To achieve highly efficient spectrum usage, dynamic sharing of scarce spectrum resources has recently become the subject of intense discussion. The technologies of dynamic spectrum sharing (DSS) have already been adopted or are scheduled to be adopted in a number of countries, and Japan is no exception. The authors and organizations collaborating in the research and development project being undertaken in Japan have studied a novel DSS system positioned between the fifth-generation mobile communication system (5G system) and different incumbent radio systems. Our DSS system has three characteristics. (1) It detects dynamically unused sharable spectrums (USSs) of incumbent radio systems for the space axis by using novel propagation models and estimation of the transmitting location with radio sensor information. (2) It manages USSs for the time axis by interference calculation with propagation parameters, fair assignment and future usage of USSs. (3) It utilizes USSs for the spectrum axis by using methods that decrease interference for lower separation distances. In this paper, we present an overview and the technologies of our DSS system and its applications in Japan.

Water detection is important for machine vision applications such as visual inspection and robot motion planning. In this paper, we propose an approach to per-pixel water detection on unknown surfaces with a hyperspectral image. Our proposed method is based on the water spectral characteristics: water is transparent for visible light but translucent/opaque for near-infrared light and therefore the apparent near-infrared spectral reflectance of a surface is smaller than the original one when water is present on it. Specifically, we use a linear combination of a small number of basis vector to approximate the spectral reflectance and estimate the original near-infrared reflectance from the visible reflectance (which does not depend on the presence or absence of water) to detect water. We conducted a number of experiments using real images and show that our method, which estimates near-infrared spectral reflectance based on the visible spectral reflectance, has better performance than existing techniques.

This paper presents an analytical model that yields the unavailability of a network function when each backup server can protect two functions and can recover one of them. Previous work describes a model to deal with the case that each function can be protected only by one server. In our model, we allow each function to be protected by multiple servers to ensure function availability. This requires us to know the feasible states of a connected component and its state transitions. By adopting the divide-and-conquer method, we enumerate the feasible states of a connected component. We then classify its state transitions. Based on the obtained feasible states and the classification of the state transitions, we enumerate the feasible states incoming to and outgoing from a general state, the transfer rates, and the conditions. With those informations, we generate multiple equations about the state transitions. Finally, by solving them, we obtain the probabilities that a connected component is in each state and calculate the unavailability of a function. Numerical results show that the average unavailability of a function is reduced by 18% and 5.7% in our two examined cases by allowing each function to be protected by multiple servers.

Well annotated dataset is crucial to the training of object detectors. However, the production of finely annotated datasets for object detection tasks is extremely labor-intensive, therefore, cloud sourcing is often used to create datasets, which leads to these datasets tending to contain incorrect annotations such as inaccurate localization bounding boxes. In this study, we highlight a problem of object detection with noisy bounding box annotations and show that these noisy annotations are harmful to the performance of deep neural networks. To solve this problem, we further propose a framework to allow the network to modify the noisy datasets by alternating refinement. The experimental results demonstrate that our proposed framework can significantly alleviate the influences of noise on model performance.

Fifth generation mobile communication system (5G) mobile operators need to explore new use cases and/or applications together with vertical industries, the industries that are potential users of 5G, in order to fully exploit the new 5G capabilities in terms of its application. Vehicle-to-Everything (V2X) communications for platooning are considered to be one of new 5G use cases requiring low-latency and ultra-reliability are required. This paper presents our field trial of dynamic mode switching for 5G New Radio (NR) based V2X sidelink communications towards application to truck platooning. The authors build a field trial environment, for V2X communications of truck platooning, with actual large-size trucks and a prototype system employing 5G NR technologies, and performed some field trials in rural areas. In this paper, we introduce the 5G NR-V2X prototype system. Its most distinctive characteristic is that the prototype system is equipped with vehicle-to-vehicle (V2V) Direct communication radio interface (i.e., sidelink), in addition to the traditional radio interfaces between base station (BS) and user equipment (UE), i.e., downlink and uplink. Moreover, it is also most distinctive that the sidelink (SL) interface supports a new function of dynamic mode switching between two modes of BS In-Coverage mode (SL Mode-1) and BS Out-of-Coverage mode (SL Mode-2) in order to achieve seamless V2V communications between BS in-coverage area and BS out-of-coverage area. Then, we present the evaluation results on over-the-air latency performance on the V2V Direct communication of the prototype using SL dynamic mode switching with two experimental base station antenna sites in a public express highway environment towards application to truck platooning. The results demonstrate that our developed the SL dynamic mode switching achieves the seamless V2V Direct communications between in-coverage area and out-of-coverage area.

In this letter, we will prove that chaotic binary sequences generated by the tent map and Walsh functions are i.i.d. (independent and identically distributed) and orthogonal to each other.

Receiver selective opening (RSO) attack for public key encryption (PKE) captures a situation where one sender sends messages to multiple receivers, an adversary can corrupt a set of receivers and get their messages and secret keys. Security against RSO attack for a PKE scheme ensures confidentiality of other uncorrupted receivers' ciphertexts. Among all of the RSO security notions, simulation-based RSO security against chosen ciphertext attack (SIM-RSO-CCA security) is the strongest notion. In this paper, we explore constructions of SIM-RSO-CCA secure PKE from various computational assumptions. Toward this goal, we show that a SIM-RSO-CCA secure PKE scheme can be constructed based on an IND-CPA secure PKE scheme and a designated-verifier non-interactive zero-knowledge (DV-NIZK) argument satisfying one-time simulation soundness. Moreover, we give the first construction of DV-NIZK argument satisfying one-time simulation soundness. Consequently, through our generic construction, we obtain the first SIM-RSO-CCA secure PKE scheme under the computational Diffie-Hellman (CDH) or learning parity with noise (LPN) assumption.

In sixth-generation (6G) mobile communication system, it is expected that extreme high data rate communication with a peak data rate over 100Gbps should be provided by exploiting higher frequency bands in addition to millimeter-wave bands such as 28GHz. The higher frequency bands are assumed to be millimeter wave and terahertz wave where the extreme wider bandwidth is available compared with 5G, and hence 6G needs to promote research and development to exploit so-called terahertz wave targeting the frequency from 100GHz to 300GHz. In the terahertz wave, there are fundamental issues that rectilinearity and pathloss are higher than those in the 28GHz band. In order to solve these issues, it is very important to clarify channel characteristics of the terahertz wave and establish a channel model, to advance 6G radio access technologies suitable for the terahertz wave based on the channel model, and to develop radio-frequency device technologies for such higher frequency bands. This paper introduces a direction of studies on 6G radio access technologies to explore the higher frequency bands and technical issues on the device technologies, and then basic computer simulations in 100Gbps transmission using 100GHz band clarify a potential of extreme high data rate over 100Gbps.

In this paper, we present an algorithm that counts the number of empty quadrilaterals whose corners are chosen from a given set S of n points in general position. Our algorithm can separately count the number of convex or non-convex empty quadrilaterals in O(T) time, where T denotes the number of empty triangles in S. Note that T varies from Ω(n2) and O(n3) and the expected value of T is known to be Θ(n2) when the n points in S are chosen uniformly and independently at random from a convex and bounded body in the plane. We also show how to enumerate all convex and/or non-convex empty quadrilaterals in S in time proportional to the number of reported quadrilaterals, after O(T)-time preprocessing.

Permutation polynomials and their compositional inverses are crucial for construction of Maiorana-McFarland bent functions and their dual functions, which have the optimal nonlinearity for resisting against the linear attack on block ciphers and on stream ciphers. In this letter, we give the explicit compositional inverse of the permutation binomial $f(z)=z^{2^{r}+2}+alpha zinmathbb{F}_{2^{2r}}[z]$. Based on that, we obtain the dual of monomial bent function $f(x)={ m Tr}_1^{4r}(x^{2^{2r}+2^{r+1}+1})$. Our result suggests that the dual of f is not a monomial any more, and it is not always EA-equivalent to f.

The recent development of deep learning-based generative models has sharply intensified the interest in data synthesis and its applications. Data synthesis takes on an added importance especially for some pattern recognition tasks in which some classes of data are rare and difficult to collect. In an iris dataset, for instance, the minority class samples include images of eyes with glasses, oversized or undersized pupils, misaligned iris locations, and iris occluded or contaminated by eyelids, eyelashes, or lighting reflections. Such class-imbalanced datasets often result in biased classification performance. Generative adversarial networks (GANs) are one of the most promising frameworks that learn to generate synthetic data through a two-player minimax game between a generator and a discriminator. In this paper, we utilized the state-of-the-art conditional Wasserstein generative adversarial network with gradient penalty (CWGAN-GP) for generating the minority class of iris images which saves huge amount of cost of human labors for rare data collection. With our model, the researcher can generate as many iris images of rare cases as they want and it helps to develop any deep learning algorithm whenever large size of dataset is needed.

We propose a new lattice-based digital signature scheme MLWRSign by modifying Dilithium, which is one of the second-round candidates of NIST's call for post-quantum cryptographic standards. To the best of our knowledge, our scheme MLWRSign is the first signature scheme whose security is based on the (module) learning with rounding (LWR) problem. Due to the simplicity of the LWR, the secret key size is reduced by approximately 30% in our scheme compared to Dilithium, while achieving the same level of security. Moreover, we implemented MLWRSign and observed that the running time of our scheme is comparable to that of Dilithium.

The extended visual cryptography scheme (EVCS) proposed by Ateniese et al. is one of variations of the visual cryptography scheme such that a secret image is recovered by superimposition of certain qualified collections of shares, where cover images are visible on respective shares. In this paper, we give a new definition of the EVCS for improving visibility of the recovered secret image as well as the cover images. We formulate the problem to construct the basis matrices of the EVCS with the minimum pixel expansion as an integer programming problem. We solve the integer programming problem for general access structures with less than or equal to five participants and show that basis matrices with a smaller pixel expansion can be obtained for certain cases. We also analyze security of the EVCS meeting the new definition from an information-theoretic viewpoint. We give a condition under which any forbidden collection of shares does not reveal any additional information on not only a secret image but also the cover images that are not visible on the other shares.

In this letter, we give a recursive construction of q-ary almost periodic complementary pairs (APCPs) based on an interleaving technique of sequences and Kronercker product. Based on this construction, we obtain new quaternary APCPs with new lengths.

Fifth generation mobile communication system (5G) mobile operators need to explore new use cases and/or applications together with vertical industries, the industries which are potential users of 5G, in order to fully exploit the new 5G capabilities in terms of its application. Vehicular communications for platooning are considered to be one of new use cases of 5G whose low-latency and ultra-reliability are required. This paper presents our field evaluations on latency and reliability performance of 5G V2V Direct communication towards application to truck platooning. The authors build a field experimental environment, for V2X communications of truck platooning, with actual large-size trucks and a prototype system employing 5G New Radio (NR) technologies, and performed some field experiments in rural areas. In this paper, we introduce the 5G NR-V2X prototype system. Its most distinctive feature is that the prototype system is equipped with V2V Direct communication radio interface (i.e., sidelink), in addition to the traditional radio interfaces between BS and UE (i.e., downlink and uplink). Then, we present the field evaluation results of radio propagation environment results and over-the-air transmission performance of latency and reliability characteristics on the V2V Direct communication of the prototype in real public express highway environment including tunnel area as well as tunnel outside area, in order to assess 5G NR-V2X system applying to truck platooning. The radio propagation and the latency performance evaluation results clarify that the latency performance is degraded due to Hybrid Automatic Repeat reQuest (HARQ) retransmission at the outside of tunnel more possibly than the inside of tunnel, since larger path loss values can be observed at the outside of tunnel than the inside of tunnel, in V2V Direct communications of truck platooning. The over-the-air latency and reliability evaluation results confirm that it is important to set an appropriate maximum number of HARQ retransmissions since there is a trade-off problem in order to realize low latency and high reliability simultaneously.

Predicting the malfunction timing of wind turbines is essential for maintaining the high profitability of the wind power generation business. Machine learning methods have been studied using condition monitoring system data, such as vibration data, and supervisory control and data acquisition (SCADA) data, to detect and predict anomalies in wind turbines automatically. Autoencoder-based techniques have attracted significant interest in the detection or prediction of anomalies through unsupervised learning, in which the anomaly pattern is unknown. Although autoencoder-based techniques have been proven to detect anomalies effectively using relatively stable SCADA data, they perform poorly in the case of deteriorated SCADA data. In this letter, we propose a power-curve filtering method, which is a preprocessing technique used before the application of an autoencoder-based technique, to mitigate the dirtiness of SCADA data and improve the prediction performance of wind turbine degradation. We have evaluated its performance using SCADA data obtained from a real wind-farm.

Iterative block decision feedback equalization with hard-decision feedback (HD-IBDFE) was proposed for single-carrier transmission with frequency-domain equalization (SC-FDE). The detection performance hinges upon not only error propagation, but also the accuracy of estimating the parameters used to re-compute the equalizer coefficients at each iteration. In this paper, we use the erasure zone (EZ) to de-emphasize the feedback values when the hard decisions are not reliable. EZ use also enables a more accurate, and yet computationally more efficient, parameter estimation method than HD-IBDFE. We show that the resulting equalizer coefficients share the same mathematical form as that of the HD-IBDFE, thereby preserving the merit of not requiring matrix inverse operations in calculating the equalizer coefficients. Simulations show that, by using the EZ and the proposed parameter estimation method, a significant performance improvement over the conventional HD-IBDFE can be achieved, but with lower complexity.

Air traffic management (ATM) systems around the world are being modernized to accommodate shifts towards performance- and trajectory-based operations. These shifts will require new indices for safety, efficiency and complexity. The authors have been developing an index for evaluating air traffic control (ATC) difficulty that utilizes the relative positions and velocity vectors of aircraft pairs as input data. Prior to practical application of the index, it is necessary to understand the effects of input data error, i.e. errors in the positions and velocities of a pair of aircraft, on the estimated difficulty value. Two sensitivity analyses were therefore performed for a pair of aircraft cruising at constant speeds on intersecting linear tracks at the same altitude. Sensitivity analysis examines how uncertainty in inputs relates to uncertainty in outputs. Firstly, an analysis of propagation error was carried out. The formula of the propagation error at a certain point was derived based on the assumed input error, and the distribution of propagation error was investigated for all possible situations and compared with the distribution of difficulty values to clarify its characteristics. Secondly, a sensitivity analysis based on variance was carried out that evaluated the effect of each input parameter using a conditional variance value called the Sobol indices. Using a Monte Carlo method, we investigated the effect of each input parameter on the calculated difficulty value for all possible situations of aircraft pairs on intersecting trajectories. As a result, it was found that the parameter that most affects the difficulty value is the intersection angle of the trajectories.

This paper describes the development of superconductor-insulator-superconductor (SIS) mixers for the Atacama Large Millimeter/submillimeter Array (ALMA) from the device point of view. During the construction phase of ALMA, the National Astronomical Observatory of Japan (NAOJ) successfully fabricated SIS mixers to meet the stringent ALMA noise temperature requirements of less than 230 K (5 times the quantum noise) for Band 10 (787-950 GHz) in collaboration with the National Institute of Information and Communications Technology. Band 10 covers the highest frequency band of ALMA and is recognized as the most difficult band in terms of superconducting technology. After the construction, the NAOJ began development studies for ALMA enhancement such as wideband and multibeam SIS mixers according to top-level science requirements, which are also presented.

This paper proposes a physical-layer cell identity (PCID) detection method that uses joint estimation of the frequency offset and secondary synchronization signal (SSS) sequence for the 5G new radio (NR) initial access with beamforming transmission at a base station. Computer simulation results show that using the PCID detection method with the proposed joint estimation yields an almost identical PCID detection probability as the primary synchronization signal (PSS) detection probability at an average received signal-to-noise ratio (SNR) of higher than approximately -5dB suggesting that the residual frequency offset is compensated to a sufficiently low level for the SSS sequence estimation. It is also shown that the PCID detection method achieves a high PCID detection probability of greater than 90% and 50% at the carrier frequency of 30 and 50GHz, respectively, at the average received SNR of 0dB for the frequency stability of a user equipment oscillator of 3ppm.