In this study, we develop a numerical method for determining transient energy deposition in biological bodies exposed to electromagnetic (EM) pulses. We use a newly developed frequency-dependent finite-difference time-domain (FD2TD) method, which is combined with the fast inverse Laplace transform (FILT) and Prony method. The FILT and Prony method are utilized to transform the Cole-Cole model of biological media into a sum of multiple Debye relaxation terms. Parameters of Debye terms are then extracted by comparison with the time-domain impulse responses. The extracted parameters are used in an FDTD formulation, which is derived using the auxiliary differential equation method, and transient energy deposition into a biological medium is calculated by the equivalent circuit method. The validity of our proposed method is demonstrated by comparing numerical results and those derived from an analytical method. Finally, transient energy deposition into human heads of TARO and HANAKO models is then calculated using the proposed method and, physical insights into pulse exposures of the human heads are provided.

Website Fingerprinting (WF) enables a passive attacker to identify which website a user is visiting over an encrypted tunnel. Current WF attacks have two strong assumptions: (i) specific tunnel, i.e., the attacker can train on traffic samples collected in a simulated tunnel with the same tunnel settings as the user, and (ii) pseudo-open-world, where the attacker has access to training samples of unmonitored sites and treats them as a separate class. These assumptions, while experimentally feasible, render WF attacks less usable in practice. In this paper, we present Gene Fingerprinting (GF), a new WF attack that achieves cross-tunnel transferability by generating fingerprints that reflect the intrinsic profile of a website. The attack leverages Zero-shot Learning — a machine learning technique not requiring training samples to identify a given class — to reduce the effort to collect data from different tunnels and achieve a real open-world. We demonstrate the attack performance using three popular tunneling tools: OpenSSH, Shadowsocks, and OpenVPN. The GF attack attains over 94% accuracy on each tunnel, far better than existing CUMUL, DF, and DDTW attacks. In the more realistic open-world scenario, the attack still obtains 88% TPR and 9% FPR, outperforming the state-of-the-art attacks. These results highlight the danger of our attack in various scenarios where gathering and training on a tunnel-specific dataset would be impractical.

A variety of smart services are being provided on multiple virtual networks embedded into a common inter-cloud substrate network. The substrate network operator deploys critical substrate nodes so that multiple service providers can achieve enhanced services due to the secure sharing of their service data. Even if one of the critical substrate nodes incurs damage, resiliency of the enhanced services can be assured due to reallocation of the workload and periodic backup of the service data to the other normal critical substrate nodes. However, the connectivity of the embedded virtual networks must be maintained so that the enhanced services can be continuously provided to all clients on the virtual networks. This paper considers resilient virtual network embedding (VNE) that ensures the connectivity of the embedded virtual networks after critical substrate node failures have occurred. The resilient VNE problem is formulated using an integer linear programming model and a distance-based method is proposed to solve the large-scale resilient VNE problem efficiently. Simulation results demonstrate that the distance-based method can derive a sub-optimum VNE solution with a small computational effort. The method derived a VNE solution with an approximation ratio of less than 1.2 within ten seconds in all the simulation experiments.

Because processes run concurrently in multitask systems, the size of the state space grows exponentially. Therefore, it is not straightforward to formally verify that such systems enjoy desired properties. Real-time constrains make the formal verification more challenging. In this paper, we propose the following to address the challenge: (1) a way to model multitask real-time systems as observational transition systems (OTSs), a kind of state transition systems, (2) a way to describe their specifications in CafeOBJ, an algebraic specification language, and (3) a way to verify that such systems enjoy desired properties based on such formal specifications by writing proof scores, proof plans, in CafeOBJ. As a case study, we model Fischer's protocol, a well-known real-time mutual exclusion protocol, as an OTS, describe its specification in CafeOBJ, and verify that the protocol enjoys the mutual exclusion property when an arbitrary number of processes participates in the protocol*.

We consider a reliable decentralized supervisory control problem for discrete event systems in the inference-based framework. This problem requires us to synthesize local supervisors such that the controlled system achieves the specification and is nonblocking, even if local control decisions of some local supervisors are not available for making the global control decision. In the case of single-level inference, we introduce a notion of reliable 1-inference-observability and show that reliable 1-inference-observability together with controllability and Lm(G)-closedness is a necessary and sufficient condition for the existence of a solution to the reliable decentralized supervisory control problem.

In this paper, a novel method of resource abstraction and an abstracted-resource model for dynamic resource control in optical access networks are proposed. Based on this proposal, an implementation assuming application to 5G mobile fronthaul and backhaul is presented. Finally, an evaluation of the processing time for resource allocation using this method is performed using a software prototype of the control function. From the results of the evaluation, it is confirmed that the proposed method offers better characteristics than former approaches, and is suitable for dynamic resource control in 5G applications.

Various electromagnetic (EM) wave applications have become commonplace, and humans are frequently exposed to EM waves. Therefore, the effect of EM waves on the human body should be evaluated. In this study, we focused on the specific absorption rate (SAR) due to the EM waves emitted from smartphones, developed high-resolution numerical smartphone models, and studied the SAR variation by changing the position and tilt angle (the angle between the display of the smartphone model and horizontal plane) of the smartphone models vis-à-vis the human abdomen, assuming the use of the smartphone at various tilt angles in front of the abdomen. The calculations showed that the surface shape of the human model influenced the SAR variation.

We present detailed measurements and analysis of the guided acoustic wave Brillouin scattering (GAWBS)-induced depolarization noise in a multi-core fiber (MCF) used for a digital coherent optical transmission. We first describe the GAWBS-induced depolarization noise in an uncoupled four-core fiber (4CF) with a 125μm cladding and compare the depolarization noise spectrum with that of a standard single-mode fiber (SSMF). We found that off-center cores in the 4CF are dominantly affected by higher-order TRn,m modes rather than the TR2,m mode unlike in the center core, and the total power of the depolarization noise in the 4CF was almost the same as that in the SSMF. We also report measurement results for the GAWBS-induced depolarization noise in an uncoupled 19-core fiber with a 240μm cladding. The results indicate that the amounts of depolarization noise generated in the cores are almost identical. Finally, we evaluate the influence of GAWBS-induced polarization crosstalk (XT) on a coherent QAM transmission. We found that the XT limits the achievable multiplicity of the QAM signal to 64 in a transoceanic transmission with an MCF.

Unsupervised Feature selection is an important dimensionality reduction technique to cope with high-dimensional data. It does not require prior label information, and has recently attracted much attention. However, it cannot fully utilize the discriminative information of samples, which may affect the feature selection performance. To tackle this problem, in this letter, we propose a novel discriminative virtual label regression method (DVLR) for unsupervised feature selection. In DVLR, we develop a virtual label regression function to guide the subspace learning based feature selection, which can select more discriminative features. Moreover, a linear discriminant analysis (LDA) term is used to make the model be more discriminative. To further make the model be more robust and select more representative features, we impose the ℓ2,1-norm on the regression and feature selection terms. Finally, extensive experiments are carried out on several public datasets, and the results demonstrate that our proposed DVLR achieves better performance than several state-of-the-art unsupervised feature selection methods.

Reboot-based recovery is a simple but powerful method to recover applications from failures and unstable states. Reboot-based recovery faces a challenge to apply it to a new type of applications, in-memory databases (DBs). Unlike legacy applications, since rebooting in-memory DBs loses memory objects including key-value pairs and DB blocks, it is required to restore them, causing severe performance degradation after the reboot. This paper presents an approach that allows us to perform reboot-based recovery of in-memory DBs with lower performance degradation. Our key insight is to decouple data content objects from all the memory objects. Our approach treats data items as data content objects, preserves data content objects on memory across reboots, and enforces restarted in-memory DBs to attach them. To show the effectiveness of our approach, we elaborate the idea into two real-world DBs, MyRocks and memcached. The prototypes successfully mitigate performance degradation after their reboot-based recovery.

In this paper, an ultra-thin wave absorber using a resistive patch array closely-placed in front of a back-metal is designed. The positively large susceptance is required for the patch array to cancel out the negatively large input susceptance of the short-circuited ultra-thin spacer behind the array. It is found that the array needs the gap of 1mm, sheet resistance of less than 20Ω/sq. and patch width of more than 15mm to obtain the zero input susceptance of the absorber with the 1/30 wavelength spacer. Moreover, these parameters were designed considering the electromagnetic coupling between the array and back-metal, and the square patch array absorbers with the thickness from 1/30 to 1/150 wavelength were designed.

The sum rate performance of nonlinier quantized precoding using Gibbs sampling are evaluated in a massive multiuser multiple-input multiple-output (MU-MIMO) system in this paper. Massive MU-MIMO is a key technology to handle the growth of data traffic. In a full digital massive MU-MIMO system, however, the resolution of digital-to-analogue converters (DACs) in transmit antenna branches have to be low to yield acceptable power consumption. Thus, a combinational optimization problem is solved for the nonlinier quantized precoding to determine transmit signals from finite alphabets output from low resolution DACs. A conventional optimization criterion minimizes errors between desired signals and received signals at user equipments (UEs). However, the system sum rate may decrease as it increases the transmit power. This paper proposes two optimization criteria that take the transmit power into account in order to maximize the sum rate. Mixed Gibbs sampling is applied to obtain the suboptimal solution of the nonlinear optimization problem. Numerical results obtained through computer simulations show that the two proposed criteria achieve higher sum rates than the conventional criterion. On the other hand, the sum rate criterion achieves the largest sum rate while it leads to less throughputs than the MMSE criterion on approximately 60% of subcarriers.

Water detection is important for machine vision applications such as visual inspection and robot motion planning. In this paper, we propose an approach to per-pixel water detection on unknown surfaces with a hyperspectral image. Our proposed method is based on the water spectral characteristics: water is transparent for visible light but translucent/opaque for near-infrared light and therefore the apparent near-infrared spectral reflectance of a surface is smaller than the original one when water is present on it. Specifically, we use a linear combination of a small number of basis vector to approximate the spectral reflectance and estimate the original near-infrared reflectance from the visible reflectance (which does not depend on the presence or absence of water) to detect water. We conducted a number of experiments using real images and show that our method, which estimates near-infrared spectral reflectance based on the visible spectral reflectance, has better performance than existing techniques.

The fifth-generation (5G) mobile communications system initially introduced massive multiple-input multiple-output (M-MIMO) with analog beamforming (BF) to compensate for the larger path-loss in millimeter-wave (mmW) bands. To solve a coverage issue and support high mobility of the mmW bands, base station (BS) cooperation technologies have been investigated in high-mobility environments. However, previous works assume one mobile station (MS) scenario and analog BF that does not suppress interference among MSs. In order to improve system performance in the mmW bands, fully digital BF that includes digital precoding should be employed to suppress the interference even when MSs travel in high mobility. This paper proposes two mmW BS cooperation technologies that are inter-baseband unit (inter-BBU) and intra-BBU cooperation for the fully digital BF. The inter-BBU cooperation exploits two M-MIMO antennas in two BBUs connected to one central unit by limited-bandwidth fronthaul, and the intra-BBU cooperates two M-MIMO antennas connected to one BBU with Doppler frequency shift compensation. This paper verifies effectiveness of the BS cooperation technologies by both computer simulations and outdoor experimental trials. First, it is shown that that the intra-BBU cooperation can achieve an excellent transmission performance in cases of two and four MSs moving at a velocity of 90km/h by computer simulations. Second, the outdoor experimental trials clarifies that the inter-BBU cooperation maintains the maximum throughput in a wider area than non-BS cooperation when only one MS moves at a maximum velocity of 120km/h.

In a multiple-input multiple-output (MIMO) system, maximum likelihood detection (MLD) is the best demodulation scheme if no a priori information is available. However, the complexity of MLD increases exponentially with the number of signal streams. Therefore, various demodulation schemes with less complexity have been proposed and some of those schemes show performance close to that of MLD. One kind of those schemes uses a Gibbs sampling (GS) algorithm. GS MIMO detection that combines feedback from turbo decoding has been proposed. In this scheme, the accuracy of GS MIMO detection is improved by feeding back loglikelihood ratios (LLRs) from a turbo decoder. In this paper, GS MIMO detection using only feedback LLRs from a turbo decoder is proposed. Through extrinsic information transfer (EXIT) chart analysis, it is shown that the EXIT curves with and without metrics calculated from received signals overlap as the feedback LLR values increase. Therefore, the proposed scheme calculates the metrics from received signals only for the first GS MIMO detection and the selection probabilities of GS MIMO detection in the following iterations are calculated based only on the LLRs from turbo decoders. Numerical results obtained through computer simulation show that the performance of proposed GS turbo MIMO detection is worse than that of conventional GS turbo MIMO detection when the number of GS iterations is small. However the performance improves as the number of GS iterations increases. When the number of GS iterations is 30 or more, the bit error rate (BER) performance of the proposed scheme is equivalent to that of the conventional scheme. Therefore, the proposed scheme can reduce the computational complexity of selection probability calculation in GS turbo MIMO detection.

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 this paper, mixed Gibbs sampling multiple-input multiple-output (MIMO) detection with forcible search is proposed. In conventional Gibbs sampling MIMO detection, the problem of stalling occurs under high signal-to-noise ratios (SNRs) which degrades the detection performance. Mixed Gibbs sampling (MGS) is one solution to this problem. In MGS, random sampling is carried out with a constant probability regardless of whether a current search falls into a local minimum. In the proposed scheme, combined with MGS, multiple candidate symbols are forcibly changed when the search is captured by a local minimum. The search restarts away from the local minimum which effectively enlarges the search area in the solution space. Numerical results obtained through computer simulation show that the proposed scheme achieves better performance in a large scale MIMO system with QPSK signals.

This paper proposes a distributed observer on a sensor network, where communication on the network is randomly performed. This work is a natural extension of Kalman consensus filter approach to the cases involving random communication. In both bidirectional and unidirectional communication cases, gain conditions that guarantee improvement of estimation error convergence compared to the case with no communication are obtained. The obtained conditions are more practical than those of previous studies and give appropriate cooperative gains for a given communication probability. The effectiveness of the proposed method is confirmed by computer simulations.

We consider the bisimilarity control problem for partially observed nondeterministic discrete event systems with deterministic specifications. This problem requires us to synthesize a supervisor that achieves bisimulation equivalence of the supervised system and the deterministic specification under partial observation. We present necessary and sufficient conditions for the existence of such a deterministic supervisor and show that these conditions can be verified polynomially.

Air discharge immunity testing for electronic equipment is specified in the standard 61000-4-2 of the International Eelectrotechnical Commission (IEC) under the climatic conditions of temperature (T) from 15 to 35 degrees Celsius and relative humidity (RH) from 30 to 60%. This implies that the air discharge testing is likely to provide significantly different test results due to the wide climatic range. To clarify effects of the above climatic conditions on air discharge testing, we previously measured air discharge currents from an electrostatic discharge (ESD) generator with test voltages from 2kV to 15kV at an approach speed of 80mm/s under 6 combinations of T and RH in the IEC specified range and non-specified climatic range. The result showed that the same absolute humidity (AH), which is determined by T and RH, provides almost the identical waveforms of the discharge currents despite different T and RH, and also that the current peaks at higher test voltages decrease as the AH increases. In this study, we further examine the combined effects of air discharges on test voltages, T, RH and AH with respect to two different approach speeds of 20mm/s and 80mm/s. As a result, the approach speed of 80mm/s is confirmed to provide the same results as the previous ones under the identical climatic conditions, whereas at a test voltage of 15kV under the IEC specified climatic conditions over 30% RH, the 20mm/s approach speed yields current waveforms entirely different from those at 80mm/s despite the same AH, and the peaks are basically unaffected by the AH. Under the IEC non-specified climatic conditions with RH less than 20%, however, the peaks decrease at higher test voltages as the AH increases. These findings obtained imply that under the same AH condition, at 80mm/s the air discharge peak is not almost affected by the RH, while at 20mm/s the lower the RH is, the higher is the peak on air discharge current.