Image Steganography by Pixel-Value Differencing Using General Quantization Ranges

A new steganographic method by pixel-value differencing(PVD)using general quantization ranges of pixel pairs’difference values is proposed.The objective of this method is to provide a data embedding technique with a range table with range widths not limited to powers of 2,extending PVD-based methods to enhance their flexibility and data-embedding rates without changing their capabilities to resist security attacks.Specifically,the conventional PVD technique partitions a grayscale image into 1×2 non-overlapping blocks.The entire range[0,255]of all possible absolute values of the pixel pairs’grayscale differences in the blocks is divided into multiple quantization ranges.The width of each quantization range is a power of two to facilitate the direct embedding of the bit information with high embedding rates.Without using power-of-two range widths,the embedding rates can drop using conventional embedding techniques.In contrast,the proposed method uses general quantization range widths,and a multiple-based number conversion mechanism is employed skillfully to implement the use of nonpower-of-two range widths,with each pixel pair being employed to embed a digit in the multiple-based number.All the message bits are converted into a big multiple-based number whose digits can be embedded into the pixel pairs with a higher embedding rate.Good experimental results showed the feasibility of the proposed method and its resistance to security attacks.In addition,implementation examples are provided,where the proposed method adopts non-power-of-two range widths and employsmultiple-based number conversion to expand the data-hiding and steganalysis-resisting capabilities of other PVD methods.

Filtering of long-term dependent fractal noise in fiber optic gyroscope

Stochastic noises of fiber optic gyroscope （FOG） mainly contain white noise and fractal noise whose long-term dependent component causes FOG a rather slow drift. In order to eliminate this component, a two-step filtering methodology is proposed. Firstly, fractional differencing （FD） method is introduced to trans-form fractal noise into fractional white noise based on the estima-tion of Hurst exponent for long-term dependent fractal process, which together with the existing white noise make up of a gener-alized white noise. Further, an improved denoising algorithm of wavelet maxima is developed to suppress the generalized white noise. Experimental results show that the basic noise terms of FOG greatly decrease, and especially the slow drift is restrained effectively. The proposed methodology provides a promising ap-proach for filtering long-term dependent fractal noise.

Background Subtraction and Frame Difference Based Moving Object Detection for Real-Time Surveillance

A new real-time algorithm is proposed in this paperfor detecting moving object in color image sequencestaken from stationary cameras.This algorithm combines a temporal difference with an adaptive background subtraction where the combination is novel.Ⅷ1en changes OCCUr.the background is automatically adapted to suit the new conditions.Forthe background model,a new model is proposed with each frame decomposed into regions and the model is based not only upon single pixel but also on the characteristic of a region.The hybrid presentationincludes a model for single pixel information and a model for the pixel’s neighboring area information.This new model of background can both improve the accuracy of segmentation due to that spatialinformation is taken into account and salientl5r speed up the processing procedure because porlion of neighboring pixel call be selected into modeling.The algorithm was successfully used in a video surveillance systern and the experiment result showsit call obtain a clearer foreground than the singleframe difference or background subtraction method.

Digital Signal Processing Based Real Time Vehicular Detection System

Traffic monitoring is of major importance for enforcing traffic management policies.To accomplish this task,the detection of vehicle can be achieved by exploiting image analysis techniques.In this paper,a solution is presented to obtain various traffic parameters through vehicular video detection system(VVDS).VVDS exploits the algorithm based on virtual loops to detect moving vehicle in real time.This algorithm uses the background differencing method,and vehicles can be detected through luminance difference of pixels between background image and current image.Furthermore a novel technology named as spatio-temporal image sequences analysis is applied to background differencing to improve detection accuracy.Then a hardware implementation of a digital signal processing (DSP) based board is described in detail and the board can simultaneously process four-channel video from different cameras. The benefit of usage of DSP is that images of a roadway can be processed at frame rate due to DSP′s high performance.In the end,VVDS is tested on real-world scenes and experiment results show that the system is both fast and robust to the surveillance of transportation.

Dry/wet snow mapping based on the synergistic use of dual polarimetric SAR and multispectral data

We propose a multi-sensor multi-spectral and bi-temporal dual-polarimetric Synthetic Aperture Radar(SAR) data integration scheme for dry/wet snow mapping using Sentinel-2 and Sentinel-1 data which are freely available to the research community. The integration is carried out by incorporating the information retrieved from ratio images of the conventional method for wet snow mapping and the multispectral data in two different frameworks. Firstly, a simple differencing scheme is employed for dry/wet snow mapping, where the snow cover area is derived using the Normalized Differenced Snow Index(NDSI). In the second framework, the ratio images are stacked with the multispectral bands and this stack is used for supervised and unsupervised classification using support vector machines for dry/wet snow mapping. We also investigate the potential of a state of the art backscatter model for the identification of dry/wet snow using Sentinel-1 data. The results are validated using a reference map derived from RADARSAT-2 full polarimetric SAR data. A good agreement was observed between the results and the reference data with an overall accuracy greater than 0.78 for the different blending techniques examined. For all the proposed frameworks, the wet snow was better identified. The coefficient of determination between the snow wetness derived from the backscatter model and the reference based on RADARSAT-2 data was observed to be 0.58 with a significantly higher root mean square error of 1.03 % by volume.

Novel algorithm on DOA estimation for correlated sources under complex symmetric Toeplitz noise

To cope with the scenario where both uncorrelated sources and coherent sources coexist, a novel algorithm to direction of arrival （DOA） estimation for symmetric uniform linear array is presented. Under the condition of stationary colored noise field, the algorithm employs a spatial differencing method to eliminate the noise covariance matrix and uncorrelated sources, then a Toeplitz matrix is constructed for the remained coherent sources. After preprocessing, a propagator method （PM） is employed to find the DOAs without any eigendecomposition. The number of sources resolved by this approach can exceed the number of array elements at a lower computational complexity. Simulation results demonstrate the effectiveness and efficiency of the proposed method.

Differences of Grammar between British English and American English

The growth of American English (AE) was based on British English (BE), as we know, when we speak of their differences, however, they are not easily accepted, although they indeed exist. Here, I will illustrate this point from three questions. First, how American English growed? Second, how British and American English came to be different;? Third, where the grammatical differences lie?

Exponential time differencing based efficient SC-PML for RCS simulation

To efficiently simulate and calculate the radar cross section(RCS) related electromagnetic problems by employing the finite-difference time-domain(FDTD) algorithm, an efficient stretched coordinate perfectly matched layer(ESC-PML) based upon the exponential time differencing(ETD) method is proposed.The proposed implementation can not only reduce the number of auxiliary variables in the SC-PML regions but also maintain the ability of the original SC-PML in terms of the absorbing performance. Compared with the other existed algorithms, the ETDFDTD method shows the least memory consumption resulting in the computational efficiency. The effectiveness and efficiency of the proposed ESC-PML scheme is verified through the RCS relevant problems including the perfect E conductor(PEC) sphere model and the patch antenna model. The results indicate that the proposed scheme has the advantages of the ETD-FDTD method and ESC-PML scheme in terms of high computational efficiency and considerable computational accuracy.

Systematic Synthesis of Compressive VDTA-Based T-T Filter with Orthogonal Control of f_o and Q

Based on sixteen nullor-mirror models of the voltage differencing transconductance amplifier (VDTA) and port admittance matrices of the tow-Thomas (T-T) filter with orthogonal control between the characteristic frequency(f_0) and figure of merit (Q),two different categories of the voltage-mode and transconductance-mode T-T filters are synthesized by the means of the nodal admittance matrix (NAM) expansion method.The category A filter that employs two compressive VDTAs and two grounded capacitors includes four structures,and the category B filter that uses two compressive VDTAs,two grounded capacitors,and one grounded resistor,also includes four structures.These circuits are suitable for integrated circuit manufacture,and their parameters f_0 and Q can be orthogonally adjusted with varying the bias currents of VDTAs.After the paper and pencil test is completed,the computer analyses,including alternating current (AC),parameter sweep,Monte Carlo (MC),and noise analyses,are performed to support the synthesis approach.

Multi-channel differencing adaptive noise cancellation with multi-kernel method

Although a various of existing techniques are able to improve the performance of detection of the weak interesting sig- nal, how to adaptively and efficiently attenuate the intricate noises especially in the case of no available reference noise signal is still the bottleneck to be overcome. According to the characteristics of sonar arrays, a multi-channel differencing method is presented to provide the prerequisite reference noise. However, the ingre- dient of obtained reference noise is too complicated to be used to effectively reduce the interference noise only using the clas- sical linear cancellation methods. Hence, a novel adaptive noise cancellation method based on the multi-kernel normalized least- mean-square algorithm consisting of weighted linear and Gaussian kernel functions is proposed, which allows to simultaneously con- sider the cancellation of linear and nonlinear components in the reference noise. The simulation results demonstrate that the out- put signal-to-noise ratio （SNR） of the novel multi-kernel adaptive filtering method outperforms the conventional linear normalized least-mean-square method and the mono-kernel normalized least- mean-square method using the realistic noise data measured in the lake experiment.

New Predictor-Corrector Methods Based on Exponential Time Differencing forSystems of Nonlinear Differential Equations

We present the new predictor-corrector methods for systems of nonlinear differential equations, based on the method of exponential time differencing. We compare the present schemes with the explicit multistep exponential time differencing and Adams–Bashforth–Moulton method. The numerical results show that the schemes are more accurate and more efficient than Adams predictor-corrector method. The exponential time differencing method has been developed and perfected by the present studies.

Universal Current-Mode Biquad Filter Using a VDTA

This paper presents a new current-mode single input multi output (SIMO) type biquad employing one voltage differencing transconductance amplifier (VDTA), two grounded capacitors and a single grounded resistor. The configuration realizes all basic filter functions (i.e. Low Pass (LP), High Pass (HP), Band Pass (BP), Notch (BR) and All Pass (AP)). The natural frequency (ω0) and bandwidth (BW) are independently tunable. The workability of proposed configuration has been verified using SPICE simulation with TSMC CMOS 0.18 μm process parameters.

Voltage-Mode Universal Biquad Filter Employing Single Voltage Differencing Differential Input Buffered Amplifier

A new multi function voltage-mode universal biquadratic filter using single Voltage Differencing Differential Input Buffered Amplifier (VD-DIBA), two capacitors and one resistor is proposed. The proposed configuration has four inputs and one output and can realize all the five standard filters from the same circuit configuration. The presented biquad filter offers low active and passive sensitivities. The validity of proposed universal biquadratic filter has been verified by SPICE simulation using 0.35 μm MIETEC technology.

A Fault Feature Extraction Model in Synchronous Generator under Stator Inter-Turn Short Circuit Based on ACMD and DEO3S

This paper proposed a new diagnosis model for the stator inter-turn short circuit fault in synchronous generators.Different from the past methods focused on the current or voltage signals to diagnose the electrical fault,the sta-tor vibration signal analysis based on ACMD(adaptive chirp mode decomposition)and DEO3S(demodulation energy operator of symmetrical differencing)was adopted to extract the fault feature.Firstly,FT(Fourier trans-form)is applied to the vibration signal to obtain the instantaneous frequency,and PE(permutation entropy)is calculated to select the proper weighting coefficients.Then,the signal is decomposed by ACMD,with the instan-taneous frequency and weighting coefficient acquired in the former step to obtain the optimal mode.Finally,DEO3S is operated to get the envelope spectrum which is able to strengthen the characteristic frequencies of the stator inter-turn short circuit fault.The study on the simulating signal and the real experiment data indicates the effectiveness of the proposed method for the stator inter-turn short circuit fault in synchronous generators.In addition,the comparison with other methods shows the superiority of the proposed model.

Autoregressive Fractionally Integrated Moving Average-Generalized Autoregressive Conditional Heteroskedasticity Model with Level Shift Intervention

In this paper, we introduce the class of autoregressive fractionally integrated moving average-generalized autoregressive conditional heteroskedasticity?(ARFIMA-GARCH) models with level shift type intervention that are capable of capturing three key features of time series: long range dependence, volatility?and level shift. The main concern is on detection of mean and volatility level shift in a fractionally integrated time series with volatility. We will denote such a time series as level shift autoregressive fractionally integrated moving average (LS-ARFIMA) and level shift generalized autoregressive conditional heteroskedasticity (LS-GARCH). Test statistics that are useful to examine if mean and volatility level shifts are present in an autoregressive fractionally integrated moving average-generalized autoregressive conditional heteroskedasticity (ARFIMA-GARCH) model are derived. Quasi maximum likelihood estimation of the model is also considered.

Monitoring the Spatio-Temporal Dynamics of Vegetation Cover in Mubi Region, Adamawa State, Nigeria

Studies around the world have shown that vegetation cover is undergoing a dramatic change at various scales. Vegetation is a very important component of the ecosystem, its destruction by whatever means will have an adverse effect on the functional role it plays in the environment. Hence, it is necessary to monitor, conserve and utilize these vital resources sustainably. This study monitors vegetation dynamics in Mubi region with the view to understand the status of vegetation cover and suggest possible conservation measures. The study used regression differencing method of change detection to identify the status and dynamics of vegetation cover in the region. Landsat satellite images were used to create Normalized Difference Vegetation Index (NDVI) using IDRISI software. The NDVI images were subjected to diverse analysis ranging from image registration to image regression, differencing and thresholding. The results from these analysis shows that vegetation cover in the region has witnessed unprecedented degradation. In the period between 1987 and 1999 (12 years) the area that experienced depletion in vegetation cover in the region was 10,501.42 hectares while the period between 1999 and 2015 (16 years) witnessed further depletion to 32,701.77 hectares. The areas that experienced restoration in vegetation cover in the region from the period between 1999 and 2015 (24,098.94 hectares) have lower areal extent compared with the period between 1987 and 1999 (44,045.80 hectares). This phenomenon is not unconnected with population growth as the region has witnessed explosive growth in the recent past. This growth in population has resulted in higher demand for food to feed the growing population thereby leading to expansion of farmland. High demands for fuelwood by the increasing populace have also contributed to increase in deforestation. Removal of vegetation cover at such a scale will eventually have negative consequences on the ecosystem as its functional roles in the environment are jeopardized. Hence, there is a need to preserve and conserve vegetal resources through sustainable use.

Dynamicity of Land Use/Land Cover(LULC):An analysis from peri-urban and rural neighbourhoods of Durgapur Municipal Corporation(DMC)in India

The availability of better economic possibilities and well-connected transportation networks has attracted people to migrate to peri-urban and rural neighbourhoods,changing the landscape of regions outside the city and fostering the growth of physical infrastructure.Using multi-temporal satellite images,the dynamics of Land Use/Land Cover(LULC)changes,the impact of urban growth on LULC changes,and regional environmental implications were investigated in the peri-urban and rural neighbourhoods of Durgapur Municipal Corporation in India.The study used different case studies to highlight the study area’s heterogeneity,as the phenomenon of change is not consistent.Landsat TM and OLI-TIRS satellite images in 1991,2001,2011,and 2021 were used to analyse the changes in LULC types.We used the relative deviation(RD),annual change intensity(ACI),uniform intensity(UI)to show the dynamicity of LULC types(agriculture land;built-up land;fallow land;vegetated land;mining area;and water bodies)during 1991-2021.This study also applied the Decision-Making Trial and Evaluation Laboratory(DEMATEL)to measure environmental sensitivity zones and find out the causes of LULC changes.According to LULC statistics,agriculture land,built-up land,and mining area increased by 51.7,95.46,and 24.79 km^(2),respectively,from 1991 to 2021.The results also suggested that built-up land and mining area had the greatest land surface temperature(LST),whereas water bodies and vegetated land showed the lowest LST.Moreover,this study looked at the relationships among LST,spectral indices(Normalized Differenced Built-up Index(NDBI),Normalized Difference Vegetation Index(NDVI),and Normalized Difference Water Index(NDWI)),and environmental sensitivity.The results showed that all of the spectral indices have the strongest association with LST,indicating that built-up land had a far stronger influence on the LST.The spectral indices indicated that the decreasing trends of vegetated land and water bodies were 4.26 and 0.43 km^(2)/a,respectively,during 1991-2021.In summary,this study can help the policy-makers to predict the increasing rate of temperature and the causes for the temperature increase with the rapid expansion of built-up land,thus making effective peri-urban planning decisions.

CMOS VDIBAs-Based Single-Resistance-Controlled Voltage-Mode Sinusoidal Oscillator

In this communication, a new single-resistance controlled sinusoidal oscillator (SRCO) has been presented. The presented SRCO uses two voltage differencing inverting buffered amplifiers (VDIBAs), one resistor and two capacitors in which one is grounded (GC) and the other one is floating (FC). The proposed structure offers the following advantageous features: 1) independent control of oscillation condition (OC) and oscillation frequency (OF);2) low passive and active sensitivities and 3) very good frequency stability. The non-ideal effects of the VDIBA on the proposed oscillator have also been investigated. The proposed SRCO has been tested for its robustness using Monte-Carlo simulations. The check of the validity of the presented SRCO has been established by SPICE simulations using 0.18 μm TSMC technology.

Block-Based Steganographic Algorithm Using Modulus Function and Pixel-Value Differencing

The main purpose in developing the steganographic algorithms lies in achieving most of the steganographic objectives which comprise the embedding capacity, imperceptibility, security, robustness and complexity. In this paper, we propose a high quality steganographic algorithm using new block structure which makes a good use of both modulus function and pixel-value differencing, namely, MF-PVD. We have made many experiments with various test images from several galleries, such as USC-SIPI and UWATERLOO-LINK. The performance of our proposed algorithm is verified using three different performance metrics which include peak signal-to-noise ratio (PSNR), structural similarity index measure (SSIM), and embedding capacity (EC). Experimental results and comparisons with six pertinent state-of-art algorithms are given to prove the validation and efficiency of the proposed algorithm.

A Homogenized Function to Recover Wave Source by Solving a Small Scale Linear System of Differencing Equations

In order to recover unknown space-dependent function G(x)or unknown time-dependent function H(t)in the wave source F(x;t)=G(x)H(t),we develop a technique of homogenized function and differencing equations,which can significantly reduce the difficulty in the inverse wave source recovery problem,only needing to solve a few equations in the problem domain,since the initial condition/boundary conditions and a supplementary final time condition are satisfied automatically.As a consequence,the eigenfunctions are used to expand the trial solutions,and then a small scale linear system is solved to determine the expansion coefficients from the differencing equations.Because the ill-posedness of the inverse wave source problem is greatly reduced,the present method is accurate and stable against a large noise up to 50%,of which the numerical tests confirm the observation.