Smaller antenna structures for long-range radar transmitters and receivers operating in the 77-GHz band for automotive application have been achieved by using antennas with a horn, lens, and microstrip antenna. The transmitter (Tx) antenna height was reduced while keeping the antenna gain high and the antenna substrate small by developing an antenna structure composed of two differential horn and lens antennas in which the diameter and focus distance of the lenses were half those in the previous design. The microstrip antennas are directly connected to the differential outputs of a monolithic microwave integrated circuit. A Tx antenna fabricated using commercially available materials was 14mm high and had an output-aperture of 18×44mm. It achieved an antenna gain of 23.5dBi. The antenna substrate must be at least 96mm2. The antenna had a flat beam with half-power elevation and azimuth beamwidths of 4.5° and 21°, respectively. A receiver (Rx) antenna array composed of four sets of horn and lens antennas with an output-aperture of 9×22mm and a two-by-two array configuration was fabricated for application in a newly proposed small front-end module with azimuth direction of arrival (DOA) estimation. The Rx antenna array had an antenna coupling of less than -31dB in the 77-GHz band, which is small enough for DOA estimation by frequency-modulated continuous wave radar receivers even though the four antennas are arranged without any separation between their output-apertures.

A polyphase sequence set with orthogonality consisting complex elements with unit magnitude, can be expressed by a unitary matrix corresponding to the complex Hadamard matrix or the discrete Fourier transform (DFT) matrix, whose rows are orthogonal to each other. Its matched filter bank (MFB), which can simultaneously output the correlation between a received symbol and any sequence in the set, is effective for constructing communication systems flexibly. This paper discusses the compact design of the MFB of a polyphase sequence set, which can be applied to any sequence set generated by the given logic function. It is primarily focused on a ZCZ code with q-phase or more elements expressed as A(N=qn+s, M=qn-1, Zcz=qs(q-1)), where q, N, M and Zcz respectively denote, a positive integer, sequence period, family size, and a zero correlation zone, since the compact design of the MFB becomes difficult when Zcz is large. It is shown that the given logic function on the ring of integers modulo q generating the ZCZ code gives the matrix representation of the MFB that M-dimensional output vector can be represented by the product of the unitary matrix of order M and an M-dimensional input vector whose elements are written as the sum of elements of an N-dimensional input vector. Since the unitary matrix (complex Hadamard matrix) can be factorized into n-1 unitary matrices of order M with qM nonzero elements corresponding to fast unitary transform, a compact MFB with a minimum number of circuit elements can be designed. Its hardware complexity is reduced from O(MN) to O(qM log q M+N).

This paper proposes a dual-polarized metasurface that utilizes multi-layer ceramic capacitors (MLCCs) for radar cross-section (RCS) reduction in the 28GHz band of the quasi-millimeter band. MLCCs are very small in size; therefore, miniaturization of the unit cell structure of the metamaterial can be expected, and the MLCCs can be periodically loaded onto a narrow object. First, the MLCC structure was modeled as a basic structure, and the effective permeability of the MLCC was determined to investigate the influence of the arrangement direction on MLCC interaction. Next, the unit cell structure of the dual-polarized metasurface was designed for an MLCC set on a dielectric substrate. By analyzing the infinite periodic structure and finite structure, the monostatic reduction characteristics, oblique incidence characteristics, and dual-polarization characteristics of the proposed metasurface were evaluated. In the case of the MLCCs arranged in the same direction, the monostatic RCS reduction was approximately 30dB at 29.8GHz, and decreased when the MLCCs were arranged in a checkerboard pattern. The monostatic RCS reductions for the 5 × 5, 10 × 10, and 20 × 20 divisions were roughly the same, i.e., 10.8, 9.9, and 10.3dB, respectively. Additionally, to validate the simulated results, the proposed dual-polarized metasurface was fabricated and measured. The measured results were found to approximately agree with the simulated results, confirming that the RCS can be reduced for dual-polarization operation.

This paper demonstrates how to achieve simulation-based strong attribute hiding against adaptive adversaries for predicate encryption (PE) schemes supporting expressive predicate families under standard computational assumptions in bilinear groups. Our main result is a simulation-based adaptively strongly partially-hiding PE (PHPE) scheme for predicates computing arithmetic branching programs (ABP) on public attributes, followed by an inner-product predicate on private attributes. This simultaneously generalizes attribute-based encryption (ABE) for boolean formulas and ABP's as well as strongly attribute-hiding PE schemes for inner products. The proposed scheme is proven secure for any a priori bounded number of ciphertexts and an unbounded (polynomial) number of decryption keys, which is the best possible in the simulation-based adaptive security framework. This directly implies that our construction also achieves indistinguishability-based strongly partially-hiding security against adversaries requesting an unbounded (polynomial) number of ciphertexts and decryption keys. The security of the proposed scheme is derived under (asymmetric version of) the well-studied decisional linear (DLIN) assumption. Our work resolves an open problem posed by Wee in TCC 2017, where his result was limited to the semi-adaptive setting. Moreover, our result advances the current state of the art in both the fields of simulation-based and indistinguishability-based strongly attribute-hiding PE schemes. Our main technical contribution lies in extending the strong attribute hiding methodology of Okamoto and Takashima [EUROCRYPT 2012, ASIACRYPT 2012] to the framework of simulation-based security and beyond inner products.

End-to-end (E2E) multilingual automatic speech recognition (ASR) systems aim to recognize multilingual speeches in a unified framework. In the current E2E multilingual ASR framework, the output prediction for a specific language lacks constraints on the output scope of modeling units. In this paper, a language supervision training strategy is proposed with language masks to constrain the neural network output distribution. To simulate the multilingual ASR scenario with unknown language identity information, a language identification (LID) classifier is applied to estimate the language masks. On four Babel corpora, the proposed E2E multilingual ASR system achieved an average absolute word error rate (WER) reduction of 2.6% compared with the multilingual baseline system.

In recent years, cognition and use of manga pervade, and people who use manga for various purposes such as entertainment, study, marketing are increasing more and more. However, when people who do not specialize in it create it for these purposes, they can write plots expressing what they want to convey but the technique of the composition which arranges elements in manga such as characters or balloons corresponding to the plot create obstacles to using its merits for comprehensibility based on high flexibility of its expression. Therefore, we consider that support of this composition technique is necessary for amateurs to use manga while taking advantage of its benefits. We propose a method of generating composition proposal to support manga creation by amateurs. For the method, we also define new manga metadata model which summarize and extend metadata models by earlier studies. It represents the compostion and the plot in manga. We apply a neural machine translation mechanism for learing the relation between the composition and the plot. It considers that the plot annotation is the source of the composition annotation that is the target, and learns from the annotation dataset based on the metadata model. We conducted experiments to evaluate how the composition proposal generated by our method helps amateur manga creation, and demonstrated that it is useful.

This paper presents non-destructive millimeter-wave (MMW) imaging of sub-millimeter-wide cracks on a concrete surface covered with paper. We measured the near-field scattering of 76.5 GHz-MMW signals at concrete surface cracks for detection of the sub-millimeter-wide cracks. A decrease in the received signal magnitude by near-field scattering at the fine concrete surface crack was slight, which yielded an unclear MMW image contrast of fine cracks at the concrete surface. We have found that the received signal magnitude at concrete surface crack is larger than that at the surface without a crack, when the paper thickness is almost equal to n/4 of the effective wavelength of the MMW signal in the paper (n=1, 3, 5 ...), thus, making MMW image contrast at the surface crack reversed. By calculating the difference of two MMW images obtained from different paper thickness, we were able to improve the MMW image contrast at the surface crack by up to 3.3 dB.

The carrier-phase multipath effect can seriously affect the accuracy of GPS-based positioning in static short baseline applications. Although several kinds of methods based on time domain and spatial domain techniques have been proposed to mitigate this error, they are still limited by the accuracy of the multipath model and the effectiveness of the correction strategy. After analyzing the existing methods, a new method based on adaptive thresholding wavelet packet transform (AW) and time domain bootstrap spatial domain search strategy (TB) is presented (AWTB). Taking advantage of adaptive thresholding wavelet packet transform, we enhance the precision of the correction model and the efficiency of the extraction method. In addition, by adopting the proposed time domain bootstrap spatial domain strategy, the accuracy and efficiency of subsequent multipath correction are improved significantly. Specifically, after applying the adaptive thresholding wavelet packet method, the mean improvement rate in the RMS values of the single-difference L1 residuals is about 27.93% compared with the original results. Furthermore, after applying the proposed AWTB method, experiments show that the 3D positioning precision is improved by about 38.51% compared with the original results. Even compared with the method based on stationary wavelet transform (SWT), and the method based on wavelet packets denoising (WPD), the 3D precision is improved by about 26.94% over the SWT method and about 22.96% over the WPD method, respectively. It is worth noting that, although the mean time consumption of the proposed algorithm is larger than the original method, the increased time consumption is not a serious burden for overall performance.

This paper presents a 28-GHz-band highly linear stacked-FET power amplifier (PA) IC. A 4-stacked-FET structure is employed for high output power considering the low breakdown voltage of scaled MOSFET transistors. A novel adaptive bias circuit is proposed to dynamically control the gate-to-source bias voltage for amplification MOSFETs. The novel adaptive bias allows the PA to attain high linearity with high back-off efficiency. In addition, the third-order intermodulation distortion (IM3) is improved by a multi-cascode structure. The PA IC is designed, fabricated and fully tested in 56-nm SOI CMOS technology. At a supply voltage of 4 V, the PA IC has achieved an output power of 20.0 dBm with a PAE as high as 38.1% at the 1-dB gain compression point (P1dB). Moreover, PAEs at 3-dB and 6-dB back-off from P1dB are 36.2% and 28.7%, respectively. The PA IC exhibits an output third-order intercept point (OIP3) of 25.0 dBm.

This letter proposes a blind phase compensation method for the phase errors in the Multi-Carrier Multiple-input multiple-output (MIMO) radar, which decouples the range and DOA coupling. The phase errors under the Linear Frequency Modulated Continuous Waveform (LFMCW) scheme are firstly derived, followed with the signal processing steps. Further, multiple targets with certain velocities can be handled uniformly without pre-knowledge of the actual range information of the targets. The evaluations of the DOA estimation performance are carried out through simulations, which validate the effectiveness of the proposed method.

This article introduces our investigation on learning state estimation in e-learning on the condition that visual observation and recording of a learner's behaviors is possible. In this research, we examined methods of adaptation for a new learner for whom a small number of ground truth data can be obtained.

The decentralized energy network is one of the promising solutions as a next-generation power grid. In this system, each house has a photovoltaic (PV) panel as a renewable energy source and a battery which is an essential component to balance between generation and demand. The common objective of the battery management on such systems is to minimize only the purchased energy from a power company, but battery degradation caused by charge/discharge cycles is also a serious problem. This paper proposes a State-of-Health (SOH) aware system-level battery management methodology for the decentralized energy network. The power distribution problem is often solved with mixed integer programming (MIP), and the proposed MIP formulation takes into account the SOH model. In order to minimize the purchased energy and reduce the battery degradation simultaneously, the optimization problem is divided into two stages: 1) the purchased energy minimization, and 2) the battery aging factor reducing, and the trade-off exploration between the purchased energy and the battery degradation is available. Experimental results show that the proposed method achieves the better trade-off and reduces the battery aging cost by 14% over the baseline method while keeping the purchased energy minimum.

This paper proposes an adaptive call-occurrence probability (COP) setting method for a slotted-ALOHA based consensus problem. Individual agents in the focused consensus problem control themselves in a distributed manner based on the partial information of overall control system which can be received only from the neighbor agents. In order to realize a reliable consensus problem based on wireless communications, we have to consider several constraints caused by the natures of wireless communications such as communication error, coverage, capacity, multi-user interference, half-duplex and so on. This work first investigates the impacts of wireless communication constraints, especially communication coverage, half-duplex, and multiple-access interference constraints, on the quality of control. To mitigate the impact of multiple-access constraint, we propose an adaptive COP setting method that changes the COP corresponding to the states of communication and control. The proposed adaptive COP based slotted-ALOHA needs the information about the number of neighbor agents at its own and neighbor agents, but can still work in a distributed manner. Computer simulations show that the proposed system can achieve better convergence performance compared to the case with the fixed COP based system.

This paper analyzes and compares two methods to estimate electromagnetically coupled noises introduced to an antenna due to the nearby circuits at a circuit design stage. One of them is to estimate the power spectrum, and the other one is to estimate the active S11 parameter at the victim antenna, respectively, and both of them use simulated standard S-parameters for the electromagnetic coupling in the circuit. They also need the assumed or measured excitation of noise sources. To confirm the validness of the two methods, an evaluation board consisting of an antenna and noise sources were designed and fabricated in which voltage controlled oscillator (VCO) chips are placed as noise sources. The generated electromagnetic noises are transferred to an antenna via loop-shaped transmission lines, degrading the performance of the antenna. In this paper, detailed analysis procedures are described using the evaluation board, and it is shown that the two methods are equivalent to each other in terms of the induced voltages in the antenna. Finally, a procedure to estimate antenna performance degradation at the design stage is summarized.

Here, we present a novel spectroscopic imaging method based on the boundary-extraction scheme for wide-beam terahertz (THz) three-dimensional imaging. Optical-lens-focusing systems for THz subsurface imaging generally require the depth of the object from the surface to be input beforehand to achieve the desired azimuth resolution. This limitation can be alleviated by incorporating a wide-beam THz transmitter into the synthetic aperture to automatically change the focusing depth in the post-signal processing. The range point migration (RPM) method has been demonstrated to have significant advantages in terms of imaging accuracy over the synthetic-aperture method. Moreover, in the RPM scheme, spectroscopic information can be easily associated with each scattering center. Thus, we propose an RPM-based terahertz spectroscopic imaging method. The finite-difference time-domain-based numerical analysis shows that the proposed algorithm provides accurate target boundary imaging associated with each frequency-dependent characteristic.

To estimate angle, velocity, and range information of multiple targets jointly in FMCW MIMO radar, two-dimensional (2D) MUSIC with matched filtering and FFT algorithm is proposed. By reformulating the received FMCW signal of the colocated MIMO radar, we exploit 2D MUSIC to estimate the angle and Doppler frequency of multiple targets. Then by using a matched filter together with the estimated angle and Doppler frequency and FFT operation, the range of the target is estimated. To effectively estimate the parameters of multiple targets with large distance differences, we also propose a successive interference cancellation method that uses the orthogonal projection. That is, rather than estimating the multiple target parameters simultaneously using 2D MUSIC, we estimate the target parameters sequentially, in which the parameters of the target having strongest reflected power are estimated first and then, their effect on the received signal is canceled out by using the orthogonal projection. Simulations verify the performance of the proposed algorithm.

Near real-time periodic tasks, which are popular in multimedia streaming applications, have deadline periods that are longer than the input intervals thanks to buffering. For such applications, the conventional frame-based schedulings cannot realize the optimal scheduling due to their shortsighted deadline assumptions. To realize globally energy-efficient executions of these applications, we propose a novel task scheduling algorithm, which takes advantage of the long deadline period. We confirm our approach can take advantage of the longer deadline period and reduce the average power consumption by up to 18%.

In this letter, we propose a novel deep domain-adaptive convolutional neural network (DDACNN) model to handle the challenging cross-corpus speech emotion recognition (SER) problem. The framework of the DDACNN model consists of two components: a feature extraction model based on a deep convolutional neural network (DCNN) and a domain-adaptive (DA) layer added in the DCNN utilizing the maximum mean discrepancy (MMD) criterion. We use labeled spectrograms from source speech corpus combined with unlabeled spectrograms from target speech corpus as the input of two classic DCNNs to extract the emotional features of speech, and train the model with a special mixed loss combined with a cross-entrophy loss and an MMD loss. Compared to other classic cross-corpus SER methods, the major advantage of the DDACNN model is that it can extract robust speech features which are time-frequency related by spectrograms and narrow the discrepancies between feature distribution of source corpus and target corpus to get better cross-corpus performance. Through several cross-corpus SER experiments, our DDACNN achieved the state-of-the-art performance on three public emotion speech corpora and is proved to handle the cross-corpus SER problem efficiently.

This Letter explores the adaptive hybrid automatic repeat request (HARQ) using rate-compatible polar codes constructed with a common information set. The rate adaptation problem is formulated using Markov decision process and solved by a dynamic programming framework in a low-complexity way. Simulation verifies the throughput efficiency of the proposed adaptive HARQ.

In this paper, we propose an adaptive fusion successive cancellation list decoder (ADF-SCL) for polar codes with single cyclic redundancy check. The proposed ADF-SCL decoder reasonably avoids unnecessary calculations by selecting the successive cancellation (SC) decoder or the adaptive successive cancellation list (AD-SCL) decoder depending on a log-likelihood ratio (LLR) threshold in the decoding process. Simulation results show that compared to the AD-SCL decoder, the proposed decoder can achieve significant reduction of the average complexity in the low signal-to-noise ratio (SNR) region without degradation of the performance. When Lmax=32 and Eb/N0=0.5dB, the average complexity of the proposed decoder is 14.23% lower than that of the AD-SCL decoder.