Mathematical Applications and Statistical Rigor (MASR)
Mathematical Applications and Statistical Rigor (MASR) is an international, peer-reviewed scholarly journal devoted to advancing research at the intersection of deep mathematical theory, rigorous statistical methodology, and impactful real-world applications. MASR is founded on the conviction that mathematics and statistics achieve their highest value when they are not only theoretically sound but also decisively relevant to contemporary scientific, technological, and societal challenges. MASR is more than a publication venue; it is a global research community committed to building a durable bridge between abstraction and application. The journal serves as a meeting point for theorists, applied scientists, and interdisciplinary researchers who seek to translate mathematical and statistical innovation into robust, actionable solutions. Researchers are welcome to submit papers to MASR after preparing them according to the SIRG template (Download from here) and following the SIRG Publisher Ethics and Malpractice Statement (See this page). (MASR) follows the SIRG Publisher peer-review process in handling all submitted papers (see this page for more details). By submitting their paper to MASR , authors confirm their agreement to SIRG Publisher terms, conditions, and publication ethics (please check the author page) and (Copyrights page). Frequency: 6 Volumes Annually Editor-in-Chief: Prof. Dr. A.M. Elsawah Beijing Normal–Hong Kong Baptist University, CHINA. Email: amelsawah@bnbu.edu.cn Elsawah is an established scholar whose research bridges the two foundational pillars of quantitative science: the design of experiments and the analysis of complex data. His work focuses on developing novel methodologies for optimal experimental design in high-dimensional and complex systems, with applications spanning chemistry, engineering, biomedicine, and industrial processes. He is particularly recognized for integrating advanced statistical design with computational techniques for simulation-based experiments. Website: https://staff.bnbu.edu.cn/amelsawah/en ================================================= For more details, please get in touch with MASR managing editor : Dr. Yasser Abdel Sattar Department of Artificial Intelligence, Faculty of Computers and Artificial Intelligence, Sphinx University, Assiut, Egypt. Email: ( editorialoffice@pub.scientificirg.com )
Scientific Innovation Research Group (SIRG)
Mathematical Applications and Statistical Rigor (MASR) content is published under a Creative Commons Attribution License (CCBY). This means that content is freely available to all readers upon publication, and content is published as soon as production is complete. Mathematical Applications and Statistical Rigor (MASR) seeks to publish the most influential papers that will significantly advance scientific understanding. Selected articles must present new and widely significant data, syntheses, or concepts. They should merit recognition by the wider scientific community and the general public through publication in a reputable scientific journal.
Bi-OSW-MF-DFA: An Enhanced Multifractal Method for Gold and Silver Market Risk Assessment
Amid global economic uncertainty and inflationary pressures, precious metals have gained prominence as safe-haven assets, yet accurately quantifying their risk remains challenging due to the inherent limitations of existing fractal analysis methods. Conventional Multifractal Detrended Fluctuation Analysis (MF-DFA) suffers from boundary-induced artifacts and computational inefficiencies, which can distort risk measurements and obscure true market dynamics. To address this gap, we introduce an enhanced method—Binary Overlapped Sliding Window MF-DFA (Bi-OSW-MF-DFA)—that mitigates segmentation discontinuities and improves computational robustness through overlapping windows and binary series partitioning. Applied to spot gold and silver markets, our approach reveals that silver exhibits stronger multifractality and higher inherent risk than gold, with long-range temporal correlations identified as the primary driver of multifractal behavior. This study offers a refined analytical framework for market risk assessment and provides actionable insights for investors and portfolio managers navigating precious metals volatility.
Computational and Data-Intensive Science
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Advances in Uniform Experimental Designs: A Decade Selective Review of Algorithmic Search and Deterministic Construction Methods
This paper presents a comprehensive and selective review of the last decade's progress in the construction of uniform experimental designs. Confronting the growing complexity of modern experiments—characterized by high-dimensional factor spaces and constrained resources—recent research has produced promising methods tools for constructing efficient, cost-effective designs. The review is organized around three pivotal themes: (1) enhanced stochastic search algorithms, including adjusted threshold accepting and permutation-projection methods, for constructing (nearly) uniform minimum aberration designs, supported by benchmarks that reduce computational search; (2) frameworks for constructing uniform fold-over designs in two-stage sequential experimentations, enabling the breaking of aliasing structures across symmetric and asymmetric designs; and (3) deterministic construction algorithms—such as multiple doubling, tripling, and quadrupling, and their integration—for efficiently generating large-scale uniform designs with low, high, or mixed levels without exhaustive search. Collectively, these advances offer researchers a robust, computationally efficient, and theoretically coherent toolkit for designing experiments across scientific and industrial domains, representing a substantial leap beyond conventional methodologies. A critical discussion and comparative analysis of the reviewed methods are also provided, along with practical recommendations for implementation.