This letter simplifies and analyze existing state evolution recursions for conjugate gradient. The proposed simplification reduces the complexity for solving the recursions from cubic order to square order in the total number of iterations. The simplified recursions are still catastrophically sensitive to numerical errors, so that arbitrary-precision arithmetic is used for accurate evaluation of the recursions.

We propose a non-photorealistic rendering method to automatically generate reaction-diffusion-pattern-like images from photographic images. The proposed method uses smoothing filter with a circular window, and changes the size of the circular window depending on the position in photographic images. By partially changing the size of the circular window, the size of reaction-diffusion patterns can be changed partially. To verify the effectiveness of the proposed method, experiments were conducted to apply the proposed method to various photographic images.

In this paper, we propose a heuristic planning method to efficiently accommodate dynamic multilayer path (MLP) demand in multilayer networks consisting of a Time Division Multiplexing (TDM) layer and a Wavelength Division Multiplexing (WDM) layer; the goal is to achieve the flexible accommodation of increasing capacity and diversifying path demands. In addition to the grooming of links at the TDM layer and the route and frequency slots for the elastic optical path to be established, MLP requires the selection of an appropriate operational mode, consisting of a combination of modulation formats and symbol rates supported by digital coherent transceivers. Our proposed MLP planning method defines a planning policy for each of these parameters and embeds the values calculated by combining these policies in an auxiliary graph, which allows the planning parameters to be calculated for MLP demand requirements in a single step. Simulations reveal that the choice of operational mode significantly reduces the blocking probability and demonstrate that the edge weights in the auxiliary graph allow MLP planning with characteristics tailored to MLP demand and network requirements. Furthermore, we quantitatively evaluate the impact of each planning policy on the MLP planning results.

BLS signature is an elliptic curve cryptography with an attractive feature that signatures can be aggregated and shortened. We have designed two ASIC architectures for hashing to the elliptic curve and pairing to minimize the latency. Also, the designs are optimized for BLS12-381, a relatively new and safe curve.

To achieve the extreme high data rate and extreme coverage extension requirements of 6G wireless communication, new spectrum in sub-THz (100-300GHz) and non-terrestrial network (NTN) are two of the macro trends of 6G candidate technologies, respectively. However, non-linearity of power amplifiers (PA) is a critical challenge for both sub-THz and NTN. Therefore, high power efficiency (PE) or low peak to average power ratio (PAPR) waveform design becomes one of the most significant 6G research topics. Meanwhile, high spectral efficiency (SE) and low out-of-band emission (OOBE) are still important key performance indicators (KPIs) for 6G waveform design. Single-carrier waveform discrete Fourier transform spreading orthogonal frequency division multiplexing (DFT-s-OFDM) has achieved many research interests due to its high PE, and it has been supported in 5G New Radio (NR) when uplink coverage is limited. So DFT-s-OFDM can be regarded as a candidate waveform for 6G. Many enhancement schemes based on DFT-s-OFDM have been proposed, including null cyclic prefix (NCP)/unique word (UW), frequency-domain spectral shaping (FDSS), and time-domain compression and expansion (TD-CE), etc. However, there is no unified framework to be compatible with all the enhancement schemes. This paper firstly provides a general description of the 6G candidate waveforms based on DFT-s-OFDM enhancement. Secondly, the more flexible TD-CE supporting methods for unified non-orthogonal waveform (uNOW) are proposed and discussed. Thirdly, a unified waveform framework based on DFT-s-OFDM structure is proposed. By designing the pre-processing and post-processing modules before and after DFT in the unified waveform framework, the three technical methods (NCP/UW, FDSS, and TD-CE) can be integrated to improve three KPIs of DFT-s-OFDM simultaneously with high flexibility. Then the implementation complexity of the 6G candidate waveforms are analyzed and compared. Performance of different DFT-s-OFDM enhancement schemes is investigated by link level simulation, which reveals that uNOW can achieve the best PAPR performance among all the 6G candidate waveforms. When considering PA back-off, uNOW can achieve 124% throughput gain compared to traditional DFT-s-OFDM.

In this study, vertically aligned carbon nanotubes (VA-CNTs) were grown from filler-added LB films with accumulated AlFe2O4 nanoparticles and palmitic acid (C16) as the filler molecule after different hydrogen reduction temperatures of 500°C and 750°C, and the grown VA-CNTs were compared and evaluated. As a result, VA-CNTs were approximately doubled in length after 500°C hydrogen reduction compared to 750°C hydrogen reduction when AlFe2O4 NPs were used. On the other hand, when the catalyst area ratio was decreased by using palmitic acid, i.e., the distance between CNTs was increased, VA-CNTs rapidly shortened after 500°C hydrogen reduction, and VA-CNTs were no longer obtained even in the range where VA-CNTs were obtained in 750°C hydrogen reduction. The inner and outer diameters of VA-CNTs decreased with decreasing catalyst area ratio at 750°C hydrogen reduction and tended to increase at 500°C hydrogen reduction. The morphology of the catalyst nanoparticles after CVD was observed to change significantly depending on the hydrogen reduction temperature and catalyst area ratio. These observations indicate that the state of the catalyst nanoparticles immediately before the CNT growth process greatly affects the physical properties of the CNTs.

An enzymatic biofuel cell (BFC) that uses lactic acid in human sweat as fuel to generate electricity is an attractive power source for wearable devices. A BFC capable of generating electricity with human sweat has been developed. It comprised a flexible tattoo seal type battery with silver oxide vapor deposited on a flexible material and conductive carbon nanotubes printed on it. The anode and cathode in this battery were arranged in a plane (planar type). This work proposes a thin laminated enzymatic BFC by inserting a cellulose nanofiber (CNF) sheet between two electrodes to absorb human sweat (stack-type). Optimization of the anode and changing the arrangement of electrodes from planar to stack type improved the output and battery life. The stack type is 43.20μW / cm2 at 180mV, which is 1.25 times the maximum power density of the planar type.

In a free-space method using a pair of horn antennas with dielectric lenses, we demonstrated that the permittivity of a sample can be estimated with good accuracy by equalizing a measured transmission coefficient of a sample to a transmission coefficient for a Gaussian beam, which is approximately equal to the transmission coefficient for a plane wave multiplied by a term that changes the phase. In this permittivity estimation method, because the spot size at the beam waist in a Gaussian beam needs to be determined, we proposed an estimation method of the spot size by employing the measurement of the Line in Thru-Reflect-Line calibration; thus, no additional measurement is required. The permittivity estimation method was investigated for the E-band (60-90 GHz), and it was demonstrated that the relative permittivity of air with a thickness of 2mm and a sample with the relative permittivity of 2.05 and a thickness of 1mm is estimated with errors less than ±0.5% and ±0.2%, respectively. Moreover, in measuring a sample without displacing the receiving horn antenna to avoid the error in measurement, we derived an expression of the permittivity estimation for S parameters measured using a vector network analyzer, and demonstrated that the measurement of a sample without antenna displacement is valid.

Mobility as a Service (MaaS) is expected to spread globally and in Japan as a solution for social issues related to transportation. Researchers have conducted MaaS trials in several cities. However, only a few trials have reached full-scale practical use. Therefore, it is essential to clarify issues such as the business model and user acceptability and seek solutions to social problems rather than simply conducting trials. This paper describes the introduction of a MaaS project supported by the Japanese government known as the “Smart Mobility Challenge” project, conducted in 2020 and 2021. We employed five themes necessary for social implementation from the first trial of this MaaS project. As a consortium, we also promoted regional demonstrations by soliciting regional applications based on these five themes. In addition, we conducted fundamental research using data from the MaaS projects to clarify local transportation issues in detail, collect residents' mobile behavior data, and assess the project's effects on the participant's happiness. We employed the life-space assessment method to investigate the spread of the residents' behavioral life-space resulting from using mobility services. The spread of the life-space mobility before and after using mobility services confirmed an expansion of the life-space because of specific services. Moreover, we conducted questionnaire surveys and clarified the relationships between life-space assessment, human characteristics, and subjective happiness using path analysis. We also conducted a persona-based approach in addition to objective data collection using GPS and wearable monitors and a web-based questionnaire. We found differences between the actual participants and participants assumed by local governments. We conducted interviews and developed tips for improving mobility service. We propose that qualitative data help clarify the image of mobility services that meet the residents' needs.

To simultaneously enhance data rate and physical layer security (PLS) for low-luminance smartphone screen to camera uplink communication, space division multiplexing using high-luminance cell-size reduction arrangement is numerically analyzed and experimentally verified. The uplink consists of a low-luminance smartphone screen and an indoor telephoto camera at a long distance of 3.5 meters. The high-luminance cell-size reduction arrangement avoids the influence of spatial inter-symbol interference (ISI) and ambient light to obtain a stable low-luminance screen. To reduce the screen luminance without decreasing the screen pixel value, the arrangement reduces only the high-luminance cell area while keeping the cell spacing. In this study, two technical issues related to high-luminance cell-size reduction arrangement are solved. First, a numerical analysis and experimental results show that the high-luminance cell-size reduction arrangement is more effective in reducing the spatial ISI at low luminance than the conventional low-luminance cell arrangement. Second, in view point of PLS enhancement at wide angles, symbol error rate should be low in front of the screen and high at wide angles. A numerical analysis and experimental results show that the high-luminance cell-size reduction arrangement is more suitable for enhancing PLS at wide angles than the conventional low-luminance cell arrangement.

To obtain a full picture of potential applications for propagation-delay based X channels, it is important to obtain all feasible schemes of cyclic interference alignment including the encoder, channel instance, and decoder. However, when the dimension goes larger, theoretical analysis about this issue will become tedious and even impossible. In this letter, we propose a computer-aided solution by searching the channel space and the scheduling space, which can find all feasible schemes in details. Examples are given for some typical X channels. Computational complexity is further analyzed.

The problem caused by fake news continues to worsen in today's online social networks. Intuitively, it seems effective to issue corrections as a countermeasure. However, corrections can, ironically, strengthen attention to fake news, which worsens the situation. This paper proposes a model for describing the interaction between fake news and the corrections as a reaction-diffusion system; this yields the mechanism by which corrections increase attention to fake news. In this model, the emergence of groups of users who believe in fake news is understood as a Turing pattern that appears in the activator-inhibitor model. Numerical calculations show that even if the network structure has no spatial bias, the interaction between fake news and the corrections creates groups that are strongly interested in discussing fake news. Also, we propose and evaluate a basic strategy to counter fake news.

Vehicles on the road are expected to connect continuously to the Internet at sufficiently high speeds, e.g., several Mbps or higher, to support multimedia applications. However, even when passing through a well-facilitated city area, Internet access can be unreliable and even disconnected if the travel speed is high. We therefore propose a network path selection technique to meet network throughput requirements. The proposed technique is based on the attractor selection model and enables vehicles to switch the path from a route connecting directly to a cellular network to a relay type through neighboring vehicles for Internet access. We also develop a mechanism that prevents frequent path switching when the performance of all available paths does not meet the requirements. We conduct field evaluations by platooning two vehicles in a real-world driving environment and confirm that the proposed technique maintains the required throughput of up to 7Mbps on average. We also evaluated our proposed technique by extensive computer simulations of up to 6 vehicles in a platoon. The results show that increasing platoon length yields a greater improvement in throughput, and the mechanism we developed decreases the rate of path switching by up to 25%.

Parallel line feeder (PLF) consisting of a two-wire transmission line operating in the MHz band has been proposed as a wide-coverage short-distance wireless charging. In the MHz band, a PLF of several meters suffers from standing wave effect, resulting in fluctuation in power transfer efficiency accordingly to the receiver's position. This paper studies a modified version of the system, where the PLF is divided into individually compensated segments to mitigate the standing wave effect. Modelling the PLF as a lossy transmission line, this paper theoretically shows that if the segments' lengths are properly determined, it is able to improve and stabilize the efficiency for all positions. Experimental results at 27.12 MHz confirm the theoretical analysis and show that a fairly high efficiency of 70% can be achieved.

With the widespread use of indoor positioning technology, the need for high-precision positioning services is rising; nevertheless, there are several challenges, such as the difficulty of simulating the distribution of interior location data and the enormous inaccuracy of probability computation. As a result, this paper proposes three different neural network model comparisons for indoor location based on WiFi fingerprint - indoor location algorithm based on improved back propagation neural network model, RSSI indoor location algorithm based on neural network angle change, and RSSI indoor location algorithm based on depth neural network angle change - to raise accurately predict indoor location coordinates. Changing the action range of the activation function in the standard back-propagation neural network model achieves the goal of accurately predicting location coordinates. The revised back-propagation neural network model has strong stability and enhances indoor positioning accuracy based on experimental comparisons of loss rate (loss), accuracy rate (acc), and cumulative distribution function (CDF).

QoS of applications is essential for content providers, and it is required to improve the end-to-end communication quality from a content provider to users. Generally, a content provider's data center network is connected to multiple ASes and has multiple egress paths to reach the content user's network. However, on the Internet, the communication quality of network paths outside of the provider's administrative domain is a black box, so multiple egress paths cannot be quantitatively compared. In addition, it is impossible to determine a unique egress path within a network domain because the parameters that affect the QoS of the content are different for each network. We propose a “Performance Aware Egress Path Discovery” method to improve QoS for content providers. The proposed method uses two techniques: Egress Peer Engineering with Segment Routing over IPv6 and Passive End-to-End Measurement. The method is superior in that it allows various metrics depending on the type of content and can be used for measurements without affecting existing systems. To evaluate our method, we deployed the Performance Aware Egress Path Discovery System in an existing content provider network and conducted experiments to provide production services. Our findings from the experiment show that, in this network, 15.9% of users can expect a 30Mbps throughput improvement, and 13.7% of users can expect a 10ms RTT improvement.

There are demands for high-speed and stable ground-to-train optical communication as a network environment for trains. The existing ground-to-train optical communication system developed by the authors uses a camera and a QPD (Quadrant photo diode) to capture beacon light. The problem with the existing system is that it is impossible to identify the ground station. In the system proposed in this paper, a beacon light modulated with the ID of the ground station is transmitted, and the ground station is identified by demodulating the image from the dual-port camera on the opposite side. In this paper, we developed an actual system and conducted experiments using a car on the road. The results showed that only one packet was lost with the ping command every 1 ms near handover. Although the communication device itself has a bandwidth of 100 Mbps, the throughput before and after the handover was about 94 Mbps, and only dropped to about 89.4 Mbps during the handover.

Let us consider a regular expression r of length m and a text string T of length n over an alphabet Σ. Then, the RE minimal substring search problem is to find all minimal substrings of T matching r. Yamamoto proposed O(mn) time and O(m) space algorithm using a Thompson automaton. In this paper, we improve Yamamoto's algorithm by introducing parallelism. The proposed algorithm runs in O(mn) time in the worst case and in O(mn/p) time in the best case, where p denotes the number of processors. Besides, we show a parameter related to the parallel time of the proposed algorithm. We evaluate the algorithm experimentally.

Convolutional Neural Networks (CNNs) have recently demonstrated outstanding performance in image retrieval tasks. Local convolutional features extracted by CNNs, in particular, show exceptional capability in discrimination. Recent research in this field has concentrated on pooling methods that incorporate local features into global features and assess the global similarity of two images. However, the pooling methods sacrifice the image's local region information and spatial relationships, which are precisely known as the keys to the robustness against occlusion and viewpoint changes. In this paper, instead of pooling methods, we propose an alternative method based on local similarity, determined by directly using local convolutional features. Specifically, we first define three forms of local similarity tensors (LSTs), which take into account information about local regions as well as spatial relationships between them. We then construct a similarity CNN model (SCNN) based on LSTs to assess the similarity between the query and gallery images. The ideal configuration of our method is sought through thorough experiments from three perspectives: local region size, local region content, and spatial relationships between local regions. The experimental results on a modified open dataset (where query images are limited to occluded ones) confirm that the proposed method outperforms the pooling methods because of robustness enhancement. Furthermore, testing on three public retrieval datasets shows that combining LSTs with conventional pooling methods achieves the best results.

The MPEG Immersive Video (MIV) standard for immersive video coding provides users with an immersive sense of 6 degrees of freedom (6DoF) of view position and orientation by efficiently compressing multiview video acquired from different positions in a limited 3D space. In the MIV reference software called Test Model for Immersive Video (TMIV), the number of pixels to be compressed and transmitted is reduced by removing inter-view redundancy. Therefore, the occupancy information that indicates whether each pixel is valid or invalid must also be transmitted to the decoder for viewport rendering. The occupancy information is embedded in a geometry atlas and transmitted to the decoder side. At this time, to prevent occupancy errors that may occur during the compression of the geometry atlas, a guard band is set in the depth dynamic range. Reducing this guard band can improve the rendering quality by allowing a wider dynamic range for depth representation. Therefore, in this paper, based on the analysis of occupancy error of the current TMIV, two methods of occupancy error correction which allow depth dynamic range extension in the case of computer-generated (CG) sequences are presented. The experimental results show that the proposed method gives an average 2.2% BD-rate bit saving for CG compared to the existing TMIV.