This paper investigates an adversarial model in the scenario of private information retrieval (PIR) from n coded storage servers, called Byzantine adversary. The Byzantine adversary is defined as the one altering b server responses and erasing u server responses to a user's query. In this paper, two types of Byzantine adversaries are considered; 1) the classic omniscient type that has the full knowledge on n servers as considered in existing literature, and 2) the reasonable limited-knowledge type that has information on only b+u servers, i.e., servers under the adversary's control. For these two types, this paper reveals that the resistance of a PIR scheme, i.e., the condition of b and u to correctly obtain the desired message, can be expressed in terms of a code parameter called the coset distance of linear codes employed in the scheme. For the omniscient type, the derived condition expressed by the coset distance is tighter and more precise than the estimation of the resistance by the minimum Hamming weight of the codes considered in existing researches. Furthermore, this paper also clarifies that if the adversary is limited-knowledge, the resistance of a PIR scheme could exceed that for the case of the omniscient type. Namely, PIR schemes can increase their resistance to Byzantine adversaries by allowing the limitation on adversary's knowledge.

In order to upgrade the refresh rate about High-Resolution (1280×1024) OLED-on-Silicon (OLEDoS) microdisplay, this paper discusses one compression scan strategy by reducing scan time redundancy. This scan strategy firstly compresses the low-bit gray level scan serial as one unit; second, the scan unit is embedded into the high-bit gray level serial and new scan sequence is generated. Furthermore, micro-display platform is designed to verify the scan strategy performance. The experiment shows that this scan strategy can deal with 144Hz refresh rate, which is obviously faster than the traditional scan strategy.

This paper investigates the sum rate (SR) maximization problem for downlink cooperative non-orthogonal multiple access (C-NOMA) systems with hardware impairments (HIs). The source node communicates with users via a half-duplex amplified-and-forward (HD-AF) relay with HIs. First, we derive the SR expression of the systems under HIs. Then, SR maximization problem is formulated under maximum power of the source, relay, and the minimum rate constraint of each user. As the original SR maximization problem is a non-convex problem, it is difficult to find the optimal resource allocation directly by tractional convex optimization method. We use variable substitution method to convert the non-convex SR maximization problem to an equivalent convex optimization problem. Finally, a joint power and rate allocation based on interior point method is proposed to maximize the SR of the systems. Simulation results show that the algorithm can improve the SR of the C-NOMA compared with the cooperative orthogonal multiple access (C-OMA) scheme.

Recently the data-driven learning of dynamic systems has become a promising approach because no physical knowledge is needed. Pure machine learning approaches such as Gaussian process regression (GPR) learns a dynamic model from data, with all physical knowledge about the system discarded. This goes from one extreme, namely methods based on optimizing parametric physical models derived from physical laws, to the other. GPR has high flexibility and is able to model any dynamics as long as they are locally smooth, but can not generalize well to unexplored areas with little or no training data. The analytic physical model derived under assumptions is an abstract approximation of the true system, but has global generalization ability. Hence the optimal learning strategy is to combine GPR with the analytic physical model. This paper proposes a method to learn dynamic systems using GPR with analytic ordinary differential equations (ODEs) as prior information. The one-time-step integration of analytic ODEs is used as the mean function of the Gaussian process prior. The total parameters to be trained include physical parameters of analytic ODEs and parameters of GPR. A novel method is proposed to simultaneously learn all parameters, which is realized by the fully Bayesian GPR and more promising to learn an optimal model. The standard Gaussian process regression, the ODE method and the existing method in the literature are chosen as baselines to verify the benefit of the proposed method. The predictive performance is evaluated by both one-time-step prediction and long-term prediction. By simulation of the cart-pole system, it is demonstrated that the proposed method has better predictive performances.

We investigate an interactive evolutionary computation (IEC) using multiple users' gaze information when users partially participate in each design evaluation. Many previous IEC systems have a problem that user evaluation loads are too large. Hence, we proposed to employ user gaze information for evaluating designs generated by IEC systems in order to solve this problem. In this proposed system, users just view the presented designs, not assess, then the system automatically creates users' favorite designs. With the user's gaze information, the proposed system generates coordination that can satisfy many users. In our previous study, we verified the effectiveness of the proposed system from a real system operation viewpoint. However, we did not consider the fluctuation of the users during a solution candidate evaluation. In the actual operation of the proposed system, users may change during the process due to the user interchange. Therefore, in this study, we verify the effectiveness of the proposed system when varying the users participating in each evaluation for each generation. In the experiment, we employ two types of situations as assumed in real environments. The first situation changes the number of users evaluating the designs for each generation. The second situation employs various users from the predefined population to evaluate the designs for each generation. From the experimental results in the first situation, we confirm that, despite the change in the number of users during the solution candidate evaluation, the proposed system can generate coordination to satisfy many users. Also, from the results in the second situation, we verify that the proposed system can also generate coordination which both users who participate in the coordination evaluation can more satisfy.

Relation extraction is one of the key basic tasks in natural language processing in which distant supervision is widely used for obtaining large-scale labeled data without expensive labor cost. However, the automatically generated data contains massive noise because of the wrong labeling problem in distant supervision. To address this problem, the existing research work mainly focuses on removing sentence-level noise with various sentence selection strategies, which however could be incompetent for disposing word-level noise. In this paper, we propose a novel neural framework considering both intra-sentence and inter-sentence relevance to deal with word-level and sentence-level noise from distant supervision, which is denoted as Sentence-Related Gated Piecewise Convolutional Neural Networks (SR-GPCNN). Specifically, 1) a gate mechanism with multi-head self-attention is adopted to reduce word-level noise inside sentences; 2) a soft-label strategy is utilized to alleviate wrong-labeling propagation problem; and 3) a sentence-related selection model is designed to filter sentence-level noise further. The extensive experimental results on NYT dataset demonstrate that our approach filters word-level and sentence-level noise effectively, thus significantly outperforms all the baseline models in terms of both AUC and top-n precision metrics.

The previous communication-induced checkpointing may considerably induce worthless forced checkpoints because each process receiving messages cannot obtain sufficient information related to non-causal Z-paths. This paper presents an enhanced sender-based message logging protocol applicable to any communication-induced checkpointing to lead to a high decrease of the forced checkpointing overhead of communication-induced checkpointing in an effective way while permitting no useless checkpoint. The protocol allows each process sending a message to know the exact timestamp of the receiver of the message in its logging procedures without any extra message. Simulation verifies their great efficiency of overhead alleviation regardless of communication patterns.

DAIHINMIN, which means Grand Pauper, is a popular playing-card game in Japan. TANHINMIN is a simplified variant of DAIHINMIN, which was proposed by Nishino in 2007 in order to investigate the mathematical properties of DAIHINMIN. In this paper, we consider a 2-player generalized TANHINMIN, where the deck size is arbitrary n. We present a linear-time algorithm that determines which player has a winning strategy after all cards are distributed to the players.

In a convex grid drawing of a plane graph, all edges are drawn as straight-line segments without any edge-intersection, all vertices are put on grid points and all facial cycles are drawn as convex polygons. A plane graph G has a convex drawing if and only if G is internally triconnected, and an internally triconnected plane graph G has a convex grid drawing on an (n-1)×(n-1) grid if either G is triconnected or the triconnected component decomposition tree T(G) of G has two or three leaves, where n is the number of vertices in G. An internally triconnected plane graph G has a convex grid drawing on a 2n×2n grid if T(G) has exactly four leaves. Furthermore, an internally triconnected plane graph G has a convex grid drawing on a 6n×n2 grid if T(G) has exactly five leaves. In this paper, we show that an internally triconnected plane graph G has a convex grid drawing on a 20n×16n grid if T(G) has exactly five leaves. We also present an algorithm to find such a drawing in linear time. This is the first algorithm that finds a convex grid drawing of such a plane graph G in a grid of O(n2) size.

The automatic analysis of retinal fundus images is of great significance in large-scale ocular pathologies screening, of which optic disc (OD) location is a prerequisite step. In this paper, we propose a method based on saliency detection and attention convolutional neural network for OD detection. Firstly, the wavelet transform based saliency detection method is used to detect the OD candidate regions to the maximum extent such that the intensity, edge and texture features of the fundus images are all considered into the OD detection process. Then, the attention mechanism that can emphasize the representation of OD region is combined into the dense network. Finally, it is determined whether the detected candidate regions are OD region or non-OD region. The proposed method is implemented on DIARETDB0, DIARETDB1 and MESSIDOR datasets, the experimental results of which demonstrate its superiority and robustness.

The fifth-generation (5G) mobile communications system initially introduced massive multiple-input multiple-output (M-MIMO) with analog beamforming (BF) to compensate for the larger path-loss in millimeter-wave (mmW) bands. To solve a coverage issue and support high mobility of the mmW bands, base station (BS) cooperation technologies have been investigated in high-mobility environments. However, previous works assume one mobile station (MS) scenario and analog BF that does not suppress interference among MSs. In order to improve system performance in the mmW bands, fully digital BF that includes digital precoding should be employed to suppress the interference even when MSs travel in high mobility. This paper proposes two mmW BS cooperation technologies that are inter-baseband unit (inter-BBU) and intra-BBU cooperation for the fully digital BF. The inter-BBU cooperation exploits two M-MIMO antennas in two BBUs connected to one central unit by limited-bandwidth fronthaul, and the intra-BBU cooperates two M-MIMO antennas connected to one BBU with Doppler frequency shift compensation. This paper verifies effectiveness of the BS cooperation technologies by both computer simulations and outdoor experimental trials. First, it is shown that that the intra-BBU cooperation can achieve an excellent transmission performance in cases of two and four MSs moving at a velocity of 90km/h by computer simulations. Second, the outdoor experimental trials clarifies that the inter-BBU cooperation maintains the maximum throughput in a wider area than non-BS cooperation when only one MS moves at a maximum velocity of 120km/h.

In a multiple-input multiple-output (MIMO) system, maximum likelihood detection (MLD) is the best demodulation scheme if no a priori information is available. However, the complexity of MLD increases exponentially with the number of signal streams. Therefore, various demodulation schemes with less complexity have been proposed and some of those schemes show performance close to that of MLD. One kind of those schemes uses a Gibbs sampling (GS) algorithm. GS MIMO detection that combines feedback from turbo decoding has been proposed. In this scheme, the accuracy of GS MIMO detection is improved by feeding back loglikelihood ratios (LLRs) from a turbo decoder. In this paper, GS MIMO detection using only feedback LLRs from a turbo decoder is proposed. Through extrinsic information transfer (EXIT) chart analysis, it is shown that the EXIT curves with and without metrics calculated from received signals overlap as the feedback LLR values increase. Therefore, the proposed scheme calculates the metrics from received signals only for the first GS MIMO detection and the selection probabilities of GS MIMO detection in the following iterations are calculated based only on the LLRs from turbo decoders. Numerical results obtained through computer simulation show that the performance of proposed GS turbo MIMO detection is worse than that of conventional GS turbo MIMO detection when the number of GS iterations is small. However the performance improves as the number of GS iterations increases. When the number of GS iterations is 30 or more, the bit error rate (BER) performance of the proposed scheme is equivalent to that of the conventional scheme. Therefore, the proposed scheme can reduce the computational complexity of selection probability calculation in GS turbo MIMO detection.

In March 2020, the 5th generation mobile communication system (5G) was launched in Japan. Frequency bands of 3.7GHz, 4.5GHz and 28GHz were allocated for 5G services, and the 5G use cases fall into three broad categories: Enhanced Mobile Broadband (eMBB), Massive Machine Type Communication (mMTC) and Ultra-Reliable Low Latency Communication (URLLC). The use cases and services that take advantage of the characteristics of each category are expected to be put to practical use, and experiments of practical use are underway. This paper introduces and demonstrates a touchless gate that can identify, authenticate and allow passage through the gate by using these features and 5G beam tracking to estimate location by taking advantage of the low latency of 5G and the straightness of the 28GHz band radio wave and its resistance to spreading. Since position estimation error due to reflected waves and other factors has been a problem, we implement an algorithm that tracks the beam and estimates the user's line of movement, and by using an infrared sensor, we made it possible to identify the gate through which the user passes with high probability. We confirmed that the 5G touchless gate is feasible for gate passage. In addition, we demonstrate that a new service based on high-speed high-capacity communication is possible at gate passage by taking advantage of the wide bandwidth of the 28GHz band. Furthermore, as a use case study of the 5G touchless gate, we conducted a joint experiment with an airline company.

This paper proposes time division multiplexing (TDM) based reference signal (RS) multiplexing for faster-than-Nyquist (FTN) signaling using orthogonal frequency division multiplexing (OFDM). We also propose a subframe structure in which a cyclic prefix (CP) is appended to only the TDM based RS block and the first FTN symbol to achieve accurate estimation of the channel response in a multipath fading channel with low CP overhead. Computer simulation results show that the loss in the required average received SNR satisfying the average block error rate (BLER) of 10-2 using the proposed TDM based RS multiplexing from that with ideal channel estimation is suppressed to within approximately 1.2dB and 1.7dB for QPSK and 16QAM, respectively. This is compared to when the improvement ratio of the spectral efficiency from CP-OFDM is 1.31 with the rate-1/2 turbo code. We conclude that the TDM based RS multiplexing with the associated CP multiplexing is effective in achieving accurate channel estimation for FTN signaling using OFDM.

A narrowband active noise control (NANC) system is very effective for controlling low-frequency periodic noise. A frequency mismatch (FM) with the reference signal will degrade the performance or even cause the system to diverge. To deal with an FM and obtain an accurate reference signal, NANC systems often employ a frequency estimator. Combining an autoregressive predictive filter with a variable step size (VSS) all-pass-based lattice adaptive notch filter (ANF), a new frequency estimation method is proposed that does not require prior information of the primary signal, and the convergence characteristics are much improved. Simulation results show that the designed frequency estimator has a higher accuracy than the conventional algorithm. Finally, hardware experiments are carried out to verify the noise reduction effect.

Ultra-densification of radio access network (RAN) is essential to efficiently handle the ever-increasing mobile data traffic. In this paper, a joint multi-layered user clustering and scheduling is proposed as an inter-cluster interference coordination scheme for ultra-dense RAN using cluster-wise distributed MIMO transmission/reception. The proposed joint multi-layered user clustering and scheduling consists of user clustering using the K-means algorithm, user-cluster layering (called multi-layering) based on the interference-offset-distance (IOD), cluster-antenna association on each layer, and layer-wise round-robin-type scheduling. The user capacity, the sum capacity, and the fairness are evaluated by computer simulations to show the effectiveness of the proposed joint multi-layered user clustering and scheduling. Also shown are uplink and downlink capacity comparisons and optimal IOD setting considering the trade-off between inter-cluster interference mitigation and transmission opportunity.

Exploring the structural information as prior to facial images is a key issue of face super-resolution (SR). Although deep convolutional neural networks (CNNs) own powerful representation ability, how to accurately use facial structural information remains challenges. In this paper, we proposed a new residual fusion network to utilize the multi-scale structural information for face SR. Different from the existing methods of increasing network depth, the bottleneck attention module is introduced to extract fine facial structural features by exploring correlation from feature maps. Finally, hierarchical scales of structural information is fused for generating a high-resolution (HR) facial image. Experimental results show the proposed network outperforms some existing state-of-the-art CNNs based face SR algorithms.

We developed a Nb 4-layer process for fabricating superconducting integrated circuits that involves using caldera planarization to increase the flexibility and reliability of the fabrication process. We call this process the planarized high-speed standard process (PHSTP). Planarization enables us to flexibly adjust most of the Nb and SiO2 film thicknesses; we can select reduced film thicknesses to obtain larger mutual coupling depending on the application. It also reduces the risk of intra-layer shorts due to etching residues at the step-edge regions. We describe the detailed process flows of the planarization for the Josephson junction layer and the evaluation of devices fabricated with PHSTP. The results indicated no short defects or degradation in junction characteristics and good agreement between designed and measured inductances and resistances. We also developed single-flux-quantum (SFQ) and adiabatic quantum-flux-parametron (AQFP) logic cell libraries and tested circuits fabricated with PHSTP. We found that the designed circuits operated correctly. The SFQ shift-registers fabricated using PHSTP showed a high yield. Numerical simulation results indicate that the AQFP gates with increased mutual coupling by the planarized layer structure increase the maximum interconnect length between gates.

Software watermarking enables one to embed some information called “mark” into a program while preserving its functionality, and to read it from the program. As a definition of function preserving, Cohen et al. (STOC 2016) proposed statistical function preserving which requires that the input/output behavior of the marked circuit is identical almost everywhere to that of the original unmarked circuit. They showed how to construct watermarkable cryptographic primitives with statistical function preserving, including pseudorandom functions (PRFs) and public-key encryption from indistinguishability obfuscation. Recently, Goyal et al. (CRYPTO 2019) introduced more relaxed definition of function preserving for watermarkable signature. Watermarkable signature embeds a mark into a signing circuit of digital signature. The relaxed function preserving only requires that the marked signing circuit outputs valid signatures. They provide watermarkable signature with the relaxed function preserving only based on (standard) digital signature. In this work, we introduce an intermediate notion of function preserving for watermarkable signature, which is called computational function preserving. Then, we examine the relationship among our computational function preserving, relaxed function preserving by Goyal et al., and statistical function preserving by Cohen et al. Furthermore, we propose a generic construction of watermarkable signature scheme satisfying computational function preserving based on public key encryption and (standard) digital signature.

This paper presents an efficient method for solving PnP, PnPf, and PnPfr problems, which are the problems of determining camera parameters from 2D-3D point correspondences. The proposed method is derived based on a simple usage of linear algebra, similarly to the classical DLT methods. Therefore, the new method is easier to understand, easier to implement, and several times faster than the state-of-the-art methods using Gröbner basis. Contrary to the existing Gröbner basis methods, the proposed method consists of three algorithms depending on the number of the points and the 3D point configuration. Experimental results show that the proposed method is as accurate as the state-of-the-art methods even in near-planar scenes while achieving up to three times faster.