This qualitative study is an investigation and assessment of distance learning in Morocco during the COVID-19 pandemic. This research surveyed 3037 students and 231 professors enrolled in different stages of higher education programs. It aims to investigate the limitations of e-learning platforms and how these activities take place at public and private Moroccan universities during the coronavirus confinement. For this purpose, two structured questionnaires were constructed by researchers from different specialties, and the type of data was based on the responses of students and professors from 15 universities. In this paper, we have used three methods: descriptive analysis, regression analysis, and qualitative response analysis. As a data analytics tool, Microsoft Power BI was used to analyze data, visualize it, and draw insights. In this study, both professors and students stated that online learning is not more interesting than ordinary learning and professors need to provide at least 50% of their teaching in face-to-face mode. Recommendations at teaching and technical levels, such as the need for technical support and training in the use of these tools, were provided to enhance and promote distance education in Morocco. The contribution of this paper comes as a result of data analysis obtained from a survey conducted in some famous Moroccan universities.

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Due to the increase of published Web Services (WSs), finding the suitable WS that satisfies the user goals among discovered WSs still needs deep investigations. Certainly, QoS requirements represent a more appropriate and decisive factor to distinguish similar WSs. A lot of research efforts in this direction have been made but are still limited due to the complexity and diversity of QoS constraints. The novelty of our approach lies in its simplicity since it is based on WS Popularity Score (WSPS). This score is computed using an algorithm based on both user's requirements and quality measures of each discovered WSs such as pertinence, age, frequency, etc. The paper reports a validation of the proposed algorithm, its implementation and evaluation trough Information Extraction (IE), in order to illustrate, and assess the convenience of our approach.

This paper presents the architecture of an interactive scheduling decision support system (ISDSS) allowing users to find the optimal solution for fertilizer production on parallel heterogeneous processors. The proposed approach takes into account different production process constraints such as launch time, delivery date, preventive maintenance and the impact of scheduling on supply chain management. The ISDSS implemented is run by a relational database used to customize the structural data and the problem parameters. A user interface is available for ISDSS users to define the scheduling problem and design the solution based on tables and graphs for detecting possible issues. The ISDSS architecture was implemented on java using independent modules.

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