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Data Mining Applications in Big Data 数据挖掘在大数据中的应用
Pub Date : 2015-09-20 DOI: 10.18495/COMENGAPP.V4I3.155
Lidong Wang, Guanghui Wang
Data mining is a process of extracting hidden, unknown, but potentially useful information from massive data. Big Data has great impacts on scientific discoveries and value creation. This paper introduces methods in data mining and technologies in Big Data. Challenges of data mining and data mining with big data are discussed. Some technology progress of data mining and data mining with big data are also presented.
数据挖掘是从海量数据中提取隐藏的、未知的、但可能有用的信息的过程。大数据对科学发现和价值创造产生了巨大影响。本文介绍了数据挖掘的方法和大数据技术。讨论了数据挖掘和大数据数据挖掘的挑战。介绍了数据挖掘和大数据数据挖掘的一些技术进展。
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引用次数: 6
RFID-based Drug Management and Monitoring System, Case of Public Hospitals in Tanzania, A Review Paper 基于rfid的药品管理与监测系统,坦桑尼亚公立医院案例,综述
Pub Date : 2015-09-20 DOI: 10.18495/COMENGAPP.V4I3.151
Prisila Ishabakaki, S. Kaijage
Radio frequency Identification (RFID) is an automatic identification technology that enables tracking of people and objects. Recently, RFID technology has been deployed in hospital environment for patient and equipment tracking, surgical equipment monitoring, medication monitoring and improving health record access in emergency cases. The main advantages RFID technology are to provide resource optimization, quality customers’ care, enhanced accuracy, efficient and effective business processes and healthcare processes. The pharmacy department undergoes challenges such as complex manual work of record keeping and inventory management. The RFID technology can be deployed in pharmacy hospital unit to automate pharmacy process. In this work we present a review on current pharmacy management practices in the case study of public hospital in Tanzania, review on different research work to address the pharmacy challenges and finally proposed a system to overcome the limitation identified in the current systems.
无线射频识别(RFID)是一种自动识别技术,可以跟踪人和物体。近年来,RFID技术已应用于医院环境中,用于患者和设备的跟踪、手术设备的监控、药物的监控以及改善急诊病例的健康记录访问。RFID技术的主要优点是提供资源优化、优质的客户护理、提高准确性、高效和有效的业务流程和医疗保健流程。药房部门面临着诸如记录保存和库存管理等复杂手工工作的挑战。RFID技术可应用于医院药房,实现药房流程自动化。在这项工作中,我们在坦桑尼亚公立医院的案例研究中对当前的药房管理实践进行了回顾,回顾了不同的研究工作,以解决药房的挑战,最后提出了一个系统,以克服当前系统中确定的限制。
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引用次数: 3
C4.5 Versus Other Decision Trees: A Review C4.5与其他决策树的对比:综述
Pub Date : 2015-09-20 DOI: 10.18495/COMENGAPP.V4I3.141
Salih Ozsoy, Gökhan Gümüş, Savriddin Khalilov
In this study, Data Mining, one of the latest technologies of the Information Systems, was introduced and Classification a Data Mining method and the Classification algorithms were discussed. A classification was applied by using C4.5 decision tree algorithm on a dataset about Labor Relations from http://archive.ics.uci.edu/ml/datasets.html . Finally, C4.5 algorithm was compared to some other decision tree algorithms. C4.5 was the one of the successful classifier.
本文介绍了信息系统的最新技术之一数据挖掘,并对数据挖掘的分类方法和分类算法进行了讨论。采用C4.5决策树算法对来自http://archive.ics.uci.edu/ml/datasets.html的劳动关系数据集进行分类。最后,将C4.5算法与其他决策树算法进行了比较。C4.5是一个成功的分类器。
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引用次数: 3
Fingerprint Enhancement Algorithm Based-on Gradient Magnitude for the Estimation of Orientation Fields 基于梯度幅度的指纹方向场估计增强算法
Pub Date : 2015-06-26 DOI: 10.18495/COMENGAPP.V4I2.154
Saparudin Saparudin, G. Sulong
An accurate estimation of fingerprint orientation fields is an important step in the fingerprint classification process. Gradient-based approaches are often used for estimating orientation fields of ridge structures but this method is susceptible to noise. Enhancement of fingerprint images improves the ridge-valley structure and increases the number of correct features thereby conducing the overall performance of the classification process. In this paper, we propose an algorithm to improve ridge orientation textures using gradient magnitude. That algorithm has four steps; firstly, normalization of fingerprint image, secondly, foreground extraction, thirdly, noise areas identification and marking using gradient coherence and finally, enhancement of grey level. We have used standard fingerprint database NIST-DB14 for testing of proposed algorithm to verify the degree of efficiency of algorithm. The experiment results suggest that our enhanced algorithm achieves visibly better noise resistance with other methods.
准确估计指纹方向场是指纹分类过程中的一个重要步骤。基于梯度的方法通常用于估计脊状结构的方向场,但这种方法容易受到噪声的影响。指纹图像的增强改善了脊谷结构,增加了正确特征的数量,从而提高了分类过程的整体性能。本文提出了一种利用梯度幅度来改进脊向纹理的算法。这个算法有四个步骤;首先对指纹图像进行归一化处理,其次进行前景提取,然后利用梯度相干性识别和标记噪声区域,最后进行灰度增强。我们使用标准指纹数据库NIST-DB14对算法进行了测试,验证了算法的效率程度。实验结果表明,与其他方法相比,增强算法的抗噪性能明显更好。
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引用次数: 1
Parallel Continuous Double Auction for Service Allocation in Cloud Computing 云计算中服务分配的并行连续双拍卖
Pub Date : 2015-06-20 DOI: 10.18495/COMENGAPP.V4I2.125
Nima Farajian, Hossein Ebrahim pour-komleh
Cloud Computing is a service oriented architecture in which every computing resources is delivered to users as a service. Nowadays market-oriented approach has attracted a lot of researchers because of its great ability to manage Cloud services efficiently and dynamically. Each service consists of various resources which all should be allocated to utilize the service. In this paper a parallel continuous double auction method for efficient service allocation in cloud computing is presented in which by using a novel parallel sorting algorithm at auctioneer, enables consumers to order various resources as workflow for utilizing requested services efficiently. Also in the presented method consumers and providers make bid and offer prices based on time factor. Experimental results show that proposed method is efficient in success rate, resource utilization and average connection time and also overall performance of system is improved by parallel approach.
云计算是一种面向服务的体系结构,其中每个计算资源都作为服务交付给用户。面向市场的方法以其高效、动态地管理云服务的能力吸引了众多研究者的关注。每个服务都由各种资源组成,所有这些资源都应该被分配以利用该服务。本文提出了一种用于云计算中服务高效分配的并行连续双拍卖方法,该方法通过在拍卖商处使用一种新颖的并行排序算法,使消费者能够将各种资源作为工作流进行排序,从而有效地利用所请求的服务。在该方法中,消费者和供应商根据时间因素进行出价和报价。实验结果表明,该方法在成功率、资源利用率、平均连接时间等方面具有较高的效率,并通过并行方式提高了系统的整体性能。
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引用次数: 4
Proposing a novel method for clock synchronization in WSN 提出了一种新的无线传感器网络时钟同步方法
Pub Date : 2015-06-20 DOI: 10.18495/COMENGAPP.V4I2.137
Seyed Kazem Kazeminezhad, S. Babaie, Amir Shiri
Wireless sensor networks (WSNs) of spatially distributed autonomous sensors are used to monitor physical or environmental conditions such as temperature, sound, pressure, etc. They are also used to cooperatively pass the collected data through the network to a main location. Due to the application of wireless sensor networks as a monitoring device in the real world, the physical time of the occurrence of events is important. Since WSNs have particular constraints and limitations, synchronizing the physical times for these networks is considered to be a complex task. Although many algorithms have been proposed for synchronizing time in the network, there are two main error factors in all the proposed algorithms. The first factor is the clock drift which might be caused by the influence of different environmental factors such as temperature, ambient temperature, humidity, it might be generated on crystal oscillator which is inevitable The second error factor is indeterminacy which is attributed to the existence of non-deterministic delays in sending and receiving messages between sensor nodes. These two factors together reduce the precision of synchronization algorithms. In this paper, the researchers proposed a new approach for dealing with the above-mentioned two problems and achieving better synchronization. The proposed approach is a combination of flooding time synchronization protocol (FTSP) and reference broadcast synchronization (RBS).This approach is intended to increase synchronization accuracy and network lifetime by reducing the number of synchronization messages sent between nodes and eliminating the most of non-deterministic errors in sending messages. The results of simulations conducted in the study indicated that the proposed approach is significantly more efficient than the FTSP and RBS methods in terms of parameters such as accurate synchronization, amount of sent packets and power consumption.
无线传感器网络(WSNs)由空间分布的自主传感器组成,用于监测物理或环境条件,如温度、声音、压力等。它们还用于通过网络将收集到的数据协同传递到主要位置。由于无线传感器网络作为一种监控设备在现实世界中的应用,事件发生的物理时间很重要。由于无线传感器网络具有特定的约束和限制,因此同步这些网络的物理时间被认为是一项复杂的任务。尽管已经提出了许多用于网络时间同步的算法,但在所有提出的算法中都存在两个主要的误差因素。第一个因素是时钟漂移,这可能是由于温度、环境温度、湿度等不同环境因素的影响造成的,它可能在晶体振荡器上产生,这是不可避免的;第二个误差因素是不确定性,这是由于传感器节点之间发送和接收消息时存在不确定性延迟。这两个因素共同降低了同步算法的精度。在本文中,研究人员提出了一种新的方法来处理上述两个问题,并实现更好的同步。该方法将泛洪时间同步协议(FTSP)和参考广播同步(RBS)相结合。这种方法旨在通过减少节点之间发送的同步消息数量和消除发送消息中的大多数不确定性错误来提高同步准确性和网络生命周期。仿真结果表明,该方法在同步精度、发送数据包数量和功耗等参数上明显优于FTSP和RBS方法。
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引用次数: 0
Energy efficient virtual machine placement algorithm with balanced resource utilization based on priority of resources 基于资源优先级均衡利用的高能效虚拟机布局算法
Pub Date : 2015-06-20 DOI: 10.18495/COMENGAPP.V4I2.134
Amin Rahimi, L. M. Khanli, S. Pashazadeh
The increasing energy consumption has become a major concern in cloud computing due to its cost and environmental damage. Virtual Machine placement algorithms have been proven to be very effective in increasing energy efficiency and thus reducing the costs. In this paper we have introduced a new priority routing VM placement algorithm and have compared it with PABFD (power-aware best fit decreasing) on CoMon dataset using CloudSim for simulation. Our experiments show the superiority of our new method with regards to energy consumption and level of SLA violations measures and prove that priority routing VM placement algorithm can be effectively utilized to increase energy efficiency in the clouds.
由于其成本和环境破坏,不断增加的能源消耗已成为云计算的主要关注点。虚拟机放置算法已被证明在提高能源效率从而降低成本方面非常有效。在本文中,我们引入了一种新的优先级路由VM放置算法,并使用CloudSim进行仿真,将其与CoMon数据集上的PABFD(功率感知最佳拟合减少)进行了比较。我们的实验表明了我们的新方法在能耗和SLA违规度量水平方面的优越性,并证明了优先路由VM放置算法可以有效地用于提高云中的能源效率。
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引用次数: 6
Network Attacks Detection by Hierarchical Neural Network 基于层次神经网络的网络攻击检测
Pub Date : 2015-06-18 DOI: 10.18495/COMENGAPP.V4I2.108
M. Javidi
Intrusion detection is an emerging area of research in the computer security and net-works with the growing usage of internet in everyday life. Most intrusion detection systems (IDSs) mostly use a single classifier algorithm to classify the network traffic data as normal behavior or anomalous. However, these single classifier systems fail to provide the best possible attack detection rate with low false alarm rate. In this paper,we propose to use a hybrid intelligent approach using a combination of classifiers in order to make the decision intelligently, so that the overall performance of the resul-tant model is enhanced. The general procedure in this is to follow the supervised or un-supervised data filtering with classifier or cluster first on the whole training dataset and then the output are applied to another classifier to classify the data. In this re- search, we applied Neural Network with Supervised and Unsupervised Learning in order to implement the intrusion detection system. Moreover, in this project, we used the method of Parallelization with real time application of the system processors to detect the systems intrusions.Using this method enhanced the speed of the intrusion detection. In order to train and test the neural network, NSLKDD database was used. Creating some different intrusion detection systems, each of which considered as a single agent, we precisely proceeded with the signature-based intrusion detection of the network.In the proposed design, the attacks have been classified into 4 groups and each group is detected by an Agent equipped with intrusion detection system (IDS).These agents act independently and report the intrusion or non-intrusion in the system; the results achieved by the agents will be studied in the Final Analyst and at last the analyst reports that whether there has been an intrusion in the system or not. Keywords: Intrusion Detection, Multi-layer Perceptron, False Positives, Signature- based intrusion detection, Decision tree, Nave Bayes Classifier
随着互联网在日常生活中的日益普及,入侵检测是计算机安全和网络领域的一个新兴研究领域。大多数入侵检测系统大多使用单一分类器算法将网络流量数据分类为正常行为或异常行为。然而,这些单一分类器系统无法在低虚警率的情况下提供最佳的攻击检测率。在本文中,我们提出了一种混合智能方法,使用分类器的组合来智能地做出决策,从而提高了结果模型的整体性能。一般过程是先对整个训练数据集使用分类器或聚类进行有监督或无监督的数据过滤,然后将输出应用到另一个分类器中对数据进行分类。在本研究中,我们将神经网络与监督学习和无监督学习相结合来实现入侵检测系统。此外,在本项目中,我们采用并行化的方法,实时应用系统处理器来检测系统入侵。该方法提高了入侵检测的速度。为了训练和测试神经网络,使用了NSLKDD数据库。我们创建了一些不同的入侵检测系统,每个系统都被认为是一个单独的代理,我们精确地进行了基于签名的网络入侵检测。在该设计中,攻击被分为4组,每组由配备入侵检测系统(IDS)的Agent进行检测。这些代理独立行动并报告系统中的入侵或非入侵;代理取得的结果将在Final Analyst中进行研究,最后由Analyst报告系统中是否存在入侵。关键词:入侵检测,多层感知器,误报,基于签名的入侵检测,决策树,朴素贝叶斯分类器
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引用次数: 1
Dynamic Location Modelling in 3D Beamforming for 5G Mobile Communications 5G移动通信3D波束成形中的动态位置建模
Pub Date : 2015-02-18 DOI: 10.18495/COMENGAPP.V4I1.116
A. Sasi, P. Santhiya
Mobile communication system is designed to provide reliable communication with more number of services and with low cost among multiple users. Due to limited frequency spectrum and resources, mobile communication requires more development in case of both establishing communication and maintenance in service quality. To fulfill these requirements, 5G mobile communication is being developed to provide high quality reliable communication and quality of service, by using beamforming model. As the trend of next generation mobile communication, 3D directional transmission is considered to give enhanced coverage model and reusability of frequency. Phase arrayed antenna is used in this beamforming model to give orthogonal communication among users. In this paper, a new modeling of beamforming is applied to give a new dimension by considering altitude with potential field strategy. Here phase arrayed antenna is replaced by 3-D smart antenna to improve the performance of 5G mobile communications. Performance evaluation outcomes 3D beamforming leads 2D beamforming in terms of communication delay, and uplink downlink throughput.
移动通信系统的目的是在多用户之间提供可靠、多业务、低成本的通信。由于频谱和资源的限制,无论是建立通信还是维护服务质量,移动通信都需要更多的发展。为了满足这些需求,正在开发5G移动通信,通过使用波束成形模型提供高质量可靠的通信和高质量的服务。作为下一代移动通信的发展趋势,三维定向传输被认为具有增强的覆盖模型和频率的可重用性。该波束形成模型采用相控阵天线实现用户间的正交通信。本文提出了一种新的波束形成模型,利用势场策略考虑高度,给出了波束形成的新维度。这里用3d智能天线代替相控阵天线,提高5G移动通信的性能。性能评估结果3D波束形成在通信延迟和上行下行链路吞吐量方面领先于2D波束形成。
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引用次数: 0
Network Selection Problems - QoE vs QoS Who is the Winner? 网络选择问题——QoE vs QoS谁是赢家?
Pub Date : 2015-02-18 DOI: 10.18495/COMENGAPP.V4I1.131
V. Mohanan, I. Aldmour
In network selection problem (NSP), there are now two schools of thought. There are those who think using QoE (Quality of Experience) is the best yardstick to measure the suitability of a Candidate Network (CN) to handover to. On the other hand, Quality of Service (QoS) is also advocated as the solution for network selection problems. In this article, a comprehensive framework that supports effective and efficient network selection is presented. The framework   attempts to provide a holistic solution to network selection problem that is achieved by combining both of the QoS and QoE measures.   Using this hybrid solution the best qualities in both methods are combined to overcome issues of the network selection problem According to ITU-R (International Telecommunications Union – Radio Standardization Sector), a 4G network is defined as having peak data rates of 100Mb/s for mobile nodes with speed up to 250 km/hr and 1Gb/s for mobile nodes moving at pedestrian speed. Based on this definition, it is safe to say that mobile nodes that can go from pedestrian speed to speed of up to 250 km/hr will be the norm in future. This indicates that the MN’s mobility will be highly dynamic. In particular, this article addresses the issue of network selection for high speed Mobile Nodes (MN) in 4G networks. The framework presented in this article also discusses how the QoS value collected from CNs can be fine-tuned to better reflect an MN’s current mobility scenario.
在网络选择问题(NSP)中,目前有两派思想。有些人认为使用QoE(体验质量)是衡量候选网络(CN)是否适合交接的最佳标准。另一方面,服务质量(QoS)也被提倡作为网络选择问题的解决方案。在本文中,提出了一个支持有效和高效的网络选择的综合框架。该框架试图通过结合QoS和QoE度量来提供网络选择问题的整体解决方案。根据ITU-R(国际电信联盟-无线电标准化部门)的定义,4G网络的定义是,移动节点的峰值数据速率为100Mb/s,速度高达250公里/小时,移动节点的峰值数据速率为1Gb/s,以行人速度移动。基于这一定义,可以肯定地说,移动节点可以从步行速度提高到高达250公里/小时的速度将是未来的常态。这表明MN的流动性将是高度动态的。本文特别讨论了4G网络中高速移动节点(MN)的网络选择问题。本文提供的框架还讨论了如何对从cnn收集的QoS值进行微调,以更好地反映MN的当前移动性场景。
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引用次数: 4
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Computer Engineering and Applications
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