In this paper a new watermarking technique which is combined with joint photographic experts group (JPEG) encoding system is presented. This method operates in the frequency domain by embedding a pseudo-random sequence of real numbers in a selected set of discrete cosine transform (DCT) coefficients. The embedded sequence is extracted without restoring the original image to fit the trend in the digital still camera (DSC) system. The proposed technique represents a major improvement on methods relying on the comparison between the watermarked and original images. Experimental results show that the proposed watermarking method is robust to several common image processing techniques, including JPEG compression, noise, and blurring. We also implement the whole design by synthesizing with TSMC 1P4M 0.35 µm standard cell. The chip size is 3.0643.064 mm2 for 46374 gate counts. The simulation speed can reach 50 MHz. The power dissipation is 69 mW at 3.3 V 50 MHz.

Simultaneous wavelength conversion utilizing four-wave mixing in optically-pumped GaN/AlN intersubband optical amplifiers has been investigated by means of a finite-difference time-domain (FDTD) model. The conversion efficiencies at a pump power of +7-+10 dBm were predicted to be -9-+6 dB depending on the frequency detuning (0.3-10.9 THz). The difference in efficiency among 18 channels of WDM signals with 100-GHz spacing was within about 3 dB.

The cost-effective provision of IP services requires multi-layered traffic engineering to obtain dynamic cooperation between IP and photonic layers. The effective control and management of generalized multi-protocol label-switching (GMPLS) networks is an essential part of this. Huge photonic capacities and the number of IP and photonic networks make it likely that enormous amounts of GMPLS network-related data will have to be managed in the near future. At the same time, routing burdens on individual GMPLS routers are critical because of the strong need for per-path quality of service (QoS). To solve these problems, we propose a hierarchically distributed network-management system (NMS) in which we flexibly allocate a GMPLS subnetwork to each sub-NMS and at the same time conduct QoS routing. The distributed nature of our architecture reduces the burden on the NMS as a whole and also lets us remove the routing-burden from GMPLS routers with minimum effect on management processes.

Fault-tolerance is an essential feature of the distributed systems where the possibility of a failure increases with the growth of the system. In spite of extensive researches over two decades, fault-tolerance systems have not succeeded in practical use. It is due to the high overhead and the unhandiness of the previous fault-tolerance systems. In this paper, we propose MPICH-GF, a user-transparent checkpointing system for grid-enabled MPICH. Our objectives are to fill the gap between the theory and the practice of fault-tolerance systems, and to provide a checkpointing-recovery system for grids. To build a fault-tolerant MPICH version, we have designed task migration, dynamic process management, and atomic message transfer. MPICH-GF requires no modification of application source codes, and it affects the MPICH communication characteristics as less as possible. The features of MPICH-GF are that it supports the direct message transfer mode and that all of the implementation has been done at the lower layer, that is, the abstract device level. We have evaluated MPICH-GF using NPB applications on Globus middleware.

Scientific computations for diffusion equations and ANNs (Artificial Neural Networks) are data intensive tasks accompanied by heavy memory access; on the other hand, their computational complexities are relatively low. Thus, this type of tasks naturally maps onto SIMD (Single Instruction Multiple Data stream) parallel processing with distributed memory. This paper proposes a high performance acceleration processor of which architecture is optimized for scientific computing using diffusion equations and ANNs. The proposed architecture includes a customized instruction set and specific hardware resources which consist of a control unit (CU), 16 processing units (PUs), and a non-linear function unit (NFU) on chip. They are effectively connected with dedicated ring and global bus structure. Each PU is equipped with an address modifier (AM) and 16-bit 1.5 k-word local memory (LM). The proposed processor can be easily expanded by multi-chip expansion mode to accommodate to a large scale parallel computation. The prototype chip is implemented with FPGA. The total gate count is about 1 million with 530, 432-bit embedded memory cells and it operates at 15 MHz. The functionality and performance of the proposed processor is verified with simulation of oil reservoir problem using diffusion equations and character recognition application using ANNs. The execution times of two applications are compared with software realizations on 1.7 GHz Pentium IV personal computer. Though the proposed processor architecture and the instruction set are optimized for diffusion equations and ANNs, it provides flexibility to program for many other scientific computation algorithms.

A new excitation enhancement technique based on a harmonic model is proposed in this paper to improve the speech quality of low-bit-rate speech coders. This technique is employed only in the decoding process of speech coders and improves high-frequency components of excitation. We develop the procedure of harmonic model parameters estimation and harmonic generation and apply the technique to a current state-of-art low bit rate speech coder. Experiments on spectrum reading and spectrum distortion measurement show that the proposed excitation enhancement technique improves speech quality.

Techniques for automatic program recognition, at the algorithmic level, could be of high interest for the area of Software Maintenance, in particular for knowledge based reengineering, because the selection of suitable restructuring strategies is mainly driven by algorithmic features of the code. In this paper an automated hierarchical concept parsing recognition technique, and a formalism for the specification of algorithmic concepts, is presented. Based on this technique, the design and development of ALCOR, a production rule based system for automatic recognition of algorithmic concepts within programs, aimed at support of knowledge based reengineering for high performance, is presented.

This paper proposes the use of the ratio of wavelet extrema numbers taken from the horizontal and vertical counts respectively as a texture feature, which is called aspect ratio of extrema number (AREN). We formulate the classification problem upon natural and synthesized texture images as an optimization problem and develop a coevolving approach to select both scalar wavelet and multiwavelet feature spaces of greater discriminatory power. Sequential searches and genetic algorithms (GAs) are comparatively investigated. The experiments using wavelet packet decompositions with the innovative packet-tree selection scheme ascertain that the classification accuracy of coevolutionary genetic algorithms (CGAs) is acceptable enough.

Bit-errors in a subband of a wavelet-based video frame during network transmission affect not only lower-level subbands within the same frame but also the subsequent frames. This is because the video frame is wavelet-transformed image with multi-levels and referenced from later frames. In this paper, we propose a new motion estimation scheme for wavelet-based video called Intra-frame Motion Estimation (IME), in which each subband except the LL subband refers to the 1-level-lower subband in the same orientation within the same frame. This scheme protects video quality by confining the effects of the bit-errors of all subbands, except the LL subband, within a frame. We evaluated the performance of our proposed scheme in a simulated wireless network environment. As a result of tests, it was shown that the proposed IME algorithm performs better than MRME, a motion-compensated video coding scheme for wavelet video, in a heavy motion video sequence, while IME outperforms MRME at a high bit-rate in small motion video sequence.

In 1987, Ito, Saito and Nishizeki proposed a secret sharing scheme realizing general access structures, called the multiple assignment secret sharing scheme (MASSS). In this paper, we propose new MASSS's which are perfect secret sharing schemes and include Shamir's (k,n)-threshold schemes as a special case. Furthermore, the proposed schemes are more efficient than the original MASSS from the viewpoint of the number of shares distributed to each participant.

A face recognition system based on the hard-limited eigenfunctions derived from the Karhunen-Loeve transform is proposed. The key of this approach is to change the inner product of the face image and the selected eigenvectors from floating point arithmetic to integer arithmetic. A database with 1000 facial images corresponding to 100 subjects is collected for system evaluation. It is demonstrated that 92% correct classification rate and 6-fold computational time saving can be achieved by the use of the first 150 hard-limited features.

All optical regenerations or wavelength conversions using SOA-based polarization discriminated switch injected by an assist light were investigated. First of all, cross gain modulation (XGM) and cross phase modulation (XPM) in a SOA injected by an external assist light were quantitatively analyzed. A simple measurement technique of XGM and XPM was shown to confirm that the injection of assist light could reduce a gain recovery time with some sacrifice for XGM and XPM efficiency. All-optical 3R regeneration using two-stage SOA-based polarization discriminated switch at 40 Gbit/s and its tolerances for some degradation against intensity deviation and optical signal-to-noise ratio (OSNR) were also shown. Finally, regeneration capability was evaluated through a dispersion shifted fiber (DSF)-based re-circulating loop transmission experiment. Those results indicate that the SOA-based polarization discriminated switch is a promising candidate for all-optical regenerator from the practical point of view.

Timing noise of 160 GHz optical pulses has been evaluated over nine decades of Fourier frequency using the optoelectronic harmonic mixing technique. For down-converting the 160 GHz pulse intensity into a low-frequency IF signal, the fourth order modulation sidebands produced by a Mach-Zehnder intensity modulator have been employed. Phase noise power spectral density and timing jitter for 155.552-GHz optical time-division multiplexed pulses and 160.640-GHz passively mode-locked pulses are measured using the time domain demodulation and time interval analysis techniques, respectively.

We demonstrate the wide-band (> 25-nm) long-distance (> 1000-km) chromatic dispersion compensation by midway spectral inversion (MSI) using a periodically-polled LiNbO3 device. In order to achieve a flat zero net dispersion, the fourth order dispersion of the single-mode fibers is canceled by MSI, while the third order dispersion is compensated for by the negative slope dispersion compensation fiber (NS-DCF). The second order dispersion is canceled out by both. The long distance propagation is realized by a double recirculation-loop system. A very flat zero dispersion is measured for the first time for over 1000-km single-mode fiber propagation with MSI dispersion compensation.

We have developed the tunable dispersion compensator based on two twin linearly chirped fiber Bragg gratings with various temperature gradients. Controlling the temperature gradient over one of the twin fiber Bragg gratings by Peltier elements, the dispersion and the dispersion slope were changed independently and continuously. The dispersion and dispersion slope compensator has a large bandwidth of 8 nm and low group-delay ripple of < 4 ps in its chirped fiber Bragg gratings. We experimentally demonstrated a precise controllability of the dispersion and the dispersion slope using linear and parabolic temperature gradient. The dispersion and the dispersion slope changes were achieved continuously with -0.67 ps/nm/ and -0.14 ps/nm2/. The transmission characteristics of the dispersion slope compensation were examined using ultra short pulses in the fiber link. When the total dispersion was zero, the distorted pulse was restored back and the tail was significantly suppressed. 160 Gbit/s signals were also demonstrated over 140 km within 1 dB power penalty by using the dispersion slope compensator.

The joint use of frequency-domain equalization and antenna diversity is presented for single-carrier (SC) transmission in a frequency-selective fading channel. Frequency-domain equalization techniques using minimum mean square error (MMSE), orthogonal restoration combining (ORC) and maximum ratio combining (MRC), those used in multi-carrier code division multiple access (MC-CDMA), are considered. As antenna diversity techniques, receive diversity and delay transmit diversity (DTD) are considered. Bit error rate (BER) performance achievable with the joint use of frequency-domain equalization and antenna diversity is evaluated by computer simulation.

In this paper, two efficient VLSI architectures for biorthogonal wavelet transform are proposed. One is constructed by the filter bank implementation and another is constructed by the lifting scheme. In the filter bank implementation, due to the symmetric property of biorthogonal wavelet transform, the proposed architecture uses fewer multipliers than the orthogonal wavelet transform. Besides, the polyphase decomposition is adopted to speed up the processing by a factor of 2. In the lifting scheme implementation, the pipeline-scheduling technique is employed to optimize the architecture. Both two architectures are with advantages of lower implementation complexity and higher throughput rate. Moreover, they can also be applied to realize the inverse DWT efficiently. Based on the above properties, the two architectures can be applied to time-critical image compressions, such as JPEG2000. Finally, the architecture constructed by the lifting scheme is implemented into a single chip on 0.35 µm 1P4M CMOS technology, and its area and working performance are 5.005 5.005 mm2 and 50 MHz, respectively.

We have developed Multi-modal Neural Networks (MNN) to improve the accuracy of symbolic sequence pattern classification. The basic structure of the MNN is composed of several sub-classifiers using neural networks and a decision unit. Two types of the MNN are proposed: a primary MNN and a twofold MNN. In the primary MNN, the sub-classifier is composed of a conventional three-layer neural network. The decision unit uses the majority decision to produce the final decisions from the outputs of the sub-classifiers. In the twofold MNN, the sub-classifier is composed of the primary MNN for partial classification. The decision unit uses a three-layer neural network to produce the final decisions. In the latter type of the MNN, since the structure of the primary MNN is folded into the sub-classifier, the basic structure of the MNN is used twice, which is the reason why we call the method twofold MNN. The MNN is validated with two benchmark tests: EPR (English Pronunciation Reasoning) and prediction of protein secondary structure. The reasoning accuracy of EPR is improved from 85.4% by using a three-layer neural network to 87.7% by using the primary MNN. In the prediction of protein secondary structure, the average accuracy is improved from 69.1% of a three-layer neural network to 74.6% by the primary MNN and 75.6% by the twofold MNN. The prediction test is based on a database of 126 non-homologous protein sequences.

In this report we present all-optical switches and modulators based on the intersubband transition in semiconductor quantum wells. The use of InGaAs/AlAsSb coupled double quantum well structures is proposed to facilitate intersubband transitions in the optical-communication band, and to reduce the intersubband absorption recovery time from several picoseconds to a few hundred femtoseconds by utilizing enhanced electron-phonon scattering. Subpicosecond all-optical gating and modulation in coupled double quantum wells are observed using pump-probe experiments at optical-communication wavelengths. The results indicate that the intersubband transition in this structure is very useful for ultrafast all-optical switching devices.

In this paper we apply a parallel adaptive solution algorithm to simulate nanoscale double-gate metal-oxide-semiconductor field effect transistors (MOSFETs) on a personal computer (PC)-based Linux cluster with the message passing interface (MPI) libraries. Based on a posteriori error estimation, the triangular mesh generation, the adaptive finite volume method, the monotone iterative method, and the parallel domain decomposition algorithm, a set of two-dimensional quantum correction hydrodynamic (HD) equations is solved numerically on our constructed cluster system. This parallel adaptive simulation methodology with 1-irregular mesh was successfully developed and applied to deep-submicron semiconductor device simulation in our recent work. A 10 nm n-type double-gate MOSFET is simulated with the developed parallel adaptive simulator. In terms of physical quantities and refined adaptive mesh, simulation results demonstrate very good accuracy and computational efficiency. Benchmark results, such as load-balancing, speedup, and parallel efficiency are achieved and exhibit excellent parallel performance. On a 16 nodes PC-based Linux cluster, the maximum difference among CPUs is less than 6%. A 12.8 times speedup and 80% parallel efficiency are simultaneously attained with respect to different simulation cases.