1,745 research outputs found
Bollywood cinema: A critical genealogy
Get PDF"Bollywood" has finally made it to the Oxford English Dictionary. The 2005 edition defines it as: "a name for the Indian popular film industry, based in Bombay. Origin 1970s. Blend of Bombay and Hollywood." The incorporation of the word in the OED acknowledges the strength of a film industry which, with the coming of sound in 1931, has produced some 9,000 films. (This must not be confused with the output of Indian cinema generally, which would be four times more). What is less evident from the OED definition is the way in which the word has acquired its current meaning and has displaced its earlier descriptors (Bombay Cinema, Indian Popular Cinema, Hindi Cinema), functioning, perhaps even horrifyingly, as an "empty signifier" (Prasad) that may be variously used for a reading of popular Indian cinema. The triumph of the term (over the others) is nothing less than spectacular and indicates, furthermore, the growing global sweep of this cinema not just as cinema qua cinema but as cinema qua social effects and national cultural coding. Although Indian film producers in particular, and pockets of Indian spectators generally, continue to feel uneasy with it (the vernacular press came around to using "Bollywood" only reluctantly), its ascendancy has been such that Bombay Dreams (the Andrew Lloyd Weber musical) and the homegrown Merchants of Bollywood both become signifiers of a cultural logic which transcends cinema and is a global marker of Indian modernity. As the Melbourne (March 2006) closing ceremony of the Commonwealth Games showed, Bollywood will be the cultural practice through which Indian national culture will be projected when the games are held in Delhi in 2010. International games (the Olympics, World Cup Soccer, Asian Games, Commonwealth Games, and so on) are often expressions of a nation's own emerging modernity. For India that modernity, in the realm of culture, is increasingly being interpellated by Bollywood
Effect of enhanced detailing and mass media on community use of ORS and zinc during a scale-up program in Gujarat and Uttar Pradesh
No full textThese data and do files are associated with the paper "Effect of enhanced detailing and mass media on community use of ORS and zinc during a scale-up program in Gujarat and Uttar Pradesh" by Felix Lam, George Pro, Shreya Agrawal, Vishal Shastri, Leslie Wentworth, Melinda Stanley, Nitin Beri, Abhishek Tupe, Ashutosh Mishra, Hamsa Subramaniam, Kate Schroder, Marta Rose Prescott, and Naresh Trikha, published in the Journal of Global Health. They include outcomes of interest, socio-demographic variables, and other variables necessary to replicate the study
Effect of enhanced detailing and mass media on community use of ORS and zinc during a scale-up program in Gujarat and Uttar Pradesh
No full textThese data and do files are associated with the paper "Effect of enhanced detailing and mass media on community use of ORS and zinc during a scale-up program in Gujarat and Uttar Pradesh" by Felix Lam, George Pro, Shreya Agrawal, Vishal Shastri, Leslie Wentworth, Melinda Stanley, Nitin Beri, Abhishek Tupe, Ashutosh Mishra, Hamsa Subramaniam, Kate Schroder, Marta Rose Prescott, and Naresh Trikha, published in the Journal of Global Health. They include outcomes of interest, socio-demographic variables, and other variables necessary to replicate the study
Computational Chemistry and Bioinformatics Research Core (CCBRC)
Get PDFDepartment/Unit poster (BioMolecular Sciences). Corresponding author: Sushil Mishra ([email protected])https://egrove.olemiss.edu/pharm_annual_posters_2022/1012/thumbnail.jp
Expertise as an aspect of author contributions
Get PDF"Authors contribute a wide variety of intellectual efforts to a research paper, ranging from initial conceptualization to final analysis and reporting, and many journals today publish the allocated responsibilities and credits with the paper. An overarching yet unreported aspect of these responsibilities is relevant expertise, that is, past experience and knowledge about the phenomenon under study and the context/techniques used to study it. Here, we study author contributions from the perspective of relevant and complementary expertise based on past authorships ""conceptual coverage"" of the paper at hand. Using concepts from the the MeSH hierarchy assigned to 10.2 million papers in MEDLINE published during 1980-2009, we find that authors collectively cover the great majority of concepts, typically with one dominant author (most often in last position but frequently 2nd-to-last) and each additional author contributing complementary expertise. For example, 2-author papers fail to cover about 20\% of the concepts (i.e, are new to the authors) while 5-author papers fail to cover about 10\%, on average. The relative expertise contributions on multi-author papers vary systematically by career stage and author-position, and has changed over time. We also provide an online tool that provides a temporal profile of expertise contributions for any author in the Author-ity 2009 dataset: http://abel.lis.illinois.edu/legolas"Open Restriction set for Item 108208 on 2018-11-17T18:33:26Z with date null by [email protected] by Shubhanshu Mishra ([email protected]) on 2018-11-17T18:50:04Z
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SIGMET - Expertise.pptx: 1397309 bytes, checksum: 2deca83ae0f1caea0cd2be8eba1b4490 (MD5)Made available in DSpace on 2018-11-17T18:50:04Z (GMT). No. of bitstreams: 3
submission.pdf: 182385 bytes, checksum: 7c4277bf437bb1f641d461ea2caa4520 (MD5)
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SIGMET - Expertise.pptx: 1397309 bytes, checksum: 2deca83ae0f1caea0cd2be8eba1b4490 (MD5)
Previous issue date: 2018-11-10National Institute on Aging of the NIH P01AG039347Directorate for Education & Human Resources of the NSF 1348742Ope
Student Performance Measure by using Different Classification Methods of Data Mining
No full textMaster of Engineering-Software EngineeringThe assessment in outcome based learning is very vital and significant approach toward measuring the student’s performance. There are many traditional methods existing in this context. The data mining is one of the intelligent computing methods which are having widely accepted features that enable the idea of its usage in assessment. Much work has been done to measure the student performance by using different methodologies and modern technologies. In this work, we have gone through the current data sets of students of the university and different classification methods of data mining are used to measure the accuracy of student performance. Based on the analysis of the result, it has been concluded that accuracy and the other measures of SVM is more than the other classification methods
Quantum Capacitance of Two-Dimensional-Material-Based Supercapacitor Electrodes
Get PDF: Electrochemical energy storage technology has emerged as one of the most viable solutions to tackle the challenge of fossil-fuel-based technology and associated global pollution. Supercapacitors are widely used for high-power applications, and there is tremendous ongoing effort to make them useful for high-energy storage applications. While electrode materials of supercapacitors play a central role in charge storage performance, insights into the contribution from different charge storage mechanisms are crucial from both fundamental and applied aspects. In this context, apart from the electric double layer and fast redox reaction at/near the surface, another pronounced contribution from the electrode is quantum capacitance (CQ). Here, the origin of CQ, how it contributes to the total capacitance, the possible strategies to improve it, and the state-of-art CQ of electrode materials, including carbon, two-dimensional materials, and their composites, are discussed. Although most of the studies on quantifying CQ are theoretical, some case studies on experimental measurements using standard electrochemical techniques are summarized. With an overview and critical analysis of theoretical studies on quantum capacitance of electrode materials, this review critically examines the supercapacitor design strategies, including choosing the right materials and electrolytes. These insights are also relevant to other types of clean energy storage technologies, including metal-ion capacitors and batteries
Age-Group prediction of facial images using different classifiers
No full textME-Software Engineering-ThesisA human face provides a lot of information which allows another person to identify their characteristics such as age, gender, etc. So the challenge is to develop an age-group prediction system by using the machine learning method. The task of estimating the human‟s age-group from their frontal facial images is very captivating, but also the challenging one due to the personalized and non-linear pattern of ageing which differs from one person to another. This work examines the problem of predicting the age-group of human on the basis of presenting a facial image with the improved accuracy of estimation. The aim of this study is to build up a framework and subsequently an algorithm that helps in estimating the age-group with the reasonable accuracy of the facial images.
In this work, a method is presented for the age-group prediction in which age-group is predicted by detecting the face or face landmarks using the Viola-Jones algorithm. After detecting the face, features including geometric features, wrinkles features are extracted and then these extracted features are used to train a classifier using Support Vector Machine (SVM) or K-Nearest Neighbors (K-NN). Finally, SVM or K-NN is used to categorize the age into one of the three different groups such as child, adult and old for the test data. The system used self-build database for the age-group classification. Finally, identification rate achieved using k-NN model produces better results than using SVM model as specified in experimental results.Computer Science and Engineering, Thapar University, Patial
Performance Evaluation of Secure OLSR under Link Spoofing Attack
No full textMobile ad hoc network (MANET) is a dynamic in nature which is constantly prone to
many severe attacks. It has a many unique features unlike conventional network. It is
a node resource constraint and self-constructed network. In this thesis, we
summarized basically security vulnerabilities in the optimized link state routing
protocol (OLSR). OLSR is mostly primarily for dense networks. The paramount
feature of OLSR is multipoint relay nodes. In our work, we suggested a prototype to
defend against link spoofing attack. Our main technique is based on interchanging
control packets by 2-hop neighbors. The major ease of our approach is that it offers
protection against link spoofing attack without having knowledge of complete
scenario. In our scenario we do not need particular hardware like Global Positioning
System (GPS). Secure-OLSR is implemented on network simulator. Our simulation
analysis indicates that proposed algorithm is good enough to detect presence of
malicious node under link spoofing attack as compared to current version of OLSR.
Our approach have higher packet delivery ratio, and throughput
Prediction of Parkinson Disorder Based on Kinect Arm Movement by Using Machine Learning Techniques
No full textMaster of Engineering -CSEParkinson Disorder is a gradually increasing neurodegenerative disease. In this, motor and non-motor symptoms can impact on human basic functions to a wide variety of range. This article describes the required features and predicts the Parkinson Disorder in a patient with higher efficacy. In this work, mean vector velocity (MVV) was performed to analyze the essential features and crossed verified it by the Rank of Correlation. Previously many scientists analyzed Parkinson disorder using the fundamental classification models and also the different techniques to identify the postural tremor in the arm. It was found that they concentrated on the slow movement of the patients. But it has been proven that some abnormalities are also present in the medium movement. In this work the main tasks involve are (I) detecting four arm-features (II) calculating the mean instantaneous velocity of that four features and (III) performance evaluation of the four classification models under Artificial Neural Network. Finally we can able to predict the Parkinson disorder for patients with having good accuracy and sensitivity
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