{"title":"A New Feature Extraction Based on Linear Support Vector Regression","authors":"Yu Zhefu, Huibiao Lu, Chuanying Jia","doi":"10.1109/FBIE.2008.66","DOIUrl":"https://doi.org/10.1109/FBIE.2008.66","url":null,"abstract":"At first, a linear support vector regression feature extraction algorithm was introduced concisely. Then two improvements were presented in order that a simply explicit nonlinear regress function can be gotten easily by SVR feature extraction. One improvement was to decrease the dimensions of input space at the expense of regression function accuracy. Another improvement was to map the linear space to polynomial space corresponding to input features. The order of polynomial space depends on practical applications. Experimental result showed the efficiency of the improvements.","PeriodicalId":415908,"journal":{"name":"2008 International Seminar on Future BioMedical Information Engineering","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-12-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116811594","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 of OFDM System for PLC in UCM Based on Precoder Algorithm","authors":"F. Cheng, Tao Qi, S. Wei, Jialin Cao, Yimin Chen","doi":"10.1109/FBIE.2008.58","DOIUrl":"https://doi.org/10.1109/FBIE.2008.58","url":null,"abstract":"In this paper, the channel of the Underground Coal Mine (UCM) PLCs is analysis, which indicates the UCM PLCs is more complex than home PLCs and this channel can be described with multi-path characteristics and strong noise interference characteristics. In conventional OFDM systems a concatenation of Viterbi and Reed Solomon forward error correction with interleaving is used to improve BER performance. But in this channel there are some spectral nulls which make the receiver can not recover the original signal. Accurate modulation should be adopted. Conventional OFDM and precoder OFDM are compared by focusing on one important aspect: BER performance. It will be shown that, for the case of the UCM power line channel, precoder OFDM offers substantial advantages over conventional OFDM. Precoder OFDM is proposed to use in UCM PLCs.","PeriodicalId":415908,"journal":{"name":"2008 International Seminar on Future BioMedical Information Engineering","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-12-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114308046","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 Research of SVM Introjecting Fuzzy Theory in Image Affective Recognition","authors":"Junjie Chen, Dawei Zhang, Haifang Li","doi":"10.1109/FBIE.2008.69","DOIUrl":"https://doi.org/10.1109/FBIE.2008.69","url":null,"abstract":"This paper introduces FSVM, which introjects fuzzy theory to SVM, achieves a classification system which classifies image layer by layer to affective semantic level by FSVM, and proposes one kind of image affective semantics classification method. The difficulty is to establish a mapping from image features to image affective semantics and how to select fitting membership function to test image semantic class. The experimental result shows that the system is simple, fast, effective, and so on, therefore our system is proved to be successful in promoting the image semantic classification to affective semantic level.","PeriodicalId":415908,"journal":{"name":"2008 International Seminar on Future BioMedical Information Engineering","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-12-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131292623","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":"Application of Genetic Algorithm on Remanufacturing Reverse Logistics Network Model","authors":"B. Yan, Danyu Lee","doi":"10.1109/FBIE.2008.107","DOIUrl":"https://doi.org/10.1109/FBIE.2008.107","url":null,"abstract":"For the goal of energy-saving and environmental protection and increasing the re-utilization of recycling products for enterprises, the paper discusses an open-loop remanufacturing reverse logistics network which has a location selection of two layers, then constructs a mixed integer linear programming model to achieve the overall minimum cost including the freight between nodes, the fixed cost, the disposal cost and operation cost of storage and demolition nodes and remanufacturing centers, the penalty cost of the unmet or remaining demand quantity, as well as the operating subsidy of recycling product from government for dealing with environmental protection. According to the characteristics of the model, the paper uses two ways to solve the problem which are Lingo and adaptive genetic algorithm based on Matlab, and then provides an instance where solution steps and results analysis are given, which verifies the feasibility of applying adaptive genetic algorithm on the reverse logistics network model.","PeriodicalId":415908,"journal":{"name":"2008 International Seminar on Future BioMedical Information Engineering","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-12-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128251051","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 a Combined Neural Networks Prediction Model for Urban Traffic Volume","authors":"Zheng Zhou, Kun Huang","doi":"10.1109/FBIE.2008.15","DOIUrl":"https://doi.org/10.1109/FBIE.2008.15","url":null,"abstract":"Urban traffic and transportation problems have become the main problem in the way of urban development. In order to resolve prediction problem of traffic volume, firstly, time series of traffic volume are reconstructed in the phase space in this paper, and correlative information in the traffic volume are extracted richly, then two-stage prediction system for traffic volume is applied: the first stage contains two parallel improved Elman neural networks, which are trained by standard back propagation algorithm, the second stage mixes prediction results of the first stage, which is trained by Karmarkarpsilas linear programming. Real example shows that predicted result of this method is famous, and this method has biggish applied potentials in the region of traffic control.","PeriodicalId":415908,"journal":{"name":"2008 International Seminar on Future BioMedical Information Engineering","volume":"48 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-12-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128088083","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 Interactive Segmentation of Medical Image Series","authors":"Wu Bingrong, Xie Mei","doi":"10.1109/FBIE.2008.96","DOIUrl":"https://doi.org/10.1109/FBIE.2008.96","url":null,"abstract":"In this paper, an algorithm based on the combination of the Canny operator and the morphology method is proposed for the semiautomatic segmentation of medical image series. Firstly, Canny operator is used to extract the whole accurate edges in the medical image series. Then find some object edge with the user interaction. And obtain the closed object edge by using the morphology methods of end point extraction, searching breakpoint, connecting breakpoints, removing burr and so on. Next, carry out expansion for the current object edge and make the expansion result as the location of object contour in the adjacent slice. With the same morphology methods, the closed object edge in the adjacent slice could be obtained automatically. Finally, make some interactive modification for the medical image series. Experiment shows that this algorithm can obtain the boundary of the desired object from a series of medical image quickly and reliably with only little user intervention.","PeriodicalId":415908,"journal":{"name":"2008 International Seminar on Future BioMedical Information Engineering","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-12-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126475914","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 Design on the Multi-temperature Testing System Based on the Laview","authors":"ChangQing Cai, Wei-jie Zhang","doi":"10.1109/FBIE.2008.121","DOIUrl":"https://doi.org/10.1109/FBIE.2008.121","url":null,"abstract":"The paper introduced a data acquisition system which is based on virtual instruments technology. The data acquisition system can not only obtain the spot signal speedily and accurately, but also can finish data acquisition, data real-time display, data conservation and the display of change tendency. The system I divided into two parts: the top machine is controlled by single chip machine; the bottom machine displays the data and saves the data with LabVIEW which is belonged to National Instruments.","PeriodicalId":415908,"journal":{"name":"2008 International Seminar on Future BioMedical Information Engineering","volume":"59 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-12-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127781446","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":"Application of Matlab in Moving Object Detecting Algorithm","authors":"Xiao Chen","doi":"10.1109/FBIE.2008.108","DOIUrl":"https://doi.org/10.1109/FBIE.2008.108","url":null,"abstract":"Moving object detecting is one of the current research hotspots and is widely used in fields such as computer vision and video processing. The study on image processing toolkit using computer language Matlab was conducted to perform moving object detecting technical processing on video images. First, video pre-processing steps such as frame separation, binary operation, gray enhancement and filter operation were conducted. Then the detection and extraction of moving object was carried out on images according to frame difference-based dynamic-background refreshing algorithm. Finally, the desired video image was synthesized through adding image casing on the moving objects in the video. The results showed that using computer language Matlab to perform moving object detecting algorithm has favorable effects.","PeriodicalId":415908,"journal":{"name":"2008 International Seminar on Future BioMedical Information Engineering","volume":"55 8","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-12-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133651437","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":"A New Kind of Super-Resolution Reconstruction Algorithm Based on the ICM and the Bilinear Interpolation","authors":"Zhang Xiang-guang","doi":"10.1109/FBIE.2008.44","DOIUrl":"https://doi.org/10.1109/FBIE.2008.44","url":null,"abstract":"Super-resolution reconstruction of image is highly dependent on the data outliers. This work addresses the super-resolution reconstruction design of the Intersecting Cortical Model (ICM) algorithm applied to the bilinear interpolation. Based on a simplification of the Pulse-Coupled Neural Network (PCNN), we propose a design strategy to reduce the effects of outliers on the reconstructed image. Intersecting Cortical Model (ICM) has gained widely research as a new artificial neural network. It derives directly from the studies of the small mammal's visual cortex. The theory analysis and the simulation experiments of the image processing indicate that this kind of super-resolution reconstruction algorithm can not only reduce the effects of outliers effectively but also keep the details of the image sufficiently.","PeriodicalId":415908,"journal":{"name":"2008 International Seminar on Future BioMedical Information Engineering","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-12-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130402070","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":"Tracking Differentiator in the Application of Signal Processing and Theory Research","authors":"Ma Zhonghua","doi":"10.1109/FBIE.2008.57","DOIUrl":"https://doi.org/10.1109/FBIE.2008.57","url":null,"abstract":"In this paper, we bring out the theory study result of tracking differentiator and example for signal processing. Tracking differentiator has the quality that does not rely on the presumed state equations when tracking projects, for further application nonlinear tracking differentiator is developed here. And with an example, we prove that the nonlinear tracking differentiator can track the project effectively and the related theory for the solution is also given.","PeriodicalId":415908,"journal":{"name":"2008 International Seminar on Future BioMedical Information Engineering","volume":"190 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-12-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134268015","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}