The Origin of the low turn-on voltage in the blue organic light-emitting diode using upconversion is discussed. We have discovered the properties of the intermediate state at the donor/acceptor interface such as the energy levels and the molecular interactions determines the efficiency of the upconversion process.

This paper presents a multi-channel biomedical sensor system with system-level chopping and stochastic analog-to-digital (A/D) conversion techniques. The system-level chopping technique extends the input-signal bandwidth and reduces the interchannel crosstalk caused by multiplexing. The system-level chopping can replace an analog low-pass filter (LPF) with a digital filter and can reduce its area occupation. The stochastic A/D conversion technique realizes power-efficient resolution enhancement. A novel auto-calibration technique is also proposed for the stochastic A/D conversion technique. The proposed system includes a prototype analog front-end (AFE) IC fabricated using a 130 nm CMOS process. The fabricated AFE IC improved its interchannel crosstalk by 40 dB compared with the conventional analog chopping architecture. The AFE IC achieved SNDR of 62.9 dB at a sampling rate of 31.25 kSps while consuming 9.6 μW from a 1.2 V power supply. The proposed resolution enhancement technique improved the measured SNDR by 4.5 dB.

The detection of hardware trojans has been extensively studied in the past. In this article, we propose a side-channel analysis technique that uses a wrapper-based feature selection technique for hardware trojan detection. The whale optimization algorithm is modified to carefully extract the best feature subset. The aim of the proposed technique is multiobjective: improve the accuracy and minimize the number of features. The power consumption traces measured from AES-128 trojan circuits are used as features in this experiment. The stabilizing property of the feature selection method helps to bring a mutual trade-off between the precision and recall parameters thereby minimizing the number of false negatives. The proposed hardware trojan detection scheme produces a maximum of 10.3% improvement in accuracy and reduction up to a single feature by employing the modified whale optimization technique. Thus the evaluation results conducted on various trust-hub cryptographic benchmark circuits prove to be efficient from the existing state-of-art methods.

This study discusses the feasibility to estimate the concentration level of Japanese document workers using computer. Based on the previous findings that dual-task scenarios increase reaction time, we hypothesized that the Kana-Kanji conversion confirmation time (KKCCT) would increase due to the decrease in cognitive resources allocated to the document task, i.e. the level of concentration on the task at hand. To examine this hypothesis, we conducted a set of experiments in which sixteen participants copied Kana text by typing and concurrently converted it into Kanji under three conditions: Normal, Dual-task, and Mental-fatigue. The results suggested the feasibility that KKCCT increased when participants were less concentrated on the task due to subtask or mental fatigue. These findings imply the potential utility of using confirmation time as a measure of concentration level in Japanese document workers.

Homomorphic encryption (HE) is public key encryption that enables computation over ciphertexts without decrypting them. To overcome an issue that HE cannot achieve IND-CCA2 security, the notion of keyed-homomorphic encryption (KH-PKE) was introduced (Emura et al., PKC 2013), which has a separate homomorphic evaluation key and can achieve stronger security named KH-CCA security. The contributions of this paper are twofold. First, recall that the syntax of KH-PKE assumes that homomorphic evaluation is performed for single operations, and KH-CCA security was formulated based on this syntax. Consequently, if the homomorphic evaluation algorithm is enhanced in a way of gathering up sequential operations as a single evaluation, then it is not obvious whether or not KH-CCA security is preserved. In this paper, we show that KH-CCA security is in general not preserved under such modification, while KH-CCA security is preserved when the original scheme additionally satisfies circuit privacy. Secondly, Catalano and Fiore (ACM CCS 2015) proposed a conversion method from linearly HE schemes into two-level HE schemes, the latter admitting addition and a single multiplication for ciphertexts. In this paper, we extend the conversion to the case of linearly KH-PKE schemes to obtain two-level KH-PKE schemes. Moreover, based on the generalized version of Catalano-Fiore conversion, we also construct a similar conversion from d-level KH-PKE schemes into 2d-level KH-PKE schemes.

Multi-band WDM transmission beyond the C+L-band is a promising technology for achieving larger capacity transmission by a limited number of installed fibers. In addition to the C- and L-band, we can expect to use the S-band as the next band. Although the development of optical components for new bands, particularly transceivers, entails resource dispersion, which is one of the barriers to the realization of multi-band systems, wavelength conversion by transparent all-optical signal processing enables new wavelength bandtransmission using existing components. Therefore, we proposed a transmission system including a new wavelength band such as the S-band and made it possible to use a transceiver for the existing band by performing the whole-band wavelength conversion without using a transceiver for the new band. As a preliminary verification to demonstrate multi-band WDM transmission including S-band, we investigated the application of a novel wavelength converter between C-band and S-band, which consists of periodically poled lithium niobate waveguide, to the proposed system. We first characterized the conversion efficiency and noise figure of the wavelength converter and estimated the transmission performance of the system through the wavelength converter. Using the evaluated wavelength converters and test signals of 64 channels arranged in the C-band at 75-GHz intervals, we constructed an experimental setup for S-band transmission through an 80-km standard single-mode fiber. We then demonstrated error-free transmission of real-time 400-Gb/s DP-16QAM signals after forward error correction decoding. From the experimental results, it was clarified that the wavelength converter which realizes the uniform lossless conversion covering the whole C-band effectively achieves the S-band WDM transmission, and it was verified that the capacity improvement of the multi-band WDM system including the S-band can be expected by applying it in combination with the C+L-band WDM system.

One of cost-effective ways to increase the transmission capacity of current standard wavelength division multiplexing (WDM) transmission systems is to use a wavelength band other than the C-band to transmit in multi-band. We proposed the concept of multi-band system using wavelength conversion, which can simultaneously process signals over a wide wavelength range. All-optical wavelength conversion could be used to convert C-band WDM signals into other bands in a highly nonlinear fiber (HNLF) by four-wave mixing and allow to simultaneously transmit multiple WDM signals including other than the C-band, with only C-band transceivers. Wavelength conversion has been reported for various nonlinear waveguide materials other than HNLF. In such nonlinear materials, we noticed the possibility of wideband transmission by dispersion-tailored silicon-on-insulator (SOI) waveguides. Based on the CMOS process has high accuracy, it is expected that the chromatic dispersion fluctuation could be reduced in mass production. As a first step in the investigation of the broadness of wavelength conversion using SOI-based waveguides, we designed and fabricated dispersion-tailored 12 strip waveguides provided with an edge coupler at both ends. Each of the 12 waveguides having different widths and lengths and is connected to fibers via lensed fibers or by lenses. In order to characterize each waveguide, the pump-probe experimental setup was constructed using a tunable light source as pump and an unmodulated 96-ch C-band WDM test signal. Using this setup, we evaluate insertion loss, input power dependence, conversion bandwidth and conversion efficiency. We confirmed C-band test signal was converted to the S-band and the L-band using the same silicon waveguide with 3dB conversion bandwidth over 100-nm. Furthermore, an increased design tolerance of at least 90nm was confirmed for C-to-S conversion by shortening the waveguide length. It is confirmed that the wavelength converters using the nonlinear waveguide has sufficiently wide conversion bandwidth to enhance the multi-band WDM transmission system.

HDR video is possible to display the maximum 1200% luminance, however, it is limited in SDR display. In this study, we expand high luminance area considering with perceptual performance to improve a presentation performance of HDR video in the SDR display. As results of objective experiments, it is recognized that the proposed method can improve the presentation performance maximally 0.8dB in WPSNR.

Neuromorphic computing with a spiking neural network (SNN) is expected to provide a complement or alternative to deep learning in the future. The challenge is to develop optimal SNN models, algorithms, and engineering technologies for real use cases. As a potential use cases for neuromorphic computing, we have investigated a person monitoring and worker support with a video surveillance system, given its status as a proven deep neural network (DNN) use case. In the future, to increase the number of cameras in such a system, we will need a scalable approach that embeds only a few neuromorphic devices in a camera. Specifically, this will require a shallow SNN model that can be implemented in a few neuromorphic devices while providing a high recognition accuracy comparable to a DNN with the same configuration. A shallow SNN was built by converting ResNet, a proven DNN for image recognition, and a new configuration of the shallow SNN model was developed to improve its accuracy. The proposed shallow SNN model was evaluated with a few neuromorphic devices, and it achieved a recognition accuracy of more than 80% with about 1/130 less energy consumption than that of a GPU with the same configuration of DNN as that of SNN.

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 training framework named the INmfCA algorithm for nonparallel voice conversion (VC) systems. To train conversion models, traditional VC frameworks require parallel corpora, in which source and target speakers utter the same linguistic contents. Although the frameworks have achieved high-quality VC, they are not applicable in situations where parallel corpora are unavailable. To acquire conversion models without parallel corpora, nonparallel methods are widely studied. Although the frameworks achieve VC under nonparallel conditions, they tend to require huge background knowledge or many training utterances. This is because of difficulty in disentangling linguistic and speaker information without a large amount of data. In this work, we tackle this problem by exploiting NMF, which can factorize acoustic features into time-variant and time-invariant components in an unsupervised manner. The method acquires alignment between the acoustic features of a source speaker's utterances and a target dictionary and uses the obtained alignment as activation of NMF to train the source speaker's dictionary without parallel corpora. The acquisition method is based on the INCA algorithm, which obtains the alignment of nonparallel corpora. In contrast to the INCA algorithm, the alignment is not restricted to observed samples, and thus the proposed method can efficiently utilize small nonparallel corpora. The results of subjective experiments show that the combination of the proposed algorithm and the INCA algorithm outperformed not only an INCA-based nonparallel framework but also CycleGAN-VC, which performs nonparallel VC without any additional training data. The results also indicate that a one-shot VC framework, which does not need to train source speakers, can be constructed on the basis of the proposed method.

This paper proposes two high-fidelity and computationally efficient neural voice conversion (VC) methods based on a direct waveform modification using spectral differentials. The conventional spectral-differential VC method with a minimum-phase filter achieves high-quality conversion for narrow-band (16 kHz-sampled) VC but requires heavy computational cost in filtering. This is because the minimum phase obtained using a fixed lifter of the Hilbert transform often results in a long-tap filter. Furthermore, when we extend the method to full-band (48 kHz-sampled) VC, the computational cost is heavy due to increased sampling points, and the converted-speech quality degrades due to large fluctuations in the high-frequency band. To construct a short-tap filter, we propose a lifter-training method for data-driven phase reconstruction that trains a lifter of the Hilbert transform by taking into account filter truncation. We also propose a frequency-band-wise modeling method based on sub-band multi-rate signal processing (sub-band modeling method) for full-band VC. It enhances the computational efficiency by reducing sampling points of signals converted with filtering and improves converted-speech quality by modeling only the low-frequency band. We conducted several objective and subjective evaluations to investigate the effectiveness of the proposed methods through implementation of the real-time, online, full-band VC system we developed, which is based on the proposed methods. The results indicate that 1) the proposed lifter-training method for narrow-band VC can shorten the tap length to 1/16 without degrading the converted-speech quality, and 2) the proposed sub-band modeling method for full-band VC can improve the converted-speech quality while reducing the computational cost, and 3) our real-time, online, full-band VC system can convert 48 kHz-sampled speech in real time attaining the converted speech with a 3.6 out of 5.0 mean opinion score of naturalness.

The plain bend in a pair of differential transmission lines causes a path difference, which leads to differential-to-common mode conversion due to the phase difference. This conversion can cause serious common-mode noise issues. We previously proposed a tightly coupled asymmetrically tapered bend to suppress forward differential-to-common mode conversion and derived the constraint conditions for high-density wiring. To provide sufficient suppression of mode conversion, however, the additional correction was required to make the effective path difference vanish. This paper proposes a practical and straightforward design methodology by using a very tightly coupled bend (decreasing the line width and the line separation of the tightly coupled bend). Full-wave simulations below 20GHz demonstrated that sufficient suppression of the forward differential-to-common mode conversion is successfully achieved as designed. Measurements showed that our design methodology is effective.

In this paper, we propose four optimization methods during the Register Transfer Level (RTL) conversion from synchronous RTL models into asynchronous RTL models. The modularization of data-path resources and the use of appropriate D flip-flops reduce the circuit area. Fixing the control signal of the multiplexers and inserting latches for the data-path resources reduce the dynamic power consumption. In the experiment, we evaluated the effect of the proposed optimization methods. The combination of all optimization methods could reduce the energy consumption by 21.9% on average compared to the ones without the proposed optimization methods.

High dynamic range (HDR) imaging refers to digital image processing that modifies the range of color and contrast to enhance image visibility. To create an HDR image, two or more images that include various information are needed. In order to convert low dynamic range (LDR) images to HDR images, we consider the possibility of using a generative adversarial network (GAN) as an appropriate deep neural network. Deep learning requires a great deal of data in order to build a module, but once the module is created, it is convenient to use. In this paper, we propose a weight map for local luminance based on learning to reconstruct locally tone-mapped images.

Impact of sampling frequency and the number of quantization bit of analog-to-digital conversion (ADC) in a direct detection lightwave system using Kramers-Kronig (KK) relation, which has been attracting attention in recent years, are numerically investigated. We studied the effect of spectral broadening caused by nonlinear operations (logarithm, square root) of the KK algorithm when the frequency gap (shift frequency) between the modulated signal and the optical tone is varied. We found that reception performances depend on both the ADC bandwidth and the relative positions of the optical tone and the spectrum. Spectral broadening caused by the logarithm operation of the KK algorithm is found to be the dominant factor of signal distortion in an ADC bandwidth limited system. We studied the effect of the number of quantization bit on the error vector magnitude (EVM) of KK relation based reception in a carrier-to-signal power ratio (CSPR) adjustable transmission system. We found that performances of KK relation based receiver can be improved by increasing the number of quantization bits. For minimum-phase-condition satisfied KK receiver, the required number of quantization bit was found to be 5 bits or more for detection of QPSK, 16-QAM and 64-QAM-modulated signal after 20-km transmission.

In inter-data center networks where high transmission capacity and spectral efficiency are required, a 16QAM format is deployed. On the other hand, in intra-data center networks, a PAM4 format is deployed to meet the demand for a simple and low-cost transceiver configuration. For a seamless and effective connection of such heterogeneous networks without using optical-electrical-optical conversion, an all-optical modulation format conversion technique is required. In this paper, we propose an all-optical PAM4 to 16QAM modulation format conversion using nonlinear optical loop mirror. The successful conversion operation from 2 × 26.6-Gbaud PAM4 signals to a 100-Gbps class 16QAM signal is verified by numerical simulation. Compared with an ideal 16QAM signal, the power penalty of the converted 16QAM signal can be kept within 0.51dB.

This paper proposes a voice conversion (VC) method based on a model that links linguistic and acoustic representations via latent phonological distinctive features. Our method, called speech chain VC, is inspired by the concept of the speech chain, where speech communication consists of a chain of events linking the speaker's brain with the listener's brain. We assume that speaker identity information, which appears in the acoustic level, is embedded in two steps — where phonological information is encoded into articulatory movements (linguistic to physiological) and where articulatory movements generate sound waves (physiological to acoustic). Speech chain VC represents these event links by using an adaptive restricted Boltzmann machine (ARBM) introducing phoneme labels and acoustic features as two classes of visible units and latent phonological distinctive features associated with articulatory movements as hidden units. Subjective evaluation experiments showed that intelligibility of the converted speech significantly improved compared with the conventional ARBM-based method. The speaker-identity conversion quality of the proposed method was comparable to that of a Gaussian mixture model (GMM)-based method. Analyses on the representations of the hidden layer of the speech chain VC model supported that some of the hidden units actually correspond to phonological distinctive features. Final part of this paper proposes approaches to achieve one-shot VC by using the speech chain VC model. Subjective evaluation experiments showed that when a target speaker is the same gender as a source speaker, the proposed methods can achieve one-shot VC based on each single source and target speaker's utterance.

A high degree of freedom in spectral domain allows us to accommodate additional optical signal processing for wavelength division multiplexing in photonic analog-to-digital conversion. We experimentally verified a spectral compression to save a necessary bandwidth for soliton self-frequency shift based optical quantization through the cascade of the four-wave mixing based and the sum-frequency generation based spectral compression. This approach can realize 0.03 nm individual bandwidth correspond to save up to more than 85 percent of bandwidth for 7-bit optical quantization in C-band.

Wavelength division multiplexing (WDM) scheme is used widely in photonic metro-core networks. In a WDM network, wavelength continuity constraint is employed to simply construct relay nodes. This constraint reduces the wavelength usage efficiency of each link. To improve the same, an all-optical wavelength converter (AO-WC) has been attracting attention in recent years. In particular, an AO-WC is a key device because it enables simultaneous conversion of multiple wavelengths of signal lights to other wavelengths, independent of the modulation format. However, each AO-WC requires installation of multiple laser sources with narrow bandwidth because the lights emitted by the laser sources are used as pump lights when the wavelengths of the signal lights are converted by the four-wave mixing (FWM) process. To reduce the number of laser sources, we propose a remote pumped AO-WC, in which the laser sources of the pump lights are aggregated into several relay nodes. When the request for the wavelength conversion from the relay node without the laser source is conveyed, the relay node with the laser source transmits the pump light through the optical link. The proposed scheme enables reduction in the number of laser sources of the pump lights. Herein we analyze the distortion of the pump light by propagating it through the optical link We also evaluate the effect of the noise in optical amplifiers and nonlinearities in optical fibers using numerical simulations employing the representative parameters for a practical WDM network.