Drivers of Agricultural Diversification in India, Haryana and the Greenbelt Farms of India

The present study discusses factors responsible for agricultural diversification at different levels : country (India), state (Haryana) and farms of Kurukshetra district in Haryana. The study regressed alternate measures of diversification namely, the Simpson index and concentration of non-food crops, on several possible factors such as income, land distribution, irrigation intensity, institutional credit, road density, urbanization and market penetration. The regression analysis suggests that increased road density, urbanization encourages commercialization of agriculture and with commercialization, farms in a region are increasingly specialized under certain crops and crop-groups as per the resource, infrastructure and institutions of the region.agricultural diversification, agriculture, India, Haryana

Pattern of Agricultural Diversification in India

Agricultural diversification as measured by increase in the percent of non-food crops has grown; whereas diversification as measured by the concentration indices has remained unchanged in the recent decade. There have been significant changes in the pattern of agricultural diversification at the regional level. Within a region, smaller sub-regions or pockets of specialization in certain crops and crop-groups have emerged. Farms do not remain diversified and the usual notion of crop diversification as a risk management practice is also belied in the present study. The study also found certain kind of structural changes in all sub-sectors of agriculture : crop, livestock, and fisheries. Concerns over extreme effects of such changes are however, not valid.agricultural diversification, Agriculture Analysis, India, non-food crops, crop, livestock, and fisheries

BULL VS BEAR MARKET- AN INVESTMENT GAME ANALYSIS USING MOVING AVERAGE METHOD

This paper aims to analyse and interpret the investor perception about investing in stock market. The market is often referred as to bull or bear market. This is key importance for financial decisions and economic analysis. The market behaves differently in these two phase. The bull market is identified when there is constant rise of stock prices whereas bear market is referred when there is fall in stock prices. These phases occur due to different trends of market or economy. Investor sentiments get affected by this. The paper tries to identify and provides understanding about the factors that causes and how it affects the psychology of investors. There are different analysis techniques used by analysts. The popular and common analysis theories are Fundamental Analysis and Technical Analysis. This paper is based on technical analysis of different category of stock with respect to wide spread industry like FMCG sector, Banking sector, Oil and Natural Gas sector, Automobiles sector and Pharmaceutical Sector etc. The paper also tries to establish whether the market is having a Bull Run or bear. The movement of stock prices is analysed in technical analysis. The data of stock prices are collected from NSE official site. The analysis in done for 5 years span starting from April 2012 to Mar 2017. Even to understand better, analysis of the stock is done on 100days moving average. Prevailing news during those times are also considered to interpret the behaviour of the investors

VLSI Design and Implementation for Adaptive Filter using LMS Algorithm

Adaptive filters, as part of digital signal systems, have been widely used, as well as in applications such as adaptive noise cancellation, adaptive beam forming, channel equalization, and system identification. However, its implementation takes a great deal and becomes a very important field in digital system world. When FPGA (Field Programmable Logic Array) grows in area and provides a lot of facilities to the designers, it becomes an important competitor in the signal processing market. In general FIR structure has been used more successfully than IIR structure in adaptive filters. However, when the adaptive FIR filter was made this required appropriate algorithm to update the filter’s coefficients. The algorithm used to update the filter coefficient is the Least Mean Square (LMS) algorithm which is known for its simplification, low computational complexity, and better performance in different running environments. When compared to other algorithms used for implementing adaptive filters the LMS algorithm is seen to perform very well in terms of the number of iterations required for convergence. This phenomenon can be achieved by a sufficient choice of bit length to represent the filter’s coefficients. This paper presents a lowcost and high performance programmable digital finite impulse response (FIR) filter. It follows the adaptive algorithm used for the development of the system. The architecture employs the computation sharing algorithm to reduce the computation complexity

Voices of rural people: Community-level assessment of effects and resilience to natural disasters in Odisha, India

Globally, natural disasters have caused a large scale of damage and destruction every year, affecting millions of people, the economy, and development – and developing countries are the most severely affected. Odisha is one of India’s most disaster-prone states. This study explores the effects of, and resilience to, cyclones, floods, droughts, and heatwaves in Odisha, and identifies government strategies that help mitigate these natural disasters. We mainly used primary data collected through a qualitative study undertaken from April 2017 to June 2017 in three districts of Odisha. We conducted in-depth interviews and focus group discussions with community members and key stakeholders at different levels. In addition, our study analyzed secondary data on natural disasters using DesInventar, a disaster information management system data source. The findings show that floods, cyclones, and drought in recent years, along with heatwaves and lightning, have severely affected the people of Odisha. The impacts of these natural disasters are calamitous – particularly on livelihoods, food security, health, water, and sanitation. These natural disasters, which have affected agriculture, fisheries, prawn cultivation, roadside vendors, and daily wage laborers, have both short- and long-term effects on the livelihoods of people in Odisha, leaving them with scarce employment opportunities. The vulnerable and marginalized sections of the population have been the most severely affected, and common coping mechanisms have included selling off livestock, borrowing food, taking loans and mortgages, and migration. The government’s measures/programs, such as an Early Warning System, Public Distribution System, Multipurpose Cyclone Rehabilitation Centers, Seasonal Residential Care Centers, and Indira Awas Yojana, play a major role in mitigating the effect of disasters among rural communities. Our study indicates that natural disasters have impacted the population of the state socioeconomically, physically, and psychologically. The effect on livelihoods, directly and indirectly, exacerbates income, food security, and health. There is an urgent need to focus on reducing people’s underlying vulnerabilities by taking proactive measures, engaging the community in decision-making, and generating alternative and sustainable livelihoods

Function approximation using back propagation algorithm in artificial neural networks

Inspired by biological neural networks, Artificial neural networks are massively parallel computing systems consisting of a large number of simple processors with many interconnections. They have input connections which are summed together to determine the strength of their output, which is the result of the sum being fed into an activation function. Based on architecture ANNs can be feed forward network or feedback networks. Most common family of feed-forward networks, called multilayer perceptron, neurons are organized into layers that have unidirectional connections between them. These connections are directed (from the input to the output layer) and have weights assigned to them. The principle of ANN is applied for approximating a function where they learn a function by looking at examples of this function. Here the internal weights in the ANN are slowly adjusted so as to produce the same output as in the examples. Performance is improved over time by iteratively updating the weights in the network. The hope is that when the ANN is shown a new set of input variables, it will give a correct output. To train a neural network to perform some task, we must adjust the weights of each unit in such a way that the error between the desired output and the actual output is reduced. This process requires that the neural network compute the error derivative of the weights (EW). In other words, it must calculate how the error changes as each weight is increased or decreased slightly. The back-propagation algorithm is the most widely used method for determining EW. We have started our program for a fixed structure network. It’s a 4 layer network with 1 input, 2 hidden and 1 output layers. No of nodes in input layer is 9 and output layer is 1. Hidden layer nodes are fixed at 4 and 3. The learning rate is taken as 0.07. We have written the program in MAT LAB and got the output of the network. The graph is plotted taking no of iteration and mean square error as parameter. The converging rate of error is very good. Then we moved to a network with all its parameter varying. We have written the program in VISUAL C++ with no. of hidden layer, no of nodes in each hidden layer, learning rate all varying. The converging plots for different structure by varying the variables are taken

Amino Acid Compositions of 27 Food Fishes and Their Importance in Clinical Nutrition

Proteins and amino acids are important biomolecules which regulate key metabolic pathways and serve as precursors for synthesis of biologically important substances; moreover, amino acids are building blocks of proteins. Fish is an important dietary source of quality animal proteins and amino acids and play important role in human nutrition. In the present investigation, crude protein content and amino acid compositions of important food fishes from different habitats have been studied. Crude protein content was determined by Kjeldahl method and amino acid composition was analyzed by high performance liquid chromatography and information on 27 food fishes was generated. The analysis showed that the cold water species are rich in lysine and aspartic acid, marine fishes in leucine, small indigenous fishes in histidine, and the carps and catfishes in glutamic acid and glycine. The enriched nutrition knowledge base would enhance the utility of fish as a source of quality animal proteins and amino acids and aid in their inclusion in dietary counseling and patient guidance for specific nutritional needs

Health and Safety Hazard Identification and Risk Assessment of Underground Cross Passage Construction in Between Two Metro Tunnels and Physicochemical and Microbial Assessment of Tap and Filtered Water in Academic Zone of NIT Rourkela

Th construction industry is an important contributor to the nation growth in terms of gross domestic product (GDP) and employment opportunity. Owing to its relatively labour intensive nature, construction works provide opportunities for employment for a wide range of people skilled, semi-skilled and unskilled. Despite its importance, construction industries are considered dangerous to work with as accidents rates, illness and injuries to workers, employees and public are increasing day by day. However, knowledge on how health and safety risks are managed on construction sites is limited. This study therefore, aims to study the current practice of health and safety risk assessment, risk communication and risk control at Delhi Metro Railways Corporation (DMRC) CC-27 site and to prepare a Risk assessment, communication and control procedure which can be applied to all the activities in the project site. In pursuing this objective, a detailed study on different procedure on health and safety risk assessment, communication and control being followed at different industries was studied and analyzed. A suitable procedure best suited to the Underground metro station construction project was proposed and validation was also done with the underground cross passage construction in between two metro tunnels. Lastly a suitable table for hazard identification and risk assessment (HIRA) and Safe Work Method Statement for the cross passage construction activity was also presente

Phishing: A Serious Threat to Online Banking

Phishing is an attempt to acquire sensitive information such as usernames, passwords, and credit card details (and sometimes, indirectly, money) by masquerading as a trustworthy entity in an electronic communication. Communications purporting to be from popular social web sites, auction sites, banks, online payment processors or IT administrators are commonly used to lure unsuspecting public. Phishing emails may contain links to websites that are infected with malware. Phishing is typically carried out by email spoofing or instant messaging, and it often directs users to enter details at a fake website whose look and feel are almost identical to the legitimate one. Phishing is an example of social engineering techniques used to deceive users, and exploits the poor usability of current web security technologies. Attempts to deal with the growing number of reported phishing incidents include legislation, user training, public awareness, and technical security measures. Many websites have now created secondary tools for applications, like maps for games, but they should be clearly marked as to who wrote them, and you should not use the same passwords anywhere on the internet