Directed model checking with distance-preserving abstractions

In directed model checking, the traversal of the state space is guided by an estimate of the distance from the current state to the nearest error state. This paper presents a distance-preserving abstraction for concurrent systems that allows one to compute an interesting estimate of the error distance without hitting the state explosion problem. Our experiments show a dramatic reduction both in the number of states explored by the model checker and in the total runtime.     

On finite dynamic equations for fluid-saturated porous media

Summary The paper concerns the relations between two principally different approaches to the formulation of momentum balance equations in porous media theories, namely, the dynamic approach similar to Biot's theory and the modern approach as a result of mixture theories extended by the concept of volume fractions. In particular, it is shown that both approaches necessarily lead to the same type of momentum balance equations and furthermore contain, in a certain sense, within the geometrically linear case, the well-known classical equations of Biot's theory.     

Verified inclusion for eigenvalues of the first order PLL equation with general phase detector characteristics

We present a method depending on matrix continued fractions and Sturm's comparison theorem to obtain verified inclusions for eigenvalues of the underlying boundary value problem of the first-order phase locked loop equation $pu'' + (\lambda + \tilde g)u = 0$ ,p = 1/SNR with general phase detector characteristic $\tilde g(\phi )$ .     

Electromagnetic field diffusion, θ-functions,and image solutions

Contents We discuss some initial and boundary value problems of one-dimensional electromagnetic field diffusion. The solutions can be given by infinite series in two essentially different (however equivalent) forms, one being the usual Fourier-expansion and the other one being an infinite series of Gaussian exponentials or related functions (as for instance error-functions). The second form can be obtained by using infinitely many images to fulfill initial and boundary conditions. Finally the mathematical relations between the two equivalent types of solutions are discussed in terms of -functions and their transformation properties. The existence of the solutions in these two different forms is very interesting from a numerical point of view also.

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Die Diffusion elektromagnetischer Felder, -Funktionen und Spiegelungsmethoden

Übersicht Es werden einige Anfangs- und Randwertprobleme eindimensionaler elektromagnetischer Felddiffusion erörtert. Die Lösungen können in zwei wesentlich verschiedenen (jedoch gleichwertigen) Formen angegeben werden, erstens in Form üblicher Fourier-Reihen und zweitens in Form unendlicher Reihen von Gaußschen Exponentialfunktionen oder damit verwandter Funktionen (z.B. Fehlerfunktionen). Diese zweite Form der Lösungen läßt sich durch die Anwendung unendlich oft wiederholter Spiegelung zur Erfüllung der Rand- und Anfangsbedingung anschaulich interpretieren. Abschließend werden die beiden Lösungstypen mit Hilfe von -Funktionen und deren Transformationseigenschaften erläutert. Die Verfügbarkeit der Lösungen in beiden Formen ist auch numerisch sehr interessant.

     

Performance Analysis of Breast Cancer Detection Method Using ANFIS Classification Approach

Breast cancer is one of the deadly diseases prevailing in women. Earlier detection and diagnosis might prevent the death rate. Effective diagnosis of breast cancer remains a significant challenge, and early diagnosis is essential to avoid the most severe manifestations of the disease. The existing systems have computational complexity and classification accuracy problems over various breast cancer databases. In order to overcome the above-mentioned issues, this work introduces an efficient classification and segmentation process. Hence, there is a requirement for developing a fully automatic methodology for screening the cancer regions. This paper develops a fully automated method for breast cancer detection and segmentation utilizing Adaptive Neuro Fuzzy Inference System (ANFIS) classification technique. This proposed technique comprises preprocessing, feature extraction, classifications, and segmentation stages. Here, the wavelet-based enhancement method has been employed as the preprocessing method. The texture and statistical features have been extracted from the enhanced image. Then, the ANFIS classification algorithm is used to classify the mammogram image into normal, benign, and malignant cases. Then, morphological processing is performed on malignant mammogram images to segment cancer regions. Performance analysis and comparisons are made with conventional methods. The experimental result proves that the proposed ANFIS algorithm provides better classification performance in terms of higher accuracy than the existing algorithms.     

An Automated Brain Image Analysis System for Brain Cancer using Shearlets

In this paper, an Automated Brain Image Analysis (ABIA) system that classifies the Magnetic Resonance Imaging (MRI) of human brain is presented. The classification of MRI images into normal or low grade or high grade plays a vital role for the early diagnosis. The Non-Subsampled Shearlet Transform (NSST) that captures more visual information than conventional wavelet transforms is employed for feature extraction. As the feature space of NSST is very high, a statistical t-test is applied to select the dominant directional sub-bands at each level of NSST decomposition based on sub-band energies. A combination of features that includes Gray Level Co-occurrence Matrix (GLCM) based features, Histograms of Positive Shearlet Coefficients (HPSC), and Histograms of Negative Shearlet Coefficients (HNSC) are estimated. The combined feature set is utilized in the classification phase where a hybrid approach is designed with three classifiers; k-Nearest Neighbor (kNN), Naive Bayes (NB) and Support Vector Machine (SVM) classifiers. The output of individual trained classifiers for a testing input is hybridized to take a final decision. The quantitative results of ABIA system on Repository of Molecular Brain Neoplasia Data (REMBRANDT) database show the overall improved performance in comparison with a single classifier model with accuracy of 99% for normal/abnormal classification and 98% for low and high risk classification.     

Rotational Spectra of the Isotopic Species of Chloroform: Experimental and Ab Initio Structures

The millimeter-wave spectra of three different samples of chloroform (CHCl3, CDCl3, and 13CHCl3) have been measured between 145 and 470 GHz which corresponds to J values between 22 and 70. We report accurate rotational and centrifugal distortion constants for the ground vibrational states of 11 isotopic species. The experimental ro, rs, rIepsilon, rrhom, and rz structures have been determined using the determined rotational constants. The structure has also been calculated ab initio at the SCF, MP2, RQCISD, and B3LYP levels using triple zeta polarized basis sets. The experimental results are found in excellent agreement with the ab initio predictions. An approximate equilibrium structure has been obtained by combining the experimental results and the ab initio calculations: re(C-H) = 1.080 (2) ?, re(C-Cl) = 1.760 (2) ?, and anglee(HCCl) = 108.23 (2) degrees. Copyright 1998 Academic Press.     

Large deformation measurement by holographic interferometry

Summary The use of holographic interferometry for the measurement of large deformations is described. From the nature of holographic interferometry it is evident that large deformations exceed the wave length of the light source used by at least ten times of this size. To obtain holographically identifiable values of large deformations, a method of successive partial lighting is used. It shows how it is possible to keep all the advantages of the holographic method and use it even under conditions which apparently exceed its possibilities of application.     

Impact of ZnO gate interfacial layer on piezoelectric response of AlGaN/GaN C-HEMT based ring gate capacitor

We report on a piezoelectric response investigation of AlGaN/GaN circular high electron mobility transistor (C-HEMT) based ring gate capacitor as a new stress sensor device to be potentially applied for dynamic high-pressure sensing. A ring gate capacitor of C-HEMT with an additional ZnO gate interfacial layer was used to measure the changes in the piezoelectric charge induced directly by the variation of piezoelectric polarization of both gate piezoelectric layers (AlGaN, ZnO) for harmonic loading at different excitation frequences. Our experimental results show that about 10 nm thick piezoelectric ZnO layer grown on ring gate/AlGaN interface of C-HEMT can yield almost a 60% increase in the piezoelectric detection sensitivity of the device due to its higher piezoelectric coefficient. A three-dimensional CoventorWare simulation is carried out to confirm the increase in the measured piezoelectric response of ZnO based ring gate capacitor of C-HEMT.