{"title":"Effects of temperature and orientation on 3.2mm radar backscattering from ice crystals","authors":"Juxiu Wu, Ming Wei, Jie Zhou, Jinhu Wang","doi":"10.1109/ICACI.2012.6463266","DOIUrl":"https://doi.org/10.1109/ICACI.2012.6463266","url":null,"abstract":"Millimeter wave radar signals depending on backscattering characteristics of particles and particles size distribution can be used to inverse the microphysical parameters of clouds, but ice clouds are composed of non-spherical ice crystals, so various factors of impacting on the scattering from non-spherical particles must be considered. However, there are few papers that account for the influence of temperature and orientation on the backscattering characteristics of hexagonal ice crystals with 3.2mm radar in detail. The effects are investigated by modeling the discrete dipole approximation (DDA) method in this paper. At vertical radar wave, the value of backscattering cross sections of hexagonal ice crystals with horizontal orientation (2D) is twofold more than random orientation (3D). With the antenna elevation angle increases, there is a large increase of radar cross sections for hexagonal columns, but a slight change for hexagonal plates with 2D. The contributions from orientations must be considered in calculating scattering characteristics of non-spherical ice crystals. Backscattering cross sections change slightly about 2.75% when the temperature changes from 0° to 173°. It should also be noted that aspect ratio has a large impact on radar cross sections. Such calculations can extend scattering characteristics database of ice particles. In this paper, we provide some ideas for exploring the scattering from ice crystal and theoretical basis for using the 3.2mm radar echo to inverse the characteristics of clouds.","PeriodicalId":404759,"journal":{"name":"2012 IEEE Fifth International Conference on Advanced Computational Intelligence (ICACI)","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131627939","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"The shape edge measure of automobile airbag based on image processing","authors":"Mujun Xie, Peng Gao, Zhiqiang Wang, Yuan-chun Li","doi":"10.1109/ICACI.2012.6463253","DOIUrl":"https://doi.org/10.1109/ICACI.2012.6463253","url":null,"abstract":"At present, micrometer is used for measure the shape edge of automobile airbag. There are some shortcomings in this method. The number of test points is limited. Test data is not comprehensive. Detection speed is slow and a fixture can only test a kind of airbag. The method of airbag shape edge detection based on image processing is researched in this paper. The image of airbag is collected by CCD, and then it is sent to the computer to be processed and segmented. The edge of image is extracted through Canny edge detection algorithm in order to acquire shape edge of airbag in this paper, and the image similarity degree are calculated to provide the information of matching in the template matching process. Finally the comprehensive test shape edge of airbag is realized. The experimental results show that the detection method is effective feasible, intuitive and clear.","PeriodicalId":404759,"journal":{"name":"2012 IEEE Fifth International Conference on Advanced Computational Intelligence (ICACI)","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131285918","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Getting scale-free network from a small world network without growth","authors":"Guangping Chen, Jiabo Hao, Zhiyuan Zhang, Yumei Tang","doi":"10.1109/ICACI.2012.6463112","DOIUrl":"https://doi.org/10.1109/ICACI.2012.6463112","url":null,"abstract":"A method that can be used to get scale-free network from a small-world network without growth under the mechanism of preferential attachment is proposed. Unlike the normal BA growth network model, in our model we remove an old node with a probability scaling with the degree of the node before adding a new node into the network, that make the size of the network fixed, but the nodes and edges are not fixed. If an old node has less degree, it has a larger probability to be removed, and its edges are deleted at the same time. It is found that the degree distribution based on our model obeys a form like power-law of BA model, but the scope of degree distribution in our model is much smaller than BA model. Therefore, the degree distribution's heave tail in our model is thinner than that in the normal BA model; thus it is different from the normal BA model. Meanwhile, there are some other properties in our model, for instance, the average clustering coefficient decreases with the renewed ratio and the power-law exponent increases with the renewed ratio to a limited value, which is equal to that in the normal BA model.","PeriodicalId":404759,"journal":{"name":"2012 IEEE Fifth International Conference on Advanced Computational Intelligence (ICACI)","volume":"41 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131320725","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"An improved sequence-based indoor localization algorithm in WSNs","authors":"Ying Yu, Lingyun Yuan, Yulan Kuang","doi":"10.1109/ICACI.2012.6463306","DOIUrl":"https://doi.org/10.1109/ICACI.2012.6463306","url":null,"abstract":"Sequence-based localization is a novel RF localization technique. The algorithm is achieved by constituting RSSI-based constraint tables and comparing data between two tables. But, the definitions of the constraint relation and the centroid in the algorithm are imperfect. In this paper, we present a new sequence localization method that involves with correlation metric and centroid. First, we use rank order correlation coefficient instead of constraint tables. It simplifies the algorithm implementation. Furthermore, the definition of centroid is amended according to the nearest location regions. It makes the algorithm more reasonable, especially in the edge of the localization area. The simulation shows that the time-consumption and the localization accuracy of the new algorithm are improved.","PeriodicalId":404759,"journal":{"name":"2012 IEEE Fifth International Conference on Advanced Computational Intelligence (ICACI)","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133769191","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Non-uniform mode-pursuing sampling method based on multivariate multimodal distribution model","authors":"Hua Su, Liangxian Gu, Chun-lin Gong","doi":"10.1109/ICACI.2012.6463175","DOIUrl":"https://doi.org/10.1109/ICACI.2012.6463175","url":null,"abstract":"A non-uniform distributing based mode-pursuing sampling method on black-box problem is proposed for the computation-intensive global optimization problem. The multivariate multimodal distribution model is established based on the expensive sample points of original optimization problem, which is controlled by the convergence principle of multiple correlation coefficient through variance of probability distribution. More design points are generated progressively around the current optimal regions and constitute the non-uniform discrete design space. Non-uniform sampling strategy changes the uniform distributing characteristic of design space, improves the utilization efficiency of design points and strengthens the distribution rationality of discrete design space. Analytical and numerical test results show that the improved method is more efficient and accurate than standard mode-pursuing sampling method and traditional algorithms, and has broad prospects for the expensive black-box problem.","PeriodicalId":404759,"journal":{"name":"2012 IEEE Fifth International Conference on Advanced Computational Intelligence (ICACI)","volume":"62 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115414981","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Research on the algorithms and key factors in optimizing supply chain inventory","authors":"Min Wu, Kongyu Yang","doi":"10.1109/ICACI.2012.6463200","DOIUrl":"https://doi.org/10.1109/ICACI.2012.6463200","url":null,"abstract":"The paper reviews the technology and methods used in optimizing supply chain inventory, and summarizes the common inventory optimization algorithms - the mathematical analysis and heuristic algorithms. At last, it points out the several key factors of optimizing supply chain inventory - the lead time, the credit of enterprises and the fuzzy level of some parameters during the optimization process, and indicates its trends.","PeriodicalId":404759,"journal":{"name":"2012 IEEE Fifth International Conference on Advanced Computational Intelligence (ICACI)","volume":"103 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124174326","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"An incremental learning algorithm for improved least squares twin support vector machine","authors":"Ling Yang, Kai Liu, Xiaodong Liang, Tao Ma","doi":"10.1109/ICACI.2012.6463207","DOIUrl":"https://doi.org/10.1109/ICACI.2012.6463207","url":null,"abstract":"In this paper, we mainly propose an incremental version of improved least squares twin support vector machine (IILSTSVM), based on inverse matrix-free method. This algorithm can meet the requirement of online learning to update the existing model. In the case of low dimension data, this method effectively improves training speed of incremental learning. According to updating inverse matrix, we can implement the incremental learning for ILSTSVM. Experiments prove that this algorithm has excellent performance on runtime and recognition rate in the low dimensional space.","PeriodicalId":404759,"journal":{"name":"2012 IEEE Fifth International Conference on Advanced Computational Intelligence (ICACI)","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117245190","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
E. Jiang, P. Zan, Suqin Zhang, Xiaojin Zhu, Y. Shao
{"title":"Optimal wavelet packet decomposition for rectal pressure signal feature extraction","authors":"E. Jiang, P. Zan, Suqin Zhang, Xiaojin Zhu, Y. Shao","doi":"10.1109/ICACI.2012.6463367","DOIUrl":"https://doi.org/10.1109/ICACI.2012.6463367","url":null,"abstract":"The method of optimal wavelet packet decomposition is proposed for rectal pressure signal feature extraction. By using wavelet packet algorithm, the mean wavelet coefficients and its corresponding energy component with high separability are selected as the feature vector according to the maximum separation degree of Fisher index, and the optimal features vector have specific sub-band wavelet packet coefficients and energy with higher separability. By comparison of the classification result and the operation time of optimized and non-optimized features vectors, the experimental results give the evidence that the proposed method is effective.","PeriodicalId":404759,"journal":{"name":"2012 IEEE Fifth International Conference on Advanced Computational Intelligence (ICACI)","volume":"219 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123925874","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Hengde Zhang, Zhiping Zong, Cong Hua, Yani Zhang, Bihui Zhang
{"title":"Comparative analysis of two sandstorm processes caused by Mongolian cyclone","authors":"Hengde Zhang, Zhiping Zong, Cong Hua, Yani Zhang, Bihui Zhang","doi":"10.1109/ICACI.2012.6463267","DOIUrl":"https://doi.org/10.1109/ICACI.2012.6463267","url":null,"abstract":"Two sandstorm processes caused by Mongolian cyclone were comparatively analyzed and diagnosed. The first process occurred during 19-22 March 2010 (case 1) and the second one during 28-30 April 2011 (case 2). The result showed that case 1 had wider range, stronger intensity and longer duration than case 2. Mongolian cyclones and upper cold vortex were main causes of these two cases. The cold front moved more southeastward and covered a larger area with stronger northerly wind in case 1. And the greater pressure gradient between cyclone center and high-pressure center was also contributed to the wider and stronger dust weather. Besides, secondary cold-front and supplemental cold air were propitious to the long-lasting dust weather. Vertical velocity was a good indication to sandstorms, and the upward motion area in case 1 was significantly larger than case 2. Helicity distribution demonstrated strong upward vortex motion which was helpful in sand rising at middle and lower troposphere, and the helicity in case 1 was more obvious. Cold advection and momentum downwash contributed to the intensification of surface pressure, cold high and pressure gradient, which leaded to stronger ground transformer wind and was favorable to the occurring of sandstorm. Case 1 had more obvious momentum downwash and transformer wind in the two cases. The decline of Ri along with increasing vertical wind shear and unstable stratification aroused and downstream transferred the sandstorm.","PeriodicalId":404759,"journal":{"name":"2012 IEEE Fifth International Conference on Advanced Computational Intelligence (ICACI)","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128180064","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Performance analysis of the graph-partitioning algorithms used in OpenFOAM","authors":"Miao Wang, Yuhua Tang, Xiaowei Guo, Xiaoguang Ren","doi":"10.1109/ICACI.2012.6463129","DOIUrl":"https://doi.org/10.1109/ICACI.2012.6463129","url":null,"abstract":"OpenFOAM is a widely used opensource CFD application. Based on mesh partitioned, applications can run in parallel to achieve better performance in OpenFOAM. When mesh generated from the liquid field is large, performance of partitioning algorithms will heavily affect the execution efficiency of the whole application. In this paper, we investigate the four partitioning algorithms implemented in OpenFOAM-Simple, Hierarchical, Scotch and Metis and analyze their performance. Performance evaluation includes partitioning time, communication overhead, quality of load balancing and application's parallel execution time based on the experiment of LinearPTT with 34,800,000 cells on Tianhe-1A. The results show that Scotch spends the most time on partitioning and Metis' partitioning time remains steady when the number of processors increases. Both Scotch and Metis introduce less communication overhead than Simple and Hierarchical. Scotch does better in balancing the cells among processors than Metis. When scales of meshes and numbers of processors increase, only Scotch and Metis are practicable with acceptable performance. But their partitioning efficiency still needs a betterment.","PeriodicalId":404759,"journal":{"name":"2012 IEEE Fifth International Conference on Advanced Computational Intelligence (ICACI)","volume":"43 4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128901369","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}