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Institution

Jadavpur University

EducationKolkata, India
About: Jadavpur University is a education organization based out in Kolkata, India. It is known for research contribution in the topics: Population & Fuzzy logic. The organization has 10856 authors who have published 27678 publications receiving 422069 citations. The organization is also known as: JU & Jadabpur University.


Papers
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Journal ArticleDOI
TL;DR: In this article, the authors explored the application of an almost new multi-objective optimization on the basis of ratio analysis (MOORA) method to solve different decision-making problems as frequently encountered in the real-time manufacturing environment.
Abstract: To meet the challenges of global competitiveness, manufacturing organizations are now facing the problems of selecting appropriate manufacturing strategies, product and process designs, manufacturing processes and technologies, and machinery and equipment. The selection decisions become more complex as the decision makers in the manufacturing environment have to assess a wide range of alternatives based on a set of conflicting criteria. To aid these selection processes, various multi-objective decision-making (MODM) methods are now available. This paper explores the application of an almost new MODM method, i.e., the multi-objective optimization on the basis of ratio analysis (MOORA) method to solve different decision-making problems as frequently encountered in the real-time manufacturing environment. Six decision-making problems which include selection of (a) an industrial robot, (b) a flexible manufacturing system, (c) a computerized numerical control machine, (d) the most suitable non-traditional machining process for a given work material and shape feature combination, (e) a rapid prototyping process, and (f) an automated inspection system are considered in this paper. In all these cases, the results obtained using the MOORA method almost corroborate with those derived by the past researchers which prove the applicability, potentiality, and flexibility of this method while solving various complex decision-making problems in present day manufacturing environment.

374 citations

Journal ArticleDOI
TL;DR: In this paper, the potential contribution of industrial energy-efficiency technologies and policies to reduce energy use and greenhouse gas emissions to 2030 is discussed, where the authors propose a framework to evaluate the potential of these technologies for mitigating greenhouse gas emission from industry.
Abstract: Industry contributes directly and indirectly (through consumed electricity) about 37% of the global greenhouse gas emissions, of which over 80% is from energy use. Total energy-related emissions, which were 9.9 GtCO2 in 2004, have grown by 65% since 1971. Even so, industry has almost continuously improved its energy efficiency over the past decades. In the near future, energy efficiency is potentially the most important and cost-effective means for mitigating greenhouse gas emissions from industry. This paper discusses the potential contribution of industrial energy-efficiency technologies and policies to reduce energy use and greenhouse gas emissions to 2030.

371 citations

Journal ArticleDOI
Mousumi Basu1
01 Mar 2011
TL;DR: Results obtained from the proposed approach have been compared to those obtained from pareto differential evolution, nondominated sorting genetic algorithm-II and strength pare to evolutionary algorithm 2.
Abstract: Economic environmental dispatch (EED) is an important optimization task in fossil fuel fired power plant operation for allocating generation among the committed units such that fuel cost and emission level are optimized simultaneously while satisfying all operational constraints. It is a highly constrained multiobjective optimization problem involving conflicting objectives with both equality and inequality constraints. In this paper, multi-objective differential evolution has been proposed to solve EED problem. Numerical results of three test systems demonstrate the capabilities of the proposed approach. Results obtained from the proposed approach have been compared to those obtained from pareto differential evolution, nondominated sorting genetic algorithm-II and strength pareto evolutionary algorithm 2.

369 citations

Journal ArticleDOI
TL;DR: In this paper, a thermophilic anaerobic microorganism is incorporated at different cell concentrations with the mixing water, and a 25% increase in 28 day compressive strength of cement mortar was achieved with the addition of about 105 cell/ml of mixing water.

366 citations

Journal ArticleDOI
TL;DR: The current deepening and widening of interest of niosomes in many scientific disciplines is reviewed and, particularly, its application in medicine is reviewed.
Abstract: Over the past several years, treatment of infectious diseases and immunisation has undergone a revolutionary shift. With the advancement of biotechnology and genetic engineering, not only a large number of disease-specific biological have been developed, but also emphasis has been made to effectively deliver these biologicals. Niosomes are vesicles composed of non-ionic surfactants, which are biodegradable, relatively nontoxic, more stable and inexpensive, an alternative to liposomes. This article reviews the current deepening and widening of interest of niosomes in many scientific disciplines and, particularly its application in medicine. This article also presents an overview of the techniques of preparation of niosome, types of niosomes, characterisation and their applications.

366 citations


Authors

Showing all 10999 results

NameH-indexPapersCitations
Subir Sarkar1491542144614
Amartya Sen149689141907
Susumu Kitagawa12580969594
Praveen Kumar88133935718
Rodolphe Clérac7850622604
Rajesh Gupta7893624158
Santanu Bhattacharya6740014039
Swagatam Das6437019153
Anupam Bishayee6223711589
Michael G. B. Drew61131524747
Soujanya Poria5717513352
Madeleine Helliwell543709898
Tapas Kumar Maji542539804
Pulok K. Mukherjee5429610873
Dipankar Chakraborti5411512078
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
202385
2022332
20211,949
20201,936
20191,737
20181,807