Given an odd prime q and an integer m ≤ q, a binary mq × q2 quasi-cyclic parity-check matrix H(m, q) can be constructed for an array low-density parity-check (LDPC) code C (m, q). In this letter, we investigate the first separating redundancy of C (m, q). We prove that H (m, q) is 1-separating for any pair of (m, q), from which we conclude that the first separating redundancy of C (m, q) is upper bounded by mq. Then we show that our upper bound on the first separating redundancy of C (m, q) is tighter than the general deterministic and constructive upper bounds in the literature. For m=2, we further prove that the first separating redundancy of C (2, q) is 2q for any odd prime q. For m ≥ 3, we conjecture that the first separating redundancy of C (m, q) is mq for any fixed m and sufficiently large q.

This paper proposes multi-gate reconfigurable (RECON) cells and a technology remapping approach using them as spare cells for post-mask functional engineering change orders (ECOs). With the rapid increase in circuit complexity, ECOs often occur in the post-mask stage of LSI designs. To deal with post-mask ECOs at a low cost, only the metal layers are redesigned by making functional changes using spare cells. For this purpose, 2T/4T/6T-RECON cells were proposed as reconfigurable spare cells. However, conventional RECON cells are used to implement single functions, which may result in unused transistors in the cells. In addition, the number of 2T/4T/6T-RECON spare cells used for post-mask ECOs varies greatly depending on the circuit to be implemented and the type of ECO that occurs. Therefore, functional ECOs may fail due to a lack of certain types of RECON cells, even if other types of RECON cells remain. To solve this problem, we propose multi-gate RECON cells that implement multiple functions in a single RECON cell while retaining the layouts of conventional 4T/6T-RECON base cells, and a technology remapping approach using them. The proposed approach not only reduces the number of used spare cells for modifications but also allows the flexible use of spare cells to fix them with less increase in wire length and delay. Experimental results have confirmed that the functional ECO success ratio is increased by 4.8pt on average and the total number of used spare cells is reduced by 5.6% on average. It has also been confirmed that the increase in wire length is reduced by 17.4% on average and the decrease in slack is suppressed by 21.6% on average.

Information-theoretic lower bounds of the Bayes risk have been investigated for a problem of parameter estimation in a Bayesian setting. Previous studies have proven the lower bound of the Bayes risk in a different manner and characterized the lower bound via different quantities such as mutual information, Sibson's α-mutual information, f-divergence, and Csiszár's f-informativity. In this paper, we introduce an inequality called a “meta-bound for lower bounds of the Bayes risk” and show that the previous results can be derived from this inequality.

Information-theoretic security and computational security are fundamental paradigms of security in the theory of cryptography. The two paradigms interact with each other but have shown different progress, which motivates us to explore the intersection between them. In this paper, we focus on Multi-Party Computation (MPC) because the security of MPC is formulated by simulation-based security, which originates from computational security, even if it requires information-theoretic security. We provide several equivalent formalizations of the security of MPC under a semi-honest model from the viewpoints of information theory and statistics. The interpretations of these variants are so natural that they support the other aspects of simulation-based security. Specifically, the variants based on conditional mutual information and sufficient statistics are interesting because security proofs for those variants can be given by information measures and factorization theorem, respectively. To exemplify this, we show several security proofs of BGW (Ben-Or, Goldwasser, Wigderson) protocols, which are basically proved by constructing a simulator.

Polarization-adjusted convolutional (PAC) codes have better error-correcting performance than polar codes mostly because of the improved weight distribution brought by the convolutional pre-transformation. In this paper, we propose the parity check PAC (PC-PAC) codes to further improve error-correcting performance of PAC codes. The design principle is to establish parity check functions between bits with distinct row weights, such that information bits of lower reliability are re-protected by the PC relation. Moreover, an algorithm to select which bits to be involved in parity-check functions is also proposed to make sure that the constructed codes have fewer minimum-weight codewords. Simulation results show that the proposed PC-PAC codes can achieve nearly 0.2dB gain over PAC codes at frame error rate (FER) about 10-3 codes.

Negation scope resolution is the process of detecting the negated part of a sentence. Unlike the syntax-based approach employed in previous researches, state-of-the-art methods performed better without the explicit use of syntactic structure. This work revisits the syntax-based approach and re-evaluates the effectiveness of syntactic structure in negation scope resolution. We replace the parser utilized in the prior works with state-of-the-art parsers and modify the syntax-based heuristic rules. The experimental results demonstrate that the simple modifications enhance the performance of the prior syntax-based method to the same level as state-of-the-art end-to-end neural-based methods.

The increasing demand for high-performance computing in recent years has led to active research on massively parallel systems. The interconnection network in a massively parallel system interconnects hundreds of thousands of processing elements so that they can process large tasks while communicating among others. By regarding the processing elements as nodes and the links between processing elements as edges, respectively, we can discuss various problems of interconnection networks in the framework of the graph theory. Many topologies have been proposed for interconnection networks of massively parallel systems. The hypercube is a very popular topology and it has many variants. The cross-cube is such a topology, which can be obtained by adding one extra edge to each node of the hypercube. The cross-cube reduces the diameter of the hypercube, and allows cycles of odd lengths. Therefore, we focus on the cross-cube and propose an algorithm that constructs disjoint paths from a node to a set of nodes. We give a proof of correctness of the algorithm. Also, we show that the time complexity and the maximum path length of the algorithm are O(n3 log n) and 2n - 3, respectively. Moreover, we estimate that the average execution time of the algorithm is O(n2) based on a computer experiment.

Compressed sensing is a rapidly growing research field in signal and image processing, machine learning, statistics, and systems control. In this survey paper, we provide a review of the theoretical foundations of compressed sensing and present state-of-the-art algorithms for solving the corresponding optimization problems. Additionally, we discuss several practical applications of compressed sensing, such as group testing, sparse system identification, and sparse feedback gain design, and demonstrate their effectiveness through Python programs. This survey paper aims to contribute to the advancement of compressed sensing research and its practical applications in various scientific disciplines.

Seen from the Internet Service Provider (ISP) side, network traffic monitoring is an indispensable part during network service provisioning, which facilitates maintaining the security and reliability of the communication networks. Among the numerous traffic conditions, we should pay extra attention to traffic anomaly, which significantly affects the network performance. With the advancement of Machine Learning (ML), data-driven traffic anomaly detection algorithms have established high reputation due to the high accuracy and generality. However, they are faced with challenges on inefficient traffic feature extraction and high computational complexity, especially when taking the evolving property of traffic process into consideration. In this paper, we proposed an online learning framework for traffic anomaly detection by embracing Gaussian Process (GP) and Sparse Representation (SR) in two steps: 1). To extract traffic features from past records, and better understand these features, we adopt GP with a special kernel, i.e., mixture of Gaussian in the spectral domain, which makes it possible to more accurately model the network traffic for improving the performance of traffic anomaly detection. 2). To combat noise and modeling error, observing the inherent self-similarity and periodicity properties of network traffic, we manually design a feature vector, based on which SR is adopted to perform robust binary classification. Finally, we demonstrate the superiority of the proposed framework in terms of detection accuracy through simulation.

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.

Synthetic aperture radar (SAR) is a device for observing the ground surface and is one of the important technologies in the field of microwave remote sensing. In SAR observation, a platform equipped with a small-aperture antenna flies in a straight line and continuously radiates pulse waves to the ground during the flight. After that, by synthesizing the series of observation data obtained during the flight, one realize high-resolution ground surface observation. In SAR observation, there are two spatial resolutions defined in the range and azimuth directions and they are limited by the bandwidth of the SAR system. The purpose of this study is to improve the resolution of SAR by sparse reconstruction. In particular, we aim to improve the resolution of SAR without changing the frequency parameters. In this paper, we propose to improve the resolution of SAR using the deconvolution iterative shrinkage-thresholding algorithm (ISTA) and verify the proposed method by carrying out an experimental analysis using an actual SAR dataset. Experimental results show that the proposed method can improve the resolution of SAR with low computational complexity.

Annealing computation has recently attracted attention as it can efficiently solve combinatorial optimization problems using an Ising spin-glass model. Stochastic cellular automata annealing (SCA) is a promising algorithm that can realize fast spin-update by utilizing its parallel computing capability. However, in SCA, pinning effect control to suppress the spin-flip probability is essential, making escaping from local minima more difficult than serial spin-update algorithms, depending on the problem. This paper proposes a novel approach called APC-SCA (Autonomous Pinning effect Control SCA), where the pinning effect can be controlled autonomously by focusing on individual spin-flip. The evaluation results using max-cut, N-queen, and traveling salesman problems demonstrate that APC-SCA can obtain better solutions than the original SCA that uses pinning effect control pre-optimized by a grid search. Especially in solving traveling salesman problems, we confirm that the tour distance obtained by APC-SCA is up to 56.3% closer to the best-known compared to the conventional approach.

Canonical decomposition for bipartite graphs, which was introduced by Fouquet, Giakoumakis, and Vanherpe (1999), is a decomposition scheme for bipartite graphs associated with modular decomposition. Weak-bisplit graphs are bipartite graphs totally decomposable (i.e., reducible to single vertices) by canonical decomposition. Canonical decomposition comprises series, parallel, and K+S decomposition. This paper studies a decomposition scheme comprising only parallel and K+S decomposition. We show that bipartite graphs totally decomposable by this decomposition are precisely P6-free chordal bipartite graphs. This characterization indicates that P6-free chordal bipartite graphs can be recognized in linear time using the recognition algorithm for weak-bisplit graphs presented by Giakoumakis and Vanherpe (2003).

We thank Kamata et al. (2023) [1] for their interest in our work [2], and for providing an explanation of the quasi-linear kernel from a viewpoint of multiple kernel learning. In this letter, we first give a summary of the quasi-linear SVM. Then we provide a discussion on the novelty of quasi-linear kernels against multiple kernel learning. Finally, we explain the contributions of our work [2].

This study proposed a novel decoupling method for four planar inverted-F antennas (PIFAs) operating at 2.0GHz (f0). The edge-to-edge and center-to-center spacings of the adjacent PIFAs are extremely small (0.05λ0 and 0.17λ0, respectively), resulting in strong mutual coupling among them. In our previous study, we proposed a structure consisting of parasitic elements (PEs) and a bridge line (BL) for the decoupling of two PIFAs. One attractive feature of the proposed method is that no adjustment of the original structure and size of the PIFAs is necessary. However, as the number of PIFAs increases to four, their decoupling becomes considerably more complicated, and impedance mismatch is also an issue to be considered. Therefore, in this study, PEs and BLs are functionally developed to simultaneously achieve low mutual coupling and improved impedance matching of the four PIFAs. The simulated results showed that loading the proposed PEs and BLs onto the four PIFAs could reduce as well as maintain all mutual coupling for less than -10dB, and simultaneously improve impedance matching. Therefore, the total antenna efficiency at 2.0GHz could be significantly improved from 64.2% to 84.8% for PIFA1 and PIFA4, and from 35.9% to 74.2% for PIFA2 and PIFA3. Four PIFAs with PEs and BLs were fabricated and measured to validate the simulation results.

The Variational Quantum Eigensolver (VQE) algorithm is gaining interest for its potential use in near-term quantum devices. In the VQE algorithm, parameterized quantum circuits (PQCs) are employed to prepare quantum states, which are then utilized to compute the expectation value of a given Hamiltonian. Designing efficient PQCs is crucial for improving convergence speed. In this study, we introduce problem-specific PQCs tailored for optimization problems by dynamically generating PQCs that incorporate problem constraints. This approach reduces a search space by focusing on unitary transformations that benefit the VQE algorithm, and accelerate convergence. Our experimental results demonstrate that the convergence speed of our proposed PQCs outperforms state-of-the-art PQCs, highlighting the potential of problem-specific PQCs in optimization problems.

An interconnection network is an inevitable component for constructing parallel computers. It connects computation nodes so that the nodes can communicate with each other. As a parallel computation essentially requires inter-node communication according to a parallel algorithm, the interconnection network plays an important role in terms of communication performance. This paper focuses on the collective communication that is frequently performed in parallel computation and this paper addresses the Cup-Stacking method that is proposed in our preceding work. The key issues of the method are splitting a large packet into slices, re-shaping the slice, and stacking the slices, in a genetic algorithm (GA) manner. This paper discusses extending the Cup-Stacking method by introducing additional items (genes) and proposes the extended Cup-Stacking method. Furthermore, this paper places comprehensive discussions on the drawbacks and further optimization of the method. Evaluation results reveal the effectiveness of the extended method, where the proposed method achieves at most seven percent improvement in duration time over the former Cup-Stacking method.

A multifunctional radar (MFR) with varying pulse sequences can change its signal characteristics and/or pattern, based on the presence of targets and to avoid being jammed. To take a countermeasure against an MFR, it is crucial for an electronic warfare (EW) system to be able to identify and separate a MFR's modes via analyzing intercepted radar signals, without a priori knowledge. In this article, two correlation-based methods, one taking the signal's order into account and another one ignoring the signal's order, are proposed and investigated for this task. The results demonstrate their great potential.

Today's electronic devices must meet many requirements, such as those related to performance, limits to the radiated electromagnetic field, size, etc. For such a design, the requirement is to have a solution that simultaneously meets multiple objectives that sometimes include conflicting requirements. In addition, it is also necessary to consider uncertain parameters. This paper proposes a new combination of statistical analysis using the Polynomial Chaos (PC) method for dealing with the random and multi-objective satisfactory design using the Preference Set-based Design (PSD) method. The application in this paper is an Electromagnetic Interference (EMI) filter for a practical case, which includes plural element parameters and uncertain parameters, which are resistors at the source and load, and the performances of the attenuation characteristics. The PC method generates simulation data with high enough accuracy and good computational efficiency, and these data are used as initial data for the meta-modeling of the PSD method. The design parameters of the EMI filter, which satisfy required performances, are obtained in a range by the PSD method. The authors demonstrate the validity of the proposed method. The results show that applying a multi-objective design method using PSD with a statistical method using PC to handle the uncertain problem can be applied to electromagnetic designs to reduce the time and cost of product development.

This paper presents a high-NIR sensitivity SOI-gate lock-in pixel with improved modulation contrast. The proposed pixel has a shallow buried channel and intermediate gates to create both a high lateral electric field and a potential barrier to parasitic light sensitivity. Device simulation results showed that parasitic light sensitivity reduced from 13.7% to 0.13% compared to the previous structure.