We call a network an anonymous network, if each vertex of the network is given no ID's. For distributed algorithms for anonymous networks, solvable problems depend strongly on the given initial conditions. In the past, initial conditions have been investigated, for example, by computation given the number of vertices as the initial condition, and in terms of what initial condition is needed to elect a leader. In this paper, we study the relations among initial conditions. To achieve this task, we define the relation between initial conditions A and B (denoted by A B) as the relation that some distributed algorithm can compute B on any network satisfying A. Then we show the following property of this relation among initial conditions. The relation is a partial order with respect to equivalence classes. Moreover, over initial conditions, it induces a lattice which has maxima and minima, and contains an infinite number of elements. On the other hand, we give new initial conditions k-LEADER and k-COLOR. k-LEADER denotes the initial condition that gives special condition only to k vertices. k-COLOR denotes the initial condition that divides the vertices into k groups. Then we investigate the property of the relation among these initial conditions.

Browsing is an important function supporting efficient access to relevant information in video archives. In this paper, we present PanoramaExcerpts -- a video browsing interface that shows a catalogue of two types of video icons: panoramic and keyframe icons. A panoramic icon is automatically synthesized from a video segment taken with camera pan or tilt using a camera parameter estimation technique. One keyframe icon is extracted for each shot to supplement the panoramic icons. A panoramic icon represents the entire visible contents of a scene extended with a camera pan or tilt, which is difficult to represent using a single keyframe. A graphical representation, called camera-work trajectory, is also proposed to show the direction and the speed of camera operation. For the automatic generation of PanoramaExcerpts, we propose an approach to integrate the following: (a) a shot-change detection method; (b) a method for locating segments that contain smooth camera operations; (c) a layout method for packing icons in a space-efficient manner. In this paper, we mainly describe (b) and (c) with experimental results.

The maximum likelihood estimate of a mixture model is usually found by using the EM algorithm. However, the EM algorithm suffers from a local optima problem and therefore we cannot obtain the potential performance of mixture models in practice. In the case of mixture models, local maxima often have too many components of a mixture model in one part of the space and too few in another, widely separated part of the space. To escape from such configurations we proposed a new variant of the EM algorithm in which simultaneous split and merge operations are repeatedly performed by using a new criterion for efficiently selecting the split and merge candidates. We apply the proposed algorithm to the training of Gaussian mixtures and the dimensionality reduction based on a mixture of factor analyzers using synthetic and real data and show that the proposed algorithm can markedly improve the ML estimates.

A novel residue arithmetic algorithm using radix-2 signed-digit (SD) number representation is presented. By this representation, memoryless residue arithmetic circuits using SD adders can be implemented. Conventional residue arithmetic circuits have been designed using binary number arithmetic system, but the carry propagation arises which limits the speed of arithmetic operations in residue modules. In this paper, a p-digit radix-2 SD number system is introduced to simplify the residue operation. For a modulus m, 2^p-1 m 2^p+2^p-1-1, in a residue number system (RNS), the modulo m addition is performed by using two p-digit SD adders, one for the addition and one for the residue operation. Thus, the modulo m addition time is independent of the word length of operands. When m=2^p or m= 2^p 1, the modulo m addition is implemented by using only one SD adder. Moreover, a modulo m multiplier is constructed using a binary modulo m SD adder tree, and the modulo m multiplication can be performed in a time proportional to log ₂ p. The VHDL implementation method for the presented algorithm is also discussed. The design and simulation results of some residue arithmetic circuits show that high speed residue arithmetic circuits can be obtained by the presented algorithms.

Causal message ordering in the context of group communication ensures that all the message receivers observe consistent ordering of events affecting a group as a whole. This paper presents a scalable causal multicast protocol for mobile distributed computing systems. In our protocol, only a part of the mobility agents in the system is involved in group computations and the resulting size of control information in messages can be kept small. Our protocol can outperform qualitatively the counterparts in terms of communication overhead and handoff complexity. An analytical model is also developed to evaluate our proposal. The performance results show that the proposed protocol is promising.

Recently, two approaches investigated indexing and retrieving videos. One approach utilized the visual features of individual objects, and the other approach exploited the spatio-temporal relationships between multiple objects. In this paper, we integrate both approaches into a new video model, called the Visual-Spatio-Temporal (VST) model to represent videos. The visual features are modeled in a topological approach and integrated with the spatio-temporal relationships. As a result, we defined rich sets of VST relationships which support and simplify the formulation of more semantical queries. An intuitive query interface which allows users to describe VST features of video objects by sketch and feature specification is presented. The conducted experiments prove the effectiveness of modeling and querying videos by the visual features of individual objects and the VST relationships between multiple objects.

We discuss human collaborative discovery processes using a production system model as a cognitive simulator. We have developed an interactive production system architecture to construct the simulator. Two production systems interactively find targets in which the only experimental results are shared; each does not know the hypothesis the other system has. Through this kind of interaction, we verify whether or not the performance of two systems interactively finding targets exceeds that of two systems independently finding targets. If we confirm the superiority of collaborative discovery, we approve of emergence by the interaction. The results are: (1) generally speaking collaboration does not produces the emergence defined above, and (2) as the different degree of hypothesis testing strategies that the two system use gets larger, the benefits of interaction gradually increases.

In this paper we have presented a new method for seismic signal analysis, based on the ARMA modeling and a fuzzy LVQ clustering method. The objective achieved in this work is to sense the changes made naturally or artificially on the seismogram signal, and to detect the sources, which caused these changes (seismic classification). During the study, we have also found out that the model is sometimes capable to alarm the further seismic events just a little time before the onset of those events (seismic prediction). So the application of the proposed method both in seismic classification and seismic prediction are studied through the experimental results. The study is based on the background noise of the teleseismic short period recordings. The ARMA model coefficients are derived for the consecutive overlapped windows. A base model is then generated by clustering the calculated model parameters, using the fuzzy LVQ method proposed by Nassery & Faez in [19]. The time windows, which do not take part in [19] model generation process, are named as the test windows. The model coefficients of the test windows are then compared to the base model coefficients through some pre-defined composition rules. The result of this comparison is a normalized value generated as a measure of similarity. The set of the consecutive similarity measures generate above, produce a curve versus the time windows indices called as the characteristic curves. The numerical results have shown that the characteristic curves often contain much vital seismological information and can be used for source classification and prediction purposes.

An automated method for cryptanalysis of DFT-based analog speech scramblers is presented through statistical estimation treatments. In the proposed system, the ciphertext only attack is formulated as a combinatorial optimization problem leading to a search for the most likely key estimate. For greater efficiency, we also explore the benefits of genetic algorithm to develop an estimation method which takes into account the doubly stochastic characteristics of the underlying keyspace. Simulation results indicate that the global explorative properties of genetic algorithms make them very effective at estimating the most likely permutation and by using this estimate significant amount of the intelligibility can be recovered from the ciphertext following the attack on DFT-based speech scramblers.

In this paper, we propose fast bitmap search algorithms to reduce the computational complexity of transform-based vector quantization (VQ) techniques, which achieve better quality in reconstructed images than the ordinary VQ. By removing the unlikely codewords in each step, the bitmap search method, which starts from the most significant bitmap then the successive significant ones, can save more than 90% computation of the ordinary transformed VQ. By applying to the singular value decomposition (SVD) VQ as an example, theoretical analyses and simulation results show that the proposed bitmap search methods dramatically reduce the computation and achieve invisible distortion in the reconstructed images.

In designing a field-programmable gate array (FPGA)-based processor for motion stereo, a parallel memory system and a simple interconnection network for parallel data transfer are essential for parallel image processing. This paper, firstly, presents an FPGA-oriented hierarchical memory system. To reduce the bandwidth requirement between an on-chip memory in an FPGA and external memories, we propose an efficient scheduling: Once pixels are transferred to the on-chip memory, operations associated with the data are consecutively performed. Secondly, a rectangular memory allocation is proposed which allocates pixels to be accessed in parallel onto different memory modules of the on-chip memory. Consequently, completely parallel access can be achieved. The memory allocation also minimizes the required capacity of the on-chip memory and thus is suitable for FPGA-based implementation. Finally, a functional unit allocation is proposed to minimize the complexity between memory modules and functional units. An experimental result shows that the performance of the processor becomes 96 times higher than that of a 400 MHz Pentium II.

In this paper, we define content-identifier (ContentID) to represent the characteristics of shot. The ContentID carries both positional and temporal color information. Based on the concept of ContentID, we propose a video retrieval method. The method is robust to compression, format conversion, frame dropping and noise such as watermark and so on. Furthermore, based on our retrieval method, we implemented a copyright protection system for digital video using spread-spectrum based watermarking technique.

A real-time adaptive segmentation method based on new distance features is proposed for the binary centroid tracker. These novel features are distances between the predicted center pixel of a target object by a tracking filter and each pixel in extraction of a moving target. The proposed method restricts clutters with target-like intensity from entering a tracking window and has low computational complexity for real-time applications compared with other complex feature-based methods. Comparative experiments show that the proposed method is superior to other segmentation methods based on the intensity feature only in target detection and tracking.

Semantic ambiguity is a serious problem in information retrieval. Query expansion has been proposed as one method of solving this problem. However, queries tend not to have much information for fitting query vectors to the latent semantics, which are difficult to express in a few query terms given by users. We propose a document vector modification method that modifies document vectors based on the relevance of documents. This method is expected to show better retrieval effectiveness than conventional methods. In this paper, we evaluate our method through retrieval experiments in which the relevance of documents extracted from scientific papers is assessed, and a comparison with tfidf is described.

An Off-line mammography screening system is used in pre-screening mammograms to separate high-risk mammograms from most normal cases. Off-line system can run before radiologist's review and is particularly useful in the national breast cancer screening program which usually consists of high percentage of normal cases. Until now, the shortcomings of on-line detection of clustered microcalcifications from a mammogram remain in the necessity of manual selection of regions of interest. The developed technique focuses on detection of microcalcifications within a region of interest indicated by the radiologist. Therefore, this kind of system is not efficient enough to process hundreds of mammograms in a short time without a large number of radiologists. In this paper, based on a "hierarchically-coarse-to-fine" approach, an off-line mammography screening system for the detection and segmentation of clustered microcalcifications is presented. A serial off-line procedures without any human intervention should consider the complexity of organization of mammograms. In practice, it is impossible to use one technique to obtain clustered microcalcifications without consideration of background text and noises from image acquisition, the position of breast area and regions of interest. "Hierarchically-coarse-to-fine" approach is a serial procedures without any manual operations to reduce the potential areas of clustered microcalcifications from a mammogram until clustered microcalcifications are found. The reduction of potential areas starts with a mammogram, through identification of the breast area, identification of the suspicious areas of clustered microcalcifications, and finally segmentation of clustered microcalcifications. It is achieved hierarchically from coarse level to fine level. In detail, the proposed system includes breast area separation, enhancement, detection and localization of suspicious areas, segmentation of microcalcifications, and target selection of microcalcifications. The system separates its functions into hierarchical steps and follows the rule of thumb "coarse detection followed by fine segmentation" in performing each step of processing. The decomposed hierarchical steps are as follows: The system first extracts the breast region from which suspicious areas are detected. Then precise clustered microcalcification regions are segmented from the suspicious areas. For each step of operation, techniques for rough detection are first applied followed by a fine segmentation to accurately detect the boundaries of the target regions. With this "hierarchically-coarse-to-fine" approach, a complicated work such as the detection of clustered microcalcifications can be divided and conquered. The effectiveness of the system is evaluated by three experienced radiologists using two mammogram databases from the Nijmegen University Hospital and the Taichung Veterans General Hospital. Results indicate that the system can precisely extract the clustered microcalcifications without human intervention, and its performance is competitive with that of experienced radiologists, showing the system as a promising asset to radiologists.

This paper deals with the decentralized supervisory control problems of uncertain discrete event systems which are represented as a set of some possible models. For a given global specification, this paper provides the necessary and sufficient conditions for the existence of local supervisors to achieve the specification under model uncertainty.

In this paper we develop a robust control theory to achieve fault-tolerant behaviors of timed discrete event systems (DESs) with model uncertainty represented as a set of some possible models. To demonstrate the effectiveness of the proposed theory, we provide a case study of a resistance spot welding process.

A minimum classification error formulation based on genetic algorithm is proposed for discriminative training of the bigram language model. Results of Chinese dialect identification were reported which demonstrate performance improvement with use of the genetic algorithm over the generalized probabilistic descent algorithm.

This Letter proposes a new three dimensional (3D) visual communication approach based on the image-based rendering. We first compactly represent a reference view set by exploiting its geometric correlation and then efficiently compress the representation with appropriate coding schemes. Experimental results demonstrate that our proposed method significantly reduces the required bitrate.

The classified side-match vector quantizer, CSMVQ, has already been presented for low-bit-rate image encoding. It exploits a block classifier to decide which class the input vector belongs to using the variances of the upper and left codewords. However, this block classifier doesn't take the variance of the current input vector itself into account. This letter presents a new CSMVQ in which a two-level block classifier is used to classify input vectors and two different master codebooks are used for generating the state codebook according to the variance of the input vector. Experimental results prove the effectiveness of the proposed CSMVQ.

In this letter we propose a filter for extracting a quasi-periodic signal from a noisy observation using wavelets. It is assumed that the instantaneous frequency of the signal is known. A particularly difficult task when the frequency and amplitude of the desired signal are varying with time is shown. The proposed algorithm is compared with three other methods.