In the theory of diffraction gratings, the conventional integral method is considered as a powerful tool of numerical analysis. But it fails to work at a critical angle of incidence, because a periodic Green's function (integral kernel) diverges. This problem was resolved by the image integral equation in a previous paper. Newly introducing the reflection extinction theorem, this paper derives the image extinction theorem and the image integral equation. Then, it is concluded that the image integral equation is made up of two physical processes: the image surface radiates a reflected plane wave, whereas the periodic surface radiates the diffracted wave.

This paper presents a new span-based dependency chart parsing algorithm that models the relations between the left and right dependents of a head. Such relations cannot be modeled in existing span-based algorithms, despite their popularity in dependency corpora. We address this problem through ternary-span combination during the subtree derivation. By modeling the relations between the left and right dependents of a head, our proposed algorithm provides a better capability of coordination disambiguation when the conjunction is annotated as the head of the left and right conjuncts. This eventually leads to state-of-the-art performance of dependency parsing on the Chinese data of the CoNLL shared task.

This paper deals with a characteristic of the so-called effective boundary condition for a plane wave scattering from periodic surfaces with perfect conductivity. The perturbation solution with all orders is explicitly given under the effective boundary condition. It is newly found that such a perturbation solution satisfies the optical theorem under the exact boundary condition. A comparison between such a perturbation solution and a reference solution for the exact boundary condition by other methods is performed. Then, the validity of such a perturbation solution is concretely discussed.

This article presents a differential fault analysis (DFA) technique using round addition for a generalized Feistel network (GFN) including CLEFIA and RC6. Here the term “round addition” means that the round operation executes twice using the same round key. The proposed DFA needs bypassing of an operation to count the number of rounds such as increment or decrement. To verify the feasibility of our proposal, we implement several operations, including increment and decrement, on a microcontroller and experimentally confirm the operation bypassing. The proposed round addition technique works effectively for the generalized Feistel network with a partial whitening operation after the last round. In the case of a 128-bit CLEFIA, we show a procedure to reconstruct the round keys or a secret key using one correct ciphertext and two faulty ciphertexts. Our DFA also works for DES and RC6.

The Generalized cross-correlation (GCC) method is most commonly used for time delay estimation (TDE). However, the GCC method can result in false peak errors (FPEs) especially at a low signal to noise ratio (SNR). These FPEs significantly degrade TDE, since the estimation error, which is the difference between a true time delay and an estimated time delay, is larger than at least one sampling period. This paper introduces an algorithm that estimates two peaks for two cross-correlation functions using three types of signals such as a reference signal, a delayed signal, and a delayed signal with an additional time delay of half a sampling period. A peak selection algorithm is also proposed in order to identify which peak is closer to the true time delay using subsample TDE methods. This paper presents simulations that compare the algorithms' performance for varying amounts of noise and delay. The proposed algorithms can be seen to display better performance, in terms of the probability of the integer TDE errors, as well as the mean and standard deviation of absolute values of the time delay estimation errors.

Facial micro-expressions are fast and subtle facial motions that are considered as one of the most useful external signs for detecting hidden emotional changes in a person. However, they are not easy to detect and measure as they appear only for a short time, with small muscle contraction in the facial areas where salient features are not available. We propose a new computer vision method for detecting and measuring timing characteristics of facial micro-expressions. The core of this method is based on a descriptor that combines pre-processing masks, histograms and concatenation of spatial-temporal gradient vectors. Presented 3D gradient histogram descriptor is able to detect and measure the timing characteristics of the fast and subtle changes of the facial skin surface. This method is specifically designed for analysis of videos recorded using a hi-speed 200 fps camera. Final classification of micro expressions is done by using a k-mean classifier and a voting procedure. The Facial Action Coding System was utilized to annotate the appearance and dynamics of the expressions in our new hi-speed micro-expressions video database. The efficiency of the proposed approach was validated using our new hi-speed video database.

We propose a new analytical method for a composite dielectric grating embedded with conducting strips using scattering factors in the shadow theory. The scattering factor in the shadow theory plays an important role instead of the conventional diffraction amplitude. By specifying the relation between scattering factors and spectral-domain Green's functions, we derive expressions of the Green's functions directly for unit surface electric and magnetic current densities, and apply the spectral Galerkin method to our formulation. From some numerical results, we show that the expressions of the Green's functions are valid, and analyze scattering characteristics by composite gratings.

In this letter, we propose an extension to the classical logarithmic total variation (LTV) model for face recognition under variant illumination conditions. LTV treats all facial areas with the same regularization parameters, which inevitably results in the loss of useful facial details and is harmful for recognition tasks. To address this problem, we propose to assign the regularization parameters which balance the large-scale (illumination) and small-scale (reflectance) components in a spatially adaptive scheme. Face recognition experiments on both Extended Yale B and the large-scale FERET databases demonstrate the effectiveness of the proposed method.

For the modeling of multipath propagation in every wireless systems, the ray tracing method has been widely studied. However, large errors may result due to the approximation of geometrical optics in curved surfaces. This paper therefore focused on the curved surfaces and edges, which are difficult to handle in ray tracing. Examples of curved surfaces can be found in arched cross-section tunnels which are common in highway networks of mountainous areas. The traditional ray tracing method of dividing the curved surface into smaller flat plates is not so accurate as the size of smaller plates may not satisfy the geometrical optics assumption, and the reflection point which satisfies Fermat's principle may not exist. In this work, a new ray tracing method is proposed with 2 contributions. The first one is the implementation of the reflection coefficient for curved surfaces in ray tracing. The second is applying the physical optics method on the caustics region. To evaluate these methods, path gain simulation results for an arched cross-section model are compared with measurements made inside an arched tunnel. To further improve the simulation results, the effect of rough surface is introduced, and the results are again compared with measurement.

Compressive sensing (CS) shows that a sparse or compressible signal can be exactly recovered from its linear measurements at a rate significantly lower than the Nyquist rate. As an extreme case, 1-bit compressive sensing (1-bit CS) states that an original sparse signal can be recovered from the 1-bit measurements. In this paper, we intrduce a Fast and Accurate Two-Stage (FATS) algorithm for 1-bit compressive sensing. Simulations show that FATS not only significantly increases the signal reconstruction speed but also improves the reconstruction accuracy.

Fault-based attacks are very powerful to recover the secret key for cryptographic implementations. In this work, we consider the faulty output value under a certain fault injection intensity as a new type of leakage called faulty behavior. We examine the data-dependency of the faulty behavior and propose a related side-channel attack called fault behavior analysis (FBA). To verify the validity of the proposed attack, we first show that our attack can work effectively on AES-COMP of SASEBO-R. Then we show how to apply the similar attack on two AES implementations with masking countermeasures, i.e., AES-MAO and AES-TI. Finally we compare the proposed FBA attack with the DFA attack and the FSA attack, trying to complete the research map for the fault-based attack based on setup-time violations.

A garbage collector relieves programmers from manual memory management and improves productivity and program reliability. However, there are many other finite system resources that programmers must manage by themselves, such as sockets and database connections. Growing resource leaks can lead to performance degradation and even program crashes. This paper presents the automatic resource collection approach called Resco (RESource COllector) to tolerate non-memory resource leaks. Resco prevents performance degradation and crashes due to resource leaks by two steps. First, it utilizes monitors to count resource consumption and request resource collections independently of memory usage when resource limits are about to be violated. Second, it responds to a resource collection request by safely releasing leaked resources. We implement Resco based on a Java Virtual Machine for Java programs. The performance evaluation against standard benchmarks shows that Resco has a very low overhead, around 1% or 3%. Experiments on resource leak bugs show that Resco successfully prevents most of these programs from crashing with little increase in execution time.

To better understand antenna properties in a narrow space such as in a densely-packed device, a circular microstrip antenna in a narrow parallel-plate waveguide is theoretically studied. An analytical expression is derived for the input impedance in a parallel-plate waveguide by using the cavity model with surface admittance on the side wall. The surface admittance is defined by the external magnetic field due to the equivalent magnetic current at the aperture and takes into account the contribution of the parallel plates to the antenna. The magnetic field external to the antenna, that is in the parallel-plate region, is determined by using a dyadic Green's function. The input impedance is then calculated by a basic definition based on the conservation of the complex power. An analytical expression which couples the resonant frequency and the surface susceptance is also formulated. Presented expressions are validated by comparison with experimental results.

IP fast rerouting has widely been studied for realizing millisecond-order recovery on pure IP networks. This paper proposes IP fast rerouting using backup topologies against concurrent double failures. The main issue in recovering from multiple failures is avoiding forwarding loops. To avoid forwarding loops, we propose a deterministic forwarding algorithm, which estimates the concurrently occurring failures from the packet header information. We also propose an efficient backup topology design algorithm which is both loop-free and which reduces the number of backup topologies. Our key idea is preparing the adequate diversity of backup routes for arbitrary source and destination pairs by combination of backup topologies. For efficient computation of diverse routes, we propose a similarity comparison-based algorithm between the original topology and the backup topologies. Our algorithm can achieve nearly optimal loop-free restoration from double failures on realistic topologies without explicit failure notification.

The accuracy of non-rigid 3D face recognition is highly influenced by the capability to model the expression deformations. Given a training set of non-neutral and neutral 3D face scan pairs from the same subject, a set of Fourier series coefficients for each face scan is reconstructed. The residues on each frequency of the Fourier series between the finely aligned pairs contain the expression deformation patterns and PCA is applied to learn these patterns. The proposed expression deformation model is then built by the eigenvectors with top eigenvalues from PCA. Recognition experiments are conducted on a 3D face database that features a rich set of facial expression deformations, and experimental results demonstrate the feasibility and merits of the proposed model.

System-on-display panel design methodologies are proposed with the purpose of integrating DCT and IDCT on display panels for image codec and peripheral systems so as to reduce the bus data rate, memory size and power consumption. Unified constant geometry algorithms and architectures including recursive additions are proposed for DCT and IDCT butterfly computation, recursive additions and interconnections between stages. These schemes facilitate VLSI implementation and improve fault tolerance, suitable for low-yield SOP processing technologies through duplicate use of a PE as all the butterfly and recursive addition stages are composed and interconnected in a regular fashion. Efficient redundancy replacement methodologies optimizing the computation speed and the amount of hardware in various application areas are also described with testability and reliability issues. Finally, a performance analysis of speed, hardware and interconnection complexity is described with the proposed work's advantages.

In this paper, a complete SSTA scheme is proposed to calculate the output waveform of a logic cell on any random selected point in the process variational space, or the mean value and variance of the output signal with very high accuracy and acceptable CPU cost. At first, Miller capacitances between the input nodes and internal nodes of a logic cell are introduced to construct the improved MCSM model so as to improve the modeling accuracy. Secondly, the stochastic collocation method jointed with the Modified Nested Sparse Grid technique is adopted for SSTA procedure to avoid the exponential increase of the collocation points number caused by tensor product. Thirdly, a Nominal waveform based Fast Simulation Method is developed to speedup the simulation on each collocation point. At last, Automatic Waveform Construction Technique is developed to construct the output waveform with the approximation points as little as possible to decrease the computational cost while guaranteeing high accuracy. Numerical results are also given to demonstrate the efficiency of the proposed algorithm.

In this paper, we propose Local Curvelet Binary Patterns (LCBP) and Learned Local Curvelet Patterns (LLCP) for presenting the local features of facial images. The proposed methods are based on Curvelet transform which can overcome the weakness of traditional Gabor wavelets in higher dimensions, and better capture the curve singularities and hyperplane singularities of facial images. LCBP can be regarded as a combination of Curvelet features and LBP operator while LLCP designs several learned codebooks from patch sets, which are constructed by sampling patches from Curvelet filtered facial images. Each facial image can be encoded into multiple pattern maps and block-based histograms of these patterns are concatenated into an histogram sequence to be used as a face descriptor. During the face representation phase, one input patch is encoded by one pattern in LCBP while multi-patterns in LLCP. Finally, an effective classifier called Weighted Histogram Spatially constrained Earth Mover's Distance (WHSEMD) which utilizes the discriminative powers of different facial parts, the different patterns and the spatial information of face is proposed. Performance assessment in face recognition and gender estimation under different challenges shows that the proposed approaches are superior than traditional ones.

This paper proposes applying intra-subframe frequency hopping (FH) to closed-loop (CL) type transmit diversity using codebook based precoding for a shared channel carrying user traffic data in discrete Fourier transform (DFT)-precoded Orthogonal Frequency Division Multiple Access (OFDMA). In the paper, we present two types of precoding schemes associated with intra-subframe FH: individual precoding vector selection between 2 slots where a 1-ms subframe comprises 2 slots among the reduced precoding codebooks, and common precoding vector selection between 2 slots. We investigate the effect of intra-subframe FH on the codebook based transmit diversity in terms of the average block error rate (BLER) performance while maintaining the same number of feedback bits required for notification of the selected precoding vector as that for the conventional CL transmit diversity without FH. Computer simulation results show that the codebook based transmit diversity with intra-subframe FH is very effective in decreasing the required average received signal-to-noise power ratio (SNR) when the fading maximum Doppler frequency, fD, is higher than approximately 50 Hz both for 2- and 4-antenna transmission in the DFT-precoded OFDMA.

This study examines the robustness of image quality factors in various types of environment illumination using a parameter design in the field of quality engineering. Experimental results revealed that image quality factors are influenced by environment illuminations in the following order: minimum luminance, maximum luminance and gamma.