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2021 International Conference on Digital Age & Technological Advances for Sustainable Development (ICDATA)最新文献

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引用次数: 0
Improvement of online real-time practical work platforms by optimizing routing and resource allocation in software-defined elastic optical data center networks: The case of the Cheikh Anta Diop University of Dakar 软件定义弹性光数据中心网络中通过优化路由和资源分配改进在线实时实际工作平台——以达喀尔谢赫·安踏·迪奥普大学为例
Eba Victoire Kié, M. Babri, C. Lishou, S. Ouya
Several research studies have shown that the socio-constructivist model allows learners to develop skills. This model advocates collaborative work between peers and pedagogical activities through practical work. With the advent of the COVID-19 pandemic and its constraints, universities have turned to online courses. Despite the use of online collaboration tools, we are finding that some real-time practical work based on screen sharing is difficult to do given the time lag between transmission and reception due to considerable latency. To overcome this latency problem we propose in this paper an algorithm that optimizes routing and resource allocation in software-defined optical data center networks, using Virtual Extensible Networks (VXLANs). This allows the implementation of socioconstructivist models while minimizing latency. Our solution is tested at the Cheikh Anta Diop University of Dakar and has significantly improved latency by making online courses and practical work in the context of COVID-19 fluid and synchronous.
几项研究表明,社会建构主义模式允许学习者发展技能。这种模式提倡同伴之间的协作,通过实际工作进行教学活动。随着新冠肺炎疫情的到来及其制约因素,大学纷纷转向在线课程。尽管使用了在线协作工具,但我们发现,由于传输和接收之间存在相当大的延迟,因此基于屏幕共享的一些实时实际工作很难完成。为了克服这种延迟问题,本文提出了一种算法,利用虚拟可扩展网络(vxlan)优化软件定义光数据中心网络中的路由和资源分配。这允许在最小化延迟的同时实现社会建构主义模型。我们的解决方案在达喀尔谢赫·安塔·迪奥普大学进行了测试,通过使COVID-19背景下的在线课程和实际工作流畅和同步,显著改善了延迟。
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引用次数: 0
Multinomial Naive Bayes Categorization for Semantic Web Services 语义Web服务的多项朴素贝叶斯分类
Naoufal El Allali, Mourad Fariss, H. Asaidi, Mohamed Bellouki
The significant existence of web services is challenging to the researchers regarding their diversity of types and their diffusion. It may lead to difficulty in identifying the relevant service during the discovery or composition process. To tackle this problem, we propose a new method to categorize semantic web services based on the Naive Bayes algorithm using a weighting method (TF-IDF), which binds a service according to its description importance offered by the service provider to be categorized in a relevant class. It enhances the performance by proposing a compatible combination of the preprocessing techniques (Natural language processing) to achieve a better classification result. This method has been tested on the OWLS-TC dataset, categorized into seven classes, and its accuracy is 93%.
web服务的显著存在对研究人员提出了挑战,因为它们的类型多样性和扩散性。它可能导致在发现或组合过程中难以识别相关服务。为了解决这一问题,我们提出了一种基于朴素贝叶斯算法的语义web服务分类新方法,该方法使用加权方法(TF-IDF),根据服务提供者提供的描述重要性将服务绑定到相关类中。它通过提出一种兼容的预处理技术(自然语言处理)组合来提高性能,以获得更好的分类结果。该方法在OWLS-TC数据集上进行了测试,分为7类,准确率为93%。
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引用次数: 0
Beta-divergence for Nonnegative Matrix Factorization 非负矩阵分解的散度
Jbari Olaya, Chakkor Otman
The beta-divergences has been largely used in the machine learning literature. In this paper, we will go into detail about what they are, where they come from, their relation with Bregman divergence, and why they are so useful in many machine learning algorithms. In particular, Nonnegative Matrix Factorization (NMF), witch we presented as an example using Majorization-Minimization approach.
beta散度在机器学习文献中被大量使用。在本文中,我们将详细介绍它们是什么,它们来自哪里,它们与Bregman散度的关系,以及为什么它们在许多机器学习算法中如此有用。特别是非负矩阵分解(NMF),我们将其作为使用最大化-最小化方法的一个例子。
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引用次数: 0
Dark data as a new challenge to improve business performances: review and perspectives 暗数据作为提高业务绩效的新挑战:回顾和观点
Loubna Moumeni, Ilham Slimani, Ilhame El Farissi, M. Saber, M. Belkasmi
Many studies in big data focus on the uses of data available to researchers, leaving without treatment data that is on the servers but of which researchers are unaware [1]. This unmanaged, unrated, and unknown data is prevalent in most companies. This overlooked information takes up valuable storage capacity and may contain hidden risks and usually lies abandoned on the periphery of the information governance agenda. In this article, we present and discuss the value of dark data and focus on risks caused by this dark data. To this end, we provide statistics of a major IDC (International Data Corporation) and other companies. We also explain how this new term in the world of data can be exploited, to avoid the risks.
许多关于大数据的研究关注的是对研究人员可用数据的使用,而没有研究人员不知道的服务器上的治疗数据[1]。这种未管理、未评级和未知的数据在大多数公司都很普遍。这些被忽视的信息占用了宝贵的存储容量,可能包含隐藏的风险,通常被遗弃在信息治理议程的外围。在本文中,我们介绍和讨论了暗数据的价值,并重点讨论了暗数据带来的风险。为此,我们提供了各大IDC(国际数据公司)等公司的统计数据。我们还解释了如何利用数据世界中的这个新术语来避免风险。
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引用次数: 1
BREEAM Communities: Criteria Aim, Status, Strengths and Weaknesses BREEAM社区:标准、目标、地位、优势和劣势
Duygu Çınar Umdu, E. Alakavuk, Aleyna Koyuncu
The point where Sustainable Development and Smart Growth understandings meet with standardization and technology has enabled eco-labels, assessment models and guidelines to emerge and become a trend. With Agenda 21, this trend has been well adopted and eco-labels, assessment models and certifications have begun to be created for many disciplines. The concept of sustainable neighbourhood, strengthened by the development of the Eco-Urbanism concept, constitutes an important basis for sustainable urban design and the Neighbourhood Sustainability Assessment (NSA) concept is nourished from this basis. BREEAM stands out as the first example developed when it comes to sustainability models of architecture and urban design. This study is a review on the criteria and indicators, purpose, status of the BREEAM Communities Model developed for smart and sustainable urban design, which is a rising value, and the scoring system was examined through BREEAM data and literature. In addition, the differences, and similarities between 5 different Neighbourhood Sustainability Assessments which are LEED ND, CASBEE UD, Citylab, and BEAM Plus Neighboorhood by 4 organizations from 70 members of the World Green Building Council, including BRE, which constitutes the BREEAM system, were investigated. As a result of all these studies, the strengths, and weaknesses of BREEAM Communities were determined.
可持续发展和智能增长的理解与标准化和技术相结合,使生态标签、评估模型和指导方针得以出现并成为一种趋势。《21世纪议程》很好地采用了这一趋势,并开始为许多学科建立生态标签、评价模式和证书。生态城市主义概念的发展加强了可持续社区的概念,构成了可持续城市设计的重要基础,社区可持续性评估(NSA)概念正是在此基础上孕育出来的。在建筑和城市设计的可持续性模型方面,BREEAM作为第一个例子脱颖而出。本研究回顾了为智慧和可持续城市设计而开发的BREEAM社区模型的标准和指标、目的、现状,并通过BREEAM数据和文献对评分系统进行了检验。此外,我们还调查了世界绿色建筑委员会70个成员中的4个组织(包括组成BREEAM系统的BRE)对LEED ND、CASBEE UD、Citylab和BEAM Plus neighborhood进行的5种不同社区可持续性评估之间的异同。通过所有这些研究,确定了BREEAM社区的优势和劣势。
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引用次数: 1
Direct Power Fuzzy Control of Three-Phase AC-DC Converter using a Space Vector Modulation 基于空间矢量调制的三相交直流变换器直接功率模糊控制
J. Lamterkati, L. Ouboubker, M. Khafallah
In the conventional Direct Power Control (DPC) the active/reactive powers and line currents have high ripples caused by the switching frequency variations. To repair it, in this paper the Space Vector Modulation (SVM) is used. This paper will aim firstly at developing a new SVM-DPC structure based Fuzzy Logic Controllers (FLC's) to overcome the SVM-DPC based Proportional-Integral (PI) controller limitations, such as the sensitivity to the external disturbances and the parameter uncertainties. In order to rectify the disadvantages of traditional SVM-DPC approach, active power and reactive power fuzzy logic controllers were designed to replace the classical active and reactive powers PI controllers. The active power and reactive power fuzzy logic controller has two inputs (active/reactive power error and its change rate) and one output (active/reactive component of the reference vector voltage). Numerical simulation results are given for conventional Proportional-integral and Fuzzy Logic Controllers to prove the performances of the proposed strategy. The simulation verifies that fuzzy SVM-DPC is able to of effectively improve control performance in terms of settling time, overshoot, steady state, line current harmonics and total harmonic distortion.
在传统的直接功率控制(DPC)中,由于开关频率的变化,有功/无功功率和线路电流存在较大的纹波。为了解决这个问题,本文采用了空间矢量调制(SVM)技术。本文首先提出了一种基于模糊逻辑控制器(FLC)的SVM-DPC结构,以克服基于SVM-DPC的比例积分(PI)控制器对外部干扰的敏感性和参数不确定性等局限性。为了纠正传统SVM-DPC方法的缺点,设计了有功和无功模糊逻辑控制器来取代经典的有功和无功PI控制器。有功和无功模糊逻辑控制器有两个输入(有功/无功误差及其变化率)和一个输出(参考矢量电压的有功/无功分量)。通过对传统比例积分控制器和模糊控制器的数值仿真,验证了所提策略的有效性。仿真结果表明,模糊SVM-DPC在稳定时间、超调量、稳态、线路电流谐波和总谐波畸变等方面都能有效改善控制性能。
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引用次数: 1
Hardware Software Co-design based CPU-FPGA Architecture: Overview and Evaluation 基于CPU-FPGA架构的软硬件协同设计:概述与评价
Said Agharass, M. Laaboubi, A. Saddik, R. Latif
Hardware/software co-design (HSCD) is an essential part of the configuration flow of current electronic system-level (ESL) devices [1]. This paper shows an overview of the hardware/software co-design approach, which aims to study the algorithmic and temporal limitations to design a robust architecture that takes maximum advantage of the desired architecture. In addition, we presented a comparative study of Sobel filters for the preprocessing of image processing algorithms. This study was based on the Intel-Altera CPU-FPGA board. We implemented the algorithm in two different methods, the first one based on the VHDL description language and the second one based on the OpenCL high-level language. The results showed that the use of VHDL has less resource consumption than the OpenCL based implementation. From the results, we can conclude that the use of VHDL takes less resources, but the problem here is the complexity of coding using this HDL. Therefore, OpenCL is very strong in speeding up algorithms that are based on massive data.
硬件/软件协同设计(HSCD)是当前电子系统级(ESL)设备配置流程的重要组成部分[1]。本文概述了硬件/软件协同设计方法,其目的是研究算法和时间限制,以设计一个健壮的体系结构,最大限度地利用所需的体系结构。此外,我们提出了一个比较研究的索贝尔滤波器的预处理图像处理算法。本研究基于Intel-Altera CPU-FPGA板。我们采用了两种不同的方法来实现算法,一种是基于VHDL描述语言,另一种是基于OpenCL高级语言。结果表明,使用VHDL比基于OpenCL的实现具有更少的资源消耗。从结果中,我们可以得出结论,使用VHDL需要更少的资源,但这里的问题是使用这种HDL编码的复杂性。因此,OpenCL在加速基于海量数据的算法方面非常强大。
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引用次数: 0
An overview on intra- and inter-patient paradigm for ECG Heartbeat Arrhythmia Classification 心电心律不齐分类的患者内与患者间模式综述
Mohamed Sraitih, Y. Jabrane, Abdelghafour Atlas
Electrocardiogram (ECG) is one the most used tool to diagnose the health problems of the heart, but a manual diagnosis of these heart-beat classes by cardiologists could be time-consuming. An automated computer aid remains important in such cases to facilitate some tasks and aid specialists rapidly define and classify arrhythmias. In this paper, we investigated paradigms used for ECG arrhythmia classification of the Intra- and inter-patient paradigm with and without the association for the advancement of medical instrumentation (AAMII) standards and presented several papers that worked on each type. We discussed a variety of limitations and revealed that there is still room for improvement in the classification's performance, especially for the NON-AAMII inter-patient paradigm, to further boost confidence for the applicability of such solutions in clinical diagnosis which is more conforming to the clinical practice in which varieties of ECG signals are collected from different subjects. Such an organized literature survey allows researchers to merge an unobstructed view on all the aspects of ECG classification for the identification of gaps and the research issues unmet so far.
心电图(ECG)是诊断心脏健康问题最常用的工具之一,但由心脏病专家手动诊断这些心跳类可能会很耗时。在这种情况下,自动计算机辅助仍然很重要,它可以促进某些任务,并帮助专家快速定义和分类心律失常。在本文中,我们研究了在有或没有医疗器械进步协会(AAMII)标准的情况下用于患者内和患者间心律失常分类的范式,并提出了针对每种类型的几篇论文。我们讨论了各种局限性,并揭示了分类的性能仍有改进的空间,特别是对于NON-AAMII患者间范式,进一步增强了该解决方案在临床诊断中的适用性的信心,更符合临床实践中收集不同受试者的各种心电信号。这样一个有组织的文献调查使研究人员能够对心电图分类的所有方面进行无障碍的观察,以确定差距和迄今为止尚未解决的研究问题。
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引用次数: 2
Generate a list of Stop Words in Moroccan Dialect from Social Network Data Using Word Embedding 利用词嵌入技术从社交网络数据中生成摩洛哥方言的停词列表
Zineb Nassr, N. Sael, F. Benabbou
Natural Language Processing (NLP) is a branch of artificial intelligence AI that helps computers understand, interpret and manipulate human language. NLP draws from many disciplines, including computer science and computational linguistics, in its pursuit to fill the gap between human communication and computer understanding. In the information age, using NLP for optimizing information search process, text summary, text, and data analysis systems become the most important. So, to achieve accuracy, redundant words without or with low semantic meaning must be filtered. These words are known as stop words. The Stop words list has been developed for languages like Arabic, English, Chinese, French, etc. But Standard Stop Words list is always missing for dialects, as Moroccan dialect. Manual Identification of stop words for the Moroccan dialect is a difficult task, especially with the diversity of ways that can be used to write a simple stop word. In this work, we propose a novel method for Moroccan dialect stop word generation. To attempt this objective, we first realize preprocessing steps to reduce noise, create stop words dictionary to enrich our database for training purposes and finally use word embedding to build stop words clusters. This list is generated from three popular social networks: Facebook, twitter, and YouTube.
自然语言处理(NLP)是人工智能的一个分支,它帮助计算机理解、解释和操纵人类语言。NLP借鉴了许多学科,包括计算机科学和计算语言学,以填补人类交流和计算机理解之间的空白。在信息时代,利用自然语言处理优化信息搜索过程、文本摘要、文本和数据分析系统变得尤为重要。因此,为了达到准确性,必须对无语义或低语义的冗余词进行过滤。这些词被称为停顿词。“停止词列表”是为阿拉伯语、英语、汉语、法语等语言开发的。但是方言的标准停顿词列表总是缺失的,比如摩洛哥方言。手工识别摩洛哥方言的停顿词是一项艰巨的任务,尤其是一个简单的停顿词有多种写法。在这项工作中,我们提出了一种新的摩洛哥方言停止词生成方法。为了实现这一目标,我们首先实现了预处理步骤以降低噪声,创建停止词字典以丰富我们的数据库以用于训练目的,最后使用词嵌入来构建停止词聚类。这份榜单来自三个流行的社交网络:Facebook、twitter和YouTube。
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引用次数: 1
期刊
2021 International Conference on Digital Age & Technological Advances for Sustainable Development (ICDATA)
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