Resilience of Indian agriculture to external shocks: Analyzing through a structural econometric model

Is Indian agriculture resilient to external shocks? This question has assumed considerable importance ever since macroeconomic reforms were implemented from the early nineties. As a result, the agricultural sector was exposed to sudden disturbances caused not just by the demand and supply conditions within the country, but also by volatility in world market price, exchange rate and surge in imports. This paper aims to evaluate the magnitude of sensitivity of agriculture to these factors and other changes, and explores policy options that may neutralize their adverse effects, maintain price incentives and stability. The analysis is based on three important tradable commodities. A structural econometric model is applied to each, separately under the exportable and importable scenarios from 1980-81 to 2002-03. Broad findings reveal agriculture to be increasingly driven by an incentive structure based on its linkages with world market price, exchange rate and other factors. Counterfactual simulation experiments indicate that due to trade and price policies, commodity prices and output tend to be much more resilient to various shocks compared to the exports and imports. --

Secure Algorithm Using Encoding, Mathematical Key Generation and Redundancy in Cloud Computing

This research paper explores the design and implementation of a customized encryption algorithm tailored to meet the unique security challenges of cloud computing environments. We discuss the algorithm's structure, customization options, and its potential benefits in enhancing data security within cloud-based applications. We introduce a tailored encryption algorithm that incorporates encoding, mathematical key generation and redundancy bits techniques to optimize data security, integrity, and efficiency within the cloud. A secure enhanced algorithm is developed. Customized encoding methods are employed to enhance data representation and facilitate efficient encryption and decryption. This includes the conversion of data into binary format for subsequent encryption. Redundancy bits are introduced into the encryption process to provide error detection and correction capabilities. The integration of these bits ensures data integrity, particularly during data transmission and storage. Random key is generated using Mathematical function. Experimental results demonstrate the algorithm's performance in terms of encryption and decryption times, file size comparisons, and data integrity measurements. Proposed Algorithm shows encryption time does not increases if the size of file bit increases. It increases only when size increases too much. It shows that encryption time is zero when size is small. With the increase of size decryption time also increases. When proposed algorithm is compared with traditional algorithm it takes less time. than RSA. However, encryption time and decryption time also depends on performance of system. Results may be differed. A novel algorithm is developed to improve the security of cloud computing. It has adopted three levels: the first level uses the Encoding Techniques. In second level: Redundancy bits are introduced Random key is generated using Mathematical function logical-mathematical functio

Approximate inference of marginals using the IBIA framework

Exact inference of marginals in probabilistic graphical models (PGM) is known to be intractable, necessitating the use of approximate methods. Most of the existing variational techniques perform iterative message passing in loopy graphs which is slow to converge for many benchmarks. In this paper, we propose a new algorithm for marginal inference that is based on the incremental build-infer-approximate (IBIA) paradigm. Our algorithm converts the PGM into a sequence of linked clique tree forests (SLCTF) with bounded clique sizes, and then uses a heuristic belief update algorithm to infer the marginals. For the special case of Bayesian networks, we show that if the incremental build step in IBIA uses the topological order of variables then (a) the prior marginals are consistent in all CTFs in the SLCTF and (b) the posterior marginals are consistent once all evidence variables are added to the SLCTF. In our approach, the belief propagation step is non-iterative and the accuracy-complexity trade-off is controlled using user-defined clique size bounds. Results for several benchmark sets from recent UAI competitions show that our method gives either better or comparable accuracy than existing variational and sampling based methods, with smaller runtimes

Plant sterols for human health- A review

The aim of the article was to review phytosterols as functional food and its significance in lowering cholesterol as well as its specific effect on human health. Phytosterols has been known for its cholesterol lowering action long time back but the uprising of phytosterols in form of functional foods gained the interest once again. Fatty food matrix provides optimal solubility but fortification of phytosterols with other food matrices like low fat fermented milk, bread, juice are showing positive results. A dose of 2 g/day of either steryl or stanyl esters has been prescribed for an optimum effect which has been confirmed by FDA and EC. A number of studies have documented the safety and the efficiency of phytosterols. But there is still a big question mark on the use of it because of their adverse effect on body in form of Phytosterol oxidation products (POPs). It needs further investigation to elucidate effect of POPs within body

IBIA: An Incremental Build-Infer-Approximate Framework for Approximate Inference of Partition Function

Exact computation of the partition function is known to be intractable, necessitating approximate inference techniques. Existing methods for approximate inference are slow to converge for many benchmarks. The control of accuracy-complexity trade-off is also non-trivial in many of these methods. We propose a novel incremental build-infer-approximate (IBIA) framework for approximate inference that addresses these issues. In this framework, the probabilistic graphical model is converted into a sequence of clique tree forests (SCTF) with bounded clique sizes. We show that the SCTF can be used to efficiently compute the partition function. We propose two new algorithms which are used to construct the SCTF and prove the correctness of both. The first is an algorithm for incremental construction of CTFs that is guaranteed to give a valid CTF with bounded clique sizes and the second is an approximation algorithm that takes a calibrated CTF as input and yields a valid and calibrated CTF with reduced clique sizes as the output. We have evaluated our method using several benchmark sets from recent UAI competitions and our results show good accuracies with competitive runtimes

Roof above the head : A qualitative assessment of rural housing in India

The development of rural housing in a manner that results in adequate, quality shelter for inhabitants of Mahatma Gandhi’s “real India” is a challenge before the nation. What are the issues confronting rural housing development in India? The litany of its woes is endless. At first impression, rural housing is vulnerable to weaknesses in the delivery system for housing materials and services. Gradually, it dawns on the observer that the sector is deeply affected by the infrastructure deficit – roads, electricity supply, drinking water and sanitation. It has been bypassed by the numerous economic revolutions that have made India a vibrant economic superpower. For instance housing finance, which played a key role in the urban housing explosion, is conspicuous by its absence in the rural setting. Additionally, the limited mobility of rural households, the lack of vibrancy in the market for village properties and the marked volatility in agricultural incomes combine to dampen the prospects of this nebulous sector.Housing

Student Performance Prediction Using Educational Data Mining Techniques

Educational sector produces data in large amount that is too voluminous and complex to understand. There is a need to efficiently filter and prioritize the data so as to deliver the relevant information to get rid of information overloading. Data mining searches through the large amount of dynamically generated data to present users with the useful and understandable patterns and trends. It has the power to use the raw data effectively which has been produced by universities, to draw the hidden patterns and the relationships among the attributes that are used in predicting the student performance, their behaviour effectively. In this paper the data mining techniques have been briefly described. The literature review of educational data mining is also done. This paper, implements data mining techniques such as Naive bayes and Support vector machine to predict the student performance

Improved Technologies for Higher Maize Production

An array of production technologies, from land preparation to harvesting, has been recommended for maize crop. Being non-tillering crop, optimum plant population can be achieved if suitable crop establishment techniques like method of sowing, sowing time, seed rate, seed treatment, crop geometry etc., are followed. Weeds can be managed well either by two hoeings 15–30 days after sowing or herbicides like atrataf 50 WP (atrazine) at 2 kg/ha on medium to heavy textured soils and 1.25 kg/ha in light soils within 10 days of sowing, using 500 litres as pre-emergence or spray 262.5 ml/acre laudis 420 SC (tembotrione) in 375 litres of water at 20 days after sowing. Integrated nutrient management strategy renders use of farm yard manure at 10–15 t/ha, Paddy straw compost at 450 kg/ha or synthetic fertilizers at 120 kg N, 60 kg P2O5 and 40 kg K2O per hectare for hybrids and 80 kg N, 30 kg P2O5 and 20 kg K2O per hectare for composites. Integrated pest management approach emphasizes on use of physical, chemical or biological measures for the control of insect-pests. Maize borer can be controlled by spraying coragen 18.5 SC at 75 ml using 150 litres water/ha. Drying of maize produce can be done sun drying, smoking or air drying for fetching better market price