MV-TMM: Une approche multi vues pour la gestion de la traçabilité des exigences

The approach MV-TMM (Multi View Traceability Management Method) presented in this thesis aims to guide the companies in their design of requirements traceability models adapted to the context of their projects. This is achieved by allowing the construction of a model based on trace fragments adapted to each phase of the development process or to a specific situation. Furthermore, the approach guides the users to use the traceability model in a requirement management tool. They help them capture and mange the evolution of the traceability data.Après une étude de l‘état de l‘art dans le domaine de la traçabilité des exigences, nous avons constaté que la gestion de la traçabilité a fait l‘objet de plusieurs travaux de recherche. Malgré ces travaux, nous avons constaté que les entreprises rencontrent encore des difficultés à intégrer la traçabilité dans leurs processus de développement. Cela est dû au manque de mécanisme de représentation des différents types d‘informations de traçabilité ainsi qu‘à la méconnaissance du processus de traçabilité des exigences dans un projet.Le travail de cette thèse propose une solution dénommée MV-TMM (un démarche multi vues pour la gestion de la traçabilité) composée de deux éléments principaux : (i) un méta modèle multi vues permettant la représentation des différents types d‘informations de traçabilité et (ii) un processus intentionnel décrivant les étapes nécessaires pour la construction et l‘usage des informations de traçabilité

MTORC1 signaling and regulation of pancreatic β-cell mass

The capacity of β cells to expand in response to insulin resistance is a critical factor in the development of type 2 diabetes. Proliferation of β cells is a major component for these adaptive responses in animal models. The extracellular signals responsible for β-cell expansion include growth factors, such as insulin, and nutrients, such as glucose and amino acids. AKT activation is one of the important components linking growth signals to the regulation of β-cell expansion. Downstream of AKT, tuberous sclerosis complex 1 and 2 (TSC1/2) and mechanistic target of rapamycin complex 1 (mTORC1) signaling have emerged as prime candidates in this process, because they integrate signals from growth factors and nutrients. Recent studies demonstrate the importance of mTORC1 signaling in β cells. This review will discuss recent advances in the understanding of how this pathway regulates β-cell mass and present data on the role of TSC1 in modulation of β-cell mass. Herein, we also demonstrate that deletion of Tsc1 in pancreatic β cells results in improved glucose tolerance, hyperinsulinemia and expansion of β-cell mass that persists with aging

TEAD and YAP regulate the enhancer network of human embryonic pancreatic progenitors.

The genomic regulatory programmes that underlie human organogenesis are poorly understood. Pancreas development, in particular, has pivotal implications for pancreatic regeneration, cancer and diabetes. We have now characterized the regulatory landscape of embryonic multipotent progenitor cells that give rise to all pancreatic epithelial lineages. Using human embryonic pancreas and embryonic-stem-cell-derived progenitors we identify stage-specific transcripts and associated enhancers, many of which are co-occupied by transcription factors that are essential for pancreas development. We further show that TEAD1, a Hippo signalling effector, is an integral component of the transcription factor combinatorial code of pancreatic progenitor enhancers. TEAD and its coactivator YAP activate key pancreatic signalling mediators and transcription factors, and regulate the expansion of pancreatic progenitors. This work therefore uncovers a central role for TEAD and YAP as signal-responsive regulators of multipotent pancreatic progenitors, and provides a resource for the study of embryonic development of the human pancreas

c2iot a framework for cloud based context aware internet of things services for smart cities

Abstract The smart city vision was born by the integration of ICT in the day to day city management operations and citizens lives, owing to the need for novel and smart ways to manage the cities resources; making them more efficient, sustainable and transparent. However, the understanding of the crucial elements to this integration and how they can benefit from each other proves difficult and unclear. In this article, we investigate the intricate synergies between different technologies and paradigms involved in the smart city vision, to help design a robust framework, capable of handling the challenges impeding its successful implementation. To this end, we propose a context-aware centered approach to present a holistic view of a smart city as viewed from the different angles (Cloud, IoT, Big Data). We also propose a framework encompassing elements from the different enablers, leveraging their strengths to build and develop smart-x applications and services

Hypothalamic Wnt signalling and its role in energy balance regulation

yesWnt signalling and its downstream effectors are well known for their roles in embryogenesis and tumourigenesis, including the regulation of cell proliferation, survival and differentiation. In the nervous system, Wnt signalling has been described mainly during embryonic development, although accumulating evidence suggests that it also plays a major role in adult brain morphogenesis and function. Studies have predominantly concentrated on memory formation in the hippocampus, although recent data indicate that Wnt signalling is also critical for neuroendocrine control of the developed hypothalamus, a brain centre that is key in energy balance regulation and whose dysfunction is implicated in metabolic disorders such as type 2 diabetes and obesity. Based on scattered findings that report the presence of Wnt molecules in the tanycytes and ependymal cells lining the third ventricle and arcuate nucleus neurones of the hypothalamus, their potential importance in key regions of food intake and body weight regulation has been investigated in recent studies. The present review brings together current knowledge on Wnt signalling in the hypothalamus of adult animals and discusses the evidence suggesting a key role for members of the Wnt signalling family in glucose and energy balance regulation in the hypothalamus in diet-induced and genetically obese (leptin deficient) mice. Aspects of Wnt signalling in seasonal (photoperiod sensitive) rodents are also highlighted, given the recent evidence indicating that the Wnt pathway in the hypothalamus is not only regulated by diet and leptin, but also by photoperiod in seasonal animals, which is connected to natural adaptive changes in food intake and body weight. Thus, Wnt signalling appears to be critical as a modulator for normal functioning of the physiological state in the healthy adult brain, and is also crucial for normal glucose and energy homeostasis where its dysregulation can lead to a range of metabolic disorders

Integrated design approach for responsive solar-shadings in double skin facades in hot arid climate

Ph. D. Thesis.To deliver climate adaptive architecture, current trends in architecture are directed towards dynamic and responsive building skins. ‘Responsive building skin’ is used to describe the ability of building envelopes to adapt in real time in response to external environmental conditions. Recent attention has focused on ‘soft robotics’ approach which uses soft and/or extensible materials to deform with muscle‐like actuation, mimicking biological systems. Material embedded actuation can autonomously alter shading systems’ morphology stimulated by external environmental conditions. Passively thermally‐activated shading systems offer responsive actuation by solar‐radiation and stratified hot air in a double skin façade (DSF) without recourse to energy consuming systems. This research identifies the intersection between bio‐inspiration, folding principles and smart materials to integrate the underlying mechanisms in responsive solar‐shading systems and assesses their environmental performance. The thesis proposes an interdisciplinary mixed methodology linking hands‐on experimentation with environmental performance simulation of responsive building skins. ‘Practice‐led approach’ is used to explore the design potential of responsive systems using smart materials. ‘Computational Fluid Dynamics’ (CFD) numerical methods are used to measure the impact of responsive solar‐shading systems on multiple environmental factors in a DSF cavity. This helps the design decisions, selection and customisation of smart materials. Hands‐on experimentation is used to explore various prototypes, leading to the selection of a folded prototype, to be simulated for environmental performance. Solar‐shading systems are tested within a DSF, in an hot arid climate. Flat and folded solar‐shading devices are installed in a DSF cavity with three aperture sizes (30%, 50% & 70%) to represent the responsive system states. Point‐in‐time simulations are carried at 9:00 am, 12:00 pm and 15:00 pm in peak summer and winter day. The developed analytical design framework presents different design parameters for responsive solar‐shading systems to guide decision‐making in research of climate actuated smart shading systems. Keywords: Responsive skins, Adaptive facades, Soft robotics, Bio‐inspiration, Origami, Deployable structures, Actuation, Smart materials, Shape memory alloys, Double skin facades, Energy efficiency, Digital simulation, CFD Modelling

Deep Learning-Based Intrusion Detection System for Advanced Metering Infrastructure

Smart grid is an alternative solution of the conventional power grid which harnesses the power of the information technology to save the energy and meet today's environment requirements. Due to the inherent vulnerabilities in the information technology, the smart grid is exposed to a wide variety of threats that could be translated into cyber-attacks. In this paper, we develop a deep learning-based intrusion detection system to defend against cyber-attacks in the advanced metering infrastructure network. The proposed machine learning approach is trained and tested extensively on an empirical industrial dataset which is composed of several attack categories including the scanning, buffer overflow, and denial of service attacks. Then, an experimental comparison in terms of detection accuracy is conducted to evaluate the performance of the proposed approach with Naive Bayes, Support Vector Machine, and Random Forest. The obtained results suggest that the proposed approaches produce optimal results comparing to the other algorithms. Finally, we propose a network architecture to deploy the proposed anomaly-based intrusion detection system across the Advanced Metering Infrastructure network. In addition, we propose a network security architecture composed of two types of Intrusion detection system types, Host and Network-based, deployed across the Advanced Metering Infrastructure network to inspect the traffic and detect the malicious one at all the levels.Comment: 7 pages, 6 figures. 2019 NISS19: Proceedings of the 2nd International Conference on Networking, Information Systems & Securit

VERS UNE ÉVALUATION ADAPTATIVE, INDIVIDUALISÉE ET ÉQUITABLE

L’adaptation et l’individualisation de l’enseignement sont au cœur des recherches actuelles dans les Environnements Informatiques pour l’Apprentissage Humain (EIAH). Ainsi des progressions cruciales ont été réalisées au cours de ces dernières années, ce qui assure l’adaptation du déroulement des apprentissages. Néanmoins, certains aspects concernant l’évaluation en ligne des apprentissages (e-Testing), sont toujours en phase de développement.L’objectif de notre travail est de valoriser les acquis de l’apprenant, dans une perspective de créer un nouvel environnement intelligent qui garantit une évaluation adaptative de l’apprenant selon son état cognitif, en mettant à profit des techniques d’intelligence artificielle, des théories en psychologie cognitive, les sciences de l’éducation, la pédagogie et la didactique

Etude de l'impact de différents algorithmes d'ordonnancement pour les femto-cellules pour des trafics temps réel dans le réseau 5G

Le déploiement des femto-cellules dans les systèmes de cinquième génération (5G), s’avère nécessaire grâce à leurs avantages en termes du nombre d'utilisateurs supporté, et de la réduction de la consommation d'énergie, permettant ainsi de répondre aux exigences des réseaux 5G. Or que l’allocation des ressources et la gestion du traffic, tout en maintenant la qualité de service (QoS) ; constituent un défi majeur en terme d’équité et de débit perçu au niveau du terminal.    Dans ce papier, un certain nombre d'algorithmes d'ordonnancement prévus d’être utilisés en 5G, à savoir l’algorithme Proportional Fair (PF), l’algorithme Exponential Proportional Fair (EXP/PF) et l’algorithme Maximum Largest Weighted Delay First (MLWDF) sont étudiés et comparés en matière d’équité (Fairness Index), de débit utile (Goodput) et d’efficacité spectrale, au niveau des femto-cellules en sens descendant

Measuring the Knowledge and Attitudes of Healthcare Professionals Towards Telemedicine: A Step Towards Improving Medical Training

Telemedicine leverages information and communication technologies for remote healthcare delivery, enhancing access to medical services, improving consultation efficiency, and coordinating care. In Morocco, its integration aims to optimise access to healthcare, especially in remote areas. To maximise the benefits, it is essential to train health professionals in telemedicine, which requires an assessment of their current knowledge and attitudes. This study aims to assess these aspects. This cross-sectional study engaged medical staff from the Faculty of Medicine, Pharmacy, and Dentistry and Hassan II University Hospital in Fez. Data were collected online using a standardized questionnaire covering socio-demographic and professional information, knowledge, experience, and satisfaction with telemedicine. Data analysis was conducted using SPSS V25, adhering to ethical standards of participant anonymity and data protection. Among 145 participants (mean age 24.99 years, 69.7% female), 95.8% were Moroccan, predominantly medical students (76.6%). While 81.7% were familiar with telemedicine concepts, 96.5% were unaware of public telemedicine programs in Morocco. Notably, 94.6% had never experienced a telemedicine consultation, though 46.8% supported its use for non-urgent cases. Most participants relied on the internet for information, with 90.9% unaware of existing regulations. Furthermore, 61% advocated for incorporating telemedicine into medical curricula, emphasizing its significance for future practice. Enhancing telemedicine knowledge and integration in Morocco\u27s healthcare system is vital. Systematic training in medical education will prepare future professionals, improve healthcare access, and underscore the strategic importance of telemedicine in evolving healthcare practices