Editor-In-Chief Chair Dr. Shiv Kumar

Ph.D. (CSE), M.Tech. (IT, Honors), B.Tech. (IT), Senior Member of IEEE, Member of the Elsevier Advisory Panel

CEO, Blue Eyes Intelligence Engineering & Sciences Publication, Bhopal (M.P.), India

Additional Director, Technocrats Institute of Technology and Science, Bhopal (MP), India

Associated Editor-In-Chief Members Dr. Hitesh Kumar

Ph.D.(ME), M.E.(ME), B.E. (ME)

Professor and Head, Department of Mechanical Engineering, Technocrats Institute of Technology, Bhopal (MP), India

Dr. Gamal Abd El-Nasser Ahmed Mohamed Said

Ph.D(CSE), MS(CSE), BSc(EE)

Department of Computer and Information Technology , Port Training Institute, Arab Academy for Science, Technology and Maritime

Transport, Egypt

Associated Editor-In-Chief Members Dr. Mayank Singh

PDF (Purs), Ph.D(CSE), ME(Software Engineering), BE(CSE), SMACM, MIEEE, LMCSI, SMIACSIT

Department of Electrical, Electronic and Computer Engineering, School of Engineering, Howard College, University of KwaZulu-

Natal, Durban, South Africa.

Scientific Editors Prof. (Dr.) Hamid Saremi

Vice Chancellor of Islamic Azad University of Iran, Quchan Branch, Quchan-Iran

Dr. Moinuddin Sarker

Vice President of Research & Development, Head of Science Team, Natural State Research, Inc., 37 Brown House Road (2nd Floor)

Stamford, USA.

Dr. Fadiya Samson Oluwaseun

Assistant Professor, Girne American University, as a Lecturer & International Admission Officer (African Region) Girne, Northern

Cyprus, Turkey.

Dr. Robert Brian Smith

International Development Assistance Consultant, Department of AEC Consultants Pty Ltd, AEC Consultants Pty Ltd, Macquarie Centre, North Ryde, New South Wales, Australia

Dr. Durgesh Mishra

Professor (CSE) and Director, Microsoft Innovation Centre, Sri Aurobindo Institute of Technology, Indore, Madhya Pradesh India

Executive Editor Dr. Deepak Garg

Professor, Department Of Computer Science And Engineering, Bennett University, Times Group, Greater Noida (UP), India

Executive Editor Members Dr. Vahid Nourani

Professor, Faculty of Civil Engineering, University of Tabriz, Iran.

Dr. Saber Mohamed Abd-Allah

Associate Professor, Department of Biochemistry, Shanghai Institute of Biochemistry and Cell Biology, Shanghai, China.

Dr. Xiaoguang Yue

Associate Professor, Department of Computer and Information, Southwest Forestry University, Kunming (Yunnan), China.

Dr. Labib Francis Gergis Rofaiel

Associate Professor, Department of Digital Communications and Electronics, Misr Academy for Engineering and Technology,

Mansoura, Egypt.

Dr. Hugo A.F.A. Santos

ICES, Institute for Computational Engineering and Sciences, The University of Texas, Austin, USA.

Dr. Sunandan Bhunia

Associate Professor & Head, Department of Electronics & Communication Engineering, Haldia Institute of Technology, Haldia

(Bengal), India.

Technical Program Committee Dr. Mohd. Nazri Ismail

Associate Professor, Department of System and Networking, University of Kuala (UniKL), Kuala Lumpur, Malaysia.

Technical Program Committee Members Dr. Haw Su Cheng

Faculty of Information Technology, Multimedia University (MMU), Jalan Multimedia (Cyberjaya), Malaysia.

Dr. Hasan. A. M Al Dabbas

Chairperson, Vice Dean Faculty of Engineering, Department of Mechanical Engineering, Philadelphia University, Amman, Jordan.

Dr. Gabil Adilov

Professor, Department of Mathematics, Akdeniz University, Konyaaltı/Antalya, Turkey.

Manager Chair Mr. Jitendra Kumar Sen

Blue Eyes Intelligence Engineering & Sciences Publication, Bhopal (M.P.), India

Editorial Chair Dr. Arun Murlidhar Ingle

Director, Padmashree Dr. Vithalrao Vikhe Patil Foundation’s Institute of Business Management and Rural Development, Ahmednagar

(Maharashtra) India.

Editorial Members Dr. J. Gladson Maria Britto

Professor, Department of Computer Science & Engineering, Malla Reddy College of Engineering, Secunderabad (Telangana), India.

Dr. Wameedh Riyadh Abdul-Adheem

Academic Lecturer, Almamoon University College/Engineering of Electrical Power Techniques, Baghdad, Iraq

Dr. S. Brilly Sangeetha

Associate Professor & Principal, Department of Computer Science and Engineering, IES College of Engineering, Thrissur (Kerala),

India

Dr. Issa Atoum

Assistant Professor, Chairman of Software Engineering, Faculty of Information Technology, The World Islamic Sciences & Education University, Amman- Jordan

Dr. Umar Lawal Aliyu

Lecturer, Department of Management, Texila American University Guyana USA.

Dr. K. Kannan

Professor & Head, Department of IT, Adhiparasakthi College of Engineering, Kalavai, Vellore, (Tamilnadu), India

Dr. Mohammad Mahdi Mansouri

Associate Professor, Department of High Voltage Substation Design & Development, Yazd Regional Electric Co., Yazd Province,

Iran.

Dr. Kaushik Pal

Youngest Scientist Faculty Fellow (Independent Researcher), (Physicist & Nano Technologist), Suite.108 Wuhan University, Hubei,

Republic of China.

Dr. Wan Aezwani Wan Abu Bakar

Lecturer, Faculty of Informatics & Computing, Universiti Sultan Zainal Abidin (Uni SZA), Terengganu, Malaysia.

Dr. P. Sumitra

Professor, Vivekanandha College of Arts and Sciences for Women (Autonomous), Elayampalayam, Namakkal (DT), Tiruchengode

(Tamil Nadu), India.

Dr. S. Devikala Rameshbabu

Principal & Professor, Department of Electronics and Electrical Engineering, Bharath College of Engineering and Technology for

Women Kadapa, (Andra Pradesh), India.

Dr. V. Lakshman Narayana

Associate Professor, Department of Computer Science and Engineering, Vignan’s Nirula Institute of Technology & Science for

women, Guntur, (Andra Pradesh), India.

S. No

Volume-8 Issue-6S4, November 2019, ISSN: 2249-8958(Online)

Published By: Blue Eyes Intelligence Engineering & Sciences Publication

Page No.

1.

Authors: Himani Sivaraman, Amit Gupta, Omdeep Gupta

Paper Title: Big Data in the Field of Logistics: A Retrospective Manner to Resolve

Abstract: Big data a term created a huge change in the under currentan upcoming revolutionizing supply chain

industry. The data is the new oil and gas for the modern word SCM has also not left untouched with its Midas

touch . The upcoming techniques of making decision to upgrade the profitability and data reverences. The

algorithms of big data and its analytical excellence tools helped making better decisions to the upper hand decision

maker and researchers. The situation of dealing a humongous and heterogenous data has been changed by these

techniques . The old school SCM methods have taken a back seat in dealing these data sources. This paper is in

advocacy of the present day techniques and create a path way to the explore the possibilities of the success of the

big data solutions

Keyword: Supply Chain Management, Information Systems, Big data, analytics, data science, References: 1. Jens Leveling, Matthias Edelbrock, Boris Otto,” Big Data Analytics for Supply Chain Management”, 12 March 2015, 2014 IEEE

International Conference on Industrial Engineering and Engineering Management 978-1-4799-6410-9

2. Matthew A. Waller and Stanley E. Fawcett, Data Science, Predictive Analytics, and Big Data: A Revolution That Will Transform Supply Chain Design and Management”, Journal of Business Logistics, 2013, 34(2): 77–84 Council of Supply Chain Management Professionals.

3. Anoop Kumar Sahu, Saurav Datta, S.S. Mahapatra. "Evaluation of performance index inresilient supply chain: a fuzzy-based approach",Benchmarking: An International Journal, 2017

4. Ivan Varela Rozados, Benny Tjahjono, “Big Data Analytics In Supply Chain Management:Trends And Related Research”, 6th International Conference on Operations and Supply Chain Management, Bali, 2014

5. Smart Service Welt Working Group, “Smart Service Welt:Recommendations for the Strategic Initiative Web-based Services for Businesses”, acatech, Berlin, 2014.

6. M.Jeseke, M. Grüner, F. Wieß, "BIG DATA IN LOGISTICS: A DHL perspective on how to move beyond the hype", DHL Customer Solutions & Innovation, 12.2013

7. S. Robak, B. Franczyk, M. Robak, “Applying big data and linked data concepts in supply chains management,” 2013 Federated

Conference on Computer Science andInformation Systems (FedCSIS), pp. 1215 – 1221, 201

8. A. Katal, M. Wazid, R. H. Goudar, “big data: Issues, Challenges, Tools and Good Practices”, IEEE Sixth International Conference on

Contemporary Computing (IC3), pp. 404-409 , 08.2013

9. S. Ghemawat, H. Gobioff, S.T. Leung, “The Google File System”, ACM SIGOPS Operating Systems Review, ACM, pp. 29-43, 08.2003

10. T. Berners-Lee, et al., “W3C Semantic Web Activity” [Online]. Available: http://www.w3.org/2001/sw, 2001

11. Sanders, N. R. (2014). Big Data Driven Supply Chain Management: A Framework for Implementing Analytics and Turning Information

into Intelligence, 1st Ed, Pearson, NJ

1-3

2.

Authors: Singh N, Dhyani A., Nainwal P., Lall S., Vijay Kumar

Paper Title: How am I able to protect myself from Counterfeit Drugs

Abstract: The market of pharmaceuticals is increasing day by day due to continuous increase in population as

well asnumber of diseases. Medicines available freely in the market without prescription are creating serious

problems for the health of people. Substandard medicines have raised a major problem globally due to lack of

prompt regulatory intervention both in developed and developing countries. These medicines have an easier access

to the distribution system. Regular consumption of counterfeit drugs can lead to adverse effect to patients and even

death. Public awareness is necessaryto avoid the use of spurious drugs. The present study provides brief overview

of counterfeit medicine and their effect on public health.

Keyword: Counterfeit, Spurious, Trade, Health, Awareness References: 1. Available at: http://www.who.int/medicines/publications.

2. Sagar BPS, Zafar R, Singh A., Health Administrator, 2006, 19(1): 65-73.

3. Newton PN, Green MD, Fernandez FM, Day NP.,Lancet, 2006, 6(9):602-613.

4. Gupta P, Singhal K, Pandey A.,Int. J Pharm. Sci Res., 2012, 3(11):4057-4064.

5. Ambroise Thomas P, The tragedy caused by fake antimalarial drugs. Mediterranean Journal of Haematology and Infectious

Diseases,2012, 4(1). PMID: 22708042

6. Verma S, Kumar R, Philip P J.,The Business of Counterfeit Drug in India, A Critical Evaluation, 2014, 4(2): 141-148.

7. Clark C, Pharm J. 2003, 271:453.

8. Khan A, Khar R. Indian J Pharm Sci., 2015; 77 (1):2-7.

9. Available at http://www.thehealthsite.com/news/Kashmir-fake-drug-scam-were-spurious-drug-responsible for high infantdeath.

10. Available at http://www.policynetwork.net/sites/default/files/IPNCounterfeit.

11. Available at http://www.modernghana.com/news.

12. Kumar R, Int. J. Pharm. Tech. Res., 2014, 6(2):720.

13. Available at http://www.mhra.gov.uk/Publication/Safetywarnings/Drug alerts .

14. Available at http://www.app1.fda.gov/for consumers/Protect yourself/HealthFraud.htm

15. Available at http:// www.fiercepharma.com/story/feds-nail-key-player-counterfeit-avastin-probe.

16. Available at http://www.cnbc.com/id/44759526.

17. Jain SK, Health Administrator, 2006, 19(1):29-40.

18. Available at http://www.hinduonnet.com/thehindu/seta.

4-5

http://www.who.int/medicines/publicationshttps://www.ncbi.nlm.nih.gov/pubmed/22708042http://www.thehealthsite.com/news/Kashmir-fake-drug-scam-were-spurious-drug-responsiblehttp://www.policynetwork.net/sites/default/files/IPNCounterfeithttp://www.modernghana.com/newshttp://www.mhra.gov.uk/Publication/Safetywarnings/Drug%20alerts/http://www.app1.fda.gov/for%20consumers/Protect%20yourself/HealthFraud.htmhttp://www.fiercepharma.com/story/feds-nail-key-player-counterfeit-avastin-probehttp://www.cnbc.com/id/44759526http://www.hinduonnet.com/thehindu/seta

19. Buowari O,Afrimedic J., 2012, 3(2):1-4.

20. BlackstoneEA,Joseph P, PociaskS, The Health and Economic Effects of Counterfeit Drugs,2014, 7(4): 216–224.

21. Chandna H,Representational image-ThePrint.in, 27 April, 2019, 3:39 pm IST.

22. "Fake drugs constitute 25% of domestic medicines market in India: ASSOCHAM", Retrieved June 5, 2017.

23. Ramalakshmi in New Delhi, Washington Post 11 Sep 2010. Available from: https://www.pressreader.com/usa/the-washington-

post/20100911/28840705498.

3.

Authors: Navin Garg, Amit Gupta

Paper Title: Edge Computing – “An Enabling Technology for Industrial IoT (IIoT) Devices” – Exploring Its

Challenges and Security Issues

Abstract: Internet of Things (IoT) is latest technology these days which generates high volume of data. Efficient

use of data analytics techniques on discrete data using Cloud Computing provides significant and precise

information. In view of the previously used applications, an application that is IoT enabled such as environmental

monitoring, application for navigation and smart healthcare systems being developed with different requirements

such as portability, fast and real-time response etc. However, the typical architecture of cloud system cannot fulfill

these requirements as the processing of the data being distributed across the world remotely from physical location

of installed IoT devices. Hence, the concept of edge computing emerged to perform data storage and processing

at the extreme end devices that is nearer to data collection sources than the cloud storage. This makes applications

computationally intelligent and location notified. But edge computing suffers from many challenges related to

security and privacy when it is been applied to data analytics in association with IoT devices. The literature

collected till date still deficient in detail review on the advancements in security and safe data analytics techniques

used in edge computing. This paper, first introduce the various concepts and characteristics related to edge

computing, and then we try to propose solutions for performing data analytics in a secured and efficient manner,

thereafter reviewing the underlying some security attacks in the field of edge computing. Based on our literature

survey, we have highlighted current open issues and some future research areas in this field

Keyword: IoT, Edge Computing, Cloud Computing

References:

1. Yuan Ai, Mugen Peng *, Kecheng Zhang: Edge computing technologies for Internet of Things: a primer:

https://doi.org/10.1016/j.dcan.2017.07.001 Received 24 April 2017; Received in revised form 28 June 2017; Accepted 2 July 2017

Available online 8 July 2017

2. M. Chiang, T. Zhang, Fog and IoT: an overview of research opportunities, IEEE Internet Things J. 3 (2016) 854–864.

3. A. Al-Fuqaha, M. Guizani, M. Mohammadi, M. Aledhari, M. Ayyash, Internet of things: a survey on enabling technologies, protocols,

and applications, IEEE Commun. Surv. Tutor. 17 (2015) 2347–2376.

4. N. Bizanis, F. Kuipers, SDN and virtualization solutions for the Internet of Things: a survey, IEEE Access. J. 4 (2016) 5591–5606.

5. Y. Mao, C. You, J. Zhang, K. Huang, K.B. Letaief, A Survey on Mobile Edge Computing: the Communication Perspective, 2017.

https://arxiv.org/abs/1701. 01090

6. Nokia Solutions and Networks, Increasing Mobile Operators' Value Proposition with Edge Computing, White Pap, 2013, pp. 1–6,

http://nsn.com/portfolio/liquid-net/ intelligent-broadband-management/liquid-applications.

7. S. Barbarossa, S. Sardellitti, P. Di Lorenzo, Communicating while computing: distributed mobile cloud computing over 5G

heterogeneous networks, IEEE Signal Process. Mag. 31 (2014) 45–55

8. P. Hu, H. Ning, T. Qiu, H. Song, Y. Wang, X. Yao, Security and privacy preservation scheme of face identification and resolution

framework using fog computing in internet of things, IEEE Internet Things J. (2017), 1–1.

6-8

4.

Authors: Shipra Gupta, Vijay Kumar, Jasmeet Kalra

Paper Title: Camel Research of Selected Pharmaceutical Industries

Abstract: The pharmaceutical industry is observed to have an unhampered growth and is anticipated to grow

supplemental a compound annual growth rate (CAGR) of 3-6% over the next five years. The worldwide

expenditure on medicines has crossed US $1.2 Trillion in 2018 and is expected to go over US $ 1.5 Trillion by

2023. The new product lift-offs, particularly the specialty range have been the major contributor in the growth

accomplishment. However, reforming per capita income, accelerating consciousness towards health, geriatric

population, elevated chronic ailments along with technological magnifications are significantly pitching towards

the growth accomplishment. The following economies have majorly pitched in towards the pharmaceuticals

expenditure in 2018: US (US $ 486 Billion), top five European markets (US $ 178 Billion), China (US $ 137

Billion), Japan (US $ 86 Billion).Looking at the trend it seems that the growth of the world-wide pharmaceutical

expenditure will majorly be moved by developed economies through innovatory products created using latest

technology. United States appears to remain a fairy godmother in the pharmaceutical industry. However, emerging

economies like Brazil, India, Russia (Tier 2 markets) and Tier 3 markets shall also confer to the growth process.

Their CAGR is projected to grow 5-8% through 2023 to reach US $ 355 – 385 Billion.

Keyword: Pharmaceutical Industries, capital adequacy, asset quality, management efficiency, earning quality,

liquidity position, ratios, performance

References:

1. Kumar S., Anjum B., and Nayyar S., (2012). Financing decisions: A study of pharmaceutical companies of India, International Journal

of Marketing, Financial Services & Management Research, 1(1), 14-28.

9-18

https://theprint.in/author/himani-chandna/http://www.downtoearth.org.in/news/fake-drugs-constitute-25-of-domestic-medicines-market-in-india-assocham-45393https://doi.org/10.1016/j.dcan.2017.07.001https://arxiv.org/abs/1701https://www.merriam-webster.com/dictionary/geriatric

2. Joseph G. & John A. Vernon. (2009). Financial risk of the Biotech Industry versus the Pharmaceutical Industry, Applied Health

Economics and Health Policy, 7, 155–165.

3. Licurse A., Barber E., Steve J., Cary G. (2010). The Impact of Disclosing Financial Ties in Research and Clinical Care A Systematic

Review, Health Care Reform, 170(8), 675-82.

4. David M. Studdert M. Mello M., Troyen A. B. (2004).Financial Conflicts of Interest in Physicians' Relationships with the

Pharmaceutical Industry , Self-Regulation in the Shadow of Federal Prosecution, Legal Issues in Medicine, 351, 1891-1900.

5. Bharathi K.,G.(2008). Intellectual capital and corporate performance in Indian pharmaceutical industry, Journal of Intellectual Capital,

9(4), 684-704.

6. Pal, K. and Soriya, S. (2012), IC performance of Indian pharmaceutical and textile industry, Journal of Intellectual Capital, 13 (1), 120-

137.

7. Garg, K. (2015). An empirical analysis of profitability position of selected private sector banks in India. Journal of Management Sciences

and Technology, 2 (3), 22-28.

8. Singh, A. K. (2015). An analysis of profitability position of private banks in India. International Journal of Scientific and Research

Publications , 5 (5), 1-11

9. Srinivasan, S. (2016). A Camel model analysis of Public,Private and Foreign Sector Banks in India. Pacific Business Review

International, 8 (9), 45-57.

10. Mishra S.K. and Aspal P.K (2013). A Camel Model Analysis of State Bank Group, World Journal of Social Sciences, 3(4), 36-55.

11. Bansal R. and Mohanty A. (2013). A Study on Financial Performance of Commercial Banks in India: Application of Camel Model, Al-

Barkaat Journal of Finance and Management, 5, 60-79.

12. Gupta R. (2014). An Analysis of Indian Public Sector Banks Using Camel Approach, IOSR Journal of Business and Management (IOSR-

JBM), 16(1), 94-102.

13. Kaur J., Kaur M. and Singh S. (2015). Financial performance analysis of selected public sector banks: A CAMEL model approach, I J A

B E R, 13(6), 4327-4348

14. Kaur J., Kaur H. V. (2016). Camel analysis of selected public sector banks, National Conference on Management, Information

Technology and Engineering (GJ-NatConMITE 2016) GIAN JYOTI E-JOURNAL, 6(3), 178-189.

15. Meena G. L. (2016). Financial Analysis of Select Banks Using Camel Approach a Study with Reference to Indian Banking Industry,

International Journal of Research and Scientific Innovation, 3(10), 30-35.

16. Muralidhara P., Lingam C. (2017). Camel Model as an Effective Measure of Financial Performance of Nationalised Banks, International

Journal of Pure and Applied Mathematics, 117(7), 255-262.

17. Panboli S., Birda K. (2019). Camel Research of Selected Private and Public Sector Banks in India, International Journal of Innovative

Technology and Exploring Engineering, 8(12), 25-35.

18. Kiran K. (2018). A CAMEL Model Analysis of Selected Public and Private Sector Banks in India, International Journal of Management,

IT & Engineering, 8 ( 8), 125-132.

19. Kumar V. and Malhotra B. (2017). A Camel Model Analysis Of Private Banks In India, EPRA International Journal of Economic and

Business Review, 5(7), 80-89.

20. Zafar, S.M, Adeel M., and Ali N. (2012). A study of ten Indian commercial bank‘s financial performance using CAMELS methodology,

IMS Manthan, 7(1), 1-14.

21. Pati K., kumar A. and Murty, A. V. N. (2017). Financial Performance of Selected Public and Private Sector Banks Based on CAMEL

Model with Reference to Indian Banking Sector, International Journal in Management and Social Science, 5(4), 23-29.

22. Balaji C. H., Kumar P. (2017). Performance evaluation of selected public & private sector banks in India: an application of camel model‖,

International Journal of Research in IT and Management, 7(3), 62-70.

23. Kaur M. and Priya R. (2017). Evaluating the performance of Public sector Banks―Bank of Baroda and Punjab National Bank: An

Application of CAMEL Model with capital and Earning Parameter, Asian Journal of Research in Business Economics and Management,

7(5), 258- 270.

24. Waleed A., Shah M. B., Mughal M. K. (2015), Comparison of Private and Public Banks Performance, IOSR Journal of Business and

Management, 17( 7)., 32-38.

25. Karthikeyan P., Shangari B. (2014). Calibrating Financial Soundness Among Selected Private Sector Banks In India By Using Camel

Model, International Journal Of Management Research And Review, 4(4), 449-454.

26. Biswas M. (2014). Performance Evaluation of Andhra Bank & Bank Of Maharashtra With Camel Model, International Journal of

Business and Administration Research Review, 1(5), 125-131.

27. Suba N. R., Jogi K. P. (2015), Evaluating Performance of Private Sector Banks HDFC & ICICI: An Application of Camel Model with

Capital & Earning Parameter, RESEARCH HUB-International Multidisciplinary Research Journal, 2(5), 1-5.

28. Lakhtaria N. J. (2013). A Comparative Study of the Selected Public Sector Banks through Camel Model, Indian Journal of Research, 2(

4), 112-119.

5.

Authors: Vijay Kumar, Archana Dhyani, N Singh

Paper Title: Deuteration as a Tool for Enhancing the Half-Life of Drug

Abstract: The aim of the article is that deuteration of any compounds leads to the enhancement of metabolic

activity.The substitution of Carbon-Hydrogen bond by Carbon –Deutrieum help for enhancing pharmacokinetic

profile of the drug. Since C-D bond is ten time more tough to C-H bond .Nowadays, many drug molecules are

deuterated to increase the residence time of the drug as well as diminution the metabolism of the drug.Deuterated

drugs also finds various therapeutic applications.The deuterated drugs is also approved by Food and Drug

Administration. The deuteration helps in increasing the dwell time of the drug and reducing frequency of dosing.

Keyword: Deuteration, half- life, pharmacokinetics, therapeutic effects

References:

1. Jing Chen , Xiaofang Luo , HuiminQiu, Vienna Mackey, Lichun Sun, Xiaoping OuyangM, Drug discovery and drug marketing with the

critical roles of modern administration, Am J Transl Res 2018;10(12):4302-4312.

2. Benedict, M., Pigford, T.H., and Levi, H.W. ,Nuclear chemical engineering. 2nd ed. McGraw-Hill, New York,1981:1008.

3. 3.Katz, J.J. 1960. The biology of heavy water. Sci. Am. 203: 106–115.

4. Chauhan P. 2016. Heavy water: alternative applications in biology, medicine and industry.

5. Chauhan P. 2016. Heavy water: alternative applications in biology, medicine and industry .

6. Edward M. Russak,Edward M. Bednarczyk, Impact of Deuterium Substitution on the Pharmacokinetics of Pharmaceuticals, Annals of

Pharmacotherapy1–6, 2018.

19-20

https://link.springer.com/journal/40258https://link.springer.com/journal/40258https://www.emerald.com/insight/search?q=G.%20Bharathi%20Kamathhttps://www.emerald.com/insight/publication/issn/1469-1930https://www.emerald.com/insight/search?q=Karam%20Palhttps://www.emerald.com/insight/search?q=Sushila%20Soriyahttps://www.emerald.com/insight/publication/issn/1469-1930

7. Graham S Timmins,Deuterated drugs; where are we now?,Expert OpinTher Pat. 2014 October ; 24(10): 1067–1075.

8. Scott L. Harbeson, Roger D. Tung, Deuterium Medicinal Chemistry: A New Approach to Drug Discovery and Development,Medchem

News No.2 ,2014:8-22

9. Anwen M. Krause-Heuer, Nageshwar R. Yepuri, Tamim A. Darwishand Peter J. Holden, Mild Conditions for Deuteration of Primary

and Secondary Arylamines for the Synthesis of Deuterated Optoelectronic Organic Molecules, Molecules 2014, 19, 18604-18617.

10. Robert B. Raffa,Joseph V. Pergolizzi1, Robert Taylor, The First Approved “Deuterated” Drug: A ShortReview of the Concept,

Pharmacology & Pharmacy, 2018, 9, 440-446.

11. Sarah Cargnin1, Marta Serafini& Tracey Pirali, A primer of deuterium in drug design,FutureMed. Chem. 2019,11(16), 2039–2042

12. Sukhninder Kaur and Monika Gupta,Deuteration as a Tool for Optimization of Metabolic Stability and Toxicity of Drugs,Global journal

ofPharmacy & pharmaceutical Science, 1(4) 2017,1-11

13. Cuibo Liu, Zhongxin Chen, Chenliang Su, Xiaoxu Zhao, QiangGao,Controllabledeuteration of

halogenated compounds by photocatalytic D2O splitting, Nature Communications ,(2018) 9:80 14. Raman Sharma, Timothy J. Strelevitz, Hongying Gao, Alan J. Clark, KlaasSchildknegt, R. Scott Obach, Sharon L. Ripp, Douglas K.

Spracklin, Larry M. Tremaine, and Alfin D. N. Vaz, Deuterium Isotope Effects on Drug PharmacokineticsSystemDependent Effects of

Specific Deuteration with Aldehyde Oxidase Cleared Drugs,Drug Metabolism And Disposition,2017,4(3):625-634

15. Maicon Guerra de Miranda, Andre Luis Mazzei Albert, JariNobrega Cardoso,RosangelaSabbatini Capella Lopes,ClaudioCerqueira

Lopes, Straightforward synthesis of 2,2,4,4,5,7,7-d7-cholestane: a new deuterated standard in petroleum analysis,Quim. Nova, 2013,

36(8), 1160-1163.

16. Yanmei Zhang, Micky D. Tortorella,Yican Wang,

JianqiLiu,ZhengchaoTu,XiaorongLiu,YangBai,DingshengWen,XinLu,YongzhiLu,and John J. Talley, Synthesis of Deuterated

Benzopyran Derivatives as Selective COX-2 Inhibitors with Improved Pharmacokinetic Properties, ACS Medicinal Chemistry Letters,

2014, 5, 1162−1166.

17. JinfangJiang,XuehaiPang,Liang Li , XiaojianDai,XingxingDiao, Xiaoyan Chen, DafangZhong,Yingwei Wang, Yuanwei Chen, Effect of

N-methyl deuteration on metabolism and pharmacokinetics of enzalutamide, Drug Design, Development and Therapy 2016:10 2181–

2191.

6.

Authors: Archana Dhyani, Nardev singh, Vijay kumar

Paper Title: Formulation and Evaluation of Herbal Shampoo Containing Extract of Grewia Optiva

Abstract: Synthetic shampoos are responsible for undesirable properties among customers. An additional

method used to decrease the use of artificial components is by adding natural component. of Grewia optiva bark

was selected on the basis of its surfactant property. The aim of this research is to formulate a hair shampoo with

Grewia optiva bark with importance on protection and efficiency. The formulation was evaluated for different

parameters. It was found that the product has good foaming capacity and capable of reduction of surface tension .

Keyword: Shampoo, Grewia optiva, surfactant, surface tension, cleansing action.

References:

1. Bouillon C. Shampoos. Clin Dermatol 1996;14:113-21.

2. M.K. Ishii,Objective and instrumental methods for evaluation of hair care product efficacy and substantiation of claims,Hair and hair

care, Marcel Dekker, Inc, New York (1997),261-302

3. Robbins CR, Interaction of shampoo and cream rinse ingredients with human hair, Chemical and physical behavior of human hair,2nd

ed. New York: Springer-Verlag; 1988: 193.

4. Mohammad Azadbakht, Taha Monadi1, Zahra Esmaeili, Aroona Chabra, Naser Tavakoli, Formulation and Evaluation of Licorice

Shampoo in Comparison with Commercial Shampoo,Journal of Pharmacy and Bioallied Sciences ¦ Volume 10 ¦ Issue 4 2018:208-215

5. Riham O. Bakr, Reham I. Amer, Marwa A. A. Fayed, Tamer I. M. Ragab, A Completely Polyherbal Conditioning and Antioxidant

Shampoo:A Phytochemical Study and Pharmaceutical Evaluation,Pharmacy and Bioallied Sciences,11(2) 2019 :105-115

6. Potluri, S.S.K. Asma, N. Rallapally, S. Durrivel, G.A. HarishReview on herbs used in Anti-dandruff shampoo and its evaluation

parameters, Indo Am J Pharm Res, 3 (4) (2013), pp. 3266-3278)

7. Bushra T.,AlQuadeib,Rana, A.Banafa,Lama A.,Al-Hadhairi,Pharmaceutical Evaluation Of Different Shampoo Brands In Local Saudi

Market, Saudi Pharmaceutical Journal , 26(1), 2018: 98-106.

8. Mehta PC, Bhatt KC, Traditional soap & detergents yielding plants of Uttaranchal, Indian Journal of Traditional

knowledge,6(2),2007:279-284.

9. Shefali Arora, Antibacterial, antifungal, antioxidant and phytochemical study on the leaves extract of Grewia optiva, Journal

of Pharmacy Research 2011,4(9),3130-3132.

10. Rasha Saad Suliman , Heyam Ali , Intan Nurulain , Nik NurShamiha , Mohamad Nizam , Sri Budiasih, Cinnamon Bark

Extract For The Formulation And Characterisation Of Antimicrobial Cream, International journal of Ayurveda Research, 8

(2), 2017:1-17.

11. Aghel N., Moghimipour B. and Dana R.A., Iranian Journal of Pharmaceutical Research 2007, 6(3), 167-172.

12. Prajapati Sonu, Sharma Pragya, Mr. Raghvendra Dubey, Dr. Sumeet Dwivedi, Formulation And Evalution Of Two In One Herbal

Conditioning Shampoo Containing Extract Of Allium Cepa And Trigonella Foenum Graecum,World Journal of Pharmaceutical and Life

Sciences,2017, 3(2): 68-71

13. Akula Nikhil Prashant, Preparation And Evaluation Of Shampoo Powder Containing Herbal Ingredients, Asian J Pharm Clin Res, 8(1),

2015, 266-270.

18. Bushra T. AlQuadeib, Eram K.D. Eltahir,Rana A. Banafa, and Lama A. Al-Hadhairi, Pharmaceutical evaluation of different shampoo

brands in local Saudi market,Saudi Pharm J. 2018 ,26(1): 98–106.

19. Krunali T., Dhara P. Evaluation Of Standards Of Some Selected Shampoo Preparation. World J. Pharm. Pharm. Sci. 2013;2:3622–3630.

20. Kumar Ashok and Roshan Mali Rakesh, Evaluation Of Prepared Shampoo Formulations And To Compare Formulated Shampoo With

Marketed Shampoos, International Journal of Pharmaceutical Sciences Review and Research 3(1), 2010;:1-7.

21. Reddy V.Sarovar, Kumar Reddy D.Jeevan , Velu M.G, Formulation and Evaluation of Antidandruff Shampoo, Journal of Pharmacy

Research, 2016,10(11),700-702 .

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7.

Authors: S. Solanki, S. Wadhwa, S. Gupta

Paper Title: Digital Technology: An Influential Factor in Investment Decision Making

https://www.nature.com/articles/s41467-017-02551-8#auth-1https://www.nature.com/articles/s41467-017-02551-8#auth-2https://www.nature.com/articles/s41467-017-02551-8#auth-3https://www.nature.com/articles/s41467-017-02551-8#auth-4https://www.nature.com/articles/s41467-017-02551-8#auth-5https://www.sciencedirect.com/science/article/pii/S131901641730172X#!https://www.sciencedirect.com/science/article/pii/S131901641730172X#!https://www.sciencedirect.com/science/article/pii/S131901641730172X#!https://www.sciencedirect.com/science/journal/13190164/26/1https://www.ncbi.nlm.nih.gov/pubmed/?term=AlQuadeib%20BT%5BAuthor%5D&cauthor=true&cauthor_uid=29379340https://www.ncbi.nlm.nih.gov/pubmed/?term=Eltahir%20EK%5BAuthor%5D&cauthor=true&cauthor_uid=29379340https://www.ncbi.nlm.nih.gov/pubmed/?term=Banafa%20RA%5BAuthor%5D&cauthor=true&cauthor_uid=29379340https://www.ncbi.nlm.nih.gov/pubmed/?term=Al-Hadhairi%20LA%5BAuthor%5D&cauthor=true&cauthor_uid=29379340https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5783807/

Abstract: The purpose of this study is to present a conceptual framework for thinking about the role of digital

technology and highlights the factors which influence the investors to make the investment decision. Researchers

examined the change found in the behavior of individual investors before and after digitalization. Researchers

have also identified the various benefits which an investor derives from the use of digital technology as it’s an

open platform to compare available investment solutions, possibility of easy comparison of return, internet posting

to choose investment related options, self decision to make investment without human involvement which

showcase the influence of the information (available through internet via websites application) on the behavior of

an individual investor i.e. how does he react to particular information received (e.g. what impact internet posting

have on the decision of an investor). In addition to this, the use of digital technology has also changed the way of

presenting a piece of information to the investors to reach at investment conclusion.

Keyword: Digital technology, Investors, Investment Decision, Digitalization.

References:

1. Antweiler, W., and M.Z. Frank, (2004) Is all that talk just noise? The information content of Internet stock message boards, Journal of

Finance,59, 1259-1294.

2. Ammann, M., Schaub, N., (2017) The impact of internet postings on individual investors. In: proceedings American Finance Association 2018 Annual Meeting.

3. Assuli,O.B., (2012) Assessing the perception of information components in financial decision support system, Decision support system,54, 795-802.

4. Avery, C.N., J.A. Chevalier, and R.J. Zeckhauser, (2016) The "CAPS" prediction system and stock market returns, Review of Finance, 20, 1363-1381.

5. Barber, M.B ,& Odean, T.(2001). The Internet and the Investor, Journal of Economic Perspective. 15, pp. 41–54. 6. Barber, Brad M. and Terrance Odean. (2001) “Boys Will be Boys: Gender, Overconfidence, and Common Stock Investment,”

forthcoming Quarterly Journal of Economics.

7. Chen, H., D. Prabuddha, Y.J. Hu, and B.-H. Hwang, (2014) Wisdom of crowds: The value of stock opinions transmitted through social media, Review of Financial Studies, 27, 1367-1403.

8. Crawford, S.S., R.G. Wesley, and A.E. Kern, (2017) Why do fund managers identify and share profitable ideas?, Journal of Financial and Quantitative Analysis, forthcoming.

9. Courbon, J.C., J. Grajew and J. Tolovi, (1978) “Design and Implementation of Interactive 10. Decision Support Systems: An Evolutionary Approach,” Technical Report, Institute 11. d’Administration des Enterprises, Grenoble, France. 12. Das, S.R., and M.Y. Chen, (2007) Yahoo! for Amazon: Sentiment extraction from small talk 26 on the web, Management Science 53,

1375-1388.

13. Dawes, R.M., Rational Choice in an Uncertain World. Harcourt, 1988. 14. Dewally,M.,(2003) Internetinvestmentadvice: Investing with a rock of salt, Financial Analyst Journal, 59, 65-77 15. Druzdzel, M.J. & Flynn, R.R., (1999) Decision support systems. Encyclopedia of library and information science, Marcel Dekker, Inc.

Last Login.

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8.

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18, pp. 351–53.

20. Jung, M. J., Naughton, J. P., Tahoun, A., Wang, C., (2017) Do firms strategically disseminate? evidence from corporate use of social media. Forthcoming in the Accounting Review.

21. Keller, Kevin L. and Richard Staelin (1987) “Effects of Quality and Quantity of Information on Decision Effectiveness.” Journal of Consumer Research. 14, pp. 200–13.

22. Lehman, M.M., (1998) “Software’s Future,” IEEE Software, 40-44. 23. Mirsch, T.; Lehrer, C.; Jung, R. (2017): Digital Nudging: Altering User Behavior in Digital Environments, in Leimeister, J.M.; Brenner,

W. (Hrsg.): Proceedings der 13. International en Tagung Wirtschaftsinformatik (WI 2017), St. Gallen, S. 634-648

24. Oskamp, Stuart. (1965) “Overconfidence in Case-study Judgments.” Journal of Consulting Psychology. 29, pp. 261–65 25. Peterson, Dane K. and Gordon F. Pitz. (1988) “Confidence, Uncertainty, and the Use of Information.” Journal of Experimental

Psychology. 14, pp. 85–92.

26. Pompian, M. M. (2006). Behavioral Finance and Wealth Management. John Wiley & Sons Inc. 27. New Jersey. 28. Snow, N. M., Rasso, J., (2017) If the tweet fits: How investors process financial information received via social media. SSRN working

paper.

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pp.42-49

35. Weber, B. W (2008) Financial DSS: Systems for Supporting Investment Decisions. 36. Handbook on Decision Support Systems 2, pp. 419-442 37. Yang, W., Lin, D., Yi, Z., (2017) Impacts of the mass media effect on investor sentiment. 38. Finance Research Letters, 22, 1–4. 39. Zhou, M., Lei, L., Wang, J., Fan, W., Wang, A. G., (2014) Social media adoption and corporate disclosure. Journal of Information

Systems, 29 (2), 23–50.

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8.

Authors: Lisa Gopal, Samir Rana, Preeti Chaudhary, Vrince Vimal

Paper Title: Unsupervised Methods for Intrusion Detection Systems and Forensic Examination

Abstract: Crime is increasing with the widespread growth of digital world. The last decade has witnessed the

elevation in the diversity and frequency of malicious usage of the network. Forensic investigators play a paramount

role in the investigation based upon collection and analysis of facts from the crime scene. Intrusion Detection

Systems, which are in use till date do not enlighten the trends in attack as they are built on various outmoded attack

classes. IDSs that uses unsupervised techniques has been discussed in the literature. It is based on the requirement

of labelled data as it is required in regular training or on the characteristics that elaborates each class without any

knowledge in the prior. Despite of being widely popular among researchers and mammoth practical applications,

fidelity of IDS Is yet debatable. This paper provides an exhaustive survey of the various unsupervised anomaly-

based intrusion detection techniques and their potential usage in their respectivedomain.

Keyword: Forensic, IDS, Unsupervised Methods, Attacks.

References:

1. A Nisioti, A Mylonas , P D. Yoo,, and V Katos,” From Intrusion Detection to Attacker Attribution: A Comprehensive Survey of

Unsupervised Methods”, IEEE Communications Surveys & Tutorials, Vol. 20, No. 4, Fourth Quarter 2018.

2. E. Vasilomanolakis, S. Karuppayah, M. Mühlhäuser, and M. Fischer, “Taxonomy and survey of collaborative intrusion detection,” ACM

Comput. Surveys, vol. 47, no. 4, p. 55, 2015.

3. “State of the Internet, Q1 2017 report,” Akamai, Cambridge, MA, USA, Rep., 2017. [Online].Available: https://www.akamai.com/fr/

fr/multimedia/documents/state-of-the-internet/q1-2017-state-of-theinternet-connectivity-report.pdf.

4. M. A. Qadeer, A. Iqbal, M. Zahid, and M. R. Siddiqui, “Network traffic analysis and intrusion detection using packet sniffer,” in Proc.

IEEE 2nd Int. Conf. Commun. Softw. Netw. (ICCSN), Singapore, Feb. 2010, pp. 13–317.

5. A. Fahad, Z. Tari, I. Khalil, A. Almalawi, and A. Y. Zomaya, “An optimal and stable feature selection approach for traffic classification

based on multi-criterion fusion,” Future Gener. Comput. Syst., vol. 36, pp. 156–169, Jul. 2014.

6. M. H. Bhuyan, D. K. Bhattacharyya, and J. K. Kalita, “A multi-step outlier-based anomaly detection approach to network-wide traffic,”

Inf. Sci., vol. 348, pp. 243–271, Jun. 2016.

7. K. A. P. Costa et al., “A nature-inspired approach to speed up optimum-path forest clustering and its application to intrusion detection

in computer networks,” Inf. Sci., vol. 294, pp. 95–108, Feb. 2015.

8. H. Bostani and M. Sheikhan, “Modification of supervised OPF-based intrusion detection systems using unsupervised learning and social

network concept,” Pattern Recognit., vol. 62, pp. 56–72, Feb. 2017.

9. F. Hosseinpour, P. V. Amoli, F. Farahnakian, J. Plosila, and T. Hämäläinen, “Artificial immune system-based intrusion detection: Innate

immunity using an unsupervised learning approach,” Int. J. Digit. Content Technol. Appl., vol. 8, no. 5, p. 1, 2014.

10. W.-C. Lin, S.-W. Ke, and C.-F. Tsai, “CANN: An intrusion detection system based on combining cluster centers and nearest neighbors,”

Knowl. Based Syst., vol. 78, pp. 13–21, Apr. 2015.

11. I. Aljarah and S. A. Ludwig, “MapReduce intrusion detection system based on a particle swarm optimization clustering algorithm,” in

Proc. IEEE Congr. Evol. Comput., Jun. 2013, pp. 955–962.

12. R. A. R. Ashfaq, X.-Z. Wang, J. Z. Huang, H. Abbas, and Y.-L. He, “Fuzziness based semi-supervised learning approach for intrusion

detection system,” Inf. Sci., vol. 378, pp. 484–497, Feb. 2017.

13. Z. Mingqiang, H. Hui, and W. Qian,“A Graph-based clustering algorithm for anomaly intrusion detection,” in Proc. IEEE 7th Int. Conf.

Comput. Sci. Educ. (ICCSE), Melbourne, VIC, Australia, Jul. 2012, pp. 1311–1314.

14. A. Bohara, U. Thakore, and W. H. Sanders, “Intrusion detection in enterprise systems by combining and clustering diverse monitor

data,” in Proc. ACM Symp. Bootcamp Sci. Security. Pittsburgh, PA, USA, Apr. 2016, pp. 7–16.

15. J. Song, H. Takakura, Y. Okabe, and K. Nakao, “Toward a more practical unsupervised anomaly detection system,” Inf. Sci., vol. 231,

pp. 4–14, May 2013.

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9.

Authors: Kshitij Kala, Sandeep Kumar Budhani, Rajendra Singh Bisht, Dhanuli Kokil Bisht, Kuljinder Singh

Bumrah

Paper Title: A Novel Sorting Method for Real and Integer Numbers: An Extension of Counting Sort

Abstract: Sorting is an essential conceptin the study of data structures. There are many sorting algorithms

that can sort elements in a given array or list. Counting sort is a sorting algorithm that has the best time complexity.

However, the counting sort algorithm only works for positive integers. In this paper, an extension of the counting

sort algorithm is proposed that can sort real numbers and integers (both positive and negative).

Keyword: Counting Sort, Sorting, Algorithm.

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