Dac-Nhuong Le

Verified email at hus.edu.vn

Faculty of Information Technology
Haiphong University, Haiphong, Vietnam



                                                                             

https://researchid.co/httpsresearchid.conhuongld

Dac-Nhuong Le (Lê Đắc Nhường) has a M.Sc. and Ph.D in computer science from Vietnam National University, Vietnam in 2009 and 2015, respectively. He is Associate Professor in Computer Science, Deputy-Head of Faculty of Information Technology, Haiphong University, Vietnam. Presently, he is also the Vice-Director of Information Technology Apply and Foreign Language Training Center in the same university.

He has a total academic teaching experience of 12 years with many publications in reputed international conferences, journals and online book chapter contributions (Indexed By: SCI, SCIE, SSCI, Scopus, ACM, DBLP). His area of research include: Soft computing, Network communication, security and vulnerability, network performance analysis and simulation, cloud computing, IoT and Image processing in biomedical.

His core work in network security, soft computing and IoT and image processing in biomedical. Recently, he has been the technique program committee, the technique reviews, the track chair for international conferences: FICTA 2014, CSI 2014, IC4SD 2015, ICICT 2015, INDIA 2015, IC3T 2015, INDIA 2016, FICTA 2016, ICDECT 2016, IUKM 2016, INDIA 2017, FICTA 2017, CISC 2017, ICICC 2018, ICCUT 2018, FICTA 2018 under Springer-ASIC/LNAI Series.

Presently, he is serving in the editorial board of international journals and he authored/edited 12 computer science books by Springer, Wiley, CRC Press.

website: http://www.dhhp.edu.vn/~nhuongld
email: nhuongld@dhhp.edu.vn

RESEARCH INTERESTS

Computer Science, Evolutionary Multi-objective Optimization, Network Communication and Security, Biomedical Imaging

FUTURE PROJECTS

Research on Some Optimization Algorithms for Risk and Conflict Management in Software Project Scheduling (NAFOSTED 102.03-2019.10)

Risks and conflicts are subjective events that interfere with the development of software projects. Because risks and conflicts cannot be completely eliminated during the project schedule due to complexity arising from unique characteristics, variability, lack of data, structure, and deviation in prediction/estimation. Many different techniques and tools have been developed to support better project scheduling, but the quantification of risk factors and conflicts has not been adequately considered. In it, the most challenging problem is estimating the time and resources for each specific task in project scheduling. Most research on software project risk analysis focuses on finding the link between risk factors and project outcomes. The goal of risk and conflict management problems in software projects is to provide a multi-objective optimization plan to manage and minimize its level of damage. Therefore, it is almost impossible to find exact algorithms in polynomial time. Then, we need to consider the design of optimal algorithms with the best approximation to help accurately predict, quantify risks, conflicts, as well as their consequences, impact on the project from the critical process, is project planning.


Applications Invited
99

Scopus Publications

2322

Scholar Citations

25

Scholar h-index

61

Scholar i10-index

Scopus Publications

  • A Novel Design of Morlet Wavelet to Solve the Dynamics of Nervous Stomach Nonlinear Model
    Zulqurnain Sabir, Muhammad Asif Zahoor Raja, S. R. Mahmoud, Mohammed Balubaid, Ali Algarni, Abdulaziz H. Alghtani, Ayman A. Aly, and Dac-Nhuong Le

    International Journal of Computational Intelligence Systems, ISSN: 18756891, eISSN: 18756883, Published: December 2022 Springer Science and Business Media LLC
    AbstractThe present study introduces a novel design of Morlet wavelet neural network (MWNN) models to solve a class of a nonlinear nervous stomach system represented with governing ODEs systems via three categories, tension, food and medicine, i.e., TFM model. The comprehensive detail of each category is designated together with the sleep factor, food rate, tension rate, medicine factor and death rate are also provided. The computational structure of MWNNs along with the global search ability of genetic algorithm (GA) and local search competence of active-set algorithms (ASAs), i.e., MWNN-GA-ASAs is applied to solve the TFM model. The optimization of an error function, for nonlinear TFM model and its related boundary conditions, is performed using the hybrid heuristics of GA-ASAs. The performance of the obtained outcomes through MWNN-GA-ASAs for solving the nonlinear TFM model is compared with the results of state of the article numerical computing paradigm via Adams methods to validate the precision of the MWNN-GA-ASAs. Moreover, statistical assessments studies for 50 independent trials with 10 neuron-based networks further authenticate the efficacy, reliability and consistent convergence of the proposed MWNN-GA-ASAs.

  • A neuro-swarming intelligent heuristic for second-order nonlinear Lane–Emden multi-pantograph delay differential system
    Zulqurnain Sabir, Muhammad Asif Zahoor Raja, Dac-Nhuong Le, and Ayman A. Aly

    Complex and Intelligent Systems, ISSN: 21994536, eISSN: 21986053, Pages: 1987-2000, Published: June 2022 Springer Science and Business Media LLC
    AbstractThe current study is related to present a novel neuro-swarming intelligent heuristic for nonlinear second-order Lane–Emden multi-pantograph delay differential (NSO-LE-MPDD) model by applying the approximation proficiency of artificial neural networks (ANNs) and local/global search capabilities of particle swarm optimization (PSO) together with efficient/quick interior-point (IP) approach, i.e., ANN-PSOIP scheme. In the designed ANN-PSOIP scheme, a merit function is proposed by using the mean square error sense along with continuous mapping of ANNs for the NSO-LE-MPDD model. The training of these nets is capable of using the integrated competence of PSO and IP scheme. The inspiration of the ANN-PSOIP approach instigates to present a reliable, steadfast, and consistent arrangement relates the ANNs strength for the soft computing optimization to handle with such inspiring classifications. Furthermore, the statistical soundings using the different operators certify the convergence, accurateness, and precision of the ANN-PSOIP scheme.

  • An adaptive traffic routing approach toward load balancing and congestion control in Cloud–MANET ad hoc networks
    Surjeet Dalal, Bijeta Seth, Vivek Jaglan, Meenakshi Malik, Surbhi, Neeraj Dahiya, Uma Rani, Dac-Nhuong Le, and Yu-Chen Hu

    Soft Computing, ISSN: 14327643, eISSN: 14337479, Pages: 5377-5388, Published: June 2022 Springer Science and Business Media LLC

  • Integrating encryption techniques for secure data storage in the cloud
    Bijeta Seth, Surjeet Dalal, Vivek Jaglan, Dac‐Nhuong Le, Senthilkumar Mohan, and Gautam Srivastava

    Transactions on Emerging Telecommunications Technologies, eISSN: 21613915, Published: April 2022 Wiley

  • LoRa based intelligent soil and weather condition monitoring with internet of things for precision agriculture in smart cities
    Dushyant Kumar Singh, Rajeev Sobti, Anuj Jain, Praveen Kumar Malik, and Dac‐Nhuong Le

    IET Communications, ISSN: 17518628, eISSN: 17518636, Pages: 604-618, Published: March 2022 Institution of Engineering and Technology (IET)

  • An efficient driver behavioral pattern analysis based on fuzzy logical feature selection and classification in big data analysis
    Meenakshi Malik, Rainu Nandal, Surjeet Dalal, Ujjawal Maan, and Dac-Nhuong Le

    Journal of Intelligent and Fuzzy Systems, ISSN: 10641246, eISSN: 18758967, Pages: 3283-3292, Published: 2022 IOS Press
    In recent years, driver behavior analysis plays a vital role to enhance passenger coverage and management resources in the smart transportation system. The real-world environment possesses the driver principles contains a lot of information like driving activities, acceleration, speed, and fuel consumption. In big data analysis, the driver pattern analyses are complex because mining information is not utilized to feature evaluations and classification. In this paper, a new efficient Fuzzy Logical-based driver behavioral pattern analysis has been proposed to offer effective recommendations to the drivers. Primarily, the feature selection can be carried out with the assist of fuzzy logical subset selection. The selected features are then evaluated using frequent pattern information and these measures will be optimized with a multilayer perception model to create behavioral weight. Afterward, the information weights are trained with a test through an optimized spectral neural network. Finally, the neurons are activated by a recurrent neural network to classify the behavioral approach for the superior recommendation. The proposed method will learn the characteristics of driving behaviors and model temporal features automatically without the need for specialized expertise in feature modelling or machine learning techniques. The simulation results manifest that the proposed framework attains better performance with 98.4% of prediction accuracy and 86.8% of precision rate as compared with existing state-of-the-art methods.

  • Adaptive Scheduling Algorithm based Task Loading in Cloud Data Centers
    Dibyendu Mukherjee, Shivnath Ghosh, Souvik Pal, Ayman A. Aly, and Dac-Nhuong Le

    IEEE Access, eISSN: 21693536, Pages: 49412-49421, Published: 2022 Institute of Electrical and Electronics Engineers (IEEE)

  • Enhanced Marathi Speech Recognition Facilitated by Grasshopper Optimisation-Based Recurrent Neural Network
    Ravindra Parshuram Bachate, Ashok Sharma, Amar Singh, Ayman A. Aly, Abdulaziz H. Alghtani, and Dac-Nhuong Le

    Computer Systems Science and Engineering, ISSN: 02676192, Pages: 439-454, Published: 2022 Computers, Materials and Continua (Tech Science Press)

  • Plant Disease Identification Based on Leaf Images Using Deep Learning
    Hardev Mukeshbhai Khandhar, Chintan Bhatt, Dac-Nhuong Le, Harshil Sharaf, and Wathiq Mansoor

    Lecture Notes in Electrical Engineering, ISSN: 18761100, eISSN: 18761119, Volume: 839, Pages: 215-224, Published: 2022 Springer Singapore

  • A Comparative Analysis of Machine Learning Models for Banking News Extraction by Multiclass Classification With Imbalanced Datasets of Financial News: Challenges and Solutions
    Varun Dogra, Sahil Verma, Kavita Verma, NZ Jhanjhi, Uttam Ghosh, and Dac-Nhuong Le

    International Journal of Interactive Multimedia and Artificial Intelligence, eISSN: 19891660, Pages: 35-52, Published: 2022 Universidad Internacional de La Rioja
    School of Computer Science and Engineering, Lovely Professional University, India Department of Computer Science and Engineering, Chandigarh University, Mohali, India School of Computer Science and Engineering, Taylor’s University, Malaysia Department of Computer Science and Data Science, Meharry School of Applied Computational Sciences, Nashville, TN, USA School of Computer Science, Duy Tan University, Danang, 550000, Vietnam Institute of Research and Development, Duy Tan University, Danang, 550000, Vietnam

  • Modeling and Simulation of Two Axes Gimbal Using Fuzzy Control
    Ayman A. Aly, Mohamed O. Elhabib, Bassem F. Felemban, B. Saleh, and Dac-Nhuong Le

    Computers, Materials and Continua, ISSN: 15462218, eISSN: 15462226, Pages: 93-107, Published: 2022 Computers, Materials and Continua (Tech Science Press)

  • Dynamic Data Optimization in IoT-Assisted Sensor Networks on Cloud Platform
    Nguyen A. Tuan, D. Akila, Souvik Pal, Bikramjit Sarkar, Thien Khai Tran, G. Mothilal Nehru, and Dac-Nhuong Le

    Computers, Materials and Continua, ISSN: 15462218, eISSN: 15462226, Pages: 1357-1372, Published: 2022 Computers, Materials and Continua (Tech Science Press)

  • A Novel Compact Frequency and Polarization Reconfigurable Slot Antenna Using PIN Diodes for Cognitive Radio Applications
    V. N. Lakshmana Kumar, M. Satyanarayana, Sohanpal Singh, and Dac-Nhuong Le

    EAI/Springer Innovations in Communication and Computing, ISSN: 25228595, eISSN: 25228609, Pages: 85-95, Published: 2022 Springer International Publishing

  • Deriving driver behavioral pattern analysis and performance using neural network approaches
    Meenakshi Malik, Rainu Nandal, Surjeet Dalal, Vivek Jalglan, and Dac-Nhuong Le

    Intelligent Automation and Soft Computing, ISSN: 10798587, eISSN: 2326005X, Pages: 87-99, Published: 2022 Computers, Materials and Continua (Tech Science Press)

  • W-GeoR: Weighted Geographical Routing for VANET’s Health Monitoring Applications in Urban Traffic Networks
    Pawan Singh, Ram Shringar Raw, Suhel Ahmad Khan, Mazin Abed Mohammed, Ayman A. Aly, and Dac-Nhuong Le

    IEEE Access, eISSN: 21693536, Pages: 38850-38869, Published: 2022 Institute of Electrical and Electronics Engineers (IEEE)

  • A comprehensive study on the role of advanced technologies in 5G based smart hospital
    Arun Kumar, R. Dhanagopal, Mahmoud A. Albreem, and Dac-Nhuong Le

    Alexandria Engineering Journal, ISSN: 11100168, Pages: 5527-5536, Published: December 2021 Elsevier BV

  • IoT enabled depthwise separable convolution neural network with deep support vector machine for COVID-19 diagnosis and classification
    Dac-Nhuong Le, Velmurugan Subbiah Parvathy, Deepak Gupta, Ashish Khanna, Joel J. P. C. Rodrigues, and K. Shankar

    International Journal of Machine Learning and Cybernetics, ISSN: 18688071, eISSN: 1868808X, Pages: 3235-3248, Published: November 2021 Springer Science and Business Media LLC
    At present times, the drastic advancements in the 5G cellular and internet of things (IoT) technologies find useful in different applications of the healthcare sector. At the same time, COVID-19 is commonly spread from animals to persons, but today it is transmitting among persons by adapting the structure. It is a severe virus and inappropriately resulted in a global pandemic. Radiologists utilize X-ray or computed tomography (CT) images to diagnose COVID-19 disease. It is essential to identify and classify the disease through the use of image processing techniques. So, a new intelligent disease diagnosis model is in need to identify the COVID-19. In this view, this paper presents a novel IoT enabled Depthwise separable convolution neural network (DWS-CNN) with Deep support vector machine (DSVM) for COVID-19 diagnosis and classification. The proposed DWS-CNN model aims to detect both binary and multiple classes of COVID-19 by incorporating a set of processes namely data acquisition, Gaussian filtering (GF) based preprocessing, feature extraction, and classification. Initially, patient data will be collected in the data acquisition stage using IoT devices and sent to the cloud server. Besides, the GF technique is applied to remove the existence of noise that exists in the image. Then, the DWS-CNN model is employed for replacing default convolution for automatic feature extraction. Finally, the DSVM model is applied to determine the binary and multiple class labels of COVID-19. The diagnostic outcome of the DWS-CNN model is tested against Chest X-ray (CXR) image dataset and the results are investigated interms of distinct performance measures. The experimental results ensured the superior results of the DWS-CNN model by attaining maximum classification performance with the accuracy of 98.54% and 99.06% on binary and multiclass respectively.

  • The impact of the covid-19 pandemic on college students: An online survey
    Thien Khai Tran, Hoa Dinh, Hien Nguyen, Dac-Nhuong Le, Dong-Ky Nguyen, An C. Tran, Viet Nguyen-Hoang, Ha Nguyen Thi Thu, Dinh Hung, Suong Tieu, Canh Khuu, and Tuan A. Nguyen

    Sustainability (Switzerland), eISSN: 20711050, Published: October-1 2021 MDPI AG
    The COVID-19 pandemic, since its beginning in December 2019, has altered every aspect of human life. In Vietnam, the pandemic is in its fourth peak and is the most serious so far, putting Vietnam in the list of top 30 countries with the highest daily cases. In this paper, we wish to identify the magnitude of its impact on college students in Vietnam. As far as we’re concerned, college students belong to the most affected groups in the population, especially in big cities that have been hitting hard by the virus. We conducted an online survey from 31 May 2021 to 9 June 2021, asking students from four representative regions in Vietnam to describe how the pandemic has changed their lifestyle and studying environment, as well as their awareness, compliance, and psychological state. The collected answers were processed to eliminate unreliable ones then prepared for sentiment analysis. To analyze the relationship among the variables, we performed a variety of statistical tests, including Shapiro–Wilk, Mc Nemar, Mann–Whitney–Wilcoxon, Kruskal–Wallis, and Pearson’s Chi-square tests. Among 1875 students who participated, many did not embrace online education. A total of 64.53% of them refused to think that online education would be the upcoming trend. During the pandemic, nearly one quarter of students were in a negative mood. About the same number showed signs of depression. We also observed that there were increasing patterns in sleeping time, body weight, and sedentary lifestyle. However, they maintained a positive attitude toward health protection and compliance with government regulations (65.81%). As far as we know, this is the first project to conduct such a large-scale survey analysis on students in Vietnam. The findings of the paper help us take notice of financial and mental needs and perspective issues for indigent students, which contributes to reducing the pandemic’s negative effects and going forwards to a better and more sustainable life.

  • Capitalizing on big data and revolutionary 5G technology: Extracting and visualizing ratings and reviews of global chain hotels
    Loveleen Gaur, Anam Afaq, Arun Solanki, Gurmeet Singh, Shavneet Sharma, N.Z. Jhanjhi, Hoang Thi My, and Dac-Nhuong Le

    Computers and Electrical Engineering, ISSN: 00457906, Published: October 2021 Elsevier BV

  • Integrated intelligence of neuro-evolution with sequential quadratic programming for second-order Lane–Emden pantograph models
    Zulqurnain Sabir, Muhammad Asif Zahoor Raja, Hafiz Abdul Wahab, Gilder Cieza Altamirano, Yu-Dong Zhang, and Dac-Nhuong Le

    Mathematics and Computers in Simulation, ISSN: 03784754, Volume: 188, Pages: 87-101, Published: October 2021 Elsevier BV

  • Nanoscale heat and mass transport of magnetized 3-D chemically radiative hybrid nanofluid with orthogonal/inclined magnetic field along rotating sheet
    Assad Ayub, Zulqurnain Sabir, Dac-Nhuong Le, and Ayman A. Aly

    Case Studies in Thermal Engineering, ISSN: 2214157X, Published: August 2021 Elsevier BV

  • Computational intelligent paradigms to solve the nonlinear sir system for spreading infection and treatment using levenberg–marquardt backpropagation
    Muhammad Umar, Zulqurnain Sabir, Muhammad Asif Zahoor Raja, Manoj Gupta, Dac-Nhuong Le, Ayman A. Aly, and Yolanda Guerrero-Sánchez

    Symmetry, eISSN: 20738994, Published: April 2021 MDPI AG
    The current study aims to design an integrated numerical computing-based scheme by applying the Levenberg–Marquardt backpropagation (LMB) neural network to solve the nonlinear susceptible (S), infected (I) and recovered (R) (SIR) system of differential equations, representing the spreading of infection along with its treatment. The solutions of both the categories of spreading infection and its treatment are presented by taking six different cases of SIR models using the designed LMB neural network. A reference dataset of the designed LMB neural network is established with the Adam numerical scheme for each case of the spreading infection and its treatment. The approximate outcomes of the SIR system based on the spreading infection and its treatment are presented in the training, authentication and testing procedures to adapt the neural network by reducing the mean square error (MSE) function using the LMB. Studies based on the proportional performance and inquiries based on correlation, error histograms, regression and MSE results establish the efficiency, correctness and effectiveness of the proposed LMB neural network scheme.

  • Rock Hyraxes Swarm Optimization: A New Nature-Inspired Metaheuristic Optimization Algorithm
    Belal Al-Khateeb, Kawther Ahmed, Maha Mahmood, and Dac-Nhuong Le

    Computers, Materials and Continua, ISSN: 15462218, eISSN: 15462226, Pages: 643-654, Published: 22 March 2021 Computers, Materials and Continua (Tech Science Press)

  • Towards aspect based requirements mining for trace retrieval of component-based software management process in globally distributed environment
    Sadia Ali, Yaser Hafeez, Mamoona Humayun, N. Z. Jhanjhi, and Dac-Nhuong Le

    Information Technology and Management, ISSN: 1385951X, eISSN: 15737667, Published: 2021 Springer Science and Business Media LLC

  • IoT Technology Enabled Heuristic Model with Morlet wavelet neural network for numerical treatment of Heterogeneous Mosquito Release Ecosystem
    Zulqurnain Sabir, Kashif Nisar, Muhammad Asif Zahoor Raja, Muhammad Reazul Haque, Muhammad Umar, Ag Asri Ag Ibrahim, and Dac-Nhuong Le

    IEEE Access, eISSN: 21693536, Pages: 132897-132913, Published: 2021 Institute of Electrical and Electronics Engineers (IEEE)

RECENT SCHOLAR PUBLICATIONS

  • A novel design of morlet wavelet to solve the dynamics of nervous stomach nonlinear model
    Z Sabir, MAZ Raja, SR Mahmoud, M Balubaid, A Algarni, AH Alghtani, ...
    International Journal of Computational Intelligence Systems 15 (1), 1-15 2022

  • Multi-Criteria Service Selection Agent for Federated Cloud
    S Sudhakar, BL Radhakrishnan, P Karthikeyan, KM Sagayam, DN Le
    Journal of Communications Software and Systems 18 (3), 217-227 2022

  • Swarm Intelligence and Machine Learning: Applications in Healthcare
    S Agarwal, M Gupta, J Agrawal, DN Le
    CRC Press 2022

  • An adaptive traffic routing approach toward load balancing and congestion control in Cloud–MANET ad hoc networks
    S Dalal, B Seth, V Jaglan, M Malik, N Dahiya, U Rani, DN Le, YC Hu
    Soft Computing 26 (11), 5377-5388 2022

  • A neuro-swarming intelligent heuristic for second-order nonlinear Lane–Emden multi-pantograph delay differential system
    Z Sabir, MAZ Raja, DN Le, AA Aly
    Complex & Intelligent Systems 8 (3), 1987-2000 2022

  • Architectural Framework for Cloud Computing
    S Pal, DN Le, PK Pattnaik
    Cloud Computing Solutions: Architecture, Data Storage, Implementation and 2022

  • Cloud‐Based Data Storage
    DN Le, S Pal, PK Pattnaik
    Cloud Computing Solutions: Architecture, Data Storage, Implementation and 2022

  • OpenFaaS
    DN Le, S Pal, PK Pattnaik
    Cloud Computing Solutions: Architecture, Data Storage, Implementation and 2022

  • Privacy Preservation Issues in Cloud Computing
    PK Pattnaik, DN Le, S Pal
    Cloud Computing Solutions: Architecture, Data Storage, Implementation and 2022

  • Applications of Wireless Sensor Network in Cloud
    PK Pattnaik, DN Le, S Pal
    Cloud Computing Solutions: Architecture, Data Storage, Implementation and 2022

  • OpenStack
    DN Le, S Pal, PK Pattnaik
    Cloud Computing Solutions: Architecture, Data Storage, Implementation and 2022

  • Eucalyptus
    DN Le, S Pal, PK Pattnaik
    Cloud Computing Solutions: Architecture, Data Storage, Implementation and 2022

  • Cloud Database
    DN Le, S Pal, PK Pattnaik
    Cloud Computing Solutions: Architecture, Data Storage, Implementation and 2022

  • OpenNebula
    DN Le, S Pal, PK Pattnaik
    Cloud Computing Solutions: Architecture, Data Storage, Implementation and 2022

  • An Approach to Live Migration of Virtual Machines in Cloud Computing Environment
    DN Le, S Pal, PK Pattnaik
    Cloud Computing Solutions: Architecture, Data Storage, Implementation and 2022

  • Auditing Concept in Cloud Computing
    DN Le, S Pal, PK Pattnaik
    Cloud Computing Solutions: Architecture, Data Storage, Implementation and 2022

  • Applications of Mobile Cloud Computing
    PK Pattnaik, DN Le, S Pal
    Cloud Computing Solutions: Architecture, Data Storage, Implementation and 2022

  • Virtualization Environment in Cloud Computing
    S Pal, DN Le, PK Pattnaik
    Cloud Computing Solutions: Architecture, Data Storage, Implementation and 2022

  • Classification of Virtualization Environment
    S Pal, DN Le, PK Pattnaik
    Cloud Computing Solutions: Architecture, Data Storage, Implementation and 2022

  • Reliability Issues in Cloud Computing Environment
    DN Le, S Pal, PK Pattnaik
    Cloud Computing Solutions: Architecture, Data Storage, Implementation and 2022

MOST CITED SCHOLAR PUBLICATIONS

  • Virtual Reality (VR) & Augmented Reality (AR) technologies for tourism and hospitality industry
    A Nayyar, B Mahapatra, D Le, G Suseendran
    International journal of engineering & technology 7 (2.21), 156-160 2018
    Citations: 123

  • An integrated interactive technique for image segmentation using stack based seeded region growing and thresholding.
    S Hore, S Chakraborty, S Chatterjee, N Dey, AS Ashour, L Van Chung, ...
    International Journal of Electrical & Computer Engineering (2088-8708) 6 (6) 2016
    Citations: 113

  • IoT enabled depthwise separable convolution neural network with deep support vector machine for COVID-19 diagnosis and classification
    DN Le, VS Parvathy, D Gupta, A Khanna, JJPC Rodrigues, K Shankar
    International Journal of Machine Learning and Cybernetics 2021, 1-14 2021
    Citations: 105

  • Advances in swarm intelligence for optimizing problems in computer science
    A Nayyar, DN Le, NG Nguyen
    CRC press 2018
    Citations: 88

  • Internet of nano things (IoNT): Next evolutionary step in nanotechnology
    A Nayyar, V Puri, DN Le
    Nanoscience and Nanotechnology 7 (1), 4-8 2017
    Citations: 81

  • Structural failure classification for reinforced concrete buildings using trained neural network based multi-objective genetic algorithm
    S Chatterjee, S Sarkar, S Hore, N Dey, AS Ashour, F Shi, DN Le
    Structural Engineering and Mechanics 63 (4), 429-438 2017
    Citations: 68

  • Synchronization phenomena investigation of a new nonlinear dynamical system 4D by Gardano’s and Lyapunov’s methods
    AA Hamad, AS Al-Obeidi, EH Al-Taiy, OI Khalaf, D Le
    Computers, Materials & Continua 66 (3), 3311-3327 2021
    Citations: 62

  • Light microscopy image de-noising using optimized LPA-ICI filter
    AS Ashour, S Beagum, N Dey, AS Ashour, DS Pistolla, GN Nguyen, ...
    Neural Computing and Applications, 1-17 2017
    Citations: 61

  • Cloud computing and virtualization
    DN Le, R Kumar, GN Nguyen, JM Chatterjee
    John Wiley & Sons 2018
    Citations: 59

  • Smart surveillance robot for real-time monitoring and control system in environment and industrial applications
    A Nayyar, V Puri, NG Nguyen, DN Le
    Information systems design and intelligent applications, 229-243 2018
    Citations: 58

  • COVID-DeepNet: hybrid multimodal deep learning system for improving COVID-19 pneumonia detection in chest X-ray images
    AS Al-Waisy, MA Mohammed, S Al-Fahdawi, MS Maashi, ...
    Computers, Materials and Continua 67 (2), 2409-2429 2021
    Citations: 57

  • Map matching algorithm: real time location tracking for smart security application
    SK Prasad, J Rachna, OI Khalaf, DN Le
    Telecommunications and Radio Engineering 79 (13) 2020
    Citations: 54

  • Efficient dual-cooperative bait detection scheme for collaborative attackers on mobile ad-hoc networks
    OI Khalaf, F Ajesh, AA Hamad, GN Nguyen, DN Le
    IEEE Access 8, 227962-227969 2020
    Citations: 52

  • Healthy and unhealthy rat hippocampus cells classification: A neural based automated system for Alzheimer disease classification
    N Dey, AS Ashour, S Chakraborty, S Samanta, D Sifaki-Pistolla, ...
    Journal of Advanced Microscopy Research 11 (1), 1-10 2016
    Citations: 52

  • A comprehensive investigation of machine learning feature extraction and classification methods for automated diagnosis of COVID-19 based on X-ray images
    M Abed, KH Mohammed, GZ Abdulkareem, M Begonya, A Salama, ...
    Computers, Materials, & Continua, 3289-3310 2021
    Citations: 49

  • A performance analysis of openstack open-source solution for IaaS cloud computing
    VN Van, LM Chi, NQ Long, GN Nguyen, DN Le
    Proceedings of the Second International Conference on Computer and 2016
    Citations: 48

  • Haralick features-based classification of mammograms using SVM
    V Bhateja, A Gautam, A Tiwari, LN Bao, SC Satapathy, NG Nhu, DN Le
    Information Systems Design and Intelligent Applications, 787-795 2018
    Citations: 45

  • Global forecasting confirmed and fatal cases of COVID-19 outbreak using autoregressive integrated moving average model
    D Dansana, R Kumar, J Das Adhikari, M Mohapatra, R Sharma, ...
    Frontiers in public health 8, 580327 2020
    Citations: 43

  • Integrating encryption techniques for secure data storage in the cloud
    B Seth, S Dalal, V Jaglan, DN Le, S Mohan, G Srivastava
    Transactions on Emerging Telecommunications Technologies 33 (4), e4108 2022
    Citations: 41

  • A hybrid approach of secret sharing with fragmentation and encryption in cloud environment for securing outsourced medical database: a revolutionary approach
    DN Le, B Seth, S Dalal
    Journal of Cyber Security and Mobility 7 (4), 379-408 2018
    Citations: 36