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Electroosmotic flow in ternary (TiO2-SiO2-Al2O3) blood-based sutterby nanomaterials with bio-active mixers

International Journal of Thermofluids 2023年 18卷

作者： Islam, Saiful Rana, B.M.J. Parvez, Md.Shohel Hossain, Md.Shahadat Rahman, M.M. Department of Mathematics Bangladesh University of Engineering and Technology Dhaka1000 Bangladesh Department of Computer Science and Engineering Stamford University Bangladesh Dhaka1217 Bangladesh Department of Applied Mathematics Gono Bishwabidyalay Dhaka1344 Bangladesh Physics Discipline Khulna University Khulna9208 Bangladesh Department of Quantitative Sciences International University of Business Agriculture and Technology Dhaka1230 Bangladesh

Medical scientists, clinicians, and bioengineers are fascinated in the detection of blood flow pattern through cardiovascular system because it is employed to diagnose the human circulatory disorders such as atherosclerosis. This work is dedicated to the mathematical modeling for the blood flow through human circulatory regimen with electroosmotic force, tri-hybrid nanoparticles, swimming microbes and activation energy. A novel ternary fluid is prepared by dispersing titania, silica, and alumina nanoparticles in pure blood. It is a well-known fact that blood is regarded as incompressible non-Newtonian fluid, due to which Sutterby fluid paradigm is regarded to detect the shear-thinning characteristics of blood precisely. To describe the electroosmotic flow, Poisson-Boltzmann expression is used. The novelty of the appraisal is the incorporation of electroosmotic force on blood flow containing with microbes and three distinct nanoparticles. Appropriate dimension-free variables are utilized to modify the dimensional system into dimension-free version. An unraveller approach, finite-difference is assigned to evaluate the numerical solution of dimensionless system accompanied by stability and convergence. The computed numerical results are sketched versus crucial factors and explored through graphs and tables. Electroosmotic variable enhances the motion of ternary blood nanofluid. Higher exponential heat source variable strengthens the thermal borderline wideness. Heat transport rate is weakened via higher estimation of thermo-migration and random motion variables. Decay in mass transport rate is noticed for thermo-migration factor. Peclet number weakens the motile microbe's density. Bio-active Lewis number strengthens the density number of motile microbes. This study is extremely worthwhile in medical domain such as cancer treatment, heart surgeries, tumor treatment, microbial fuel cells, and microfluidic systems. © 2023 The Author(s)

关键词： Electroosmosis

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Scheduling Dual-Arm Cluster Tools With Multiple Wafer Types and Residency Time Constraints

引用

IEEE/CAA Journal of Automatica Sinica 2020年第3期7卷 776-789页

作者： Jipeng Wang Hesuan Hu Chunrong Pan Yuan Zhou Liang Li IEEE School of Mechano-Electronic Engineering Xidian UniversityXi’an 710071China School of Computer Science and Engineering College of EngineeringNanyang Technological UniversitySingapore 639798Singapore School of Mechanical and Electrical Engineering Jiangxi University of Science and TechnologyGanzhou 341000China Department of Information Engineering Electrical Engineering and Applied MathematicsUniversity of SalernoFisciano 84084Italy

Accompanying the unceasing progress of integrated circuit manufacturing technology, the mainstream production mode of current semiconductor wafer fabrication is featured with multi-variety, small batch, and individual customization, which poses a huge challenge to the scheduling of cluster tools with single-wafer-type fabrication. Concurrent processing multiple wafer types in cluster tools, as a novel production pattern, has drawn increasing attention from industry to academia, whereas the corresponding research remains insufficient. This paper investigates the scheduling problems of dual-arm cluster tools with multiple wafer types and residency time constraints. To pursue an easy-to-implement cyclic operation under diverse flow patterns,we develop a novel robot activity strategy called multiplex swap sequence. In the light of the virtual module technology, the workloads that stem from bottleneck process steps and asymmetrical process configuration are balanced satisfactorily. Moreover, several sufficient and necessary conditions with closed-form expressions are obtained for checking the system's schedulability. Finally, efficient algorithms with polynomial complexity are developed to find the periodic scheduling, and its practicability and availability are demonstrated by the offered illustrative examples.

关键词： Cluster tools multiple wafer types scheduling semiconductor manufacturing wafer fabrication

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Energy-Efficient Transmission in Wireless Networks Using Resnet with Gravitational Search Algorithm

Energy-Efficient Transmission in Wireless Networks Using Res...

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Disruptive Technologies (ICDT), International Conference on

作者： Rajakumari S Kantharaju HC Shadab Ahmad Rupa Rani Sharma S. Sudha T Ramesh Department of Mathematics R.M.D. Engineering College Department of AI & ML Vemana Institute of Technology Bengaluru Karnataka India Department of Electrical and Computer Engineering Samara University Afar region Ethiopia Department of Applied Science G.L Bajaj Institute of Technology and Management Greater Noida Uttar Pradesh India Department of ECE Sri Ranganathar Institute of Engineering and Technology Coimbatore Tamilnadu India Department Of Computer Science and Engineering R.M.K Engineering College

Although wireless networks are extremely important in modern communication, one of the most significant challenges they face is the quantity of energy that they use. Within this study, a new way of sending data over wireless networks is suggested. The gravitational search algorithm (GSA) and residue networks of the ResNet type are used together in this method. By using wireless networks, the main goal of this method is to find answers to problems that come up with using energy more efficiently. The creation and use of a hybrid ResNet-GSA model for wireless communication is one of the most important parts of our method. Because it follows the rules of gravity, GSA can quickly look through the solution space to find the right parameter values. At the same time, the network works better when the deep learning features of ResNet are used. The results of our research show that there are big improvements in how much energy is used compared to using traditional ways. If you want to cut down on the amount of energy used, the ResNet-GSA strategy that was suggested also works well. The findings demonstrate that optimisation techniques and deep learning methodologies are not only compatible with one another but also perform effectively together to make wireless networks more environmentally friendly.

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Generalized Cauchy–Riemann Equations with Power-law Singularities in Coefficients of Lower Order

Generalized Cauchy–Riemann Equations with Power-law Singula...

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International Scientific Conference on Modern Methods, Problems and Applications of Operator Theory and Harmonic Analysis, OTHA 2020

作者： Soldatov, A.P. Rasulov, A.B. Federal Research Center "Computer Science and Control" of the Russian Academy of Sciences Moscow Center for Fundamental and Applied Mathematics Moscow Russia National Research University "Moscow Power Engineering Institute" Moscow Russia

ISBN: (纸本)9783030774929

The generalized Cauchy-Riemann equation uz¯+ au+ bū= f is considered with coefficients having power singularities at the origin. More exactly it is assumed that a(z) = O(|z|−α−1), α∈ , and b(z) = O(|z|−1) as z → 0. With the help of so called modified Pompeiu integral a general solution of this equation is described. © 2021, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Integral equations

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Automated Discovery of Continuous Dynamics from Videos

arXiv

引用

arXiv 2024年

作者： Huang, Kuang Cho, Dong Heon Chen, Boyuan Department of Applied Physics and Applied Mathematics Columbia University 500 W. 120th Street New YorkNY10027 United States Department of Computer Science Duke University 308 Research Dr. DurhamNC27705 United States Department of Mechanical Engineering and Material Science Duke University 121 Hudson Hall DurhamNC27708 United States Department of Electrical and Computer Engineering Duke University 100 Science Dr. DurhamNC27708 United States

Dynamical systems form the foundation of scientific discovery, traditionally modeled with predefined state variables such as the angle and angular velocity, and differential equations such as the equation of motion for a single pendulum. We propose an approach to discover a set of state variables that preserve the smoothness of the system dynamics and to construct a vector field representing the system’s dynamics equation, automatically from video streams without prior physical knowledge. The prominence and effectiveness of the proposed approach are demonstrated through both quantitative and qualitative analyses of various dynamical systems, including the prediction of characteristic frequencies and the identification of chaotic and limit cycle behaviors. This shows the potential of our approach to assist human scientists in scientific discovery. Copyright © 2024, The Authors. All rights reserved.

关键词： System theory

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Analysis of Extreme Rainfall Trends Over 75 Locations (District Wise) of Uttar Pradesh, India using Daily Gridded Rainfall Data (1973-2023)

Analysis of Extreme Rainfall Trends Over 75 Locations (Distr...

引用

Cognitive Computing in engineering, Communications, sciences and Biomedical Health Informatics (IC3ECSBHI), International Conference on

作者： Sushil Kumar Arun Kumar Amarendra Singh Amar Pratap Bhaskar Anurag Singh Baghel Jagabandhu Panda Deparment of Applied Mathematics Gautam Buddha University Greater Noida India Department of Mathematics M.M.H. College Ghaziabad India Centre for Atmospheric Sciences IIT Delhi India Department of Computer Science and Engineering Gautam Buddha University Greater Noida India Department of Earth and Atmospheric Sciences National Institute of Technology Rourkela India

ISBN: (数字)9798331518523

ISBN: (纸本)9798331518530

This study analyzes rainfall patterns in selected districts of Uttar Pradesh, India, using daily gridded rainfall data from the India Meteorological Department (IMD) for the period 1973 to 2023. Trends in severe daily rainfall occurrences were identified using the Mann-Kendall (MK) test. The inverse distance weighting (IDW) interpolation method was used to visualise the geographical distribution of rainfall patterns. The results demonstrate that while monsoon patterns were declining in certain areas, they were increasing in others. The study sheds light on how Uttar Pradesh's agricultural planning and water resource management are affected by rainfall unpredictability.

关键词： Climate change Irrigation Interpolation Rain Disasters Monsoons Market research Planning Floods Water resources

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Prediction of Passenger Car Friction Brake Application Based on Longitudinal Dynamics Using On-Road Vehicle Driving Data

SSRN

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SSRN 2023年

作者： Jensen, Kenneth M. Santos, Ilmar F. Clemmensen, Line Katrine Harder Theodorsen, Søren Corstens, Harry J.P. Department of Civil and Mechanical Engineering Technical University of Denmark Kgs. Lyngby Denmark Department of Applied Mathematics and Computer Science Technical University of Denmark Kgs. Lyngby Denmark ILIAS Solutions Brussels Belgium

This work considers the problem of predicting the braking state of vehicles, i.e. when the friction brakes are being applied. The work is aimed at providing the foundation for the prediction of brake pad wear from vehicle usage data. The braking state is predicted from vehicle longitudinal dynamics, considering 6-axis inertial measurement unit (IMU), global navigation satellite system (GNSS), and vehicle on-board diagnostics (OBD-II) data, along with sensor fusion for more accurate vehicle state estimation. The proposed method aims at providing broad applicability to different vehicles, by using only standard OBD-II data instead of relying on manufacturer specific data. Rolling resistance coefficient and product of aerodynamic drag coefficient and frontal area are estimated using linear regression on data from vehicle coast-down tests with the drivetrain disengaged. Engine mass moment of inertia along with engine braking torque is estimated from similar tests with the drivetrain engaged in different gears. The engine braking torque is approximated using a polynomial expression in the engine speed. Braking state predictions are made by comparing measured longitudinal decelerations with estimated, assuming that if the measured exceeds the estimated, then the difference is caused by the application of the friction brakes. Experimental validation was carried out using two modern passenger cars. Comparisons of measured and estimated decelerations from coast-down tests with fitted parameters show good agreements when the drivetrain is disengaged, as well as engaged. For one vehicle labels for the braking state are obtained indirectly using a camera pointed at the brake pedal, using object tracking to determine if the brakes are being applied. For the other vehicle, the braking states are obtained more directly trough access to the brake pressure. Overall prediction performance is good with accuracy >94% and precision around 99%, while recall is around 90% across the two v

关键词： Parameter estimation

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Anomaly Detection with Variance Stabilized Density Estimation

arXiv

引用

arXiv 2023年

作者： Rozner, Amit Battash, Barak Li, Henry Wolf, Lior Lindenbaum, Ofir Faculty of Engineering Bar Ilan University Ramat-Gan Israel Department of Applied Mathematics Yale University New HavenCT United States School of Computer Science Tel Aviv University Tel-Aviv Israel

We propose a modified density estimation problem that is highly effective for detecting anomalies in tabular data. Our approach assumes that the density function is relatively stable (with lower variance) around normal samples. We have verified this hypothesis empirically using a wide range of real-world data. Then, we present a variance-stabilized density estimation problem for maximizing the likelihood of the observed samples while minimizing the variance of the density around normal samples. To obtain a reliable anomaly detector, we introduce a spectral ensemble of autoregressive models for learning the variance-stabilized distribution. We have conducted an extensive benchmark with 52 datasets, demonstrating that our method leads to state-of-the-art results while alleviating the need for data-specific hyperparameter tuning. Finally, we have used an ablation study to demonstrate the importance of each of the proposed components, followed by a stability analysis evaluating the robustness of our model. © 2023, CC BY.

关键词： Anomaly detection

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Continuous Image Outpainting with Neural ODE

SSRN

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SSRN 2023年

作者： Gao, Penglei Yang, Xi Zhang, Rui Huang, Kaizhu Department of Computer Science University of Liverpool United Kingdom School of Advanced Technology Department of Foundational Mathematics Xi’an Jiaotong-Liverpool University China Institute of Applied Physical Sciences and Engineering Duke Kunshan University China

Different from image inpainting, generalised image outpainting aims to extend appealing content all-side around a given image. Existing state-of-the-art outpainting methods often rely on discrete extrapolation to extend the feature map in the bottleneck. They thus suffer from content unsmoothness, especially in circumstances where the outlines of objects in the extrapolated regions are incoherent with the input sub-images. To mitigate this issue, we design a novel bottleneck with Neural ODEs to make continuous extrapolation in latent space, which could be a plug-in for many deep learning frameworks. Our ODE-based network continuously transforms the state and makes accurate predictions by learning the incremental relationship among latent points, leading to both smooth and structured feature representation. Experimental results on three real-world datasets both applied on transformer-based and CNN-based frameworks show that our methods could generate more realistic and coherent images against the state-of-the-art image outpainting approaches. © 2023, The Authors. All rights reserved.

关键词： Extrapolation

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Prediction of Vehicle Braking State Based on Longitudinal Dynamics Using On-Road Driving Data

SSRN

引用

SSRN 2023年

作者： Jensen, Kenneth M. Santos, Ilmar F. Clemmensen, Line K.H. Theodorsen, Søren Corstens, Harry J.P. Department of Civil and Mechanical Engineering Technical University of Denmark Kgs. Lyngby Denmark Department of Applied Mathematics and Computer Science Technical University of Denmark Kgs. Lyngby Denmark ILIAS Solutions Brussels Belgium

This work considers the problem of predicting the braking state of vehicles i.e., when the friction brakes are being applied. The work is aimed at providing the foundation for the prediction of brake pad wear from vehicle usage data. The braking state is predicted from vehicle longitudinal dynamics, considering 6-axis inertial measurement unit (IMU), global navigation satellite system (GNSS), and vehicle on-board diagnostics (OBD-II) data, along with sensor fusion for more accurate vehicle state estimation. The proposed method aims at providing broad applicability to different vehicles, by using only standard OBD-II data instead of relying on manufacturer specific data. Rolling resistance coefficient and product of aerodynamic drag coefficient and frontal area are estimated using linear regression on data from vehicle coast-down tests with the drivetrain disengaged. Engine mass moment of inertia along with engine braking torque is estimated from similar tests with the drivetrain engaged in different gears. The engine braking torque is approximated using a polynomial expression in the engine speed. Braking state predictions are made by comparing measured longitudinal decelerations with estimated, assuming that if the measured exceeds the estimated, then the difference is caused by the application of the friction brakes. Experimental validation was carried out using two modern passenger cars. Comparisons of measured and estimated decelerations from coast-down tests with fitted parameters show good agreements when the drivetrain is disengaged, as well as engaged. For one vehicle labels for the braking state are obtained indirectly using a camera pointed at the brake pedal, using object tracking to determine if the brakes are being applied. For the other vehicle, the braking states are obtained more directly trough access to the brake pressure. Overall prediction performance is good with accuracy >94% and precision around 99%, while recall is around 90% across the two v

关键词： Parameter estimation

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