The power reduction of display devices has become an important issue for extending battery life and running time when they are used in digital multimedia broadcasting (DMB) mobile phones. DMB mobile phones generally use 16-bit data per pixel to reduce power consumption even though a liquid crystal display (LCD) graphic controller can support 16-, 18-, and 24-bit data per pixel. Also, the total transmission time of 16-bit data per pixel is only half that for 18- and 24-bit data per pixel. Decoded 24-bit image data in the frame memory of a DMB decoder are asymmetrically truncated to 16-bit image data. This results in a lack of smoothness such as blocking effects and/or pseudo edge artifacts. To solve these problems, the author proposes and implements a new asymmetric pixel data truncation error compensation algorithm using 1-bit least significant bit (LSB) data expansion with correlated color information for the purpose of ensuring smoothness. In the experimental results, the proposed algorithm is able to correct various artifacts.

In recent years, algorithms based on Computer Algebra ([1]-[3]) have been introduced into a range of control design problems because of the capacity to handle unknown parameters as indeterminates. This feature of algorithms in Computer Algebra reduces the costs of computer simulation and the trial and error process involved, enabling us to design and analyze systems more theoretically with the behavior of given parameters. In this paper, we apply Computer Algebra algorithms to H∞ control theory, representing one of the most successful achievements in post-modern control theory. More specifically, we consider the H∞ norm minimization problem using a state feedback controller. This problem can be formulated as follows: Suppose that we are given a plant described by the linear differential equation = Ax + B1w + B2u, z = Cx + Du, where A,B1,B2,C,D are matrices whose entries are polynomial in an unknown parameter k. We apply a state feedback controller u = -F x to the plant, where F is a design parameter, and obtain the system = (A - B2F)x + B1w, z =(C - DF)x. Our task is to compute the minimum H∞ norm of the transfer function G(s)(=(C - DF)(sI - A + B2F)-1B1) from w to z achieved using a static feedback controller u = -Fx, where F is a constant matrix. In the H∞ control theory, it is only possible to check if there is a controller such that ||G(s)||∞ < γ is satisfied for a given number γ, where ||G(s)||∞ denotes the H∞ norm of the transfer function G(s). Thus, a typical procedure to solve the H∞ optimal problem would involve a bisection method, which cannot be applied to plants with parameters. In this paper, we present a new method of solving the H∞ norm minimization problem that can be applied to plants with parameters. This method utilizes QE (Quantifier Elimination) and a variable elimination technique in Computer Algebra, and expresses the minimum of the H∞ norm as a root of a bivariate polynomial. We also present a numerical example to illustrate each step of the algorithm.

In this paper, we propose two weighting techniques to improve performances of query expansion in biomedical document retrieval, especially when a short biomedical term in a query is expanded with its synonymous multi-word terms. When a query contains synonymous terms of different lengths, a traditional IR model highly ranks a document containing a longer terminology because a longer terminology has more chance to be matched with a query. However, such preference is clearly inappropriate and it often yields an unsatisfactory result. To alleviate the bias weighting problem, we devise a method of normalizing the weights of query terms in a long multi-word biomedical term, and a method of discriminating terms by using inverse terminology frequency which is a novel statistics estimated in a query domain. The experiment results on MEDLINE corpus show that our two simple techniques improve the retrieval performance by adjusting the inadequate preference for long multi-word terminologies in an expanded query.

In order to find paths guaranteed by Quality of Service (QoS), the link state database (LSDB), containing QoS constraint information, and residing in routers, needs to be well managed. However, there is a trade-off between the exact reflection of the current link status and the update cost to calculate and maintain this data. In order to perfectly reflect the current link state, each router immediately notifies its neighbors whenever link state information changes. However, this may degrade the performance of the router. On the other hand, if current link state information is not updated routinely, route setup requests may be rejected because of the discrepancy between the current link state information and the previously updated link state information in the LSDB. Therefore, we need link state update (LSU) algorithms making it possible to appropriately update the LSDB. In addition, to facilitate implementation, they also should have low-complexity and must be adaptive under the variation of network conditions. In this paper, we propose an enhanced simple-adaptive (ESA) LSU algorithm, to reduce the generation of LSU messages while maintaining simplicity and adaptivity. The performance of this algorithm is compared with five existing algorithms by rigorous simulations. The comparision shows that the ESU algorithm can adapt to changes in network conditions and its performance is superior to existing LSU algorithms.

In rich scattering environments, multiple antenna systems designed to accomplish spatial multiplexing have enormous potential of lifting the capacity of corresponding multiple input multiple output channels. In this paper, we present a new low complexity algorithm for decision feedback equalization detector in the SM scheme. The basic idea is to reduce the joint optimization problem to separate optimization problems to achieve better performance-complexity tradeoffs. Concretely, we separately optimize the detection order and the detector filters so that the complexity of the entire signal detection task is reduced. The new order search rule approximates the optimal Bell Labs layered space time (BLAST) approach from a geometrical perspective, and the detector filters are derived using a Cholesky based QR decomposition. The new algorithm is able to switch from zero forcing to minimum mean square error without additional operations and the computational effort is a small fraction of that in the optimal BLAST algorithm. Despite its low complexity, the error performance of new detector closely approximates that of the standard BLAST.

Eye tracking is a useful tool for accurately mapping where and for how long an individual learner looks at a video/image, in order to obtain immediate information regarding the distribution of a learner's attention among the elements of a video/image. This paper describes a quantitative investigation into the effect of voice navigation in web-based learning materials.

Wireless mesh networks are attracting more and more attention as a promising technology for the next generation access infrastructure. QoS support is a unavoidable task given the rising popularity of multimedia applications, and also a challenging task for multi-hop wireless mesh networks. Among the numerous QoS factors, end-to-end delay is one of the most critical and important issues, especially for the real time applications. Over multi-hop wireless mesh networks, end-to-end delay of a flow is highly dependant on the number of hops as well as congestion condition of the hop nodes that the flow traverses through. In this paper, we propose QoS priority control schemes based on the end-to-end QoS delay metrics in order to increase traffic accommodation, i.e., the numbers of real-time flows which satisfy the requirements of end-to-end delay and packet delivery ratio over multi-hop wireless mesh networks. The first scheme enables source and forwarding nodes to perform priority control based on the number of hops of routes. The second scheme enables nodes to perform priority control based on the congestion condition of the hop nodes, where the flow traverses through. The effectiveness of the proposed schemes is investigated with NS-2 network simulator for voice and video traffics over multi-hop wireless mesh networks. Simulation results show that the scheme greatly improves the traffic accommodation for voice and video applications in multi-hop wireless mesh networks.

This paper addresses the ambiguity of radar altimetry related to the statistical nature of the Earth's surface roughness. A hypothetic altimetry method, which provides a simple way to quantify the measures of ambiguity, is proposed. Cramer-Rao lower bounds on the variances of estimates for the mean altitude and root-mean-square height of the sea surface are suggested as such quantitative measures. The accuracy of some types of air- and spaceborne radar altimeters is numerically analyzed against the derived lower bounds.

The thin film transistor liquid crystal display (TFT-LCD) image has nonuniform brightness, which is a major difficulty in finding the Mura defect region. To facilitate Mura segmentation, globally widely varying background signal must be flattened and then Mura signal must be enhanced. In this paper, Mura signal enhancement and background-signal-flattening methods using wavelet coefficient processing are proposed. The wavelet approximation coefficients are used for background-signal flattening, while wavelet detail coefficients are employed to magnify the Mura signal on the basis of an adapted contrast sensitivity function (CSF). Then, for the enhanced image, trimodal thresholding segmentation technique and a false-region elimination method based on the human visual system (HVS) are employed for reliable Mura segmentation. The experimental results show that the proposed algorithms produce promising results and can be applied to automated inspection systems for finding Muras in a TFT-LCD image.

In this paper, we propose the use of a discrete-time connection oriented Internet service system with a release delay for broadband, high-speed, high-capacity and high-reliability Internet requirements. The release delay called close-delay is set before the release process of a connection. An upper limit length T called timer length is set as a system parameter for the close-delay period. We build a batch arrival Geom*/G/1 queue model with a setup/close-delay/close-down strategy to characterize the system operation. By using a discrete-time imbedded Markov chain approach, we derive the stationary distribution of the system, and present the formula for Probability Generation Functions of the queue length, waiting time, busy period and busy cycle. Correspondingly, we describe the performance measures for the packet response time, setup ratio, and utility of connection. We also develop a cost model to determine the optimal timer length and its expected optimal cost. Based on numerical results, we discuss the influence of the timer length for the close-delay period on the system performance and investigate the minimum timer length and the minimum cost for different offered loads and different burst degrees, and show that the choice of the timer length is significant in improving the system performance.

This paper analyses the autocorrelation function of return waveforms in high precision radar altimeters employing chirp-pulse transmit signal under the condition of near-nadir deviations of the antenna boresight axis. It is shown that in case of ultra wideband transmit signals providing very high time resolution the correlation function can be approximated by a product of two separate functions of time.

This letter introduces a simple way of estimating the integer frequency offset (IFO) of OFDM-based digital video broadcasting (DVB) systems. By modifying the conventional maximum likelihood (ML) estimator to include the multi-stage estimation strategy, the IFO estimator is derived. Simulations indicate that the proposed IFO estimator works robustly when compared to ML estimator.

In a frequency-selective multiple-input multiple-output (MIMO) channel, the optimum transmission is achieved by beamforming with eigenvectors obtained at each discrete frequency point, i.e., an extension of eigenbeam-space division multiplexing (E-SDM). However, the calculation load of eigenvalue decomposition at the transmitter increases in proportion to the number of frequency points. In addition, frequency-independent eigenvectors increase the delay spread of the effective channel observed at the receiver. In this paper, we propose a pseudo eigenvector scheme for the purpose of mitigating the calculation load and maintaining frequency continuity (or decreasing the delay spread). First, we demonstrate that pseudo eigenvectors reduce the delay spread of the effective channels with low computational complexity. Next, the practical performance of the pseudo E-SDM (PE-SDM) transmission is evaluated. The simulation results show that PE-SDM provides almost the same or better performance compared with E-SDM when the receiver employs a time-windowing-based channel estimation available in the low delay spread cases.

Pairing based cryptography has been researched intensively due to its beneficial properties. In 2005, Wu et al. [3] proposed an identity-based key agreement for peer group communication from pairings. In this letter, we propose attacks on their scheme, by which the group fails to agree upon a common communication key.

Ziv-Lempel incremental parsing [1] is a fundamental algorithm for lossless data compression. There is a simple enumerative implementation [7] which preserves a duality between the encoder and the decoder. However, due to its compactness, the implementation when combined with a complete integer code, allows only an input sequence with a length consistent with the parsing boundaries. In this letter, we propose a simple additional mechanism for post-processing a binary file of arbitrary length, provided the file punctuation is externally managed.

In this paper, we present a new fast Fourier transform (FFT) algorithm to reduce the table size of twiddle factors required in pipelined FFT processing. The table size is large enough to occupy significant area and power consumption in long-point FFT processing. The proposed algorithm can reduce the table size to half, compared to the radix-22 algorithm, while retaining the simple structure. To verify the proposed algorithm, a 2048-point pipelined FFT processor is designed using a 0.18 µm CMOS process. By combining the proposed algorithm and the radix-22 algorithm, the table size is reduced to 34% and 51% compared to the radix-2 and radix-22 algorithms, respectively. The FFT processor occupies 1.28 mm2 and achieves a signal-to-quantization-noise ratio (SQNR) of more than 50 dB.

This paper presents 3D keyframe animation watermarking using orientation interpolators. 3D keyframe animation consists of a number of transform nodes, including a geometrical node from the initial model and several interpolator nodes that represent object movement. Therefore, the proposed algorithm randomly selects transform nodes with orientation interpolator nodes, then resamples the quaternion components to maintain a uniform key time. Thereafter, watermark bits are embedded into quaternion components with large rotation angles. Experimental results verify the robustness of the proposed algorithm to geometrical and timeline attacks, along with the subjective and objective quality of its invisibility.

In order to obtain better generalization performance in supervised learning, model parameters should be determined appropriately, i.e., they should be determined so that the generalization error is minimized. However, since the generalization error is inaccessible in practice, the model parameters are usually determined so that an estimator of the generalization error is minimized. The regularized subspace information criterion (RSIC) is such a generalization error estimator for model selection. RSIC includes an additional regularization parameter and it should be determined appropriately for better model selection. A meta-criterion for determining the regularization parameter has also been proposed and shown to be useful in practice. In this paper, we show that there are several drawbacks in the existing meta-criterion and give an alternative meta-criterion that can solve the problems. Through simulations, we show that the use of the new meta-criterion further improves the model selection performance.

In this paper, we describe a single system image (SSI) architecture for distributed systems. The SSI architecture is constructed through three components: single process space (SPS), process migration, and dynamic load balancing. These components attempt to share all available resources in the cluster among all executing processes, so that the distributed system operates like a single node with much more computing power. To this end, we first resolve broken pipe problems and bind errors on server socket in process migration. Second, we realize SPS based on block process identifier (PID) allocation. Finally, we design and implement a dynamic load balancing scheme. The dynamic load balancing scheme exploits our novel metric, effective tasks, to effectively distribute jobs to a large distributed system. The experimental results show that these three components present scalability, new functionality, and performance improvement in distributed systems.

The directional MAC protocols improve spatial reuse, but require the exact location of destination and have the problem of deafness. In this paper, we propose a dual-channel MAC protocol with directional antennas for mobile ad-hoc networks. In the proposed MAC protocol, RTS/CTS are sent omnidirectionally as nodes do not have the exact location of the destination in mobile environments. Omnidirectional transmissions on control channel overcome deafness, but have low spatial reuse. We propose a new blocking algorithm to improve spatial reuse on control channel. We use the negative CTS (NCTS) to solve the exposed terminal problem. We confirm throughput of the proposed MAC protocol by simulations using Qualnet ver. 3.8 simulator.