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Computationally Intensive Problems in General Math and Engineering: Basic Research and Development

This two-part special issue for the Journal of Big Data covers computationally intensive problems in engineering and focuses on mathematical mechanisms of interest for emerging problems such as Partial Difference Equations, Tensor Calculus, Mathematical Logic, and Algorithmic Enhancements based on Artificial Intelligence. Applications of the research highlighted in the collection include, but are not limited to: Earthquake Engineering, Spatial Data Analysis, Geo Computation, Geophysics, Genomics and Simulations for Nature Based Construction, and Aerospace Engineering. Featured lead articles are co-authored by three esteemed Nobel laureates: Jean-Marie Lehn, Konstantin Novoselov, and Dan Shechtman.

This special issue is separated into two distinct collections: part one covers basic research and development for problems in general engineering, and part two covers applicative research and education. View part two here.

  1. Optical coherence tomography angiography (OCTA) has been a frequently used diagnostic method in neovascular age-related macular degeneration (nAMD) because it is non-invasive and provides a comprehensive view ...

    Authors: Wei Feng, Meihan Duan, Bingjie Wang, Yu Du, Yiran Zhao, Bin Wang, Lin Zhao, Zongyuan Ge and Yuntao Hu
    Citation: Journal of Big Data 2023 10:111
  2. Ensuring the optimal performance of power transformers is a laborious task in which the insulation system plays a vital role in decreasing their deterioration. The insulation system uses insulating oil to cont...

    Authors: Manuel J. Jiménez-Navarro, María Martínez-Ballesteros, Francisco Martínez-Álvarez and Gualberto Asencio-Cortés
    Citation: Journal of Big Data 2023 10:80
  3. SRAM and DRAM memory technologies have been dominant in the implementations of memory subsystems. In recent years, and mainly driven by the huge memory demands of big data applications, NVRAM technology has em...

    Authors: Miguel A. Avargues, Manel Lurbe, Salvador Petit, Maria E. Gomez, Rui Yang, Xiaoping Zhu, Guanhao Wang and Julio Sahuquillo
    Citation: Journal of Big Data 2023 10:75
  4. This article presents a taxonomy and represents a repository of open problems in computing for numerically and logically intensive problems in a number of disciplines that have to synergize for the best perfor...

    Authors: Zoran Babović, Branislav Bajat, Vladan Đokić, Filip Đorđević, Dražen Drašković, Nenad Filipović, Borko Furht, Nikola Gačić, Igor Ikodinović, Marija Ilić, Ayhan Irfanoglu, Branislav Jelenković, Aleksandar Kartelj, Gerhard Klimeck, Nenad Korolija, Miloš Kotlar…
    Citation: Journal of Big Data 2023 10:73
  5. Extensive prior work has provided methods for the optimization of routing based on weights assigned to travel duration, and/or travel cost, and/or the distance traveled. Routing can be in various modalities, s...

    Authors: Naphtali Rishe, M. Hadi Amini and Malek Adjouadi
    Citation: Journal of Big Data 2023 10:57
  6. Distributed computing continuum systems (DCCS) make use of a vast number of computing devices to process data generated by edge devices such as the Internet of Things and sensor nodes. Besides performing compu...

    Authors: Praveen Kumar Donta, Boris Sedlak, Victor Casamayor Pujol and Schahram Dustdar
    Citation: Journal of Big Data 2023 10:53
  7. Beyond detecting brain lesions or tumors, comparatively little success has been attained in identifying brain disorders such as Alzheimer’s disease (AD), based on magnetic resonance imaging (MRI). Many machine...

    Authors: Bin Lu, Hui-Xian Li, Zhi-Kai Chang, Le Li, Ning-Xuan Chen, Zhi-Chen Zhu, Hui-Xia Zhou, Xue-Ying Li, Yu-Wei Wang, Shi-Xian Cui, Zhao-Yu Deng, Zhen Fan, Hong Yang, Xiao Chen, Paul M. Thompson, Francisco Xavier Castellanos…
    Citation: Journal of Big Data 2022 9:101

New Content ItemProf. Veljko Milutinovic
Fellow of the IEEE and of the Academy of Europe, Indiana University, Bloomington, IND, USA, Adjunct Professor, University of Belgrade, SRB, EUR, Visiting Professor

Prof. Veljko Milutinovic (1951) received his PhD from the University of Belgrade in Serbia, spent about a decade on various faculty positions in the USA (mostly at Purdue University and more recently at the University of Indiana in Bloomington), and was a co-designer of the DARPAs pioneering GaAs RISC microprocessor on 200MHz (about a decade before the first commercial effort on that same speed) and was a co-designer also of the related GaAs Systolic Array (with 4096 GaAs microprocessors). Later, for almost three decades, he taught and conducted research at the University of Belgrade in Serbia, for departments of EE, MATH, BA, and PHYS/CHEM. His research is mostly in datamining algorithms and dataflow computing, with the emphasis on mapping of data analytics algorithms onto fast energy efficient architectures. Most of his research was done in cooperation with industry (Intel, Fairchild, Honeywell, Maxeler, HP, IBM, NCR, RCA, etc... ). For 10 of his books, forewords were written by 10 different Nobel Laureates with whom he cooperated on his past industry sponsored projects. He published 40 books (mostly in the USA), he has over 100 papers in SCI journals (mostly in IEEE and ACM journals), and he presented invited talks at over 400 destinations worldwide. He has well over 1000 Thomson-Reuters WoS citations, well over 1000 Elsevier SCOPUS citations, and about 4000 Google Scholar citations. His Google Scholar h index is equal to 36. He is a Life Fellow of the IEEE since 2003 and a Member of The Academy of Europe since 2011. He is a member of the Serbian National Academy of Engineering and a Foreign Member of the Montenegro National Academy of Sciences and Arts.

New Content ItemJean-Marie Lehn
University of Strasbourg, France
Jean-Marie Lehn received the Nobel Prize in Chemistry in 1987, together with Donald Cram and Charles Pedersen for his synthesis of cryptands. Lehn was an early innovator in the field of supermolecular chemistry, i.e. the chemistry of host-guest molecular assemblies created by intermolecular interactions, and continues to innovate in this field.


New Content ItemKonstantin Novoselov
University of Manchester, UK
Konstantin Novoselov received the Nobel Prize in Physics in 2010, together with Andre Geim, for their groundbreaking experiments on graphene, a two-dimensional material with remarkable properties such as high electrical conductivity, mechanical strength, and transparency. Novoselov and Geim's discovery of graphene was published in 2004, and it opened up new possibilities for the development of innovative technologies in various fields.


New Content ItemDan Shechtman
Technion, Israel
Dan Shechtman received the Nobel Prize in Chemistry in 2011, for the discovery of quasicrystals, a type of solid material with a highly ordered structure that was previously thought to be impossible. However, further investigation revealed that the pattern was due to a new type of crystal structure, which did not fit the conventional rules of crystallography. This discovery eventually led to a new field of research in materials science.

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