The traffic congestion problem in urban areas is worsening since traditional traffic signal control systems cannot provide] efficient traffic regulation. Therefore, dynamic traffic signal control in Intelligent Transportation System (ITS) recently has received increasing attention. This study devised a multi-agent architecture, the Adaptive and Cooperative Traffic light Agent Model (ACTAM), for a decentralized traffic signal control system. The proposed architecture comprises a data storage and communication layer, a traffic regulation factor processing layer, and a decision-making layer. This study focused on utilizing the cooperation of multi-agents and the prediction mechanism of our architecture, the Forecast Module, to forecast future traffic volume in each individual intersection. The Forecast Module is designed to forecast traffic volume in an intersection via multi-agent cooperation by exchanging traffic volume information for adjacent intersections, since vehicles passing through nearby intersections were believed to significantly influence the traffic volume of specific intersections. The proposed architecture can achieve dynamic traffic signal control. Thus, total delay time of the traffic network under ACTAM can be reduced by 37% compared to the conventional fixed sequence traffic signal control strategy. Consequently, traffic congestion in urban areas can be alleviated by adopting ACTAM.

This paper investigates the lossless video aggregation and transport, a concept of transmitting a group of video sessions as a bundle over a communication network. We focus on the design of optimal transmission plan with minimum receiver buffer requirement for stored variable bit-rate (VBR) videos over a constant bit-rate (CBR) channel without incurring buffer underflow and overflow. For a single video, an efficient algorithm is proposed to calculate the optimal transmission plan in only O(N) time, a significant improvement of the previous result with time complexity of O(N2log N). For multiple video sessions, we propose an aggregation scheme to calculate the changes of optimal transmission plans at the joints or separations, where a session bundled in the aggregated video stream begins or stops. The experimental results show that our algorithms stand out in terms of simplicity and efficiency.

As the increasing complexity of chip design, reducing both power consumption and clock skew becomes a crucial research topic in clock network synthesis. Among various clock network synthesis approaches, clock tree has less power consumption in comparison with clock mesh structure. In contrast, clock mesh has a higher tolerance of process variation and hence is easier to satisfy the clock skew constraint. To reduce the power consumption of clock mesh network, an effective way is to minimize the wire capacitance of stub wires. In addition, integration of clock gating and register clustering techniques on clock mesh network can further reduce dynamic power consumption. In this paper, under both enable timing constraint and clock skew constraint, we propose a methodology to reduce the switching capacitance by non-uniform clock mesh synthesis, clock gate insertion and register clustering. In comparison with clock mesh synthesis and clock gating technique individually, experimental results show that our methodology can improve both the clock skew and switching capacitance efficiently.

In this paper, a multiple-object tracking approach in large-scale scene is proposed based on visual sensor network. Firstly, the object detection is carried out by extracting the HOG features. Then, object tracking is performed based on an improved particle filter method. On the one hand, a kind of temporal and spatial dynamic model is designed to improve the tracking precision. On the other hand, the cumulative error generated from evaluating particles is eliminated through an appearance model. In addition, losses of the tracking will be incurred for several reasons, such as occlusion, scene switching and leaving. When the object is in the scene under monitoring by visual sensor network again, object tracking will continue through object re-identification. Finally, continuous multiple-object tracking in large-scale scene is implemented. A database is established by collecting data through the visual sensor network. Then the performances of object tracking and object re-identification are tested. The effectiveness of the proposed multiple-object tracking approach is verified.

This paper proposes a cumulative DNL (CDNL) test methodology for the BIST of ADCs. It analyzes the histogram of the DNL of a predetermined k LSBs distance to determine the DNL and gain error. The advantage of this method over others is that the numbers of required code bins and required samples are significantly reduced. The simulation and measurements of a 12-bit ADC show that the proposed CDNL has an error of less than 5% with only 212 samples, which can only be achieved with 222 samples using the conventional method. It only needs 16 registers to store code bins in this experiment.

In cognitive radio networks, the primary user (PU) can lease a fraction of its licensed spectrum to the secondary users (SUs) in exchange for their cooperative transmission if it has a minimum transmission rate requirement and is experiencing a bad channel condition. However, due to the selfish nature of the SUs, they may not cooperate to meet the PU's Quality of Service (QoS) requirement. On the other hand, the SUs may not exploit efficiently the benefit from cooperation if they compete with each other and collaborate with the PU independently. Therefore, when SUs belong to the same organization and can work as a group, how to stimulate them to cooperate with the PU and thus guarantee the PU's QoS requirement, and how to coordinate the usage of rewarded spectrum among these SUs after cooperation are critical challenges. In this paper, we propose a two-level bargaining framework to address the aforementioned problems. In the proposed framework, the interactions between the PU and the SUs are modeled as the upper level bargaining game while the lower level bargaining game is used to formulate the SUs' decision making process on spectrum sharing. We analyze the optimal actions of the users and derive the theoretic results for the one-PU one-SU scenario. To find the solutions for the one-PU multi-SU scenario, we put forward a revised numerical searching algorithm and prove its convergence. Finally, we demonstrate the effectiveness and efficiency of the proposed scheme through simulations.

This paper discusses the on-line frequency identification problem for a measured sinusoidal signal by using the adaptive method and filter theory. The proposed method is based on an identity between the sinusoidal signal and its second order derivative. For a set of chosen parameters, the proposed method is robust to the initial phase, the amplitude, and the frequency in a wide range. The convergence rate can be adjusted by the chosen parameters. The estimation error mainly depends on the frequency of the sinusoid, the measurement noise and a key design parameter.

Large amounts of color-printed documents are published now everyday. Some OCR approaches of color-printed document images are provided, but they cannot normally work if the input images skew. In the past years, many algorithms are provided to detect the skew of monochrome document images but none of them process color-printed document images. All of these methods assume that text is printed in black on a white background and cannot be applied to detect skew in color-printed document images. In this paper, we propose an algorithm to detect the skew angle of a color-printed document image and reconstruct it. Our approach first determines variation of color-transition count at each angle (from -45 to +45) and the angle of maximal variation is regarded as the skew angle. Then, a scanning-line model reconstructs the image. We test 100 color-printed document images of various kinds and get good results (93 succeed and 7 fail). The average processing time of A4 size image is 2.76 seconds and the reconstruction time is 3.97 seconds on a Pentium III 733 PC.

This letter proposes a novel high performance crypto coprocessor that relies on Reconfigurable Cryptographic Blocks. We implement the prototype of the coprocessor on Xilinx FPGA chip. And the pipelining technique is adopted to realize data paralleling. The results show that the coprocessor, running at 189MHz, outperforms the software-based SSL protocol.