A novel enhancement for the memory-based particle filter is proposed for visual pose tracking under severe occlusions. The enhancement is the addition of a detection-based memory acquisition mechanism. The memory-based particle filter, called M-PF, is a particle filter that predicts prior distributions from past history of target state stored in memory. It can achieve high robustness against abrupt changes in movement direction and quick recovery from target loss due to occlusions. Such high performance requires sufficient past history stored in the memory. Conventionally, M-PF conducts online memory acquisition which assumes simple target dynamics without occlusions for guaranteeing high-quality histories of the target track. The requirement of memory acquisition narrows the coverage of M-PF in practice. In this paper, we propose a new memory acquisition mechanism for M-PF that well supports application in practical conditions including complex dynamics and severe occlusions. The key idea is to use a target detector that can produce additional prior distribution of the target state. We call it M-PFDMA for M-PF with detection-based memory acquisition. The detection-based prior distribution well predicts possible target position/pose even in limited-visibility conditions caused by occlusions. Such better prior distributions contribute to stable estimation of target state, which is then added to memorized data. As a result, M-PFDMA can start with no memory entries but soon achieve stable tracking even in severe conditions. Experiments confirm M-PFDMA's good performance in such conditions.

To acquire a second language, one must develop an ear and tongue for the correct stress and intonation patterns of that language. In English language teaching, there is an effective method called Jazz Chants for working on the sound system. In this paper, we propose a method for predicting stressed words, which play a crucial role in Jazz Chants. The proposed method is specially designed for stress prediction in Jazz chants. It exploits several sources of information including words, POSs, sentence types, and the constraint on the number of stressed words in a chant text. Experiments show that the proposed method achieves an F-measure of 0.939 and outperforms the other methods implemented for comparison. The proposed method is expected to be useful in supporting non-native teachers of English when they teach chants to students and create chant texts with stress marks from arbitrary texts.

Link prediction is the task of inferring the existence or absence of certain relationships among data objects such as identity, interaction, and collaboration. Link prediction is found in various applications in the fields of information integration, recommender systems, bioinformatics, and social network analysis. The increasing interest in dynamically changing networks has led to growing interest in a more general link prediction problem called temporal link prediction in the data mining and machine learning communities. However, only links among nodes at the same time point are considered in temporal link prediction. We propose a new link prediction problem called cross-temporal link prediction in which the links among nodes at different time points are inferred. A typical example of cross-temporal link prediction is cross-temporal entity resolution to determine the identity of real entities represented by data objects observed in different time periods. In dynamic environments, the features of data change over time, making it difficult to identify cross-temporal links by directly comparing observed data. Other examples of cross-temporal links are asynchronous communications in social networks such as Facebook and Twitter, where a message is posted in reply to a previous message. We adopt a dimension reduction approach to cross-temporal link prediction; that is, data objects in different time frames are mapped into a common low-dimensional latent feature space, and the links are identified on the basis of the distance between the data objects. The proposed method uses different low-dimensional feature projections in different time frames, enabling it to adapt to changes in the latent features over time. Using multi-task learning, it jointly learns a set of feature projection matrices from the training data, given the assumption of temporal smoothness of the projections. The optimal solutions are obtained by solving a single generalized eigenvalue problem. Experiments using a real-world set of bibliographic data for cross-temporal entity resolution and a real-world set of emails for unobserved asynchronous communication inference showed that introducing time-dependent feature projections improved the accuracy of link prediction.

Timing asynchronism strongly degrades the performance of analog network coded (ANC) bi-directional transmission. This letter investigates receiver design for asynchronous broadband bi-directional transmission over frequency selective fading channels. Based on time domain oversampling, we propose fractionally spaced frequency domain minimum mean square error (MMSE) equalizers for bi-directional ANC based on orthogonal frequency division multiplexing (OFDM) and cyclic prefixed single carrier (CP-SC) radio access. Simulation results show that the proposed fractionally spaced equalizer (FSE) can eliminate the negative effect of timing misalignment in bi-directional transmissions.

In time-varying frequency selective channels, to obtain high-rate joint time-frequency diversity, linear dispersion coded orthogonal frequency division multiplexing (LDC-OFDM), has recently been proposed. Compared with OFDM systems, single-carrier systems may retain the advantages of lower PAPR and lower sensitivity to carrier frequency offset (CFO) effects, which motivates this paper to investigate how to achieve joint frequency and time diversity for high-rate single-carrier block transmission systems. Two systems are proposed: linear dispersion coded cyclic-prefix single-carrier modulation (LDC-CP-SCM) and linear dispersion coded zero-padded single-carrier modulation (LDC-ZP-SCM) across either multiple CP-SCM or ZP-SCM blocks, respectively. LDC-SCM may use a layered two-stage LDC decoding with lower complexity. This paper analyzes the diversity properties of LDC-CP-SCM, and provides a sufficient condition for LDC-CP-SCM to maximize all available joint frequency and time diversity gain and coding gain. This paper shows that LDC-ZP-SCM may be effectively equipped with low-complexity minimum mean-squared error (MMSE) equalizers. A lower complexity scheme, linear transformation coded SCM (LTC-SCM), is also proposed with good diversity performance.

Multicarrier communications including orthogonal frequency-division multiplexing (OFDM) is a technique which has been adopted for various wireless applications. However, a major drawback to the widespread acceptance of OFDM is the high peak-to-mean envelope power ratio (PMEPR) of uncoded OFDM signals. Finding methods for construction of sequences with low PMEPR is an active research area. In this paper, by employing some new shortened and extended Golay complementary pairs as the seeds, we enlarge the family size of near-complementary sequences given by Yu and Gong. We also show that the new set of sequences we obtained is just a reversal of the original set. Numerical results show that the enlarged family size is almost twice of the original one. Besides, the Hamming distances of the binary near-complementary sequences are also analyzed.

In orthogonal frequency division multiplexing (OFDM) based systems, intercarrier interference (ICI) created by the time varying property of wireless fading channels, degrades the data detection performance. This degradation strengthens especially when the mobile speed is relatively high or the number of subcarriers is large. Here, we interpret the time varying channel as the linear transformation of the time invariant channel impulse response. By using this new channel model, the time varying component can be reduced in the time domain by applying the inverse transformation to the received sequence. Then, the remaining time invariant channel component is removed by the equalization in the frequency domain. Some complexity reduction schemes are also proposed to make the proposed method feasible for practical implementation. The simulation results show that the new method offers a significant improvement in terms of bit error rate performance, especially when the number of subcarriers is larger than about 500.

Image warping is usually used to perform real-time geometric transformation of the images captured by the CMOS image sensor of video camera. Several existing look-up table (LUT)-based algorithms achieve real-time performance; however, the size of the LUT is still large, and it has to be stored in off-chip memory. To reduce latency and bandwidth due to the use of off-chip memory, this paper proposes an improved LUT (ILUT) scheme that compresses the LUT to the point that it can be stored in on-chip memory. First, a one-step transformation is adopted instead of using several on-line calculation stages. The memory size of the LUT is then reduced by utilizing the similarity of neighbor coordinates, as well as the symmetric characteristic of video camera images. Moreover, an elaborate pipeline hardware structure, cooperating with a novel 25-point interpolation algorithm, is proposed to accelerate the system and reduce further memory usage. The proposed system is implemented by a field-programmable gate array (FPGA)-based platform. Two different examples show that the proposed ILUT achieves real-time performance with small memory usage and low system requirements.

Constructing APN or 4-differentially uniform permutations achieving all the necessary criteria is an open problem, and the research on it progresses slowly. In ACISP 2011, Carlet put forth an idea for constructing differentially uniform permutations using extension fields, which was illustrated with a construction of a 4-differentially uniform (n,n)-permutation. The permutation has optimum algebraic degree and very good nonlinearity. However, it was proved to be a permutation only for n odd. In this note, we investigate further the construction of differentially uniform permutations using extension fields, and construct a 4-differentially uniform (n,n)-permutation for any n. These permutations also have optimum algebraic degree and very good nonlinearity. Moreover, we consider a more general type of construction, and illustrate it with an example of a 4-differentially uniform (n,n)-permutation with good cryptographic properties.

We propose a reduced complexity maximum likelihood sequence detection (MLSD) equalizer for wireless communications using bidirectional decision feedback equalizers (DFEs). We apply reduced-length two-level estimates produced by a bidirectional DFE. Therefore, the computationally expensive MLSD algorithm is applied sparingly for two-level signals with the effective channel length shorter than the original channel, regardless of the original constellation size of the symbols. Simulation results show that the proposed algorithm outperforms existing combination schemes based on bidirectional DFEs, especially for large constellations.

In this paper, we examine a new P2P traffic localization approach that exploits peer selection adaptation (i.e., preferring peers who are likely to provide better performance), called Netpherd. Netpherd enables peers to communicate with local domain peers by manipulating networking performance across network domains (i.e., adding an artificial delay to inter-domain traffic). Our feasibility study shows that Netpherd reduces the inter-domain traffic by influencing peer selection adaptation. Netpherd also improves download performance of the peers who know many local domain peers. We discuss one guideline to improve Netpherd based on the feasibility study and verify the guideline with evaluation results.

For advanced mobile communication systems that adopt orthogonal frequency-division multiple access (OFDMA) technologies, intercarrier interference (ICI) significantly degrades performance when mobility is high. Standard specifications and concerns about complexity demand low-cost methods with deployment readiness and decent performance. In this paper, novel zero forcing (ZF) and minimum mean-square error (MMSE) equalizers based on per-subcarrier adaptive (PSA) processing and perturbation-based (PB) approximation are introduced. The proposed equalizers strike a good balance between implementation cost and performance; therefore they are especially suitable for OFDMA downlink receivers. Theoretical analysis and simulations are provided to verify our claims.

Fast and accurate estimation of missing relations, e.g., similarity, distance and kernel, among objects is now one of the most important techniques required by major data mining tasks, because the missing information of the relations is needed in many applications such as economics, psychology, and social network communities. Though some approaches have been proposed in the last several years, the practical balance between their required computation amount and obtained accuracy are insufficient for some class of the relation estimation. The objective of this paper is to formalize a problem to quickly and efficiently estimate missing relations among objects from the other known relations among the objects and to propose techniques called “PSD Estimation” and “Row Reduction” for the estimation problem. This technique uses a characteristic of the relations named “Positive Semi-Definiteness (PSD)” and a special assumption for known relations in a matrix. The superior performance of our approach in both efficiency and accuracy is demonstrated through an evaluation based on artificial and real-world data sets.

Ground antennas are suitable for use in mobile electronic devices due to their compactness. These ground antennas incorporate two capacitors for controlling the resonance frequency and a shorting loop for impedance matching. In this work, we compare the performance of a ground antenna with that of a meandered inverted-F antenna (IFA). It is numerically and experimentally shown that a ground antenna can yield simultaneous improvements in both the antenna size and radiation efficiency when compared to the meandered IFA. The bandwidth of the ground antenna for a voltage standing wave ratio (VSWR) of 3:1 is 240 MHz from 2350 MHz to 2590 MHz, while the minimum total antenna efficiency is 62% within the 2.4 GHz ISM band.

This paper presents a compact metal plate lens antenna for evaluating a wave absorber placed on ceiling of the ETC gate. The focal distance of the lens was derived to be 129 cm by the geometrical optics procedure. By arranging the lens in front of a horn antenna, the gain and beamwidth characteristics were improved from 18 dBi to 26 dBi and from 22 degrees to 7 degrees, respectively. Then the antenna characteristics were evaluated when the distance between the antenna and the lens was changed in order to miniaturize the lens antenna. As the result, the changes in beamwidth were held to within 1 dB when the lens came close to the horn antenna. Scattering, phase and electric field intensity of electromagnetic wave were evaluated to clarify the foundation of the given characteristics. It was found that the field intensity for the miniaturized lens antenna is stronger than that for GO designed one though the phase uniformity is worse. The distance between the horn antenna and lens can be reduced to 80 cm. The absorption characteristics for the arranged absorbers which have different absorptions were measured, and it was shown that the proposed method was suitable for specifying the deteriorated absorber in the ETC system.

The mode-matching applications to scattering from circular and annular apertures in a thick perfectly conducting plane are reviewed. The Hankel and Weber transforms are utilized to solve the boundary-value problems of circular and annular apertures. Simple electrostatic problems are presented to illustrate the mode-matching method in terms of the Hankel and Weber transforms. Various types of Weber transform are discussed with boundary-value problems. Electromagnetic radiation and scattering from circular and annular aperture geometries are summarized. The utility of the mode-matching method in circular and annular aperture scattering is emphasized.

This paper proposes a virtual layered successive detector with adaptive transmit signal phase rotation for quadrature amplitude modulation (QAM) that enables high speed communication even in downlinks of wireless communication systems. It is shown that the detection performance is degraded when the eigenvalue of a virtual channel becomes close to the power of the additive white Gaussian noise (AWGN). Therefore, adaptive transmit signal phase rotation is introduced for the detector to improve the transmission performance. For the transmit phase rotation, three techniques to search the rotation angles are proposed, which can reduce the feedback information from the receiver to the transmitter. Among the three proposed techniques, the technique called “iterative variable step step search” is shown to achieve the best performance. Actually, it is confirmed by computer simulation that the variable step search makes the detector attain about 17 dB of a gain at the bit error rate (BER) of 10-5 in 42 multiple-input-multiple-output (MIMO) systems.

A novel online speaker clustering method based on a generative model is proposed. It employs an incremental variant of variational Bayesian learning and provides probabilistic (non-deterministic) decisions for each input utterance, on the basis of the history of preceding utterances. It can be expected to be robust against errors in cluster estimation and the classification of utterances, and hence to be applicable to many real-time applications. Experimental results show that it produces 50% fewer classification errors than does a conventional online method. They also show that it is possible to reduce the number of speech recognition errors by combining the method with unsupervised speaker adaptation.

This paper presents a simple 3-D array configuration for high-resolution 2-D Direction-Of-Arrival (DOA) estimation. Planar array structures like Uniform Rectangular Array (URA) or Uniform Circular Array (UCA) often well estimate azimuth angle but cannot well estimate elevation angle because of short antenna aperture in elevation direction. One may put more number of array elements to improve elevation angle estimation accuracy, however it will require very large hardware and software cost. This paper presents a simple 3-D array structure for high-resolution 2-D DOA estimation only by modifying the height of some array elements in a planar array. Based on the analysis of Cramer-Rao Lower Bound (CRLB) formulation and its dependency on the height of array elements, we develop a simple 3-D array structure which improves elevation angle estimation accuracy while preserving azimuth angle estimation accuracy.

Directional antennas provide numerous benefits, such as higher gains, increased transmission range, and lower interferences. In this paper, we propose a reliable broadcast protocol for directional antenna referred to as beam table-based reliable broadcast for directional antennas (BTRB). The BTRB employs (1) ACK-based scheme to provide full reliability; (2) spatio-temporal ACK combination to resolve the problems of ACK implosion and transmission delay; and (3) beam table caching to represent spatial relationship among destination nodes in the broadcast group. Performance evaluation has shown that the proposed BTRB shows full reliability and outperforms existing reliable broadcast schemes with respect to transmission delay by about 55%.