Optical network technologies for future digital cinema

Digital technology has transformed the information flow and support infrastructure for numerous application domains, such as cellular communications. Cinematography, traditionally, a film based medium, has embraced digital technology leading to innovative transformations in its work flow. Digital cinema supports transmission of high resolution content enabled by the latest advancements in optical communications and video compression. In this paper we provide a survey of the optical network technologies for supporting this bandwidth intensive traffic class. We also highlight the significance and benefits of the state of the art in optical technologies that support the digital cinema work flow

Foreign Direct Investment (FDI) and Gross Domestic Product (GDP) in Bangladesh: A Cointegration Analysis

This paper investigates the long-run relationship between GDP and FDI in Bangladesh for a period of 42 years ranges from 1972 to 2013 by using time series econometric technique. The empirical results show that there is a significant positive correlation between GDP and FDI. The results also show that FDI and GDP are cointegrated in the long-run. For the supplement of the results of cointegration analysis, this study also examine the causal relationships by using Granger causality test and find strong evidence for unidirectional causality running between GDP through FDI in the long run. Keywords: FDI, GDP, Unit Root, Cointegration, Granger Causality

GREEN SYNTHESIS OF SILVER NANOPARTICLES USING THE LEAF EXTRACT OF PUTRANJIVA ROXBURGHII WALL. AND THEIR ANTIMICROBIAL ACTIVITY.

 Objective: This study deals with the synthesis of silver nanoparticles (AgNP's) from the extract of the leaves of the plant Putranjiva roxburghii wall.Using biological method, i.e., green synthesis.Methods: The extract from the leaves acts as a reducing and stabilizing agent for the AgNP's. Further characterization was done using varioustechniques like ultraviolet (UV)-visible spectrophotometry, which shows surface plasmon resonance, Fourier transform infra-red spectroscopyanalysis shows formation of various bonds, scanning electron microscope (SEM) and transmission electron microscope (TEM) analysis depictsthe distribution and average size of nanoparticles. The antimicrobial activity was also checked against various bacteria and fungi using minimuminhibitory concentration and well diffusion assay.Result: UV analysis shows strong plasmon resonance between 420 and 480 nm SEM analysis shows the distribution of synthesized nanoparticles,whereas TEM analysis shows the average particle size to be near about 5 nm and well diffusion assay proved that these nanoparticles are effectiveagainst different microorganisms.Conclusion: P. roxburghii wall. shows strong potential for the reduction of silver from Ag+ to Ag0 and nanoparticles so formed are strongly activeagainst various microorganism.Keywords: Putranjiva roxburghii, Fourier transform infra-red, Scanning electron microscope, Transmission electron microscope

Application merging in the ECOIN context mediation system using the context linking approach

Thesis (M. Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2003.Includes bibliographical references (p. 81-82).Integrating data from heterogeneous data sources means dealing with context differences. That is, differences in the assumptions that are made regarding format and interpretation of the data. The Context Interchange (COIN) group has developed a formalism to describe the context assumptions of data sources and data receivers. An ECOIN application ties various sources together by being mapping them to a common ontology, or domain model. ECOIN applications allow the context differences between data sources to be resolved through context mediation. Users may then desire to merge together multiple ECOIN applications so that context differences across a much wider range of sources can be resolved with minimal additional effort. Accordingly, the work of this thesis focuses on the problem of merging ECOIN applications. The approach to merging discussed herein is termed context-linking. Context-linking allows the merging of ECOIN applications with minimal effort having to be spent on merging the ontologies of the two applications. This is achieved by employing a virtual approach to ontology merging that gives the appearance of a merged ontology. This thesis describes the merging process, presents a detailed case study, demonstrates the benefits of merging and presents the design for CLAMP, a tool that facilitates ECOIN application merging.by M. Bilal Kaleem.M.Eng

Effect of Job Environment on Pulmonary Functions of Railway Employees

Background: To seek relationship between job related exposure of Pakistan Railways workers and the development of respiratory diseases. Methods: One hundred (100) exposed railway workers and a reference group of 100 office workers were recruited in the study. Respiratory symptoms, smoking habits, physical examination findings, chest x-ray and spirometry results were recorded on standard proforma. Results: The FEV1/FVC ratio was significantly lower in the Railway workers than in the reference group (p<0.001). Exposed Railway employees had significantly high (p<0.001) incidence of pulmonary diseases as compared to the reference group. Disproportionately higher incidence of chronic obstructive airway disease was observed in the exposed Railway employees who smoked as compared to the non-smokers in the same group (p<0.001). Conclusion: In exposed Railway workers there is an increased risk of respiratory symptoms, decline in lung functions and chronic obstructive pulmonary disease (COPD) as compared to referents. There is disproportionately higher incidence of COPD among the smokers in the Railway workers as compared to the non-smokers in the same group

MLGCN: An Ultra Efficient Graph Convolution Neural Model For 3D Point Cloud Analysis

The analysis of 3D point clouds has diverse applications in robotics, vision and graphics. Processing them presents specific challenges since they are naturally sparse, can vary in spatial resolution and are typically unordered. Graph-based networks to abstract features have emerged as a promising alternative to convolutional neural networks for their analysis, but these can be computationally heavy as well as memory inefficient. To address these limitations we introduce a novel Multi-level Graph Convolution Neural (MLGCN) model, which uses Graph Neural Networks (GNN) blocks to extract features from 3D point clouds at specific locality levels. Our approach employs precomputed graph KNNs, where each KNN graph is shared between GCN blocks inside a GNN block, making it both efficient and effective compared to present models. We demonstrate the efficacy of our approach on point cloud based object classification and part segmentation tasks on benchmark datasets, showing that it produces comparable results to those of state-of-the-art models while requiring up to a thousand times fewer floating-point operations (FLOPs) and having significantly reduced storage requirements. Thus, our MLGCN model could be particular relevant to point cloud based 3D shape analysis in industrial applications when computing resources are scarce