Yu Xiao | Mathematics | Best Researcher Award

Posted on by Research Awards

Assoc Prof Dr. Yu Xiao | Mathematics | Best Researcher Award

Doctoral Supervisor at Harbin Institute of Technology, China.

Yu Xiao, an Associate Professor at Harbin Institute of Technology, holds a Ph.D. in Mathematics and specializes in numerical methods for stochastic differential equations, stability and synchronization theory, and networked control systems. His research focuses on almost sure stability in stochastic systems under periodic intermittent control, employing advanced methodologies like stochastic analysis and multiple Lyapunov functions. Xiao has collaborated extensively with industry experts, resulting in over 40 SCI-indexed publications covering diverse topics. His contributions highlight practical applications of theoretical frameworks, reflecting his significant impact in both academic research and industrial applications.

Professional Profiles:

Education 🎓

Yu Xiao, born in 1978, completed his Ph.D. at the School of Mathematics, Harbin Institute of Technology, in 2011. He holds the position of Associate Professor at the same institution. His research focuses on numerical methods for stochastic differential equations, stability and synchronization theory, and networked control systems. This background highlights his extensive academic training, current professional role, and specific research interests in mathematical methodologies applied to complex systems and control theories.

Research and Innovations

Yu Xiao is actively involved in several research areas, focusing primarily on numerical methods for stochastic differential equations, stability and synchronization theory, and networked control systems. His completed and ongoing research projects include work on periodic intermittent control for almost sure stability of stochastic strict-feedback semi-Markov jump systems, indexed in SCI. He has collaborated extensively with industry experts, contributing to the publication of over 40 SCI papers. Additionally, Yu Xiao has two patents under process and has published two journal articles in prominent scientific databases. He holds membership in the Mathematical Society of Heilongjiang Province, China, demonstrating his commitment to advancing mathematical research and applications.

Contributions

In his recent research, Yu Xiao explores almost sure stability (ASS) for stochastic strict-feedback semi-Markov jump systems (SSSJSs) under periodic intermittent control (PIC). The study systematically designs virtual controllers that culminate in an actual controller, establishing ASS conditions through stochastic analysis and the application of a multiple Lyapunov function method. These conditions are intricately linked to control width and period, effectively reducing conservatism. The research substantiates its findings with compelling simulation examples, showcasing the practical applicability and robustness of the proposed methodologies in enhancing system stability and performance.

Area of Research

Yu Xiao specializes in numerical methods for stochastic differential equations, stability and synchronization theory, and networked control systems. With a Ph.D. from the School of Mathematics at Harbin Institute of Technology and current role as Associate Professor at the same institution, his research spans diverse applications in control theory. His work notably explores almost sure stability in stochastic strict-feedback semi-Markov jump systems under periodic intermittent control, employing innovative methods like stochastic analysis and multiple Lyapunov functions. Xiao’s contributions extend beyond theoretical frameworks, demonstrating practical applications through extensive collaborations with industry experts and a robust publication record in SCI-indexed journals. His dedication to advancing control methodologies underscores his impact in both academic and industrial settings

Publications

  1. Almost sure synchronization of stochastic multi-links semi-Markov jump systems via aperiodically intermittent control
    • Authors: Gao, C., Gu, H., Xiao, Y., Guo, B.
    • Journal: Communications in Nonlinear Science and Numerical Simulation, 2024, 135, 108028
  2. Almost sure exponential synchronization analysis of stochastic strict-feedback systems with semi-Markov jump
    • Authors: Gao, C., Zhang, L., Zhang, H., Xiao, Y.
    • Journal: Engineering Applications of Artificial Intelligence, 2024, 133, 108453
  3. Synchronization of multi-link and multi-delayed inertial neural networks with Markov jump via aperiodically intermittent adaptive control
    • Authors: Guo, B., Xiao, Y.
    • Journal: Mathematics and Computers in Simulation, 2024, 219, pp. 435–453
  4. Dynamical analysis of higher-order rogue waves on the various backgrounds for the reverse space–time Fokas–Lenells equation
    • Authors: Song, J.-Y., Xiao, Y., Zhang, C.-P.
    • Journal: Applied Mathematics Letters, 2024, 150, 108971
  5. Aperiodically synchronization of multi-links delayed complex networks with semi-Markov jump and their numerical simulations to single-link robot arms
    • Authors: Gao, C., Guo, B., Xiao, Y., Bao, J.
    • Journal: Neurocomputing, 2024, 575, 127286
    • Citations: 2
  6. Solitonic interactions and explicit solutions for the (2+1) -dimensional nonlocal derivative nonlinear Schrödinger equation
    • Authors: Xiao, Y., Song, J.-Y., Zhang, C.-P.
    • Journal: Nonlinear Dynamics, 2024, 112(5), pp. 3797–3809
  7. Intermittent synchronization for multi-link and multi-delayed large-scale systems with semi-Markov jump and its application of Chua’s circuits
    • Authors: Guo, B., Xiao, Y.
    • Journal: Chaos, Solitons and Fractals, 2023, 174, 113762
    • Citations: 3 (Open access)
  8. Synchronization of Markov Switching Inertial Neural Networks with Mixed Delays under Aperiodically On-Off Adaptive Control
    • Authors: Guo, B., Xiao, Y.
    • Journal: Mathematics, 2023, 11(13), 2906
    • Citations: 3
  9. Soliton solutions and their dynamics of local and nonlocal (2+1)-dimensional Fokas–Lenells equations
    • Authors: Song, J.-Y., Xiao, Y., Bao, J.-C., Tang, H.-C.
    • Journal: Optik, 2023, 273, 170486
    • Citations: 1
  10. Intermittent control for synchronization of hybrid multi-weighted complex networks with reaction-diffusion effects
    • Authors: Guo, B., Xiao, Y.
    • Journal: Mathematical Methods in the Applied Sciences, 2023, 46(1), pp. 1137–1155
    • Citations: 4

 

 

Amjad Alipanah | Mathematics | Best Researcher Award

Posted on by Research Awards

Mr. Amjad Alipanah | Mathematics | Best Researcher Award

PhD at University of Kurdistan, Iran.

Amjad Alipanah is an esteemed Associate Professor of Applied Mathematics at the University of Kurdistan, Sanandaj, Iran. Born on September 23, 1974, he has a distinguished academic background with a BSc in Mathematics from the University of Kurdistan and both an MSc and PhD in Applied Mathematics from AmirKabir University, Tehran, Iran. His research focuses on spectral and pseudospectral methods, finite difference methods, calculus of variations, approximation theory, and numerical analysis. With a robust portfolio of journal publications and conference papers, he has significantly contributed to the field. Alipanah is also a dedicated educator, teaching a variety of undergraduate and graduate courses and supervising numerous postgraduate theses. His work has earned him top ranks as a graduate student and a prominent position in the academic community. 🌐✨

Professional Profiles:

Education

Amjad Alipanah received his Bachelor of Science (BSc) degree in Mathematics from the University of Kurdistan, Sanandaj, Iran, in 2000. He then pursued his Master of Science (MSc) in Applied Mathematics at AmirKabir University, Tehran, Iran, specializing in Partial Differential Equations with a focus on Finite Difference Methods. His master’s thesis, titled “Numerical Solution of Sine-Gordon Equation,” was supervised by Professor Mehdi Dehghan. Alipanah continued his academic journey at AmirKabir University, earning a PhD in Applied Mathematics in 2005 with a specialization in Optimal Control. His doctoral research, “Using Cardinal Functions in Spectral Methods,” was supervised by Professor Mohsen Razzaghi, with Associate Professor Mostafa Shamsi serving as his adviser.

Professional Experience

Amjad Alipanah currently holds the position of Associate Professor of Applied Mathematics at the University of Kurdistan in Sanandaj, Iran. His professional journey is marked by his extensive teaching and research contributions in the field of applied mathematics. Throughout his career, he has been involved in various research projects and has published numerous journal articles and conference papers on topics such as spectral and pseudospectral methods, finite difference methods, and numerical analysis. In addition to his research endeavors, Dr. Alipanah has supervised many postgraduate theses, guiding students through complex mathematical problems and innovative solutions. His commitment to education is evident through his teaching of a broad range of undergraduate and graduate courses, including Numerical Solution of Partial Differential Equations, Numerical Methods in Linear Algebra, and Advanced Numerical Analysis. 🧑‍🏫📊✨

Research Interest

Amjad Alipanah’s research interests lie predominantly in applied mathematics, with a focus on several specialized areas. These include spectral and pseudospectral methods, which are used for solving differential equations with high accuracy; finite difference methods, which are numerical techniques for approximating solutions to differential equations; and the calculus of variations, which deals with optimizing functionals. He is also deeply engaged in approximation theory, a branch of mathematics that focuses on how functions can best be approximated with simpler functions, and numerical analysis, which involves the development and analysis of algorithms for solving mathematical problems numerically. His diverse research interests reflect his commitment to advancing mathematical methods and their applications in solving real-world problems. 📚🔢💡

Award and Honors

Amjad Alipanah has received several prestigious awards and honors throughout his academic career. He graduated first in his class with a Bachelor of Science degree from the University of Kurdistan in 2000. Continuing his academic excellence, he also graduated first in his class with a Master of Science degree from AmirKabir University in Tehran, Iran, in 2002. These accolades highlight his dedication and exceptional performance in the field of mathematics. 🎓✨

Research Skills

Amjad Alipanah possesses a wide range of research skills that reflect his expertise in applied mathematics. He has mastery in employing spectral and pseudospectral methods for solving differential equations and optimization problems. His proficiency in finite difference methods allows him to approximate solutions to differential equations effectively. Amjad is also skilled in the calculus of variations, which involves optimization techniques for functional analysis, crucial for understanding complex physical systems. Additionally, his expertise in approximation theory enables him to develop and analyze methods for approximating functions and solving mathematical problems. His extensive experience in numerical analysis involves the development and application of algorithms for solving mathematical problems numerically. These comprehensive skills equip him to tackle complex mathematical challenges and contribute significantly to his field. 📊🔍

Publications

  1. Numerical solution of singularly perturbed singular third-order boundary value problems with nonclassical sinc method
    • Authors: A. Alipanah, K. Mohammadi, R.M. Haji
    • Year: 2024
    • Citations: 0
  2. On solving some stochastic delay differential equations by Daubechies wavelet
    • Authors: N.M. Shariati, M. Yaghouti, A. Alipanah
    • Year: 2024
    • Citations: 0
  3. Numerical solution of system of second-order integro-differential equations using nonclassical sinc collocation method
    • Authors: M. Ghasemi, K. Mohammadi, A. Alipanah
    • Year: 2023
    • Citations: 3
  4. Numerical solution of third-order singular boundary value problems with nonclassical SE-sinc-collocation and nonclassical DE-sinc-collocation
    • Authors: A. Alipanah, K. Mohammadi, M. Shiralizadeh
    • Year: 2023
    • Citations: 2
  5. Collocation method using auto-correlation functions of compact supported wavelets for solving Volterra’s population model
    • Authors: A. Alipanah, M. Zafari
    • Year: 2023
  6. Numerical solution of the system of second-order integro-differential equations using non-classical double sinc method
    • Authors: K. Mohammadi, A. Alipanah
    • Year: 2023
    • Citations: 3
  7. Numerical solution of third-order boundary value problems using non-classical sinc-collocation method
    • Authors: A. Alipanah, K. Mohammadi, M. Ghasemi
    • Year: 2023
    • Citations: 3
  8. Approximate solutions to the Allen–Cahn equation using rational radial basis functions method
    • Authors: M. Shiralizadeh, A. Alipanah, M. Mohammadi
    • Year: 2023
    • Citations: 1
  9. A convergent wavelet-based method for solving linear stochastic differential equations included 1D and 2D noise
    • Authors: N.M. Shariati, M. Yaghouti, A. Alipanah
    • Year: 2023
    • Citations: 2
  10. On the Stability of Filon–Clenshaw–Curtis Rules
    • Authors: H. Majidian, M. Firouzi, A. Alipanah
    • Year: 2022

 

 

Ayyub Sheikhi | Mathematics | Best Researcher Award

Posted on by Research Awards

Assoc Prof Dr. Ayyub Sheikhi | Mathematics | Best Researcher Award

Department of Statistics at Shahid Bahonar University of Kerman, Iran.

Ayyub Sheikhi possesses a robust set of research skills honed through years of academic and professional experience. Proficient in both theoretical and applied aspects of statistics and data science, he excels in experimental design, statistical analysis, and modeling techniques. Ayyub demonstrates proficiency in various statistical software packages, including R, and is adept at implementing advanced methodologies such as machine learning algorithms and Bayesian inference. His research skills also extend to data visualization and interpretation, allowing him to effectively communicate complex statistical findings to diverse audiences. Ayyub’s expertise in statistical research methodologies is further augmented by his ability to collaborate across interdisciplinary teams and lead projects from conception to completion. With a keen attention to detail and a commitment to methodological rigor, Ayyub Sheikhi continues to make significant contributions to the advancement of statistical science.

Professional Profiles:

Education

Ayyub Sheikhi pursued his academic journey in statistics and applied mathematics, earning his Ph.D. in Applied Mathematics from Shahid Bahonar University of Kerman, Iran, in 2012. Prior to that, he completed his Master of Science in Statistics at AmirKabir University of Technology, Tehran, Iran, and his Bachelor of Science in Statistics at Shahid Bahonar University of Kerman. His educational background equipped him with a strong foundation in mathematical and statistical principles, which he has since applied in both academic and professional settings, contributing significantly to the field of statistics and data science.

Professional Experience

Ayyub Sheikhi has garnered extensive professional experience in academia, research, and leadership roles. From 2018 to 2020, he served as the Head of the Department of Statistics at Shahid Bahonar University of Kerman, Iran, where he demonstrated his leadership skills in managing departmental affairs and fostering academic excellence. Concurrently, since 2015, he has held the position of Assistant Professor in the Department of Statistics at the same university, contributing to both teaching and research activities. In 2020, he was promoted to the position of Associate Professor, recognizing his scholarly achievements and expertise in the field. Additionally, since 2021, Ayyub has taken on the role of Head of the “Data Mining and Machine Learning” group at the Mahani Mathematical Research Institute, Shahid Bahonar University of Kerman, further showcasing his commitment to advancing statistical research and methodologies. Moreover, he has enriched his professional experience through a research fellowship at the University of Plymouth, UK, during the academic year 2023-2024, broadening his perspective and collaborating with international scholars in the field of statistics and data science.

Research Interest

Ayyub Sheikhi’s research interests encompass a diverse array of topics within the field of statistics and data science. He is particularly interested in Bayesian methods, change-point detection, and dynamic time series analysis, exploring innovative approaches to model complex data structures and uncover temporal patterns. Additionally, he focuses on copula-related techniques for analyzing dependence structures in multivariate data, aiming to develop robust methodologies for financial modeling and risk management. Ayyub also investigates machine learning methods, such as clustering algorithms and support vector machines, with a specific focus on their applications in outlier detection, classification, and regression tasks. Furthermore, he is keen on exploring the intersection of statistics with other disciplines, including economics, medicine, and engineering, to address real-world challenges and advance interdisciplinary research initiatives. Overall, Ayyub’s research interests reflect his dedication to advancing statistical theory and methodology while addressing practical problems across various domains.

Award and Honors

Ayyub Sheikhi, a prominent figure in the field of statistics and data science, has accumulated a wealth of experience and expertise over the years. He has held various academic and research positions, including serving as the Head of the Department of Statistics at Shahid Bahonar University of Kerman, Iran, from 2018 to 2020, and as an Assistant Professor and later an Associate Professor in the same department. Ayyub’s academic journey began with a Ph.D. in Applied Mathematics from Shahid Bahonar University of Kerman, Iran, in 2012, complemented by an M.Sc. in Statistics from AmirKabir University of Technology, Tehran, and a B.Sc. in Statistics from Shahid Bahonar University of Kerman. His scholarly contributions extend beyond academia, as evidenced by his involvement in various visiting appointments, publication of books, development of statistical packages, and leadership in research projects. Ayyub’s commitment to excellence and innovation in statistics continues to drive advancements in the field, positioning him as a respected authority and mentor within the academic community.

Research Skills

Dr. Sheikhi Ayyub possesses a breadth of research skills spanning statistical and mathematical domains, underpinned by a dedication to practical problem-solving. His expertise encompasses statistical inference, where he adeptly employs hypothesis testing, estimation, and model fitting to derive meaningful insights from data. Proficient in data analysis techniques, Dr. Ayyub excels in uncovering patterns and trends within complex datasets, thereby facilitating informed decision-making processes. Moreover, he demonstrates a keen understanding of machine learning algorithms, employing them for tasks ranging from classification and regression to clustering and anomaly detection, thereby enhancing predictive modeling capabilities. Additionally, Dr. Ayyub showcases proficiency in time series analysis, employing various techniques to analyze temporal data, identify patterns, and forecast future values effectively. Furthermore, his expertise extends to Bayesian statistics, copula models, and robust statistical methods, further enriching his analytical toolkit. Proficient in utilizing statistical software packages like R, Python, and MATLAB, Dr. Ayyub applies these skills across interdisciplinary research endeavors, contributing to advancements in fields ranging from healthcare and economics to engineering and finance.

Publications

  1. A two-stage Bridge estimator for regression models with endogeneity based on control function method
    • Authors: Bahador, F., Sheikhi, A., Arabpour, A.
    • Year: 2024
    • Journal: Computational Statistics
    • Volume: 39
    • Issue: 3
    • Pages: 1351–1370
    • Citations: 0
  2. Convex weak concordance measures and their constructions
    • Authors: Mesiar, R., Kolesárová, A., Sheikhi, A., Shvydka, S.
    • Year: 2024
    • Journal: Fuzzy Sets and Systems
    • Volume: 478
    • Pages: 108841
    • Citations: 1
  3. Multivariate Asymmetric Distributions of Copula Related Random Variables
    • Authors: Sheikhi, A., Arad, F., Mesiar, R.
    • Year: 2023
    • Journal: Austrian Journal of Statistics
    • Volume: 52
    • Issue: 4
    • Pages: 1–14
    • Citations: 0
  4. A dimension reduction in neural network using copula matrix
    • Authors: Sheikhi, A., Mesiar, R., Holeňa, M.
    • Year: 2023
    • Journal: International Journal of General Systems
    • Volume: 52
    • Issue: 2
    • Pages: 131–146
    • Citations: 3
  5. Convex concordance measures
    • Authors: Mesiar, R., Kolesárová, A., Sheikhi, A.
    • Year: 2022
    • Journal: Fuzzy Sets and Systems
    • Volume: 441
    • Pages: 366–377
    • Citations: 2
  6. Copula-based Berkson measurement error models
    • Authors: Ziaei, A.R., Zare, K., Sheikhi, A.
    • Year: 2022
    • Journal: Iranian Journal of Fuzzy Systems
    • Volume: 19
    • Issue: 4
    • Pages: 165–175
    • Citations: 0
  7. A heteroscedasticity diagnostic of a regression analysis with copula dependent random variables
    • Authors: Sheikhi, A., Arad, F., Mesiar, R.
    • Year: 2022
    • Journal: Brazilian Journal of Probability and Statistics
    • Volume: 36
    • Issue: 2
    • Pages: 408–419
    • Citations: 0
  8. ON ASYMMETRIC DISTRIBUTIONS OF COPULA RELATED RANDOM VARIABLES WHICH INCLUDES THE SKEW-NORMAL ONES
    • Authors: Sheikhi, A., Arad, F., Mesiar, R.
    • Year: 2022
    • Journal: Kybernetika
    • Volume: 58
    • Issue: 6
    • Pages: 984–995
    • Citations: 1
  9. Asymmetric distributions based on the t-copula
    • Authors: Arad, F., Sheikhi, A.
    • Year: 2022
    • Conference: 9th Iranian Joint Congress on Fuzzy and Intelligent Systems, CFIS 2022
    • Citations: 0
  10. On a generalization of the test of endogeneity in a two stage least squares estimation
    • Authors: Sheikhi, A., Bahador, F., Arashi, M.
    • Year: 2022
    • Journal: Journal of Applied Statistics
    • Volume: 49
    • Issue: 3
    • Pages: 709–721
    • Citations: 11

 

 

DROH ARSENE BEHI | Mathematics | Best Researcher Award

Posted on by Research Awards

Dr. DROH ARSENE BEHI | Mathematics | Best Researcher Award

Assistant Professor of UNIVERSITE DE MAN, COTE D’IVOIRE, Côte d’Ivoire.

Dr. Droh Arsene Behi is a distinguished mathematician with a PhD in Mathematics and Applications from Université Félix Houphouët-Boigny, specializing in EDP, Numerical Analysis, and Optimization. He holds a Master’s degree in Mathematics and Applications, a Master’s in Mathematical Sciences, a Bachelor’s degree in Mathematical Sciences, and a General University Diploma, all from Université Félix Houphouët-Boigny. Dr. Behi has a rich professional background, having worked as a secondary school teacher at the Ministry of Education in Côte d’Ivoire from 2008 to 2015 and again from 2018 to 2022. Since 2022, he has been a Lecturer-Researcher at the University of Man. Proficient in French and English, and skilled in software like Word, Excel, Geogebra, and Scilab, Dr. Behi is known for his dedication to mathematics and computing, and his ability to work under pressure both individually and in teams.

Professional Profiles:

Education

Dr. Droh Arsene Behi has an extensive academic background in mathematics, culminating in a doctoral degree. He earned his PhD in Mathematics and Applications, specializing in EDP, Numerical Analysis, and Optimization, from Université Félix Houphouët-Boigny in Côte d’Ivoire, completing his thesis on September 1, 2021. Prior to his doctorate, Dr. Behi obtained a Master of Mathematics and Applications with a focus on EDP, Numerical Analysis, and Optimization from the same university in 2014-2015. He also holds a Master’s degree in Mathematical Sciences, which he completed in 2013-2014, and a Bachelor’s degree in Mathematical Sciences, obtained in 2011-2012, both from Université Félix Houphouët-Boigny. Dr. Behi’s foundational education includes a General University Diploma in Mathematical Sciences, which he earned in 2004-2005 from Université Félix Houphouët-Boigny. His academic journey began with a Baccalaureate Series C from Lycée Moderne de Man, Côte d’Ivoire, completed in 1998-1999. Throughout his educational path, Dr. Behi has consistently focused on mathematical sciences, developing a deep expertise in numerical analysis and optimization.

Professional Experience

Dr. Droh Arsene Behi has accumulated extensive professional experience in the field of education and research. From 2008 to 2015, and again from 2018 to 2022, he served as a secondary school teacher under the Ministry of Education, Technical Education, and Vocational Training in Côte d’Ivoire. During this period, he imparted knowledge and fostered academic growth among his students. In 2022, he transitioned to higher education as a Lecturer-Researcher at the Ministry of Higher Education and Scientific Research, University of Man, Côte d’Ivoire. His role involves not only teaching but also contributing to academic research, particularly in the areas of EDP, Numerical Analysis, and Optimization. Throughout his career, Dr. Behi has demonstrated a strong commitment to education, reflected in his continuous efforts to enhance his teaching methodologies and research capabilities. His proficiency in software tools such as Word, Excel, Geogebra, and Scilab has further augmented his teaching and research efficiency.

Research Interest

Dr. Droh Arsene Behi’s research interests lie primarily in the field of nonlinear analysis, particularly focusing on EDP (partial differential equations), numerical analysis, and optimization. His work aims to advance theoretical understanding and practical applications of these mathematical concepts. He is deeply engaged in exploring innovative solutions and methodologies within these domains, contributing significantly to the body of knowledge in mathematical sciences.

Award and Honors

Throughout his academic and professional journey, Dr. Behi has received several awards and honors. Notably, he earned a Doctoral thesis in Mathematics and Applications with a specialization in EDP, Numerical Analysis, and Optimization from the Université Félix HOUPHOUËT-BOIGNY, showcasing his expertise and dedication to his field. His academic achievements and contributions to mathematics have been recognized by his peers and institutions alike, underscoring his commitment to excellence in research and education.

Research Skills

Dr. Behi possesses a robust set of research skills that have significantly contributed to his success as a researcher and educator. He is proficient in various software tools essential for mathematical analysis, including Word, Excel, Geogebra, and Scilab. His ability to conduct thorough and precise numerical analyses, combined with his expertise in optimization techniques, enables him to tackle complex mathematical problems effectively. Additionally, Dr. Behi’s strong foundation in nonlinear analysis and his practical approach to applying theoretical concepts to real-world scenarios highlight his versatility and capability as a researcher in the field of mathematics.

Publications

  1. Study of Nonlinear Second-Order Differential Inclusion Driven by a Φ-Laplacian Operator Using the Lower and Upper Solutions Method
    • Authors: Béhi, D.A., Adjé, A., Etienne Goli, K.C.
    • Journal: Journal of Mathematics, 2024, 2024, 2258546
    • Citations: 0
  2. A Variational Method for Multivalued Boundary Value Problems
    • Authors: Béhi, D.A., Adjé, A.
    • Journal: Abstract and Applied Analysis, 2020, 2020, 8463263
    • Citations: 0