In this paper, we propose an optimized virtual re-convergence system especially to reduce the visual fatigue caused by binocular stereoscopy. Our unique idea to reduce visual fatigue is to utilize the virtual re-convergence based on the optimized disparity-map that contains more depth information in the negative disparity area than in the positive area. Therefore, our system facilitates a unique search-range scheme, especially for negative disparity exploration. In addition, we used a dedicated method, using a so-called Global-Shift Value (GSV), which are the total shift values of each image in stereoscopy to converge a main object that can mostly affect visual fatigue. The experimental result, which is a subjective assessment by participants, shows that the proposed method makes stereoscopy significantly comfortable and attractive to view than existing methods.

This paper presents a novel 2-D (2-dimension) receiver that adopts the reception scheme to promote OFDM-DS-CDMA (orthogonal frequency division multiplexing multi-carrier coded-division multiple-access) system performance. The system model includes spread coding and a system block diagram of the 2-D receiver shown graphically with 3-D (three dimensions) plots. The analytical calculation of system performance for an OFDM-DS-CDMA system combined with the proposed receiver equipment is investigated. To evaluate the results from the channel fading effect is considered over the correlated fading environments. The correlated-Nakagami-m statistical distribution is taken into account in the evaluation. The results show that the number of users, the number of subcarriers and the fading channel correlation generally affect OFDM-DS-CDMA systems. The system is also influenced by the Doppler shift and the signal propagation environment (fading parameter).

Face image hashing is an emerging method used in biometric verification systems. In this paper, we propose a novel face image hashing method based on a new technique called discriminative projection selection. We apply the Fisher criterion for selecting the rows of a random projection matrix in a user-dependent fashion. Moreover, another contribution of this paper is to employ a bimodal Gaussian mixture model at the quantization step. Our simulation results on three different databases demonstrate that the proposed method has superior performance in comparison to previously proposed random projection based methods.

Most of the IP mobility management schemes based on the IETF's MIPv6 may not be suitable for delay-sensitive vehicular applications since there will be frequent service disruptions as the moving vehicles frequently change their points of wireless network attachment. This paper presents a fast IP mobility management scheme for vehicular networks where multiple wireless network interfaces are used to perform fast handovers without handover latency or packet loss. In order to do this, the IETF standard HMIPv6 has been extended, where multiple simultaneous tunnels between the HMIPv6 mobility anchor point (MAP) and the mobile gateway are dynamically constructed. We have designed the architecture for a mobile gateway for supporting multiple tunnels, the structure of the extension MAP (E-MAP), and the signaling procedure to achieve fast IP handover in vehicular networks. Both mathematical analysis and simulation have been done for performance evaluation. The results show that the proposed scheme is superior to HMIPv6 and MIPv6 with regard to handover latency and packet loss as the vehicle moves between different wireless network cells at high speed.

Switch-and-stay combining (SSC) is a simple diversity technique where a single radio frequency (RF) chain is connected to one of several antenna branches and stays there if the channel quality is satisfied or otherwise switches to a new branch. Compared with Selection Combining (SC), SSC requires less overhead in channel estimation and antenna selection feedback. In this paper, we analyze the performance of SSC in a time-correlated flat fading channel and with causal channel state information. We derive the general expressions for the distribution of the output signal-to-noise ratio (SNR), outage rate and average bit error rate (ABER) and then the analytical results are compared with the simulation results under the Jakes Rayleigh fading channel. Our results show that (1) For slowly varying channels, L branch SSC can achieve the full diversity order and the same outage rate as SC; (2) Increasing the number of antenna branches can improve the performance of SSC, however, the gain from adding antennas diminishes quickly as the channel variation speed increases. Moreover, to avoid the complexity in optimizing the fixed threshold, we also propose a simple adaptive SSC scheme which has almost the same ABER as the SSC with optimized fixed threshold.

We are interested in retrieving video shots or videos containing particular people from a video dataset. Owing to the large variations in pose, illumination conditions, occlusions, hairstyles and facial expressions, face tracks have recently been researched in the fields of face recognition, face retrieval and name labeling from videos. However, when the number of face tracks is very large, conventional methods, which match all or some pairs of faces in face tracks, will not be effective. Therefore, in this paper, an efficient method for finding a given person from a video dataset is presented. In our study, in according to performing research on face tracks in a single video, we also consider how to organize all the faces in videos in a dataset and how to improve the search quality in the query process. Different videos may include the same person; thus, the management of individuals in different videos will be useful for their retrieval. The proposed method includes the following three points. (i) Face tracks of the same person appearing for a period in each video are first connected on the basis of scene information with a time constriction, then all the people in one video are organized by a proposed hierarchical clustering method. (ii) After obtaining the organizational structure of all the people in one video, the people are organized into an upper layer by affinity propagation. (iii) Finally, in the process of querying, a remeasuring method based on the index structure of videos is performed to improve the retrieval accuracy. We also build a video dataset that contains six types of videos: films, TV shows, educational videos, interviews, press conferences and domestic activities. The formation of face tracks in the six types of videos is first researched, then experiments are performed on this video dataset containing more than 1 million faces and 218,786 face tracks. The results show that the proposed approach has high search quality and a short search time.

A workflow net (WF-net for short) is a Petri net which represents a workflow. There are two important subclasses of WF-nets: extended free-choice (EFC for short) and well-structured (WS for short). It is known that most actual workflows can be modeled as EFC WF-nets; Acyclic WS is a subclass of acyclic EFC but has more analysis methods. An acyclic EFC WF-net may be transformed to an acyclic WS WF-net without changing the external behavior of the net. We name such a transformation Acyclic EFC WF-net refactoring. We give a formal definition of acyclic EFC WF-net refactoring problem. We also give a necessary condition and a sufficient condition for solving the problem. Those conditions can be checked in polynomial time. These result in the enhancement of the analysis power of acyclic EFC WF-nets.

In this paper, we propose a novel approach for presenting the local features of digital image using 1D Local Patterns by Multi-Scans (1DLPMS). We also consider the extentions and simplifications of the proposed approach into facial images analysis. The proposed approach consists of three steps. At the first step, the gray values of pixels in image are represented as a vector giving the local neighborhood intensity distrubutions of the pixels. Then, multi-scans are applied to capture different spatial information on the image with advantage of less computation than other traditional ways, such as Local Binary Patterns (LBP). The second step is encoding the local features based on different encoding rules using 1D local patterns. This transformation is expected to be less sensitive to illumination variations besides preserving the appearance of images embedded in the original gray scale. At the final step, Grouped 1D Local Patterns by Multi-Scans (G1DLPMS) is applied to make the proposed approach computationally simpler and easy to extend. Next, we further formulate boosted algorithm to extract the most discriminant local features. The evaluated results demonstrate that the proposed approach outperforms the conventional approaches in terms of accuracy in applications of face recognition, gender estimation and facial expression.

Reversible color component transforms derived by the LU factorization are briefly described. It is possible to obtain an reversible implementation to a given component transform, even if the original transform is irreversible. Some examples are presented and their performances are compared in image compression.

Users recently find their interests by checking the contents published or mentioned by their immediate neighbors in social networking services. We propose semantics-based link navigation; links guide the active user to potential neighbors who may provide new interests. Our method first creates a graph that has users as nodes and shared interests as links. Then it divides the graph by link pruning to extract practical numbers, that the active user can navigate, of interest-sharing groups, i.e. communities of interests (COIs). It then attaches a different semantic tag to the link to each representative user, which best reflects the interests of COIs that they are included in, and to the link to each immediate neighbor of the active user. It finally calculates link attractiveness by analyzing the semantic tags on links. The active user can select the link to access by checking the semantic tags and link attractiveness. User interests extracted from large scale actual blog-entries are used to confirm the efficiency of our proposal. Results show that navigation based on link attractiveness and representative users allows the user to find new interests much more accurately than is otherwise possible.

In this paper, we propose three Deflection-Routing-based Multicast (DRM) schemes for a bufferless NoC. The DRM scheme without packets replication (DRM_noPR) sends multicast packet through a non-deterministic path. The DRM schemes with adaptive packets replication (DRM_PR_src and DRM_PR_all) replicate multicast packets at the source or intermediate node according to the destination position and the state of output ports to reduce the average multicast latency. We also provide fault-tolerant supporting in these schemes through a reinforcement-learning-based method to reconfigure the routing table to tolerate permanent faulty links in the network. Simulation results illustrate that the DRM_PR_all scheme achieves 41%, 43% and 37% less latency on average than that of the DRM_noPR scheme and 27%, 29% and 25% less latency on average than that of the DRM_PR_src scheme under three synthetic traffic patterns respectively. In addition, all three fault-tolerant DRM schemes achieve acceptable performance degradation at various link fault rates without any packet lost.

In this paper, the problem of control reconfiguration in the presence of actuator failure preserving the nominal controller is addressed. In the actuator failure condition, the processing algorithm of the control signal should be adapted in order to re-achieve the desired performance of the control loop. To do so, the so-called reconfiguration block, is inserted into the control loop to reallocate nominal control signals among the remaining healthy actuators. This block can be either a constant mapping or a dynamical system. In both cases, it should be designed so that the states or output of the system are fully recovered. All these situations are completely analysed in this paper using a novel structural approach leading to some theorems which are supported in each section by appropriate simulations.

In this paper, we propose a test generation method for diagnosing transition faults. The proposed method assumes launch on capture test, and it generates test vectors for given fault pairs using a stuck-at ATPG tool so that they can be distinguished. If a given fault pair is indistinguishable, it is identified, and thus the proposed method achieves a complete diagnostic test generation. The conditions for distinguishing a fault pair are carefully considered, and they are transformed into the conditions of the detection of a stuck-at fault, and some additional logic gates are inserted in a CUT during the test generation process. Experimental results show that the proposed method can generate test vectors for distinguishing the fault pairs that are not distinguished by commercial tools, and also identify indistinguishable fault pairs.

Non-negative matrix factorization (NMF) is widely used for monaural musical sound source separation because of its efficiency and good performance. However, an additional clustering process is required because the musical sound mixture is separated into more signals than the number of musical tracks during NMF separation. In the conventional method, manual clustering or training-based clustering is performed with an additional learning process. Recently, a clustering algorithm based on the mel-frequency cepstrum coefficient (MFCC) was proposed for unsupervised clustering. However, MFCC clustering supplies limited information for clustering. In this paper, we propose various timbre features for unsupervised clustering and a clustering algorithm with these features. Simulation experiments are carried out using various musical sound mixtures. The results indicate that the proposed method improves clustering performance, as compared to conventional MFCC-based clustering.

Based on our previous work, this work presents a complete method for time-domain processing of frequency-domain data with evenly-spaced frequency indices, together with its application. The proposed method can be used to calculate the cross spectral and power spectral densities for the frequency indices of interest. A promising application for the time-domain processing of frequency-domain data, particularly for calculating the summation of frequency-domain cross- and auto-correlations in orthogonal frequency-division multiplexing (OFDM) systems, is studied. The advantages of the time-domain processing of frequency-domain data are 1) the ability to rapidly acquire the properties that are readily available in the frequency domain and 2) the reduced complexity. The proposed fast algorithm directly employs time-domain samples, and hence, does not need the fast Fourier transform (FFT) operation. The proposed algorithm has a lower complexity (required complex multiplications ∼ O(N)) than conventional techniques.

The cause-and-effect relation between plasmon-resonance absorption and surface wave in a sinusoidal metal grating is investigated. By introducing an equivalent impedance model, similar to an equivalent circuit on an electric circuit, which is an impedance boundary value problem on the fictitious surface over the grating, we estimate the surface wave from the eigen field of the model by using the resonance property of the scattered field. Through numerical examples, we illustrate that the absorption in the grating occurs in the condition of exciting the surface wave along the model, and the real part of the surface impedance is negative on about half part of the fictitious surface in the condition.

We present an economical and fault-tolerant load balancing strategy (EFTLBS) based on an operator replication mechanism and a load shedding method, that fully utilizes the network resources to realize continuous and highly-available data stream processing without dynamic operator migration over wide area networks. In this paper, we first design an economical operator distribution (EOD) plan based on a bin-packing model under the constraints of each stream bandwidth as well as each server's CPU capacity. Next, we devise super-operator (SO) that load balances multi-degree operator replicas. Moreover, for improving the fault-tolerance of the system, we color the SOs based on a coloring bin-packing (CBP) model that assigns peer operator replicas to different servers. To minimize the effects of input rate bursts upon the system, we take advantage of a load shedding method while keeping the QoS guarantees made by the system based on the SO scheme and the CBP model. Finally, we substantiate the utility of our work through experiments on ns-3.

The double threshold detecting strategy is widely used for spatially distributed target detection in practical systems. However, the detector is limited in terms of robustness and effectiveness. In this paper, an improved double threshold detector is proposed that avoids these shortcomings. In the proposed detector, the energy in range cells that exceed the first threshold is accumulated and then the output of the accumulator is compared with the second threshold for detection. The threshold selection strategy is derived to guarantee the constant false-alarm rate (CFAR) property. A simulation shows that the proposed detector is superior to the conventional approach in terms of both robustness and effectiveness.

Hypercomplex polar Fourier analysis treats a signal as a vector field and generalizes the conventional polar Fourier analysis. It can handle signals represented by hypercomplex numbers such as color images. Hypercomplex polar Fourier analysis is reversible that means it can reconstruct image. Its coefficient has rotation invariance property that can be used for feature extraction. However in order to increase the computation speed, fast algorithm is needed especially for image processing applications like realtime systems and limited resource platforms. This paper presents fast hypercomplex polar Fourier analysis based on symmetric properties and mathematical properties of trigonometric functions. Proposed fast hypercomplex polar Fourier analysis computes symmetric points simultaneously, which significantly reduce the computation time.

In this paper, we propose a novel path tracking control algorithm for an underactuated autonomous underwater vehicle (AUV). The underactuated AUV is controlled by the thrust force and the yaw torque: no sway thruster is used. To deal with this underactuated AUV problem in the path tracking, we introduce an approach angle which makes the AUV converge to the reference path. To design the path tracking controller, we obtain the vehicle's error dynamics in the body-fixed frame, and then design the path tracking controller based on the dynamic surface control (DSC) method. The proposed controller only needs the information of the position and the heading angle of the reference path. Some simulation results demonstrate the effectiveness of the proposed controller.