Wireless sensor networks are characterized by multihop network. Some nodes in network are required to forward a disproportionately high amount of traffic and die early, leaving the unmonitored areas in network and...
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Wireless sensor networks are characterized by multihop network. Some nodes in network are required to forward a disproportionately high amount of traffic and die early, leaving the unmonitored areas in network and leading to the problem of energy hole. This paper investigates a variety of strategies to avoid the energy hole, such as communication power control, data aggregation, nonuniform energy distribution, mobile node auxiliary and clustering. The analysis and comparison of different strategies are given and the advantages and disadvantage of them are discussed in this paper.
The effects of carbon/slag molar ratio, chloride amount and temperature on equilibrium molar ratio (REq) of CO to CO2 for off-gas produced by carbochlorination of titanium slag were firstly investigated by thermodynam...
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The effects of carbon/slag molar ratio, chloride amount and temperature on equilibrium molar ratio (REq) of CO to CO2 for off-gas produced by carbochlorination of titanium slag were firstly investigated by thermodynamic calculation of equilibrium components of off-gas. The experimental CO/CO2 molar ratio (REx) was then obtained to be 0.2-0.3 by the carbochlorination experiment using a novel combined fluidized bed as chlorination reactor. To further investigate the reaction effect of the novel process mentioned above, REx, REq and corresponding reference data (RRe) were compared. The results indicate that REx is similar to RRe (0.5-1.2) but different from REq (≥4.3), which is consistent with anticipation of REx for the novel combined fluidized bed. The difference between REx and corresponding REq is mainly attributed to short retention time (about 1 s) of materials in combined fluidized bed and carbochlorination of oxide impurities contained in titanium slag, such as CaO, MgO and SiO2.
Due to FPGA's flexibility and parallelism, it is popular for accelerating image processing. In this paper, a double-parallel architecture based on FPGA has been exploited to speed up median filter and edge detecti...
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Due to FPGA's flexibility and parallelism, it is popular for accelerating image processing. In this paper, a double-parallel architecture based on FPGA has been exploited to speed up median filter and edge detection tasks, which are essential steps during image processing. The double-parallel scheme includes an image-level parallel and an operation-level parallel. The image-level parallel is a high-level parallel which divides one image into different parts and processes them concurrently. The operation-level parallel, which is embedded in each image-level parallel thread, fully explores every parallel part inside the concrete algorithms. The corresponding design is based on a DE2 Development Board which contains a CYCLONE II FPGA device. Meanwhile, the same task has also been implemented on PC and DSP for performance comparison. Despite the fact that operating frequencies of used PC and DSP are much higher than FPGA's, FPGA costs less time per computed image than both of them. By taking advantage of the double-parallel technique, the speed/frequency ratio of FPGA is 202 times faster than PC and 147 times faster than DSP. Finally, a detailed discussion about different platforms is conducted, which analyzes advantages and disadvantages of used computing platforms. This paper reveals that the proposed double-parallel scheme can dramatically speed up image processing methods even on a low-cost FPGA platform with low frequency and limited resources, which is very meaningful for practical applications.
Video-based traffic flow monitoring is a fast emerging field based on the continuous development of computer vision. A survey of the state-of-the-art video processing techniques in traffic flow monitoring is presented...
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Video-based traffic flow monitoring is a fast emerging field based on the continuous development of computer vision. A survey of the state-of-the-art video processing techniques in traffic flow monitoring is presented in this paper. Firstly, vehicle detection is the first step of video processing and detection methods are classified into background modeling based methods and non-background modeling based methods. In particular, nighttime detection is more challenging due to bad illumination and sensitivity to light. Then tracking techniques, including 3D model-based, region-based, active contour-based and feature-based tracking, are presented. A variety of algorithms including MeanShift algorithm, Kalman Filter and Particle Filter are applied in tracking process. In addition, shadow detection and vehicles occlusion bring much trouble into vehicle detection, tracking and so on. Based on the aforementioned video processing techniques, discussion on behavior understanding including traffic incident detection is carried out. Finally, key challenges in traffic flow monitoring are discussed.
Pseudo-particle modeling (PPM), a molecular modeling method which combines time-driven algorithms and hard molecule modeling, was originally developed for simulating gas in complexmultiphasesystems (Ge & Li, 200...
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Pseudo-particle modeling (PPM), a molecular modeling method which combines time-driven algorithms and hard molecule modeling, was originally developed for simulating gas in complexmultiphasesystems (Ge & Li, 2003; Ge et al., 2005; Ge, 1998). In this work, the properties of two- and three-dimensional pseudo-particle systems, namely, mean free path, compressibility factor, self-diffusion coefficient and shear viscosity, are systematically measured by using PPM. it is found that in terms of an effective diameter, the results well conform to the Chapman-Enskog theory, thus suggesting that PPM can be employed to simulate the micro- and meso-scale behavior of ordinary gas and fluid flows.
The component concentrations measurement of sodium aluminate solution are critical to the process of alumina production, they affect the product quality. However, they can not be measured online at present, thus the c...
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The component concentrations measurement of sodium aluminate solution are critical to the process of alumina production, they affect the product quality. However, they can not be measured online at present, thus the control and optimal operation is hardly to be achieved. This paper presents an on-line fuzzy modeling method to predict the component concentrations. It includes an on-line clustering approach which can be applied in a general class of fuzzy TKS models. Stable learning algorithms for the premise and the consequence parts of fuzzy rules are also given. A measuring device is developed to achieve the proposed method and industry experiments are conducted in the alumina production process, the predicted results show the effectiveness of the proposed method.
Along with the fast development of computer technology and measurement techniques, fundamental research on fluidization is faced with both new challenges and opportunities. Among others, great attention should be focu...
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Along with the fast development of computer technology and measurement techniques, fundamental research on fluidization is faced with both new challenges and opportunities. Among others, great attention should be focused on the meso-scale structure of fluidized beds, to study the quantitative prediction theory and optimum control method for the meso-scale structure of fluidized beds, and to establish the modeling of the relationship between meso-scale structure and momentum transfer, heat transfer, mass transfer, and chemical reaction. These efforts, combined with advanced computer simulation, are expected to solve difficult problems in optimum control and scale-up of fluidized bed processes and equipment.
The ACP (Artificial societies, Computational experiments and Parallel execution) approach has provided us an opportunity to look into new methods in addressing transportation problems from new perspectives. In this pa...
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The ACP (Artificial societies, Computational experiments and Parallel execution) approach has provided us an opportunity to look into new methods in addressing transportation problems from new perspectives. In this paper, we present our works and results of applying ACP approach in modeling and analyzing transportation system, especially carrying out computational experiments based on artificial transportation systems. Two aspects in the modeling process are analyzed. The first is growing artificial transportation system from bottom up using agent-based technologies. The second is modeling environment impacts in simple-is-consistent principle. Finally, two computational experiments are carried out on one specific ATS, Jinan ATS, and numerical results are presented to illustrate the applications of our method.
Linear wireless sensor networks are characterized by a linear topology and multihop forwarding patterns. Sensors closer to the base station are usually required to forward a large amount of traffic for sensors far...
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ISBN:
(纸本)9781457715860
Linear wireless sensor networks are characterized by a linear topology and multihop forwarding patterns. Sensors closer to the base station are usually required to forward a large amount of traffic for sensors farther from the base station, leading to the environment cannot be effectively monitored. The energy consumption balance is achieved in the paper by adjusting the distance between nodes. The distance of nodes near the base station become short because they have to forward the more traffic. The node deployment is converted to optimization problems of distance distribution between nodes. The network lifetime under different number of forwarding region is discussed. Simulation results show that this deployment strategy obtains the energy consumption balance.
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