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.

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.

We provide a formal proof for the indifferentiability of SKINNY-HASH internal function from a random oracle. SKINNY-HASH is a family of sponge-based hash functions that use functions (instead of permutations) as primitives, and it was selected as one of the second round candidates of the NIST lightweight cryptography competition. Its internal function is constructed from the tweakable block cipher SKINNY. The construction of the internal function is very simple and the designers claim n-bit security, where n is the block length of SKINNY. However, a formal security proof of this claim is not given in the original specification of SKINNY-HASH. In this paper, we formally prove that the internal function of SKINNY-HASH has n-bit security, i.e., it is indifferentiable from a random oracle up to O(2n) queries, substantiating the security claim of the designers.

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.

The microfabrication technique based on synchrotron radiation (SR) direct etching process has recently been applied to construct PTFE microstructures. This paper proposes a PTFE substrate integrated waveguide (PTFE SIW). It is expected that the PTFE SIW contributes to the improvement of the structural strength. A rectangular through-hole is introduced taking the advantage of the SR direct etching process. First, a PTFE SIW for the Q-band is designed. Then, a cruciform 3-dB directional coupler consisting of the PTFE SIW is designed and fabricated by the SR direct etching process. The validity of the PTFE SIW coupler is confirmed by measuring the frequency characteristics of the S-parameters. The mechanical strength of the PTFE SIW and the peeling strength of its Au film are also additionally investigated.

The Tokyo subway is one of the most complex subway networks in the world and it is difficult to compute a visually readable metro map using existing layout methods. In this paper, we present a new method that can generate complex metro maps such as the Tokyo subway network. Our method consists of two phases. The first phase generates rough metro maps. It decomposes the metro networks into smaller subgraphs and partially generates rough metro maps. In the second phase, we use a local search technique to improve the aesthetic quality of the rough metro maps. The experimental results including the Tokyo metro map are shown.

Multiple-valued bent functions are functions with highest nonlinearity which makes them interesting for multiple-valued cryptography. Since the general structure of bent functions is still unknown, methods for construction of bent functions are often based on some deterministic criteria. For practical applications, it is often necessary to be able to construct a bent function that does not belong to any specific class of functions. Thus, the criteria for constructions are combined with exhaustive search over all possible functions which can be very CPU time consuming. A solution is to restrict the search space by some conditions that should be satisfied by the produced bent functions. In this paper, we proposed the construction method based on spectral subsets of multiple-valued bent functions satisfying certain appropriately formulated restrictions in Galois field (GF) and Reed-Muller-Fourier (RMF) domains. Experimental results show that the proposed method efficiently constructs ternary and quaternary bent functions by using these restrictions.

Resource sharing is to ensure required resources available for their demanders. However, due to the lack of proper sharing model, the current sharing rate of the scientific and technological resources is low, impeding technological innovation and value chain development. Here we propose a novel method to share scientific and technological resources by storing resources as nodes and correlations as links to form a complex network. We present a few-shot relational learning model to solve the cold-start and long-tail problems that are induced by newly added resources. Experimentally, using NELL-One and Wiki-One datasets, our one-shot results outperform the baseline framework - metaR by 40.2% and 4.1% on MRR in Pre-Train setting. We also show two practical applications, a resource graph and a resource map, to demonstrate how the complex network helps resource sharing.

Paper recommendation has become an increasingly important yet challenging task due to the rapidly expanding volume and scope of publications in the broad research community. Due to the lack of user profiles in public digital libraries, most existing methods for paper recommendation are through paper similarity measurements based on citations or contents, and still suffer from various performance issues. In this paper, we construct a graphical form of citation relations to identify relevant papers and design a hybrid recommendation model that combines both citation- and content-based approaches to measure paper similarities. Considering that citations at different locations in one article are likely of different significance, we define a concept of citation similarity with varying weights according to the sections of citations. We evaluate the performance of our recommendation method using Spearman correlation on real publication data from public digital libraries such as CiteSeer and Wanfang. Extensive experimental results show that the proposed hybrid method exhibits better performance than state-of-the-art techniques, and achieves 40% higher recommendation accuracy in average in comparison with citation-based approaches.

Most gait recognition approaches rely on silhouette-based representations due to high recognition accuracy and computational efficiency. A fundamental problem for those approaches is how to extract individuality-preserved silhouettes from real scenes accurately. Foreground colors may be similar to background colors, and the background is cluttered. Therefore, we propose a method of individuality-preserving silhouette extraction for gait recognition using standard gait models (SGMs) composed of clean silhouette sequences of various training subjects as shape priors. The SGMs are smoothly introduced into a well-established graph-cut segmentation framework. Experiments showed that the proposed method achieved better silhouette extraction accuracy by more than 2.3% than representative methods and better identification rate of gait recognition (improved by more than 11.0% at rank 20). Besides, to reduce the computation cost, we introduced approximation in the calculation of dynamic programming. As a result, without reducing the segmentation accuracy, we reduced 85.0% of the computational cost.

In wireless links between ground stations and UAVs (Unmanned Aerial Vehicles), wireless signals may be attenuated by obstructions such as buildings. A three-dimensional RSS (Received Signal Strength) map (3D-RSS map), which represents a set of RSSs at various reception points in a three-dimensional area, is a promising geographical database that can be used to design reliable ground-to-air wireless links. The construction of a 3D-RSS map requires higher computational complexity, especially for a large 3D area. In order to sequentially estimate a 3D-RSS map from partial observations of RSS values in the 3D area, we propose a graph Laplacian-based sequential smooth estimator. In the proposed estimator, the 3D area is divided into voxels, and a UAV observes the RSS values at the voxels along a predetermined path. By considering the voxels as vertices in an undirected graph, a measurement graph is dynamically constructed using vertices from which recent observations were obtained and their neighboring vertices, and the 3D-RSS map is sequentially estimated by performing graph Laplacian regularized least square estimation.

The increased performance of mobile terminals has made it feasible to collect data using users' terminals. By making the best use of the network performance data widely collected in this way, network operators should deeply understand the current network conditions, identify the performance-degraded components in the network, and estimate the degree of their performance degradation. For their demands, one powerful solution with such end-to-end data measured by users' terminals is network tomography. Meanwhile, with the advance of network virtualization by software-defined networking, routing is dynamically changed due to congestion or other factors, and each end-to-end measurement flow collected from users may pass through different paths between even the same origin-destination node pair. Therefore, it is difficult and costly to identify through which path each measurement flow has passed, so it is also difficult to naively apply conventional network tomography to such networks where the measurement paths cannot be uniquely determined. We propose a novel network tomography for the networks with undeterministic routing where the measurement flows pass through multiple paths in spite of the origin-destination node pair being the same. The basic idea of our method is to introduce routing probability in accordance with the aggregated information of measurement flows. We present two algorithms and evaluate their performances by comparing them with algorithms of conventional tomography using determined routing information. Moreover, we verify that the proposed algorithms are applicable to a more practical network.

The Internet of Things (IoT) implicates an infrastructure that creates new value by connecting everything with communication networks, and its construction is rapidly progressing in anticipation of its great potential. Enhancing the security of IoT is an essential requirement for supporting IoT. For ensuring IoT security, it is desirable to create a situation that even a terminal component device with many restrictions in computing power and energy capacity can easily verify other devices and data and communicate securely by the use of public key cryptography. To concretely achieve the big goal of penetrating public key cryptographic technology to most IoT end devices, we elaborated the secure cryptographic unit (SCU) built in a low-end microcontroller chip. The SCU comprises a hardware cryptographic engine and a built-in access controlling functionality consisting of a software gate and hardware gate. This paper describes the outline of our SCU construction technology's research and development and prospects.

Various graph algorithms have been developed with multiple random walks, the movement of several independent random walkers on a graph. Designing an efficient graph algorithm based on multiple random walks requires investigating multiple random walks theoretically to attain a deep understanding of their characteristics. The first meeting time is one of the important metrics for multiple random walks. The first meeting time on a graph is defined by the time it takes for multiple random walkers to meet at the same node in a graph. This time is closely related to the rendezvous problem, a fundamental problem in computer science. The first meeting time of multiple random walks has been analyzed previously, but many of these analyses focused on regular graphs. In this paper, we analyze the first meeting time of multiple random walks in arbitrary graphs and clarify the effects of graph structures on expected values. First, we derive the spectral formula of the expected first meeting time on the basis of spectral graph theory. Then, we examine the principal component of the expected first meeting time using the derived spectral formula. The clarified principal component reveals that (a) the expected first meeting time is almost dominated by $n/(1+d_{ m std}^2/d_{ mavg}^2)$ and (b) the expected first meeting time is independent of the starting nodes of random walkers, where n is the number of nodes of the graph. davg and dstd are the average and the standard deviation of weighted node degrees, respectively. Characteristic (a) is useful for understanding the effect of the graph structure on the first meeting time. According to the revealed effect of graph structures, the variance of the coefficient dstd/davg (degree heterogeneity) for weighted degrees facilitates the meeting of random walkers.

SPHINCS+ is a state-of-the-art post-quantum hash-based signature that is a candidate for the NIST post-quantum cryptography standard. For a target bit security, SPHINCS+ supports many different tradeoffs between the signature size and the signing speed. SPHINCS+ provides 6 parameter sets: 3 parameter sets for size optimization and 3 parameter sets for speed optimization. We propose new parameter sets with better performance. Specifically, SPHINCS+ implementations with our parameter sets are up to 26.5% faster with slightly shorter signature sizes.

In this study, we devised a biofuel cell (BFC) by impregnating sheet-like cellulose nanofiber (CNF) with liquid fuel (fructose) and sandwiching it with the electrodes, making the structure simple and compact. CNF was considered as a suitable material for BFC because it is biocompatible, has a large specific surface area, and exhibits excellent properties as a catalyst and an adsorbent. In this BFC device, graphene-coated carbon fiber woven cloth (GCFC) was used as the material for preparing the electrodes, and the amount of enzyme modification on the surface of each electrode was enhanced. Further, as the distance between the electrodes was same as the thickness of the sheet-shaped CNF, it facilitated the exchange of protons between the electrodes. Moreover, the cathode, which requires an oxidation reaction, was exposed to the atmosphere to enhance the oxygen uptake. The maximum power density of the CNF-type BFC was recorded as 114.5 µW/cm2 at a voltage of 293 mV. This is more than 1.5 times higher than that of the liquid-fuel-type BFC. When measured after 24 h, the maximum power density was recorded as 44.9 µW/cm2 at 236 mV, and the output was maintained at 39% of that observed at the beginning of the measurement. However, it is not the case with general BFCs, where the power generation after 24 h is less than 5%. Therefore, the CNF-type BFCs have a longer lifespan and are fuel efficient.

Ising machines have attracted attention as they are expected to solve combinatorial optimization problems at high speed with Ising models corresponding to those problems. An induced subgraph isomorphism problem is one of the decision problems, which determines whether a specific graph structure is included in a whole graph or not. The problem can be represented by equality constraints in the words of combinatorial optimization problem. By using the penalty functions corresponding to the equality constraints, we can utilize an Ising machine to the induced subgraph isomorphism problem. The induced subgraph isomorphism problem can be seen in many practical problems, for example, finding out a particular malicious circuit in a device or particular network structure of chemical bonds in a compound. However, due to the limitation of the number of spin variables in the current Ising machines, reducing the number of spin variables is a major concern. Here, we propose an efficient Ising model mapping method to solve the induced subgraph isomorphism problem by Ising machines. Our proposed method theoretically solves the induced subgraph isomorphism problem. Furthermore, the number of spin variables in the Ising model generated by our proposed method is theoretically smaller than that of the conventional method. Experimental results demonstrate that our proposed method can successfully solve the induced subgraph isomorphism problem by using the Ising-model based simulated annealing and a real Ising machine.

This paper deals with the problem of enumerating 3-edge-connected spanning subgraphs of an input plane graph. In 2018, Yamanaka et al. proposed two enumeration algorithms for such a problem. Their algorithm generates each 2-edge-connected spanning subgraph of a given plane graph with n vertices in O(n) time, and another one generates each k-edge-connected spanning subgraph of a general graph with m edges in O(mT) time, where T is the running time to check the k-edge connectivity of a graph. This paper focuses on the case of the 3-edge-connectivity in a plane graph. We give an algorithm which generates each 3-edge-connected spanning subgraph of the input plane graph in O(n2) time. This time complexity is the same as the algorithm by Yamanaka et al., but our algorithm is simpler than theirs.

AI (artificial intelligence) has grown at an overwhelming speed for the last decade, to the extent that it has become one of the mainstream tools that drive the advancements in science and technology. Meanwhile, the paradigm of edge computing has emerged as one of the foremost areas in which applications using the AI technology are being most actively researched, due to its potential benefits and impact on today's widespread networked computing environments. In this paper, we evaluate two major entry-level offerings in the state-of-the-art edge device technology, which highlight increased computing power and specialized hardware support for AI applications. We perform a set of deep learning benchmarks on the devices to measure their performance. By comparing the performance with other GPU (graphics processing unit) accelerated systems in different platforms, we assess the computational capability of the modern edge devices featuring a significant amount of hardware parallelism.

History data of edit operations are more beneficial than those stored in version control systems since they provide detailed information on how source code was changed. Meanwhile, a large number of recorded edit operations discourage developers and researchers from roughly understanding the changes. To assist with this task, it is desirable that they easily obtain traceability links for changed program elements over two source code snapshots before and after a code change. In this paper, we propose a graph representation called Operation History Graph (OHG), which presents code change information with such traceability links that are inferred from the history of edit operations. An OHG instance is generated by parsing any source code snapshot restored by edit histories and combining resultant abstract syntax trees (ASTs) into a single graph structure. To improve the performance of building graph instances, we avoided simply maintaining every program element. Any program element presenting the inner-structure of methods and non-changed elements are omitted. In addition, we adopted a lightweight static analysis for type name resolving to reduce required memory resource in the analysis while the accuracy of name resolving is preserved. Moreover, we assign a specific ID to each node and edge in the graph instance so that a part of the graph data can be separately stored and loaded on demand. These decisions make it feasible to build, manipulate, and store the graph with limited computer resources. To demonstrate the usefulness of the proposed operation history graph and verify whether detected traceability links are sufficient to reveal actual changes of program elements, we implemented tools to generate and manipulate OHG instances. The evaluation on graph generation performance shows that our tool can reduce the required computer resource as compared to another tool authors previously proposed. Moreover, the evaluation on traceability shows that OHG provides traceability links with sufficient accuracy as compared to the baseline approach using GumTree.