A NOVEL STILL IMAGE MOSAIC ALGORITHM CONSTRUCTION USING FEATURE BASED METHOD

An image mosaic is a method of assembling multiple overlapping images of same scene into a larger one. The output of image mosaic will be the union of two input images. In this paper we have to use three step automatic image mosaic method. The first step is taking two input images and finding out the corners in both the images, second step is finding its matched corner and third step is its blending and we get final output mosaic. The experimental results show the proposed algorithm produces an improvement in mosaic accuracy, efficiency and robustness

Efficient Domain Partitioning for Stencil-based Parallel Operators

Partial Differential Equations (PDEs) are used ubiquitously in modelling natural phenomena. It is generally not possible to obtain an analytical solution and hence they are commonly discretized using schemes such as the Finite Difference Method (FDM) and the Finite Element Method (FEM), converting the continuous PDE to a discrete system of sparse algebraic equations. The solution of this system can be approximated using iterative methods, which are better suited to many sparse systems than direct methods. In this thesis we use the FDM to discretize linear, second order, Elliptic PDEs and consider parallel implementations of standard iterative solvers. The dominant paradigm in this field is distributed memory parallelism which requires the FDM grid to be partitioned across the available computational cores. The orthodox approach to domain partitioning aims to minimize only the communication volume and achieve perfect load-balance on each core. In this work, we re-examine and challenge this traditional method of domain partitioning and show that for well load-balanced problems, minimizing only the communication volume is insufficient for obtaining optimal domain partitions. To this effect we create a high-level, quasi-cache-aware mathematical model that quantifies cache-misses at the sub-domain level and minimizes them to obtain families of high performing domain decompositions. To our knowledge this is the first work that optimizes domain partitioning by analyzing cache misses, establishing a relationship between cache-misses and domain partitioning. To place our model in its true context, we identify and qualitatively examine multiple other factors such as the Least Recently Used policy, Cache Line Utilization and Vectorization, that influence the choice of optimal sub-domain dimensions. Since the convergence rate of point iterative methods, such as Jacobi, for uniform meshes is not acceptable at a high mesh resolution, we extend the model to Parallel Geometric Multigrid (GMG). GMG is a multilevel, iterative, optimal algorithm for numerically solving Elliptic PDEs. Adaptive Mesh Refinement (AMR) is another multilevel technique that allows local refinement of a global mesh based on parameters such as error estimates or geometric importance. We study a massively parallel, multiphysics, multi-resolution AMR framework called BoxLib, and implement and discuss our model on single level and adaptively refined meshes, respectively. We conclude that “close to 2-D” partitions are optimal for stencil-based codes on structured 3-D domains and that it is necessary to optimize for both minimizing cache-misses and communication. We advise that in light of the evolving hardware-software ecosystem, there is an imperative need to re-examine conventional domain partitioning strategies

IN VITRO ANTIBACTERIAL ACTIVITY OF GREEN TEA EXTRACT AGAINST MULTIDRUG-RESISTANT BACTERIA

Objectives: This study aimed to evaluate the antimicrobial activity of ethanolic extract of green tea (Camellia sinensis) against multidrug-resistant strains of the pathogenic bacteria: Extended-spectrum-β-lactamase (ESBL) producing Enterobacteriaceae, Carbapenem-resistant Enterobacteriaceae (CRE), and Metallo-β-lactamase (MBL) producing Pseudomonas aeruginosa strains. Methods: In this cross-sectional study, the antibacterial activity of ethanolic extract of commercial green tea against the 23 multidrug-resistant test strains was evaluated by the Agar well diffusion method, and the minimum inhibitory concentration of the extract for the test strains was determined by Agar plate dilution method. Results: Ethanolic extract of green tea was found to exhibit a remarkably significant antimicrobial activity against the ATCC (American type culture collection) control strains: E. coli ATCC 25922 and P. aeruginosa ATCC 27853 with slightly higher activity against later as compared to the former. The extract exhibited a significant antibacterial activity against multidrug-resistant bacterial strains. The highest activity was shown against ESBL producing strains, followed by CRE strains and the least activity against MBL producers. Conclusion: This study strongly depicts that the ethanolic extract of green tea exhibits significant antibacterial activity even against multidrug-resistant strains. Hence, such plant extracts could be a potential source of bioactive lead compounds that could be utilized in developing herbal antimicrobials as an alternative strategy for tackling the problem of antimicrobial resistance

ENSURING BILLING ACCURACY FOR OFFLINE CHARGING IN 5G NETWORKS

Ensuring Accounting accuracy is paramount in any mobile network. With the advent of Control and User Plane Separation (CUPS) in Third Generation Partnership Project (3GPP) specifications, beginning in 4G network implementations and extending to 5G network implementations, the erstwhile monolithic gateway has been split into two independent nodes, a control plane network function referred to as the Session Management (SMF) and a user plane network function referred to as the User Plane Function (UPF). This separation renders the UPF unaware of some of the events that have occurred at the SMF, which can result in billing inaccuracies. Proposed herein are techniques that may provide subscriber usage accounting accuracy and may also facilitate optimizing signaling between the SMF and the UPF