An adaptation of Text2Onto for supporting the French language

The ontologies are progressively imposing themselves in the field of knowledge management. While the manual construction of an ontology is by far the most reliable, this task has proved to be too tedious and expensive. To assist humans in the process of building an ontology, several tools have emerged proposing the automatic or semi-automatic construction of ontologies. In this context, Text2Onto has become one of the most recognized ontology learning tools. The performance of this tool is confirmed by several research works. However, the development of this tool is based on Princeton WordNet (PWN) for English. As a result, it is limited to the processing of textual resources written in English. In this paper, we present our approach based on JWOLF, a Java API to access the free WordNet for French that we have developed to adapt this tool for the construction of ontologies from corpus in French. To evaluate the usefulness of our approach, we assessed the performance of the improved version of Text2Onto on a simplistic corpus of French language documents. The results of this experiment have shown that the improved version of Text2Onto according to our approach is effective for the construction of an ontology from textual documents in the French language

Onto2DB: towards an eclipse plugin for automated database design from an ontology

Ontologies are spreading more and more in the field of information technologies as a privileged solution allowing the formalization of knowledge. The theoretical model of ontologies is most promising. They are increasingly ubiquitous given the benefits they present. Despite the proliferation of research proposing approaches dedicated to the design of a database from an ontology, the tools to design a database from an ontology are rare or inaccessible. Thus, in this contribution, we present our approach for the development of an Eclipse Plug-in, in order to automatically generate a conceptual model of a relational database from an ontology. To evaluate the usefulness of our approach, we used our resulting Eclipse Plug-in to automatically generate a conceptual model of a relational database from an ontology, customize it, and automatically generate the corresponding SQL script for Data Definition. The results of this experiment showed that our Plug-in constitutes a concretization of our approach and a means of automatic translation from the ontological model to the relational model

The impact of IT investment on firm performance based on MCDM techniques

In the recent past years, researchers have presented conflicting results regarding the impact of information technology investment on firm performance. Almost all studies on information technology productivity and it role for companies performance are based on data collected and meta-analysis and do not offer a methodology or prototype of analysis in any field This study presents an attempt to adopt a multi-criteria decision making approach to evaluate the non-financial performance of companies using two famous methods. Furthermore, our results try to investigate the effects of information technology investments on firms’ non-financial performance. Finding show that investment in information systems is not necessarily related to achieving a good non-financial performance at the firm level

A fuzzy-based prediction approach for blood delivery using machine learning and genetic algorithm

Multiple diseases require a blood transfusion on daily basis. The process of a blood transfusion is successful when the type and amount of blood is available and when the blood is transported at the right time from the blood bank to the operating room. Blood distribution has a large portion of the cost in hospital logistics. The blood bank can serve various hospitals; however, amount of blood is limited due to donor shortage. The transportation must handle several requirements such as timely delivery, vibration avoidance, temperature maintenance, to keep the blood usable. In this paper, we discuss in first section the issues with blood delivery and constraint. The second section present routing and scheduling system based on artificial intelligence to deliver blood from the blood-banks to hospitals based on single blood bank and multiple blood banks with respect of the vehicle capacity used to deliver the blood and creating the shortest path. The third section consist on solution for predicting the blood needs for each hospital based on transfusion history using machine learning and fuzzy logic. The last section we compare the results of well-known solution with our solution in several cases such as shortage and sudden changes

Function and Topology of Toc64,a subunit of the protein translocation machinery of the chloroplast outer envelope

Precursor protein targeting toward surfaces of organelles is assisted by different cytosolic chaperones. The Toc translocon recognizes precursor proteins and facilitates their translocation across the outer envelope of chloroplasts. Toc64 is a subunit of the chloroplast protein import machinery. This work focuses on topological and functional properties of Toc64. The topological prediction of the protein by different programs revealed that Toc64 contains three transmembrane domains, which has been confirmed by the obtained biochemical an experimental results. It was demonstrated that the TPR domain of Toc64 is cytosolic exposed, whereas a second domain of about 30 kDa is exposed to the intermembrane space and protected by the chloroplast outer envelope, which is a part of the amidase and charged regions. Functional analysis demonstrated that Toc64 is a bi-functional preprotein receptor. First, the cytosolic exposed TPR is the docking site for Hsp90 bound precursor proteins. The Hsp90 is recognised by the clamp type TPR of Toc64. Hence, a novel mechanism in which chaperones are recruited for a specific targeting event by a membrane-inserted receptor is outlined. Second, the intermembrane space exposed domain allows the association of Toc64 with the Toc complex and is involved in precursor protein recognition and translocation across the intermembrane space. This domain also participates in the formation of the intermembrane space complex, which involves Toc12, isHsp70 and Tic22

Dysgraphia detection based on convolutional neural networks and child-robot interaction

Dysgraphia is a disorder of expression with the writing of letters, words, and numbers. Dysgraphia is one of the learning disabilities attributed to the educational sector, which has a strong impact on the academic, motor, and emotional aspects of the individual. The purpose of this study is to identify dysgraphia in children by creating an engaging robot-mediated activity, to collect a new dataset of Latin digits written exclusively by children aged 6 to 12 years. An interactive scenario that explains and demonstrates the steps involved in handwriting digits is created using the verbal and non-verbal behaviors of the social humanoid robot Nao. Therefore, we have collected a dataset that contains 11,347 characters written by 174 participants with and without dysgraphia. And through the advent of deep learning technologies and their success in various fields, we have developed an approach based on these methods. The proposed approach was tested on the generated database. We performed a classification with a convolutional neural network (CNN) to identify dysgraphia in children. The results show that the performance of our model is promising, reaching an accuracy of 91%

From IT service management to IT service governance: An ontological approach for integrated use of ITIL and COBIT frameworks

Some companies have achieved better performance as a result of their IT investments, while others have not, as organizations are interested in calculating the value added by their IT. There is a wide range of literature that agrees that the best practices used by organizations promote continuous improvement in service delivery. Nevertheless, overuse of these practices can have undesirable effects and unquantified investments. This paper proposed a practical tool formally developed according to the DSR design science approach, it addresses a domain relevant to both practitioners and academics by providing IT service governance (ITSG) domain model ontology, concerned with maximizing the clarity and veracity of the concepts within it. The results revealed that the proposed ontology resolved key barriers to ITSG process adoption in organizations, and that combining COBIT and ITIL practices would help organizations better manage their IT services and achieve better business-IT alignment

A design of a multi-agent recommendation system using ontologies and rule-based reasoning: pandemic context

Learners attend their courses in remote or hybrid systems find it difficult to follow one size fits all courses. These difficulties have increased with the pandemic, lockdown, and the stress they cause. Hence, the role of adaptive systems to recommend personalized learning resources according to the learner's profile. The purpose of this paper is to design a system for recommending learning objects according learner's condition, including his mental state, his COVID-19 history, as well as his social situation and ability to connect to the e-learning system on a regular basis. In this article, we present an architecture of a recommendation system for personalized learning objects based on ontologies and on rule-based reasoning, and we will also describe the inference rules required for the adaptation of the educational content to the needs of the learners, taking into account the learner’s health and mental state, as well as his social situation. The system designed, and validated using the unified modeling language (UML). It additionally allows teachers to have a holistic view of learners’ progress and situations

Multi-objective IT Project Selection Model for Improving SME Strategy Deployment

Due to the limited financial resources of small and Medium-sized enterprises (SMEs), the proven approaches for selecting IT project portfolio for large enterprises may fail to perform in SMEs; SME top management want to make sure that the corporate strategy is carried out effectively by IT project portfolio before investing in such projects. In order to provide automated support to the selection of IT projects, it seems inevitable that a multi-objective approach is required in order to balance possible competing and conflicting objectives. Under such an approach, individual projects would be evaluated not just on their own performance but on the basis of their contribution to balance the overall portfolio. In this paper, we extend and explore the concept of IT project selection to improve SME strategy deployment. In particular, we present a model that assesses an individual project in terms of its contribution to the overall strategic objectives of the portfolio. A simulation using the model illustrates how SME can rapidly achieve maximal business goals by deploying the multi-objective algorithm when selecting IT projects

Contribution à l’automatisation des processus de fragmentation, de duplication et de réplication des Bases de Données Distribuées à base des Protocoles Réseaux

La gestion distribuée des données nécessite des processus automatisés, bien adaptés aux règles de fragmentation, de duplication et de réplication de ces données sur plusieurs serveurs de Bases De Données (BDD). Notre contribution consiste à mettre en place des processus pour l’amélioration de la stratégie de gestion distribuée des données en intégrant tous les aspects d’analyse lexicale et syntaxique concernant les besoins en données significatives de chaque serveur, en particulier celles qui répondent aux différentes requêtes ou demandes les plus fréquemment soumises par les utilisateurs locaux. Il s’agit du développement d’un compilateur d’algèbre relationnelle et de requêtes SQL. L’automatisation de ces processus permettra aux administrateurs de BDD distribuées d’utiliser plus facilement les sous BDD en fonction du nombre de sites (serveurs de BDD) et des contraintes de division exprimées par les besoins des utilisateurs locaux. Les principaux apports de cette automatisation peuvent être résumés ainsi : Répartition automatique d’une BDD globale en plusieurs sous BDD locales,Extraction de données recherchées indépendamment de l’emplacement physique de leurs sources,Transfert global des données en cascade entre sites,Amélioration de l’équilibre de charges sur les serveurs,Allocation dynamique des fragments de données à plusieurs serveurs