Recent progress in research on the finite element method (FEM) for optical waveguide design and analysis is reviewed, focusing on the author's works. After briefly reviewing fundamentals of FEM such as a theoretical framework, a conventional nodal element, a newly developed edge element to eliminate nonphysical, spurious solutions, and a perfectly matched layer to avoid undesirable reflections from computational window edges, various FEM techniques for a guided-mode analysis, a beam propagation analysis, and a waveguide discontinuity analysis are described. Some design examples are introduced, including current research activities on multi-core fibers.

We propose a power-saving mechanism (PSM) specific to request-and-response-based applications, which simply changes the order of the operating procedure of the legacy PSM by considering the attributes of the request-and-response delay. We numerically analyze the PSM with respect to the energy consumption and buffering delay and characterize this performance by employing a simple energy-delay trade-off (EDT) curve that is determined by the operating parameters. The resulting EDT curve clearly shows that the proposed PSM outperforms the legacy PSM.

This paper describes experiments on passive Multiple-Input Multiple-Output (MIMO) transmission with load modulation. PIN diodes are used as the variable impedance element at the tag side to realize multi-level modulation. The results indicate that the transmission rate of passive MIMO is up to 2 times higher than that of Single-Input Single-Output (SISO) with the same transmission power when the distance between the reader and the tag is 0.5m. Also, when the distance is 1m, MIMO offers up to 1.7 times higher transmission rate than SISO. These results indicate that passive MIMO offers high-speed data transmission even when the distance is doubled.

Cloud computing has rising as a new popular service paradigm with typical advantages as ease of use, unlimited resources and pay-as-you-go pricing model. Cloud resources are more flexible and cost-effective than private or colocation resources thus more suitable for storing the outdated backup data that are infrequently accessed by continuous data protection (CDP) systems. However, the cloud achieves low cost at the same time may slow down the recovery procedure due to its low bandwidth and high latency. In this paper, a novel block-level CDP system architecture: MYCDP is proposed to utilize cloud resources as the back-end storage. Unlike traditional delta-encoding based CDP approaches which should traverse all the dependent versions and decode the recovery point, MYCDP adopts data deduplication mechanism to eliminate data redundancy between all versions of all blocks, and constructs a version index for all versions of the protected storage, thus it can use a query-and-fetch process to recover version data. And with a specific version index data structure and a disk/memory hybrid cache module, MYCDP reduces the storage space consumption and data transfer between local and cloud. It also supports deletion of arbitrary versions without risk of invalidating some other versions. Experimental results demonstrate that MYCDP can achieve much lower cost than traditional local based CDP approaches, while remaining almost the same recovery speed with the local based deduplication approach for most recovery cases. Furthermore, MYCDP can obtain both faster recovery and lower cost than cloud based delta-encoding CDP approaches for any recovery points. And MYCDP gets more profits while protecting multiple systems together.

Smart city services are implemented using various data collected from houses and infrastructure within a city. As the volume and variety of the smart city data becomes huge, individual services have suffered from expensive computation effort and large processing time. In order to reduce the effort and time, this paper proposes a concept of Materialized View as a Service (MVaaS). Using the MVaaS, every application can easily and dynamically construct its own materialized view, in which the raw data is converted and stored in a convenient format with appropriate granularity. Thus, once the view is constructed, the application can quickly access necessary data. In this paper, we design a framework of MVaaS specifically for large-scale house log, managed in a smart-city data platform. In the framework, each application first specifies how the raw data should be filtered, grouped and aggregated. For a given data specification, MVaaS dynamically constructs a MapReduce batch program that converts the raw data into a desired view. The batch is then executed on Hadoop, and the resultant view is stored in HBase. We present case studies using house log in a real home network system. We also conduct an experimental evaluation to compare the response time between cases with and without MVaaS.

With the advances in wireless Internet and mobile positioning technology, location-based services (LBSs) have become popular. In LBSs, users must send their exact locations in order to use the services, but they may be subject to several privacy threats. To solve this problem, query processing algorithms based on a cloaking method have been proposed. The algorithms use spatial cloaking methods to blur the user's exact location in a region satisfying the required privacy threshold (k). With the cloaked region, an LBS server can execute a spatial query processing algorithm preserving their privacy. However, the existing algorithms cannot provide good query processing performance. To resolve this problem, we, in this paper, propose a k-NN query processing algorithm based on network Voronoi diagram for spatial networks. Therefore, our algorithm can reduce network expansion overhead and share the information of the expanded road network. In order to demonstrate the efficiency of our algorithms, we have conducted extensive performance evaluations. The results show that our algorithm achieves better performance on retrieval time than the existing algorithms, such as PSNN and kRNN. This is because our k-NN query processing algorithm can greatly reduce a network expansion cost for retrieving k POIs.

Coalition Structure Generation (CSG) is a main research issue in the domain of coalition games. A majority of existing works assume that the value of a coalition is independent of others in the coalition structure. Recently, there has been interest in a more realistic settings, where the value of a coalition is affected by the formation of other coalitions. This effect is known as externality. The focus of this paper is to make use of Maximum Satisfiability (MaxSAT) to solve the CSG problem where externalities may exist. In order to reduce the exponentially growing number of possible solutions in the CSG problem, we follow the previous works by representing the CSG problem as sets of rules in MC-nets (without externalities) and embedded MC-nets (with externalities). Specifically, enlightened by the previous MC-net-based algorithms exploiting the constraints among rule relations to solve the CSG problem, we encode such constraints into weighted partial MaxSAT (WPM) formulas. Experimental results demonstrate that an off-the-shelf MaxSAT solver achieves significant improvements compared to the previous algorithm for the same set of problem instances.

In recent years, computation offloading, through which applications on a mobile device can offload their computations onto more resource-rich clouds, has emerged as a promising technique to reduce battery consumption as well as augment the devices' limited computation and memory capabilities. In order for computation offloading to be energy-efficient, an accurate estimate of battery consumption is required to decide between local processing and computation offloading. In this paper, we propose a novel technique for estimating battery consumption without requiring detailed information about the mobile application's internal structure or its execution behavior. In our approach, the relationship is derived between variables that affect battery consumption (i.e., the input to the application, the transmitted data, and resource status) and the actual consumed energy from the application's past run history. We evaluated the performance of the proposed technique using two different types of mobile applications over different wireless network environments such as 3G, Wi-Fi, and LTE. The experimental results show that our technique can provide tolerable estimation accuracy and thus make correct decisions between local processing and computation offloading.

We address the problem of estimating the difference between two probability densities. A naive approach is a two-step procedure that first estimates two densities separately and then computes their difference. However, such a two-step procedure does not necessarily work well because the first step is performed without regard to the second step and thus a small error in the first stage can cause a big error in the second stage. Recently, a single-shot method called the least-squares density-difference (LSDD) estimator has been proposed. LSDD directly estimates the density difference without separately estimating two densities, and it was demonstrated to outperform the two-step approach. In this paper, we propose a variation of LSDD called the constrained least-squares density-difference (CLSDD) estimator, and theoretically prove that CLSDD improves the accuracy of density difference estimation for correctly specified parametric models. The usefulness of the proposed method is also demonstrated experimentally.

Blur distortion is a common artifact in image communication and affects the perceived sharpness of a digital image. In this paper, we capitalize on the mathematical knowledge of Gaussian convolution and propose a strategy to minimally reblur test images. From the reblur algorithm, synthetic reblur images are created. We propose a new blind blur metric which makes use of the reblur images to produce blur scores. Compared to other no-reference blur assessments, the proposed method has the advantages of fast computation and training-free operation. Experiment results also show that the proposed method can produce blur scores which are highly correlated with human perception of blurriness.

An optoelectronic 32-bit serial-to-parallel converter with a novel conversion scheme and shared-trigger configuration has been developed for the label processing of 100-Gbps (25-Gbps $ imes 4 lambda)$ optical packets. No external optical trigger source is required to operate the converter, as the optical packet itself is used to perform self-triggering. Compared to prior optoelectronic label converters, the new device has a much higher gain even while converting labels at higher data rates, and exhibits tolerance to the voltage swing of received packets. The device response is presented together with the experimental demonstration of serial-to-parallel conversion for 4 different labels at 25 Gbps.

Performance suveyrance of CPML (Convolutional PML) for FDTD (Finite-Difference Time-Domain) method in cylindrical coordinate system was carried out. The CPML was placed perpendicularly to the radial axis and designed to absorb diverging or converging waves. To be able to analyze microstructured optical fibers and disk/ring resonators we introduced finite axial wavenumbers into the FDTD formulation. We investigated the dependence of reflectivity upon CPML's constituteve parameters such as $kappa$ and $sigma$ for various curvature radii and the axial wavenumbers. As a result of evaluation we found that the reflectivity gradually increased togather with the increase of the wavenumber. We also confirmed that the absorption performance was of the similar order for the converging waves and the diverging ones provided that their curvature radii were the same.

In this paper, the function expansion based topology optimization is employed to the automatic optimization of the waveguide dispersion property, and the optimum design of low-dispersion slow-light photonic crystal waveguides is demonstrated. In order to realize low-dispersion and large group index, an objective function to be optimized is expressed by the weighted sum of the objective functions for the desired group index and the low-dispersion property, and weighting coefficients are updated through the optimization process.

In this work, a gate-all-around (GAA) tunneling field-effect transistor (TFET) with InGaAs/Si heterojunction for high-performance and low-standby power operations is studied. Gallium (Ga) compositon ($x)$ in In$_{1-x}$Ga$_{x}$As source substantially affects the physical properties related with device performances including lattice constant, bandgap energy, effective tunneling mass, channel mobility, and others. Thus, it is worthy investigating the effect of Ga fraction on performances of the proposed heterojunction TFET. For this goal, the device design and its performance evaluation are carried out by technology computer-aided design (TCAD). Direct-current (DC) performances are investigated in terms of on-state current ($I_{ m{on}})$, off-state current ($I_{ m{off}})$, current ratio ($I_{ m{on}}$/$I_{ m{off}})$, and subthreshold swing ($S$). Furthermore, it is shown that the device with an n-type Si insertion layer between source and channel demonstrates the enhanced DC characteristics.

A switchable microwave reflector, reflection of which is actively controlled using diodes was proposed. Pin diodes have large resistance and capacitance without DC bias and small resistance and inductance with DC bias in microwave band. The reflector was designed by using the characteristics. In this paper, effects of a periodic structure on the reflector were verified with simulation and equivalent circuit model. A prototype reflector was able to switch between about $-20$ dB and $-0.1$ dB reflection coefficient at 2 GHz.

The main purpose of this paper is to apply the boundary integral equation (BIE) method to the analysis of spoof localized surface plasmons (spoof LSPs) excited in a perfectly conducting cylinder with longitudinal corrugations. Frequency domain BIE schemes based on electric field integral equation (EFIE), magnetic field integral equation (MFIE) and combined field integral equation (CFIE) formulations are used to solve two-dimensional electromagnetic (EM) problems of scattering from the cylinder illuminated by a transverse electric plane wave. In this approach effects of spoof LSPs are included in the secondary surface current and charge densities resulting from the interaction between the plane wave and the cylinder. Numerical results obtained with the BIE schemes are validated by comparison with that of a recently proposed modal solution based on the metamaterial approximation.

In this paper, we first prove beyond-birthyday-bound security for the Misty structure. Specifically, we show that an r-round Misty structure is secure against CCA attacks up to $O(2^{rac{rn}{r+7}})$ query complexity, where n is the size of each round permutation. So for any ε>0, a sufficient number of rounds would guarantee the security of the Misty structure up to 2n(1-ε) query complexity.

Scheduling imposes a trade-off between sum capacity and fairness among users. In some situations, fairness needs to be given the first priority. Therefore, a scheduling algorithm which can flexibly control sum capacity and fairness is desirable. In this paper, assuming the single-carrier frequency division multiple access (SC-FDMA), we propose three scheduling algorithms: modified max-map, proportional fairness (PF)-map, and max-min. The available subcarriers are grouped into a number of subcarrier-blocks each having the same number of subcarriers. The scheduling is done on a subcarrier-block by subcarrier-block basis to take advantage of the channel frequency-selectivity. The same number of non-contiguous subcarrier-blocks is assigned to selected users. The trade-off between sum capacity and fairness is controlled by changing the number of simultaneously scheduling users per time-slot. Capacity, fairness, and peak-to-average power ratio (PAPR) when using the proposed scheduling algorithms are examined by computer simulation.

In this letter, a new sparse locality preserving projection (SLPP) algorithm is developed and applied to facial expression recognition. In comparison with the original locality preserving projection (LPP) algorithm, the presented SLPP algorithm is able to simultaneously find the intrinsic manifold of facial feature vectors and deal with facial feature selection. This is realized by the use of l1-norm regularization in the LPP objective function, which is directly formulated as a least squares regression pattern. We use two real facial expression databases (JAFFE and Ekman's POFA) to testify the proposed SLPP method and certain experiments show that the proposed SLPP approach respectively gains 77.60% and 82.29% on JAFFE and POFA database.