Loc Nguyen

Designation:
Professor
Department:
Department of Mathematics
University:
Independent scholar
Country:
Vietnam
Email: Journal Associated: Annals of Mathematics and Physics Biography:

Loc Nguyen is an independent scholar from 2017. He holds Master degree in Computer Science from University of Science, Vietnam in 2005. He holds PhD degree in Computer Science and Education at Ho Chi Minh University of Science in 2009. His PhD dissertation was certificated by World Engineering Education Forum (WEEF) and awarded by Standard Scientific Research and Essays as excellent PhD dissertation in 2014. He holds Postdoctoral degree in Computer Science, certified by Institute for Systems and Technologies of Information, Control and Communication (INSTICC) in 2015. Now he is interested in poetry, computer science, statistics, mathematics, education, and medicine. He serves as reviewer and editor in a wide range of international journals and conferences from 2014. He is volunteer of Statistics Without Borders from 2015. He was granted as Mathematician by London Mathematical Society for Postdoctoral research in Mathematics from 2016. He is awarded as Professor by Scientific Advances and Science Publishing Group from 2016. He was awarded Doctorate of Statistical Medicine by Ho Chi Minh City Society for Reproductive Medicine (HOSREM) from 2016. He has published 71 papers and preprints in journals, books and conference proceedings. He is author of 2 scientific books and 1 postdoctoral dissertation. He is author and creator of 6 scientific and technological products.

Research Interest: optimization, applied mathematics

URL: http://www.locnguyen.net

Grants: Research Incentive Fund (RIF) Grant Activity Code: R19093– Zayed University, UAE.

List of Publications:
•    Amer, A. A., Abdalla, H. I., & Nguyen, L. (2021, February 10). Enhancing recommendation systems performance using highly-effective similarity measures. (J. Lu, E. A. Edmonds, & H. Fujita, Eds.) Knowledge-Based Systems, 217. doi:10.1016/j.knosys.2021.106842
•    Nguyen, L (2021, January 26). A general framework of particle swarm optimization. Preprints 2021, 2020100550 (doi: 10.20944/preprints202101.0528.v1).
•    Nguyen, L (2020, November 1). Conditional Mixture Model for Modeling Attributed Dyadic Data. Preprints 2020, 2020100550 (doi: 10.20944/preprints202011.0266.v1).
•    Nguyen, L (2020, November 1). Learning Dyadic Data and Predicting Unaccomplished Co-Occurrent Values by Mixture Model. Preprints 2020, 2020100550 (doi: 10.20944/preprints202011.0038.v1).
•    Nguyen, L (2020, October 28). Conditional Mixture Model and Its Application for Regression Model. Preprints 2020, 2020100550 (doi: 10.20944/preprints202010.0550.v2).
•    Shafiq, A., & Nguyen, L (2020, January). Marangoni convective flow of nanoliquid towards a riga surface. ResearchGate 2020 Preprint.
•    Nguyen, L., & Amer, A. A. (2019, October 17). Advanced Cosine Measures for Collaborative Filtering. (ITS, Ed.) Adaptation and Personalization (ADP), 1(1), 21-41. doi:10.31058/j.adp.2019.11002
•    Nguyen, L., & Shafiq, A. (2019, January 29). Semi-mixture Regression Model for Incomplete Data. (T. Schmutte, Ed.) Adaptation and Personalization (ADP), 1(1), 1-20. doi:10.31058/j.adp.2019.11001
•    Nguyen, L., & Shafiq, A. (2018, December 31). Mixture Regression Model for Incomplete Data. (L. E. Istael, Ed.) Revista Sociedade Científica, 1(3), 1-25. doi:10.5281/zenodo.2528978
•    Nguyen, L., & Ho, Thu-Hang T. (2018, December 17). Fetal Weight Estimation in Case of Missing Data. (T. Schmutte, Ed.) Experimental Medicine (EM), 1(2), 45-65. doi:10.31058/j.em.2018.12004
•    Nguyen, L., & Ho, Thu-Hang T. (2018, August 1). Phoebe Framework and Experimental Results for Estimating Fetal Age and Weight. In T. F. Heston, & T. F. Heston (Ed.), eHealth - Making Health Care Smarter (pp. 99-123). Rijeka, Croatia: InTechOpen. doi:10.5772/intechopen.74883
•    Nguyen, L. (2018, July 10). Proposal of Evaluating Patients' Satisfaction about Quality of Healthcare System by Non-parametric Quality Control. Open Science Framework (OSF) Preprints. doi:10.17605/OSF.IO/VUMHN
•    Nguyen, L., & Ho, Thu-Hang T. (2018, May 7). Early Fetal Weight Estimation with Expectation Maximization Algorithm. (T. Schmutte, Ed.) Experimental Medicine (EM), 1(1), 12-30. doi:10.31058/j.em.2018.11002
•    Nguyen, L., Do, M.-P. T. (2018, January 18). A Novel Collaborative Filtering Algorithm by Bit Mining Frequent Itemsets. PeerJ Preprints, 6(e26444v1). doi:10.7287/peerj.preprints.26444v1
•    Nguyen, L. (2018, January 17). A Maximum Likelihood Mixture Approach for Multivariate Hypothesis Testing in case of Incomplete Data. Open Science Framework (OSF) Preprints. Retrieved from http://osf.io/whvq8
•    Nguyen, L. (2018, January 17). Nonparametric Hypothesis Testing Report. Open Science Framework (OSF) Preprints. Retrieved from http://osf.io/tj9cf
•    Nguyen, L. (2017, November 2). Converting Graphic Relationships into Conditional Probabilities in Bayesian Network. In J. P. Tejedor, & J. P. Tejedor (Ed.), Bayesian Inference (pp. 97-143). Rijeka, Croatia: InTechOpen. doi:10.5772/intechopen.70057
•    Nguyen, L. (2017, April 24). A Proposal of Loose Asymmetric Cryptography Algorithm. Proceedings of The 2nd International Conference on Software, Multimedia and Communication Engineering (SMCE 2017), DEStech Transactions on Computer Science and Engineering (pp. 414-422). Shanghai: DEStech. doi:10.12783/dtcse/smce2017/12462
•    Nguyen, L. (2017, June 9). Global Optimization with Descending Region Algorithm. (L. Nguyen, & et al., Eds.) Special Issue “Some Novel Algorithms for Global Optimization and Relevant Subjects”, Applied and Computational Mathematics (ACM), 6(4-1), 72-82. doi:10.11648/j.acm.s.2017060401.17
•    Nguyen, L., & Ho, Thu-Hang T. (2017, March 13). Experimental Results of Phoebe Framework: Optimal Formulas for Estimating Fetus Weight and Age. (H. J. Shaji, M. C. Portillo, & M. M. Zdanowicz, Eds.) Journal of Community & Public Health Nursing, 3(2), 1-5. doi:10.4172/2471-9846.1000163
•    Nguyen, L. (2016, October 31). Beta Likelihood Estimation in Learning Bayesian Network Parameter. In United Scholars Publications (Author), Advances in Computer Networks and Information Technology (Vol. II). USA: CreateSpace Independent Publishing Platform. Retrieved from https://goo.gl/R4dwrf
•    Nguyen, L. (2016, October 18). Estimating Peak Bone Mineral Density in Osteoporosis Diagnosis by Maximum Distribution. International Journal of Clinical Medicine Research (IJCMR), 3(5), 76-80. Retrieved from http://www.aascit.org/journal/archive2?journalId=906&paperId=4532
•    Nguyen, L. (2016, August 18). A New Aware-context Collaborative Filtering Approach by Applying Multivariate Logistic Regression Model into General User Pattern. (F. Shi, Ed.) Journal of Data Analysis and Information Processing (JDAIP), 4(3), 124-131. doi:10.4236/jdaip.2016.43011
•    Nguyen, L. (2016, June 17). Longest-path Algorithm to Solve Uncovering Problem of Hidden Markov Model. (L. Nguyen, & M. A. MELLAL, Eds.) Special Issue “Some Novel Algorithms for Global Optimization and Relevant Subjects”, Applied and Computational Mathematics (ACM), 6(4-1), 39-47. doi:10.11648/j.acm.s.2017060401.13
•    Nguyen, L. (2016, June 17). Tutorial on Hidden Markov Model. (L. Nguyen, & M. A. MELLAL, Eds.) Special Issue “Some Novel Algorithms for Global Optimization and Relevant Subjects”, Applied and Computational Mathematics (ACM), 6(4-1), 16-38. doi:10.11648/j.acm.s.2017060401.12
•    Nguyen, L. (2016, June 17). Tutorial on Support Vector Machine. (L. Nguyen, & M. A. MELLAL, Eds.) Special Issue “Some Novel Algorithms for Global Optimization and Relevant Subjects”, Applied and Computational Mathematics (ACM), 6(4-1), 1-15. doi:10.11648/j.acm.s.2017060401.11
•    Nguyen, L. (2016, June 10). Continuous Observation Hidden Markov Model. (M. G. De Garcia, Ed.) Kasmera Journal, 44(6), 65-149.
•    Nguyen, L. (2016, April 27). Beta Likelihood Estimation and Its Application to Specify Prior Probabilities in Bayesian Network. (H. M. Srivastava, P. Bracken, R. Jedynak, anonymous, & S. Zimeras, Eds.) British Journal of Mathematics & Computer Science, 16(3), 1-21. doi:10.9734/BJMCS/2016/25731.
•    Nguyen, L. (2016, April 8). New version of CAT algorithm by maximum likelihood estimation. (B. N. Buszewski, Ed.) Sylwan Journal, 160(4), 218-244.
•    Nguyen, L. (2016, March 28). Theorem of SIGMA-gate Inference in Bayesian Network. (V. S. Franz, Ed.) Wulfenia Journal, 23(3), 280-289.
•    Nguyen, L. (2016, February). Specifying Prior Probabilities in Bayesian Network by Maximum Likelihood Estimation method. (B. N. Buszewski, Ed.) Sylwan Journal, 160(2), 281-298.
•    Nguyen, L., & Ho, H. (2015, November 23). A proposed method for choice of sample size without pre-defining error. (F. Shi, Ed.) Journal of Data Analysis and Information Processing (JDAIP), 3(4), 163-167. doi:10.4236/jdaip.2015.34016
•    Nguyen, L., Do, M.-P. T. (2015, November 13). Hudup: A Framework of E-commercial Recommendation Algorithms. In A. Fred, J. Dietz, D. Aveiro, K. Liu, & J. Filipe (Ed.), Final Program and Book of Abstracts of The 7th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management (IC3K 2015) (p. 56). Lisbon: SCITEPRESS. Retrieved from https://goo.gl/BQaEcm
•    Nguyen, L. (2015, November 13). A New Approach for Collaborative Filtering based on Bayesian Network Inference. The 7th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management. 1: KDIR (IC3K-2015), pp. 475-480. Lisbon, Portugal: SCITEPRESS - Science and Technology Publications, Lda. doi:10.5220/0005635204750480
•    Nguyen, L. (2015, October 9). An Advanced Approach of Local Counter Synchronization in Timestamp Ordering Algorithm in Distributed Concurrency Control. (N. John, Ed.) Open Access Library Journal (OALib Journal), 2(10), 1-5. doi:10.4236/oalib.1100982
•    Nguyen, L. (2015, September 28). Introduction to A Framework of E-commercial Recommendation Algorithms. (A. e. Shabayek et al., Eds.) American Journal of Computer Science and Information Engineering (AJCSIE), 2(4), 33-44. Retrieved from http://www.aascit.org/journal/archive2?journalId=912&paperId=1894.
•    Nguyen, L. (2015, January 22). A User Modeling System for Adaptive Learning. In S. Schreiter (Ed.), The 2014 International Conference on Interactive Collaborative Learning (ICL 2014) (pp. 864-866). The 2014 World Engineering Education Forum (WEEF2014), Dubai, UAE: IEEE. doi:10.1109/ICL.2014.7017887
•    Nguyen, L., & Ho, H. (2015, January 12). A fast computational formula for Kappa coefficient. (A. Genc, S.-A. Xue, R. Rison, & V. Rocha, Eds.) Science Journal of Clinical Medicine (SJCM), 4 (1), 1-3. doi:10.11648/j.sjcm.20150401.11
•    Nguyen, L. (2015, January 10). Feasible length of Taylor polynomial on given interval and application to find the number of roots of equation. (A. Moustafa et al., Eds.) International Journal of Mathematical Analysis and Applications, 1 (5), 80-83. Retrieved from http://www.aascit.org/journal/archive2?journalId=921&paperId=1017
•    Nguyen, L. (2014, December 6). Evaluating Adaptive Learning Model. The 2014 International Conference on Interactive Collaborative Learning (ICL 2014) (pp. 818-822). Dubai, UAE: IEEE. doi:10.1109/ICL.2014.7017878
•    Nguyen, L. (2014, October 21). Improving analytic function approximation by minimizing square error of Taylor polynomial. (A. Moustafa et al., Eds.) International Journal of Mathematical Analysis and Applications, 1 (4), 63-67. Retrieved from http://www.aascit.org/journal/archive2?journalId=921&paperId=1016
•    Nguyen, L. (2014, September). Theorem of logarithm expectation and its application to prove sample correlation coefficient as unbiased estimate. (A. Guezane-Lakoud, W. P. Fox, E. Francomano, S. A. Episkoposian, E. Nadaraya, A. N. Raikov, et al., Eds.) Journal of Mathematics and System Science(JMSS), 4 (9), 605-608. doi:10.17265/2159-5291/2014.09.003
•    Nguyen, L. (2014, May). A New Algorithm for Modeling and Inferring User's Knowledge by Using Dynamic Bayesian Network. (M. Z. Raqab, Ed.) Statistics Research Letters (SRL), 3 (2). Retrieved from http://www.srl-journal.org/paperInfo.aspx?ID=6933
•    Nguyen, L. (2014, May 28). User Model Clustering. (F. Shi, Ed.) Journal of Data Analysis and Information Processing (JDAIP), 2 (2), 41-48. doi:10.4236/jdaip.2014.22006
•    Nguyen, L., & Ho, H. (2014, March 30). A framework of fetal age and weight estimation. (B. S. Shetty, J. Morales, a. badawy, C. Mowa, K. K. Shukla, T. Chen, et al., Eds.) Journal of Gynecology and Obstetrics (JGO), 2 (2), 20-25. doi:10.11648/j.jgo.20140202.13
•    Nguyen, L. (2013). A New Approach for Modeling and Discovering Learning Styles by Using Hidden Markov Model. (G. Perry et al., Eds.) Global Journal of Human Social Science: G - Linguistics & Education, 13 (4 Version 1.0 Year 2013), 1-10. Retrieved from http://socialscienceresearch.org/index.php/GJHSS/article/view/609
•    Nguyen, L. (2013, July 15). Overview of Bayesian Network. Ho Chi Minh University of Technology, Vietnam. Warri, Delta State, Nigeria: Science Journal Publication. doi:10.7237/sjms/105
•    Nguyen, L. (2013, June). The Bayesian approach and suggested stopping criterion in Computerized Adaptive Testing. (A. T. Al-Taani, Ed.) International Journal of Research in Engineering and Technology (IJRET), 2 (1-2103), 36-38. Retrieved from https://goo.gl/kXxczD
•    Nguyen, L. (2013, June 5). A new method to determine separated hyper-plane for non-parametric sign test in multivariate data. In V.-D. Le, A. Mukhopadhyay, & G.-T. Pham (Ed.), STATISTICS and its INTERACTIONS with OTHER DISCIPLINES (SIOD 2013). Ho Chi Minh: Ton Duc Thang University. doi:10.13140/RG.2.2.20886.86080/1
•    Nguyen, L., Do, M.-P. T., Vu, N. T., & Tran, D. N. (2013, March 20). A New Approach for Collaborative Filtering Based on Mining Frequent Itemsets. In Selamat, A., Nguyen, Ngoc T., & Haron, H. (Ed.), ACIIDS'13 Proceedings of the 5th Asian conference on Intelligent Information and Database Systems. II, pp. 19-29. Kuala Lumpur: Springer. doi:10.1007/978-3-642-36543-0_3
•    Nguyen, L. (2011). The method of seven qigong exercises of archery simulation. (V. H. Nguyen, Ed.) Nguyen Hoai Van's website.
•    Do, M.-P. T., Nguyen, D. V., & Nguyen, L. (2010, August 20). Model-based Approach for Collaborative Filtering. Proceedings of The 6th International Conference on Information Technology for Education (IT@EDU2010) (pp. 217-225). Ho Chi Minh, Vietnam: Ho Chi Minh University of Information Technology. Retrieved from https://goo.gl/BHu7ge
•    Nguyen, L. (2010). Discovering User Interests by Document Classification. In I.-H. Ting, H.-J. Wu, T.-H. Ho, I.-H. Ting, H.-J. Wu, & T.-H. Ho (Eds.), Mining and Analyzing Social Networks (Vol. 288 In series “Studies in Computational Intelligence”, pp. 139-159). Springer Berlin Heidelberg. doi:10.1007/978-3-642-13422-7_9
•    Nguyen, L. (2010). Overview of The System of Acupuncture Spots in Oriental Medicine based on Oriental Philosophy. (L. Nguyen, Ed.) Retrieved from Loc Nguyen's Homepage: https://goo.gl/78K1Pr
•    Nguyen, L. (2009, September 25). Incorporating Bayesian Inference into Adaptation Rules in AHA architecture. Proceedings of 12th International Conference Interests Interactive Computer aided Learning (ICL2009). Villach, Austria: Kassel University Press, Kassel, Germany. Retrieved from http://www.icl-conference.org/dl/proceedings/2009/archive.htm
•    Nguyen, L. (2009, August 31). A Proposal Discovering User Interests by Support Vector Machine and Decision Tree on Document Classification. The International Workshop on Social Networks Mining and Analysis for Business Applications (SNMABA2009) in conjunction with The 2009 IEEE International Conference on Social Computing (SocialCom2009), 4, pp. 809-814. Vancouver, Canada: Computational International Conference on Science and Engineering 2009 (CSE '09), IEEE. doi:10.1109/CSE.2009.112
•    Nguyen, L., & Do, P. (2009, July 16). Evolution of Parameters in Bayesian Overlay Model. In H. R. Arabnia, D. d. Fuente, & J. A. Olivas (Ed.), Proceedings of The 2009 International Conference on Artificial Intelligence (IC-AI’09), The 2009 World Congress in Computer Science, Computer Engineering, and Applied Computing (WORLDCOMP’09) (pp. 324-329). Monte Carlo Resort, Las Vegas, Nevada, USA: CSREA Press USA. Retrieved from https://goo.gl/QwMYqq
•    Fröschl, C., & Nguyen, L. (2009, July 16). State of the Art of Adaptive Learning. In H. R. Arabnia, A. Bahrami, & A. M. Solo (Ed.), Proceedings of The 2009 International Conference on e-Learning, e-Business, Enterprise Information Systems, and e-Government (EEE 2009). The 2009 World Congress in Computer Science, Computer Engineering, and Applied Computing (WORLDCOMP’09) (pp. 126-133). Las Vegas, Nevada, USA: CSREA Press USA. Retrieved from https://goo.gl/Xn39eN
•    Nguyen, L., & Dong, B.-T. T. (2009, July 10). ZEBRA: A new User Modeling System for Triangular Model of Learners‘ Characteristics. In G. D. Magoulas, P. Charlton, D. Laurillard, K. Papanikolaou, & M. Grigoriadou (Ed.), AIED 2009: 14th conference on Artificial Intelligence in Education, Proceedings of the Workshop on “Enabling creative learning design: how HCI, User Modeling and Human Factors Help” (pp. 42-51). Brighton, United Kingdom: IOS Press Amsterdam, The Netherlands, The Netherlands. Retrieved from https://goo.gl/cVzC6h
•    Nguyen, L., & Do, P. (2009, June 3). Learning Concept Recommendation based on Sequential Pattern Mining. In E. Chang, F. Hussain, & E. Kayacan (Ed.), Proceedings of The 2009 Third International Digital Ecosystems and Technologies Conference (IEEE-DEST 2009) (pp. 66-71). Istanbul, Turkey: IEEE. doi:10.1109/DEST.2009.5276694
•    Nguyen, L., & Do, P. (2009). Combination of Bayesian Network and Overlay Model in User Modeling. (M. E. Auer, Ed.) International Journal of Emerging Technologies in Learning (iJET), 4 (4), 41-45. doi:10.3991/ijet.v4i4.684
•    Fröschl, C., Nguyen, L., & Do, P. (2008, November). Learner Model in Adaptive Learning. The 2008 World Congress on Science, Engineering and Technology (WCSET2008), 35, pp. 296-400. Paris, France: World Congress on Science, Engineering and Technology (WASET). Retrieved from https://goo.gl/MEZVJ2
•    Nguyen, L. (2006, January). Image Retrieval by MMM Model on Combination of Image Low-Level Features and High-Level Semantics (Truy tìm ảnh qua mô hình MMM kết hợp giữa đặc trưng cấp thấp và ngữ nghĩa cấp cao của ảnh). (T.-A. Vo, & M.-P. T. Ho, Eds.) An Giang University Journal of Science, 25. Retrieved from https://goo.gl/rP2tsZ

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