This paper presents a class-E power amplifier (PA) with a novel harmonic tuning circuit (HTC) based on composite right-/left-handed transmission lines (CRLH TLs). One of the issues of conventional harmonically tuned PAs is the limited PAE bandwidth. It is shown by simulation that class-E amplifiers have potential of maintaining high PAE over a wider frequency range than for example class-F amplifiers. To make full use of class-E amplifiers with the superior characteristics, an HTC using double CRLH TL stub structure is proposed. The HTC is not only compact but also enhances the inherently wide operation frequency range of class-E amplifier. A 2-GHz 6W GaN-HEMT class-E PA using the proposed HTC demonstrated a PAE bandwidth (≥65%) of 380MHz with maximum drain efficiency and PAE of 78.5% and 74.0%, respectively.

A detailed investigation of DC and RF performance of AlGaN/GaN HEMT on 3C-SiC/low resistive silicon (LR-Si) substrate by introducing a thick GaN layer is reported in this paper. The hetero-epitaxial growth is achieved by metal organic chemical vapor deposition (MOCVD) on a commercially prepared 6-inch LR-Si substrate via a 3C-SiC intermediate layer. The reported HEMT exhibited very low RF loss and thermally stable amplifier characteristics with the introduction of a thick GaN layer. The temperature-dependent small-signal and large-signal characteristics verified the effectiveness of the thick GaN layer on LR-Si, especially in reduction of RF loss even at high temperatures. In summary, a high potential of the reported device is confirmed for microwave applications.

Drones have been attractive for many kinds of industries, but limited power supply from batteries has impeded drones from being operated for longer hours. Microwave power transmission (MPT) is one of the most prospective technologies to release them from the limitation. Since, among several types of drones, micro-drone has shorter available flight time, it is reasonable to provide micro-drone with wireless charging access with an MPT system. However, there is no suitable rectenna for micro-drone charging applications in preceding studies. In this paper, an MPT system for micro-drone was proposed at C-band where a lightweight and compact rectenna array with 20-W class output power was developed. Under illumination of a flat-top beam with 203 mW/cm2 of power density, a 16-element rectenna array was measured. The 16-element rectenna was formed with the aid of a honeycomb substrate for lightness and GaAs Schottky barrier diodes for high output. It was 37.5 g in weight and 146.4 mm by 146.4 mm in size. It output 27.0 W of dc power at 19.0 V at 5.8 GHz when radio frequency power of 280 W was generated by the injection-locked magnetron and 134 W was transmitted from the transmitting phased array. The power-to-weight ratio was 0.72W/g. The power conversion efficiency was 61.9%. These numbers outperformed the rectennas in the preceding studies and are suitable for an MPT system to micro-drone.

Low-temperature deposition of Y2O3 at 80°C is studied using an yttrium precursor of tris(butylcyclopentadienyl)yttrium (Y(BuCp)3) and plasma exited humidified argon oxidizer. The deposition is demonstrated using an atomic-layer-deposition sequence; the Y(BuCp)3 and the oxidizing gases are time separately introduced to the reaction chamber and these injections are repeated. To determine the gas introduction conditions, surface reactions of Y(BuCp)3 adsorption and its oxidization are observed by an in-situ IR absorption spectroscopy. The deposited film is confirmed as fully oxidized Y2O3 by X-ray photoelectron spectroscopy. The present deposition is applicable for the deposition of Y2O3 film on flexible polyethylene terephthalate films.

The low temperature deposition of AlN at 160 °C is examined by using trimethyl aluminum (TMA) and NH radicals from plasma excited Ar diluted ammonia. For the deposition, a plasma tube separated from the reaction chamber is used to introduce the neutral NH radicals on the growing surface without the direct impacts of high-speed species and UV photons, which might be effective in suppressing the plasma damage to the sample surfaces. To maximize the NH radical generation, the NH3 and Ar mixing ratio is optimized by plasma optical emission spectroscopy. To determine the saturated condition of TMA and NH radical irradiations, an in-situ surface observation of IR absorption spectroscopy (IRAS) with a multiple internal reflection geometry is utilized. The low temperature AlN deposition is performed with the TMA and NH radical exposures whose conditions are determined by the IRAS experiment. The spectroscopic ellipsometry indicates the all-round surface deposition in which the growth per cycles measured from front and backside surfaces of the Si sample are of the same range from 0.39∼0.41nm/cycle. It is confirmed that the deposited film contains impurities of C, O, N although we discuss the method to decrease them. X-ray diffraction suggests the AlN polycrystal deposition with crystal phases of AlN (100), (002) and (101). From the saturation curves of TMA adsorption and its nitridation, their chemical reactions are discussed in this paper. In the present paper, we discuss the possibility of the low temperature AlN deposition.

We fabricated Fe-silicide nanodots (NDs) on an ultrathin SiO2 layer and evaluated changes in electron transport properties with and without magnetic field application. High-density NDs with an areal density as high as ∼1011cm-2 were formed on thermally grown SiO2 by exposing ultrathin Fe/Si-NDs structures to a remote H2 plasma without external heating. In electron transport properties related to current-time characteristics for a diode with Fe electrode and charging energy to NDs, clear changes in current levels through NDs and electron injection modulation of NDs depending on intensity of magnetic fields were observed.

A static timing analysis (STA) tool for a 28nm atom-switch FPGA (AS-FPGA) is introduced to validate the signal delay of an application circuit before implementation. High accuracy of the STA tool is confirmed by implementing a practical application circuit on the 28nm AS-FPGA. Moreover, dramatic improvement of delay and power is demonstrated in comparison with a previous 40nm AS-FPGA.

A light field (LF), which is represented as a set of dense, multi-view images, has been used in various 3D applications. To make LF acquisition more efficient, researchers have investigated compressive sensing methods by incorporating certain coding functionalities into a camera. In this paper, we focus on a challenging case called snapshot compressive LF imaging, in which an entire LF is reconstructed from only a single acquired image. To embed a large amount of LF information in a single image, we consider two promising methods based on rapid optical control during a single exposure: time-multiplexed coded aperture (TMCA) and coded focal stack (CFS), which were proposed individually in previous works. Both TMCA and CFS can be interpreted in a unified manner as extensions of the coded aperture (CA) and focal stack (FS) methods, respectively. By developing a unified algorithm pipeline for TMCA and CFS, based on deep neural networks, we evaluated their performance with respect to other possible imaging methods. We found that both TMCA and CFS can achieve better reconstruction quality than the other snapshot methods, and they also perform reasonably well compared to methods using multiple acquired images. To our knowledge, we are the first to present an overall discussion of TMCA and CFS and to compare and validate their effectiveness in the context of compressive LF imaging.

Crowdedness of buses is playing an increasingly important role in the disease control of COVID-19. The lack of a practical approach to sensing the crowdedness of buses is a major problem. This paper proposes a bus crowdedness sensing system which exploits deep learning-based object detection to count the numbers of passengers getting on and off a bus and thus estimate the crowdedness of buses in real time. In our prototype system, we combine YOLOv5s object detection model with Kalman Filter object tracking algorithm to implement a sensing algorithm running on a Jetson nano-based vehicular device mounted on a bus. By using the driving recorder video data taken from real bus, we experimentally evaluate the performance of the proposed sensing system to verify that our proposed system system improves counting accuracy and achieves real-time processing at the Jetson Nano platform.

A multibeam massive multiple input multiple output (MIMO) configuration employs beam selection with high power in the analog part and executes a blind algorithm such as the independent component analysis (ICA), which does not require channel state information in the digital part. Two-dimensional (2-D) multibeams are considered in actual power losses and beam steering errors regarding the multibeam patterns. However, the performance of these 2-D beams depends on the beam pattern of the multibeams, and they are not optimal multibeam patterns suitable for multibeam massive MIMO configurations. In this study, we clarify the performance difference due to the difference of the multibeam pattern and consider the multibeam pattern suitable for the system condition. Specifically, the optimal multibeam pattern was determined with the element spacing and beamwidth of the element directivity as parameters, and the effectiveness of the proposed method was verified via computer simulations.

The colors of objects in natural images are affected by the color of lighting, and accurately estimating an illuminant's color is indispensable in analyzing scenes lit by colored lightings. Recent lighting environments enhance colorfulness due to the spread of light-emitting diode (LED) lightings whose colors are flexibly controlled in a full visible spectrum. However, existing color estimations mainly focus on the single illuminant of normal color ranges. The estimation of multiple illuminants of unusual color settings, such as blue or red of high chroma, has not been studied yet. Therefore, new color estimations should be developed for multiple illuminants of various colors. In this article, we propose a color estimation for LED lightings using Color Line features, which regards the color distribution as a straight line in a local area. This local estimate is suitable for estimating various colors of multiple illuminants. The features are sampled at many small regions in an image and aggregated to estimate a few global colors using supervised learning with a convolutional neural network. We demonstrate the higher accuracy of our method over existing ones for such colorful lighting environments by producing the image dataset lit by multiple LED lightings in a full-color range.

We have fabricated two-tiered heterostructures consisting of phosphorus δ-doped Si quantum dots (Si-QDs) and undoped Si-QDs and studied their electron field emission properties. Electron emission was observed from the P-doped Si-QDs stack formed on the undoped Si-QDs stack by applying a forward bias of ∼6 V, which was lower than that for pure Si-QDs stack. This result is attributed to electric field concentration on the upper P-doped Si-QD layers beneath the layers of the undoped Si-QDs stack due to the introduction of phosphorus atom into the Si-QDs, which was positively charged due to the ionized P donor. The results lead to the development of planar-type electron emission devices with a low-voltage operation.

This paper proposes a topology of high power, MHz-frequency, half-bridge resonant inverter ideal for low-loss Gallium Nitride high electron mobility transistor (GaN-HEMT). General GaN-HEMTs have drawback of low drain-source breakdown voltage. This property has prevented conventional high-frequency series resonant inverters from delivering high power to high resistance loads such as 50Ω, which is typically used in radio frequency (RF) systems. High resistance load causes hard-switching also and reduction of power efficiency. The proposed topology overcomes these difficulties by utilizing a proposed ‘L-S network’. This network is effective combination of a simple impedance converter and a series resonator. The proposed topology provides not only high power for high resistance load but also arbitrary design of output wattage depending on impedance conversion design. In addition, the current through the series resonator is low in the L-S network. Hence, this series resonator can be designed specifically for harmonic suppression with relatively high quality-factor and zero reactance. Low-distortion sinusoidal 3kW output is verified in the proposed inverter at 13.56MHz by computer simulations. Further, 99.4% high efficiency is achieved in the power circuit in 471W experimental prototype.

In this paper, we propose a new algorithm to generate Speech-like Emotional Sound (SES). Emotional expressions may be the most important factor in human communication, and speech is one of the most useful means of expressing emotions. Although speech generally conveys both emotional and linguistic information, we have undertaken the challenge of generating sounds that convey emotional information alone. We call the generated sounds “speech-like,” because the sounds do not contain any linguistic information. SES can provide another way to generate emotional response in human-computer interaction systems. To generate “speech-like” sound, we propose employing WaveNet as a sound generator conditioned only by emotional IDs. This concept is quite different from the WaveNet Vocoder, which synthesizes speech using spectrum information as an auxiliary feature. The biggest advantage of our approach is that it reduces the amount of emotional speech data necessary for training by focusing on non-linguistic information. The proposed algorithm consists of two steps. In the first step, to generate a variety of spectrum patterns that resemble human speech as closely as possible, WaveNet is trained with auxiliary mel-spectrum parameters and Emotion ID using a large amount of neutral speech. In the second step, to generate emotional expressions, WaveNet is retrained with auxiliary Emotion ID only using a small amount of emotional speech. Experimental results reveal the following: (1) the two-step training is necessary to generate the SES with high quality, and (2) it is important that the training use a large neutral speech database and spectrum information in the first step to improve the emotional expression and naturalness of SES.

We introduce a new type of exponentiation algorithm in GF(2m) using Euclidean inversion. Our approach is based on the fact that Euclidean inversion cost much less logic gates than ordinary multiplication in GF(2m). By applying signed binary form of the exponent instead of classic binary form, the proposed algorithm can reduce the number of operations further compared with the classic algorithms.

We studied whether a statement similar to the Ghouila-Houri's theorem might hold for alternating orientations of cocomparability graphs. In this paper, we give the negative answer. We prove that it is NP-complete to decide whether a cocomparability graph has an orientation that is alternating and acyclic. Hence, cocomparability graphs with an acyclic alternating orientation form a proper subclass of alternately orientable cocomparability graphs. We also provide a separating example, that is, an alternately orientable cocomparability graph such that no alternating orientation is acyclic.

Multiparty computation (MPC) is a cryptographic method that enables a set of parties to compute an arbitrary joint function of the private inputs of all parties and does not reveal any information other than the output. MPC based on a secret sharing scheme (SS-MPC) and garbled circuit (GC) is known as the most common MPC schemes. Another cryptographic method, homomorphic encryption (HE), computes an arbitrary function represented as a circuit by using ciphertexts without decrypting them. These technologies are in a trade-off relationship for the communication/round complexities, and the computation cost. The private decision tree evaluation (PDTE) is one of the key applications of these technologies. There exist several constant-round PDTE protocols based on GC, HE, or the hybrid schemes that are secure even if a malicious adversary who can deviate from protocol specifications corrupts some parties. There also exist other protocols based only on SS-MPC that are secure only if a semi-honest adversary who follows the protocol specification corrupts some parties. However, to the best of our knowledge, there are currently no constant-round PDTE protocols based only on SS-MPC that are secure against a malicious adversary. In this work, we propose a constant-round four-party PDTE protocol that achieves malicious security. Our protocol provides the PDTE securely and efficiently even when the communication environment has a large latency.

This paper aims to design multiple-input multiple-output (MIMO) radar receiving weights and transmitting waveforms, in order to obtain better spatial filtering performance and enhance the robustness in the case of signal-dependent interference and jointly inaccurate estimated angles of target and interference. Generally, an alternate iterative optimization algorithm is proposed for the joint design problem. Specifically, the receiving weights are designed by the generalized eigenvalue decomposition of the matrix which contains the estimated information of the target and interference. As the cost function of the transmitting waveform design is fractional, the fractional optimization problem is first converted into a secondary optimization problem. Based on the proposed algorithm, a closed-form solution of the waveform is given using the alternating projection. At the analysis stage, in the presence of estimated errors under the environment of signal-dependent interference, a robust signal-to-interference and noise ratio (SINR) performance is obtained using a small amount of calculation with an iterative procedure. Numerical examples verify the effectiveness of the performances of the designed waveform in terms of the SINR, beampattern and pulse compression.

In this paper, we report an experimental and numerical analysis of ultrahigh-speed coherent Nyquist pulse transmission. First, we describe a low-nonlinearity dispersion compensator for ultrahigh-speed coherent Nyquist pulse transmission; it is composed of a chirped fiber Bragg grating (CFBG) and a liquid crystal on silicon (LCoS) device. By adopting CFBG instead of inverse dispersion fiber, the nonlinearity in a 160km transmission line was more than halved. Furthermore, by eliminating the group delay fluctuation of the CFBG with an LCoS device, the residual group delay was reduced to as low as 1.42ps over an 11nm bandwidth. Then, by using the transmission line with the newly constructed low-nonlinearity dispersion compensator, we succeeded in improving the BER performance of single-channel 15.3Tbit/s-160km transmission by one-third compared with that of a conventional dispersion-managed transmission line and obtained a spectral efficiency of 8.7bit/s/Hz. Furthermore, we numerically analyzed the BER performance of its Nyquist pulse transmission. The numerical results showed that the nonlinear impairment in the transmission line is the main factor limiting the transmission performance in a coherent Nyquist pulse transmission, which becomes more significant at higher baud rates.

Selecting visually overlapping image pairs without any prior information is an essential task of large-scale structure from motion (SfM) pipelines. To address this problem, many state-of-the-art image retrieval systems adopt the idea of bag of visual words (BoVW) for computing image-pair similarity. In this paper, we present a method for improving the image pair selection using BoVW. Our method combines a conventional vector-based approach and a set-based approach. For the set similarity, we introduce a modified version of the Simpson (m-Simpson) coefficient. We show the advantage of this measure over three typical set similarity measures and demonstrate that the combination of vector similarity and the m-Simpson coefficient effectively reduces false positives and increases accuracy. To discuss the choice of vocabulary construction, we prepared both a sampled vocabulary on an evaluation dataset and a basic pre-trained vocabulary on a training dataset. In addition, we tested our method on vocabularies of different sizes. Our experimental results show that the proposed method dramatically improves precision scores especially on the sampled vocabulary and performs better than the state-of-the-art methods that use pre-trained vocabularies. We further introduce a method to determine the k value of top-k relevant searches for each image and show that it obtains higher precision at the same recall.