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Search Results: 1 - 10 of 3191 matches for " Uday Shankar Chakraborty "
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On Nil-Symmetric Rings
Uday Shankar Chakraborty,Krishnendu Das
Journal of Mathematics , 2014, DOI: 10.1155/2014/483784
Abstract: The concept of nil-symmetric rings has been introduced as a generalization of symmetric rings and a particular case of nil-semicommutative rings. A ring is called right (left) nil-symmetric if, for , where are nilpotent elements, implies . A ring is called nil-symmetric if it is both right and left nil-symmetric. It has been shown that the polynomial ring over a nil-symmetric ring may not be a right or a left nil-symmetric ring. Further, it is also proved that if is right (left) nil-symmetric, then the polynomial ring is a nil-Armendariz ring. 1. Introduction Throughout this paper, all rings are associative with unity. Given a ring , and denote the set of all nilpotent elements of and the polynomial ring over , respectively. A ring is called reduced if it has no nonzero nilpotent elements; is said to be Abelian if all idempotents of are central; is symmetric [1] if implies for all . An equivalent condition for a ring to be symmetric is that whenever product of any number of elements of the ring is zero, any permutation of the factors still gives the product zero [2]. is reversible [3] if implies for all ; is called semicommutative [4] if implies for all . In [5], Rege-Chhawchharia introduced the concept of an Armendariz ring. A ring is called Armendariz if whenever polynomials , satisfy , then for each . Liu-Zhao [6] and Antoine [7] further generalize the concept of an Armendariz ring by defining a weak-Armendariz and a nil-Armendariz ring, respectively. A ring is called weak-Armendariz if whenever polynomials ,?? satisfy , then for each . A ring is called nil-Armendariz if whenever ,?? satisfy , then for each . Mohammadi et al. [8] initiated the notion of a nil-semicommutative ring as a generalization of a semicommutative ring. A ring is nil-semicommutative if implies for all . In their paper it is shown that, in a nil-semicommutative ring , forms an ideal of . Getting motivated by their paper we introduce the concept of a right (left) nil-symmetric ring which is a generalization of symmetric rings and a particular case of nil-semicommutative rings. Thus all the results valid for nil-semicommutative rings are valid for right (left) nil-symmetric rings also. We also prove that if a ring is right (left) nil-symmetric and Armendariz, then is right (left) nil-symmetric. In the context, there are also several other generalizations of symmetric rings (see [9, 10]). 2. Right (Left) Nil-Symmetric Rings For a ring , and denote the full matrix ring and the upper triangular matrix ring over , respectively. We observe that if is a ring, then Definition 1. A ring
Rural Stay Exposure for Undergraduate Medical Student
Uday Shankar Singh
National Journal of Community Medicine , 2011,
Abstract: Not Available
Interpolation of Generalized Functions Using Artificial Neural Networks  [PDF]
Raghu T Mylavarapu, Bharadwaja Krishnadev Mylavarapu, Uday Shankar Sekhar
Journal of Computer and Communications (JCC) , 2018, DOI: 10.4236/jcc.2018.67004
Abstract: In this paper we employ artificial neural networks for predictive approximation of generalized functions having crucial applications in different areas of science including mechanical and chemical engineering, signal processing, information transfer, telecommunications, finance, etc. Results of numerical analysis are discussed. It is shown that the known Gibb’s phenomenon does not occur.
Trend in GHG Emissions from Northeast and West Coast Regions of India
Tongdimenba Jamir,Uday Shankar De
Environmental Research, Engineering and Management , 2013, DOI: 10.5755/j01.erem.63.1.2739
Abstract: Climate change due to increasing concentrations of greenhouse gases (GHGs) has emerged as a serious global environmental issue. An attempt has been made to assess the GHG emissions in two geographical regions of India i.e. the Northeast Region (NER) and the West coast Region (WCR) during the period of 1980-2005. The analysis reveals an increasing trend in GHG emissions from the study regions except for CH4, which shows a decreasing trend in Goa and Kerala. As far as state wise GHG emissions are concerned; Assam ranks first in CO2, CH4 and N2O emissions from the NER. Konkan ranks first in CO2 and CH4 emissions, while Kerala ranks first in N2O emissions representing the WCR. Analysis of the compounded annual growth rate reveals higher for the WCR in CO2 and CH4 emissions except N2O where the NER remains the highest. In order to find the association between GHG emissions and climatic response, the mean air temperature for 26 stations in both regions were subjected to trend analysis. The findings show warming trends in the mean air temperature over a majority of the stations indicating a possible role by increased GHGs. Further, the analysis reveals a positive correlation of population and GHG emissions significantly at 99% for both the regions. DOI: http://dx.doi.org/10.5755/j01.erem.63.1.2739
A solution to robot selection problems using data envelopment analysis
Suprakash Mondal,Shankar Chakraborty
International Journal of Industrial Engineering Computations , 2013, DOI: 10.5267/j.ijiec.2013.03.007
Abstract: Selection of industrial robots for the present day’s manufacturing organizations is one of the most difficult assignments due to the presence of a wide range of feasible alternatives. Robot manufacturers are providing advanced features in their products to sustain in the globally competitive environment. For this reason, selection the most suitable robot for a given industrial application now becomes a more complicated task. In this paper, four models of data envelopment analysis (DEA), i.e. Charnes, Cooper and Rhodes (CCR), Banker, Charnes and Cooper (BCC), additive, and cone-ratio models are applied to identify the feasible robots having the optimal performance measures, simultaneously satisfying the organizational objectives with respect to cost and process optimization. Furthermore, the weighted overall efficiency ranking method of multi-attribute decision-making theory is also employed for arriving at the best robot selection decision from the short-listed competent alternatives. In order to demonstrate the relevancy and distinctiveness of the adopted DEA-based approach, two real time industrial robot selection problems are solved.
Using MACBETH method for supplier selection in manufacturing environment
Prasad Karande,Shankar Chakraborty
International Journal of Industrial Engineering Computations , 2013,
Abstract: Supplier selection is always found to be a complex decision-making problem in manufacturing environment. The presence of several independent and conflicting evaluation criteria, either qualitative or quantitative, makes the supplier selection problem a candidate to be solved by multi-criteria decision-making (MCDM) methods. Even several MCDM methods have already been proposed for solving the supplier selection problems, the need for an efficient method that can deal with qualitative judgments related to supplier selection still persists. In this paper, the applicability and usefulness of measuring attractiveness by a categorical-based evaluation technique (MACBETH) is demonstrated to act as a decision support tool while solving two real time supplier selection problems having qualitative performance measures. The ability of MACBETH method to quantify the qualitative performance measures helps to provide a numerical judgment scale for ranking the alternative suppliers and selecting the best one. The results obtained from MACBETH method exactly corroborate with those derived by the past researchers employing different mathematical approaches.
Application of PROMETHEE-GAIA method for non-traditional machining processes selection
Prasad Karande,Shankar Chakraborty
Management Science Letters , 2012,
Abstract: With ever increasing demand for manufactured products of hard alloys and metals with high surface finish and complex shape geometry, more interest is now being paid to non-traditional machining (NTM) processes, where energy in its direct form is used to remove material from workpiece surface. Compared to conventional machining processes, NTM processes possess almost unlimited capabilities and there is a strong believe that use of NTM processes would go on increasing in diverse range of applications. Presence of a large number of NTM processes along with complex characteristics and capabilities, and lack of experts in NTM process selection domain compel for development of a structured approach for NTM process selection for a given machining application. Past researchers have already attempted to solve NTM process selection problems using various complex mathematical approaches which often require a profound knowledge in mathematics/artificial intelligence from the part of process engineers. In this paper, four NTM process selection problems are solved using an integrated PROMETHEE (preference ranking organization method for enrichment evaluation) and GAIA (geometrical analysis for interactive aid) method which would act as a visual decision aid to the process engineers. The observed results are quite satisfactory and exactly match with the expected solutions.
Non-conventional optimization techniques in optimizing non-traditional machining processes: A review
Arindam Debroy,Shankar Chakraborty
Management Science Letters , 2013,
Abstract: With the ever-increasing demands for high surface finish and complex shape geometries, conventional metal removal methods are now being replaced by non-traditional machining (NTM) processes. These NTM processes use energy in its direct form to remove materials in the form of atoms or molecules to obtain the required accuracy and burr-free machined surface. In order to exploit the optimal capabilities of the NTM processes, it is often required to determine the best possible combinations of their controllable parameters. Different non-conventional optimization techniques have been used for dealing with these process optimization problems because of their inherent advantages and capabilities for arriving at the almost global optimal solutions. This paper reviews the applications of different non-conventional optimization techniques for parametric optimization of NTM processes. It is observed that electrical discharge machining processes have been optimized most number of times, followed by wire electrical discharge machining processes. In most of the cases, the past researchers have preferred to maximize material removal rate. Genetic algorithm has been found to be the most popular non-conventional optimization technique.
Selection of materials using multi-criteria decision-making methods with minimum data
Shankar Chakraborty,Prasenjit Chatterjee
Decision Science Letters , 2013, DOI: 10.5267/j.dsl.2013.03.005
Abstract: Selection of material for a specific engineering component, which plays a significant role in its design and proper functioning, is often treated as a multi-criteria decision-making (MCDM) problem where the most suitable material is to be chosen based on a given set of conflicting criteria. For solving these MCDM problems, the designers do not generally know what should be the optimal number of criteria required for arriving at the best decisive action. Those criteria should be independent to each other and their number should usually limit to seven plus or minus two. In this paper, five material selection problems are solved using three common MCDM techniques to demonstrate the effect of number of criteria on the final rankings of the material alternatives. It is interesting to observe that the choices of the best suited materials solely depend on the criterion having the maximum priority value. It is also found that among the three MCDM methods, the ranking performance of VIKOR (Vlse Kriterijumska Optimizacija Kompromisno Resenje) method is the best.
A Fuzzy-MOORA approach for ERP system selection
Prasad Karande,Shankar Chakraborty
Decision Science Letters , 2012, DOI: 10.5267/j.dsl.2012.07.001
Abstract: In today’s global and dynamic business environment, manufacturing organizations face the tremendous challenge of expanding markets and meeting the customer expectations. It compels them to lower total cost in the entire supply chain, shorten throughput time, reduce inventory, expand product choice, provide more reliable delivery dates and better customer service, improve quality, and efficiently coordinate demand, supply and production. In order to accomplish these objectives, the manufacturing organizations are turning to enterprise resource planning (ERP) system, which is an enterprise-wide information system to interlace all the necessary business functions, such as product planning, purchasing, inventory control, sales, financial and human resources into a single system having a shared database. Thus to survive in the global competitive environment, implementation of a suitable ERP system is mandatory. However, selecting a wrong ERP system may adversely affect the manufacturing organization’s overall performance. Due to limitations in available resources, complexity of ERP systems and diversity of alternatives, it is often difficult for a manufacturing organization to select and install the most suitable ERP system. In this paper, two ERP system selection problems are solved using fuzzy multi-objective optimization on the basis of ratio analysis (MOORA) method and it is observed that in both the cases, SAP is the best solution.
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