A surrogate-based electromagnetic (EM) optimization using neural networks (NNs) is presented for computationally efficient microwave bandpass filter (BPF) design. This paper first describes the forward problem (EM analysis) and the inverse problems (EM design), and the two fundamental issues in BPF designs. The first issue is that the EM analysis is a time-consuming task, and the second one is that EM design highly depends on the structural optimization performed with the help of EM analysis. To accelerate the optimization design, two surrogate models of forward and inverse models are introduced here, which are built with the NNs. As a result, the inverse model can instantaneously guess initial structural parameters with high accuracy by simply inputting synthesized coupling-matrix elements into the NN. Then, the forward model in conjunction with optimization algorithm enables designers to rapidly find optimal structural parameters from the initial ones. The effectiveness of the surrogate-based EM optimization is verified through the structural designs of a typical fifth-order microstrip BPF with multiple couplings.

Laser Doppler Vibrometers (LDVs) enable the acquisition of remote speech signals by measuring small-scale vibrations around a target. They are now widely used in the fields of information acquisition and national security. However, in remote speech detection, the coherent measurement signal is subject to environmental noise, making detecting and reconstructing speech signals challenging. To improve the detection distance and speech quality, this paper proposes a highly accurate real-time speech measurement method that can reconstruct speech from noisy coherent signals. First, the I/Q demodulation and arctangent phase discrimination are used to extract the phase transformation caused by the acoustic vibration from coherent signals. Then, an innovative smoothness criterion and a novel phase difference-based dynamic bilateral compensation phase unwrapping algorithm are used to remove any ambiguity caused by the arctangent phase discrimination in the previous step. This important innovation results in the highly accurate detection of phase jumps. After this, a further innovation is used to enhance the reconstructed speech by applying an improved waveform-based linear prediction coding method, together with adaptive spectral subtraction. This removes any impulsive or background noise. The accuracy and performance of the proposed method were validated by conducting extensive simulations and comparisons with existing techniques. The results show that the proposed algorithm can significantly improve the measurement of speech and the quality of reconstructed speech signals. The viability of the method was further assessed by undertaking a physical experiment, where LDV equipment was used to measure speech at a distance of 310m in an outdoor environment. The intelligibility rate for the reconstructed speech exceeded 95%, confirming the effectiveness and superiority of the method for long-distance laser speech measurement.

In this paper, an experimental method is proposed for extracting the primary and secondary parameters of transmission lines with frequency dispersion. So far, there is no report of these methods being applied to transmission lines with frequency dispersion. This paper provides an experimental evaluation means of transmission lines with frequency dispersion and clarifies the issues when applying the proposed method. In the proposed experimental method, unnecessary components such as connectors are removed by using a simple de-embedding method. The frequency response of the primary and secondary parameters extracted by using the method reproduced all dispersion characteristics of a transmission line with frequency dispersion successfully. It is demonstrated that an accurate RLGC equivalent-circuit model is obtained experimentally, which can be used to quantitatively evaluate the frequency/time responses of shielded-FPC with frequency dispersion and to validate RLGC equivalent-circuit models extracted by using electromagnetic field analysis.

In this study, we develop a numerical method for determining transient energy deposition in biological bodies exposed to electromagnetic (EM) pulses. We use a newly developed frequency-dependent finite-difference time-domain (FD2TD) method, which is combined with the fast inverse Laplace transform (FILT) and Prony method. The FILT and Prony method are utilized to transform the Cole-Cole model of biological media into a sum of multiple Debye relaxation terms. Parameters of Debye terms are then extracted by comparison with the time-domain impulse responses. The extracted parameters are used in an FDTD formulation, which is derived using the auxiliary differential equation method, and transient energy deposition into a biological medium is calculated by the equivalent circuit method. The validity of our proposed method is demonstrated by comparing numerical results and those derived from an analytical method. Finally, transient energy deposition into human heads of TARO and HANAKO models is then calculated using the proposed method and, physical insights into pulse exposures of the human heads are provided.

To realize a stable and efficient wireless power transfer (WPT) system that can be used in any environment, it is necessary to inspect the influence of environmental interference along the power transmission path of the WPT system. In this paper, attempts have been made to reduce the influence of the medium with a dielectric and conductive loss on the WPT system using spiral resonators for resonator-coupled type wireless power transfer (RC-WPT) system. An important element of the RC-WPT system is the resonators because they improve resonant characteristics by changing the shape or combination of spiral resonators to confine the electric field that mainly causes electrical loss in the system as much as possible inside the resonator. We proposed a novel dual-spiral resonator as a candidate and compared the basic characteristics of the RC-WPT system with conventional single-spiral and dual-spiral resonators. The parametric values of the spiral resonators, such as the quality factors and the coupling coefficients between resonators with and without a lossy medium in the power transmission path, were examined. For the lossy mediums, pure water or tap water filled with acryl bases was used. The maximum transmission efficiency of the RC-WPT system was then observed by tuning the matching condition of the system. Following that, the transmission efficiency of the system with and without lossy medium was investigated. These inspections revealed that the performance of the RC-WPT system with the lossy medium using the modified shape spiral resonator, which is the dual-spiral resonator proposed in our laboratory, outperformed the system using the conventional single-spiral resonator.

We consider the coding problem for lossy source coding with side information at the decoder, which is known as the Wyner-Ziv source coding problem. The goal of the coding problem is to find the minimum rate such that the probability of exceeding a given distortion threshold is less than the desired level. We give an equivalent expression of the minimum rate by using the chromatic number and notions of covering of a set. This allows us to analyze the coding problem in terms of graph coloring and covering.

The growing threat of Hardware Trojans (HT) in the System-on-Chips (SoC) industry has given way to the embedded systems researchers to propose a series of detection methodologies to identify and detect the presence of Trojan circuits or logics inside a host design in the various stages of the chip design and manufacturing process. Many state of the art works propose different techniques for HT detection among which the popular choice remains the Side-Channel Analysis (SCA) based methods that perform differential analysis targeting the difference in consumption of power, change in electromagnetic emanation or the delay in propagation of logic in various paths of the circuit. Even though the effectiveness of these methods are well established, the evaluation is carried out on simplistic models such as AES coprocessors and the analytical approaches used for these methods are limited by some statistical metrics such as direct comparison of EM traces or the T-test coefficients. In this paper, we propose two new detection methodologies based on Machine Learning algorithms. The first method consists in applying the supervised Machine Learning (ML) algorithms on raw EM traces for the classification and detection of HT. It offers a detection rate close to 90% and false negative smaller than 5%. In the second method, we propose an outlier/novelty algorithms based approach. This method combined with the T-test based signal processing technique, when compared with state-of-the-art, offers a better performance with a detection rate close to 100% and a false positive smaller than 1%. In different experiments, the false negative is nearly the same level than the false positive and for that reason the authors only show the false positive value on the results. We have evaluated the performance of our method on a complex target design: RISC-V generic processor. Three HTs with their corresponding sizes: 0.53%, 0.27% and 0.09% of the RISC-V processors are inserted for the experimentation. In this paper we provide elaborative details of our tests and experimental process for reproducibility. The experimental results show that the inserted HTs, though minimalistic, can be successfully detected using our new methodology.

In this paper, an ultra-thin wave absorber using a resistive patch array closely-placed in front of a back-metal is designed. The positively large susceptance is required for the patch array to cancel out the negatively large input susceptance of the short-circuited ultra-thin spacer behind the array. It is found that the array needs the gap of 1mm, sheet resistance of less than 20Ω/sq. and patch width of more than 15mm to obtain the zero input susceptance of the absorber with the 1/30 wavelength spacer. Moreover, these parameters were designed considering the electromagnetic coupling between the array and back-metal, and the square patch array absorbers with the thickness from 1/30 to 1/150 wavelength were designed.

The art gallery problem is to find a set of guards who together can observe every point of the interior of a polygon P. We study a chromatic variant of the problem, where each guard is assigned one of k distinct colors. The chromatic art gallery problem is to find a guard set for P such that no two guards with the same color have overlapping visibility regions. We study the decision version of this problem for orthogonal polygons with r-visibility when the number of colors is k=2. Here, two points are r-visible if the smallest axis-aligned rectangle containing them lies entirely within the polygon. In this paper, it is shown that determining whether there is an r-visibility guard set for an orthogonal polygon with holes such that no two guards with the same color have overlapping visibility regions is NP-hard when the number of colors is k=2.

The optical properties of new tricyanopyrroline (TCP)-based chromophores with a benzyloxy group bound to aminobenzene donor unit were characterized by hyper-Rayleigh scattering (HRS), absorption spectrum, and 1H-NMR measurements, and the influence of the benzyloxy group on TCP-based chromophores was discussed based on the data. A positive effect of NLO properties was found in TCP-based NLO chromophores with a benzyloxy group compared with benchmark NLO chromophores without the benzyloxy group, suggesting an influence of intra-molecular hydrogen bond. Furthermore, we propose a formation of double intra-molecular hydrogen bonds in the TCP chromophore with monoene as the π-conjugation bridge and aminobenzene with a benzyloxy group as the donor unit.

This paper proposes a novel radio access scheme that uses duplicated transmission via multiple frequency channels to achieve mission critical Internet of Things (IoT) services requiring highly reliable wireless communications; the interference constraints that yield the required reliability are revealed. To achieve mission critical IoT services by wireless communication, it is necessary to improve reliability in addition to satisfying the required transmission delay time. Reliability is defined as the packet arrival rate without exceeding the desired transmission delay time. Traffic of the own system and interference from the other systems using the same frequency channel such as unlicensed bands degrades the reliability. One solution is the frequency/time diversity technique. However, these techniques may not achieve the required reliability because of the time taken to achieve the correct reception. This paper proposes a novel scheme that transmits duplicate packets utilizing multiple wireless interfaces over multiple frequency channels. It also proposes a suppressed duplicate transmission (SDT) scheme, which prevents the wastage of radio resources. The proposed scheme achieves the same reliable performance as the conventional scheme but has higher tolerance against interference than retransmission. We evaluate the relationship between the reliability and the occupation time ratio where the interference occupation time ratio is defined as the usage ratio of the frequency resources occupied by the other systems. We reveal the upper bound of the interference occupation time ratio for each frequency channel, which is needed if channel selection control is to achieve the required reliability.

Cross-component linear model (CCLM) chromaticity prediction is a new technique introduced in Versatile Video Coding (VVC), which utilizes the reconstructed luminance component to predict the chromaticity parts, and can improve the coding performance. However, it increases the coding complexity. In this paper, how to accelerate the chroma intra-prediction process is studied based on texture characteristics. Firstly, two observations have been found through experimental statistics for the process. One is that the choice of the chroma intra-prediction candidate modes is closely related to the texture complexity of the coding unit (CU), and the other is that whether the direct mode (DM) is selected is closely related to the texture similarity between current chromaticity CU and the corresponding luminance CU. Secondly, a fast chroma intra-prediction mode decision algorithm is proposed based on these observations. A modified metric named sum modulus difference (SMD) is introduced to measure the texture complexity of CU and guide the filtering of the irrelevant candidate modes. Meanwhile, the structural similarity index measurement (SSIM) is adopted to help judging the selection of the DM mode. The experimental results show that compared with the reference model VTM8.0, the proposed algorithm can reduce the coding time by 12.92% on average, and increases the BD-rate of Y, U, and V components by only 0.05%, 0.32%, and 0.29% respectively.

This paper proposes a salient chromagram by removing local trend to improve cover song identification accuracy. The proposed salient chromagram emphasizes tonal contents of music, which are well-preserved between an original song and its cover version, while reducing the effects of timber difference. We apply the proposed salient chromagram to the sequence-alignment based cover song identification. Experiments on two cover song datasets confirm that the proposed salient chromagram improves the cover song identification accuracy.

Silver electrical contacts were separated at constant opening speed in a 200V-500VDC/10A resistive circuit. Break arcs were extinguished by magnetic blowing-out with transverse magnetic field of a permanent magnet. The permanent magnet was appropriately located to simplify the lengthened shape of the break arcs. Magnetic flux density of the transverse magnetic field was varied from 20 to 140mT. Images of the break arcs were observed from the horizontal and vertical directions using two high speed cameras simultaneously. Arc length just before extinction was analyzed from the observed images. It was shown that shapes of the break arcs were simple enough to trace the most part of paths of the break arcs for all experimental conditions owing to simplification of the shapes of the break arcs by appropriate arrangement of the magnet. The arc length increased with increasing supply voltage and decreased with increasing magnetic flux density. These results will be discussed in the view points of arc lengthening time and arc lengthening velocity.

Motion deblurring for noisy and blurry images is an arduous and fundamental problem in image processing community. The problem is ill-posed as many different pairs of latent image and blur kernel can render the same blurred image, and thus, the optimization of this problem is still unsolved. To tackle it, we present an effective motion deblurring method for noisy and blurry images based on prominent structure and a data-driven heavy-tailed prior of enhanced gradient. Specifically, first, we employ denoising as a preprocess to remove the input image noise, and then restore strong edges for accurate kernel estimation. The image extreme channels-based priors (dark channel prior and bright channel prior) as sparse complementary knowledge are exploited to extract prominent structure. High closeness of the extracted structure to the clear image structure can be obtained via tuning the parameters of extraction function. Next, the integration term of enhanced interim image gradient and clear image heavy-tailed prior is proposed and then embedded into the image restoration model, which favors sharp images over blurry ones. A large number of experiments on both synthetic and real-life images verify the superiority of the proposed method over state-of-the-art algorithms, both qualitatively and quantitatively.

In this letter, a quantitative evaluation index of contrast improvement of color images for dichromats is proposed. The index is made by adding two parameters to an existing index to make evaluation results consistent with human evaluation results. The effectiveness and validity of the proposed index are verified by experiments.

Authors had proposed a hybrid electromagnetic field analysis method suitable for an airport surface so far. In this paper, the hybrid method is validated by measurements by using a 1/50 scale-model of an airport considering several layouts of the buildings and sloping ground. The measured power distributions agreed with the analyzed ones within 5 dB errors excepting null points and the null positions of the distribution is also estimated within one wavelength errors.

For actual multi-channel differential signaling system, the ideal balance or symmetrical topology cannot be established, and hence, an imbalance component is excited. However a theoretical analysis method of evaluating the voltage and current distribution on the differential-paired lines, which allows to anticipate EM radiation at the design stage and to study possible means for suppressing imbalance components, has not been implemented. To provide the basic considerations for electromagnetic (EM) radiation from practical asymmetrical differential-paired lines structure with equi-length routing used in high-speed board design, this paper newly proposes an analytical method for evaluating the voltage and current at any point on differential-paired lines by expressing the differential paired-lines with an equivalent source circuit and an equivalent load circuit. The proposed method can predict S-parameters, distributions of voltage and current and EM radiation with sufficient accuracy. In addition, the proposed method provides enough flexibility for different geometric parameters and can be used to develop physical insights and design guidelines. This study has successfully established a basic method to effectively predict signal integrity and EM interference issues on a differential-paired lines.

In recent years, deep neural network (DNN) has achieved considerable results on many artificial intelligence tasks, e.g. natural language processing. However, the computation complexity of DNN is extremely high. Furthermore, the performance of traditional von Neumann computing architecture has been slowing down due to the memory wall problem. Processing in memory (PIM), which places computation within memory and reduces the data movement, breaks the memory wall. ReRAM PIM is thought to be a available architecture for DNN accelerators. In this work, a novel design of ReRAM neuromorphic system is proposed to process DNN fully in array efficiently. The binary ReRAM array is composed of 2T2R storage cells and current mirror sense amplifiers. A dummy BL reference scheme is proposed for reference voltage generation. A binary DNN (BDNN) model is then constructed and optimized on MNIST dataset. The model reaches a validation accuracy of 96.33% and is deployed to the ReRAM PIM system. Co-design model optimization method between hardware device and software algorithm is proposed with the idea of utilizing hardware variance information as uncertainness in optimization procedure. This method is analyzed to achieve feasible hardware design and generalizable model. Deployed with such co-design model, ReRAM array processes DNN with high robustness against fabrication fluctuation.

Plane wave scattering from a circular conducting cylinder and a circular conducting strip has been formulated by equivalent surface currents which are postulated from the scattering geometrical optics (GO) field. Thus derived radiation far fields are found to be the same as those formulated by a conventional physical optics (PO) approximation for both E and H polarizations.