<p>Shiv Nadar University is a comprehensive, multidisciplinary, research-focused, and student-centric University offering a full range of academic programs at the undergraduate, postgraduate and doctoral level. With state-of-the-art infrastructure, the University comprises of academic wings, sophisticated labs, international standard sports facilities, amphitheaters, auditorium, conference rooms and smart classrooms. The University&rsquo;s goal is to become internationally recognized for the quality of its research and creative endeavors and their applicability to improving quality of life, generating new insights and expanding the boundaries of human knowledge creativity. Committed to excellence in teaching, research and service, the University aims to serve the higher education needs of India and the world beyond.</p>

Shiv Nadar University

Center for Informatics

VIJAY KUMAR FOUNDATION CHENNAI (INDIA)

First principles modeling of Segregation of Nd to YAG grain boundarie

Frontiers in the Design of Materials

Ab initio Design of Novel Materials with Optimized Properties at the Atomic Scale

Using first principles calculations within the generalized gradient approximation, the structural stability of compound Mo-S clusters at subnanometer level is discussed based on results obtained for various Mo 5Sn isomers with n = 5-15. The symmetrical Mo-S bonds generally lead to higher stability, while the formation of S-S bond and the observation of magnetism in these clusters lower the structural stability. Mo5Sn isomers with n = 6, 8 and 11 are found to be most stable. The addition of sulfur atoms is quite favorable in the edge capped square pyramid and face capped trigonal bipyrammid isomers. {\textcopyright}2007 Society of Nano Science and Technology.

World University root node

Materials Transactions

Understandng the structural stability of compound Mo-S clusters at sub-nanometer level

Owing to the superiority of Dynamic Time Warping as a similarity measure of time series, it can become an effective tool for fault diagnosis in chemical process plants. However, direct application of Dynamic Time Warping can be computationally inefficient, given the complexity involved. In this work we have tackled this problem by employing a warping window constraint and a Lower Bounding measure. A novel methodology for online fault diagnosis with Dynamic Time Warping has been suggested and its performance has been investigated using two simulated case studies. © Springer-Verlag Berlin Heidelberg 2007.

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Fault diagnosis using dynamic time warping

Gam Asn clusters with m+n=2,4,...,16 are studied using first-principles methods based on density functional theory. We demonstrate that with sufficient accuracy in numerical computation, the pseudopotential-plane-wave method is capable of predicting relative stability and composition-dependent properties of the binary clusters at the same quality level as all electron calculations. The calculated binding energy of the Gam Asn clusters decreases with increasing Ga to As ratio in the clusters and as expected, binary clusters are energetically favored compared to pure metal clusters of Ga and As formed with the same numbers of atoms. The highest occupied molecular orbital-lowest unoccupied molecular orbital gap decreases as a function of Ga concentration in the clusters, while the electron affinity and ionization energy show weak dependence on composition. The electron affinity increases slowly with Ga to As ratio, but the ionization energy shows a decreasing trend. However, there are large fluctuations in the predicted composition-dependent physical properties. {\textcopyright} 2007 The American Physical Society.

Physical Review B - Condensed Matter and Materials Physics

Composition dependence of structural and electronic properties of Gam Asn clusters from first principles

Using first-principles calculations with ultrasoft pseudopotential formalism and the generalized gradient approximation for the exchange-correlation functional, we study the stability of MonS m (n = 1-6 and m ranging from n to 3n) clusters and obtain the optimal stoichiometry for each n corresponding to the magic cluster. It is found that in this size range, the lowest-energy structures favor a core of metal atoms, which is covered by sulfur. In particular, we observe that for Mo 6S14 isolated clusters, a 3D structure is significantly lower in energy as compared to platelet structures found recently on Au (111) surface. The composition ratio between S and Mo in the magic clusters is less than 2 for n = 3 and greater than 2 for n < 3. The structural stability of the magic clusters arises from the optimization of the Mo-Mo and Mo-S bonding as well as the symmetry of the cluster. Addition of a terminal sulfur in a magic cluster generally lowers its binding energy. The presence of partially occupied d-orbitals in Mo atoms contributes to Mo-Mo bonding and for higher S concentration it leads to sulfur-sulfur bond formation. The variation in energy due to a change in the sulfur composition suggests that sulfurization of the magic clusters is generally more favorable than desulfurization. {\textcopyright} 2007 American Chemical Society.

Journal of Physical Chemistry A

Ab initio study of structural stability of Mo-S clusters and size specific stoichiometries of magic clusters

We employed a granular support vector Machines(GSVM) for prediction of soluble proteins on over expression in Escherichia coli. Granular computing splits the feature space into a set of subspaces (or information granules) such as classes, subsets, clusters and intervals [14]. By the principle of divide and conquer it decomposes a bigger complex problem into smaller and computationally simpler problems. Each of the granules is then solved independently and all the results are aggregated to form the final solution. For the purpose of granulation association rules was employed. The results indicate that a difficult imbalanced classification problem can be successfully solved by employing GSVM. © Springer-Ver lag Berlin Heidelberg 2007.

Granular support vector machine based method for prediction of solubility of proteins on overexpression in Escherichia coli

Ayurveda is a traditional medicine and natural healing system in India. Nadi-Nidan (pulse-based diagnosis) is a prominent method in Ayurveda, and is known to dictate all the salient features of a human body. In this paper, we provide details of our procedure for obtaining the complete spectrum of the nadi pulses as a time series. The system Nadi Tarangini1 contains a diaphragm element equipped with strain gauge, a transmitter cum amplifier, and a digitizer for quantifying analog signal. The system acquires the data with 16-bit accuracy with practically no external electronic or interfering noise. Prior systems for obtaining the nadi pulses have been few and far between, when compared to systems such as ECG. The waveforms obtained with our system have been compared with these other similar equipment developed earlier, and is shown to contain more details. The pulse waveform is also shown to have the desirable variations with respect to age of patients, and the pressure applied at the sensing element. The system is being evaluated by Ayurvedic practitioners as a computer-aided diagnostic tool. © 2007 IEEE.

Annual International Conference of the IEEE Engineering in Medicine and Biology - Proceedings

Nadi tarangini: A pulse based diagnostic system

We report results of an ab initio study on the stability of hydrogenated empty cages Xn Hn with X=Si, Ge and Sn and n=8, 10, 12, 14, 16, 18, 20, 24 and 28. All these cages have large highest-occupied-lowest-unoccupied molecular orbital (HOMO-LUMO) gaps. The HOMO-LUMO gap for Ge cages is found to be even larger than the values for Si cages, though in bulk Ge has a smaller band gap than Si. Cages with n=16 and 20 are found to be particularly stable in the form of fullerene structures. The bonding in the dodecahedral X20 H20 cage is very close to s p3 type and it leads to the highest stability of this cage with perfect icosahedral symmetry. Endohedral doping of the empty cages such as Sin Hn (n=10-28), with different guest atoms shows that doping can be used to manipulate the HOMO-LUMO gap with the possibility of varying their optical properties as well as to prepare species with large magnetic moments. Depending upon the guest atom, the character of the HOMO and the LUMO states and their origins either from the cage or the guest atom changes. This could lead to their applications in sensors. In contrast to the metal-encapsulated silicon-caged clusters, the embedding energy of the guest atom in the hydrogenated silicon fullerenes is small in most cases due to the weak interactions with the cage and therefore these slaved guest atoms can keep their atomic properties to a large extent. We find that atoms with closed electronic shell configurations such as Ca, Ba,... generally occupy the center of the cage. However, Be and other open electronic shell atoms tend to drift towards the wall of the cage. Doping of halogens such as iodine and alkalis such as Na can be used to produce, respectively hole and electron doping while transition-metal atoms such as V, Cr, Mn and Fe are shown to produce atomiclike magnetic moments in many cases. In most of these cases the HOMO-LUMO gap becomes small because the guest atom orbital(s) are only partially occupied. However, for Ni and Zn the HOMO-LUMO gap is large as the hybridized d orbitals become fully occupied. An interesting finding is that the endohedral doping can lead to a higher-energy undoped cage isomer to become the lowest-energy doped isomer. Implications of this result for endohedral fullerenes of carbon are also discussed. {\textcopyright} 2007 The American Physical Society.

Hydrogenated caged clusters of Si, Ge and Sn and their endohedral doping with atoms: Ab initio calculations

Identification of Nuclear protein localization assumes significance as it can provide in depth insight for genome regulation and function annotation of novel proteins. A multiclass SVM classifier with various input features was employed for nuclear protein compartment identification. The input features include factor solution scores and evolutionary information (position specific scoring matrix (PSSM) score) apart from conventional dipeptide composition and pseudo amino acid composition. All the SVM classifiers with different sets of input features performed better than the previously available prediction classifiers. The jack-knife success rate thus obtained on the benchmark dataset constructed by Shen and Chou [Shen, H.B., Chou, K.C., 2005, Predicting protein subnuclear location with optimized evidence-theoretic K-nearest classifier and pseudo amino acid composition. Biochem. Biophys. Res. Commun. 337, 752-756] is 71.23%, indicating that the novel pseudo amino acid composition approach with PSSM and SVM classifier is very promising and may at least play a complimentary role to the existing methods. © 2007 Elsevier B.V. All rights reserved.