2011 IEEE Workshop On Merging Fields Of Computational Intelligence And Sensor Technology最新文献

TasteIT Analyzing chemical sensor data using fuzzy logic 用模糊逻辑分析化学传感器数据

2011 IEEE Workshop On Merging Fields Of Computational Intelligence And Sensor Technology Pub Date : 2011-04-11 DOI: 10.1109/MFCIST.2011.5949520

W. Heiden, M. Turek, M. Schöning

引用次数: 0

Robot routing using clustering-based parallel genetic algorithm with migration 机器人路由采用基于聚类的并行遗传算法进行迁移

2011 IEEE Workshop On Merging Fields Of Computational Intelligence And Sensor Technology Pub Date : 2011-04-11 DOI: 10.1109/MFCIST.2011.5949511

Ko-Ming Chiu, Jing-Sin Liu

{"title":"Robot routing using clustering-based parallel genetic algorithm with migration","authors":"Ko-Ming Chiu, Jing-Sin Liu","doi":"10.1109/MFCIST.2011.5949511","DOIUrl":"https://doi.org/10.1109/MFCIST.2011.5949511","url":null,"abstract":"Wireless sensor network (WSN) technology is widely used in environment monitoring, health care, surveillance systems and unmanned space or planet exploration. This paper focuses on routing problems with data gathering by a mobile robot in a WSN, also referred to as a Traveling Salesman Problem with Neighborhoods (TSPN) or NP-hard problem. In this paper, we propose a clustering-based parallel genetic algorithm with migration (CBPGA), so that the mobile robot can gather all data from all sensors and the travel costs of the mobile robot clearly decrease. First, a clustering algorithm is used to effectively reduce the number of visited nodes, especially in situations with dense sensor distributions or large sensing radii. Next, the set of visited nodes is encoded as chromosomes by a chromosome generation algorithm (CGA), and the master-slave parallel genetic algorithm with migration is performed to more efficiently generate the near-optimal route. Lastly, a travel cost-reduction scheme is used to remove redundant travel costs. Simulation results confirm that the clustering-based parallel genetic algorithm with migration more efficiently generates a near-optimal route that reduces the travel costs of a mobile robot in robot routing problems with WSN.","PeriodicalId":378791,"journal":{"name":"2011 IEEE Workshop On Merging Fields Of Computational Intelligence And Sensor Technology","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-04-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116724544","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}

引用次数: 16

Precise indoor localization with low-cost field-programmable gate arrays 精确的室内定位与低成本的现场可编程门阵列

2011 IEEE Workshop On Merging Fields Of Computational Intelligence And Sensor Technology Pub Date : 2011-04-11 DOI: 10.1109/MFCIST.2011.5949513

E. Heinrich, R. Joost, M. Lüder, R. Salomon

引用次数: 3

Intelligent sensing of biomedical signals - Lung tumor motion prediction for accurate radiotherapy 生物医学信号的智能传感。用于精确放射治疗的肺肿瘤运动预测

2011 IEEE Workshop On Merging Fields Of Computational Intelligence And Sensor Technology Pub Date : 2011-04-11 DOI: 10.1109/MFCIST.2011.5949518

K. Ichiji, N. Homma, I. Bukovský, M. Yoshizawa

{"title":"Intelligent sensing of biomedical signals - Lung tumor motion prediction for accurate radiotherapy","authors":"K. Ichiji, N. Homma, I. Bukovský, M. Yoshizawa","doi":"10.1109/MFCIST.2011.5949518","DOIUrl":"https://doi.org/10.1109/MFCIST.2011.5949518","url":null,"abstract":"This paper presents a medical application of the intelligent sensing, a new lung tumor motion prediction method for tumor following radiation therapy. An essential core of the method is accurate estimation of complex fluctuation of time-variant periodical nature of lung tumor motion. Such estimation can be achieved by using a novel multiple time-variant seasonal autoregressive integral moving average (TVSARIMA) model in which several windows of different lengths are used to calculate correlation based time-variant periods of the motion. The proposed method provides the resulting prediction as a combination of those based on different window lengths. We have compared unweighted average, multiple regression, and multilayer perceptron (MLP) for the combinations with some conventional predictions by using real data of lung tumor motion. The proposed methods with the multiple regression and MLP based combinations showed high accurate prediction and are superior to the single TVSARIMA based prediction. The best prediction performance was achieved by using the MLP based combination. The average errors were 0.7953 ± 0.0243 mm at 0.5 s ahead and 0.8581±0.0510 mm at 1.0 s ahead predictions, respectively. The results of the proposed method are clinically sufficient and superior to the conventional methods. Thus the proposed TVSARIMA with an appropriate combination method is useful for improving the prediction performance.","PeriodicalId":378791,"journal":{"name":"2011 IEEE Workshop On Merging Fields Of Computational Intelligence And Sensor Technology","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-04-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132184139","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}

引用次数: 5

Reconstructing the geometry of an object using 3D TOF Camera 利用三维TOF相机重建物体的几何形状

2011 IEEE Workshop On Merging Fields Of Computational Intelligence And Sensor Technology Pub Date : 2011-04-11 DOI: 10.1109/MFCIST.2011.5949516

Sobers L. X. Francis, S. Anavatti, M. Garratt

{"title":"Reconstructing the geometry of an object using 3D TOF Camera","authors":"Sobers L. X. Francis, S. Anavatti, M. Garratt","doi":"10.1109/MFCIST.2011.5949516","DOIUrl":"https://doi.org/10.1109/MFCIST.2011.5949516","url":null,"abstract":"This paper describes the effective way for reconstructing the geometry of a 3D object with a time-of-flight (TOF) camera. These TOF cameras can provide the range information and the 3D coordinates of the object in real time. The range information is obtained by estimating the runtime of the light which is emitted, reflected by the object and received by the camera unit. We also describe a simple approach to calibrate the camera's range data with respect to the object distance. These measured range data is also compared with the manufactures data. The proposed algorithm uses the range information and the camera specification data for the geometrical representation of the object. These range data are also utilised to separate the object from the background. The algorithm uses the depth data of all the pixels of the camera and stores in the form of matrix array to extract the object information. Using suitable mathematical approach, the technique converts the range values into 2D & 3D image representation of the object. Experimental results are presented to demonstrate the utility of this technique.","PeriodicalId":378791,"journal":{"name":"2011 IEEE Workshop On Merging Fields Of Computational Intelligence And Sensor Technology","volume":"50 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-04-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128202328","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}

引用次数: 7

Experimental research of high-speed electrical motor supercharger dynamic properties 高速电机增压器动态特性实验研究

2011 IEEE Workshop On Merging Fields Of Computational Intelligence And Sensor Technology Pub Date : 2011-04-11 DOI: 10.1109/MFCIST.2011.5949510

M. Novak, J. Novak, Z. Cerovsky

引用次数: 3

Locating sensors with fuzzy logic algorithms 用模糊逻辑算法定位传感器

2011 IEEE Workshop On Merging Fields Of Computational Intelligence And Sensor Technology Pub Date : 2011-04-11 DOI: 10.1109/MFCIST.2011.5949514

D. F. L. Marín, J. Barbancho, F. J. Molina, C. León

引用次数: 6

Controlling aseptic sterilization processes by means of a multi-sensor system 用多传感器系统控制无菌灭菌过程

2011 IEEE Workshop On Merging Fields Of Computational Intelligence And Sensor Technology Pub Date : 2011-04-11 DOI: 10.1109/MFCIST.2011.5949519

S. Reisert, H. Geissler, Rudolf Flörke, P. Wagner, T. Wagner, M. Schöning

引用次数: 2

SRD - Towards a system for the in-situ detection of the stapedius reflex 对镫骨反射的原位检测系统的研究

2011 IEEE Workshop On Merging Fields Of Computational Intelligence And Sensor Technology Pub Date : 2011-04-11 DOI: 10.1109/MFCIST.2011.5949515

M. Lüder, R. Warmuth, E. Heinrich, R. Joost, R. Salomon

引用次数: 0

Multiscale Analysis of False Neighbors for state space reconstruction of complicated systems 复杂系统状态空间重构中的假邻域多尺度分析

2011 IEEE Workshop On Merging Fields Of Computational Intelligence And Sensor Technology Pub Date : 2011-04-11 DOI: 10.1109/MFCIST.2011.5949517

I. Bukovský, W. Kinsner, V. Maly, K. Krehlik

引用次数: 4