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In recent years, urban heat island effect has become a hot international issue. In this study, referencing Jimenez-Munoz & Jose A. Sobrino's single-channel method, surface temperature inversion was conducted to HJ-1B satellite remote sensing image under extreme temperature events on July 6, 2010 in Beijing using thermal infrared band image provided by environmental mitigation satellite HJ-1B. We extracted and analyzed the area and distribution of urban heat island under the influence of extreme high temperature, and compared with those of temperature rating chart on July 9, 2009 in Beijing. These researches show that comparing with non-extreme high temperature, there is a reducing of the area of urban middle temperature zone under the extreme high temperature and increasing of that of hot zone. Thus, the total area of urban heat island increased. In addition, Landuse has a great influence of the urban heat island. When the temperature rises, the increasing margin of surface temperature in the plant developed is small and that in urban lands is large. We also get a conclusion that as temperature increasing, the distribution of urban heat island is a radiant extension from the city center to the outer suburbs.

With the rapid development of electronic technology, on-line fault diagnosis of electronic equipment has become a hot research field. After some basic concepts and principles of fault diagnosis are introduced, this paper focuses on the diagnosis method based on knowledge technology, expounds in detail the diagnosis principle and research achievement such as the fault tree, pattern recognition, expert system, neural network, and the rough set. Finally, the new development and the problems of the fault diagnosis technique are summarized, looking to the future development of fault diagnosis technique which is based on Knowledge technology.

Power MOSFET is an important part in the main circuit of switching power supply. Its reliability has generated widespread concern. The study indicates that there are over 31% faults by cause of MOSFET in the failure statistics of circuit components. The key indicator of MOSFET failure is on-resistance parameter drift. In order to realize the online identification of MOSFET on-resistance, this paper takes Buck circuit for example, and constructs the hybrid model of Buck based on hybrid system theory. The method is presented to identify the parameters by using the Kalman algorithm. The paper conducts a series of simulation experiments in the Simulink environment. The experimental results show that this method of identifying MOSFET on-resistance is valid and that the on-resistance estimation error is less than 3% compared with the default value. Compared with the recursive least squares method, the Kalman parameter identification has better convergence. The results provide the theory basis and methods for the analysis of the MOSFET parameters failure.

Internet traffic classification is of prime importance to the areas of network management and security monitoring, network planning, and QoS provision. But the Traditional Classifications depend on certain header fields (take port numbers for instance). These port-based and payload-based approaches will be out of action when a lot of applications like P2P use dynamic port numbers. Masquerading techniques and payload encryption requires a high amount of resource of computing and is easily infeasible in the protocol that unknown or encrypted. This paper describes a different level in network traffic-analysis using an unsupervised machine learning technique. In this approach flows are automatically classified by exploiting the different statistics characteristics of flow. We implement and estimate the efficiency and feasibility of our approach using data at different location of Internet. A new attribute selection method is put forward to determine optimal attribute set and evaluate the influence.

Baiyangdian wetland is the largest freshwater lake in the north of China with an area of 366Km2. Recent years, the water quality of this area is degenerating. According to the field data in October 2006, the water quality belongs to organic pollution type. In September 2008, 67 water quality samples in Baiyangdian wetland were collected, with the parameters including pH, chlorophyll-a, dissolved oxygen (DO), blue-green algae and total dissolved solid. Evaluation result shows that Baiyangdian wetland was contaminated seriously with water quality of V grade referring to the GB3838–2002. Chlorophyll concentration in northern region is higher than that of southern region, which is up to 66.16g / L. At the same time water upwelling radiance was measured at 18 sampling stations by using field spectroradiometer (ASD FieldSpec). To contrastively analyze the characters of spectral curves of water body at different sampling points, in-situ measured spectrums are normalized. By comparing spectral curves of water, with the chlorophyll concentrations of 6.64 g / L, 20.08 g / L and 63.03 g / L respectively, it can be found that the reflectance peaks get lower in the region of 560–575nm along with the increase of chlorophyll concentrations. While at the band scope around 700nm, reflectance peaks rise as chlorophyll concentrations increasing, accompanying a ‘red shift’ of peak. Through calculating correlation coefficient between Chlorophyll-a concentration and normalized reflection of water, the highest positive correlation is 0.9133 at band of 722 nm. The bands near 550nm and 670nm show a negative relationship, while bands near 700nm represent positive correlation. These bands can be chosen for chlorophyll concentration retrieval by using remotely sensed data.

On the Internet, the nude images caused the spread of a large number of social problems, how to identify the nude image accurately is a problem needing to be solved urgently. Therefore, we integrate both image processing method and support vector machines (SVM), this paper studies a new and enhanced approach on recognition of nude image, namely, combine a face detection model, skin color model and texture model, extract six nude image feature vectors. Additionally, some important factors of SVM are fixed by experiments, such as the training set, kernel function and the cost. The experimental results demonstrate that performing SVM-based nude image detective classification more effective in that it improves the prediction accuracies at the same time.

In Northern China, main water supply is groundwater. In recent years, as the city's construction and development, long-term over-exploitation of groundwater has induced land subsidence which endangers the safety of human lives and properties. Because Beijing is a region seriously lack of water, five water sources for emergent events were built in order to meet the demand for urban water supply. Groundwater in such sources has been exploited in large-scale, high-intensity and concentratively, which will change groundwater system and result in related environmental-induced geological disasters. Shunyi District, as the place in which China's largest and most advanced Capital International Airport locates, meets more and more geological disasters such as land subsidence and ground fissure. Nature-human coupled factors impact on land subsidence progressing is focused in Shunyi District, the selected study area in this research. In the study, multi-scale remotely sensed imageries are utilized to extract human activity impact factors, especially in built-up areas. Hydrologic data is collected, and precipitation is defined as one of the natural factors. Comparison is made on relations between intensity change of accumulative ground subsidence and factors including precipitation, shallow groundwater exploitation amount, and land use in the period of 1990 to 2006. Meanwhile, contribution of nature-human impact factors on land subsidence is determined by AHP, and a Grey model is constructed in this research to forecast the intensity of ground subsidence in order to provide reference for prevention, control and slowdown on land subsidence.

Land subsidence is one of the environmental disasters induced by long-term over-exploitation of groundwater in Beijing. In order to keep sustainable social-economic development, this article analyzed the correlation between nature-human activities coupled factors and land subsidence on basis of remote sensing images and in-field data. At the same time, to obtain the principle driving factors of land surface sink, this paper chooses seven factors including the property of unsaturated zone, distribution of faults, precipitation, bedrock burying depth, build-up area, groundwater annual exploitation intensity and groundwater level, as natural-human coupled factors, which are relative main factors inducing land subsidence. And Principal Components Analysis (PCA) method is utilized to analyze the contribution of these factors to surface subsidence in Shun Yi district.

The development of courses system for embed system and the exploration of realistic embedded systems design experience for students are described in the paper. The design pay more attention on developing students's professional skills that will serve students well in their careers besides the requisite related basic theory. The curriculum design is shaped into two technology courses mainstreams, one is for universal processors system and the other focus on system on programmable chip (SOPC), a novel schedule of embedded systems education with professional engineering practice and progressive cooperative experiential learning is putted forward. The effect of the schedule from lecturers' response and student's assessment comments show that it is effective to develop the student's engineering practice, teamwork and active-learning skills.

The development of courses system for embed system and the exploation realistic embedded systems design experience for students are described in the paper. The Information technology education requires exposing students to the current edge of research. To ensure that student projects are along the same trajectory that the industry is progressing, educators must continually introduce emerging techniques, practices, and applications into the curriculum. The curriculum design is shaped into two technology courses mainstreams, one is for universal processors system and the other focus on system on programmable chip (SOPC), a novel schedule of embedded systems education with professional engineering practice and progressive cooperative experiential learning is putted forward in the paper.

By utilizing SPORT5 and aerial images, Great Wall of Ming Dynasty in Beijing has been investigated in detail and current distribution of Great Wall has been reported. In this paper, DEM is assisted to extract Great Wall information and the length of Great Wall has also been calculated. It studies the relationship between Great Wall and the surrounding land use, villages, roads, terrain by using GIS spatial analysis method. Finally, the influence weight of every relevant factor is calculated by AHP(Analytic Hierarchy Process) method and this thesis sets up buffer model and confirms the protection zone, all these has proposed scientific basis for the protection, management, and investigation of Great Wall in Beijing.

As to high-resolution remote sensing imagery classification based on object-orientated methodology, the precision is related to feature configuration and classification algorithm. In this paper, the IKONOS multi-spectral image is selected as sample data, and segmentated into many image objects. Firstly, the supervising classification is applied to extract land cover thematic information, based on nearest distance and SVM methods respectively, and the total classification accuracy is analysed and compared with each other. Follow the feature space is changed into different dimensionality, and the relation between feature configuration and classification accuracy is discussed respectively with nearest distance and SVM methods. The results show that the SVM classifier can well relax the relationship between image classification and representative feature configuration, and improved the insufficiency of nearest distance methodology during nonlinearity classification processing.

In this paper single-band and single-polarization Radarsat-1 SAR image is used to evaluate image classification with textural analysis. Firstly, the statistic information of sample were analyzed using semivariogram to determine the optimum parameters for textural extraction; Then four textures such as Homogeneity, Mean, Angle Second Moment and Entropy had been calculated based on GLCM, and the image data were processed using Support Vector Machine classification. The results show that the water and settlement areas are extracted accurately with accuracy 99.34% and 82.54%, and the SVM method has better extension ability for SAR image classification; Assisting with textural information, the image classification based on SVM has a obvious enhancement to original SAR, especially for some complex objects such as settlement areas(about increasing accuracy 18%).

Spatial resolution is an important index to evaluate the quality of remote sensing images. For the application of remote sensing satellite images, improving spatial resolution is significant. Super-resolution technology is one of the important ways to improve spatial resolution. According to the single visual light image, this paper discusses two super-resolution algorithms. One is mixed pixel quadtree decomposition algorithm based on weight analysis. The other one is mixed pixel quadtree decomposition algorithm based on edge detection. The experimental results indicate that: the algorithms can improve the spatial resolution of remote sensing images, and make the appearance of cultural feature clearer; important information beyond the limits of their spatial resolution from satellite images can be obtained.

It is presented that extraction of global and local feature based on digital microbial image analysis and fusion local and global features for microbe recognition. The global features are extracted by invariant moments and co-occurrence matrix, in which invariant moments computation is simplified by computing geometric moment and central moment based on the edge of microbe instead of the field of it. Curvature changing detection for microbe is characterized as local features by wavelet transform. Min-max was applied for normalization and after the fusion of normalized global match degree and normalized local match degree, the recognition result is the class that included the template image corresponding to the largest fused match degree. The experimental results show that fusing local and global features is effective for microbe image analysis and recognition.

Current techniques for beef quality evaluations rely on sensory methods. These procedures are subjective, prone to error, and difficult to quantify. Automated evaluation of color and odor is desirable to reduce subjectivity and discrepancies and assist with the creation of standards for inspectors worldwide. The objectives of this study were to develop color machine vision techniques for visual evaluation and to test electronic nose sensors for odor raw and beef. A color machine vision system was developed to analyze the color of beef samples. The system was able to analyze the color of samples with non-uniform color surfaces. An electronic nose sensors was used to measure odors of beef and beef stored at different temperatures, with different levels of spoilage. Discriminant function analysis was used as the pattern recognition technique to differentiate samples based on odors. Results showed that the electronic nose could discriminate differences in odor due to storage time and spoilage levels for beef. Results also showed good correlation of sensor reading with sensory scores overall, the electronic nose showed good sensitivity and accuracy. Results from this work could lead to methodologies that will assist in the objective and repeatable quality evaluation of beef. These methods have potential in industrial and regulatory application where rapid response, no sample preparation, and no need for chemicals are required.

A biosensor building on F0F1-ATPase for clenbuterol detection is constructed. The energy for ATP synthesis is provided from downhill proton transport along the proton gradient across membranes. This potential is formed by the electron transfer chains of respiration. The fluorescence probe F1300, which was sensitive to pH changes, was labeled into inner chromatophores to indicate the proton-flux during ATP synthesis. It's found that different loads onto the beta-subunit of chromatophores could affect its synthesis activity with different level. According to this principle, a biosensor was constructed based on ATPase to detect clenbuterol and the detecting mechanism depended on proton-flux driven by rotary catalytic ATP synthesis. The experiment results showed that the precision of clenbuterol detection by the biosensor could reach 10-12 g/L and the new biosensor might prove to be a useful nano-device for super-sensitive detection.

A biosensor based on FoF1-ATPase with immunological and biochemical techniques to achieve the goal of clenbuterol detection is constructed. The enzyme FoF1-ATPase is a molecular motor that converts the chemical energy stored in the molecule adenosine tri-phosphate (ATP) into mechanical rotation of its gamma sub-unit. During steady state catalysis, the three catalytic sites of FoF1-ATPase operate in a cooperative fashion such that at every instant each site is in a different conformation corresponding to a different stage along the catalytic cycle. Notwithstanding a large amount of biochemical and, recently, structural data we still lack an understanding of how ATP hydrolysis in FoF1-ATPase is coupled to mechanical motion and how the catalytic sites achieve cooperativity during rotatory catalysis. It's found that different loads onto the subunit of chromatophores could affect its synthesis activity to different extent. The detecting mechanism was depended on proton-flux driven by rotary catalytic ATP synthesis. The results clearly showed that the detection of clenbuterol by the biosensor was 10-12g/L. The results showed that the new biosensor may prove to be a useful nano-device for super-sensitive detection. The activity of FoF1-ATPase is affected with different loads of rotary molecular motors.

Remote sensing technology was selected and combined with field survey to extract land-cover information of Beijing. Taking the land-cover layer in 2000 as the background data, the updated layer data of 2005 and 2006 were produced by using remote sensing image change detection methodology. Technical Criterion for Eco-environmental Status Evaluation, a newly published standard of environmental protection industry (HJ/T192-2006) in China, was referenced. Then, the indices of biology abundance, vegetation covering, water network density, land degeneration and environment quality of Beijing in 2000, 2005 and 2006 were calculated respectively. The integrated ecologic environmental status indices were calculated based on above results. We carried out the classified evaluation and integrated analysis on the change of Beijing ecological environment status between 2000 and 2006. It was found that the ecological environment status of Beijing in recent years was maintained on the GOOD level. Nevertheless, it shows there are obvious changes among some environmental factors. Primarily, vegetation-covering rate decreasing, residential land expansion, water resources lesson and air pollution emission control are the most factors those affect Beijing ecological environment status. Suggestions for enhancing Beijing ecological environment status were put forward. Characteristics of applying remote sensing technology to the evaluation of ecological environment status were analyzed also.

With the development of remote sensing and geographical information system technologies, they are being applied to the every periods of flood disaster monitor and evaluation more and more. In the aspect of data acquisition, China is preparing for the launch of the small satellite constellation for environment and disaster. Currently, it is the principal problem that design and develop an integrative application platform for the flood disaster emergency response, the fast loss evaluation and the salvation decision-making support based on existing data, software and methodologies. At the same time, the trend of technology developing must be considered. Taking the requirement of China civil affairs department and the new satellite remote sensing data source guarantee into account, three key technologies about the development of flood disaster emergency response decisionmaking support system were designed. Based on the object- oriented, reuse, geodatabase, component object model and RS, GIS software technologies, the demonstrative application of key technologies in the integrative operational system was realized. Existing RS data were selected to simulate the future data. The demonstrative operational system has the characteristics of continuous monitoring, extensible, easy-to-use and so on. It can be utilized in many phases of operational work of flood disaster administration. Good effect was viewed in the usage of China National Natural Disaster Reduction Center.

This article proposes a method of fusing the optical data before the flood and SAR (synthetic aperture radar) data during the flood. The main goal of this study is to evaluate the capability of data fusion to combine the information from Landsat ETM image with Radarsat SAR image for water body and flooded area extraction. The Landsat ETM data will basically provide the information of landform and background information which includes the normal water extent. The Radarsat SAR data however was taken during flood will provide information mainly on water body extent and flooded area. In the result image, flooded area was significantly enhanced. We can distinguish the flooded area and normal water area easily.