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2015 IEEE Seventh International Conference on Intelligent Computing and Information Systems (ICICIS)最新文献

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Prospective, knowledge based clinical risk analysis: The OPT-model 前瞻性的、基于知识的临床风险分析:opt模型
T. Schrader, K. Loewe, Lutz Pelchen, Eberhard Beck
5%-10% of all medical procedures are erroneous. It is estimated that about 10.000 persons in Germany die due to errors in medical interventions. The clinical risk management analyses the reasons for errors and avoidable events, in most cases retrospectively. Approaches such as Hazards & Operability Study (HAZOP) are applied routinely in technical environments. In a quite small number of rather medical specific procedures especially in laboratories the risk management demands HAZOP. In the clinical domain this approach is not used due to the difficulties to describe medical processes and task with all different kinds of properties.
5%-10%的医疗程序是错误的。据估计,德国约有1万人因医疗干预中的错误而死亡。临床风险管理分析错误和可避免事件的原因,在大多数情况下是回顾性的。危险与可操作性研究(HAZOP)等方法通常应用于技术环境。在相当少数的医疗特定程序中,特别是在实验室中,风险管理要求HAZOP。在临床领域,由于难以描述具有各种不同性质的医疗过程和任务,因此不使用这种方法。
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引用次数: 1
Performance testing as a service for web applications 性能测试作为web应用程序的服务
Amira Ali, N. Badr
Software testing is a vital activity that is undertaken during software engineering life cycle to ensure software quality and reliability. Performance testing is a type of software testing that is done to shows how web application behaves under a certain workload. Cloud computing as an emerging technology can be used in the field of software engineering to provide cloud testing in order to overcome all deficiencies of conventional testing by leveraging cloud computing resources. As a result, testing-as-a-service (TaaS) is introduced as a service model that performs all testing activities in fully automated manner, on demand with a pay-for use basis. Moreover, TaaS increases testing efficiency and reduces time and cost required for testing. In this paper, performance TaaS framework for web applications is introduced which provides all performance testing activities including automatic test case generation and test execution. In addition, the proposed framework addresses many issues as: maximize resource utilization and continuous monitoring to ensure system reliability.
软件测试是软件工程生命周期中为保证软件质量和可靠性而进行的一项重要活动。性能测试是一种软件测试,用于显示web应用程序在特定工作负载下的表现。云计算作为一种新兴技术,可用于软件工程领域提供云测试,利用云计算资源克服传统测试的所有不足。因此,测试即服务(TaaS)作为一种服务模型被引入,该模型以完全自动化的方式执行所有测试活动,并在按需付费的基础上使用。此外,TaaS提高了测试效率,减少了测试所需的时间和成本。本文介绍了面向web应用程序的性能TaaS框架,该框架提供了所有性能测试活动,包括自动生成测试用例和自动执行测试用例。此外,提出的框架解决了许多问题,如:最大限度地利用资源和持续监测,以确保系统的可靠性。
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引用次数: 10
Analysis of Automatic Multi-label GrabCut using NPR for natural image segmentation 基于NPR的自动多标签GrabCut自然图像分割分析
D. Khattab, H. M. Ebeid, M. Tolba, A. S. Hussein
Automatic Multi-label GrabCut is an extension of the standard GrabCut technique to segment a given image automatically into its natural segments without any user intervention. The Normalized Probabilistic Rand (NPR) index is able to give meaningful comparisons by comparing different images and different segmentations of the same image. In this paper, more analysis is conducted to evaluate the efficiency of the developed automatic multi-label GrabCut using the NPR index. Based on using more than one human ground truth, segmentations are conducted on a large scale of the Berkeley's benchmark of natural images. The NPR, PR and GCE metrics produced acceptable accuracy measures emphasizing the scalability of the proposed technique for large scale datasets. Comparisons are applied for different images and experiments show that the NPR is the most efficient score to determine good segmentation compared to other metrics.
自动多标签GrabCut是标准GrabCut技术的扩展,可以自动将给定图像分割成其自然片段,而无需任何用户干预。归一化概率兰德(NPR)指数能够通过比较不同的图像和同一图像的不同分割来给出有意义的比较。本文利用NPR指标对所开发的自动多标签抓取切割的效率进行了进一步的分析。基于使用多个人类地面真理,在伯克利自然图像基准的大规模上进行分割。NPR、PR和GCE指标产生了可接受的精度测量,强调了所提出的技术在大规模数据集上的可扩展性。对不同的图像进行了比较,实验表明,与其他指标相比,NPR是确定良好分割的最有效分数。
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引用次数: 0
An intelligent optimization approach for storage space allocation at seaports: A case study 港口存储空间分配的智能优化方法:一个案例研究
Gamal Abd El-Nasser A. Said, El-Sayed M. El-Horbaty
Storage space allocation problem at container terminals is NP-hard combinatorial optimization problem. This paper proposes a new approach based on genetic algorithm to optimize the solution for storage space allocation problem in container terminal at seaports. A new mathematical model is formulated to avoid bottlenecks in container yard operations, and to minimize vessels service time in port. Also, a simulation model using discrete event simulation tool is conducted to optimize the solution for storage space allocation problem is presented in this study. The proposed approach is applied on a real case study data of container terminal at Damietta port. The computational results show the effectiveness of the proposed approach.
集装箱码头存储空间分配问题是一个NP-hard组合优化问题。本文提出了一种基于遗传算法的港口集装箱码头存储空间分配问题的优化求解方法。为了避免集装箱堆场作业中的瓶颈,最大限度地减少船舶在港服务时间,建立了新的数学模型。同时,利用离散事件仿真工具建立仿真模型,对存储空间分配问题进行优化求解。将该方法应用于达米埃塔港集装箱码头的实际案例研究数据。计算结果表明了该方法的有效性。
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引用次数: 5
Deep analysis of knowledge in one's writings 对著作中知识的深刻分析
E. Elsayed, Eman M. Elgamal, K. Eldahshan
Reading the opinion behind the text is a big challenge. In another way, we need to automatically read opinions and moods as a natural language. Ontology -based plays a main role to solve the problems in this field. That is from the features of the ontology based as covering the semantics of the concepts. So, in this paper, we propose a flexible classification opinion mining tool. This proposed method based on ontology- based. The proposed method uses NLTK (Natural Language Processing Toolkit) with Python as a useful knowledge to get more representative word occurrences in the corpus. Also, we not only use a WordNet and SentiWordNet ontologies to assign the word as POS (part of speech), but we also create a specific purpose ontology by OWL editor as Protégé. Then we create a more general opinion mining tool where the specific purpose ontology file was selected to use for classification the text. We apply our proposed method on lists of long texts for different writers, and then we can classify these writers depending on their writings.
阅读文章背后的观点是一个很大的挑战。换句话说,我们需要自动地将观点和情绪视为一种自然语言。基于本体的方法在解决这一领域的问题中起着重要的作用。即从本体的特征出发,作为覆盖语义的概念。因此,本文提出了一种灵活的分类意见挖掘工具。提出了一种基于本体的方法。该方法使用NLTK(自然语言处理工具包)和Python作为有用的知识,以在语料库中获得更多有代表性的单词出现。同样,我们不仅使用WordNet和SentiWordNet本体来将单词指定为词性(词性),而且我们还通过OWL编辑器创建了一个特定用途的本体,作为prot。然后,我们创建了一个更通用的意见挖掘工具,其中选择了特定目的本体文件用于文本分类。我们将我们提出的方法应用于不同作家的长文本列表,然后我们可以根据这些作家的作品对他们进行分类。
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引用次数: 0
Evaluation of feature selection on human activity recognition 特征选择在人体活动识别中的评价
Hussein Mazaar, E. Emary, H. Onsi
The paper presents an approach for feature selection in human activity recognition. Features are extracted based on spatiotemporal orientation energy and activity template, while feature reduction has been studied thoroughly using various techniques. Due to high dimensional data from extraction phase, a model with less features which are important and significant can build attractive, interpretative and accurate model. Finally, activity classification is done using SVM. With experiments to classify six activities of the KTH Dataset, significant feature reductions were reported with optimal embedded selection recorded for Gradient Boosting and R-Square techniques. The results show a reduction in time and improvement in accuracy. The Comparison to related work were given.
提出了一种人体活动识别中的特征选择方法。特征提取主要基于时空方向能和活动模板,而特征约简则采用多种技术进行了深入研究。由于提取阶段的数据是高维的,用较少的重要和有意义的特征来构建具有吸引力、可解释性和准确性的模型。最后,利用支持向量机对活动进行分类。通过对KTH数据集的六个活动进行分类的实验,报告了显著的特征减少,并记录了梯度增强和r平方技术的最佳嵌入选择。结果表明,该方法缩短了时间,提高了精度。并与相关工作进行了比较。
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引用次数: 8
Strategy to establish an e-library for university theses in the central library of the University of Mustansiriya (experimental study) 穆斯坦西里亚大学中央图书馆建立大学论文电子图书馆的策略(实验研究)
Zainab Abdel Wahed El-Waily
The enormous acceleration in using information technology beside the Changing and complexity of the Beneficiaries tasks although that the researchers have no much time, for one side, From another side The emergence of the Internet network the strong contender for digital libraries, all of that led to the need to make our libraries keep pace with the current reality through opening the digital libraries as a part of its traditional libraries or independently from it. But unfortunately most of the digital libraries establishment experiments have failed in doing its job for many reasons, from the most important reasons is that there is no the needed strategy for establish the digital library, and from that the researchers start focus on how important is the establishment strategy and it is needed to go throw each stage in the Strategy in order to have a successful experiment achieving the tasks which it has been built for.
信息技术的飞速发展,受益人任务的变化和复杂性,虽然研究人员没有太多的时间,但从一方面来说,从另一方面来说,互联网网络的出现是数字图书馆的有力竞争者,这一切都导致了我们需要通过将数字图书馆作为传统图书馆的一部分或独立于传统图书馆开放,使我们的图书馆跟上当前的现实。但不幸的是,大多数数字图书馆建设实验都失败了,原因有很多,最重要的原因是没有建立数字图书馆所需的战略,从这一点开始,研究者们开始关注建立战略的重要性,以及需要把战略的每个阶段都扔掉,才能有一个成功的实验来实现它所建立的任务。
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引用次数: 2
Trust management in cloud computing: A survey 云计算中的信任管理:调查
Merrihan B. Monir, M. H. AbdElaziz, Abdelaziz A. Abdelhamid, El-Sayed M. Ei-Horbaty
Cloud computing is a new computing model that involves outsourcing of computer technologies due to the lack of their availability in certain locations. However, when there is no previous experience between cloud service providers and their consumers, consumers often hold a degree of uncertainty about the reliability, quality and performance of the services being offered. This paper presents a survey about the current trust management techniques regarding to the performance of cloud service providers taking into consideration other aspects like privacy, security, credibility, user feedback, etc.
云计算是一种新的计算模型,由于在某些地方缺乏可用性,它涉及到计算机技术的外包。然而,当云服务提供商与其消费者之间没有以往的经验时,消费者往往对所提供服务的可靠性、质量和性能存在一定程度的不确定性。本文介绍了一项关于云服务提供商性能的当前信任管理技术的调查,同时考虑了隐私、安全、可信度、用户反馈等其他方面。
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引用次数: 16
Classification of thrombosis collagen diseases based on C4.5 algorithm 基于C4.5算法的血栓性胶原蛋白疾病分类
S. Soliman, Safia Abbas, A. M. Salem
Recently, collagen diseases propagated due to many factors such as pressure and pollution. Thrombosis is one of the most famous collagen diseases that obstruct the blood flow causing vital complications for crucial parts of the circulatory system. Such diseases cause a high risk for the doctors due to the huge number of the laboratory examinations and the efforts to diagnosis. Accordingly, this paper implements C4.5 algorithm, as one of the most famous data mining techniques, on real thrombosis dataset. The dataset was collected from Chiba University as a challenging dataset for thrombosis diagnosis. The results show that the C4.5 could diagnose the thrombosis degree with accuracy 98.4%.
近年来,由于压力、污染等多种因素,胶原蛋白疾病不断蔓延。血栓形成是最著名的胶原蛋白疾病之一,它会阻碍血液流动,导致循环系统关键部位的严重并发症。由于大量的实验室检查和诊断工作,这类疾病对医生来说风险很高。因此,本文在真实血栓形成数据集上实现了C4.5算法这一最著名的数据挖掘技术。该数据集来自千叶大学,是血栓诊断的一个具有挑战性的数据集。结果表明,C4.5对血栓形成程度的诊断准确率为98.4%。
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引用次数: 6
A study on PCG as a biometric approach PCG作为生物识别方法的研究
M. Bassiouni, W. Khalifa, EL-Sayed A. El Dahshan, Abdel-Badeeh M. Salam
Phonocardiogram (PCG) is an emerging biometric modality that has seen about fifteen years of development. This paper provides a review of some of the most famous techniques that have been applied to the use of the PCG for biometric recognition. The paper also presents datasets used in PCG as well as the devices needed to capture them. PCG main modules are features extraction, reduction and classification schemes. The paper is concluded by a comparative analysis of the authentication performance of PCG biometric systems.
心音图(PCG)是一种新兴的生物识别技术,已经发展了大约15年。本文提供了一些最著名的技术,已应用于使用PCG生物特征识别的回顾。本文还介绍了PCG中使用的数据集以及捕获这些数据所需的设备。PCG主要模块有特征提取、约简和分类方案。最后对PCG生物识别系统的认证性能进行了比较分析。
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引用次数: 4
期刊
2015 IEEE Seventh International Conference on Intelligent Computing and Information Systems (ICICIS)
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