beamforming has extended its applications to surface-wave measurement. In surface-wave measurement, beamforming provides unique advantages over other surface-wave methods, such as full automation in data analysis as well as directional signal reception to minimize scattered noise and multiple reflections in signals. However, certain defects depreciate the value of beamforming in terms of its practicality and feasibility. These include the requirement of having many receivers and the loss of small wavelength data due to spatial aliasing. It leads to insensitivity in identification of lateral variability, which creates the problem of having to smooth out geologic features and complexities like folding, faults and fractures. In this paper, advances in the refinement of beamforming were described on two counts: improvement of sensitivity in identification of lateral variability and recovery of aliased wave numbers, which enables evaluation of shallow material. On the passage to refinement, synthetic waveforms for typical layering systems were generated to figure out characteristics of beamformer velocities in comparison with SASW velocities and theoretical normal-mode velocities.
The recognition of microcalcifications and masses from digital mammographic images are important to aid the detection of breast cancer. In this paper, we applied morphological techniques to extract the embedded structures from the images for subsequent analysis. A mammographic phantom was created with embedded structures such as micronodules, nodules and fibrils. For the preprocessing techniques, intensity transformation of gray scale was applied to the image. The structures of the image were enhanced and segmented using dilation for a morphological operation with morphological closing. Next, low pass Gaussian filter was applied to the image to smooth and reduce noises. It was found that our method improved the detection of microcalcifications and masses with high Peak Signal To Noise Ratio (PSNR).
Thirty-two points in Kuala Lumpur were selected where traffic personnel were on duty. Sound level readings were taken three times a day. Generally, the traffic noise levels were between 75 dBA to 85 dBA. The maximum sound level recorded was 108.2 dBA. Noise emitted by traffic equipment and vehicles were up to 133 dBA. Results of audiometric tests revealed that out of 30 who were tested, 24 or 80% were positive for noise-induced hearing loss. A questionnaire survey revealed a lack of knowledge on occupational safety and personal protective equipment.
Working for a minimum of 8 hours, 6 days a week might have exposed the workers of public transportation to
high noise risks. However, occupational exposures in their workplace have not been adequately characterized and
identified. Assessment of occupational noise exposure among workers at five public transportation stations was made
using Sound Level Meter and through questionnaire survey. The data obtained was combined to estimate the work
shift exposure level and health impacts to the workers by using statistical analysis. The respondents participated in the
survey to identify the symptoms of noise-induced hearing loss and other health-related problems. Results of the study
indicated that occupational noise exposure among workers for Mean Continuous Equivalent Level, Leq= 76.17 dB(A)
presents small risks of developing a hearing disability. Some of the workers show symptoms of noise-induced hearing
loss and are annoyed by the sources of noise present at the public transportation.
The ability to produce performances at highest level under physically and emotionally demanding conditions underline the worth of a sportsperson. These stressful conditions places demands on the cognitive resources of the sportsperson; especially in anticipatory actions that require the allocation of cognitive resources. This study investigated the effects of cognitive stress on the temporal anticipation of a timing motor task. A repeated measures design was applied with two independent variables; cognitive stress and levels of difficulty, which included easy, intermediate and difficult. Study participants were 18 male and 18 female undergraduates of the Physical Education programme of Universiti Putra Malaysia. The experimental task involved performing a timing motor task across the three levels of difficulty, under two conditions as follows: (i) without cognitive stress, and (ii) under cognitive stress. Cognitive stress was induced via the continuous subtraction of two from a two-digit number. Participants performed the task individually and the sequence of the experimental task was counter-balanced. A two-way within subject ANOVA was
performed to ascertain the effects of cognitive stress on the temporal anticipation of the timing motor task. Data yielded significant difference in means for the stress main effect [Λ = .64, F (1.35) = 19.89, p < 0.05]; and the task main effect [Λ = .84, F (2, 34) = 3.35, p < 0.05]. Post hoc comparisons produced a significant difference in the means of the performance of the timing motor task at all three levels of difficulty. Data showed that cognitive stress had an effect on the temporal anticipation of the timing motor task. These results are explained from attentional and the neuromotor noise perspectives. It was concluded that the significant difference in the performance of the experimental task was due to the competition for intentional resources and the decrease of the signal to noise ratio due to cognitive stress.
The construction industry is one of the major sectors in Malaysia. Apart from providing
facilities, services and goods it also offers employment opportunities to local and
foreign workers. In fact, the construction workers are exposed to high risk of noises
being generated from various sources including excavators, bulldozers, concrete mixer
and piling machines. Previous studies indicated that the piling and concrete work were
recorded as the main source that contributed to the highest level of noise among
others. Therefore, the aim of this study is to obtain the level of noise exposure during
piling process and to determine the awareness of workers against noise pollution at
the construction site. Initially, the reading of noise level was obtained at construction
site by using a digital sound level meter (SLM) and noise exposure to the workers was
mapped. Readings were taken from four different distances; 5, 10, 15 and 20 meters
from the piling machine. Furthermore, a set of questionnaire was also distributed to
assess the knowledge of regarding noise pollution at the construction site. The result
showed that the mean noise level at 5 meters distance was more than 90 dB, which
exceeded the recommended level. Although the level of awareness of regarding the
effect of noise pollution is satisfactory but majority of workers (90%) still did not wear
ear muffs during working periods. Therefore, the safety module guidelines related to
noise pollution controls should be implemented to provide a safe working environment
and prevent initial occupational hearing loss.
In diversity combining at the receiver, the output signal-to-noise ratio (SNR) is often maximized by using the maximal ratio combining (MRC) provided that the channel is perfectly estimated at the receiver. However, channel estimation is rarely perfect in practice, which results in deteriorating the system performance. In this paper, an imperialistic competitive algorithm (ICA) is proposed and compared with two other evolutionary based algorithms, namely, particle swarm optimization (PSO) and genetic algorithm (GA), for diversity combining of signals travelling across the imperfect channels. The proposed algorithm adjusts the combiner weights of the received signal components in such a way that maximizes the SNR and minimizes the bit error rate (BER). The results indicate that the proposed method eliminates the need of channel estimation and can outperform the conventional diversity combining methods.