A new sputtering technique named "itshape limited reaction sputtering" is proposed and the feasibility toward an ultra-thin gate insulator is investigated. 5-10 nm thick ZrO2 films were prepared on Si(100) substrates and analyzed by XPS, HR-RBS and RHEED. Significant Zr diffusion into the Si substrate and interface oxidation were not observed. An optimum film was obtained at growth temperature of 300, oxygen flow rate of 4.2% and 500-10 sec RTA. The equivalent oxide thickness of 2 nm was realized with leakage current of 10-7 A/cm2 at 1.5 MV/cm.

Software inspection is one of the most effective methods to detect defects. However, inspections are not always worthwhile. This letter proposes an inspection cost model to describe inspections-related costs and extended metrics to evaluate the cost effectiveness of software inspections.

Recent new technologies of electro-mechanical conversion devices have been reviewed. Especially, the electrochemical properties of anisotropic actuators using polypyrrole have been reviewed in detailed and the realization of the bimorph (or bending beam) structure without artificial adhesive agent is introduced.

In-plane-aligned a-axis-oriented YBa2Cu3O7-δ (YBCO) thin films are attractive for the formation of planar intrinsic Josephson devices. In this study, these films were deposited by dc sputtering on LaSrGaO4 (LSGO) (100) substrates and the dependence of the characteristics on the deposition conditions was investigated. In-plane-aligned a-axis-oriented YBCO thin films were successfully grown in the substrate temperature range of 555-615. With the temperature gradient method, it was seen that the critical temperature of the film increased to 81 K. The current-voltage characteristic along the c-axis exhibited clear multibranch structures. These results indicate that ion-cleaning of the substrate surface broadens the growth temperature range of these films and planar intrinsic Josephson devices can be fabricated from these films.

In this paper, a novel description method of the contour of a shape using extended fractal interpolation functions (EFIFs) is presented. Although the scope of application of traditional FIFs has been limited to cases in which a given signal is represented by a single-valued function, the EFIFs derived by the introduction of a new parameter can describe a multiple-valued signal such as the contour of a shape with a high level of accuracy. Furthermore, the proposed description method possesses the useful property that once a given contour has been modeled by the proposed description method, the shape can be easily expanded at an arbitrary expansion rate. Experimental results show the effectiveness and usefulness of the proposed description method for representing contours.

Although many researchers have verified the superiority of Support Vector Machine (SVM) on text categorization tasks, some recent papers have reported much lower performance of SVM based text categorization methods when focusing on all types of parts of speech (POS) as input words and treating large numbers of training documents. This was caused by the overfitting problem that SVM sometimes selected unsuitable support vectors for each category in the training set. To avoid the overfitting problem, we propose a two step text categorization method with a variable cascaded feature selection (VCFS) using SVM. VCFS method selects a pair of the best number of words and the best POS combination for each category at each step of the cascade. We made use of the difference of words with the highest mutual information for each category on each POS combination. Through the experiments, we confirmed the validation of VCFS method compared with other SVM based text categorization methods, since our results showed that the macro-averaged F1 measure (64.8%) of VCFS method was significantly better than any reported F1 measures, though the micro-averaged F1 measure (85.4%) of VCFS method was similar to them.

Photocatalytic TiO2 films were prepared by reactive gas flow sputtering (GFS), which enables sputter-deposition at a high pressure of about 100 Pa. A pure Ti tube was used as the target, and the O2 gas was supplied in front of the substrate, resulting in a very stable discharge and a high deposition rate of 80 nm/min. The crystal structure and morphology of TiO2 films were found to strongly depend on the flow rate of O2 gas during sputtering. Polycrystalline films composed of rutile and anatase crystallites were deposited at a low O2 flow rate of less than 2 sccm when Ar flow rate was set at 300 sccm, and amorphous films were deposited at higher O2 flow rates. Polycrystalline films composed of very small crystallites showed high levels of photocatalytic activity, while amorphous films showed no activity.

Polyurethane elastomer (PUE) films similar to polymer gel materials have been found to exhibit the electrostriction effect. We proposed the application their to a moving device such as an actuator without ionic solvent using the electrostriction effect of PUE. The actuators are of monomorph type fabricated by PUE film and metal electrodes evaporated at different thicknesses on the film surface. Because these actuators work at high voltage more than 1 KV, we controlled the molecular structure of the films by doping C60 derivatives (fullerenol) into PUE so that the actuators could operate under a low voltage. In order to clear the bending mechanism of actuators, we measured the space charge of PUE films using the pulsed electroacoustic method.

This paper proposes a new decision feedback decoding scheme for Alamouti-based space-time block coding (STBC) transmission over time-selective fading channels. In wireless channels, time-selective fading effects arise mainly due to Doppler shift and carrier frequency offset. Modelling the time-selective fading channels as the first-order Gauss-Markov processes, we use recursive algorithms such as Kalman filtering, LMS and RLS algorithms for channel tracking. The proposed scheme consists of the symbol decoding stage and channel tracking algorithms. Computer simulations confirm that the proposed scheme shows the better performance and robustness to time-selectivity.

This letter introduces a novel multi-user detection method, successive interference cancellation based on the order of log-likelihood-ratio(LLR-SIC), for code division multiple access (CDMA) systems. Unlike the conventional successive interference cancellation (SIC) based on the order of correlation, LLR-SIC operates on the fact that the user with the largest absolute value of log-likelihood ratio (LLR) should be first detected and cancelled from received signal. Simulation results show that LLR-SIC significantly outperforms the conventional SIC and partial parallel interference cancellation (P-PIC) over Rayleigh fading channels, and that LLR-SIC performance is not sensitive to channel estimation error at medium Eb/N0.

A computationally efficient time delay and Doppler estimation algorithm is proposed for active sonar with a Linear Frequency Modulated (LFM) signal. To reduce the computational burden of the conventional estimation algorithm, an algebraic equation is used which represents the relationship between the time delay and the Doppler in the cross-ambiguity function (CAF) of the LFM signal. The algebraic equation is derived based on the Fast Maximum Likelihood (FML) algorithm. The use of this algebraic relation enables the time delay and Doppler to be estimated with two 1-D searches instead of the conventional 2-D search.

To increase the spectral utilization efficiency of a wireless link, multiple-input multiple-output (MIMO) systems can be employed to transmit several data streams in parallel at the same time and on the same frequency but from different transmit antennas. However, at the receiver side multi-stream detection is needed. In this paper, ordered successive MMSE detection (OSD) is considered as a low-complexity detection scheme. OSD's main computational cost lies in computing the nulling weights that correspond to each stage of successive detection. In this paper, we develop an efficient semi-adaptive approach to generate MMSE weights. This semi-adaptive approach efficiently combines two approaches: channel estimates-based direct matrix inversion weights generation (direct approach) and Recursive Least Squares (RLS) algorithm-based weights generation (adaptive approach). Although the direct approach alone performs better than the adaptive approach, it is more complex for updating weights within the tracking mode. On the other hand, the adaptive approach alone is less complex in updating weights within the tracking mode, but converges slowly within the training mode. Our combined semi-adaptive approach effectively offsets these disadvantages. We demonstrate, through computer simulations, that the semi-adaptive approach can achieve the BER of the direct approach in slow time-varying MIMO channels, while its computational complexity is less than or comparable to that of the adaptive approach.

In this paper, using p-ary bent functions defined on vector space over the finite field Fpk, we generalized the construction method of the families of p-ary bent sequences with balanced and optimal correlation properties introduced by Kumar and Moreno for an odd prime p, called generalized p-ary bent sequences. It turns out that the family of balanced p-ary sequences with optimal correlation property introduced by Moriuchi and Imamura is a special case of the newly constructed generalized p-ary bent sequences.

Kernel methods such as the support vector machines map input vectors into a high-dimensional feature space and linearly separate them there. The dimensionality of the feature space depends on a kernel function and is sometimes of an infinite dimension. The Gauss kernel is such an example. We discuss the effective dimension of the feature space with the Gauss kernel and show that it can be approximated to a sum of polynomial kernels and that its dimensionality is determined by the boundedness of the input space by considering the Taylor expansion of the kernel Gram matrix.

This paper presents a novel technique for reconstructing an outdoor sculpture from an uncalibrated image sequence acquired around it using a hand-held camera. The technique introduced here uses only the silhouettes of the sculpture for both motion estimation and model reconstruction, and no corner detection nor matching is necessary. This is very important as most sculptures are composed of smooth textureless surfaces, and hence their silhouettes are very often the only information available from their images. Besides, as opposed to previous works, the proposed technique does not require the camera motion to be perfectly circular (e.g., turntable sequence). It employs an image rectification step before the motion estimation step to obtain a rough estimate of the camera motion which is only approximately circular. A refinement process is then applied to obtain the true general motion of the camera. This allows the technique to handle large outdoor sculptures which cannot be rotated on a turntable, making it much more practical and flexible.

The reduction of undesired electromagnetic emissions in switched power converters is a hot topic. Here, we propose a chaos based methodology to synthesize PWM-like signals for controlling the drives of induction motors. This approach reduces drastically the interference due to the drive-motor ensemble, and does not significantly alter the motor performance. The benefit is a 20 dB reduction in the peak of the emitted power density spectrum. This result is herein confirmed three times: first with an analytical approach based on approximations whose impact is progressively reduced; then by means of simulation; finally by laboratory testing of a working prototype.

We propose using SQP (Sequential Quadratic Programming) to directly recover 3D quadratic surface parameters from multiple views. A surface equation is used as a constraint. In addition to the sum of squared reprojection errors defined in the traditional bundle adjustment, a Lagrangian term is added to force recovered points to satisfy the constraint. The minimization is realized by SQP. Our algorithm has three advantages. First, given corresponding features in multiple views, the SQP implementation can directly recover the quadratic surface parameters optimally instead of a collection of isolated 3D points coordinates. Second, the specified constraints are strictly satisfied and the camera parameters and 3D coordinates of points can be determined more accurately than that by unconstrained methods. Third, the recovered quadratic surface model can be represented by a much smaller number of parameters instead of point clouds and triangular patches. Experiments with both synthetic and real images show the power of this approach.

Distributed database systems require a commit process to preserve the ACID property of transactions executed on a number of system sites. With the appearance of main memory database system, the database processing time has been reduced in the order of magnitude, since the database access does not incur any disk access at all. However, when it comes to distributed main memory database systems, the distributed commit process is still very slow since the disk logging at several sites has to precede the transaction commit. In this paper, we re-evaluate various distributed commit protocols and come up with a causal commit protocol suitable for distributed main memory database systems. To evaluate the performance of the proposed commit protocol, extensive simulation study has been performed. The simulation results confirm that the new protocol greatly reduces the time to commit the distributed transactions without any consistency problem.

In this paper, we propose a new method of automatic speech summarization for each utterance, where a set of words that maximizes a summarization score is extracted from automatic speech transcriptions. The summarization score indicates the appropriateness of summarized sentences. This extraction is achieved by using a dynamic programming technique according to a target summarization ratio. This ratio is the number of characters/words in the summarized sentence divided by the number of characters/words in the original sentence. The extracted set of words is then connected to build a summarized sentence. The summarization score consists of a word significance measure, linguistic likelihood, and a confidence measure. This paper also proposes a new method of measuring summarization accuracy based on a word network expressing manual summarization results. The summarization accuracy of each automatic summarization is calculated by comparing it with the most similar word string in the network. Japanese broadcast-news speech, transcribed using a large-vocabulary continuous-speech recognition (LVCSR) system, is summarized and evaluated using our proposed method with 20, 40, 60, 70 and 80% summarization ratios. Experimental results reveal that the proposed method can effectively extract relatively important information by removing redundant or irrelevant information.

Determining consistent global checkpoints of a distributed computation has applications in the areas such as rollback recovery, distributed debugging, output commit and others. Netzer and Xu introduced the notion of zigzag paths and presented necessary and sufficient conditions for a set of checkpoints to be part of a consistent global checkpoint. This result also reveals that determining the existence of zigzag paths between checkpoints is crucial for determining consistent global checkpoints. Recent research also reveals that determining zigzag paths on-line is not possible. In this paper, we present an off-line method for determining the existence of zigzag paths between checkpoints.