There are continuous and strong demands for the DC-DC converter to reduce the size of passive components and increase the system power density. Advances in CMOS processes and GaN FETs enabled the switching frequency of DC-DC converters to be beyond 10MHz. The advancements of 3-D integrated magnetics will further reduce the footprint. In this paper, the overview of beyond-10MHz DC-DC converters will be provided first, and our recent achievements are introduced focusing on 3D-integration of Fe-based metal composite magnetic core inductor, and GaN FET control designs.

A multibeam massive multiple input multiple output (MIMO) configuration employs beam selection with high power in the analog part and executes a blind algorithm such as the independent component analysis (ICA), which does not require channel state information in the digital part. Two-dimensional (2-D) multibeams are considered in actual power losses and beam steering errors regarding the multibeam patterns. However, the performance of these 2-D beams depends on the beam pattern of the multibeams, and they are not optimal multibeam patterns suitable for multibeam massive MIMO configurations. In this study, we clarify the performance difference due to the difference of the multibeam pattern and consider the multibeam pattern suitable for the system condition. Specifically, the optimal multibeam pattern was determined with the element spacing and beamwidth of the element directivity as parameters, and the effectiveness of the proposed method was verified via computer simulations.

In 2015, the Ministry of Land, Infrastructure and Transportation started to provide information on aircraft flying over Japan, called CARATS Open Data, and to promote research on aviation systems actively. The airspace is divided into sectors, which are used for limiting air traffic to control safely and efficiently. Since the demand for air transportation is increasing, new optimization techniques and efficient control have been required to predict and resolve demand-capacity imbalances in the airspace. In this paper, we aim to construct mathematical models of the inter-sector air traffic flow from CARATS Open Data. In addition, we develop methods to predict future sector demand. Accuracy of the prediction is evaluated by comparison between predicted sector demand and the actual data.

A surrogate-based electromagnetic (EM) optimization using neural networks (NNs) is presented for computationally efficient microwave bandpass filter (BPF) design. This paper first describes the forward problem (EM analysis) and the inverse problems (EM design), and the two fundamental issues in BPF designs. The first issue is that the EM analysis is a time-consuming task, and the second one is that EM design highly depends on the structural optimization performed with the help of EM analysis. To accelerate the optimization design, two surrogate models of forward and inverse models are introduced here, which are built with the NNs. As a result, the inverse model can instantaneously guess initial structural parameters with high accuracy by simply inputting synthesized coupling-matrix elements into the NN. Then, the forward model in conjunction with optimization algorithm enables designers to rapidly find optimal structural parameters from the initial ones. The effectiveness of the surrogate-based EM optimization is verified through the structural designs of a typical fifth-order microstrip BPF with multiple couplings.

The colors of objects in natural images are affected by the color of lighting, and accurately estimating an illuminant's color is indispensable in analyzing scenes lit by colored lightings. Recent lighting environments enhance colorfulness due to the spread of light-emitting diode (LED) lightings whose colors are flexibly controlled in a full visible spectrum. However, existing color estimations mainly focus on the single illuminant of normal color ranges. The estimation of multiple illuminants of unusual color settings, such as blue or red of high chroma, has not been studied yet. Therefore, new color estimations should be developed for multiple illuminants of various colors. In this article, we propose a color estimation for LED lightings using Color Line features, which regards the color distribution as a straight line in a local area. This local estimate is suitable for estimating various colors of multiple illuminants. The features are sampled at many small regions in an image and aggregated to estimate a few global colors using supervised learning with a convolutional neural network. We demonstrate the higher accuracy of our method over existing ones for such colorful lighting environments by producing the image dataset lit by multiple LED lightings in a full-color range.

In this manuscript, we propose a joint channel and power assignment algorithm for an unmanned aerial vehicle (UAV) swarm communication system based on multi-agent deep reinforcement learning (DRL). Regarded as an agent, each UAV to UAV (U2U) link can choose the optimal channel and power according to the current situation after training is successfully completed. Further, a mixing network is introduced based on DRL, where Q values of every single agent are non-linearly mapped, and we call it the QMIX algorithm. As it accesses state information, QMIX can learn to enrich the joint action value function. The proposed method can be used for both unicast and multicast scenarios. Experiments show that each U2U link can be trained to meet the constraints of UAV communication and minimize the interference to the system. For unicast communication, the communication rate is increased up to 15.6% and 8.9% using the proposed DRL method compared with the well-known random and adaptive methods, respectively. For multicast communication, the communication rate is increased up to 6.7% using the proposed QMIX method compared with the DRL method and 13.6% using DRL method compared with adaptive method. Besides, the successful transmission probability can maintain a high level.

Logical matrices are binary matrices often used to represent relations. In the map folding problem, each folded state corresponds to a unique partial order on the set of squares and thus could be described with a logical matrix. The logical matrix representation is powerful than graphs or other common representations considering its association with category theory and homology theory and its generalizability to solve other computational problems. On the application level, such representations allow us to recognize map folding intuitively. For example, we can give a precise mathematical description of a folding process using logical matrices so as to solve problems like how to represent the up-and-down relations between all the layers according to their adjacency in a flat-folded state, how to check self-penetration, and how to deduce a folding process from a given order of squares that is supposed to represent a folded state of the map in a mathematical and natural manner. In this paper, we give solutions to these problems and analyze their computational complexity.

Couplers in a film-type capacitive wireless power charging (CWC) system for an implantable medical device were designed and analyzed in this work. Due to the high conductivity of the human body, two paths contribute to the power transmission, namely a high-frequency current and an electric field. This was confirmed by an equivalent circuit of the system. During analysis of the system, we used pig skin with subcutaneous fat, which has a high affinity with the human body, to search for a highly efficient electrode shape. Subsequently, we fabricated the designed coupler and measured ηmax. An ηmax of 56.6% was obtained for a half-circular coupler with a radius of 20 mm and a distance of 10 mm between adjacent couplers. This study will contribute to the realization of implantable devices that can be recharged during breaks or while sleeping at home and is expected to significantly reduce the burden on patients.

In this paper, we propose a new algorithm to generate Speech-like Emotional Sound (SES). Emotional expressions may be the most important factor in human communication, and speech is one of the most useful means of expressing emotions. Although speech generally conveys both emotional and linguistic information, we have undertaken the challenge of generating sounds that convey emotional information alone. We call the generated sounds “speech-like,” because the sounds do not contain any linguistic information. SES can provide another way to generate emotional response in human-computer interaction systems. To generate “speech-like” sound, we propose employing WaveNet as a sound generator conditioned only by emotional IDs. This concept is quite different from the WaveNet Vocoder, which synthesizes speech using spectrum information as an auxiliary feature. The biggest advantage of our approach is that it reduces the amount of emotional speech data necessary for training by focusing on non-linguistic information. The proposed algorithm consists of two steps. In the first step, to generate a variety of spectrum patterns that resemble human speech as closely as possible, WaveNet is trained with auxiliary mel-spectrum parameters and Emotion ID using a large amount of neutral speech. In the second step, to generate emotional expressions, WaveNet is retrained with auxiliary Emotion ID only using a small amount of emotional speech. Experimental results reveal the following: (1) the two-step training is necessary to generate the SES with high quality, and (2) it is important that the training use a large neutral speech database and spectrum information in the first step to improve the emotional expression and naturalness of SES.

We introduce a new type of exponentiation algorithm in GF(2m) using Euclidean inversion. Our approach is based on the fact that Euclidean inversion cost much less logic gates than ordinary multiplication in GF(2m). By applying signed binary form of the exponent instead of classic binary form, the proposed algorithm can reduce the number of operations further compared with the classic algorithms.

The r-th nonlinearity of Boolean functions is an important cryptographic criterion associated with higher order linearity attacks on stream and block ciphers. In this paper, we tighten the lower bound of the second-order nonlinearity of a class of Boolean function over finite field F2n, fλ(x)=Tr(λxd), where λ∈F*2r, d=22r+2r+1 and n=7r. This bound is much better than the lower bound of Iwata-Kurosawa.

S-box is one of the core components of symmetric cryptographic algorithms, but differential distribution table (DDT) is an important tool to research some properties of S-boxes to resist differential attacks. In this paper, we give a relationship between the sum-of-squares of DDT and the sum-of-squares indicator of (n, m)-functions based on the autocorrelation coefficients. We also get some upper and lower bounds on the sum-of-squares of DDT of balanced (n, m)-functions, and prove that the sum-of-squares of DDT of (n, m)-functions is affine invariant under affine affine equivalent. Furthermore, we obtain a relationship between the sum-of-squares of DDT and the signal-to-noise ratio of (n, m)-functions. In addition, we calculate the distributions of the sum-of-squares of DDT for all 3-bit S-boxes, the 4-bit optimal S-boxes and all 302 balanced S-boxes (up to affine equivalence), data experiments verify our results.

We studied whether a statement similar to the Ghouila-Houri's theorem might hold for alternating orientations of cocomparability graphs. In this paper, we give the negative answer. We prove that it is NP-complete to decide whether a cocomparability graph has an orientation that is alternating and acyclic. Hence, cocomparability graphs with an acyclic alternating orientation form a proper subclass of alternately orientable cocomparability graphs. We also provide a separating example, that is, an alternately orientable cocomparability graph such that no alternating orientation is acyclic.

The Graph Coloring Problem (GCP) is a fundamental combinatorial optimization problem that has many practical applications. Degree of SATURation (DSATUR) and Recursive Largest First (RLF) are well known as typical solution construction algorithms for GCP. It is necessary to update the vertex degree in the subgraph induced by uncolored vertices when selecting vertices to be colored in both DSATUR and RLF. There is an issue that the higher the edge density of a given graph, the longer the processing time. The purposes of this paper are to propose a degree updating method called Adaptive Degree Updating (ADU for short) that improves the issue, and to evaluate the effectiveness of ADU for DSATUR and RLF on DIMACS benchmark graphs as well as random graphs having a wide range of sizes and densities. Experimental results show that the construction algorithms with ADU are faster than the conventional algorithms for many graphs and that the ADU method yields significant speed-ups relative to the conventional algorithms, especially in the case of large graphs with higher edge density.

Hierarchical ID-based authenticated key exchange (HID-AKE) is a cryptographic protocol to establish a common session key between parties with authentication based on their IDs with the hierarchical delegation of key generation functionality. All existing HID-AKE schemes are selective ID secure, and the only known standard model scheme relies on a non-standard assumption such as the q-type assumption. In this paper, we propose a generic construction of HID-AKE that is adaptive ID secure in the HID-eCK model (maximal-exposure-resilient security model) without random oracles. One of the concrete instantiations of our generic construction achieves the first adaptive ID secure HID-AKE scheme under the (standard) k-lin assumption in the standard model. Furthermore, it has the advantage that the computational complexity of pairing and exponentiation operations and the communication complexity do not depend on the depth of the hierarchy. Also, the other concrete instantiation achieves the first HID-AKE scheme based on lattices (i.e., post-quantum).

Multiparty computation (MPC) is a cryptographic method that enables a set of parties to compute an arbitrary joint function of the private inputs of all parties and does not reveal any information other than the output. MPC based on a secret sharing scheme (SS-MPC) and garbled circuit (GC) is known as the most common MPC schemes. Another cryptographic method, homomorphic encryption (HE), computes an arbitrary function represented as a circuit by using ciphertexts without decrypting them. These technologies are in a trade-off relationship for the communication/round complexities, and the computation cost. The private decision tree evaluation (PDTE) is one of the key applications of these technologies. There exist several constant-round PDTE protocols based on GC, HE, or the hybrid schemes that are secure even if a malicious adversary who can deviate from protocol specifications corrupts some parties. There also exist other protocols based only on SS-MPC that are secure only if a semi-honest adversary who follows the protocol specification corrupts some parties. However, to the best of our knowledge, there are currently no constant-round PDTE protocols based only on SS-MPC that are secure against a malicious adversary. In this work, we propose a constant-round four-party PDTE protocol that achieves malicious security. Our protocol provides the PDTE securely and efficiently even when the communication environment has a large latency.

A branching program is a well-studied model of computation and a representation for Boolean functions. It is a directed acyclic graph with a unique root node, some accepting nodes, and some rejecting nodes. Except for the accepting and rejecting nodes, each node has a label with a variable and each outgoing edge of the node has a label with a 0/1 assignment of the variable. The satisfiability problem for branching programs is, given a branching program with n variables and m nodes, to determine if there exists some assignment that activates a consistent path from the root to an accepting node. The width of a branching program is the maximum number of nodes at any level. The satisfiability problem for width-2 branching programs is known to be NP-complete. In this paper, we present a satisfiability algorithm for width-2 branching programs with n variables and cn nodes, and show that its running time is poly(n)·2(1-µ(c))n, where µ(c)=1/2O(c log c). Our algorithm consists of two phases. First, we transform a given width-2 branching program to a set of some structured formulas that consist of AND and Exclusive-OR gates. Then, we check the satisfiability of these formulas by a greedy restriction method depending on the frequency of the occurrence of variables.

In a previous study, we proposed a new method based on copula theory to evaluate the detection performance of distributed-processing multistatic radar systems, in which the dependence of local decisions was modeled by a Gaussian copula with linear dependence and no tail dependence. However, we also noted that one main limitation of the study was the lack of investigations on the tail-dependence and nonlinear dependence among local detectors' inputs whose densities have long tails and are often used to model clutter and wanted signals in high-resolution radars. In this work, we attempt to overcome this shortcoming by extending the application of the proposed method to several types of multivariate copula-based dependence models to clarify the effects of tail-dependence and different dependence models on the system detection performance in detail. Our careful analysis provides two interesting and important clarifications: first, the detection performance degrades significantly with tail dependence; and second, this degradation mainly originates from the upper tail dependence, while the lower tail and nonlinear dependence unexpectedly improve the system performance.

The fast evolving credential attacks have been a great security challenge to current password-based information systems. Recently, biometrics factors like facial, iris, or fingerprint that are difficult to forge rise as key elements for designing passwordless authentication. However, capturing and analyzing such factors usually require special devices, hindering their feasibility and practicality. To this end, we present WiASK, a device-free WiFi sensing enabled Authentication System exploring Keystroke dynamics. More specifically, WiASK captures keystrokes of a user typing a pre-defined easy-to-remember string leveraging the existing WiFi infrastructure. But instead of focusing on the string itself which are vulnerable to password attacks, WiASK interprets the way it is typed, i.e., keystroke dynamics, into user identity, based on the biologically validated correlation between them. We prototype WiASK on the low-cost off-the-shelf WiFi devices and verify its performance in three real environments. Empirical results show that WiASK achieves on average 93.7% authentication accuracy, 2.5% false accept rate, and 5.1% false reject rate.

The road space rationing (RSR) method regulates a period in which a user group can make telephone calls in order to decrease the call attempt rate and induce calling parties to shorten their calls during disaster congestion. This paper investigates what settings of this indirect control induce more self-restraint and how the settings change calling parties' behavior using experimental psychology. Our experiments revealed that the length of the regulated period differently affected calling parties' behavior (call duration and call attempt rate) and indicated that the 60-min RSR method (i.e., 10 six-min periods) is the most effective setting against disaster congestion.