This paper describes the effectiveness of the geometric multi-grid method in a current density analysis using a numerical human body model. The scalar potential finite difference (SPFD) method is used as a numerical method for analyzing the current density inside a human body due to contact with charged objects in a low-frequency band, and research related to methods to solve faster large-scale simultaneous equations based on the SPFD method has been conducted. In previous research, the block incomplete Cholesky conjugate gradients (ICCG) method is proposed as an effective method to solve the simultaneous equations faster. However, even though the block ICCG method is used, many iterations are still needed. Therefore, in this study, we focus on the geometric multi-grid method as a method to solve the problem. We develop the geometric-multi-grid method and evaluate performances by comparing it with the block ICCG method in terms of computation time and the number of iterations. The results show that the number of iterations needed for the geometric multi-grid method is much less than that for the block ICCG method. In addition, the computation time is much shorter, depending on the number of threads and the number of coarse grids. Also, by using multi-color ordering, the parallel performance of the geometric multi-grid method can be greatly improved.

This paper discusses a static analysis problem, called absolute consistency problem, for relational schema mappings. A given schema mapping is said to be absolutely consistent if every source instance has a corresponding target instance. Absolute consistency is an important property because it guarantees that data exchange never fails for any source instance. Originally, for XML schema mappings, the absolute consistency problem was defined and its complexity was investigated by Amano et al. However, as far as the authors know, there are no known results for relational schema mappings. In this paper, we focus on relational schema mappings such that both the source and the target schemas have functional dependencies, under the assumption that mapping rules are defined by constant-free tuple-generating dependencies. In this setting, we show that the absolute consistency problem is in coNP. We also show that it is solvable in polynomial time if the tuple-generating dependencies are full and the size of the left-hand side of each functional dependency is bounded by some constant. Finally, we show that the absolute consistency problem is coNP-hard even if the source schema has no functional dependency and the target schema has only one; or each of the source and the target schemas has only one functional dependency such that the size of the left-hand side of the functional dependency is at most two.

The security and reliability of Arabic text exchanged via the Internet have become a challenging area for the research community. Arabic text is very sensitive to modify by malicious attacks and easy to make changes on diacritics i.e. Fat-ha, Kasra and Damma, which are represent the syntax of Arabic language and can make the meaning is differing. In this paper, a Hybrid of Natural Language Processing and Zero-Watermarking Approach (HNLPZWA) has been proposed for the content authentication and tampering detection of Arabic text. The HNLPZWA approach embeds and detects the watermark logically without altering the original text document to embed a watermark key. Fifth level order of word mechanism based on hidden Markov model is integrated with digital zero-watermarking techniques to improve the tampering detection accuracy issues of the previous literature proposed by the researchers. Fifth-level order of Markov model is used as a natural language processing technique in order to analyze the Arabic text. Moreover, it extracts the features of interrelationship between contexts of the text and utilizes the extracted features as watermark information and validates it later with attacked Arabic text to detect any tampering occurred on it. HNLPZWA has been implemented using PHP with VS code IDE. Tampering detection accuracy of HNLPZWA is proved with experiments using four datasets of varying lengths under multiple random locations of insertion, reorder and deletion attacks of experimental datasets. The experimental results show that HNLPZWA is more sensitive for all kinds of tampering attacks with high level accuracy of tampering detection.

Secure multi-party computation (MPC) allows a set of parties to compute a function jointly while keeping their inputs private. MPC has been actively studied, and there are many research results both in the theoretical and practical research fields. In this paper, we introduce the basic matters on MPC and show recent practical advances. We first explain the settings, security notions, and cryptographic building blocks of MPC. Then, we show and discuss current situations on higher-level secure protocols, privacy-preserving data analysis, and frameworks/compilers for implementing MPC applications with low-cost.

Phase-based video magnification methods can magnify and reveal subtle motion changes invisible to the naked eye. In these methods, each image frame in a video is decomposed into an image pyramid, and subtle motion changes are then detected as local phase changes with arbitrary orientations at each pixel and each pyramid level. One problem with this process is a long computational time to calculate the local phase changes, which makes high-speed processing of video magnification difficult. Recently, a decomposition technique called the Riesz pyramid has been proposed that detects only local phase changes in the dominant orientation. This technique can remove the arbitrariness of orientations and lower the over-completeness, thus achieving high-speed processing. However, as the resolution of input video increases, a large amount of data must be processed, requiring a long computational time. In this paper, we focus on the correlation of local phase changes between adjacent pyramid levels and present a novel decomposition technique called the local Riesz pyramid that enables faster phase-based video magnification by automatically processing the minimum number of sufficient local image areas at several pyramid levels. Through this minimum pyramid processing, our proposed phase-based video magnification method using the local Riesz pyramid achieves good magnification results within a short computational time.

Radio frequency energy transfer (RET) technology has been introduced as a promising energy harvesting (EH) method to supply power in both wireless communication (WLC) and power-line communication (PLC) systems. However, current RET modified MAC (medium access control) protocols have been proposed only for WLC systems. Due to the difference in the MAC standard between WLC and PLC systems, these protocols are not suitable for PLC systems. Therefore, how to utilize RET technology to modify the MAC protocol of PLC systems (i.e., IEEE 1901), which can use the radio frequency signal to provide the transmission power and the PLC medium to finish the data transmission, i.e., realizing the ‘cooperative communication’ remains a challenge. To resolve this problem, we propose a RET modified MAC protocol for PLC systems (RET-PLC MAC). Firstly, we improve the standard PLC frame sequence by adding consultation and confirmation frames, so that the station can obtain suitable harvested energy, once it occupied the PLC medium, and the PLC system can be operated in an on-demand and self-sustainable manner. On this basis, we present the working principle of RET-PLC MAC. Then, we establish an analytical model to allow mathematical verification of RET-PLC MAC. A 2-dimension discrete Markov chain model is employed to derive the numerical analysis results of RET-PLC MAC. The impacts of buffer size, traffic rate, deferral counter process of 1901, heterogeneous environment and quality of information (QoI) are comprehensively considered in the modeling process. Moreover, we deduce the optimal results of system throughput and expected QoI. Through extensive simulations, we show the performance of RET-PLC MAC under different system parameters, and verify the corresponding analytical model. Our work provides insights into realizing cooperative communication at PLC's MAC layer.

This paper presents a comparative loss analysis performed between an LLC converter and a phase-shift converter under the same size conditions using a power supply manufactured for information communications equipment. It is also shown herein that the LLC converter has a much higher ratio of transformer loss to total loss than the phase-shift converter and that the cause is the difference in the number of transformer turns between the two converters. Further, the ON-resistance of the secondary-side rectifier element and the number of transformer primary turns are shown to determine which of the two converters is superior in terms of low loss.

Wireless full duplex (FD) communication can double the point-to-point throughput. To fully realize the benefits of the FD technique in wireless local area networks (WLANs), it is important to design the medium access control (MAC) protocols for FD communications. In FD MAC protocols, when a node wins the channel contention and transmits a primary transmission, its destination node can start a secondary transmission triggered by the primary transmission. Each secondary transmitter transmits a data frame even if its backoff timer is not zero. However, the backoff scheme in the FD MAC protocols follows the conventional scheme based on the distributed coordination function (DCF). Therefore, the nodes with FD MAC initialize the contention window (CW) size to minimum CW (CWmin) after their successful secondary transmissions. Therefore, CW initialization in the FD MAC causes further collisions at stations (STAs), which degrades network throughput. This paper proposes a novel backoff scheme for FD MAC protocols. In the proposed scheme, the CW size and backoff timer are not initialized but kept the current value after secondary transmissions. The proposed scheme can mitigate frame collisions at STAs and increase FD-transmission opportunity in the network, and then enhance the throughput significantly. This paper presents comprehensive performance evaluation in simulations, including non-saturation and saturation conditions, and co-existence conditions with legacy half duplex (HD) STAs. For performance analysis, this paper establishes Markov-chain models for the proposed scheme. The analytical results show theoretically that the operation of the proposed scheme enhances network throughput. The simulation results and analytical results show the effectiveness of the proposed scheme.

Matching circuits using LC elements are widely applied to high-frequency circuits such as power amplifier (PA) and low-noise amplifier (LNA). For determining matching condition of multi-stage matching circuits, this paper shows that any multi-stage LC-Ladder matching circuit with resistive termination can be decomposed to the extended L-type matching circuits with resistive termination containing negative elements where the analytical solution exists. The matching conditions of each extended L-type matching circuit are obtained easily from the termination resistances and the design frequency. By synthesizing these simple analysis solutions, it is possible to systematically determine the solution even in a large number of stages (high order) matching circuits.

This study focuses on computer based foreign language vocabulary learning systems. Our objective is to automatically build vocabulary decks with desired levels of relative difficulty relations. To realize this goal, we exploit the fact that word frequency is a good indicator of vocabulary difficulty. Subsequently, for composing the decks, we pose two requirements as uniformity and diversity. Namely, the difficulty level of the cards in the same deck needs to be uniform enough so that they can be grouped together and difficulty levels of the cards in different decks need to be diverse enough so that they can be grouped in different decks. To assess uniformity and diversity, we use rank-biserial correlation and propose an iterative algorithm, which helps in attaining desired levels of uniformity and diversity based on word frequency in daily use of language. In experiments, we employed a spaced repetition flashcard software and presented users various decks built with the proposed algorithm, which contain cards from different content types. From users' activity logs, we derived several behavioral variables and examined the polyserial correlation between these variables and difficulty levels across different word classes. This analysis confirmed that the decks compiled with the proposed algorithm induce an effect on behavioral variables in line with the expectations. In addition, a series of experiments with decks involving varying content types confirmed that this relation is independent of word class.

This paper presents an analysis of the relationship between noise and bandwidth in visible light communication (VLC) systems. In the past few years, pre-emphasis and post-equalization techniques were proposed to extend the bandwidth of VLC systems. However, these bandwidth extension techniques also influence noise and sensitivity of the VLC systems. In this paper, first, we build a system model of VLC transceivers and circuit models of pre-emphasis and post-equalization. Next, we theoretically compare the bandwidth and noise of three different transceiver structures comprising a single pre-emphasis circuit, a single post-equalization circuit and a combination of pre-emphasis and post-equalization circuits. Finally, we validate the presented theoretical analysis using experimental results. The result shows that for the same resonant frequency, and for high signal-to-noise ratio (S/N), VLC systems employing post-equalization or pre-emphasis have the same bandwidth extension ability. Therefore, a transceiver employing both the pre-emphasis and post-equalization techniques has a bandwidth √2 times the bandwidth of the systems employing only the pre-emphasis or post-equalization. Based on the theoretical analysis of noise, the VLC system with only active pre-emphasis shows the lowest noise, which is a good choice for low-noise systems. The result of this paper may provide a new perspective of noise and sensitivity of the bandwidth extension techniques in VLC systems.

We address the security issue of RSA with implicitly related keys in this paper. Informally, we investigate under what condition is it possible to efficiently factorize RSA moduli in polynomial time given implicit relation of the related private keys that certain portions of bit pattern are the same. We formulate concrete attack scenarios and propose lattice-based cryptanalysis by using lattice reduction algorithms. A subtle lattice technique is adapted to represent an unknown private key with the help of known implicit relation. We analyze a simple case when given two RSA instances with the known amount of shared most significant bits (MSBs) and least significant bits (LSBs) of the private keys. We further extend to a generic lattice-based attack for given more RSA instances with implicitly related keys. Our theoretical results indicate that RSA with implicitly related keys is more insecure and better asymptotic results can be achieved as the number of RSA instances increases. Furthermore, we conduct numerical experiments to verify the validity of the proposed attacks.

An increasing number of IoT devices are being introduced to the market in many industries, and the number of devices is expected to exceed billions in the near future. With this trend, many researchers have proposed new architectures to manage IoT devices, but the proposed architecture requires a huge memory footprint and computation overheads to look-up billions of devices. This paper proposes a hybrid hashing architecture called H- TLA to solve the problem from an architectural point of view, instead of modifying a hashing algorithm or designing a new one. We implemented a prototype system that shows about a 30% increase in performance while conserving uniformity. Therefore, we show an efficient architecture-level approach for addressing billions of devices.

Previously, dynamic multi-hop shortcut (DMHS) communications to improve packet delivery rate and reduce end-to-end transmission delay was proposed. In this letter, we theoretically derive the end-to-end throughput of DMHS considering the retransmission at each node for a simple network model without considering collision. Moreover, we show the validity of the derived expression using computer simulations, and we clarify the effect of various parameters on the throughput using DMHS.

In a dense wireless network, concurrent transmissions normally increase interference and reduce network performance. In such an environment, however, there is a possibility that a frame can be decoded correctly if its receive power is higher than that of another frame by some predefined value (i.e., the so-called capture effect). As a result, the unfairness of throughputs among network nodes likely occurs in that context. This research aims to quantify the throughput performance of only one access point Wireless Local Area Networks (WLANs) with dense network nodes in the presence of the capture effect. We first propose a new analytical model, which can express not only WLANs' throughputs but also WLANs' unfairness transmission. The validity of the proposed model is confirmed by simulation results. Second, relying on the model, we present a novel Medium Access Control (MAC) protocol-based solution, which realizes throughput fairness between network nodes induced by the capture effect.

This work aims to determine the propensity of password creation through the lens of language spheres. To this end, we consider four different countries, each with a different culture/language: China/Chinese, United Kingdom (UK) and India/English, and Japan/Japanese. We first employ a user study to verify whether language and culture are reflected in password creation. We found that users in India, Japan, and the UK prefer to create their passwords from base words, and the kinds of words they are incorporated into passwords vary between countries. We then test whether the findings obtained through the user study are reflected in a corpus of leaked passwords. We found that users in China and Japan prefer dates, while users in India, Japan, and the UK prefer names. We also found that cultural words (e.g., “sakura” in Japan and “football” in the UK) are frequently used to create passwords. Finally, we demonstrate that the knowledge on the linguistic background of targeted users can be exploited to increase the speed of the password guessing process.

We have designed gate arrays using low-temperature poly-Si thin-film transistors and confirmed the correct operations. Various kinds of logic gates are beforehand prepared, contact holes are later bored, and mutual wiring is formed between the logic gates on demand. A half adder, two-bit decoder, and flip flop are composed as examples. The static behaviors are evaluated, and it is confirmed that the correct waveforms are output. The dynamic behaviors are also evaluated, and it is concluded that the dynamic behaviors of the gate array are less deteriorated than that of the independent circuit.

Full duplex (FD) communication can potentially double the throughput of a point-to-point link in wireless communication. Additionally, FD communication can mitigate the hidden node collision problem. The MAC protocols for FD communications are classified into two types; synchronous FD MAC and asynchronous one. Though the synchronous FD MAC mitigates hidden node collisions by using control frame, overhead duration for each data frame transmission may be a bottleneck for the networks. On the other hand, the asynchronous FD MAC mitigates the hidden node collisions by FD communication. However, it wastes more time due to transmission failure than synchronous FD MAC. Clarifying the effect of two major FD MAC types on networks requires a quantitative evaluation of the effectiveness of these protocols in networks with hidden node collisions. This paper proposes performance analysis of FD MAC protocols for wireless local area networks with hidden node collisions. Through the proposed analytical model, the saturated throughputs in FD WLANs with both asynchronous and synchronous FD MAC for any number of STAs and any payload size can be obtained.

This paper describes a novel approach to flexible control of speaker characteristics using tensor representation of multiple Gaussian mixture models (GMM). In voice conversion studies, realization of conversion from/to an arbitrary speaker's voice is one of the important objectives. For this purpose, eigenvoice conversion (EVC) based on an eigenvoice GMM (EV-GMM) was proposed. In the EVC, a speaker space is constructed based on GMM supervectors which are high-dimensional vectors derived by concatenating the mean vectors of each of the speaker GMMs. In the speaker space, each speaker is represented by a small number of weight parameters of eigen-supervectors. In this paper, we revisit construction of the speaker space by introducing the tensor factor analysis of training data set. In our approach, each speaker is represented as a matrix of which the row and the column respectively correspond to the dimension of the mean vector and the Gaussian component. The speaker space is derived by the tensor factor analysis of the set of the matrices. Our approach can solve an inherent problem of supervector representation, and it improves the performance of voice conversion. In addition, in this paper, effects of speaker adaptive training before factorization are also investigated. Experimental results of one-to-many voice conversion demonstrate the effectiveness of the proposed approach.

This paper proposes a method to create various training images for instance segmentation in a semi-supervised manner. In our proposed learning scheme, a few 3D CG models of target objects and a large number of images retrieved by keywords from the Internet are employed for initial model training and model update, respectively. Instance segmentation requires pixel-level annotations as well as object class labels in all training images. A possible solution to reduce a huge annotation cost is to use synthesized images as training images. While image synthesis using a 3D CG simulator can generate the annotations automatically, it is difficult to prepare a variety of 3D object models for the simulator. One more possible solution is semi-supervised learning. Semi-supervised learning such as self-training uses a small set of supervised data and a huge number of unsupervised data. The supervised images are given by the 3D CG simulator in our method. From the unsupervised images, we have to select only correctly-detected annotations. For selecting the correctly-detected annotations, we propose to quantify the reliability of each detected annotation based on its silhouette as well as its textures. Experimental results demonstrate that the proposed method can generate more various images for improving instance segmentation.