In this paper, a test architecture optimization for system-on-a-chip under floorplanning constraints is proposed. The models of previous test architecture optimizations were too ideal to be applied to industrial SOCs. To make matters worse, they couldn't treat topological locality of cores, that is, floorplanning constraints. The optimization proposed in this paper can avoid long wires for TAMs in consideration of floorplanning constraints and finish optimizing test architectures within reasonable computation time.

In this paper, we propose a formal method for detection of three automation surprises in human-machine interaction; a mode confusion, a refusal state, and a blocking state. The mode confusion arises when a machine is in a different mode from that anticipated by the user, and is the most famous automation surprise. The refusal state is a situation that the machine does not respond to a command the user executes. The blocking state is a situation where an internal event occurs, leading to change of an interface the user does not know. In order to detect these phenomena, we propose a composite model in which a machine and a user model evolve concurrently. We show that the detection of these phenomena in human-machine interaction can be reduced to a reachability problem in the composite model.

We have investigated the pretilt angle of liquid crystal (LC) molecules induced by photo-alignment films of polyimide (Azo-PI) containing azobenzene in the backbone structure. To generate finite pretilt angles, the Azo-PI film with inclined alignment of the backbone structure was prepared by a double light-exposure method. In this method the corresponding polyamic acid (Azo-PAA) film was first exposed to linearly polarized ultraviolet/visible (UV/VIS) light (LP-light) at normal incidence, and then oblique angle irradiation of unpolarized UV/VIS light (UP-light) was performed in the plane of incidence perpendicular to the polarization direction of the LP-light. Repeated photo-isomerization reactions of azobenzene induce the alignment of the Azo-PAA backbone structure. By thermally imidizing the photo-treated film we obtained a thermally and optically stable Azo-PI film. The orientational distribution of the Azo-PI backbone structure was determined by measuring the polarized infrared absorption spectra as a function of the sample rotation angle and the angle of incidence. The pretilt angle of LC molecules was determined by a crystal rotation method. We found that the average inclination angle of the Azo-PI backbone structure increased with the UP-light exposure. The pretilt angle of LC molecules, measured from the surface plane, also increased with the UP-light exposure. We succeeded in generating a pretilt angle of 3. The relation between the LC pretilt angle and the average inclination angle of the Azo-PI backbone structure is discussed.

Efficient general secure multiparty computation (MPC) protocols were previously proposed, and the combination with the efficient auction circuits achieves the efficient sealed-bid auctions with the full privacy and correctness. However, the combination requires that each bidder submits ciphertexts of bits representing his bid, and their zero-knowledge proofs. This cost amounts to about 80 multi-exponentiations in usual case that the bid size is 20 bits (i.e. about 1,000,000 bid prices). This paper proposes sealed-bid auction protocols based on the efficient MPC protocols, where a bidder can submit only a single ciphertext. The bidder's cost is a few multi-exponentiations, and thus the proposed protocols are suitable for mobile bidders. A novel technique for the realization is a bit-slicing conversion by multiple servers, where a single ciphertext for a bid is securely converted into ciphertexts of bits representing the bid.

A digital/analog hybrid system is presented which implements the cardinal polynomial spline interpolation of arbitrary degree. Based on the fact that the (m-1)st derivative of a spline of degree m-1 is a staircase function, this system generates a cardinal spline of degree m-1 by m-1 cascaded integrators with a staircase function input. A given sequence of sampled values are transformed by a digital filter into coefficients for the B-spline representation of the spline interpolating the sampled values. The values of its (m-1)st derivative with respect to time are computed by the recurrence formula interpreting differentiation of the spline as difference of the coefficients. Then a digital-to-analog converter generates a staircase function representing the (m-1)st derivative, which is integrated by a cascade of m-1 analog integrators to make the expected spline. In order to cope with the offset errors involved in the integrators, a dynamical sampled-data control is attached. An analog-to-digital converter is employed to sample the output of the cascaded integrators. Target state of the cascaded integrators at each sampling instance is computed from the coefficients for the B-spline representation. The state error between the target and the estimated is compensated by feeding back a weighted sum of the state error to the staircase input.

Whereas the autocorrelation is frequently used for pitch estimation, the resultant estimates usually suffer from inaccuracy. Instead of upsampling, we can improve the accuracy of the estimates by applying polynomial interpolation to the autocorrelation directly. For that purpose, four kernels, which are interpolating quadratic, quadratic-B spline, cubic-B spline, and cubic convolution kernels respectively, have been compared. Experiments show that the cubic B spline kernel shows the best performance, a little inferior to the computationally intensive upsampling procedure. The quadratic B spline kernel shows also reasonable performance with the merit of the further reduced computational complexities compared with the cubic B spline kernel.

In this study, a CG animation tool was designed that allows interpolation and extrapolation of two types of repeated motions including finger actions, for quantitative analyses of the relationship between features of human motions and subjective impressions. Three-dimensional human motions are measured with a magnetic motion capture and a pair of data gloves, and then relatively accurate time-series joint data are generated utilizing statistical characteristics. Based on the data thus obtained, time-series angular data of each joint for two dancing motions is transformed into frequency domain by Fourier transform, and spectral shape of each dancing action is interpolated. The interpolation and extrapolation of two motions can be synthesized with simple manner by changing an weight parameter while keeping good harmony of actions. Using this CG animation tool as a motion synthesizer, repeated human motions such as a dancing action that gives particular impressions on the observers can be quantitatively measured and analyzed by the synthesis of actions.

With the explosive growth of the Internet system, demands for broadband communication networks have rapidly increased to provide high quality network services. For this purpose, the IEEE 802.6 MAC standard protocol defines the distributed-queue dual bus (DQDB) for metropolitan area networks (MANs). The isochronous channel reuse problem (ICRP) has been studied for efficient use of DQDB by finding proper channel assignments to incoming connection requests. In this paper, we first define the generalized isochronous channel reuse problem (GICRP) as a generalization of ICRP, to afford demands of simultaneously satisfying plural connection requests such as for multicast applications, where certain sets of connection requests must be assigned channels simultaneously. We prove the NP-completeness of its decision problem. Then, we propose a minimum dead space (MDS) algorithm as a heuristic approach to GICRP. The extensive simulation results show that with shorter computation time, our MDS algorithm can always find better channel assignments reducing the waiting time for packet transmissions than the best existing algorithm for conventional ICRP.

A new and fast fingerprint classification method based on direction patterns is presented in this paper. This method is developed to be applicable to today's embedded fingerprint authentication system, in which small area sensors are widely used. Direction patterns are well treated in the direction map at block level, where each block consists of 88 pixels. It is demonstrated that the search of directions pattern in specific area, generally called as pattern area, is able to classify fingerprints clearly and quickly. With our algorithm, the classification accuracy of 89% is achieved over 4000 images in the NIST-4 database, slightly lower than the conventional approaches. However, the classification speed is improved tremendously up to about 10 times as fast as conventional singular point approaches.

By modelling the quantization error as additive white noise in the transform domain, Wiener filter is used to reduce quantization noise for DCT coded images in DCT domain. Instead of deriving the spectrum of the transform coefficient, a DPCM loop is used to whiten the quantized DCT coefficients. The DPCM loop predicts the mean for each coefficient. By subtracting the mean, the quantized DCT coefficient is converted into the sum of prediction error and quantization noise. After the DPCM loop, the prediction error can be assumed uncorrelated to make the design of the subsequent Wiener filter easy. The Wiener filter is applied to remove the quantization noise to restore the prediction error. The original coefficient is reconstructed by adding the DPCM predicted mean with the restored prediction error. To increase the prediction accuracy, the decimated DCT coefficients in each subband are interpolated from the overlapped blocks.

A novel binary line-pattern algorithm for embedded fingerprint authentication system is introduced in this paper. In this algorithm, each line-pattern is a one-dimension binary matrix that describes the alternation pattern of ridge and valley in fingerprint image. Two parallel lines or two cross lines in a certain scope make up related line-pattern pair. Several such line-pattern pairs at different parts of a fingerprint image can describe another intrinsic feature besides traditional minutiae feature. Experimental results showed this algorithm was not only efficient but also effective. Furthermore, a hybrid fingerprint match scheme is also introduced in this paper. It has the following features: (i) minutiae matching is firstly carried out to calculate the similarity score between the query fingerprint and the template fingerprint, and moreover, the translation and rotation parameters are obtained at the same time; (ii) line-pattern algorithm is immediately performed based on the parameters obtained after minutiae matching to get another similarity score; (iii) the final matching score is the combination of the minutiae matching score and the line-pattern matching score. Experiments were conducted on the FVC2002 database and our private database respectively. Both of the results were inspiring. In detail, at the same FAR value, the FRR of this hybrid match algorithm is to be 2-8% lower than only minutiae-based matching algorithm.

An all-optical switch based on a single photonic crystal defect with an air-bridge configuration and two-photon absorption was proposed, fabricated and characterized. In optical measurements, we obtained a sharp defect mode with a quality factor higher than 600 at 1.55 µm. More importantly, we observed its nonlinear response to the excitation of ultrashort pulses by utilizing two-photon absorption. Nonliner refractive index change of about -410-3 was achieved at a pumping power density of 3.6109 W/cm2.

Sampling is important for many applications in research areas such as graphics, vision, and image processing. In this paper, we present a novel stratified sampling algorithm (SSA) for the coiled tubing surface with a given probability density function. The algorithm is developed from the inverse function of the integration for the areas of the coiled tubing surface. We exploit a Hierarchical Allocation Strategy (HAS) to preserve sample stratification when generating any desirable sample numbers. This permits us to reduce variances when applying our algorithm to Monte Carlo Direct Lighting for realistic image generation. We accelerate the sampling process using a segmentation technique in the integration domain. Our algorithm thus runs 324 orders of magnitude faster when using faster SSA algorithm where the order of the magnitude is proportional to the sample numbers. Finally, we employ a parabolic interpolation technique to decrease the average errors occurred for using the segmentation technique. This permits us to produce nearly constant average errors, independent of the sample numbers. The proposed algorithm is novel, efficient in computing and feasible for realistic image generation using Monte Carlo method.

In this paper, we propose a new technique to generate virtual views of three-dimensional (3D) models. The technique is implemented into our facial pose transformation system, which takes only one frontal image and transforms it into virtual views. In our system, to overcome the complex of 3D geometric model, Image Based Rendering based algorithm and mesh-based methods are applied. We also introduce our new Invertible Meshwarp Algorithm, which is developed based on Two-pass Meshwarp Algorithm. Firstly, in the system, for any given person, we take a frontal face image to compose a frontal mesh for it. The standard mesh set of a specific person is created for several face sides; front, half left, half right, left and right side. The other meshes are then automatically generated based on the standard mesh set and the frontal mesh. Continually, we use Invertible Meshwarp Algorithm, which improvably solves the overlap or inversion of neighbor vertices of those created meshes. This step will finalize the generation of different views or the virtual looks of the frontal face image. We then evaluate our transformation system performance by comparing the normalized distance between several feature points in the real and transformed face images. The system is built based on C/C++ language and our result shows that the average error in the feature location is about 7% of the distance from the center of both eyes to the center of a mouth between the actual and transformed face images.

This paper addresses issues regarding to the development of teleconferencing support collaboration focusing on the realistic sensation domain. It argues that the gaze communications are the important mechanisms to enable visual channel and social presence in human-human communications. We propose a new aspect to establish multiple eye contacts and community awareness in multiparty videoconference (VC). The participants can aware of being recognized from any remote sites while they are talking with each other. Community awareness means the ability to aware of group communication in the videoconference. The participant can recognize of who is talking with whom and any communicative groups in a conference. An intelligent image arrangement through a unique position of camera is built and simulated. The systematic placement of images serves the gaze communications by utilizing the characteristic of gaze direction and image's position. The experimental results show that the proposed approach has the significant improvement in the interpersonal communication compared with the conventional VC system.

Support vector algorithms try to maximize the shortest distance between sample points and discrimination hyperplane. This paper suggests the total margin algorithms which consider the distance between all data points and the separating hyperplane. The method extends and modifies the existing algorithms. Experimental studies show that the total margin algorithms provide good performance comparing with the existing support vector algorithms.

In this paper, general definitions of collusion secure codes are shown. Previously defined codes such as frameproof code, secure frameproof code, identifiable parent property code, totally c-secure code, traceability code, and (c,g/s)-secure code are redefined under various marking assumptions which are suitable for most of the fingerprinting systems. Then, new relationships among the combined notions of codes and the marking assumptions are revealed. Some (non)existence results are also shown.

This paper describes an adaptive fingerprint-sensing scheme for a user authentication system with a fingerprint sensor LSI to obtain high-quality fingerprint images suitable for identification. The scheme is based on novel evaluation indexes of fingerprint-image quality and adjustable analog-to-digital (A/D) conversion. The scheme adjusts dynamically an A/D conversion range of the fingerprint sensor LSI while evaluating the image quality during real-time fingerprint-sensing operation. The evaluation indexes pertain to the contrast and the ridgelines of a fingerprint image. The A/D conversion range is adjusted by changing quantization resolution and offset. We developed a fingerprint sensor LSI and a user authentication system to evaluate the adaptive fingerprint-sensing scheme. The scheme obtained a fingerprint image suitable for identification and the system achieved an accurate identification rate with 0.36% of the false rejection rate (FRR) at 0.075% of the false acceptance rate (FAR). This confirms that the scheme is very effective in achieving accurate identification.

In this paper, we describe how to exploit a machine-readable dictionary (MRD) and domain-specific text corpus in supporting the construction of domain ontologies that specify taxonomic and non-taxonomic relationships among given domain concepts. In building taxonomic relationships (hierarchical structure) of domain concepts, some hierarchical structure can be extracted from a MRD with marked subtrees that may be modified by a domain expert, using matching result analysis and trimmed result analysis. In building non-taxonomic relationships (specification templates) of domain concepts, we construct concept specification templates that come from pairs of concepts extracted from text corpus, using WordSpace and an association rule algorithm. A domain expert modifies taxonomic and non-taxonomic relationships later. Through case studies with "the Contracts for the International Sales of Goods (CISG)" and "XML Common Business Library (xCBL)", we make sure that our system can work to support the process of constructing domain ontologies with a MRD and text corpus.

In this paper, we propose two fast codebook generation algorithms for entropy-constrained vector quantization. The first algorithm uses the angular constraint to reduce the search area and to accelerate the search process in the codebook design. It employs the projection angles of the vectors to a reference line. The second algorithm has feature of using a suitable hyperplane to partition the codebook and image data. These algorithms allow significant acceleration in codebook design process. Experimental results are presented on image block data. These results show that our new algorithms perform better than the previously known methods.