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Networks,” IEEE Trans. Med. Imaging. Vol.16, no.6, pp.911-918, December 1997. [36] A.Pitiot, A.W.Toga, N.Ayache, P.Thompson,“Texture Based MRI Segmentation with a Two-Stage Hybrid Neural Classifier,” Proceedings of the 2002 International Joint Conference on Neural Networks.vol.3, pp.2053-2058, 12- 17 May 2002. [37] Wu Y, Giger ML, Doi K et al,“Artificial Neural Network in Mammography: Application to Decision Making in the Diagnosis of Breast Cancer,” Radiology. Vol.187, pp.81- 87, April 1993. [38] Tourassi GD, Floyd CE Jr,“Artificial Neural Networks for Single Photon Emission Computed Tomography,” Invest Radiol. Vol.28, no.8 , pp.671-677, August 1993. [39] Maclin PS, Dempsey J,“Using Artificial Neural Networks to Diagnose Hepatic Masses,”Journal of Medical Systems. Vol.16, no.5, pp.215-225, October 1992. [40] Wolberg WH, Sreet WN, Mangasarian OL,“Image Analysis and Machine Learning Applied to Breast Cancer Diagnosis and Prognosis,” Anal Quant Cytol Histol. 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Doi,“Effect of a Small Number of Training Cases on the Performance of Massive Training Artificial Neural Network (MTANN) for Reduction of False Positives in Computerized Detection of Lung Nodules in Low-Dose CT,” In Proc. SPIE (Medical Imaging). Vol.5023, pp.1355-1366, July 2003. [45] K. Suzuki and K. Doi,“Characteristics of a Massive Training Artificial Neural Network (MTANN) in the Distinction Between Lung Nodules and Vessels in CT images,” in Computer Assisted Radiology and Surgery (CARS), Chicago, IL, pp.923–928, 2004. [46] H. Arimura, S. Katsuragawa, K. Suzuki, F. Li, J. Shiraishi, S. Sone, and K. Doi,“Computerized Scheme for Automated Detection of Lung Nodules in Low-Dose CT Images for Lung Cancer Screening,” Acad. Radiol. Vol.11, no.6, pp.617-629, June 2004. [47] K. Suzuki, J. Shiraishi, H. Abe, H. MacMahon, and K. 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ISBN 978-952-5726-09-1 (Print) Proceedings of the Second International Symposium on Networking and Network Security (ISNNS ’10) Jinggangshan, P. R. China, 2-4, April. 2010, pp. 027-030 Research and Application of Auto-profiling Control Algorithm for 0Cr18Ni10Ti Qiang Wang 1 , XuGuang Min 2 , ZhongYue Xiao 1 , and Yanhui Zhou 1 1 Jinggangshan University, Ji’an, China Email: wangqiang2188@tom.com 2 Jiangxi Science&Technology Normal University, Nanchang, China Abstract—The paper analysis the material composition, properties and application technology of 0Cr18Ni10Ti , and it is an understanding of the material’s mechanical properties and corrosion-resistance. The using of stabilization heat treatment process, solution heat treatment, controlling the chemical composition and production process conditions, etc. improved the overall performance of 0Cr18Ni10Ti and the capacity of arain boundary corrosion resistance.Method of the multi-punching process and profiling&following control algorithm processing is then established and controlled to the machining ration speed, tool feed and cutting depth,which achieves better results. The practical application indicates that producing the flexible laminated membrane coupling by using 0Cr18Ni10Ti makes the coupling highly efficient and reliable in transmission, lighter, easier to assemble/disassemble, easier to machine and less costly, and thereby that such an application is noticeably superior than those of traditional materials. It guarantees product quality and increased work efficiency. Index Terms—control algorithm; 0CrNi10Ti; Coupling Disk; Solution Heat Treatment; Stabilization Treatment I. INTRODUCTION Stainless steel, one of the greatest inventions in 20th century, covers a range of more than 300 steels. Materials under this category are widely used for their excellent corrosion- and erosion-resistance features and their high comprehensive performances, and consequently they include nearly all steels for special purpose. How the steels are corrosion-resistant is decided by the alloy elements contained in them, which resist faintly corrosive media including water, steam and air as well chemical erosive media like acid, alkali and salt. Chromium (Cr) is a basic element in stainless steels that works against corrosion. When chromium content in steel reaches at some 12%, the element reacts with oxygen in corrosive medium and develops a thin oxide film on the surface which prevents further corrosion in substrate. Among the steels of various substrates, ferritic stainless steel, containing chromium between 12% and 30%, possesses good corrosion-resistance, tenacity and solderability, all of which increase along with higher chromium content, and it behaves better than other stainless steels in resistance to chloride stress corrosion. Martensitic stainless steel is of high strength but of poor plasticity and solderability. Whereas Austenitic stainless steel contains chromium more than 18% in content and nickel about 8% and trifle of molybdenum, titanium, nitrogen © 2010 ACADEMY PUBLISHER AP-PROC-CS-10CN006 27 and other elements. This metal, combining merits of austenitic steel and ferritic stainless steel, is of desirable comprehensive performances and resistance to multiple corrosions, in addition to its superplasticity. One typical member of this family is 0Cr18Ni10Ti. By using the profiling&following control algorithm processing and controlled to the machining ration speed, tool feed and cutting depth,which achieves better mechanical processing results. II. OVERVIEW OF 0CR18NI10TI 0Cr18Ni10Ti, also called as SS321, is a kind of chromium-nickel austenite stainless steel in series 300. Besides chromium, as is known, stainless steel is often made with alloy elements like nickel, molybdenum, titanium, niobium, copper, nitrogen and others, which are added in to meet the requirements of proper use in different situations and of good machining properties. For instance, steel with trifle sulfur and phosphor is easier to be machined, that with molybdenum given a special structure which is corrosion-resistant and thus usable in food industry and medical operation apparatus industry. The 0Cr18Ni10Ti is one of the most used stainless steel. It is of performances similar to 0Cr18Ni9 except that the former contains titanium, which is added to restrain the precipitation of (Cr, Fe) 23C6 at the grain boundaries and reduce the intergranular corrosion possibility, thus enhancing the material in its weld corrosion-resistance. Thanks to its excellent mechanical properties and anti-corrosion performances, the material is widely used across industries. A. Compositions The material is defined with a broad range of chemical elements, as shown in Table I. However, rigid control of its chemical composition is significant. As Cr, Ni and Ti elements are vital to the resistance to intergranular corrosion, the chemical composition in the steel should be determined specifically according to the operational requirements of parts made from it and to the conditions of processing equipments. In case that the material is to be used for welding, some ferrite retained in the steel is helpful to improve its welding performance. Then the content of ferrite should be properly figured out in procedure of composition decision, where Fisher Phase Diagram is used to determine the as-cast ferrite content based on nickel equivalent and chromium equivalent. The chemical elements possibly contained in 0Cr18Ni10Ti
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distance of view point. Given that
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Ⅳ. EVALUATION OF BLENDED LEARNING
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symmetric with respect to the origi
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each sample belongs to each categor
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A. Data Preparing To generate our t
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oth α and β . determination of Qu
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Strong earthquake 0.1< M L
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indirect causes, and the logical re
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egression. Granger causality test i
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B. Evaluation We have evaluated thi
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used as a source and neighboring ce
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Figure 3. Drainage networks generat
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Combinational logic unit failures i
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Tabal.1 Combinational fault logic t
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under the endorsement of both the m
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TABLE I. DESCRIPTION OF PROPOSITION
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Figure 2. The process of the invers
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Figure 9. (a)the original image.(b)
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In order to reduce to the number of
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that studying being going to be to
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Reference[10] analyzed the evolutio
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module, communication module, apper
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After the comprehensive performance
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system testing can be seen that the
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III. AUTONOMIC RESOURCE ALLOCATION
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The QoE i (T i ) is the ith user’
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nodes will be formed one cluster, t
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Where n is the number of data point
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Keyboard event Application User mod
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SQL Azure will eventually include a
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The nodes in the suffix tree are dr
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[3] Y. Li, S. M. Chung, and J. D. H
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some drilling fluid produces hydrog
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"normalization", whose membership b
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and minimum structural elements in
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esults of the spatial transform par
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B. Research on protocol actions Com
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ACKNOWLEDGMENT This work is funded
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A. Problem Description In a small b
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[4] Huang, Hung, and J. Y. jen Hsu.
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Further by calculating, the followi
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TABLE II. THE CONCENTRATION BETWEEN
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private key that obtained by using
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ontology, and the domain dictionary
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Eq.4 is NP-hard and can be solved b
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Where: G i is the selection field o
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If there is X j in a generation, wh
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Theorem 2.4([10]). Let L 1 and L 2
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The relation between the lattice im
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Figure 2. Example of single-step de
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evocation and the fourth group stor
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focused mainly on rule-based forms
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Ⅵ. CONCLUSION Figure 6. The Flask
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EDCF in comparison with DCF, has so
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B. Simulation results and analysis
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in routing table. When search resou
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others through the selective emotio
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such as weather information, techno
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the opening window, a related page
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1) Process context storage areas. I
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V. CONCLUSION In this thesis, sCPU-
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main types of horizontal search env
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Enterprise Portal security provides
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() t = [ S () t S () t ] T N S ,...
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[2] Kumaravel, N., and Kavitha, V.,
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output, so BP network has been wide
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input to the artificial neural netw
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(2) In a process (tokens from outsi
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The reduction process consists of t
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all eight normal vectors are identi
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is B object , and the number of emp
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xi, j y' = εα ( (1 + tanh( )) −
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Error 8000 7000 6000 5000 4000 3000
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Architecture (AMBA) a new bus archi
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In order to ensure the smooth proce
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In this paper, we adopt two Sobel o
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four layers.The far right of the gr
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TABLE II. OPERATIONAL EMPLOYEE TABL
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A. Object-relational Type To audit
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to execution time. Also, DBA would
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Liping Chen .......................
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