A new sentiment analysis method to detect and Analyse sentiments of Covid-19 moroccan tweets using a recommender approach.

Since the beginning of the covid-19 crisis, people from all over the world have used social media platforms to publish their opinions, sentiments, and ideas about the coronavirus epidemic and their news. Due to the nature of social networks, users share an immense amount of data every day in a freeway, which gives them the possibility to express opinions and sentiments about the coronavirus pandemic regardless of the time and the place. Moreover, The rapid number of exponential cases globally has become the apprehension of panic, fear, and anxiety among people. In this paper, we propose a new sentiment analysis approach to detect sentiments in Moroccan tweets related to covid-19 from March to October 2020. The proposed model is a recommender approach using the advantages of recommendation systems for classifying each tweet into three classes: positive, negative, or neutral. Experimental results show that our method gives good accuracy(86%) and outperforms the well-known machine learning algorithms. We find also that the sentiments of users changed from period to period, and that the evolution of the epidemiological situation in morocco affects the sentiments of users.

Strategic design of precautionary measures for airport passengers in times of global health crisis Covid 19: Parametric modelling and processing algorithms.

Presently, the negative results of a pandemic loom in a threatening manner on an international scale. Facilities such as airports have contributed significantly to the global spread of the COVID-19 virus. Therefore, in order to address this challenge, studies on sanitary risk management and the proper application of countermeasures should be carried out. To measure the consequences over passenger flow, simulation modelling has been set up at Casablanca Mohammed V International Airport. Several scenarios using daily traffic data were run in different circumstances. This allowed the development of some assumptions regarding the overall capacity of the airport. The proposed simulations make it possible to calculate the number of passengers to be processed in accordance with the available check-in counters based on the proposed sanitary measures.

Bibliometric method for mapping the state of the art of scientific production in Covid-19.

Global scientific production around the Covid-19 pandemic, in the various disciplines on the various international scientific bibliographic databases, has grown exponentially. The latter builds a source of scientific enrichment and an important lever for most researchers around the world, each of its field and its position with an ultimate aim of overcoming this pandemic. In this direction, bibliometric data constitute a fundamental source in the process of evaluation of scientific production in the academic world; bibliometrics provides researchers and institutions with crucial strategic information for the enhancement of their research results with the local and international scientific community, especially in this international pandemic.

Handwritten mathematical symbols dataset.

Due to the technological advances in recent years, paper scientific documents are used less and less. Thus, the trend in the scientific community to use digital documents has increased considerably. Among these documents, there are scientific documents and more specifically mathematics documents. In this context, we present our own dataset of handwritten mathematical symbols composed of 10,379 images. This dataset gathers Arabic characters, Latin characters, Arabic numerals, Latin numerals, arithmetic operators, set-symbols, comparison symbols, delimiters, etc.