Novel registration algorithm for 3-D images captured from multiple views of object surface

A novel algorithm of 3-D surface image registration is proposed. It makes use of the array information of 3-D points and takes vector/vertex-like features as the basis of the matching. That array information of 3-D points can be easily obtained when capturing original 3-D images. The iterative least-mean-squared （LMS） algorithm is applied to optimizing adaptively the transformation matrix parameters. These can effectively improve the registration performance and hurry up the matching process. Experimental results show that it can reach a good subjective impression on aligned 3-D images. Although the algorithm focuses primarily on the human head model, it can also be used for other objects with small modifications.

The parallel 3D magnetotelluric forward modeling algorithm

The workload of the 3D magnetotelluric forward modeling algorithm is so large that the traditional serial algorithm costs an extremely large compute time. However, the 3D forward modeling algorithm can process the data in the frequency domain, which is very suitable for parallel computation. With the advantage of MPI and based on an analysis of the flow of the 3D magnetotelluric serial forward algorithm, we suggest the idea of parallel computation and apply it. Three theoretical models are tested and the execution efficiency is compared in different situations. The results indicate that the parallel 3D forward modeling computation is correct and the efficiency is greatly improved. This method is suitable for large size geophysical computations.

Quantitative structure-property relationship study of the solubility of thiazolidine-4-carboxylic acid derivatives using ab initio and genetic algorithm-partial least squares

A quantitative structure-activity relationships （QSAR） study is suggested for the prediction of solubility of some thiazolidine-4- carboxylic acid derivatives in aqueous solution. Ab initio theory was used to calculate some quantum chemical descriptors including electrostatic potentials and local charges at each atom, HOMO and LUMO energies, etc. Modeling of the solubility of thiazolidine- 4-carboxylic acid derivatives as a function of molecular structures was established by means of the partial least squares （PLS）. The subset of descriptors, which resulted in the low prediction error, was selected by genetic algorithm. This model was applied for the prediction of the solubility of some thiazolidine-4-carboxylic acid derivatives, which were not in the modeling procedure. The relative errors of prediction lower that -4% was obtained by using GA-PLS method. The resulted model showed high prediction ability with RMSEP of 3.8836 and 2.9500 for PLS and GA-PLS models, respectively.

Unfolding analysis of LaBr3:Ce gamma spectrum with a detector response matrix constructing algorithm based on energy resolution calibration

With respect to the gamma spectrum, the energy resolution improves with increase in energy. The counts of full energy peak change with energy, and this approximately complies with the Gaussian distribution. This study mainly examines a method to deconvolve the LaBr_3:Ce gamma spectrum with a detector response matrix constructing algorithm based on energy resolution calibration.In the algorithm, the full width at half maximum(FWHM)of full energy peak was calculated by the cubic spline interpolation algorithm and calibrated by a square root of a quadratic function that changes with the energy. Additionally, the detector response matrix was constructed to deconvolve the gamma spectrum. Furthermore, an improved SNIP algorithm was proposed to eliminate the background. In the experiment, several independent peaks of ^(152)Eu,^(137)Cs, and ^(60)Co sources were detected by a LaBr_3:Ce scintillator that were selected to calibrate the energy resolution. The Boosted Gold algorithm was applied to deconvolve the gamma spectrum. The results showed that the peak position difference between the experiment and the deconvolution was within ± 2 channels and the relative error of peak area was approximately within 0.96–6.74%. Finally, a ^(133) Ba spectrum was deconvolved to verify the efficiency and accuracy of the algorithm in unfolding the overlapped peaks.

Interplay of neuropilin-1 and semaphorin 3A after partial hepatectomy in rats

AIM： To elucidate the role of neuropilin-1 （Nrp-1） and semaphorin 3A （Sema3A） in sinusoidal remodeling dur- ing liver regeneration in rats. METHODS： Male Wistar/ST rats at 7 wk of age, weigh- ing about 200 g, were used for all animal experiments. In vivo, at 24, 48, 72, 96, 144 and 192 h after two- thirds partial hepatectomy （PHx）, the remnant livers were removed. Liver tissues were immunohistochemi- cally stained for Nrp-1, Sema3A and SE-1, a liver sinu- soidal endothelial cell （SEC） marker. Total RNA of the liver tissue was extracted and reversely transcribed into cDNA. The mRNA expression of Sema3A was ana- lyzed by quantitative real-time polymerase chain reac- tion and normalized to that of ribosomal protein $18. In vitro, SECs were isolated from rat liver and cultured in endothelial growth medium containing 20 ng/mL vascular endothelial cell growth factor. Migration of SECs in primary culture was assessed by cell transwell assay with or without recombinant Sema3A. Apoptotic cells were determined by a terminal deoxynucleotidyl transferase-mediated deoxyuridine triphosphate nick end labeling method. RESULTS： In vitro, immunohistochemistry study re- vealed that Sema3A and Nrp-1 were constitutively ex- pressed in hepatocytes and SECs, respectively, in normal rat liver tissues. Nrp-1 expression in SECs was quantified by the percentage of immunostained area with anti- Nrp-1 antibody in relation to the area stained with SE-1. Between 24 h and 96 h following resection of liver, Nrp-1 expression in SECs was transiently increased. Compared with the baseline （5.2% ± 0.1%）, Nrp-1 expression in SECs significantly increased at 24 h （17.3% ± 0.7%, P 〈 0.05）, 48 h （39.1% ± 0.6%, P 〈 0.01）, 72 h （46.9% ± 4.5%, P 〈 0.01） and 96 h （29.9% ±3.8%, P 〈 0.01） after PHx, then returned to the basal level at termination of liver regeneration. Interestingly, the expression of Sema3A was inversely associated with that of Nrp-1 in liver after PHx. Sema3A mRNA expres- sion was significantly reduced by about 75% over the period 24-144 h after PHx （P 〈 0.05）, and returned to basal levels at 192 h after PHx. In vitro, SECs isolated from rats after PHx （PHx-SECs） were observed to mi- grate to the lower chamber of the cell transwell system after incubation for 24 h, but not cells from normal rats （CONT-SECs）, indicating that mobility of PHx-SECs increases as compared with that of CONT-SECs. More- over, recombinant Sema3A significantly attenuated mi- gration in PHx-SECs in primary culture （vehicle-treated 100% ± 7.9% vs Sema3A-treated 42.6% ± 5.4%, P 〈 0.01）, but not in CONT-SECs. Compared with CONT- SECs, the apoptotic rate of PHx-SECs decreased by 78.3% （P 〈 0.05）. There was no difference in apopto- sis between CONT-SECs that were treated with vehicle and Sema3A. However, in PHx-SECs, apoptosis was induced by the presence of 5 nmol Sema3A for 24 h （vehicle-treated 21.7%±7.6% vs Sema3A-treated 104.3% ± 8.9%, P 〈 0.05）. In addition, immunohisto- chemistry confirmed the increased expression of Nrp-1 in PHx-SECs, while it was noted to a lesser extent in CONT-SECs. CONCLUSION： The interplay of Nrp-1 and Sema3A shown in our results may lead to a better understand- ing of interaction between sinusoidal remodeling and SECs during liver regeneration.

Oscillations during partial oxidation of methane to synthesis gas over Ru/Al_2O_3 catalyst

Oscillations in temperatures of catalyst bed as well as concentrations of gas phase species at the exit of reactor were observed during the partial oxidation of methane to synthesis gas over Ru/Al2O3 in the temperature range of 600 to 850℃. XRD, H2-TPR and in situ Raman techniques was used to characterize the catalyst. Two types of ruthenium species, i.e. the ruthenium species weakly interacted with Al2O3 and that strongly interacted with the support, were identified by H2-TPR experiment. These species are responsible for two types of oscillation profiles observed during the reaction. The oscillations were the result of these ruthenium species switching cyclically between the oxidized state and the reduced state under the reaction condition. These cyclic transformations, in turn, were the result of temperature variations caused by the varying levels of the strongly exothermic CH4 combustion and the highly endothermic CH4 reforming （with H2O and CO2） reactions （or the less exothermic direct partial oxidation of methane to CO and H2）, which were favored by the oxidized and the metallic sites, respectively. The major pathway of synthesis gas formation over the catalyst was via the combustion-reforming mechanism.

Catalytic Partial Oxidation of Methane over Ni/CeO_2-ZrO_2-Al_2O_3

Nickel catalysts supported on CeO2-ZrO2-CeO2,ZrO2-Al2O3 and Al2O3 were prepared and characterized by means of X-ray diffraction（XRD）,BET areas,H2 temperature-programmed reduction（H2-TPR）,and X-ray photoelectron spectroscopy（XPS）.Through the test of catalytic partial oxidation of methane（CPOM）,Ni/CeO2-ZrO2-Al2O3 displayed the highest activity,which resulted from its largest BET area and best NiO dispersion.Furthermore,Ni/CeO2-ZrO2-Al2O3 maintained a long-time stability in CPOM,which was attributed to its best coking resistance among all the prepared catalysts.

New Improved Maximum Power Point Tracking Algorithm for Partially Shaded PV Systems

The paper presents new MPPT algorithm for partial shading of series connected PV cells/modules. In the shaded condition, there is a problem of decrease in the total output power of the PV system. The proposed algorithm aims to reduce this problem by active bypassing of the shaded cells. The algorithm senses the irradiance of each cell and performs calculation in order to decide if to actively bypass the shaded cell or not. Extensive simulation results proved that algorithm works and increases the output power under partial shading conditions. Furthermore, the algorithm becomes more efficient when the number of cells is increased.

Optimization algorithm for rapid 3D gravity inversion

The practical application of 3D inversion of gravity data requires a lot of computation time and storage space.To solve this problem,we present an integrated optimization algorithm with the following components:(1)targeting high accuracy in the space domain and fast computation in the wavenumber domain,we design a fast 3D forward algorithm with high precision;and(2)taking advantage of the symmetry of the inversion matrix,the main calculation in gravity conjugate gradient inversion is decomposed into two forward calculations,thus optimizing the computational efficiency of 3D gravity inversion.We verify the calculation accuracy and efficiency of the optimization algorithm by testing various grid-number models through numerical simulation experiments.

Correlation analysis and partial least square modeling to quantify typical minerals with Chang'E-3 visible and near-infrared imaging spectrometer's ground validation data

In 2013, Chang'E-3 program will develop lunar mineral resources in-situ detection. A Visible and Near-infrared Imaging Spectrometer(VNIS) has been selected as one payload of CE-3 lunar rover to achieve this goal. It is critical and urgent to evaluate VNIS' spectrum data quality and validate quantification methods for mineral composition before its launch. Ground validation experiment of VNIS was carried out to complete the two goals, by simulating CE-3 lunar rover's detection environment on lunar surface in the laboratory. Based on the hyperspectral reflectance data derived, Correlation Analysis and Partial Least Square(CA-PLS) algorithm is applied to predict abundance of four lunar typical minerals(pyroxene, plagioclase, ilmenite and olivine) in their mixture. We firstly selected a set of VNIS' spectral parameters which highly correlated with minerals' abundance by correlation analysis(CA), and then stepwise regression method was used to find out spectral parameters which make the largest contributions to the mineral contents. At last, functions were derived to link minerals' abundance and spectral parameters by partial least square(PLS) algorithm. Not considering the effect of maturity, agglutinate and Fe0, we found that there are wonderful correlations between these four minerals and VNIS' spectral parameters, e.g. the abundance of pyroxene correlates positively with the mixture's absorption depth, the value of absorption depth added as the increasing of pyroxene's abundance. But the abundance of plagioclase correlates negatively with the spectral parameters of band ratio, the value of band ratio would decrease when the abundance of plagioclase increased. Similar to plagioclase, the abundance of ilmenite and olivine has a negative correlation with the mixture's reflectance data, if the abundance of ilmenite or olivine increase, the reflectance values of the mixture will decrease. Through model validation, better estimates of pyroxene, plagioclase and ilmenite's abundances are given. It is concluded that VNIS has the capability to be applied on lunar minerals' identification, and CA-PLS algorithm has the potential to be used on lunar surface's in-situ detection for minerals' abundance prediction.

Using MC Algorithm to Implement 3D Image Reconstruction for Yunnan Weather Radar Data

3D image reconstruction for weather radar data can not only help the weatherman to improve the forecast efficiency and accuracy, but also help people to understand the weather conditions easily and quickly. Marching Cubes (MC) algorithm in the surface rendering has more excellent applicability in 3D reconstruction for the slice images;it may shorten the time to find and calculate the isosurface from raw volume data, reflect the shape structure more accurately. In this paper, we discuss a method to reconstruct the 3D weather cloud image by using the proposed Cube Weighting Interpolation (CWI) and MC algorithm. Firstly, we detail the steps of CWI, apply it to project the raw radar data into the cubes and obtain the equally spaced cloud slice images, then employ MC algorithm to draw the isosurface. Some experiments show that our method has a good effect and simple operation, which may provide an intuitive and effective reference for realizing the 3D surface reconstruction and meteorological image stereo visualization.

Simple Insulin Dose Adjustment Using 3-3-1 Algorithm in Japanese Patients with Type 2 Diabetes: Start Kanazawa Study (Self-Titration Aggressive Algorithm with Glargine Trial)

We implemented a 3-3-1 algorithm in order to provide safe and simple self-titration in patients who newly initiated BOT as well as who were already on BOT and evaluated its utility in clinical setting. A total of 46 patients, 21 patients in the newly-initiated group and 25 patients in the existing BOT group performed dose adjustment using 3-3-1 algorithm. HbA1c was significantly improved 4 weeks after the initiation from 8.5% ± 1.2% at baseline to 7.3% ± 0.7% at the final evaluation (p 0.01, vs. Baseline). The average daily insulin units increased throughout the study period from 10.1 ± 6.7 at baseline to 14.6 ± 8.9 units at the final evaluation. Weight didn’t significantly change throughout the study (p = 0.12). The incidents of hypoglycemia were 0.8/month during the insulin dose self-adjustment period and 0.4/month during the follow-up period. The 3-3-1 algorithm using insulin glargine provided a safe and simple dose adjustment and demonstrated its utility in patients who were newly introduced to insulin treatment as well as who were already on BOT.

An improved 3D shape haptic rendering algorithm for finger mounted vibrotactile device

To improve the sense of reality on perception, an improved algorithm of 3D shape haptic rendering is put forward based on a finger mounted vibrotactile device. The principle is that the interactive information and the shape information are conveyed to users when they touch virtual objects at mobile terminals by attaching the vibrotactile feedback on a fingertip. The extraction of shape characteristics, the interactive information and the mapping of shape in formation of vibration stimulation are key parts of the proposed algorithm to realize the real tactile rendering. The contact status of the interaction process, the height information and local gradient of the touch point are regarded as shape information and used to control the vibration intension, rhythm and distribution of the vibrators. With different contact status and shape information, the vibration pattern can be adjusted in time to imitate the outlines of virtual objects. Finally, the effectiveness of the algorithm is verified by shape perception experiments. The results show that the improved algorithm is effective for 3D shape haptic rendering.

Improvement of Binocular Reconstruction Algorithm for Measuring 3D Pavement Texture Using a Single Laser Line Scanning Constraint

The dense and accurate measurement of 3D texture is helpful in evaluating the pavement function.To form dense mandatory constraints and improve matching accuracy,the traditional binocular reconstruction technology was improved threefold.First,a single moving laser line was introduced to carry out global scanning constraints on the target,which would well overcome the difficulty of installing and recognizing excessive laser lines.Second,four kinds of improved algorithms,namely,disparity replacement,superposition synthesis,subregion segmentation,and subregion segmentation centroid enhancement,were established based on different constraint mechanism.Last,the improved binocular reconstruction test device was developed to realize the dual functions of 3D texture measurement and precision self-evaluation.Results show that compared with traditional algorithms,the introduction of a single laser line scanning constraint is helpful in improving the measurement’s accuracy.Among various improved algorithms,the improvement effect of the subregion segmentation centroid enhancement method is the best.It has a good effect on both overall measurement and single pointmeasurement,which can be considered to be used in pavement function evaluation.

Adaptive Window Based 3-D Feature Selection for Multispectral Image Classification Using Firefly Algorithm

Feature extraction is the most critical step in classification of multispectral image.The classification accuracy is mainly influenced by the feature sets that are selected to classify the image.In the past,handcrafted feature sets are used which are not adaptive for different image domains.To overcome this,an evolu-tionary learning method is developed to automatically learn the spatial-spectral features for classification.A modified Firefly Algorithm(FA)which achieves maximum classification accuracy with reduced size of feature set is proposed to gain the interest of feature selection for this purpose.For extracting the most effi-cient features from the data set,we have used 3-D discrete wavelet transform which decompose the multispectral image in all three dimensions.For selecting spatial and spectral features we have studied three different approaches namely overlapping window(OW-3DFS),non-overlapping window(NW-3DFS)adaptive window cube(AW-3DFS)and Pixel based technique.Fivefold Multiclass Support Vector Machine(MSVM)is used for classification purpose.Experiments con-ducted on Madurai LISS IV multispectral image exploited that the adaptive win-dow approach is used to increase the classification accuracy.

Adaptive tracking algorithm based on 3D variable turn model

Satisfactory results cannot be obtained when three-dimensional (3D) targets with complex maneuvering characteristics are tracked by the commonly used two-dimensional coordinated turn (2DCT) model. To address the problem of 3D target tracking with strong maneuverability, on the basis of the modified three-dimensional variable turn (3DVT) model, an adaptive tracking algorithm is proposed by combining with the cubature Kalman filter (CKF) in this paper. Through ideology of real-time identification, the parameters of the model are changed to adjust the state transition matrix and the state noise covariance matrix. Therefore, states of the target are matched in real-time to achieve the purpose of adaptive tracking. Finally, four simulations are analyzed in different settings by the Monte Carlo method. All results show that the proposed algorithm can update parameters of the model and identify motion characteristics in real-time when targets tracking also has a better tracking accuracy.

Estimation of Crop Biomass Using GF-3 Polarization SAR Data Based on Genetic Algorithm Feature Selection

In recent years,Polarization SAR(PolSAR)has been widely used in the filed of crop biomass estimation.However,high dimensional features extracted from PolSAR data will lead to information redundancy which will result in low accuracy and poor transfer ability of the estimation model.Aiming at this problem,we proposed a estimation method of crop biomass based on automatic feature selection method using genetic algorithm(GA).Firstly,the backscattering coefficient,the polarization parameters and texture features were extracted from PolSAR data.Then,these features were automatically pre-selected by GA to obtain the optimal feature subset.Finally,based on this subset,a support vector regression machine(SVR)model was applied to estimate crop biomass.The proposed method was validated using the GaoFen-3(GF-3)QPSΙ(C-band,quad-polarization)SAR data.Based on wheat and rape biomass samples acquired from a synchronous field measurement campaign,the proposed method achieve relative high validation accuracy(over 80%)in both crop types.For further analyzing the improvement of proposed method,validation accuracies of biomass estimation models based on several different feature selection methods were compared.Compared with feature selection based on linear correlation,GA method has increased by 5.77%in wheat biomass estimation and 11.84%in rape biomass estimation.Compared with the method of recursive feature elimination(RFE)selection,the proposed method has improved crops biomass estimation accuracy by 3.90%and 5.21%,respectively.

AN ACCELERATION FOR THE EIGENSYSTEM REALIZATION ALGORITHM WITH PARTIAL SINGULAR VALUES DECOMPOSITION

The real-time identification of dynamic parameters is importantfor the control system of spacecraft. The eigensystme realizationalgorithm (ERA) is currently the typical method for such applica-tion. In order to identify the dynamic parameter of spacecraftrapidly and accurately, an accelerated ERA with a partial singularvalues decomposition (PSVD) algorithm is presented. In the PSVD, theHankel matrix is reduced to dual diagonal form first, and thentransformed into a tridiagonal matrix.

PARTIAL ELIMINTATION ALGORITHM FOR A LINEAR RECURRENCE SYSTEM R(n, m) OF ORDER m

This paper presents an algorithm for computing a linear recurrence system R(n, m) of order m for n equations on MIMD parallel system. This algorithm is not only easy to be programmed on a parallel computer system, but also reduces the data-waiting time due to compute-ahead strategy. The paper analyses how to achieve maximal load balancing when the algorithm is implemented on MIMD parallel system. By the end of the paper, an analysis on the speedup and parallel efficiency are given. The results indicate that the new parallel elimination algorithm has great improvement compared with the old ones.

Optimality Conditions and Algorithms for Direct Optimizing the Partial Differential Equations

New form of necessary conditions for optimality (NCO) is considered. They can be useful for design the direct infinite- dimensional optimization algorithms for systems described by partial differential equations (PDE). Appropriate algo-rithms for unconstrained minimizing a functional are considered and tested. To construct the algorithms, new form of NCO is used. Such approach demonstrates fast uniform convergence at optimal solution in infinite-dimensional space.