A grating consisting of a periodic array of InSb-coated dielectric cylinders on a substrate is analyzed at THz frequencies using the frequency-dependent finite-difference time-domain method based on the trapezoidal recursive convolution technique. The transmission characteristics of an infinite periodic array are investigated not only at normal incidence but also at oblique incidence. The incident field is shown to be coupled to the substrate due to the guided-mode resonance (GMR), indicating the practical application of a grating coupler. For the sensor application, the frequency shift of the transmission dip is investigated with attention to the variation of the background refractive index. It is found that the shift of the dip involving the surface plasmon resonance is almost ten times as large as that of the dip only from the GMR. We finally analyze a finite periodic array of the cylinders. The field radiation from the array is discussed, when the field propagates through the substrate. It is shown that the radiation direction can be controlled with the frequency of the propagating field.

We demonstrated a compact 16×16 multicast switch (MCS) made from a silica-based planar lightwave circuit (PLC). The switch utilizes a new electrical connection method based on surface mount technology (SMT). Five electrical connectors are soldered directly to the PLC by using the standard reflow process used for electrical devices. We reduced the chip size to half of one made with conventional wire bonding technology. We obtained satisfactory solder contacts and excellent switching properties. These results indicate that the proposed method is suitable for large-scale optical switches including MCSs, variable optical attenuators, dispersion compensators, and so on.

The machine-to-machine (M2M) service network platform that accommodates and controls various types of Internet of Things devices has been presented. This paper investigates program file placement strategies for the M2M service network platform that achieve low blocking ratios of new task requests and accommodate as many tasks as possible in the dynamic scenario. We present four strategies for determining program file placement, which differ in the computation method and whether the relocation of program files being used by existing tasks is allowed or not. Simulation results show that a strategy based on solving a mixed-integer linear programming model achieves the lowest blocking ratio, but a heuristic algorithm-based strategy can be an attractive option by allowing recomputation of the placement when the placement cannot be obtained at the timing of new task request arrival.

In this letter, we propose a novel robust transferable subspace learning (RTSL) method for cross-corpus facial expression recognition. In this method, on one hand, we present a novel distance metric algorithm, which jointly considers the local and global distance distribution measure, to reduce the cross-corpus mismatch. On the other hand, we design a label guidance strategy to improve the discriminate ability of subspace. Thus, the RTSL is much more robust to the cross-corpus recognition problem than traditional transfer learning methods. We conduct extensive experiments on several facial expression corpora to evaluate the recognition performance of RTSL. The results demonstrate the superiority of the proposed method over some state-of-the-art methods.

A planar electromagnetic field stirrer with periodically arranged metal patterns and diode switches is proposed for improving uneven heating of a heated object placed in a microwave oven. The reflection phase of the proposed stirrer changes by switching the states of diodes mounted on the stirrer and the electromagnetic field in the microwave oven is stirred. The temperature distribution of a heated object located in a microwave oven was simulated and measured using the stirrer in order to evaluate the improving effect of the uneven heating. As the result, the heated parts of the objects were changed with the diode states and the improving effect of the uneven heating was experimentally indicated.

A limited number of types of sound event occur in an acoustic scene and some sound events tend to co-occur in the scene; for example, the sound events “dishes” and “glass jingling” are likely to co-occur in the acoustic scene “cooking.” In this paper, we propose a method of sound event detection using graph Laplacian regularization with sound event co-occurrence taken into account. In the proposed method, the occurrences of sound events are expressed as a graph whose nodes indicate the frequencies of event occurrence and whose edges indicate the sound event co-occurrences. This graph representation is then utilized for the model training of sound event detection, which is optimized under an objective function with a regularization term considering the graph structure of sound event occurrence and co-occurrence. Evaluation experiments using the TUT Sound Events 2016 and 2017 detasets, and the TUT Acoustic Scenes 2016 dataset show that the proposed method improves the performance of sound event detection by 7.9 percentage points compared with the conventional CNN-BiGRU-based detection method in terms of the segment-based F1 score. In particular, the experimental results indicate that the proposed method enables the detection of co-occurring sound events more accurately than the conventional method.

In this paper, we propose an interactive system for controlling the pressure while cutting paper with a knife. The purpose is to improve the cutting skill of novices learning the art of paper-cutting. Our system supports skill improvement for novices by measuring and evaluating their cutting pressure in real-time. In this study, we use a knife with a blade attached to a stylus with a pressure sensor, which can measure the pressure, coordinates, and cutting time. We have developed a similar support system using a stylus and a tablet device. This system allows the user to experience the pressure of experts through tracing. Paper-cutting is created by cutting paper with a knife. The practice system in this paper provides practice in an environment more akin to the production of paper cutting. In the first experiment, we observed differences in cutting ability by comparing cutting pressures between novices and experts. As a result, we confirmed that novices cut paper at a higher pressure than experts. We developed a practice system that guides the novices on controlling the pressure by providing information on the cutting pressure values of experts. This system shows the difference in pressure between novices and experts using a synchronous display of color and sound. Using these functions, novices learn to adjust their cutting pressure according to that of experts. Determining the right cutting pressure is a critical skill in the art of paper-cutting, and we aim to improve the same with our system. In the second experiment, we tested the effect of the practice system on the knife device. We compared the changes in cutting pressure with and without our system, the practice methods used in the workshop, and the previously developed stylus-based support system. As a result, we confirmed that practicing with the knife device had a better effect on the novice's skill in controlling cutting pressure than other practice methods.

This letter studies the physical layer security of an unmanned aerial vehicle (UAV)-enabled multicasting system, where a UAV serves as a mobile transmitter to send a common confidential message to a group of legitimate users under the existence of multiple eavesdroppers. The worst situation in which each eavesdropper can wiretap all legitimate users is considered. We seek to maximize the average secrecy rate by jointly optimizing the UAV's transmit power and trajectory over a given flight period. The resulting optimization problem is nonconvex and intractable to solve. To circumvent the nonconvexity, we propose an iterative algorithm to approximate the solution based on the alternating optimization and successive convex approximation methods. Simulation results validate the convergence and effectiveness of our proposed algorithm.

We have investigated the in-situ N2-plasma nitridation for high-k HfN gate insulator formed by electron cyclotron resonance (ECR) plasma sputtering to improve the electrical characteristics. It was found that the increase of nitridation gas pressure for the deposited HfN1.1 gate insulator, such as 98 mPa, decreased both the hysteresis width in C-V characteristics and leakage current. Furthermore, the 2-step nitiridation process with the nitridation gas pressure of 26 mPa followed by the nitridation at 98 mPa realized the decrease of equivalent oxide thickness (EOT) to 0.9 nm with decreasing the hysteresis width and leakage current. The fabricated metal-insulator-semiconductor field-effect transistor (MISFET) with 2-step nitridation showed a steep subthreshold swing of 87 mV/dec.

Biometric template protection techniques have been proposed to address security and privacy issues inherent to biometric-based authentication systems. However, it has been shown that the robustness of most of such techniques against reversibility and linkability attacks are overestimated. Thus, a thorough security analysis of recently proposed template protection schemes has to be carried out. Negative iris recognition is an interesting iris template protection scheme based on the concept of negative databases. In this paper, we present a comprehensive security analysis of this scheme in order to validate its practical usefulness. Although the authors of negative iris recognition claim that their scheme possesses both irreversibility and unlinkability, we demonstrate that more than 75% of the original iris-code bits can be recovered using a single protected template. Moreover, we show that the negative iris recognition scheme is vulnerable to attacks via record multiplicity where an adversary can combine several transformed templates to recover more proportion of the original iris-code. Finally, we demonstrate that the scheme does not possess unlinkability. The experimental results, on the CASIA-IrisV3 Interval public database, support our theory and confirm that the negative iris recognition scheme is susceptible to reversibility, linkability, and record multiplicity attacks.

An LLC converter has high efficiency and low noise and has thus recently attracted attention in the field of power supplies for use in information and communication systems. A planar transformer is thought to be particularly effective in a high-frequency switching power supply because an ideal primary-secondary interleave structure can be formed by the multilayer structure, and the alternating-current (AC) resistance can be reduced. Based on these facts, we investigated the use of planar transformers in LLC converters. However, high-frequency oscillation, which is not observed in a normal winding transformer, appears in the secondary side current, and the power supply loss is also higher. Our investigation found that the current oscillation and an increase in loss were caused by a primary-secondary capacitance of the transformer. This paper presents countermeasures used to reduce the capacitance between the primary and secondary windings, and a new layer structure for the transformer that reduces the capacitance. The loss is calculated through a simulation and experimentally, and good agreement is obtained. The proposed transformer offers the high efficiency of 98.1% in a 200 W, 12 V output power supply.

A consecutive-k-out-of-n:G system consists of n components which are arranged in a line and the system works if and only if at least k consecutive components work. This paper discusses the optimization problems for a consecutive-k-out-of-n:G system. We first focus on the optimal number of components at the system design phase. Then, we focus on the optimal replacement time at the system operation phase by considering a preventive replacement, which the system is replaced at the planned time or the time of system failure which occurs first. The expected cost rates of two optimization problems are considered as objective functions to be minimized. Finally, we give study cases for the proposed optimization problems and evaluate the feasibility of the policies.

This paper considers a velocity control problem for merging and splitting maneuvers of vehicle platoons. In this paper, an external device sends velocity commands to some vehicles in the platoon, and the others adjust their velocities autonomously. The former is pinning control, and the latter is consensus control in multi-agent control. We propose a switched pinning control algorithm. Our algorithm consists of three sub-methods. The first is an optimal switching method of pinning agents based on an MLD (Mixed Logical Dynamical) system model and MPC (Model Predictive Control). The second is a representation method for dynamical platoon formation with merging and splitting maneuver. The platoon formation follows the positional relation between vehicles or the formation demand from the external device. The third is a switching reduction method by setting a cost function that penalizes the switching of the pinning agents in the steady-state. Our proposed algorithm enables us to improve the consensus speed. Moreover, our algorithm can regroup the platoons to the arbitrary platoons and control the velocities of the multiple vehicle platoons to each target value.

Differential code biases (DCBs) are important parameters that must be estimated accurately for precise positioning and Satellite Based Augmentation Systems (SBAS) ionospheric related parameter generation. In this paper, in order to solve the performance degradation problem of the traditional minimum STD searching algorithm in disturbed ionosphere status and in geomagnetic low latitudes, we propose a linear planar based minimum STD searching algorithm. Firstly, we demonstrate the linear planar trend of the local vertical TEC and introduce the linear planar model based minimum standard variance searching method. Secondly, we validate the correctness of our proposed method through theoretical analysis and propose bias detection to avoid large estimation bias. At last, we show the performance of our proposed method under different geomagnetic latitudes, different seasons and different ionosphere status. The experimental results show that for the traditional minimum STD searching algorithm based on constant model, latitude difference is the key factor affecting the performance of DCB estimation. The DCB estimation performance in geomagnetic mid latitudes is the best, followed by the high latitudes and the worst is for the low latitudes. While the algorithm proposed in this paper can effectively solve the performance degradation problem of DCB estimation in geomagnetic low latitudes by using the linear planar model which is with a higher degree of freedom to model the local ionosphere characteristics and design dJ to screen the epochs. Through the analysis of the DCB estimation results of a large number of stations, it can be found that the probability of large estimation deviation of the traditional method will increase obviously under the disturb ionosphere conditions, but the algorithm we proposed can effectively control the amplitude of the maximum deviation and alleviate the probability of large estimation deviation in disturb ionosphere status.

MATLAB/Simulink is the de facto standard tool for the model-based development (MBD) of control software for automotive systems. A Simulink model developed in MBD for real automotive systems involves complex computation as well as tens of thousands of blocks. In this paper, we focus on decision coverage (DC), condition coverage (CC) and modified condition/decision coverage (MC/DC) criteria, and propose a Monte-Carlo test suite generation method for large and complex Simulink models. In the method, a candidate test case is generated by assigning random values to the parameters of signal templates with specific waveforms. We try to find contributable candidates in a plausible and understandable search space, specified by a set of templates. We implemented the method as a tool, and our experimental evaluation showed that the tool was able to generate test suites for industrial implementation models with higher coverages and shorter execution times than Simulink Design Verifier. Additionally, the tool includes a fast coverage measurement engine, which demonstrated better performance than Simulink Coverage in our experiments.

When a unit repeats some works over again and undergoes minimal repairs at failures, it is more practical to replace it preventively at the end of working cycles or at its failure times. In this case, it would be an interesting problem to know which is better to replace the unit at a number of working cycles or at random failures from the point of cost. For this purpose, we give models of the expected cost rates for the following replacement policies: (1) The unit is replaced at a working cycle N and at a failure number K, respectively; (2) Replacement first and last policies with working cycle N and failure number K, respectively; (3) Replacement overtime policies with working cycle N and failure number K, respectively. Optimizations and comparisons of the policies for N and K are made analytically and numerically.

Under the framework of traditional power spectrum based feature extraction, in order to extract more discriminative information for playback attack detection, this paper proposes a feature by making use of deep neural network to describe the nonlinear relationship between power spectrum and discriminative information. Namely, constant-Q deep coefficients (CQDC). It relies on constant-Q transform, deep neural network and discrete cosine transform. In which, constant-Q transform is used to convert signal from the time domain into the frequency domain because it is a long-term transform that can provide more frequency detail, deep neural network is used to extract more discriminative information to discriminate playback speech from genuine speech and discrete cosine transform is used to decorrelate among the feature dimensions. ASVspoof 2017 corpus version 2.0 is used to evaluate the performance of CQDC. The experimental results show that CQDC outperforms the existing power spectrum obtained from constant-Q transform based features, and equal error can reduce from 19.18% to 51.56%. In addition, we found that discriminative information of CQDC hides in all frequency bins, which is different from commonly used features.

The requirement of safety, roadway capacity and efficiency in the vehicular network, which makes vehicular platoons concept continue to be of interest. For the authentication in vehicular platoons, efficiency and cooperation are the two most important things. Cooperative authentication is a way to recognize false identities and messages as well as saving resources. However, taking part in cooperative authentication makes the vehicle more vulnerable to privacy leakage which is commonly done by location tracking. Moreover, vehicles consume their resources when cooperating with others during the process of cooperation authentication. These two significant factors cause selfish behaviors of the vehicles not to participate in cooperate cooperation actively. In this paper, an infinitely repeated game for cooperative authentication in vehicular platoons is proposed to help analyze the utility of all nodes and point out the weakness of the current collaborative authentication protocol. To deal with this weakness, we also devised an enhanced cooperative authentication protocol based on mechanisms which makes it easier for vehicles to stay in the cooperate strategy rather than tend to selfish behavior. Meanwhile, our protocol can defense insider attacks.

With the recent advances in e-commerce, it has become important to recommend not only mass-produced daily items, such as books, but also items that are not mass-produced. In this study, we present an algorithm for real estate recommendations. Automatic property recommendations are a highly difficult task because no identical properties exist in the world, occupied properties cannot be recommended, and users rent or buy properties only a few times in their lives. For the first step of property recommendation, we predict users' preferences for properties by combining content-based filtering and Multi-Layer Perceptron (MLP). In the MLP, we use not only attribute data of users and properties, but also deep features extracted from property floor plan images. As a result, we successfully predict users' preference with a Matthews Correlation Coefficient (MCC) of 0.166.

To develop countermeasures against fault attacks, it is important to model an attacker's ability. The instruction skip model is a well-studied practical model for fault attacks on software. Contrastingly, few studies have investigated the instruction replacement model, which is a generalization of the instruction skip model, because replacing an instruction with a desired one is considered difficult. Some previous studies have reported successful instruction replacements; however, those studies concluded that such instruction replacements are not practical attacks because the outcomes of the replacements are uncontrollable. This paper proposes the concept of a controllable instruction replacement technique that uses the laser irradiation of flash memory. The feasibility of the proposed technique is demonstrated experimentally using a smartcard-type ARM SC100 microcontroller. Then, practical cryptosystem attacks that exploit the proposed technique are investigated. The targeted cryptosystems employ the AES with software-based anti-fault countermeasures. We demonstrate that an existing anti-instruction-skip countermeasure can be circumvented by replacing a critical instruction, e.g., a branch instruction to detect fault occurrence.