Recently, space-time block codes (STBCs) obtained from coordinate interleaved orthogonal designs (CIODs) have attracted considerable attention, due to the advantages of full-diversity transmission and single-symbol decodability. In this letter, we design a novel STBC from CIOD for two transmit antennas. The proposed code guarantees full-diversity and full-rate along with low peak-to-minimum power ratio (PMPR). Furthermore, in contrast to the existing Alamouti code, the performance of the proposed code is not degraded even in severely time-selective fading channels.

Owing to the large amount of speckle noise and ill-defined edges present in echocardiographic images, computer-based boundary detection of the left ventricle has proved to be a challenging problem. In this paper, a Markovian level set method for boundary detection in long-axis echocardiographic images is proposed. It combines Markov random field (MRF) model, which makes use of local statistics with level set method that handles topological changes, to detect a continuous and smooth boundary. Experimental results show that higher accuracy can be achieved with the proposed method compared with two related MRF-based methods.

Bicubic interpolation is one of the standard approaches for image magnification since it can be easily computed and does not require a priori knowledge nor a complicated model. In spite of such convenience, the images enlarged by bicubic interpolation are blurry, in particular for large magnification factors. This may be explained by four constraints of bicubic interpolation. Hence, by relaxing or replacing the constraints, we propose a new magnification method, which performs better than bicubic interpolation, but retains its compactness. One of the constraints is about criterion, which we replace by a criterion requiring that all pixel values are reproduced and preferential components in input images are perfectly reconstructed. We show that, by choosing the low frequency components or edge enhancement components in the DCT basis as the preferential components, the proposed method performs better than bicubic interpolation, with the same, or even less amount of computation.

When the bit rate of a compressed video sequence is reduced by a frequency domain transcoder system, the rate control scheme plays a very important role in maintaining consistent video quality. In this paper, we propose an efficient rate control scheme based on the complexity of MB (Macro Block) while conventional transcoding schemes use that of a picture. Since the frequency domain transcoder has to calculate the spatial activity of MB to adjust the quantization step, a process of converting the DCT (Discrete Cosine Transform) data into spatial one is required. The proposed scheme calculates the spatial activity from DCT data without converting them to pixel domain.

This paper proposes a novel robust fundamental frequency (F0) estimation algorithm based on complex-valued speech analysis for an analytic speech signal. Since analytic signal provides spectra only over positive frequencies, spectra can be accurately estimated in low frequencies. Consequently, it is considered that F0 estimation using the residual signal extracted by complex-valued speech analysis can perform better for F0 estimation than that for the residual signal extracted by conventional real-valued LPC analysis. In this paper, the autocorrelation function weighted by AMDF is adopted for the F0 estimation criterion and four signals; speech signal, analytic speech signal, LPC residual and complex LPC residual, are evaluated for the F0 estimation. Speech signals used in the experiments were an IRS filtered speech corrupted by adding white Gaussian noise or Pink noise whose noise levels are 10, 5, 0, -5 [dB]. The experimental results demonstrate that the proposed algorithm based on complex LPC residual can perform better than other methods in noisy environment.

The specification of a Multi-Agent System (MAS) involves the identification of a large number of entities and their relationships. This is a non-trivial task that requires managing different views of the system. Many problems concerning this issue originate in the presence of contradictory goals and tasks, inconsistencies, and unexpected behaviours. Such troublesome configurations should be detected and prevented during the development process in order to study alternative ways to cope with them. In this paper, we present methods and tools that support the management of contradictions during the analysis and design of MAS. Contradiction management in MAS has to consider both individual (i.e. agent) and social (i.e. organization) aspects, and their dynamics. Such issues have already been considered in social sciences, and more concretely in the Activity Theory, a social framework for the study of interactions in activity systems. Our approach applies knowledge from Activity Theory in MAS, especially its base of contradiction patterns. That requires a formalization of this social theory in order to be applicable in a software engineering context and its adaptation to agent-oriented methodologies. Then, it will be possible to check the occurrence of contradiction patterns in a MAS specification and provide solutions to those situations. This technique has been validated by implementing an assistant for the INGENIAS Development Kit and has been tested with several case studies. This paper shows part of one of these experiments for a web application.

An integration of the access/backbone network is expected to become indispensable in the future. We analyze the current and future optical networks and we describe the promising technologies. GMPLS architecture in backbone networks and WDM PON architecture in access networks will play the most important roles. We overview recent studies on the access/backbone integrated network to achieve guaranteed QoS. We also describe the developed system architecture as a milestone toward the access/backbone integrated network.

We present a novel training method for recognizing traffic sign symbols. The symbol images captured by a car-mounted camera suffer from various forms of image degradation. To cope with degradations, similarly degraded images should be used as training data. Our method artificially generates such training data from original templates of traffic sign symbols. Degradation models and a GA-based algorithm that simulates actual captured images are established. The proposed method enables us to obtain training data of all categories without exhaustively collecting them. Experimental results show the effectiveness of the proposed method for traffic sign symbol recognition.

Test compression / decompression using variable-length coding is an efficient method for reducing the test application cost, i.e., test application time and the size of the storage of an LSI tester. However, some coding techniques impose slow test application, and consequently a large test application time is required despite the high compression. In this paper, we clarify the fact that test application time depends on the compression ratio and the length of codewords and then propose a new Huffman-based coding method for achieving small test application time in a given test environment. The proposed coding method adjusts both of the compression ratio and the minimum length of the codewords to the test environment. Experimental results show that the proposed method can achieve small test application time while keeping high compression ratio.

In this paper, we discuss the relationship between the test generation complexity for path delay faults (PDFs) and that for stuck-at faults (SAFs) in combinational and sequential circuits using the recently introduced τk-notation. On the other hand, we also introduce a class of cyclic sequential circuits that are easily testable, namely two-column distributive state-shiftable finite state machine realizations (2CD-SSFSM). Then, we discuss the relevant conjectures and unsolved problems related to the test generation for sequential circuits with PDFs under different clock schemes and test generation models.

A new method for data hiding in binary images based on block pattern coding and dynamic programming with distortion-minimizing capabilities is proposed. Up to three message data bits can be embedded into each 22 block in an input image by changing the block's pixel pattern into another, which represents the value of the message data bits as a code according to a block pattern encoding table. And extraction of hidden message data is accomplished by block pattern decoding. To minimize the resulting image distortion, two optimization techniques are proposed. The first is to use multiple block pattern encoding tables, from which an optimal one is selected specifically for each input image, and the second is to use a dynamic programming algorithm to divide the message data into bit segments for optimal embedding in a sense of minimizing the number of binary bit flippings. Accordingly, not only more data bits can be embedded in an image block on the average, but the resulting image distortion is also reduced in an optimal way. Experimental results are also included to show the effectiveness of the proposed approach.

In this paper, a new method for clustering of players in order to analyze games in soccer videos is proposed. The proposed method classifies players who are closely related in terms of soccer tactics into one group. Considering soccer tactics, the players in one group are located near each other. For this reason, the Euclidean distance between the players is an effective measurement for the clustering of players. However, the distance is not sufficient to extract tactics-based groups. Therefore, we utilize a modified version of the community extraction method, which finds community structure by dividing a non-directed graph. The use of this method in addition to the distance enables accurate clustering of players.

We point out the unstable operation of reverse traffic management in the cdma2000 1xEV-DO system, and propose a new rate control scheme that controls the reverse traffic load more precisely. The proposed scheme is modeled as a multidimensional Markov process and compared with the conventional scheme. The analysis results show that the proposed rate control scheme has a lower overload probability and higher reverse link throughput than the conventional one.

Existing methods for inverse motion compensation (IMC) in the DCT domain have not considered the unrestricted motion vector (UMV). In the existing methods, IMC is performed to deal with the UMV in the spatial domain after the inverse DCT (IDCT). We propose an IMC method which can deal with the UMV directly in the DCT domain without the use of the IDCT/DCT required by the existing methods. The computational complexity of the proposed method can be reduced by about half of that of the brute-force method operating in the spatial domain. Experimental results show that the proposed method can efficiently reduce the processing time with similar visual quality.

This paper proposes probabilistic pruning techniques for a Bayesian video face recognition system. The system selects the most probable face model using model posterior distributions, which can be calculated using a Sequential Monte Carlo (SMC) method. A combination of two new pruning schemes at the resampling stage significantly boosts computational efficiency by comparison with the original online learning algorithm. Experimental results demonstrate that this approach achieves better performance in terms of both processing time and ID error rate than a contrasting approach with a temporal decay scheme.

Future optical code division multiple access (CDMA) networks should be designed for multirate and fully integrated multimedia services. In the conventional schemes, multilength optical orthogonal codes (OOCs) are designed to support multirate systems, while variable-weight OOCs are designed to support differentiated quality of service (QoS) for multimedia applications. In this paper, a novel class of optical signature codes; multiple-length variable-weight optical orthogonal codes (MLVW-OOC) is proposed for supporting multirate and integrated multimedia services in optical CDMA networks. The proposed MLVW-OOC has features that are easy to construct variable-weight codes and expanded to multiple-length codes. A construction method for designing MLVW-OOCs up to three levels of codes is discussed. The designed MLVW-OOCs can support differentiated requirements on data rates and QoS for several types of services in the networks. A code analysis for obtaining the value of cross-correlation constraints or multiple access interference (MAI) computation for several levels of codes is also suggested. The cross-correlation constraints of the proposed codes are better than the conventional codes such as multilength OOCs. Finally, the bit error probability performance of the two-level MLVW-OOC is evaluated analytically. The results show that the proposed MLVW-OOC can provide differentiated bit error probability performances for several combinations of data rates and QoS.

For a microstrip antenna (MSA) with a ring-shaped slot on formed on the ground plane, downsizing the microstrip patch and expanding the circularly polarized bandwidth have been achieved successfully. The dimensions of the patch are 6.8 mm7.4 mm and the minimum axial ratio (AR) of 0.6 dB is obtained at 6.1 GHz. In addition, its AR is less than 3 dB at the relative bandwidth of 3.5%. The bandwidth of the proposed MSA is twice that of conventional single-feeding circularly polarized MSAs; however, its size is only half that of conventional MSAs.

In this paper, we propose a novel bicubic method for digital image interpolation. Since the conventional bicubic method does not consider image local features, the interpolated images obtained by the conventional bicubic method often have a blurring problem. In this paper, the proposed bicubic method adopts both the local asymmetry features and the local gradient features of an image in the interpolation processing. Experimental results show that the proposed method can obtain high accuracy interpolated images.

To achieve scalability and security, large networks are often structured hierarchically as a collection of domains. In hierarchical networks, the topology and QoS parameters of a domain have to be first aggregated before being propagated to other domains. However, topology aggregation may distort useful information. Although spanning tree aggregation can perfectly encode attribute information of symmetric networks, it can not be applied to asymmetric networks directly. In this paper, we propose a spanning tree based attribute aggregation method for asymmetric networks. The time complexity of the proposed method and the space complexity of its resulted aggregated topology are the same with that of the spanning tree aggregation method in symmetric networks. This method can guarantee that the attributes of more than half of the links in the networks are unaltered after aggregation. Simulation results show that the proposed method achieves the best tradeoff between information accuracy and space complexity among the existing asymmetric attribute aggregation methods.

The key weakness of Low-Density Parity Check codes is the complexity of the encoding scheme. The generator matrices can be made by Gaussian elimination of parity check matrices for normal block codes. Richardson succeeded in making parity bits from parity check matrices by the low density computation. In this letter, we focus on the execution of numerical experiments which show that even if the matrix D, which is the part of the Richardson's LDPC matrix, is restricted, proposed LDPC codes is lower complexity than Richardson's LDPC codes. The constraint of D results in reducing complexity from O(n + g2) to O(n) due to the omission of computing inverse matrices of φ and T in Richardson's encoding scheme. All the sub-matrices in parity check matrix are composed of Circulant Permutation Matrices based on Galois Fields.