A novel delta-sigma modulator that employs a non-uniform quantizer whose spacing is adjusted by reference to the statistical properties of the input signal is proposed. The proposed delta-sigma modulator has less quantization noise compared to the one that uses a uniform quantizer with the same number of output values. With respect to the quantizer on its own, Lloyd proposed a non-uniform quantizer that is best for minimizing the average quantization noise power. The applicable condition of the method is that the statistical properties of the input signal, the probability density, are given. However, the procedure cannot be directly applied to the quantizer in the delta-sigma modulator because it jeopardizes the modulator's stability. In this paper, a procedure is proposed that determine the spacing of the quantizer with avoiding instability. Simulation results show that the proposed method reduces quantization noise by up to 3.8 dB and 2.8 dB with the input signal having a PAPR of 16 dB and 12 dB, respectively, compared to the one employing a uniform quantizer. Two alternative types of probability density function (PDF) are used in the proposed method for the calculation of the output values. One is the PDF of the input signal to the delta-sigma modulator and the other is an approximated PDF of the input signal to the quantizer inside the delta-sigma modulator. Both approaches are evaluated to find that the latter gives lower quantization noise.

In this paper, a fast and automated method of counting pedestrians in crowded areas is proposed along with three contributions. We firstly propose Local Empirical Templates (LET), which are able to outline the foregrounds, typically made by single pedestrians in a scene. LET are extracted by clustering foregrounds of single pedestrians with similar features in silhouettes. This process is done automatically for unknown scenes. Secondly, comparing the size of group foreground made by a group of pedestrians to that of appropriate LET captured in the same image patch with the group foreground produces the density ratio. Because of the local scale normalization between sizes, the density ratio appears to have a bound closely related to the number of pedestrians who induce the group foreground. Finally, to extract the bounds of density ratios for groups of different number of pedestrians, we propose a 3D human models based simulation in which camera viewpoints and pedestrians' proximity are easily manipulated. We collect hundreds of typical occluded-people patterns with distinct degrees of human proximity and under a variety of camera viewpoints. Distributions of density ratios with respect to the number of pedestrians are built based on the computed density ratios of these patterns for extracting density ratio bounds. The simulation is performed in the offline learning phase to extract the bounds from the distributions, which are used to count pedestrians in online settings. We reveal that the bounds seem to be invariant to camera viewpoints and humans' proximity. The performance of our proposed method is evaluated with our collected videos and PETS 2009's datasets. For our collected videos with the resolution of 320 × 240, our method runs in real-time with good accuracy and frame rate of around 30 fps, and consumes a small amount of computing resources. For PETS 2009's datasets, our proposed method achieves competitive results with other methods tested on the same datasets [1],[2].

Execution performance is critical for large-scale and data-intensive workflows. This paper proposes DISWOP, a novel scheduling algorithm for data-intensive workflow optimizations; it consists of three main steps: workflow process generation, task & resource mapping, and task clustering. To evaluate the effectiveness and efficiency of DISWOP, a comparison evaluation of different workflows is conducted a prototype workflow platform. The results show that DISWOP can speed up execution performance by about 1.6-2.3 times depending on the task scale.

Orthogonal frequency-division multiplexing (OFDM) is a popular air interface technology that is adopted as a standard modulation scheme for 4G communication systems owing to its excellent spectral efficiency. For OFDM systems, synchronization problems have received much attention along with peak-to-average power ratio (PAPR) reduction. In addition to frequency offset estimation, frame synchronization is a challenging problem that must be solved to achieve optimal system performance. In this paper, we present a maximum likelihood (ML) frame synchronizer for OFDM systems. The synchronizer exploits a synchronization word and cyclic prefixes together to improve the synchronization performance. Numerical results show that the performance of the proposed frame synchronizer is better than that of conventional schemes. The proposed synchronizer can be used as a reference for evaluating the performance of other suboptimal frame synchronizers. We also modify the proposed frame synchronizer to reduce the implementation complexity and propose a near-ML synchronizer for time-varying fading channels.

Some optical components have polarization dependent loss (PDL), which degrades the performance of optical measurement systems. Various PDL suppression methods have been proposd, most of them have rather complicated structures. In this paper we propose a new simple method for PDL suppression, in which a single birefringent element is concatenated to a PDL device with their birefringent axes offset by π/4. The effectiveness of the proposed method is verified by experiments, that is, polarization dependent loss variation amplitude V of a device relative to its average loss is reduced from 90% to 2% by using a 2 m long PANDA fiber for an LED light source whose central wavelength λ0 and spectral width Δλ are 847 nm and 55 nm, respectively. Furthermore, for an SLD light source with λ0=1539 nm and Δλ=71 nm, V as much as 80% is reduced to 2% by using the same PANDA fiber.

In this paper, an improved GPS/RFID integration method based on Sequential Iterated Reduced Sigma Point Kalman Filter (SIRSPKF) is proposed for vehicle navigation applications. It is applied to improve the accuracy, reliability and availability of satellite positioning in the areas where the satellite visibility is limited. An RFID system is employed to assist the GPS system in achieving high accuracy positioning. Further, to reduce the measurement noise and decrease the computational complexity caused by the integrated GPS/RFID, SIRSPKF is investigated as the dominant filter for the proposed integration. Performances and computational complexities of different integration scenarios with different filters are compared in this paper. A field experiment shows that both accuracy and availability of positioning can be improved significantly by this low-cost GPS/RFID integration method with the reduced computational load.

The radio frequency identification (RFID) system has attracting attention as a new identification source that achieves a ubiquitous environment. Each RFID tag has a unique ID code, and is attached on an object whose information it contains. A user reads the unique ID code using RFID readers and obtains information about the object. One of the important applications of RFID technology is the indoor position estimation of RFID tags. It can be applied to navigation systems for people in complex buildings. In this paper, we propose an effective position estimation method named Broad-type Multi-Sensing-Range (B-MSR) method to improve the estimation error of the conventional methods using sensor model. A new reader antenna with two flexible antenna elements is introduced into B-MSR. The distance between two flexible antenna elements can be adjusted. Thus, two kinds of system parameters can be controlled, the distance between two antenna elements and the transmission power of the RFID reader. In this paper, four sensing ranges are settled by controlling the values of two parameters. The performance evaluation shows four characteristics of B-MSR. Firstly, it reduces the initial estimation error. Secondly, it reduces the moving distance. Thirdly, it reduces the number of different sensing points. Fourthly, it shortens the required estimation time.

In this paper, we propose a method capable of shortening the distance from a noise detection microphone to a loudspeaker in active noise control system with non-minimum phase secondary path. The distance can be basically shortened by forming the noise control filter, which produces the secondary noise provided by the loudspeaker, with the cascade connection of a non-recursive filter and a recursive filter. The output of the recursive filter, however, diverges even when the secondary path includes only a minimum phase component. In this paper, we prevent the divergence by utilizing MINT (multi-input/output inverse theorem) method increasing the number of secondary paths than that of primary paths. MINT method, however, requires a large scale inverse matrix operation, which increases the processing cost. We hence propose a method reducing the processing cost. Actually, MINT method has only to be applied to the non-minimum phase components of the secondary paths. We hence extract the non-minimum phase components and then apply MINT method only to those. The order of the inverse matrix thereby decreases and the processing cost can be reduced. We finally show a simulation result demonstrating that the proposed method successfully works.

Visual degradation is usually introduced during 3D mesh simplification. The main issue in mesh simplification is to maximize the simplification ratio while minimizing the visual degradation. Therefore, effective and objective evaluation of the visual degradation is essential in order to select the simplification ratio. Some objective geometric and subjective perceptual metrics have been proposed. However, few objective metrics have taken human visual characteristics into consideration. To evaluate the visual degradation introduced by mesh simplification for a 3D triangular object, we integrate the structural degradation with mesh saliency and propose a new objective and multi-scale evaluation metric named Global Perceptual Structural Degradation (GPSD). The proper selection of the simplification ratio under a given distance-to-viewpoint is also discussed in this paper. The accuracy and validity of the proposed metric have been demonstrated through subjective experiments. The experimental results confirm that the GPSD metric shows better 3D model-based multi-scale perceptual evaluation capability.

This paper proposes a method for reconstructing a smooth and accurate 3D surface. Recent machine vision techniques can reconstruct accurate 3D points and normals of an object. The reconstructed point cloud is used for generating its 3D surface by surface reconstruction. The more accurate the point cloud, the more correct the surface becomes. For improving the surface, how to integrate the advantages of existing techniques for point reconstruction is proposed. Specifically, robust and dense reconstruction with Shape-from-Silhouettes (SfS) and accurate stereo reconstruction are integrated. Unlike gradual shape shrinking by space carving, our method obtains 3D points by SfS and stereo independently and accepts the correct points reconstructed. Experimental results show the improvement by our method.

In this paper, we present an automatic vision-based traffic sign recognition system, which can detect and classify traffic signs at long distance under different lighting conditions. To realize this purpose, the traffic sign recognition is developed in an originally proposed dual-focal active camera system. In this system, a telephoto camera is equipped as an assistant of a wide angle camera. The telephoto camera can capture a high accuracy image for an object of interest in the view field of the wide angle camera. The image from the telephoto camera provides enough information for recognition when the accuracy of traffic sign is low from the wide angle camera. In the proposed system, the traffic sign detection and classification are processed separately for different images from the wide angle camera and telephoto camera. Besides, in order to detect traffic sign from complex background in different lighting conditions, we propose a type of color transformation which is invariant to light changing. This color transformation is conducted to highlight the pattern of traffic signs by reducing the complexity of background. Based on the color transformation, a multi-resolution detector with cascade mode is trained and used to locate traffic signs at low resolution in the image from the wide angle camera. After detection, the system actively captures a high accuracy image of each detected traffic sign by controlling the direction and exposure time of the telephoto camera based on the information from the wide angle camera. Moreover, in classification, a hierarchical classifier is constructed and used to recognize the detected traffic signs in the high accuracy image from the telephoto camera. Finally, based on the proposed system, a set of experiments in the domain of traffic sign recognition is presented. The experimental results demonstrate that the proposed system can effectively recognize traffic signs at low resolution in different lighting conditions.

This paper presents a novel inpainting method based on structure estimation. The method first estimates an initial image that captures the rough structure and colors in the missing region. This image is generated by probabilistically estimating the gradient within the missing region based on edge segments intersecting its boundary, and then by flooding the colors on the boundary into the missing region. The color flooding is formulated as an energy minimization problem, and is efficiently optimized by the conjugate gradient method. Finally, by locally replacing the missing region with local patches similar to both the adjacent patches and the initial image, the inpainted image is synthesized. The initial image not only serves as a guide to ensure the underlying structure is preserved, but also allows the patch selection process to be carried out in a greedy manner, which leads to substantial speedup. Experimental results show the proposed method is capable of preserving the underlying structure in the missing region, while achieving more than 5 times faster computational speed than the state-of-the-art inpainting method. Subjective evaluation of image quality also shows the proposed method outperforms the previous methods.

Mining and explaining relationships between concepts are challenging tasks in the field of knowledge search. We propose a new approach for the tasks using disjoint paths formed by links in Wikipedia. Disjoint paths are easy to understand and do not contain redundant information. To achieve this approach, we propose a naive method, as well as a generalized flow based method, and a technique for mining more disjoint paths using the generalized flow based method. We also apply the approach to classification of relationships. Our experiments reveal that the generalized flow based method can mine many disjoint paths important for understanding a relationship, and the classification is effective for explaining relationships.

In this paper, the research advances in silicon based millimeter wave and THz ICs in the State Key Laboratory of Millimeter Waves is reviewed, which consists of millimeter wave amplifiers, mixers, oscillators at Q, V and W and D band based on CMOS technology, and several research approaches of THz passive ICs including cavity and filter structures using SIW-like (Substrate Integrated Waveguide-like) guided wave structures based on CMOS and MEMs process. The design and performance of these components and devices are presented.

The applications of dynamic content updates for a group of users, for example weather reports and news broadcast, have been shown to benefit significantly from Delay Tolerant Networks (DTNs) communication mechanisms. In this paper, we study the performance of dynamic content updates over DTNs by focusing on the latest content distribution, which is an important factor of the system energy consumption and content update efficiency. By characterizing the content generating process and content sharing process, we obtain an explicit expression for the latest content distribution, and prove it theoretically. Moreover, through simulations based on two synthetical mobility models and a real-world scenario, we demonstrate the accuracy and correctness of the theoretically obtained result.

A time-reversal (TR) approach with multiple signal classification (MUSIC) provides super-resolution for detection and localization using multistatic data collected from an array antenna system. The theory of TR-MUSIC assumes that the number of antenna elements is greater than that of scatterers (targets). Furthermore, it requires many sets of frequency-domain data (snapshots) in seriously noisy environments. Unfortunately, these conditions are not practical for real environments due to the restriction of a reasonable antenna structure as well as limited measurement time. We propose an approach that treats both noise reduction and relaxation of the transceiver restriction by using a time-domain gating technique accompanied with the Fourier transform before applying the TR-MUSIC imaging algorithm. Instead of utilizing the conventional multistatic data matrix (MDM), we employ a modified MDM obtained from the gating technique. The resulting imaging functions yield more reliable images with only a few snapshots regardless of the limitation of the antenna arrays.

Multimedia transactions between vehicles are expected to become a promising application in VANETs but security is a fundamental issue that must be resolved before such transactions can become practical and trusted. Existing certificate-based digital signature schemes are ineffective for ensuring the security of multimedia transactions in VANETs. This ineffectiveness exists because there is no guarantee that (1) vehicles can download the latest certificate revocation lists or that (2) vehicles can complete a multimedia transaction before leaving their communication range. These two problems result, respectively, from a lack of infrastructure and from the inconsistent connectivity inherent in VANETs. In this paper, we propose a digital signature approach that combines a certificateless signature scheme and short-lived public keys to alleviate these problems. We then propose a security protocol that uses the proposed signature approach for multimedia transactions between vehicles. The proposed protocol enables vehicles to trade in multimedia resources without an online trust authority. We provide an analytical approach to optimizing the security of the proposed protocol. The security and performance of our protocol are evaluated via simulation and theoretical analysis. Based on these evaluations, we contend that the proposed protocol is practical for multimedia transactions in VANETs in terms of security and performance.

Cubic TCP, one of transport protocols designed for high bandwidth-delay product (BDP) networks, has successfully been deployed in the Internet. Multi-homed computers with multiple interfaces to access the Internet via high speed links will become more popular. In this work, we introduce an extended version of Cubic TCP for multiple paths, called MPCubic. The extension process is approached from an analysis model of Cubic by using coordinated congestion control between paths. MPCubic can spread its traffic across paths in load-balancing manner, while preserving fair sharing with regular TCP, Cubic, and MPTCP at common bottlenecks. Moreover, to improve resilience to link failure, we propose a multipath fast recovery algorithm. The algorithm can significantly reduce the recovery time of data rate after restoration of failed links. These techniques can be useful for resilient high-bandwidth applications (for example, tele-health conference) in disaster-affected areas. Our simulation results show that MPCubic can achieve stability, throughput improvement, fairness, load-balancing, and quick data rate recovery from link failure under a variety of network conditions.

Ternary content addressable memory (TCAM) is becoming very popular for designing high-throughput forwarding engines on routers. However, TCAM has potential problems in terms of hardware and power costs, which limits its ability to deploy large amounts of capacity in IP routers. In this paper, we propose new hardware architecture for fast forwarding engines, called fast prefix search RAM-based hardware (FPS-RAM). We designed FPS-RAM hardware with the intent of maintaining the same search performance and physical user interface as TCAM because our objective is to replace the TCAM in the market. Our RAM-based hardware architecture is completely different from that of TCAM and has dramatically reduced the costs and power consumption to 62% and 52%, respectively. We implemented FPS-RAM on an FPGA to examine its lookup operation.

This paper shows a new pulse swallow programmable frequency divider with the division step size of 0.5. To realize the division step size of 0.5 by a conventional pulse swallow method, we propose a parallel dual modulus prescaler with the division ratio of P and P + 0.5. It consists of simple circuit elements and has an advantage over the conventional dual modulus prescaler with the division step size of 0.5 in high frequency operation. The proposed parallel dual modulus prescaler with the division ratio 8 and 8.5 is implemented in the 0.13-µm CMOS technology. The proposed architecture achieves 7 times higher frequency operation than the conventional one theoretically. It is verified the functions over 5 GHz.