We evaluated soft-error tolerance by heavy-ion irradiation test on three-types of flip-flops (FFs) named the standard FF (STDFF), the dual feedback recovery FF (DFRFF), and the DFRFF with long delay (DFRFFLD) in 22 and 65 nm fully-depleted silicon on insulator (FD-SOI) technologies. The guard-gate (GG) structure in DFRFF mitigates soft errors. A single event transient (SET) pulse is removed by the C-element with the signal delayed by the GG structure. DFRFFLD increases the GG delay by adding two more inverters as delay elements. We investigated the effectiveness of the GG structure in 22 and 65 nm. In 22 nm, Kr (40.3 MeV-cm2/mg) and Xe (67.2 MeV-cm2/mg) irradiation tests revealed that DFRFFLD has sufficient soft-error tolerance in outer space. In 65 nm, the relationship between GG delay and CS reveals the GG delay time which no error was observed under Kr irradiation.

Orthogonal frequency division multiplexing with index modulation (OFDM-IM) is a novel scheme where the information bits are conveyed through the subcarrier activation pattern (SAP) and the symbols on the active subcarriers. Specifically, the subcarriers are partitioned into many subblocks and the subcarriers in each subblock can have two states, active or idle. Unfortunately, OFDM-IM inherits the high peak-to-average power ratio (PAPR) problem from the classical OFDM. The OFDM-IM signal with high PAPR induces in-band distortion and out-of-band radiation when it passes through high power amplifier (HPA). Recently, there are attempts to reduce PAPR by exploiting the unique structure of OFDM-IM, which is adding dither signals in the idle subcarriers. The most recent work dealing with the dither signals is using dithers signals with various amplitude constraints according to the characteristic of the corresponding OFDM-IM subblock. This is reasonable because OFDM subblocks have distinct levels of robustness against noise. However, the amplitude constraint in the recent work is efficient for only additive white Gaussian noise (AWGN) channels and cannot be used for maximum likelihood (ML) detection. Therefore, in this paper, based on pairwise error probability (PEP) analysis, a specific constraint for the dither signals is derived over a Rayleigh fading channel.

Direct-current biased optical orthogonal frequency division multiplexing (DCO-OFDM) converts bipolar OFDM signals into unipolar non-negative signals by introducing a high DC bias, which satisfies the requirement that the signal transmitted by intensity modulated/direct detection (IM/DD) must be positive. However, the high DC bias results in low power efficiency of DCO-OFDM. An adaptively biased optical OFDM was proposed, which could be designed with different biases according to the signal amplitude to improve power efficiency in this letter. The adaptive bias does not need to be taken off deliberately at the receiver, and the interference caused by the adaptive bias will only be placed on the reserved subcarriers, which will not affect the effective information. Moreover, the proposed OFDM uses Hartley transform instead of Fourier transform used in conventional optical OFDM, which makes this OFDM have low computational complexity and high spectral efficiency. The simulation results show that the normalized optical bit energy to noise power ratio (Eb(opt)/N0) required by the proposed OFDM at the bit error rate (BER) of 10-3 is, on average, 7.5 dB and 3.4 dB lower than that of DCO-OFDM and superimposed asymmetrically clipped optical OFDM (ACO-OFDM), respectively.

Use case descriptions describe features consisting of multiple concepts with following a procedural flow. Because existing feature location techniques lack a relation between concepts in such features, it is difficult to identify the concepts in the source code with high accuracy. This paper presents a technique to locate concepts in a feature described in a use case description consisting of multiple use case steps using dependency between them. We regard each use case step as a description of a concept and apply an existing concept location technique to the descriptions of concepts and obtain lists of modules. Also, three types of dependencies: time, call, and data dependencies among use case steps are extracted based on their textual description. Modules in the obtained lists failing to match the dependency between concepts are filtered out. Thus, we can obtain more precise lists of modules. We have applied our technique to use case descriptions in a benchmark. Results show that our technique outperformed baseline setting without applying the filtering.

An optical mode multiplexer was newly designed and fabricated using LiNbO3 waveguides. The multiplexer consists of an asymmetric directional coupler capable of achieving the phase-matching condition by the voltage adjustment. The mode conversion efficiency between TM0 and TM1 modes was quantitatively measured to be 0.86 at maximum.

A 150 GHz fundamental oscillator employing an inter-stage matching network based on a transmission line is presented in this letter. The proposed oscillator consists of a two-stage common-emitter amplifier loop, whose inter-stage connections are optimized to meet the oscillation condition. The oscillator is designed in a 130-nm SiGe BiCMOS process that offers fT and fMAX of 350 GHz and 450 GHz. According to simulation results, an output power of 3.17 dBm is achieved at 147.6 GHz with phase noise of -115 dBc/Hz at 10 MHz offset and figure-of-merit (FoM) of -180 dBc/Hz.

We have realized a design automation platform of hardware accelerator for pairing operation over multiple elliptic curve parameters. Pairing operation is one of the fundamental operations to realize functional encryption. However, known as a computational complexity-heavy algorithm. Also because there have been not yet identified standard parameters, we need to choose curve parameters based on the required security level and affordable hardware resources. To explore this design optimization for each curve parameter is essential. In this research, we have realized an automated design platform for pairing hardware for such purposes. Optimization results show almost equivalent to those prior-art designs by hand.

Synthesis problems on multiplayer non-zero-sum games (MG) with multiple environment players that behave rationally are the problems to find a good strategy of the system and have been extensively studied. This paper concerns the synthesis problems on stochastic MG (SMG), where a special controller other than players, called nature, which chooses a move in its turn randomly, may exist. Two types of synthesis problems on SMG exist: cooperative rational synthesis problem (CRSP) and non-cooperative rational synthesis problem (NCRSP). The rationality of environment players is modeled by Nash equilibria, and CRSP is the problem to decide whether there exists a Nash equilibrium that gives the system a payoff not less than a given threshold. Ummels et al. studied the complexity of CRSP for various classes of objectives and strategies of players. CRSP fits the situation where the system can make a suggestion of a strategy profile (a tuple of strategies of all players) to the environment players. However, in real applications, the system may rarely have an opportunity to make suggestions to the environment, and thus CRSP is optimistic. NCRSP is the problem to decide whether there exists a strategy σ0 of the system satisfying that for every strategy profile of the environment players that forms a 0-fixed Nash equilibrium (a Nash equilibrium where the system's strategy is fixed to σ0), the system obtains a payoff not less than a given threshold. In this paper, we investigate the complexity of NCRSP for positional (i.e. pure memoryless) strategies. We consider ω-regular objectives as the model of players' objectives, and show the complexity results of the problem for several subclasses of ω-regular objectives. In particular, the problem for terminal reachability (TR) objectives is shown to be Σp2-complete.

Software development companies must consider employees' job satisfaction and turnover intentions. To explain the related factors, this study focused on future perspective index (FPI). FPI was assumed to relate positively to satisfaction and negatively to turnover. In the analysis, we compared the FPI with existing factors that are considered to be related to job satisfaction. We discovered that the FPI was promising for enhancing explanatory power, particularly when analyzing satisfaction.

Representation learning is a crucial and complex task for multivariate time series data analysis, with a wide range of applications including trend analysis, time series data search, and forecasting. In practice, unsupervised learning is strongly preferred owing to sparse labeling. However, most existing studies focus on the representation of individual subseries without considering relationships between different subseries. In certain scenarios, this may lead to downstream task failures. Here, an unsupervised representation learning model is proposed for multivariate time series that considers the semantic relationship among subseries of time series. Specifically, the covariance calculated by the Gaussian process (GP) is introduced to the self-attention mechanism, capturing relationship features of the subseries. Additionally, a novel unsupervised method is designed to learn the representation of multivariate time series. To address the challenges of variable lengths of input subseries, a temporal pyramid pooling (TPP) method is applied to construct input vectors with equal length. The experimental results show that our model has substantial advantages compared with other representation learning models. We conducted experiments on the proposed algorithm and baseline algorithms in two downstream tasks: classification and retrieval. In classification task, the proposed model demonstrated the best performance on seven of ten datasets, achieving an average accuracy of 76%. In retrieval task, the proposed algorithm achieved the best performance under different datasets and hidden sizes. The result of ablation study also demonstrates significance of semantic relationship in multivariate time series representation learning.

In the research of machine reading comprehension of Japanese how-to tip QA tasks, conventional extractive machine reading comprehension methods have difficulty in dealing with cases in which the answer string spans multiple locations in the context. The method of fine-tuning of the BERT model for machine reading comprehension tasks is not suitable for such cases. In this paper, we trained a generative machine reading comprehension model of Japanese how-to tip by constructing a generative dataset based on the website “wikihow” as a source of information. We then proposed two methods for multi-task learning to fine-tune the generative model. The first method is the multi-task learning with a generative and extractive hybrid training dataset, where both generative and extractive datasets are simultaneously trained on a single model. The second method is the multi-task learning with the inter-sentence semantic similarity and answer generation, where, drawing upon the answer generation task, the model additionally learns the distance between the sentences of the question/context and the answer in the training examples. The evaluation results showed that both of the multi-task learning methods significantly outperformed the single-task learning method in generative question-and-answer examples. Between the two methods for multi-task learning, that with the inter-sentence semantic similarity and answer generation performed the best in terms of the manual evaluation result. The data and the code are available at https://github.com/EternalEdenn/multitask_ext-gen_sts-gen.

This study investigates the improvement of the channel capacity of 5-GHz-band multiple-input multiple-output (MIMO) communication using microwave-guided modes propagating along a polyvinyl chloride (PVC) pipe wall for a buried pipe inspection robot. We design a planar Yagi-Uda antenna to reduce transmission losses in communication with PVC pipe walls as propagation paths. Coupling efficiency between the antenna and a PVC pipe is improved by attaching a PVC adapter with the same curvature as the PVC pipe's inner wall to the Yagi-Uda antenna to eliminate any gap between the antenna and the inner wall of the PVC pipe. The use of a planar Yagi-Uda antenna with a PVC adaptor decreases the transmission loss of a 5-GHz-band microwave signal propagating along a 1-m-lomg straight PVC pipe wall by 7dB compared to a dipole antenna. The channel capacity of a 2×2 MIMO system using planar Yagi-Uda antennas is more than twice that of the system using dipole antennas.

In a field of biomedical engineering, not only low-pass filters for high frequency elimination but also notch filters for suppressing powerline interference are necessary to process low-frequency biosignals. For integration of low-frequency filters, chip implementation of large capacitances is major difficulty. As methods to enhance capacitances with small chip area, use of capacitance multipliers is effective. This letter describes design consideration of integrated low-frequency low-pass notch filter employing capacitance multipliers. Two main points are presented. Firstly, a new floating capacitance multiplier is proposed. Secondly, a technique to reduce the number of capacitance multipliers is proposed. By this technique, power consumption is reduced. The proposed techniques are applied a 3rd order low-pass notch filter. Simulation results show the effectiveness of the proposed techniques.

The novel optical path routing architecture named flexible waveband routing networks is reviewed in this paper. The nodes adopt a two-stage path routing scheme where wavelength selective switches (WSSs) bundle optical paths and form a small number of path groups and then optical switches without wavelength selectivity route these groups to desired outputs. Substantial hardware scale reduction can be achieved as the scheme enables us to use small scale WSSs, and even more, share a WSS by multiple input cores/fibers through the use of spatially-joint-switching. Furthermore, path groups distributed over multiple bands can be switched by these optical switches and thus the adaptation to multi-band transmission is straightforward. Network-wide numerical simulations and transmission experiments that assume multi-band transmission demonstrate the validity of flexible waveband routing.

To cope with the drastic increase in traffic, space division multiplexing elastic optical networks (SDM-EONs) have been investigated. In multicore fiber environments that realize SDM-EONs, crosstalk (XT) occurs between optical paths transmitted in the same frequency slots of adjacent cores, and the quality of the optical paths is degraded by the mutual influence of XT. To solve this problem, we propose a core and spectrum assignment method that introduces the concept of prohibited frequency slots to protect the degraded optical paths. First-fit-based spectrum resource allocation algorithms, including our previous study, have the problem that only some frequency slots are used at low loads, and XT occurs even though sufficient frequency slots are available. In this study, we propose a core and spectrum assignment method that introduces the concepts of “adjacency criterion” and “XT budget” to suppress XT at low and middle loads without worsening the path blocking rate at high loads. We demonstrate the effectiveness of the proposed method in terms of the path blocking rate using computer simulations.

A city-level digital twin is a critical enabling technology to construct a smart city that helps improve citizens' living conditions and quality of life. Currently, research and development regarding the digital replica city are pursued worldwide. However, many research projects only focus on creating the 3D city model. A mechanism to involve key players, such as data providers, service providers, and application developers, is essential for constructing the digital replica city and producing various city applications. Based on this motivation, the authors of this paper are pursuing a research project, namely Decentralized Digital Twin EcoSystem (D2EcoSys), to create an ecosystem to advance (and self-grow) the digital replica city regarding time and space directions, city services, and values. This paper introduces an overview of the D2EcoSys project: vision, problem statement, and approach. In addition, the paper discusses the recent research results regarding networking technologies and demonstrates an early testbed built in the Kashiwa-no-ha smart city.

Many nodes in Internet of Things (IoT) rely on batteries for power. Additionally, the demand for executing compute-intensive and latency-sensitive tasks is increasing for IoT nodes. In some practical scenarios, the computation tasks of WDs have the non-separable characteristic, that is, binary offloading strategies should be used. In this paper, we focus on the design of an efficient binary offloading algorithm that minimizes system energy consumption (EC) for TDMA-based wireless-powered multi-access edge computing networks, where WDs either compute tasks locally or offload them to hybrid access points (H-APs). We formulate the EC minimization problem which is a non-convex problem and decompose it into a master problem optimizing binary offloading decision and a subproblem optimizing WPT duration and task offloading transmission durations. For the master problem, a DRL based method is applied to obtain the near-optimal offloading decision. For the subproblem, we firstly consider the scenario where the nodes do not have completion time constraints and obtain the optimal analytical solution. Then we consider the scenario with the constraints. By jointly using the Golden Section Method and bisection method, the optimal solution can be obtained due to the convexity of the constraint function. Simulation results show that the proposed offloading algorithm based on DRL can achieve the near-minimal EC.

Quantum key distribution or secret key distribution (SKD) has been studied to deliver a secrete key for secure communications, whose security is physically guaranteed. For practical deployment, such systems are desired to be overlaid onto existing wavelength-multiplexing transmission systems, without using a dedicated transmission line. This study analytically investigates the feasibility of the intensity-modulation/direction-detection (IM/DD) SKD scheme being wavelength-multiplexed with conventional wavelength-division-multiplexed (WDM) signals, concerning spontaneous Raman scattering light from conventional optical signals. Simulation results indicate that IM/DD SKD systems are not degraded when they are overlaid onto practically deployed dense WDM transmission systems in the C-band, owing to the feature of the IM/DD SKD scheme, which uses a signal light with an intensity level comparable to conventional optical signals unlike conventional quantum key distribution schemes.

Recent character detectors have been modeled using deep neural networks and have achieved high performance in various tasks, such as text detection in natural scenes and character detection in historical documents. However, existing methods cannot achieve high detection accuracy for wooden slips because of their multi-scale character sizes and aspect ratios, high character density, and close character-to-character distance. In this study, we propose a new U-Net-based character detection and localization framework that learns character regions and boundaries between characters. The proposed method enhances the learning performance of character regions by simultaneously learning the vertical and horizontal boundaries between characters. Furthermore, by adding simple and low-cost post-processing using the learned regions of character boundaries, it is possible to more accurately detect the location of a group of characters in a close neighborhood. In this study, we construct a wooden slip dataset. Experiments demonstrated that the proposed method outperformed existing character detection methods, including state-of-the-art character detection methods for historical documents.

We propose a non-photorealistic rendering method for automatically generating point-light-style (PLS) images from photographic images using peripheral difference filters with different window sizes. The proposed method can express PLS patterns near the edges of photographic images as dots. To verify the effectiveness of the proposed method, experiments were conducted to visually confirm PLS images generated from various photographic images.