Simulation of scaling effects of thermal emission from non-isothermal pixels with the typical three-dimensional structure

This paper suggests approaches to simulate scaling effects of thermal emission from non-isothermal pixels with a typical three-dimensional structure. We simulate effective emissivities of various V-shaped valleys by using our Monte Carlo method under the isothermal assumption. An analytical formula of the effective emissivities is derived based on photon rebounding between surfaces in the valleys. The comparison between the simulated and the analytically modelled effective emissivities shows that the analytical formula is highly accurate. After simulating effective emissivities of the V-shaped valley under several non-isothermal conditions, we find that the structure and component temperature difference of a pixel cause the scaling effects of thermal emission of the pixel. The results, therefore, prove that Planck's law has to be corrected for remote sensing to estimate land surface temperature with high accuracy.     

Estimation of critical dimensions for a trapezoidal-shaped steel fin using hybrid differential evolution algorithm

This paper deals with the inverse prediction of parameters in a trapezoidal fin with temperature-dependent thermal conductivity and heat transfer coefficient. Three critical dimensions along with the relevant heat transfer coefficient at the fin base have been simultaneously predicted for satisfying a given temperature distribution on the surface of the trapezoidal fin. The inverse problem is solved by a hybrid differential evolution-nonlinear programming (DE-NLP) optimization method. For a given fin material which is considered to be stainless steel, it is found from the present study that many feasible dimensions exist which satisfy a given temperature distribution, thereby providing flexibility in selecting any dimensions from the available alternatives by appropriately regulating the base heat transfer coefficient. A very good estimation of the unknown parameters has been obtained even for temperature distribution involving random measurement errors which is confirmed by the comparisons of the reconstructed distributions. It is concluded that for a given fin material, the hybrid DE-NLP algorithm satisfactorily estimates feasible dimensions of a trapezoidal fin even with random measurement error of 11 %.

     

A mono-window algorithm for retrieving land surface temperature from Landsat TM data and its application to the Israel-Egypt border region

Remote sensing of land surface temperature (LST) from the thermal band data of Landsat Thematic Mapper (TM) still remains unused in comparison with the extensive studies of its visible and near-infrared (NIR) bands for various applications. The brightness temperature can be computed from the digital number (DN) of TM6 data using the equation provided by the National Aeronautics and Space Administration (NASA). However, a proper algorithm for retrieving LST from the only one thermal band of the sensor still remains unavailable due to many difficulties in the atmospheric correction. Based on thermal radiance transfer equation, an attempt has been made in the paper to develop a mono-window algorithm for retrieving LST from Landsat TM6 data. Three parameters are required for the algorithm: emissivity, transmittance and effective mean atmospheric temperature. Method about determination of atmospheric transmittance is given in the paper through the simulation of atmospheric conditions with LOWTRAN 7 program. A practicable approach of estimating effective mean atmospheric temperature from local meteorological observation is also proposed in the paper when the in situ atmospheric profile data is unavailable at the satellite pass, which is generally the case in the real world especially for the images in the past. Sensitivity analysis of the algorithm indicates that the possible error of ground emissivity, which is difficult to estimate, has relatively insignificant impact on the probable LST estimation error i T, which is sensible to the possible error of transmittance i 6 and mean atmospheric temperature i T a . Validation of the simulated data for various situations of seven typical atmospheres indicates that the algorithm is able to provide an accurate LST retrieval from TM6 data. The LST difference between the retrieved and the simulated ones is less than 0.4°C for most situations. Application of the algorithm to the sand dunes across the Israel-Egypt border results in a reasonable LST estimation of the region. Based on this LST estimation, spatial variation of the interesting thermal phenomenon has been analysed for comparison of LST difference across the border. The result shows that the Israeli side does have significantly higher surface temperature in spite of its denser vegetation cover than the Egyptian side where bare sand is prevalent.     

Numerical schemes for the forward–backward heat equation

This paper is concerned with a class of forward–backward heat equations. We use Saulyev's scheme to formulate certain approximation schemes. Then a non-overlap domain decomposition method is presented for the numerical solution. The numerical experiments show that the given algorithm is feasible and effective.     

一个从MODIS数据同时反演地表温度和发射率的神经网络算法

MODIS的三个热红外波段29、31、32建立了三个辐射传输方程,这三个方程包含了5个未知数(大气平均作用温度、地表温度和三个波段的发射率)。用JPL提供的大约160种地物的波谱数据对MODIS三个波段(29/31/32)发射率之间的关系和用MODTRAN4对大气透过率和大气水汽含量之间关系进行模拟分析。分析结果表明地球物理参数之间存在着大量的潜在信息。由于潜在的信息难以严格地用数学表达式来描述,因此神经网络是非常适合被用来解这种病态反演问题。利用辐射传输模型(RM)和神经网络(NN)反演分析表明神经网络能够被用来精确地同时从MODIS数据中反演地表温度和发射率。地表温度的平均反演误差在0.4°C以下;波段29/31/32发射率平均反演误差都在0.008以下。     

输入输出双线性系统的递推辨识与实现算法

本文对输入输出双线性系统给出了一套完整的辨识方法。首先给出了输入输出方程的一般形式,并对于一类规范型给出了相应地输入输出差分方程。然后给出了确定系统的结构指标和参数估计的递推算法,它改进了由Katta和Nurges(1984)给出的方法,大大缩短了计量时间。另外,还给出了状态方法的简单实现算法。最后,给出了仿真例子说明算法的有效性。     

The effective resolution element of Landsat Thematic Mapper

Abstract

As part of the U.K.'s contribution to NASA's Landsat [mage Data Quality Analysis (LIDQA) programme the system performance of the Thematic Mapper (TM) scanner has been studied by the determination of the Effective Resolution Element (ERE), a measure of its spatial resolution. Two methods have been used, the first by a simulation of the TM's spatial responses in an analytical model and the second by measurements of water bodies on a selected Landsat-5 TM scene. Bands 1-4 of the Thematic Mappers of both Landsat-4 and Landsal-5 have an effective resolution element by the former method of 52 m. This compares with a value of 122 m for band 4, near-infrared, of the Multispectral Scanner (MSS) by the same method. An image-derived value, by the latter method, for band 4 of the Landsat-5 TM scene is approximately 75 m. This increase in the ERE over the sensor-only value is attributed to additional factors within the imagery such as the pixel sampling of the scene, ground segment processing and the contribution of atmospheric effects. The image-derived measure of the ERE will give a useful indication of the size of targets that can be recorded to a given radiometric accuracy and can thus determine the type of informational classes that may be utilized from present methods of automated classifications of remotely-sensed data.     

Optimization of spectral band envelopes with the use of variable metric methods

A comparative study of the efficiency of 11 iterative algorithms, belonging to the class of variable metric methods was carried out, in application to the problem of optimization of spectral band envelopes.The combination of these 11 correction algorithms with 5 various 1-D minimization methods yielded an ensemble of 55 computational procedures, which were programmed in Turbo Pascal and—independently —in C++. The efficiency of the methods was tested on 33 simulated and experimental band envelopes, with the number of bands ranging from 1 to 20, amounting to 4–80 optimized band parameters.The detailed analysis of the obtained results indicates the best performance of the Goldfarb II algorithm, combined with the geometrical contraction/expansion minimization method with Goldstein's test. Very good performance is shown also by the Davidon-Fletcher-Powell method, the Broyden-Fletcher-Goldfarb-Shanno method and the unified Fletcher algorithm.     

Identification of time‐varying OE models in presence of non‐Gaussian noise: Application to pneumatic servo drives

Intensive research in the field of mathematical modeling of pneumatic servo drives has shown that their mathematical models are nonlinear in which many important details cannot be included in the model. Owing the influence of the combination of heat coefficient, unknown discharge coefficient, and change of temperature, it was supposed that parameters of the pneumatic cylinder are random (stochastic parameters). On the other side, it has been well known that the nonlinear model can be approximated by a linear model with time‐varying parameters. Due to the aforementioned reasons, it can be assumed that the pneumatic cylinder model is a linear stochastic model with variable parameters. In practical conditions, in measurements, there are rare, inconsistent observations with the largest part of population of observations (outliers). Therefore, synthesis of robust algorithms is of primary interest. In this paper, the robust recursive algorithm for output error models with time‐varying parameters is proposed. The convergence property of the proposed robust algorithm is analyzed using the methodology of an associated ordinary differential equation system. Because ad hoc selection of model orders leads to overparameterization or parsimony problem, the robust Akaike's criterion is proposed to overcome these problems. By determining the least favorable probability density for a given class of probability distribution represents a base for design of the robust version of Akaike's criterion. The behavior of the proposed robust identification algorithm is considered through intensive simulations that demonstrate the superiority of the robust algorithm in relation to the linear algorithms (derived under an assumption that the stochastic disturbance has a Gaussian distribution). The good practical values of the proposed robust algorithm to identification of the pneumatic cylinder are illustrated by experimental results. Copyright © 2016 John Wiley & Sons, Ltd.     

Calibration and modelling of MAESTRO 1 polarimetric SAR data of a forest area in Les Landes,France

Abstract. The results of an analysis of polarimetric P, Land C-band SAR data from the JPL AIRSAR of a forest area of maritime pine in Les Landes, southwest France, are described and discussed. The data were acquired in connection with the MAESTRO I Campaign organized by ESA and JRC/lspra. Cross-talk and channel imbalance distortions are removed in a calibration process using the SAR data itself and trihedral corner reflectors positioned at the scene. Two calibration methods have been implemented and compared: the iterative Klein algorithm and the non-iterative Quegan algorithm. Quegan's method shows the largest reduction of the cross-talk, and the most stable and easily interpreted results. Also, absolute calibration using the integral method has been performed. The results presented show that P band (and to some extent L band) is very sensitive to trunk biomass using single-polarization radar data, at least at the incidence angles in the range from 38° to 52°, whereas C band is less sensitive. Also, the cylinder model by Durden et al. of the baekseattering from a forest has been implemented and the results show good agreement with the SAR data. The dominant scattering mechanisms have been determined using the model at P and L bands.     

模拟跨导滤波器多目标并行进化的设计

以往模拟滤波器的设计,需要经过人工多次修改、计算和调试。提出一种模拟跨导滤波器的硬件进化结构及多目标并行进化的设计方法。应用一种基于渗透原理迁移策略的多目标并行遗传算法,实现跨导滤波器的参数优化。对多目标并行遗传算法的遗传操作进行了改进,构造了适合滤波器参数进化的多目标适应度函数。在高[Q]值的跨导滤波器的设计中,采用级联法构成的四阶带通跨导滤波器能够满足其在阻带、通带以及过渡带方面的性能要求,对其实效性进行了仿真和验证,进化的参数数值与理论结果符合得非常好。     

Multiobjective approach for detecting communities in heterogeneous networks

Online social networks have a strong potential to be divided into a number of dense substructures, called communities. In such heterogeneous networks, the communities refer not only to dense parts of links but also to clusters present among other dimensions such as users' profiles, comments, and information flows. To find communities in these networks, researchers have developed a number of methods; however, to the best of the authors' knowledge, these methods are limited in taking only 2 dimensions into account, and they are also not able to give a sense of how users behave in their communities. To deal with these issues, this paper proposes a multiobjective optimization model in which a specific objective function has been used for each considered dimension in a given network. Because of the NP‐hardness of the studied problem, an efficient and effective multiobjective metaheuristic algorithm has been developed. By juxtaposing the nondominated solutions obtained, the proposed algorithm can demonstrate how users behave in their communities. To illustrate the effectiveness of the algorithm, a set of experiments with a comprehensive evaluation method is provided. The results show the superiority and the stability of the proposed algorithm.     

A novel approach for electromagnetic inverse scattering of a two‐dimensional perfect electric conductor object

A two‐dimensional shape determination technique for a perfect electric conductor target using electromagnetic inverse scattering is presented. The proposed algorithm uses the scattered field pattern and an inverse scattering technique derived from Green's function to retrieve the geometry of an unknown target. This method uses the scattering field data over a band of observation points, which is synthesized using frequency domain “method of moment” computational technique. We have verified this algorithm with four different types of numerical examples.     

Classification of patterns representing Apples and Oranges in three-qubit system

The study of the classification of Apples and Oranges in a warehouse has been undertaken in a three-qubit system using the method of repeated iterations in Grover’s algorithm and Ventura’s algorithm separately. Operator describing an inversion about average has been constructed as a square matrix of order eight, the phase inversion operators and corresponding iteration operators for patterns separately representing Apples and Oranges have been derived, and various possible superpositions as the choice for search states for the classification of these patterns have been obtained for starting states consisting of two patterns and a single pattern, respectively. It has been demonstrated that on the second iteration of the exclusion superposition by the corresponding iteration operators, the patterns Apples and Oranges, respectively, are most suitably classified using the Grover’s algorithm. The probabilities of classifications of Apples have also been calculated by using Ventura’s algorithm (Ventura and Martinez in Inf Sci 124:273–296, 2000; Found Phys Lett 12:547–559, 1999) for all the possible superpositions as the search states, and the results have been compared with those of Grover’s algorithm and it has been demonstrated that in general for classification of a given pattern (Apples) in three-qubit system, the Grover’s and Ventura’s algorithms are effective in the cases where the number of patterns in the stored database is larger or smaller, respectively.     

Determination of zeros of polynomials by synthetic division †

An algorithm is introduced for finding zeros of polynomials with real as well as complex coefficients. Based on the geometrical and functional properties of polynomials, the method can determine accurate distinct and repeated zeros of polynomials. The convergence of Newton's method plays an important role in this method. It has been found that the region of convergence by Newton's method is adequate. The important feature of this procedure is the obtaining of zeros of polynomials by combining Newton's method, synthetic division and functional properties of polynomials. The algorithm has been tested on many examples and numerical calculations have produced a greater degree of accuracy.     

A Simultaneous Localization and Mapping Algorithm in Complex Environments: SLASEM

In this paper we present an algorithm for the application of simultaneous localization and mapping in complex environments. Instead of building a grid map or building a feature map with a small number of the obstacles' geometric parameters, the proposed algorithm builds a sampled environment map (SEM) to represent a complex environment with a set of environment samples. To overcome the lack of one-toone correspondence between environment samples and raw observations, the signed orthogonal distance function is proposed to be used as the observation model. A method considering geometric constraints is presented to remove redundant environment samples from the SEM. We also present a method to improve the SEM's topological consistency by using corner constraints. The proposed algorithm has been verified in a simulation and an indoor experiment. The results show that the algorithm can localize the robot and build a complex map effectively.     

A multi-objective artificial immune algorithm for parameter optimization in support vector machine

Support vector machine (SVM) is a classification method based on the structured risk minimization principle. Penalize, C; and kernel, σ parameters of SVM must be carefully selected in establishing an efficient SVM model. These parameters are selected by trial and error or man's experience. Artificial immune system (AIS) can be defined as a soft computing method inspired by theoretical immune system in order to solve science and engineering problems. A multi-objective artificial immune algorithm has been used to optimize the kernel and penalize parameters of SVM in this paper. In training stage of SVM, multiple solutions are found by using multi-objective artificial immune algorithm and then these parameters are evaluated in test stage. The proposed algorithm is applied to fault diagnosis of induction motors and anomaly detection problems and successful results are obtained.     

Minimum Ultimate Band Design of Discrete Sliding Mode Control

The paper presents a generalized understanding on the dynamics of the sliding variable for discrete time sliding mode control systems via a fresh approach involving several bands in the space of the sliding variable. Using this analysis, controller parameters can be obtained once the ultimate band is chosen. It is shown that on choosing the least ultimate band, the control becomes non‐switching and Gao's reaching law becomes identical to Utkin's reaching law. On other occasions, the ultimate band obtained using this approach is clearly less than that obtained in previous works using Gao's reaching law. The analysis is presented for both state feedback and multirate output feedback cases.     

Ground-based method for measuring thermal infrared effective emissivities: Implications and perspectives on the measurement of land surface temperature from satellite data

Thermal infrared emissivity is an important parameter for surface characterization and for determining surface temperature. The field-based measurements for ground and vegetation emissivities in 8-14 w m waveband were performed with an emissivity box. A theoretical analysis was carried out using the box and a correcting factor has been determined. The average value for thermal band emissivity of the exposed bare soil was found to be around 0.909; the average value measured for most of the varieties of vegetation present were in the range of 0.980-0.985. A theoretical model is used for obtaining effective emissivity in the 8-14 w m region from Advanced Very High Resolution Radiometer (AVHRR) data considering the proportion of vegetation cover in a pixel and the field-measured emissivity values. The error of the methodology is found to be within 1.5%. Narrow band emissivities for AVHRR channels 4 and 5 have been derived from the emissivity values in the 8-14 w m waveband. The surface temperature has been derived from AVHRR data using a split-window algorithm as a function of emissivities derived in narrow bands. The split-window algorithm accounted for absorption effects of the atmosphere by incorporating the water vapour concentration measured in the campaign. A good agreement was obtained between the satellite-derived surface temperature and the in situ observations. The result suggest that the methodology allows us to derive land surface temperature with an accuracy better than 1.5° C provided the surface emissivity is known. The paper describes the field-based emissivity measurement and approach for deriving surface temperature over land surface.