In this letter, we propose a supervised bimodal emotion recognition approach based on two important human emotion modalities including facial expression and body gesture. A effectively supervised feature fusion algorithms named supervised multiset canonical correlation analysis (SMCCA) is presented to established the linear connection between three sets of matrices, which contain the feature matrix of two modalities and their concurrent category matrix. The test results in the bimodal emotion recognition of the FABO database show that the SMCCA algorithm can get better or considerable efficiency than unsupervised feature fusion algorithm covering canonical correlation analysis (CCA), sparse canonical correlation analysis (SCCA), multiset canonical correlation analysis (MCCA) and so on.

To achieve high end-to-end availability in nationwide optical transport network across thousands of office buildings, it is important to properly make each function redundant, and execute protection switching, repair failed functions and recover redundancy to prevent multiple simultaneous failures. High redundancy leads to high system cost and high power consumption, and tight conditions for recovery leads to high maintenance cost. Therefore it is important to optimize the balance between redundancy and maintenance condition based on appropriate availability indicators. We previously proposed a resource-pool control mechanism for a nationwide optical transport network that can optimize the balance. This paper proposes an end-to-end availability evaluation scheme for a nationwide optical transport network with our mechanism, by which network operators can design the pool-resource amount of each function and the maintenance conditions for each network area properly to satisfy the end-to-end availability requirement. Although the maintenance conditions are usually discussed based on failure-recovery times, they should be discussed based on cost- or load-based volumes for this design. This paper proposes a maintenance-operation-load evaluation scheme, which derives the required number of maintenance staff members from failure-recovery times. We also discuss the design of the pool-resource amount and maintenance conditions for each network area of a nationwide network based on the proposed evaluation schemes.

When trying to estimate time-varying multipath channels by applying a basis expansion model (BEM) in orthogonal frequency division multiplexing (OFDM) systems, pilot clusters are contaminated by inter-carrier interference (ICI). The pilot cluster ICI (PC-ICI) degrades the estimation accuracy of BEM coefficients, which degrades system performance. In this paper, a PC-ICI suppression scheme is proposed, in which two coded symbols defined as weighted sums of data symbols are inserted on both sides of each pilot cluster. Under the assumption that the channel has Flat Doppler spectrum, the optimized weight coefficients are obtained by an alternating iterative optimization algorithm, so that the sum of the PC-ICI generated by the encoded symbols and the data symbols is minimized. By approximating the optimized weight coefficients, they are independent of the channel tap power. Furthermore, it is verified that the proposed scheme is robust to the estimation error of the normalized Doppler frequency offset and can be applied to channels with other types of Doppler spectra. Numerical simulation results show that, compared with the conventional schemes, the proposed scheme achieves significant improvements in the performance of PC-ICI suppression, channel estimation and system bit-error-ratio (BER).

Wireless information and power transfer technology is a promising means of supplying power for remote terminals in future communication systems. This paper investigates time-splitting (TS) recource allocation schemes for multi-cell massive MIMO systems with downlink (DL) wireless power transfer and uplink (UL) user information transmission under a harvest-then-transmit protocol. In order to jointly optimize the power and time allocation, two power minimization problems are formulated under different constraints on the minimal quality-of-service (QoS) requirement. Then, these original non-convex problems are transformed into their convex approximated ones which can be solved iteratively by successive convex approximation. Simulation results show that by exploiting the diversity effect of large-scale antenna arrays, the complexity-reduced asymptotic recourse allocation scheme almost match the power efficiency of the nonasymptotic scheme.

In this paper, we propose a novel primary user detection scheme for spectrum sensing in cognitive radio. Inspired by the conventional signal classification approach, the spectrum sensing is translated into a classification problem. On the basis of feature-based classification, the spectral correlation of a second-order cyclostationary analysis is applied as the feature extraction method, whereas a stacked denoising autoencoders network is applied as the classifier. Two training methods for signal detection, interception-based detection and simulation-based detection, are considered, for different prior information and implementation conditions. In an interception-based detection method, inspired by the two-step sensing, we obtain training data from the interception of actual signals after a sophisticated sensing procedure, to achieve detection without priori information. In addition, benefiting from practical training data, this interception-based detection is superior under actual transmission environment conditions. The alternative, a simulation-based detection method utilizes some undisguised parameters of the primary user in the spectrum of interest. Owing to the diversified predetermined training data, simulation-based detection exhibits transcendental robustness against harsh noise environments, although it demands a more complicated classifier network structure. Additionally, for the above-described training methods, we discuss the classifier complexity over implementation conditions and the trade-off between robustness and detection performance. The simulation results show the advantages of the proposed method over conventional spectrum-sensing schemes.

In this paper, we developed saccade-induced line displays including flashing period controllers. The displays speeded up the flashing period of one line using LED drivers and Arduino Uno equipped with AVR microcomputers. It was shown that saccades were easily induced when the observer alternately looks at the two fast flashing line displays apart. Also, we were able to find the optimum flashing period using a controller that can speed up the flashing period and change its speed. We found that the relationship between the viewing angle of the observer and the optimum flashing period is almost proportional.

Recently, a control technique of light distribution pattern has become important to improve the functionality and the light utilization efficiency of electronic displays, illumination devices and so on. As a light control technique, polymer-dispersed liquid crystals (PDLCs) have been commonly used so far. However, a precise control of the light diffusion distribution of conventional PDLC has been difficult due to the random polymer network structure, which results in the low light utilization efficiency. On the other hand, reverse-mode PDLCs with homogeneously aligned molecules can anisotropically diffuse light. The reverse-mode PDLC, however, has polarization dependency in the haze value due to homogeneously aligned molecules, which also results in the low light utilization efficiency. Therefore, it is necessary to establish the optimization method of light diffusion distribution without the molecules alignment treatment, and we have proposed a novel PDLC with structure-controlled polymer network which was fabricated by the irradiation with uni-directionally diffused UV light. In this paper, we investigated the effect of the process temperature during UV irradiation on the internal structure and light diffusion distribution of the proposed PDLC. As a result, in case that the mixture during UV irradiation was in isotropic phase, we clarified that the structure-controlled PDLCs with alternating striped LCs/polymer pattern could be obtained because the mixture was sufficiently irradiated with uni-directionally diffused UV light. For the high haze, this structure-controlled PDLC should be fabricated as low temperature as possible with maintaining the mixture in isotropic phase so that the mixture was not a nano-scaled molecular mixing state. Also, this PDLC had no polarization dependency in the haze value and could electrically switch the light distribution pattern between anisotropic light diffusion and light transmission. From the above results, we concluded that the proposed PDLC could precisely control the light diffusion distribution, and realize the high light utilization efficiency.

Computer-generated hologram based on ray-sampling plane method was newly applied to the projection-type holographic display that consists of the holographic projection and the holographic optical element screen. In the proposed method, geometric deformation characteristic of the holographic image via the display system was mathematically derived and canceled out by the coordinate transformation of ray-sampling condition to avoid the image distortion. In the experiment, holographic image reconstruction with the arbitral depth expression without image distortion could be optically demonstrated.

In this paper, we examined the transfer method of fluororesin as the novel formation method of polymer wall in order to realize the lattice-shaped polymer walls without patterned light irradiation using photomask. We clarified that the transfer method was effective for formation of polymer wall structure on flexible substrate.

We have proposed a mortar-shaped structure to improve response time and alignment uniformity of twisted vertically aligned (TVA) mode liquid crystal displays (LCDs) for high-contrast reflective color LCDs. From the results of the simulation, we clarified that response time, alignment uniformity and viewing angle range of TVA-mode LCDs were improved by controlling the liquid crystal alignment axis-symmetrically in each pixel.

We have developed the high speed bandpass liquid crystal filter with narrow full width at half maximum (FWHM) of 5nm for real-time multi spectral imaging systems. We have successfully achieved short wavelength-switching time of 30ms by the optimization of phase retardation of thin liquid crystal cells.

Security researchers/vendors detect malicious websites based on several website features extracted by honeyclient analysis. However, web-based attacks continue to be more sophisticated along with the development of countermeasure techniques. Attackers detect the honeyclient and evade analysis using sophisticated JavaScript code. The evasive code indirectly identifies vulnerable clients by abusing the differences among JavaScript implementations. Attackers deliver malware only to targeted clients on the basis of the evasion results while avoiding honeyclient analysis. Therefore, we are faced with a problem in that honeyclients cannot analyze malicious websites. Nevertheless, we can observe the evasion nature, i.e., the results in accessing malicious websites by using targeted clients are different from those by using honeyclients. In this paper, we propose a method of extracting evasive code by leveraging the above differences to investigate current evasion techniques. Our method analyzes HTTP transactions of the same website obtained using two types of clients, a real browser as a targeted client and a browser emulator as a honeyclient. As a result of evaluating our method with 8,467 JavaScript samples executed in 20,272 malicious websites, we discovered previously unknown evasion techniques that abuse the differences among JavaScript implementations. These findings will contribute to improving the analysis capabilities of conventional honeyclients.

Data breach and data destruction attack have become the critical security threats for the ICT (Information and Communication Technology) infrastructure. Both the Internet service providers and users are suffering from the cyber threats especially those to confidential data and private information. The requirements of human social activities make people move carrying confidential data and data breach always happens during the transportation. The Internet connectivity and cryptographic technology have made the usage of confidential data much secure. However, even with the high deployment rate of the Internet infrastructure, the concerns for lack of the Internet connectivity make people carry data with their mobile devices. In this paper, we describe the main patterns of data breach occur on mobile devices and propose a secure in-depth file system concealed by GPS-based mounting authentication to mitigate data breach on mobile devices. In the proposed in-depth file system, data can be stored based on the level of credential with corresponding authentication policy and the mounting operation will be only successful on designated locations. We implemented a prototype system using Veracrypt and Perl language and confirmed that the in-depth file system worked exactly as we expected by evaluations on two locations. The contribution of this paper includes the clarification that GPS-based mounting authentication for a file system can reduce the risk of data breach for mobile devices and a realization of prototype system.

Bitcoin is the leading cryptocurrency in the world with a total marketcap of nearly USD 33 billion, [1] with 370,000 transactions recorded daily[2]. Pseudo-anonymous, decentralized peer-to-peer electronic cash systems such as Bitcoin have caused a paradigm shift in the way that people conduct financial transactions and purchase goods. Although cryptocurrencies enable users to securely and anonymously exchange money, they can also facilitate illegal criminal activities. Therefore, it is imperative that law enforcement agencies develop appropriate analytical processes that will allow them to identify and investigate criminal activities in the Blockchain (a distributed ledger). In this paper, INTERPOL, through the INTERPOL Global Complex for Innovation, proposes a Bitcoin analytical framework and a software system that will assist law enforcement agencies in the real-time analysis of the Blockchain while providing digital crime analysts with tracing and visualization capabilities. By doing so, it is feasible to render transactions decipherable and comprehensible for law enforcement investigators and prosecutors. The proposed solution is evaluated against three criminal case studies linked to Darknet markets, ransomware and DDoS extortion.

This paper presents an efficient acceleration algorithm for Lloyd-type k-means clustering, which is suitable to a large-scale and high-dimensional data set with potentially numerous classes. The algorithm employs a novel projection-based filter (PRJ) to avoid unnecessary distance calculations, resulting in high-speed performance keeping the same results as a standard Lloyd's algorithm. The PRJ exploits a summable lower bound on a squared distance defined in a lower-dimensional space to which data points are projected. The summable lower bound can make the bound tighter dynamically by incremental addition of components in the lower-dimensional space within each iteration although the existing lower bounds used in other acceleration algorithms work only once as a fixed filter. Experimental results on large-scale and high-dimensional real image data sets demonstrate that the proposed algorithm works at high speed and with low memory consumption when large k values are given, compared with the state-of-the-art algorithms.

High-performance computing (HPC) has penetrated into various research fields, yet the increase in computing power is limited by conventional electrical interconnections. The proposed architecture, NEST, exploits wavelength routing in arrayed waveguide grating routers (AWGRs) to achieve a scalable, low-latency, and high-throughput network. For the intra pod and inter pod communication, the symmetrical topology of NEST reduces the network diameter, which leads to an increase in latency performance. Moreover, the proposed architecture enables exponential growth of network size. Simulation results demonstrate that NEST shows 36% latency improvement and 30% throughput improvement over the dragonfly on an average.

Recently, the demand for the digitization of manga is increased. Then, in the case of an old manga where the original pictures have been lost, we have to digitize it from comics. However, the show-through phenomenon would be caused by scanning of the comics since it is represented as the double sided images. This letter proposes the manga show-through cancellation method based on the deep convolutional neural network (CNN). Numerical results show that the effectiveness of the proposed method.

Visual tracking has been studied for several decades but continues to draw significant attention because of its critical role in many applications. This letter handles the problem of fixed template size in Kernelized Correlation Filter (KCF) tracker with no significant decrease in the speed. Extensive experiments are performed on the new OTB dataset.

A new hybrid brain-computer interface (BCI), which is based on sequential controls by eye tracking and steady-state visual evoked potentials (SSVEPs), has been proposed for high-speed spelling in virtual reality (VR) with a 40-target virtual keyboard. During target selection, gaze point was first detected by an eye-tracking accessory. A 4-target block was then selected for further target selection by a 4-class SSVEP BCI. The system can type at a speed of 1.25 character/sec in a cue-guided target selection task. Online experiments on three subjects achieved an averaged information transfer rate (ITR) of 360.7 bits/min.

Automatic monitoring of food intake in free living conditions is still an open problem to solve. This paper presents a novel necklace-type wearable system embedded with a piezoelectric sensor to monitor ingestive behavior by detecting skin motion from the lower trachea. Detected events are incorporated for food classification. Unlike the previous state-of-the-art piezoelectric sensor based system that employs spectrogram features, we have tried to fully exploit time-domain based signals for optimal features. Through numerous evaluations on the length of a frame, we have found the best performance with a frame length of 70 samples (3.5 seconds). This demonstrates that the chewing sequence carries important information for food classification. Experimental results show the validity of the proposed algorithm for food intake detection and food classification in real-life scenarios. Our system yields an accuracy of 89.2% for food intake detection and 80.3% for food classification over 17 food categories. Additionally, our system is based on a smartphone app, which helps users live healthy by providing them with real-time feedback about their ingested food episodes and types.