We follow the consequences of internal equilibrium in non-equilibrium systems that has been introduced recently [Phys. Rev. E 81, 051130 (2010)] to obtain the generalization of Maxwell's relation and the Clausius-Clapeyron relation that are normally given for equilibrium systems. The use of Jacobians allow for a more compact way to address the generalized Maxwell relations; the latter are available for any number of internal variables. The Clausius-Clapeyron relation in the subspace of observables show not only the non-equilibrium modification but also the modification due to internal variables that play a dominant role in glasses. Real systems do not directly turn into glasses (GL) that are frozen structures from the supercooled liquid state L; there is an intermediate state (gL) where the internal variables are not frozen. Thus, there is no single glass transition. A system possess several kinds of glass transitions, some conventional (L \rightarrow gL; gL\rightarrow GL) in which the state change continuously and the transition mimics a continuous or second order transition, and some apparent (L\rightarrow gL; L\rightarrow GL) in which the free energies are discontinuous so that the transition appears as a zeroth order transition, as discussed in the text. We evaluate the Prigogine-Defay ratio {\Pi} in the subspace of the observables at these transitions. We find that it is normally different from 1, except at the conventional transition L\rightarrow gL, where {\Pi}=1 regardless of the number of internal variables.

To investigate the consequences of component confinement such as at a glass transition and the well-known energy or enthalpy gap (between the glass and the perfect crystal at absolute zero, see text), we follow our previous approach [Phys. Rev. E 81, 051130 (2010)] of using the second law applied to an isolated system {\Sigma}_0 consisting of the homogeneous system {\Sigma} and the medium {\Sigma}. We establish on general grounds the continuity of the Gibbs free energy G(t) of {\Sigma} as a function of time at fixed temperature and pressure of the medium. It immediately follows from this and the observed continuity of the enthalpy during component confinement that the entropy S of the open system {\Sigma} must remain continuous during a component confinement such as at a glass transition. We use these continuity properties and the recently developed non-equilibrium thermodynamics to formulate thermodynamic principles of additivity, reproducibility, continuity and stability that must also apply to non-equilibrium systems in internal equilibrium. We find that the irreversibility during a glass transition only justifies the residual entropy S_{R} to be at least as much as that determined by disregarding the irreversibility, a common practice in the field. This justifies a non-zero residual entropy S_{R} in glasses, which is also in accordance with the energy or enthalpy gap at absolute zero. We develop a statistical formulation of the entropy of a non-equilibrium system, which results in the continuity of entropy during component confinement in accordance with the second law and sheds light on the mystery behind the residual entropy, which is consistent with the recent conclusion [Symmetry 2, 1201 (2010)] drawn by us.

Human Interactive Proofs (HIPs) are automatic reverse Turing tests designed to distinguish between various groups of users. Completely Automatic Public Turing test to tell Computers and Humans Apart (CAPTCHA) is a HIP system that distinguish between humans and malicious computer programs. Many CAPTCHAs have been proposed in the literature that text-graphical based, audio-based, puzzle-based and mathematical questions-based. The design and implementation of CAPTCHAs fall in the realm of Artificial Intelligence. We aim to utilize CAPTCHAs as a tool to improve the security of Internet based applications. In this paper we present a framework for a text-based CAPTCHA based on Devanagari script which can exploit the difference in the reading proficiency between humans and computer programs. Our selection of Devanagari script-based CAPTCHA is based on the fact that it is used by a large number of Indian languages including Hindi which is the third most spoken language. There is potential for an exponential rise in the applications that are likely to be developed in that script thereby making it easy to secure Indian language based applications.

In most of the Optical Character Recognition soft-wares, a substantial percentage of errors are caused by the incor-rect segmentation of degraded words. This is especially true forrecognizing old books, newspapers and historical manuscripts.In this paper, we propose multiple segmentation methods whichaddress the problem of cuts and merges in degraded words. Wehave created an annotated dataset of 1034 word images withpixel level ground truth for quantitative evaluation of the meth-ods. We compare the methods with a baseline implementationbased on connected component analysis. We report substantialimprovement in accuracy both at character and at word level.Keywords-Character Segmentation; Degradation Correction;Malayalam; Indian Language;

People start learning to read and write during the early stage of education. As years pass by they may have acquired good reading and writing skills. It may not be difficult for them to read any kind of either printed or handwritten characters. Most people have no problem in reading any kind of light prints or heavy prints, upside down prints, prints of different fonts and styles, handwritten whether it is neatly or sloppily written. But Computers may find difficultly in deciphering many kinds of printed characters which is of different fonts and styles or handwritten characters. To evolve a panacea to this problem human brains have been indulging in various research activities. This paper is a humble attempt for the recognition of handwritten Malayalam (a South Indian Language) characters. In our study we have classified the connected characters into 3 categories. Here we propose an algorithm which uses the inveterate characteristic features to recognize these characters with perceptive accuracy by utilizing the intensity variations in the way in which they may be written. This algorithm recognizes the antediluvian script of Malayalam characters which are connected in nature. Here the input is a 24-bit bmp image which can be enscribed using the Light pen. The output is editable version of the recognized Malayalam characters. In our study we have classified the connected characters into 3 categories. The algorithm is tested for 3 sets of samples ranging 402 letters in noiseless environment and produces accuracy of 94%.

This paper proposes an algorithm for the recognition of handwritten characters in Malayalam, a South Indian language. It introduces the salient features of Malayalam script and lists the approaches used for character recognition. Malayalam scripts are rich in patterns because of their complex curved form, larger number of basic elements and the presence of conjuncts. The combinations of such patterns make the recognition of characters much complex and these patterns should be exploited to arrive at the solution. Here an image of handwritten Malayalam characters is given as the input and an editable document of Malayalam characters in a predefined format is produced as output. In this paper, initially the overall structure of OCR system is presented. Then, the OCR process is presented in three modules: Pre-processing, Skeletonization and Recognition. In Pre-processing, we scan the input image and separate each character from it. In Skeletonization, we obtain one pixel thick skeleton of the character. In Recognition, we classify the characters based on their features. The features of the characters are extracted based on the analysis of position and count of the horizontal and vertical lines.