An algorithm for encoding low-density parity check (LDPC) codes is investigated. The algorithm computes parity check symbols by solving a set of sparse equations, and the triangular factorization is employed to solve the equations efficiently. It is shown analytically and experimentally that the proposed algorithm is more efficient than the Richardson's encoding algorithm if the code has a small gap.

In this paper an analysis of component and system reliability for lattice systems is proposed when component failures are not statistically independent. We deal the case that the failure rate of a component depends on the number of the adjacent failed components. And we discuss the maintainability of the system when a failed component is replaced by a spare component. At first we discuss the approximated reliability of each component. Then we estimate the mean number of failed components. Furthermore, the system reliability is approximated by using the component reliability.

In this paper, we propose a new method that can remove view-disturbing noises from stereo images. One of the thorny problems in outdoor surveillance by a camera is that adherent noises such as waterdrops on the protecting glass surface lens disturb the view from the camera. Therefore, we propose a method for removing adherent noises from stereo images taken with a stereo camera system. Our method is based on the stereo measurement and utilizes disparities between stereo image pair. Positions of noises in images can be detected by comparing disparities measured from stereo images with the distance between the stereo camera system and the glass surface. True disparities of image regions hidden by noises can be estimated from the property that disparities are generally similar with those around noises. Finally, we can remove noises from images by replacing the above regions with textures of corresponding image regions obtained by the disparity referring. Experimental results show the effectiveness of the proposed method.

This paper considers the reliable multicast transport protocols used in hybrid networks that include wired and wireless networks and transparent proxy servers. We present four analytic performance models of two extreme reliable multicast transport protocols, sender-initiated and receiver-initiated, and supported and unsupported by transparent proxy servers are considered in each reliable multicast protocol. We analyze the throughputs of these four different models mathematically. Numerical results show that transparent proxy servers give good effects to overall performance. Furthermore, the receiver-initiated reliable multicast supported by transparent proxy servers gives better performances of total throughput than sender-initiated reliable multicast supported by transparent proxy servers. We provide efficiency criterion of the optimal number of transparent proxy servers for each protocol under varying wireless loss probabilities. Numerical results are verified by simulations.

This paper presents an approach that uses the Viterbi algorithm in a stereo correspondence problem. We propose a matching process which is visualized as a trellis diagram to find the maximum a posterior result. The matching process is divided into two parts: matching the left scene to the right scene and matching the right scene to the left scene. The last result of stereo problem is selected based on the minimum error for uniqueness by a comparison between the results of the two parts of matching process. This makes the stereo matching possible without explicitly detecting occlusions. Moreover, this stereo matching algorithm can improve the accuracy of the disparity image, and it has an acceptable running time for practical applications since it uses a trellis diagram iteratively and bi-directionally. The complexity of our proposed method is shown approximately as O(N2P), in which N is the number of disparity, and P is the length of the epipolar line in both the left and right images. Our proposed method has been proved to be robust when applied to well-known samples of stereo images such as random dot, Pentagon, Tsukuba image, etc. It provides a 95.7 percent of accuracy in radius 1 (differing by 1) for the Tsukuba images.

When a large-size car exists on the ETC lane (Electronic Toll Collection System), there is the possibility that the interference on the adjacent lane occurs by the scattering waves from one. In this paper, we propose a new improvement method which the transparent EM wave absorber is placed between the ETC lane and the adjacent one in order to suppress the scattering waves from a large-size car. Therefore, we design the transparent EM wave absorber which consists of the transparent resistive and conductive films. Then, this absorber is produced, and its reflection and transmission coefficients are evaluated. In addition, its transmittance in optics is evaluated. As the results, the reflectivity of this absorber is obtained lower than -20 dB in the oblique incident angle from 0to 30at 5.8 GHz circular polarized wave, abbreviated as CP wave, and also the transmittivity is obtain lower than -27 dB in the oblique incident angle from 0to 70, respectively. On the other hand, the transmittance in optics is obtained higher than 60%. Moreover, we study experimentally on the ETC system with placing this absorber between the ETC lane and the adjacent one. We measured the distribution of receiving power on the adjacent lane, when a water sprinkler existed on the ETC lane. As a result, it is confirmed that the receiving power on the adjacent lane could be realized lower than -70.5 dBm, and then a new improvement method has proven to be very useful in the ETC system.

Recently, DOAS (differential optical absorption spectroscopy) has been used for nondestructive air monitoring, in which the LS (least squares) method is used to calculate trace gas concentrations due to its computational simplicity. This paper applies the ICA (independent component analysis) method to the DOAS system of air monitoring, since the LS method is insufficient to recover the desired spectra perfectly due to sparsity characteristic. If the sparsity of reference spectra in the DOAS system imposes the assumption of independence, the ICA algorithm can be used. The proposed method is used to regress the observed spectrum on the estimates of the reference spectra. The ICA algorithm can be seen as a preprocessing method where the ICs of the references are used as the input in the regression. The performance of the proposed method is evaluated in simulation studies using synthetic data.

This paper focuses on the underdetermined blind source separation (BSS) of three speech signals mixed in a real environment from measurements provided by two sensors. To date, solutions to the underdetermined BSS problem have mainly been based on the assumption that the speech signals are sufficiently sparse. They involve designing binary masks that extract signals at time-frequency points where only one signal was assumed to exist. The major issue encountered in previous work relates to the occurrence of distortion, which affects a separated signal with loud musical noise. To overcome this problem, we propose combining sparseness with the use of an estimated mixing matrix. First, we use a geometrical approach to detect when only one source is active and to perform a preliminary separation with a time-frequency mask. This information is then used to estimate the mixing matrix, which allows us to improve our separation. Experimental results show that this combination of time-frequency mask and mixing matrix estimation provides separated signals of better quality (less distortion, less musical noise) than those extracted without using the estimated mixing matrix in reverberant conditions where the reverberant time (TR) was 130 ms and 200 ms. Furthermore, informal listening tests clearly show that musical noise is deeply lowered by the proposed method comparatively to the classical approaches.

In this paper, we propose a statistical model for detecting article errors, which Japanese learners of English often make in English writing. It is based on the three head words--the verb head, the preposition, and the noun head. To overcome the data sparseness problem, we apply the backed-off estimate to it. Experiments show that its performance (F-measure=0.70) is better than that of other methods. Apart from the performance, it has two advantages: (i) Rules for detecting article errors are automatically generated as conditional probabilities once a corpus is given; (ii) Its recall and precision rates are adjustable.

This paper presents a technique for designing a dielectric Electronically Steerable Parasitic Array Radiator (Espar) antenna to achieve miniaturization of the conventional Espar antenna. The antenna's size is reduced by immersing the central active element in a dielectric cylinder, mounting the surrounding planar parasitic elements at the circumference of the cylinder, and decreasing the radius of the ground skirt to that of the parasitic elements. An example of a polycarbonate (εr = 2.9 + j0.006) Espar antenna operating at 2.484 GHz is optimised by using a genetic algorithm in conjunction with an FEM-based cost function. The designed antenna generates a half-power beam width of 78and a main lobe that elevates at an angle of only 5from the horizontal plane. The designed antenna is also fabricated and measured. Good agreement between the measurement and simulation results is obtained. We reduce the size of the designed Espar antenna to 1/8 the size of its conventional counterpart while achieving a 12improvement in half-power beam width.

This paper presents an analysis of the applicability of Sparse Kernel Principal Component Analysis (SKPCA) for feature extraction in speech recognition, as well as, a proposed approach to make the SKPCA technique realizable for a large amount of training data, which is an usual context in speech recognition systems. Although the KPCA (Kernel Principal Component Analysis) has proved to be an efficient technique for being applied to speech recognition, it has the disadvantage of requiring training data reduction, when its amount is excessively large. This data reduction is important to avoid computational unfeasibility and/or an extremely high computational burden related to the feature representation step of the training and the test data evaluations. The standard approach to perform this data reduction is to randomly choose frames from the original data set, which does not necessarily provide a good statistical representation of the original data set. In order to solve this problem a likelihood related re-estimation procedure was applied to the KPCA framework, thus creating the SKPCA, which nevertheless is not realizable for large training databases. The proposed approach consists in clustering the training data and applying to these clusters a SKPCA like data reduction technique generating the reduced data clusters. These reduced data clusters are merged and reduced in a recursive procedure until just one cluster is obtained, making the SKPCA approach realizable for a large amount of training data. The experimental results show the efficiency of SKPCA technique with the proposed approach over the KPCA with the standard sparse solution using randomly chosen frames and the standard feature extraction techniques.

We propose a robust edge detection method based on independent component analysis (ICA). It is known that most of the basis functions extracted from natural images by ICA are sparse and similar to localized and oriented receptive fields, and in the proposed edge detection method, a target image is first transformed by ICA basis functions and then the edges are detected or reconstructed with sparse components only. Furthermore, by applying a shrinkage algorithm to filter out the components of noise in the ICA domain, we can readily obtain the sparse components of the original image, resulting in a kind of robust edge detection even for a noisy image with a very low SN ratio. The efficiency of the proposed method is demonstrated by experiments with some natural images.

This paper first discusses the misinterpretation of the concept of "ubiquitous computing" that Mark Weiser originally proposed in 1991. Weiser's main message was not the ubiquity of computers, but the transparency of interface that determines users' perception of digital technologies embedded in our physical environment seamlessly. To explore Weiser's philosophy of transparency in interfaces, this paper presents the design of an interface that uses glass bottles as "containers" and "controls" for digital information. The metaphor is a perfume bottle: Instead of scent, the bottles have been filled with music -- classical, jazz, and techno music. Opening each bottle releases the sound of a specific instrument accompanied by dynamic colored light. Physical manipulation of the bottles -- opening and closing -- is the primary mode of interaction for controlling their musical contents. The bottles illustrates Mark Weiser's vision of the transparent (or invisible) interface that weaves itself into the fabric of everyday life. The bottles also exploits the emotional aspects of glass bottles that are tangible and visual, and evoke the smell of perfume and the taste of exotic beverages. This paper describes the design goals of the bottle interface, the arrangement of musical content, the implementation of the wireless electromagnetic tag technology, and the feedback from users who have played with the system.

To overcome inefficiencies on tree-based and mesh-based scheme, overlay multicast scheme for MANET has been recently proposed to provide higher packet delivery ratio than the former as well as more efficient resource usage than the latter. However, previous all overlay multicast schemes are not designed with any considerations for dense/sparse environments resulted from unlimited movement of mobile nodes. For this reason, all packets should be transmitted in the form of unicast packet so they cannot fully make use of node's broadcast capability even though some group members are densely distributed within single-hop on the same shared media. Due to above reason, this causes extra forwarding overhead, low resource utilization as well as high packet collision. In this paper, we propose a novel hybrid overlay multicast scheme, EAOM (Environment-Aware Overlay Multicast), which uses neighboring group members' information to deliver packet with low cost. In EAOM, a group member has two modes depending on the number of neighboring group members. Under dense environment, host group model in wired network is applied. While in sparse environment, packets are delivered to each receiver along overlay DDT (Data Delivery Tree) as same as previous overlay multicast schemes. Hence, EAOM can not only remove mentioned obstacles in dense environment, but also cope with network mobility very well in sparse environment. Using simulation results, we demonstrate that EAOM has good packet delivery ratio, low control overhead as well as short end-to-end delay.

In this paper, a fragment-processing solution in 3D graphics rendering algorithms based on fragment lists (i.e. A-buffer) for minimizing loss of image quality is described. While all fragment information should be preserved for exact hidden surface removal, this places additional strain on hardware in terms of silicon gates and clock cycles. Therefore, we propose a fragment processing technique that can effectively merge fragments in order to decrease the depth of fragment lists. It renders scenes quite accurately even in the case when three fragments intersect each other. This algorithm improves hardware acceleration without deteriorating image quality.

ESPAR (Electronically Steerable Passive Array Radiator) antennas were proposed as candidates for low-cost analog adaptive beamforming. The radiation pattern is controlled in an azimuthal plane by variable reactors loaded on each passive element. This paper estimates the frequency bandwidth of an ESPAR antenna in a single beam scanning operation. Bandwidth in terms of gain is predicted statistically as functions of beam direction and dynamic range of variable reactance. The -3 dB bandwidth of 7-element ESPAR antennas can be about 30%, 25% and 15% for the range of reactance of -100Ω Xn 100Ω, -50Ω Xn 50Ω and -100Ω Xn 0Ω, respectively, while the improper choice of reactance sets results in narrow bandwidth less than 5%.

In this paper, we propose an algorithm that automatically generates the intermediate scenes using the bidirectional disparity morphing (BDM) from the parallel stereo images. The two-step search strategy is used for speeding up the computation of the bidirectional disparity map and three occluding patterns are used for smoothing the computed disparities more elaborately. Using the bidirectional disparity map, we interpolate the left and the right image to their intermediate scenes. Then we dissolve two interpolated images into the desired intermediate scene which the holes are removed and the effect of the disparity estimation errors is minimized. We implemented the proposed algorithm on TM1300 supported by TriMedia using pSOSytem which enables to do multiprocessing. As a result, we can interpolate the high-quality intermediate scenes with real-time process.

Harmonic distortions of a recently developed lightweight film-type ESPAR (Electronically Steerable Passive Array Radiator) antenna are investigated experimentally. These distortions arise from the nonlinearity of the varactor diodes that are directly integrated with the parasitic radiator elements to control the antenna's radiation pattern. A reactive-near-field measurement technique that employs low-interference probes in an ultra-small anechoic box is used to reduce experimental time and cost. An anti-series varactor pair is introduced and compared with the conventional single varactor. Consequently, an ESPAR antenna equipped with the anti-series varactor pair exhibits remarkable suppression of nonlinear distortion. In particular, the second- and the third-order harmonic is reduced by approximately 20 dB and 12 dB from the level of a single varactor type ESPAR antenna, respectively.

In this paper, an associative memory model with a forgetting process proposed by Mezard et al. is investigated as a means of storing sparsely encoded patterns by the SCSNA proposed by Shiino and Fukai. Similar to the case of storing non-sparse (non-biased) patterns as analyzed by Mezard et al., this sparsely encoded associative memory model is also free from a catastrophic deterioration of the memory caused by memory pattern overloading. We theoretically obtain a relationship between the storage capacity and the forgetting rate, and find that there is an optimal forgetting rate leading to the maximum storage capacity. We call this the optimal storage capacity rate. As the memory pattern firing rate decreases, the optimal storage capacity increases and the optimal forgetting rate decreases. Furthermore, we shown that the capacity rate (i.e. the ratio of the storage capacity for the conventional correlation learning rule to the optimal storage capacity) is almost constant with respect to the memory pattern firing rate.

Finding corresponding edges is considered being the most difficult part of edge-based stereo matching algorithms. Usually, correspondence for a feature point in the first image is obtained by searching in a predefined region of the second image, based on epipolar line and maximum disparity. Reduction of search region can increase performances of the matching process, in the context of execution time and accuracy. Traditionally, hierarchical multiresolution techniques, as the fastest methods are used to decrease the search space and therefore increase the processing speed. Considering maximum of directional derivative of disparity in real scenes, we formulated some relations between maximum search space in the second images with respect to relative displacement of connected edges (as the feature points), in successive scan lines of the first images. Then we proposed a new matching strategy to reduce the search space for edge-based stereo matching algorithms. Afterward, we developed some fast stereo matching algorithms based on the proposed matching strategy and the hierarchical multiresolution techniques. The proposed algorithms have two stages: feature extraction and feature matching. We applied these new algorithms on some stereo images and compared their results with those of some hierarchical multiresolution ones. The execution times of our proposed methods are decreased between 30% to 55%, in the feature matching stage. Moreover, the execution time of the overall algorithms (including the feature extraction and the feature matching) is decreased between 15% to 40% in real scenes. Meanwhile in some cases, the accuracy is increased too. Theoretical investigation and experimental results show that our algorithms have a very good performance with real complex scenes, therefore these new algorithms are very suitable for fast edge-based stereo applications in real scenes like robotic applications.