Abstract-This paper presents an issue that is important to consider when developing a learning environment whose field is constantly evolving mainly in terms of the use of training platforms. Research in this field has enabled the successful use of information technologies for the benefit of human learning, while placing the learner at the heart of pedagogic situations. It is also an environment that integrates human agents (tutors, learners) and artificial (computers) and allows them to interact locally or through computer networks, as well as conditions for accessing local or distributed training resources. Moreover, several computing environments for human learning (CEHL) platforms are available on the web for free access. These platforms are environments that offer a learner a multitude of courses in various formats in order to satisfy the learner's desire to learn. Several CEHL platforms are available on the web for free access. But learning itself is not enough and that is why a new generation of advanced learning systems that integrate new pedagogical approaches giving the learner an active role to learn and acquire knowledge has emerged by offering more Interactivity and incorporating a more learner-centered vision. These new generations of advanced learning systems adapt to learners and their profiles by taking into account their cognitive, intellectual and motivational characteristics. An adaptation that cannot be achieved without the complicity of ontological engineering, which plays a very important role in the sharing of knowledge between humans and computers, and between computers and sharing, and reuse of concepts through computational semantics. By the same way, this paper aims at creating a process of modeling and managing profiles of learners based on ontology whatever the learning situation may be. This management process is implemented in computer's environment based on the learner's ontology that supports the learner by detecting the gaps in several factors in order to improve them and adapt the pedagogical content to the learner's profile.
Building quality educational resources with new technologies requires offering learners and teachers a simple computing environment that would be adapted and would allow it to use its pedagogy in respondent contents of learner's needs, in terms of adaptability, portability monitoring and evaluation. In this article, the focal point is reminding the architecture of our Dynamic Adaptive Hypermedia (DAH) system, we shall focus on these different elements namely, the model domain, the student's model, teaching model, the courses' generator, and the multimedia database. Then, we will detail the steps of the proposed approach to the development of educational content through this (DAH) system, dedicated to both teachers and learners. The purpose is to come up with a mechanism that can adapt the course to the learner's profile, in a Computing Environment For Human Learning (CEHL). In this article, we are putting much importance on the various information stored in the models of our system, which would be useful to dynamically generate structured and comprehensive educational content according to cognitive status and the learner's style. The aim is to try hard and to look for pedagogical contents, dealing with concepts of a particular field of knowledge that is adapted to a particular learner. In other words, we want to develop a generic model of interactive multimedia
Efficiency is crucial, in Emergency Departments (EDs). It can be hindered by the number of patients. In this study we present a solution that utilizes the increasing amount of healthcare data and advancements in data analysis techniques. Our approach involves a combination of LSTM and Decision Tree models to enhance the accuracy of predicting volume, in EDs. The results indicate that our model outperforms existing methods suggesting its potential to improve ED efficiency.
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