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EN
Generally, gross errors exist in observations, and they affect the accuracy of results. We review methods to detect the gross errors by Robust estimation method based on L1-estimation theory and their validity in adjustment of geodetic networks with different condition. In order to detect the gross errors, we transform the weight of accidental model into equivalent one using not standardized residual but residual of observation, and apply this method to adjustment computation of triangulation network, traverse network, satellite geodetic network and so on. In triangulation network, we use a method of transforming into equivalent weight by residual and detect gross error in parameter adjustment without and with condition. The result from proposed method is compared with the one from using standardized residual as equivalent weight. In traverse network, we decide the weight by Helmert variance component estimation, and then detect gross errors and compare by the same way with triangulation network In satellite geodetic network in which observations are correlated, we detect gross errors transforming into equivalent correlation matrix by residual and variance inflation factor and the result is also compared with the result from using standardized residual. The results of detection are shown that it is more convenient and effective to detect gross errors by residual in geodetic network adjustment of various forms than detection by standardized residual.
EN
Bacteria constitute a large domain of prokaryotic microorganisms present in marine ecosystems and play a significant role in energy flow and nutrient cycling. Bacterial community changes may affect organisms of higher trophic levels. We conducted field monitoring to study the relationship between dissolved organic carbon (DOC) and the bacterial community in the coastal waters of Incheon, Korea. Results showed that abiotic factors, such as temperature, salinity, dissolved oxygen (DO), pH, and dissolved inorganic nutrients, were not significantly different among the sampling sites during the study period. On the other hand, nutrient conditions were significantly different among the sites between 2012-2013 and 2014. Nitrogen was the limiting factor from 2012 to 2013, and phosphate in 2014. Biotic data showed that DOC affected both bacterial abundance and bacterial composition. A similar fluctuation pattern was observed for phytoplankton and Chlorophyll a. However, a close correlation was not observed between phytoplankton and other variables. Redundancy analysis (RDA) and Pearson correlation analysis of abiotic and biotic factors also showed that DOC concentration and bacterial abundance were correlated. Therefore, DOC appears to be an important factor affecting bacterial abundance and composition in the coastal waters of Incheon, Korea.
EN
In this study, we have developed the manufacturing technology for high strength gray cast irons by using the spent permanent magnet scraps. The cast specimen inoculated by using a spent magnet scraps showed the excellent tensile strength up to 306MPa. This tensile strength value is 50MPa higher than that of the specimen cast without inoculation, and is similar to that of the specimen inoculated by using the expensive misch-metal. These superior mechanical properties are attributed to complex sulfides created during solidification that promote the formation and growth of Type-A graphite. It is therefore concluded that spent magnets scrap can provide an efficient and cost-effective inoculation agent for the fabrication of high-performance gray cast iron.
4
Content available remote Chemically synthesized PbS nanoparticulate thin films for a rapid NO2 gas sensor
EN
Rapid NO2 gas sensor has been developed based on PbS nanoparticulate thin films synthesized by Successive Ionic Layer Adsorption and Reaction (SILAR) method at different precursor concentrations. The structural and morphological properties were investigated by means of X-ray diffraction and field emission scanning electron microscope. NO2 gas sensing properties of PbS thin films deposited at different concentrations were tested. PbS film with 0.25 M precursor concentration showed the highest sensitivity. In order to optimize the operating temperature, the sensitivity of the sensor to 50 ppm NO2 gas was measured at different operating temperatures, from 50 to 200 degrees C. The gas sensitivity increased with an increase in operating temperature and achieved the maximum value at 150 degrees C, followed by a decrease in sensitivity with further increase of the operating temperature. The sensitivity was about 35 % for 50 ppm NO2 at 150 degrees C with rapid response time of 6 s. T90 and T10 recovery time was 97 s at this gas concentration.
EN
The tin metal could be retractable from wasted tin scrap, sludge, and wasted electroplated solution hydrometallurgical treatment, and purification process. In order to be used as resource of electronic devices, the retracted crude metal should be purified to the extent of higher than 99.9%. In this study, tin electro-refining process was performed to purify the casted tin crude metal at various experimental conditions: at the current density of 3, 5A/dm2, and in various electrolytes such as hydrochloric acid, sulfuric acid and methansulfonic acid. Additional experiment was conducted using Rotating Disk Electrode (RDE) in order to investigate the rate determining step of tin electro-refining process. The current efficiency, 65.6%, was achievable at the condition of current density, 5A/dm2, and in the electrolyte of Hydrochloric acid. During tin electro-refining process, impurity dissolved from tin crude metal into the electrolyte was analyzed using Inductively Coupled Plasma Optical Emission Spectrometer (ICP-OES), and the result showed the concentration of impurity metal gradually increased. Quantitative analysis on casted tin crude metal showed that it consists of tin with 93.9 wt.% and several impurity metals of Ag, Bi, Pb, Cu, and etc. After tin electro-refining process, the purity of tin increased up to 99.985 wt.%.
EN
In order to fabricate graphite nanosheets from graphite flakes, edge-functionalized graphite nanosheets were prepared by a functionalization method using phthalic acid as the molecule to be grafted. A polyphosphoric acid/P2O5 solution containing graphite and phthalic acid were heated at different temperatures for 72 h in a nitrogen atmosphere. It was confirmed by transmission electron microscopy and atomic force microscopy that the resultant phthalic acid-functionalized graphite nanosheets had a large surface area of 20.69 μm2 in average and an average thickness of 1.39 nm. It was also found by X-ray diffractometry and Fourier transform infrared spectroscopy (FT-IR) analysis that the functionalization caused the formation of C=O bonds at the edges of the graphite nanosheets. The yield from this functionalization method was found to be dependent on the reaction temperature, only when it is between 70 and 130°C, because of the dehydration of phthalic acid at higher temperatures. This was confirmed by FT-IR analysis and the observation of low thermal energies at low temperatures.
EN
The movement of people can be considered as the flow of liquid, so we can use the methods employed for the flow of liquid to understand the motion of a crowd. Based on this, we present a novel framework for abnormal behavior detection in crowded scenes. We extract a topological structure from the crowd with the topology simplification algorithm. However, a conventional topology simplification algorithm can not work well if we apply it to the crowd directly because there is too much noises produced by the random motion of the people in the original image. To overcome this, we make a step forward by optimizing this model using Particle Swarm Optimization (PSO) to perform the advection of particle population spread randomly over the image frames. Then we propose two new methods for analyzing the boundary point structure and extraction of a critical point from the particle motion field; both methods can be used to describe the global topological structure of the crowd motion. The advantage of our approach is that each kind of abnormal event can be described as a specific change in the topological structure, so we do not need construct a complex classifier, but can classify the crowd anomalies dynamically and directly. Moreover, the approach monitors the crowd motion macroscopically, making it insensitive to the motion of an individual, disregarding the global movement. The result of an experiment conducted on a common data set shows that our method is both precise and stable.
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