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A highly efficient algorithm for analysis of electromagnetic scattering by a large cluster of independently moving objects is proposed in this paper. A double octree structure is introduced, which consists of a main octree stationary to the cluster as a whole, and many sub-octrees moving with individual objects. Based on the new double octree structure, the computation of interactions between two elements is divided into four categories: the two elements are on the same object and are near; the two elements are on the same object but are far; the two elements are on different objects but the two objects are adjacent; the two elements are on different objects and the two objects are non-adjacent. For different interacting categories, different approaches are adopted to maximize the computing efficiency. The new algorithm enables possible fast simulations of scattering by hundreds of independently moving objects. Compared with the conventional Multilevel Fast Multipole Algorithm (MLFMA) and the recently developed Multi-Moving-Object (MMO)-MLFMA, the present scheme has substantial improvement in saving CPU time, providing a viable solution for engineering applications. Numerical validations for accuracy and efficiency are performed.

In the satellite microwave power transmission (MPT) system, antenna arrays are usually adopted for a higher gain. For the passive wideband antenna array, wideband power dividers are essential when the feed network is constructed. Because the microstrip-slotline coupled power divider could achieve wide bandwidth and compact size at the same time, it becomes a potential candidate for the feed network. However, impedance matching is always needed in the slotline, e.g., the fixed slotline length or the stepped impedance transformation. So, the power divider is not flexible. In this paper, a flexible Microstrip-Slotline-Microstrip (MSM) power divider is presented. When the ratio of the coupling coefficients $n_{1}$ of the microstrip-to-slotline transition (MST) and $n_{2}$ of the slotline-to-microstrip transitions (SMT) is 2, the MST and SMTs could be self-matched respectively. Then no impedance matching is needed anymore in the slotline. Thus, the slotline length can be arbitrarily chosen, and no stepped impedance transformations are needed. This power divider eliminates the drawback limiting the free wire routing for the microstrip-slotline coupled feed network. It could serve as a new kind of feed network, especially be considered when the simple T-junction feed network cannot achieve enough bandwidth. Besides, a wideband Vivaldi array with this feed network is presented.

In this paper, we utilize the deep learning approach for the subwavelength imaging in far-field, which is realized by the near-field resonant metalens at microwave frequencies. The resonating metalens consisting of split-ring resonators (SRRs) are equipped with the strong magnetic coupling ability and can convert evanescent waves into propagating waves using the localized resonant modes. The propagating waves in the far-field are utilized as the input of a trained deep convolutional neural network (CNN) to realize the imaging. The training data for establishing the deep CNN are obtained by the EM simulation tool. Besides, the white Gaussian noise is added into the training data to simulate the interference in the real application scenario. The proposed CNN composes of three pairs of convolutional and activation layers with one additional fully connected layer to realize the recognition, i.e., the imaging process. The feasibility of utilizing the trained deep CNN for imaging is validated by numerical benchmarks. Distinguished from the subwavelength imaging methods, the spatial response and Green's function need not be measured and evaluated in the proposed method.

Data hiding techniques for steganography, which embed secret data in multimedia imperceptibly, are useful for protecting information security. By taking advantage of the popularity of MIDI files on the Internet, a new data hiding method via MIDI files is proposed, which modifies the velocities of musical note sequences to embed secret data. Initially, musical note sequences with monotonic pitches, each consisting of at least three consecutive notes with pitches either entirely non-decreasing or entirely non-increasing, are found from an input MIDI file. Next, for each of such musical note sequences, a reference velocity is generated for each non-end note in the sequence by a linear interpolation scheme. Then, a number of data bits are embedded into each non-end note by adding the decimal value of the bits to or subtracting the value from the corresponding reference velocity value to yield a new velocity for the note. The new velocity value does not differ much from the original one and fits the velocity trend in the musical note sequence, so that the resulting stego-MIDI file does not yield abnormal note strengths and the musical expression is kept. Moreover, a melody humanization scheme is proposed for modifying the velocity values in strength-invariant MIDI channels to create data embeddability without producing unreasonable melodies. The original MIDI file size is also kept unchanged after data embedding, avoiding attracting attentions from hackers. Experimental results show the feasibility of the proposed method. Also, a comparison with five other methods show that the method has the merit of reducing the resulting melody distortion or file-size change while yielding a reasonable secret-bit embedding rate.

Pulmonary valve diseases in children and adults include different degrees of stenosis, regurgitation, or congenital defects. Valve repair or replacement surgery is used to treat valvular dysfunction and to improve regurgitations flow for pulmonary valve pathologies. Handmade trileaflet valve designs with different ranges of diameters have been used for pulmonary valved conduit reconstruction among children or adult patients with available conditions. In this paper, we propose a multiple regression model as a cascade-correlation-network-based estimator to determine optimal trileaflet parameters, including width, length, and upper/lower curved structures, for trileaflet valve reconstruction. The diameter of the main pulmonary artery is determined via computed tomography pulmonary angiography, and a trileaflet valve template is rapidly sketched. The actual valve is constructed using an expanded polytetrafluoroethylene material. Using an experimental pulmonary circulation loop system, design parameters and valve efficacy can be validated by the Taguchi method through calculation of signal-to-noise ratios. Experimental results indicate that in contrast to commercial valve stents, the handmade trileaflet valve exhibits good performance and is a valuable option in treatment of severe pulmonary regurgitation.

This paper presents the procedure for evaluating the electromagnetic field induced by the wake of an undersea-moving slender body. The slender body is considered equivalent to a pair of Havelock point sources that can generate wake flow fields. The electric current generated in the seawater is calculated by means of the moving conductive seawater that cuts the earth’s magnetic field. The electromagnetic fields in the air and in the seawater are then determined by solving the Maxwell equations with appropriate boundary conditions. The induced electromagnetic fields include two parts: One is the attenuating oscillation that can be ascribed to the free surface Kelvin wake, and the other is the bipolar pulse that can be ascribed to the localized volume wake. Near the sea surface, the magnitude of the former is typically a few hundred pico-tesla, while that of the latter could be greater by ten times.

Percutaneous pulmonary valve implantation is an improved technique that is used to treat narrowed pulmonary valves or leaky pulmonary valves in patients with congenital heart disease. This technique represents a promising strategy to reduce surgical risk and operation. In clinical cases, commercial valve stents are sometimes not available for children or special subjects due to restrictions in stent size. Hence, the handmade pulmonary valved conduit provides a strategy to design stents with customized size for valve replacement. In this paper, we propose a meta-learning-based intelligent model to train an estimator (including two sub-estimators) to determine optimal trileaflet parameters for customized trileaflet valve reconstruction. This estimation model overcomes the problem of empirical parameter determination. The meta-learning model possesses learning-to-optimization capability for training generalized regression neural network by particle swarm optimization algorithm. Through incremental training patterns, this scheme can gradually enhance optimization to provide refined parameters for customized designs that can be applicable to individuals of all age groups. The customized handmade pulmonary valved conduit was validated by assessing the regurgitation fraction and the heart pump efficiency using an experimental cardiopulmonary circulation loop system.