We designed multilayer wavelength-selective reflector films by stacking thin-films of transparent polymer. The optimum structure of the multilayer is determined using a combination of characteristic matrix method and a version of genetic algorithm. Such multilayer films can be used in LCD devices to enhance the color saturation of the display.

This letter presents a novel approach for automatic multimodal affect recognition. The audio and visual channels provide complementary information for human affective states recognition, and we utilize Boltzmann zippers as model-level fusion to learn intrinsic correlations between the different modalities. We extract effective audio and visual feature streams with different time scales and feed them to two component Boltzmann chains respectively. Hidden units of the two chains are interconnected to form a Boltzmann zipper which can effectively avoid local energy minima during training. Second-order methods are applied to Boltzmann zippers to speed up learning and pruning process. Experimental results on audio-visual emotion data recorded by ourselves in Wizard of Oz scenarios and collected from the SEMAINE naturalistic database both demonstrate our approach is robust and outperforms the state-of-the-art methods.

We present transmission- and reflection-type measurement methods for the differential mode delay (DMD) of a multimode optical fiber (MMF) optimized for high-speed local area networks (LANs) for the 850-nm band. Compared with a previously reported transmission-type measurement method for the 1550-nm wavelength band, we demonstrate here high-resolution DMD measurement methods for MMFs in the 850-nm band. As the method is based on a Fourier-domain intermodal interference technique, the measurement sensitivity is ∼60-dB, and it requires a fiber only a few meters in length. The shorter wavelength also allows a threefold improvement in the measurement resolution. The reflection-type measurement technique is a more practical than the transmission-type measurement technique for the field testing of short MMFs already installed in networks. We believe that this method will be a practical tool not only for field testing of short-length MMFs already installed in networks but also for the development of new plastic optical fibers (POFs).

Multiple-shot person re-identification, which is valuable for application in visual surveillance, tackles the problem of building the correspondence between images of the same person from different cameras. It is challenging because of the large within-class variations due to the changeable body appearance and environment and the small between-class differences arising from the possibly similar body shape and clothes style. A novel method named “Bi-level Relative Information Analysis” is proposed in this paper for the issue by treating it as a set-based ranking problem. It creatively designs a relative dissimilarity using set-level neighborhood information, called “Set-level Common-Near-Neighbor Modeling”, complementary to the sample-level relative feature “Third-Party Collaborative Representation” which has recently been proven to be quite effective for multiple-shot person re-identification. Experiments implemented on several public benchmark datasets show significant improvements over state-of-the-art methods.

This paper describes a novel technique to replace some of the driven elements in an array antenna with parasitic elements. First, the antenna characteristics are studied by simulation for a basic unit array with one driven and two parasitic elements. The entire antenna is backed with a flat reflector to conform to practical applications. The parasitic elements are excited by the neighboring driven elements through the electromagnetic coupling effect. It is shown that at the optimal coupling condition, the radiation patterns are almost identical with those of an array antenna whose elements are all driven without coupling. The simulation result is confirmed by performing an experiment at 5.8GHz (λ =51.7mm). Finally, a 12-element array is formed by combining four unit arrays. The simulation results show that the maximum antenna gain is 19.4dBi, indicating that there is no penalty with respect to the antenna gain of a fully driven 12-element array. Therefore, the array antenna can be considerably simplified by replacing 67% of its elements with parasitic elements.

This paper describes how to design matching structures to improve the frequency characteristics of one-dimensional finite periodic structures. In particular, it deals with one-dimensional finite superlattices. A downhill simplex method is used to determine some of the structural parameters of the matching structure. Numerical examples show that this method is effective in improving the frequency characteristics of finite superlattices.

Channel modeling, which is quite important for wireless communications system design, is difficult to be statistically generated from experimental results due to the expense and time constraints. However, with the computational electromagnetics method, the Electro-Magnetic (EM) field can be emulated and the corresponding EM wave propagation scenario can be analyzed. In this letter, the Finite Integration Technique (FIT) method is utilized to calculate the EM wave propagation of the onboard mobile communications in the cabin of an aircraft. With the simulation results, the channel model is established. Compared with Finite-Difference Time-Domain (FDTD), the proposed scheme is more accurate, which is promising to be used in the cabin channel modeling for onboard mobile system design.

An on-chip SIDO DC-DC boost converter core that can be used for both battery and solar cell operating applications is proposed. The converter is able to supply a current of up to around 30mA with an on-chip driver and more than 100mA by using an off-chip power MOS driver. The cross regulation problem was solved by inserting an extra cycle. Efficiencies of 85% and 84% were achieved for each driving mode. Complicated maximum power point tracking (MPPT) controls are available for a solar cell operation. An embedded micro-computer can be used to calculate a complicated algorithm. The converter exploits 99% of the expected maximum power of the solar cell. The converter protects the leak current that flows through the solar cell when there is no light. The proposed protection circuits reduce the leak current by three orders of magnitude without any performance loss.

The present paper proposes two new methods for constructing polyphase asymmetric zero-correlation zone (A-ZCZ) sequence sets. In previous studies, the authors proposed methods for constructing quasi-optimal polyphase A-ZCZ sequence sets using perfect sequences and for constructing optimal polyphase A-ZCZ sequence sets using discrete Fourier transform (DFT) matrices. However, in these methods, the total number of sequences in an A-ZCZ sequence set cannot exceed the period of the perfect sequence or the dimension of the DFT matrix used for constructing the A-ZCZ sequence set. We now propose two extended versions of these methods. The proposed methods can generate a quasi-optimal or optimal polyphase A-ZCZ sequence set where the total number of sequences exceeds the period of the perfect sequence or the dimension of the DFT matrix. In other words, the proposed methods can generate new A-ZCZ sequence sets that cannot be obtained from the known methods.

This paper addresses the sensing-throughput tradeoff problem by using cluster-based cooperative spectrum sensing (CSS) schemes in two-layer hierarchical cognitive radio networks (CRNs) with soft data fusion. The problem is formulated as a combinatorial optimization problem involving both discrete and continuous variables. To simplify the solution, a reasonable weight fusion rule (WFR) is first optimized. Thus, the problem devolves into a constrained discrete optimization problem. In order to efficiently and effectively resolve this problem, a lexicographical approach is presented that solving two optimal subproblems consecutively. Moreover, for the first optimal subproblem, a closed-form solution is deduced, and an optimal clustering scheme (CS) is also presented for the second optimal subproblem. Numerical results show that the proposed approach achieves a satisfying performance and low complexity.

In 2001, Boneh and Franklin realized the first Identity-Based Encryption (IBE), and at the same time they proposed a simple way to revoke users from the system. Later, Boldyreva et al. pointed out that Boneh-Franklin's revocation method is not scalable well and they proposed the first IBE scheme with efficient revocation. Recently, Tseng and Tsai [Computer Journal, Vol.55 No.4, page 475-486, 2012] claimed that Boldyreva et al.'s scheme requires a secure channel between each user and the key generation center in the key update phase, and proposed a new revocable IBE (RIBE) with a public channel by extending the Boneh-Franklin scheme. In this paper, we revisit Tseng and Tsai's result; we first point out that secure channels (except for the initial key setup) are not mandatory in the definition of RIBE scheme formalized by Boldyreva et al. Next, we show that Boldyreva et al.'s scheme does not require any secure channels (except for the initial key setup), which is different from what Tseng and Tsai claimed and so invalidates their contribution of the first RIBE with a public channel. Moreover, we point out that there are simple techniques to remove secure channels from the Boneh-Franklin RIBE. Interestingly, we show that the secure-channel-free Boneh-Franklin RIBE scheme is secure against decryption key exposure, whereas the Tseng-Tsai RIBE scheme is vulnerable to this attack.

In tooth contour extraction there is insufficient intensity difference in x-ray images between the tooth and dental bone. This difference must be enhanced in order to improve the accuracy of tooth segmentation. This paper proposes a method to improve the intensity between the tooth and dental bone. This method consists of an estimation of tooth orientation (intensity projection, smoothing filter, and peak detection) and PCA-Stacked Gabor with ellipse Gabor banks. Tooth orientation estimation is performed to determine the angle of a single oriented tooth. PCA-Stacked Gabor with ellipse Gabor banks is then used, in particular to enhance the border between the tooth and dental bone. Finally, active contour extraction is performed in order to determine tooth contour. In the experiment, in comparison with the conventional active contour without edge (ACWE) method, the average mean square error (MSE) values of extracted tooth contour points are reduced from 26.93% and 16.02% to 19.07% and 13.42% for tooth x-ray type I and type H images, respectively.

This paper proposes novel robust speech F0 estimation using Summation Residual Harmonics (SRH) based on TV-CAR (Time-Varying Complex AR) analysis. The SRH-based F0 estimation was proposed by A. Alwan, in which the criterion is calculated from LP residual signals. The criterion is summation of residual spectrum value for harmonics. In this paper, we propose SRH-based F0 estimation based on the TV-CAR analysis, in which the criterion is calculated from the complex AR residual. Since complex AR residual provides higher resolution of spectrum, it can be considered that the criterion is effective for F0 estimation. The experimental results demonstrate that the proposed method performs better than conventional methods; weighted auto-correlation and YIN.

In this paper, we propose a use of the group sparsity in adaptive learning of second-order Volterra filters for the nonlinear acoustic echo cancellation problem. The group sparsity indicates sparsity across the groups, i.e., a vector is separated into some groups, and most of groups only contain approximately zero-valued entries. First, we provide a theoretical evidence that the second-order Volterra systems tend to have the group sparsity under natural assumptions. Next, we propose an algorithm by applying the adaptive proximal forward-backward splitting method to a carefully designed cost function to exploit the group sparsity effectively. The designed cost function is the sum of the weighted group l1 norm which promotes the group sparsity and a weighted sum of squared distances to data-fidelity sets used in adaptive filtering algorithms. Finally, Numerical examples show that the proposed method outperforms a sparsity-aware algorithm in both the system-mismatch and the echo return loss enhancement.

For quantized control, one of the powerful approaches is to use a dynamic quantizer, which has internal memories for signal quantization, with a conventional controller in the feedback control loop. The design of dynamic quantizers has become a major topic, and a number of results have been derived so far. In this paper, we extend the authors' recent result on dynamic quantizers, and applied them to a more general class of nonlinear systems, called the nonaffine nonlinear systems. Based on the performance index representing the degradation caused by the signal quantization, we propose practical dynamic quantizers, which include the authors' former result as a special case. Moreover, we provide theoretical results on the performance and on the stability of the resulting quantized systems.

This paper deals with the problem of underdetermined blind source separation (BSS) where the number of sources is unknown. We propose a BSS approach that simultaneously estimates the number of sources, separates the sources based on the sparseness of speech, estimates the direction of arrival of each source, and performs permutation alignment. We confirmed experimentally that reasonably good separation was obtained with the present method without specifying the number of sources.

In the recently developed Flexible Wireless System (FWS), the same platform needs to deal with different wireless systems. This increases nonlinear distortion in its wideband power amplifier (PA) because the PA needs to concurrently amplify multi-band signals. By taking higher harmonics as well as inter- and cross-modulation distortion into consideration, we have developed a method to analytically evaluate the adjacent channel leakage power ratio (ACPR) and error vector magnitude (EVM) on the basis of the PA's nonlinear characteristics. We devise a novel method for modeling the PA amplifying dual-band signals. The method makes it possible to model it merely by performing a one-tone test, making use of the Volterra series expansion and the general Wiener model. We then use the Mehler formula to derive the closed-form expressions of the PA's output power spectral density (PSD), ACPR, and EVM. The derivations are based on the assumption that the transmitted signals are complex Gaussian distributed in orthogonal frequency division multiplexing (OFDM) transmission systems. We validate the method by comparing measurement and simulation results and confirm it can appropriately predict the ACPR and EVM performance of the nonlinear PA output with OFDM inputs. In short, the method enables correct modeling of a wideband PA that amplifies dual-band signals merely by conducting a one-tone test.

Metamaterials are generally defined as a class of artificial effective media which macroscopically exhibit extraordinary electromagnetic properties that may not be found in nature, and are composed of periodically structured dielectric, or magnetic, or metallic materials. This paper reviews recently developed electromagnetic modeling methods of metamatericals and their inherent basic ideas, with a focus on full wave numerical techniques. Methods described in this paper are the Method of Moments (MoM) and the Finite Difference Time Domain (FDTD) Method for scattering problems excited by an incident plane wave and a single nonperiodic source, and the Finite Element Method (FEM), the Finite Difference Frequency Domain (FDFD) method and the FDTD method for band diagram calculations.

Self-resonant helical antenna and capacitor-loaded helical antenna of the same dimension for coupled-resonant wireless power transfer is discussed. At first, fundamental difference of the self-resonant and the capacitor-loaded antenna is demonstrated by calculating electric- and magnetic-coupling coefficient. Next, performance of the helical antennas are discussed from viewpoints of 1) transmission efficiency, 2) undesired emission, 3) near-field leakage, 4) effect of human body and 5) effect of conductivity. We have found that the self-resonant helical antenna has an advantage in low transmission loss due to a conductivity of wire. On the other hand, the capacitor-loaded antenna has an advantage in low emission, long transfer distance, and low influence of resonant frequency from human body. This is because both electric-field coupling and magnetic-field coupling are dominant for the self-resonant antenna while only magnetic-field coupling is dominant in the capacitor-loaded antenna.

Automated or semi-automated annotation is a practical solution for large-scale corpus construction. However, the special characteristics of Thai language, such as lack of word-boundary and sentence-boundary markers, trigger several issues in automatic corpus annotation. This paper presents a multi-stage annotation framework, containing two stages of chunking and three stages of tagging. The two chunking stages are pattern matching-based named entity (NE) extraction and dictionary-based word segmentation while the three succeeding tagging stages are dictionary-, pattern- and statist09812490981249ical-based tagging. Applying heuristics of ambiguity priority, NE extraction is performed first on an original text using a set of patterns, in the order of pattern ambiguity. Next, the remaining text is segmented into words with a dictionary. The obtained chunks are then tagged with types of named entities or parts-of-speech (PoS) using dictionaries, patterns and statistics. Focusing on the reduction of human intervention in corpus construction, our experimental results show that the dictionary-based tagging process can assign unique tags to 64.92% of the words, with the remaining of 24.14% unknown words and 10.94% ambiguously tagged words. Later, the pattern-based tagging can reduce unknown words to only 13.34% while the statistical-based tagging can solve the ambiguously tagged words to only 3.01%.