This paper presents an image watermarking method for two purposes: to notify the copyright owner with a visible watermark, and to protect the copyright with an invisible watermark. These two watermarks are embedded in different blocks with different methods. Simulation results show that the visible watermark is hard to remove and the invisible watermark is robust.

Within a few years it will be possible to integrate a billion transistors on a single chip operating at frequency more than 10 GHz. At this integration level, we propose using a multi-level ISA to express fine-grain data parallelism to hardware instead of using a huge transistor budget to dynamically extract it. Since the fundamental data structures for a wide variety of data parallel applications are scalar, vector, and matrix, our proposed Trident processor extends a scalar ISA with vector and matrix instruction sets to effectively process matrix formulated applications. Like vector architectures, the Trident processor consists of a set of parallel lanes (each lane contains a set of vector pipelines and a slice of register file) combined with a fast scalar core. However, Trident processor can effectively process on the parallel lanes not only vector but also matrix data. One key point of our architecture is the local communication within and across lanes to overcome the limitations of the future VLSI technology. Another key point is the effective execution of a mixture of scalar, vector, and matrix operations. This paper describes the architecture of the Trident processor and evaluates its performance on BLAS and on the standard matrix bidiagonalization algorithm. The last one is evaluated as an example of an entire application based on a mixture of scalar, vector, and matrix operations. Our results show that many data parallel applications, such as scientific, engineering, multimedia, etc., can be speeded up on the Trident processor. Besides, the scalability of the Trident processor does not require more fetch, decode, or issue bandwidth, but requires only replication of parallel lanes.

We have developed an ultrahigh-sensitivity "New Super-HARP" handheld camera, which has a sensitivity that is about 100 times as great as that of a CCD camera. The sensitivity of TV cameras is determined by the performance of the imaging device. We developed the world's first imaging device that achieves high sensitivity and high picture quality by using the avalanche multiplication phenomenon in an amorphous selenium photoconductive target. This "Super-HARP" pickup tube, which has already been used in TV production, has a selenium target 8-µm thick. It is about 10 times as sensitive as CCDs. We have now developed a greatly improved version of the Super-HARP tube with a target 25-µm thick. This improved version, called the New Super-HARP pickup tube, is about 10 times as sensitive as the Super-HARP pickup tube. The New Super-HARP handheld camera equipped with the new tubes has a maximum sensitivity of 11 lx at F8. This camera is a powerful tool for reporting breaking news at night and other low-light conditions, the production of scientific programs, and numerous other applications.

NK-Landscapes are stochastically generated fitness functions on bit strings, parameterized with N bits and K epistatic interactions between bits. The term epistasis describes nonlinearities in fitness functions due to changes in the values of interacting bits. Empirical studies have shown that the overall performance of random bit climbers on NK-Landscapes is superior to the performance of some simple and enhanced genetic algorithms (GAs). Analytical studies have also lead to suggest that NK-Landscapes may not be appropriate for testing the performance of GAs. In this work we study the effect of selection, drift, mutation, and recombination on NK-Landscapes for N = 96. We take a model of generational parallel varying mutation GA (GA-SRM) and switch on and off its major components to emphasize each of the four processes mentioned above. We observe that using an appropriate selection pressure and postponing drift make GAs quite robust on NK-Landscapes; different to previous studies, even simple GAs with these two features perform better than a random bit climber (RBC+) for a broad range of classes of problems (K 4). We also observe that the interaction of parallel varying mutation with crossover improves further the reliability of the GA, especially for 12 < K < 32. Contrary to intuition, we find that for small K a mutation only evolutionary algorithm (EA) is very effective and crossover may be omitted; but the relative importance of crossover interacting with varying mutation increases with K performing better than mutation alone (K > 12). This work indicates that NK-Landscapes are useful for testing each one of the major processes involved in a GA and for assessing the overall behavior of a GA on complex non-linear problems. This study also gives valuable guidance to practitioners applying GAs to real world problems of how to configure the GA to achieve better results as the non-linearity and complexity of the problem increases.

We show that the necessary and sufficient condition for the existence of a balanced bowtie decomposition of the complete multigraph λKn is n 5 and λ(n-1) 0 (mod 12). Decomposition algorithms are also given.

General packet radio service (GPRS) uses a two-stage mechanism to allocate uplink radio resource to mobile stations (MSs). In stage-1, the base station (BS) assigns several packet data channels (PDCHs) to an MS. Furthermore, a PDCH may be assigned to multiple MSs. In stage-2, therefore, the BS selects one of the multiplexed MSs in a PDCH to use the radio resource. In this paper, maintaining a load balance between PDCHs in stage-1 is examined and several selection schemes to lower the mis-selection rate in stage-2 are proposed. From our simulation results, the cost deduced from the poor load balancing and selection schemes render a lower system throughput and a non-negligible increase in packet queuing delay. Among the various stage-2 selection policies, round robin with linearly-accumulated adjustment (RRLAA) has the lowest mis-selection rate and outperforms the one without any heuristic by up to 50%.

A new type of photodetector called "photosensitive floating field emitter, (PFFE)" has been proposed. The PFFE device combines an n-type cone-shaped triode field emitter with a-Si p-i-n photodiode film. However, a PFFE cannot detect two-dimensional distributions of light intensity. In this paper, we propose a novel structure to overcome the above this problem of the PFFE. The device was fabricated on a silicon-on-sapphire substrate to permit irradiation from the backside. p-n photodiodes were constructed within a field emitters, the n+ region being separated by p+ regions to permit detection of two- dimensional light distributions. The emission current of the PFFE/SOS was found to be proportional to the illumination intensity, but the quantum efficiency was only about 2%. This quantum efficiency is lower than that expected. Under irradiation, the emission current increased, but the gate-leakage current increased. This gate-leakage current was several orders of magnitude larger than the emission current. Almost photo-generated electrons lost in the gate electrode.

Digital watermarking systems are required to embed as much information as possible in a digital media without the perceptual distortion as well as to extract it correctly with high probabilities, even though the media is subjected to many kinds of operations. To this end, guided scrambling (GS) techniques, usually used for a recording channel, are applied to digital watermarking systems. A simple GS scheme can make the power of a watermark signal larger against the power of media noise under the condition of preserving the perceptual fidelity, resulting in smaller error probabilities of the retrieved watermark bits. In addition, watermarking systems based on the GS can have more robustness to some specified operations if the prior information on the operations is given to the embedder. JPEG compression is a good example of such an operation when still images are transmitted over the Internet. In order for watermark signals to be more tolerable to the known JPEG attack, the GS-based watermark embedder is informed of advance knowledge of the JPEG compression. Further, a configuration of the GS concatenated with turbo coding is introduced to lower the bit error rate more.

Affine arithmetic is a kind of interval arithmetic defined by Stolfi et al. In affine arithmetic, it is difficult to realize the efficient nonlinear binomial operations. The purpose of this letter is to propose a new dividing method which is able to supply more suitable evaluation than the old dividing method. And this letter also shows the efficiency of the new dividing method by numerical examples.

Several 2 nm seed layers were sputtered to increase coercivity (Hc) and anisotropy (Ku) of CoCrPt/Ti perpendicular recording media. Among them 2 nm Ag seed layer was very effective to increase Hc of (Co78Cr22)100-xPtx/Ti (x = 14, 20). However, the effect was more pronounced when (Co78Cr22)100-xPtx/Ti became thinner. In addition α[=4π(dM/dH)Hc] decreased when the Ag layer was used. The film thickness below which the seed Ag layer was effective was reduced with decreasing Pt content. However, the Ag seed layer did not promote (0002) texture of Ti and CoCrPt layers. Domain size was reduced when the Ag seed layer was used. The effects of Ag seed layer are thought to be due to change of exchange constant of the grains, for which the grain boundary plays an important role. Effects of film thickness and Pt content can also be explained successfully by the variation of exchange constant due to grain boundary. Some experimental evidence as well as crude mode for exchange constant variation are given.

In this paper, we propose an answer seeking algorithm for question answering that integrates structural matching and paraphrasing, and report the results of our empirical evaluation conducted with the aim of examining effects of incorporating those two components. According to the results, the contribution of structural matching and paraphrasing was not so large as expected. Based on error analysis, we conclude that structural matching-based approaches to answer seeking require technologies for (a) coreference resolution, (b) processing of parse forests instead of parse trees, and (c) large-scale acquisition of paraphrase patterns.

Power control error is well known for its negative effects on CDMA system capacity. In this Letter, an analytical model is developed to estimate the uplink capacity for a SIR-based power controlled CDMA cellular system. The voice capacity reduction due to power control error is numerically examined with this model.

Although there has been a great deal of research on automatic summarization, most methods rely on statistical methods, disregarding relationships between extracted textual segments. We propose a novel method to extract a set of comprehensible sentences which centers on several key points to ensure sentence connectivity. It features a similarity network from documents with a lexical dictionary, and spreading activation to rank sentences. We show evaluation results of a multi-document summarization system based on the method participating in a competition of summarization, TSC (Text Summarization Challenge) task, organized by the third NTCIR project.

An ultra-high-sensitivity HDTV color camcorder (camera with VTR) has been developed featuring image intensifiers with GaAsP photocathodes, which provide very high quantum efficiency. To achieve superior performance and a compact camera body, we combined three 1-inch image intensifiers with a 2/3-inch taking lens and three 2/3-inch CCDs by means of a new optical system capable of enlarging and reducing images. The camcorder provides excellent color reproducibility even under low light level conditions (0.2 lx) at an iris setting of f/2, with a signal-to-noise ratio of 55 dB at pedestal level. Its sensitivity is about 400 times greater than that of current HDTV CCD camcorders, making it particularly well suited for capturing images of faint objects in space, aurora, etc., filming the nocturnal activities of animals in their natural settings, and reporting breaking news at night.

In light of the increasing number of computer applications that rely heavily on multimedia data, the database community has focused on the management and retrieval of multidimensional data. Nearest Neighbor queries (NN queries) have been widely used to perform content-based retrieval (e.g., similarity search) in multimedia applications. Incremental NN (INN) query is a kind of NN queries and can also be used when the number of the NN objects to be retrieved is not known in advance. This paper points out the weaknesses of the existing INN search algorithms and proposes a new one, called Batch-Incremental Nearest Neighbor search algorithm (denoted B-INN search algorithm), which can be used to process the INN query efficiently. The B-INN search algorithm is different from the existing INN search algorithms in that it does not employ the priority queue that is used in the existing INN search algorithms and is very CPU and memory intensive for large databases in high-dimensional spaces. And it incrementally reports b(b > 1) objects simultaneously (Batch-Incremental), whereas the existing INN search algorithms report the neighbors one by one. In order to implement the B-INN search, a new search (called k-d-NN search) with a new pruning strategy is proposed. Performance tests indicate that the B-INN search algorithm clearly outperforms the existing INN search algorithms in high-dimensional spaces.

In this paper, we consider the all-to-all broadcast problem in optical broadcast star networks using Wavelength Division Multiplexing. Our network model assumes that receivers are fixed-tuned and transmitters are tunable such that optical lasers assigned to transmitters have limited access to the network bandwidth; hence, each node must be equipped with multiple optical lasers and/or multiple optical filters in order to maintain a single-hop network. This paper is primarily concerned with single-hop networks, in which each node is assigned a single optical filter. Lower bounds are first established on the number of lasers per each node and the minimum schedule length, and a schedule achieving the minimum schedule length is presented. The results are applicable to arbitrary tuning delays, arbitrary numbers of wavelength channels, and optical lasers' arbitrary tuning ranges. Network models with optical devices having limited tuning ranges have not yet been considered in connection with transmission schedules, and this is the first work in this new direction.

In this paper, a Compensatory Neuro-Fuzzy Network (CNFN) for nonlinear system control is proposed. The compensatory fuzzy reasoning method is using adaptive fuzzy operations of neural fuzzy network that can make the fuzzy logic system more adaptive and effective. An on-line learning algorithm is proposed to automatically construct the CNFN. They are created and adapted as on-line learning proceeds via simultaneous structure and parameter learning. The structure learning is based on the fuzzy similarity measure and the parameter learning is based on backpropagation algorithm. The advantages of the proposed learning algorithm are that it converges quickly and the obtained fuzzy rules are more precise. The performance of CNFN compares excellently with other various exiting model.

In many cryptographic applications, a large-order finite field is used as a definition field, and accordingly, many researches on a fast implementation of such a large-order extension field are reported. This paper proposes a definition field Fpm with its characteristic p a pseudo Mersenne number, the modular polynomial f(x) an irreducible all-one polynomial (AOP), and using a suitable basis. In this paper, we refer to this extension field as an all-one polynomial field (AOPF) and to its basis as pseudo polynomial basis (PPB). Among basic arithmetic operations in AOPF, a multiplication between non-zero elements and an inversion of a non-zero element are especially time-consuming. As a fast realization of the former, we propose cyclic vector multiplication algorithm (CVMA), which can be used for possible extension degree m and exploit a symmetric structure of multiplicands in order to reduce the number of operations. Accordingly, CVMA attains a 50% reduction of the number of scalar multiplications as compared to the usually adopted vector multiplication procedure. For fast realization of inversion, we use the Itoh-Tsujii algorithm (ITA) accompanied with Frobenius mapping (FM). Since this paper adopts the PPB, FM can be performed without any calculations. In addition to this feature, ITA over AOPF can be composed with self reciprocal vectors, and by using CVMA this fact can also save computation cost for inversion.

In this paper color image compression using a fuzzy Hopfield-model net based on rough-set reasoning is created to generate optimal codebook based on Vector Quantization (VQ) in Discrete Wavelet Transform (DWT). The main purpose is to embed rough-set learning scheme into the fuzzy Hopfield network to construct a compression system named Rough Fuzzy Hopfield Net (RFHN). First a color image is decomposed into 3-D pyramid structure with various frequency bands. Then the RFHN is used to create different codebooks for various bands. The energy function of RFHN is defined as the upper- and lower-bound fuzzy membership grades between training samples and codevectors. Finally, near global-minimum codebooks in frequency domain can be obtained when the energy function converges to a stable state. Therefore, only 32/N pixels are selected as the training samples if a 3N-dimensional color image was used. In the simulation results, the proposed network not only reduces the consuming time but also preserves the compression performance.

This study describes the feasibility of using the penalty-function nonlinear programming neural network method to find the optimal power generating output which minimizes both the costs of generating power and power transmission losses. This method depends on neural network technology in acquiring exterior penalty function. Employing nonlinear function in equality and inequality constraints, the model is established using a neural network and additional objective functions; these additional objective functions expand cost function by using an appropriate penalty function. In this study, a 26-busbar including six generators was used to test the penalty function nonlinear programming neural network method. A comparison with the sequential unconstrained minimization technique (SUMT) demonstrates the reliability and precision of the optimal solution obtained using the new method.