Derivation of Optimal Global Equalization Function with Variable Size Block Based Local Contrast Enhancement

A conventional global contrast enhancement is difficult to apply in various images because image quality and contrast enhancement are dependent on image characteristics largely. And a local contrast enhancement not only causes a washed-out effect, but also blocks. To solve these drawbacks, this paper derives an optimal global equalization function with variable size block based local contrast enhancement. The optimal equalization function makes it possible to get a good quality image through the global contrast enhancement. The variable size block segmentation is firstly exeoated using intensity differences as a measure of similarity. In the second step, the optimal global equalization function is obtained from the enhanced contrast image having variable size blocks. Conformed experiments have showed that the proposed algorithm produces a visually comfortable result image.

Novel LMS adaptive filtering algorithm with variable step size

By analyzing algorithms available for variable step size least mean square(LMS)adaptive filter,a new modified LMS adaptive filtering algorithm with variable step size is proposed,along with performance analysis based on different parameters.Compared with the existing algorithms through the simulation,the proposed algorithm has faster convergence speed and smaller steady state error.

Fast Approaches for Sub-pixel Precision Variable Block Size Motion Estimation

The new features of H. 264 video coding standard make the motion estimation module much more time consuming than before. Especially, the motion search is required for each of the 4 modes for inter prediction. In order to reduce the computational complexity, we analyze the statistics of results of motion estimation, such as the continuity of best modes of blocks in successive frames and the chance to give up a sub-partition mode （smaller than 16 × 16） after integer-pixel motion estimation, from which we suggest to make mode prediction based on the motion information of the previous frame and skip sub-pixel motion estimation in subpartition mode selectively. According to the experimental result, the proposed algorithm can save 75 % of the computational time with a slight degradation （0.03 dB） on PSNR compared with the pseudocode of fast search motion estimation in JM12.2.

Study of Variable Step Size LMS Adaptive Algorithm Based on Variable Region

This paper puts forward a new variable step size LMS adaptive algorithm based on variable region. The step size p（k） in the algorithm varies with the variation of the region of deviation e （k） to ensure the optimization of the three performance objectives including initial convergent speed, trace ability of the time-varying system and steady disregulation. The paper demonstrates the convergence of the algorithm accompanied by random noise,

Joint receiving mechanism based on blind equalization with variable step size for M-QAM modulation

The problem of inter symbol interference（ ISI） in wireless communication systems caused by multipath propagation when using high order modulation like M-Q AMis solved. Since the wireless receiver doesn＇t require a training sequence,a blind equalization channel is implemented in the receiver to increase the throughput of the system. To improve the performances of both the blind equalizer and the system,a joint receiving mechanismincluding variable step size（ VSS） modified constant modulus algorithms（ MC-MA） and modified decision directed modulus algorithms（ MD DMA） is proposed to ameliorate the convergence speed and mean square error（ MSE） performance and combat the phase error when using high order QAM modulation. The VSS scheme is based on the selection of step size according to the distance between the output of the equalizer and the desired output in the constellation plane. Analysis and simulations showthat the performance of the proposed VSS-MCMA-MD DMA mechanismis better than that of algorithms with a fixed step size. In addition,the MCMA-MDDMA with VSS can performthe phase recovery by itself.

Design of digital calibration based on variable step size of sub-binary SAR ADC

Addressing the impact of capacitor mismatch on the conversion accuracy of successive approximation register analog-to-digital converter(SAR ADC),a 12-bit 1 MS/s sub-binary SAR ADC designed using variable step size digital calibration was proposed.The least mean square(LMS)calibration algorithm was employed with a ramp signal used as the calibration input.Weight errors,extracted under injected disturbances,underwent iterative training to optimize weight values.To address the trade-off between conversion accuracy and speed caused by a fixed step size,a novel variable step size algorithm tailored for SAR ADC calibration was proposed.The core circuit and layout of the SAR ADC were implemented using the Taiwan Semiconductor Manufacturing Company(TSMC)0.35μm complementary metal-oxide-semiconductor(CMOS)commercial process.Simulation of the SAR ADC calibration algorithm was conducted using Simulink,demonstrating quick convergence and meeting conversion accuracy requirements compared to fixed step size simulation.The results indicated that the convergence speed of the LMS digital calibration algorithm with variable step size was approximately eight times faster than that with a fixed step size,also yielding a lower mean square error(MSE).After calibration,the simulation results for the SAR ADC exhibited an effective number of bit(ENOB)of 11.79 bit and a signal-to-noise and distortion ratio(SNDR)of 72.72 dB,signifying a notable enhancement in the SAR ADC performance.

Improved finite difference method for pressure distribution of aerostatic bearing

An improved finite difference method （FDM）is described to solve existing problems such as low efficiency and poor convergence performance in the traditional method adopted to derive the pressure distribution of aerostatic bearings. A detailed theoretical analysis of the pressure distribution of the orifice-compensated aerostatic journal bearing is presented. The nonlinear dimensionless Reynolds equation of the aerostatic journal bearing is solved by the finite difference method. Based on the principle of flow equilibrium, a new iterative algorithm named the variable step size successive approximation method is presented to adjust the pressure at the orifice in the iterative process and enhance the efficiency and convergence performance of the algorithm. A general program is developed to analyze the pressure distribution of the aerostatic journal bearing by Matlab tool. The results show that the improved finite difference method is highly effective, reliable, stable, and convergent. Even when very thin gas film thicknesses （less than 2 Win）are considered, the improved calculation method still yields a result and converges fast.

A nonparametric variable step-size subband adaptive filtering algorithm for acoustic echo cancellation

Acoustic echo cancellation is often applied in communication and video call system to reduce unnecessary echoes generated between speakers and microphones.In these systems,the speech input signal of the adaptive filter is often colored and unstable,which decays the convergence rate of the adaptive filter if the NLMS algorithm is used.In this paper,an improved nonparametric variable step-size subband(NPVSS-NSAF)algorithm is proposed to address the problem.The variable step-size is derived by minimizing the sum of the square Euclidean norm of the difference between the optimal weight vectors to be updated and the past estimated weight vectors.Then the parameters are eliminated by using the power of subband signal noise equal to the power of subband posteriori error.The performance of the proposed algorithm is simulated in the aspects of misalignment and return loss enhancement.Experiment results show a fast convergence rate and low misalignment of the proposed algorithm in system identification.

An Efficient Reference Free Adaptive Learning Process for Speech Enhancement Applications

In issues like hearing impairment,speech therapy and hearing aids play a major role in reducing the impairment.Removal of noise signals from speech signals is a key task in hearing aids as well as in speech therapy.During the transmission of speech signals,several noise components contaminate the actual speech components.This paper addresses a new adaptive speech enhancement(ASE)method based on a modified version of singular spectrum analysis(MSSA).The MSSA generates a reference signal for ASE and makes the ASE is free from feeding reference component.The MSSA adopts three key steps for generating the reference from the contaminated speech only.These are decomposition,grouping and reconstruction.The generated reference is taken as a reference for variable size adaptive learning algorithms.In this work two categories of adaptive learning algorithms are used.They are step variable adaptive learning(SVAL)algorithm and time variable step size adaptive learning(TVAL).Further,sign regressor function is applied to adaptive learning algorithms to reduce the computational complexity of the proposed adaptive learning algorithms.The performance measures of the proposed schemes are calculated in terms of signal to noise ratio improvement(SNRI),excess mean square error(EMSE)and misadjustment(MSD).For cockpit noise these measures are found to be 29.2850,-27.6060 and 0.0758 dB respectively during the experiments using SVAL algorithm.By considering the reduced number of multiplications the sign regressor version of SVAL based ASE method is found to better then the counter parts.

Quantitative Stereological Estimations of Structural Patterns of the Glandular Tree in Benign Hyperplasia of Prostate

Background: Benign prostate hyperplasia (BPH) is the most common benign disease of human prostate. Currently BPH is associated with unregulated proliferation of connective tissue and glandular epithelium within the prostatic transition zone, and it has been described as relevant characteristic of BPH—the increase of the total number of cells, and not only an increase in cell size. To date, there are few studies on the quantitative morphology of glandular tree of BPH compared with normal prostate. The scarce investigations about this particular suggest that the glandular tree branches and expands as the hyperplastic transformation occurs in the prostate. Methods: To verify if this gland expansion and branching was similar to that occurs in the normal prostate, this study deals with the estimation of several stereological parameters as: labeling index for the proliferating cell nuclear antigen to quantify the rate of proliferation of prostate epithelium, average thickness of glandular epithelium, fraction of the volume occupied by the epithelium relative to the total prostate volume, connectivity density of prostate glands, to quantify the branching of prostate glands, and the average volume and the volume-weighted mean glandular volume of prostate acini to assess the mean size of the prostate acini and its variability. Results: All these estimates have been performed in prostate specific antigen immunostained sections from prostates of young men (controls) and in adenomectomy specimens from the adenofibromiomatous variety of BPH. Conclusion: We conclude that the epithelial proliferation is not the only factor intervening in the development of BPH. In addition, a more prolonged survival of epithelial population, together with some degree of hypertrophy of acini expressed by the increase of volume fraction and thickness of acinar epithelium, is relevant in order to the growth and expansion of the BPH glandular tree that shows more abundant and heterogeneous acinar sprouts than in normal prostate.

Variable-step-size second-order-derivative multistep method for solving first-order ordinary differential equations in system simulation

According to the relationship between truncation error and step size of two implicit second-order-derivative multistep formulas based on Hermite interpolation polynomial,a variable-order and variable-step-size numerical method for solving differential equations is designed.The stability properties of the formulas are discussed and the stability regions are analyzed.The deduced methods are applied to a simulation problem.The results show that the numerical method can satisfy calculation accuracy,reduce the number of calculation steps and accelerate calculation speed.

Geographical classification of Nanfeng mandarin by near infrared spectroscopy coupled with chemometrics methods

Near infrared spectroscopy(NIRS),coupled with principal component analysis and wavelength selection techniques,has been sed to develop a robust and reliable reduced-spectrum classifi-cation model for determining the geographical origins of Nanfeng mandarins.The application of the changeable size moving window principal component analysis(CSMWPCA)provided a notably improved lassification model,with correct classification rates of 92.00%,100.00%,90.00%,100.00%,100.00%,100.00%and 100.00%for Fujian,Guangxi,Hunan,Baishe,Baofeng,Qiawan,Sanxi samples,respectively,as well as,a total dassification rate of 97.52%in the wavelength range from 1007 to 1296 nm.To test and apply the proposed method,the procedure was applied to the analysis of 59 samples in an independent test set.Good identification results(correct rate of 96.61%)were also received.The improvement achieved by the application of CSMWPCA method was particularly remarkable when taking the low complexities of the final model(290 variables)into account.The results of the study showed the great potential of NIRS as a fast,nondestructive and environmentally acceptable method for the rapid and reliable determination for geographical classifcation of Nanfeng mandarins.

Dynamic Simulation of Distribution Networks Using Multi-stage Discontinuous Galerkin Method

Dynamic simulation plays a fundamental role in security evaluation of distribution networks(DNs).However,the strong stiffness and non-linearity of distributed generation(DG)models in DNs bring about burdensome computation and noteworthy instability on traditional methods which hampers the rapid response of simulation tool.Thus,a novel L-stable approximate analytical method with high accuracy is proposed to handle these problems.The method referred to as multistage discontinuous Galerkin method(MDGM),first derives approximate analytical solutions(AASs)of state variables which are explicit symbolic expressions concerning system states.Then,in each time window,it substitutes values for symbolic variables and trajectories of state variables are obtained subsequently.This paper applies MDGM to DG models to derive AASs.Local-truncation-error-based variable step size strategy is also developed to further improve simulation efficiency.In addition,this paper establishes detailed MDGM-based dynamic simulation procedure.From case studies on a numerical problem,a modified 33-bus system and a practical large-scale DN,it can be seen that proposed method demonstrates fast and dependable performance compared with the traditional trapezoidal method.

Multiple CRC-aided variable successive cancellation list decoder of polar codes

In order to change the path candidates, reduce the average list size, and make more paths pass cyclic redundancy check （CRC）, multiple CRC-aided variable successive cancellation list （SCL） decoding algorithm is proposed. In the decoding algorithm, the whole unfrozen bits are divided into several parts and each part is concatenated with a corresponding CRC code, except the last part which is concatenated with a whole unfrozen CRC code. Each CRC detection is performed, and only those satisfying each part CRC become the path candidates. A variable list is setup for each part to reduce the time complexity. Variable list size is setup for each part to reduce the time complexity until one survival path in each part can pass its corresponding CRC. The results show that the proposed algorithm can reduce the average list size, and the frame error rate （FER） performance, and has a better performance with the increase of the part number.

Individual variability in life-history traits drives population size stability

Understanding how population sizes vary over time is a key aspect of ecological research. Unfortunately, our under- standing of population dynamics has historically been based on an assumption that individuals are identical with homogenous life-history properties. This assumption is certainly false for most natural systems, raising the question of what role individual variation plays in the dynamics of populations. While there has been an increase of interest regarding the effects of within popula- tion variation on the dynamics of single populations, there has been little study of the effects of differences in within population variation on patterns observed across populations. We found that life-history differences （clutch size） among individuals ex- plained the majority of the variation observed in the degree to which population sizes of eastern fence lizards Sceloporus undula- tus fluctuated. This finding suggests that differences across populations cannot be understood without an examination of differences at the level of a system rather than at the level of the individual

A three-stage method with efficient calculation for lot streaming flow-shop scheduling

An important production planning problem is how to best schedule jobs(or lots)when each job consists of a large number of identical parts.This problem is often approached by breaking each job/lot into sublots(termed lot streaming).When the total number of transfer sublots in lot streaming is large,the computational effort to calculate job completion time can be significant.However,researchers have largely neglected this computation time issue.To provide a practical method for production scheduling for this situation,we propose a method to address the n-job,m-machine,and lot streaming flow-shop scheduling problem.We consider the variable sublot sizes,setup time,and the possibility that transfer sublot sizes may be bounded because of capacity constrained transportation activities.The proposed method has three stages:initial lot splitting,job sequencing optimization with efficient calculation of the makespan/total flow time criterion,and transfer adjustment.Computational experiments are conducted to confirm the effectiveness of the three-stage method.The experiments reveal that relative to results reported on lot streaming problems for five standard datasets,the proposed method saves substantial computation time and provides better solutions,especially for large-size problems.

Effect of atmospheric parameters on fine particulate concentration in suburban Shanghai

A study was conducted on the effect of atmospheric parameters, including temperature, wind speed, and relative humidity, on fine particulate mass concentrations measured in Jiading District of Shanghai, China, during the period from January 2009 to January 2010. A sensitivity analysis was applied to investigate the interaction between atmospheric parameters and particulate mass concentration. The experiment revealed that the concentration of particulates increased with particle size from 0.1 to 1.0 μm, and decreased with the increase of particle size from 1.0 to 2.5 μm. The effects of atmospheric parameters on fine mass concentrations were significantly particle size-dependent. The PM1.0-2.5 may come from the size increase of smaller particulates after moisture absorption, And the variation of concentrations of PM0.1-l.0 was mainly attributed to the accumulation of PM0.1. The ventilation index and dilution index were calcu- lated on the basis of data collected in December 2009. A correlation analysis indicated that there was a significant relation between these two indexes and the particulate concentration by examining the three particle size ranges, 0.0-0.1, 0.1-1.0, and 1,0-2.5 μm. The Spearman correlation coefficients that related the ventilation index to the concentration for the three particle size ranges were -0.45, -0.56 and -0.47, respectively, while the coefficients that related the dilution index to the concentration were -0.36, -0.42 and -0.45, respectively.

GRID-INDEPENDENT CONSTRUCTION OF MULTISTEP METHODS

A new polynomial formulation of variable step size linear multistep methods is pre- sented, where each k-step method is characterized by a fixed set of k - 1 or k parameters. This construction includes all methods of maximal order （p = k for stiff, and p = k ＋ 1 for nonstiff problems）. Supporting time step adaptivity by construction, the new formulation is not based on extending classical fixed step size methods; instead classical methods are obtained as fixed step size restrictions within a unified framework. The methods are imple- mented in MATLAB, with local error estimation and a wide range of step size controllers. This provides a platform for investigating and comparing different multistep method in realistic operational conditions. Computational experiments show that the new multi- step method construction and implementation compares favorably to existing software, although variable order has not yet been included.