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2014 9th International Conference on Computer Engineering & Systems (ICCES)最新文献

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A proposed SNOMED CT ontology-based encoding methodology for diabetes diagnosis case-base 提出了一种基于SNOMED CT本体的糖尿病诊断病例库编码方法
Pub Date : 2014-12-01 DOI: 10.1109/ICCES.2014.7030954
Shaker El-Sappagh, Mohammed M Elmogy, A. Riad, H. Zaghloul, F. Badria
Domain knowledge ontology supports the implementation of intelligent Case Based Reasoning (CBR) systems. Standardized terminologies support efficient indexing and processing of patient data. It is an essential element for the implementation of knowledge-based clinical decision support by exploiting pre-defined semantic relationships, both hierarchical and non-hierarchical in nature. Systemized Nomenclature of Medicine-Clinical Terms (SNOMED CT) is the most comprehensive and complete terminology. This paper proposes an encoding methodology for clinical data using SNOMED CT. A case study for a diabetes diagnosis data set will be tested where SNOMED CT provides a concept coverage of ~75% for its clinical terms. Custom codes will be provided for uncovered terms. The encoded data set is derived from electronic health record database, and it represents a case base knowledge. The collected concept IDs will be used to build a domain ontology for diabetes diagnosis CBR. This ontology contains 550 concept IDs. The encoded case base and the domain ontology can be used to build a knowledge intensive CBR.
领域知识本体支持智能案例推理(CBR)系统的实现。标准化的术语支持对患者数据进行高效的索引和处理。它是通过利用预定义的语义关系来实现基于知识的临床决策支持的基本要素,这些语义关系在本质上是分层的和非分层的。《医学临床术语系统命名法》是我国最全面、最完整的医学临床术语。本文提出了一种SNOMED CT临床数据的编码方法。将测试一个糖尿病诊断数据集的案例研究,其中SNOMED CT为其临床术语提供了约75%的概念覆盖率。未覆盖条款将提供自定义代码。编码的数据集来源于电子病历数据库,它代表了一个病例库知识。收集到的概念id将用于构建糖尿病诊断CBR的领域本体。这个本体包含550个概念id。编码后的案例库和领域本体可用于构建知识密集型案例推理。
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引用次数: 11
Software performance engineering using UML2SAN: Deadlock prediction of funds transfer 使用UML2SAN的软件性能工程:资金转移的死锁预测
Pub Date : 2014-12-01 DOI: 10.1109/ICCES.2014.7030978
Ihab Sbeity, M. Dbouk
In order to allow software designers to determine the performance of software during design, Connie Smith has introduced the concept of Software Performance Engineering (SPE). The idea is to bring performance evaluation into the software design process. Several approaches have been proposed to provide such techniques. Some of them propose to derive from a UML (Unified Modeling Language) model a performance model. UML2SAN is one of the most recent works in SPE, that permits to generate a performance model (SAN: Stochastic Automata Network) from UML specifications. In this paper, we verify the convenience of UML2SAN by predicting deadlock of transfer funds in a banking system during the design phase.
为了让软件设计者在设计过程中确定软件的性能,Connie Smith引入了软件性能工程(SPE)的概念。其理念是将性能评估带入软件设计过程。已经提出了几种方法来提供这种技术。他们中的一些人建议从UML(统一建模语言)模型派生出性能模型。UML2SAN是SPE中最新的工作之一,它允许从UML规范生成性能模型(SAN:随机自动机网络)。在本文中,我们通过在设计阶段预测银行系统中转移资金的死锁来验证UML2SAN的便利性。
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引用次数: 1
Arabic sign language recognition using leap motion sensor 使用跳跃运动传感器的阿拉伯手语识别
Pub Date : 2014-12-01 DOI: 10.1109/ICCES.2014.7030987
A. S. Elons, Menna Ahmed, Hwaidaa Shedid, M. Tolba
Researchers in sign language recognition customized different sensors to capture hand signs. Gloves, digital cameras, depth cameras and Kinect were used alternatively in most systems. Due to signs closeness, input accuracy is a very essential constraint to reach a high recognition accuracy. Although previous systems accomplished high recognition accuracy, they suffer from stability in realistic environment due to variance in signing speed, lighting, etc... In this paper, a recognition system for ArSL has been developed based on a new digital sensor called “Leap Motion”. This sensor tackles the major issues in vision-based systems such as skin color, lighting etc... Leap motion captures hands and fingers movements in 3D digital format. The sensor throws 3D digital information in each frame of movement. These temporal and spatial features are fed into a Multi-layer perceptron Neural Network (MLP). The system was tested on 50 different dynamic signs (distinguishable without non-manual features) and the recognition accuracy reached 88% for two different persons. Although Leap motion tracks both hands accurately, unfortunately Leap motion does not track non-manual features. This system can be enhanced by adding other sensors to track other non-manual features such as facial expressions and body poses. The proposed sensor can work simultaneously with leap motion to capture all sign's features.
手语识别的研究人员定制了不同的传感器来捕捉手势。手套、数码相机、深度相机和Kinect在大多数系统中交替使用。由于符号的接近性,输入精度是达到高识别精度的一个非常重要的约束。虽然以前的系统实现了很高的识别精度,但由于签名速度、照明等方面的差异,它们在现实环境中受到稳定性的影响。本文开发了一种基于新型数字传感器Leap Motion的ArSL识别系统。这种传感器解决了基于视觉的系统中的主要问题,如肤色、照明等。Leap motion以3D数字格式捕捉手和手指的运动。传感器在运动的每一帧中抛出3D数字信息。这些时空特征被输入到多层感知器神经网络(MLP)中。该系统对50种不同的动态标志(无非手动特征可区分)进行了测试,对两种不同的人的识别准确率达到88%。虽然Leap motion可以准确地跟踪双手,但不幸的是,Leap motion无法跟踪非手动功能。这个系统可以通过添加其他传感器来跟踪其他非手动特征,如面部表情和身体姿势来增强。所提出的传感器可以与跳跃运动同时工作,以捕获所有标志的特征。
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引用次数: 82
ICF based automation system for spinal cord injuries rehabilitation 基于ICF的脊髓损伤康复自动化系统
Pub Date : 2014-12-01 DOI: 10.1109/ICCES.2014.7030955
Rehab Mahmoud, Nashwa El-Bendary, Hoda M. O. Mokhtar, A. Hassanien
Disabilities, specially the ones caused by injuries of spinal cord, affect both people's behavior and participation in daily activities. Therefore, developing automated systems that monitor and assess the progress of Spinal Cord Injury (SCI) patients represents an accelerated need. In this paper we utilize the framework of the International Classification for Functioning, disability and health (ICF) in order to propose an automatic system for SCI patients progress monitoring and rehabilitation. The ICF is a reference classification system that aims at improving integration of health information and ensuring the collection of accurate health data. The proposed system is divided into three phases; namely (1) ICF code construction, (2) progress monitoring, and (3) progress assessment phases. Comparing the manual expert-based progress assessment to experimental results obtained by the proposed system in this article, an efficiency of 100% has been achieved by the three previously stated phases of the proposed system.
残疾,特别是由脊髓损伤引起的残疾,既影响人们的行为,也影响人们对日常活动的参与。因此,开发监测和评估脊髓损伤(SCI)患者进展的自动化系统代表了一种加速的需求。在本文中,我们利用国际功能、残疾和健康分类(ICF)的框架,提出了一个用于脊髓损伤患者进展监测和康复的自动系统。ICF是一个参考分类系统,旨在改进卫生信息的整合并确保收集准确的卫生数据。建议的系统分为三个阶段;即(1)ICF代码构建阶段,(2)进度监控阶段,(3)进度评估阶段。将本文中基于人工专家的进度评估与所提出的系统所获得的实验结果进行比较,所提出的系统的三个阶段的效率达到了100%。
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引用次数: 8
Effect of hough forests parameters on face detection performance: An empirical analysis 霍夫森林参数对人脸检测性能影响的实证分析
Pub Date : 2014-12-01 DOI: 10.1109/ICCES.2014.7030924
M. Hassaballah, Mourad Ahmed, H. Alshazly
Face detection as one of the most challenging tasks in computer vision has received a lot of attention in recent decades due to its wide range of use in face based image analysis. In this paper, we propose an efficient approach for face detection that efficiently combines generalized Hough transform within random decision forests framework. In this approach, we train random decision forests that directly maps the image patch appearance to the probabilistic vote about the possible location of the face centroid; the detection hypotheses then correspond to the maxima of the Hough image. The random decision forests construction and prediction abilities depend on setting some parameters, which in turns affects the performance of the method. Therefore, the impact of these parameters that most influence the behavior of the forest for detecting faces is studied through experiments on the widely used CMU+MIT database. Moreover, a comparison with some published methods is presented.
人脸检测作为计算机视觉中最具挑战性的任务之一,由于其在基于人脸的图像分析中的广泛应用,近几十年来受到了广泛的关注。本文提出了一种在随机决策森林框架下有效结合广义霍夫变换的人脸检测方法。在这种方法中,我们训练随机决策森林,将图像斑块的外观直接映射到关于人脸质心可能位置的概率投票;然后检测假设对应于霍夫图像的最大值。随机决策森林的构建和预测能力取决于一些参数的设置,而这些参数的设置又会影响方法的性能。因此,通过在广泛使用的CMU+MIT数据库上进行实验,研究这些对森林人脸检测行为影响最大的参数的影响。并与一些已发表的方法进行了比较。
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引用次数: 0
Hybrid Named Entity Recognition - Application to Arabic Language 混合命名实体识别-应用于阿拉伯语
Pub Date : 2014-12-01 DOI: 10.1109/ICCES.2014.7030933
Mohamed A. Meselhi, Hitham M. Abo Bakr, I. Ziedan, K. Shaalan
Most Named Entity Recognition (NER) systems follow either a rule-based approach or machine learning approach. In this paper, we introduce out attempt at developing a hybrid NER system, which combines the rule-based approach with a machine learning approach in order to obtain the advantages of both approaches and overcomes their problems [1]. The system is able to recognize eight types of named entities including Location, Person, Organization, Date, Time, Price, Measurement and Percent. Experimental results on ANERcorp dataset indicated that our hybrid approach outperforms the rule-based approach and the machine learning approach when they are processed separately. Moreover, our hybrid approach outperforms the state-of-the-art of Arabic NER.
大多数命名实体识别(NER)系统遵循基于规则的方法或机器学习方法。在本文中,我们介绍了开发混合NER系统的尝试,该系统将基于规则的方法与机器学习方法相结合,以获得两种方法的优点并克服它们的问题[1]。该系统能够识别八种类型的命名实体,包括地点,人,组织,日期,时间,价格,测量和百分比。在ANERcorp数据集上的实验结果表明,我们的混合方法在分别处理时优于基于规则的方法和机器学习方法。此外,我们的混合方法优于最先进的阿拉伯NER。
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引用次数: 8
Copy-rotate-move forgery detection based on spatial domain 基于空间域的复制-旋转-移动伪造检测
Pub Date : 2014-12-01 DOI: 10.1109/ICCES.2014.7030944
Sondos M. Fadl, N. Semary, M. Hadhoud
Digital image tampering becomes a common information falsification trend. Copy-Move forgery is one of the tampering types that are used. Image forgery is the science of detecting image tempering whether with a previous knowledge about the source image (active) or without (passive). In this paper, we propose a method which is efficient and fast for detecting Copy-Move regions even when the copied region was undergone rotation modify in spatial domain. The proposed method accelerates blocking matching strategy by parallel comparing between blocks. Firstly, the image is divided into fixed-size overlapping blocks then features are extracted for each block. k-means clustering technique is used to cluster the blocks into different cluster. The feature vectors of each cluster blocks are lexicographically sorted by radix sort, and then a similarity measure is calculated between each nearby blocks to determine their similarity. The experimental results show that the proposed method can detect the duplicated regions efficiently even when an image was modified by jpeg compression, rotation and smoothing conditions. The proposed system reduced processing time up to 75% of other previous works.
数字图像篡改已成为一种普遍的信息篡改趋势。复制-移动伪造是使用的篡改类型之一。图像伪造是一门检测图像篡改的科学,无论是否事先知道源图像(主动)或没有(被动)。本文提出了一种即使被复制区域在空间域中进行了旋转修改,也能快速有效地检测出复制-移动区域的方法。该方法通过块间并行比较加速块匹配策略。首先将图像分割成固定大小的重叠块,然后对每个块提取特征;采用k-均值聚类技术将数据块聚到不同的聚类中。对每个聚类块的特征向量按字典顺序进行基数排序,然后计算邻近块之间的相似性度量以确定它们的相似性。实验结果表明,该方法在jpeg压缩、旋转、平滑等条件下均能有效检测出重复区域。建议的系统将处理时间减少到以前其他工作的75%。
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引用次数: 11
EMD thresholding and denoising inspired by wavelet technique 基于小波变换的EMD阈值和去噪
Pub Date : 2014-12-01 DOI: 10.1109/ICCES.2014.7030940
S. Elgamel
Empirical mode decomposition (EMD) is used as denoising technique to enhance the signal to noise ratio (SNR) for noisy signals. A new EMD denoising algorithm named EMD iterative altering thresholding and denoising (EMD-IATD) based on the traditional EMD thresholding and denoising (EMD-TD) and inspirited Wavelet denoising technique is developed in this paper. The improved SNR of the new EMD-IATD over the traditional EMD-TD algorithm is assessed using range of simulated and real environments.
采用经验模态分解(EMD)作为去噪技术来提高噪声信号的信噪比。本文在传统的EMD阈值与去噪(EMD- td)和启发小波去噪技术的基础上,提出了一种新的EMD迭代改变阈值与去噪(EMD- iatd)算法。利用模拟和真实环境对新EMD-IATD算法相对于传统EMD-TD算法的信噪比进行了评估。
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引用次数: 3
Acceleration of accurate floating point operations using SIMD 使用SIMD加速精确浮点运算
Pub Date : 2014-12-01 DOI: 10.1109/ICCES.2014.7030962
DiaaEldin M. Abdalla, A. M. Zaki, Ayman M. Bahaa-Eldin
Several computing systems that use decimal number calculations suffer from the accumulation and propagation of errors. Decimal numbers are represented using specific length floating point formats and hence there will always be a truncation of extra fraction bits causing errors. Several solutions had been proposed for such a problem. Among those accurate calculation systems was the usage of vectors of floating point numbers to represent decimal values with very large accuracy, known as Multi-Number System (MN). Unfortunately, MN calculations are time consuming and are not suitable for real time applications. Several attempts for special architectures had been proposed to speed up those calculations. In this work, the Single Instruction Multiple Data (SIMD) paradigm found in modern CPUs is exploited to accelerate the MN calculations. The basic arithmetic operation algorithms had been modified to utilize the SIMD architecture and a new Square representation of operands had been proposed, this representation was introduced because the MN operations are sequential and iterative, and thus we can't apply the SIMD parallel instructions directly. The proposed architecture has an execution time that is 35% of the original MN execution time for the division, which is the most time consuming operation while preserving the same accuracy.
一些使用十进制数计算的计算系统受到误差积累和传播的影响。十进制数使用特定长度的浮点格式表示,因此总是会截断额外的分数位,从而导致错误。针对这个问题已经提出了几种解决办法。在这些精确的计算系统中,使用浮点数向量以非常高的精度表示十进制值,称为多数字系统(Multi-Number System, MN)。不幸的是,MN计算非常耗时,不适合实时应用程序。为了加速这些计算,已经提出了几种特殊架构的尝试。在这项工作中,利用现代cpu中的单指令多数据(SIMD)范式来加速MN计算。将基本的算术运算算法修改为使用SIMD架构,并提出了一种新的操作数的Square表示,由于MN运算是顺序的和迭代的,因此不能直接应用SIMD并行指令。所建议的体系结构的执行时间是原始MN执行时间的35%,这是在保持相同精度的情况下最耗时的操作。
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引用次数: 1
A fast non-local based stereo matching algorithm using graph cuts 一种基于图切的快速非局部立体匹配算法
Pub Date : 2014-12-01 DOI: 10.1109/ICCES.2014.7030943
Doaa A. Altantawy, Marwa Obbaya, S. Kishk
In this paper, a new segment-based stereo matching algorithm (FastNL_Gc) is introduced. FastNL_Gc depends locally on the introduced Non-Local-Mean (NL-Mean) approach that provides a fast denoising technique with an edge preserving property in the initial disparity map estimation and globally on graph cuts for the disparity plane assignment using a new energy formulation of the stereo problem in segment domain. The methodology is tested on Middlebury stereo benchmark and the results indicate that the proposed FastNL_Gc method is compatible with the current state-of-the-art stereo matching algorithms in dealing with the conventionally difficult areas, such as textureless regions, disparity discontinuous boundaries and occluded portions.
本文提出了一种新的基于分段的立体匹配算法FastNL_Gc。FastNL_Gc局部依赖于引入的非局部均值(NL-Mean)方法,该方法在初始视差图估计中提供了一种具有边缘保持特性的快速去噪技术,全局依赖于使用分段域立体问题的新能量公式进行视差平面分配的图切割。在Middlebury立体基准上对该方法进行了测试,结果表明,FastNL_Gc方法在处理无纹理区域、视差不连续边界和遮挡部分等常规困难区域方面与当前最先进的立体匹配算法兼容。
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引用次数: 10
期刊
2014 9th International Conference on Computer Engineering & Systems (ICCES)
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