Article
Engineering, Electrical & Electronic
Yanyan Shi, Yuehui Wu, Meng Wang, Zuguang Rao, Bin Yang, Feng Fu, Yajun Lou
Summary: This article proposes a novel approach for image reconstruction of conductivity distribution in electrical impedance tomography (EIT). The approach introduces a fidelity term based on L-1 norm to stabilize the problem and enforce sparsity in the solution. It also introduces a hybrid penalty term combining first-order and high-order total variation to preserve sharp profiles and suppress the staircase effect.
IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT
(2022)
Article
Biochemical Research Methods
Phaneendra K. Yalavarthy, Sandeep Kumar Kalva, Manojit Pramanik, Jaya Prakash
Summary: Photoacoustic/Optoacoustic tomography aims to reconstruct maps of initial pressure rise caused by light pulse absorption in tissue, posing an ill-conditioned and under-determined problem with limited detection positions. A new inversion method integrating denoising procedure within iterative model-based reconstruction was developed to improve quantitative performance, with a non-local means step resulting in 2.5 dB signal-to-noise ratio improvement compared to TV-based reconstruction.
JOURNAL OF BIOPHOTONICS
(2021)
Article
Mathematics
Kuan Li, Chun Huang, Ziyang Yuan
Summary: This paper investigates error estimations for total variation regularization, which is applied in various fields such as signal processing, imaging, and machine learning. The study focuses on properties of the minimizer for the TV regularization problem, including stability, consistency, and convergence rate. Both a priori and a posteriori rules are considered, with an improved convergence rate based on sparsity assumption. Additionally, the paper discusses non-sparsity conditions commonly found in practice, presenting corresponding convergence rates under mild conditions.
Article
Engineering, Electrical & Electronic
Chaitanya Narendra, Puyan Mojabi
Summary: This article presents an improved inverse scattering algorithm for designing reflectionless lossless permittivity profiles that can transform an input field into an output field with desired characteristics.
IEEE TRANSACTIONS ON ANTENNAS AND PROPAGATION
(2022)
Article
Mathematics, Applied
Yiming Gao, Zhengmeng Jin, Xu Li
Summary: In this paper, a variational model based on dynamic optimal transportation and total generalized variation is proposed for CT reconstruction. It aims to reduce the radiation dose for patients and improve image quality and structure preservation. The final state image of the optimal transport problem is reconstructed through CT inversion, utilizing the given initial state as a template for structural information. The proposed model is solved numerically using a first-order algorithm based on the primal-dual method and demonstrated to achieve high-quality and structurally preserved image reconstruction in sparse-view CT.
Article
Engineering, Mechanical
M. Aucejo, O. De Smet
Summary: Input estimation remains a significant issue in structural dynamics, with two main groups of inverse methods in time and frequency domains. This paper introduces a generalized multiplicative regularization for estimating mechanical loads on linear structures, demonstrating high solution accuracy through numerical and real-world applications. The extra tuning parameter in this approach plays a key role in enhancing results amidst measurement noise levels.
MECHANICAL SYSTEMS AND SIGNAL PROCESSING
(2021)
Article
Operations Research & Management Science
Spyridon Pougkakiotis, Jacek Gondzio
Summary: This paper combines an infeasible Interior Point Method (IPM) with the Proximal Method of Multipliers (PMM) to form the IP-PMM algorithm, suitable for solving linearly constrained convex quadratic programming problems. The algorithm uses a single penalty parameter of the logarithmic barrier, inherits the polynomial complexity of IPMs, and is applicable for solving infeasible problems.
COMPUTATIONAL OPTIMIZATION AND APPLICATIONS
(2021)
Article
Engineering, Electrical & Electronic
Suryakanta Parida, Rajasmita Malik, R. K. Parida, B. N. Parida, Nimai C. Nayak
Summary: The microcellular xGnP-loaded EVA/EOC ternary blend nanocomposites were prepared using a melt blending process. The morphological and mechanical properties, as well as the conductivity, were investigated.
JOURNAL OF MATERIALS SCIENCE-MATERIALS IN ELECTRONICS
(2022)
Article
Chemistry, Analytical
Georgios Kargas, Nikolaos Ntoulas, Andreas Tsapatsouli
Summary: The irrigation of green roofs with recycled or saline water can help save valuable drinking water. Monitoring the substrate electrical conductivity (ECsw) is crucial for the sustainable growth of plants on green roofs. This study estimated the ECsw of an extensive green roof substrate using the WET-2 dielectric sensor. The use of the salinity index method reliably predicted the ECsw up to 10-11 dS m(-1), but overestimated it at very low electrical conductivity levels.
Article
Operations Research & Management Science
Stefano Cipolla, Jacek Gondzio
Summary: In this work, we propose the Proximal Stabilized IPM (PS-IPM), which is a Primal Dual Regularized Interior Point Method (PDR-IPM) based on the Proximal Point Method. The PS-IPM is supported by theoretical results and can handle degenerate problems. Additionally, we analyze the relationship between regularization parameters and the computational footprint of solving the Newton linear systems. We show that general purposes preconditioners are still effective in subsequent IPM iterations with the help of a new rearrangement of the Schur complement.
JOURNAL OF OPTIMIZATION THEORY AND APPLICATIONS
(2023)
Article
Engineering, Environmental
Junpyo Hong, Jisung Kwon, Dohyun Im, Jeonggil Ko, Chae Yun Nam, Hyeong Gyu Yang, Sun Ho Shin, Soon Man Hong, Seung Sang Hwang, Ho Gyu Yoon, Albert S. Lee
Summary: Multiple conductive fillers were incorporated in a polypropylene matrix through melt processing. The properties of the composites, including electrical conductivity, thermal conductivity, and EMI shielding were examined based on different filler compositions. The study also investigated the correlation between electrical conductivity and EMI shielding properties using a theoretical model.
CHEMICAL ENGINEERING JOURNAL
(2023)
Article
Engineering, Electrical & Electronic
Yu Wang, Feng Dong, Shangjie Ren
Summary: Electrical impedance tomography (EIT) is a promising medical/industrial imaging modality due to its safety, high temporal resolution, and functional imaging characteristics. However, the low spatial resolution caused by the ill-posedness of the inverse problem has hindered its practical applications. This study proposes a flexible image-guided inclusion boundary reconstruction (IGBR) framework for EIT to alleviate this problem. The proposed method shows high applicability to various prior images and achieves high-precision shape reconstruction and conductivity estimation.
IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT
(2022)
Article
Engineering, Electrical & Electronic
Xiuzhu Ye, Naike Du, Daohan Yang, Xujin Yuan, Rencheng Song, Sheng Sun, Daining Fang
Summary: An effective quasi-real-time inversion algorithm based on SR-GAN is proposed for imaging 2D biaxial anisotropic scatterers. The algorithm resolves the angle-dependent reconstruction effect by introducing VGG loss and improves imaging quality and resolution compared to traditional algorithms. Numerical results validate the effectiveness of the proposed method and demonstrate reduced computational time, enabling quasi-real-time imaging.
IEEE TRANSACTIONS ON ANTENNAS AND PROPAGATION
(2022)
Article
Automation & Control Systems
Yanyan Shi, Yuhang Zhang, Meng Wang, Yajun Lou, Shuo Zheng
Summary: Electrical impedance tomography (EIT) is a research hotspot with broad applications, and this study proposes a novel method combining Tikhonov regularization with wavelet frame for image reconstruction in EIT. Simulation experiments demonstrate that the proposed method outperforms other commonly used methods in terms of reconstruction quality and noise robustness. Experimental results based on phantom data further confirm the superiority of the proposed method over other methods.
TRANSACTIONS OF THE INSTITUTE OF MEASUREMENT AND CONTROL
(2023)
Article
Remote Sensing
Guangyi Wang, Youmin Zhang, Wen-Fang Xie, Yaohong Qu, Licheng Feng
Summary: A novel hyperspectral linear unmixing method via fusion of collaborative sparsity and multi-band non-local total variation is proposed to improve the accuracy of sparsity representation. The method analyzes the sparsity and spatial correlation of hyperspectral pixels and constructs a hyperspectral linear sparse unmixing model. Experimental results show the feasibility and effectiveness of the proposed method compared to current mainstream hyperspectral sparse unmixing algorithms.
INTERNATIONAL JOURNAL OF REMOTE SENSING
(2022)