Based on the concept of sliding mode control, this paper investigates the upper bound covariance assignment with H∞ norm and variance constrained problem for bilinear stochastic systems. We find that the invariance property of sliding mode control ensures nullity of the matched bilinear term in the system on the sliding mode. Moreover, using the upper bound covariance control approach and combining the sliding phase and hitting phase of the system design, we will derive the control feedback gain matrix G, which is essential to the controller u(t) design, to achieve the performance requirements. Finally, a numerical example is given to illustrate the control effect of the proposed method.

Fully automatic reconstruction of 3D models from images is well-known to be a difficult problem. For many applications, a limited amount of human assistance is allowed and can greatly reduce the complexity of the 3D reconstruction problem. In this paper, we present an easy-to-use method for aligning a parameterized 3D CAD model to images taken from different views. The shape parameters of the 3D CAD model can be recovered accurately. Our work is composed of two parts. In the first part, we developed an interactive tool which allows the user to associate the features in the CAD model to the features in the 2D images. This interactive tool is designed to achieve efficiency and accuracy. In the second part, 3D information extracted from different stereo views are integrated together by using an optimization technique to obtain accurate shape parameters. Some experimental results have been shown to demonstrate the accuracy and usefulness of the recovered CAD model.

The existing research on Amdahl's law is limited to multi/many-core processors, and cannot be applied to the important parallel processing architecture of coarse-grained reconfigurable arrays. This paper studies the relation between the multi-level parallelism of block cipher algorithms and the architectural characteristics of coarse-grain reconfigurable arrays. We introduce the key variables that affect the performance of reconfigurable arrays, such as communication overhead and configuration overhead, into Amdahl's law. On this basis, we propose a performance model for coarse-grain reconfigurable block cipher array (CGRBA) based on the extended Amdahl's law. In addition, this paper establishes the optimal integer nonlinear programming model, which can provide a parameter reference for the architecture design of CGRBA. The experimental results show that: (1) reducing the communication workload ratio and increasing the number of configuration pages reasonably can significantly improve the algorithm performance on CGRBA; (2) the communication workload ratio has a linear effect on the execution time.

Throughput capacity is of great importance for the design and performance optimization of mobile ad hoc networks (MANETs). We study the exact per node throughput capacity of MANETs under a general 2HR-(g, x, f) routing scheme which combines erasure coding and packet replication techniques. Under this scheme, a source node first encodes a group of g packets into x (x ≥ g) distinct coded packets, and then replicates each of the coded packets to at most f relay nodes which help to forward them to the destination node. All original packets can be recovered once the destination node receives any g distinct coded packets of the group. To study the throughput capacity, we first construct two absorbing Markov chain models to depict the complicated packet delivery process under the routing scheme. Based on these Markov models, an analytical expression of the throughput capacity is derived. Extensive simulation and numerical results are provided to verify the accuracy of theoretical results on throughput capacity and to illustrate how system parameters will affect the throughput capacity in MANETs. Interestingly, we find that the replication of coded packets can improve the throughput capacity when the parameter x is relatively small.

This paper presents a 28-GHz-band highly linear stacked-FET power amplifier (PA) IC. A 4-stacked-FET structure is employed for high output power considering the low breakdown voltage of scaled MOSFET transistors. A novel adaptive bias circuit is proposed to dynamically control the gate-to-source bias voltage for amplification MOSFETs. The novel adaptive bias allows the PA to attain high linearity with high back-off efficiency. In addition, the third-order intermodulation distortion (IM3) is improved by a multi-cascode structure. The PA IC is designed, fabricated and fully tested in 56-nm SOI CMOS technology. At a supply voltage of 4 V, the PA IC has achieved an output power of 20.0 dBm with a PAE as high as 38.1% at the 1-dB gain compression point (P1dB). Moreover, PAEs at 3-dB and 6-dB back-off from P1dB are 36.2% and 28.7%, respectively. The PA IC exhibits an output third-order intercept point (OIP3) of 25.0 dBm.

Address configuration is a key problem in data center networks. The core issue of automatic address configuration is assigning logical addresses to the physical network according to a blueprint, namely logical-to-device ID mapping, which can be formulated as a graph isomorphic problem and is hard. Recently years, some work has been proposed for this problem, such as DAC and ETAC. DAC adopts a sub-graph isomorphic algorithm. By leveraging the structure characteristic of data center network, DAC can finish the mapping process quickly when there is no malfunction. However, in the presence of any malfunctions, DAC need human effort to correct these malfunctions and thus is time-consuming. ETAC improves on DAC and can finish mapping even in the presence of malfunctions. However, ETAC also suffers from some robustness and efficiency problems. In this paper, we present GA-MAP, a data center networks address mapping algorithm based on genetic algorithm. By intelligently leveraging the structure characteristic of data center networks and the global search characteristic of genetic algorithm, GA-MAP can solve the address mapping problem quickly. Moreover, GA-MAP can even finish address mapping when physical network involved in malfunctions, making it more robust than ETAC. We evaluate GA-MAP via extensive simulation in several of aspects, including computation time, error-tolerance, convergence characteristic and the influence of population size. The simulation results demonstrate that GA-MAP is effective for data center addresses mapping.

This paper presents new approaches for the estimation of range between the preceding vehicle and the experimental vehicle, estimation of vehicle size and its projective size, and dynamic camera calibration. First, our proposed approaches adopt a camera model to transform coordinates from the ground plane onto the image plane to estimate the relative position between the detected vehicle and the camera. Then, to estimate the actual and projective size of the preceding vehicle, we propose a new estimation method. This method can estimate the range from a preceding vehicle to the camera based on contact points between its tires and the ground and then estimate the actual size of the vehicle according to the positions of its vertexes in the image. Because the projective size of a vehicle varies with respect to its distance to the camera, we also present a simple and rapid method of estimating a vehicle's projective height, which allows a reduction in computational time for size estimation in real-time systems. Errors caused by the application of different camera parameters are also estimated and analyzed in this study. The estimation results are used to determine suitable parameters during camera installation to suppress estimation errors. Finally, to guarantee robustness of the detection system, a new efficient approach to dynamic calibration is presented to obtain accurate camera parameters, even when they are changed by camera vibration owing to on-road driving. Experimental results demonstrate that our approaches can provide accurate and robust estimation results of range and size of target vehicles.

This study presents several optimization approaches for the MPEG-2/4 Audio Advanced Coding (AAC) Low Complexity (LC) encoding and decoding processes. Considering the power consumption and the peripherals required for consumer electronics, this study adopts the TI OMAP5912 platform for portable devices. An important optimization issue for implementing AAC codec on embedded and mobile devices is to reduce computational complexity and memory consumption. Due to power saving issues, most embedded and mobile systems can only provide very limited computational power and memory resources for the coding process. As a result, modifying and simplifying only one or two blocks is insufficient for optimizing the AAC encoder and enabling it to work well on embedded systems. It is therefore necessary to enhance the computational efficiency of other important modules in the encoding algorithm. This study focuses on optimizing the Temporal Noise Shaping (TNS), Mid/Side (M/S) Stereo, Modified Discrete Cosine Transform (MDCT) and Inverse Quantization (IQ) modules in the encoder and decoder. Furthermore, we also propose an efficient memory reduction approach that provides a satisfactory balance between the reduction of memory usage and the expansion of the encoded files. In the proposed design, both the AAC encoder and decoder are built with fixed-point arithmetic operations and implemented on a DSP processor combined with an ARM-core for peripheral controlling. Experimental results demonstrate that the proposed AAC codec is computationally effective, has low memory consumption, and is suitable for low-cost embedded and mobile applications.

In this paper, a new compensation scheme and a corresponding pass element structure for a CMOS low-dropout regulator (LDO) are presented. The proposed approach effectively alleviates the strict stability constraint on the ESR of the output capacitor. Stability of a CMOS LDO with the conventional compensation requires the effective series resistance (ESR) of the output capacitor in a tunnel-like region. With the proposed design approach, an LDO can be stable using an output capacitor without ESR. A 2.5 V/150 mA LDO has been implemented using a 0.5-µm 1P2M CMOS process. The experimental results illustrate that the proposed LDO is stable with an output capacitor of 0.33 µF and no ESR.

Changes in recent business and scientific environment have created a necessity for more efficient and effective workflow infrastructure. With increasing emphasis on Service-oriented architecture, service composition becomes a hot topic in workflow research. This paper proposes a novel approach of using ECA rules to realize the workflow modeling and implementation for service composition. First of all, the concept and formalization of ECA rule-based workflow is presented. Special activities and data structures are customized for the purpose of service composition. Second, an automatic event composition and decomposition algorithm is developed to ensure the correctness and validness of service composition at design time. Finally, the proposed ECA rule-based approach for service composition is illustrated through the implementation of a workflow prototype system.

In our previous project, an XML-based authoring tool was provided for teachers to script multimedia teaching material with animated agents, and a stand-alone learning system was designed for students to display the material and interact with animated agents. We also provided evidence that the authoring tool and learning system in computer-assisted learning systems successfully enhances learning performance. The aim of this study is to continue the previous project, to develop a Web-based multimedia learning system that presents materials and an animated agent on a Web browser. The Web-based multimedia learning system can provide an opportunity for students to engage in independent learning or review of school course work. In order to demonstrate the efficiency of this learning system, it was applied to one elementary school. An experimental material, `Road Traffic Safety', was presented in two learning systems: a Web-based PowerPoint learning system and a Web-based multimedia learning system. The experiment was carried out in two classes that had a total of thirty-one 3rd-grade students. The results suggest that using our authoring tool in a Web-based learning system can improve learning, and in particular, enhance learners' problem-solving ability. Students with higher achievement on the post-test showed better comprehension in problem-solving questions. Furthermore, the feedback from the questionnaire surveys show students' learning interest can be fostered when an animated agent is integrated into multimedia teaching materials, and that students prefer to adopt the Web-based multimedia learning system for independent learning after school.

In this study, a precoding scheme based on QR-decomposition is proposed for mitigating the inter-carrier-interference (ICI) in orthogonal-frequency-division-multiplexing (OFDM) systems. The proposed approach first subjects the ICI matrix to QR decomposition so that the ICI effect is transformed into its spectrally causal equivalent. With this causality, the precoding can then be conducted based on the resultant spectrally causal matrix. In addition, by using the stationary property of the ICI factors, in conjunction with zero padding, we implement the QR-based precoding in a segmentation manner which can significantly alleviate the computational complexity imposed by QR decomposition while eliminating ICI within each segment. This study also analyzes the residue interference power induced by the segmentation. The residue interference power is then accordingly used to determine the order of zero padding. Computer simulations support the validity of the proposed approach.

In this study, we have proposed an efficient automatic multilevel thresholding method for image segmentation. An effective criterion for measuring the separability of the homogenous objects in the image, based on discriminant analysis, has been introduced to automatically determine the number of thresholding levels to be performed. Then, by applying this discriminant criterion, the object regions with homogeneous illuminations in the image can be recursively and automatically thresholded into separate segmented images. The proposed method is fast and effective in analyzing and thresholding the histogram of the image. In order to conduct an equitable comparative performance evaluation of the proposed method with other thresholding methods, a combinatorial scheme is also introduced to properly reduce the computational complexity of performing multilevel thresholding. The experimental results demonstrated that the proposed method is feasible and computationally efficient in automatic multilevel thresholding for image segmentation.

Malware has become a growing threat as malware writers have learned that signature-based detectors can be easily evaded by packing the malware. Packing is a major challenge to malware analysis. The generic unpacking approach is the major solution to the threat of packed malware, and it is based on the intrinsic nature of the execution of packed executables. That is, the original code should be extracted in memory and get executed at run-time. The existing generic unpacking approaches need a simulated environment to monitor the executing of the packed executables. Unfortunately, the simulated environment is easily detected by the environment-sensitive packers. It makes the existing generic unpacking approaches easily evaded by the packer. In this paper, we propose a novel unpacking approach, BareUnpack, to monitor the execution of the packed executables on the bare-metal operating system, and then extracts the hidden code of the executable. BareUnpack does not need any simulated environment (debugger, emulator or VM), and it works on the bare-metal operating system directly. Our experimental results show that BareUnpack can resist the environment-sensitive packers, and improve the unpacking effectiveness, which outperforms other existing unpacking approaches.

A 0.18 µm 1.5 V/50 mA stability-enhanced low dropout regulator (LDO) is presented. A multi-path error amplifier and a split pass device structure are utilized for pole-zero pair compensation. The proposed LDO can be stable without a load capacitor and also stable with different combinations of load capacitors and equivalent series resistance.

Efficient parallel algorithms for several problems on proper circular arc graphs are presented in this paper. These problems include finding a maximum matching, partitioning into a minimum number of induced subgraphs each of which has a Hamiltonian cycle (path), partitioning into induced subgraphs each of which has a Hamiltonian cycle (path) with at least k vertices for a given k, and adding a minimum number of edges to make the graph contain a Hamiltonian cycle (path). It is shown here that the above problems can all be solved in logarithmic time with a linear number of EREW PRAM processors, or in constant time with a linear number of BSR processors. A more important part of this work is perhaps the extension of basic BSR to allow simultaneous multiple BROADCAST instructions.

This paper describes the application of two attractive categories of topic modeling techniques to the problem of spoken document retrieval (SDR), viz. document topic model (DTM) and word topic model (WTM). Apart from using the conventional unsupervised training strategy, we explore a supervised training strategy for estimating these topic models, imagining a scenario that user query logs along with click-through information of relevant documents can be utilized to build an SDR system. This attempt has the potential to associate relevant documents with queries even if they do not share any of the query words, thereby improving on retrieval quality over the baseline system. Likewise, we also study a novel use of pseudo-supervised training to associate relevant documents with queries through a pseudo-feedback procedure. Moreover, in order to lessen SDR performance degradation caused by imperfect speech recognition, we investigate leveraging different levels of index features for topic modeling, including words, syllable-level units, and their combination. We provide a series of experiments conducted on the TDT (TDT-2 and TDT-3) Chinese SDR collections. The empirical results show that the methods deduced from our proposed modeling framework are very effective when compared with a few existing retrieval approaches.

On the basis of the relation between the multichannel prediction model and the 2-D prediction model, the convergence properties of prediction error covariance, prediction coefficients and corresponding 2-D polynomials of the latter model are derived from the known convergence properties of those of the former model. Furthermore, the formulas of the convergence order of the 2-D prediction model are obtained by using the knowledge of the convergence order of 2-D correlation sequence {γi,j}.

In this paper, a novel direct torque control (DTC) for a dual-three-phase induction motor(DTPIM) is presented. A rule-based optimum selection scheme for the space voltage vector is proposed. A fast torque response with low ripples of torque and flux is achieved. To further reduce the ripple of torque and stator flux, a fuzzy logic estimator for the duty ratio is developed, so that the average effective voltage on the motor can be flexibly changed within the sampling period. The simulation results clearly demonstrate precise control of the stator flux and torque with the new DTC method and a better steady state performance with the proposed fuzzy logic technique.

We report some leading research on superconducting devices in Taiwan. Research includes thin films, Josephson junctions, junction arrays and resonators etc. In device physics characteristics of Josephson junctions, junction array, and SQUIDs are reported. Applications of SQUIDs include: (1) studies of brain activities (magnetoencenphalogram) using multichannel low Tc SQUIDs system; (2) detection of weak magnetic fields (magnetocardiogragh, etc. ) using high-Tc SQUIDs; (3) nondestructive evaluation (NDE) of deep flaws using high-Tc SQUIDs. Research projects in the future in our group are briefly reported.