Large amplitude vibrations of circular plates with mixed boundary conditions

In this paper, a method of analysing large amplitude vibrations of circular plates with mixed boundary conditions is explained and is illustrated with an example where part of the boundary is clamped and the remaining simply-supported     

A high-performance computing method for data allocation in distributed database systems

Enhancing the performance of the DDBs (Distributed Database system) can be done by speeding up the computation of the data allocation, leading to higher speed allocation decisions and resulting in smaller data redundancy and shorter processing time. This paper deals with an integrated method for grouping the distributed sites into clusters and customizing the database fragments allocation to the clusters and their sites. We design a high speed clustering and allocating method to determine which fragments would be allocated to which cluster and site so as to maintain data availability and a constant systemic reliability, and evaluate the performance achieved by this method and demonstrate its efficiency by means of tabular and graphical representation. We tested our method over different network sites and found it reduces the data transferred between the sites during the execution time, minimizes the communication cost needed for processing applications, and handles the database queries and meets their future needs.     

A technique for generating natural colour images from false colour composite images

Colour is widely used in remote sensing work. In many instances, the use of colour conveys additional information both visually and scientifically. Remote sensing satellites view the earth in different spectral bands, viz. near infrared (NIR), red, green, and blue bands, in a conventional multispectral imaging system. In the absence of a blue channel, colour images can be generated using near infrared, red, and green bands in what is known as a false colour composite (FCC) and does not look natural, like the image we see with the naked eye. For a trained interpreter, this does not pose any problems. However, when the intended use is a fly‐through of a draped terrain, visual interpretation, or a display, meant for the non‐remote sensing professional, this becomes a handicap. To overcome this, there is a requirement to generate natural colour composites (NCC) from the given false colour composite, which demands the simulation of a blue band to be combined with green and red bands. This paper describes a unique method of generating a blue band to form natural colour images from a given false colour image set. We use a spectral transformation method to establish a relationship between the false colour and true colour image pairs provided by a sensor with all the four bands, which has a broader spectral coverage. A transformation function is fitted by selecting radiometric control points along the line of geometric registration to find a set of coefficients to be used for simulating a blue band. This blue band, along with the green and red bands, provides a near true colour or ‘natural colour’ on the display. In this paper, we present a set of adjustable radiometric transformation coefficients to accommodate variation in spatial and dynamic range offered by sensors to generate natural colour. These coefficients seem to work on a large number of images of different seasons, provided similar spectral bands and terrain are used. The proposed ‘natural colour generator’ can be used in changing false colour images to natural colour images with the aim of ‘what you get is what you would have seen’.     

Satellite- and ground-based measurements of CO2 over the Indian region: its seasonal dependencies,spatial variability,and model estimates

ABSTRACT

The present study demonstrates the distribution of carbon dioxide (CO₂) concentration over the Indian region and the surrounding oceanic regions during 2009–2012, using measurements from satellites viz., Greenhouse Gases Observing Satellite (GOSAT) and Atmospheric Infrared Sounder, Carbon Tracker (CT) model simulations and flask measurements from two Indian stations Sinhagad (SNG) (73°45′ E, 18°21′36″ N) and Cape Rama (CRI) (73°54′ E, 15°6′ N). The concentration of CO₂ is observed to be maximum during pre-monsoon and shows a decreasing phase during the post-monsoon season. In a regional scale, it is found that Indo-Gangetic Plain and northern India have relatively higher concentrations compared to the other regions. The probability distribution of the concentration differences shows that for most of the time, the differences lie between ±3 ppmv between GOSAT and CT. The comparison between the CO₂ flask measurements over SNG and CRI with respect to that of GOSAT and CT clearly reveals that the differences in CO₂ are as high as 10 ppmv between the ground- and satellite-based measurements. Further, we utilized the Lagrangian model FLEXible PARTicle (FLEXPART) to understand the source?receptor relationship over CRI, SNG, and over the equatorial Indian Ocean (IO). The source contributions from the northern and eastern continental regions of the Indian region are found to be more influential over SNG compared to CRI. It is also found from simulations that the equatorial IO has less influence from the continental source and therefore has a reduced seasonal variability compared to the other regions considered in the present study.     

Computational Approaches for Studying the Granular Dynamics of Continuous Blending Processes, 2 – Population Balance and Data‐Based Methods

The application of computationally inexpensive modeling methods for a predictive study of powder mixing is discussed. A multidimensional population balance model is formulated to track the evolution of the distribution of a mixture of particle populations with respect to position and time. Integrating knowledge derived from a discrete element model, this method can be used to predict residence time distribution, mean and relative standard deviation of the API concentration in a continuous mixer. Low‐order statistical models, including response surface methods, kriging, and high‐dimensional model representations are also presented. Their efficiency for design optimization and process design space identification with respect to operating and design variables is illustrated.

     

Effective allocation of customers to distribution centres: A multiple ant colony optimization approach

The global and competitive business environment has identified the importance of a quick and efficient service towards the customers in the past few decades. Distribution centre (DC) plays an important role in maintaining the uninterrupted flow of goods and materials between the manufacturer and customers. The performance of the supply chain network can be easily improved by an effective or balanced allocation of customers to DCs. Improper or unbalanced allocation of customers can lead to the under- or overutilization of facilities and can further deteriorate the customer service. Performance of the DC can be judged on the basis of its ability to provide the right goods, at the right time and at the right place. The lead time or transit time to deliver the goods to the customers is an important parameter for the measuring the efficiency and effectiveness of a particular DC in a supply chain. In this paper, a multiple ant colony optimization (MACO) approach is discussed in an effort to design a balanced and efficient supply chain network that maintains the best balance of transit time and customers service. The focus of this paper is on the effective allocation of the customers to the DCs with the two-fold objective of minimization of the transit time and degree of imbalance of the DCs. MACO technique is a modified form of the traditional ant colony system, where multiple ant colonies cooperate with each other to find the best possible customer allocation pattern for the DC. The proposed technique shows better performance because of its nature of considering both positive and negative feedback in search of optimum or near-optimum results. The developed algorithm based on the proposed approach is tested on a real practical problem and the results are discussed in this paper.     

Rising Crack-Growth-Resistance (R-Curve) Behavior of Toughened Alumina and Silicon Nitride

R -curves for a sinter/HIPed SiC(whisker)-reinforced alumina and a sintered silicon nitride were assessed by direct measurements of lengths of cracks associated with Vickers indentation flaws. The fracture toughness measurements based on (a) initial (as-indented) crack lengths, (b) equilibrium growth of cracks during increasing far-field loading, and (c) crack lengths corresponding to unstable fracture showed definitive trends of R -curves for both materials. The fracture mechanics analyses employed an indenter-material constant that was independently estimated using a physical model for the residual driving force and a free surface correction factor that accounted for the effects of size and shape of the cracks on stress intensity. It is shown that R -curve estimations based on crack length measurements have the intrinsic advantage that crack length dependence of fracture toughness is not assumed a priori as is done in conventional analysis based on strength. The measured fracture toughness of SiC(whisker)-reinforced alumina was in agreement with the prediction of a toughening model based on crack bridging by partially debonded whiskers.     

Identification of tubulin drug binding sites and prediction of relative differences in binding affinities to tubulin isotypes using digital signal processing

Microtubules are involved in numerous cellular processes including chromosome segregation during mitosis and, as a result, their constituent protein, tubulin, has become a successful target of several chemotherapeutic drugs. In general, these drugs bind indiscriminately to tubulin within both cancerous and healthy cells, resulting in unwanted side effects. However, differences between beta-tubulin isotypes expressed in a wide range of cell types may aid in the development of anti-tubulin drugs having increased specificity for only certain types of cells. Here, we describe a digital signal processing (DSP) method that is capable of predicting hot spots for the tubulin family of proteins as well as determining relative differences in binding affinities to these hot spots based only on the primary sequence of 10 human tubulin isotypes. Due to the fact that several drug binding sites have already been characterized within beta-tubulin, we are able to correlate hot spots with the binding sites for known chemotherapy drugs. We have also verified the accuracy of this method using the correlation between the binding affinities of characterized drugs and the tubulin isotypes. Additionally, the DSP method enables the rapid estimation of relative differences in binding affinities within the binding sites of tubulin isotypes that are yet to be experimentally determined.