The largest growth in water usage among water-using industries has been in agriculture due to the growing need for agricultural goods to feed the world's expanding population. Presently, agricultural water conservation encompasses a range of technologies that are mostly grounded in human understanding, but also include a number of complex strategies that significantly rely on cutting-edge mechanical and electrical techniques. Modern agronomic practices like precision agriculture may conserve water. Precision agriculture is a modern agronomic strategy that may preserve water.Modern agricultural investments, land transfers, and urbanisation have left these irregular and traditionally built villages with an ambiguous and ever-changing land use pattern. This may hinder water-saving adoption. In addition to taking into account the growth of the agricultural sector, the agricultural water management policy prioritises the long-term ecological economy and the sustainability of the water resource supply network. Water needs are predicted to rise significantly by the end of the twenty-first century, particularly for irrigation. Reducing the amount of water used in agriculture is crucial. With temperatures rising and droughts occurring more frequently in many nations, water is a vital component of agricultural output. Certain technology-based practices coupled with efficient farmers and humans management of water resources will be the key features for improving water conservation.
Abstract. Due to a change in the landscape, the climate of Uttarakhand state is changing rapidly, impacting the weather, further affecting human beings and vegetation. Nowadays, remote sensing is a favorable tool for monitoring the vegetation condition using NDVI and EVI. Studying the relationship between vegetation and climate more extensively, it is necessary to better understand the anomaly of ecosystems with climate change. This study is carried out to evaluate the vegetation cover dynamics by establishing the association between climate parameters and vegetation indices over the rain-fed districts (Nainital, Bageshwar, Champawat, Dehradun) of Uttarakhand for the period of 20 years. In this study, Google Earth Engine (GEE) is used to extract the MODIS NDVI and EVI at 250 m spatial resolution & 16-day temporal resolution data. The climate parameters for the rain-fed district (study area) are extracted from Indian Meteorological Department (IMD) Pun website for the period from 2000 to 2020. According to the annual vegetation dynamics, the peak attained by both indices is during the monsoon season, and hence they both show identical patterns to each other. Linear Regression Analysis results show a strong impact of climate on vegetation. Both indices shows a positive correlation with climate parameters where minimum temperature and rainfall are strongly correlated with EVI. Thus, the study reveals that EVI is proven to be more appropriate indices for monitoring vegetation cover as compared to NDVI for the study area.
While fertiliser subsidy has probably been one of the most hotly debated issues in the
country over the past two decades, the debate reached a new height following a
recommendation by the Prime Minister's Economic Advisory Council (PMEAC) in its
latest Economic Outlook 2012113 that are progressively losing their relevance
and are becoming unbearable fiscal burden so a beginning can be made in dismantling
fertiliser subsidy. In view of this, the present paper analyses the fertiliser subsidy
from two different aspects, both important for policy planners in the country. First, who
is benefiting from the current system of fertiliser subsidies and secondly what is the
impact of recent policy changes on fertiliser consumption and prices and proposed removal
of fertiliser subsidies on farm income. Fertiliser subsidies account for a significant share
of the total support to agriculture and have increased by about 560 per cent between
triennium ending (TE) 2003-04 and TE 2010-11 mainly due to steep increase in
international prices of fertilisers and feedstocks/raw materials, increased consumption
and unchanged farm gate prices. The findings suggest that all farmers benefit from
subsidies, however, small and marginal farmers receive about 53 per cent of the subsidy,
higher than their share in total cropped area (44.3%), The partial decontrol of fertiliser
sector which has led to unprecedented increase in prices of phosphatic (P) and potassic
(K) fertilisers (about 160% in DAP and 280% in MOP) and relatively cheaper nitrogenous
(N) fertilisers, led to sharp fall in consumption of P and K fertilisers, thereby imbalance
in use of N, P and K nutrients. Moreover, dependence on expensive imports has
significantly increased during the last 6-7 years. The results show that removal of fertiliser
subsidy will make farming unprofitable in many states and therefore removal of fertiliser
subsidies will not be in the interest of farming community, particularly, small and marginal
farmers and less developed states/regions. The paper argues for containing subsidy but
without hurting interest of millions of small and marginal farmers including tenant
cultivators. As radical reforms like dismantling of subsidy and deregulation of fertiliser
industry in one go are neither economically desirable nor politically feasible, a case can
be made for continuation of fertiliser subsidy with better targeting and rationing to
achieve socio-economic objectives of national food security, poverty alleviation and
farmers' welfare as well as subsidy reduction.
We present FailAmp, a novel LLVM program transformation algorithm that makes programs employing structured index calculations more robust against soft errors. Without FailAmp, an offset error can go undetected; with FailAmp, all subsequent offsets are relativized, building on the faulty one. FailAmp can exploit ISAs such as ARM to further reduce overheads. We verify correctness properties of FailAMP using an SMT solver, and present a thorough evaluation using many high-performance computing benchmarks under a fault injection campaign. FailAmp provides full soft-error detection for address calculation while incurring an average overhead of around 5%.
This paper proposes a system which will detect emotion and mental state of a person by detecting the pose of a person. Detection of emotion will be based on body parts not on facial expressions. Work done on emotion detection is basically done on facial expression, according to the psychological study it is found that every body part shows an expression. We already have frameworks for facial expression detection but for body gestures we dont have any framework. Here we study the normal body pose first and then we can estimate the difference between a person who is calm and the person who is showing deviation. Along with the shoulder movement, we studied the hand gestures so that we can get much more promising and sound results. By combining both the results for hand and shoulder together we will get the approximate picture of the persons state of mind. Our approach is based on bodily gestures, and we are trying to detect emotions from them. Thus, to detect bodily expressions we have written an algorithm which will help us to predict the behavior of a person. The experimental result shows that by using EDBL algorithm we can infer emotions and state of mind from human pose, in terms of body gesture including shoulder and hand. EDBL algorithm helps in detecting emotions even if we exclude the facial expressions.
'%3e%3ccircle r='20' fill='%23008'/%3e%3ccircle r='17.5' fill='%23fff'/%3e%3ccircle r='3.5' fill='%23008'/%3e%3cg id='d'%3e%3cg id='c'%3e%3cg id='b'%3e%3cg id='a' fill='%23008'%3e%3ccircle r='.875' transform='rotate(7.5 -8.75 133.5)'/%3e%3cpath d='M0 17.5.6 7 0 2l-.6 5L0 17.5z'/%3e%3c/g%3e%3cuse xlink:href='%23a' transform='rotate(15)'/%3e%3c/g%3e%3cuse xlink:href='%23b' transform='rotate(30)'/%3e%3c/g%3e%3cuse xlink:href='%23c' transform='rotate(60)'/%3e%3c/g%3e%3cuse xlink:href='%23d' transform='rotate(120)'/%3e%3cuse xlink:href='%23d' transform='rotate(-120)'/%3e%3c/g%3e%3c/svg%3e)