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SSRN 2024年

作者： Shao, Pei-Chiang Department of Applied Mathematics Chung Yuan Christian University Zhongli District Taoyuan City320314 Taiwan Undergraduate Program in College of Electrical Engineering and Computer Science Chung Yuan Christian University Zhongli District Taoyuan City320314 Taiwan

Severe intensity inhomogeneity (InH) and complex real-world textures cause great difficulties and become two important issues in image segmentation and object extraction applications. Plenty of methods are proposed to tackle these issues, however, they usually perform poorly on images possess both InH and texture. In this paper, we propose a region-based active contour model for segmenting images with simultaneous inhomogeneity and texture. A new bias field possesses both global and local smoothness properties is proposed to handle the InH issue, and a pixel inhomogeneity factor (PIF) is employed to jointly deal with InH and textured images. We also employ the total variation (TV) regularization to further smooth and denoise the transformed PIF image, making the segmentation process to have the nice properties of global convergence and independence of contour initialization. A large number of numerical experiments and comparisons are conducted to demonstrate the effective performance of the newly proposed method. © 2024, The Authors. All rights reserved.

关键词： Textures

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Spherical fuzzy programming approach to optimize the transportation problem

Research Square

引用

Research Square 2022年

作者： Kaur, Manbir Yadav, Rakesh Department of Applied Mathematics Sardar Beant Singh State University Punjab Gurdaspur India Department of Mathematics School of Chemical Engineering & Physical Sciences Lovely Professional University Punjab Phagwara India

In any real life problems, decision making plays very important role. It is always observable that uncertainty, hesitation, vagueness etc involves in real life situations. The existence of such factors results in increases the difficulty for decision maker(s) to decide the accurate/precise,crisp value of parameters involved in the specific problem. In present study, the uncertainty included in transportation problem is deal with the proposed method based on derived accuracy function. The function is derived with centroid method and further is used to covert the fuzzy number into crisp value in proposed approach. The applicability and validity is presented with the numerical illustration. The superiority and comparative study is shown by applying it to the real life transportation problem as a case study of Dinanagar city, India. © 2022, CC BY.

关键词： Fuzzy sets

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Ternary system approach in separation and purification of biodiesel fuel: An organised review

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Journal of Molecular Liquids 2024年 415卷

作者： Adama, Kenneth Kennedy Anani, Osikemekha Anthony Ukhurebor, Kingsley Eghonghon Isaac, Oamen Festus Aigbe, Uyiosa Osagie Hossain, Ismail Aluyor, Emmanuel Osikhuemeh Audu, Kimble Thomas Okpo Department of Chemical Engineering Faculty of Engineering Edo State University Edo State Uzairue Nigeria Laboratory for Ecotoxicology and Hydrobiology Department of Animal and Environmental Biology Delta State University Abraka Delta State Nigeria Department of Physics Faculty of Science Edo State University Edo State Uzairue Nigeria Department of Mechanical Engineering Faculty of Engineering Edo State University Uzairue Edo State Nigeria Department of Mathematics and Physics Faculty of Applied Sciences Cape Peninsula University of Technology Cape Town South Africa Department of Nuclear and Renewable Energy Ural Federal University Yekaterinburg620002 Russia Department of Chemical Engineering Faculty of Engineering University of Benin Edo State Benin-City Nigeria

Application of a ternary system (TS) approach involving ternary phase diagrams from liquid-–liquid equilibrium (LLE) data can assist in highlighting constituent components in biodiesel (BD) systems at investigated conditions, thereby improving the purification process. The LLE system is a mass transfer operation in which a liquid solution is contacted with a second immiscible or nearly immiscible liquid selected preferentially to remove desired components based on the solubilities of the components and their chemical differences. Different sources of feedstock for BD production are presented, as well as highlighting the necessity for enhanced feedstock quality to obtain high-quality BD. Different TS studies and approaches over the last few decades are enumerated and discussed. Furthermore, different local composition modelling approaches to the study of TS in BD are presented, highlighting the importance of component phase distribution within the ternary BD system for optimisation of the purification process and validation of experimental results based on simulated models. The ternary approach method can serve as a potential means for designing efficient separation systems that optimise BD purification after the transesterification reaction, thereby improving efficiency, material and operational cost reduction, and the elimination of wastewater generation. In this regard, this paper precisely reviews the separation and purification of BD using TS approaches. © 2024 Elsevier B.V.

关键词： Ternary systems

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Recent Advances and Applications of Machine Learning in Experimental Solid Mechanics: A Review

arXiv

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arXiv 2023年

作者： Jin, Hanxun Zhang, Enrui Espinosa, Horacio D. Department of Mechanical Engineering Northwestern University EvanstonIL60208 United States Theoretical and Applied Mechanics Program Northwestern University EvanstonIL60208 United States Division of Applied Mathematics Brown University ProvidenceRI02912 United States

For many decades, experimental solid mechanics has played a crucial role in characterizing and understanding the mechanical properties of natural and novel materials. Recent advances in machine learning (ML) provide new opportunities for the field, including experimental design, data analysis, uncertainty quantification, and inverse problems. As the number of papers published in recent years in this emerging field is exploding, it is timely to conduct a comprehensive and up-to-date review of recent ML applications in experimental solid mechanics. Here, we first provide an overview of common ML algorithms and terminologies that are pertinent to this review, with emphasis placed on physics-informed and physics-based ML methods. Then, we provide thorough coverage of recent ML applications in traditional and emerging areas of experimental mechanics, including fracture mechanics, biomechanics, nano- and micro-mechanics, architected materials, and 2D material. Finally, we highlight some current challenges of applying ML to multi-modality and multi-fidelity experimental datasets and propose several future research directions. This review aims to provide valuable insights into the use of ML methods as well as a variety of examples for researchers in solid mechanics to integrate into their experiments. © 2023, CC BY.

关键词： Machine learning

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Discrete null field equation methods for solving Laplace's equation: Boundary layer computations

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Numerical Methods for Partial Differential Equations 2024年第4期40卷 e23092-e23092页

作者： Zhang, Li-Ping Li, Zi-Cai Lee, Ming-Gong Huang, Hung-Tsai School of Mathematical Sciences Qufu Normal University Shandong Qufu China Department of Applied Mathematics National Sun Yat-sen University Kaohsiung Taiwan Department of Tourism and Leisure/Ph.D. Program in Engineering Science Chung Hua University Hsinchu Taiwan Department of Data Science and Analytics I-Shou University Kaohsiung Taiwan

Consider Dirichlet problems of Laplace's equation in a bounded simply-connected domain (Formula presented.), and use the null field equation (NFE) of Green's representation formulation, where the source nodes (Formula presented.) are located on a pseudo-boundary (Formula presented.) outside (Formula presented.) but not close to its boundary (Formula presented.). Simple algorithms are proposed in this article by using the central rule for the NFE, and the normal derivatives (Formula presented.) of the solutions on the boundary (Formula presented.) can be easily obtained. These algorithms are called the discrete null field equation method (DNFEM) because the collocation equations are, indeed, the direct discrete form of the NFE. The bounds of the condition number are like those by the method of fundamental solutions (MFS) yielding the exponential growth as the number of unknowns increases. One trouble of the DNFEM is the near singularity of integrations for the solutions in boundary layers in Green's representation formulation. The traditional BEM also suffers from the same trouble. To deal with the near singularity, quadrature by expansions and the sinh transformation are often used. To handle this trouble, however, we develop two kinds of new techniques: (I) the interpolation techniques by Taylor's formulas with piecewise (Formula presented.) -degree polynomials and the Fourier series, and (II) the mini-rules of integrals, such as the mini-Simpson's and the mini-Gaussian rules. Error analysis is made for technique I to achieve optimal convergence rates. Numerical experiments are carried out for disk domains to support the theoretical analysis made. The numerical performance of the DNFEM is excellent for disk domains to compete with the MFS. The errors with (Formula presented.) can be obtained by combination algorithms, which are satisfactory for most engineering problems. In summary, the new simple DNFEM is based on the NFE, which is different from the boundary elem

关键词： Fourier series

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On Optimal Control of Hybrid Dynamical Systems using Complementarity Constraints

arXiv

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arXiv 2025年

作者： Kazi, Saif R. Wang, Kexin Biegler, Lorenz T. T-5 Applied Mathematics and Plasma Physics Los Alamos National Laboratory Los AlamosNM87545 United States College of Control Science and Engineering Zhejiang University Zhejiang Hangzhou310027 China Department of Chemical Engineering Carnegie Mellon University PittsburghPA15213 United States

Optimal control for switch-based dynamical systems is a challenging problem in the process control literature. In this study, we model these systems as hybrid dynamical systems with finite number of unknown switching points and reformulate them using non-smooth and non-convex complementarity constraints as a mathematical program with complementarity constraints (MPCC). We utilize a moving finite element based strategy to discretize the differential equation system to accurately locate the unknown switching points at the finite element boundary and achieve high-order accuracy at intermediate non-collocation points. We propose a globalization approach to solve the discretized MPCC problem using a mixed NLP/MILP-based strategy to converge to a non-spurious first-order optimal solution. The method is tested on three dynamic optimization examples, including a gas-liquid tank model and an optimal control problem with a sliding mode *** Codes 34A36, 93C30, 90C33, 49M37 © 2025, CC BY.

关键词： Optimal control systems

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Marine macro-litter sources and ecological impact: a review

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Environmental Chemistry Letters 2024年第3期22卷 1257-1273页

作者： Le, Van-Giang Nguyen, Hoang-Lam Nguyen, Minh-Ky Lin, Chitsan Hung, Nguyen T. Quang Khedulkar, Akhil P. Hue, Nguyen K. Trang, Phung T. Thu Mungray, Arvind Kumar Nguyen, D. Duc Central Institute for Natural Resources and Environmental Studies Vietnam National University Hanoi111000 Viet Nam Department of Civil Engineering McGill University MontrealQC Canada Faculty of Environment and Natural Resources Nong Lam University Hamlet 6 Linh Trung Ward Thu Duc City Ho Chi Minh City700000 Viet Nam Ph.D. Program in Maritime Science and Technology National Kaohsiung University of Science and Technology Kaohsiung81157 Taiwan Department of Marine Environmental Engineering National Kaohsiung University of Science and Technology Kaohsiung81157 Taiwan Department of Biomedical Engineering and Environmental Science National Tsing Hua University Hsinchu30013 Taiwan Environmental Research Center Institute of Hydrology and Meteorology Science and Climate Change Hanoi111000 Viet Nam Department of Chemical Engineering Sardar Vallabhbhai National Institute of Technology Gujarat Surat395007 India Department of Civil and Energy System Engineering Kyonggi University Suwon16227 Korea Republic of Institute of Applied and Sustainable Technology Nguyen Tat Thanh University Ho Chi Minh City700000 Viet Nam

Marine pollution by various debris is rising in the context of increasing urbanization, industrialization and worldwide trade. Here, we review marine macro-litter with focus on sources, abundance, distribution, and impact on aquatic wildlife, human health, and the economy. We observe that about 75–80% of marine litter originates from land-based sources, including poorly managed landfills and improper disposal. Macro-litter ingestion by marine life is of growing concern, in particular concerning the presence of plastics and associated pollutants, e.g., bisphenol A and phthalates, in fishes. These pollutants are accumulated and transferred to human via seafood. Marine plastic pollution induces a substantial rise of economic costs due to the decline of ecosystem services. Mitigation of marine plastic pollution should be done by following the ten Rs principles of refuse, rethink, reduce, re-use, repair, refurbish, remanufacture, repurpose, recycle, and recover. © The Author(s), under exclusive licence to Springer Nature Switzerland AG 2024.

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Enhancement of effluent degradation by zinc oxide, carbon nitride, and carbon xerogel trifecta on brass monoliths

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Environmental Science and Pollution Research 2024年第40期31卷 53472-53496页

作者： da Silva, Émerson Felipe Mendonça Garcia, Ramón Raudel Peña Rodrigues, Liana Alvares Napoleão, Daniella Carla Sanz, Oihane Almeida, Luciano Costa Department of Chemical Engineering Technology and Geoscience Center Federal University of Pernambuco PE Recife50740-521 Brazil Pós Graduate Program in Materials Science and Engineering Federal University of Piauí PI Teresina64049-550 Brazil Academic Unit of Cabo de Santo Agostinho Federal Rural University of Pernambuco PE Cabo de Santo Agostinho54518-430 Brazil Dept. of Applied Chemistry Chemistry Faculty University of the Basque Country UPV/EHU P. Lardizabala 3 San Sebastian20018 Spain Escola de Engenharia de Lorena EEL/USP Estrada Municipal Do Campinho S/N São Paulo LorenaCEP 12602-810 Brazil

In recent years, heterogeneous photocatalysis has emerged as a promising alternative for the treatment of organic pollutants. This technique offers several advantages, such as low cost and ease of operation. However, finding a semiconductor material that is both operationally viable and highly active under solar irradiation remains a challenge, often requiring materials of nanometric size. Furthermore, in many processes, photocatalysts are suspended in the solution, requiring additional steps to remove them. This can render the technique economically unviable, especially for nanosized catalysts. This work demonstrated the feasibility of using a structured photocatalyst (ZnO, g-C3N4, and carbon xerogel) optimized for this photodegradation process. The synthesized materials were characterized by nitrogen adsorption and desorption, X-ray diffraction (XRD), and diffuse reflectance spectroscopy (DRS). Adhesion testing demonstrated the efficiency of the deposition technique, with film adhesion exceeding 90%. The photocatalytic evaluation was performed using a mixture of three textile dyes in a recycle photoreactor, varying pH (4.7 and 10), recycle flow rate (2, 4, and 6 L h−1), immobilized mass (1, 2, and 3 mg cm−2), monolith height (1.5, 3.0, and 4.5 cm), and type of radiation (solar and visible artificials;and natural solar). The structured photocatalyst degraded over 99% of the dye mixture under artificial radiation. The solar energy results are highly promising, achieving a degradation efficiency of approximately 74%. Furthermore, it was possible to regenerate the structured photocatalyst up to seven consecutive times using exclusively natural solar light and maintain a degradation rate of around 70%. These results reinforce the feasibility and potential application of this system in photocatalytic reactions, highlighting its effectiveness and sustainability. © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2024.

关键词： Heterojunctions

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Dynamic financial processes identification using sparse regressive reservoir computers

arXiv

引用

arXiv 2023年

作者： Vides, Fredy Nogueira, Idelfonso B.R. Banegas, Lendy Flores, Evelyn Department of Statistics and Research National Commission of Banks and Insurance Companies of Honduras Honduras Honduras Department of Applied Mathematics Universidad Nacional Autónoma de Honduras Honduras Honduras Department of Chemical Engineering Norwegian University of Science and Technology Norway

In this document, we present key findings in structured matrix approximation theory, with applications to the regressive representation of dynamic financial processes. Initially, we explore a comprehensive approach involving generic nonlinear time delay embedding for time series data extracted from a financial or economic system under examination. Subsequently, we employ sparse least-squares and structured matrix approximation methods to discern approximate representations of the output coupling matrices. These representations play a pivotal role in establishing the regressive models corresponding to the recursive structures inherent in a given financial system. The document further introduces prototypical algorithms that leverage the aforementioned techniques. These algorithms are demonstrated through applications in approximate identification and predictive simulation of dynamic financial and economic processes, encompassing scenarios that may or may not exhibit chaotic behavior. Copyright © 2023, The Authors. All rights reserved.

关键词： Least squares approximations

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Comparison of the Effectiveness of Machine Learning Techniques for the Number of Road Traffic Injuries

Comparison of the Effectiveness of Machine Learning Techniqu...

引用

International ECTI Northern Section Conference on Electrical, Electronics, Computer and Telecommunications engineering (ECTI-NCON)

作者： Wirawan Puttamat Wikanda Phaphan Anuchit Jitpattanakul Chainarong Pianpailoon Sakorn Mekruksavanich Department of Mathematics Faculty of Education Chaiyaphum Rajabhat University Chaiyaphum Thailand Department of Applied Statistics Faculty of Applied Science King Mongkut’s University of Technology North Bangkok Bangkok Thailand Research Group in Statistical Learning and Inference Department of Mathematics Faculty of Applied Science King Mongkut’s University of Technology North Bangkok Bangkok Thailand Intelligent and Nonlinear Dynamic Innovations Research Center Curriculum and Teaching Program (Mathematics) Faculty of Education Sakon Nakhon Rajabhat University Sakon Nakhon Thailand Department of Computer Engineering School of Information and Communication University of Phayao Phayao Thailand

This article aims to compare forecasting techniques with machine learning techniques for predicting the number of people injured in road accidents using data from the Injury Information Collaboration Center, department of Disease Control, Ministry of Public Health Outpatient Files (OPD) spanning the years 2018 to 2022. The four machine-learning techniques examined in this study include Decision Tree Regression, Random Forest Regression, Support Vector Regression, and Multiple Linear Regression. The data analysis was performed using the R programming language. The results revealed that the Decision Tree Regression technique yielded the most accurate predictions for the number of road traffic injuries, as evidenced by its lowest values of MAE, MSE, and RMSE.

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