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Innovative Maritime Operations Management Using Blockchain Technology & Standardization 使用区块链技术和标准化的创新海事运营管理
Q3 Decision Sciences Pub Date : 2022-01-01 DOI: 10.13052/jicts2245-800X.1041
Manos-Nikolaos Papadakis;Evangelia Kopanaki
Modern economy faces one of its' greatest challenges of all times and disruptive innovations are available to corporations as solutions to major business drawbacks (e.g., traceability, communication, data exchange, information modelling etc.). The Maritime Industry combines multiple supply chain stakeholders and operations, globally, generating critical data and exchanging important documents. Mostly, these are paper-based and proprietary. For this industry, digitally exchanged data, must be unambiguous, semantically aligned between trading partners and shared with resilience in real-time using a common operational language. This could be achieved through the prominent from Bitcoin Cryptocurrency Blockchain Technology as a digital verification mechanism complying with global identification, technical and data exchange standards. Acknowledging the difficulties faced in the Maritime Business Operations' Management, this paper examines the strategic impact of Standards and Blockchain Technology in the industry's processes.
现代经济面临着有史以来最大的挑战之一,企业可以利用颠覆性创新来解决主要业务缺陷(如可追溯性、通信、数据交换、信息建模等)。海运业将全球多个供应链利益相关者和运营结合在一起,生成关键数据并交换重要文件。大多数情况下,这些都是基于纸面的和专有的。对于这个行业来说,数字交换的数据必须毫不含糊,在贸易伙伴之间语义一致,并使用通用操作语言实时共享。这可以通过比特币加密货币区块链技术作为一种符合全球身份识别、技术和数据交换标准的数字验证机制来实现。鉴于海事业务运营管理面临的困难,本文考察了标准和区块链技术在行业流程中的战略影响。
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引用次数: 0
Modelling IoT Behaviour in Supply Chain Business Processes with BPMN: A Systematic Literature Review 用BPMN建模供应链业务流程中的物联网行为:系统文献综述
Q3 Decision Sciences Pub Date : 2022-01-01 DOI: 10.13052/jicts2245-800X.1035
Ihsane Abouzid;Younes Karfa Bekali;Rajaa Saidi
The Internet of Things (IoT) enables to connect physical world to digital processes, allowing real-world data to be fed into business processes. This revolution helps in the making of more informed business decisions as well as the automation and/or improvement of business processes tasks. The successful integration of IoT into business operations is required to realize these benefits. Supporting the modelling of IoT-enhanced business proccesess is the first step toward this goal. Despite the fact that numerous papers studied this topic, it is unclear what the current state of the art is in terms of modelling solutions and gaps. We conduct a systematic literature review in this work to determine how current solutions model IoT into business operations, and whether the standard Business Process Model and Notation (BPMN) has emerged as the de facto standard for business process modelling [20], [26]). The Object Management Group (OMG) developed BPMN, which is now an ISO standard BPMN is already enough for a full modelling of IoT integration, or the extensions are needed. We found and analysed the several existing alternative solutions after reviewing all the literature on this issue. Furthermore, we discuss some key aspects of the planned additions that should be addressed in the near future, such as the absence of standardization.
物联网(IoT)能够将物理世界连接到数字流程,允许将真实世界的数据输入到业务流程中。这场革命有助于做出更明智的业务决策,以及自动化和/或改进业务流程任务。物联网与商业运营的成功整合是实现这些优势的必要条件。支持物联网增强业务流程的建模是实现这一目标的第一步。尽管有许多论文研究了这一主题,但目前尚不清楚建模解决方案和差距的现状。我们在这项工作中进行了系统的文献综述,以确定当前的解决方案如何将物联网建模为业务运营,以及标准业务流程模型和符号(BPMN)是否已成为业务流程建模的事实标准[20],[26])。对象管理小组(OMG)开发的BPMN,现在是ISO标准的BPMN已经足以对物联网集成进行全面建模,或者需要扩展。在查阅了所有关于这一问题的文献后,我们发现并分析了几种现有的替代解决方案。此外,我们还讨论了在不久的将来应该解决的计划添加的一些关键方面,例如缺乏标准化。
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引用次数: 3
COVID-19 Impact Sentiment Analysis on a Topic-based Level 基于主题的新冠肺炎影响情绪分析
Q3 Decision Sciences Pub Date : 2022-01-01 DOI: 10.13052/jicts2245-800X.1027
Mustapha Hankar;Marouane Birjali;Anas El-Ansari;Abderrahim Beni-Hssane
Last December 2019, health officials in Wuhan, a province from China, identified a novel coronavirus called SARS-CoV-2 causing pneumonia. In March 2020, World Health Organization (WHO) declared COVID-19 disease being a pandemic. During quarantine periods, people all over the globe were living under severe and overwhelming circumstances and expressing feelings of loneliness, dread, and anxiety. The pandemic has had a significant impact on the labor markets. As a result, several employees have lost their jobs while others are in grave danger to lose their positions the next day. In this paper, we developed a hybrid approach integrating sentiment analysis combined with topic modeling to analyze the impact of the COVID-19 pandemic on Moroccan citizens. The data used in this study includes comments collected from a well-known news website in Morocco called Hespress. Our approach follows a two-step process. In the first step, we implement a topic modeling method to analyze and extract topics from Arabic comments, and in the second step, we perform topic-based sentiment analysis to classify people's feedback on extracted topics. The final results revealed that the expressed sentiments regarding all the topics are highly negative.
去年12月,中国武汉省的卫生官员发现了一种新型冠状病毒,称为导致肺炎的SARS-CoV-2。2020年3月,世界卫生组织(世界卫生组织)宣布新冠肺炎为一种流行病。在隔离期间,全球各地的人们都生活在严峻的环境中,表达着孤独、恐惧和焦虑的情绪。疫情对劳动力市场产生了重大影响。因此,一些员工失去了工作,而其他员工则面临着第二天失去职位的严重危险。在本文中,我们开发了一种将情绪分析与主题建模相结合的混合方法,以分析新冠肺炎大流行对摩洛哥公民的影响。这项研究中使用的数据包括从摩洛哥一家名为Hespress的知名新闻网站收集的评论。我们的方法遵循两个步骤。在第一步中,我们实现了一种主题建模方法来分析和提取阿拉伯语评论中的主题,在第二步中,基于主题的情感分析来对人们对提取的主题的反馈进行分类。最终结果显示,对所有话题表达的情绪都是高度负面的。
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引用次数: 0
Sentence-Level Sentiment Classification A Comparative Study Between Deep Learning Models 句子层次情感分类——深度学习模型的比较研究
Q3 Decision Sciences Pub Date : 2022-01-01 DOI: 10.13052/jicts2245-800X.10213
Sara Mifrah;El Habib Benlahmar
Sentiment classification provides a means of analysing the subjective information in the text and subsequently extracting the opinion. Sentiment analysis is the method by which people extract information from their opinions, judgments and emotions about entities. In this paper we propose a comparative study between the most deep learning models used in the field of sentiment analysis; L-NFS (Linguistique Neuro Fuzzy System), GRU (Gated Recurrent Unit), BiGRU (Bidirectional Gated Recurrent Unit), LSTM (Long Short-Term Memory), BiLSTM (Bidirectional Long Short-Term Memory) and BERT(Bidirectional Encoder Representation from Transformers), we used for this study a large Corpus contain 1.6 Million tweets, as devices we train our models with GPU (graphics processing unit) processor. As result we obtain the best Accuracy and F1-Score respectively 87.36% and 0.87 for the BERT Model.
情感分类提供了一种分析文本中主观信息并随后提取观点的方法。情绪分析是人们从对实体的看法、判断和情绪中提取信息的方法。在本文中,我们提出了情感分析领域中使用的最深入的学习模型之间的比较研究;L-NFS(语言学家神经模糊系统)、GRU(门控递归单元)、BiGRU(双向门控递归单元,作为设备,我们使用GPU(图形处理单元)处理器来训练我们的模型。结果,BERT模型的准确率和F1得分分别为87.36%和0.87。
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引用次数: 0
Blockchain Technology for a Safe and Transparent Covid-19 Vaccination 用于安全透明的新冠肺炎疫苗接种的区块链技术
Q3 Decision Sciences Pub Date : 2022-01-01 DOI: 10.13052/jicts2245-800X.1022
Maha Filali Rotbi;Saad Motahhir;Abdelaziz El Ghzizal
In late 2019, we witnessed the apparition of the covid-19 virus. The virus appeared first in Wuhan, and due to people travel was spread worldwide. Exponential spread as well as high mortality rates, the two characteristics of the SARS-CoV-2 virus that pushed the entire world into a global lockdown. Health and economic crisis, along with social distancing have put the globe in a highly challenging situation. Unprecedented pressure on the health care system exposed many loopholes not only in this industry but many other sectors, which resulted in a set of new challenges that researchers and scientists among others must face. In all these circumstances, we could attend, in a surprisingly short amount of time, the creation of multiple vaccine candidates. The vaccines were clinically tested and approved, which brought us to the phase of vaccination. Safety, security, transparency, and traceability are highly required in this context. As a contribution to assure an efficient vaccination campaign, in this paper we suggest a Blockchain-based system to manage the registration, storage, and distribution of the vaccines. This manuscript has been presented as preprint in Blockchain technology for a Safe and Transparent Covid-19 Vaccination: https://arxiv.org/abs/2104.05428
2019年末,我们目睹了新冠肺炎病毒的出现。病毒首先出现在武汉,由于人们的旅行,病毒在全球范围内传播。指数级传播和高死亡率是严重急性呼吸系统综合征冠状病毒2型病毒的两个特征,它将整个世界推向全球封锁。健康和经济危机,加上保持社交距离,使全球处于极具挑战性的境地。医疗保健系统面临的前所未有的压力不仅暴露了该行业的许多漏洞,也暴露了许多其他部门的漏洞,这导致了研究人员和科学家等必须面对的一系列新挑战。在所有这些情况下,我们可以在令人惊讶的短时间内参与多种候选疫苗的研制。疫苗经过临床测试并获得批准,这使我们进入了疫苗接种阶段。在这种情况下,高度要求安全、保障、透明和可追溯性。为了确保有效的疫苗接种活动,在本文中,我们建议建立一个基于区块链的系统来管理疫苗的注册、存储和分发。这篇手稿已作为区块链技术的预印本提交,用于安全透明的新冠肺炎疫苗接种:https://arxiv.org/abs/2104.05428
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引用次数: 13
6G Mobile Communication Networks: Key Services and Enabling Technologies 6G移动通信网络:关键服务和赋能技术
Q3 Decision Sciences Pub Date : 2022-01-01 DOI: 10.13052/jicts2245-800X.1011
Sanjay Kumar
The deployment of 5G (fifth generation mobile communication) network has already started. Although, 5G will offer significant improvements over the existing systems, but will not be able to fulfil the emerging future demands. Therefore, development of communication networks beyond 5G will be required, leading to 6G. 6G will satisfy unprecedented requirements and expectations that 5G cannot meet. This paper highlights various new services to be offered by 6G, and a few enabling technologies for 6G development.
5G(第五代移动通信)网络的部署已经开始。尽管5G将在现有系统的基础上进行重大改进,但无法满足未来新出现的需求。因此,需要发展5G以外的通信网络,从而实现6G。6G将满足5G无法满足的前所未有的要求和期望。本文重点介绍了6G将提供的各种新服务,以及6G开发的一些支持技术。
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引用次数: 0
A Moroccan Sign Language Recognition Algorithm Using a Convolution Neural Network 一种基于卷积神经网络的摩洛哥手语识别算法
Q3 Decision Sciences Pub Date : 2022-01-01 DOI: 10.13052/jicts2245-800X.1033
Nourdine Herbaz;Hassan El Idrissi;Abdelmajid Badri
Gesture recognition is an open phenomenon in computer vision, and one of the topics of current interest. Gesture recognition has many applications in the interpretation of sign language, one is in human-computer interaction, and the other is in immersive game technology. For this reason, we have developed a model of image processing recognition of gestures, based on artificial neural networks, starting from data collection, identification, tracking and classification of gestures, to the display of the obtained results. We propose an approach to contribute to the translation of sign language into voice/text format. In this paper, we present a Moroccan sign language recognition system using a convolutional neural network (CNN). This system includes an important data set of more than 20 files. Each file contains 1000 static images of each signal from several different angles that we collected with a camera. Different sign language models were evaluated and compared with the proposed CNN model. The proposed system achieved an accuracy of 99.33% and achieved best performance with an accuracy rate of 98.7%.
手势识别是计算机视觉中一个开放的现象,也是当前研究的热点之一。手势识别在手语翻译中有很多应用,一个是在人机交互中,另一个是沉浸式游戏技术。为此,我们开发了一个基于人工神经网络的手势图像处理识别模型,从手势的数据收集、识别、跟踪和分类,到显示获得的结果。我们提出了一种有助于将手语翻译成语音/文本格式的方法。在本文中,我们提出了一个使用卷积神经网络(CNN)的摩洛哥手语识别系统。该系统包括一个由20多个文件组成的重要数据集。每个文件包含我们用相机收集的来自几个不同角度的每个信号的1000张静态图像。对不同的手语模型进行了评估,并与所提出的CNN模型进行了比较。所提出的系统实现了99.33%的准确率,并以98.7%的准确率获得了最佳性能。
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引用次数: 1
Semantic Web and Internet of Things: Challenges, Applications and Perspectives 语义网与物联网:挑战、应用与展望
Q3 Decision Sciences Pub Date : 2022-01-01 DOI: 10.13052/jicts2245-800X.1029
Fatima Zahra Amara;Mounir Hemam;Meriem Djezzar;Moufida Maimor
The apparent growth of the internet of things (IoT) has allowed its deployment in many domains. The IoT devices sense their surroundings and transmit the data via the Web. According to statistics, due to the proliferation of smart devices, the number of active IoT devices is expected to exceed 25.4 billion by 2030.11https://dataprot.net/statistics/iot-statistics/ A large number of IoT objects gather an enormous amount of raw data. The data generated by various IoT objects and sensors are heterogeneous, with varying types and formats. Therefore, it is difficult for IoT systems to share and reuse raw IoT data, which causes the problem of lack of interoperability. The lack of interoperability in IoT systems creates a problematic issue that prevents IoT systems from performing well. To address this issue, data modeling and knowledge representation using semantic web technologies may be an appropriate solution to give meaning to raw IoT data and convert it to an enriched data format. The primary goal of this research section is to highlight the best outcomes for semantic interoperability among IoT systems, which can serve as a guideline for future studies via the presentation of a literature review on semantic interoperability for Internet of Things systems, including challenges, prospects, and recent work. The paper also provides an overview of the application of semantic web technologies in IoT systems, such as specific ontologies, frameworks, and application domains that use semantic technologies in the IoT areas to solve interoperability and heterogeneity problems.
物联网(IoT)的明显增长使其能够在许多领域进行部署。物联网设备感知周围环境并通过网络传输数据。据统计,由于智能设备的激增,到2030.11年,活跃的物联网设备数量预计将超过254亿台https://dataprot.net/statistics/iot-statistics/大量的物联网对象收集了大量的原始数据。各种物联网对象和传感器生成的数据是异构的,具有不同的类型和格式。因此,物联网系统很难共享和重用原始物联网数据,这导致了缺乏互操作性的问题。物联网系统缺乏互操作性造成了一个问题,阻碍了物联网系统的良好运行。为了解决这个问题,使用语义网络技术的数据建模和知识表示可能是赋予原始物联网数据意义并将其转换为丰富数据格式的合适解决方案。本研究部分的主要目标是强调物联网系统之间语义互操作性的最佳结果,这可以作为未来研究的指导方针,通过介绍物联网系统语义互操作的文献综述,包括挑战、前景和最近的工作。本文还概述了语义网络技术在物联网系统中的应用,例如在物联网领域使用语义技术来解决互操作性和异构性问题的特定本体、框架和应用领域。
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引用次数: 2
Data Profiling and Machine Learning to Identify Influencers from Social Media Platforms 数据分析和机器学习识别社交媒体平台的影响者
Q3 Decision Sciences Pub Date : 2022-01-01 DOI: 10.13052/jicts2245-800X.1026
Bahaa Eddine Elbaghazaoui;Mohamed Amnai;Youssef Fakhri
Because of the numerous applications domains in which social media networks can be used, the huge volume of data and information uploaded by them is gaining significant interest. Publishing allows consumers to express their thoughts on products and services. Some feedbacks could also influence other users on those things. Therefore, extracting and identifying influencers from social media networks, also profiling their product perceptions and preferences, is critical for marketers to use efficient viral marketing and recommendation strategies. Our major goal in this research is to find the best machine learning model for characterizing influencers on social media networks. However, to achieve this objective, our strategy revolves around applying the PageRank algorithm to profile influential nodes throughout the social media network graph. The results of our experiment showed that the correlation is always different when adding a new parameter to machine learning models, also to determine the suitable model for our needs. In any event, the experiment outcomes are critical and significant to profiling influencers from social media platforms.
由于社交媒体网络可用于众多应用领域,因此其上传的大量数据和信息正引起人们的极大兴趣。发布可以让消费者表达他们对产品和服务的想法。一些反馈也可能影响其他用户对这些事情的看法。因此,从社交媒体网络中提取和识别有影响力的人,并分析他们的产品感知和偏好,对于营销人员使用有效的病毒式营销和推荐策略至关重要。我们在这项研究中的主要目标是找到最好的机器学习模型来表征社交媒体网络上的影响者。然而,为了实现这一目标,我们的策略围绕着应用PageRank算法来评测整个社交媒体网络图中有影响力的节点。我们的实验结果表明,在为机器学习模型添加新参数时,相关性总是不同的,也是为了确定适合我们需求的模型。无论如何,实验结果对于分析社交媒体平台上的影响者至关重要。
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引用次数: 2
6G Networks Orientation by Quantum Mechanics 量子力学对6G网络的定位
Q3 Decision Sciences Pub Date : 2022-01-01 DOI: 10.13052/jicts2245-800X.1013
Paulo Sergio Rufino Henrique;Ramjee Prasad
Quantum mechanics is a part of physics that studies the interactions of matter, light, and particles at the atomic and subatomic levels. Since its initial concepts in the early 1900s built upon extensive research of Nobel laureates such as Max Planck, Niels Bohr, Albert Einstein, and Richard Feynman, amongst others to the first proposed quantum computers by Paul Benioff in 1980, the concept of quantum technologies has evolved. Two central studies derived from quantum mechanics that can support and revolutionize future wireless technologies are quantum computers and quantum communications. The investigation for building the next generation of wireless networks has begun. Therefore, many technological opportunities for applying innovative solutions and advanced concepts are on the table as an option to unlock the full potential of 6G for providing an intelligent, superfast, and secure network. Having said that, quantum mechanics come into play to offer a breakthrough opportunity that will change the world since the popularization of the Internet, and it will propel 6G use cases to be remarkably successful, but only if quantum physics can be engineered and converged into the forementioned quantum technologies to support the achievement of Society 5.0. Therefore, overcoming the quantum challenges, 6G can benefit in many ways. One of them is Quantum computing (QC) that will surpass the computational capabilities of classic computers limited by binary transactions known as bits to resolve future challenges using quantum states to process information in quantum bits (Qubits). Correspondingly, quantum computing will merge with Artificial Intelligence (AI) to create a new model known as Quantum Machine Learning (QML) to deal with the exponential growth of Big Data faster than any existing computational model. In Addition, quantum communications will deliver a safer network, utilizing Quantum Key Distribution (QKD) and inaugurate the next generation of the Internet, much safer for all. Thus, this paper presents a holistic overview of Quantum as a service (QaaS) as a future deployment in the 6G architecture, but only if quantum technologies can be mastered in the next upcoming years. Most likely that QaaS will become available for commercial purposes by the hyperscalers, the ones able to cope with the total cost of ownership (TCO) of these state of art technologies.
量子力学是物理学的一部分,研究物质、光和粒子在原子和亚原子水平上的相互作用。自20世纪初量子技术的最初概念建立在马克斯·普朗克、尼尔斯·玻尔、阿尔伯特·爱因斯坦和理查德·费曼等诺贝尔奖获得者对1980年保罗·贝尼奥夫首次提出的量子计算机的广泛研究基础上以来,量子技术的概念一直在发展。量子力学的两项核心研究是量子计算机和量子通信,它们可以支持并彻底改变未来的无线技术。构建下一代无线网络的研究已经开始。因此,应用创新解决方案和先进概念的许多技术机会都摆在桌面上,作为释放6G提供智能、超高速和安全网络的全部潜力的一种选择。话虽如此,量子力学的发挥将提供一个突破性的机会,自互联网普及以来,这将改变世界,它将推动6G用例取得显著成功,但前提是量子物理学能够被设计并融合到前面提到的量子技术中,以支持Society 5.0的实现。因此,克服量子挑战,6G可以从许多方面受益。其中之一是量子计算(QC),它将超越被称为比特的二进制事务限制的经典计算机的计算能力,以解决未来使用量子态处理量子比特中信息的挑战。相应地,量子计算将与人工智能(AI)合并,创建一种称为量子机器学习(QML)的新模型,以比任何现有计算模型更快的速度应对大数据的指数增长。此外,量子通信将利用量子密钥分发(QKD)提供一个更安全的网络,并开创下一代互联网,对所有人来说都更安全。因此,本文对量子即服务(QaaS)作为6G架构中的未来部署进行了全面概述,但前提是量子技术能够在未来几年掌握。最有可能的是,QaaS将由超规模公司用于商业目的,这些公司能够应对这些最先进技术的总拥有成本(TCO)。
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引用次数: 1
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Journal of ICT Standardization
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