This paper proposes a novel image integral equation of the first type (IIE-1) for a TE plane wave scattering from periodic rough surfaces with perfect conductivity by means of the method of image Green's function. Since such an IIE-1 is valid for any incident wavenumbers including the critical wavenumbers, the analytical properties of the scattered wavefield can be generally and rigorously discussed. This paper firstly points out that the branch point singularity of the bare propagator inevitably appears on the incident wavenumber characteristics of the scattered wavefield and its related quantities just at the critical wavenumbers. By applying a quadrature method, the IIE-1 becomes a matrix equation to be numerically solved. For a periodic rough surface, several properties of the scattering are shown in figures as functions of the incident wavenumbers. It is then confirmed that the branch point singularity clearly appears in the numerical solution. Moreover, it is shown that the proposed IIE-1 gives a numerical solution satisfying sufficiently the optical theorem even for the critical wavenumbers.

Flexible resource utilization in terms of adaptive use of optical bandwidth with agile reconfigurability is key for future metro networks. To address this issue, we focus on optical subwavelength switched network architectures that leverage high-speed optical switching technologies and can accommodate dynamic traffic cost-effectively. Although optical subwavelength switched networks have been attracting attention, most conventional studies apply static (pre-planned) protection scenarios in the networks of limited sizes. In this paper, we discuss optical switch requirements, the use of transceivers, and protection schemes to cost-effectively create large-scale reliable metro networks. We also propose a cost-effective adaptive protection scheme appropriate for optical subwavelength switched networks using our fast time-slot allocation algorithm. The proposed scheme periodically re-optimizes the bandwidth of both working and protection paths to prevent bandwidth resources from being wasted. The numerical examples verify the feasibility of our proposed scheme and the impact on network resources.

Conversion between multi-level modulation formats is one of key processing functions for flexible networking aimed at high spectral efficiency (SE) in optical fiber transmission. The authors previously proposed an all-optical format conversion system from binary phase-shift keying (BPSK) to quadrature PSK (QPSK) and reported an experimental demonstration. In this paper, we consider its reversed conversion, that is, from QPSK to BPSK. The proposed system consists of a highly nonlinear fiber used to generate complex conjugate signal, and a 3-dB directional coupler used to produce converted signals by interfering the incident signal with the complex conjugate signal. The incident QPSK stream is converted into two BPSK tributaries without any loss of transmitting data. We show the system performances such as bit-error-rate and optical signal-to-noise ratio penalty evaluated by numerical simulation.

Compared to the traditional functional dependency (FD), the extended conditional functional dependency (CFD) has shown greater potential for detecting and repairing inconsistent data. CFDMiner is a widely used algorithm for mining constant-CFDs. But the search space of CFDMiner is too large, and there is still room for efficiency improvement. In this paper, an efficient pruning strategy is proposed to optimize the algorithm by reducing the search space. Both theoretical analysis and experiments have proved the optimized algorithm can produce the consistent results as the original CFDMiner.

In everyday life, people use past events and their own knowledge in predicting probable unfolding of events. To obtain the necessary knowledge for such predictions, newspapers and the Internet provide a general source of information. Newspapers contain various expressions describing past events, but also current and future events, and opinions. In our research we focused on automatically obtaining sentences that make reference to the future. Such sentences can contain expressions that not only explicitly refer to future events, but could also refer to past or current events. For example, if people read a news article that states “In the near future, there will be an upward trend in the price of gasoline,” they may be likely to buy gasoline now. However, if the article says “The cost of gasoline has just risen 10 yen per liter,” people will not rush to buy gasoline, because they accept this as reality and may expect the cost to decrease in the future. In the following study we firstly investigate future reference sentences in newspapers and Web news. Next, we propose a method for automatic extraction of such sentences by using semantic role labels, without typical approaches (temporal expressions, etc.). In a series of experiments, we extract semantic role patterns from future reference sentences and examine the validity of the extracted patterns in classification of future reference sentences.

In this paper, we propose a communication-efficient top-k continuous query processing method on distributed local nodes where data are horizontally partitioned. A designated coordinator server takes the role of issuing queries from users to local nodes and delivering the results to users. The final results are requested via a top-k subscription which lets local nodes know which data and updates need to be returned to users. Our proposed method makes use of the active previously posed queries to identify a small set of needed top-k subscriptions. In addition, with the pre-indexed nodes' skylines, the number of local nodes to be subscribed can be significantly reduced. As a result, only a small number of subscriptions are informed to a small number of local nodes resulting in lower communication overhead. Furthermore, according to dynamic data updates, we also propose a method that prevents nodes from reporting needless updates and also maintenance procedures to preserve the consistency. The results of experiments that measure the volume of transferred data show that our proposed method significantly outperforms the previously proposed methods.

Virtualization is no longer an emerging research area since the virtual processor and memory operate as efficiently as the physical ones. However, I/O performance is still restricted by the virtualization overhead caused by the costly and complex I/O virtualization mechanism, in particular by massive exits occurring on the guest-host switch and redundant processing of the I/O stacks at both guest and host. A para-virtual device driver may reduce the number of exits to the hypervisor, whereas the network stacks in the guest OS are still duplicated. Previous work proposed a socket-outsourcing technique that bypasses the redundant guest network stack by delivering the network request directly to the host. However, even by bypassing the redundant network paths in the guest OS, the obtained performance was still below 60% of the native device, since notifications of completion still depended on the hypervisor. In this paper, we propose vCanal, a novel network virtualization framework, to improve the performance of network access in the virtual machine toward that of the native machine. Implementation of vCanal reached 96% of the native TCP throughput, increasing the UDP latency by only 4% compared to the native latency.

This paper gives an array-based practical encoder for the lossless data compression algorithm known as Compression by Substring Enumeration (CSE). The encoder makes use of the relation between CSE and the Burrows-Wheeler transform. We also modify the decoding algorithm to accommodate to the proposed encoder. Thanks to the proposed encoder and decoder, we can apply CSE to long data of more than tens of megabytes. We show compression results obtained when we perform experiments on such long data. The results empirically validate theoretical predictions on CSE.

In a public-key encryption scheme, if a sender is not concerned about the security of a message and is unwilling to generate costly randomness, the security of the encrypted message can be compromised. In this work, we characterize such lazy parties, who are regarded as honest parties, but are unwilling to perform a costly task when they are not concerned about the security. Specifically, we consider a rather simple setting in which the costly task is to generate randomness used in algorithms, and parties can choose either perfect randomness or a fixed string. We model lazy parties as rational players who behave rationally to maximize their utilities, and define a security game between the parties and an adversary. Since a standard secure encryption scheme does not work in this setting, we provide constructions of secure encryption schemes in various settings.

The feasibility condition of interference alignment (IA) for multiple-input multiple-output two-way interference channel is studied in this paper. A necessary condition and a sufficient condition on the IA feasibility are established and the sum degrees of freedom (DoF) for a broad class of network topologies is characterized. The numerical results demonstrate that two-way operation with appropriate IA is able to achieve larger sum DoF than the conventional one-way operation.

Random forest regressor has recently been proposed as a local landmark estimator in the face alignment problem. It has been shown that random forest regressor can achieve accurate, fast, and robust performance when coupled with a global face-shape regularizer. In this paper, we extend this approach and propose a new Local Forest Classification and Regression (LFCR) framework in order to handle face images with large yaw angles. Specifically, the LFCR has an additional classification step prior to the regression step. Our experiment results show that this additional classification step is useful in rejecting outliers prior to the regression step, thus improving the face alignment results. We also analyze each system component through detailed experiments. In addition to the selection of feature descriptors and several important tuning parameters of the random forest regressor, we examine different initialization and shape regularization processes. We compare our best outcomes to the state-of-the-art system and show that our method outperforms other parametric shape-fitting approaches.

The acquisition of accurate channel state information at the transmitter (CSIT) is a difficult task in multiple-input multiple-output (MIMO) systems. Partial CSIT is a more realistic assumption, especially for high-mobility mobile users (MUs) whose channel varies very rapidly. In this letter, we propose a MIMO two-way relaying (MTWR) scheme, in which the communication between the BS and a high-mobility MU is assisted by other low-mobility MUs serving as relays. This produces a beamforming effect that can significantly improve the performance of the high-mobility MU, especially for a large number of MUs and unreliable CSIT.

In this paper, we formulate an optimal stabilization problem of quantitative discrete event systems (DESs) under partial observation. A DES under partial observation is a system where its behaviors cannot be completely observed by a supervisor. In our framework, the supervisor observes not only masked events but also masked states. Our problem is then to synthesize a supervisor that drives the DES to a given target state with the minimum cost based on the detected sequences of masked events and states. We propose an algorithm for deciding the existence of an optimal stabilizing supervisor, and compute it if it exists.

Tag collision has a negative impact on the performance of RFID systems. In this letter, we propose an algorithm termed anti-collision protocol based on improved collision detection (ACP-ICD). In this protocol, dual prefixes matching and collision bit detection technique are employed to reduce the number of queries and promptly identify tags. According to the dual prefixes matching method and collision bit detection in the process of collision arbitration, idle slots are eliminated. Moreover, the reader makes full use of collision to improve identification efficiency. Both analytical and simulation results are presented to show that the performance of ACP-ICD outperforms existing anti-collision algorithms.

This paper presents a novel MEMD interval thresholding denoising, where relevant modes are selected by the similarity measure between the probability density functions of the input and that of each mode. Simulation and measured EEG data processing results show that the proposed scheme achieves better performance than other traditional denoisings.

It is known that in the selected mapping (SLM) scheme for orthogonal frequency division multiplexing (OFDM), correlation (CORR) metric outperforms the peak-to-average power ratio (PAPR) metric in terms of bit error rate (BER) performance. It is also well known that four times oversampling is used for estimating the PAPR performance of continuous OFDM signal. In this paper, the oversampling effect of OFDM signal is analyzed when CORR metric is used for the SLM scheme in the presence of nonlinear high power amplifier. An analysis based on the correlation coefficients of the oversampled OFDM signals shows that CORR metric of two times oversampling in the SLM scheme is good enough to achieve the same BER performance as four times and 16 times oversampling cases. Simulation results confirm that for the SLM scheme using CORR metric, the BER performance for two times oversampling case is almost the same as that for four and 16 times oversampling cases.

Computer networks require sophisticated control mechanisms to realize fair resource allocation among users in conjunction with efficient resource usage. To successfully realize fair resource allocation in a network, someone should control the behavior of each user by considering fairness. To provide efficient resource utilization, someone should control the behavior of all users by considering efficiency. To realize both control goals with different granularities at the same time, a hierarchical network control mechanism that combines microscopic control (i.e., fairness control) and macroscopic control (i.e., efficiency control) is required. In previous works, Aida proposed the concept of chaos-based hierarchical network control. Next, as an application of the chaos-based concept, Aida designed a fundamental framework of hierarchical transmission rate control based on the chaos of coupled relaxation oscillators. To clarify the realization of the chaos-based concept, one should specify the chaos-based hierarchical transmission rate control in enough detail to work in an actual network, and confirm that it works as intended. In this study, we implement the chaos-based hierarchical transmission rate control in a popular network simulator, ns-2, and confirm its operation through our experimentation. Results verify that the chaos-based concept can be successfully realized in TCP/IP networks.

Many actual systems, e.g. computer programs, can be modeled as a subclass of Petri nets, called bridge-less workflow nets. For bridge-less workflow nets, we revealed the following properties: (i) any acyclic bridge-less workflow net is free choice; (ii) an acyclic bridge-less workflow net is sound iff it is well-structured; and (iii) any sound bridge-less workflow net is well-structured. We also proposed a necessary and sufficient condition to decide whether a given workflow net is bridge-less, and then constructed a polynomial-time procedure for it.

Dynamic instruction window resizing (DIWR) is a scheme that effectively exploits both memory-level parallelism and instruction-level parallelism by configuring the instruction window size appropriately for exploiting each parallelism. Although a previous study has shown that the DIWR processor achieves a significant speedup, power consumption has not been explored. The power consumption is increased in DIWR because the instruction window resources are enlarged in memory-intensive phases. If the power consumption exceeds the power budget determined by certain requirements, the DIWR processor must save power and thus, the performance previously presented cannot be achieved. In this paper, we explore to what extent the DIWR processor can achieve improved performance for a given power budget, assuming that dynamic voltage and frequency scaling (DVFS) is introduced as a power saving technique. Evaluation results using the SPEC2006 benchmark programs show that the DIWR processor, even with a constrained power budget, achieves a speedup over the conventional processor over a wide range of given power budgets. At the most important power budget point, i.e., when the power a conventional processor consumes without any power constraint is supplied, DIWR achieves a 16% speedup.

Noise and area consumption has been a trade-off in circuit design. Especially for switched-capacitor filters (SCF), kT/C noise gives a limitation to the minimum value of unit capacitance. In case of SCFs with a large capacitance spread, this limitation will result in a large area consumption due to large capacitors. This paper introduces a technique to reduce capacitance spread using charge scaling. It will be shown that this technique can reduce total capacitance of SCFs without deteriorating their noise performances. A design method to reduce the output noise of SC low-pass filters (LPF) based on the combination of cut-set scaling, charge scaling and adaptive configuration is proposed. The proposed technique can reduce the output noise voltage by 30% for small input signals.