A New Approach for Solving Inverse Scattering Problems with Overset Grid Generation Method

This paper presents a new approach of Forward-Backward Time-Stepping (FBTS) utilizing Finite-Difference Time-Domain (FDTD) method with Overset Grid Generation (OGG) method to solve the inverse scattering problems for electromagnetic (EM) waves. The proposed FDTD method is combined with OGG method to reduce the geometrically complex problem to a simple set of grids. The grids can be modified easily without the need to regenerate the grid system, thus, it provide an efficient approach to integrate with the FBTS technique. Here, the characteristics of the EM waves are analyzed. For the research mentioned in this paper, the ‘measured’ signals are syntactic data generated by FDTD simulations. While the ‘simulated’ signals are the calculated data. The accuracy of the proposed approach is validated. Good agreements are obtained between simulation data and measured data. The proposed approach has the potential to provide useful quantitative information of the unknown object particularly for shape reconstruction, object detection and others

An Efficient of Chimera Grid Scheme with Spline Interpolation in FBTS Inversion Technique for Extremely Dense Breast Cancer Detection

Microwave imaging system is classified as non-invasive, simple to perform and inexpensive compared to MRI and X-Ray machine. Therefore, the novel idea of this research work is to develop a Chimera Grid Scheme (CGS) incorporate with the microwave inverse scattering technique in a low cost, non-ionising and safe short-range. The CGS with spline interpolation in Forward Backward Time-Stepping (FBTS) inversion technique can determined an accurate result especially for the biological anomalies like breast tumours at an early curable stage due to the high electrical properties contrast between malignant cells and normal cells. The findings showed that the proposed method successfully detected and reconstructed the breast structure in relative permittivity profiles. The quantitative information of reconstructed images, such as location, shape, size and internal composition also can be obtained. Furthermore, the normalised functional error for proposed method was also lower than the FDTD method in FBTS. At iteration, the difference of normalised functional error between these two methods was . The result shows that the CGS method in FBTS inversion technique would reconstruct breast composition more precisely

An Efficient of Overlapping Grid Method with Scattering Technique in Time Domain for Numerical Modeling

An Overlapping Grid Method (OGM) with Biquadratic Spline Interpolation in scattering technique was developed to solve the direct and inverse scattering issues. A two-dimensional (2D) numerical image model was used to analyze the accuracy of the proposed method in a direct scattering process. It was discovered that when the sub-grid, s ∆x increased, the absolute error for the electric field amplitude will also increase. The results also discovered that as the grid size ratio increased, the absolute error of the amplitude EZ will also increase. The findings show that smaller grid spacing and a finer grid size can produce more accurate results. The Overlapping Grid Method (OGM) with Biquadratic Spline Interpolation was expanded by incorporating with Forward-Backward Time Stepping (FBTS) technique to solve inverse scattering issues. Homogenous embedded objects with a square and circular shape are used to validate the efficiency of the proposed method. The findings showed that the proposed numerical method could detect and reconstruct embedded objects in different shapes. The efficiency of the proposed method was examined by Mean Square Error (MSE) and normalizing the functional error. The findings revealed that the MSE of dielectric profiles for the proposed method were lower than the FDTD method in FBTS. The relative permittivity and conductivity profile differed by 27.06% and 20%, respectively. Hence, it was proven that the proposed method successfully solved a known drawback to the FDTD method and produced more accurate and efficient results

An efficient of overlapping grid method with scattering technique in time domain for numerical modeling

An Overlapping Grid Method (OGM) with Biquadratic Spline Interpolation in scattering technique was developed to solve the direct and inverse scattering issues. A two-dimensional (2D) numerical image model was used to analyze the accuracy of the proposed method in a direct scattering process. It was discovered that when the sub-grid, sxΔ increased, the absolute error for the electric field amplitude will also increase. The results also discovered that as the grid size ratio increased, the absolute error of the amplitude ZE will also increase. The findings show that smaller grid spacing and a finer grid size can produce more accurate results. The Overlapping Grid Method (OGM) with Biquadratic Spline Interpolation was expanded by incorporating with Forward-Backward Time Stepping (FBTS) technique to solve inverse scattering issues. Homogenous embedded objects with a square and circular shape are used to validate the efficiency of the proposed method. The findings showed that the proposed numerical method could detect and reconstruct embedded objects in different shapes. The efficiency of the proposed method was examined by Mean Square Error (MSE) and normalizing the functional error. The findings revealed that the MSE of dielectric profiles for the proposed method were lower than the FDTD method in FBTS. The relative permittivity and conductivity profile differed by 27.06% and 20%, respectively. Hence, it was proven that the proposed method successfully solved a known drawback to the FDTD method and produced more accurate and efficient results

Two-dimensional Forward-Backward Time-Stepping approach for tumor detection in dispersive breast tissues

The Forward-Backward Time-Stepping (FBTS) technique is applied to determine the presence and location of malignant tumor in the heterogeneous breast model. A new strategy is integrated in the FBTS algorithm to accurately estimate the dielectric properties of tissues. We demonstrate 2-D FBTS technique utilizing the numerical dispersive breast model in a free space. This new strategy manipulating Debye dispersion equation is proposed to treat dispersive case. Numerical simulation results show the FBTS algorithm has the potential to provide useful quantitative information of the breast\u27s internal composition.2009 Mediterranean Microwave Symposium (MMS) : Tangiers, Morocco, 2009.11.15-2009.11.1

Classification of capsicum leaf disease from a complex cluster of leaves using an improved multiple layers ShuffleNet CNN model

Capsicum, also known as chili pepper or bell pepper, is cultivated worldwide and holds significant economic importance as a condiment, vegetable, and medicinal plant. One of the major challenges in capsicum cultivation is the accurate identification of leaf diseases. Leaf diseases can have a detrimental effect on the quality of capsicum production, leading to substantial losses for farmers. Several machine learning (ML) algorithms and convolutional neural network (CNN) models have been developed to classify capsicum leaf diseases under controlled conditions, where leaves are uniform and backgrounds are uncomplicated. These models have achieved an average accuracy of classification. However, classifying diseases becomes relatively challenging when a diseased leaf grows alongside a cluster of other leaves. Having a reliable model that can accurately classify capsicum leaf diseases within a cluster of leaves would greatly benefit farmers. Therefore, the aim of this study was to propose a model capable of classifying capsicum leaf diseases both from a uniform background and within a complex cluster of leaves. Firstly, a dataset comprising images of diseased capsicum leaves, including discolored leaves, grey spots, and leaf curling, was acquired. Subsequently, an improved multiple-layer ShuffleNet CNN model was employed to classify the different types of capsicum leaf diseases. The proposed model demonstrated superior performance compared to existing models, achieving a classification accuracy of 99.30%. Furthermore, it was concluded that augmenting the layers of ShuffleNet, utilizing a 0.01 initial learning rate, employing 50 maximum epochs, using a minibatch size of 64, conducting 10 iterations, and incorporating 205 validation iterations all contributed to the improved ShuffleNet model's success

Microwave breast imaging by the filtered forward-backward time-stepping method

In this paper, an inverse scattering technique referred to as the filtered forward-backward time-stepping method is applied to microwave imaging for breast cancer detection. A two-dimensional numerical breast phantom (derived from MR images) with high contrast between fat and fibroglandular tissues, and low contrast between fibroglandular and tumor tissues are used to assess the efficacy of the proposed method.2010 URSI International Symposium on Electromagnetic Theory (EMTS 2010) : Berlin, Germany, 2010.08.16-2010.08.1

A new approach for solving inverse scattering problems with overset grid generation method

This paper presents a new approach of Forward-Backward Time-Stepping (FBTS) utilizing Finite-Difference Time-Domain (FDTD) method with Overset Grid Generation (OGG) method to solve the inverse scattering problems for electromagnetic (EM) waves. The proposed FDTD method is combined with OGG method to reduce the geometrically complex problem to a simple set of grids. The grids can be modified easily without the need to regenerate the grid system, thus, it provide an efficient approach to integrate with the FBTS technique. Here, the characteristics of the EM waves are analyzed. For the research mentioned in this paper, the 'measured' signals are syntactic data generated by FDTD simulations. While the 'simulated' signals are the calculated data. The accuracy of the proposed approach is validated. Good agreements are obtained between simulation data and measured data. The proposed approach has the potential to provide useful quantitative information of the unknown object particularly for shape reconstruction, object detection and others. © 2017 Universitas Ahmad Dahlan

B2-Spline Interpolation Technique for Overset Grid Generation and Finite-Difference Time-Domain Method

—In this paper, B2-spline interpolation technique for Overset Grid Generation and FiniteDifference Time-Domain (OGG-FDTD) method was developed. B2-spline or biquadratic spline interpolation offers better accuracy than bilinear interpolation. Two-dimensional (2D) numerical simulations were carried out for electromagnetic (EM) field analysis to measure the scattered fields for an unknown object in free space and dielectric medium. In this work, two antennas were utilised as transmitter and receiver sequentially to transmit microwave pulses and collect the scattered fields for an unknown object in OGG-FDTD lattice. In order to analyse the stability and efficiency of the proposed method, the scattered fields for the unknown object were investigated with error analysis. The results showed that the OGG-FDTD method with B2-spline interpolation gave lower relative error than bilinear interpolation with 0.0009% of difference in free space, 0.0033% of difference in Case A dielectric medium, 0.236% of difference in Case B dielectric medium, and 0.003% of difference in Case C dielectric medium. Besides, the Mean Square Error (MSE) for the OGG-FDTD method with B2-spline interpolation was also lower than the bilinear interpolation. Hence, it proves that the OGG-FDTD method with B2-spline interpolation has the ability to measure the scattered fields around an unknown object accurately. For future work, the proposed method can be applied to inverse scattering to detect and reconstruct buried objects with arbitrary shapes in a complex media