A method based on covariance differencing for a uniform linear array is proposed to counter the problem of direction finding of narrowband signals under a colored noise environment. By assuming a Hermitian symmetric Toeplitz matrix for the unknown noise, the array covariance matrix is transformed into a centrohermitian matrix in an appropriate way allowing the noise component to be eliminated. The modified covariance differencing algorithm provides accurate direction of arrival (DOA) estimation when the incident signals are uncorrelated or just two of the signals are coherent. If there are more than two coherent signals, the presented method combined with spatial smoothing (SS) scheme can be used. Unlike the original method, the new approach dispenses the need to determine the true angles and the phantom angles. Simulation results demonstrate the effectiveness of presented algorithm.

This paper addresses an application of the potential game theory to a power-aware mobile sensor coverage problem where each sensor tries to maximize a probability of target detection in a convex mission space. The probability of target detection depends on a sensing voltage of each mobile sensor as well as its current position. While a higher sensing voltage improves the target detection probability, this requires more power consumption. In this paper, we assume that mobile sensors have different sensing capabilities of detecting a target and they can adaptively change sensing areas by adjusting their sensing voltages. We consider an objective function to evaluate a trade-off between improving the target detection probability and reducing total power consumption of all sensors. We represent a sensing voltage and a position of each mobile sensor using a barycentric coordinate over an extended strategy space. Then, the sensor coverage problem can be formulated as a potential game where the power-aware objective function and the barycentric coordinates correspond to a potential function and players' mixed strategies, respectively. It is known that all local maximizers of a potential function in a potential game are equilibria of replicator dynamics. Based on this property of potential games, we propose decentralized control for the power-aware sensor coverage problem such that each mobile sensor finds a locally optimal position and sensing voltage by updating its barycentric coordinate using replicator dynamics.

This paper proposes an unsupervised word segmentation algorithm that identifies word boundaries in continuous source language text in order to improve the translation quality of statistical machine translation (SMT) approaches. The method can be applied to any language pair in which the source language is unsegmented and the target language segmentation is known. In the first step, an iterative bootstrap method is applied to learn multiple segmentation schemes that are consistent with the phrasal segmentations of an SMT system trained on the resegmented bitext. In the second step, multiple segmentation schemes are integrated into a single SMT system by characterizing the source language side and merging identical translation pairs of differently segmented SMT models. Experimental results translating five Asian languages into English revealed that the proposed method of integrating multiple segmentation schemes outperforms SMT models trained on any of the learned word segmentations and performs comparably to available monolingually built segmentation tools.

Based on sliding-window rule application and extraction filtering, we present a framework for extracting multi-slot frames describing chemical reactions from Thai free text with unknown target-phrase boundaries. A supervised rule learning algorithm is employed for automatic construction of pattern-based extraction rules from hand-tagged training phrases. A filtering method is devised for removal of incorrect extraction results based on features observed from text portions appearing between adjacent slot fillers in source documents. Extracted reaction frames are represented as concept expressions in description logics and are used as metadata for document indexing. A document knowledge base supporting semantics-based information retrieval is constructed by integrating document metadata with domain-specific ontologies.

This paper proposes Bayesian context clustering using cross validation for hidden Markov model (HMM) based speech recognition. The Bayesian approach is a statistical technique for estimating reliable predictive distributions by treating model parameters as random variables. The variational Bayesian method, which is widely used as an efficient approximation of the Bayesian approach, has been applied to HMM-based speech recognition, and it shows good performance. Moreover, the Bayesian approach can select an appropriate model structure while taking account of the amount of training data. Since prior distributions which represent prior information about model parameters affect estimation of the posterior distributions and selection of model structure (e.g., decision tree based context clustering), the determination of prior distributions is an important problem. However, it has not been thoroughly investigated in speech recognition, and the determination technique of prior distributions has not performed well. The proposed method can determine reliable prior distributions without any tuning parameters and select an appropriate model structure while taking account of the amount of training data. Continuous phoneme recognition experiments show that the proposed method achieved a higher performance than the conventional methods.

In this paper, we establish our child safety system model related to the addressing contradictory issue of wireless sensor networks caused by the mutual authentication and privacy protection of an end-user. Based on the system model, we propose the novel location-aware and privacy-preserving approach for providing child safety over wireless sensor networks. Although we illustrate our protocol over the sensor networks, the proposed protocol can be operated by various wireless networks (e.g., WiFi and UWB) which can support RSSI (Received Signal Strength Indication). Compared to a few previous works, the proposed approach can show the potential of enhancing accuracy with location information, preserve the privacy of an end-user, and provide the capability of controlling the child safety service to an end-user.

A new type of modulation called continuous-phase parallel-combinatory high-compaction multicarrier modulation (CPPC/HC-MCM) is proposed. CPPC/HC-MCM employs the technique of continuous-phase modulation (CPM) and avoids the formation of amplitude gaps between two successive signals to enhance the spectral efficiency of conventional PC/HC-MCM. Results of simulations show that CPPC/HC-MCM is spectrally efficient and achieves a smaller bit error rate than conventional (unmodulated) PC/HC-MCM at a common spectral efficiency even if the peak-to-average power ratio is considered.

This letter presents an experiment for estimating accurate state in distributed power systems. This letter employs a technique that combines a projected Jacobi method with a parallel dual-type method to solve the distributed state estimation with constraints problems. Via numerous tests, this letter demonstrates the efficiency of the proposed method on the IEEE 118-bus with four subsystems in a PC network.

The long-standing problem of predicting circuit performance variations without a huge number of statistical investigations is demonstrated to be solvable by a surface-potential-based MOSFET model. Direct connection of model parameters to physical device parameters reflecting process variations and the reduced number of model parameters are the enabling key model properties. It has been proven that the surface-potential-based model HiSIM2 is capable of reproducing measured I-V and its derivatives' variations with those of device/process related model parameters. When used to predict 51-stage ring oscillator frequency variation including both inter- and intra-chip variation, it reproduces measurements with shortened simulation time.

This paper proposes a modified per-survivor iterative timing recovery scheme, which exploits a new split-preamble strategy in conjunction with a per-survivor processing soft-output Viterbi algorithm (PSP-SOVA). The conventional split-preamble strategy places a preamble at the beginning of a data sector and uses it to run a phase-locked loop during acquisition to find an initial phase/frequency offset. However, the proposed scheme splits the preamble into two parts. The first part is placed at the beginning of the data sector, whereas the second part is divided into small clusters, each of which is then embedded uniformly within the data stream. This split preamble is utilized to adjust the branch metric calculation in PSP-SOVA to ensure that the survivor path occurs in a correct direction. Results indicate that the proposed scheme yields a better performance than a conventional receiver with separate timing recovery and turbo equalization, and the iterative timing recovery scheme proposed in [1],[2], especially when the timing jitter is large. In addition, we also show that the proposed scheme can automatically correct a cycle slip much more efficiently than the others.

We describe a technique for the registration of three dimensional (3D) knee femur surface points from MR image data sets; it is a technique that can track local cartilage thickness changes over time. In the first coarse registration step, we use the direction vectors of the volume given by the cloud of points of the MR image to correct for different knee joint positions and orientations in the MR scanner. In the second fine registration step, we propose a global search algorithm that simultaneously determines the optimal transformation parameters and point correspondences through searching a six dimensional space of Euclidean motion vectors (translation and rotation). The present algorithm is grounded on a mathematical theory - Lipschitz optimization. Compared with the other three registration approaches (ICP, EM-ICP, and genetic algorithms), the proposed method achieved the highest registration accuracy on both animal and clinical data.

Based on the known quadriphase zero correlation zone (ZCZ) sequences ZCZ4(N,M,T), four families of 16-QAM sequences with ZCZ are presented, where the term "QAM sequences" means the sequences over the quadrature amplitude modulation (QAM) constellation. When the quadriphase ZCZ sequences employed by this letter arrive at the theoretical bound on the ZCZ sequences, and are of the even family size M or the odd width T of ZCZ, two of the resulting four 16-QAM sequence sets satisfy the bound referred to above. The proposed sequences can be potentially applied to communication systems using 16-QAM constellation as spreading sequences so that the multiple access interference (MAI) and multi-path interference (MPI) are removed synchronously.

The actual blurring function or point spread function (PSF) in an image, in most cases, is similar to a parametric or ideal model. Recently proposed blind deconvolution methods employ this idea for learning during the estimation of PSF. Its dependence on the estimated values may result in ineffective learning when the model is erroneously selected. To overcome this problem, we propose to exploit the image maxima in order to extract a reference point spread function (RPSF). This is only dependent on the degraded image and has a structure that closely resembles a parametric motion blur assuming a known blur support size. Its usage will result in a more stable learning and estimation process since it does not change with respect to iteration or any estimated value. We define a cost function in the vector-matrix form which accounts for the blurring function contour as well as learning towards the RPSF. The effectiveness of using RPSF and the proposed cost function under various motion directions and support sizes will be demonstrated by the experimental results.

A critical problem with wireless LAN-based positioning systems is the degradation in position estimation accuracy due to complex variation in the strength of the received signal, which originates in the nature of the underlying wireless channel. Handling such variation effectively is essential for the creation of practical wireless LAN-based positioning systems. In this paper, we propose a collaborative mechanism for correcting position estimation errors. The main objective is to assist users in correcting estimation errors manually by providing access to a shared body of accumulated information on corrections made by many other users. In particular, the mechanism is designed to enable any group of users to collaboratively build upon this body of information. Finally, we evaluate the effectiveness of the proposed mechanism through experiments. The results confirm that the proposed mechanism can provide effective estimation error correction in a realistic environment.

In this paper, we study the minimum spanning tree problem with label selection, that is, the problem of finding a minimum spanning tree of a vertex-labeled graph where the weight of each edge may vary depending on the selection of labels of vertices at both ends. The problem is especially important as the application to mathematical OCR. It is shown that the problem is NP-hard. However, for the application to mathematical OCR, it is sufficient to deal with only graphs with small tree-width. In this paper, a linear-time algorithm for series-parallel graphs is presented. Since the minimum spanning tree problem with label selection is closely related to the generalized minimum spanning tree problem, their relation is discussed.

Four-wave mixing (FWM) compensation using digital coherent detection is experimentally demonstrated. Two lights and the induced FWM components are combined with phase-locked local oscillator lights and received individually. The received signals are combined electrically and the signal-to-FWM crosstalk ratio is improved to more than 30 dB by backward propagation.

Thin films of a divinyl derivative of tetraphenyldiaminobiphenyl DvTPD were prepared by vapor deposition followed by annealing. After annealing at 200°C for 1 h, the film became practically insoluble to organic solvents due to polymerization. Electrical characteristics of the films were measured by current-voltage measurement, time-of-flight measurement, and dielectric measurement. It was found that the hole mobility of DvTPD decreases when the film is polymerized. As a consequence of the decrease of hole mobility, carrier balance in the emissive layer of an organic light emitting diode (OLED) was improved, leading to a higher quantum efficiency and a pure emission spectrum. The dielectric measurement also confirmed the high thermal stability of the polymerized film.

In this letter, we analyze the effect of the size of observed data on the performance of time delay estimation (TDE) in the chirp spread spectrum (CSS) system. By adjusting the size of observed data, we reduce the effect of DC offsets, which would otherwise degrade the performance of TDE based on CSS, and we optimize the performance of TDE in CSS system. Finally, we derive the optimal size of observed data of TDE in CSS system.

Ad Hoc Routing (AHR) was proposed to replace optimal routing in cluster-based multihop networks since it offers lower implementation complexity. However, this complexity reduction comes at the cost of an increase in the required transmission power. In addition, when the conventional distributed relay selection is applied to implement AHR, another increase in the required transmission power occurs due to the receiver selection error. In this paper, Ad Hoc Cooperative Routing (AHCR) that integrates the cooperative transmission with AHR is presented to reduce the difference between the required transmission power of AHR and that of optimal routing. Besides, Distributed Ad Hoc Cooperative Routing (DAHCR) scheme 1 that combines the cooperative transmission with AHR is proposed to reduce the difference between the required transmission power of DAHR and that of AHR. We then address the problem of DAHCR scheme 1 and propose DAHCR scheme 2. Simulation results show that the required transmission power of AHCR and DAHCR scheme 1 is less than that of AHR and DAHR, respectively. In addition, DAHCR scheme 2 further reduces the required transmission power of DAHCR scheme 1. On the other hand, DAHCR scheme 1 increases the complexity by 43% compared to DAHR. Besides, DAHCR scheme 2 increases the complexity by 1.97% compared to DAHCR scheme 1.

We review our recent work on ultra-long-haul wavelength division multiplexed (WDM) transmission with high spectral efficiency (SE) employing tight pre-filtering and multi-symbol detection. We start the discussion with a theoretical evaluation of the SE limit of pre-filtered modulation in optical fiber communication systems. We show that pre-filtering induced symbol correlation generates a modulation with memory and thus, a higher SE limit than that of the original memory-less modulation. We also investigate the merits of utilizing the pre-filtering induced symbol correlation with multi-symbol detection to achieve high SE transmission. We demonstrate transoceanic WDM transmission of a pre-filtered polarization division multiplexed return-to-zero quaternary phased shift keying (PDM-RZ-QPSK) modulation format with multi-symbol detection, achieving 419% SE which is higher than the SE limit of the original memory-less PDM-RZ-QPSK format.