Pub Date : 2023-01-01DOI: 10.13052/jicts2245-800X.1115
Xiaogang Li;Di Su;Dongxu Chang;Jiajia Liu;Liwei Wang;Zhansheng Tian;Shuxuan Wang;Wei Sun
Since UAV aerial images are usually captured by UAVs at high altitudes with oblique viewing angles, the amount of data is large, and the spatial resolution changes greatly, so the information on small targets is easily lost during segmentation. Aiming at the above problems, this paper presents a semantic segmentation method for UAV images, which introduces a multi-scale feature extraction and fusion module based on the encoding-decoding framework. By combining multi-scale channel feature extraction and multi-scale spatial feature extraction, the network can focus more on certain feature layers and spatial regions when extracting features. Some invalid redundant features are eliminated and the segmentation results are optimized by introducing global context information to capture global information and detailed information. Moreover, one compares the proposed method with FCN-8s, MSDNet, and U-Net network models on the large-scale multi-class UAV dataset UAVid. The experimental results indicate that the proposed method has higher performance in both MIoU and MPA, with an overall improvement of 9.2% and 8.5%, respectively, and its prediction capability is more balanced for both large-scale and small-scale targets.
{"title":"Multi-scale Feature Extraction and Fusion Net: Research on UAVs Image Semantic Segmentation Technology","authors":"Xiaogang Li;Di Su;Dongxu Chang;Jiajia Liu;Liwei Wang;Zhansheng Tian;Shuxuan Wang;Wei Sun","doi":"10.13052/jicts2245-800X.1115","DOIUrl":"https://doi.org/10.13052/jicts2245-800X.1115","url":null,"abstract":"Since UAV aerial images are usually captured by UAVs at high altitudes with oblique viewing angles, the amount of data is large, and the spatial resolution changes greatly, so the information on small targets is easily lost during segmentation. Aiming at the above problems, this paper presents a semantic segmentation method for UAV images, which introduces a multi-scale feature extraction and fusion module based on the encoding-decoding framework. By combining multi-scale channel feature extraction and multi-scale spatial feature extraction, the network can focus more on certain feature layers and spatial regions when extracting features. Some invalid redundant features are eliminated and the segmentation results are optimized by introducing global context information to capture global information and detailed information. Moreover, one compares the proposed method with FCN-8s, MSDNet, and U-Net network models on the large-scale multi-class UAV dataset UAVid. The experimental results indicate that the proposed method has higher performance in both MIoU and MPA, with an overall improvement of 9.2% and 8.5%, respectively, and its prediction capability is more balanced for both large-scale and small-scale targets.","PeriodicalId":36697,"journal":{"name":"Journal of ICT Standardization","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/iel7/10251929/10261463/10261466.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"67954662","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}
Pub Date : 2023-01-01DOI: 10.13052/jicts2245-800X.1114
Yin Ying;Zhihong Zhou;Quanhai Zhang
The development of fifth generation mobile communication (5G) technology and Internet of Things (IoT) has enabled more mobile terminals to access the network and generate huge amounts of information content. This will make it difficult for the traditional IP-based host-to-host model to cope with the demand for massive data transmission, making network congestion an increasingly serious problem. To cope with these problems, a new network architecture, the Information-Centric Networking (ICN), a content network with content caching as one of its most core functions, has emerged. In addition, in the era when 5G and future 6G networks gradually realize the interconnection of everything, the Information-Centric Internet of Things (IC-IoT) based on ICN architecture has emerged, and a large number of IoT devices can use ICN nodes as edge devices to realize collaborative caching. The caching capacity of IC-IoT is directly related to the transmission efficiency and capacity of the whole network, and the performance of IC-IoT caching capacity is the top priority of research in this field. To address the above issues, the research in this paper focuses on deploying blockchains in IC-IoT networks and using the consensus mechanism of custom blockchains to motivate ICN nodes and non-ICN nodes in the network to perform caching collaboratively, which in turn improves the caching capacity of the whole network. The main work of this paper has the following points. First, incentivize IC-IoT collaborative caching based on blockchain consensus mechanism: by deploying blockchain in IC-IoT, rewarding nodes that obtain bookkeeping rights to incentivize network-wide collaborative caching, and designing experiments to compare the caching capacity of the network before and after the incentive; second, improve DPoS consensus mechanism to incentivize collaborative caching: Experiments are designed to compare the incentive capacity of PoW consensus mechanism and improved DPoS consensus mechanism for IC-IoT network collaborative caching, and to select the consensus mechanism with better performance; third, the design and implementation of IC-IoT test bed: write ICN program to form ICN network from basic communication to multiple nodes, and then deploying blockchain on the network for subsequent extension studies. This thesis demonstrates the feasibility of using blockchain for IC-IoT network cache collaborative incentive, and proves that the blockchain incentive method in this paper can improve the throughput of IC-IoT network cache by building a test bed.
{"title":"Blockchain-based Collaborative Caching Mechanism for Information Center IoT","authors":"Yin Ying;Zhihong Zhou;Quanhai Zhang","doi":"10.13052/jicts2245-800X.1114","DOIUrl":"https://doi.org/10.13052/jicts2245-800X.1114","url":null,"abstract":"The development of fifth generation mobile communication (5G) technology and Internet of Things (IoT) has enabled more mobile terminals to access the network and generate huge amounts of information content. This will make it difficult for the traditional IP-based host-to-host model to cope with the demand for massive data transmission, making network congestion an increasingly serious problem. To cope with these problems, a new network architecture, the Information-Centric Networking (ICN), a content network with content caching as one of its most core functions, has emerged. In addition, in the era when 5G and future 6G networks gradually realize the interconnection of everything, the Information-Centric Internet of Things (IC-IoT) based on ICN architecture has emerged, and a large number of IoT devices can use ICN nodes as edge devices to realize collaborative caching. The caching capacity of IC-IoT is directly related to the transmission efficiency and capacity of the whole network, and the performance of IC-IoT caching capacity is the top priority of research in this field. To address the above issues, the research in this paper focuses on deploying blockchains in IC-IoT networks and using the consensus mechanism of custom blockchains to motivate ICN nodes and non-ICN nodes in the network to perform caching collaboratively, which in turn improves the caching capacity of the whole network. The main work of this paper has the following points. First, incentivize IC-IoT collaborative caching based on blockchain consensus mechanism: by deploying blockchain in IC-IoT, rewarding nodes that obtain bookkeeping rights to incentivize network-wide collaborative caching, and designing experiments to compare the caching capacity of the network before and after the incentive; second, improve DPoS consensus mechanism to incentivize collaborative caching: Experiments are designed to compare the incentive capacity of PoW consensus mechanism and improved DPoS consensus mechanism for IC-IoT network collaborative caching, and to select the consensus mechanism with better performance; third, the design and implementation of IC-IoT test bed: write ICN program to form ICN network from basic communication to multiple nodes, and then deploying blockchain on the network for subsequent extension studies. This thesis demonstrates the feasibility of using blockchain for IC-IoT network cache collaborative incentive, and proves that the blockchain incentive method in this paper can improve the throughput of IC-IoT network cache by building a test bed.","PeriodicalId":36697,"journal":{"name":"Journal of ICT Standardization","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/iel7/10251929/10261463/10261471.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"68101488","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}
Pub Date : 2023-01-01DOI: 10.13052/jicts2245-800X.1112
Ronghu Zhou
For enhance running effectiveness efficiency of logistics carriage supervisory depended on wireless sensor network (WSN), a novel wireless sensor network optimized by improved bat algorithm is established. Firstly, working theory and system framework of WSN depended on logistics monitoring system are analyzed. Secondly, B-MAC protocol is used in proposed wireless sensor network, and corresponding models are established, and recovery ratio of wireless sensor network is defined, and node deployment optimization of wireless sensor network is constructed. Thirdly, the optimization algorithm of node deployment of WSN is designed based on amended bat algorithm, and analysis procedure of this algorithm is established. Finally, a simulation analysis is carried out, analysis results show that performance of proposed WSN logistics carriage supervisory based on improved bat algorithm is better, which has quicker convergence speed and higher convergence precision, and reliability of proposed WSN logistics carriage supervisory is improved, the energy consumption of sensor node data transmission is reduced, and the life of WSN is improved. Proposed WSN based on logistics carriage supervisory based on improved BA has higher coverage ratio and higher efficiency. Therefore proposed wireless sensor network based on logistics carriage supervisory based on improved bat algorithm can obtain better monitoring efficiency, which has prospect application view.
{"title":"Research on Efficiency Optimization of Logistics Vehicle Monitoring Model Based on Wireless Sensor Network","authors":"Ronghu Zhou","doi":"10.13052/jicts2245-800X.1112","DOIUrl":"https://doi.org/10.13052/jicts2245-800X.1112","url":null,"abstract":"For enhance running effectiveness efficiency of logistics carriage supervisory depended on wireless sensor network (WSN), a novel wireless sensor network optimized by improved bat algorithm is established. Firstly, working theory and system framework of WSN depended on logistics monitoring system are analyzed. Secondly, B-MAC protocol is used in proposed wireless sensor network, and corresponding models are established, and recovery ratio of wireless sensor network is defined, and node deployment optimization of wireless sensor network is constructed. Thirdly, the optimization algorithm of node deployment of WSN is designed based on amended bat algorithm, and analysis procedure of this algorithm is established. Finally, a simulation analysis is carried out, analysis results show that performance of proposed WSN logistics carriage supervisory based on improved bat algorithm is better, which has quicker convergence speed and higher convergence precision, and reliability of proposed WSN logistics carriage supervisory is improved, the energy consumption of sensor node data transmission is reduced, and the life of WSN is improved. Proposed WSN based on logistics carriage supervisory based on improved BA has higher coverage ratio and higher efficiency. Therefore proposed wireless sensor network based on logistics carriage supervisory based on improved bat algorithm can obtain better monitoring efficiency, which has prospect application view.","PeriodicalId":36697,"journal":{"name":"Journal of ICT Standardization","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/iel7/10251929/10261463/10261470.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"67954660","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}
Pub Date : 2023-01-01DOI: 10.13052/jicts2245-800X.1111
Wei Han;Shenggang Wu
Recent studies have found the mapping relationship between channel state information used in commercial Wi-Fi devices and environmental changes in the indoor environment, which can be used for sensing purposes. With the advantages of low cost and wide deployment of Wi-Fi facilities, passive indoor tracking systems based on Wi-Fi have huge potential. This article proposes and builds a passive indoor tracking system using commercial Wi-Fi devices, which realizes the function of tracking the human body's trajectory in indoor environment. The system uses only commercial Wi-Fi devices. It processes the collected channel state information data by sending and receiving two pairs of Wi-Fi devices, and extract the movement information the messy data to obtain the trajectory of the human body. The system conducts a geometric feature analysis in the complex plane to obtain accurate displacement information, and utilize a fusion algorithm, combining the AoA (Angle of Arrival) information obtained by MUSIC algorithm, to obtain accurate human trajectory. In the experiment, the complex plane geometric feature analysis algorithm reaches centimeter-level accuracy in obtaining displacement information, while the system reaches decimeter-level accuracy on in obtaining indoor human trajectory on a simulation dataset.
{"title":"Passive Indoor Tracking Fusion Algorithm Using Commodity Wi-Fi","authors":"Wei Han;Shenggang Wu","doi":"10.13052/jicts2245-800X.1111","DOIUrl":"https://doi.org/10.13052/jicts2245-800X.1111","url":null,"abstract":"Recent studies have found the mapping relationship between channel state information used in commercial Wi-Fi devices and environmental changes in the indoor environment, which can be used for sensing purposes. With the advantages of low cost and wide deployment of Wi-Fi facilities, passive indoor tracking systems based on Wi-Fi have huge potential. This article proposes and builds a passive indoor tracking system using commercial Wi-Fi devices, which realizes the function of tracking the human body's trajectory in indoor environment. The system uses only commercial Wi-Fi devices. It processes the collected channel state information data by sending and receiving two pairs of Wi-Fi devices, and extract the movement information the messy data to obtain the trajectory of the human body. The system conducts a geometric feature analysis in the complex plane to obtain accurate displacement information, and utilize a fusion algorithm, combining the AoA (Angle of Arrival) information obtained by MUSIC algorithm, to obtain accurate human trajectory. In the experiment, the complex plane geometric feature analysis algorithm reaches centimeter-level accuracy in obtaining displacement information, while the system reaches decimeter-level accuracy on in obtaining indoor human trajectory on a simulation dataset.","PeriodicalId":36697,"journal":{"name":"Journal of ICT Standardization","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/iel7/10251929/10261463/10261465.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"67954661","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}
Pub Date : 2023-01-01DOI: 10.13052/jicts2245-800X.1113
Xiaoxia Li
Establishing an efficient cloud computing task scheduling model is the object of many scholars' research. In view of the low scheduling efficiency in cloud computing task scheduling, we propose a cloud computing task scheduling algorithm based on the fusion of the Fireworks Algorithm and Bird Swarm Algorithm (IFWA-BSA). Firstly, we describe the cloud computing task scheduling model based on time and cost constraint functions, secondly, we use chaotic backward learning and Coasean distribution for optimization in FWA initialization; we set thresholds for the radius of core fireworks and non-core fireworks for optimization; we filter the IFWA individuals after each iteration by BSA algorithm, and finally, we use the IFWA-BSA algorithm is used in cloud computing task scheduling model to solve the optimal solution. In the simulation experiments, IFWA-BSA has obvious advantages over ACO, PSO and FWA in the comparison of execution time and consumption cost indexes, which reduces the scheduling time and cost of cloud computing.
{"title":"An IFWA-BSA Based Approach for Task Scheduling in Cloud Computing","authors":"Xiaoxia Li","doi":"10.13052/jicts2245-800X.1113","DOIUrl":"https://doi.org/10.13052/jicts2245-800X.1113","url":null,"abstract":"Establishing an efficient cloud computing task scheduling model is the object of many scholars' research. In view of the low scheduling efficiency in cloud computing task scheduling, we propose a cloud computing task scheduling algorithm based on the fusion of the Fireworks Algorithm and Bird Swarm Algorithm (IFWA-BSA). Firstly, we describe the cloud computing task scheduling model based on time and cost constraint functions, secondly, we use chaotic backward learning and Coasean distribution for optimization in FWA initialization; we set thresholds for the radius of core fireworks and non-core fireworks for optimization; we filter the IFWA individuals after each iteration by BSA algorithm, and finally, we use the IFWA-BSA algorithm is used in cloud computing task scheduling model to solve the optimal solution. In the simulation experiments, IFWA-BSA has obvious advantages over ACO, PSO and FWA in the comparison of execution time and consumption cost indexes, which reduces the scheduling time and cost of cloud computing.","PeriodicalId":36697,"journal":{"name":"Journal of ICT Standardization","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/iel7/10251929/10261463/10261464.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"67954659","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}
Pub Date : 2022-01-01DOI: 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.
{"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":null,"pages":null},"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}
Pub Date : 2022-01-01DOI: 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.
{"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":null,"pages":null},"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}
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.
{"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":null,"pages":null},"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}
Pub Date : 2022-01-01DOI: 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.
{"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":null,"pages":null},"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}
Pub Date : 2022-01-01DOI: 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
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