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In wireless power transfer systems, geometries of a transmitter coil and a receiver coil considerably influence power transmission efficiency (PTE) and the magnetic field leakage. However, a method to simultaneously optimize the geometries of both the transmitter and receiver coils is yet to be devised, and custom design for each electronic device remains unfeasible. In this study, using mesh current distribution analysis, we optimized the current distribution in the design area of the transmitter and receiver coils to simultaneously optimize the geometries of the transmitter coil and the receiver coil. Two types of design methods were devised by using two types of optimization: one to maximize PTE and the other to maximize PTE under cancellation conditions of the magnetic field leakage. The first method designs the coil geometries for maximizing PTE and the second method designs for canceling the magnetic field leakage. Electromagnetic simulations and experimental analysis using a metal three-dimensional printer revealed that the design objectives were accomplished because it was confirmed that the coils designed to maximize PTE achieved higher PTE and the coils designed to cancel the magnetic field leakage achieved lower magnetic field leakage intensity. The results of this study proved that the automatic coil design can become a feasible method in various applications.

Compensating for deviations in the resonant frequency is crucial in magnetic resonance coupling wireless power transfer (WPT) systems. Thus, this study proposes a communication-less receiver-side resonant frequency-tuning scheme that compensates for the reactance in the receiver without communicating with the transmitter. The proposed scheme comprises an inductor-capacitor-capacitor compensation topology at the transmitter and a half-bridge circuit at the receiver, whose operating phase is set to be orthogonal to the receiver current. Resonant frequency tuning can be achieved by adjusting the DC voltage applied to the half-bridge circuit to maximize the power received at the load. The reactance compensation ability of the proposed scheme is analyzed through experiments on a 200 kHz WPT system. When the secondary capacitance deviated from −20% to +20%, the efficiency degradation was maintained within 6.7% with the proposed scheme, whereas the efficiency degraded by up to 33.3% without compensation.

Cross-organizational process mining aims to discover an entire process model across multiple organizations where their identifier (ID) systems are not managed uniformly, and each organization has an independent ID system. Cross-organizational process mining has been gaining popularity as information systems increase in complexity. However, previous methods have limitations in that they do not work well for event logs that contain only common items, or cyclic orchestrations, which indicates that the model contains loops. In this paper, we propose an accurate cross-organizational process mining technique based on a step-by-step case ID identification mechanism that uses only common items in event logs and can handle cyclic orchestrations. Step-by-step case ID identification repeats the following steps: 1) identification of case IDs based on activity connection of adjacent event pairs, and 2) extraction of additional activity connections by leveraging the newly identified case IDs. We alternately identify the most probable case ID pairs and remove events belonging to these identified case IDs from the event log, which contributes to extracting additional activity connections and narrowing down the candidates of case ID pairs. Evaluation using real-world event logs showed that the proposed method generates the process model with more than 98.4% precision and more than 94.2% recall for two datasets, outperforming previous methods.

The reduction of coil design cost is essential to integrating wireless power transfer (WPT) systems in electronic devices. However, the power transfer efficiency of WPT systems is influenced by operating conditions, such as the surrounding material and compatibility between transmitter and receiver coils. Further, experienced engineers are faced with the task of adjusting coil parameters using trial and error methods, which is time-consuming. To overcome this problem, we propose a general coil design method based on a current distribution analysis. This design method comprises a two-dimensional current distribution calculation method for the design of a highly efficient coil and coil layout determination method based on the current distribution. We design a coil attached to a metal plate and validate through simulations and experiments that the proposed design achieves the highest power transfer efficiency at 6.78 MHz among multiple coils designed by sweeping design parameters.

Neuroscience suggests that the sparse behavior of a neural population underlies the mechanisms of the auditory system for monaural overlapped speech separation. This study investigates leveraging sparse approximation to improve speech separation in a conventional deep learning algorithm. We develop a combined model that embeds a sparse approximation algorithm, a multilayered iterative soft thresholding algorithm (ML-ISTA), into a conventional time-domain-based speech separation algorithm, Conv-TasNet. Adopting ML-ISTA is a crucial enabler for the embedding process and helps avoid solving a bi-level optimization problem comprising sparse approximation and speech separation. ML-ISTA performs sparse approximation through forward calculations, thereby eliminating the optimization of sparse approximation. The combined model is trained with WSJ0-2mix, the Wall Street Journal English corpus for two-speaker mixed speech without noisy or reverberant interference, to clarify the proposed method’s performance. The model demonstrates that sparse approximation improves separation performance regardless of the approximation setting. The peak performance of the model exceeds that of Conv-TasNet by 1.1% to 4.7% in four speech quality criteria. Moreover, sparse approximation accelerates the combined model performance gain at the early stages of learning relative to Conv-TasNet. The primary novelty of the study is embedding the sparse approximation algorithm, ML-ISTA, into a deep-learning-based speech separation framework and the experimental proof of improved separation performance in the proposed algorithm.

Multiple-input multiple-output (MIMO) wireless power transfer (WPT) systems present various advantages to users, including improved power transfer efficiency, adjustable transmission power, and reduced magnetic field leakage. An essential aspect of controlling MIMO WPT systems is the estimation of $Z$ parameters, which characterize the behavior of the linear electrical network in these systems. In this study, we propose a method to estimate all elements of the $Z$ parameters without requiring synchronization between the transmitters and receivers. Instead, the elements are estimated based on the measured complex amplitudes of voltage and current at the transmitters, as well as the direct current (DC) at the output of the full-bridge rectifiers on the receivers. Importantly, all these measurements can be obtained at a minimal cost. Further, circuit simulations and experiments are also conducted to evaluate the performance of the proposed method. Specifically, a $2 \times 2$ MIMO WPT system is employed for the circuit simulations and experiments, and the $Z$ parameters are estimated under various receiver position conditions. The evaluation of the simulation and experimental results is based on the power transmission efficiency of the system, considering the estimated $Z$ parameters. The simulation and experimental results demonstrate that the difference between the power transfer efficiency based on the estimated $Z$ parameters and the theoretical maximum efficiency based on the true $Z$ parameters is found to fall within the range of 0.06 % and 0.4 %, respectively.

Abstract This paper proposes and experimentally evaluates, a reconfigurable intelligent surface (RIS) control system for multiple users using stereo camera images. The aim is to enable fast and fair received signal strength (RSS) beamforming for multiple users. In the proposed system, a stereo camera is mounted on top of the RIS. Human bodies are recognized from the obtained images. Subsequently, the beam directions and the phase of the RIS are calculated for the estimated positions. The stereo camera‐based scheme enables fast beamforming because channel state information estimation is omitted. Moreover, identical RSS beamforming is enabled by calculating the weighted sums of the RIS phases for multiple users utilizing distance and angle information of users from the RIS obtained using the stereo camera. Experiments are conducted in an anechoic chamber using RIS operating at 28 GHz. The efficacy of the RIS control system using stereo camera images and its ability to increase the RSS fairly for multiple users is validated via simulations and experiments.

LoRa communication protocol using 920 MHz-band has been opened to the public for Internet of Things (IoT) application and a wide variety of telemeter usage since 2017 in Japan. It is expected to be used for collection of scientific observations and monitoring data at Syowa Station. In JARE61, we have investigated the radio environment of the 920 MHz-band, and its possible impact on the ongoing scientific observations in Syowa Station．A member of the wintering team carries a handy transmitter in the nearby area of Syowa Station, East-ongul Island. The transmitter sends GPS location and time data to the receiver (LoRa gateway) located at the roof handrail of the observation building. Six surveys have been conducted, and we confirmed the reachability of the radio signal in and outside of the Syowa Station. The possibilities of the 920 MHz-band application have been suggested to use monitoring station infrastructure and scientific observations.

Deploying 2-D arrays of multiple transmitters is a promising approach for extending wireless power transfer (WPT) to wide surfaces. However, these arrays involve “null zones,” where the transfer efficiency drops significantly. Although this problem can be hypothetically addressed by employing a receiver array and dynamically selecting the appropriate transmitter/receiver pair, designing receiver arrays that achieve high efficiency throughout the surface remains a challenging task. In this study, we propose a genetic algorithm (GA)-based approach to designing receiver arrays free of “null zones”. The main objective is enhancing worst-case scenarios, which in contrast to improving best-case scenarios, reveals significant complexities due to the need for considering numerous possible placements. We overcome this problem by establishing a design flow that leverages the simulated transfer efficiency at numerous positions throughout the surface. Our approach increased the simulated transfer efficiency at the worst position from 3.8% to 42.6%, and we confirmed these results through measurements at the extracted points.

LoRa is a low-power long-range IoT standard that uses the chirp spread spectrum technique, and we have strived to further extend its coverage by utilizing the direct device-to-device (D2D) links to construct a multi-hop relay network. In LoRa, the spreading factor (SF) is an important parameter, which not only provides great flexibility between the data rate and sensitivity but also presents a new dimension for multiple accesses. Our approach to improving the capacity of a multihop LoRa network is to attempt to off-load the data traffic into several subnets by utilizing this multiple-access dimension. Each subnet rooted at a sink node is allocated a specific SF on the basis of network clustering. This enables packet transmission in parallel with multiple SFs to become feasible. To allow such parallel transmissions, our considerations are: 1) ensuring the connectivity of all subnets; 2) off-loading the traffic according to the number of nodes, data rates, and network topologies of each subnet; and 3) shortening the airtime of each subnet by reducing the hop count. Toward these objectives, we present a tree-based SF clustering algorithm (TSCA) to conduct SF allocation in a multihop LoRa network. The TSCA focuses on balancing the airtime between the subnets while ensuring connectivity. Furthermore, we use simulations to show that our approach can significantly increase the network performance compared with other approaches. We additionally deploy a real-chip experiment to evaluate the feasibility of parallel transmission in practice.