A Review on Artificial Intelligence(AI), Big Data and Block Chain : Future Impact and Business Opportunities

A Review on Artificial Intelligence(AI), Big Data and Block Chain : Future Impact and Business Opportunities

Ahamed Golam Azam

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A Review on Artificial Intelligence(AI), Big Data and Block Chain : Future Impact and Business Opportunities

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Mega trends are global, sustained, and macroeconomic forces of development that impacts business, economy, society, cultures and personal lives thus defines our future life. For different industries technological megatrends have different impacts. The way we have seen the technological development over last 10 years there is no doubt within 2030, technology is the sector which will have profound global impact in all kind of business entities. Financial sectors is already using the most of these technological megatrends and other sectors such as logistics, education, health care are also implementing these. The paper consists of three trend reflections where I have chosen three technological megatrends-Artificial Intelligence, Big Data and Block Chain for the analysis of their future impact on businesses and how the businesses can create greater value by the implementation of these technologies.

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Recommendations are made for providing near term support for national economic recovery whilst also demonstrating the advantages of sustained development of the measurement infrastructure in the medium-term to maximize the potential of future innovative and disruptive technologies. These recommendations, whilst focused on consideration of the UK, should apply globally. References: [1] G. Tassey, "Underinvestment in public good technologies," J Technol. Transfer, Vol. 30, pp. 89-113, 2004. https://doi.org/10.1007/s10961-004-4360-0 [2] M. King, and E. Renedo, "Achieving the 2.4% GDP target: The role of measurement in increasing investment in R&D and innovation," NPL Report IEA 3, NPL, Teddington, UK, March 2020. [3] M. King and G. Tellett, "The National Measurement System: A Customer Survey for Three of the Core Labs in the National Measurement System," NMS Customer Survey Report 2018, NPL Teddington, UK, April 2020 [4] H. Kunzmann, T. Pfeifer, R. Schmitt, H. 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Patel, "Hydroxychloroquine or chloroquine with or without a macrolide for treatment of COVID-19: a multinational registry analysis," Lancet, 2020, https://doi.org/10.1016/S0140-6736(20)31180-6 (Print: ISSN 1931-5775) (Online: ISSN 2381-0580) ©2021 NCSL International Smart Power Supply Calibration System Iraj Vasaeli , Brandon Umansky NCSLI Measure | Vol. 13 No. 1 (2021) | doi.org/10.51843/measure.13.1.2 Publisher: NCSL International | Published February 2021 | Pages 22-27 Abstract: This paper details the development of an automated procedure to conduct calibrations of power supplies at Jet Propulsion Laboratory, California Institute of Technology (JPL). The fundamentals of power supply calibrations are given, and discussion on the method by which this custom software handles that calibration. Additionally, this technique provides real time uncertainty quantification of the calibrations. 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(Print: ISSN 1931-5775) (Online: ISSN 2381-0580) © 2021 NCSL International Computer Aided Verification of Voltage Dips and Short Interruption Generators for Electromagnetic Compatibility Immunity Test in Accordance with IEC 61000-4-11: 2004 + AMD: 2017 Hau Wah Lai , Cho Man Tsui , Hing Wah Li NCSLI Measure | Vol. 13 No. 1 (2021) | doi.org/10.51843/measure.13.1.3 Publisher: NCSL International | Published February 2021 | Pages 28-39 Abstract: This paper describes a procedure and a computer-aided system developed by the Standards and Calibration Laboratory (SCL) for verification of voltage dip and short interruption generators in accordance with the international standard IEC 61000-4-11:2004+AMD1:2017. The verification is done by calibrating the specified parameters and comparing with the requirements stated in the standard. The parameters that should be calibrated are the ratios of the residual voltages to the rated voltage, the accuracy of the phase angle at switching, and the rise time, fall time, overshoot and undershoot of the switching waveform. A specially built adapter is used to convert the high voltage output waveforms of the generators to lower level signals to be acquired by a digital oscilloscope. The other circuits required for the testing are also provided. In addition, the paper discusses the uncertainty evaluations for the measured parameters. References: [1] T. Williams, and K. Armstrong, "EMC for Systems and Installations Part 6 - Low-Frequency Magnetics Fields (Emissions and Immunity) Mains Dips, Dropouts, Interruptions, Sags, Brownouts and Swells," EMC Compliance Journal, August 2000. [2] M.I. Montrose, and E. M. 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(Print: ISSN 1931-5775) (Online: ISSN 2381-0580) © 2021 NCSL International Validation of the Photometric Method Used for Micropipette Calibration Elsa Batista , Isabel Godinho, George Rodrigues, Doreen Rumery NCSLI Measure | Vol. 13 No. 1 (2021) | doi.org/10.51843/measure.13.1.4 Publisher: NCSL International | Published February 2021 | Pages 40-45 Abstract: There are two methods generally used for calibration of micropipettes: the gravimetric method described in ISO 8655-6:2002 and the photometric method described in ISO 8655-7:2005. In order to validate the photometric method, several micropipettes of different capacities from 0.1 µL to 1000 µL were calibrated using both methods (gravimetric and photometric) in two different laboratories, IPQ (Portuguese Institute for Quality) and Artel. These tests were performed by six different operators. 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(Print: ISSN 1931-5775) (Online: ISSN 2381-0580) © 2021 NCSL International Material Flow Rate Estimation in Material Extrusion Additive Manufacturing G. P. Greeff NCSLI Measure | Vol. 13 No. 1 (2021) | doi.org/10.51843/measure.13.1.5 Publisher: NCSL International | Published February 2021 | Pages 46-56 Abstract: The additive manufacturing of products promises exciting possibilities. Measurement methodologies, which measure an in-process dataset of these products and interpret the results, are essential. However, before developing such a level of quality assurance several in-process measurands must be realized. One of these is the material flow rate, or rate of adding material during the additive manufacturing process. Yet, measuring this rate directly in material extrusion additive manufacturing presents challenges. 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How to Cite This Article

Ahamed Golam Azam. 2020. \u201cA Review on Artificial Intelligence(AI), Big Data and Block Chain : Future Impact and Business Opportunities\u201d. Global Journal of Management and Business Research - B: Economic & Commerce GJMBR-B Volume 20 (GJMBR Volume 20 Issue B10): .

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Submission ReceivedNovember 5, 2020
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