Saturday, 6 June 2020

Nader Ale Ebrahim's publications list on SSRN

Source: https://papers.ssrn.com

Nader Ale Ebrahim

Centre for Research Services, Institute of Management and Research Services (IPPP), University of Malaya (UM)

Visiting Research Fellow

Kuala Lumpur, Wilayah Persekutuan 50603

University of Malaya (UM)

Kuala Lumpur, Wilayah Persekutuan 50603

Malaysia

http://https://umresearch.um.edu.my/

University of Malaya (UM) - Department of Engineering Design and Manufacture

Kuala Lumpur, 50603

Malaysia

SCHOLARLY PAPERS

102

DOWNLOADS

35,207

SSRN CITATIONS

52

CROSSREF CITATIONS

179

Ideas:

“ Publishing a research paper is the beginning of research impact and visibility life cycle. "Research Tools" help the researchers to spend their time on discovery instead of the search. ”

(Rank)

Virtual Teams: A Literature Review

Australian Journal of Basic and Applied Sciences, Vol. 3, No. 3, pp. 2653-2669, 2009

Number of pages: 17 Posted: 07 Nov 2009

Nader Ale Ebrahim, Shamsuddin Ahmed and Zahari Taha

Downloads 5,252 (1,520)

Citation 1

Effective Strategies for Increasing Citation Frequency

International Education Studies, Vol. 6, No. 11, pp. 93-99, 2013

Number of pages: 7 Posted: 25 Oct 2013

Nader Ale Ebrahim, Hadi Salehi, Mohamed Amin Embi, Farid Habibi, Hossein Gholizadeh, Seyed Mohammad Motahar and Ali Ordi

Centre for Research Services, Institute of Management and Research Services (IPPP), University of Malaya (UM)University of Malaya (UM) - Department of Engineering Design and Manufacture, Islamic Azad University, Najafabad Branch, Universiti Kebangsaan Malaysia - Faculty of Education, University of Economic Sciences, University of Ottawa, Ottawa Hospital Research Institute, Universiti Kebangsaan Malaysia - Faculty of Information Science and Technology and Universiti Teknologi Malaysia - Advance Informatics School (AIS)

Downloads 4,239 (2,245)

Citation 1

A Comparison between Two Main Academic Literature Collections: Web of Science and Scopus Databases

Asian Social Science, Vol. 9, No. 5, pp. 18-26, April 27, 2013

Number of pages: 9 Posted: 29 Apr 2013 Last Revised: 09 May 2013

Arezoo Aghaei Chadegani, Hadi Salehi, Melor Yunus, Hadi Farhadi, Masood Fooladi, Maryam Farhadi and Nader Ale Ebrahim

Islamic Azad University, Islamic Azad University, Najafabad Branch, National University of Malaysia - Faculty of Education, National University of Malaysia (UKM) - Research Center for Islamic Economics and Finance (EKONIS-UKM), Islamic Azad University, Mobarakeh Branch, National University of Malaysia (UKM) and Centre for Research Services, Institute of Management and Research Services (IPPP), University of Malaya (UM)University of Malaya (UM) - Department of Engineering Design and Manufacture

Downloads 2,147 (7,054)

Citation 2

Virtual R&D Teams in Small and Medium Enterprises: A Literature Review

Scientific Research and Essays, Vol. 4, No. 13, pp. 1575–1590, December 2009

Number of pages: 16 Posted: 05 Jan 2010 Last Revised: 19 Jun 2014

Nader Ale Ebrahim, Shamsuddin Ahmed and Zahari Taha

Downloads 1,650 (10,971)

Citation 1

Introduction to the Research Tools Mind Map

Research World, Vol. 10, No. 4, pp. 1-3,

Number of pages: 3 Posted: 17 Jun 2013

Nader Ale Ebrahim

Centre for Research Services, Institute of Management and Research Services (IPPP), University of Malaya (UM)University of Malaya (UM) - Department of Engineering Design and Manufacture

Downloads 1,090 (20,682)

Ethical and Unethical Methods of Plagiarism Prevention in Academic Writing

International Education Studies, vol. 7, no. 7, pp. 52-62, 2014

Number of pages: 11 Posted: 24 Jun 2014

Kaveh Bakhtiyari, Hadi Salehi, Mohamed Amin Embi, Masoud Shakiba, Azam Zavvari, Masoomeh Shahbazi-Moghadam, Nader Ale Ebrahim and Marjan Mohammadjafari

University of Duisburg-Essen, Islamic Azad University, Najafabad Branch, Universiti Kebangsaan Malaysia - Faculty of Education, National University of Malaysia (UKM), National University of Malaysia (UKM), Universiti Teknologi MARA (UiTM), Centre for Research Services, Institute of Management and Research Services (IPPP), University of Malaya (UM)University of Malaya (UM) - Department of Engineering Design and Manufacture and University of Malaya (UM)

Downloads 1,028 (22,584)

Virtual Teams and Management Challenges

Downloads 767 ( 34,331)

SMEs; Virtual Research and Development (R&D) Teams and New Product Development: A Literature Review

International Journal of the Physical Sciences, Vol. 5, No. 7, pp. 916-930, July 2010

Number of pages: 15 Posted: 10 Sep 2010

Nader Ale Ebrahim, Shamsuddin Ahmed and Zahari Taha

Downloads 736 (36,303)

Visibility and Citation Impact

International Education Studies, Vol. 7, No. 4, pp. 120-125, 2014

Number of pages: 6 Posted: 03 Apr 2014

Nader Ale Ebrahim, Hadi Salehi, Mohamed Amin Embi, Farid Habibi, Hossein Gholizadeh and Seyed Mohammad Motahar

Centre for Research Services, Institute of Management and Research Services (IPPP), University of Malaya (UM)University of Malaya (UM) - Department of Engineering Design and Manufacture, Islamic Azad University, Najafabad Branch, Universiti Kebangsaan Malaysia - Faculty of Education, University of Economic Sciences, University of Ottawa, Ottawa Hospital Research Institute and Universiti Kebangsaan Malaysia - Faculty of Information Science and Technology

Downloads 668 (41,297)

Citation 1

10.

Modified Stage-Gate: A Conceptual Model of Virtual Product Development Process

African Journal of Marketing Management, Vol. 1, No. 9, pp. 211-219, December 2009

Number of pages: 9 Posted: 16 Dec 2009 Last Revised: 01 Jul 2014

Nader Ale Ebrahim, Shamsuddin Ahmed and Zahari Taha

Downloads 666 (41,453)

Citation 1

11.

Virtual Teams for New Product Development: An Innovative Experience for R&D Engineers

European Journal of Educational Studies, Vol. 1, No. 3, pp. 109-123, October 2009

Number of pages: 15 Posted: 07 Nov 2009

Nader Ale Ebrahim, Shamsuddin Ahmed and Zahari Taha

Downloads 616 (45,997)

12.

Determinants of Foreign Direct Investment in Iran: An Empirical Study Using Structural Equation Modelling

Middle East FORUM, Vol. 1, Issue, 9, pp. 71-85, December 2009

Number of pages: 15 Posted: 14 Oct 2011

Ahmad Jafarnejad, Arash Golnam and Nader Ale Ebrahim

Faculty of Management, University of Tehran, The Society of Iranian Industries & Mines - Research & Development Centers and Centre for Research Services, Institute of Management and Research Services (IPPP), University of Malaya (UM)University of Malaya (UM) - Department of Engineering Design and Manufacture

Downloads 577 (50,127)

13.

Innovation and R&D Activities in Virtual Team

European Journal of Scientific Research, Vol. 34, No. 3, pp. 297-307, 2009

Number of pages: 11 Posted: 07 Nov 2009

Nader Ale Ebrahim, Shamsuddin Ahmed and Zahari Taha

Downloads 530 (55,766)

14.

Work Together...When Apart Challenges and What is Need for Effective Virtual Teams

Journal of Information, Knowledge and Research in Business Management and Administration, Vol. 1, No. 1, pp. 1-3, October 2010

Number of pages: 3 Posted: 23 Sep 2010

R. R. Raval, Nader Ale Ebrahim, Shamsuddin Ahmed and Zahari Taha

C. U. Shah College Of Engineering and Technology, Centre for Research Services, Institute of Management and Research Services (IPPP), University of Malaya (UM)University of Malaya (UM) - Department of Engineering Design and Manufacture, University of Malaya (UM) and University of Malaya (UM)

Downloads 427 (72,804)

15.

Critical Factors for New Product Developments in SMEs Virtual Team

African Journal of Business Management, Vol. 4, No. 11, pp. 2247-2257, September 4, 2010

Number of pages: 11 Posted: 09 Oct 2010

Nader Ale Ebrahim, Shamsuddin Ahmed and Zahari Taha

Downloads 423 (73,617)

16.

Supplier Assessment and Selection Using Fuzzy Analytic Hierarchy Process in a Steel Manufacturing Company

Journal of Scientific Research and Reports, vol. 3, no. 10, pp. 1319-1338, 2014

Number of pages: 20 Posted: 15 Apr 2014

Farzad Tahriri, Mohammad Dabbagh and Nader Ale Ebrahim

University of Malaya (UM) - Faculty of Engineering, University of Malaya (UM) - Faculty of Computer Science and Information Technology and Centre for Research Services, Institute of Management and Research Services (IPPP), University of Malaya (UM)University of Malaya (UM) - Department of Engineering Design and Manufacture

Downloads 394 (80,003)

17.

Virtual R&D Teams and SMEs Growth: A Comparative Study Between Iranian and Malaysian SMEs

African Journal of Business Management, Vol. 4, No. 11, pp. 2368-2379, September 2010

Number of pages: 12 Posted: 09 Oct 2010

Nader Ale Ebrahim, Shamsuddin Ahmed and Zahari Taha

Downloads 394 (80,003)

Citation 1

18.

Effective Virtual Teams for New Product Development

Scientific Research and Essay, 7(21), 1971-1985, June 2012

Number of pages: 15 Posted: 17 Jun 2012

Nader Ale Ebrahim, Shamsuddin Ahmed, Salwa Hanim Abdul Rashid and Zahari Taha

Centre for Research Services, Institute of Management and Research Services (IPPP), University of Malaya (UM)University of Malaya (UM) - Department of Engineering Design and Manufacture, University of Malaya (UM), University of Malaya (UM) - Department of Engineering Design and Manufacture and University Malaysia Pahang - Department of Manufacturing Engineering

Downloads 360 (88,818)

19.

Contribution of Information and Communication Technology (ICT) in Country’s H-Index

Journal of Theoretical and Applied Information Technology, vol. 57, no. 1, 10 November, 2013.

Number of pages: 6 Posted: 11 Nov 2013

Maryam Farhadi, Hadi Salehi, Mohamed Amin Embi, Masood Fooladi, Hadi Farhadi, Arezoo Aghaei Chadegani and Nader Ale Ebrahim

National University of Malaysia (UKM), Islamic Azad University, Najafabad Branch, Universiti Kebangsaan Malaysia - Faculty of Education, Islamic Azad University, Mobarakeh Branch, National University of Malaysia (UKM) - Research Center for Islamic Economics and Finance (EKONIS-UKM), Islamic Azad University and Centre for Research Services, Institute of Management and Research Services (IPPP), University of Malaya (UM)University of Malaya (UM) - Department of Engineering Design and Manufacture

Downloads 355 (90,245)

20.

Does it Matter Which Citation Tool is Used to Compare the H-Index of a Group of Highly Cited Researchers?

Australian Journal of Basic and Applied Sciences, Vol. 7, No. 4, pp. 198-202, March 2013

Number of pages: 5 Posted: 06 Jun 2013

Hadi Farhadi, Hadi Salehi, Melor Yunus, Arezoo Aghaei Chadegani, Maryam Farhadi, Masood Fooladi and Nader Ale Ebrahim

National University of Malaysia (UKM) - Research Center for Islamic Economics and Finance (EKONIS-UKM), Islamic Azad University, Najafabad Branch, National University of Malaysia - Faculty of Education, Islamic Azad University, National University of Malaysia (UKM), Islamic Azad University, Mobarakeh Branch and Centre for Research Services, Institute of Management and Research Services (IPPP), University of Malaya (UM)University of Malaya (UM) - Department of Engineering Design and Manufacture

Downloads 351 (91,467)

Citation 1

21.

Maximized Research Impact: An Effective Strategies for Increasing Citations

Managing and Leading Creative Universities – Foundations of Successful Science Management: A Hands-On Guide for (Future) Academics (pp. 29-51). Tampere, Finland: International Ambient Media Association (iAMEA); ISBN 978-952-7023-16-7

Number of pages: 23 Posted: 23 Jan 2018

Nader Ale Ebrahim, Hossein Gholizadeh and Artur Lugmayr

Downloads 337 (95,727)

22.

Relationship Among Economic Growth, Internet Usage and Publication Productivity: Comparison Among ASEAN and World's Best Countries

Modern Applied Science, 8(2), 160-170, 2014, doi: 10.5539/mas.v8n2p160

Number of pages: 11 Posted: 20 Mar 2014

Hossein Gholizadeh, Hadi Salehi, Mohamed Amin Embi, Mahmoud Danaee, Seyed Mohammad Motahar, Nader Ale Ebrahim, Farid Habibi and Noor Azuan Abu Osman

University of Ottawa, Ottawa Hospital Research Institute, Islamic Azad University, Najafabad Branch, Universiti Kebangsaan Malaysia - Faculty of Education, University Malaya, Universiti Kebangsaan Malaysia - Faculty of Information Science and Technology, Centre for Research Services, Institute of Management and Research Services (IPPP), University of Malaya (UM)University of Malaya (UM) - Department of Engineering Design and Manufacture, University of Economic Sciences and University of Malaya (UM) - Faculty of Engineering

Downloads 337 (95,727)

23.

Self-Efficacy, Scientific Reasoning, and Learning Achievement in the STEM Project-Based Learning Literature

The Journal of Nusantara Studies (JONUS), vol. 2, pp. 29-43

Number of pages: 15 Posted: 30 Jan 2018

Seyedh Mahboobeh Jamali, Ahmad Nurulazam Md Zain, Mohd Ali Samsudin and Nader Ale Ebrahim

Universiti Sains Malaysia (USM) - School of Educational Studies, Universiti Sains Malaysia (USM), Universiti Sains Malaysia (USM) - School of Educational Studies and Centre for Research Services, Institute of Management and Research Services (IPPP), University of Malaya (UM)University of Malaya (UM) - Department of Engineering Design and Manufacture

Downloads 327 (98,918)

Citation 3

24.

Effective Factors for Increasing University Publication and Citation Rate

Asian Social Science, vol. 11, no. 16, pp. 338-348, 2015

Number of pages: 11 Posted: 25 Jun 2015 Last Revised: 02 Jul 2015

Masoomeh Shahbazi-Moghadam, Hadi Salehi, Nader Ale Ebrahim, Marjan Mohammadjafari and Hossein Gholizadeh

Universiti Teknologi MARA (UiTM), Islamic Azad University, Najafabad Branch, Centre for Research Services, Institute of Management and Research Services (IPPP), University of Malaya (UM)University of Malaya (UM) - Department of Engineering Design and Manufacture, University of Malaya (UM) and University of Ottawa, Ottawa Hospital Research Institute

Downloads 312 (104,246)

Citation 1

25.

Managing Communication in New Product Development Process: Virtual R&D Teams and Information Technology

United Kingdom - Malaysia - Ireland Engineering Science Conference, pp. 495-502, 2011

Number of pages: 8 Posted: 30 Oct 2011 Last Revised: 22 Jun 2014

Nader Ale Ebrahim, Shamsuddin Ahmed, Salwa Hanim Abdul Rashid and Zahari Taha

Centre for Research Services, Institute of Management and Research Services (IPPP), University of Malaya (UM)University of Malaya (UM) - Department of Engineering Design and Manufacture, University of Malaya (UM), University of Malaya (UM) - Department of Engineering Design and Manufacture and University Malaysia Pahang - Department of Manufacturing Engineering

Downloads 293 (111,551)

26.

Applying System Dynamics to Confront Complex Decision Making in R&D Systems

5th Conference of Industries and Mines R&D Centers, November 22-23, 2005

Number of pages: 42 Posted: 08 Apr 2011

Arash Golnam and Nader Ale Ebrahim

The Society of Iranian Industries & Mines - Research & Development Centers and Centre for Research Services, Institute of Management and Research Services (IPPP), University of Malaya (UM)University of Malaya (UM) - Department of Engineering Design and Manufacture

Downloads 278 (117,960)

27.

Does Criticisms Overcome the Praises of Journal Impact Factor?

Asian Social Science, Vol. 9, No. 5, pp. 176-182, April 2013.

Number of pages: 7 Posted: 28 Apr 2013 Last Revised: 09 May 2013

Masood Fooladi, Hadi Salehi, Melor Yunus, Maryam Farhadi, Arezoo Aghaei Chadegani, Hadi Farhadi and Nader Ale Ebrahim

Islamic Azad University, Mobarakeh Branch, Islamic Azad University, Najafabad Branch, National University of Malaysia - Faculty of Education, National University of Malaysia (UKM), Islamic Azad University, National University of Malaysia (UKM) - Research Center for Islamic Economics and Finance (EKONIS-UKM) and Centre for Research Services, Institute of Management and Research Services (IPPP), University of Malaya (UM)University of Malaya (UM) - Department of Engineering Design and Manufacture

Downloads 252 (130,674)

28.

SMEs: ERP or Virtual Collaboration Teams

First Enterprise Resource Planning Conference, 2009

Number of pages: 12 Posted: 30 Dec 2010

Nader Ale Ebrahim, Shamsuddin Ahmed and Zahari Taha

Downloads 251 (131,202)

29.

The Effectiveness of Virtual R&D Teams in SMEs: Experiences of Malaysian SMEs

Downloads 245 (134,430)

Citation 5

30.

Major Trends in Distance Education Research: A Combination of Bibliometric and Thematic Analyze

International Journal of Information Research and Review, vol. 5, no. 2, pp. 5352-5359

Number of pages: 8 Posted: 20 May 2018

Azadeh Amoozegar, Rouhollah Khodabandelou and Nader Ale Ebrahim

University Putra Malaysia, Alzahra University and Centre for Research Services, Institute of Management and Research Services (IPPP), University of Malaya (UM)University of Malaya (UM) - Department of Engineering Design and Manufacture

Downloads 242 (136,114)

Citation 1

31.

Modified Kardashian Index: A Measure of Discrepant Social Media Profile for Scientists

Number of pages: 2 Posted: 02 Apr 2015

Nader Ale Ebrahim

Centre for Research Services, Institute of Management and Research Services (IPPP), University of Malaya (UM)University of Malaya (UM) - Department of Engineering Design and Manufacture

Downloads 238 (138,359)

32.

Maximize Visibility: A Way to Increase Citation Frequency

UM HIR SPECIAL FEATURE (27 May 2013), pp. 1-5, 27 May, 2013.

Number of pages: 5 Posted: 07 Nov 2013

Nader Ale Ebrahim and Hadi Salehi

Downloads 238 (138,359)

33.

Analysis of Opportunities and Challenges for R&D Management and the Role of the R&D Society for its Improvement – A Case Study in Iran

The R&D Management Conference, Newby Bridge, Cumbria, UK, 2006

Number of pages: 7 Posted: 08 Apr 2011

Nader Ale Ebrahim, Reza R. Tavakkoli-Moghaddam, Arash Golnam, Morteza Vasei and Ali Ghazizadeh

Centre for Research Services, Institute of Management and Research Services (IPPP), University of Malaya (UM)University of Malaya (UM) - Department of Engineering Design and Manufacture, Department of Industrial Engineering, Faculty of Engineering, University of Tehran, The Society of Iranian Industries & Mines - Research & Development Centers, affiliation not provided to SSRN and Planning Director

Downloads 236 (139,476)

34.

Virtual Teams: A New Opportunity to Develop a Business

International Conference on Entrepreneurship Across Boundaries, 2010

Number of pages: 5 Posted: 19 Dec 2010

Nader Ale Ebrahim, Shamsuddin Ahmed, Salwa Hanim Abdul Rashid and Zahari Taha

Centre for Research Services, Institute of Management and Research Services (IPPP), University of Malaya (UM)University of Malaya (UM) - Department of Engineering Design and Manufacture, University of Malaya (UM), University of Malaya (UM) - Department of Engineering Design and Manufacture and University Malaysia Pahang - Department of Manufacturing Engineering

Downloads 226 (145,499)

35.

R&D Networking and Value Creation in SMEs

Seventh conference of Industries and Mines R&D Centers - R&D and Network Value Creation, Tehran, Iran, June 29-30, 2008

Number of pages: 6 Posted: 13 Jan 2011

Nader Ale Ebrahim, Shamsuddin Ahmed and Zahari Taha

Downloads 225 (146,096)

Citation 1

36.

Equality of Google Scholar with Web of Science Citations: Case of Malaysian Engineering Highly Cited Papers

Modern Applied Science, Vol. 8, No. 5, pp. 63-69, 2014

Number of pages: 7 Posted: 09 Aug 2014 Last Revised: 10 Aug 2014

Nader Ale Ebrahim, Hadi Salehi, Mohamed Amin Embi, Mahmoud Danaee, Marjan Mohammadjafari, Azam Zavvari, Masoud Shakiba and Masoomeh Shahbazi-Moghadam

Centre for Research Services, Institute of Management and Research Services (IPPP), University of Malaya (UM)University of Malaya (UM) - Department of Engineering Design and Manufacture, Islamic Azad University, Najafabad Branch, Universiti Kebangsaan Malaysia - Faculty of Education, University Malaya, University of Malaya (UM), National University of Malaysia (UKM), National University of Malaysia (UKM) and Universiti Teknologi MARA (UiTM)

Downloads 219 (149,926)

37.

Technology Use in the Virtual R&D Teams

American Journal of Engineering and Applied Sciences, Vol. 5, No. 1, pp. 9-14, 2012

Number of pages: 6 Posted: 06 Feb 2012

Nader Ale Ebrahim, Shamsuddin Ahmed, Salwa Hanim Abdul Rashid and Zahari Taha

Centre for Research Services, Institute of Management and Research Services (IPPP), University of Malaya (UM)University of Malaya (UM) - Department of Engineering Design and Manufacture, University of Malaya (UM), University of Malaya (UM) - Department of Engineering Design and Manufacture and University Malaysia Pahang - Department of Manufacturing Engineering

Downloads 215 (152,537)

Citation 22

38.

Physical Activity and Aging Research: A Bibliometric Analysis

Journal of Aging and Physical Activity (2015) doi: 10.1123/japa.2015-0188

Number of pages: 26 Posted: 18 Dec 2015

Andre Müller, Payam Ansari, Nader Ale Ebrahim and Selina Khoo

National University of Singapore (NUS), University of Malaya (UM), Centre for Research Services, Institute of Management and Research Services (IPPP), University of Malaya (UM)University of Malaya (UM) - Department of Engineering Design and Manufacture and University of Malaya (UM)

Downloads 210 (155,905)

39.

A Conceptual Model of Virtual Product Development Process

2nd Seminar on Engineering and Information Technology, (SEIT 2009), Universiti Malaysia Sabah, Kota Kinabalu, Sabah, Malaysia, July 8-9, 2009

Number of pages: 6 Posted: 22 Dec 2010

Nader Ale Ebrahim, Shamsuddin Ahmed and Zahari Taha

Downloads 210 (155,905)

40.

Virtual Marketing in Virtual Enterprises

International Marketing Management Conference (IRMMC), 2008

Number of pages: 12 Posted: 08 Apr 2011

Nader Ale Ebrahim, Hamid A. Fattahi and Arash Golnam

Downloads 202 (161,756)

41.

Benefits and Pitfalls of Virtual R&D Teams: An Empirical Study

6th International Communication & Information Technology Management Conference, 2010

Number of pages: 5 Posted: 20 Dec 2010

Nader Ale Ebrahim, Shamsuddin Ahmed and Zahari Taha

Downloads 201 (162,488)

42.

Major Trends in Knowledge Management Research: A Bibliometric Study

Scientometrics, vol. 107, no. 3, pp. 1249-1264, June, 2016.

Number of pages: 24 Posted: 17 May 2016

Peyman Akhavan, Nader Ale Ebrahim, Mahdieh A. Fetrati and Amir Pezeshkan

Malek Ashtar University of Technology, Centre for Research Services, Institute of Management and Research Services (IPPP), University of Malaya (UM)University of Malaya (UM) - Department of Engineering Design and Manufacture, Aalborg University - Department of Business and Management and University of Baltimore

Downloads 199 (164,032)

Citation 3

43.

Virtual R&D Teams Definition

Number of pages: 3 Posted: 21 Mar 2013

Nader Ale Ebrahim

Centre for Research Services, Institute of Management and Research Services (IPPP), University of Malaya (UM)University of Malaya (UM) - Department of Engineering Design and Manufacture

Downloads 193 (168,748)

Citation 1

44.

Virtual R&D Teams for NPD in SMEs: Past, Present and Future Trend

Asia pacific Conference on Management of Technology and Technology Entrepreneurship, Melaka, Malaysia, October 29-30, 2008

Number of pages: 10 Posted: 22 Dec 2010

Nader Ale Ebrahim, Shamsuddin Ahmed and Zahari Taha

Downloads 191 (170,237)

45.

Does a Long Reference List Guarantee More Citations? Analysis of Malaysian Highly Cited and Review Papers

The International Journal of Management Science and Business, Vol. 1, No. 3, pp. 6-15, 2015

Number of pages: 11 Posted: 04 Mar 2015

Nader Ale Ebrahim, H. Ebrahimian, Maryam Mousavi and Farzad Tahriri

Centre for Research Services, Institute of Management and Research Services (IPPP), University of Malaya (UM)University of Malaya (UM) - Department of Engineering Design and Manufacture, University Malaya - Institute of Mathematical Sciences, Faculty Science, University of Malaya - Centre for Product Design and Manufacturing, Department of Mechanical Engineering, Faculty of Engineering and University of Malaya (UM) - Faculty of Engineering

Downloads 188 (172,745)

46.

Heavy Duty Fleet and Transportation in Iran the Past, the Present Condition, the Future Perspectives and its Interaction with Economy

FISITA 2006 World Automotive Congress, Yokohama, Japan

Number of pages: 12 Posted: 10 Apr 2011

Nader Ale Ebrahim and Arash Golnam

Downloads 185 (175,258)

47.

Knowledge Management in Iran

Knowledge Management International Conference and Exhibition (KMICE), 2006

Number of pages: 7 Posted: 08 Apr 2011

Nader Ale Ebrahim, Ali Ghazizadeh and Arash Golnam

Downloads 185 (175,258)

48.

New Product Development in Virtual Environment

International Conference on Technology Management and Innovation in China: Challenges and Opportunities in the 21st Century, 2008

Number of pages: 16 Posted: 19 Dec 2010

Nader Ale Ebrahim, Shamsuddin Ahmed and Zahari Taha

Downloads 175 (184,126)

49.

Economic Growth and Internet Usage Impact on Publication Productivity Among ASEAN's and World's Best Universities

Modern Applied Science, Vol. 8, No. 5, pp. 169-178

Number of pages: 10 Posted: 12 Sep 2014

Hossein Gholizadeh, Hadi Salehi, Mohamed Amin Embi, Mahmoud Danaee, Ali Ordi, Farid Habibi, Nader Ale Ebrahim and Noor Azuan Abu Osman

University of Ottawa, Ottawa Hospital Research Institute, Islamic Azad University, Najafabad Branch, Universiti Kebangsaan Malaysia - Faculty of Education, University Malaya, Universiti Teknologi Malaysia - Advance Informatics School (AIS), University of Economic Sciences, Centre for Research Services, Institute of Management and Research Services (IPPP), University of Malaya (UM)University of Malaya (UM) - Department of Engineering Design and Manufacture and University of Malaya (UM) - Faculty of Engineering

Downloads 168 (190,743)

50.

Trend of 100 Top-Cited Articles on Agricultural Risk

Paper presented at the 2nd Kuala Lumpur International Agriculture, Forestry & Plantation Conference (KLIAFP 2016), Hotel Putra, Kuala Lumpur, Malaysia

Number of pages: 12 Posted: 22 Feb 2016

Ali Sayyad, Mohd Mansor Ismail and Nader Ale Ebrahim

Department of Agribusiness and information system University Putra Malaysia, Malaysia, Department of Agribusiness and information system University Putra Malaysia, Malaysia and Centre for Research Services, Institute of Management and Research Services (IPPP), University of Malaya (UM)University of Malaya (UM) - Department of Engineering Design and Manufacture

Downloads 167 (191,718)

51.

Virtual Collaborative R&D Teams in Malaysia Manufacturing SMEs

2nd International Conference on Mechanical, Industrial, and Manufacturing Technologies, 2011

Number of pages: 4 Posted: 01 Mar 2011

Nader Ale Ebrahim, Shamsuddin Ahmed, Salwa Hanim Abdul Rashid, Zahari Taha and Md. Abdul Wazed

Centre for Research Services, Institute of Management and Research Services (IPPP), University of Malaya (UM)University of Malaya (UM) - Department of Engineering Design and Manufacture, University of Malaya (UM), University of Malaya (UM) - Department of Engineering Design and Manufacture, University Malaysia Pahang - Department of Manufacturing Engineering and University of Malaya (UM)

Downloads 165 (193,720)

52.

Publication Trends in Physics Education: A Bibliometric Study

Journal of Educational Research, vol. 35, pp. 19-36, 2 June, 2015.

Number of pages: 14 Posted: 03 Jun 2017

Seyedh Mahboobeh Jamali, Ahmad Nurulazam Md Zain, Mohd Ali Samsudin and Nader Ale Ebrahim

Downloads 164 (194,710)

Citation 1

53.

Consideration of the Virtual Team Work and Disabled Citizens, as Promising Opportunity Providers for the E-Government Infrastructure's Formation

Second Conference on Electronic City, 2009

Number of pages: 8 Posted: 13 Jan 2011

Mohammad Ali Shafia, Nader Ale Ebrahim, Shamsuddin Ahmed and Zahari Taha

University of Science and Technology - Faculty of Industrial Engineering, Centre for Research Services, Institute of Management and Research Services (IPPP), University of Malaya (UM)University of Malaya (UM) - Department of Engineering Design and Manufacture, University of Malaya (UM) and University of Malaya (UM)

Downloads 163 (195,778)

54.

Demystifying the Legend of Resistance to Change

IAMOT 2008: 17th International Conference on Management of Technology, April 6-10, 2008

Number of pages: 8 Posted: 08 Apr 2011

Hamid Tahbaz Tavakoli, Nader Ale Ebrahim and Arash Golnam

The R&D Society of Iranian Industries and Mines, Centre for Research Services, Institute of Management and Research Services (IPPP), University of Malaya (UM)University of Malaya (UM) - Department of Engineering Design and Manufacture and The Society of Iranian Industries & Mines - Research & Development Centers

Downloads 159 (201,044)

55.

Virtual R&D Teams: Innovation and Technology Facilitator

Engineering Education in 2025, 2009

Number of pages: 14 Posted: 13 Jan 2011

Nader Ale Ebrahim, Shamsuddin Ahmed and Zahari Taha

Downloads 154 (205,343)

56.

Virtual Environments Innovation and R&D Activities: Management Challenges

Proceedings of the International Graduate on Engineering and Science, 2008

Number of pages: 9 Posted: 30 Dec 2010

Nader Ale Ebrahim, Shamsuddin Ahmed and Zahari Taha

Downloads 152 (207,625)

57.

Dealing with Virtual R&D Teams in New Product Development

The 9th Asia Pacific Industrial Engineering & Management Systems Conference and the 11th Asia Pacific Regional Meeting of the International Foundation for Production Research, December 3-5, 2008, Nusa Dua, Bali, Indonesia

Number of pages: 12 Posted: 22 Dec 2010

Nader Ale Ebrahim, Shamsuddin Ahmed and Zahari Taha

Downloads 151 (208,750)

58.

Virtual Collaborative R&D Teams in Malaysian Manufacturing SMEs

Advanced Materials Research, pp. 1653-1659, 2012

Number of pages: 7 Posted: 06 Feb 2012

Nader Ale Ebrahim, Shamsuddin Ahmed, Salwa Hanim Abdul Rashid, Zahari Taha and Md. Abdul Wazed

Centre for Research Services, Institute of Management and Research Services (IPPP), University of Malaya (UM)University of Malaya (UM) - Department of Engineering Design and Manufacture, University of Malaya (UM), University of Malaya (UM) - Department of Engineering Design and Manufacture, University Malaysia Pahang - Department of Manufacturing Engineering and University of Malaya (UM)

Downloads 148 (212,258)

59.

Innovation Process is Facilitated in Virtual Environment of R&D Teams

International Conference on Education and New Learning Technologies, 2009

Number of pages: 10 Posted: 20 Dec 2010

Mohammad Ali Shafia, Nader Ale Ebrahim, Shamsuddin Ahmed and Zahari Taha

Downloads 146 (214,635)

60.

R&D Management in Iran, Opportunities and Threats

16th International Conference on Management of Technology (IAMOT), 2007

Number of pages: 7 Posted: 08 Apr 2011

Nader Ale Ebrahim, Ali Ghazizadeh, Arash Golnam and Hamid Tahbaz Tavakoli

Centre for Research Services, Institute of Management and Research Services (IPPP), University of Malaya (UM)University of Malaya (UM) - Department of Engineering Design and Manufacture, Planning Director, The Society of Iranian Industries & Mines - Research & Development Centers and The R&D Society of Iranian Industries and Mines

Downloads 145 (215,792)

61.

Virtuality, Innovation and R&D Activities

14th International Conference, 'Thinking Minds: Nurturing the Design of a Better Future', June 22-26, 2009, Malaysia

Number of pages: 15 Posted: 22 Dec 2010

Nader Ale Ebrahim, Shamsuddin Ahmed and Zahari Taha

Downloads 144 (217,018)

62.

Virtual R&D Teams: A Potential Growth of Education-Industry Collaboration

Downloads 144 (217,018)

Citation 1

63.

Virtual R&D Team: Technology Transfer Facilitator

18th International Conference on Management of Technology, 2009

Number of pages: 10 Posted: 04 May 2011

Nader Ale Ebrahim, Mohammad Ali Shafia and Hamid Tahbaz Tavakoli

Centre for Research Services, Institute of Management and Research Services (IPPP), University of Malaya (UM)University of Malaya (UM) - Department of Engineering Design and Manufacture, University of Science and Technology - Faculty of Industrial Engineering and The Society of Iranian Industries & Mines - Research & Development Centers

Downloads 143 (218,237)

64.

Virtual R&D Teams: A Sustainable Infrastructure for Promoting SMEs

2nd Engineering Conference, 2008

Number of pages: 7 Posted: 30 Dec 2010

Nader Ale Ebrahim, Shamsuddin Ahmed and Zahari Taha

Downloads 135 (228,404)

65.

Models for Component Commonality in Multistage Production

2nd International Conference on Mechanical, Industrial, and Manufacturing Technologies (MIMT 2011)

Number of pages: 5 Posted: 17 Aug 2011

Md. Abdul Wazed, Yusoff Nukman, Nader Ale Ebrahim and Shamsuddin Ahmed

University of Malaya (UM), University of Malaya, Centre for Research Services, Institute of Management and Research Services (IPPP), University of Malaya (UM)University of Malaya (UM) - Department of Engineering Design and Manufacture and University of Malaya (UM)

Downloads 134 (229,770)

66.

A Comprehensive Comparison of Educational Growth within Four Different Developing Countries between 1990 and 2012

Revista de Gestão e Secretariado, vol. 6, no. 3, pp. 152-174, 2016

Number of pages: 17 Posted: 06 Apr 2016

Masoud Shakiba, Nader Ale Ebrahim, Mahmoud Danaee, Kaveh Bakhtiyari and Elankovan Sundararajan

National University of Malaysia (UKM), Centre for Research Services, Institute of Management and Research Services (IPPP), University of Malaya (UM)University of Malaya (UM) - Department of Engineering Design and Manufacture, University Malaya, University of Duisburg-Essen and Center for Software Technology and Management, Faculty of Information Science and Technology, Universiti Kebangsaan Malaysia

Downloads 133 (231,187)

67.

Virtual Teams for NPD – An Innovative Experience for R&D Engineers

International Conference on Advances in Mechanical Engineering, 2009

Number of pages: 10 Posted: 30 Dec 2010

Nader Ale Ebrahim, Shamsuddin Ahmed and Zahari Taha

Downloads 133 (231,187)

68.

Concurrent Collaboration in Research and Development

National Conference on Design and Concurrent Engineering (DECON) October 28-29, 2008, Melaka, Malaysia

Number of pages: 4 Posted: 22 Dec 2010

Nader Ale Ebrahim, Shamsuddin Ahmed and Zahari Taha

Downloads 133 (231,187)

69.

The 100 Most Cited Papers In 'Industrial Design': A Bibliometric Analysis

Post print of: Abedini, A., Rahman, R., Sadeghi Naeini, H., & Ale Ebrahim, N. (2017). The100 Most Cited Papers in “Industrial Design”: A Bibliometric Analysis . Exacta – Engenharia de Produção, 15(3), 369 - 374. doi: 10.5585/ExactaEP.v15n3.7659

Number of pages: 17 Posted: 20 Oct 2017

Ahmad Abedini, Rizal Rahman, Hassan Sadeghi Naeini and Nader Ale Ebrahim

Iran University of Science and Technology - Department of Industrial Engineering, Iran University of Science and Technology, University of Malaya (UM) and Centre for Research Services, Institute of Management and Research Services (IPPP), University of Malaya (UM)University of Malaya (UM) - Department of Engineering Design and Manufacture

Downloads 132 (232,613)

Citation 1

70.

Increasing Visibility and Enhancing Impact of Research

Asia Research News 2017

Number of pages: 3 Posted: 30 Apr 2017

Yiibonn Bong and Nader Ale Ebrahim

University of Malaya and Centre for Research Services, Institute of Management and Research Services (IPPP), University of Malaya (UM)University of Malaya (UM) - Department of Engineering Design and Manufacture

Downloads 132 (232,613)

71.

Self-Efficacy, Scientific Reasoning, and Learning Achievement in the STEM PjBL Literature

International Postgraduate Conference on Research in Education (IPCoRE 2017), School of Educational Studies, Universiti Sains Malaysia (USM), Penang, Malaysia

Number of pages: 11 Posted: 30 Jan 2018

Seyedh Mahboobeh Jamali, Ahmad Nurulazam Md Zain, Mohd Ali Samsudin and Nader Ale Ebrahim

Downloads 131 (233,946)

72.

Literature, Principle and the Basics of Network Value Creation in R&D: The Relationship with Economy

Seventh Conference of Industries and Mines R&D Centers - R&D and Network Value Creation, Tehran, Iran, June 29-30, 2008

Number of pages: 8 Posted: 13 Jan 2011

Nader Ale Ebrahim, Shamsuddin Ahmed and Zahari Taha

Downloads 131 (233,946)

73.

The Rise of Alternative Metrics (Altmetrics) for Research Impact Measurement

Asia Research News 2017

Number of pages: 3 Posted: 04 Apr 2017

Yiibonn Bong and Nader Ale Ebrahim

Downloads 130 (236,662)

74.

Envisages of New Product Developments in Small and Medium Enterprises Through Virtual Team

International Conference on Industrial Engineering and Operations Management, 2010

Number of pages: 10 Posted: 20 Dec 2010

Nader Ale Ebrahim, Shamsuddin Ahmed and Zahari Taha

Downloads 130 (235,333)

75.

The Biggest Experience to Reduce Environmental Pollutants by Substitute Fuel CNG in the Middle East & the Middle Asia

9th International Association for Natural Gas Vehicles (IANGV) Conference, Buenos Aires, 2004

Number of pages: 25 Posted: 10 Apr 2011

Ali momeni, Maziar Rostamnezhad and Nader Ale Ebrahim

affiliation not provided to SSRN, Diesel Co. and Centre for Research Services, Institute of Management and Research Services (IPPP), University of Malaya (UM)University of Malaya (UM) - Department of Engineering Design and Manufacture

Downloads 125 (242,377)

76.

Optimize Your Article for Search Engine

University of Malaya Research Bulletin, Vol. 2, No. 1, 23, December 2014

Number of pages: 3 Posted: 02 Apr 2015

Nader Ale Ebrahim

Centre for Research Services, Institute of Management and Research Services (IPPP), University of Malaya (UM)University of Malaya (UM) - Department of Engineering Design and Manufacture

Downloads 124 (243,838)

77.

The Scientific Articles on Art Criticism

Asian Social Science, vol. 11, no. 13, pp. 130-138, 2015

Number of pages: 9 Posted: 22 May 2015

Mina Hedayat, Pegah Jahangiri, Aida Torkamani, Mahsa Mashayekhi, Sabzali Musa Kahn and Nader Ale Ebrahim

University of Malaya (UM), University of Malaya (UM), University of Malaya (UM), University of Applied Science and Technology, University of Malaya (UM) and Centre for Research Services, Institute of Management and Research Services (IPPP), University of Malaya (UM)University of Malaya (UM) - Department of Engineering Design and Manufacture

Downloads 123 (245,348)

78.

Process Construct in the Virtual R&D Teams

in Proceedings of the Asia Pacific Industrial Engineering & Management Systems Conference (APIEMS 2012), Patong Beach, Phuket, Thailand, 2012, pp. 1822-1828, December 2012

Number of pages: 7 Posted: 22 Feb 2013

Nader Ale Ebrahim, Shamsuddin Ahmed, Salwa Hanim Abdul Rashid, Zahari Taha and Marjan Mohammadjafari

Centre for Research Services, Institute of Management and Research Services (IPPP), University of Malaya (UM)University of Malaya (UM) - Department of Engineering Design and Manufacture, University of Malaya (UM), University of Malaya (UM) - Department of Engineering Design and Manufacture, University Malaysia Pahang - Department of Manufacturing Engineering and University of Malaya (UM)

Downloads 123 (245,348)

79.

SMEs and Virtual R&D Teams: A Motive Channel for Relationship between SMEs

International Conference for Technical Postgraduates, December 2009

Number of pages: 7 Posted: 20 Dec 2010

Nader Ale Ebrahim

Centre for Research Services, Institute of Management and Research Services (IPPP), University of Malaya (UM)University of Malaya (UM) - Department of Engineering Design and Manufacture

Downloads 123 (245,348)

80.

Virtual R&D Teams: A New Model for Product Development

International Journal of Innovation - IJI, 3(2), 01-27. doi: 10.5585/iji.v3i2.43

Number of pages: 27 Posted: 21 Oct 2015 Last Revised: 22 Oct 2015

Nader Ale Ebrahim

Centre for Research Services, Institute of Management and Research Services (IPPP), University of Malaya (UM)University of Malaya (UM) - Department of Engineering Design and Manufacture

Downloads 121 (248,402)

81.

Qualitative and Quantitative Analysis of Solar Hydrogen Generation Literature from 2001 to 2014

Scientometrics, vol. 105, no. 2, pp. 759-771

Number of pages: 12 Posted: 26 Oct 2015

Mohammad Reza Maghami, Shahin Navabi Asl, Mohammad Ismaeil Rezadad, Nader Ale Ebrahim and Chandima Gomes

University Putra Malaysia, Islamic Azad University (IAU), University of Malaya (UM) - Faculty of Engineering, Centre for Research Services, Institute of Management and Research Services (IPPP), University of Malaya (UM)University of Malaya (UM) - Department of Engineering Design and Manufacture and University Putra Malaysia

Downloads 120 (249,962)

Citation 1

82.

Research, Development, Production and Performance of Heavy Duty CNG Fleets in Iran

ANGVA 2005, Kuala Lumpur, Malaysia

Number of pages: 13 Posted: 10 Apr 2011

Nader Ale Ebrahim, Maziar Rostamnezhad and Ali momeni

Downloads 119 (251,517)

83.

A Bibliometric Analysis on 'Fertility Rate' Research Trends

International Journal of Professional Business Review, Vol. 1, No. 1, pp. 1-14, July 2016

Number of pages: 14 Posted: 01 Aug 2016

Shalini Nagaratnam, Nader Ale Ebrahim and Muzafar Shah Habibullah

Taylor's University, Centre for Research Services, Institute of Management and Research Services (IPPP), University of Malaya (UM)University of Malaya (UM) - Department of Engineering Design and Manufacture and Universiti Putra Malaysia

Downloads 117 (254,655)

Citation 1

84.

100 Most Cited Articles in Urban Green and Open Spaces: A Bibliometric Analysis

Current World Environment, Vol. 10, No. 2, 2015

Number of pages: 16 Posted: 15 Aug 2015

Mehdi Rakhshandehroo, Mohd Johari Mohd Yusof, Nader Ale Ebrahim, Ali Sharghi and Roozbeh Kianpour

University Putra Malaysia, University Putra Malaysia, Centre for Research Services, Institute of Management and Research Services (IPPP), University of Malaya (UM)University of Malaya (UM) - Department of Engineering Design and Manufacture, Shahid Rajaee Teacher Training University (SRTTU) and Science and Research Branch of Islamic Azad University

Downloads 116 (256,174)

Citation 1

85.

Establish a Digital Footprint for Your Publication by Using Twitter

University of Malaya Research Bulletin, Vol. 2, No. 1, pp. 35-36

Number of pages: 2 Posted: 15 Feb 2016

Nader Ale Ebrahim

Centre for Research Services, Institute of Management and Research Services (IPPP), University of Malaya (UM)University of Malaya (UM) - Department of Engineering Design and Manufacture

Downloads 114 (259,380)

86.

Evaluating the Academic Trend of RFID Technology Based on SCI and SSCI Publications from 2001 to 2014

Scientometrics, 1-24. doi: 10.1007/s11192-016-2095-y

Number of pages: 28 Posted: 12 Aug 2016

Masoud Shakiba, Azam Zavvari, Nader Ale Ebrahim and Mandeep Singh Jit Singh

National University of Malaysia (UKM), National University of Malaysia (UKM), Centre for Research Services, Institute of Management and Research Services (IPPP), University of Malaya (UM)University of Malaya (UM) - Department of Engineering Design and Manufacture and National University of Malaysia (UKM)

Downloads 96 (291,819)

87.

Supply Chain Integration: A Review and Bibliometric Analysis

International Journal of Economics & Management Sciences, Vol. 6, No. 5, July 2017

Number of pages: 26 Posted: 13 Nov 2017

Ali Asgari, AbuBakar Bin Hamid and Nader Ale Ebrahim

Universiti Teknologi Malaysia (UTM), Independent and Centre for Research Services, Institute of Management and Research Services (IPPP), University of Malaya (UM)University of Malaya (UM) - Department of Engineering Design and Manufacture

Downloads 95 (293,813)

88.

Open Innovation: A Bibliometric Study

International Journal of Innovation (IJI), vol. 5, no. 3 (2017)

Number of pages: 13 Posted: 05 Oct 2017

Nader Ale Ebrahim and Yiibonn Bong

Downloads 94 (295,766)

89.

Recent Developments in Metamodel Based Robust Black-Box Simulation Optimization: An Overview

Decision Science Letters, vol. 8, no. 1, pp. 17-44

Number of pages: 39 Posted: 23 Jun 2018

Amir Parnianifard, A Azfanizam, Mohd Khairol Anuar Mohd Ariffin, Mohd Idris Shah Ismail and Nader Ale Ebrahim

University Putra Malaysia, University Putra Malaysia, University Putra Malaysia, University Putra Malaysia and Centre for Research Services, Institute of Management and Research Services (IPPP), University of Malaya (UM)University of Malaya (UM) - Department of Engineering Design and Manufacture

Downloads 87 (310,490)

90.

Impact of Article Page Count and Number of Authors on Citations in Disability Related Fields: A Systematic Review Article

Iranian Journal of Public Health, Vol. 45, no. 9, pp. 1118-1125

Number of pages: 8 Posted: 04 Oct 2016

Abubakar Ahmed, Mastura Adam, Norafida Ghafar, Murtala Muhammad and Nader Ale Ebrahim

University of Malaya (UM), University of Malaya - Department of Architecture, University of Malaya (UM), University of Malaya (UM) and Centre for Research Services, Institute of Management and Research Services (IPPP), University of Malaya (UM)University of Malaya (UM) - Department of Engineering Design and Manufacture

Downloads 71 (349,720)

91.

35-year Research History of Cytotoxicity and Cancer: A Quantitative and Qualitative Analysis

Asian Pac J Cancer Prev, vol. 17, no. 7, pp. 3139-3145, 2016

Number of pages: 7 Posted: 16 Sep 2016

Reyhaneh Farghadani, Batoul Sadat Haerian, Nader Ale Ebrahim and Sekaran Muniandy

University of Malaya (UM), University of Malaya (UM), Centre for Research Services, Institute of Management and Research Services (IPPP), University of Malaya (UM)University of Malaya (UM) - Department of Engineering Design and Manufacture and University of Malaya (UM)

Downloads 69 (355,223)

92.

A Bibliometric Approach to Tracking Big Data Research Trends

Journal of Big Data, Vol. 4, No. 30, September 2017

Number of pages: 23 Posted: 18 Dec 2019

Ali Kalantari, Amirrudin Kamsin, Halim Shukri Kamaruddin, Nader Ale Ebrahim, Abdullah Gani, Ali Ebrahimi and Shahaboddin Shamshirband

University of Malaya (UM), University of Malaya (UM) - Faculty of Computer Science and Information Technology, USCI University, Centre for Research Services, Institute of Management and Research Services (IPPP), University of Malaya (UM)University of Malaya (UM) - Department of Engineering Design and Manufacture, University of Malaya (UM) - Faculty of Computer Science and Information Technology, University of Malaya (UM) - Faculty of Computer Science and Information Technology and Ton Duc Thang University

Downloads 68 (358,064)

93.

Impact of Published Articles on Trade Liberalization from 1980-2015: A Bibliometric Study

AFRREV IJAH: An International Journal of Arts and Humanities, Vol. 6, No. 3, pp. 16-32, 2017

Number of pages: 18 Posted: 21 Sep 2017

Murtala Muhammad, Nader Ale Ebrahim, Gold Kafilah and Abubakar Ahmed

University of Malaya (UM), Centre for Research Services, Institute of Management and Research Services (IPPP), University of Malaya (UM)University of Malaya (UM) - Department of Engineering Design and Manufacture, University of Malaya and University of Malaya (UM)

Downloads 58 (388,018)

94.

The Rise of 'Trade Liberalization': Bibliometric Analysis of Trade Liberalization Study

Mediterranean Journal of Social Sciences, vol. 8, no. 2, pp. 97-104, March 2017, DOI: 10.5901/mjss.2017.v8n2p97

Number of pages: 8 Posted: 08 Mar 2017

Murtala Muhammad, Abubakar Ahmed, Gold Kafilah, Murtala Muhammad and Nader Ale Ebrahim

University of Malaya (UM), University of Malaya (UM), University of Malaya, University of Malaya (UM) and Centre for Research Services, Institute of Management and Research Services (IPPP), University of Malaya (UM)University of Malaya (UM) - Department of Engineering Design and Manufacture

Downloads 56 (394,676)

95.

Five Decades of Scientific Development on 'Attachment Theory': Trends and Future Landscape

Pertanika Journal of Social Sciences & Humanities, 26(3), 1-16, 2018

Number of pages: 16 Posted: 13 Dec 2018

Elaheh Farahmand, Mariani Md Nor, Abbas Ghanbari Baghestan, Nader Ale Ebrahim and Nasrin Matinnia

University of Malaya (UM) - Department of Educational Psychology and Counselling, University of Malaya (UM), University of Tehran, Centre for Research Services, Institute of Management and Research Services (IPPP), University of Malaya (UM)University of Malaya (UM) - Department of Engineering Design and Manufacture and Islamic Azad University (IAU) - Department of Nursing

Downloads 40 (454,002)

96.

The Effect of STEM Project Based Learning on Self-Efficacy Among High-School Physics Students

Journal of Turkish Science Education, vol. 16, no. 1, pp. 94-108, 2020

Number of pages: 15 Posted: 07 May 2020

Mohd Ali Samsudin, Seyedh Mahboobeh Jamali, Ahmad Nurulazam Md Zain and Nader Ale Ebrahim

Universiti Sains Malaysia (USM) - School of Educational Studies, Universiti Sains Malaysia (USM) - School of Educational Studies, Universiti Sains Malaysia (USM) and Centre for Research Services, Institute of Management and Research Services (IPPP), University of Malaya (UM)University of Malaya (UM) - Department of Engineering Design and Manufacture

Downloads 29 (510,460)

97.

Relationship of Google Scholar Versions and Paper Citations

Number of pages: 11 Posted: 13 Jun 2019

Marjan Mohammadjafari, Hadi Salehi, Kaveh Bakhtiyari, Nader Ale Ebrahim, Mahmoud Danaee, Masoud Shakiba, Masoomeh Shahbazi-Moghadam and Azam Zavvari

University of Malaya (UM), Islamic Azad University, Najafabad Branch, University of Duisburg-Essen, Centre for Research Services, Institute of Management and Research Services (IPPP), University of Malaya (UM)University of Malaya (UM) - Department of Engineering Design and Manufacture, University Malaya, National University of Malaysia (UKM), Universiti Teknologi MARA (UiTM) and National University of Malaysia (UKM)

Downloads 24 (533,347)

98.

Effects of Digital Game-Based Learning on Elementary Science Learning: A Systematic Review

IEEE Access, 7(1) (2019)

Number of pages: 22 Posted: 11 Jun 2019

Mahmood H. Hussein, Siew Hock Ow, Sau Cheong Loh, Meow-Keong Thong and Nader Ale Ebrahim

Department of Software Engineering, Faculty of Computer Science and Information Technology, University of Malaya, 50603, Kuala Lumpur, Malaysia, affiliation not provided to SSRN, Department of Educational Psychology and Counselling, Faculty of Education, University of Malaya, 50603 Kuala Lumpur, Malaysia, Department of Paediatrics, Faculty of Medicine, University of Malaya, 50603 Kuala Lumpur, Malaysia and Centre for Research Services, Institute of Management and Research Services (IPPP), University of Malaya (UM)University of Malaya (UM) - Department of Engineering Design and Manufacture

Downloads 14 (596,271)

99.

Publishing Research Support Documents in Open Access Platform to Improve Research Impact

Number of pages: 6 Posted: 28 Mar 2019

Nader Ale Ebrahim and Yiibonn Bong

Downloads 13 (602,869)

100.

Two Decades of Research on Early Career Faculties (ECFs): A Bibliometric Analysis of Trends across Regions

Pertanika Journal of Social Sciences & Humanities (JSSH), 28(1), 325 - 342, 2020

Number of pages: 26 Posted: 21 Apr 2020

Farrah Dina Yusop, Fauza Ab Ghaffar, Mahmoud Danaee, Amira Firdaus, Nur Azah Hamzaid, Zahiruddin Fitri Abu Hassan, Fatiha Senom, Nader Ale Ebrahim, Yiibonn Bong and MC Yap

Universiti Malaya - Academic Enhancement and Leadership Development Centre (ADeC), Fauza Ab Ghaffar, University Malaya, Department of Media and Communication Studies, Faculty of Arts and Social Sciences, Universiti Malaya, Department of Biomedical Engineering, Faculty of Engineering, Universiti Malaya, Department of Building Surveying, Faculty of Built Environment, Universiti Malaya, Department of Language and Literacy Education, Faculty of Education, Universiti Malaya, Centre for Research Services, Institute of Management and Research Services (IPPP), University of Malaya (UM)University of Malaya (UM) - Department of Engineering Design and Manufacture, University of Malaya and Department of Curriculum and Instructional Technology, Faculty of Education, Universiti Malaya

Downloads 11 (616,553)

101.

Publication Trends in Drug Delivery and Magnetic Nanoparticles

Nanoscale Research Letters, 14(59), 2019

Number of pages: 14 Posted: 10 Jun 2019

Saba Ale Ebrahim, Amirhossein Ashtari, Maysam Zamani Pedram and Nader Ale Ebrahim

Faculty of Electrical Engineering, K.N. Toosi University of Technology, Tehran, Iran, Faculty of Electrical Engineering, K.N. Toosi University of Technology, Tehran, Iran, Faculty of Electrical Engineering, K.N. Toosi University of Technology, Tehran, Iran and Centre for Research Services, Institute of Management and Research Services (IPPP), University of Malaya (UM)University of Malaya (UM) - Department of Engineering Design and Manufacture

Downloads 10 (623,282)

102.

A Bibliometric Analysis of M-Learning from Topic Inception to 2015

International Journal of Mobile Learning and Organisation, vol. 13, no. 1, pp. 91-112, 2019.

Posted: 03 Jan 2019

Monther M. Elaish, Liyana Shuib, Norjihan Abdul Ghani, Ghulam Mujtaba Kayani and Nader Ale Ebrahim

Department of Information Systems, Faculty of Computer Science and Information Technology, University of Malaya, University of Malaya (UM), Department of Information Systems, Faculty of Computer Science and Information Technology, University of Malaya, Comsats University Islamabad and Centre for Research Services, Institute of Management and Research Services (IPPP), University of Malaya (UM)University of Malaya (UM) - Department of Engineering Design and Manufacture

Quantitative and Qualitative Analysis of Time-Series Classification Using Deep Learning

Source: https://ieeexplore.ieee.org/abstract/document/9090138

Quantitative and Qualitative Analysis of Time-Series Classification Using Deep Learning

Under a Creative Commons License

Abstract:

Time-series classification is utilized in a variety of applications leading to the development of many data mining techniques for time-series analysis. Among the broad range of time-series classification algorithms, recent studies are considering the impact of deep learning methods on time-series classification tasks. The quantity of related publications requires a bibliometric study to explore most prominent keywords, countries, sources and research clusters. The paper conducts a bibliometric analysis on related publications in time-series classification, adopted from Scopus database between 2010 and 2019. Through keywords co-occurrence analysis, a visual network structure of top keywords in time-series classification research has been produced and deep learning has been introduced as the most common topic by additional inquiry of the bibliography. The paper continues by exploring the publication trends of recent deep learning approaches for time-series classification. The annual number of publications, the productive and collaborative countries, the growth rate of sources, the most occurred keywords and the research collaborations are revealed from the bibliometric analysis within the study period. The research field has been broken down into three main categories as different frameworks of deep neural networks, different applications in remote sensing and also in signal processing for time-series classification tasks. The qualitative analysis highlights the categories of top citation rate papers by describing them in details.

Published in: IEEE Access ( Volume: 8 )

Page(s): 90202 - 90215

Date of Publication: 08 May 2020

Electronic ISSN: 2169-3536

DOI: 10.1109/ACCESS.2020.2993538

The graphical workflow of bibliometric and qualitative analysis on the usage of deep learning algorithms in time-series classification-related literature published within... View more

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SECTION I.

Introduction

A time-series is a series of observations expressed as temporal data points ordered in time, such as stocks market, human activity, audio, etc. Classification is a predictive modeling problem included in time-series data mining tasks [1]. Different classification problems are caused once dealing with rich and diverse-range time-series data domains such as, finance, medical science and engineering [2]. Variant experiments are conducted by UCR repository, the biggest set of real-world time-series data [3]. These actions along with many others are untaken in order to solve time-series classification problems [4]. Time-series classification techniques can be basically categorized to three main divisions of distance-based, using a distance function for similarity measurement, model-based, using statistical models for classification, and feature-based, using feature vectors classification methods [5].

Euclidean Distance (ED) and Dynamic Time Warping (DTW) are commonly used measurements in distance-based methods. The classification task is done by metric classifiers, such as Support Vector Machines (SVM) and K-Nearest Neighbors (KNN). SVM classifiers have been using embedded distance features for time-series data by computing EDs inside the classification task [6]. The SVM method is an effective approach in case of high dimensional data and superior in classification accuracy [7]. KNN classification is done by using the most frequent label in the k closest data points. The 1-Nearest Neighbor classifier with DTW distance (1NN-DTW) is the most effective time-series classifier, however it carries high computational cost as a concern [8]. 1NN-DTW classifier has shown a simple but strong golden baseline by achieving comparable results among other classifiers [9], [10]. Therefore, latest developments have focused on overpowering the 1NN-DTW method in time-series classification tasks [11].

Simple time-series representations, such as naïve Bayes and Hidden Markov Model (HMM), are classified using model-based methods. A naïve Bayes classifier selects the highest conditional probability among every class features [5]. HMM has also been used to classify time-series data into time-step related states probabilistically [12]. Feature-based methods, such as decision trees, Shapelet Transform (ST), and Artificial Neural Networks (ANNs), perform a feature extraction procedure to classify vector of features instead. Time-series shapelets are similar subsequences presented as features for classification [13]. Using decision tree classifiers based on time-series shapelets has led to faster and more accurate results [14]. Shapelet-based algorithms have also provided interpretable results with low performance on early time-series classification [15]. Researchers are considering ANNs for time-series manipulation mostly in modeling and forecasting [16]. Moreover, ANNs have received inconclusive results in case of complex nonlinear data classification tasks using their nonlinear learning ability [17].

Non-automatic feature selection is a challenging stage for numeric data which may lead to information loss through discretization [18]. Variant Machine Learning (ML) state-of-the-art classifiers were evaluated on both univariate and multivariate time-series datasets because of their great performance. ML algorithms are modified to more accurate time-series classifiers, as their limited performance is probably due to the high dimensionality of large time-series datasets [19]. In recent years, deep learning has become extremely popular and widely applied to a number of classification tasks. Deep learning frameworks automatically learn and extract features from raw data, not requiring individual hand-crafted features [20]. These methods are applied to univariate as well as multivariate time-series datasets by supporting multiple inputs and outputs [21].

Deep learning methods for time-series classification can be characterized in terms of generative and discriminative models. Generative approach contains Autoencoders and Echo State Networks (ESNs), while discriminative approach contains feature engineering and end-to-end methods [11]. ESNs are used for modeling and classification of nonlinear time-series [22]. These algorithms have been applied to different time-series data, studying the effects of ESNs network architecture on data characteristics [4]. Autoencoders are used to pre-train time-series classifiers as nonlinear feature extractors. Autoencoder deep neural networks such as Recurrent Neural Networks (RNNs) and Convolutional Neural Networks (CNNs) have been at the center of recent studies. These methods are outperforming traditional methods for time-series classification in terms of automatic deep feature generation, classification accuracy and noise tolerance [23]. Recently, a Long Short Term Memory (LSTM) RNN model has been proposed for more accurate and less complex image time-series classification, and also another trained deep RNN approach has provided useful representations for time-series classifiers [24], [25].

Nowadays, different machine learning and deep learning methods are considering time-series data collected from all sorts of domains including industry, medicine, finance, and agriculture, for variant applications such as image, video, gesture, motion, signal, agricultural, and fault classification. Due to the variety of applications, a significant number of publications are conducted in time-series classification field, noting that recent studies are mostly focused on using deep learning based algorithms for the tasks. Readers can find several comprehensive reviews and surveys in time-series data mining tasks and, more specifically, in using deep learning methods for time-series classification. The review papers have provided technical information about basic definitions, theories, and structures; existing literatures, their methods and outcomes; and current and future methods, applications and challenges [1], [5], [11], [19]. In contrast to the reviews mentioned above, a Bibliometric analysis has been carried out in this paper to visualize the trends in existing literature and overview current state-of-the-art topics to help future research.

Unlike traditional narrative literature reviews, which rely on the experience and knowledge of the researchers, bibliometric analysis provides a perspective that can easily be scaled from micro to macro levels [26], [27]. Bibliometrics is defined as measuring academic and organizational performance based on several indicators such as number of publications, number of citations, and collaboration networks [28]. Bibliometric analysis is a powerful tool for quantitatively investigating scientific outputs [29]. Bibliometric analysis of scholarly publications, lead to development of different metrics gaining insight into the intellectual structure of a broad academic discipline and evaluating the impact of scientific documents [30], [31]. A bibliometric study analyses the research productivity, top-cited publications, countries’ scholarly outputs, most frequent keywords and the trend of publications to quantitatively explore a specific research area [32].

There are many Bibliometric analyses applied in different fields of studies including research performance in social science [33], green supply chain [34], knowledge management [31], university research performance [35], fuzzy research [36], drug delivery [32] and many others. Meanwhile, there are also a few Bibliometric studies close to the research area of time-series classification using deep learning, such as global research on artificial intelligence [37], analysis of global remote sensing research [38], support vector machines research trend [39], temporal topic modelling [40], analysis of affective computing researchers [41], and application of artificial intelligence to wastewater treatment [42]. However, none of these studies directly concentrates on using deep learning for time-series classification tasks. On one side, the previous published studies have not treated bibliometric approach in the field of time-series classification using deep learning to the best of our current knowledge. On the other side, bibliometric analysis alone cannot be a substitute for qualitative peer assessment [43]. Therefore, bibliometric results should be used with precautions to evaluate the relevant scholarly outputs [44]. Using qualitative analysis alongside a bibliometric study will elaborate more insight into scholarly outputs [45], [46]. Therefore, top papers for qualitative analysis were selected based on annual citation rate. Citation analysis is an important method of evaluating the impact of a research article [47]. The number of publication citations reflects its contribution to the field of interest and it is often considered as a proxy for its influential [48]. This research aims to explore the research status of deep learning frameworks used for time-series classification tasks, within the past decade, by both the bibliometric and the qualitative approaches. The study highlights the research focuses and hotspots of time-series classification algorithms and applications, that enable scholars to understand the develop trajectories, the key factors of current research, and future challenges of the research area.

SECTION II.

Methodology

There are two major databases for collecting the scholarly publications data, namely Web of Science (WoS)¹ and Scopus² [49]. While WoS is considered one of the largest and most trustworthy databases for literature retrieval and analysis, the journal coverage of Scopus appears more comprehensive than WoS [50]. To choose a suitable database for the current research, a primary title search of “classification” [5] and a topic search of (“time series” OR “time sequence”) were run on both WoS and Scopus databases. The number of documents retrieved were 2,431 publications for WoS and 2,974 publications for Scopus database. These are the number of documents published in all years, containing the word “classification” in their title and the phrase “time series” or “time sequence” in their title, abstract or keywords. Hence, the data was collected from Scopus database on 6th of April 2020 due to the larger number of publications.

In order to select the most recent documents, results were limited to the publications since the year 2010. Therefore, the number of retrieved documents have dropped from 2,974 publications to 2,309. Documents of the year 2020 are excluded from the results, and the final data consists of a total number of 2,201 documents. These are the documents published during 2010–2019 about all variant frameworks and applications for time-series classification task. The VOS Viewer software [51] is used to demonstrate annual number of publications and visualize the top 20 productive countries and the top 50 keywords in time-series classification research. VOS Viewer is a software which plots distance-based maps and clusters keywords retrieved from both titles and abstracts of research documents [52], [53]. The bibliometric visualization map includes linked nodes, where every node is a representation of a keyword, a country, an institute, or an author [54]. The total number of 2,201 documents were refined to 419 by (deep) AND (“neural network∗ ” OR “learning”) search terms. These 419 publications are directly relevant to deep learning methods used in time-series classification research area.

There may be some limitations in data collection procedure of this study, as similarly in other bibliometric studies. The main dataset consists of publications available in Scopus database including classification in their title and either time-series or time-sequence in their topic (title, abstract or keywords). Followed by that, the final dataset is refined by publications including phrases such as either deep learning or deep neural network. However, some authors may have been using the possible synonyms of these phrases instead. Although about 95% of documents are indexed by both WoS and Scopus databases [49], the study will not cover literatures specifically from WoS database. Overall, the large number of publications considered in this bibliometric analysis ensures that the literature represents the major research efforts in time-series classification using deep learning field.

The data is analysed by Bibliometrix-package,³ which is an R-Tool for comprehensive science mapping analysis [55]. The Bibliometrix-package is designed for quantitative research in Scientometrics and Bibliometrics. The tool provides various routines for importing bibliographic data from well-known databases such as Scopus and WoS. The data collection procedure is illustrated in FIGURE 1, as Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) flow diagram [56]. The bibliometric analysis results are combined with a qualitative analysis of publications content. The top 50 most frequently cited articles, among all 419 publications, are categorized into three main subjects. Followed by that, articles with a considerable number of citation per year were selected for a qualitative literature review.

FIGURE 1.

The PRISMA flow diagram for the bibliometric analysis on time-series classification using deep learning.

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SECTION III.

Quantitative Analysis

A total number of 2,201 papers were published on the topic of Time-Series Classification from 2010 to 2019. FIGURE 2 shows an exponential uptrend in the annual number of publications in Time-Series Classification research area. In early 2010, the yearly output of research papers was just above 100. However, the Time-Series Classification research productivity increased slowly over the first 3 years specifically in 2011, where 134 published documents were recorded. There was a very slight rise in publication rates in 2013 and 2015 with 152 and 193 papers respectively. As FIGURE 2 depicts, more and more scholars paid attention to this area from 2015 onwards, where the productivity has started to grow faster. This trend has continued to rise right through 2019, publishing about 459 documents in that year. In general, the yearly scientific production in Time-Series Classification is 4.06 fold during 2010–2019 period.

FIGURE 2.

Analysis of publication years in time-series classification from 2010 to 2019.

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FIGURE 3 visualizes the top 20 productive countries involved in Time-Series Classification research area. The documents published by these 20 top countries was reported as 79.3% of the total number of the publications. The top list includes 11 Western countries and nine Asian countries. China is ranked first collaborating with the total number of 462 papers published, followed by the United States collaborating with 425 and Germany with 174 publications. These three countries are located in different continents: (1) China signifies the best ranking country in Asia; (2) the United States performs North and South America; and (3) Germany marks the highest publication among other countries in Europe. These information show that each continent has a leading country in Time-Series Classification research activities. It’s worth noting that China and the United States are two main research centres of this field, while Germany is in fact joining Time-Series Classification research powers in near future.

FIGURE 3.

Density visualization map of top 20 countries collaboration in time-series classification bibliometric analysis.

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Co-occurrence analysis has been carried out among all sorts of keywords including author’s keywords and Scopus keywords index. Keywords with the minimum number of 60 occurrences were included in the analysis. The bibliometric analysis in Time-Series Classification includes 12,107 keywords, in which an overall number of 50 met the threshold. FIGURE 4 shows the network structure of 50 high frequency author’s keywords and keywords index. Keywords different colours indicate the initial date of their related publications, and lines show the co-occurrence links between different keywords. Time-Series Classification-related publications have been using classical Algorithms and Radiometers from the very beginning in 2014. Time-Series Classification tasks started using Learning Algorithms, followed by Machine Learning approaches in 2017.

FIGURE 4.

The network structure of top 50 keywords (author’s keywords and keywords index) in time-series classification bibliometric analysis.

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After conducting co-occurrence analysis among keywords, it was revealed that the hottest topics in the literature are Deep Learning, Deep Neural Networks, Convolution and Convolutional Neural Network coloured in dark orange. In order to confirm the recently added keywords which may not have enough occurrences to be considered in FIGURE 4, another keywords analysis on publications of years 2018 and 2019 has been conducted. Convolutional Neural Network, LSTM, and Deep Learning are mentioned as the top three keywords during this period. Therefore, the paper focuses on Deep Learning based methods used for Time-Series Classification.

Refining the original 2,201 documents to Deep Learning methods resulted a total number of 419 documents retrieved from Scopus database. Table 1 shows the details of this result. There are 1,409 active authors using Deep Learning in Time-Series Classification tasks. The average number of authors per document is calculated as 3.36, proposing that related articles are mostly the result of collaborative research attempts. There are only 15 single-authored documents on Time-Series Classification using Deep Learning in the analysed dataset. The other 404 documents are co-authored by 1,394 different people. Considerably, the average number of authors authorizing the publications, represented as the global collaboration index, is calculated as 3.45. This shows a high trend of co-authorship in Time-Series Classification research products focused on Deep Learning algorithms. According to Table 1, the recorded average number of 6.921 citations per documents appeared to be low, demonstrating smaller number of highly cited and more low-cited publications.

TABLE 1 The Summarized Data for the Bibliometric Study on Time-Series Classification Using Deep Learning

FIGURE 5 indicates the rapid increase in the number of publications in Time-Series Classification using Deep Learning. As the cumulative graph shows, the area of Time-Series Classification using Deep Learning is approaching 215 publications per year in 2019. This is approximately half of the total number of 459 publications on Time-Series Classification in that year. Interestingly, the rise in the number of research productions in Time-Series Classification has slowed down compared to the fast rate of research on Time-Series Classification using Deep Learning. As it is shown in FIGURE 5, Deep Learning methods have made their place through Time-Series Classification tasks right after 2013, where the number of published documents has grown from 1 in 2013 to 12 in 2015. Continuously, a sharp growth pattern has appeared after 2015 for the research productions on Time-Series Classification using Deep Learning, which means more researchers are focusing in this new area.

FIGURE 5.

A cumulative graph of publication years in time-series classification research field limited to deep learning methods from 2010 to 2019.

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FIGURE 6 shows the scientific collaboration network of the top 20 countries in the analysis of Time-Series Classification using Deep Learning. The research collaboration between different countries is shown by coloured lines and their size shows the strength of cooperation between two connected countries. China, as the most productive country in Time-Series Classification research field, has remained at the first place of the list with the total of 114 published documents in Time-Series Classification using Deep Learning. These publications are mostly collaborated with the USA, followed by Canada, Singapore, Hong Kong and Finland. The USA has ranked the second by collaborating with 87 papers, just above 20% of the total publications in Time-Series Classification using Deep Learning research area since the year 2010.

FIGURE 6.

The network structure of top 20 countries collaboration in time-series classification using deep learning bibliometric analysis.

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As the collaboration pathways show, United Kingdom and Germany have a considerable number of joint papers. The total number of related collaborated publications is reported as 34 documents for United Kingdom and 29 documents for Germany in the time span of 2010-2019. Other high collaborative countries include France, Canada, India, Switzerland, Finland, Australia and Denmark. Different colours in FIGURE 6 show different clusters of international research cooperation. Two main country clusters can be concluded from the graph: (1) the “China, USA and Canada” community; (2) the “Germany, United Kingdom, Netherland and India” community. Other two smaller communities as “Spain, Brazil and France”, and “Australia, Switzerland and France” can be seen. These collaboration communities help researchers around the world to spot their colleagues to establish more research productions.

FIGURE 7 indicates the number of multiple and single publications in Time-Series Classification using Deep Learning across top-cited countries. The top countries are selected based on the nationality of the corresponding author. There are a total of 57 articles written by Chinese corresponding authors including nine multiple country publications (MCPs) and 48 single country publications (SCPs). American corresponding authors have made USA the most collaborative country, contributing by more than 20% of its total literature production in about 10 years. French and German corresponding authors show an equal research productivity of 17 articles in the field of Time-Series Classification using Deep Learning, in which their publications contain four and nine MCPs respectively. As FIGURE 7 shows, most published documents are written by authors from the same country, which means that authors usually collaborate with people in the same national background.

FIGURE 7.

Total number of publications (multiple country publication and single country publication) by top 20 corresponding author’s countries in time-series classification using deep learning.

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The 10-year development of sources in the field of Time-Series Classification using Deep Learning is shown in FIGURE 8. The graph shows the different number of published documents by top 10 most productive sources during the time period of 2010 to 2019. The scientific journal of IEEE Access has marked an increasing occurrence in the number of publications in Time-Series Classification using Deep Learning. New researchers using Deep Learning methods on Time-Series Classification tasks are more likely to publish their papers in the IEEE Access journal as it has published around 13 related papers in 2019. Other than IEEE Access, the occurrences of some more sources like Lecture Notes in Computer Science and Remote Sensing journal have developed rapidly since 2018, reaching to over eight annual publications in 2019. Although sources such as Procedia Computer Science journal and SPIE Conference Proceedings started publishing papers related to Time-Series Classification using Deep Learning in early 2015, nowadays they are publishing fewer articles compared to others.

FIGURE 8.

Annual occurrences (with Loess Smoothing) of top 10 sources in time-series classification using deep learning from 2010 to 2019.

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Table 2 represents the occurrence of the top author’s keywords in the time span of 2010-2019. The list covers keywords which have appeared at least eight times in all publications included in the analysed dataset. Accordingly, among 982 identified author’s keywords in Time-Series Classification using Deep Learning, only 18 have met the threshold. Deep Learning as the strongest keyword with the total of 81 occurrences, is the most preferred phrase to express the concept. The keywords such as Classification, Time Series Classification, and Convolutional Neural Network/s (CNN) are commonly used in the keywords set of related publications. As Table 2 indicates, researchers are more frequently using CNN methods for classifying time-series datasets compared to Long Short Term Memory (LSTM) or other Recurrent Neural Network/s (RNN) algorithms. Interestingly, all these top author’s keywords have increasing occurrences in recent publications.

TABLE 2 The Occurrence of Top Author’s Keywords in Time-Series Classification Using Deep Learning Bibliometric Analysis

FIGURE 9 visually discovers the extracted keywords index from Scopus database by clustering them into variant categories using clustering techniques in combination with multidimensional scaling (MDS). The conceptual structure map of top 30 index keywords indicates that publications related to Time-Series Classification using Deep Learning can be organised into three main clusters. The red cluster, as the most comprehensive cluster, brings together the index keywords of all publications included in the analysed dataset considering different deep learning algorithms for time-series classification. The cluster contains 19 top index keywords like Deep Learning, Deep Neural Networks, Convolutional Neural Network, Recurrent Neural Networks, Long Short Term Memory, Feature Extraction, Multivariate Time-Series and others.

FIGURE 9.

Conceptual structure map (with multidimensional scaling) of top 30 Scopus keywords index in time-series classification using deep learning bibliometric analysis.

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The green cluster gathers three index keywords such as Support Vector Machines (SVM), Image Classification and Remote Sensing. Most publications including these index keywords have designed and used deep learning methods for remotely sensed time-series datasets classification. The blue cluster is comprised of the remaining eight top index keywords mainly including Machine Learning, Signal Processing, Human, Brain, Electroencephalography, Time-Series Analysis and Artificial Neural Network. Research articles in this cluster have proposed variant deep learning-based signal classification methods and applications. More specifically, these articles contain general discussions about the usage of previous machine learning or artificial neural network based algorithms.

SECTION IV.

Qualitative Analysis

Keywords cluster analysis helps identify research trends and status in the field of time-series classification focusing on deep learning methods. The knowledge clusters show prominent groups of themes and characterize the research directions based on the extracted keywords index from the literature. Time-series classification most productive literatures generally concentrate on novel deep learning algorithms and their application in image classification and signal processing. In this section the noticeable research clusters identified through the bibliometric analysis are qualitatively analysed. Keywords index automatic clustering is combined with a qualitative analysis of the publications content.

All documents in time-series classification using deep learning according to Scopus database are sorted by annual citation rate in descending order. Each paper’s citation rate is calculated by dividing total citations received by the number of years passed since publication. Evaluating top-cited papers’ content helps to identify the most significant research topics within the study areas. Publications with the highest citation rate are qualitatively analysed based on all titles and abstracts of the full paper set. The top 50 most frequently cited papers are categorized into common key research directions shown in Table 3 in Appendix. Review papers are excluded from the qualitative analysis set as they carry information about all three categories.

TABLE 3 Top 50 Most-Cited Papers Categorized into Three Main Research Clusters

Documents with the highest citation rates are selected from the top of the most-cited articles list for more in-depth analysis. The nominated articles have been cited at least 10 times per year with their average citation rates ranging from 49.00 to 10.40. Top 23 most-cited articles are considered for detailed qualitative analysis since the number of citations per year suddenly drops to 8.20 afterwards. Three main research topics of time-series classification using different Deep Neural Networks (DNNs) algorithms for variant remote sensing and signal processing purposes are conducted during the analysis. The extracted research areas confirm the revealed research clusters of previous factorial analysis. The following section presents an overview of every highly cited paper purpose related to each research cluster.

A. Different Deep Neural Networks Algorithms for Time-Series Classification

Different baseline models are proposed for time-series classification using DNNs. Variant network architectures are capable of providing fully comprehensive baseline models. Plain artificial neural networks baselines such as Multilayer Perceptron (MLP) are considered similar to the best traditional 1 Nearest Neighbor - Dynamic Time Warping (1NN-DTW) baseline. Feature extraction using Fully Conventional Networks (FCNs) has performed better than traditional approaches. Deeper neural networks have also been applied to time-series data using residual networks such as ResNet structure. The different baseline models classify time-series from scratch with minimum complexity [9].

Time-series classification has been done by combining FCNs and LSTM from Recurrent Neural Networks (RNNs) family. LSTM-FCN has supplemented FCNs performance by raising model parameters count and minimizing dataset pre-processing. Although Attention Long Short Term Memory - FCNs (ALSTM-FCN) have provided a strong baseline using attention mechanism, the cells failed in classifying some time-series datasets [57]. Convolutional Neural Network (CNN) framework has improved time-series classification accuracy and noise tolerance by automatically generating deep input features [23]. However, several machine learning algorithms exist, outperforming the standard CNN in terms of time-series classification accuracy [2].

Computer vision classification and imputation algorithms can be used due to time-series encoding as images. Gramian Angular Fields (GAF) and Markov Transition Fields (MTF) are different frameworks used for time-series image translation. A proposed method has combined representations as GAF-MTF images and applied Tiled Convolutional Neural Networks (Tiled CNNs) for classification [58]. Using transfer learning for deep learning baseline models is counted as a replacement for time-series classification from scratch. Transfer Deep Convolutional Neural Networks (DCNNs) has improved the accuracy of different time-series classification by fine tuning the model after pre-training [59].

Different deep learning frameworks are suggested for multivariate time-series (with at least two time-dependant variables) classification. Feature learning using Multi-Channels Deep Convolutional Neural Networks (MC-DCNNs) has improved in performance compared to the traditional feature-based approaches. The baseline represents features at the last network layer as a combination of learned features from univariate time-series of every channel [18], [20]. Multivariate Convolutional Neural Network (MVCNN) is an extension of the CNN framework considering multivariate and lag-feature characteristics for multivariate time-series classification [60]. Both LSTM-FCN and ALSTM-FCN algorithms are recently developed to be used as multivariate time-series classifiers. The method has improved the accuracy and minimized the pre-processing as a result of enhancing the fully convolutional block [61].

B. Applications of Time-Series Classification in Remote Sensing

Deep learning-based classification frameworks have been used as the most efficient approaches for remotely sensed time-series datasets. Time-series observations from multitemporal remote sensing benefits in different vegetation types classification. Different deep learning classification algorithms are applied to process vegetation index (VI) time-series. Landsat Enhanced Vegetation Index (EVI) time-series classify economic summer crops designed by One-Dimensional Convolutional Neural Networks (Conv1D) and LSTM. The Conv1D-based model has achieved the highest accuracy as a multi-level feature extraction. The LSTM baseline model has also been efficient in describing temporal patterns at different frequencies [62].

DNN-based approaches have integrated time-series Landsat information from USDA’s Common Land Units (CLUs) for field-level crop-type classification. The baseline model has applied field-level and in-season classification on corn/soybean dominated fields with higher performance and lower costs [63]. Agricultural land-cover mapping is improving due to the speckle noise in radar images compared to optical images. Three-dimensional crops information is available using multitemporal Synthetic Aperture Radar (SAR) Sentinel-1 remote sensing data. Deep RNN-based techniques have been applied to the radar time-series data achieving great performance classification [64].

Different RNN algorithms such as LSTM model has also classified multitemporal spatial data from satellite images time-series (SITS) using alternative feature representations [65]. For a full representation of land-cover classification information for SITS, a deep learning two-branch architecture as a mixture of CNN and RNN algorithms is proposed [66]. Temporal Convolutional Neural Network (TempCNN) method has also been efficient in more accurate classification of SITS by learning temporal and spectral features automatically [67].

C. Applications of Time-Series Classification in Signal Processing

Deep learning has proposed variant signal classification methods using visual inspection of signals. Many sleep disorders have been recognised via sleep stage (every 30 seconds of signal) classification. DNN methods based on linear spatial filtering and temporal convolutions have exploited the multivariate and multimodal time-series of Polysomnography (PSG) signals containing electroencephalography (EEG), electrocardiography (ECG), electrooculography (EOG), and electromyography (EMG). The model classifies real-time sleep stages performing with minimum computational time and cost compared to convolutional networks or decision trees [68]. Heart interbeat RR time-series are composed into Intrinsic Mode Functions (IMFs) for feature evaluation. DNNs are coupled with deep features extracted from RR time-series and EEG signals for classification of sleep stages [69].

Different deep learning methods are developed for nonstationary time-series classification as EEG signals in motor imagery classification. Multilevel convolutional feature extraction methods have been applied to CNNs for EEG decoding [70]. Restricted Boltzmann Machine (RBM) based deep learning scheme has improved the performance of motor imagery classification using an additional network output layer of Frequential Deep Belief Network (FDBN). In FDBN, frequency domain input of EEG signals is generated by either Fast Fourier Transform (FFT) or Wavelet Package Decomposition (WPD) and passes through RBMs for classification [71]. Semi-supervised paradigm of Deep Belief Networks (DBNs) has provided fast classification of multiple time-series EEG waveforms. DBNs method has also resulted powerful anomaly measurement of clinical EEG signals using raw time-series inputs [72].

Different deep learning algorithms are proposed for multivariate time-series classification using multivariate sensor signals from semiconductor manufacturing process. Advanced Fault Detection and Classification (FDC) along with CNN model (FDC-CNN) has outperformed others by locating time-series information which represent process faults [73]. Similar deep learning approach of DCNN has been applied to manufacturing gearbox fault type and fault severity classification. Underlying deep features of time-frequency images have been extracted for classification. Graphical images are encoded from one-dimensional time-series vibration signals through wavelet analysis. The image processing advantage of DCNNs has resulted great classification accuracy in dynamical systems [74].

SECTION V.

Conclusion and Future WORK

The study provides a detailed quantitative and qualitative analysis, based on publications in time-series classification retrieved from Scopus database from 2010 to 2019. The bibliometric analysis on time-series classification discovered the most recent subfield of study as deep learning. The dataset is refined by deep learning exploring the development status in terms of publication years, countries, sources, keywords and topics. The annual publications in time-series classification using deep learning research field has increased in the past 10 years, showing the potential to grow rapidly in the future. The analysis of international cooperation helps fresh researchers to spot potential research collaborators. According to countries related publications, China is the most productive country collaborating with over a hundred publications in time-series classification using deep learning during 2010-2019. The USA is also known as the most collaborative country in this bibliographic set, as American corresponding authors have several collaborations with other nations.

Studying the evolution of journals publishing time-series classification using deep learning research, identifies highly-targeted sources for new researchers of the field. As a result of the source growth analysis, IEEE Access appears to be the highly productive platform in which most researchers on time-series classification using deep learning publish their papers. Finding research hotspots is possible by calculating the total appearances of keywords during this 10-year period. The analysis of author’s keywords occurrence shows that scientific productions in time-series classification using deep learning are mainly concerned with convolutional neural networks, long short term memory, machine learning, recurrent neural networks, deep neural networks, time-series analysis, EEG, remote sensing, dynamic time warping, transfer learning, crop classification and multivariate time-series.

Topical analysis within the field of time-series classification using deep learning provides the active core categories in this area. The factorial analysis of keywords index and the qualitative analysis of top-cited publications content demonstrate the same research themes concentrated on deep learning algorithms, remote sensing and signal processing applications. A large number of publications in time-series classification using deep learning are directing their studies to the different baselines of deep neural networks with special emphasis on deep convolutional neural network frameworks.

This paper is intended to explain how the research frontiers in time-series classification using deep learning area have changed over the past decade. The paper is crucial for understanding the usage of deep learning algorithms for time-series classification tasks and following the research directions for further developments in the field. Research on improving deep learning algorithms and extending their applications for time-series classification tasks are still ongoing. It can be predicted that a wide range of researchers will start working on the mentioned hot research topics of time-series classification research field focusing on deep learning methods, leading to a great number of publications.

Authors

Saba Ale Ebrahim

School of Electrical Engineering, Iran University of Science and Technology, Tehran, Iran

Saba Ale Ebrahim was born in Tehran, Iran, in February 1996. She received the B.Sc. degree in electrical engineering (control engineering) from the K. N. Toosi University of Technology (KNTU), in 2018. She is currently pursuing the master’s degree in control engineering with the Iran University of Science and Technology (IUST). Her research interests include control systems, time-series classification, fault detection, biomedical applications of control, drug delivery, magnetic nanoparticles, and microelectromechanical systems (MEMS).

Javad Poshtan

School of Electrical Engineering, Iran University of Science and Technology, Tehran, Iran

Javad Poshtan received the B.Sc. degree in electrical engineering from Tehran University, Tehran, Iran, in 1987, the M.Sc. degree from the Sharif University of Technology, Tehran, in 1991, and the Ph.D. degree from the University of New Brunswick, Fredericton, NB, Canada, in 1997. He has been with the Department of Electrical Engineering, Iran University of Science and Technology, Tehran, since 1997. As a Professor at IUST, he is involved in academic and research activities in areas, such as control systems theory, system identification, and fault diagnosis.

Seyedh Mahboobeh Jamali

Eshragh Institute, Ministry of Education district 7, Tehran, Iran

Seyedh Mahboobeh Jamali received the Ph.D. degree in physics education from the School of Educational Studies (PPIP), Universiti Sains Malaysia, Penang, Malaysia. She has over 29 years’ experience in teaching physics at High school levels. Her current research interests include working on the effect of science, technology, engineering, and mathematics (STEM) project-based learning, on the problem solving ability of High school physics students and their achievements. Besides, of her major interest, she involves in improving research visibility and impact projects to increase a university’s international ranking. She is interpreting the bibliometric study results as well.

Nader Ale Ebrahim

Research and Technology Department, Alzahra University, Tehran, Iran

Nader Ale Ebrahim received the Ph.D. degree in technology management. He is currently working as an Adjunct Lecturer with Alzahra University. He is also a Research Visibility and Impact Freelancer Consultant. He was working as a Visiting Research Fellow with the Centre for Research Services, Institute of Management and Research Services (IPPP), University of Malaya. He has over 23 years’ experience in the field of virtual Research and Development teams. His current research interests include open access, research visibility, research tools, and bibliometrics. He is well known as the Creator of Research Tools Box. He believes that research cycle does not ends with publications alone, thus he encourages pro-activeness in dissemination of research output.

Alzahra University ranked 400+ in THE Asia University Rankings 2020

Source: https://www.linkedin.com

Times Higher Education (THE) Asia University Rankings 2020: results announced. Alzahra University ranked 400+ in THE Asia University Rankings 2020 https://lnkd.in/fGZWy2M

Thursday, 4 June 2020

Declaration on transparent editorial policies for academic journals

Source: https://www.ru.nl/science/isis/research/transparency-declaration/

Declaration on transparent editorial policies for academic journals

Peer review and post-publication discussions are important pillars of quality management in academic publishing. However, it is surprisingly hard to learn the details of research journals’ peer review procedures and editorial policies from their websites and editorial instructions. Journal websites often do not contain information about reviewer selection, review criteria, blinding, the use of digital tools such as text similarity scanners, as well as policies on corrections and retractions.

Transparency about editorial policies is vital for several reasons. Authors are entitled to know exactly how and on what grounds their manuscript will be assessed. Reviewers benefit from clear and specific instructions about their task and role in the review process. Quality journals may distinguish themselves from predatory ones by articulating clear editorial policies. Transparent policies also enable research on the benefits of different peer review practices, which is required to ultimately facilitate better review. In general, transparency is crucial for building trust in the community, which is essential for the functioning of science.

Transparent editorial policies should explain procedures for four publication and peer review phases:

At submission
Explain editorial governance, including the precise composition of the editorial board, the scope of the journal, the applicable ethics policies, and the use of journal metrics, including rejection rates.
During review
Explain the criteria for article selection (e.g. the relevance of novelty and/or anticipated impact and methodological rigour) and the timing of review in the publication process (e.g. whether registered reports and/or post-publication review are used). Be clear about the extent to which authors’ and reviewers’ identities will be known (blinding), and to whom review reports will be communicated. Specify how reviewers will be selected, instructed, or possibly trained. Also explain how digital tools such as similarity scanners and scanners for digital image manipulation will be used and whether any reporting guidelines are applied.
Publication
Make information about the review process of published articles available on the article-level, by detailing the roles in the review process (e.g. specify how many reviewers were involved and what other people contributed to the final decision), what criteria for acceptance and what digital tools were used.
Post-publication
Explain the criteria and procedures for corrections, expressions of concern, retractions, or other rectifications or changes to published material.

Transparent editorial policies should be explicit and detailed. For example, mentioning that ‘blind review’ is performed is not enough, since this can refer to anonymised authors, authors removed from references, anonymised reviewers, identities that are revealed after review or publication, or even anonymised editors. Similarly, announcing the use of a similarity check does not explain what will be done with the results. Hence, procedures should be specified in detail. Information about editorial policies should be kept up to date and changes should be documented and archived. This can either be done on the journal homepage, in the guide for authors or on the article-level along with published articles.

Making editorial policies transparent will require an effort by publishers and editors. However, it builds trust in the research community and constitutes an essential measure to improve the fairness, integrity and quality of the journal review process.

This declaration was issued by the participants of the meeting “IT Tools in Academic Publishing: between Expectations and Challenges”, Leiden University 5-6 July 2018.

Authors

The participants of the workshop are authors of this declaration. While drawing on their professional backgrounds, the participants are signatories of the declaration in their private capacity:

IJsbrand Jan Aalbersberg (Elsevier)
Isabelle Boutron (Paris Descartes University, INSERM- Sorbonne Paris Cité)
Kim Eggleton (IOP)
Joed Elich (Brill)
Catriona Fennell (Elsevier)
Laura Henderson (Frontiers Media)
Jean Philippe de Jong (Koninklijke Nederlandse Akademie van Wetenschappen)
Cyril Labbé (Université Grenoble Alpes)
Ana Marušić (University of Split School of Medicine, European Association of Science Editors)
Bahar Mehmani (Elsevier)
Hans van der Mey (Brill)
Alenka Princic (TU Delft library)
Brandon Stell (PubPeer)
Jason Roberts (Origin Editorial)
Johan Rooryck (Leiden University)
Jelte Wicherts (Tilburg University, StatCheck)

Workshop Organisers:

Willem Halffman (Radboud University)
Serge Horbach (Radboud University, Leiden University)
Thed van Leeuwen (Leiden University)
Andrea Reyes Elizondo (Leiden University)
Sarah de Rijcke (Leiden University)

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Do you also want to sign the declaration on transparent editorial policies for academic journals? Sign it today.

Sign the transparency declaration

Signatories

Institutional signatories

The European Association of Science Editors (EASE)

Cabells

Individual signatories

Jing Wang - Radboud University
Alex La Vos - Radboud University
Tung Tung Chan - Centre for Science and Technology Studies, Leiden University
Munawar A. Anees - Dr. Hasan Murad Centre for Knowledge Futures
Dario Vasquez - International Journal of Management, Economics and Social Sciences
M. S. Ahmad - Science Publications
Itsar Bolo Rangka - Universitas Indraprasta PGRI Jakarta
Ch. Mahmood Anwar - Scholars Index
Alexander Kostyuk - Virtus Interpress
Ksenija Bazdaric - Croatian Medical Journal and European Scence Editing
Paola De Castro - Istituto Superiore di Sanità
Wytske Hepkema - Radboud University
Farrokh Habibzadeh - NIOC Health Organization, Iran
Kamlesh Kumar Sahu - Indian Journal of Psychiatric Social Work
Carlos Mauricio Moreno Tellez - Revista Facultad de Ingeniería (UPTC)
Héctor Luis Pittman Villarreal - Common Ground Research Networks
Natalino Perovano Filho - Revista ODEERE
Luis Álvarez Rodas - Universidad Politecnica Salesiana
Maria Giovanna Guedes Farias - Universidade Federal do Ceará, Revista Informação em Pauta
Fouad K. Mohammad - Ministry of Higher Education and Scientific Research, Iraq
Mirta Natalia Bertune Fatgala - Universidad Nacional de La Matanza
German Gonzalez - Estudios económicos
Michal Kokowski - Studia Historiae Scientiarum
Tomàs Baiget - Ediciones Profesionales de la Información SL
Nader Ale Ebrahim - Alzahra University

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Saturday, 6 June 2020

Nader Ale Ebrahim

Centre for Research Services, Institute of Management and Research Services (IPPP), University of Malaya (UM)

Visiting Research Fellow

University of Malaya (UM) - Department of Engineering Design and Manufacture

102

35,207

52

179

Scholarly Papers (102)

Quantitative and Qualitative Analysis of Time-Series Classification Using Deep Learning

Introduction

Methodology

Quantitative Analysis

Qualitative Analysis

A. Different Deep Neural Networks Algorithms for Time-Series Classification

B. Applications of Time-Series Classification in Remote Sensing

C. Applications of Time-Series Classification in Signal Processing

Conclusion and Future WORK

Authors

Thursday, 4 June 2020

Declaration on transparent editorial policies for academic journals

Authors