Memoryless Thermodynamics? A Reply

We reply to arXiv:1508.00203 `Comment on "Identifying Functional Thermodynamics in Autonomous Maxwellian Ratchets" (arXiv:1507.01537v2)'.Comment: 4 pages; http://csc.ucdavis.edu/~cmg/compmech/pubs/MerhavReply.ht

FoodNet: Recognizing Foods Using Ensemble of Deep Networks

In this work we propose a methodology for an automatic food classification system which recognizes the contents of the meal from the images of the food. We developed a multi-layered deep convolutional neural network (CNN) architecture that takes advantages of the features from other deep networks and improves the efficiency. Numerous classical handcrafted features and approaches are explored, among which CNNs are chosen as the best performing features. Networks are trained and fine-tuned using preprocessed images and the filter outputs are fused to achieve higher accuracy. Experimental results on the largest real-world food recognition database ETH Food-101 and newly contributed Indian food image database demonstrate the effectiveness of the proposed methodology as compared to many other benchmark deep learned CNN frameworks.Comment: 5 pages, 3 figures, 3 tables, IEEE Signal Processing Letter

PT-Symmetric, Quasi-Exactly Solvable matrix Hamiltonians

Matrix quasi exactly solvable operators are considered and new conditions are determined to test whether a matrix differential operator possesses one or several finite dimensional invariant vector spaces. New examples of $2\times 2$-matrix quasi exactly solvable operators are constructed with the emphasis set on PT-symmetric Hamiltonians.Comment: 14 pages, 1 figure, one equation corrected, results adde

Distinguishing Posed and Spontaneous Smiles by Facial Dynamics

Smile is one of the key elements in identifying emotions and present state of mind of an individual. In this work, we propose a cluster of approaches to classify posed and spontaneous smiles using deep convolutional neural network (CNN) face features, local phase quantization (LPQ), dense optical flow and histogram of gradient (HOG). Eulerian Video Magnification (EVM) is used for micro-expression smile amplification along with three normalization procedures for distinguishing posed and spontaneous smiles. Although the deep CNN face model is trained with large number of face images, HOG features outperforms this model for overall face smile classification task. Using EVM to amplify micro-expressions did not have a significant impact on classification accuracy, while the normalizing facial features improved classification accuracy. Unlike many manual or semi-automatic methodologies, our approach aims to automatically classify all smiles into either `spontaneous' or `posed' categories, by using support vector machines (SVM). Experimental results on large UvA-NEMO smile database show promising results as compared to other relevant methods.Comment: 16 pages, 8 figures, ACCV 2016, Second Workshop on Spontaneous Facial Behavior Analysi

Impurity Substitution in Bismuth and Thallium Cuprates: Suppression of T_c and Estimation of Pseudogap

Suppression of T_c in bilayer bismuth and thallium cuprates, by substitution of Co impurities at Cu sites, are taken for examination. T_c suppression data on differently doped Bi2212 and Tl2212 are analysed within the unitary pair-breaking formalism due to Abrikosov and Gorkov, by fitting data points to a phenomenological relation valid for weak coupling d-wave superconductors. Values of the pseudogap magnitude at each doping are thereby estimated within a "fermi-level density of states suppression" picture. Pseudogap magnitude from our estimation is observed to have a correspondence with a related characteristic temperature T^\star obtained by thermoelectric power measurements. Effects of pseudogap, on the density of states, is studied by calculating the susceptibility which shows a broad peak at high temperature. This peak feature in susceptibility is indicative of an unusual metallic state which could further be explored by systematic other measurements.Comment: Latex file, 14 pages, 3 figures (ps files included). To appear in Physica

Bound and scattering states of extended Calogero model with an additional PT invariant interaction

Here we discuss two many-particle quantum systems, which are obtained by adding some nonhermitian but PT (i.e. combined parity and time reversal) invariant interaction to the Calogero model with and without confining potential. It is shown that the energy eigenvalues are real for both of these quantum systems. For the case of extended Calogero model with confining potential, we obtain discrete bound states satisfying generalised exclusion statistics. On the other hand, the extended Calogero model without confining term gives rise to scattering states with continuous spectrum. The scattering phase shift for this case is determined through the exchange statistics parameter. We find that, unlike the case of usual Calogero model, the exclusion and exchange statistics parameter differ from each other in the presence of PT invariant interaction.Comment: 7 pages, latex, uses czjphys.cls, contributed to the `1st International Workshop on Pseudo-Hermitian Hamiltonians in Quantum Physics', Prague, June 16-17, 200