Linear Transformation Function Research Articles

Transient response of a signal through a dispersive invisibility cloak.

The transient response of the invisibility cloak has long been an interesting research topic, since it is valuable to further understand the steady-state process and to design more effective cloaks. Here we investigate the transient response of a set of dispersive invisibility cloaks impinged on by a sinusoidal signal or a modulated Gaussian pulse using the finite difference time domain method. Cylindrical cloaks with linear, convex, and concave transformation functions are studied. We find that their time to reach a steady state is different and they grow significantly when the thickness of the cloak decreases. Moreover, a centrally depressed ladder-like spatial time delay distribution is observed with a modulated Gaussian pulse. We show that the central frequency of the Gaussian pulse suffers a blue-shift in the forward scattering direction in agreement with previous theoretical predictions.

Image Encryption Using Block Cipher Based Serpent Algorithm

In an encryption scheme, the message or information, referred to as plaintext, is encrypted using an encryption algorithm, generating cipher textthat can only be read if decrypted.A proposal algorithm forimages protectionis depending on the block cipher serpent algorithm infeistel network structure, because numbers of round and linear transformation function and used block size of 512 bits rather than 128 bitshas more complexity for attacker or unauthorized person to discover original images.In modified serpent, the correlation coefficient decreases to below the traditional serpent algorithm. When 64*64 pixel bitmap image is used the correlation coefficient for gray level between plain image and cipher image is (0.0023) in modified serpent and (0.0814) in traditional serpent.

Correction of illumination fluctuations in phase-shifting technique by use of fringe histograms.

With phase-shifting technique, the illumination fluctuations may decrease measurement accuracy. This paper presents a simple method for solving this problem by use of fringe histograms. A fringe pattern containing bright and dark fringes is recognized as an image having two classes of pixels following a bimodal histogram, and the optimal threshold for segmenting this pattern enables maximizing its intervariance between the two classes. Using this optimal threshold, some statistics of the segmented classes, that is, their means, keep stable during phase shifting. Using these means of classes as nodes allows us to determine a linear transformation function by which the fluctuations of the fringe patterns in background intensities and modulations are corrected. Numerical simulation and experimental results demonstrate this method to be efficient and effective in improving the phase measuring accuracies with phase-shifting technique.

Inter-Utility Performance Benchmarking Model for Small-to-Medium-Sized Water Utilities: Aggregated Performance Indices

AbstractAbout 95% of the water supply systems in Canada are being operated by small-to-medium-sized water utilities (SMWU) serving populations less than 50,000. The representation of these utilities in National Water and Wastewater Benchmarking Initiative (NWWBI) is almost negligible due to less awareness, issues related to data availability, and financial constraints. In the present work, an inter-utility performance benchmarking model (IU-PBM) is developed, which entails consideration of 47 performance indicators (PIs) for different functional components of SMWU, such as water resources and environment, personnel, physical assets, quality of service, water quality and public health, and financial aspects. For performance benchmarking, 47 (linear, exponential, logarithmic, and polynomial) transformation functions have been established to translate the calculated PIs into performance levels between 10 and 100, which is based on literature, NWWBI reports, and expert judgment. The weights are estimated usin...

Model Generation of Accented Speech using Model Transformation and Verification for Bilingual Speech Recognition

Nowadays, bilingual or multilingual speech recognition is confronted with the accent-related problem caused by non-native speech in a variety of real-world applications. Accent modeling of non-native speech is definitely challenging, because the acoustic properties in highly-accented speech pronounced by non-native speakers are quite divergent. The aim of this study is to generate highly Mandarin-accented English models for speakers whose mother tongue is Mandarin. First, a two-stage, state-based verification method is proposed to extract the state-level, highly-accented speech segments automatically. Acoustic features and articulatory features are successively used for robust verification of the extracted speech segments. Second, Gaussian components of the highly-accented speech models are generated from the corresponding Gaussian components of the native speech models using a linear transformation function. A decision tree is constructed to categorize the transformation functions and used for transformation function retrieval to deal with the data sparseness problem. Third, a discrimination function is further applied to verify the generated accented acoustic models. Finally, the successfully verified accented English models are integrated into the native bilingual phone model set for Mandarin-English bilingual speech recognition. Experimental results show that the proposed approach can effectively alleviate recognition performance degradation due to accents and can obtain absolute improvements of 4.1%, 1.8%, and 2.7% in word accuracy for bilingual speech recognition compared to that using traditional ASR approaches, MAP-adapted, and MLLR-adapted ASR methods, respectively.

External Cylindrical Invisibility Cloaks With Small Material Dynamic Range

By means of the commonly used transformation optics, and a general transformation function, new sets of external cylindrical invisibility cloaks are proposed. For the proposed cloaks, a rigorous analysis is performed and the results indicate zero scattering coefficients outside of the cloaks. Later, a numerical investigation shows that the material dynamic range (MDR) of the proposed cloaks can be as small as half of that of the previously introduced cloak which was based on a simple linear transformation function. The obtained analytical results are verified using a Finite-Element computational analysis.

Commercial Bank Efficiency Evaluation in Consideration of the Undesirable Output and Its Link with Stakeholders Relationship: An Application of China’s Commercial Banks

Based on the modern contract theory, expectancy theory, and stakeholder theory, this paper analyzes how stakeholders relationship influences the efficiency of commercial banks and finds that the efficiency is a function of stakeholders relationship. A DEA model with Seiford's linear transformation function is developed to evaluate the efficiency in consideration of the undesirable output. The panel Tobit model is established to conduct empirical research with data of 14 Chinese commercial banks from 2004 to 2012. The study finds that except for business customer relation, stakeholder relationship is the key variable that influences comprehensive efficiency of commercial banks.

Wavelength-band Transformation Method of Gray-body Infrared Image Using Surface Temperature Estimation

Infrared (IR) imaging systems obtain thermal images by converting surface temperature into two-dimensional images by measuring IR radiation from an object’s surface. This research proposes a wavelength-band transformation method to convert an IR image of an arbitrary wavelength-bandwidth into an IR image of another wavelength-bandwidth. We estimate the temperature of an arbitrary wavelength by obtaining the radiance from the black body radiation theory and the linear transformation function of the gray level from the radiance. We generate an IR image for another wavelength-bandwidth by calculating the radiance of another wavelength-bandwidth using the estimated temperature. The validity of the proposed method was verified through simulations. The IR target image was generated using RadThermIR software, and images, acquired from a thermal observation device, were used as IR background image.

Feature space optimization for content-based image retrieval

Substantial benefits can be gained from effective Relevance Feedback techniques in content-based image retrieval. However, existing techniques are limited due to computational cost and/or by being restricted to linear transformations on the data. In this study we analyze the role of nonlinear transformations in relevance feedback. We present two promising Relevance Feedback methods based on Genetic Algorithms used to enhance the performance on the task of image retrieval according to the user's interests. The first method adjusts the dissimilarity function by using weighting functions while the second method redefines the features space by means of linear and nonlinear transformation functions. Experimental results on real data sets demonstrate that our methods are effective and the results show that the transformation approach outperforms the weighting approach, achieving a precision gain of up to 70%. Our results indicate that nonlinear transformations have a great potential in capturing the user's interests in image retrieval and should be further analyzed employing other learning/optimization mechanisms.

OLED 디스플레이를 위한 저전력 대조비 향상 기법

A low power contrast enhancement algorithm for OLED displays is proposed in this work. The proposed algorithm increases the contrast of the image based on a linear transformation function, while reducing the power consumption of OLED displays. Furthermore, the proposed algorithm extends the global contrast enhancement to local contrast enhancement using the block-based transformation function. Simulation results demonstrate that the proposed algorithm reduces the power consumption, while enhancing the contrast of an input image.

Do benchmark revisions affect the consumption-to-output and investment-to-output ratios in Germany?

The balanced growth and stochastic growth theory implies stable consumption-to-output and investment-to-output ratios. It is tested by cointegration techniques for three different German data vintages. Systems cointegration tests are helpful in revealing inconsistencies across vintages. Differencing and rebasing, often used to adjust for benchmark revisions, are generally not sufficient to ensure consistent real-time macroeconomic data. Vintage transformation functions estimated by cointegrating regressions are more flexible. Empirically, the cointegrating property between consumption and output, as well as between investment and output, is often found, whereas the one-to-one relationship is mostly rejected. Moreover, the linear transformation function is helpful in describing the relation between two older final vintages. This function seems to be insufficient if the most recent data collection framework is involved.

Equivalent configurations of optical transformation media

We demonstrate that a medium consisting of two adjoining distinct layers of transformation materials, corresponding respectively to two linear coordinate transformations, can behave effectively as that of the same region transformed by another linear transformation. The equivalence means that, irrespective of the direction of incident wave, the fields of the medium exterior to the transformed regions of the two configurations are exactly the same. This property can also apply to a domain that is transformed by a piecewise linear transformation function, and to a medium that is mapped by a general curved function. This proof is shown analytically based on a rigorous Fourier-Bessel analysis. The equivalence suggests that, for a given transformed domain, one can find an infinite number of complementary media that altogether can give a desired effective response of certain transformation path.

Forecasting by Dynamic Regression Models with an Application

Dynamic Regression Model is that model which takes the time into account. The modeling of the Dynamic Regression shows how the output is resulted from the input. This depends on the following: 1. The relation of the lag time with the input and output. 2. The time composition for the turbulence series (random error) In order provide mathematical model, the relative model was identified by specifying the linear transformation function. The relative model of the transformation function was of the degree (0, 0, 1). When the values of turbulence series were examined by using auto - correlation and partial auto correlation coefficients, it is found that all of the coefficients were insignificant and that consequently proves the turbulence series which is a series of random residuals, so that:- N‌t=at. Nt=at.

Genetic algorithms for optimality of data hiding in digital images

This paper investigates the scope of usage of Genetic Algorithms (GA) for data hiding in digital images. The tool has been explored in this topic of research to achieve an optimal solution in multidimensional nonlinear problem of conflicting nature that exists among imperceptibility, robustness, security and payload capacity. Two spatial domain data hiding methods are proposed where GA is used separately for (i) improvement in detection and (ii) optimal imperceptibility of hidden data in digital images respectively. In the first method, GA is used to achieve a set of parameter values (used as Key) to represent optimally the derived watermark in the form of approximate difference signal used for embedding. In the second method, GA is used for finding out values of parameters, namely reference amplitude (A) and modulation index (μ) both with linear and non linear transformation functions, for achieving the optimal data imperceptibility. Results on robustness for both the methods against linear, non linear filtering, noise addition, and lossy compression as well as statistical invisibility of the hidden data are reported here for some benchmark images.

α-Jacobian environmental adaptation

The robustness of automatic speech recognition systems to noise is still a problem, especially for small footprint systems. This paper addresses the problem of noise robustness using model compensation methods. Such algorithms are already available, but their complexity is usually high. An often-referenced method for achieving noise robustness is parallel model combination (PMC). Several algorithms have been proposed to develop more computationally efficient methods than PMC. For example, Jacobian adaptation approximates PMC with a linear transformation function in the cepstral domain. However, the Jacobian approximation is valid only for test environments that are close to the training conditions whereas, in real test conditions, the mismatch between the test and training environments is usually large. In this paper, we propose two methods, respectively called static and dynamic α-Jacobian adaptation (or α-JAC), to compute new linear approximations of PMC for realistic test environments. We further extend both algorithms to compensate for additive and convolutional noise and we derive the corresponding non-linear algorithm that is approximated. All these algorithms are experimentally compared in important mismatch conditions. As compared to Jacobian adaptation, improvements are observed with both static and dynamic α-Jacobian adaptation.

Classificação e eliminação dos ruídos em imagens hiperespectrais pela análise seqüencial da transformação por Fração de Ruído Mínima

As imagens hiperespectrais são muito suscetíveis às interferências de ruídos, o que dificulta a identificação e a quantificação mineral. Portanto, torna-se fundamental o emprego de técnicas para minimizá-los. Um eficiente procedimento matemático para redução de ruídos é a Fração de Ruído Mínima (MNF). Esse método é derivado e análogo à transformação Análise de Componentes Principais, distinguindo-se por promover a maximização do ruído ao invés da variância dos dados, o que proporciona um ordenamento que reflete a qualidade das imagens. A transformação MNF pode ser subdividida em quatro etapas: a) obtenção de uma amostra do ruído; b) formulação de um índice de fracionamento do ruído; c) implementação de uma função de transformação linear no molde da APC, e d) inversão do MNF considerando apenas as informações de sinais. No presente trabalho é proposta uma metodologia de MNF seqüencial, utilizando referências internas e externas da imagem. Como referência externa foi utilizada a referência escura coletada durante o vôo simultaneamente à obtenção da imagem. A referência interna foi obtida por técnicas estatísticas para a segmentação da fração do ruído em relação ao sinal. Três tipos de ruídos podem ser definidos conforme a variância e correlação: a) ruídos não-correlacionados e com igual variância; b) ruídos altamente correlacionados; e c) ruídos com matriz de covariância desconhecida. Para as imagens AVIRIS pode-se esquematizar um procedimento seqüencial de MNF com duas etapas, sendo que, na primeira, são eliminados os ruídos de referência interna e na segunda, os de referência externa relativos ao ruído instrumental. Esse procedimento permite distinguir diferentes tipos de ruídos e eliminá-los seqüencialmente, de forma simples e eficiente.

The radiometric normalization of multitemporal Thematic Mapper imagery of the midlands of Ireland - a case study

Two Landsat Thematic Mapper (TM) scenes of the same area of the midlands of Ireland were required to be radiometrically normalized. Standard techniques were reviewed and considered unsuitable. A hybrid approach was adopted that used linear transformation functions. As part of this approach, a novel thresholding-based method for extracting reference data from a land cover class with sub-pixel scale elements was developed. This method was shown to be robust with a consistency of ca - 1 digital number (DN) being achievable in the extracted reference data. A procedure for removing pixels influenced by thin cloud and associated shadow was included. The radiometric normalization approach produced acceptable Root Mean Square Errors in the range 0.8-2.5 DN. Whereas the strategies and methodologies developed were appropriate to the particular environment, the developmental process may serve as a template for analysts working in similar environments elsewhere.

Reducing Prediction Error by Transforming Input Data for Neural Networks

The application of neural networks (NNs) in construction cover a large range of topics, including estimating construction costs and markup estimation, predicting construction productivity, predicting settlements during tunneling, and predicting the outcome of construction litigation. The primary purpose of data transformation is to modify the distribution of input variables so that they can better match outputs. The performance of a NN is often improved through data transformations. There are three existing data transformation methods: linear transformation, statistical standardization, and mathematical functions. This paper presents another data transformation method using cumulative distribution functions, simply addressed as distribution transformation. This method can transform a stream of random data distributed in any range to data points uniformly distributed on the interval [0,1]. Therefore, all neural input variables can be transformed to the same ground-uniform distributions on [0,1]. The transformation can also serve the specific need of neural computation that requires all input data to be scaled to the range [1,1] or [0,1]. The paper applies distribution transformation to two examples. Example 1 fits a cowboy hat surface because it provides a controlled environment for generating accurate input and output data patterns. The results show that distribution transformation improves the network performance by 50% over linear transformation. Example 2 is a real tunneling project, the Brasilia Tunnel, in which distribution transformation has reduced the prediction error by more than 13% compared with linear transformation.

Wearing-out of components in a variable environment

Abstract The probabilistic model for the wearing-out component’s performance is studied, based on the Markov-Additive Principle (MAP) of wearing-out. It is proved that under certain assumptions this principle leads to the accelerated life model (ALM), according to which the lifetime distribution functions (DFs) in some baseline (reference) and real environments are connected via a general time transformation function. The specific linear transformation function is widely used in the accelerated testing procedures. The change point in environment is considered and the remaining lifetime DF is derived in the formal way for various settings. The effect of shocks, increasing the components wear-out, is studied as well as the effect of an operation of the opposite nature that decreases wear-out. Different maintenance activities usually can be considered as wear-out decreasing. Several generalisations are presented.

On the determination of functions from their integral values along certain manifolds

When one integrates a function of two variables x,y - a point function f(P) in the plane - subject to suitable regularity conditions along an arbitrary straight line g then one obtains in the integral values F(g), a line function. In Part A of the present paper the problem which is solved is the inversion of this linear functional transformation, that is the following questions are answered: can every line function satisfying suitable regularity conditions be regarded as constructed in this way? If so, is f uniquely known from F and how can f be calculated? In Part B a solution of the dual problem of calculating a line function F(g) from its point mean values f(P) is solved in a certain sense. Finally, in Part C certain generalizations are discussed, prompted by consideration of non-Euclidean manifolds as well as higher dimensional spaces. The treatment of these problems, themselves of interest, gains enhanced importance through the numerous relationships that exist between this topic and the theory of logarithmic and Newtonian potentials. These are mentioned at appropriate places in the text.