In this paper, we propose a robust output feedback control method for nonlinear systems with uncertain time-varying parameters associated with diagonal terms and there are additional external disturbances. First, we provide a new practical guidance of obtaining a compact set which contains the allowed time-varying parameters by utilizing a Lyapunov equation and matrix inequalities. Then, we show that all system states and observer errors of the controlled system remain bounded by the proposed controller. Moreover, we show that the ultimate bounds of some system states and observer errors can be made (arbitrarily) small by adjusting a gain-scaling factor depending on the system nonlinearity. With an application example, we illustrate the effectiveness of our control scheme over the existing one.

This paper proposes an id-eCK secure identity-based authenticated key exchange (ID-AKE) scheme, where the id-eCK security implies that a scheme resists against leakage of all combinations of master, static, and ephemeral secret keys except ones trivially break the security. Most existing id-eCK secure ID-AKE schemes require two symmetric pairing operations or a greater number of asymmetric pairing, which is faster than symmetric one, operations to establish a session key. However, our scheme is realized with a single asymmetric pairing operation for each party, and this is an advantage in efficiency. The proposed scheme is based on the ID-AKE scheme by McCullagh and Barreto, which is vulnerable to an active attack. To achieve id-eCK security, we apply the HMQV construction and the NAXOS technique to the McCullagh-Barreto scheme. The id-eCK security is proved under the external Diffie-Hellman for target group assumption and the q-gap-bilinear collision attack assumption.

High-speed serial data communication is essential for connecting peripherals in high-performance computing systems. Interlaken is a high-speed serial data communication protocol that has been widely adopted in various applications as it can run on multiple medias such as PCBs, blackplans or over cables. The Interlaken uses 64b/67b line coding to maintain the run length (RL) and the running disparity (RD) with the advantage of an inversion bit that indicates whether the receiver must flip the data or not. By using the inversion bit, it increases 1bit overhead to every data word. This paper proposes 64b/i67b line coding technique for encoding and decoding to improve the cumulative running disparity of 64b/67b without additional bit overhead. The results have been obtained from simulations that use random data and the Squash data set, and the proposed method reduces the maximum cumulative running disparity value up to 33%.

When applying estimation methods, the issue of outliers is inevitable. The extent of their influence has not been clarified, though several studies have evaluated outlier elimination methods. It is unclear whether we should always be sensitive to outliers, whether outliers should always be removed before estimation, and what amount of precaution is required for collecting project data. Therefore, the goal of this study is to illustrate a guideline that suggests how sensitively we should handle outliers. In the analysis, we experimentally add outliers to three datasets, to analyze their influence. We modified the percentage of outliers, their extent (e.g., we varied the actual effort from 100 to 200 person-hours when the extent was 100%), the variables including outliers (e.g., adding outliers to function points or effort), and the locations of outliers in a dataset. Next, the effort was estimated using these datasets. We used multiple linear regression analysis and analogy based estimation to estimate the development effort. The experimental results indicate that the influence of outliers on the estimation accuracy is non-trivial when the extent or percentage of outliers is considerable (i.e., 100% and 20%, respectively). In contrast, their influence is negligible when the extent and percentage are small (i.e., 50% and 10%, respectively). Moreover, in some cases, the linear regression analysis was less affected by outliers than analogy based estimation.

This paper proposes coded modulation for physical layer network coding in multiple input multiple output orthogonal frequency division multiplexing (MIMO-OFDM) bi-directional wireless relay systems where precoding is applied. The proposed coded modulation enables the relays to decode the received signals, which improves the transmission performance. Soft input decoding for the proposed coded modulation is proposed. Furthermore, we propose two precoder weight optimization techniques, called “per subcarrier weight optimization” and “total weight optimization”. This paper shows a precoder configuration based on the optimization with the lattice reduction or the sorted QR-decomposition. The performance of the proposed network coding is evaluated by computer simulation in a MIMO-OFDM two-hop wireless relay system with the 16 quadrature amplitude modulation (QAM) or the 256QAM. The proposed coded modulation attains a coding gain of about 2dB at the BER of 10-4. The total weight optimization achieves about 1dB better BER performance than the other at the BER of 10-4.

This paper presents the first attribute-based signature (ABS) scheme in which the correspondence between signers and signatures is captured in an arithmetic model of computation. Specifically, we design a fully secure, i.e., adaptively unforgeable and perfectly signer-private ABS scheme for signing policies realizable by arithmetic branching programs (ABP), which are a quite expressive model of arithmetic computations. On a more positive note, the proposed scheme places no bound on the size and input length of the supported signing policy ABP's, and at the same time, supports the use of an input attribute for an arbitrary number of times inside a signing policy ABP, i.e., the so called unbounded multi-use of attributes. The size of our public parameters is constant with respect to the sizes of the signing attribute vectors and signing policies available in the system. The construction is built in (asymmetric) bilinear groups of prime order, and its unforgeability is derived in the standard model under (asymmetric version of) the well-studied decisional linear (DLIN) assumption coupled with the existence of standard collision resistant hash functions. Due to the use of the arithmetic model as opposed to the boolean one, our ABS scheme not only excels significantly over the existing state-of-the-art constructions in terms of concrete efficiency, but also achieves improved applicability in various practical scenarios. Our principal technical contributions are (a) extending the techniques of Okamoto and Takashima [PKC 2011, PKC 2013], which were originally developed in the context of boolean span programs, to the arithmetic setting; and (b) innovating new ideas to allow unbounded multi-use of attributes inside ABP's, which themselves are of unbounded size and input length.

This paper proposes an image inpainting algorithm based on multiple linear models and matrix rank minimization. Several inpainting algorithms have been previously proposed based on the assumption that an image can be modeled using autoregressive (AR) models. However, these algorithms perform poorly when applied to natural photographs because they assume that an image is modeled by a position-invariant linear model with a fixed model order. In order to improve inpainting quality, this work introduces a multiple AR model and proposes an image inpainting algorithm based on multiple matrix rank minimization with sparse regularization. In doing so, a practical algorithm is provided based on the iterative partial matrix shrinkage algorithm, with numerical examples showing the effectiveness of the proposed algorithm.

Location and feature representation of object's parts play key roles in fine-grained visual recognition. To promote the final recognition accuracy without any bounding boxes/part annotations, many studies adopt object location networks to propose bounding boxes/part annotations with only category labels, and then crop the images into partial images to help the classification network make the final decision. In our work, to propose more informative partial images and effectively extract discriminative features from the original and partial images, we propose a two-stage approach that can fuse the original features and partial features by evaluating and ranking the information of partial images. Experimental results show that our proposed approach achieves excellent performance on two benchmark datasets, which demonstrates its effectiveness.

For low-density parity-check (LDPC) codes, the penalized decoding method based on the alternating direction method of multipliers (ADMM) can improve the decoding performance at low signal-to-noise ratios and also has low decoding complexity. There are three effective methods that could increase the ADMM penalized decoding speed, which are reducing the number of Euclidean projections in ADMM penalized decoding, designing an effective penalty function and selecting an appropriate layered scheduling strategy for message transmission. In order to further increase the ADMM penalized decoding speed, through reducing the number of Euclidean projections and using the vertical layered scheduling strategy, this paper designs a fast converging ADMM penalized decoding method based on the improved penalty function. Simulation results show that the proposed method not only improves the decoding performance but also reduces the average number of iterations and the average decoding time.

Mode-by-mode impulse responses, or spectral transfer matrix (STM) of birefringent fibers are measured by using linear optical sampling, with assist of polarization multiplexed probe pulse. By using the eigenvalue analysis of the STM, the differential mode delay and PMD vector of polarization-maintaining fiber are analyzed as a function of optical frequency over 1THz. We show that the amplitude averaging of the complex impulse responses is effective for enhancing the signal-to-noise ratio of the measurement, resulting in improving the accuracy and expanding the bandwidth of the measurement.

For actual multi-channel differential signaling system, the ideal balance or symmetrical topology cannot be established, and hence, an imbalance component is excited. However a theoretical analysis method of evaluating the voltage and current distribution on the differential-paired lines, which allows to anticipate EM radiation at the design stage and to study possible means for suppressing imbalance components, has not been implemented. To provide the basic considerations for electromagnetic (EM) radiation from practical asymmetrical differential-paired lines structure with equi-length routing used in high-speed board design, this paper newly proposes an analytical method for evaluating the voltage and current at any point on differential-paired lines by expressing the differential paired-lines with an equivalent source circuit and an equivalent load circuit. The proposed method can predict S-parameters, distributions of voltage and current and EM radiation with sufficient accuracy. In addition, the proposed method provides enough flexibility for different geometric parameters and can be used to develop physical insights and design guidelines. This study has successfully established a basic method to effectively predict signal integrity and EM interference issues on a differential-paired lines.

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.

Contextual information is a crucial factor in natural language processing tasks such as sequence labeling. Previous studies on contextualized embedding and word embedding have explored the context of word-level tokens in order to obtain useful features of languages. However, unlike it is the case in English, the fundamental task in East Asian languages is related to character-level tokens. In this paper, we propose a contextualized character embedding method using n-gram multi-sequences information with long short-term memory (LSTM). It is hypothesized that contextualized embeddings on multi-sequences in the task help each other deal with long-term contextual information such as the notion of spans and boundaries of segmentation. The analysis shows that the contextualized embedding of bigram character sequences encodes well the notion of spans and boundaries for word segmentation rather than that of unigram character sequences. We find out that the combination of contextualized embeddings from both unigram and bigram character sequences at output layer rather than the input layer of LSTMs improves the performance of word segmentation. The comparison showed that our proposed method outperforms the previous models.

In inter-data center networks where high transmission capacity and spectral efficiency are required, a 16QAM format is deployed. On the other hand, in intra-data center networks, a PAM4 format is deployed to meet the demand for a simple and low-cost transceiver configuration. For a seamless and effective connection of such heterogeneous networks without using optical-electrical-optical conversion, an all-optical modulation format conversion technique is required. In this paper, we propose an all-optical PAM4 to 16QAM modulation format conversion using nonlinear optical loop mirror. The successful conversion operation from 2 × 26.6-Gbaud PAM4 signals to a 100-Gbps class 16QAM signal is verified by numerical simulation. Compared with an ideal 16QAM signal, the power penalty of the converted 16QAM signal can be kept within 0.51dB.

We developed a polarization-independent and reserved-band-less complementary spectral inverted optical phase conjugation (CSI-OPC) device using dual-band difference frequency generation based on highly efficient periodically poled LiNbO3 waveguide technologies. To examine the nonlinearity mitigation in a long-haul transmission using a large number of OPCs, we installed a CSI-OPC device in the middle of a pure silica core fiber-based recirculating loop transmission line with a length of 320km. First, we examined the fiber-input power tolerance after 5,120-km and 6,400-km transmission using 22.5-Gbaud PDM-16QAM 10-channel DWDM signals and found a Q-factor improvement of over 1.3dB along with enhanced power tolerance thanks to mitigating the fiber nonlinearity. We then demonstrated transmission distance extension using the CSI-OPC device. The use of multiple CSI-OPCs enables an obvious performance improvements attained by extending the transmission distance from 6,400km to 8,960km, which corresponds to applying the CSI-OPC device 28 times. Moreover, there was no Q-factor degradation for the link in a linear regime after applying the CSI-OPC device more than 16 times. These results demonstrate that the CSI-OPC device can improve the nonlinear tolerance of PDM-16QAM signals without an excess penalty.

Road traffic collisions are an extremely serious and often fatal issue. One promising approach to mitigate such collisions is the use of connected car services that share road traffic information obtained from vehicles and cameras over mobile networks. In connected car services, it is important for data chunks to arrive at a destination node within a certain deadline constraint. In this paper, we define a flow from a vehicle (or camera) to the same vehicle (or camera) via an MEC server, as a mission critical (MC) flow, and call a deadline of the MC flow the MC deadline. Our research objective is to achieve a higher arrival ratio within the MC deadline for the MC flow that passes through both the radio uplink and downlink. We previously developed a deadline-aware scheduler with consideration for quality fluctuation (DAS-QF) that considers chunk size and a certain deadline constraint in addition to radio quality and utilizes these to prioritize users such that the deadline constraints are met. However, this DAS-QF does not consider that the congestion levels of evolved NodeB (eNB) differ depending on the eNB location, or that the uplink congestion level differs from the downlink congestion level in the same eNB. Therefore, in the DAS-QF, some data chunks of a MC flow are discarded in the eNB when they exceed either the uplink or downlink deadline in congestion, even if they do not exceed the MC deadline. In this paper, to reduce the eNB packet drop probability due to exceeding either the uplink and downlink deadline, we propose a deadline coordination function (DCF) that adaptively sets each of the uplink and downlink deadlines for the MC flow according to the congestion level of each link. Simulation results show that the DAS-QF with DCF offers higher arrival ratios within the MC deadline compared to DAS-QF on its own

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 proposes an active vibration-suppression control method for the systems with multiple disturbances using only the relative displacements and velocities. The controller can suppress the vibration of the main body in the world coordinate, where a velocity disturbance and a force disturbance affect the system simultaneously. The added device plays a similar role as an accelerometer, but we avoid the algebraic loop. The main idea of the feedback law is to convert a nonlinear system into an aseismatic desired system by using the energy shaping technique. A parameter selection procedure is derived by combining the constraints of nonlinear IDA-PBC and the evaluation of the control performance of the linearly approximated system. The effectiveness of the proposed method is confirmed by simulations for an example.

In this letter, a piecewise linear (PWL) sigmoid function approximation based on the statistical distribution probability of the neurons' values in each layer is proposed to improve the network recognition accuracy with only addition circuit. The sigmoid function is first divided into three fixed regions, and then according to the neurons' values distribution probability, the curve in each region is segmented into sub-regions to reduce the approximation error and improve the recognition accuracy. Experiments performed on Xilinx's FPGA-XC7A200T for MNIST and CIFAR-10 datasets show that the proposed method achieves 97.45% recognition accuracy in DNN, 98.42% in CNN on MNIST and 72.22% on CIFAR-10, up to 0.84%, 0.57% and 2.01% higher than other approximation methods with only addition circuit.

In this letter, the principle of LLR-based successive-cancellation (SC) polar decoding algorithm is explored. In order to simplify the logarithm and exponential operations in the updating rules for polar codes, we further utilize a piece-wise linear algorithm to approximate the transcendental functions, where the piece-wise linear algorithm only consists of multiplication and addition operations. It is demonstrated that with one properly allowable maximum error δ chosen for success-failure algorithm, performances approach to that of the standard SC algorithm can be achieved. Besides, the complexity reduction is realized by calculating a linear function instead of nonlinear function. Simulation results show that our proposed piece-wise SC decoder greatly reduces the complexity of the SC-based decoders with no loss in error correcting performance.