Optimising Farm Plans in Different Farming Systems

This study has been conducted to optimize farm plans in different farming systems in Orathanadu block of the Thanjavur district in Tamil Nadu by randomly selecting 150 livestock farmers from 6 villages. A linear programming (LP) model has been developed to arrive at the optimal farm plans for different categories of farms (landless, marginal, small and large) separately. The net returns from dairying have been found as Rs 25,864, which is about 29.7 per cent to the total and it also could contribute maximum to employment (55 per cent). The optimal plan for small-farmer category has revealed that dairy animals have contributed maximum net returns (Rs 31,640) to the aggregate net returns (Rs 49,105). Dairy animals have also generated an employment of 840 humandays as against 45, 80 and 38.6 humandays, from paddy–I, paddy–II and groundnut crops, respectively. The optimal plan for marginal farmers has indicated that dairy animals and sheep could be more attractive in terms of income and employment generation. Optimal plan for landless households has revealed that 5 dairy animals, 15 goats and 15 sheep could be valuable for increasing their income and employment. Income increase in the optimal farm plans has been found maximum (223.5 per cent) in large-farmer category, followed by small (192.7 per cent), marginal (180.1 per cent) and landless households (116 per cent). The increase in employment of family labour in the optimal plan over the existing plan in all categories has indicated that optimal combination of enterprises could reduce unemployment.Farm Management,

An Intelligent Genetic Algorithm for Mining Classification Rules in Large Datasets

Genetic algorithm is a popular classification algorithm which creates a random population of candidate solutions and makes them to evolve into a suitable accurate solution for a given problem by processing them iteratively for several generations. During each generation the training data set is accessed by the genetic algorithm only for the population member's fitness calculation and no other extra knowledge about the problem domain is extracted from the training data set. Even the domain knowledge stored in the chromosome code of the population may be lost in the future generations due to genetic operations. All the genetic operations like crossover and mutation are probability based and they do not depend upon the domain knowledge. This phenomenon makes the genetic algorithm to converge slowly. This paper proposes a genetic algorithm which tries to gain maximum knowledge in between the generations and store them in the form of knowledge chromosomes. The gained knowledge is used to make predictions about the search space and to guide the search process to an area with potential solutions in the subsequent generations. This makes the genetic algorithm to converge quickly which in turn reduces the learning cost. The experiments show that the run time is reduced considerably when compared with the state-of-the-art evolutionary algorithm

Experimental Investigation of Catalytic Surface Reaction for Different Metal Surfaces

The use of a catalytic surface to enhance chemical reaction rates is a well established and common practice. However, its use in combustion devices for enhancing combustion reaction is somewhat less common and more recent. Catalytic combustors, because of their inherent ability to operate at very lean air fuel mixtures, can maintain a relatively low combustion temperature and hence reduce the formation of NOx significantly. Further the catalytic coating on the combustion chamber walls enhances the combustion process by increased rate of pre-flame reactions. This provides a basis for catalytic combustion in lean burn engine. A considerable amount of effort has been devoted in the present work to this experimental study and compares different catalyst reaction performance.A cylindrical chamber is fabricated and air-fuel mixture is passed through the chamber. A metal tube coated with the catalyst is placed inside the control volume and it is heated by an electric heater. The air-fuel mixture undergoes pre-flame combustion reaction and as a result of this, the miniature temperature increases. Various catalytic surfaces like mild steel, Nickel, Chromium and copper were tested. The activation temperatures of these catalytic surfaces were obtained from this experimental work. Keywords: catalytic reaction, LPG, activation energy, catalytic coatin

A fast genetic algorithm for mining classification rules in large datasets

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Optimising Farm Plans in Different Farming Systems

This study has been conducted to optimize farm plans in different farming systems in Orathanadu block of the Thanjavur district in Tamil Nadu by randomly selecting 150 livestock farmers from 6 villages. A linear programming (LP) model has been developed to arrive at the optimal farm plans for different categories of farms (landless, marginal, small and large) separately. The net returns from dairying have been found as Rs 25,864, which is about 29.7 per cent to the total and it also could contribute maximum to employment (55 per cent). The optimal plan for small-farmer category has revealed that dairy animals have contributed maximum net returns (Rs 31,640) to the aggregate net returns (Rs 49,105). Dairy animals have also generated an employment of 840 humandays as against 45, 80 and 38.6 humandays, from paddy–I, paddy–II and groundnut crops, respectively. The optimal plan for marginal farmers has indicated that dairy animals and sheep could be more attractive in terms of income and employment generation. Optimal plan for landless households has revealed that 5 dairy animals, 15 goats and 15 sheep could be valuable for increasing their income and employment. Income increase in the optimal farm plans has been found maximum (223.5 per cent) in large-farmer category, followed by small (192.7 per cent), marginal (180.1 per cent) and landless households (116 per cent). The increase in employment of family labour in the optimal plan over the existing plan in all categories has indicated that optimal combination of enterprises could reduce unemployment

Minig rules of concept drift using genetic algorithm

In a database the data concepts changes over time and this phenomenon is called as concept drift. Rules of concept drift describe how the concept changes and sometimes they are interesting and mining those rules becomes more important. CDR tree algorithm is currently used to identify the rules of concept drift. Building a CDR tree becomes a complex process when the domain values of the attributes get increased. Genetic Algorithms are traditionally used for data mining tasks. In this paper, a Genetic Algorithm based approach is proposed for mining the rules of concept drift, which makes the mining task simpler and accurate when compared with the CDR-tree algorithm

Reduction of nitrogen oxide emissions using nickel-copper alloy catalyst in diesel engines

167-171<span style="font-size:11.0pt;line-height:115%; font-family:" calibri","sans-serif";mso-ascii-theme-font:minor-latin;mso-fareast-font-family:="" "times="" new="" roman";mso-fareast-theme-font:minor-fareast;mso-hansi-theme-font:="" minor-latin;mso-bidi-font-family:arial;mso-ansi-language:en-us;mso-fareast-language:="" en-us;mso-bidi-language:ar-sa"="">Results of experiments conducted for the reduction of NOx in diesel engine exhaust using nickel copper alloy, marketed under the name Monel, are reported. At temperatures above 600 K, and space velocities up to 40000 h-1, Monel is found to reduce about 70% of NOx in diesel engine exhaust. Monel in wire form, have been used for minimized swelling effect and thereby increasing its life, as the catalyst life is limited by physical deteriorations of catalyst, which causes increase in exhaust back pressure. Study on warm up characteristics of the catalyst system show rapid bed warm-up and possible reduction in catalyst mass without affecting the NOx reduction performance.</span

Perception of Employees towards TPM implementation in Foundry Industry with Reference to Coimbatore District

Total Productive Maintenance (TPM) is really an economical method by means it will be able to keep up with the shrub, machinery/ gear in addition to resources inside rewarding condition throughout minimum expense. Well retained machineries leads to productivity. With the companies who are into the foundry industry, the TPM quality policy is to consistently provide superior quality products and services, surpassing customer expectations on time at affordable prices. The main objective is that to study the roles of various people involved in the TPM and to identify the tangible and intangible benefits of TPM. For this a sample of 130 was collected from the respondents were analysed by descriptive statistics, regression analysis, Kruskallwallis, Rank correlation, and SEM analysis. The conclusion is that the TPM is effectively implemented with the organisation and further slight changes have to be made which leads to cost effectiveness towards the company