This paper presents a compact fully-differential distributed amplifier using a coupled inductor. Differential distributed amplifiers are widely required in optical communication systems. Most of the distributed amplifiers reported in the past are single-ended or pseudo-differential topologies. In addition, the differential distributed amplifiers require many inductors, which increases the silicon cost. In this study, we use differentially coupled inductors to reduce the chip area to less than half and eliminate the difficulties in layout design. The challenge in using coupled inductors is the capacitive parasitic coupling that degrades the flatness of frequency response. To address this challenge, the odd-mode image parameters of a differential artificial transmission line are derived using a simple loss-less model. Based on the analytical results, we optimize the dimensions of the inductor with the gradient descent algorithm to achieve accurate impedance matching and phase matching. The amplifier was fabricated in 0.18-µm CMOS technology. The core area of the amplifier is 0.27 mm2, which is 57% smaller than the previous work. Besides, we demonstrated a small group delay variation of ±2.7 ps thanks to the optimization. the amplifier successfully performed 30-Gbps NRZ and PAM4 transmissions with superior jitter performance. The proposed technique will promote the high-density integration of differential traveling wave devices.

This contribution introduces a novel, dielectric waveguide based, permittivity sensor. Next to the fundamental hybrid mode theory, which predicts exceptional wave propagation behavior, a design concept is presented that realizes a pseudo-transmission measurement approach for attenuating feed-side reflections. Furthermore, a transmission line length independent signal processing is introduced, which fosters the robustness and applicability of the sensor concept. Simulation and measurement results that prove the sensor concept and validate the high measurement accuracy, are presented and discussed in detail.

This paper formulates a class-E synchronous RF rectifier from a new viewpoint. The key point is to introduce a matrix and convolute the DC terms into RF matrices. The explicit expression of input impedance is demonstrated in plane geometry. We find out their input impedance exhibits a geodesic arc in hyperbolic geometry under ZVS operation, where the theoretical RF-DC conversion efficiency results in 100%. We verify the developed theory both numerically (circuit simulation) and experimentally (6.78MHz, 100W). We confirm that the input impedance becomes a geodesic arc for a wide range of DC load resistance. The presented theory is quite elegant since it is based on a matrix-based formulation and plane-geometrical expression.

The generation and reduction reaction of magnesium plasma were studied using a cylindrical transverse magnetic-mode applicator in magnetic and electric field modes. By heating Mg powder using the magnetic field mode, plasma was generated with the evaporation of Mg and stably sustained. When the Mg plasma sample was introduced into the reaction zone and exposed to microwave and lamp heating, a reduction reaction of scandium oxide also occurred. The results of this study provide prospects for the development of a larger microwave refining system.

The increasing demand for millimeter-wave (mmWave) frequencies with wider signal bandwidths, such as 5G NR, requires large investments on test equipment. This work presents a 5G mmWave up/down-converter with a 40 GHz LO, fabricated in custom PCBs with off-the-shelf components. The mmWave converter has broad IF and RF bandwidths of 1∼5 GHz and 21∼45 GHz, and the built-in LO generates 20∼29.5 GHz and 33.5∼40 GHz of output. To achieve high linearity of the converter simultaneously, the LO must produce low-phase-noise and be capable of high harmonics/spur rejection, and design techniques related to these features are demonstrated. Additionally, a reconfigurable IF amplifier for bi-directional conversion is included and demonstrates low gain variation to maintain the linearity of the wideband modulation signals. The final designed converter is tested with 5G OFDM 64-QAM 100 MHz 1-CC (4-CC) signals and shows RF/IF output power of -3/8 dBm with a linear range of 35 (30)/38 (33) dB at an EVM of 25 dB.

In this paper, we describe a wavelength-division multiplexing visible-light communication (VLC) system using two colored light-emitting diodes (LEDs) with similar emission wavelengths. A multi-input multi-output signal-separation method using a neural network is proposed to cancel the optical cross chatter caused by the spectral overlap of LEDs. The experimental results demonstrate that signal separation using neural networks can be achieved in wavelength-multiplexed VLC systems with a bit error rate of less than 3.8×10-3 (forward error correction limit). Furthermore, the simulation results reveal that the carrier-to-noise ratio (CNR) is improved by 2dB for the successive interference canceller (SIC) compared to the zero-forcing method.

We evaluated the energy efficiency per 1-bit transmission of an optical light source on InP substrate to achieve optical interconnection. A semiconductor optical amplifier (SOA) assisted extended reach EADFB laser (AXEL) was utilized as the optical light source to enhance the energy efficiency compared to the conventional electro-absorption modulator integrated with a DFB laser (EML). The AXEL has frequency bandwidth extendibility for operation of over 100Gbit/s, which is difficult when using a vertical cavity surface emitting laser (VCSEL) without an equalizer. By designing the AXEL for low power consumption, we were able to achieve 64-Gbit/s, 1.0pJ/bit and 128-Gbit/s, 1.5pJ/bit operation at 50°C with the transmitter dispersion and eye closure quaternary of 1.1dB.

Indoor free space optical (FSO) communication technology that provides high-speed connectivity to edge users is expected to be introduced in the near future mobile communication system, where the silicon photonics solid-state beam scanning device is a promising tool because of its low cost, long-term reliability, and other beneficial properties. However, the current two-dimensional beam scanning devices using grating coupler arrays have difficulty in increasing the transmission capacity because of bandwidth regulation. To solve the problem, we have introduced a broadband surface optical coupler, “elephant coupler,” which has great potential for combining wavelength and spatial division multiplexing technologies into the beam scanning device, as an alternative to grating couplers. The prototype port-selective silicon beam scanning device fabricated using a 300 mm CMOS pilot line achieved broadband optical beam emission with a 1 dB-loss bandwidth of 40 nm and demonstrated beam scanning using an imaging lens. The device has also exhibited free-space signal transmission of non-return-to-zero on-off-keying signals at 10 Gbps over a wide wavelength range of 60 nm. In this paper, we present an overview of the developed beam scanning device. Furthermore, the theoretical design guidelines for indoor mobile FSO communication are discussed.

The optical phased array (OPA) is an emerging non-mechanical device that enables high-speed beam steering by emitting precisely phase-controlled lightwaves from numerous optical antennas. In practice, however, it is challenging to drive all phase shifters on an OPA in a deterministic manner due to the inevitable fabrication-induced phase errors and crosstalk between the phase shifters. In this work, we fabricate a 16-element silicon photonic non-redundant OPA chip with integrated phase monitors and experimentally demonstrate accurate monitoring of the relative phases of light from each optical antenna. Under the beam steering condition, the optical phase retrieved from the on-chip phase monitors varies linearly with the steering angle, as theoretically expected.

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.

We propose a novel mode-multiplexed light source using angularly-multiplexed volume holograms. Mode division multiplexing beams can be generated from a simple transmitter that is made of a laser array, single lens, and volume holograms. Hologram media has low recording sensitivity; hence, using holograms in the communication band is difficult. However, a dual wavelength method that uses different wavelengths for recording and reading holograms can realize the volume holograms for the infrared region. The volume holograms for three spatial mode multiplexing are formed using a compact Michelson interferometer type recording setup; simultaneous generations of three modes were demonstrated using a fiber array or vertical cavity surface emitting laser array with the volume holograms. A low loss coupling of three modes to few-mode-fiber can be achieved through the precise design and recording of volume holograms. The simple and low-cost mode-multiplexed light source using the volume holograms has the potential to broaden the application of MDM.

The maximal independent set (MIS) problem is one of the most fundamental problems in the field of distributed computing. This paper focuses on the MIS problem with unreliable communication between processes in the system. We propose a relaxed notion of MIS, named almost MIS (ALMIS), and show that the loosely-stabilizing algorithm proposed in our previous work can achieve exponentially long holding time with logarithmic convergence time and space complexity regarding ALMIS, which cannot be achieved at the same time regarding MIS in our previous work.

The Variational Quantum Eigensolver (VQE) algorithm is gaining interest for its potential use in near-term quantum devices. In the VQE algorithm, parameterized quantum circuits (PQCs) are employed to prepare quantum states, which are then utilized to compute the expectation value of a given Hamiltonian. Designing efficient PQCs is crucial for improving convergence speed. In this study, we introduce problem-specific PQCs tailored for optimization problems by dynamically generating PQCs that incorporate problem constraints. This approach reduces a search space by focusing on unitary transformations that benefit the VQE algorithm, and accelerate convergence. Our experimental results demonstrate that the convergence speed of our proposed PQCs outperforms state-of-the-art PQCs, highlighting the potential of problem-specific PQCs in optimization problems.

Existing simple routing protocols (e.g., OSPF, RIP) have some disadvantages of being inflexible and prone to congestion due to the concentration of packets on particular routers. To address these issues, packet routing methods using machine learning have been proposed recently. Compared to these algorithms, machine learning based methods can choose a routing path intelligently by learning efficient routes. However, machine learning based methods have a disadvantage of training time overhead. We thus focus on a lightweight machine learning algorithm, OS-ELM (Online Sequential Extreme Learning Machine), to reduce the training time. Although previous work on reinforcement learning using OS-ELM exists, it has a problem of low learning accuracy. In this paper, we propose OS-ELM QN (Q-Network) with a prioritized experience replay buffer to improve the learning performance. It is compared to a deep reinforcement learning based packet routing method using a network simulator. Experimental results show that introducing the experience replay buffer improves the learning performance. OS-ELM QN achieves a 2.33 times speedup than a DQN (Deep Q-Network) in terms of learning speed. Regarding the packet transfer latency, OS-ELM QN is comparable or slightly inferior to the DQN while they are better than OSPF in most cases since they can distribute congestions.

An interconnection network is an inevitable component for constructing parallel computers. It connects computation nodes so that the nodes can communicate with each other. As a parallel computation essentially requires inter-node communication according to a parallel algorithm, the interconnection network plays an important role in terms of communication performance. This paper focuses on the collective communication that is frequently performed in parallel computation and this paper addresses the Cup-Stacking method that is proposed in our preceding work. The key issues of the method are splitting a large packet into slices, re-shaping the slice, and stacking the slices, in a genetic algorithm (GA) manner. This paper discusses extending the Cup-Stacking method by introducing additional items (genes) and proposes the extended Cup-Stacking method. Furthermore, this paper places comprehensive discussions on the drawbacks and further optimization of the method. Evaluation results reveal the effectiveness of the extended method, where the proposed method achieves at most seven percent improvement in duration time over the former Cup-Stacking method.

Learning analytics (LA) has emerged as a technique for educational quality improvement in many learning contexts, including blended learning (BL) courses. Numerous studies show that students' academic performance is significantly impacted by their ability to engage in self-regulated learning (SRL). In this study, learning behaviors indicating SRL and motivation are elucidated during a BL course on second language learning. Online trace data of a mobile language learning application (m-learning app) is used as a part of BL implementation. The observed motivation were of two categories: high-level motivation (study in time, study again, and early learning) and low-level motivation (cramming and catch up). As a result, students who perform well tend to engage in high-level motivation. While low performance students tend to engage in clow-level motivation. Those findings are supported by regression models showing that study in time followed by early learning significantly influences the academic performance of BL courses, both in the spring and fall semesters. Using limited resource of m-learning app log data, this BL study could explain the overall BL performance.

In this study, we present a spherical style deformation algorithm to be applied on single component models that can deform the models with spherical style, while preserving the local details of the original models. Because 3D models have complex skeleton structures that consist of many components, the deformation around connections between each single component is complicated, especially preventing mesh self-intersections. To the best of our knowledge, there does not exist not only methods to achieve a spherical style in a 3D model consisting of multiple components but also methods suited to a single component. In this study, we focus on spherical style deformation of single component models. Accordingly, we propose a deformation method that transforms the input model with the spherical style, while preserving the local details of the input model. Specifically, we define an energy function that combines the as-rigid-as-possible (ARAP) method and spherical features. The spherical term is defined as l2-regularization on a linear feature; accordingly, the corresponding optimization can be solved efficiently. We also observed that the results of our deformation are dependent on the quality of the input mesh. For instance, when the input mesh consists of many obtuse triangles, the spherical style deformation method fails. To address this problem, we propose an optional deformation method based on convex hull proxy model as the complementary deformation method. Our proxy method constructs a proxy model of the input model and applies our deformation method to the proxy model to deform the input model by projection and interpolation. We have applied our proposed method to simple and complex shapes, compared our experimental results with the 3D geometric stylization method of normal-driven spherical shape analogies, and confirmed that our method successfully deforms models that are smooth, round, and curved. We also discuss the limitations and problems of our algorithm based on the experimental results.

This paper describes a public web service called Kiite Cafe that lets users get together virtually to listen to music. When users listen to music on Kiite Cafe, their experiences are enhanced by two architectures: (i) visualization of each user's reactions, and (ii) selection of songs from users' favorite songs. These architectures enable users to feel social connection with others and the joy of introducing others to their favorite songs as if they were together listening to music in person. In addition, the architectures provide three user experiences: (1) motivation to react to played songs, (2) the opportunity to listen to a diverse range of songs, and (3) the opportunity to contribute as a curator. By analyzing the behavior logs of 2,399 Kiite Cafe users over a year, we quantitatively show that these user experiences can generate various effects (e.g., users react to a more diverse range of songs on Kiite Cafe than when listening alone). We also discuss how our proposed architectures can enrich music listening experiences with others.

Until today, digital image watermarking has not been large-scale used in the industry. The first reason is that the watermarking efficiency is low and the real-time performance cannot be satisfied. The second reason is that the watermarking scheme cannot cope with various attacks. To solve above problems, this paper presents a multi-domain based digital image watermarking scheme, where a fast DFT (Discrete Fourier Transform) based watermarking method is proposed for synchronization correction and an IWT-DCT (Integer Wavelet Transform-Discrete Cosine Transform) based watermarking method is proposed for information embedding. The proposed scheme has high efficiency during embedding and extraction. Compared with five existing schemes, the robustness of our scheme is very strong and our scheme can cope with many common attacks and compound attacks, and thus can be used in wide application scenarios.

The diffusion model has achieved success in generating and editing high-quality images because of its ability to produce fine details. Its superior generation ability has the potential to facilitate more detailed segmentation. This study presents a novel approach to segmentation tasks using an inverse heat dissipation model, a kind of diffusion-based models. The proposed method involves generating a mask that gradually shrinks to fit the shape of the desired segmentation region. We comprehensively evaluated the proposed method using multiple datasets under varying conditions. The results show that the proposed method outperforms existing methods and provides a more detailed segmentation.