Journal of ICT Standardization最新文献

{"title":"Innovative Maritime Operations Management Using Blockchain Technology & Standardization","authors":"Manos-Nikolaos Papadakis;Evangelia Kopanaki","doi":"10.13052/jicts2245-800X.1041","DOIUrl":"https://doi.org/10.13052/jicts2245-800X.1041","url":null,"abstract":"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.","PeriodicalId":36697,"journal":{"name":"Journal of ICT Standardization","volume":"10 4","pages":"469-507"},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/iel7/10251929/10254731/10255401.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"68009017","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Modelling IoT Behaviour in Supply Chain Business Processes with BPMN: A Systematic Literature Review","authors":"Ihsane Abouzid;Younes Karfa Bekali;Rajaa Saidi","doi":"10.13052/jicts2245-800X.1035","DOIUrl":"https://doi.org/10.13052/jicts2245-800X.1035","url":null,"abstract":"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.","PeriodicalId":36697,"journal":{"name":"Journal of ICT Standardization","volume":"10 3","pages":"439-467"},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/iel7/10251929/10255395/10255414.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"67890238","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"COVID-19 Impact Sentiment Analysis on a Topic-based Level","authors":"Mustapha Hankar;Marouane Birjali;Anas El-Ansari;Abderrahim Beni-Hssane","doi":"10.13052/jicts2245-800X.1027","DOIUrl":"https://doi.org/10.13052/jicts2245-800X.1027","url":null,"abstract":"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.","PeriodicalId":36697,"journal":{"name":"Journal of ICT Standardization","volume":"10 2","pages":"219-240"},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/iel7/10251929/10254727/10255411.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"68110506","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Sentence-Level Sentiment Classification A Comparative Study Between Deep Learning Models","authors":"Sara Mifrah;El Habib Benlahmar","doi":"10.13052/jicts2245-800X.10213","DOIUrl":"https://doi.org/10.13052/jicts2245-800X.10213","url":null,"abstract":"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.","PeriodicalId":36697,"journal":{"name":"Journal of ICT Standardization","volume":"10 2","pages":"339-351"},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/iel7/10251929/10254727/10255397.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"68110509","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Blockchain Technology for a Safe and Transparent Covid-19 Vaccination","authors":"Maha Filali Rotbi;Saad Motahhir;Abdelaziz El Ghzizal","doi":"10.13052/jicts2245-800X.1022","DOIUrl":"https://doi.org/10.13052/jicts2245-800X.1022","url":null,"abstract":"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","PeriodicalId":36697,"journal":{"name":"Journal of ICT Standardization","volume":"10 2","pages":"125-144"},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/iel7/10251929/10254727/10255416.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"68110514","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"6G Mobile Communication Networks: Key Services and Enabling Technologies","authors":"Sanjay Kumar","doi":"10.13052/jicts2245-800X.1011","DOIUrl":"https://doi.org/10.13052/jicts2245-800X.1011","url":null,"abstract":"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.","PeriodicalId":36697,"journal":{"name":"Journal of ICT Standardization","volume":"10 1","pages":"1-10"},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/iel7/10251929/10255387/10255399.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"68134608","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A Moroccan Sign Language Recognition Algorithm Using a Convolution Neural Network","authors":"Nourdine Herbaz;Hassan El Idrissi;Abdelmajid Badri","doi":"10.13052/jicts2245-800X.1033","DOIUrl":"https://doi.org/10.13052/jicts2245-800X.1033","url":null,"abstract":"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%.","PeriodicalId":36697,"journal":{"name":"Journal of ICT Standardization","volume":"10 3","pages":"411-425"},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/iel7/10251929/10255395/10255398.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"68169374","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Semantic Web and Internet of Things: Challenges, Applications and Perspectives","authors":"Fatima Zahra Amara;Mounir Hemam;Meriem Djezzar;Moufida Maimor","doi":"10.13052/jicts2245-800X.1029","DOIUrl":"https://doi.org/10.13052/jicts2245-800X.1029","url":null,"abstract":"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.\u0000¹\u0000¹\u0000https://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.","PeriodicalId":36697,"journal":{"name":"Journal of ICT Standardization","volume":"10 2","pages":"261-291"},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/iel7/10251929/10254727/10255413.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"68110507","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Data Profiling and Machine Learning to Identify Influencers from Social Media Platforms","authors":"Bahaa Eddine Elbaghazaoui;Mohamed Amnai;Youssef Fakhri","doi":"10.13052/jicts2245-800X.1026","DOIUrl":"https://doi.org/10.13052/jicts2245-800X.1026","url":null,"abstract":"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.","PeriodicalId":36697,"journal":{"name":"Journal of ICT Standardization","volume":"10 2","pages":"201-218"},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/iel7/10251929/10254727/10255427.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"68110515","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"6G Networks Orientation by Quantum Mechanics","authors":"Paulo Sergio Rufino Henrique;Ramjee Prasad","doi":"10.13052/jicts2245-800X.1013","DOIUrl":"https://doi.org/10.13052/jicts2245-800X.1013","url":null,"abstract":"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.","PeriodicalId":36697,"journal":{"name":"Journal of ICT Standardization","volume":"10 1","pages":"39-62"},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/iel7/10251929/10255387/10255390.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"68134613","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}