We propose a speaker adaptation method based on the probabilistic principal component analysis (PPCA) of acoustic models. We define a training matrix which is represented in a two-way array and decompose the training models by PPCA to construct bases. In the two-way array representation, each training model is represented as a matrix and the columns of each training matrix are treated as training vectors. We formulate the adaptation equation in the maximum a posteriori (MAP) framework using the bases and the prior.

The volumetric representations of deformable objects suffer from high memory and computational costs. In this work we analyze an approach of constructing low-resolution mass spring models (MSMs) on the basis of a high-resolution reference MSM. Preserving the physical properties of the modeled objects is emphasized such that their motion is consistent and independent of the spring network resolution. We varied the node merging algorithm and analyzed how various aspects of the simplification process affected the properties of the model and how these properties translated into visual behavior in a simulation.

The rendering mechanism plays an indispensable role in browser-based Web application. It generates active webpages dynamically and provides human-readable layout through template engines, which are used as a standard programming model to separate the business logic and data computations from the webpage presentation. The client-side rendering mechanism, owing to the advances of rich application technologies, has been widely adopted. The adoption of client side rendering brings not only various merits but also new problems. In this paper, we propose and construct “pagelet”, a segment-based template engine for developing flexible and extensible Web applications. By presenting principles, practice and usage experience of pagelet, we conduct a comprehensive analysis of possible advantages and disadvantages brought by client-side rendering mechanism from the viewpoints of both developers and end-users.

Light source estimation and virtual lighting must be believable in terms of appearance and correctness in augmented reality scenes. As a result of illumination complexity in an outdoor scene, realistic lighting for augmented reality is still a challenging problem. In this paper, we propose a framework based on an estimation of environmental lighting from well-defined objects, specifically human faces. The method is tuned for outdoor use, and the algorithm is further enhanced to illuminate virtual objects exposed to direct sunlight. Our model can be integrated into existing mobile augmented reality frameworks to enhance visual perception.

Digital map systems can be categorized, based on the support they provide, into map navigation systems and map touring systems. Map navigation systems put more focus on helping travelers finding routes or directions instantly. By contrast, map touring systems such as Google Maps running on desktop computers are built to support users in developing their routes and survey knowledge before they go for travel. In this paper, traveler conceptual models are proposed as an interaction paradigm to enhance user immersion and interaction experience on map touring systems. A map touring system, MapXplorer, is also introduced as a proof of concept with its system design and implementation explained in detail. Twenty participants were invited to join the user study that investigates users' performance and preferences on navigation and exploration tasks. The results of experiments show that the proposed system surpasses traditional map touring systems on both navigation and exploration tasks for about 50 percent on average, and provides better user experience.

Wireless patient monitoring is an active research area with the goal of ubiquitous health care services. This study presents a novel means of exploiting the distributed source coding (DSC) in low-complexity compression of ECG signals. We first convert the ECG data compression to an equivalent channel coding problem and exploit a linear channel code for the DSC construction. Performance is further enhanced by the use of a correlation channel that more precisely characterizes the statistical dependencies of ECG signals. Also proposed is a modified BCJR algorithm which performs symbol decoding of binary convolutional codes to better exploit the source's a priori information. Finally, a complete setup system for online ambulatory ECG monitoring via mobile cellular networks is presented. Experiments on the MIT-BIH arrhythmia database and real-time acquired ECG signals demonstrate that the proposed system outperforms other schemes in terms of encoder complexity and coding efficiency.

Recently, we proposed a weak-form discretization scheme to derive second-order difference equations from the governing equation of the scattering problem. In this paper, under the scope of the proposed scheme, numerical expressions for the waveguide boundary conditions are derived as perfectly absorbing conditions for input and output ports. The waveguide boundary conditions play an important role in extracting the quasi-localized wave as an eigenstate with a complex eigenvalue. The wave-number dependence of the resonance curve in Fano resonance is reproduced by using a semi-analytic model that is developed on the basis of the phase change relevant to the S-matrix. The reproduction confirms that the eigenstate with a complex eigenvalue does cause the observed Fano resonance.

The increasing demand of indoor location based service (LBS) has promoted the development of localization techniques. As an important alternative, fingerprinting localization technique can achieve higher localization accuracy than traditional trilateration and triangulation algorithms. However, it is computational expensive to construct the fingerprint database in the offline phase, which limits its applications. In this paper, we propose an efficient indoor positioning system that uses a new empirical propagation model, called regional propagation model (RPM), which is based on the cluster based propagation model theory. The system first collects the sparse fingerprints at some certain reference points (RPs) in the whole testing scenario. Then affinity propagation clustering algorithm operates on the sparse fingerprints to automatically divide the whole scenario into several clusters or sub-regions. The parameters of RPM are obtained in the next step and are further used to recover the entire fingerprint database. Finally, the location estimation is obtained through the weighted k-nearest neighbor algorithm (WkNN) in the online localization phase. We also theoretically analyze the localization accuracy of the proposed algorithm. The numerical results demonstrate that the proposed propagation model can predict the received signal strength (RSS) values more accurately than other models. Furthermore, experiments also show that the proposed positioning system achieves higher localization accuracy than other existing systems while cutting workload of fingerprint calibration by more than 50% in the offline phase.

We propose a novel IDDQ outlier screening flow through a two-phase approach: a clustering-based filtering and an estimation-based current-threshold determination. In the proposed flow, a clustering technique first filters out chips that have high IDDQ current. Then, in the current-threshold determination phase, device-parameters of the unfiltered chips are estimated based on measured IDDQ currents through Bayesian inference. The estimated device-parameters will further be used to determine a statistical leakage current distribution for each test pattern and to calculate a and suitable current-threshold. Numerical experiments using a virtual wafer show that our proposed technique is 14 times more accurate than the neighbor nearest residual (NNR) method and can achieve 80% of the test escape in the case of small leakage faults whose ratios of leakage fault sizes to the nominal IDDQ current are above 40%.

Virtual memory systems page out a cluster of contiguous modified pages in virtual memory to a swap disk at one disk I/O but cannot find large clusters in applications mainly changing non-contiguous pages. Our proposal stores small clusters at one disk I/O. This decreases disk writes for paging out small clusters, thus improving page-out performance.

We are developing an optical layer-2 switch network that uses both wavelength-division multiplexing and time-division multiplexing technologies for efficient traffic aggregation in metro networks. For efficient traffic aggregation, path bandwidth control is key because it strongly affects bandwidth utilization efficiency. We propose a fast time-slot allocation method that uses hierarchical calculation, which divides the network-wide bandwidth-allocation problem into small-scale local bandwidth-allocation problems and solves them independently. This method has a much shorter computation complexity and enables dynamic path bandwidth control in large-scale networks. Our network will be able to efficiently accommodate dynamic traffic with limited resources by using the proposed method, leading to cost-effective metro networks.

In this invited paper, software defined network (SDN)-based approaches for future cost-effective optical mobile backhaul (MBH) networks are discussed, focusing on key principles, throughput optimization and dynamic service provisioning as its use cases. We propose a novel physical-layer aware throughput optimization algorithm that confirms > 100Mb/s end-to-end per-cell throughputs with ≥2.5Gb/s optical links deployed at legacy cell sites. We also demonstrate the first optical line terminal (OLT)-side optical Nyquist filtering of legacy 10G on-off-keying (OOK) signals, enabling dynamic >10Gb/s Orthogonal Frequency Domain Multiple Access (OFDMA) λ-overlays for MBH over passive optical network (PON) with 40-km transmission distances and 1:128 splitting ratios, without any ONU-side equipment upgrades. The software defined flexible optical access network architecture described in this paper is thus highly promising for future MBH networks.

Electromagnetic scattering problems of canonical 2D structures can be analyzed with a high degree of accuracy by using the point matching method with mode expansion. In this paper, we will extend our previous method to 3D electromagnetic scattering problems and investigate the radar cross section of spherical shells and the computational accuracy.

Location fingerprinting utilizes periodic beacons transmitted by Wireless Local Area Network (WLAN) Access Points (APs) to provide localization in indoor environments. Currently no method is able to quantify the effectiveness of localization information provided by individual APs. Such a metric would enable the optimal placement of new APs as well as eliminating redundant APs so as to reduce the resources consumed by indoor localization software in client devices. This paper proposes LocationInfo, a metric that utilizes walk test data for quantifying the localization efficacy of APs. The performance of LocationInfo is evaluated using two experimental settings. First, it is used for identifying the optimal location for new APs. Second, it is used for filtering out excess APs in a crowded WLAN environment. In both experiments, LocationInfo outperforms existing metrics.

Acoustic feedback is a major complaint of hearing aid users. Adaptive filters are a common method for suppressing acoustic feedback in digital hearing aids. In this letter, we propose a new variable step-size algorithm for normalized least mean square and an affine projection algorithm to combine with a variable step-size affine projection algorithm and global speech absence probability in an adaptive filter. The computer simulation used to test the proposed algorithm results in a lower misalignment error than the comparison algorithm at a similar convergence rate. Therefore, the proposed algorithm suggests an effective solution for the feedback suppression system of digital hearing aids.

This paper proposes a new spectrum sharing scheme which uses one-sided collaboration. In the proposed system, the transmitter of the secondary system relays the primary signal and overlays its own data on the retransmitted primary signal. The results of the theoretical analysis show that the proposed scheme with regenerative relay allows the secondary system to communicate at the same speed as the primary system that disregards the presence of the secondary system.

Most images obtained with imaging sensors contain Bayer patterns and suffer from blurring caused by the lens. In order to convert a blurred Bayer-patterned image into a viewable image, demosaicing and deblurring are needed. These concepts have been major research areas in digital image processing for several decades. Despite their importance, their performance and efficiency are not satisfactory when considered independently. In this paper, we propose a joint deblurring and demosaicing method in which edge direction and edge strength are estimated in the Bayer domain and then edge adaptive deblurring and edge-oriented interpolation are performed simultaneously from the estimated edge information. Experimental results show that the proposed method produces better image quality than conventional algorithms in both objective and subjective terms.

This paper proposes a simple and practical scheme to decide the direction of a phased array antenna beam in wireless access systems using Radio-over-Fiber (RoF) technique. The feasibility of the proposed scheme is confirmed by the optical and wireless transmission experiments using 2GHz RoF signals. In addition, two-dimensional steering operation in the millimeter-wave band is demonstrated for targeting future high-speed wireless communication systems. The required system parameters for practical use are also provided by investigating the induced transmission penalties. The proposed detection scheme is applicable to two-dimensional antenna beam steering in the millimeter-wave band by properly designing the fiber length and wavelength variable range.

This paper proposes a new algorithm for substring searching. Our algorithm is an improvement on the famous BM algorithm. When a mismatch happens while searching a substring (pattern), the BM algorithm will use two strategies to calculate shifting distances of the substring respectively and selects the larger one. In comparison, our algorithm uses each of the two strategies for their most suitable cases separately without a selection operation. Experimental results demonstrated that our algorithm is more efficient than the BM algorithm and the Quick Search algorithm, especially for binary strings and DNA strings.

Artificial blurring is a typical operation in image forging. Most existing image forgery detection methods consider only one single feature of artificial blurring operation. In this manuscript, we propose to adopt feature fusion, with multifeatures for artificial blurring operation in image tampering, to improve the accuracy of forgery detection. First, three feature vectors that address the singular values of the gray image matrix, correlation coefficients for double blurring operation, and image quality metrics (IQM) are extracted and fused using principal component analysis (PCA), and then a support vector machine (SVM) classifier is trained using the fused feature extracted from training images or image patches containing artificial blurring operations. Finally, the same procedures of feature extraction and feature fusion are carried out on the suspected image or suspected image patch which is then classified, using the trained SVM, into forged or non-forged classes. Experimental results show the feasibility of the proposed method for image tampering feature fusion and forgery detection.