1,372 research outputs found
Solar Power in the Garden State
No full textThis special issue on energy and solar power in New Jersey was made possible because of the extensive portfolio of research centers and institutes at the Edward J. Bloustein School of Planning and Public Policy. Dr. Frank A. Felder, an Associate Research Professor, has been director of the School’s Center for Energy, Economic & Environmental Policy (CEEEP) since 2006. Frank is a nuclear engineer with a PhD degree from MIT, and he, along with his CEEEP colleague, Shankar N. Chandramowli, coauthored the main article in this issue of the Advance & Rutgers Report. CEEEP has worked extensively with the New Jersey Board of Public Utilities on projects, including New Jersey’s current Energy Master Plan.Shining Brightly: Bloustein's Centers of Excellence / by James W. Hughes and Joseph S. Seneca -- Solar Power in the Garden States / by Shankar N. Chandramowli and Frank A. Felder.Guest contributors include Shankar N. Chandramowli and Frank A. Felder, PhD, Director—Center for Energy, Economic and Environmental Policy at the Edward J. Bloustein School of Planning and Public PolicyReports published as Issue Paper Number 5, May 2011, in Advance & Rutgers Report, Special Issue
Experimental investigation and comparative machine learning prediction of the compressive strength of recycled aggregate concrete incorporated with fly ash, GGBS, and metakaolin
No full textRecycled aggregates (RA) can provide a sustainable solution for replacing natural aggregates (NA) in the concrete mix. However, the stakeholders and inspection professionals lack confidence in predicting their compressive strength (CS) due to limited databases. Most of them solely focus on the concrete mix with natural aggregates only. Even though numerous researchers have proposed alternative mix designs for recycled aggregate concrete (RAC), utilizing RA is still not practicable. One of them is the lack of a simple and effective compressive strength prediction that uses RAC. This study focuses on the application of six different machine learning (ML) techniques: XG Boost, K-nearest neighbors (KNN), artificial neural network (ANN), support vector machine (SVM), linear regression, decision tree (DT), and random forest (RF), for predicting the CS of concrete mixed with RA. The input variables are weights of coarse RA, Portland cement, fly ash, ground granulated blast furnace slag, and metakaolin. The database is prepared by experimental testing of concrete cube specimens for 188 mixes in the concrete technology laboratory of IIT Bhubaneswar. For most of the mixes, coarse RA was the only coarse aggregate to get the compressive strength. It includes variations in water/binder from 0.25 to 0.75. It was observed that the addition of flyash, GGBS, and MK significantly impacted the CS at a later age. The ML model indicates that an accuracy of 0.95 was achieved on the current test database for predicting CS. Among all the machine-learning algorithms, XG Boost can be used for forecasting compressive strength since it provides excellent accuracy with minimal computation. This research can be used as a data-driven novel solution for developing concrete mixes to achieve a specified CS. However, this work employs only experimental data as a machine learning input, which can be improved further by including databases from the literature
Unfolding the contribution of environmental and anthropogenic variables in forest fire over western Himalayan fire regime
No full textIn last few decades, a surge of uncontrolled wild and forest fire has been observed over biomes, mostly from tropical and subtropical regions. The present study has disentangled the contribution of different environmental and anthropogenic factors in forest fire over the western Himalayan (Uttarakhand and Himachal Pradesh) fire regime, which is an active fire hotspot in India. Fire-CCI v5.1 data was used to labelled fire and non-fire pixel. The climatic (e.g. maximum and minimum temperature, precipitation, solar radiation, vapour pressure, wind speed, water vapour deficit, soil moisture and palmer drought index), physiographic (elevation, slope, aspect and roughness), anthropogenic (population density and human modification) and locational (latitude and longitude) variables were utilized to unfold their contribution in forest fire by the aid of Random Forest (RF) a machine learning technique. After parameterization, a 10-fold cross-validation RF model was built over the whole dataset and the average overall accuracy, precision, recall, F-1 score and overall accuracy were estimated as 0.94 (±0.002), 0.86 (±0.003), 0.91 (±0.002) and 0.91 (±0.002), respectively. Furthermore, the whole dataset (2005-2018) was divided into two parts, training set (2005-2017) and testing (2018), to get a robust model. The testing accuracy (overall accuracy = 0.82, precision =0.79, recall = 0.95, F1 score = 0.86 and area under curve (AUC) = 0.95) suggested a reliable performance of RF model in forest fire classification (fire and non-fire). The contributions of the selected variables were retrieved from the feature importance of the RF model. The maximum temperature exhibited the highest importance, followed by elevation, minimum temperature and location variable (latitude and longitude). The population density and human modification (gHM) are moderately contributing to western Himalayan forest fire. Keywords: Forest fire; Western Himalaya; Random Forest </p
Interview with Scott Barretta, freelance researcher and author
No full textThis interview was conducted as a teaching interview to instruct field school participants in interviewing technique; Interviewer: Michael Taft, Recordist: Guha Shankar. Recorded at Barnard Observatory (University of Mississippi)
Contribution of Shankar Nighantu w.r.t. Vishahara Dravyas: A Review
No full textToxicity, which may be intentional, unintentional or accidental, is a grave problem throughout the world from ages. Advancements in the literature of Ayurveda address this problem by including the various treatments of toxicities, where Shankar Nighantu is one of them. Shankar Nighantu is a modern lexicon in Ayurvedic Materia Medica, originating in the 20th century and written by Shankar datta Gauda in the Hindi language. This lexicon based on Ayurvedic and Unani references, constructed in Hindi alphabetical order, is in three parts and contains vast information about the botanical characteristics, medicinal properties, and therapeutic indications of numerous plants, animals, and their products, as well as metals and minerals, aiding in the effective practice of this ancient healing tradition in contemporary times. Various Vishahara dravyas (Antivenom or Anti-toxic properties or Anti-poisonous drugs) are also listed highlighting the significance of toxicity treatment. Vishahara dravyas are elements that can prevent and eliminate toxins or poisons from the body. These elements play a crucial role in Ayurveda, which emphasises the importance of detoxification for maintaining health and treating diseases. Unani dravyas that are referred from ‘Makhjan’, are also mentioned as a unique entity as Vishahara property in this Nighantu. This Nighantu also includes various drugs used as folklore medicine. The author indicates various single drug as well as compound formulations to be used as antitoxic. Chuk, Hatthajodi, Chumbak patthar (Magnetic stone) are a few controversial and unexplored drugs that need further research for its antitoxic properties. This literary review aims to focus on the data found in Shankar Nighantu regarding various antitoxic drugs that is Vishahara dravyas. It will assist researchers and medical practitioners in gaining better insight about principle of treatment of toxicity
India’s Macroeconomic Performance and Policies since 2000
No full textThe paper reviews Indias macroeconomic performance and policies since 2000. The first section briefly summarizes key macroeconomic developments regarding economic growth, inflation, external balance, the fiscal situation and aggregate savings and investment. The second section considers some of the challenges posed to macroeconomic management in this period and the efficacy of the policy responses adopted. In particular, it analyses the progress in fiscal consolidation and the policies adopted to deal with the challenge of the unprecedented surge in external capital inflows into India. The final section outlines some of the major macro policy issues that need to be addressed in the years ahead, including : the resurgence of high fiscal deficits; the issues relating to external convertibility and exchange rate management; the role of the Reserve Bank of India in macroeconomic policy and coping with a weak international economic environment.economic growth, inflation, Fiscal Policy, savings and investment, Capital Inflows, exchange rate policy, central bank role
Investigation of electronic and magnetic properties of Ni0.5Cu0.5Fe2O4: theoretical and experimental
No full textGovernmentality for positive project management
No full textGreen Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.Integral Design & Managemen
EducaSUN: Replenishing Our Spirits and Advancing Justice
No full textTaking care of ourselves is an essential part of taking care of others. The wellness of educators and youth service providers plays a significant role in advancing equity and academic excellence for children and adolescents. Mitigating the prevalence and intensity of compassion fatigue and traumatic stress is imperative to creating safe, healthy, inclusive and empowering educational environments. Internationally renowned social justice scholar-educator, author and artivist, Dr. Rajni Shankar-Brown illustrates that we must actively embrace, practice and prioritize radical self-care as we work to dismantle persistent social inequalities and the growing opportunity gap. Promoting collective wellbeing is essential to addressing equity issues impacting our youth. Through a deeper understanding of the intersectional complexities of poverty in juxtaposition with multiple dimensions of wellness, Dr. Shankar-Brown invites us to collectively create what she calls EducaSUN. Grounded in social justice research and healing-centered engagement, this presentation invites participants to engage in critical reflection, exploration, and discovery to increase positive impact in our increasingly diverse schools and communities. By intentionally practicing radical self-care, we can replenish our spirits and further our efforts in advancing educational justice
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Susham Bedi: A Literary Life
No full textThe Hindi Urdu Flagship’s Jishnu Shankar sits down with well-known Hindi writer and actress Susham Bedi to discuss her journey into a life of Hindi letters. Bedi describes her childhood and adolescence in India, her acting career, and some sources of inspiration for her most famous stories. The interview is wonderful listening comprehension practice for intermediate Hindi students and a fascinating insight in to the life of a Hindi writer. Bedi is the author of a number of well-known Hindi novels and short-stories. Two of these novels, Havan andVapasi, were also translated into Urdu and published in Pakistan. Bedi has also been involved in Hindi language pedagogy for more than a decade. She teaches at Columbia University and has developed a number of widely used Hindi comprehension materials. In addition to her work with Hindi language and literature, Bedi has had a highly successful career as a stage and screen actress. She featured in many well-known Hindi theater productions during the 1960s and 70s; more recently, she has appeared in a number of American television shows (True Crime, Third Watch, Law & Order: SVU) and movies (The Guru, ABCD).Asian Studie
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