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From Network Functions to NetApps: The 5GASP Methodology 从网络功能到NetApps: 5GASP方法论
IF 3.1 4区 计算机科学 Q3 COMPUTER SCIENCE, INFORMATION SYSTEMS Pub Date : 2022-01-01 DOI: 10.32604/cmc.2022.021754
Jorge Gallego-Madrid, R. Sanchez-Iborra, A. Skarmeta
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引用次数: 1
Graphical Transformation of OWL Ontologies to Event-B Formal Models OWL本体到事件- b形式模型的图形化转换
IF 3.1 4区 计算机科学 Q3 COMPUTER SCIENCE, INFORMATION SYSTEMS Pub Date : 2022-01-01 DOI: 10.32604/CMC.2022.015987
Eman H. Alkhammash
: Formal methods use mathematical models to develop systems. Ontologies are formal specifications that provide reusable domain knowledge representations. Ontologies have been successfully used in several data-driven applications, including data analysis. However, the creation of formal models from informal requirements demands skill and effort. Ambiguity, incon-sistency, imprecision, and incompleteness are major problems in informal requirements. To solve these problems, it is necessary to have methods and approaches for supporting the mapping of requirements to formal specifications. The purpose of this paper is to present an approach that addresses this challenge by using the Web Ontology Language (OWL) to construct Event-B formal models and support data analysis. Our approach reduces the burden of working with the formal notations of OWL ontologies and Event-B models and aims to analyze domain knowledge and construct Event-B models from OWL ontologies using visual diagrams. The idea is based on the transformation of OntoGraf diagrams of OWL ontologies to UML-B diagrams for the purpose of bridging the gap between OWL ontologies and Event-B models. Visual data exploration assists with both data analysis and the development of Event-B formal models. To manage complexity, Event-B supports stepwise refinement to allow each requirement to be introduced at the most appropriate stage in the development process. UML-B supports refinement, so we also introduce an approach that allows us to divide and layer OntoGraf diagrams.
形式化方法使用数学模型来开发系统。本体是提供可重用领域知识表示的正式规范。本体已经成功地用于几个数据驱动的应用程序,包括数据分析。然而,从非正式的需求中创建正式的模型需要技巧和努力。歧义、不一致、不精确和不完整是非正式需求中的主要问题。为了解决这些问题,有必要使用方法和途径来支持需求到正式规范的映射。本文的目的是提出一种方法,通过使用Web本体语言(OWL)来构建Event-B形式化模型并支持数据分析,从而解决这一挑战。我们的方法减少了处理OWL本体和Event-B模型的形式化符号的负担,旨在分析领域知识并使用可视化图从OWL本体构建Event-B模型。这个想法是基于OWL本体的OntoGraf图到UML-B图的转换,目的是弥合OWL本体和Event-B模型之间的差距。可视化数据探索有助于数据分析和Event-B形式化模型的开发。为了管理复杂性,Event-B支持逐步细化,以允许在开发过程中最适当的阶段引入每个需求。UML-B支持细化,因此我们还引入了一种方法,允许我们对OntoGraf图进行划分和分层。
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引用次数: 1
Analysis and Assessment of Wind Energy Potential of Socotra Archipelago in Yemen 也门索科特拉群岛风能潜力分析与评价
IF 3.1 4区 计算机科学 Q3 COMPUTER SCIENCE, INFORMATION SYSTEMS Pub Date : 2022-01-01 DOI: 10.32604/cmc.2022.019626
Murad A. A. Almekhlafi, F. Al-Wesabi, Imran Khan, N. Nemri, Khalid Mahmood, Hany Mahgoub, N. Negm, Amin M. El-Kustaban, A. Zahary
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引用次数: 2
Double-E-Triple-H-Shaped NRI-Metamaterial for Dual-Band Microwave Sensing Applications 用于双频微波传感的双e-三h形nri超材料
IF 3.1 4区 计算机科学 Q3 COMPUTER SCIENCE, INFORMATION SYSTEMS Pub Date : 2022-01-01 DOI: 10.32604/cmc.2022.022042
Shafayat Hossain, Md. Iquebal Hossain Patwary, Sikder Sunbeam Islam, Sultan Mahmud, Norbahiah binti Misran, Ali F. Almutairi, M. Tariqul Islam
This paper presents a new Double-E-Triple-H-Shaped NRI (negative refractive index) metamaterial (MM) for dual-band microwave sensing applications. Here, a horizontal H-shaped metal structure is enclosed by two face-to-face E-shaped metal structures. This double-E-H-shaped design is also encased by two vertical H-shaped structures along with some copper links. Thus, the Double-E-Triple-H-Shaped configuration is developed. Two popular substrate materials of Rogers RO 3010 and FR-4 were adopted for analyzing the characteristics of the unit cell. The proposed structure exhibits transmission resonance inside the S-band with NRI and ENG (Epsilon Negative) metamaterial properties, and inside the C-band with ENG and MNG (Mu Negative) metamaterial properties. A good effective medium ratio (EMR) of 8.06 indicates the compactness and effectiveness of the proposed design. Further analysis has been done by changing the thickness of the substrate material as well and a significant change in the effective medium ratio is found. The validity of the proposed structure is confirmed by an equivalent circuit model. The simulated result agrees well with the calculated result. For exploring microwave sensing applications of the proposed unit cell, permittivity and pressure sensitivity performance were investigated in different simulation arrangements. The compact size, effective parameters, high sensitivity and a good EMR represent the proposed metamaterial as a promising solution for S-band and C-band microwave sensing applications.
本文提出了一种新的双e-三h形负折射率超材料(MM),用于双频微波传感。在这里,一个水平的h型金属结构被两个面对面的e型金属结构包围。这个双e- h形的设计也被两个垂直的h形结构和一些铜链包围。因此,形成了双e三h形结构。采用罗杰斯ro3010和FR-4两种流行的衬底材料分析了单元电池的特性。该结构在s波段内具有NRI和ENG (Epsilon Negative)超材料性质,在c波段内具有ENG和MNG (Mu Negative)超材料性质。有效介质比(EMR)为8.06,表明了该设计的紧凑性和有效性。通过改变衬底材料的厚度进行了进一步的分析,发现有效介质比发生了显著变化。通过等效电路模型验证了该结构的有效性。模拟结果与计算结果吻合较好。为了探索所提出的单元电池的微波传感应用,研究了不同模拟布置下的介电常数和压敏性能。该材料具有紧凑的尺寸、有效的参数、高灵敏度和良好的EMR特性,是s波段和c波段微波传感应用的理想解决方案。
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引用次数: 2
Performance Analysis of Multi-Channel CR Enabled IoT Network with Better Energy Harvesting 具有更好能量收集的多通道CR支持物联网网络性能分析
IF 3.1 4区 计算机科学 Q3 COMPUTER SCIENCE, INFORMATION SYSTEMS Pub Date : 2022-01-01 DOI: 10.32604/cmc.2022.021860
Nasir Mahmood, M. Usman Ghani Khan
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引用次数: 0
Detection of Low Sugar Concentration Solution Using Frequency Selective Surface (FSS) 频率选择表面(FSS)检测低糖溶液
IF 3.1 4区 计算机科学 Q3 COMPUTER SCIENCE, INFORMATION SYSTEMS Pub Date : 2022-01-01 DOI: 10.32604/cmc.2022.022694
N. S. Ishak, F. C. Seman, N. Zainal, N. A. Awang
: Sugar is important in daily food intake since it is used as food preservative and sweetener. Therefore, is important to analyze the influence of sugar on the spectroscopic properties of the sample. Terahertz spectroscopy is proven to be useful and an efficient method for sugar detection as well as for future food quality industry. However, the lack of detection sensitivity in Terahertz Spectroscopy has prevented it from being used in a widespread spectroscopic analysis technology. In this paper, Frequency Selective Surface (FSS) using the Terahertz Spectroscopy Time Domain Spectrum (THz-TDS) which operates at terahertz frequency range has been demonstrated for application of sugar detection. The FSS is designed with a circle slot structure and has been optimized in line with the molecular resonance of glucose and fructose at different level concentration at 1.98 THz and 1.80 THz, respectively. Transmission magnitude of glucose and sucrose is inversely proportional with the level of sugar concentrations. The realization of the FSS structure is using electron beam lithography and wet etching technique. Results show that the FSS performance for glucose and sucrose reveal fair shifts in measured transmission magnitude from its original in CST by approximately 30%. The use of fabricated FSS with circle structure indicates that the concentration can be improved averagely at 25% for glucose and 13% for sucrose. Thus, it shows that the FSS circle structure combined with THz-TDS has the potential to become an alternative method for food sensing technology in the future.
糖在日常食物摄入中很重要,因为它被用作食物防腐剂和甜味剂。因此,分析糖对样品光谱性质的影响具有重要意义。太赫兹光谱被证明是一种有用的和有效的方法来检测糖以及未来的食品质量工业。然而,太赫兹光谱检测灵敏度的不足阻碍了其在光谱分析技术中的广泛应用。本文演示了工作在太赫兹频率范围的太赫兹光谱时域谱(THz-TDS)的频率选择表面(FSS)在糖检测中的应用。FSS设计为圆槽结构,并根据葡萄糖和果糖在不同浓度下分别在1.98 THz和1.80 THz下的分子共振进行了优化。葡萄糖和蔗糖的透射量与糖浓度成反比。FSS结构的实现采用了电子束光刻和湿法蚀刻技术。结果表明,葡萄糖和蔗糖的FSS性能显示,在CST中,测量到的传输幅度比原始传输幅度大了大约30%。利用圆形结构制备的FSS表明,葡萄糖和蔗糖的浓度分别平均提高了25%和13%。因此,这表明FSS圆结构与太赫兹- tds相结合有可能成为未来食品传感技术的替代方法。
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引用次数: 1
Empirical Assessment of Bacillus Calmette-Gu閞in Vaccine to Combat COVID-19 卡介苗-谷芽孢杆菌閞抗新冠肺炎疫苗的实证评价
IF 3.1 4区 计算机科学 Q3 COMPUTER SCIENCE, INFORMATION SYSTEMS Pub Date : 2022-01-01 DOI: 10.32604/cmc.2022.016424
Nikita Jain, Vedika Gupta, Chinmay Chakraborty, Agam Madan, Deepali Virmani, L. Salas-Morera, L. García-Hernández
COVID-19 has become one of the critical health issues globally, which surfaced first in latter part of the year 2019. It is the topmost concern for many nations' governments as the contagious virus started mushrooming over adjacent regions of infected areas. In 1980, a vaccine called Bacillus Calmette-Guerin (BCG) was introduced for preventing tuberculosis and lung cancer. Countries that have made the BCG vaccine mandatory have witnessed a lesser COVID-19 fatality rate than the countries that have not made it compulsory. This paper's initial research shows that the countries with a long-term compulsory BCG vaccination system are less affected by COVID-19 than those without a BCG vaccination system. This paper discusses analytical data patterns for medical applications regarding COVID-19 impact on countries with mandatory BCG status on fatality rates. The paper has tackled numerous analytical challenges to realize the full potential of heterogeneous data. An analogy is drawn to demonstrate how other factors can affect fatality and infection rates other than BCG vaccination only, such as age groups affected, other diseases, and stringency index. The data of Spain, Portugal, and Germany have been taken for a case study of BCG impact analysis. © 2021 Tech Science Press. All rights reserved.
COVID-19已成为全球重大卫生问题之一,于2019年下半年首次浮出水面。随着这种传染性病毒开始在受感染地区的邻近地区迅速蔓延,这是许多国家政府最关心的问题。1980年,一种名为卡介苗(BCG)的疫苗被引入,用于预防结核病和肺癌。强制接种卡介苗的国家的COVID-19死亡率低于未强制接种的国家。本文的初步研究表明,与没有卡介苗接种制度的国家相比,长期实行卡介苗强制接种制度的国家受COVID-19的影响较小。本文讨论了关于COVID-19对强制使用BCG的国家对死亡率影响的医疗应用分析数据模式。本文解决了许多分析挑战,以实现异构数据的全部潜力。通过类比说明除了卡介苗接种之外,其他因素如何影响致死率和感染率,如受影响年龄组、其他疾病和严格性指数。西班牙、葡萄牙和德国的数据被用于BCG影响分析的案例研究。©2021科技科学出版社。版权所有。
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引用次数: 0
A Monte Carlo Based COVID-19 Detection Framework for Smart Healthcare 基于蒙特卡罗的智能医疗COVID-19检测框架
IF 3.1 4区 计算机科学 Q3 COMPUTER SCIENCE, INFORMATION SYSTEMS Pub Date : 2022-01-01 DOI: 10.32604/cmc.2022.020016
Tallat Jabeen, Ishrat Jabeen, Humaira Ashraf, Noor Zaman Jhanjhi, M. Humayun, Mehedi Masud, S. Aljahdali
COVID-19 is a novel coronavirus disease that has been declared as a global pandemic in 2019. It affects the whole world through person-to-person communication. This virus spreads by the droplets of coughs and sneezing, which are quickly falling over the surface. Therefore, anyone can get easily affected by breathing in the vicinity of the COVID-19 patient. Currently, vaccine for the disease is under clinical investigation in different pharmaceutical companies. Until now, multiple medical companies have delivered health monitoring kits. However, a wireless body area network (WBAN) is a healthcare system that consists of nano sensors used to detect the real-time health condition of the patient. The proposed approach delineates is to fill a gap between recent technology trends and healthcare structure. If COVID-19 affected patient is monitored through WBAN sensors and network, a physician or a doctor can guide the patient at the right time with the correct possible decision. This scenario helps the community to maintain social distancing and avoids an unpleasant environment for hospitalized patients Herein, a Monte Carlo algorithm guided protocol is developed to probe a secured cipher output. Security cipher helps to avoid wireless network issues like packet loss, network attacks, network interference, and routing problems. Monte Carlo based covid-19 detection technique gives 90% better results in terms of time complexity, performance, and efficiency. Results indicate that Monte Carlo based covid-19 detection technique with edge computing idea is robust in terms of time complexity, performance, and efficiency and thus, is advocated as a significant application for lessening hospital expenses.
COVID-19是2019年被宣布为全球大流行的新型冠状病毒疾病。它通过人与人之间的交流影响着整个世界。这种病毒通过咳嗽和打喷嚏的飞沫传播,这些飞沫会迅速落在表面。因此,任何人在COVID-19患者附近呼吸都很容易受到影响。目前,该疾病的疫苗正在不同的制药公司进行临床研究。到目前为止,多家医疗公司已经提供了健康监测工具包。然而,无线体域网络(WBAN)是一种由纳米传感器组成的医疗保健系统,用于检测患者的实时健康状况。提议的方法描述是填补最近的技术趋势和医疗保健结构之间的差距。如果通过WBAN传感器和网络监测COVID-19患者,医生或医生可以在适当的时间指导患者做出正确的决定。这种场景有助于社区保持社交距离,并避免住院患者的不愉快环境。在此,开发了蒙特卡洛算法指导协议来探测安全的密码输出。安全密码有助于避免无线网络问题,如丢包、网络攻击、网络干扰和路由问题。基于蒙特卡罗的covid-19检测技术在时间复杂度、性能和效率方面提高了90%。结果表明,基于蒙特卡罗的基于边缘计算思想的covid-19检测技术在时间复杂度、性能和效率方面都具有鲁棒性,因此被认为是减少医院费用的重要应用。
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引用次数: 9
Kernel Granulometric Texture Analysis and Light RES-ASPP-UNET Classification for Covid-19 Detection 核粒织构分析及轻res - asp - unet分类
IF 3.1 4区 计算机科学 Q3 COMPUTER SCIENCE, INFORMATION SYSTEMS Pub Date : 2022-01-01 DOI: 10.32604/cmc.2022.020820
R. Gopi, P. Muthusamy, P. Suresh, C. G. Gabriel Santhosh Kumar, Irina V. Pustokhina, Denis A. Pustokhin, K. Shankar
This research article proposes an automatic frame work for detecting COVID -19 at the early stage using chest X-ray image. It is an undeniable fact that coronovirus is a serious disease but the early detection of the virus present in human bodies can save lives. In recent times, there are somany research solutions that have been presented for early detection, but there is still a lack in need of right and even rich technology for its early detection. The proposed deep learning model analysis the pixels of every image and adjudges the presence of virus. The classifier is designed in such a way so that, it automatically detects the virus present in lungs using chest image. This approach uses an image texture analysis technique called granulometric mathematical model. Selected features are heuristically processed for optimization using novel multi scaling deep learning called light weight residual-atrous spatial pyramid pooling (LightRES-ASPP-Unet) Unet model. The proposed deep LightRES-ASPPUnet technique has a higher level of contracting solution by extracting major level of image features. Moreover, the corona virus has been detected using high resolution output. In the framework, atrous spatial pyramid pooling (ASPP) method is employed at its bottom level for incorporating the deep multi scale features in to the discriminative mode. The architectural working starts from the selecting the features from the image using granulometric mathematical model and the selected features are optimized using LightRESASPP- Unet. ASPP in the analysis of images has performed better than the existing Unet model. The proposed algorithm has achieved 99.6% of accuracy in detecting the virus at its early stage. © 2022 Tech Science Press. All rights reserved.
本文提出了一种利用胸部x线图像进行COVID -19早期检测的自动框架。冠状病毒是一种严重的疾病,这是不可否认的事实,但早期发现人体内存在的病毒可以挽救生命。近年来,已经提出了许多早期检测的研究方案,但仍然缺乏正确甚至丰富的早期检测技术。提出的深度学习模型分析每张图像的像素并判断是否存在病毒。分类器是这样设计的,它可以通过胸部图像自动检测出肺部存在的病毒。该方法采用了一种称为颗粒数学模型的图像纹理分析技术。采用一种新型的多尺度深度学习方法,即轻量级剩余空间金字塔池(lightres - asp -Unet) Unet模型,对所选特征进行启发式处理并进行优化。提出的deep lightres - aspppunet技术通过提取图像主要层次的特征,具有更高层次的压缩解。此外,已经使用高分辨率输出检测到冠状病毒。在该框架中,底层采用非均匀空间金字塔池(ASPP)方法,将深层多尺度特征融合到判别模式中。架构工作从使用粒度数学模型从图像中选择特征开始,并使用LightRESASPP- Unet对选择的特征进行优化。ASPP在图像分析方面的表现优于现有的Unet模型。该算法在病毒早期检测准确率达到99.6%。©2022科技科学出版社。版权所有。
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引用次数: 0
Parametric Study of Hip Fracture Risk Using QCT-Based Finite Element Analysis 基于qct有限元分析的髋部骨折风险参数化研究
IF 3.1 4区 计算机科学 Q3 COMPUTER SCIENCE, INFORMATION SYSTEMS Pub Date : 2022-01-01 DOI: 10.32604/cmc.2022.018262
Fatemeh Ahmadi Zeidabadi, Sajjad Amiri Doumari, Mohammad Dehghani, Z. Montazeri, Pavel Trojovsk� Gaurav Dhiman
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引用次数: 2
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