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On optimizing the blocking step of indirect enzyme-linked immunosorbent assay for Epstein-Barr virus serology

Lim CS, Krishnan G, Sam CK, Ng CC

Clin Chim Acta, 2013 Jan 16;415:158-61.
PMID: 23043757 DOI: 10.1016/j.cca.2012.08.031

Because blocking agent occupies most binding surface of a solid phase, its ability to prevent nonspecific binding determines the signal-to-noise ratio (SNR) and reliability of an enzyme-linked immunosorbent assay (ELISA).

Matched MeSH terms: Signal-To-Noise Ratio
The quantification of PET-CT radiotracers to determine minimal scan time using quadratic formulation

Said MA, Musarudin M, Zulkaffli NF

Ann Nucl Med, 2020 Dec;34(12):884-891.
PMID: 33141408 DOI: 10.1007/s12149-020-01543-x

OBJECTIVE: 18F is the most extensively used radioisotope in current clinical practices of PET imaging. This selection is based on the several criteria of pure PET radioisotopes with an optimum half-life, and low positron energy that contributes to a smaller positron range. In addition to 18F, other radioisotopes such as 68Ga and 124I are currently gained much attention with the increase in interest in new PET tracers entering the clinical trials. This study aims to determine the minimal scan time per bed position (Tmin) for the 124I and 68Ga based on the quantitative differences in PET imaging of 68Ga and 124I relative to 18F.
METHODS: The European Association of Nuclear Medicine (EANM) procedure guidelines version 2.0 for FDG-PET tumor imaging has adhered for this purpose. A NEMA2012/IEC2008 phantom was filled with tumor to background ratio of 10:1 with the activity concentration of 30 kBq/ml ± 10 and 3 kBq/ml ± 10% for each radioisotope. The phantom was scanned using different acquisition times per bed position (1, 5, 7, 10 and 15 min) to determine the Tmin. The definition of Tmin was performed using an image coefficient of variations (COV) of 15%.
RESULTS: Tmin obtained for 18F, 68Ga and 124I were 3.08, 3.24 and 32.93 min, respectively. Quantitative analyses among 18F, 68Ga and 124I images were performed. Signal-to-noise ratio (SNR), contrast recovery coefficients (CRC), and visibility (VH) are the image quality parameters analysed in this study. Generally, 68Ga and 18F gave better image quality as compared to 124I for all the parameters studied.
CONCLUSION: We have defined Tmin for 18F, 68Ga and 124I SPECT CT imaging based on NEMA2012/IEC2008 phantom imaging. Despite the long scanning time suggested by Tmin, improvement in the image quality is acquired especially for 124I. In clinical practice, the long acquisition time, nevertheless, may cause patient discomfort and motion artifact.

Matched MeSH terms: Signal-To-Noise Ratio
Investigating the performance of an amplitude-independent algorithm for detecting the hand muscle activity of stroke survivors

Hameed HK, Wan Hasan WZ, Shafie S, Ahmad SA, Jaafar H, Inche Mat LN

J Med Eng Technol, 2020 Apr;44(3):139-148.
PMID: 32396756 DOI: 10.1080/03091902.2020.1753838

To make robotic hand devices controlled by surface electromyography (sEMG) signals feasible and practical tools for assisting patients with hand impairments, the problems that prevent these devices from being widely used have to be overcome. The most significant problem is the involuntary amplitude variation of the sEMG signals due to the movement of electrodes during forearm motion. Moreover, for patients who have had a stroke or another neurological disease, the muscle activity of the impaired hand is weak and has a low signal-to-noise ratio (SNR). Thus, muscle activity detection methods intended for controlling robotic hand devices should not depend mainly on the amplitude characteristics of the sEMG signal in the detection process, and they need to be more reliable for sEMG signals that have a low SNR. Since amplitude-independent muscle activity detection methods meet these requirements, this paper investigates the performance of such a method on people who have had a stroke in terms of the detection of weak muscle activity and resistance to false alarms caused by the involuntary amplitude variation of sEMG signals; these two parameters are very important for achieving the reliable control of robotic hand devices intended for people with disabilities. A comparison between the performance of an amplitude-independent muscle activity detection algorithm and three amplitude-dependent algorithms was conducted by using sEMG signals recorded from six hemiparesis stroke survivors and from six healthy subjects. The results showed that the amplitude-independent algorithm performed better in terms of detecting weak muscle activity and resisting false alarms.

Matched MeSH terms: Signal-To-Noise Ratio
Fulltext Multi-level basis selection of wavelet packet decomposition tree for heart sound classification

Safara F, Doraisamy S, Azman A, Jantan A, Abdullah Ramaiah AR

Comput Biol Med, 2013 Oct;43(10):1407-14.
PMID: 24034732 DOI: 10.1016/j.compbiomed.2013.06.016

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.

Matched MeSH terms: Signal-To-Noise Ratio
Fulltext Tamper localization and lossless recovery watermarking scheme with ROI segmentation and multilevel authentication

Liew SC, Liew SW, Zain JM

J Digit Imaging, 2013 Apr;26(2):316-25.
PMID: 22555905 DOI: 10.1007/s10278-012-9484-4

Tamper localization and recovery watermarking scheme can be used to detect manipulation and recover tampered images. In this paper, a tamper localization and lossless recovery scheme that used region of interest (ROI) segmentation and multilevel authentication was proposed. The watermarked images had a high average peak signal-to-noise ratio of 48.7 dB and the results showed that tampering was successfully localized and tampered area was exactly recovered. The usage of ROI segmentation and multilevel authentication had significantly reduced the time taken by approximately 50 % for the tamper localization and recovery processing.

Matched MeSH terms: Signal-To-Noise Ratio
Fulltext Acoustic cardiac signals analysis: a Kalman filter-based approach

Salleh SH, Hussain HS, Swee TT, Ting CM, Noor AM, Pipatsart S, et al.

Int J Nanomedicine, 2012;7:2873-81.
PMID: 22745550 DOI: 10.2147/IJN.S32315

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.

Matched MeSH terms: Signal-To-Noise Ratio
An expectation-maximization algorithm based Kalman smoother approach for single-trial estimation of event-related potentials

Ting CM, Samdin SB, Salleh ShH, Omar MH, Kamarulafizam I

Annu Int Conf IEEE Eng Med Biol Soc, 2012;2012:6534-8.
PMID: 23367426 DOI: 10.1109/EMBC.2012.6347491

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.

Matched MeSH terms: Signal-To-Noise Ratio
Correlation between subjective and objective assessment of magnetic resonance (MR) images

Chow LS, Rajagopal H, Paramesran R, Alzheimer's Disease Neuroimaging Initiative

Magn Reson Imaging, 2016 07;34(6):820-831.
PMID: 26969762 DOI: 10.1016/j.mri.2016.03.006

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.

Matched MeSH terms: Signal-To-Noise Ratio
Fulltext Increasing iterative reconstruction strength at low tube voltage in coronary CT angiography protocols using 3D-printed and Catphan® 500 phantoms

Abdullah KA, McEntee MF, Reed WM, Kench PL

J Appl Clin Med Phys, 2020 Sep;21(9):209-214.
PMID: 32657493 DOI: 10.1002/acm2.12977

PURPOSE: The purpose of this study was to investigate the effect of increasing iterative reconstruction (IR) algorithm strength at different tube voltages in coronary computed tomography angiography (CCTA) protocols using a three-dimensional (3D)-printed and Catphan® 500 phantoms.
METHODS: A 3D-printed cardiac insert and Catphan 500 phantoms were scanned using CCTA protocols at 120 and 100 kVp tube voltages. All CT acquisitions were reconstructed using filtered back projection (FBP) and Adaptive Statistical Iterative Reconstruction (ASIR) algorithm at 40% and 60% strengths. Image quality characteristics such as image noise, signal-noise ratio (SNR), contrast-noise ratio (CNR), high spatial resolution, and low contrast resolution were analyzed.
RESULTS: There was no significant difference (P > 0.05) between 120 and 100 kVp measures for image noise for FBP vs ASIR 60% (16.6 ± 3.8 vs 16.7 ± 4.8), SNR of ASIR 40% vs ASIR 60% (27.3 ± 5.4 vs 26.4 ± 4.8), and CNR of FBP vs ASIR 40% (31.3 ± 3.9 vs 30.1 ± 4.3), respectively. Based on the Modulation Transfer Function (MTF) analysis, there was a minimal change of image quality for each tube voltage but increases when higher strengths of ASIR were used. The best measure of low contrast detectability was observed at ASIR 60% at 120 kVp.
CONCLUSIONS: Changing the IR strength has yielded different image quality noise characteristics. In this study, the use of 100 kVp and ASIR 60% yielded comparable image quality noise characteristics to the standard CCTA protocols using 120 kVp of ASIR 40%. A combination of 3D-printed and Catphan® 500 phantoms could be used to perform CT dose optimization protocols.

Matched MeSH terms: Signal-To-Noise Ratio
Analysis of model-based and model-free CEST effect quantification methods for different medical applications

Foo LS, Yap WS, Hum YC, Manan HA, Tee YK

J Magn Reson, 2020 01;310:106648.
PMID: 31760147 DOI: 10.1016/j.jmr.2019.106648

Chemical exchange saturation transfer (CEST) magnetic resonance imaging (MRI) holds great potential to provide new metabolic information for clinical applications such as tumor, stroke and Parkinson's Disease diagnosis. Many active research and developments have been conducted to translate this emerging MRI technique for routine clinical applications. In general, there are two CEST quantification techniques: (i) model-free and (ii) model-based techniques. The reliability of these quantification techniques depends heavily on the experimental conditions and quality of the collected data. Errors such as noise may lead to misleading quantification results and thus inaccurate diagnosis when CEST imaging becomes a standard or routine imaging scan in the future. This paper investigates the accuracy and robustness of these quantification techniques under different signal-to-noise (SNR) levels and magnetic field strengths. The quantified CEST effect before and after adding random Gaussian White Noise using model-free and model-based quantification techniques were compared. It was found that the model-free technique consistently yielded larger average percentage error across all tested parameters compared to its model-based counterpart, and that the model-based technique could withstand SNR of about 3 times lower than the model-free technique. When applied on noisy brain tumor, ischemic stroke, and Parkinson's Disease clinical data, the model-free technique failed to produce significant differences between normal and abnormal tissue whereas the model-based technique consistently generated significant differences. Although the model-free technique was less accurate and robust, its simplicity and thus speed would still make it a good approximate when the SNR was high (>50) or when the CEST effect was large and well-defined. For more accurate CEST quantification, model-based techniques should be considered. When SNR was low (<50) and the CEST effect was small such as those acquired from clinical field strength scanners, which are generally 3T and below, model-based techniques should be considered over model-free counterpart to maintain an average percentage error of less than 44% even under very noisy condition as tested in this work.

Matched MeSH terms: Signal-To-Noise Ratio
Fulltext Automatic Artifact Removal in EEG of Normal and Demented Individuals Using ICA-WT during Working Memory Tasks

Al-Qazzaz NK, Hamid Bin Mohd Ali S, Ahmad SA, Islam MS, Escudero J

Sensors (Basel), 2017 Jun 08;17(6).
PMID: 28594352 DOI: 10.3390/s17061326

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.

Matched MeSH terms: Signal-To-Noise Ratio
Reducing charging effects in scanning electron microscope images by Rayleigh contrast stretching method (RCS)

Wan Ismail WZ, Sim KS, Tso CP, Ting HY

Scanning, 2011 Jul-Aug;33(4):233-51.
PMID: 21611953 DOI: 10.1002/sca.20237

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.

Matched MeSH terms: Signal-To-Noise Ratio
Effect of iterative reconstruction algorithm levels on noise index and figure-of-merit in CT pulmonary angiography examinations

Harun HH, Karim MKA, Abbas Z, Sabarudin A, Muniandy SC, Ibahim MJ

J Xray Sci Technol, 2020;28(5):893-903.
PMID: 32741801 DOI: 10.3233/XST-200699

PURPOSE: To evaluate the influence of iterative reconstruction (IR) levels on Computed Tomography (CT) image quality and to establish Figure of Merit (FOM) value for CT Pulmonary Angiography (CTPA) examinations.
METHODS: Images of 31 adult patients who underwent CTPA examinations in our institution from March to April 2019 were retrospectively collected. Other data, such as scanning parameters, radiation dose and body habitus information from the subjects were also recorded. Six different levels of IR were applied to the volume data of the subjects. Five circles of the region of interest (ROI) were drawn in five different arteries namely, pulmonary trunk, right pulmonary artery, left pulmonary artery, ascending aorta and descending aorta. The mean Signal-to-noise ratio (SNR) was obtained, and the FOM was calculated in a fraction of the SNR2 divided by volume-weighted CT dose index (CTDIvol) and SNR2 divided by the size-specific dose estimates (SSDE).
RESULTS: Overall, we observed that the mean value of CTDIvol and SSDE were 13.79±7.72 mGy and 17.25±8.92 mGy, respectively. Notably, SNR values significantly increase with increase of the IR level (p

Matched MeSH terms: Signal-To-Noise Ratio
Fulltext Evaluation of an integrated 3D-printed phantom for coronary CT angiography using iterative reconstruction algorithm

Abdullah KA, McEntee MF, Reed W, Kench PL

J Med Radiat Sci, 2020 Sep;67(3):170-176.
PMID: 32219989 DOI: 10.1002/jmrs.387

INTRODUCTION: 3D-printed imaging phantoms are now increasingly available and used for computed tomography (CT) dose optimisation study and image quality analysis. The aim of this study was to evaluate the integrated 3D-printed cardiac insert phantom when evaluating iterative reconstruction (IR) algorithm in coronary CT angiography (CCTA) protocols.
METHODS: The 3D-printed cardiac insert phantom was positioned into a chest phantom and scanned with a 16-slice CT scanner. Acquisitions were performed with CCTA protocols using 120 kVp at four different tube currents, 300, 200, 100 and 50 mA (protocols A, B, C and D, respectively). The image data sets were reconstructed with a filtered back projection (FBP) and three different IR algorithm strengths. The image quality metrics of image noise, signal-noise ratio (SNR) and contrast-noise ratio (CNR) were calculated for each protocol.
RESULTS: Decrease in dose levels has significantly increased the image noise, compared to FBP of protocol A (P

Matched MeSH terms: Signal-To-Noise Ratio
Fulltext Gaussian smoothing and modified histogram normalization methods to improve neural-biomarker interpretations for dyslexia classification mechanism

Usman OL, Muniyandi RC, Omar K, Mohamad M

PLoS One, 2021;16(2):e0245579.
PMID: 33630876 DOI: 10.1371/journal.pone.0245579

Achieving biologically interpretable neural-biomarkers and features from neuroimaging datasets is a challenging task in an MRI-based dyslexia study. This challenge becomes more pronounced when the needed MRI datasets are collected from multiple heterogeneous sources with inconsistent scanner settings. This study presents a method of improving the biological interpretation of dyslexia's neural-biomarkers from MRI datasets sourced from publicly available open databases. The proposed system utilized a modified histogram normalization (MHN) method to improve dyslexia neural-biomarker interpretations by mapping the pixels' intensities of low-quality input neuroimages to range between the low-intensity region of interest (ROIlow) and high-intensity region of interest (ROIhigh) of the high-quality image. This was achieved after initial image smoothing using the Gaussian filter method with an isotropic kernel of size 4mm. The performance of the proposed smoothing and normalization methods was evaluated based on three image post-processing experiments: ROI segmentation, gray matter (GM) tissues volume estimations, and deep learning (DL) classifications using Computational Anatomy Toolbox (CAT12) and pre-trained models in a MATLAB working environment. The three experiments were preceded by some pre-processing tasks such as image resizing, labelling, patching, and non-rigid registration. Our results showed that the best smoothing was achieved at a scale value, σ = 1.25 with a 0.9% increment in the peak-signal-to-noise ratio (PSNR). Results from the three image post-processing experiments confirmed the efficacy of the proposed methods. Evidence emanating from our analysis showed that using the proposed MHN and Gaussian smoothing methods can improve comparability of image features and neural-biomarkers of dyslexia with a statistically significantly high disc similarity coefficient (DSC) index, low mean square error (MSE), and improved tissue volume estimations. After 10 repeated 10-fold cross-validation, the highest accuracy achieved by DL models is 94.7% at a 95% confidence interval (CI) level. Finally, our finding confirmed that the proposed MHN method significantly outperformed the normalization method of the state-of-the-art histogram matching.

Matched MeSH terms: Signal-To-Noise Ratio
Fulltext Cortical signal-in-noise coding varies by noise type, signal-to-noise ratio, age, and hearing status

Maamor N, Billings CJ

Neurosci Lett, 2017 01 01;636:258-264.
PMID: 27838448 DOI: 10.1016/j.neulet.2016.11.020

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.

Matched MeSH terms: Signal-To-Noise Ratio*
Computer assisted diagnostic system in tumor radiography

Faisal A, Parveen S, Badsha S, Sarwar H, Reza AW

J Med Syst, 2013 Jun;37(3):9938.
PMID: 23504472 DOI: 10.1007/s10916-013-9938-3

An improved and efficient method is presented in this paper to achieve a better trade-off between noise removal and edge preservation, thereby detecting the tumor region of MRI brain images automatically. Compass operator has been used in the fourth order Partial Differential Equation (PDE) based denoising technique to preserve the anatomically significant information at the edges. A new morphological technique is also introduced for stripping skull region from the brain images, which consequently leading to the process of detecting tumor accurately. Finally, automatic seeded region growing segmentation based on an improved single seed point selection algorithm is applied to detect the tumor. The method is tested on publicly available MRI brain images and it gives an average PSNR (Peak Signal to Noise Ratio) of 36.49. The obtained results also show detection accuracy of 99.46%, which is a significant improvement than that of the existing results.

Matched MeSH terms: Signal-To-Noise Ratio
Simultaneous analysis of silicon and boron dissolved in water by combination of electrodialytic salt removal and ion-exclusion chromatography with corona charged aerosol detection

Mori M, Sagara K, Arai K, Nakatani N, Ohira S, Toda K, et al.

J Chromatogr A, 2016 Jan 29;1431:131-7.
PMID: 26755416 DOI: 10.1016/j.chroma.2015.12.064

Selective separation and sensitive detection of dissolved silicon and boron (DSi and DB) in aqueous solution was achieved by combining an electrodialytic ion isolation device (EID) as a salt remover, an ion-exclusion chromatography (IEC) column, and a corona charged aerosol detector (CCAD) in sequence. DSi and DB were separated by IEC on the H(+)-form of a cation exchange resin column using pure water eluent. DSi and DB were detected after IEC separation by the CCAD with much greater sensitivity than by conductimetric detection. The five-channel EID, which consisted of anion and cation acceptors, cathode and anode isolators, and a sample channel, removed salt from the sample prior to the IEC-CCAD. DSi and DB were scarcely attracted to the anion accepter in the EID and passed almost quantitatively through the sample channel. Thus, the coupled EID-IEC-CCAD device can isolate DSi and DB from artificial seawater and hot spring water by efficiently removing high concentrations of Cl(-) and SO4(2-) (e.g., 98% and 80% at 0.10molL(-1) each, respectively). The detection limits at a signal-to-noise ratio of 3 were 0.52μmolL(-1) for DSi and 7.1μmolL(-1) for DB. The relative standard deviations (RSD, n=5) of peak areas were 0.12% for DSi and 4.3% for DB.

Matched MeSH terms: Signal-To-Noise Ratio
Fulltext A novel utility function for energy-efficient power control game in cognitive radio networks

Al-Gumaei YA, Noordin KA, Reza AW, Dimyati K

PLoS One, 2015;10(8):e0135137.
PMID: 26258522 DOI: 10.1371/journal.pone.0135137

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.

Matched MeSH terms: Signal-To-Noise Ratio
Fulltext Acoustic change complex in background noise: phoneme level and timing effects

Billings CJ, Grush LD, Maamor N

Physiol Rep, 2017 Nov;5(20).
PMID: 29051305 DOI: 10.14814/phy2.13464

The effects of background noise on speech-evoked cortical auditory evoked potentials (CAEPs) can provide insight into the physiology of the auditory system. The purpose of this study was to determine background noise effects on neural coding of different phonemes within a syllable. CAEPs were recorded from 15 young normal-hearing adults in response to speech signals /s/, /ɑ/, and /sɑ/. Signals were presented at varying signal-to-noise ratios (SNRs). The effects of SNR and context (in isolation or within syllable) were analyzed for both phonemes. For all three stimuli, latencies generally decreased and amplitudes generally increased as SNR improved, and context effects were not present; however, the amplitude of the /ɑ/ response was the exception, showing no SNR effect and a significant context effect. Differential coding of /s/ and /ɑ/ likely result from level and timing differences. Neural refractoriness may result in the lack of a robust SNR effect on amplitude in the syllable context. The stable amplitude across SNRs in response to the vowel in /sɑ/ suggests the combined effects of (1) acoustic characteristics of the syllable and noise at poor SNRs and (2) refractory effects resulting from phoneme timing at good SNRs. Results provide insights into the coding of multiple-onset speech syllables in varying levels of background noise and, together with behavioral measures, may help to improve our understanding of speech-perception-in-noise difficulties.

Matched MeSH terms: Signal-To-Noise Ratio

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