Chapter Diachronic evolution of the coastline of Bordj El Kiffane (Algiers, Algeria) in absence and presence of coastal protection structures

The coastal area of Bordj El Kiffane has experienced an artificialisation of its shoreline since 1980. This caused a remarkable decline of the shoreline. To remedy this, the solution recommended was the combination of several protection methods. In order to determine the consequence of the protective structures, a study of the historical evolution of the coastline was performed with ArcGIS and DSAS. The results allowed determining its evolutionary rates and comparing the evolutions on different periods in absence and presence of the protection structures

Contribution à la conception d'un système d'aide à la décision pour la gestion de situations de tension au sein des systèmes hospitaliers. Application à un service d'urgence.

The management of patient flow, especially the flow resulting from health (flu, heat waves and exceptional circumstances) is one of the most important problems to manage in the emergency department (ED). To handle the influx of patients, emergency departments require significant human and material resources, and a high degree of coordination between these resources. Under these conditions, the medical and the paramedical staffs are often confronted with strain situations which greatly complicate their task. The main purpose of this thesis is to contribute to improving the management of situations of tension occurring in the emergency department by providing a decision support system, SAGEST. This DSS allows i) a proactive control of the ED: predicting at short and/or medium-term the occurrence of potential strain situations and proposing corrective actions to prevent the occurrence of these situations, ii) a reactive control in the case of no-detection of the strain situation occurrence. A functional architecture of the SAGEST system, based on the manager’s decision making process is proposed. Used methodologies and models embedded in the main functions and the knowledge base of the SAGEST system are described. Finally, experiments and results of different models of SAGEST system applied to the paediatric emergency department (PED) of the Regional University Hospital of Lille are presented and discussed.La prise en charge des flux des patients, en particulier les flux récurrents et consécutifs à des crises sanitaires (grippes, canicules, situations exceptionnelles) est l'un des problèmes les plus importants auquel les services des urgences (SU) doivent faire face. Pour gérer cet afflux de patients, les services des urgences nécessitent des ressources humaines et matérielles importantes, ainsi qu'un degré élevé de coordination entre ces ressources. Dans ces conditions, le personnel médical se voit confronté très fréquemment à des situations de tension qui compliquent très fortement sa tâche. L‘objet de cette thèse est de contribuer à l’amélioration de la gestion des situations de tension se produisant dans un service d’urgence en proposant un système d’aide à la décision, SAGEST (Système d’Aide à la décision pour la GEstion des Situations de Tensions), permettant i) le pilotage proactif du SU : prévision à court et/ou moyen terme de l'apparition de situations de tension et l'évolution du flux patients et la proposition d'actions de correction afin d'éviter l’occurrence de ces situations et ii) le pilotage réactif dans le cas où l'occurrence de la situation de tension n'a pas été détectée. Une architecture fonctionnelle du système SAGEST, s'appuyant sur le processus décisionnel du responsable du service d'urgence, est proposée. Les méthodologies et les modèles utilisés dans la construction des principales fonctions et de la base de connaissances sont décrits. Enfin, les résultats d’application des différents modèles du système SAGEST pour le service d’urgence pédiatrique (SUP) du centre hospitalier régional universitaire du Lille sont présentés et discutés

Forecasting of Photovoltaic Solar Power Production Using LSTM Approach

Solar-based energy is becoming one of the most promising sources for producing power for residential, commercial, and industrial applications. Energy production based on solar photovoltaic (PV) systems has gained much attention from researchers and practitioners recently due to its desirable characteristics. However, the main difficulty in solar energy production is the volatility intermittent of photovoltaic system power generation, which is mainly due to weather conditions. For the large-scale solar farms, the power imbalance of the photovoltaic system may cause a significant loss in their economical profit. Accurate forecasting of the power output of PV systems in a short term is of great importance for daily/hourly efficient management of power grid production, delivery, and storage, as well as for decision-making on the energy market. The aim of this chapter is to provide reliable short-term forecasting of power generation of PV solar systems. Specifically, this chapter presents a long short-term memory (LSTM)-based deep learning approach for forecasting power generation of a PV system. This is motivated by the desirable features of LSTM to describe dependencies in time series data. The performance of the algorithm is evaluated using data from a 9 MWp grid-connected plant. Results show promising power forecasting results of LSTM

Pattern recognition and diagnosis of short and open circuit faults inverter in induction motor drive using neural networks

Nowadays, feeding induction motors with voltage source inverters under faulty conditions is a major challenge. For this reason, electrical systems must be well thought out to provide good diagnostics for these elements. Consequently, the early detection of faults is very important to establish strategies that allow us to control the operation and take preventive measures to avoid frequent failures. Our aim in this paper is to train multilayer neural networks using features extracted from currents and voltages measurements to detect and classify open and short-circuit switch faults in source voltage inverters. Simulation results show that instead of using several types of features extracted from measurements of several signal cycles as in previous works, a two-component feature obtained from one cycle is sufficient to obtain an excellent accuracy. The normalized mean Clark currents and the power spectrum using the fast Fourier transform have been used as features for open switches and short-circuit faults respectively

Peaks Over Threshold–based detector design for structural health monitoring: Application to aerospace structures

Structural health monitoring offers new approaches to interrogate the integrity of complex structures. The structural health monitoring process classically relies on four sequential steps: damage detection, localization, classification, and quantification. The most critical step of such process is the damage detection step since it is the first one and because performances of the following steps depend on it. A common method to design such a detector consists of relying on a statistical characterization of the damage indexes available in the healthy behavior of the structure. On the basis of this information, a decision threshold can then be computed in order to achieve a desired probability of false alarm. To determine the decision threshold corresponding to such desired probability of false alarm, the approach considered here is based on a model of the tail of the damage indexes distribution built using the Peaks Over Threshold method extracted from the extreme value theory. This approach of tail distribution estimation is interesting since it is not necessary to know the whole distribution of the damage indexes to develop a detector, but only its tail. This methodology is applied here in the context of a composite aircraft nacelle (where desired probability of false alarm is typically between 1024 and 1029) for different configurations of learning sample size and probability of false alarm and is compared to a more classical one which consists of modeling the entire damage indexes distribution by means of Parzen windows. Results show that given a set of data in the healthy state, the effective probability of false alarm obtained using the Peaks Over Threshold method is closer to the desired probability of false alarm than the one obtained using the Parzen-window method, which appears to be more conservative

Ozone measurements monitoring using data-based approach

The complexity of ozone (O 3 ) formation mechanisms in the troposphere makes the fast and accurate modeling of ozone very challenging. In the absence of a process model, principal component analysis (PCA) has been extensively used as a data-based monitoring technique for highly correlated process variables; however, conventional PCA-based detection indices often fail to detect small or moderate anomalies. In this work, we propose an innovative method for detecting small anomalies in highly correlated multivariate data. The developed method combines the multivariate exponentially weighted moving average (MEWMA) monitoring scheme with PCA modeling in order to enhance anomaly detection performance. Such a choice is mainly motivated by the greater ability of the MEWMA monitoring scheme to detect small changes in the process mean. The proposed PCA-based MEWMA monitoring scheme is successfully applied to ozone measurements data collected from Upper Normandy region, France, via the network of air quality monitoring stations. The detection results of the proposed method are compared to that declared by Air Normand air monitoring association

Décompression chirurgicale du syndrome de défilé thoraco-brachial

Le syndrome de défilé thoraco-brachial est une pathologie souvent méconnue à cause de diagnostic difficile par manque des signes pathognomoniques conduisant souvent à des errances. Les manifestations cliniques dépendent selon qu’il s’agit d’une compression nerveuse, vasculaire ou vasculo-nerveuse. Le but de cette étude est de décrire certains aspects cliniques particuliers et évaluer le résultat fonctionnel après la décompression chirurgicale du paquet vasculo-nerveux. Notre étude rétrospective a porté sur l’analyse des données cliniques, radiologiques, IRM et EMG sur les patients opérés entre janvier 2010 et juillet 2013 du syndrome de défilé thoraco-brachial dans le service de traumatologie orthopédie de l’hôpital Ibn Sina de Rabat. 15 cas ont été colligés : 12 cas post traumatiques (fracture de la clavicule) et 3 cas d’origines congénitales, dont l’âge moyen était 35 ans (20 à 50 ans ) avec 9 femmes et 6 hommes. A la fin du traitement, le score de Dash est passé de 109 (46% Normal=0) à 70 (20%), et le stress test de Roos était de 70/100 à 80/100. Le résultat était excellent dans 12 cas soit (80%) et moins bon dans dans 3 cas (20%). En définitive, la résection de malformations osseuses, l’excision des brides et la neurolyse du plexus brachial suivie de la rééducation a donné une bonne évolution fonctionnelle

Calibration & Temperature Controlled Setup for Air Quality Sensors

Indoor air pollution is a major issue affecting public health. Due to hot climate, humidity and lack of natural green spaces, life is mostly confined indoors in many countries of the MENA region. Vulnerable population, including young children and senior citizens who spend most of their time indoors, are at risk because of the effects of indoor air quality (IAQ) on their health. An indoor air quality monitoring system is a need of the hour to detect and improve Indoor Air Quality (IAQ). The monitoring systems presently available are bulky, expensive and need periodic calibration to maintain high degree of accuracy. Frequent recalibration of a number of densely deployed individual sensors in the network is a time-consuming and laborious task therefore self-calibration is indispensable. Gas sensors, even if factory-calibrated, tend to drift with time/usage. Therefore these should be regularly calibrated under controlled environments. Calibration may be carried out using test gas mixtures with known composition. Pre-mixed gas cylinders with known composition may be used for the purpose; however this solution is not flexible as the number of calibration points and testing conditions (e.g. effect of temperature and humidity on CO2 sensor) are limited. In the current project, a computer-controlled test and calibration test bed system is being designed and assembled along with temperature controller. Calibration set-up would help in self calibration of the air quality sensors. Calibration curves obtained from proposed calibration test bed are updated automatically and fed into the sensor node through wireless communication without going in the field or replacing the sensor. A computer-controlled test and calibration test bed system is designed and assembled containing the sensor(s) under test and in which gas composition; temperature can be precisely and dynamically controlled. ATMEGA328 micro controller is used to receive the temperature set point from the computer running the test rig.qscienc

Determining the Outdoor Air Ventilation with Carbon Dioxide (CO2) as a Tracer Gas

Insufficient ventilation can lead to occupant complaints of discomfort and reduced productivity as human and building generated pollutants build up. Some combinations of these elevated pollutants may have short or long-term detrimental health effects. Carbon Dioxide (CO2) is very rarely a pollutant of direct health concern itself. Rather a tracer gas, because building occupants exhale CO2 and is used as a tracer gas that is an excellent indicator of adequate (or inadequate) ventilation. Keeping in view this fact we measured CO2 as a marker, or tracer gas, to determine the outdoor air ventilation (dilution air) rate in an occupied space. Low CO2 concentration, when measured during periods of average and higher occupancy, implies that human generated pollutants are being properly diluted. And in the absence of a specific pollutant source, it is a rough estimator that the thousands of potential building generated pollutants are being dispersed. This makes it a key indoor air quality indicator.qscienc

Hydrothermal Synthesis and Characterisation of Bioactive Glass-Ceramic Nanorods

In this study fabrication of rod-like bioactive glass-ceramics (BGCs) using hydrothermal treatment based on a sol-gel precursor is reported for the first time. BGCs with composition 58 wt% SiO2, 33 wt% CaO and 9 wt% P2O5 were synthesized in different thermal conditions (200 and 220 °C) and characterised with regard to morphology, chemical composition and crystallinity. The bioactivity of the materials was assessed by immersion in simulated body fluid for up to 7 days. The results revealed that as the reaction temperature increased from 200 to 220 °C, the diameter of rods was reduced from microscale to nanoscale and the crystallinity was enhanced. It was also found that the BGC nanorods have higher surface area and consequently enhanced bioactivity than BGC microrods. This technique provides a facile method for rapid production of BGC nanorods at relatively low temperature which may have the potential to be used as bioactive composite reinforcement or for bone grafting applications