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Deep bed filtration model for cake filtration and erosion

Applied Mathematics and Mechanics(English Edition) 2024年第2期45卷 355-372页

作者： L.I.KUZMINA Y.V.OSIPOV A.R.PESTEREV Department of Applied Mathematics HSE UniversityMoscow 101000Russia Department of Computer Science and Applied Mathematics Moscow State University of Civil EngineeringMoscow 129337Russia

Many phenomena in nature and technology are associated with the filtration of suspensions and colloids in porous media. Two main types of particle deposition,namely, cake filtration at the inlet and deep bed filtration throughout the entire porous medium, are studied by different models. A unified approach for the transport and deposition of particles based on the deep bed filtration model is proposed. A variable suspension flow rate, proportional to the number of free pores at the inlet of the porous medium, is considered. To model cake filtration, this flow rate is introduced into the mass balance equation of deep bed filtration. For the cake filtration without deposit erosion,the suspension flow rate decreases to zero, and the suspension does not penetrate deep into the porous medium. In the case of the cake filtration with erosion, the suspension flow rate is nonzero, and the deposit is distributed throughout the entire porous medium. An exact solution is obtained for a constant filtration function. The method of characteristics is used to construct the asymptotics of the concentration front of suspended and retained particles for a filtration function in a general form. Explicit formulae are obtained for a linear filtration function. The properties of these solutions are studied in detail.

关键词： deep bed filtration cake filtration porous medium particle deposition and erosion analytical solution concentration front

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Towards Enhancing Child Safety: A Deep Learning Approach to Detect Child Safe and Unsafe Objects

Towards Enhancing Child Safety: A Deep Learning Approach to ...

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2024 IEEE International Women in engineering (WIE) Conference on electrical and computer engineering, WIECON-ECE 2024

作者： Khan, Fairuz Areefin Dey, Ashim Chittagong University of Engineering and Technology Department of Electrical and Electronic Engineering Chittagong4349 Bangladesh Chittagong University of Engineering and Technology Department of Computer Science and Engineering Chittagong4349 Bangladesh

ISBN: (纸本)9798331535476

The safety and well-being of children are a paramount concern, and the accurate detection of potentially haz-ardous objects is crucial in ensuring their protection, especially in indoor situations. In the Artificial Intelligence (AI) age, the future belongs to domestic robots;they will be used for child education, surveillance, and healthcare support. Early identification of unsafe objects and intervention by these next-generation social family robots can play an essential role in providing a safer environment for children. Keeping these issues in mind, this study aims to tackle daily risks and accidents that endanger children by using computer vision to detect unsafe objects. To achieve this goal, a unique dataset namely ChildSUn is introduced containing approximately 5350 images of child-safe and unsafe objects of ten categories. Various CNN architectures, including custom CNN, VGG16, VGG19, ResNet50, Inception-V3, EfficientNet-B0, and MobileNetV2, are implemented on the prepared dataset. A deep dive analysis is performed on the implemented models. The EfficientNet-B0 model showed exceptional performance, reaching a remarkable level of accuracy of 99.63% on the test dataset. These findings underscore the potential of EfficientNet-B0 as an effective solution for real-world child safety applications and encourage further exploration of deep learning techniques to enhance child protection globally. We hope this work will pave the way for future social household robot development, which will ensure child safety in any place. © 2024 IEEE.

关键词： Deep learning

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FeFET Based Logic-in-Memory Pipeline-Style Circuits 17

FeFET Based Logic-in-Memory Pipeline-Style Circuits

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17th IEEE International Conference on Solid-State and Integrated Circuit Technology, ICSICT 2024

作者： Li, Yang Yang, Zhaohui Xia, Yinshui Ningbo University Faculty of Electrical Engineering and Computer Science Ningbo315211 China

ISBN: (纸本)9798350361834

Emerging non-volatile memory technologies provides a solution to break through the limitations of the vonNeumann architecture and using these technologies to develop logic-in-memory circuits. In this paper, we propose a novel circuit design style based on hafnium oxide ferroelectric memory technology, using a accumulator as an example. This design method offers a new direction for the development of logic-in-memory circuits. Additionally, the method significantly increases data processing capability and provides greater flexibility for circuit design. © 2024 IEEE.

关键词： Ferroelectric RAM

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Probabilistic Model Checking of Temporal Interaction Dynamics in the Supreme Court 11th

Probabilistic Model Checking of Temporal Interaction Dynami...

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11th International Symposium on From Data to Models and Back, DataMod 2023

作者： Das, Susmoy Sharma, Arpit Department of Electrical Engineering and Computer Science Indian Institute of Science Education and Research Bhopal Bhopal India

ISBN: (纸本)9783031872167

The Supreme Court plays an extremely critical role in ensuring adherence to the rule of law and in strengthening the democracy. Due to this reason, modeling and analysis of small group interactions in the courtroom setting is an important task as it can help in understanding court decision-making. We apply probabilistic model checking for the modeling and analysis of temporal interaction dynamics in the context of the Supreme Court of the United States. We have used the transcripts of the oral arguments of cases from the Supreme Court for constructing a discrete-time Markov reward model (DTMRM). Next, we formulate interesting queries over interaction by using probabilistic computation tree logic (PCTL) and PCTL with rewards and verify them using a probabilistic symbolic model checker (PRISM). Our experimental results show that probabilistic model checking is very effective in identifying trends, hidden patterns, and how justices behave during the trials. These results not only provide valuable feedback to the justices but may also be used by the advocates and law students for finding better ways to present their arguments in the court. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Markov processes

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A Generalization of the Achievable Rate of a MISO System Using Bode-Fano Wideband Matching Theory

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IEEE Transactions on Wireless Communications 2024年第10期23卷 13313-13329页

作者： Deshpande, Nitish Vikas Castellanos, Miguel R. Khosravirad, Saeed R. Du, Jinfeng Viswanathan, Harish Heath, Robert W. University of California San Diego Department of Electrical and Computer Engineering La Jolla CA92093 United States North Carolina State University Department of Electrical and Computer Engineering RaleighNC27606 United States Nokia Bell Laboratories Murray HillNJ07974 United States

Impedance-matching networks affect power transfer from the radio frequency (RF) chains to the antennas. Their design impacts the signal to noise ratio (SNR) and the achievable rate. In this paper, we maximize the information-theoretic achievable rate of a multiple-input-single-output (MISO) system with wideband matching constraints. Using a multiport circuit theory approach with frequency-selective scattering parameters, we propose a general framework for optimizing the MISO achievable rate that incorporates Bode-Fano wideband matching theory. We express the solution to the achievable rate optimization problem in terms of the optimized transmission coefficient and the Lagrangian parameters corresponding to the Bode-Fano inequality constraints. We apply this framework to a single electric Chu's antenna and an array of dipole antennas. We compare the optimized achievable rate obtained numerically with other benchmarks like the ideal achievable rate computed by disregarding matching constraints and the achievable rate obtained by using sub-optimal matching strategies like conjugate matching and frequency-flat transmission. We also propose a practical methodology to approximate the achievable rate bound by using the optimal transmission coefficient to derive a physically realizable matching network through the ADS software. © 2024 IEEE.

关键词： Scattering parameters

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Personalized Treatment Classification for Breast Cancer Patients using Random Forest Algorithm 2

Personalized Treatment Classification for Breast Cancer Pati...

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2nd DMIHER International Conference on Artificial Intelligence in Healthcare, Education and Industry, IDICAIEI 2024

作者： Fadnavis, Rupa A. Kshirsagar, M.M. Yeshwantrao Chavan College of Engineering Department of Computer Science and Engineering Nagpur India Yeshwantrao Chavan College of Engineering Department of Computer Technology Nagpur India

ISBN: (纸本)9798331528713

In traditional treatments of breast cancer patients, people get the similar treatment that means it follows a "one-size-fits-all"approach. Over a while, doctors have noticed that some treatments have given better results for some people than others. Everyone has their own unique identifying features, and so the treatment to the individual patients also needs to be tailor made. Personalized medicine (PM) for breast cancer considers individual differences in people's lifestyle, surroundings, and genetics, and it provides medicos with the information they need to target disease specific treatments. (ML)Machine learning plays an important role in personalized medicine (PM). It uses computational algorithms to analyze large amounts of data from different input sources such as medical records, molecular, genetic information, and data from clinical trials for finding patterns and predict outcomes. This information can then be used to tailor treatments specifically to an individual's characteristics and assist doctor in finding risk of disease and finding optimal treatments. The paper discusses about application of supervised machine learning (ML)algorithm: Random Forest algorithms for classification of three treatments of breast cancer patients namely chemotherapy, hormonal therapy and amputation. © 2024 IEEE.

关键词： Random forests

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Examination of H&E-stained Oral Cavity-Derived Cancer Image: A Study using UDL-Model

Examination of H&E-stained Oral Cavity-Derived Cancer Image:...

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2024 International Conference on System, Computation, Automation and Networking, ICSCAN 2024

作者： Mohan, Ramya Rajinikanth, Venkatesan Department of Computer Science and Engineering TN Chennai602105 India Division of Research and Innovation Department of Computer Science and Engineering TN Chennai602105 India

ISBN: (纸本)9798331510022

Oral cancer (OC) is a harsh disease that demands timely detection and intervention. Histopathological image-assisted OC detection involves the assessment of tissue specimens under a microscope to detect abnormal cellular structures (ACS) and patterns. Analyzing the ACS and patterns is necessary to confirm the OC. This study presents a deep-learning (DL) segmentation method to isolate the required portion from the histopathology image. This study utilized the Unified Deep-Learning (UDL) model to improve segmentation precision. The examination scheme comprises several stages: (i) collection of images and masks from the data repository, followed by resizing to 224x224 pixels;(ii) segmentation of the required image section using a UDL scheme;(iii) comparison of the segmented region with the mask and computation of image metrics;and (iv) validation of the UDL model's results against other selected DL schemes. This study use 300 images for training and 100 images for validation/testing. The total experimental result (mean ± standard deviation) obtained during the testing task is deemed to validate the efficacy of the UDL model. The findings of this study validate that the suggested model facilitates superior segmentation accuracy (>93%) on the selected database. © 2024 IEEE.

关键词： Lung cancer

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A Study on Partially Homomorphic Encryption 17

A Study on Partially Homomorphic Encryption

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17th International Conference on Ubiquitous Information Management and Communication, IMCOM 2023

作者： Ryu, Jihyeon Kim, Keunok Won, Dongho Sungkyunkwan University Department of Computer Science and Engineering Suwon Korea Republic of Sungkyunkwan University Department of Electrical and Computer Engineering Suwon Korea Republic of

ISBN: (纸本)9781665453486

Recently, data experts can obtain a large amount of data with the development of the Internet. When computing such data, cloud services that do not use the personal device's memory are becoming popular. However, storing sensitive data as a source in the cloud carries the risk of hijacking. To compensate for this, homomorphic encryption, which encrypts and stores sensitive data, and can safely operate in an encrypted state, is being studied. In this paper, we analyze four methods of partially homomorphic encryption among homomorphic encryption methods. We compare and analyze the key size and ciphertext size of four partially homomorphic encryptions, Paillier, ElGamal, ASHE, and Symmetria. © 2023 IEEE.

关键词： Cryptography

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A Hybrid Non-Conformal Volume Surface Integral Equation Method

A Hybrid Non-Conformal Volume Surface Integral Equation Meth...

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2024 International Applied Computational Electromagnetics Society Symposium, ACES-China 2024

作者： Jiang, Yifei Shao, Hanru Ningbo University Faculty of Electrical Engineering and Computer Science Ningbo315211 China

ISBN: (纸本)9798350355581

Traditional volume surface integral equation for analysis of metal-dielectric composites requires the target mesh to be conformal, which leads to over-meshing of the multi-scale model and reduces the solution efficiency. In order to deal with this problem, a non-conformal volume surface integral equation (VSIE) method based on the discontinuous Galerkin volume integral equation (DGVIE) and the grid-robust higher order vector basis (GRHOVB) surface integral equation is proposed in this paper to enhance the computing efficiency. In this method, the DGVIE is used to deal with dielectric target, which avoids the computation of higher-order singular integrals and facilitates the use of volume non-conformal meshing and mixed basis function discretization. The GRHOVB function is used to deal with PEC target, so that the surface mesh also does not need to be conformal. Numerical results verify the good performance of this non-conformal method. © 2024 IEEE.

关键词： Mesh generation

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A Model-Free Approach for Load Frequency Control Using Deep Reinforcement Learning

A Model-Free Approach for Load Frequency Control Using Deep ...

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2025 IEEE Texas Power and Energy Conference, TPEC 2025

作者： Pandey, Bimal Nguyen, Nga University of Wyoming Electrical Engineering & Computer Science LaramieWY82071 United States

ISBN: (纸本)9798331541125

Frequency stability is crucial for the proper operation of the power grids. The changing landscapes in power systems, raised by continuously increasing demand and rapid decommissioning of conventional generation, have changed the frequency dynamics significantly. Load frequency control (LFC) is a mechanism for regulating frequency and ensuring stability by balancing supply and load. Conventional control strategies, which require accurate representation of the mathematical methods, can face difficulty in modeling the complexity of power dynamics. Therefore, this paper proposes a model-free strategy utilizing deep reinforcement learning (DRL) for implementing the LFC mechanism without the involvement of a central controlling. The problem is formulated as a deep deterministic policy gradient (DDPG) to find an optimal solution for regulating frequency control operations at primary and secondary stages. The proposed framework enables the generating unit, acting as an agent, to identify the optimal actions for maintaining system stability by analyzing generation and load patterns. The DRL-based method utilizes the test signal to change the dynamics of the system, and the agent modeled using the recurrent neural network (RNN) framework inside DDPG learns to balance the generation according to the load and ensures restoration of the deviated frequency. The performance of the implemented method is validated with the proportional and integral (PI) controller. © 2025 IEEE.

关键词： Deep reinforcement learning

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