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.

We revisit the design of Lesamnta-LW, which is one of the three lightweight hash functions specified in ISO/IEC 29192-5:2016. Firstly, we present some updates on the bounds of the number of active S-boxes for the underlying 64-round block cipher. While the designers showed that the Viterbi algorithm ensured 24 active S-boxes after 24 rounds, our tool based on Mixed Integer Linear Programming (MILP) in the framework of Mouha et al. ensures the same number of active S-boxes only after 18 rounds. The tool completely evaluates the tight bound of the number of active S-boxes, and it shows that the bound is 103 for full (64) rounds. We also analyze security of the Shuffle operation in the round function and resistance against linear cryptanalysis. Secondly, we present a new mode for a pseudorandom function (PRF) based on Lesamnta-LW. It is twice as efficient as the previous PRF modes based on Lesamnta-LW. We prove its security both in the standard model and the ideal cipher model.

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.

In daily reality, people often pay attention to several objects that change positions while being observed. In the laboratory, this process is investigated by a phenomenon known as multiple object tracking (MOT) which is a task that evaluates attentive tracking performance. Recent findings suggest that the attentional set for multiple moving objects whose depth changes in three dimensions from one plane to another is influenced by the initial configuration of the objects. When tracking objects, it is difficult for people to expand their attentional set to multiple-depth planes once attention has been focused on a single plane. However, less is known about people contracting their attentional set from multiple-depth planes to a single-depth plane. In two experiments, we examined tracking accuracy when four targets or four distractors, which were initially distributed on two planes, come together on one of the planes during an MOT task. The results from this study suggest that people have difficulty changing the depth range of their attention during attentive tracking, and attentive tracking performance depends on the initial attentional set based on the configuration prior to attentive tracking.

Computing the weight distribution of a code is a challenging problem in coding theory. In this paper, the weight distributions of (256, k) extended binary primitive BCH codes with k≤71 and k≥187 are given. The weight distributions of the codes with k≤63 and k≥207 have already been obtained in our previous work. Affine permutation and trellis structure are used to reduce the computing time. Computer programs in C language which use recent CPU instructions, such as SIMD, are developed. These programs can be deployed even on an entry model workstation to obtain the new results in this paper.

This letter reports on the effectiveness of applying the K-singular value decomposition (SVD) dictionary learning to the electroencephalogram (EEG) compressed sensing framework with outlier detection and independent component analysis. Using the K-SVD dictionary matrix with our design parameter optimization, for example, at compression ratio of four, we improved the normalized mean square error value by 31.4% compared with that of the discrete cosine transform dictionary for CHB-MIT Scalp EEG Database.

In this paper, we address the problem of detector design in severely frequency-selective channels for spatial multiplexing systems that adopt filter bank multicarrier based on offset quadrature amplitude modulation (FBMC/OQAM) as the communication waveforms. We consider decision feedback equalizers (DFEs) that use multiple feedback filters to jointly cancel the post-cursor components of inter-symbol interference, inter-antenna interference, and, in some configuration, inter-subchannel interference. By exploiting the special structures of the correlation matrix and the staggered property of the FBMC/OQAM signals, we obtain an efficient method of computing the DFE coefficients that requires a smaller number of multiplications than the linear equalizer (LE) and conventional DFE do. The simulation results show that the proposed detectors considerably outperform the LE and conventional DFE at moderate-to-high signal-to-noise ratios.

This review provides a current overview of the fabrication processes for superconducting digital circuits at CRAVITY (clean room for analog and digital superconductivity) at the National Institute of Advanced Industrial Science and Technology (AIST), Japan. CRAVITY routinely fabricates superconducting digital circuits using three types of fabrication processes and supplies several thousand chips to its collaborators each year. Researchers at CRAVITY have focused on improving the controllability and uniformity of device parameters and the reliability, which means reducing defects. These three aspects are important for the correct operation of large-scale digital circuits. The current technologies used at CRAVITY permit ±10% controllability over the critical current density (Jc) of Josephson junctions (JJs) with respect to the design values, while the critical current (Ic) uniformity is within 1σ=2% for JJs with areas exceeding 1.0 µm2 and the defect density is on the order of one defect for every 100,000 JJs.

Autonomous vehicles and advanced driver assistant systems (ADAS) are receiving notable attention as research fields in both academia and private industry. Some decision-making systems use sets of logical rules to map knowledge of the ego-vehicle and its environment into actions the ego-vehicle should take. However, such rulesets can be difficult to create — for example by manually writing them — due to the complexity of traffic as an operating environment. Furthermore, the building blocks of the rules must be defined. One common solution to this is using an ontology specifically aimed at describing traffic concepts and their hierarchy. These ontologies must have a certain expressive power to enable construction of useful rules. We propose a process of generating sets of explanatory rules for ADAS applications from data using ontology as a base vocabulary and present a ruleset generated as a result of our experiments that is correct for the scope of the experiment.

Feature detection and matching procedure require most of processing time in image matching where the time dramatically increases according to the number of feature points. The number of features is needed to be controlled for specific applications because of their processing time. This paper proposes a feature detection method based on significancy of local features. The feature significancy is computed for all pixels and higher significant features are chosen considering spatial distribution. The method contributes to reduce the number of features in order to match two images with maintaining high matching accuracy. It was shown that this approach was faster about two times in average processing time than FAST detector for natural scene images in the experiments.

This paper presents the physical-layer cell identity (PCID) detection probability using the narrowband primary synchronization signal (NPSS) and narrowband secondary synchronization signal (NSSS) based on the narrowband Internet-of-Things (NB-IoT) radio interface considering frequency offset and the maximum Doppler frequency in the 28-GHz band. Simulation results show that the autocorrelation based NPSS detection method is more effective than the cross-correlation based NPSS detection using frequency offset estimation and compensation before the NPSS received timing detection from the viewpoints of PCID detection probability and computational complexity. We also show that when using autocorrelation based NPSS detection, the loss in the PCID detection probability at the carrier frequency of fc =28GHz compared to that for fc =3.5GHz is only approximately 5% at the average received signal-to-noise ratio (SNR) of 0dB when the frequency stability of a local oscillator of a user equipment (UE) set is 20ppm. Therefore, we conclude that the multiplexing schemes and sequences of NPSS and NSSS based on the NB-IoT radio interface associated with autocorrelation based NPSS detection will support the 28-GHz frequency spectra.

Most aggregate signature schemes are relying on pairings, but high computational and storage costs of pairings limit the feasibility of those schemes in practice. Zhao proposed the first pairing-free aggregate signature scheme (AsiaCCS 2019). However, the security of Zhao's scheme is based on the hardness of a newly introduced non-standard computational problem. The recent impossibility results of Drijvers et al. (IEEE S&P 2019) on two-round pairing-free multi-signature schemes whose security based on the standard discrete logarithm (DL) problem have strengthened the view that constructing a pairing-free aggregate signature scheme which is proven secure based on standard problems such as DL problem is indeed a challenging open problem. In this paper, we offer a novel solution to this open problem. We introduce a new paradigm of aggregate signatures, i.e., aggregate signatures with an additional pre-communication stage. In the pre-communication stage, each signer interacts with the aggregator to agree on a specific random value before deciding messages to be signed. We also discover that the impossibility results of Drijvers et al. take effect if the adversary can decide the whole randomness part of any individual signature. Based on the new paradigm and our discovery of the applicability of the impossibility result, we propose a pairing-free aggregate signature scheme such that any individual signature includes a random nonce which can be freely generated by the signer. We prove the security of our scheme based on the hardness of the standard DL problem. As a trade-off, in contrast to the plain public-key model, which Zhao's scheme uses, we employ a more restricted key setup model, i.e., the knowledge of secret-key model.

A universal interconnection network implements arbitrary interconnections among n terminals. This paper considers a problem to realize such a network using contact switches. When n=2, it can be implemented with a single switch. The number of different connections among n terminals is given by the Bell number B(n). The Bell number shows the total number of methods to partition n distinct elements. For n=2, 3, 4, 5 and 6, the corresponding Bell numbers are 2, 5, 15, 52, and 203, respectively. This paper shows a method to realize an n terminal universal interconnection network with $rac {3}{8}(n^2-1)$ contact switches when n=2m+1≥5, and $rac {n}{8}(3n+2)$ contact switches, when n=2m≥6. Also, it shows that a lower bound on the number of contact switches to realize an n-terminal universal interconnection network is ⌈log 2B(n)⌉, where B(n) is the Bell number.

Data parallelism is the dominant method used to train deep learning (DL) models on High-Performance Computing systems such as large-scale GPU clusters. When training a DL model on a large number of nodes, inter-node communication becomes bottle-neck due to its relatively higher latency and lower link bandwidth (than intra-node communication). Although some communication techniques have been proposed to cope with this problem, all of these approaches target to deal with the large message size issue while diminishing the effect of the limitation of the inter-node network. In this study, we investigate the benefit of increasing inter-node link bandwidth by using hybrid switching systems, i.e., Electrical Packet Switching and Optical Circuit Switching. We found that the typical data-transfer of synchronous data-parallelism training is long-lived and rarely changed that can be speed-up with optical switching. Simulation results on the Simgrid simulator show that our approach speed-up the training time of deep learning applications, especially in a large-scale manner.

In the context of Web 2.0, the interaction between users and resources is more and more frequent in the process of resource sharing and consumption. However, the current research on resource pricing mainly focuses on the attributes of the resource itself, and does not weigh the interests of the resource sharing participants. In order to deal with these problems, the pricing mechanism of resource-user interaction evaluation based on multi-agent game theory is established in this paper. Moreover, the user similarity, the evaluation bias based on link analysis and punishment of academic group cheating are also included in the model. Based on the data of 181 scholars and 509 articles from the Wanfang database, this paper conducts 5483 pricing experiments for 13 months, and the results show that this model is more effective than other pricing models - the pricing accuracy of resource resources is 94.2%, and the accuracy of user value evaluation is 96.4%. Besides, this model can intuitively show the relationship within users and within resources. The case study also exhibits that the user's knowledge level is not positively correlated with his or her authority. Discovering and punishing academic group cheating is conducive to objectively evaluating researchers and resources. The pricing mechanism of scientific and technological resources and the users proposed in this paper is the premise of fair trade of scientific and technological resources.

In this letter, we investigate tight analytical and asymptotic upper bounds for bit error rate (BER) of constitutional codes over exponentially correlated Nakagami-m fading channels. Specifically, we derive the BER expression depending on an exact closed-form formula for pairwise error event probabilities (PEEP). Moreover, the corresponding asymptotic analysis in high signal-to-noise ratio (SNR) regime is also explored, which is verified via numerical results. This allows us to have explicit insights on the achievable coding gain and diversity order.