Agent-based modeling and simulation for the design of the future european Air Traffic Management system: the experience of CASSIOPEIA

The SESAR (Single European Sky ATM Research) program is an ambitious re-search and development initiative to design the future European air traffic man-agement (ATM) system. The study of the behavior of ATM systems using agent-based modeling and simulation tools can help the development of new methods to improve their performance. This paper presents an overview of existing agent-based approaches in air transportation (paying special attention to the challenges that exist for the design of future ATM systems) and, subsequently, describes a new agent-based approach that we proposed in the CASSIOPEIA project, which was developed according to the goals of the SESAR program. In our approach, we use agent models for different ATM stakeholders, and, in contrast to previous work, our solution models new collaborative decision processes for flow traffic management, it uses an intermediate level of abstraction (useful for simulations at larger scales), and was designed to be a practical tool (open and reusable) for the development of different ATM studies. It was successfully applied in three stud-ies related to the design of future ATM systems in Europe

Impacts de restrictions en eau d'irrigation sur les exploitations et les filières agricoles en Beauce

Beaucoup d’agriculteurs, comme les opérateurs des filières aval qui collectent ou transforment leur production, dépendent de l'irrigation. Or, dans de nombreuses régions du monde, structurellement ou conjoncturellement, les ressources en eau disponibles déclinent et sont soumises à des contingentements de plus en plus sévères. Cette étude vise à analyser les conséquences de scénarios de fortes baisses de la disponibilité en eau sur les stratégies des agriculteurs en termes de choix d’assolement et de mode de conduite et d’irrigation des cultures ainsi que l’effet de ces stratégies sur l’organisation de filières locales. Elle a été mise en oeuvre en France, dans la plaine de la Beauce, où une forte proportion de l'agriculture est irriguée à partir d'une ressource souterraine soumise à un dispositif de gestion volumétrique. L’évaluation des impacts de restrictions d’eau s’appuie sur une analyse économique des filières locales ainsi que sur des ateliers participatifs regroupant des agriculteurs et des opérateurs des unités aval. Les résultats montrent les effets de restrictions d’eau sur les choix d’assolement des agriculteurs, les volumes de production à l’échelle du territoire, les marges brutes des exploitations et les valeurs ajoutées des filières. / Many farmers, and the large set of downstream operators who depend on their farm products, have become depend-ent on irrigation. But, in many parts of the world, water resources are declining for structural or temporary reasons. Farmers have to reduce water consumption by growing crops with lower water requirement and apply optimal irri-gation strategies. The strategies they choose can have major consequences for downstream operators and local agro-industries. This paper analyzes the impacts and consequences of high water restrictions scenarios for farmers and the subsectors depending on their production. This approach was imple-mented in France, in the region of Beauce, where irrigation relies on groundwater use and on a volumetric management of the local aquifer. Scenarios based on two different levels of water availability reduction were assessed and strategies to face reduced water availability were analyzed for both farmers and downstream operators. The analysis was based on a technical diagnosis of the local organization, an eco-nomic analysis of value added, and participatory workshops including farmers, downstream operators and state repre-sentatives. Our analyses showed how farmers would adapt to water restriction and, depending on their choice of pro-duction, how their strategies could impact the volume of production at sub-regional level, the value added at subsec-tor level and could lead to competition between down-stream operators

Systems and technologies for objective evaluation of technical skills in laparoscopic surgery

Minimally invasive surgery is a highly demanding surgical approach regarding technical requirements for the surgeon, who must be trained in order to perform a safe surgical intervention. Traditional surgical education in minimally invasive surgery is commonly based on subjective criteria to quantify and evaluate surgical abilities, which could be potentially unsafe for the patient. Authors, surgeons and associations are increasingly demanding the development of more objective assessment tools that can accredit surgeons as technically competent. This paper describes the state of the art in objective assessment methods of surgical skills. It gives an overview on assessment systems based on structured checklists and rating scales, surgical simulators, and instrument motion analysis. As a future work, an objective and automatic assessment method of surgical skills should be standardized as a means towards proficiency-based curricula for training in laparoscopic surgery and its certification

Prediction of intraoperative complexity from preoperative patient data for laparoscopic cholecystectomy.

Different reasons may cause difficult intraoperative surgical situations. This study aims to predict intraoperative complexity by classifying and evaluating preoperative patient data. The basic prediction problem addressed in this paper involves the classification of preoperative data into two classes: easy (Class 0) and complex (Class 1) surgeries.preoperative patient data were collected from 337 patients admitted to the Klinikum rechts der Isar hospital in Munich, Germany for laparoscopic cholecystectomy (LAPCHOL) in the period of 2005-2008. The data include the patient's body mass index (BMI), sex, inflammation, wall thickening, age and history of previous surgery, as well as the name and level of experience of the operating surgeon. The operating surgeon was asked to label the intraoperative complexity after the surgery: '0' if the surgery was easy and '1' if it was complex. For the classification task a set of classifiers was evaluated, including linear discriminant classifier (LDC), quadratic discriminant classifier (QDC), Parzen and support vector machine (SVM). Moreover, feature-selection was applied to derive the optimal preoperative patient parameters for predicting intraoperative complexity.Classification results indicate a preference for the LDC in terms of classification error, although the SVM classifier is preferred in terms of results concerning the area under the curve. The trained LDC or SVM classifier can therefore be used in preoperative settings to predict complexity from preoperative patient data with classification error rates below 17%. Moreover, feature-selection results identify bias in the process of labelling surgical complexity, although this bias is irrelevant for patients with inflammation, wall thickening, male sex and high BMI. These patients tend to be at high risk for complex LAPCHOL surgeries, regardless of labelling bias.Intraoperative complexity can be predicted before surgery according to preoperative data with accuracy up to 83% using an LDC or SVM classifier. The set of features that are relevant for predicting complexity includes inflammation, wall thickening, sex and BMI score

Recognizing surgical patterns

In the Netherlands, each year over 1700 patients die from preventable surgical errors. Numerous initiatives to improve surgical practice have had some impact, but problems persist. Despite the introduction of checklists and protocols, patient safety in surgery remains a continuing challenge. This is complicated by some surgeons viewing their own work as an artistic manoeuver whose workflow cannot be captured. However, safeguarding patient safety is also a hospital's management responsibility and no longer only in the surgeon's hands. In spite of the inherent variations, surgeries of the same kind produce similar data, and are usually performed in similar workflows. Surgery is characterized by a peri-operative pipeline of pre-, intra- and post-operative processes. To both reduce errors and improve efficiency, the workflow in the peri-operative pipeline should be designed and planned as effectively as possible in terms of flow of patients and allocation of scarce resources such as operating rooms, instruments and personnel. Currently, planning is done on a very basic level, without using real-world data to learn and improve efficiency. Fortunately, there is lot of available, but unexploited data about surgical interventions that can be used for this purpose. The aim of this thesis is to use acquired and registered peri-operative data to support hospital management to improve safety and efficiency in surgery. The method of assessing safety and efficiency in surgery for individual patients needs to be tailored to each patient. As a result generalization of the results is difficult. We discuss how pattern recognition (PR) provides tools for the assessment of surgical outcome for individual patients. It also allows for handling of outliers and does not impose the same restrictions on data collection procedures as for randomized controlled trials. We show that PR is a pragmatic next step towards data intensive operating rooms with evidence based support for surgeries. Below the techniques as proposed in this thesis are brie y described. To support pre-operative planning of surgeries, assessment of surgical complexity is needed beforehand in order to prepare and possibly avoid complications and delays. This complexity assessment can also aid surgeons in decisions regarding how to proceed with the surgical procedure, for instance by taking extra precautions or making a referral to a more experienced surgeon when a complex surgery is predicted. We show how to use readily available patient data to predict surgical complexity. Classifiers are trained and evaluated using readily collected data from patients undergoing laparoscopic cholecystectomy (LAPCHOL). It is shown that complexity of LAPCHOL surgeries can be predicted in the pre-operative stage with accuracy up to 83% using an LDC or SVM classifier. We also derived the set of features that are relevant for predicting complexity including inflammation, wall thickening, sex and BMI score. To realize intra-operative safety and efficiency goals in surgery, hospitals are searching for autonomous systems for monitoring the surgical workflow in the operating room (OR). In this thesis we propose an autonomous registration technique for the OR. Registering the time of use of surgical instruments and the sequence in which they are used enables us to detect the surgical steps, including the duration of each step. By deploying this as a real-time system, dynamic support for the surgical team and dynamic planning of patients can be performed. For monitoring the usage of surgical instruments, signals from sensors which can detect video, motion and RFID tags can be used. For the application in the OR, it is necessary that these sensors are designed to meet the requirements of the OR environment, specifically with respect to sterilization and non-intrusiveness. We propose a tracking system to detect and track instruments in endoscopic video using biocompatible and sterilization-proof colour markers. The system tracks single and multiple instruments in the video. The output of the tracking tool is a log file with an identifier of the instrument used and the duration of its use for each entry. These instrument logs are then used for workflow mining and outlier detection in surgery. We derived a surgical consensus from multiple surgery logs using global multiple sequence alignment. We showed that the derived consensus conforms to the main steps of laparoscopic cholecystectomy as described in best practices. Using global pair-wise alignment, we showed that outliers from this consensus can be detected using the surgical log. These outliers are commonly simple variations in the execution of the surgical procedure, but can also represent serious complications or errors. To improve post-operative efficiency, accurate predictions of patients' length of stay (LOS) in the postanesthesia care unit (PACU) may lead to cost savings and a number of other efficiency benefits. We propose to use available perioperative data to predict the PACU LOS, using the features case demographics, intra-operative parameters, medications, patient co-morbidities, and surgeon. A linear regression method was used along with ordinary least square regression and `least absolute shrinkage and selection operator' (LASSO-) regression. A forward feature selection approach was then used to identify and rank factors that impact PACU LOS. We showed that PACU LOS can be predicted by perioperative factors with an improvement of 12-18 minutes compared to using the mean baseline. If this prediction is updated with online information, mainly by monitoring post-operative oxygen saturation, future work could lead to real-time LOS algorithms based on peri-operative factors to predict, manage and possibly intercept anticipated, prolonged PACU LOS. This thesis has proposed and demonstrated the application of pattern recognition tools to log, assess and predict surgical workflow parameters. Work in this thesis did not directly contribute to reduce errors and safety in the OR. However, the tools developed in the thesis can be used to support standardization of surgical workflow to both reduce errors and support surgical planning. Moreover, the proposed techniques for the operating room can be used in other medical domains such as the intensive care unit with only small contextual modifications.Bimechanical engineeringMechanical, Maritime and Materials Engineerin

Etude sur les conséquences de l'économie agricole régionale des contraintes en matière de gestion de l'eau : pistes de réflexion pour une priorisation des prélèvements

Le présent document constitue le rapport final de travaux bénéficiant d'une subvention du Ministère de l'Agriculture et de la Pêche sur le programme 215 sous action 22. Elle fait l'objet d'une convention qui lie le Cemagref et la DRAF du Centre et du Loiret sur l'année 2007 pour la réalisation de l'opération suivante : étude sur les conséquences de l'économie agricole régionale des contraintes en matière de gestion de l'eau : pistes de réflexion pour une priorisation des prélèvements

Evaluation des impacts de restrictions d’eau pour l’usage agricole Une démarche à l’échelle des filières de production

Beaucoup d’agriculteurs, comme les opérateurs des filières aval qui transforment leur production, dépendent aujourd’hui des ressources en eau souterraine. Or, dans de nombreuses régions du monde, en climat aride comme tempéré, les nappes souterraines sont surexploitées et les ressources disponibles déclinent. Les agriculteurs sont alors confrontés à une pression croissante pour préserver cette ressource. Cette situation les amène d’une part, à économiser l’eau en mettant l’accent sur des productions moins consommatrices, d’autre part, à mieux valoriser les quantités utilisées. Plusieurs stratégies sont envisageables comme modifier les choix d’assolement ou adapter les modes de conduite des cultures. Ces stratégies peuvent avoir des conséquences importantes sur l’organisation des filières aval. Cette communication propose les bases d’une démarche visant à analyser les conséquences de fortes restrictions d’eau sur l’organisation de filières locales. Elle a été mise en oeuvre en France, sur le cas de la nappe de Beauce, en partenariat avec la profession agricole, les opérateurs des unités de transformation et les représentants de l’Etat. Elle permet d’analyser les adaptations et les stratégies de chacun face à des baisses de volumes d’eau disponibles. Elle met en évidence les interactions entre les opérateurs d’une même filière et les interactions entre différentes filières. Many farmers, and the large set of downstream operators who depend on their farm products, have become dependent on groundwater resources. Although overexploitation of groundwater resources is far from being a universal phenomenon, it can be observed not only in arid areas but also in the areas with a temperate climate. In regions where groundwater resources are declining, farmers have to reduce water consumption by growing crops with lower water requirement, or apply optimal irrigation strategies. The strategies they choose can have major consequences for downstream operators and local agro- industries. This paper presents an approach to analyze the impacts on and consequences of high water restrictions for the subsectors. This approach was implemented in the region of Beauce, in France, in collaboration with farmers, downstream operators and state representatives. Adaptations and strategies to face reduced water availability were analyzed in economic and technical terms for both farmers and downstream operators. Participatory workshops brought together different downstream operators who could become competitors for the same resource and highlighted interactions between operators in the same subsector as well as interactions between different sectors