Djamel Berrabah, Stéphane Gançarski, Sarah Kaddour Chikh, Cécile Le Pape
We present a new approach for concurrency control over XML documents. Unlike most of other approaches, we use an optimistic scheme, since we believe that it is better suited for Web applications. The originality of our solution resides in the fact that we use path expressions associated with operations to detect conflicts between transactions. This makes our approach scalable since conflict detection except in few cases does not depend on the database size nor on the amount of modified fragments. In this paper, we describe and motivate our concurrency mechanism architecture, we describe the conflict detection algorithm which is the core of our proposal and exhibit first experimental results.
{"title":"Optimistic path-based concurrency control over XML documents","authors":"Djamel Berrabah, Stéphane Gançarski, Sarah Kaddour Chikh, Cécile Le Pape","doi":"10.1145/1456223.1456303","DOIUrl":"https://doi.org/10.1145/1456223.1456303","url":null,"abstract":"We present a new approach for concurrency control over XML documents. Unlike most of other approaches, we use an optimistic scheme, since we believe that it is better suited for Web applications. The originality of our solution resides in the fact that we use path expressions associated with operations to detect conflicts between transactions. This makes our approach scalable since conflict detection except in few cases does not depend on the database size nor on the amount of modified fragments. In this paper, we describe and motivate our concurrency mechanism architecture, we describe the conflict detection algorithm which is the core of our proposal and exhibit first experimental results.","PeriodicalId":309453,"journal":{"name":"International Conference on Soft Computing as Transdisciplinary Science and Technology","volume":"39 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129874683","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}
L. Ballerini, M. Calisti, S. Damas, O. Cordón, J. Santamaría
In this work we propose a new method to segment range images. It automatically extracts invariant features directly from point clouds. Points belonging to such features are used as the input to improve an evolutionary approach to 3D range image registration in forensic anthropology. We use such features in the automatic reconstruction of an accurate 3D model of the skull. Our reconstruction method includes a pre-alignment stage, that uses a subset of feature points, and a refinement stage. Results are presented over a set of instances of real problems.
{"title":"Automatic 3D skull reconstruction using invariant features","authors":"L. Ballerini, M. Calisti, S. Damas, O. Cordón, J. Santamaría","doi":"10.1145/1456223.1456314","DOIUrl":"https://doi.org/10.1145/1456223.1456314","url":null,"abstract":"In this work we propose a new method to segment range images. It automatically extracts invariant features directly from point clouds. Points belonging to such features are used as the input to improve an evolutionary approach to 3D range image registration in forensic anthropology. We use such features in the automatic reconstruction of an accurate 3D model of the skull. Our reconstruction method includes a pre-alignment stage, that uses a subset of feature points, and a refinement stage. Results are presented over a set of instances of real problems.","PeriodicalId":309453,"journal":{"name":"International Conference on Soft Computing as Transdisciplinary Science and Technology","volume":"229 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133857268","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}
F. Alim-Ferhat, H. Bessalah, H. Salhi, S. Seddiki, M. Issad, O. Kerdjidj
This paper is devoted to the implementation of a new combined method based on wavelet transform and neurons network (WT-SOM) and designed for the compression of medical images on FPGA VirtexII circuit. Medical images present specific characteristics which require to be exploited by an explicit and efficient compression algorithm. Compression is a vital operation for images transmission, since huge volume data is generally presented. The Vector Quantization (VQ) constitutes a crucial stage in Digital images compression. In order to improve the performances of its implementation, the (VQ) allows to create a dictionary on the level "block" by a neuronal approach that of Kohonen (Self Organizing Map: SOM), tools widely used for lossless compression and high dimensional data for their implementation performances on Virtex II FPGA circuit. It is currently a very active field, and the implementation of neurons networks on FPGA circuit with a large number of neurons remains a difficult and costly task.
本文致力于在FPGA VirtexII电路上实现一种基于小波变换和神经元网络的医学图像压缩新方法(WT-SOM)。医学图像具有特定的特征，需要通过明确而有效的压缩算法加以利用。压缩是图像传输的一个重要操作，因为图像传输的数据通常是海量的。矢量量化(VQ)是数字图像压缩的关键环节。为了提高其实现的性能，(VQ)允许通过Kohonen(自组织映射:SOM)的神经元方法在“块”级别上创建字典，Kohonen(自组织映射:SOM)是广泛用于无损压缩和高维数据的工具，用于Virtex II FPGA电路的实现性能。目前，神经网络是一个非常活跃的领域，但在FPGA上实现大量神经元的神经网络仍然是一项困难而昂贵的任务。
{"title":"WT-SOM network implementation on FPGA for the medical images compression","authors":"F. Alim-Ferhat, H. Bessalah, H. Salhi, S. Seddiki, M. Issad, O. Kerdjidj","doi":"10.1145/1456223.1456318","DOIUrl":"https://doi.org/10.1145/1456223.1456318","url":null,"abstract":"This paper is devoted to the implementation of a new combined method based on wavelet transform and neurons network (WT-SOM) and designed for the compression of medical images on FPGA VirtexII circuit. Medical images present specific characteristics which require to be exploited by an explicit and efficient compression algorithm. Compression is a vital operation for images transmission, since huge volume data is generally presented. The Vector Quantization (VQ) constitutes a crucial stage in Digital images compression. In order to improve the performances of its implementation, the (VQ) allows to create a dictionary on the level \"block\" by a neuronal approach that of Kohonen (Self Organizing Map: SOM), tools widely used for lossless compression and high dimensional data for their implementation performances on Virtex II FPGA circuit. It is currently a very active field, and the implementation of neurons networks on FPGA circuit with a large number of neurons remains a difficult and costly task.","PeriodicalId":309453,"journal":{"name":"International Conference on Soft Computing as Transdisciplinary Science and Technology","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131007469","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}
In this paper, we present the capabilities of fuzzy logic to cope with complex problems and to summarize or synthetize large amounts of data. We first describe the major theoretical tools we mainly use, namely similarity measures and fuzzy inductive learning, and then their applications on several examples that illustrate various aspects of a fuzzy set based knowledge representation
{"title":"Fuzzy logic to cope with complex problems: some examples of real-world applications","authors":"B. Bouchon-Meunier","doi":"10.1145/1456223.1456306","DOIUrl":"https://doi.org/10.1145/1456223.1456306","url":null,"abstract":"In this paper, we present the capabilities of fuzzy logic to cope with complex problems and to summarize or synthetize large amounts of data. We first describe the major theoretical tools we mainly use, namely similarity measures and fuzzy inductive learning, and then their applications on several examples that illustrate various aspects of a fuzzy set based knowledge representation","PeriodicalId":309453,"journal":{"name":"International Conference on Soft Computing as Transdisciplinary Science and Technology","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125528890","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}
In this paper we introduce a method for calculating the volume of spontaneous intracerebral hematomas from a sequence of tomographic scans. The described approach is a modification of a gold standard method called step-section planimetry. It uses image interpolation techniques to increase the accuracy of the obtained volume and employs semi-automatic segmentation to facilitate physicians' work. The method is designed to perform especially well for highly irregular shapes that are characteristic for intracerebral hematomas. The obtained results are compared with two existing commercial approaches.
{"title":"Calculating accurate volume of spontaneous intracerebral hematoma","authors":"Radosław Cichocki, M. Tabakov, H. Kwasnicka","doi":"10.1145/1456223.1456254","DOIUrl":"https://doi.org/10.1145/1456223.1456254","url":null,"abstract":"In this paper we introduce a method for calculating the volume of spontaneous intracerebral hematomas from a sequence of tomographic scans. The described approach is a modification of a gold standard method called step-section planimetry. It uses image interpolation techniques to increase the accuracy of the obtained volume and employs semi-automatic segmentation to facilitate physicians' work. The method is designed to perform especially well for highly irregular shapes that are characteristic for intracerebral hematomas. The obtained results are compared with two existing commercial approaches.","PeriodicalId":309453,"journal":{"name":"International Conference on Soft Computing as Transdisciplinary Science and Technology","volume":"52 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125542791","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}
The segmentation of medical scans (CT, MRI, etc.) and the subsequent identification of key features therein, such as organs and tumours, is an important precursor to many medical imaging applications. It is a difficult problem, not least because of the extent to which the shapes of organs can vary from one image to the next. One interesting approach is to start by partitioning the image into a region hierarchy, in which each node represents a contiguous region of the image. This is a well-known approach in the literature: the resulting hierarchy is variously referred to as a partition tree, an image tree, or a semantic segmentation tree. Such trees summarise the image information in a helpful way, and allow efficient searches for regions which satisfy certain criteria. However, once built, the hierarchy tends to be static, making the results very dependent on the initial tree construction process (which, in the case of medical images, is done independently of any anatomical knowledge we might wish to bring to bear). In this paper, we describe our approach to the automatic feature identification problem, in particular explaining why modifying the hierarchy at a later stage can be useful, and how it can be achieved. We illustrate the efficacy of our method with some preliminary results showing the automatic identification of ribs.
{"title":"Region analysis of abdominal CT scans using image partition forests","authors":"S. Golodetz, I. Voiculescu, S. Cameron","doi":"10.1145/1456223.1456312","DOIUrl":"https://doi.org/10.1145/1456223.1456312","url":null,"abstract":"The segmentation of medical scans (CT, MRI, etc.) and the subsequent identification of key features therein, such as organs and tumours, is an important precursor to many medical imaging applications. It is a difficult problem, not least because of the extent to which the shapes of organs can vary from one image to the next. One interesting approach is to start by partitioning the image into a region hierarchy, in which each node represents a contiguous region of the image. This is a well-known approach in the literature: the resulting hierarchy is variously referred to as a partition tree, an image tree, or a semantic segmentation tree. Such trees summarise the image information in a helpful way, and allow efficient searches for regions which satisfy certain criteria. However, once built, the hierarchy tends to be static, making the results very dependent on the initial tree construction process (which, in the case of medical images, is done independently of any anatomical knowledge we might wish to bring to bear). In this paper, we describe our approach to the automatic feature identification problem, in particular explaining why modifying the hierarchy at a later stage can be useful, and how it can be achieved. We illustrate the efficacy of our method with some preliminary results showing the automatic identification of ribs.","PeriodicalId":309453,"journal":{"name":"International Conference on Soft Computing as Transdisciplinary Science and Technology","volume":"50 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127435975","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}
J. Hippolyte, C. Bloch, P. Chatonnay, C. Espanet, D. Chamagne, G. Wimmer
This paper presents an original method of permanent magnet motor optimal design developped by both Electrical Engineering and Computer Science laboratories. An Evolutionary Algorithm combining Genetic Algorithms and Multiagent Systems is used. This Genetic Multiagent System parameters are determined using a robust design method based on the Taguchi approach. The quality of the algorithm is evaluated considering the multiobjective quality of the solutions it delivers on a permanent magnet machine constrained optimization. Contradictory objectives as efficiency and weight have a large influence on the design of electrical machines. Performances of the resulting tuned up algorithm are compared with previous results from the authors.
{"title":"Tuning an evolutionary algorithm with taguchi methods and application to the dimensioning of an electrical motor","authors":"J. Hippolyte, C. Bloch, P. Chatonnay, C. Espanet, D. Chamagne, G. Wimmer","doi":"10.1145/1456223.1456279","DOIUrl":"https://doi.org/10.1145/1456223.1456279","url":null,"abstract":"This paper presents an original method of permanent magnet motor optimal design developped by both Electrical Engineering and Computer Science laboratories. An Evolutionary Algorithm combining Genetic Algorithms and Multiagent Systems is used. This Genetic Multiagent System parameters are determined using a robust design method based on the Taguchi approach. The quality of the algorithm is evaluated considering the multiobjective quality of the solutions it delivers on a permanent magnet machine constrained optimization. Contradictory objectives as efficiency and weight have a large influence on the design of electrical machines. Performances of the resulting tuned up algorithm are compared with previous results from the authors.","PeriodicalId":309453,"journal":{"name":"International Conference on Soft Computing as Transdisciplinary Science and Technology","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129095509","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}
Andrea Seraghiti, S. Delpriori, E. Lattanzi, A. Bogliolo
Autonomous wireless sensor networks are subject to power, bandwidth, and resource limitations that can be represented as capacity constraints imposed to their equivalent flow networks. The maximum sustainable workload of a sensor net work (i.e., the maximum data flow from the sensor nodes to the collection point which is compatible with the capacity constraints) is the maxflow of the flow network. This paper presents a self-adapting maxflow routing algorithm which is able to route any sustainable workload while automatically adapting to time-varying operating conditions. The algorithm has been implemented on top of OMNeT++ [1] in order to address practical issues and to enable simulation-based assessment and design exploration Simulation results demonstrate the effectiveness and the applicability of the proposed approach
{"title":"Self-adapting maxflow routing algorithm for WSNs: practical issues and simulation-based assessment","authors":"Andrea Seraghiti, S. Delpriori, E. Lattanzi, A. Bogliolo","doi":"10.1145/1456223.1456361","DOIUrl":"https://doi.org/10.1145/1456223.1456361","url":null,"abstract":"Autonomous wireless sensor networks are subject to power, bandwidth, and resource limitations that can be represented as capacity constraints imposed to their equivalent flow networks. The maximum sustainable workload of a sensor net work (i.e., the maximum data flow from the sensor nodes to the collection point which is compatible with the capacity constraints) is the maxflow of the flow network.\u0000 This paper presents a self-adapting maxflow routing algorithm which is able to route any sustainable workload while automatically adapting to time-varying operating conditions. The algorithm has been implemented on top of OMNeT++ [1] in order to address practical issues and to enable simulation-based assessment and design exploration Simulation results demonstrate the effectiveness and the applicability of the proposed approach","PeriodicalId":309453,"journal":{"name":"International Conference on Soft Computing as Transdisciplinary Science and Technology","volume":"46 3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129564659","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}
Ergude Bao, Yang Yang, Hui Chen, Yuan-Yuan Lu, Xiao Liu, Weisheng Li
The application level load balancing problem that CPU time provided for each data unit is steady but CPU time needed by them is different has been drawing people's attention these years, but actually, the problem that CPU time needed by each data unit is the same but CPU time provided for them is non-steady has more practical value. This paper starts from the changing of provided CPU time for each computing process in a cluster, selects counter propagation neutral network as a basis from 3 predict methods, which can bring high accuracy but only cost a low complexity and can also well manage the interdependency of provided CPU time among the computing processes, then studies and implements an self-adaptive allocation algorithm for parallel programs. From the result of tests, the algorithm can largely raise the efficiency of parallel algorithms. Encapsulate this algorithm into MPI API for engineering applications, and as long as software developers substitute this API for message send and receive functions, adaptive allocation can be achieved. The API encapsulating the algorithm is especially applicable for Microsoft Windows Compute Cluster Server (WCCS) and it is the extension of this system.
{"title":"A study and implementation of self-adaptive allocation algorithm for parallel program","authors":"Ergude Bao, Yang Yang, Hui Chen, Yuan-Yuan Lu, Xiao Liu, Weisheng Li","doi":"10.1145/1456223.1456342","DOIUrl":"https://doi.org/10.1145/1456223.1456342","url":null,"abstract":"The application level load balancing problem that CPU time provided for each data unit is steady but CPU time needed by them is different has been drawing people's attention these years, but actually, the problem that CPU time needed by each data unit is the same but CPU time provided for them is non-steady has more practical value. This paper starts from the changing of provided CPU time for each computing process in a cluster, selects counter propagation neutral network as a basis from 3 predict methods, which can bring high accuracy but only cost a low complexity and can also well manage the interdependency of provided CPU time among the computing processes, then studies and implements an self-adaptive allocation algorithm for parallel programs. From the result of tests, the algorithm can largely raise the efficiency of parallel algorithms. Encapsulate this algorithm into MPI API for engineering applications, and as long as software developers substitute this API for message send and receive functions, adaptive allocation can be achieved. The API encapsulating the algorithm is especially applicable for Microsoft Windows Compute Cluster Server (WCCS) and it is the extension of this system.","PeriodicalId":309453,"journal":{"name":"International Conference on Soft Computing as Transdisciplinary Science and Technology","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129815799","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}
Image segmentation is a crucial stage in the analysis of dermoscopic images as the extraction of exact boundaries of skin lesions is esseintial for accurate diagnosis. One approach to image segmentation is based on the idea of clustering pixels with similar characteristics. Fuzzy c-means is a popular clustering based algorithm that is often employed in medical image segmentation, however due to its iterative nature also has excessive computational requirements. In this paper we introduce a new mean shift based fuzzy c-means algorithm that requires less computational time compared to previous techniques while providing good segmentation performance. The proposed segmentation method incorporates a mean field term within the standard fuzzy c-means objective function. Since mean shift can quickly and reliably find cluster centres, the entire strategy is capable of effeciently detecting regions within an image. Experimental results on a large dataset of dermoscopic images demonstrates that our algorithm is able to accurately and efficiently extract skin lesion borders.
{"title":"Anisotropic mean shift based fuzzy c-means segmentation of skin lesions","authors":"Huiyu Zhou, G. Schaefer, A. Sadka, M. E. Celebi","doi":"10.1145/1456223.1456313","DOIUrl":"https://doi.org/10.1145/1456223.1456313","url":null,"abstract":"Image segmentation is a crucial stage in the analysis of dermoscopic images as the extraction of exact boundaries of skin lesions is esseintial for accurate diagnosis. One approach to image segmentation is based on the idea of clustering pixels with similar characteristics. Fuzzy c-means is a popular clustering based algorithm that is often employed in medical image segmentation, however due to its iterative nature also has excessive computational requirements. In this paper we introduce a new mean shift based fuzzy c-means algorithm that requires less computational time compared to previous techniques while providing good segmentation performance. The proposed segmentation method incorporates a mean field term within the standard fuzzy c-means objective function. Since mean shift can quickly and reliably find cluster centres, the entire strategy is capable of effeciently detecting regions within an image. Experimental results on a large dataset of dermoscopic images demonstrates that our algorithm is able to accurately and efficiently extract skin lesion borders.","PeriodicalId":309453,"journal":{"name":"International Conference on Soft Computing as Transdisciplinary Science and Technology","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121223281","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}
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