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Semantic eSystems: Engineering methods, techniques, and tools
Software: Practice and Experience ( IF 3.5 ) Pub Date : 2021-01-11 , DOI: 10.1002/spe.2952
Thar Baker 1 , Dhiya Al‐Jumeily 2 , Zakaria Maamar 3 , Zahir Tari 4
Affiliation  

We are delighted to present this novel special issue, which emphasizes semantic eSystems and their engineering methods, techniques, and tools.

“eSystems” are those interdisciplinary cost‐effective and interconnected solutions that leverage advanced information and communication technologies' techniques and tools to gain competitive advantage. Recent years have witnessed increasing interest in the design and development of various eSystem‐based applications, ranging from real‐world to machine and robotic applications. An essential feature in eSystems is their intelligent ability to “speak” and interact with one another to support function “extensibility” so that complex interactions could be established with other eSystems.

Therefore, connecting disparate eSystems “on the fly” necessitates engineering a dialog channel such that it enables data fusion, exchange, and link in a unified and understandable way. While data emitted from eSystems are of different formats, sizes, and types, adopting semantic data technologies is a natural way to address these differences. Simply put, semantics is about agreeing on a common understanding of data that need to be exchanged between systems and between humans and systems.

This special issue received 22 submissions, which were aligned with the theme of semantic eSystems' methods, techniques, and tools. Those submissions came from diverse researchers from academia, industry, and individuals from all over the globe. First, all submissions were screened closely by the editors to check their suitability with the special issue's list of topics. Second, after multiple rounds of peer review, only 11 high‐quality submissions were accepted for publication in this special issue.

Those accepted papers address the semantic eSystems theme from different perspectives including, for instance, efficient semantic–visual indexing model for large‐scale image retrieval in cloud environment, trilateration‐based indoor localization engineering technique for visible light communication system, graph‐based system to enable efficient transformation of enterprise infrastructures, recognizing physical activities having complex interclass variations using semantic data of smartphone, spatiotemporal‐based sentiment analysis on tweets for risk assessment of an event using the deep‐learning approach, sentiment‐based eSystem using hybridized fuzzy and deep neural network for measuring customer satisfaction, data fusion analysis for emotion recognition with thermal image and Internet of Thing devices, unified framework to manage cybersecurity and safety in manufacturing industry, graph‐based convolutional neural network stock price prediction with leading indicators, author classification using transfer learning and predicting stars in coauthor networks, and DNA signal analysis tool: intelligent noise suppression window filter.



中文翻译:

语义电子系统:工程方法,技术和工具

我们很高兴提出这个新颖的特殊问题,该问题强调语义eSystem及其工程方法,技术和工具。

“ eSystems”是那些利用先进的信息和通信技术的技术和工具来获得竞争优势的跨学科,具有成本效益和相互联系的解决方案。近年来,人们目睹了对各种基于eSystem的应用程序的设计和开发的兴趣,这些应用程序从现实世界到机器和机器人应用程序不等。eSystems的一项基本功能是它们具有“说话”并可以相互交互以支持功能“可扩展性”的智能能力,因此可以与其他eSystems建立复杂的交互。

因此,“动态”连接不同的eSystems必须设计一个对话通道,以便它能够以统一且易于理解的方式进行数据融合,交换和链接。尽管从eSystems发出的数据具有不同的格式,大小和类型,但是采用语义数据技术是解决这些差异的自然方法。简而言之,语义就是要就需要在系统之间以及人与系统之间交换的数据达成共识。

本期特刊共收到22篇论文,与语义eSystems的方法,技术和工具的主题保持一致。这些论文来自学术界,工业界以及来自全球各地的个人。首先,编辑们仔细筛选了所有提交的内容,以通过特刊主题列表检查其适用性。其次,经过多轮同行评审,本期仅接受11篇高质量的论文发表。

这些被接受的论文从不同的角度论述了语义eSystems主题,例如,用于在云环境中进行大规模图像检索的有效语义-视觉索引模型,用于可见光通信系统的基于三边测量的室内定位工程技术,基于图的系统,等等。使用智能手机的语义数据实现企业基础架构的高效转换,识别具有复杂类间差异的体育活动,使用深度学习方法对推文进行基于时空的情感分析以对事件进行风险评估,使用模糊和深度神经网络进行基于情感的eSystem用于测量客户满意度的网络,用于通过热图像和Thing设备联网进行情感识别的数据融合分析,统一的框架来管理制造业的网络安全和安全,具有领先指标的基于图的卷积神经网络股票价格预测,使用共同学习网络中的转移学习和预测星标对作者进行分类以及DNA信号分析工具:智能噪声抑制窗口滤波器。

更新日期:2021-02-16
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