The situations where several population parameters need to be estimated simultaneously arise frequently in wide areas of applications, including reliability modeling, survival analysis and biological study. In this paper, we propose Bayesian methods of estimation of the ordered parameters of the two exponential populations, which incorporate the prior information about the simple order restriction, but sometimes breaks the order restriction. A simulation study shows that the proposed estimators are more efficient (in terms of mean square errors) than the isotonic regression of the maximum likelihood estimators with equal weights. An illustrative example is finally presented.

A novel DC-to-960 MHz impulse radio ultra-wideband (IR-UWB) transceiver based on threshold detection technique is developed. It features a digital pulse-shaping transmitter, a DC power-free pulse discriminator and an error-recovery phase-frequency detector. The developed transceiver in 90 nm CMOS achieves the lowest energy consumption of 2.2 pJ/bit transmitter and 1.9 pJ/bit receiver at 100 Mbps in the UWB transceivers.

A lexicon-driven segmentation-recognition scheme on Bangla handwritten city-name recognition is proposed for Indian postal automation. In the proposed scheme, at first, binarization of the input document is done and then to take care of slanted handwriting of different individuals a slant correction technique is performed. Next, due to the script characteristics of Bangla, a water reservoir concept is applied to pre-segment the slant corrected city-names into possible primitive components (characters or its parts). Pre-segmented components of a city-name are then merged into possible characters to get the best city-name using the lexicon information. In order to merge these primitive components into characters and to find optimum character segmentation, dynamic programming (DP) is applied using total likelihood of the characters of a city-name as an objective function. To compute the likelihood of a character, Modified Quadratic Discriminant Function (MQDF) is used. The features used in the MQDF are mainly based on the directional features of the contour points of the components. We tested our system on 84 different Bangla city-names and 94.08% accuracy was obtained from the proposed system.

Dimensionality reduction is one of the important preprocessing steps in practical pattern recognition. SEmi-supervised Local Fisher discriminant analysis (SELF)--which is a semi-supervised and local extension of Fisher discriminant analysis--was shown to work excellently in experiments. However, when data dimensionality is very high, a naive use of SELF is prohibitive due to high computational costs and large memory requirement. In this paper, we introduce computational tricks for making SELF applicable to large-scale problems.

This paper proposes a MIMO-OFDM precoder that can minimize a BER upper bound of the maximum likelihood detector (MLD) under a non-cooperative downlink multicell co-channel interference (CCI) environment. Since there is no cooperation among base stations (BSs), it is assumed that information on the interference can be estimated at a mobile station (MS) and then fed back to the desired BS for the precoder. The proposed scheme controls its precoding parameters under a transmit power constraint so as to minimize the BER upper bound, which is derived from the pairwise error probability (PEP) averaged with respect to CCI plus noise. Computer simulations demonstrate that the proposed precoder can effectively improve BER performance of cell edge users and is superior in terms of BER to the eigenmode and the minimum mean squared error (MMSE) precoded transmissions which aim to maximize the channel capacity and to minimize MSE, respectively.

We propose a learning and control model of the arm for a loading task in which an object is loaded onto one hand with the other hand, in the sagittal plane. Postural control during object interactions provides important points to motor control theories in terms of how humans handle dynamics changes and use the information of prediction and sensory feedback. For the learning and control model, we coupled a feedback-error-learning scheme with an Actor-Critic method used as a feedback controller. To overcome sensory delays, a feedforward dynamics model (FDM) was used in the sensory feedback path. We tested the proposed model in simulation using a two-joint arm with six muscles, each with time delays in muscle force generation. By applying the proposed model to the loading task, we showed that motor commands started increasing, before an object was loaded on, to stabilize arm posture. We also found that the FDM contributes to the stabilization by predicting how the hand changes based on contexts of the object and efferent signals. For comparison with other computational models, we present the simulation results of a minimum-variance model.

The use of cross-polarized antennas for multiple-input multiple-output (MIMO) systems is receiving attention as they are able to double the number of antenna for half antenna spacing needs. This paper presents the channel correlation property of the 3rd Generation Partner Project (3GPP)/3GPP2 spatial channel model (SCM) with the polarization propagation. The statistical average of the per path polarization correlation given random cross-polarization discrimination (XPD) with co-located ideal tilted dipole antennas is derived. The impact on the random behavior of the polarization correlation due to the slant offset angle, the per path angular spread (AS), and the random XPD is analyzed. The simulation results show that the variation of polarization correlation caused by the random XPD is maximized with a 58 slant offset angle under the assumptions of all predefined scenarios in SCM. The per path AS has minor impact on the statistics of the polarization correlations. The randomness of polarization correlation is negligible for an XPD with small standard deviation.

In this paper, a novel design method of critically sampled contourlet transform (CSCT) is proposed. The original CT which consists of Laplacian pyramid and directional filter bank provides efficient frequency plane partition for image representation. However its overcompleteness is not suitable for some applications such as image coding, its critical sampling version has been studied recently. Although several types of the CSCT have been proposed, they have problems on their realization or unnatural frequency plane partition which is different from the original CT. In contrast to the way in conventional design methods based on a "top-down" approach, the proposed method is based on a "bottom-up" one. That is, the proposed CSCT decomposes the frequency plane into small directional subbands, and then synthesizes them up to a target frequency plane partition, while the conventional ones decompose into it directly. By this way, the proposed CSCT can design an efficient frequency division which is the same as the original CT for image representation can be realized. In this paper, its effectiveness is verified by non-linear approximation simulation.

This work elucidates the evolution of three generations of the laboratory information system in the National Taiwan University Hospital, which were respectively implemented in an IBM Series/1 minicomputer, a client/server and a plug-and-play HL7 interface engine environment respectively. The experience of using the HL7 healthcare information exchange in the hospital information system, laboratory information system, and automatic medical instruments over the past two decades are illustrated and discussed. The latest design challenge in developing intelligent laboratory information services is to organize effectively distributed and heterogeneous medical instruments through the message gateways. Such experiences had spread to some governmental information systems for different purposes in Taiwan; besides, the healthcare information exchange standard, software reuse mechanism, and application service provider adopted in developing the plug-and-play laboratory information system are also illustrated.

A novel bimodal method for face recognition under low-level lighting conditions is proposed. It fuses an enhanced gray level image and an illumination-invariant geometric image at the feature-level. To further improve the recognition performance under large variations in attributions such as poses and expressions, discriminant features are extracted from source images using the wavelet transform-based method. Features are adaptively fused to reconstruct the final face sample. Then FLD is used to generate a supervised discriminant space for the classification task. Experiments show that the bimodal method outperforms conventional methods under complex conditions.

In this paper, we propose designing method for separable-denominator two-dimensional Infinite Impulse Response (IIR) filters (separable 2D IIR filters) by Successive Projection (SP) methods using the stability criteria based on the system matrix. It is generally known that separable 2D IIR filters are stable if and only if each of the denominators is stable. Therefore, the stability criteria of 1D IIR filters can be used for separable 2D IIR filters. The stability criteria based on the system matrix are a necessary and sufficient condition to guarantee stability in 1D IIR filters. Therefore, separable 2D IIR filters obtained by the proposed design method have a smaller error ripple than those obtained by the conventional design method using the stability criterion of Rouche's theorem.

With the advent of the deep submicron age, circuit performance is strongly impacted by process variations and the influence on the circuit delay to the power-supply voltage increases more and more due to CMOS feature size shrinkage. Power grid optimization which considers the timing error risk caused by the variations and IR drop becomes very important for stable and hi-speed operation of system-on-chip. Conventionally, a lot of power grid optimization algorithms have been proposed, and most of them use IR drop as their object functions. However, the IR drop is an indirect metric and we suspect that it is vague metric for the real goal of LSI design. In this paper, first, we propose an approach which uses the "timing error risk caused by IR drop" as a direct objective function. Second, the critical path map is introduced to express the existence of critical paths distributed in the entire chip. The timing error risk is decreased by using the critical path map and the new objective function. Some experimental results show the effectiveness.

Block-based SSTA analyzes the timing variation of a chip caused by process variations effectively. However, block-based SSTA cannot identify critical nodes, nodes that highly influence the timing yield of a chip, used as the effective guidance of timing yield optimization. In this paper, we propose a new timing criticality to identify those nodes, referred to as the timing yield criticality (TYC). The proposed TYC is defined as the change in the timing yield, which is induced by the change in the mean arrival time at a node. For efficiency, we estimate the TYC through linear approximation instead of propagating the changed arrival time at a node to its fanouts. In experiments using the ISCAS 85 benchmark circuits, the proposed method estimated TYCs with the expense of 9.8% of the runtime for the exact computation. The proposed method identified the node that gives the greatest effect on the timing yield in all benchmark circuits, except C6288, while existing methods did not identify that for any circuit. In addition, the proposed method identified 98.4% of the critical nodes in the top 1% in the effect on the timing yield, while existing methods identified only about 10%.

This paper introduces a theory for fast optimization of the circuit topology and parameters in sinusoidal oscillators. The theory starts from a system model composed of standard active and passive elements. We then include even the output load in the circuit, so that there is no longer any interaction with the outside of the system through the port. This model is thus called no-input-no-output (NINO) oscillator. The circuit is cut at an arbitrary branch, and is characterized in terms of the scalar impedance from the cut point. This is called active impedance because it is a function of not only the stimulating frequency but also the active device gain. The oscillation frequency and necessary device gain are estimated by solving impedance-domain Barkhausen equilibrium equations. This estimation works for the adjustment of circuit elements to meet the specified oscillation frequency. The estimation of necessary device gain enables us to maximize the oscillation amplitude, thanks to the inherent negative-slope nonlinearity of active devices. The active impedance is also used to derive the oscillation Q (quality) factor, which serves as a key criterion for sideband noise minimization i.e. frequency spectrum purification. As an alternative measure to active impedance, we also introduce branch admittance matrix determinant. This has the same numerical effect as the scalar impedance but can be used to formulate oscillator characteristics in a more elegant fashion, and provides a lucent picture of the physical behavior of each element in the circuit. Based on the proposed theory, we provide the tabled formulas of oscillation frequency, necessary device gain, active Q factor for a variety of typical Colpitts, Hartley, and cross-coupled twin-FET (field-effect transistor) oscillators.

In this paper, we propose a new algorithm to detect the presence of narrow band interference signals on the band of an Ultra Wide-Band (UWB) system when the UWB spectrum overlaps the bands of other narrow band wireless services. In our proposed algorithm for an UWB Multi-Band Orthogonal Frequency Division Multiplexing (MB-OFDM) system, an appropriate model is selected from the assumed interference models based on the Akaike Information Criterion (AIC) which is an explicit theoretic criterion and a measure of fit of the model. The proposed algorithm does not need a priori information on the interference signals except that we can reduce a computational complexity to implement the algorithm if we have knowledge of the bands of the interference signals. Furthermore, we introduce the Expectation Maximization (EM) algorithm to our algorithm in order to estimate the transmitted signals and the interference signals simultaneously. The proposed algorithm may not require the pilot symbols in the assumed UWB system to detect the presence of other systems. By computer simulations, we show that the proposed algorithm validly detects the presence of interference signals on the UWB band.

In this paper we mainly focus on the effect of a ferromagnetic material on the critical current of Bi-2223 tape. The magnetic field distributions of tapes with several different layouts of a ferromagnetic material are investigated by calculation and the corresponding critical current is tested experimentally. The analysis indicates that the critical current of the tape can be improved effectively by laying the ferromagnetic material perpendicularly next to the tape edge. Furthermore, various other ferromagnetic parameters are also important for reducing the magnetic field induced by the current flowing through the tape.

We propose a novel efficient three-dimensional geometrical consistency criterion for detection of a set of facial feature points. Many face recognition methods employing a single image require localization of particular facial feature points and their performance is highly dependent on localization accuracy in detecting these feature points. The proposed method is able to calculate alignment error of a point set rapidly because calculation is not iterative. Also the method does not depend on the type of point detection method used and no learning is needed. Independently detected point sets are evaluated through matching to a three-dimensional generic face model. Correspondence error is defined by the distance between the feature points defined in the model and those detected. The proposed criterion is evaluated through experiment using various facial feature point sets on face images.

This paper proposes a new minimum BER (MBER) criterion precoding method that is robust to imperfect channel state information (CSI) for MIMO-OFDM mobile communications. The proposed MBER precoding aims to minimize BER of the maximum likelihood detection (MLD), on the condition that the transmitter can obtain only imperfect CSI owing to channel estimation and quantization errors of the feedback CSI. The proposed scheme controls its precoding parameters under a transmit power constraint by minimizing an upper bound of BER which is derived from the pairwise error probability and averaged with respect to the CSI error. In contrast with a conventional power allocation MBER precoding method that is also robust to the CSI error, the proposed scheme does not make any assumption on the precoding parameters so as to reduce complexity. Thus, it is expected to outperform the conventional scheme at the cost of higher complexity. Computer simulations demonstrate that the proposed precoding method outperforms a conventional nonrobust MBER precoder and the conventional robust power allocation MBER precoding method when the amount of the CSI error is not considerable.

The multistage Wiener filter (MWF) outperforms the full rank Wiener filter in low sample support environments. However, the MWF adaptive process should be stopped at an optimum stage to get the best performance. There are two methods to stop the MWF adaptive process. One method is to calculate until the final full-stage, and the second method is to terminate at r-stage less than full-stage. The computational load is smaller in the latter method, however, a performance degradation is caused by an additional or subtractive stage calculation. Therefore, it is very important for the r-stage calculation to stop an adaptive process at the optimum stage. In this paper, we propose a simple method based on a cross-correlation coefficient to stop the MWF adaptive process. Because its coefficient is calculated by the MWF forward recursion, the optimum stage is determined automatically and additional calculations are avoided. The performance was evaluated by simulation examples, demonstrating the superiority of the proposed method.

The management of subscriptions and events is an important task in the content-based publish/subscribe system. A good management mechanism can not only produce lower matching costs to speed up the delivery of matched events to the interested subscribers but can also induce good load balancing for subscription storage. In this paper, we consider the construction of this kind of system over a peer-to-peer overlay network and propose two message-to-node mapping schemes for system management. We both analyze and simulate the performance of the proposed schemes. The simulation results show the superiority of our schemes over existing ones.