Enhancing Learning Object Analysis through Fuzzy C-Means Clustering and Web Mining Methods

The development of learning objects (LO) and e-pedagogical practices has significantly influenced and changed the performance of e-learning systems. This development promotes a genuine sharing of resources and creates new opportunities for learners to explore them easily. Therefore, the need for a system of categorization for these objects becomes mandatory. In this vein, classification theories combined with web mining techniques can highlight the performance of these LOs and make them very useful for learners. This study consists of two main phases. First, we extract metadata from learning objects, using the algorithm of Web exploration techniques such as feature selection techniques, which are mainly implemented to find the best set of features that allow us to build useful models. The key role of feature selection in learning object classification is to identify pertinent features and eliminate redundant features from an excessively dimensional dataset. Second, we identify learning objects according to a particular form of similarity using Multi-Label Classification (MLC) based on Fuzzy C-Means (FCM) algorithms. As a clustering algorithm, Fuzzy C-Means is used to perform classification accuracy according to Euclidean distance metrics as similarity measurement. Finally, to assess the effectiveness of LOs with FCM, a series of experimental studies using a real-world dataset were conducted. The findings of this study indicate that the proposed approach exceeds the traditional approach and leads to viable results. Doi: 10.28991/ESJ-2023-07-03-010 Full Text: PD

Profil Épidémiologique Des Pathologies Respiratoires Aux Services De Pneumologie De La Ville De Meknès (Maroc)

Introduction: Les pathologies respiratoires représentent l’une des causes majeures de morbidité et de mortalité. De ce fait, l’objectif majeur de la présente investigation est d’évaluer le profil épidémiologique des pathologies respiratoires des sujets hospitalisés aux services de pneumologie de Meknès (Maroc). Méthodes: Pour ce faire, une étude rétrospective et descriptive a été menée sur 2842 patients hospitalisés et traités aux services de pneumologie de l’hôpital Mohammed V et de Sidi Saïd, sur une période de cinq ans (1er janvier 2010 au 31 décembre 2014). Résultats: L’analyse des résultats a montré que les pathologies les plus répandues parmi les sujets hospitalisés ont été l’asthme (47,7 %), la tuberculose (17,48 %), les  pneumopathies (11,78 %) et la bronchopneumopathie chronique obstructive (BPCO) (11,29 %). L’asthme était plus prononcé chez les femmes (58,36 %) (p < 0,001) alors que la tuberculose et la BPCO étaient plus fréquentes chez les hommes avec, respectivement, des taux de 56,44 % et de 89,1 % (p < 0.001). Conclusion: Les pathologies respiratoires représentent un véritable problème à la fois sanitaire et socio-économique pour les familles et les structures sanitaires de la ville de Meknès. Introduction: Respiratory pathologies represent one of the major causes of morbidity and mortality. Therefore, the main objective of the present investigation is to evaluate the epidemiological profile of respiratory pathologies of subjects hospitalized at the pneumology department of Meknes (Morocco). Methods: For this purpose, a retrospective and descriptive study was carried out on 2842 patients hospitalized and treated at the Respiratory Departments of Mohammed V Hospital and Sidi Said, over a period of five years (January 1, 2010 to December 31, 2014). Results:  the analysis of the results showed that the most common pathologies among the hospitalized subjects were asthma (47.7%), tuberculosis (17.48%), pneumopathy (11.78%) and chronic obstructive pulmonary disease (COPD) (11.29%). Asthma was more pronounced in women (58.36%) (p < 0.001) while tuberculosis and COPD were more common in men with rates of 56.44% and 89.1% (p < 0.001), respectively. Conclusion: Respiratory diseases represent a real health and socio-economic problem for families and health facilities in Meknes, a city in Morocco

Utilisation Des Tubes A Diffusion Passive Pour La Surveillance De La Pollution Automobile Dans La Ville De Meknes

Road traffic emission is one of the major sources of air pollution which can cause several human health problems including cardiorespiratory diseases. The aim of our study is to monitor air quality in Meknes city (Morocco) by measuring nitrogen dioxide (NO2) and benzene (C6H6) concentration mainly generated by road traffic. To this end, we deployed passive diffusion tubes at 14 sampling sites during two measurement campaigns in the summer of 2014 and the winter of 2015 using car and underground proximity sites. In parallel with the winter measurement campaign, road traffic counting sessions were conducted on the main roads of the city in order to determine average daily traffic intensity. Results of this study show that the atmospheric concentrations of NO2 and C6H6 reach maximum values in the city center and decrease towards its periphery. The average value of NO2 in all targeted sites was around 32, 59 μg / m3, which is lower than the EU limit of 40 μg / m3. The average concentration of C6H6 in Meknes was equal to 1,77 μg / m3, a value close to the quality objective set by the European Union (2 μg / m3) and well below the annual Moroccan limit (10 μg / m3). The use of GIS (geographic information system) for coupling the results of measurement campaigns and those of traffic counting made it possible to determine the areas most affected by these tracers and thus to set up very high spatial resolution cartography

Profil Epidémiologique des Pathologies Respiratoires Chez les Enfants Hospitalisés aux Services de Pédiatrie de la Ville de Meknès (Maroc)

Background: Respiratory diseases are a common cause of consultation and hospitalization in the paediatric service. The purpose of this study was to ascertain the epidemiological profile of respiratory infections among children in Meknes city. Methods: Data from records of children with respiratory infections admitted to the pediatric services in Meknes (Mohammed V Public Hospital and Sidi Said Hospital) in Morocco over a five-year period were extracted. Our cross-sectional observational study concerned 4040 cases hospitalized from January 1st, 2010 to December 31st, 2014, among children aged 0 to 15 and living in Meknes. Results: Hospitalizations for acute bronchiolitis (p < 0.001), asthma exacerbations (p < 0.001), acute pneumonitis (P < 0.001), bronchitis (p < 0.001), and laryngitis (P < 0.001) were more common in male patients, while females were more affected by whooping cough. Hospitalizations for bronchiolitis were more frequent in the automn-winter season in infants (< 2 years). Conclusion: Respiratory diseases constitute a significant burden of childhood illnesses. In our study, hospitalizations for respiratory illness were largely dominated by acute bronchiolitis and asthma exacerbation. Children under 5 were the most represented and the majority of hospitalized patients for respiratory diseases were male. Acute bronchiolitis was more frequent in the autumn-winter period and mainly affected the infants.Introduction: Les pathologies respiratoires représentent un motif fréquent de consultation et d’hospitalisation au service de pédiatrie. L’objectif de cette recherche est d’étudier le profil épidémiologique des affections respiratoires infantiles dans la ville de Meknès. Méthodes: Il s’agit d’une étude observationnelle transversale pourtant sur 4040 cas hospitalisés pour affectionsrespiratoires aux services de pédiatrie de la ville de Meknès(Hôpital public Mohammed V et Sidi Saïd) du premier janvier 2010 au 31 décembre 2014. Ont été inclus dans ce travail, les enfants âgés de 0 à 15 ans résidants à Meknès et ayant été hospitalisés aux services de pédiatrie pour affections respiratoires. Résultats: Les hospitalisations pour bronchiolite aiguë (p < 0,001), exacerbation d’asthme (p < 0,001), pneumopathie aiguë (p < 0,001), bronchite (p < 0,001) et laryngite (p < 0,001) étaient plus fréquentes chez les patients du sexe masculin, alors que le sexe féminin était plus touché par la coqueluche. Les hospitalisations pour bronchiolite étaient plus fréquentes en période automno-hivernale chez les nourrissons (< 2 ans). Conclusion: Les hospitalisations pour affections respiratoires ont été largement dominées par la bronchiolite aigue et l’exacerbation d’asthme. Les patients ayant moins de 5 ans ont été les plusreprésentés dans l’étude et la majorité des cas hospitalisés pour affections respiratoires étaient de sexe masculin. La bronchiolite aigue était plus fréquente en période automno-hivernale et touchait plus les nourrissons

Profil épidémiologique des maladies cardiovasculaires dans la Ville de Meknès (Maroc)

Introduction: In Morocco, very little published work has focused on cardiovascular diseases. As a result, the main objective of this research is to evaluate the epidemiological profile of cardiovascular diseases in patients who are hospitalized and treated in the cardiology department of Mohammed V Hospital, Meknes (Morocco). Methods: This is a retrospective descriptive and analytical study of 1112 patients admitted to this department over a fouryear period (from January 1, 2011 to December 31, 2014). Results: 54.49 % of patients were women and the most affected age group was 45-64 years old (42.08 %) (p < 0.001). The most common pathologies among hospitalized patients were: ischemic heart disease which represented the first cause of hospitalization with 341 cases corresponding to 30.66 %, followed by heart failure (20.59 %). Ischemic heart disease was more common in men (p = 0.05) while women were more affected by high blood pressure (p = 0.0096), heart failure (p = 0.06) and venous thrombosis (p < 0.05). Conclusion: Cardiovascular pathologies represent a real health and socio-economic problem for families and health facilities. The frequency and severity of these diseases should prompt us to do further research on this topic to find the most plausible solutions to reduce negative impacts

Multi-Label Classification of Learning Objects Using Clustering Algorithms Based on Feature Selection

In the field of online learning, the development of learning objects (LOs) has increased. LOs promote reusing and referencing educational content in various learning environments. However, despite this progress, the lack of a conceptual model for sharing suitable LOs between learners makes multiple challenges. In this regard, multi-label classification plays a significant role to make high-quality LOs, which can be accessible and reusable. This article highlights a new way of using learning objects based on Multi-Label Classification (MLC) and clustering algorithms with feature selection techniques. It suggests a new system that makes the most suitable choice among many alternative sources based on the Sharable Content Object Reference Model (SCORM). The proposed algorithm has been tested on a real-world application dataset related to the data analysis service for the learning science community. The experimental results show that our algorithm outperforms the traditional approach and produces good results

Maximizing reusability of learning objects through machine learning techniques

Abstract Maximizing the reusability of learning objects through machine learning techniques has significantly transformed the landscape of e-learning systems. This progress has fostered authentic resource sharing and expanded opportunities for learners to explore these materials with ease. Consequently, a pressing need arises for an efficient categorization system to organize these learning objects effectively. This study consists of two primary phases. Firstly, we extract metadata from learning objects using web exploration algorithms, specifically employing feature selection techniques to identify the most relevant features while eliminating redundant ones. This step drastically reduces the dataset’s dimensionality, enabling the creation of practical and useful models. In the second phase, we employ machine learning algorithms to categorize learning objects based on their specific forms of similarity. These algorithms are adept at accurately classifying objects by measuring their similarity using Euclidean distance metrics. To evaluate the effectiveness of learning objects through machine learning techniques, a series of experimental studies were conducted using a real-world dataset. The results of this study demonstrate that the proposed machine learning approach surpasses traditional methods, yielding promising and efficient outcomes for enhancing learning object reusability

Crystal structure of tetraaquabis(1,3-dimethyl-2,6-dioxo-7 H -purin-7-ido-κ N 7 )cobalt(II)

International audienceThe title complex, [Co(C7H7N4O2)2(H2O)4], comprises mononuclear molecules consisting of a CoII ion, two deprotonated theophylline ligands (systematic name: 1,3-dimethyl-7H-purine-2,6-dione) and four coordinating water molecules. The CoII atom lies on an inversion centre and has a slightly distorted octahedral coordination environment, with two N atoms of two trans-oriented theophylline ligands and the O atoms of four water molecules. An intramolecular hydrogen bond stabilizes this conformation. A three-dimensional supramolecular network structure is formed by intermolecular O-H...O and O-H...N hydrogen bonds

Tris(1,10-phenanthroline-κ2N,N′)nickel(II) bis(hexafluoridophosphate)

The asymmetric unit of the title compound, [Ni(C36H24N6)3](PF6)2, contains one and a half nickel(II) complex dications and three hexafluoridophosphate anions, one of the dications having crystallographic twofold rotational symmetry. Each NiII atom displays a distorted octahedral coordination geometry provided by the six N atoms of three bidentate 1,10-phenanthroline ligands with bite angles of 79.68 (11)–80.76 (12)°. In the crystal, C—H...F hydrogen bonds link the anions and dications into a three-dimensional supramolecular framework. Within the framework complex dications with twofold rotational symmetry are linked by weak π–π stacking interactions [centroid-to-centroid distances = 3.712 (2) Å]

Engineering of H‐Bonding Interactions in PVA/g‐C 3 N 4 Hybrids for Enhanced Structural, Thermal, and Mechanical Properties: Toward Water‐Responsive Shape Memory Nanocomposites

International audienc