2021 International Conference on Digital Age & Technological Advances for Sustainable Development (ICDATA)最新文献_第2页

Extended T-Type Topology of Single-Phase Multi-Level Inverter 单相多电平逆变器的扩展t型拓扑

2021 International Conference on Digital Age & Technological Advances for Sustainable Development (ICDATA) Pub Date : 2021-06-01 DOI: 10.1109/ICDATA52997.2021.00043

A. Ouchatti, Azeddine Wahbi, A. Moutabir, Youness Benkhanous, A. Taouni, Redouane Majdoul

引用次数: 0

Competenty-Based Approach for Learning Objects sequencing using DNA computing 基于能力的DNA计算学习对象排序方法

2021 International Conference on Digital Age & Technological Advances for Sustainable Development (ICDATA) Pub Date : 2021-06-01 DOI: 10.1109/ICDATA52997.2021.00030

D. Amina, Mohamed Ben Ali Yamina

引用次数: 1

A Survey of Spam Bots Detection in Online Social Networks 在线社交网络中垃圾邮件机器人检测的调查

2021 International Conference on Digital Age & Technological Advances for Sustainable Development (ICDATA) Pub Date : 2021-06-01 DOI: 10.1109/ICDATA52997.2021.00021

Zineb Ellaky, F. Benabbou, Sara Ouahabi, N. Sael

{"title":"A Survey of Spam Bots Detection in Online Social Networks","authors":"Zineb Ellaky, F. Benabbou, Sara Ouahabi, N. Sael","doi":"10.1109/ICDATA52997.2021.00021","DOIUrl":"https://doi.org/10.1109/ICDATA52997.2021.00021","url":null,"abstract":"Online Social networks (OSN) have become an integral part of people's lives. People from all over the world interact instantly between each other by sharing pictures and content. They can also express their opinion about politics, sport, and be part of influencing users in OSN. So, with the large growth of the number of users of OSN, it has become a target for the vicious people that post spam contents and messages. The malicious social bots (MSB) are one of the biggest threats that menace the social networks security and several studies have been conducted to detect them. In this work we focus on spam bots and reviewed all the existing bot detection techniques based on different features extracted from users' profiles and interactions. The paper analyzed and compared the proposed techniques between 2014 and 2021 to get the most relevant features that improve the spam bot detection and the most efficient Machine learning ML and Deep learning DL techniques from OSN. An investigation on existing datasets is proposed, some limitations of the studied approaches are outlined and future directions for social bot techniques detection improvement are proposed.","PeriodicalId":231714,"journal":{"name":"2021 International Conference on Digital Age & Technological Advances for Sustainable Development (ICDATA)","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117142753","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

An Evidence-Based Approach on Public Health Decisions in Low-Middle Income Countries: Use Case of Senegal at the Verge of COVID-19 中低收入国家公共卫生决策的循证方法:以处于COVID-19边缘的塞内加尔为例

2021 International Conference on Digital Age & Technological Advances for Sustainable Development (ICDATA) Pub Date : 2021-06-01 DOI: 10.1109/ICDATA52997.2021.00046

Jesus Ekie, Bassirou Gueye, Tresor Ekie, I. Niang

{"title":"An Evidence-Based Approach on Public Health Decisions in Low-Middle Income Countries: Use Case of Senegal at the Verge of COVID-19","authors":"Jesus Ekie, Bassirou Gueye, Tresor Ekie, I. Niang","doi":"10.1109/ICDATA52997.2021.00046","DOIUrl":"https://doi.org/10.1109/ICDATA52997.2021.00046","url":null,"abstract":"The advent of health crises like COVID-19 in West Africa, and more particularly in Senegal, led the MoHSA, with the support of several development partners, to set up a real-time alert and information reporting system through the mInfoSante project. These informations are retrieved from Chief Nursing Officers, Chief Veterinary Officers, and more than 2,000 Community Watch & Alert Committees dispatched throughout the national territory. The ease of use of mInfoSante and its advantages has seduced professionals in the health sector. However, one will quickly realize that the exploitation of information can be tedious without the support of a system dedicated to this task. Due to the specificity of the sector as well as the technical and institutional environment, we had to adapt to a certain number of constraints in the identification and implementation of such a solution. To do this, we have studied a set of open-source and powerful Business Intelligence and Dashboarding solutions. According to the performed analysis, our solution, which make use of REST-based service composition, presents advantages of having functionalities related to the distributed storage & processing of large data sets, a capacity for rapid processing of all data types, good computing power offered by its optimized components, and fault tolerance due to integration of distributed infrastructure model.","PeriodicalId":231714,"journal":{"name":"2021 International Conference on Digital Age & Technological Advances for Sustainable Development (ICDATA)","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128725212","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

Sentiment analysis through word embedding using AraBERT: Moroccan dialect use case 基于AraBERT摩洛哥方言用例的词嵌入情感分析

2021 International Conference on Digital Age & Technological Advances for Sustainable Development (ICDATA) Pub Date : 2021-06-01 DOI: 10.1109/ICDATA52997.2021.00024

Yassir Matrane, F. Benabbou, N. Sael

{"title":"Sentiment analysis through word embedding using AraBERT: Moroccan dialect use case","authors":"Yassir Matrane, F. Benabbou, N. Sael","doi":"10.1109/ICDATA52997.2021.00024","DOIUrl":"https://doi.org/10.1109/ICDATA52997.2021.00024","url":null,"abstract":"Nowadays, Sentiment Analysis (SA) represents a big chunk of Natural Language Processing (NLP) problems. The latter makes it possible to assign feelings and polarity to portions of text, which comes handy in multiple areas of social conduct such as product reviewing in business, determining political opinions of the masses and other uses. Nevertheless, sentiment analysis can be tricky when dealing with unstructured languages due to the lack of conventional syntactic and morphological structures. In this paper, we discuss several attempts of the literature at solving the challenge of Sentiment analysis of regional dialects, and we propose an approach based on AraBERT word embedding for Moroccan dialect (MD) sentiment analysis. The method goes through a pipeline of steps starting with preprocessing, lexicon-based translation and feature extraction. Afterwards we conduct a comparative study, in 2-way classification, of machine learning algorithms as SVM, DT, LR, RF, NB and deep learning algorithms such as LSTM, BiLSTM and LSTM-CNN from state of art. On the other hand, we managed to train our model with four different outputs in 4 way classification. As a result, BiLSTM proved to be the best in both 2-way classification scoring 83% accuracy, and in 4-way classification achieving scores ranging between 62% and 92% of accuracy for each of the 4 classes.","PeriodicalId":231714,"journal":{"name":"2021 International Conference on Digital Age & Technological Advances for Sustainable Development (ICDATA)","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115049621","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 3

Elearning 4.0 for higher education: literature review, trends and perspectives 高等教育的电子学习4.0:文献综述，趋势和观点

2021 International Conference on Digital Age & Technological Advances for Sustainable Development (ICDATA) Pub Date : 2021-06-01 DOI: 10.1109/ICDATA52997.2021.00032

Abdelghani Babori, Khalid Ghoulam, N. Falih, Hicham Ouchitachen

引用次数: 2

Towards precision agriculture in Morocco: A machine learning approach for recommending crops and forecasting weather 摩洛哥走向精准农业:推荐作物和预测天气的机器学习方法

2021 International Conference on Digital Age & Technological Advances for Sustainable Development (ICDATA) Pub Date : 2021-06-01 DOI: 10.1109/ICDATA52997.2021.00026

Chouaib El Hachimi, S. Belaqziz, S. Khabba, A. Chehbouni

{"title":"Towards precision agriculture in Morocco: A machine learning approach for recommending crops and forecasting weather","authors":"Chouaib El Hachimi, S. Belaqziz, S. Khabba, A. Chehbouni","doi":"10.1109/ICDATA52997.2021.00026","DOIUrl":"https://doi.org/10.1109/ICDATA52997.2021.00026","url":null,"abstract":"Statistical models predict that the world's population will reach 8.5 billion by the end of 2030. This represents a real threat to our food security and puts the current food production system under pressure. Efficient use of Earth's natural resources is the only solution to facing future challenges such as global hunger. The implementation of precision agriculture using new technologies such as artificial intelligence, big data, IoT and remote sensing is the first step towards this goal. In this paper, we investigated several machine learning models to create two services: one for recommending the best crop to grow based on soil and the region's weather characteristics, and another for the forecasting of the hourly average air temperature. Performance evaluation results for the first service show that Random Forest has the best metrics as a classifier (accuracy = 100%, precision = 100%, recall = 100%) compared to K-Nearest Neighbors (KNN), Decision Tree, Naive Bayes, Logistic Regression, Convolutional Neural Network, and Feed Forward Neural Network. This is a confirmation that classic machine learning algorithms perform better on small-size datasets. In our case, we used a dataset of 2200 instances available online. On the other hand, Facebook Prophet was more accurate (R2 = 0.81, RMSE = 3.74) than our proposed LSTM architecture in time series forecasting at hourly scale using historical weather data provided by the weather station of our study area. These two optimal models are then integrated as the first building blocks in our decision support platform, intended for both farmers and policymakers with the aim of making agriculture in Morocco more efficient and more sustainable.","PeriodicalId":231714,"journal":{"name":"2021 International Conference on Digital Age & Technological Advances for Sustainable Development (ICDATA)","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129315833","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 8

Real-time Facemask Detector using Deep Learning and Raspberry Pi 实时面具检测器使用深度学习和树莓派

2021 International Conference on Digital Age & Technological Advances for Sustainable Development (ICDATA) Pub Date : 2021-06-01 DOI: 10.1109/ICDATA52997.2021.00014

Ikram Ben abdel ouahab, Lotfi Elaachak, M. Bouhorma, Yasser A. Alluhaidan

{"title":"Real-time Facemask Detector using Deep Learning and Raspberry Pi","authors":"Ikram Ben abdel ouahab, Lotfi Elaachak, M. Bouhorma, Yasser A. Alluhaidan","doi":"10.1109/ICDATA52997.2021.00014","DOIUrl":"https://doi.org/10.1109/ICDATA52997.2021.00014","url":null,"abstract":"Medical staffs wear face masks to prevent the spread of the disease. Nowadays, with the coronavirus pandemic everyone must wear a facemask for the same reason. When a person near to you coughs, talks, sneezes he could release germs into the air that may infect you or anyone nearby. Wearing a facemask is a part of an infection control strategy to avoid and eliminate cross-contamination. Even so, people are getting tired of wearing facemasks or they are not conscious enough of the seriousness of the actual covid19. In this paper, we propose a facemask detector based on IoT embedded devices and deep learning algorithm. Our main goal is to warn people in real-time if they are not wearing a facemask or they are not wearing it correctly. The proposed solution generates loud vocal alerts after detection disrespect of facemask wear in real-time for a fast reaction. To have the most efficient detector in real-time we tested the facemask detection model using various versions of the Raspberry Pi and NCS2. As a result, the facemask detector works perfectly on powerful devices, however its performance decrease in realtime using less powerful devices such as an old version of the Raspberry Pi.","PeriodicalId":231714,"journal":{"name":"2021 International Conference on Digital Age & Technological Advances for Sustainable Development (ICDATA)","volume":"34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132420667","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 4

Predicting the Traffic Congestion and Optimal Route in a Smart City Exploiting IoT Devices 利用物联网设备预测智慧城市交通拥堵和最优路径

2021 International Conference on Digital Age & Technological Advances for Sustainable Development (ICDATA) Pub Date : 2021-06-01 DOI: 10.1109/ICDATA52997.2021.00019

Abderrahim Zannou, Abdelhak Boulaalam, E. Nfaoui

{"title":"Predicting the Traffic Congestion and Optimal Route in a Smart City Exploiting IoT Devices","authors":"Abderrahim Zannou, Abdelhak Boulaalam, E. Nfaoui","doi":"10.1109/ICDATA52997.2021.00019","DOIUrl":"https://doi.org/10.1109/ICDATA52997.2021.00019","url":null,"abstract":"Monitoring and managing traffic congestion is the most challenging problem for many cities today. It has an effect on the environment and disrupts our everyday lives. As the population expands, the number of roads and cars, creating a slew of issues such as travel time delays, fuel waste, air pollution, and transportation-related issues. On another side, the Internet of Things (IoT) provides different devices and systems to monitor and manage the real-time traffic for smart cities. In this paper, we propose a new approach to avoid traffic congestion and obtain an optimal route for vehicles in the smart city exploiting IoT devices. To do this, we create a map of all possible sources and destinations, secondly and we suggested new parameters to determine the optimal path for the vehicle's traffic. The first phase is to obtain a set of candidate paths for each possible source and destination using Ant Colony Optimization based on the unvaried constraints. The second phase is to obtain the principal path for the vehicle to achieve its destination. The simulation results show that our solution reduces the distance and the time of travel and avoids traffic congestion.","PeriodicalId":231714,"journal":{"name":"2021 International Conference on Digital Age & Technological Advances for Sustainable Development (ICDATA)","volume":"39 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128630494","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Enhanced VGG19 Model for Accident Detection and Classification from Video 视频事故检测与分类的增强VGG19模型

2021 International Conference on Digital Age & Technological Advances for Sustainable Development (ICDATA) Pub Date : 2021-06-01 DOI: 10.1109/ICDATA52997.2021.00017

S. Bouhsissin, N. Sael, F. Benabbou

引用次数: 2