50 research outputs found
Not Available
No full textVersion: 1.0.0
Imports: utils, minimalRSD, stats
Published:2017-03-21
Author: Shwetank Lall [aut, cre], Arpan Bhowmik [ctb], Eldho Varghese [aut], Seema Jaggi [ctb], Cini Varghese [ctb]
Maintainer: Shwetank Lall
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
NeedsCompilation: no
Citation: FMC citation info
In views: ExperimentalDesignAn R package to generate cost effective minimally changed run sequences for symmetrical as well as asymmetrical factorial designsNot Availabl
Monitoring the Impacts of Artificial Recharge Structures on Water Table at Ambedkar Nagar, Uttar Pradesh, India
No full textTo study the groundwater recharge through rainfall and artificial recharge structures in selected dry well in different locations of UP was experimented. The data was recorded (1998-2017) to execute the artificial recharge structure at the appropriate locations with best geological condition to enhance the recharge rate at least cost for control of declining groundwater level. Study reveals that the stochastic auto regressive lime series model is an effective tool for management of ground water resource at pre and post monsoon. The variation of pre and post monsoon ground water level is maximum as the physical soil characteristics including hydraulic conductivity may enhance the recharge rate at least cost
Development of Autoregressive Time Series Model for Prediction of Rainfall and Runoff for Manshara Watershed of Lower Gomati Catchment
No full textA study was conducted to develop a stochastic time series model for prediction of annual rainfall and runoff in Manshara watershed of lower Gomati catchment. This is one of the sub-watersheds of lower Gomati catchment and has anareaofll.18 km2• The developed model is based on 13 years data from 1991 to 2003. Autoregressive (AR) model of order 0, 1 and 2 proposed by Kottegoda and Horder (1980) were tried. The goodness off it and adequacy of models were tested by Box-Pierce Portmonteau test, Akaike Information Criterion (AlC) and various statistical characteristics viz., Mean Forecast Error (MFE), Mean Absolute Error (MAE), Mean Relative Error (MRE), Mean Square Error (MSE), Root Mean Square Error (RMSE) and Integral Square Error (lSE). Based on the results, it was concluded that AR (1) model can be effectively used for prediction of rainfall and runoff in Manshara watershed
From Iteration to System Failure: Characterizing the FITness of Periodic Weakly-Hard Systems
No full textEstimating metrics such as the Mean Time To Failure (MTTF) or its inverse, the Failures-In-Time (FIT), is a central problem in reliability estimation of safety-critical systems. To this end, prior work in the real-time and embedded systems community has focused on bounding the probability of failures in a single iteration of the control loop, resulting in, for example, the worst-case probability of a message transmission error due to electromagnetic interference, or an upper bound on the probability of a skipped or an incorrect actuation. However, periodic systems, which can be found at the core of most safety-critical real-time systems, are routinely designed to be robust to a single fault or to occasional failures (case in point, control applications are usually robust to a few skipped or misbehaving control loop iterations). Thus, obtaining long-run reliability metrics like MTTF and FIT from single iteration estimates by calculating the time to first fault can be quite pessimistic. Instead, overall system failures for such systems are better characterized using multi-state models such as weakly-hard constraints. In this paper, we describe and empirically evaluate three orthogonal approaches, PMC, Mart, and SAp, for the sound estimation of system’s MTTF, starting from a periodic stochastic model characterizing the failure in a single iteration of a periodic system, and using weakly-hard constraints as a measure of system robustness. PMC and Mart are exact analyses based on Markov chain analysis and martingale theory, respectively, whereas SAp is a sound approximation based on numerical analysis. We evaluate these techniques empirically in terms of their accuracy and numerical precision, their expressiveness for different definitions of weakly-hard constraints, and their space and time complexities, which affect their scalability and applicability in different regions of the space of weakly-hard constraints
The Untold Story of USA Presidential Elections in 2016 - Insights from Twitter Analytics
No full textPart 4: Social Media and Web 3.0 for SmartnessInternational audienceElections are the most critical events for any nation and paves the path for future growth and prosperity of the economy. Due to its high impact, a lot of discussions take place among all stakeholders in social media. In this study, we attempt to examine the discussions surrounding USA Election, 2016 in Twitter. Further we highlight some of the domains influencing the voter behaviour by applying the outcome of Twitter analytics to Newman and Sheth’s model of Voter Choice. Through the analysis of 784,153 tweets from 287,838 users over 18 weeks, we present interesting findings on what may have affected the polarization of USA elections
Development of mathematical model for estimation of wetting front advance under drip irrigation in sandy loam soil
No full textThe immediate impact of the COVID-19 pandemic on motor neuron disease services and mortality in Scotland
No full textThe article The immediate impact of the COVID‑19 pandemic on motor neuron disease services and mortality in Scotland, written by Stella A. Glasmacher, Juan Larraz, Arpan R. Mehta, Patrick K. A. Kearns, Michael Wong, Judith Newton, Richard Davenport, George Gorrie, Ian Morrison, Javier Carod Artal, Siddharthan Chandran, Suvankar Pal and CARE-MND Consortium, was originally published online on 5 September 2020 with Open Access under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made.</p
Increasing low frequency sound attenuation using compounded single layer of sonic crystal
No full textApplicability of HEC-RAS & GFMS tool for 1D water surface elevation/flood modeling of the river: a Case Study of River Yamuna at Allahabad (Sangam), India
No full textAssessing the Impact of Groundwater Recharge on Underground Reservoir Replenishment in Eastern Uttar Pradesh, India
No full textGroundwater is considered a fresh resource of water and its uses have tremendously increased in the recent past due to an increase in population, rapid urbanization, and industrialization. In India, the groundwater level is declining in some parts of the country due to over-exploitation, low or negligible recharge of aquifer systems, and unsustainable development of groundwater resources. The groundwater modeling is an important tool for studying the past and present groundwater behavior and in the development of future strategies for sustainable groundwater management plans. To study the Impact of groundwater recharge on the replenishment of underground reservoir, Ballia district of Uttar Pradesh has been selected which is one of the districts of the most populous state of India, Uttar Pradesh. An attempt has been made to develop a groundwater model using Modflow software to simulate the groundwater trends and predict future groundwater heads. The calibration and validation of the model were done for 5 years and 3 years respectively. The correlation coefficient for calibration and validation was found 0.85 and root mean square errors vary from 2.89 to 3.2m variation in future trends of groundwater heads. The results of the study show that the developed model can be effectively used to predict the future groundwater heads. The groundwater flow was observed from the northwest to southeast direction. It was predicted from the study that groundwater draft will increase by 10% with a decrease in groundwater level by approximately 0.24 m in the north-west direction by the year 2025. However, no impact was observed in the south side of the district and it was predicted that the groundwater level would remain the same in this zone during the next 3 years
