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Data mining-based algorithm for assortment planning

Journal of Management Analytics 2020年第3期7卷 443-457页

作者： Praveen Ranjan Srivastava satyendra sharma Simran Kaur Information Technology Indian Institute of Management(IIM)RohatakRohtakIndia Operation and Supply Chain Birla Institute of Technology and Science(BITS)PilaniPilaniRajasthanIndia Computer Science Birla Institute of Technology and Science(BITS)PilaniPilaniRajasthanIndia

With increasing varieties and products,management of limited shelf space becomes quite difficult for ***,an efficient product assortment,which in turn helps to plan the organization of various products across limited shelf space,is extremely important for *** can be distinguished based on quality,price,brand,and other attributes,and decision needs to be made about an assortment of the products based on these *** efficient assortment planning improves the financial performance of the retailer by increasing profits and reducing operational *** techniques can be very effective in grouping products,stores,*** help managers solve the problem of assortment *** paper proposes data mining approaches for assortment planning for profit maximization with space,and cost constraints by mapping it into well-known knapsack problem.

关键词： Retail assortment SKU rationalization data mining

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Developing a Bayesian belief network model for prediction of R&D project success

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Journal of Management Analytics 2017年第3期4卷 321-344页

作者： satyendra Kumar sharma Udayan Chanda Department of Management Birla Institute of Technology&SciencePilaniRajasthan 333031India

The project success is critical to the business performance in the era of fierce competition and *** basis for project success lies in the capabilities of managing risks *** has always been considerably risky;however,managing Research and Development(R&D)project risks has become even more important given today’s tight schedules and limited *** management has to be an integral part of the development *** purpose of this research is to develop a model to assess and estimate the risk exposure of an R&D project.A risk quantification model based on the Bayesian belief network is proposed,which is effective in capturing the interaction between various risk *** aim of this model is to empower the project managers to predict the failure risk probability of R&D projects.

关键词： R&D projects Bayesian belief networks risk identification risk assessment

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Impact of Elevated CO<sub>2</sub>on Wheat Growth and Yield under Free Air CO<sub>2</sub>Enrichment

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American Journal of Climate Change 2017年第4期6卷 573-596页

作者： Vivek Pandey Marisha sharma Farah Deeba Vivek K. Maurya Sunil K. Gupta satyendra P. Singh Aradhana Mishra Chandra Shekhar Nautiyal Plant Ecology & Environmental Sciences CSIR-National Botanical Research Institute Lucknow India Division of Plant Microbe Interaction CSIR-National Botanical Research Institute Lucknow India

Impact of elevated CO2 (free air CO2 enrichment) was studied on wheat (Triticum aestivum L. var Kundan) growth, yield and proteome. Elevated CO2 significantly impacted both underground (+24%) and aboveground (+15%) biomass. Grain weight/plant and harvest index were increased by 35% and 11.4%, respectively under high CO2. On the other hand, seed protein content was decreased by 19% under CO2 enrichment while seed starch and soluble sugar contents were increased by 8% and 23%, respectively. Wheat leaf proteomics revealed that 50 proteins were showing differential expression. Twenty proteins were more abundant while 30 were less abundant. Thirty two proteins were identified by MALDI TOF TOF. More abundant proteins were related to defense, photosynthesis, energy metabolism etc. While less abundant proteins were related to glycolysis and gluconeogenesis. Wheat grain proteomics revealed that out of 49 differentially abundant proteins, 24 were more in abundance and 25 were less in abundance in wheat grains under eCO2 condition. Thirty three proteins were identified and functionally characterized. They were found to be involved mainly in carbon metabolism, storage, defence and proteolysis. Gluten proteins are the major component of wheat storage proteins. Our results showed that both high and low molecular weight glutenins were more in eCO2 wheat seeds while there was no change in gliadin evels. This might alter wheat dough strength. Concentration of grain Cr and As was increased at eCO2 while that of Fe, Cu, Zn and Se were found to be decreased. Dynamics of carbon utilization and metabolic abilities of soil microbes under eCO2 were significantly altered. Our study showed that altered wheat seed composition is cause for concern vis-à-vis nutrition and health and for industries which may have implications for agriculturally dominated country like India.

关键词： Carbon Dioxide FACE Wheat Proteomics Grain Yield Soil Microbes

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