We describe a co-channel interference rejection scheme that is suitable for QR-decomposition maximum likelihood detection (MLD) in multiple-input and multiple output (MIMO) systems. A pre-whitening matrix for interference rejection is decomposed into a triangular matrix and its Hermitian matrix by using a complex Gaxpy version of the Cholesky algorithm. The decomposed triangular matrix is used as a spatial pre-filter to whiten co-channel interference. Simulation results demonstrate that the proposed scheme can suppress co-channel interference streams at the cost of receive diversity order and achieves better transmission performance than QR-decomposition MLD itself in MIMO channels with co-channel interference.

There are two main methods for pandemic simulations: the SEIR model and the MAS model. The SEIR model can deal with simulations quickly for many homogeneous populations with simple ordinary differential equations; however, the model cannot accommodate many detailed conditions. The MAS model, the multi-agent simulation, can deal with detailed simulations under the many kinds of initial and boundary conditions with simple social network models. However, the computing cost will grow exponentially as the population size becomes larger. Thus, simulations in the large-scale model would hardly be realized unless supercomputers are available. By combining these two methods, we may perform the pandemic simulations in the large-scale model with lower costs. That is, the MAS model is used in the early stage of a pandemic simulation to determine the appropriate parameters to be used in the SEIR model. With these obtained parameters, the SEIR model may then be used. To investigate the validity of this combined method, we first compare the simulation results between the SEIR model and the MAS model. Simulation results of the MAS model and the SEIR model that uses the parameters obtained by the MAS model simulation are found to be close to each other.

This paper proposes a new circuit-fed 2-D amplifying array architecture using the multi-ported aperture-coupled patch antennas. The power distribution achieved by this array is formed by stacking three kinds of basic cells repeatedly. Each cell, which serves as a radiator and also a power relay, has a multi-ported patch antenna and one or two amplifiers. The signal transmission coefficient of the cell from the input port to the output port is designed with a power level of 0 dB and a phase of 360. An X-band 4 3 element array with uniform amplitude distribution is demonstrated. The measured results, such as the antenna gain and the radiation patterns, agree very well with the predicted ones, due to the precision design of the basic cells. The measured gain of the antenna array is 27.7 dBiA at the frequency of 10.4 GHz on the H-plane, with a half-power beamwidth of 14 in the H-plane and 16 in the E-plane.

The situations where several population parameters need to be estimated simultaneously arise frequently in wide areas of applications, including reliability modeling, survival analysis and biological study. In this paper, we propose Bayesian methods of estimation of the ordered parameters of the two exponential populations, which incorporate the prior information about the simple order restriction, but sometimes breaks the order restriction. A simulation study shows that the proposed estimators are more efficient (in terms of mean square errors) than the isotonic regression of the maximum likelihood estimators with equal weights. An illustrative example is finally presented.

This paper proposes an approach to image segmentation using Iterated Graph Cuts based on local texture features of wavelet coefficients. Using Haar Wavelet based Multiresolution Analysis, the low-frequency range (smoothed image) is used for the n-link and the high-frequency range (local texture features) is used for the t-link along with the color histogram. The proposed method can segment an object region having not only noisy edges and colors similar to the background, but also heavy texture change. Experimental results illustrate the validity of our method.

Traditional frequent pattern mining algorithms do not consider different semantic significances (weights) of the items. By considering different weights of the items, weighted frequent pattern (WFP) mining becomes an important research issue in data mining and knowledge discovery area. However, the existing state-of-the-art WFP mining algorithms consider all the data from the very beginning of a database to discover the resultant weighted frequent patterns. Therefore, their approaches may not be suitable for the large-scale data environment such as data streams where the volume of data is huge and unbounded. Moreover, they cannot extract the recent change of knowledge in a data stream adaptively by considering the old information which may not be interesting in the current time period. Another major limitation of the existing algorithms is to scan a database multiple times for finding the resultant weighted frequent patterns. In this paper, we propose a novel large-scale algorithm WFPMDS (Weighted Frequent Pattern Mining over Data Streams) for sliding window-based WFP mining over data streams. By using a single scan of data stream, the WFPMDS algorithm can discover important knowledge from the recent data elements. Extensive performance analyses show that our proposed algorithm is very efficient for sliding window-based WFP mining over data streams.

By modifying the private key and the public key setting in Boneh-Lynn-Shacham's short signature shcheme, a variation of BLS' short signature scheme is proposed. Based on this variation, we present a very efficient threshold signature scheme where the number of pairing computation for the signaure share verification reduces to half.

This paper describes a design method of cosine-modulated filter banks (CMFB's) for an efficient coding of images. Whereas the CMFB has advantages of low design and implementation cost, subband filters of the CMFB do not have linear phase property. This prevents from employing a symmetric extension in transformation process, and leads to a degradation of the image compression performance. However, a recently proposed smooth extension alleviates the problem with CMFB's. As a result, well-designed CMFB's can be expected to be good candidates for a transform block in image compression applications. In this paper, we present a novel design approach of regular CMFB's. After introducing a regularity constraint on lattice parameters of a prototype filter in paraunitary (PU) CMFB's, we also derive a regularity condition for perfect reconstruction (PR) CMFB's. Finally, we design regular 8-channel PUCMFB and PRCMFB by an unconstrained optimization of residual lattice parameters, and several simulation results for test images are compared with various transforms for evaluating the proposed image coder based on the CMFB's with one degree of regularity. In addition, we show a computational complexity of the designed CMFB's.

Particle Swarm Optimization (PSO) is a search method which utilizes a set of agents that move through the search space to find the global minimum of an objective function. The trajectory of each particle is determined by a simple rule incorporating the current particle velocity and exploration histories of the particle and its neighbors. Since its introduction by Kennedy and Eberhart in 1995, PSO has attracted many researchers due to its search efficiency even for a high dimensional objective function with multiple local optima. The dynamics of PSO search has been investigated and numerous variants for improvements have been proposed. This paper reviews the progress of PSO research so far, and the recent achievements for application to large-scale optimization problems.

We propose a user-defined on-demand matching strategy, called O-matching, in which users can control the order of matching arguments of each operation symbol. In ordinary matching schemes it is not important to set the order of matching, however, in on-demand matching schemes, it is very important since an input term may be changed while doing the on-demand matching process. O-matching is suitable to combine with the E-strategy, which is a user-defined reduction strategy in which users can control the order of reducing arguments. We show a sufficient condition under which the E-strategy with O-matching is correct for head normal forms, that is, any reduced term is a head normal form.

Some wireless OFDMA communication systems support the frequency reuse factor of 1. In order to reduce co-channel interference (CCI) caused by neighbor cells, the fractional frequency reuse (FFR) can be employed. A promising frequency partitioning policy and subcarrier allocation for FFR are essential. In this letter, we employ an efficient frequency partitioning mechanism with less interference and propose an efficient subcarrier allocation algorithm to maximize the sum of users capacity under FFR. We show that the proposed algorithm has higher spectral efficiency than the conventional method as well as significantly high system fairness.

Most large-scale distributed file systems decouple a metadata operation from read and write operations for a file. In the distributed file systems, a certain server named a metadata server (MDS) is responsible for maintaining the metadata information of the file systems. In this paper, we propose a new metadata management scheme in order to provide the high metadata throughput and scalability for a cluster of MDSs. First, we derive a new metadata distribution technique. Then, we present a load balancing technique based on the distribution technique. Several experiments show that our scheme outperforms existing metadata management scheme in terms of scalability and load balancing.

Moving object completion is a process of completing moving object's missing information based on local structures. Over the past few years, a number of computable algorithms of video completion have been developed, however most of these algorithms are based on the pixel domain. Little theoretical and computational work in video completion is based on the compressed domain. In this paper, a moving object completion method on the compressed domain is proposed. It is composed of three steps: motion field transferring, thin plate spline interpolation and combination. Missing space-time blocks will be completed by placing new motion vectors on them so that the resulting video sequence will have as much global visual coherence with the video portions outside the hole. The experimental results are presented to demonstrate the efficiency and accuracy of the proposed algorithm.

This paper presents a grouped scan slice encoding technique using scan slice repetition to simultaneously reduce test data volume and test application time. Using this method, many scan slices that would be incompatible with the conventional selective scan slice method can be encoded as compatible scan slices. Experiments were performed with ISCAS'89 and ITC'99 benchmark circuits, and results show the effectiveness of the proposed method.

We present recent progress of high-speed Mach-Zehnder modulator technologies for advanced modulation formats. Multi-level quadrature amplitude modulation signal can be synthesized by using parallel Mach-Zehnder modulators. We can generate complicated multi-level optical signals from binary data streams, where binary modulated signals are vectorially summed in optical circuits. Frequency response of each Mach-Zehnder interferometer is also very important to achieve high-speed signals. We can enhance the bandwidth of the response, with thin substrate. 87 Gbaud modulation was demonstrated with a dual-parallel Mach-Zehnder modulator.

A critical problem after a natural/manmade disaster is to provide immediate post-disaster communication links between the disaster victims and some overlay networks. This paper proposes a novel scheme that uses the surviving Mobile handSets (MS) as sensing nodes to form an auto-configured Hierarchical Cognitive Radio Network (H-CRN). The implementation of this H-CRN is explained through detailed problem scenario statement and step-by-step implementation of automatic identification of emergency situation by the MS nodes. An overview of the cross-layer framework used by the MS nodes is also presented. This novel scheme is tested through some hypothesis along with probability calculations for successful identification of emergency situation, formation of ad hoc group and Emergency Beacon Message (EBM) transmission.

This letter proposes a busy-tone based scheme for reliable and efficient broadcasting in mobile ad hoc networks. Control packets such as RTS, CTS and ACK are ignored in the broadcast scheme, and two busy tones are used, one for channel reservation and the other for negative acknowledgement. Unlike traditional schemes for reliable broadcasting, the proposed scheme is highly efficient as it achieves both collision avoidance and fast packet loss recovery. Simulation results are presented which show the effectiveness of the proposed scheme.

An improved iterative minimum mean-squared error (MMSE) channel estimation method is proposed for joint coding and precoding OFDM systems. Compared with the traditional simplified estimator, the proposed scheme provides higher estimation quality with slight complexity increment at low signal-to-noise ratio (SNR) values. The performance of the iterative receiver including the proposed estimator approaches that of the perfect MMSE estimator without any simplification.

Internet routers need to classify incoming packets quickly into flows in order to support features such as Internet security, virtual private networks and Quality of Service (QoS). Packet classification uses information contained in the packet header, and a predefined rule table in the routers. Packet classification of multiple fields is generally a difficult problem. Hence, researchers have proposed various algorithms. This study proposes a multi-dimensional encoding method in which parameters such as the source IP address, destination IP address, source port, destination port and protocol type are placed in a multi-dimensional space. Similar to the previously best known algorithm, i.e., bitmap intersection, multi-dimensional encoding is based on the multi-dimensional range lookup approach, in which rules are divided into several multi-dimensional collision-free rule sets. These sets are then used to form the new coding vector to replace the bit vector of the bitmap intersection algorithm. The average memory storage of this encoding is θ (LNlog N) for each dimension, where L denotes the number of collision-free rule sets, and N represents the number of rules. The multi-dimensional encoding practically requires much less memory than bitmap intersection algorithm. Additionally, the computation needed for this encoding is as simple as bitmap intersection algorithm. The low memory requirement of the proposed scheme means that it not only decreases the cost of packet classification engine, but also increases the classification performance, since memory represents the performance bottleneck in the packet classification engine implementation using a network processor.

To mitigate the asynchronous ICI (Inter-Cell Interference), SCM (Spatial Covariance Matrix) of the asynchronous ICI plus background noise should be accurately estimated for MIMO-OFDMA (Multiple-input Multiple-output-Orthogonal Frequency Division Multiple Access) system. Generally, it is assumed that the SCM of the asynchronous ICI plus background noise is estimated by using training symbols. However, it is difficult to measure the interference statistics for a long time and considering that training symbols are not appropriate for OFDMA system such as LTE (3GPP Long Term Evolution). Therefore, noise reduction method is required to improve the estimation accuracy. Although the conventional time-domain low-pass type weighting method can be effective for noise reduction, it causes significant estimation error due to the spectral leakage in practical OFDM system. Therefore, we propose a time-domain sinc type weighing method which can not only reduce noise effectively minimizing estimation error caused by the spectral leakage but also can be implemented using frequency-domain weighted moving average filter easily. We also consider the iterative CFR (Channel Frequency Response) and SCM estimation method which can effectively reduce the estimation error of both CFR and SCM, and improve the performance for LTE system. By using computer simulation, we show that the proposed method can provide up to 2.5 dB SIR (Signal to Interference Ratio) gain compared with the conventional method, and verify that the proposed method is attractive and suitable for implementation with stable operation.