{"title":"Image Segmentation Method with Positron Emission Tomography Time Sequence Images","authors":"Chih-Yu Hsu, Y. Lai, Chih-Cheng Chen, Yu-Tzu Lee","doi":"10.1109/IBICA.2011.96","DOIUrl":"https://doi.org/10.1109/IBICA.2011.96","url":null,"abstract":"Positron emission tomography(PET)images are often used to detect physiology function.However,PET images have more blurs than anatomic images,such as magnetic resonance imaging(MRI)and computed tomography(CT).With the graylevel of PET images,Doctors need to manually obtain the region of interest(ROI).THis paper presents a PET image segmentation technology based on the wavelet theory.Through sampling,recombination,and fetching the thresholds of images,theimage segmentation with 1960 dynamic PET images of abdominal organs were conducted. Compared with a sigle PET image, the image segmentation technology proposed can accurately and rapidly identify the boundaries of organs,such as the small intestines,the liver,and the kidney,as well as efficiently provide the ROI information for doctors.","PeriodicalId":158080,"journal":{"name":"2011 Second International Conference on Innovations in Bio-inspired Computing and Applications","volume":"117 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121054943","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 Optimization of Reconfigurable Manufacturing Cell with Flexible Routing Capacity in Presence of Unreliable Machines","authors":"Wan-Ling Li, Muhammed Hafidz Fazli, T. Murata","doi":"10.1109/IBICA.2011.58","DOIUrl":"https://doi.org/10.1109/IBICA.2011.58","url":null,"abstract":"The paper is presented an approach of preventive maintenance that improves and enhances downside production efficiencies based on the non-stop maintenance. The approach focuses on reconfiguration and rerouting; besides, to prepare alternative configurations according to different reliability for each machine. In addition reliable probability of machines, there exist critical factors such as intercellular part movement, machine reallocation, machine utilization, part loading/unloading, and alternative routings that affect seriouslyproduction result. The important point that the so-greatperformance of my approach compared to others (e.g.machines are stopped to maintain) would be offset by theadvantages in terms of flexibility and limited use of resources.There are two objectives as follows, to achieve a condition ofnonstop maintenance, and to decrease drop of theperformances. Furthermore, the approach meaningfully notonly enhances production capabilities but also intelligentlyeliminate unexpected events. Finally, the impact of anapproach is illustrated through a small example.","PeriodicalId":158080,"journal":{"name":"2011 Second International Conference on Innovations in Bio-inspired Computing and Applications","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127602600","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 Real Time Personal Identification Based on Fourier Transform of Palmprint Recognition","authors":"Shunyu Yang","doi":"10.1109/IBICA.2011.89","DOIUrl":"https://doi.org/10.1109/IBICA.2011.89","url":null,"abstract":"In this paper, we propose a real time personal identification based on Fourier transform for palm-print recognition. An auto hand gesture segmentation method is proposed in the paper and after the segmentation, a modified Fourier transform are used for the image processing. Machine leaning based trainings are used to get the palm print trait database. At last, performances are shown for theidentification.","PeriodicalId":158080,"journal":{"name":"2011 Second International Conference on Innovations in Bio-inspired Computing and Applications","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133896861","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 Intrusion Detection Based on an Improved K-means Algorithm","authors":"Shenghui Wang","doi":"10.1109/IBICA.2011.72","DOIUrl":"https://doi.org/10.1109/IBICA.2011.72","url":null,"abstract":"Traditional machine learning methods for intrusiondetection can only detect known attacks since these methodsclassify data based on what they have learned. New attacks areunknown and are difficult to detect because they have notlearned. In this paper, we present an improved k-meansclustering-based intrusion detection method, which trains onunlabeled data in order to detect new attacks. The result ofexperiments run on the KDD Cup 1999 data set shows theimprovement in detection rate and decrease in false positiverate and the ability to detect unknown intrusions.","PeriodicalId":158080,"journal":{"name":"2011 Second International Conference on Innovations in Bio-inspired Computing and Applications","volume":"61 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128147101","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}
Chao-Ho Chen, Tsong-Yi Chen, Jeremy Lin, Da-Jinn Wang
{"title":"People Tracking in the Multi-camera Surveillance System","authors":"Chao-Ho Chen, Tsong-Yi Chen, Jeremy Lin, Da-Jinn Wang","doi":"10.1109/IBICA.2011.5","DOIUrl":"https://doi.org/10.1109/IBICA.2011.5","url":null,"abstract":"This paper is dedicated to people tracking and identification in the multi-camera surveillance system. In the proposed method, each people-image is extracted among each camera and then is labeled with its color vector. Color vector provides a similar probability for each person appeared in different camera¡¦s surveillance frame. By combining the pedestrian¡¦s trajectory with relations among different surveillance areas, people identification can be achieved substantially. The experimental results show that the proposed method can effectively track and identify the moving people for normal situations in the multi-camera surveillance system.","PeriodicalId":158080,"journal":{"name":"2011 Second International Conference on Innovations in Bio-inspired Computing and Applications","volume":"54 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133061097","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":"Using the Image Recognition Techniques to Implement an Automatic Examining Mechanism for the Sports Fitness","authors":"C. Tzeng, T. Wey","doi":"10.1109/IBICA.2011.24","DOIUrl":"https://doi.org/10.1109/IBICA.2011.24","url":null,"abstract":"In this paper, a color-based recognition approach is proposed to recognize and track the trajectory of moving object and use this approach for the examining of sports fitness to construct an automatic examining system. The quantity for the specific movements will be measured and counted by this system to substitute for traditional method to eliminate the error due to subjective evaluation. This automatic examining system can reduce the error rates as well as decrease the use of manpower, and to reduce the overall examining time effectively. So, doing the examination of sports fitness by this system in the campus is so easy, convenient, and practical, and it is not rigidly suffer from the manpower issue, the venue and the inconsistent action. It seems from the experimental results, this proposed method can indeed achieve the goal of automatic examining and will be focused on the promotion of the design and application of the overall system","PeriodicalId":158080,"journal":{"name":"2011 Second International Conference on Innovations in Bio-inspired Computing and Applications","volume":"146 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132078159","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":"Image Recognition Based on Kernel Self-Optimized Learning","authors":"S. Bu, Xun-Fei Liu, S. Chu, J. Roddick","doi":"10.1109/IBICA.2011.23","DOIUrl":"https://doi.org/10.1109/IBICA.2011.23","url":null,"abstract":"Image recognition technologies have been used in many areas, and feature extraction of image is key step for image recognition. A novel feature extraction method using kernel self-optimized learning for image recognition. The scheme of image feature extraction includes textural extraction using Gabor wavelet, textural features reduction based on class-wise locality preserving projection with the nearest neighbor graph and common kernel discriminant vector. The nearest neighbor classifier is applied to image classification. The feasibility and performance of the algorithm are testified in the public image databases.","PeriodicalId":158080,"journal":{"name":"2011 Second International Conference on Innovations in Bio-inspired Computing and Applications","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125431306","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":"Design and Realization of Distinctive Data Interface Based on SAP HR System","authors":"Wei Zhou, Xiao-Qian Zhu, Li-Xuan Ye","doi":"10.1109/IBICA.2011.73","DOIUrl":"https://doi.org/10.1109/IBICA.2011.73","url":null,"abstract":"The paper analyzes the situation while the SAP HR system is running independently, its personal information, department information, and the relationship between them need to be referenced by multiple peripheral systems. So the target systems need to synchronize the HR data with SAP periodically. Currently, most databases are accessed directly by ODBC/JDBC, which are much more expensive, except oriented databases. To resolve these problems, the paper introduces a new method , using SAP-SFU-BIMS to be the data interface between SAP HR system and peripheral systems. The result shows that the method can improve the performance while reducing the number of interfaces between SAP system and peripheral systems. It provides a good reference for the design of data transfer interface.","PeriodicalId":158080,"journal":{"name":"2011 Second International Conference on Innovations in Bio-inspired Computing and Applications","volume":"2013 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123828461","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}
Chih-Yuan Lien, Chien-Chuan Huang, Pei-Yin Chen, Hung-Yu Yang
{"title":"An Efficient Denoising Approach for Random-Valued Impulse Noise in Digital Images","authors":"Chih-Yuan Lien, Chien-Chuan Huang, Pei-Yin Chen, Hung-Yu Yang","doi":"10.1109/IBICA.2011.8","DOIUrl":"https://doi.org/10.1109/IBICA.2011.8","url":null,"abstract":"An efficient edge-preserving algorithm for removal of random-valued impulse noise from corrupted images is proposed in this paper. We employ an efficient impulse noise detector to detect the noisy pixels, and an edge-preserving filter to reconstruct the intensity values of noisy pixels. Extensive experimental results show that the proposed technique not only preserves the edge features, but also obtains excellent performances in terms of quantitative evaluation and visual quality. Since our algorithm requires only low computational complexity, it is very suitable to be applied to many real-time applications.","PeriodicalId":158080,"journal":{"name":"2011 Second International Conference on Innovations in Bio-inspired Computing and Applications","volume":"50 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131925839","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}
T. Wey, Te-Hsuan Liu, Min-Chuan Lin, Ruey-Lue Wang, C.-M. Yeh, Chen-Wei Yu, Chen-Fu Lin, H. Tsai, Y. Juang
{"title":"A CMOS Temperature Sensor Using Cascoded PNP Transistors","authors":"T. Wey, Te-Hsuan Liu, Min-Chuan Lin, Ruey-Lue Wang, C.-M. Yeh, Chen-Wei Yu, Chen-Fu Lin, H. Tsai, Y. Juang","doi":"10.1109/IBICA.2011.61","DOIUrl":"https://doi.org/10.1109/IBICA.2011.61","url":null,"abstract":"In this paper, a CMOS temperature sensor using cascaded PNP transistors was designed and measured. The commonly used band gap reference current source, which used bipolar junction transistors (BJTs) to implement output current components with negative and positive temperature coefficients, was adopted to generate a temperature-insensitive reference current source. The base-emitter voltage (VEB), i.e. output voltage, of a PNP BJT under a constant collector biasing current demonstrates a negative temperature coefficient. To enhance sensitivity of transfer characteristics of the output voltage versus temperature, two PNP BJTs under a constant collector biasing current were arranged into a Darlington-pair topology and were used as a temperature sensor. Temperature sensor has the sensitivity of-3.93 mV/„aC with the temperature error of „b0.6„aC or so for the calibrated temperature ranging from-15„aC to 110„aC.","PeriodicalId":158080,"journal":{"name":"2011 Second International Conference on Innovations in Bio-inspired Computing and Applications","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133466367","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}