12,916 research outputs found
My Name Is Deepak
No full textThis chapter looks at the author's responses to being given a nickname by his co-workers: Tupac. They do it in a friendly manner, but the author doesn’t understand the connection with the American rapper. It makes him think about who he is, his identity, and how people see him in his adopted country.</p
Green approaches to biocomposite materials science and engineering/ Deepak Verma, Siddharth Jain, Xiaolei Zhang, and Prakash Chandra Gope, editors.
No full textIncludes bibliographical references and index."This book explores timely research on the various available types of natural fibers and the use of these fibers as a sustainable alternative to synthetic fibers and polymers by emphasizing research-based solutions for sustainability across various industries"--Provided by publisher.Natural fibers for the production of green composites / Xiaolei Zhang [and 3 others] -- Processing technologies for green composites production / Deepak Verma, Garvit Joshi, Rajneesh Dabral -- Concurrent design of green composites / Muhd Ridzuan Mansor [and 5 others] -- Effect of bamboo hybridization and staking sequence on mechanical behavior of bamboo-glass hybrid composite / Piyush P. Gohil [and 3 others] -- Estimation of mechanical and tribological properties of epoxy-based green composites / Supriyo Roy [and 3 others] -- Fabrication and processing of pineapple leaf fiber reinforced composites / S. H. Sheikh Md. Fadzullah, Zaleha Mustafa -- Green composites and their properties: a brief introduction / Deepak Verma [and 4 others] -- Rice husk reinforcement in polymer composites / Sanjay Sharma, Deepak Verma -- Techno-economic and life cycle assessment for the production of green composites / Siddharth Jain, Xiaolei Zhang -- Banana fiber reinforcement and application in composites: a review / Abhinav Shandilya, Ayush Gupta, Deepak Verma -- Bamboo fiber-reinforced composites / Irem Sanal -- Coir fiber-reinforced composites / Irem Sanal.1 online resource (322 pages)
Recommended from our members
Relational Care - with Mary Larkin and Manik Deepak-Gopinath [Podcast]
No full textWhat is 'relational care' and how can it improve the day-to-day experience of carers and those they care for? What are its implications for relationships between staff and service users in care settings? And how does the concept of relational care enable us to re-imagine the role of place and space in the experience of care? These are some of the questions we explore in this episode with Mary Larkin and Manik Deepak-Gopinath who recently completed a research project on the value and practice of relational care with older people.
Mary is Professor of Care, Carers and Caring at The Open University in the UK, where her research has focused on carers and caring and adult social care. She is the co-author, most recently of Family Carers and Caring, published in 2023 by Emerald. Manik is a Lecturer in Ageing, also at The Open University, and is a critical gerontologist with interests in the intersection of ageing, place and wellbeing, and in the intimate and family ties of older adults
Sideffective - system to mine patient reviews: sentiment analysis
No full textSideffective is the system to crawl, rank and analyze patient testimonials about side ffeects from common medications. Since the wealth of any mining model is the Data corpus, the data collection phase involved extensive crawling of massive medical websites comprised of user forums from the internet. Subsequently, the raw files were subjected to certain site-specific parsing routines, yielding outputs conforming to a well-defined data model. Currently, the system holds close to 400,000 user testimonials pertaining to more than 2500 drugs/medicines. Sideffective aims at gathering and aggregating this wealth of information, build useful associations and present interesting observations and numeric validations, all in a user-friendly interface. The important issues that we have tried to tackle are: Extracting side effects without relying on pre-built lists, aggregating distribution of different side effect for a give drug, site-specific search, ranking and determining the negativity of reviews. The system has been jointly built by Deepak Yalamanchi and Sangeetha Rajagopalan under the guidance of Prof. Tomasz Imielinski. This thesis focuses mainly on Sentiment Analysis of patient reviews. While most existing sentiment analysis systems are predicated by POS (parts of speech) tagging or Bayesian sentiment analysis methods, the same cannot be applied to medical reviews as they generally carry a negative flavor in them. We thereby approached the problem by identifying the features in the sentence and calibrating the sentiment on a Negativity Meter based on their relation to sentiment words. A feature, as defined for the purpose of this thesis, can be a medicine, a side effect or a symptom. The sentiment of each feature is determined by the aggregate of all its polarities with respect to each sentiment word, where the polarity is determined by an inverse relation to the distance of the feature from the sentiment word. Each sentence is then evaluated by the cumulative polarity of all the features contained in it. Sentiment of a review is determined by individually determining the sentiment of each sentence and then getting a weighted sum score of all the sentences in the review. The accuracy of a sentiment analysis system is, in principle, how well it agrees with human judgments. Experimental results, involving human reviewers (extracted from site: www.askapatient.com) and correlating them back to the negativity rating of each review yield conclusive results, demonstrating the effectiveness of the technique. We have also implemented a customized Lucene search on the data using a multi-review summarization approach and a ranking scheme based on the feature-list. Ranking priority is given to the review that has the largest feature list size.M.S.Includes bibliographical referencesby Deepak Yalamanch
A model of cooperative R&D among competitors
Full text link"Revision: January 1990."Includes bibliographical references (p. 29-32).Deepak K. Sinha and Michael A. Cusumano
Congestion control for streaming video and audio applications
No full textThesis (S.M.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2001.Includes bibliographical references (p. 52-54).by Deepak Bansal.S.M
Nanostructured mixed transition metal oxides for high performance asymmetric supercapacitors: Facile synthetic strategy
Full text linkAbstract not availableSanaz Tajik, Deepak P. Dubal, Pedro Gomez-Romero, Amir Yadegari, Alimorad Rashidi, Bahram Nasernejad, Inamuddin, Abdullah M. Asir
Problemas do discurso de Deepak Chopra: uma análise metalinguística de “A cura quântica”
Full text linkIn this article, our objective is to make some contributions to the debate around the “quantum mysticism” phenomenon, exploring discursive aspects that permeate an utterance with this kind of theme. To this end, we bring forth an analysis of the book Quantum healing by Deepak Chopra, based on the philosophy of the Bakhtin Circle. We investigate not only the author's argumentative strategies, but we also connect the constituent elements of this utterance (theme, structure and style) with its context of publication, production and reception. We end our arguments recognizing the incoherence that Chopra demonstrates with his intertwining of mystical and alternative conceptions with a scientific worldview, while uttering inconsistent metaphors and serious contradictions, but we also highlight that the author was able to influence the way in which concepts related to Quantum Physics circulate outside the academia.Neste artigo, nosso objetivo é contribuir para o debate sobre o misticismo quântico, explorando aspectos discursivos que permeiam um enunciado com tal tema. Para tanto, realizamos uma análise metalinguística do livro A cura quântica de Deepak Chopra, com base na filosofia da linguagem do Círculo de Bakhtin. Investigamos não apenas as estratégias argumentativas do autor, mas também conectamos os elementos constitutivos desse enunciado (tema, estrutura e estilo) com seu contexto de produção e publicação. A partir da análise reconhecemos a incoerência de Chopra ao sintetizar visões de mundo místicas e alternativas e uma visão de mundo científica repleta de metáforas inconsistentes e graves contradições, mas destacando como o autor conseguiu influenciar o modo como conceitos relacionados à Física Quântica são mobilizados fora do contexto acadêmico
Multi-View Clustering
No full textWith a plethora of data capturing modalities becoming available, the same data object often leaves different kinds of digital footprints. This naturally leads to datasets comprising the same set of data objects represented in different forms, called multi-view data. Among the most fundamental tasks in unsupervised learning is that of clustering, the task of grouping data objects into groups of related objects. Multi-view clustering (MVC) is a flourishing field in unsupervised learning; the MVC task considers leveraging multiple views of data objects in order to arrive at a more effective and accurate grouping than what can be achieved by just using one view of data. Multi-view clustering methods differ in the kind of modelling they use in order to fuse multiple views, by managing the synergies, complimentarities, and conflicts across data views, and arriving at a single clustering output across the multiple views in the dataset. This chapter provides a survey of a sample of multi-view clustering methods, with an emphasis on bringing out the wide diversity in solution formulations that have been considered. We pay specific attention to enable the reader understand the intuition behind each method ahead of describing the technical details of the method, to ensure that the survey is accessible to readers who may not be machine learning specialists. We also outline some popular datasets that have been used to empirically evaluate MVC methods
- …
