A method for the determination of aflatoxins B1 and B2 in peanuts and corn based products is described. The samples were extracted with a mixture of acetonitrile-water (84:16), followed by multifunctional clean-up and liquid chromatography with fluorescence detection. Both calibration curves showed good correlation from 4.0 to 32.0 ppb for aflatoxin B1 (r=0.9999) and 1.2 to 9.6 ppb for aflatoxin B2 (r=0.9997). The detection limit of aflatoxins B1 and B2 were established at 0.1 and 0.03 ppb, respectively, based on signal-to-noise ratio of 3:1. Average recoveries for the determination of aflatoxins B1 and B2 at 10 and 3 ppb spiking levels, respectively ranged from 94.2 to 107.6%. A total of 20 peanut samples and corn based products were obtained from retail shop and local market around Kuala Terengganu and analyzed for aflatoxins B1 and B2 contents, using the proposed method. Aflatoxins B1 and B2 were detected in 5 out of the 9 peanuts samples and 5 out of the 11 corn based products, at levels ranging from 0.2 to 101.8 ppb.
In spite of extensive research conducted to study how human brain works, little is known about a special function of the brain that stores and manipulates information-the working memory-and how noise influences this special ability. In this study, Functional magnetic resonance imaging (fMRI) was used to investigate brain responses to arithmetic problems solved in noisy and quiet backgrounds.
The higher field strength magnetic resonance imaging (MRI) such as 3 Tesla (T) and above generates noise that has potential detrimental effects on the hearing. Temporary threshold shifts following MRI examination have been reported for MRI with lower field strength. Such effect, however, have not been reported so far for a 3T MRI. We report a case that exemplifies the possible detrimental effects of a 3 T MRI generated noise on the auditory system. Our patient underwent investigation of his chronic backache in a 3 T MRI unit and developed hearing loss and tinnitus post-MRI examination. Hearing assessment was done using pure tone audiogram, distortion product otoacoustic emission (DPOAE) and brainstem electrical response audiometry (BERA) which revealed a unilateral sensorineural hearing loss which recovered within 3 days. However the tinnitus persisted. This is possibly a case of temporary threshold shift following noise exposure. However a sudden sensorineural hearing loss remains the other possibility.
The effect of noise on employees of dental clinics is debatable. The purposes of this study were to determine the intensity and frequency components of dental instruments used by dental staff nurses and the prevalence of noise induced hearing loss.
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.
Background: Level of comfort in working environment can contribute to increase level of health, emotion during working, level of safety, quality and productivity of work. A study of physical factors (heat, noise and lighting) is important to determine the level of comfort during working. This study was carried out to study those physical factors upon comfort level during working among Casting Shop workers in a car manufacturing factory.
Methods: Instruments for the physical monitoring including Questemp°36 Thermal Environment Monitor, Sound Level Meter and Lux Meter were used at seven measured areas. The information about the level of comfort during working was collected using questionnaires among 65 respondents by random sampling method.
Results: Measured data showed there were four measured areas which Wet Bulb Globe Temperature indoor (WBGTi) value are above the standard limit recommended by ACGIH, three measured areas recorded noise level above the standard limit recommended by Factories and Machineries (Noise Exposure) 1989, while there was no measured area recorded lighting reading below the standard limit recommended by MS ISO 8995:2005. Result from questionnaire found that the majority of the workers did not feel comfortable towards the heat and noise level in their workplace while most of the respondents felt comfortable towards lighting level in their workplace. Mean of WBGTi reading and lighting reading have a significant difference (p
Sound is one of the source of energy generated by vibration and is carried through the air in a form of pressure waves (Frederick, 1975). This pressure waves consist of pulsation or vibration of molecules of an elastic medium such as gas, liquid and even solid (Gerber, 1974). Due to its nature, sound can be irritating when it is excessive. The excessive amount of sound is called noise. Exposure to noise is common to the workers working at the industry. This can lead to hearing loss. Hearing loss is one of the most common health problems in the industrialized world. Working activities have been related to noise exposure due to increase use of machine that generates sounds. Many workers throughout the world experience hazardous noise exposure which is ≥ 85 decibels (dB) (Seter, 1998). Based on the previous study in the European region, most of the employers had difficulties to compensate workers diagnosed with hearing loss or hearing impairment cause by the working nature. (Rachiotis et al., 2006). According to European Survey on Working Conditions, about 7% of the workers considered that their work affects their health in the form of hearing disorders. Occupational risk factors for hearing loss include occupational noise, whole body vibration, work-related diseases and exposure to chemical. In this report, we specified in the noise exposure level of the workers.
To reduce undesirable charging effects in scanning electron microscope images, Rayleigh contrast stretching is developed and employed. First, re-scaling is performed on the input image histograms with Rayleigh algorithm. Then, contrast stretching or contrast adjustment is implemented to improve the images while reducing the contrast charging artifacts. This technique has been compared to some existing histogram equalization (HE) extension techniques: recursive sub-image HE, contrast stretching dynamic HE, multipeak HE and recursive mean separate HE. Other post processing methods, such as wavelet approach, spatial filtering, and exponential contrast stretching, are compared as well. Overall, the proposed method produces better image compensation in reducing charging artifacts.
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.
Sensorineural hearing loss is a common and important source of disability among the workers and often caused by occupational noise exposure. Aims of the study were to determine the prevalence and contributing factors of hearing loss among airport workers. A cross-sectional study was carried out at an airport in Malaysia. This study used stratified sampling method that involved 358 workers who were working in 3 different units between November 2008 and March 2009. Data for this study were collected by using questionnaires eliciting sociodemographic, occupational exposure history (previous and present), life-style including smoking habits and health-related data. Otoscopic and pure-tone audiometric tests were conducted for hearing assessment. Noise exposure status was categorize by using a noise logging dosimeter to obtain 8-hour Time-Weighted Average (TWA). Data was analyzed by using SPSS version 12.0.1 and EpiInfo 6.04. The prevalence of hearing loss was 33.5%. Age >40 years old (aOR 4.3, 95%CI 2.2-8.3) is the main risk factors for hearing loss followed by duration of noise exposure >5 years (aOR 2.5, 95%CI 1.4-4.7), smoking (aOR 2.1, 95%CI 1.2-3.4), duration of service >5 years (aOR 2.1, 95%CI 1.1-3.9), exposure to explosion (aOR 6.1, 95%CI 1.3-29.8), exposure to vibration (aOR 2.2, 95%CI 1.1-4.3) and working in engineering unit (aOR 5.9, 95%CI 1.1-30.9). The prevalence rate ratio of hearing loss for nonsmokers aged 40 years old and younger, smokers aged 40 years old and younger, non-smokers older than 40 years old and smokers older than 40 years old was 1.0, 1.7, 2.8 and 4.6 respectively. This result contributes towards better understanding of risk factors for hearing loss, which is relatively common among Malaysian workers.
In this paper, a variable threshold voice activity detector (VAD) is developed to control the operation of a two-sensor adaptive noise canceller (ANC). The VAD prohibits the reference input of the ANC from containing some strength of actual speech signal during adaptation periods. The novelty of this approach resides in using the residual output from the noise canceller to control the decisions made by the VAD. Thresholds of full-band energy and zero-crossing features are adjusted according to the residual output of the adaptive filter. Performance evaluation of the proposed approach is quoted in terms of signal to noise ratio improvements as well mean square error (MSE) convergence of the ANC. The new approach showed an improved noise cancellation performance when tested under several types of environmental noise. Furthermore, the computational power of the adaptive process is reduced since the output of the adaptive filter is efficiently calculated only during non-speech periods.
Auscultation of the heart is accompanied by both electrical activity and sound. Heart auscultation provides clues to diagnose many cardiac abnormalities. Unfortunately, detection of relevant symptoms and diagnosis based on heart sound through a stethoscope is difficult. The reason GPs find this difficult is that the heart sounds are of short duration and separated from one another by less than 30 ms. In addition, the cost of false positives constitutes wasted time and emotional anxiety for both patient and GP. Many heart diseases cause changes in heart sound, waveform, and additional murmurs before other signs and symptoms appear. Heart-sound auscultation is the primary test conducted by GPs. These sounds are generated primarily by turbulent flow of blood in the heart. Analysis of heart sounds requires a quiet environment with minimum ambient noise. In order to address such issues, the technique of denoising and estimating the biomedical heart signal is proposed in this investigation. Normally, the performance of the filter naturally depends on prior information related to the statistical properties of the signal and the background noise. This paper proposes Kalman filtering for denoising statistical heart sound. The cycles of heart sounds are certain to follow first-order Gauss-Markov process. These cycles are observed with additional noise for the given measurement. The model is formulated into state-space form to enable use of a Kalman filter to estimate the clean cycles of heart sounds. The estimates obtained by Kalman filtering are optimal in mean squared sense.
This paper applies an expectation-maximization (EM) based Kalman smoother (KS) approach for single-trial event-related potential (ERP) estimation. Existing studies assume a Markov diffusion process for the dynamics of ERP parameters which is recursively estimated by optimal filtering approaches such as Kalman filter (KF). However, these studies only consider estimation of ERP state parameters while the model parameters are pre-specified using manual tuning, which is time-consuming for practical usage besides giving suboptimal estimates. We extend the KF approach by adding EM based maximum likelihood estimation of the model parameters to obtain more accurate ERP estimates automatically. We also introduce different model variants by allowing flexibility in the covariance structure of model noises. Optimal model selection is performed based on Akaike Information Criterion (AIC). The method is applied to estimation of chirp-evoked auditory brainstem responses (ABRs) for detection of wave V critical for assessment of hearing loss. Results shows that use of more complex covariances are better estimating inter-trial variability.
Environmental factors such as temperature, lighting and noise have very significant impact to workers’ health, safety, comfort, performance and productivity. In an ergonomically design industrial work environment, these factors need to be control at their optimum levels. The main objective of this study is to find the effect of temperature, illuminance and sound pressure level on workers’ productivity in automotive industry. To perform this study a workstation in an automotive component manufacturing was selected as the location of the study. Results of data analysis showed there were relationships between temperature, illuminance and noise on workers’ productivity. Later, the authors’ developed multiple linear equation models to represent the relationships between temperature, illuminance and noise on the workers’ productivity. These multiple linear equation models could be used to predict the production rate for the workstation by referring to the value of temperature, illuminance and noise level.
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).
Accurate inspection of welded materials is important in relation to achieve acceptable standards. Radiography, a non-destructive test method, is commonly used to evaluate the internal condition of a material with respect to defect detection. The presence of noise in low resolution of radiographic images significantly complicates analysis; therefore attaining higher quality radiographic images makes defect detection more readily achievable. This paper presents a study pertaining to the quality enhancement of radiographic images with respect to different types of defects. A series of digital radiographic weld flaw images were smoothed using multiple smoothing techniques to remove inherent noise followed by top and bottom hat morphological transformations. Image quality was evaluated quantitatively with respect to SNR, PSNR and MAE. The results indicate that smoothing enhances the quality of radiographic images, thereby promoting defect detection with the respect to original radiographic images.
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.
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.
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.