Clinical Value of Dual-energy CT in Detection of Pancreatic Adenocarcinoma: Investigation of the Best Pancreatic Tumor Contrast to Noise Ratio

Objective To quantitatively compare and determine the best pancreatic tumor contrast to noise ratio (CNR) in different dual-energy derived datasets. Methods In this retrospective, single center study, 16 patients (9 male, 7 female, average age 59.4±13.2 years) with pathologically diagnosed pancreatic cancer were enrolled. All patients received an abdominal scan using a dual source CT scanner 7 to 31 days before biopsy or surgery. After injection of iodine contrast agent, arterial and pancreatic parenchyma phase were scanned consequently, using a dual-energy scan mode (100 kVp/230 mAs and Sn 140 kVp/178 mAs) in the pancreatic parenchyma phase. A series of derived dual-energy datasets were evaluated including non-liner blending (non-linear blending width 0-500 HU; blending center -500 to 500 HU), mono-energetic (40-190 keV), 100 kVp and 140 kVp. On each datasets, mean CT values of the pancreatic parenchyma and tumor, as well as standard deviation CT values of subcutaneous fat and psoas muscle were measured. Regions of interest of cutaneous fat and major psoas muscle of 100 kVp and 140 kVp images were calculated. Best CNR of subcutaneous fat (CNR F ) and CNR of the major psoas muscle (CNR M ) of non-liner blending and mono-energetic datasets were calculated with the optimal mono-energetic keV setting and the optimal blending center/width setting for the best CNR. One Way ANOVA test was used for comparison of best CNR between different dual-energy derived datasets. Results The best CNR F (4.48±1.29) was obtained from the non-liner blending datasets at blending center -16.6±103.9 HU and blending width 12.3±10.6 HU. The best CNR F (3.28±0.97) was obtained from the mono-energetic datasets at 73.3±4.3 keV. CNR F in the 100 kVp and 140 kVp were 3.02±0.91 and 1.56±0.56 respectively. Using fat as the noise background, all of these images series showed significant differences (P<0.01) except best CNR F of mono-energetic image sets vs. CNR F of 100 kVp image (P=0.460). Similar results were found using muscle as the noise background (mono-energetic image vs. 100 kVp image: P=0.246; mono-energetic image vs. non-liner blending image: P=0.044; others: P<0.01). Conclusion Compared with mono-energetic datasets and low kVp datasets, non-linear blending image at automatically chosen blending width/window provides better tumor to the pancreas CNR, which might be beneficial for better detection of pancreatic tumors.

A blind source separation algorithm based on negentropy and signal noise ratio

A novel blind source separation （BSS） algorithm based on the combination of negentropy and signal noise ratio （SNR） is presented to solve the deficiency of the traditional independent component analysis （ICA） algorithm after the introduction of the principle and algorithm of ICA. The main formulas in the novel algorithm are elaborated and the idiographic steps of the algorithm are given. Then the computer simulation is used to test the performance of this algorithm. Both the traditional FastlCA algorithm and the novel ICA algorithm are applied to separate mixed signal data. Experiment results show the novel method has a better performance in separating signals than the traditional FastlCA algorithm based on negentropy. The novel algorithm could estimate the source signals from the mixed signals more precisely.

Adaptive Bistable Stochastic Resonance Based Weak Signal Reception in Additive Laplacian Noise

Weak signal reception is a very important and challenging problem for communication systems especially in the presence of non-Gaussian noise,and in which case the performance of optimal linear correlated receiver degrades dramatically.Aiming at this,a novel uncorrelated reception scheme based on adaptive bistable stochastic resonance(ABSR)for a weak signal in additive Laplacian noise is investigated.By analyzing the key issue that the quantitative cooperative resonance matching relationship between the characteristics of the noisy signal and the nonlinear bistable system,an analytical expression of the bistable system parameters is derived.On this basis,by means of bistable system parameters self-adaptive adjustment,the counterintuitive stochastic resonance(SR)phenomenon can be easily generated at which the random noise is changed into a benefit to assist signal transmission.Finally,it is demonstrated that approximately 8dB bit error ratio(BER)performance improvement for the ABSR-based uncorrelated receiver when compared with the traditional uncorrelated receiver at low signal to noise ratio(SNR)conditions varying from-30dB to-5dB.

Influence of the nonlinear propagation effect on the optical signal-to-noise ratio of 400G optical fiber communication systems

The influence of the nonlinear propagation effect on three 400 Gb/s/ch （400G） optical fiber communication systems with typical modulation formats, dual-carrier 16-quadrature amplitude modulation （16QAM）, single-carrier 16QAM （single-16QAM）, and four-carrier quadrature phase-shift keying, are investigated. The received optical signal-to-noise ratio （OSNR）, affected by the nonlinear interference noise together with the amplified spontaneous emission noise, are compared with three 400G systems and a standard 100 Gb/s/ch system by numerical simulations. Both single channel and multichannel cases are considered. Single-16QAM is found to have the best OSNR among those modulation formats.

Noise reduction and signal to noise ratio improvement in magneto-optical polarization rotation measurement

The measurement of an extremely small magneto-optical polarization rotation angle with high sensitivity is integral to many scientific and technological applications. In this Letter, we have presented a technique based on Faraday modulation combined with the optical differential method to measure an extremely small polari- zation rotation angle with high sensitivity. The theoretical and experimental results show that common mode noise is reduced appreciably and signal to noise ratio is enhanced. The effectiveness of this technique has been demonstrated by measuring the Verdet constant of terbium gallium garnet glass and measuring the small polari- zation rotation angle. A sensitivity of enhancement of one order of magnitude has been achieved using differ- ential detection based on Faraday modulation.

Simultaneous optical signal to noise ratio and symbol rate estimation with blind chromatic dispersion compensation for auxiliary amplitude modulation optical signals

Based on the peak to valley ratio（PTVR） of the average magnitude difference function（AMDF）, we present a novel optical signal to noise ratio（OSNR） and symbol rate（SR） estimation method for commonly used auxiliary amplitude modulations（AAMs）. Moreover, it is demonstrated that the influence of chromatic dispersion（CD）on the method can be mitigated by maximizing the PTVR of the AMDF with additional tunable dispersion compensators. The results of simulations show that the OSNR estimation error can be kept within 0.8 dB in the wide OSNR range of（12, 32） dB, while the SR estimation error is below 0.079% for four widely used10 Gsymbol/s AAM signals.

Numerical analysis of Raman amplification and optical signal-to-noise ratio in a photonic crystal fiber

A numerical design on the triangular photonic crystal fiber （PCF） based backward multi-pump Raman amplifier is presented. It is demonstrated that high flat Raman gain can be reached based on PCF. Influences of different geometric parameters and germanium doping concentrations on the Raman net gain, amplified spontaneous emission （ASE） noise and double Rayleigh backscattering （DRBS） of the signal have been analyzed. For optimizing crystal fiber Raman amplifier （FRA）, there is tradeoff between the geometric parameter and germanium doping concentration of triangular PCF. The results show that PCF is an appropriate candidate for high gain Raman amplifiers.

An Algorithm to Reduce Compression Ratio in Multimedia Applications

In recent years,it has been evident that internet is the most effective means of transmitting information in the form of documents,photographs,or videos around the world.The purpose of an image compression method is to encode a picture with fewer bits while retaining the decompressed image’s visual quality.During transmission,this massive data necessitates a lot of channel space.In order to overcome this problem,an effective visual compression approach is required to resize this large amount of data.This work is based on lossy image compression and is offered for static color images.The quantization procedure determines the compressed data quality characteristics.The images are converted from RGB to International Commission on Illumination CIE La^(∗)b^(∗);and YCbCr color spaces before being used.In the transform domain,the color planes are encoded using the proposed quantization matrix.To improve the efficiency and quality of the compressed image,the standard quantization matrix is updated with the respective image block.We used seven discrete orthogonal transforms,including five variations of the Complex Hadamard Transform,Discrete Fourier Transform and Discrete Cosine Transform,as well as thresholding,quantization,de-quantization and inverse discrete orthogonal transforms with CIE La^(∗)b^(∗);and YCbCr to RGB conversion.Peak to signal noise ratio,signal to noise ratio,picture similarity index and compression ratio are all used to assess the quality of compressed images.With the relevant transforms,the image size and bits per pixel are also explored.Using the(n,n)block of transform,adaptive scanning is used to acquire the best feasible compression ratio.Because of these characteristics,multimedia systems and services have a wide range of possible applications.

The most homogeneous dip-scanning method using edgepreserving smoothing for seismic noise attenuation

Highlighting and analyzing the geological features of faults and fractures in seismic data is particularly important for hydrocarbon exploration and exploitation since they are often essential for finding and delineating reservoirs. We apply edge-preserving smoothing （EPS） to seismic processing and propose a most homogeneous dip-scanning method. The method preserves the geological features, eliminate random noise efficiently, obtain dip information, and improve the accuracy of identifying the oil and gas traps.

A Novel Peak-to-Average Power Ratio Reduction Scheme via Tone Reservation in OFDM Systems

In this paper, a novel signal-to-clipping noise ratio and least squares approximation tone reservation scheme(SCR-LSA TR) is proposed to reduce the peak-to-average power ratio for orthogonal frequency division multiplexing systems. During the SCR procedure, only the element with the maximal amplitude is picked for processing, which not only decreases the algorithm complexity, but also helps to overcome the BER deterioration. With the LSA method, the amplitude of the peak-cancelling signals can approximate to that of the original clipping noise as much as possible. Through the combination of the optimization factor in the LSA method, the classic SCR method can achieve better PAPR reduction with faster convergence. Simulation results show that the proposed SCR-LSA TR scheme has less in-band distortion and smaller out-of-band spectral radiation. The BER of the proposed scheme shows a better performance especially under the 16-QAM over the additive white Gaussian noise channel.

Arrival time measurements of first arrival phases P and PKIKP using the method of fixed scale wavelet transformation ratio

The arrival times of first teleseismic phases are difficult to be measured precisely because of slowly and gradually changed onsets and weak amplitudes. The arrival times measured manually are usually behind the real ones. In this paper, using the ratio method of fixed scale wavelet transformations improved by us, the arrival times for the first arrival phases (such as P and PKIKP) at the teleseismic and far-teleseismic distances were measured. The results are reasonable and reliable based on the analysis and discussion of the reliabilities and errors.

Effect of Asymmetric Potential and Gaussian Colored Noise on Stochastic Resonance

The phenomenon of stochastic resonance （SR） in a bistable nonlinear system is studied when the system is driven by the asymmetric potential and additive Gaussian colored noise. Using the unified colored noise approximation method, the additive Gaussian colored noise can be simplified to additive Gaussian white noise. The signal-to-noise ratio （SNR） is calculated according to the generalized two-state theory （shown in [H.S. Wio and S. Bouzat, Brazilian J.Phys. 29 （1999） 136]）. We find that the SNR increases with the proximity of a to zero. In addition, the correlation time T between the additive Gaussian colored noise is also an ingredient to improve SR. The shorter the correlation time T between the Gaussian additive colored noise is, the higher of the peak value of SNR.

Signal Separation and Instantaneous Frequency Estimation Based on Multi-scale Chirplet Sparse Signal Decomposition

An approach based on multi-scale ehirplet sparse signal decomposition is proposed to separate the malti-component polynomial phase signals, and estimate their instantaneous frequencies. In this paper, we have generated a family of multi-scale chirplet functions which provide good local correlations of chirps over shorter time interval. At every decomposition stage, we build the so-called family of chirplets and our idea is to use a structured algorithm which exploits information in the family to chain chirplets together adaptively as to form the polyncmial phase signal component whose correlation with the current residue signal is largest. Simultaueously, the polynomial instantaneous frequency is estimated by connecting the linear frequency of the chirplet functions adopted in the current separation. Simulation experiment demonstrated that this method can separate the camponents of the multi-component polynamial phase signals effectively even in the low signal-to-noise ratio condition, and estimate its instantaneous frequency accurately.

The Ultimate Noise Limit for Hall Plates in Voltage, Current, and Hybrid Operating Modes

If Hall plates are used as magnetic field sensors they are usually powered up by a current source connected to a pair of non-neighboring contacts. The output voltage is tapped at another pair of non-neighboring contacts. In this paper we study more general operating conditions of Hall plates with an arbitrary number of contacts. In such hybrid operating modes current sources are connected to a first set of contacts and voltage sources to a second set of contacts. Output voltages are tapped at the first set of contacts and output currents are measured at the second set of contacts. All these output signals are multiplied by coefficients and added up. The purpose of this work is to figure out which operating mode and which Hall plate achieve maximum signal at minimum thermal noise and power dissipation. To this end we develop a theory, which gives the ratio of signal over noise and power as a function of the resistance matrix of Hall plates, of the supply voltages and currents, and of the coefficients. Optimization is done analytically in closed form and numerically for specific examples. The results are: 1) all operating modes have identical noise performance if their parameters are optimized;2) for any Hall plate one can measure its resistance matrix and insert its values into our formulae to obtain the optimum supply currents and coefficients for optimum noise performance.

A Robust Asynchrophasor in PMU Using Second-Order Kalman Filter

Phasor Measurement Units(PMUs)provide Global Positioning System(GPS)time-stamped synchronized measurements of voltage and current with the phase angle of the system at certain points along with the grid system.Those synchronized data measurements are extracted in the form of amplitude and phase from various locations of the power grid to monitor and control the power system condition.A PMU device is a crucial part of the power equipment in terms of the cost and operative point of view.However,such ongoing development and improvement to PMUs’principal work are essential to the network operators to enhance the grid quality and the operating expenses.This paper introduces a proposed method that led to lowcost and less complex techniques to optimize the performance of PMU using Second-Order Kalman Filter.It is based on the Asyncrhophasor technique resulting in a phase error minimization when receiving the signal from an access point or from the main access point.The MATLAB model has been created to implement the proposed method in the presence of Gaussian and non-Gaussian.The results have shown the proposed method which is Second-Order Kalman Filter outperforms the existing model.The results were tested usingMean Square Error(MSE).The proposed Second-Order Kalman Filter method has been replaced with a synchronization unit into thePMUstructure to clarify the significance of the proposed new PMU.

Regulatory Genes Through Robust-SNR for Binary Classification Within Functional Genomics Experiments

The current study proposes a novel technique for feature selection by inculcating robustness in the conventional Signal to noise Ratio(SNR).The proposed method utilizes the robust measures of location i.e.,the“Median”as well as the measures of variation i.e.,“Median absolute deviation(MAD)and Interquartile range(IQR)”in the SNR.By this way,two independent robust signal-to-noise ratios have been proposed.The proposed method selects the most informative genes/features by combining the minimum subset of genes or features obtained via the greedy search approach with top-ranked genes selected through the robust signal-to-noise ratio(RSNR).The results obtained via the proposed method are compared with wellknown gene/feature selection methods on the basis of performance metric i.e.,classification error rate.A total of 5 gene expression datasets have been used in this study.Different subsets of informative genes are selected by the proposed and all the other methods included in the study,and their efficacy in terms of classification is investigated by using the classifier models such as support vector machine(SVM),Random forest(RF)and k-nearest neighbors(k-NN).The results of the analysis reveal that the proposed method(RSNR)produces minimum error rates than all the other competing feature selection methods in majority of the cases.For further assessment of the method,a detailed simulation study is also conducted.

An Enhanced Graphical Authentication Scheme Using Multiple-Image Steganography

Most remote systems require user authentication to access resources.Text-based passwords are still widely used as a standard method of user authentication.Although conventional text-based passwords are rather hard to remember,users often write their passwords down in order to compromise security.One of the most complex challenges users may face is posting sensitive data on external data centers that are accessible to others and do not be controlled directly by users.Graphical user authentication methods have recently been proposed to verify the user identity.However,the fundamental limitation of a graphi-cal password is that it must have a colorful and rich image to provide an adequate password space to maintain security,and when the user clicks and inputs a pass-word between two possible grids,the fault tolerance is adjusted to avoid this situation.This paper proposes an enhanced graphical authentication scheme,which comprises benefits over both recognition and recall-based graphical techniques besides image steganography.The combination of graphical authentication and steganography technologies reduces the amount of sensitive data shared between users and service providers and improves the security of user accounts.To evaluate the effectiveness of the proposed scheme,peak signal-to-noise ratio and mean squared error parameters have been used.

Doppler shift estimation methods in mobile communication systems

Several Doppler shift estimators, including mean logarithm envelope difference (MLED) method, auto-correlation function (ACF) method, zero crossing rate (ZCR) method and mean square phase difference (MSPD) method were discussed and compared. The estimation principle and theoretical estimation bias of these estimators under Rayleigh fading channels were analyzed; furthermore, the Cramer Rao bound (CRB) of Doppler shift estimation was deduced, and a novel modification method based on two-dimensional polynomial fitting was proposed to reduce the Doppler shift estimation bias. We verified our algorithms with the Monte Carlo computer simulation; simulation results showed better variance performance of modified methods than those of the original methods. In addition, the applicable situations of these estimators were discussed.

Analysis of geophone properties effects for land seismic data

The properties of the seismic geophones are important factors for high-resolution seismic exploration and have a great influence on data quality. For this reason, we have tested three kinds of geophones currently used in several regions with different geological features： desert, saline-alkali farmland, and carbonate areas in mountainous regions in order to test their property indexes. Based on the geophone vibration equation and from the property index effects ofgeophone and the connection of the geophones on seismic data, we analyzed seismic data quality acquired inthe tested regions and suggest that suitable geophone property indexes, reasonable choice of geophone types, and the suitable geophone connection can enhance the signal/noise ratio of seismic data.

Fourier Spectrometer based on Wide-range and Phase-locked Michelson Interferometer with Femtosecond Laser Excitation

A wide-range and phase-locked Michelson interferometer technique is described. This technique combined with femtosecond laser is used to measure the spectrum of the rare-earth ion Nd：YVO4, which presents very high signal to noise ratio of interferometric intensity output and higher spectral resolution than traditional grating spectrophotometer.