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2020 IEEE 14th International Conference on Application of Information and Communication Technologies (AICT)最新文献

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Transformation, Analysis and Visualization of Distributed Temperature Sensing Data generated by Oil Wells 油井分布式温度传感数据的转换、分析与可视化
I. Karimov, S. Jafarova, M. Zeynalli, S. Rustamov, A. Adamov, Aslan Babakhanov
This research paper examines the full lifecycle of the case of turning the gas and oil industry to a data-driven operation model. The study presents the approach of re-engineering production data, building a predictive model for temperature forecast, statistical analysis, and visualization of Distributed Temperature Sensing (DTS) data provided by the oil-gas industry. For better analysis, the raw data have been pre-processed and organized according to the proper model. Furthermore, after the data organization, we proceed with observing relationships among three features (Date, Depth and Temperature), analyze vague upheavals and similarities utilizing plot histograms, scatterplots, box plots, heatmaps, violin plots for better visualization. Since the drastic temperature change indicates the anomaly, several alternative Outlier Detection Techniques are offered to predict early equipment failure and prevent production outage. Our results indicated a high correlation between depth and temperature, presence of trend in temperature distribution, and temperature drops in specific ranges. Proper analysis of the data allows the specialist to understand reservoir performance and prolong the production file of the wells.
本研究报告探讨了油气行业转向数据驱动运营模式的整个生命周期。该研究提出了重新设计生产数据的方法,建立了一个预测模型,用于温度预测、统计分析和油气行业提供的分布式温度传感(DTS)数据的可视化。为了更好地分析,原始数据已经按照适当的模型进行了预处理和组织。此外,在数据组织之后,我们继续观察三个特征(日期、深度和温度)之间的关系,利用直方图、散点图、箱形图、热图和小提琴图来分析模糊的剧变和相似性,以更好地可视化。由于剧烈的温度变化表明异常,因此提供了几种替代的异常检测技术来预测早期设备故障并防止生产中断。结果表明,深度与温度高度相关,温度分布存在趋势,温度下降在特定范围内。对数据进行适当的分析可以帮助专家了解储层的动态,并延长油井的生产时间。
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引用次数: 0
Algorithm for the Abnormal Ventricular Electrical Excitation Detection 异常心室电兴奋检测算法
Z. Yuldashev, A. Nemirko, D. Ripka
Detection algorithm of the ventricular late potentials using surface ECG signal for the diagnostics of abnormal electrical excitation of ventricular myocardium is developed, ventricular late potentials indicators reflecting the area size and degree of the ventricular excitation abnormality, verification method of abnormality detection using intracardial electrograms are suggested.
提出了利用体表心电信号检测心室晚电位诊断心室心肌异常电兴奋的算法,提出了反映心室兴奋异常面积大小和程度的心室晚电位指标,以及心内电图检测异常的验证方法。
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引用次数: 0
Flying Ad hoc Network Expedited by DTN Scenario: Reliable and Cost-effective MAC Protocols Perspective 由DTN场景加速的飞行自组织网络:可靠和经济的MAC协议的观点
Sobiya Arsheen, A. Wahid, Khaleel Ahmad, Khujamatov Khalim
Flying Adhoc Network (FANET) is an emerging topic of research in the wireless network area, FANET has several common features with its predecessor e.g. Mobile Adhoc Network (MANET) and Vehicle Adhoc Network (VANET), but the network has several unique features also which make it different from other networks. The sparseness of nodes, coupled with frequent changing of topology significantly affects the data transmission rate of the network. To overcome this problem, FANET can be assisted with Delay Tolerant Network (DTN) approach to exploit its mobility and routing features. The main aim of this work is to make Flying Adhoc Network reliable by deploying two MAC protocols i.e. IEEE 802.11 and IEEE 802.15 and realize the functionality of Delay Tolerant Network (DTN) in a FANET.
飞行自组网(Flying Adhoc Network,简称FANET)是无线网络领域的一个新兴研究课题,它既有其前身移动自组网(MANET)和车载自组网(VANET)的一些共同特点,又有一些独特的特点,使其区别于其他网络。节点的稀疏性,加上拓扑结构的频繁变化,极大地影响了网络的数据传输速率。为了克服这一问题,可以利用容延迟网络(DTN)方法来辅助FANET,利用其移动性和路由特性。本工作的主要目的是通过部署IEEE 802.11和IEEE 802.15两种MAC协议,使飞行Adhoc网络可靠,并在FANET中实现延迟容忍网络(DTN)功能。
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引用次数: 20
Web-based Sound and Speech Training Software to Help Hearing-impaired People 帮助听障人士的基于网络的声音和语言训练软件
M. Farkhadov, N. Petukhova, Mukhabbat Farkhadova
This paper proposes a computerized audio simulator to teach how to correctly pronounce sounds, syllables, and words of the Russian language; the simulator is based on automatic speech recognition systems. The sound and speech simulator is designed to help hearing-impaired people to learn how to correctly pronounce sounds. If we deploy such a service on the Internet and provide high-speed online access to the service, we significantly increase the number of people who can learn how to pronounce sounds.
本文提出了一种计算机音频模拟器,用于教授俄语语音、音节和单词的正确发音;该模拟器基于自动语音识别系统。声音和语音模拟器是为了帮助听力受损的人学习如何正确发音而设计的。如果我们在互联网上部署这样的服务,并提供高速在线访问服务,我们将大大增加能够学习如何发音的人数。
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引用次数: 0
Threats Classification Method for the Transport Infrastructure of a Smart City 智慧城市交通基础设施威胁分类方法
K. Izrailov, A. Chechulin, L. Vitkova
The concept of a Smart City is the forefront in the development of our near future. One of the most important parts of such cities is the transport infrastructure. Threats implementation for such infrastructure can have critical consequences for a city. To prevent such threats in the future we should investigate and counteraction them in the present. The first step in this way can be the creation of a threats classification for the transport infrastructure of a Smart City. The paper describes a set of methods that can be used for this. As a result, a scheme for categorical and cluster classifications creation is proposed. The categorical classification relies on the division of categories for elements grouping. The cluster one uses machine learning methods for elements grouping. Examples of classifications applying for the top-10 threats from the official state database are given.
智慧城市的概念是我们不久的将来发展的前沿。这些城市最重要的部分之一是交通基础设施。此类基础设施的威胁实施可能对城市产生严重后果。为了防止将来出现这种威胁,我们现在就应该对它们进行调查和反击。以这种方式进行的第一步可以是为智慧城市的交通基础设施创建威胁分类。本文介绍了一套可用于此的方法。在此基础上,提出了一种分类和聚类分类创建方案。类别分类依赖于对元素分组的类别划分。集群一使用机器学习方法对元素进行分组。给出了应用于国家官方数据库的前10大威胁的分类示例。
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引用次数: 1
Improvement the schemes and models of detecting network traffic anomalies on computer systems 改进计算机系统网络流量异常检测的方案和模型
Yusupov Sabirjan Yusupdjanovich, Gulomov Sherzod Rajaboevich
This paper proposes an approach to the classification of network anomalies and provides a description of the relationship of anomalies classified due to the occurrence and nature of changes in network traffic. A scheme for detecting network anomalies and abuses based on network traffic indicators also models for identifying and detecting network anomalies are presented.
本文提出了一种网络异常分类的方法,描述了网络流量变化的发生和性质所分类的异常之间的关系。提出了一种基于网络流量指标的网络异常和滥用检测方案,以及识别和检测网络异常的模型。
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引用次数: 2
An Experimental Design Approach to Analyse the Performance of Island-Based Parallel Artificial Bee Colony Algorithm 基于孤岛的并行人工蜂群算法性能分析的实验设计方法
Thaer Thaher, Badie Sartawi
The Artificial Bee Colony (ABC) is a novel nature-inspired metaheuristic optimization algorithm that mimics the behavior of honey bees searching for food sources. The main drawback of ABC, similar to the most of metaheuristics, is the premature convergence (i.e., the earlier stuck into local optima). Recently, the structured population approach, in which the individuals are distributed into multiple sub-populations (called islands), has been widely exploited to maintain the required diversity during the search process and thus reducing the prematurity problem. In this paper, the island model, which is a common structured population approach, is incorporated with the ABC to introduce a parallel variant called (iABC). Besides, an experimental design approach is proposed to analyze the sensitivity of iABC to the parameters of the island model as well as the main specific parameters. The linear regression model and the Analysis of variance (ANOVA) are utilized to estimate the effect of parameters and identify the importance of them. Two well-known benchmark functions are used for evaluation purposes. Experimental results revealed that most parameters and their low-order interactions have a significant influence on the performance of the iABC. Furthermore, the proposed iABC proved its superiority compared to other state-of-the-art algorithms.
人工蜂群(ABC)是一种新颖的自然启发的元启发式优化算法,它模仿蜜蜂寻找食物来源的行为。ABC的主要缺点,类似于大多数元启发式,是过早收敛(即,早期陷入局部最优)。近年来,将个体分布到多个亚种群(称为岛屿)中的结构化种群方法已被广泛用于在搜索过程中保持所需的多样性,从而减少早产问题。本文将海岛模型作为一种常见的结构化种群方法,与ABC相结合,引入了一种并行的变量(iABC)。此外,提出了一种实验设计方法来分析iABC对岛屿模型参数和主要具体参数的敏感性。利用线性回归模型和方差分析(ANOVA)来估计参数的影响和识别它们的重要性。两个众所周知的基准函数用于评估目的。实验结果表明,大多数参数及其低阶相互作用对iABC的性能有显著影响。此外,与其他最先进的算法相比,所提出的iABC证明了其优越性。
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引用次数: 3
Reliable Priority Based QoS Real-Time Traffic Routing in VANET: Open Issues & Parameter VANET中基于可靠优先级的QoS实时流量路由:开放问题与参数
K. Nisar, A. Mu'azu, Ibrahim A. Lawal, Sohrab Khan, Shuaib K. Memon
It has proven that to provide priority to different traffic types in wireless vehicular networking (VANET) is attracting wide attention for guaranteeing high quality real-time traffic routing. Choosing a reliable and stable route with Quality of Service (QoS) constraints is always a challenging task because of the high mobility in VANET. This paper proposes an approach that prioritizes the transmission of traffic data packet according to the transmission distance and urgency metrics of messages before making a selection of routes. The approach utilizes a priority classifying a mechanism to differentiate traffic information into various priorities imposed in the VANET communications. The performance of the proposed approach was simulated extensively using NCTUns simulator in terms of throughput, packet loss and delay. The results obtained show efficient solutions on the impact of mobility for the prioritized flows in enhancing safety messaging. This approach makes safety messages to be transmitted with high reliability and low delay as compared to non-prioritized traffic flows.
实践证明,在无线车联网(VANET)中为不同的交通类型提供优先级是保证高质量实时交通路由的重要途径。由于VANET的高移动性,在服务质量(QoS)约束下选择可靠稳定的路由一直是一个具有挑战性的任务。本文提出了在选择路由之前,根据报文的传输距离和紧急度指标对流量数据包的传输进行优先级排序的方法。该方法利用优先级分类机制将交通信息区分为VANET通信中施加的各种优先级。利用NCTUns模拟器对该方法的吞吐量、丢包率和时延进行了仿真。得到的结果显示了在增强安全消息传递中对优先流的移动性影响的有效解决方案。与非优先级交通流相比,该方法使安全消息的传输具有高可靠性和低延迟。
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引用次数: 3
Explained Artificial Intelligence Helps to Integrate Artificial and Human Intelligence Into Medical Diagnostic Systems: Analytical Review of Publications 解释人工智能有助于将人工智能和人类智能集成到医疗诊断系统中:出版物的分析评论
M. Farkhadov, Aleksander Eliseev, N. Petukhova
Artificial intelligence-based medical systems can by now diagnose various disorders highly accurately. However, we should stress that despite encouraging and ever improving results, people still distrust such systems. We review relevant publications over the past five years, to identify the main causes of such mistrust and ways to overcome it. Our study showes that the main reasons to distrust these systems are opaque models, blackbox algorithms, and potentially unrepresentful training samples. We demonstrate that explainable artificial intelligence, aimed to create more user-friendly and understandable systems, has become a noticeable new topic in theoretical research and practical development. Another notable trend is to develop approaches to build hybrid systems, where artificial and human intelligence interact according to the teamwork model.
目前,基于人工智能的医疗系统可以非常准确地诊断各种疾病。然而,我们应该强调的是,尽管令人鼓舞和不断改善的结果,人们仍然不信任这样的系统。我们审查了过去五年的有关出版物,以确定这种不信任的主要原因和克服这种不信任的方法。我们的研究表明,不信任这些系统的主要原因是不透明的模型、黑箱算法和潜在的不具代表性的训练样本。我们证明,可解释的人工智能,旨在创造更多的用户友好和可理解的系统,已经成为一个值得注意的理论研究和实践发展的新课题。另一个值得注意的趋势是开发构建混合系统的方法,其中人工智能和人类智能根据团队合作模型进行交互。
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引用次数: 2
Towards Secured Service Provisioning for the Internet of Healthcare Things 面向医疗物联网的安全服务配置
Fahiba Farhin, M. S. Kaiser, M. Mahmud
The Internet of Healthcare Things (IoHT) is an emerging intelligent pervasive framework that interconnects smart healthcare devices, stakeholders (e.g., doctors, patients, researchers, healthcare professionals, etc.), and infrastructure using smart sensors. Emergence of novel tools and techniques for data sensing and analysis during the last decade have allowed many researchers to develop and deliver services tailored for the IoHT. This resulted in a considerable number of research outcomes addressing the applications, challenges, and probable solutions targeting secured communication within the IoHT framework. Despite considerable efforts dedicated to it, secured service provisioning still remains as a major challenge. This work provides a detailed account on the current challenges and solutions towards providing secured service provisioning focusing on the IoHT attacks and countermeasures with an aim to facilitate more investigation in this area.
医疗物联网(IoHT)是一种新兴的智能普及框架,它将智能医疗设备、利益相关者(例如医生、患者、研究人员、医疗保健专业人员等)和使用智能传感器的基础设施相互连接。在过去的十年中,数据传感和分析的新工具和技术的出现,使许多研究人员能够开发和提供适合IoHT的服务。这导致了相当多的研究成果,解决了IoHT框架内安全通信的应用、挑战和可能的解决方案。尽管为此付出了相当大的努力,但安全服务供应仍然是一个主要挑战。这项工作详细介绍了当前的挑战和解决方案,以提供安全的服务供应,重点是物联网攻击和对策,旨在促进该领域的更多调查。
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引用次数: 10
期刊
2020 IEEE 14th International Conference on Application of Information and Communication Technologies (AICT)
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