Jadavpur University

About: Jadavpur University is a education organization based out in Kolkata, India. It is known for research contribution in the topics: Population & Fuzzy logic. The organization has 10856 authors who have published 27678 publications receiving 422069 citations. The organization is also known as: JU & Jadabpur University.

A refined garnet - biotite Fe−Mg exchange geothermometer and its application in amphibolites and granulites

Abstract: A new formulation of garnet-biotite Fe−Mg exchange thermometer has been developed through statistical regression of the reversed experimental data of Ferry and Spear. Input parameters include available thermo-chemical data for quaternary Fe−Mg−Ca−Mn garnet solid solution and for excess free energy terms, associated with mixing of Al and Ti, in octahedral sites, in biotite solid solution. The regression indicates that Fe−Mg mixing in biotite approximates a symmetrical regular solution model showing positive deviation from ideality withW FeMg bi =1073±490 cal/mol. ΔH r and ΔS r for the garnet-biotite exchange equilibrium were derived to be 4301 cal and 1.85 cal respectively. The resultant thermometer gives consistent results for rocks with a much wider compositional range than can be accommodated by earlier formulations.

Static Local Field Factor for Dielectric Screening Function of Electron Gas at Metallic and Lower Densities

Abstract: A simple parametric form for the static local field factor G(q) which appears in the dielectric screening theory of an electron gas is proposed. A very accurate fit of Ceperley–Alder data of electron correlation energy in the entire density range using Levin–Weniger interpolant is obtained and used for the calculation of G(q). Both the short- and long- wavelength limits of G(q) are satis ed exactly in the present formulation which ensures fulfilment of a number of other legitimate criteria and produces some interesting results. A comparative study of the various static local eld factors derived so far vis-a-vis the present work is made. Even within the approximations of a static self-consistent theory, reasonable prediction regarding Wigner Crystallization is obtained in the present work.

An Evolutionary Multiobjective Sleep-Scheduling Scheme for Differentiated Coverage in Wireless Sensor Networks

Abstract: We propose an online, multiobjective optimization (MO) algorithm to efficiently schedule the nodes of a wireless sensor network (WSN) and to achieve maximum lifetime. Instead of dealing with traditional grid or uniform coverage, we focus on the differentiated or probabilistic coverage where different regions require different levels of sensing. The MO algorithm helps to attain a better tradeoff among energy consumption, lifetime, and coverage. The algorithm can be run every time a node failure occurs due to power failure of the node battery so that it may reschedule the network. This scheduling is modeled as a combinatorial, multiobjective, and constrained optimization problem with energy and noncoverage as the two objectives. The basic evolutionary multiobjective optimizer used is known as decomposition-based multiobjective evolutionary algorithm (MOEA/D) which is modified by integrating the concept of fuzzy Pareto dominance. The performance of the resulting algorithm, which is called MOEA/DFD, is compared with the performance of the original MOEA/D, which is another very well known MO algorithm called nondominated sorting genetic algorithm (NSGA-II), and an IBM optimization software package called CPLEX. In all the tests, MOEA/DFD is observed to outperform all other algorithms.