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Modelling teens clothing fashion preferences using machine learning

WSEAS Transactions on Information science and Applications 2006年第10期3卷 2054-2065页

作者： Kokol, Peter Verlič, Mateja Križmarić, Miljenko Laboratory for System Design Faculty of Electrical Engineering and Computer Science University of Maribor Slovenia Smetanova 17 2000 Maribor Slovenia College of Nursing Studies University of Maribor Zitna 15 2000 Maribor Slovenia

Fashion is one of the most visible media of the change in modern society. It reflects the change in aesthetic, economic, political, cultural and social life. Individuals and society use fashion to communicate their taste and lifestyle, teens for example employing different clothing styles. On the individual there are two basic forces involved namely the 'differentiating force" and the "socialising force". Those two forces are central in an individual's self - negotiation between the need for exhibiting and the need to conform to the social norms and are expressed in personal fashion styles. The aim of this paper is to model this expression on the case of teens, more precisely to model clothing fashion preferences of teens employing machine learning techniques.

关键词： Learning systems

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Blood Coagulation and Living Tissue Sterilization by Floating-Electrode Dielectric Barrier Discharge in Air

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Plasma Chemistry and Plasma Processing 2006年第1期27卷 113-114页

作者： Gregory Fridman Marie Peddinghaus Manjula Balasubramanian Halim Ayan Alexander Fridman Alexander Gutsol Ari Brooks Gary Friedman School of Biomedical Engineering Science and Health Systems Drexel University Philadelphia USA Pathology and Laboratory Medicine Department College of Medicine Drexel University Philadelphia USA Department of Mechanical Engineering and Mechanics College of Engineering Drexel University Philadelphia USA Department of Surgery College of Medicine Drexel University Philadelphia USA Department of Electrical and Computer Engineering College of Engineering College of Engineering Drexel University Philadelphia USA

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Robust Adaptive Control for Complex Systems Employing ANN Emulation of Nonlinear Functions

Robust Adaptive Control for Complex Systems Employing ANN Em...

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Seminar on Neural Network Applications in electrical engineering

作者： Georgi M. Dimirovski Yuanwei Jing Yanxin Zhang Miomir K. Vukobratovic Faculty of Electrical Engineering SS Cyril and Methodius University Skopje Macedonia Department of Computer Engineering Dogus University Kadikoy Istanbul Turkey School of Information Science and Engineering Northeastern University Shenyang China Laboratory of Robotics & Flexible Automation Mihajlo Pupin Institute Belgrade Serbia

A new robust adaptive control design synthesis, which employs both high-order neural networks and math-analytical results, for a class of complex nonlinear mechatronic systems possessing similarity property has been derived. This approach makes an adequate use of the structural feature of composite similarity systems and neural networks to resolve the representation issue of uncertainty interconnections and subsystem gains by on-line updating the weights. This synthesis does guarantee the real stability in closed-loop but requires skills to obtain larger attraction domains. Mechatronic example of an axis-tray drive system, possessing uncertainties, is used to illustrate the proposed technique

关键词： Robust control Adaptive control Emulation Network synthesis Neural networks Mechatronics Uncertainty Artificial neural networks Control system synthesis Stability

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Knowledge-driven 3-D Extraction of the Masseter from MR Data

Knowledge-driven 3-D Extraction of the Masseter from MR Data

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Annual International Conference of the IEEE engineering in Medicine and Biology Society (EMBC)

作者： H.P. Ng S.H. Ong K.W.C. Foong P.S. Goh W.L. Nowinski Biomedical Imaging Laboratory Agency for Science Technology and Research Singapore NUS Graduate School for Integrative Sciences and Engineering Singapore Department of Electrical and Computer Engineering National University of Singapore Singapore Department of Preventive Dentistry National University of Singapore Singapore Department of Diagnostic Radiology National University of Singapore Singapore

In this paper, we propose a knowledge-driven highly automatic methodology for extracting the masseter from magnetic resonance (MR) data sets for clinical purposes. The masseter is a muscle of mastication which acts to raise the jaw and clench the teeth. In our initial work, we designed a process which allowed us to perform 2-D segmentation of the masseter on 2-D MR images. In the methodology proposed here, we make use of ground truth to first determine the index of the MR slice in which we will carry out 2-D segmentation of the masseter. Having obtained the 2-D segmentation, we will make use of it to determine the region of interest (ROI) of the masseter in the other MR slices belonging to the same data set. The upper and lower thresholds applied to these MR slices, for extraction of the masseter, are determined through the histogram of the 2-D segmented masseter. Visualization of the 3-D masseter is achieved via volume rendering. Our methodology has been applied to five MR data sets. Validation was done by comparing the segmentation results obtained by using our proposed methodology against manual contour tracings, obtaining an average accuracy of 83.5%

关键词： Data mining Image segmentation Masticatory muscles Surges Surgery Shape biomedical imaging Bones Facial muscles Cities and towns

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Determination of the Grey Level Ranks for the Segmentation of Textured Images

Determination of the Grey Level Ranks for the Segmentation o...

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IEEE International Symposium on Industrial Electronics (ISIE)

作者： Z. Ameur A. Adane S. Ameur Faculty of Electrical Engineering and Computer Science Department of Electronics Laboratory of Random Phenomena Analysis and Modeling LAMPA Mouloud Mammeri University Tizi Ouzou Algeria Faculty of Electronics and Computer Science Department of Telecommunications Laboratory of Image Processing and Radiation University of Sciences and Technology of Algiers U. S. T. H. B. Bab-Ezzouar Algeria

In many cases, an image is made of various types of texture. Such diversity can be usefully exploited to get a suitable decomposition of the image into typical classes and then, identify its constitutive elements. Among the approaches used to segment textured images, those based on the statistical analysis of the neighborhood of each pixel seem to be most efficient. In this paper, this kind of method is implemented, which consists in coding the pixels surrounding each point of the image by taking into account the path traveling through them and their grey levels. The rank vectors namely the codes obtained for all the possible paths, are then classified using the K-means algorithm. Considering the 24- rank vectors, this method is tested on different images of the Brodatz album and compared with Laws filters and GLCM. It yields a satisfactory reproduction of the image contours and a classification ratio exceeding 98 %. The 24 rank based-method is also applied to meteorological images collected by Meteosat over Europe and North Africa during December 1994. It is found that these images can be segmented into eight typical classes assignable to the soils, the seas and the clouds observed in the regions under study.

关键词： Image segmentation Pixel Statistical analysis Image coding Testing Filters Meteorology Europe Africa Soil

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Medical Image Segmentation Using K-Means Clustering and Improved Watershed Algorithm

Medical Image Segmentation Using K-Means Clustering and Impr...

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IEEE Southwest Symposium on Image Analysis and Interpretation

作者： H.P. Ng S.H. Ong K.W.C. Foong P.S. Goh W.L. Nowinski Biomedical Imaging Laboratory Agency for Science Technology and Research Singapore Graduate School for Integrative Sciences and Engineering NUS Singapore Department of Electrical and Computer Engineering National University of Singapore Sun Microsystems Singapore Department of Preventive Dentistry National University of Singapore Sun Microsystems Singapore Department of Diagnostic Radiology National University of Singapore Sun Microsystems Singapore

ISBN: (纸本)1424400694

We propose a methodology that incorporates k-means and improved watershed segmentation algorithm for medical image segmentation. The use of the conventional watershed algorithm for medical image analysis is widespread because of its advantages, such as always being able to produce a complete division of the image. However, its drawbacks include over-segmentation and sensitivity to false edges. We address the drawbacks of the conventional watershed algorithm when it is applied to medical images by using k-means clustering to produce a primary segmentation of the image before we apply our improved watershed segmentation algorithm to it. The k-means clustering is an unsupervised learning algorithm, while the improved watershed segmentation algorithm makes use of automated thresholding on the gradient magnitude map and post-segmentation merging on the initial partitions to reduce the number of false edges and over-segmentation. By comparing the number of partitions in the segmentation maps of 50 images, we showed that our proposed methodology produced segmentation maps which have 92% fewer partitions than the segmentation maps produced by the conventional watershed algorithm

关键词： biomedical imaging Image segmentation Clustering algorithms Medical diagnostic imaging Partitioning algorithms Pixel Image edge detection Rain Surface morphology Surface topography

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Template-based Automatic Segmentation of Masseter Using Prior Knowledge

Template-based Automatic Segmentation of Masseter Using Prio...

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IEEE Southwest Symposium on Image Analysis and Interpretation

作者： H.P. Ng S.H. Ong P.S. Goh K.W.C. Foong W.L. Nowinski Biomedical Imaging Laboratory Agency for Science Technology and Research Singapore Graduate School for Integrative Sciences and Engineering NUS Singapore Department of Electrical and Computer Engineering National University of Singapore Sun Microsystems Singapore Department of Diagnostic Radiology National University of Singapore Sun Microsystems Singapore Department of Preventive Dentistry National University of Singapore Sun Microsystems Singapore

ISBN: (纸本)1424400694

In this paper, we propose a knowledge-based, fully automatic methodology for segmenting the masseter, which is a muscle of mastication, from 2-D magnetic resonance (MR) images for clinical purposes. To our knowledge, there is currently no methodology which automatically segments the masseter from MR images. Our methodology uses five ground truths, where the masseter has been manually segmented and verified by medical experts, to serve as the reference and provide prior knowledge. The prior knowledge involved is the spatial relationship between the region of interest (ROI) of the head and ROI of the masseter. In the segmentation process, anisotropic diffusion first smoothens the ROI of the latter, and thresholding removes unwanted neighboring regions of the masseter. A template of the masseter is then used to obtain an initial segmentation of the muscle, which serves as the initialization to the gradient vector flow (GVF) snake for refining the initial segmentation. We performed 2-D segmentation of the masseter on a total of 25 MR images, which belong to the mid-facial region through the mandible from five data sets. Validation was done by comparing the segmentation results obtained by using our proposed methodology against manual segmentations done by medical experts, obtaining an average accuracy of 92%

关键词： Image segmentation Masticatory muscles biomedical imaging Surgery Head Bones Medical diagnostic imaging Image processing biomedical engineering Knowledge engineering

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Introducing Grammatical Evolution in Fetal Heart Rate Analysis and Classification

Introducing Grammatical Evolution in Fetal Heart Rate Analys...

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International IEEE Conference on Intelligent Systems, IS

作者： Ioannis Tsoulos George Georgoulas Dimitris Gavrilis Chrysostomos Stylios Joao Bemardes Peter Groumpos Computer Science Department University of Ioannina Ioannina Greece Laboratory for Automation and Robotics University of Patras Patras Greece Department of Electrical and Computer Engineering University of Patras Patras Greece Laboratory for Automation and Robotics Informatics and Management Artas Greece Department of Gynecology and Obstetrics Porto Portugal Department of Gynecology and Obstetrics Porto Faculty of Medicine Porto Portugal Laboratory for Automation & Robotics University of Patras Patras Greece

Electronic fetal monitoring is an essential tool for fetal surveillance during labor. It is mainly based on the monitoring and evaluation of the fetal heart rate (FHR) signal, which has to be interpreted online. Evaluation and interpretation of FHR gives an indication of the fetal condition. A lot of research efforts have been done towards the development of automatic and reliable methods for processing and evaluating FHR. This research work introduces an integrated methodology for processing and classifying FHR based on the novel approach of grammatical evolution for feature construction and selection. The proposed methodology is presented, and it is applied to a data set. Experimental results are promising paving the way for further research in that direction

关键词： Fetal heart rate Robotics and automation Signal processing Heart rate measurement computerized monitoring Neural networks Cardiology Laboratories Telephony Medical robotics

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Preliminary Evaluation of Recommended Airline Exercises for Optimal Calf Muscle Pump Activity

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European Journal of Vascular and Endovascular Surgery 2006年第3期32卷 340-340页

作者： K.J. O'Donovan T. Bajd P.A. Grace D.T. O'Keeffe G.M. Lyons Biomedical Electronics Laboratory Department of Electronic and Computer Engineering University of Limerick Limerick Ireland Laboratory of Robotics and Biomedical Engineering Faculty of Electrical Engineering University of Ljubljana Ljubljana Slovenia Vascular Imaging Laboratory Department of Vascular Surgery Mid-Western Regional Hospital Limerick Ireland

Objectives A preliminary study to investigate which of the recommended airline exercises for DVT prevention produce optimal calf muscle pump activity. Methods Four subjects were instructed to carry out ten lower leg exercises based on those recommended by airlines for DVT prevention. An EMG sensor was used to record calf muscle activity and a motion analysis system was used to ensure the exercise was conducted correctly. Results Statistical analysis showed significant differences in the level of calf muscle pump activity induced by the different exercises. Heel rise foot pumps were shown to induce highest levels of activity while many exercises did not induce any significant calf muscle activity at all. Conclusion These findings indicate that a further, more detailed examination of the exercises recommended to passengers for DVT prevention on long distance flights should be conducted to determine the potential benefit to the health and safety of the passenger.

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HIGH-RISE BUILDINGS UNDER EARTHQUAKE EXCITATION: STABILIZATION USING SMC

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IFAC Proceedings Volumes 2006年第16期39卷 776-781页

作者： Georgi M. Dimirovski Jun Zhao Miomir K. Vukobratovic Dogus University Faculty of Engineering Dept. of Computer Engineering Acibadem Zeamet Sk. 21 Kadikoy TR-34722 Istanbul Rep. of Turkey Fax: ++90-216-327-9631 Tel: ++90-216-327-1104 SS Cyril and Methodius University Faculty of Electrical Engineering Rugjer Boskovic b.b. Karpos II MK-1000 Skopje Rep. of Macedonia Northestern University School of Information Science and Engineering Institute of Control Science Shenyang Liaoning CN-110004 P. R. of China Fax: ++86-24-8367-2273 Tel: ++86-24-2389-3000 Mihailo Pupin Institute Laboratory of Robotics & Automation Volgina 15 Karaburma 11000 F. R. Serbia and Montenegro Fax: ++381-11-2775-870 Tel: ++381-11-2774-236

The goal to control the dynamics of high-rise buildings either to ameliorate the damage or prevent their destruction when subject to an earthquake excitation has been subject of extensive research. All known control designs have advantages and disadvantages as well as operating limits. The application of sliding-mode control to controlling earthquake induced vibrations of a multi-story structural system as an active seismic compensation plus base isolation has been investigated. The performance has been compared to the one of traditional industrial controls, and relevant conclusions drawn. Simulation results, carried out using El Centro earthquake acceleration, have shown that the sliding mode control can decrease significantly displacements of the floors.

关键词： Earthquake sliding mode control structural systems vibration control

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