1991. Branding strategies for real estate companies in Delhi-NCRRajan Gupta, Saibal K. Pal, Saibal K. Pal, 2012, samostojni znanstveni sestavek ali poglavje v monografski publikaciji Opis: Real estate is one of the fastest growing industries in India mainly due to rising population and income, movement of people to larger cities & towns and increasing demand-supply gap. Many Indian and foreign companies have started investing heavily in this sector as bright prospects can be witnessed in metro and big cities as well as smaller towns in India. Major players like DLF, Unitech, Ansals, Omaxe and Parsavnath Developers have shown good turnover in recent times and many others are in the process of establishing themselves in this business. With New Delhi being the national capital of India, this region provides variety of opportunities to people from different parts of the country. Properties ranging from one bedroom residential flats to lavish bungalows and from small shops and offices to large commercial spaces and business centers are all in demand. The number of real estate and construction companies in this region has also increased drastically, thereby increasing competition amongst them. Different companies have started adopting unique and innovative marketing strategies for attracting different categories of customers in this region. This paper first analyzes existing marketing strategies that are adopted by popular real estate firms for addressing different customer segments and then suggests newer ones to attract business from investors and buyers in the Delhi - National Capital Region (NCR) for residential purpose. Secondary information from various sources was used and primary information was collected by interacting with real estate developers and different categories of customers. Innovative applications of Information Technology in this industry are also portrayed in this paper.
Ključne besede: real estate, brand differentiation, marketing strategy, consumer behaviour
Objavljeno v RUNG: 05.04.2021; Ogledov: 2109; Prenosov: 0
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1992. Impact of make-in-India campaign on foreign investors towards FDI in IndiaRajan Gupta, Saibal K. Pal, Saibal K. Pal, 2016, samostojni znanstveni sestavek ali poglavje v monografski publikaciji Opis: Make in India is not just an arousing call for investors, to contribute their serving into the developing economy of India, but a pledge to stimulate the development of manufacturing sector of the country. The major aim of this paper is to discover the determining factors of Foreign Direct Investment (FDI), persuading investors to come and investment in India. This paper deals with primary aspects of Make in India campaign and Foreign Direct Investment. In this study, the dependent variable is Foreign Direct Investment and Independent variables are the determinants impacting FDI (market size, GDP, openness of the economy, labor cost and productivity, tax policies, infrastructure, foreign exchange rate, political stability and government regulations). According to the results, this study reveals the positive impact of Make in India campaign and variables impacting FDI for enhancing the domestic wealth of the nation and upholding the pace of progression and advancement. It will be useful for various stakeholders to understand the viewpoints of various investors from different countries looking forward to invest in India.
Ključne besede: make in India, foreign direct investment, Indian economy, foreign investors
Objavljeno v RUNG: 05.04.2021; Ogledov: 2012; Prenosov: 0
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1993. Measuring data quality across open government datasetsRajan Gupta, Sushmita Yadav, Avinash Prasad, Saibal K. Pal, 2019, objavljeni znanstveni prispevek na konferenci Opis: Data Quality has become the base for any analytical operation or modelling. Poor Quality of data can lead to poor analytical modeling, which in turn can lead to poor decision making and predictions, which can finally impact the revenue and working of an organization. This is true for both public and private sector organizations. With rise in E-Governance, lot of nations and their respective public sector units are making use of publicly available datasets. But are these datasets reliable and have good quality. This is the major research question studied in this paper. The study collected publicly available datasets from Open Government Data platforms across 8 different nations around the world. More than 300 datasets having roughly 3.5 million rows were assessed for various data quality measures. The various parameters studied for the data were valid data types, correctness, completeness, statistical features, variability, comparability, duplicacy and the likes. Script was written in R to check the value for various measures. It was found that different countries had advantages on different parameters. Not one country was found to have all the parameters to be of high quality. Different ranges were found for the dataset for various parameters which was helpful in determining the overall quality of the dataset. This will be helpful for various public and private sector organizations in assessing the quality of datasets they intend to work on. Substantial efforts and resources can be saved on Advanced Analytics if the quality of dataset can be determined in advance. The proposed data quality assessment model can be applied on any private or public dataset. Different industry and organizations can set different threshold values for the parameters to benchmark their analytical process. Both practitioners and researchers can be benefitted from this research work.
Ključne besede: data quality assessment, open government datasets, e-governance, data quality measures
Objavljeno v RUNG: 05.04.2021; Ogledov: 2112; Prenosov: 0
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1997. Effects of polyethylene terephthalate (PET) microplastics and acid rain on physiology and growth of Lepidium sativumSara Pignattelli, Andrea Broccoli, Manuela Piccardo, Antonio Terlizzi, Monia Renzi, 2021, izvirni znanstveni članek Opis: This study evaluated the chronic toxicity (30 days) of different sizes of polyethylene terephthalate (PET)
microplastics (60e3000 mm) provided alone or in combination with acid rain, on garden cress (Lepidium
sativum). Both biometrical and physiological traits have been evaluated: i) percentage inhibition of seed
germination, plant height, leaf number and fresh biomass production; ii) oxidative stress responses
(hydrogen peroxide; ascorbic acid and glutathione production); iii) impairment in photosynthetic machinery
in term of pigments production; iv) aminolevulinic acid and proline production. Results highlighted
that different sizes of PET, alone or in combination with acid rain, are able to negatively affect
both biometrical and physiological plant traits. In particular, the lower size of microplastics is able to
negatively affect growth and development, as well as to trigger the oxidative burst. Regarding the pigments
production, PET coupled with acid rain, induced a higher production of Chl-b, and an inhibition of
aminolevulinic acid.
Ključne besede: polyethylene terephthalate, acid rain, lepidium sativum, oxidative burst, germinability, chlorophylls
Objavljeno v RUNG: 02.04.2021; Ogledov: 1939; Prenosov: 0
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1998. Technological and analytical review of contact tracing apps for COVID-19 managementRajan Gupta, Gaurav Pandey, Poonam Chaudhary, Saibal K. Pal, 2021, izvirni znanstveni članek Opis: Role of technology is improving for COVID-19 management all around the world. Usage of mobile applications, web applications, cloud computing, and related technologies have helped many public administrators worldwide manage the current pandemic. Contact tracing applications are such mobile app solutions that are used by more than 100 countries today. This study presents a structured research review-based framework related to multiple contact tracing applications. The various components of the framework are related to technological working, design architecture, and feature analysis of the applications, along with the analysis of the acceptance of such applications worldwide. Also, components focusing on the security features and analysis of these applications based on Data Privacy, Security Vetting, and different attacks have been included in the research framework. Many applications are yet to explore the analytical capabilities of the data generated through contact tracing. The various use-cases identified for these applications are detecting positive case probability, identifying a containment zone in the country, finding regional hotspots, monitoring public events & gatherings, identifying sensitive routes, and allocating resources in various regions during the pandemic. This study will act as a guide for the users researching contact tracings applications using the proposed four-layered framework for their app assessment.
Ključne besede: novel corona virus, location technology, contact tracing applications, Aarogya Setu App, data science, data analysis
Objavljeno v RUNG: 02.04.2021; Ogledov: 1955; Prenosov: 0
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1999. Introduction to algorithmic governmentRajan Gupta, Saibal K. Pal, znanstvena monografija Opis: This book introduces the Algorithmic Government or Government by Algorithm, which refers to authorizing machines in the Public Sector for automated decision-making based on Artificial Intelligence, Data Science, and other technologies. It is an emerging concept introduced globally and will be considered revolutionary in the future. The book covers concepts, applications, progress status, and potential use-cases of Algorithmic Government. This book serves as introductory material for the readers from technology, public policy, administration, and management fields.
Ključne besede: algorithmic government, automated decision making, artificial intelligence, public sector, government by algorithms, algorithmic bias
Objavljeno v RUNG: 02.04.2021; Ogledov: 2631; Prenosov: 36
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2000. Design & analysis of clustering based intrusion detection schemes for e-governanceRajan Gupta, Sunil K. Muttoo, Saibal K. Pal, 2016, objavljeni znanstveni prispevek na konferenci Opis: The problem of attacks on various networks and information systems is increasing. And with systems working in public domain like those involved under E-Governance are facing more problems than others. So there is a need to work on either designing an altogether different intrusion detection system or improvement of the existing schemes with better optimization techniques and easy experimental setup. The current study discusses the design of an Intrusion Detection Scheme based on traditional clustering schemes like K-Means and Fuzzy C-Means along with Meta-heuristic scheme like Particle Swarm Optimization. The experimental setup includes comparative analysis of these schemes based on a different metric called Classification Ratio and traditional metric like Detection Rate. The experiment is conducted on a regular Kyoto Data Set used by many researchers in past, however the features extracted from this data are selected based on their relevance to the E-Governance system. The results shows a better and higher classification ratio for the Fuzzy based clustering in conjunction with meta-heuristic schemes. The development and simulations are carried out using MATLAB.
Ključne besede: particle swarm optimization, intrusion detection, anomaly detection, intrusion detection system, network intrusion detection
Objavljeno v RUNG: 02.04.2021; Ogledov: 2048; Prenosov: 9
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