For almost a half-decade, the unique autocorrelation properties of Golay complementary pairs (GCP) have added a significant value to the key performance of conventional time-domain multiplexed fiber Bragg grating sensors (TDM-FBGs). However, the employment of the unipolar form of Golay coded TDM-FBG has suffered from several performance flaws, such as limited improvement of the signal-to-noise ratio (SNIR), noisy backgrounds, and distorted signals. Therefore, we propose and experimentally implement several digital filtering techniques to mitigate such limitations. Moving averages (MA), Savitzky-Golay (SG), and moving median (MM) filters were deployed to process the signals from two low reflectance FBG sensors located after around 16 km of fiber. The first part of the experiment discussed the sole deployment of Golay codes from 4 bits to 256 bits in the TDM-FBG sensor. As a result, the total SNIR of around 8.8 dB was experimentally confirmed for the longest 256-bit code. Furthermore, the individual deployment of MA, MM, and SG filters within the mentioned decoded sequences secured a further significant increase in SNIR of around 4, 3.5, and 3 dB, respectively. Thus, the deployment of the filtering technique alone resulted in at least four times faster measurement time (equivalent to 3 dB SNIR). Overall, the experimental analysis confirmed that MM outperformed the other two techniques in better signal shape, fastest signal transition time, comparable SNIR, and capability to maintain high spatial resolution.
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.
Wavelet packet transform decomposes a signal into a set of orthonormal bases (nodes) and provides opportunities to select an appropriate set of these bases for feature extraction. In this paper, multi-level basis selection (MLBS) is proposed to preserve the most informative bases of a wavelet packet decomposition tree through removing less informative bases by applying three exclusion criteria: frequency range, noise frequency, and energy threshold. MLBS achieved an accuracy of 97.56% for classifying normal heart sound, aortic stenosis, mitral regurgitation, and aortic regurgitation. MLBS is a promising basis selection to be suggested for signals with a small range of frequencies.
The present study was conducted to determine quantitatively the correlation between injected radiotracer and signal-to-noise ratio (SNR) based on differences in physiques and stages of cancer. Eight different activities were evaluated with modelled National Electrical Manufacturers Association (NEMA) of the International Electrotechnical Commission (IEC) PET's phantom with nine different tumour-to-background ratio (TBR). The findings suggest that the optimal value of dosage is required for all categories of patients in the early stages of cancer diagnosis.
We demonstrate a multi-wavelength light source using a semiconductor optical amplifier (SOA) in conjunction with an array waveguide grating (AWG). The experimental results showed more than 20 channels with a wavelength separation of 0.8 nm and an optical signal-to-noise ratio of more than 10 dB under room temperature. The channels operated at the wavelength region from 1530.4 nm to 1548.6 nm, which corresponded to AWG filtering wavelengths with SOA drive current of 350 mA. The proposed light source had the advantages of a simple and compact structure, multi-wavelength operation and the system could be upgraded to generate more wavelengths.
Textitis is a new term used to refer to the degenerative-strain osteoarthritis that comes from excessive use of a smart phone. 18F-NaF is increasingly used in diagnosing skeletal pain that is not identified on radiographs. We report a case of a 26-y-old woman with left breast cancer referred for 18F-NaF PET/CT, who was complaining of right thumb and wrist pain. Findings were negative for bone secondaries. Dedicated hands views were acquired on a positron emission mammography scanner and showed focal uptake at the first carpometacarpal and second metacarpophalangeal joints. On the basis of the strong history, the findings were likely due to active arthritic changes caused by repetitive strain injury from excessive text messaging.
We experimentally investigate the performance of L-band multiwavelength Brillouin-Raman fiber laser (MBRFL) under forward and backward pumped environments utilizing a linear cavity. A short length of 1.18 km dispersion compensating fiber is used as a nonlinear gain medium for both Brillouin and Raman gain. Experimental results indicate that the gain in the copumped laser configuration is higher than the gain in the counterpumped configuration. A stable and constant number of Brillouin Stokes lines up to 23 Stokes, with channel spacing of 0.08 nm and more than 20 dB of optical signal to noise ratio, can be generated as well as tuning over 20 nm in the L-band region from 1570 to 1590 nm. The laser generating the Brillouin Stokes lines exhibits flat amplitude bandwidth and high average output power of 0.8 and 1.6 dBm for the copropagation and counterpropagation pumps, respectively. Moreover, the tuning range bandwidth of the MBRFL can be predicted from the oscillated Brillouin pump gain profile.
This paper presents a new practical QPSK receiver that uses digitized samples of incoming QPSK analog signal to determine the phase of the QPSK symbol. The proposed technique is more robust to phase noise and consumes up to 89.6% less power for signal detection in demodulation operation. On the contrary, the conventional QPSK demodulation process where it uses coherent detection technique requires the exact incoming signal frequency; thus, any variation in the frequency of the local oscillator or incoming signal will cause phase noise. A software simulation of the proposed design was successfully carried out using MATLAB Simulink software platform. In the conventional system, at least 10 dB signal to noise ratio (SNR) is required to achieve the bit error rate (BER) of 10(-6), whereas, in the proposed technique, the same BER value can be achieved with only 5 dB SNR. Since some of the power consuming elements such as voltage control oscillator (VCO), mixer, and low pass filter (LPF) are no longer needed, the proposed QPSK demodulator will consume almost 68.8% to 99.6% less operational power compared to conventional QPSK demodulator.
Medical Image Quality Assessment (IQA) plays an important role in assisting and evaluating the development of any new hardware, imaging sequences, pre-processing or post-processing algorithms. We have performed a quantitative analysis of the correlation between subjective and objective Full Reference - IQA (FR-IQA) on Magnetic Resonance (MR) images of the human brain, spine, knee and abdomen. We have created a MR image database that consists of 25 original reference images and 750 distorted images. The reference images were distorted with six types of distortions: Rician Noise, Gaussian White Noise, Gaussian Blur, DCT compression, JPEG compression and JPEG2000 compression, at various levels of distortion. Twenty eight subjects were chosen to evaluate the images resulting in a total of 21,700 human evaluations. The raw scores were then converted to Difference Mean Opinion Score (DMOS). Thirteen objective FR-IQA metrics were used to determine the validity of the subjective DMOS. The results indicate a high correlation between the subjective and objective assessment of the MR images. The Noise Quality Measurement (NQM) has the highest correlation with DMOS, where the mean Pearson Linear Correlation Coefficient (PLCC) and Spearman Rank Order Correlation Coefficient (SROCC) are 0.936 and 0.938 respectively. The Universal Quality Index (UQI) has the lowest correlation with DMOS, where the mean PLCC and SROCC are 0.807 and 0.815 respectively. Student's T-test was used to find the difference in performance of FR-IQA across different types of distortion. The superior IQAs tested statistically are UQI for Rician noise images, Visual Information Fidelity (VIF) for Gaussian blur images, NQM for both DCT and JPEG compressed images, Peak Signal-to-Noise Ratio (PSNR) for JPEG2000 compressed images.
The study of binding affinity is essential in surface plasmon resonance (SPR) sensing because it allows researchers to quantify the affinity between the analyte and immobilised ligands of an SPR sensor. In this study, we demonstrate the derivation of the binding affinity constant, K, for Pb2+and Hg2+ions according to their SPR response using a gold/silver/gold/chitosan-graphene oxide (Au/Ag/Au/CS-GO) sensor for the concentration range of 0.1-5 ppm. The higher affinity of Pb2+to binding with the CS-GO sensor explains the outstanding sensitivity of 2.05 °ppm-1against 1.66 °ppm-1of Hg2+. The maximum signal-to-noise ratio (SNR) upon detection of Pb2+is 1.53, and exceeds the suggested logical criterion of an SNR. The Au/Ag/Au/CS-GO SPR sensor also exhibits excellent repeatability in Pb2+due to the strong bond between its functional groups and this cation. The adsorption data of Pb2+and Hg2+on the CS-GO sensor fits well with the Langmuir isotherm model where the affinity constant, K, of Pb2+and Hg2+ions is computed. The affinity of Pb2+ions to the Au/Ag/Au/CS-GO sensor is significantly higher than that of Hg2+based on the value of K, 7 × 10⁵ M-1and 4 × 10⁵ M-1, respectively. The higher shift in SPR angles due to Pb2+and Hg2+compared to Cr3+, Cu2+and Zn2+ions also reveals the greater affinity of the CS-GO SPR sensor to them, thus supporting the rationale for obtaining K for these two heavy metals. This study provides a better understanding on the sensing performance of such sensors in detecting heavy metal ions.
In this paper, the influence of processing input parameters on the heat-affected zone (HAZ) of three different material thicknesses of sugar palm fiber reinforced unsaturated polyester (SPF-UPE) composites cut with a CO2 laser was investigated. Laser power, traverse speed, and gas pressure were selected as the most influential input parameters on the HAZ to optimize the HAZ response with fixing all of the other input parameters. Taguchi's method was used to determine the levels of parameters that give the best response to the HAZ. The significance of input parameters was also determined by calculating the max-min variance of the average of the signal-to-noise ratio (S/N) ratio for each parameter. Analysis of variation (ANOVA) was used to determine each input parameter's contribution to the influence on HAZ depth. The general results show that the minimum levels of laser power and the highest levels of traverse speed and gas pressure gave the optimum response to the HAZ. Gas pressure had the most significant effect on the HAZ, with contribution decreases as the material thickness increased, followed by the traverse speed with contribution increases with the increase in material thickness. Laser power came third, with a minimal contribution to the effect on the HAZ, and it did not show a clear relationship with the change in material thickness. By applying the optimum parameters, the desired HAZ depth could be obtained at relatively low values.
The purpose of this study was to determine the effects of noise type, signal-to-noise ratio (SNR), age, and hearing status on cortical auditory evoked potentials (CAEPs) to speech sounds. This helps to explain the hearing-in-noise difficulties often seen in the aging and hearing impaired population. Continuous, modulated, and babble noise types were presented at varying SNRs to 30 individuals divided into three groups according to age and hearing status. Significant main effects of noise type, SNR, and group were found. Interaction effects revealed that the SNR effect varies as a function of noise type and is most systematic for continuous noise. Effects of age and hearing loss were limited to CAEP latency and were differentially modulated by energetic and informational-like masking. It is clear that the spectrotemporal characteristics of signals and noises play an important role in determining the morphology of neural responses. Participant factors such as age and hearing status, also play an important role in determining the brain's response to complex auditory stimuli and contribute to the ability to listen in noise.
A critical step in detection of primary intracerebral haemorrhage (ICH) is an accurate assessment of computed tomography (CT) brain images. The correct diagnosis relies on imaging modality and quality of acquired images. The authors present an enhancement algorithm which can improve the clarity of edges on CT images. About 40 samples of CT brain images with final diagnosis of primary ICH were obtained from the UKM Medical Centre in Digital Imaging and Communication in Medicine format. The images resized from 512 × 512 to 256 × 256 pixel resolution to reduce processing time. This Letter comprises of two main sections; the first is denoising using Wiener filter, non-local means and wavelet; the second section focuses on image enhancement using a modified unsharp masking (UM) algorithm to improve the visualisation of ICH. The combined approach of Wiener filter and modified UM algorithm outperforms other combinations with average values of mean square error, peak signal-to-noise ratio, variance and structural similarity index of 2.89, 31.72, 0.12 and 0.98, respectively. The reliability of proposed algorithm was evaluated by three blinded assessors which achieved a median score of 65%. This approach provides reliable validation for the proposed algorithm which has potential in improving image analysis.
A widely tunable low stimulated Brillouin scattering (SBS) photonic crystal fiber (PCF) based multi-wavelength Brillouin-erbium fiber laser is presented. The fiber laser structure utilizes a pre-amplified Brillouin pump (BP) technique with 100 m of PCF and a tunable band-pass filter within a Fabry-Perot cavity. A total of 14 Brillouin Stokes lines can be tuned over 29 nm from 1540 nm to 1569 nm. The wide tunability was only limited by the bandwidth of the tunable band-pass filter. A constant channel spacing of 0.079 nm and signal to noise ratio (SNR) of more than 20 dB for each Brillouin Stokes lines were also observed.
Image noise is a variation of uneven pixel values that occurs randomly. A good estimation of image noise parameters is crucial in image noise modeling, image denoising, and image quality assessment. To the best of our knowledge, there is no single estimator that can predict all noise parameters for multiple noise types. The first contribution of our research was to design a noise data feature extractor that can effectively extract noise information from the image pair. The second contribution of our work leveraged other noise parameter estimation algorithms that can only predict one type of noise. Our proposed method, DE-G, can estimate additive noise, multiplicative noise, and impulsive noise from single-source images accurately. We also show the capability of the proposed method in estimating multiple corruptions.
Interference resulting from Cognitive Radios (CRs) is the most important aspect of cognitive radio networks that leads to degradation in Quality of Service (QoS) in both primary and CR systems. Power control is one of the efficient techniques that can be used to reduce interference and satisfy the Signal-to-Interference Ratio (SIR) constraint among CRs. This paper proposes a new distributed power control algorithm based on game theory approach in cognitive radio networks. The proposal focuses on the channel status of cognitive radio users to improve system performance. A new cost function for SIR-based power control via a sigmoid weighting factor is introduced. The existence of Nash Equilibrium and convergence of the algorithm are also proved. The advantage of the proposed algorithm is the possibility to utilize and implement it in a distributed manner. Simulation results show considerable savings on Nash Equilibrium power compared to relevant algorithms while reduction in achieved SIR is insignificant.
Spectrum scarcity is a major challenge in wireless communications systems requiring efficient usage and utilization. Cognitive radio network (CRN) is found as a promising technique to solve this problem of spectrum scarcity. It allows licensed and unlicensed users to share the same licensed spectrum band. Interference resulting from cognitive radios (CRs) has undesirable effects on quality of service (QoS) of both licensed and unlicensed systems where it causes degradation in received signal-to-noise ratio (SIR) of users. Power control is one of the most important techniques that can be used to mitigate interference and guarantee QoS in both systems. In this paper, we develop a new approach of a distributed power control for CRN based on utility and pricing. QoS of CR user is presented as a utility function via pricing and a distributed power control as a non-cooperative game in which users maximize their net utility (utility-price). We define the price as a real function of transmit power to increase pricing charge of the farthest CR users. We prove that the power control game proposed in this study has Nash Equilibrium as well as it is unique. The obtained results show that the proposed power control algorithm based on a new utility function has a significant reduction in transmit power consumption and high improvement in speed of convergence.
Characterizing dementia is a global challenge in supporting personalized health care. The electroencephalogram (EEG) is a promising tool to support the diagnosis and evaluation of abnormalities in the human brain. The EEG sensors record the brain activity directly with excellent time resolution. In this study, EEG sensor with 19 electrodes were used to test the background activities of the brains of five vascular dementia (VaD), 15 stroke-related patients with mild cognitive impairment (MCI), and 15 healthy subjects during a working memory (WM) task. The objective of this study is twofold. First, it aims to enhance the recorded EEG signals using a novel technique that combines automatic independent component analysis (AICA) and wavelet transform (WT), that is, the AICA-WT technique; second, it aims to extract and investigate the spectral features that characterize the post-stroke dementia patients compared to the control subjects. The proposed AICA-WT technique is a four-stage approach. In the first stage, the independent components (ICs) were estimated. In the second stage, three-step artifact identification metrics were applied to detect the artifactual components. The components identified as artifacts were marked as critical and denoised through DWT in the third stage. In the fourth stage, the corrected ICs were reconstructed to obtain artifact-free EEG signals. The performance of the proposed AICA-WT technique was compared with those of two other techniques based on AICA and WT denoising methods using cross-correlation X C o r r and peak signal to noise ratio ( P S N R ) (ANOVA, p ˂ 0.05). The AICA-WT technique exhibited the best artifact removal performance. The assumption that there would be a deceleration of EEG dominant frequencies in VaD and MCI patients compared with control subjects was assessed with AICA-WT (ANOVA, p ˂ 0.05). Therefore, this study may provide information on post-stroke dementia particularly VaD and stroke-related MCI patients through spectral analysis of EEG background activities that can help to provide useful diagnostic indexes by using EEG signal processing.
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.
Current wavelet thresholding methods for cardiogram signals captured by flexible wearable sensors face a challenge in achieving both accurate thresholding and real-time signal denoising. This paper proposes a real-time accurate thresholding method based on signal estimation, specifically the normalized ACF, as an alternative to traditional noise estimation without the need for parameter fine-tuning and extensive data training. This method is experimentally validated using a variety of electrocardiogram (ECG) signals from different databases, each containing specific types of noise such as additive white Gaussian (AWG) noise, baseline wander noise, electrode motion noise, and muscle artifact noise. Although this method only slightly outperforms other methods in removing AWG noise in ECG signals, it far outperforms conventional methods in removing other real noise. This is attributed to the method's ability to accurately distinguish not only AWG noise that is significantly different spectrum of the ECG signal, but also real noise with similar spectra. In contrast, the conventional methods are effective only for AWG noise. In additional, this method improves the denoising visualization of the measured ECG signals and can be used to optimize other parameters of other wavelet methods to enhancing the denoised periodic signals, thereby improving diagnostic accuracy.