Volume 6 | Issue 1 |

 Abstract

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Creative Commons Attribution 4.0 and The Open Definition

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Employers and Employees Relationship in India

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Creative Commons Attribution 4.0 and The Open Definition

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The Mahabharata is full of amazing characters. Among these characters, women play significant roles in the epic. We are well acquainted with some women characters like Draupadi, Kunti and Gandhari but there are many women in the epic which are not well known to the general reader. This chapter is proposed to examine these lesser-known women characters of the epic and their unexplored identities. These women are also important in the epic and they contribute in the epic in their own way.In the present industrial scenario, the Indian economy has to face global competition as there is a rush of foreign capital and industry in our country. Therefore, this change in economic environment has affected the total gamut of styles, structures and contents of all those who are at stake in the field of economic firmament (heaven) and concept of industrial relations. There is need for change in the direction of labour-management relations, change in the comradeship between the two protagonists of labour and management which is to be governed by a totally new set off parameters. The gradual realization by both partners who are to survive, have to surrender their sectional interests in the interest of the economy of the country. Moreover, the rapid development in industry and need for attainment of economic reliance are the two major jobs which the country need to set out to accomplice these tasks in addition to others. The key to achieve this objective is increased production which depends upon the effective co-operation between labour and management at every stage. The way to ensure their co-operation is to satisfy their psychological and social needs in addition to economic needs.

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Creative Commons Attribution 4.0 and The Open Definition

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Unexplored, neglected, personality, Individuality

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Creative Commons Attribution 4.0 and The Open Definition

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Licence: creative commons attribution 4.0

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Creative Commons Attribution 4.0 and The Open Definition

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SUGGESTIONS FOR IMPROVING LABOUR-MANAGEMENT RELATIONS IN INDIA

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Creative Commons Attribution 4.0 and The Open Definition

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Labour welfare is a vital element of labour-management relations. Labour welfare is an extension of the term welfare and its application to labour. Welfare means faring and doing well. There are several advantages of labour welfare such as Improvement in labour-management relations, increase in the efficiency and income, high morale of workers, creation of permanent labour force, improvement in the mental and moral health etc. This paper tells about concept, definition, scope etc. of labour welfare.Sustainable agriculture has the potential to tackle most of the socio-economic and environmental problems originated out of unsustainable farm practices. The concept of sustainable agriculture revolves around three main goals-environmental health, economic profitability and socio-economic equity. Aware of this, Government of India has launched numerous polices and schemes which cater the needs for key inputs in a sustainable manner. The present paper aims to enlist and assess major initiatives of India such as National Mission on Sustainable Agriculture, Parampragat Krishi Vikas Yojna, PM Krishi Sinchayi Yojna, PM Fasal Bima Yojna, Soil Health Card scheme etc.The objective of the study is to analyze the efforts and approach of India for the development of sustainable agriculture.

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Creative Commons Attribution 4.0 and The Open Definition

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Key Words: Labour, Welfare, Welfare State, Facility

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Creative Commons Attribution 4.0 and The Open Definition

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India’s Approach toward Sustainable Agriculture: A Review of Government’s Initiatives

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Creative Commons Attribution 4.0 and The Open Definition

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India’s Approach toward Sustainable Agriculture: A Review of Government’s Initiatives

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Creative Commons Attribution 4.0 and The Open Definition

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Creative Commons Attribution 4.0 and The Open Definition

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Discrimination, Prejudices, Reservation, Castes and Categories.

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Creative Commons Attribution 4.0 and The Open Definition

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This paper describes a low-power (LP) programmable generator capable of producing pseudorandom test patterns with desired toggling levels and increased fault coverage gradient compared with the best-to-date built-in self-test (BIST)- primarily Based Pseudorandom test pattern generators. It is comprised of a linear finite state machine (a linear feedback shift register or a hoop generator) driving an appropriate phase shifter, and it comes with a variety of features permitting this device to supply binary sequences with preselected toggling (PRESTO) activity. We tend to introduce a technique to automatically choose many controls of the generator offering easy and precise tuning. The identical technique is subsequently used to deterministically guide the generator toward test sequences with improved fault-coverage- to pattern- count ratios. Furthermore, this paper proposes an LP test compression technique that permits shaping the test power envelope in a fully predictable, accurate, and flexible fashion by adapting the PRESTO-based logic BIST (LBIST) infrastructure. The proposed hybrid scheme efficiently combines test compression with LBIST, where both techniques can work synergistically to deliver top quality tests. Experimental results obtained for industrial styles illustrate the feasibility of the proposed test schemes and are reported herein.

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Creative Commons Attribution 4.0 and The Open Definition

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Built-in self-test (BIST), low-power (LP) test, pseudorandom test pattern generators (PRPGs), and test data volume compression

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Creative Commons Attribution 4.0 and The Open Definition

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Positioning extortion in the versatile App advertise alludes to fake or tricky exercises which have a motivation behind knocking up the Apps in the ubiquity list. In reality, it turns out to be increasingly visit for App designers to utilize shady means, for example, blowing up their Apps' deals or posting fake App appraisals, to submit positioning extortion. While the significance of anticipating positioning misrepresentation has been broadly perceived, there is constrained comprehension and research around there. To this end, in this paper, we give an all-encompassing perspective of positioning extortion and propose a positioning misrepresentation location framework for versatile Apps. In particular, we initially propose to precisely find the positioning misrepresentation by mining the dynamic time frames, to be specific driving sessions, of versatile Apps. Such driving sessions can be utilized for recognizing the nearby oddity rather than worldwide inconsistency of App rankings. Moreover, we examine three kinds of confirmations, i.e., positioning based confirmations, rating based confirmations and survey based confirmations, by demonstrating Apps' positioning, rating and audit practices through measurable speculations tests. Also, we propose an improvement based total strategy to incorporate every one of the confirmations for extortion identification. At long last, we assess the proposed framework with certifiable App information gathered from the iOS App Store for quite a while period. In the trials, we approve the adequacy of the proposed framework, and demonstrate the versatility of the location calculation and some consistency of positioning misrepresentation exercises.

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Creative Commons Attribution 4.0 and The Open Definition

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Mobile Apps, ranking fraud detection, evidence aggregation, historical ranking records, rating and review

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Creative Commons Attribution 4.0 and The Open Definition

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In this paper, we propose two new strategies to adequately take care of this issue by taking in two discriminative proclivity networks from these feebly named pictures. We initially propose another technique called regularized low-rank portrayal by viably using pitifully administered data to take in a low-rank remaking coefficient framework while investigating different subspace structures of the information. In particular, by acquainting an uncommonly planned regularizer with the low-rank portrayal strategy, we punish the comparing reproduction coefficients identified with the circumstances where a face is recreated by utilizing face pictures from different subjects or by utilizing itself. With the derived recreation coefficient network, a discriminative fondness framework can be gotten. In addition, we likewise build up another separation metric learning strategy called questionably directed basic metric learning by utilizing feebly administered data to look for a discriminative separation metric. Subsequently, another discriminative fondness lattice can be acquired utilizing the closeness grid (i.e., the portion framework) in view of the Mahalanobis separations of the information. Watching that these two liking networks contain correlative data, we additionally join them to get an intertwined liking lattice, in view of which we build up another iterative plan to derive the name of each face. Complete tests show the adequacy of our approach.

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Creative Commons Attribution 4.0 and The Open Definition

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Af?nity matrix, caption-based face naming, distance metric learning, low-rank representation (LRR).

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Licence: creative commons attribution 4.0

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

POS, parts of speech, tagger, Chhattisgarhi, Natural Language processing

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Creative Commons Attribution 4.0 and The Open Definition