In this paper, a new predictive model, adapted to QTM (Quaternary Triangular Mesh) pixel compression, is introduced. Our approach starts with the principles of proposed predictive models based on available QTM neighbo...In this paper, a new predictive model, adapted to QTM (Quaternary Triangular Mesh) pixel compression, is introduced. Our approach starts with the principles of proposed predictive models based on available QTM neighbor pixels. An algorithm of ascertaining available QTM neighbors is also proposed. Then, the method for reducing space complexities in the procedure of predicting QTM pixel values is presented. Next, the structure for storing compressed QTM pixel is proposed. In the end, the experiment on comparing compression ratio of this method with other methods is carried out by using three wave bands data of 1 km resolution of NOAA images in China. The results indicate that: 1) the compression method performs better than any other, such as Run Length Coding, Arithmetic Coding, Huffman Cod- ing, etc; 2) the average size of compressed three wave band data based on the neighbor QTM pixel predictive model is 31.58% of the origin space requirements and 67.5% of Arithmetic Coding without predictive model.展开更多
For Wireless Sensor Networks （WSN） is responsible for sensing, collecting, processing and monitoring of environmental data, but it might be limited in resources. This paper describes in detail the compressed sensing...For Wireless Sensor Networks （WSN） is responsible for sensing, collecting, processing and monitoring of environmental data, but it might be limited in resources. This paper describes in detail the compressed sensing theory, study the wireless sensor network data conventional compression and network coding method. The linear network coding scheme based on sparse random projection theory of compressed sensing. Simulation results show that this system satisfies the requirements of the reconstruction error of packets needed to reduce the number of nodes to the total number of 30%, improves the efficiency of data communications in wireless sensor network, reduce the energy consumption of the system. With other wireless sensor network data compression algorithm, the proposed algorithm has the advantages of simple realization, the compression effect is good, especially suitable for resource limited, and the accuracy requirements are not particularly stringent in wireless sensor networks.展开更多
On January 21, 2015, a sharp increase of the solar wind dynamic pressure impacted the magnetosphere. The magnetopause moved inward to the region L< 8 without causing a geomagnetic storm. The flux of the relativisti...On January 21, 2015, a sharp increase of the solar wind dynamic pressure impacted the magnetosphere. The magnetopause moved inward to the region L< 8 without causing a geomagnetic storm. The flux of the relativistic electrons in the outer radiation belt decreased by half during this event based on the observations of the particle radiation monitor(PRM) of the fourth of the China-Brazil Earth Resource Satellites(CBERS-4). The flux remained low for approximately 11 d; it did not recover after a small magnetic storm on January 26 but after a small magnetic storm on February 2. The loss and recovery of the relativistic electrons during this event are investigated using the PRM data, medium-and high-energy electron observations of NOAA-15 and the Van Allen Probes, medium-energy electron observations of GOES-13, and wave observations of the Van Allen Probes. This study shows that the loss of energetic electrons in this event is related to magnetospheric compression. The chorus waves accelerate the medium-energy electrons, which causes the recovery of relativistic electrons. The Van Allen Probes detected strong chorus waves in the region L =3–6 from January 21 to February 2. However, the flux of medium-energy electrons was low in the region. This implies that the long-lasting lack of recovery of the relativistic electrons after this event is due to the lack of the medium-energy"seed" electrons. The medium-energy electrons in the outer radiation belt may be a clue to predict the recovery of relativistic electrons.展开更多
基金Project 40471108 supported by the National Natural Science Foundation of China
文摘In this paper, a new predictive model, adapted to QTM (Quaternary Triangular Mesh) pixel compression, is introduced. Our approach starts with the principles of proposed predictive models based on available QTM neighbor pixels. An algorithm of ascertaining available QTM neighbors is also proposed. Then, the method for reducing space complexities in the procedure of predicting QTM pixel values is presented. Next, the structure for storing compressed QTM pixel is proposed. In the end, the experiment on comparing compression ratio of this method with other methods is carried out by using three wave bands data of 1 km resolution of NOAA images in China. The results indicate that: 1) the compression method performs better than any other, such as Run Length Coding, Arithmetic Coding, Huffman Cod- ing, etc; 2) the average size of compressed three wave band data based on the neighbor QTM pixel predictive model is 31.58% of the origin space requirements and 67.5% of Arithmetic Coding without predictive model.
文摘For Wireless Sensor Networks （WSN） is responsible for sensing, collecting, processing and monitoring of environmental data, but it might be limited in resources. This paper describes in detail the compressed sensing theory, study the wireless sensor network data conventional compression and network coding method. The linear network coding scheme based on sparse random projection theory of compressed sensing. Simulation results show that this system satisfies the requirements of the reconstruction error of packets needed to reduce the number of nodes to the total number of 30%, improves the efficiency of data communications in wireless sensor network, reduce the energy consumption of the system. With other wireless sensor network data compression algorithm, the proposed algorithm has the advantages of simple realization, the compression effect is good, especially suitable for resource limited, and the accuracy requirements are not particularly stringent in wireless sensor networks.
基金supported by the National Natural Science Foundation of China(Grant No.41374181)the National Key Scientific Instrument and Equipment Development Projects of China(Grant No.2012YQ03014207)
文摘On January 21, 2015, a sharp increase of the solar wind dynamic pressure impacted the magnetosphere. The magnetopause moved inward to the region L< 8 without causing a geomagnetic storm. The flux of the relativistic electrons in the outer radiation belt decreased by half during this event based on the observations of the particle radiation monitor(PRM) of the fourth of the China-Brazil Earth Resource Satellites(CBERS-4). The flux remained low for approximately 11 d; it did not recover after a small magnetic storm on January 26 but after a small magnetic storm on February 2. The loss and recovery of the relativistic electrons during this event are investigated using the PRM data, medium-and high-energy electron observations of NOAA-15 and the Van Allen Probes, medium-energy electron observations of GOES-13, and wave observations of the Van Allen Probes. This study shows that the loss of energetic electrons in this event is related to magnetospheric compression. The chorus waves accelerate the medium-energy electrons, which causes the recovery of relativistic electrons. The Van Allen Probes detected strong chorus waves in the region L =3–6 from January 21 to February 2. However, the flux of medium-energy electrons was low in the region. This implies that the long-lasting lack of recovery of the relativistic electrons after this event is due to the lack of the medium-energy"seed" electrons. The medium-energy electrons in the outer radiation belt may be a clue to predict the recovery of relativistic electrons.
