Towards finding the best-fit distribution for OSN data

The Journal of Supercomputing - Currently, all online social networks (OSNs) are considered to follow a power-law distribution. In this paper, the degree distribution for multiple OSNs has been...     

A simulation study of reduction kinetics for sponge iron production in a rotary hearth furnace

ABSTRACT

A mathematical model has been developed by coupling genetic algorithm (GA) with heat and material balance equations to estimate rate parameters and solid-phase evolution related to the reduction of iron ore-coal composite pellets in a multi-layer bed Rotary hearth Furnace (RHF). The present process involves treating iron ore-coal composite pellets in a crucible over the hearth in RHF. The various solid phases evolved at the end of the process are estimated experimentally, and are used in conjunction with the model to estimate rate parameters. The predicted apparent activation energy for the wustite reduction step is found to be lower than those of the reduction of higher oxides. The thermal efficiency is found to decrease significantly with an increase in the carbon content of the pellet. Thermal efficiency was also found to increase mildly up to three layers. Multilayer bed remains as a potential design parameter to increase thermal efficiency.     

Impact of Climate Change on Future Flood Susceptibility: an Evaluation Based on Deep Learning Algorithms and GCM Model

Floods are common and recurring natural hazards which damages is the destruction for society. Several regions of the world with different climatic conditions face the challenge of floods in different magnitudes. Here we estimate flood susceptibility based on Analytical neural network (ANN), Deep learning neural network (DLNN) and Deep boost (DB) algorithm approach. We also attempt to estimate the future rainfall scenario, using the General circulation model (GCM) with its ensemble. The Representative concentration pathway (RCP) scenario is employed for estimating the future rainfall in more an authentic way. The validation of all models was done with considering different indices and the results show that the DB model is most optimal as compared to the other models. According to the DB model, the spatial coverage of very low, low, moderate, high and very high flood prone region is 68.20%, 9.48%, 5.64%, 7.34% and 9.33% respectively. The approach and results in this research would be beneficial to take the decision in managing this natural hazard in a more efficient way.

     

An application of chemometric techniques to analyze the effects of the wave function modifications on the intermolecular stretching frequencies of the hydrogen-bonded complexes

Factorial design and principal component models are used to determine how ab initio H-bond stretching frequencies depend on characteristics of the molecular orbital wave functions of acetylene–HX, ethylene–HX and cyclopropane–HX π-type hydrogen complexes with X=F, Cl, CN, NC and CCH. The results obtained for the three sets of complexes show that factorial design and principal component analyses complement each other. Factorial design calculations clearly show that these frequencies are affected mostly by inclusion of electron correlation on the calculation level. On average, their values are increased by about 25 cm⁻¹ due to a change from the Hartree–Fock (HF) to Möller–Plesset 2 (MP2) level. Valence, diffuse and polarization main effects as well as valence–diffuse, diffuse–correlation and polarization–correlation interaction effects are also important to better describe a factorial model to the H-bond stretching frequencies of these hydrogen complexes. This simplified model has been successful in reproducing the complete ab initio results, which correspond to two hundred and forty calculations. Principal component analyses applied only to hydrogen-bonded complexes whose experimental frequencies are known, has revealed that the six-dimensional original space can be accurately represented by a bidimensional space defined by two principal components. Its graphical representation reveals that the experimental intermolecular stretching frequencies are in closest agreement with the MP2/6–31+G and MP2/6–311+G ab initio results.     

A control-theoretic approach to distributed discrete-valued decision-making in networks of sensing agents

We address the problem of global sensor fusion for the purpose of distributed decision-making, from a control-theoretic perspective. In particular, we introduce a quasi-linear stochastic distributed protocol, using which a network of sensing agents can reach agreement in order to take a collective action. Using control-theoretic methods, we design the parameters of our protocol - which include weights in the local update rules used by the agents and a finite stopping time - to achieve agreement in a fair and rapid manner. We show analytically that the developed protocol achieves fair agreement with certainty in the noise-free case and achieves fair agreement with high probability even in the presence of communication noise and assuming very little information storage capability for the agents. Our development is illustrated throughout with a canonical example motivated by autonomous vehicle control.     

Perspectives on Design and Innovation

A series of studies of top European and other firms has revealed patterns of design management associated with commercial success. Firms that invest resources and professional expertise in product and industrial design in traditional and new industries have been commercially more successful than firms that pay less attention to these aspects of design. As an industry matures there is a shift in emphasis from design associated with technological innovation, to designs supporting technical improvements, and then to supporting user needs, fashion and product variants. These issues are illustrated through the history of the evolution of the bicycle.     

Structure and stability of an immunoglobulin superfamily domain from twitchin, a muscle protein of the nematode Caenorhabditis elegans

The NMR solution structure of an immunoglobulin superfamily module of twitchin (Ig 18') has been determined and the kinetic and equilibrium folding behaviour characterised. Thirty molecular coordinates were calculated using a hybrid distance geometry-simulated annealing protocol based on 1207 distance and 48 dihedral restraints. The atomic rms distributions about the mean coordinate for the ensemble of structures is 0.55( +/- 0.09) A for backbone atoms and 1.10( +/- 0.08) A for all heavy atoms. The protein has a topology very similar to that of telokin and the titin Ig domains and thus it falls into the I set of the immunoglobulin superfamily. The close agreement between the predicted and observed structures of Ig 18' demonstrates clearly that the I set profile can be applied in the structure prediction of immunoglobulin-like domains of diverse modular proteins. Folding studies reveal that the protein has relatively low thermodynamic stability, deltaG(H2O)U-F = 4.0 kcal mol(-1) at physiological pH. Unfolding studies suggest that the protein has considerable kinetic stability, the half life of the unfolding is greater than 40 minutes in the absence of denaturant.