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In this paper, an experimental validation of a numerical procedure for estimating the structure-borne Underwater Radiated Noise (URN) Transfer Function (TF) of a marine structure based on the SEA theory has been performed. For the purpose, the structure-borne URN TF of a central point-excited one-side fluid-loaded four-edge stiffened plate in a reverberant water tank has been measured and compared with the SEA result. Additionally, the practical applicability of the procedure for a real ship structure has been demonstrated by comparing the URN analysis result based on the transfer function method and the measurement result for a Korean research vessel, ‘Cheong-Hae’. From the results, it is confirmed that the presented procedure can be used to estimate the structure-borne URN level emitted from the vibrating fluid-loaded side shells of a ship structure.

Purpose: The Radiofrequency (RF)‐induced heating for an active implantable medical device (AIMD) with dual parallel leads is evaluated in this paper. The coupling effects between dual parallel leads are studied via simulations and experiments methods. The global transfer function technique is used to assess the RF‐induced heating for dual‐lead AIMDs inside four human body models. Methods: RF‐induced heating for spinal cord stimulator systems with 60 and 90 cm length leads are studied at three parallel dual‐lead configurations (closely spaced, 8 mm spaced, and 40 mm spaced) and a single‐lead configuration. The global transfer function method is used to develop the AIMD models of different configurations and is used for lead‐tip heating assessments inside human body models. Results: In simulation studies, the peak 1g specific absorption rate/temperatrue rises of dual parallel leads systems is lower than those from the single‐lead system. In experimental American Society for Testing and Materials phantom studies, the temperature rises for the single‐lead AIMD system can be 2.4 times higher than that from dual‐lead AIMD systems. For the spinal cord stimulator systems used in the study, the statistical analysis shows the RF‐induced heating of dual‐lead configurations are also lower than those from the single‐lead configuration inside all four human body models. Conclusion: For the AIMD system in this study, it shows that the coupling effects between the dual parallel leads of AIMD systems can reduce RF‐induced heating. The global transfer function for different spatial distance dual‐lead configurations can potentially provide a method for the RF‐induced heating evaluation for dual‐lead AIMD systems. [ABSTRACT FROM AUTHOR]

To speed up the process for designing finite thinned arrays, an efficient artificial neural network (ANN) model considering mutual coupling effects is proposed in this communication. Array elements are divided into three categories based on the active element pattern (AEP) technique, and subarrays are constructed to extract the AEP of each category of elements as training samples. The proposed model including parallel ANN branches takes into account the mutual coupling between elements and avoids the calculation of the radiation pattern of the entire array. To improve modeling performance, furthermore, a prior knowledge input technique is used to reduce the complexity of the input–output relationship that an ANN has to learn. The existing knowledge is obtained by back propagation (BP) ANN modeling. Once the knowledge-based model is well trained, it is repeatedly called by the genetic algorithm (GA) for the optimal solution as a substitute for the full-wave simulation. Numerical examples of a U-shaped slot thinned array and a dual-layer patch thinned array are utilized to verify the efficiency of the proposed scheme. [ABSTRACT FROM AUTHOR]

The Fourier series is introduced as a transfer function (TF) in the artificial neural network (ANN) for parametric modeling of microwave filters in this letter. The reported pole-residue-based TF leads to an order-changing problem of input samples from vector fitting, which is usually solved with an order-tracking technique or data classification. The proposed Fourier series-based TF does not have to carry out the time-consuming operation because the only coefficient order can be determined for all input samples in an iterative process. Compared with the pole-residue-based TF, moreover, the ANN training involves a small number of TF coefficients in the proposed method. The predicted electromagnetic (EM) response is obtained from the coefficients of the ANN output. An example of the ultrawideband (UWB) filter is employed to verify the effectiveness of the Fourier series-based TF. [ABSTRACT FROM AUTHOR]

Purpose: During MR scans, abandoned leads from active implantable medical devices (AIMDs) can experience excessive heating at the lead tip, depending on the type of termination applied to the proximal contacts (proximal end treatment). The influence of different proximal end treatments (ie, [1] freely exposed in the tissue, [2] terminated with metal in contact with the tissue, or [3] capped with plastic, and thereby fully insulated, on the RF‐induced lead‐tip heating) are studied. A technique to ensure that MR Conditional AIMD leads remain MR Conditional even when abandoned is recommended. Methods: Abandoned leads from three MR Conditional AIMDs ([1] a sacral neuromodulation system, [2] a cardiac rhythm management pacemaker system, and [3] a deep brain stimulator system) were investigated in this study. The computational lead models (ie, the transfer functions) for different proximal end treatments were measured and used to assess the in vivo lead‐tip heating for four virtual human models (FATS, Duke, Ella, and Billie) and compared with the lead‐tip heating of the complete MR Conditional AIMD system. Result: The average and maximum lead‐tip heating for abandoned leads proximally capped with metal is always lower than that from the complete AIMD system. Abandoned leads proximally insulated could lead to an average in vivo temperature rise up to 3.5 times higher than that from the complete AIMD system. Conclusion: For the three investigated AIMDs under 1.5T MR scanning, our results indicate that RF‐induced lead‐tip heating of abandoned leads strongly depends on the proximal lead termination. A metallic cap applied to the proximal termination of the tested leads could significantly reduce the RF‐induced lead‐tip heating. [ABSTRACT FROM AUTHOR]

To improve the convenience and efficiency of antenna design, in this article, a novel inverse artificial neural network (ANN) model is proposed in which antenna performance indexes are set as the input and corresponding geometrical variables are set as the output. To solve the multiobjective problem of antenna modeling, the first part of the ANN model involves three parallel and independent branches for S-parameter, gain, and radiation pattern, and the second part outputs a final predicted result. Once the training is completed, the proposed inverse model can provide antenna geometries directly without being repetitively called by an optimization algorithm. Compared with the inverse extreme learning machine and five state-of-art forward models, the proposed model uses a small number of training samples and directly obtains the satisfying values of geometrical variables without any optimization process. [ABSTRACT FROM AUTHOR]