In the present work, we investigate the inverse problem of reconstructing the parameter of an integro-differential parabolic equation, which comes from pollution problems in porous media, when the final observation is...In the present work, we investigate the inverse problem of reconstructing the parameter of an integro-differential parabolic equation, which comes from pollution problems in porous media, when the final observation is given. We use the optimal control framework to establish both the existence and necessary condition of the minimizer for the cost func- tional. Furthermore, we prove the stability and the local uniqueness of the minimizer. Some numerical results will be presented and discussed.展开更多
We present two recent methods,called UTAGMS and GRIP,from the viewpoint of robust ranking of multi-criteria alternatives.In these methods,the preference information provided by a single or multiple Decision Makers(DMs...We present two recent methods,called UTAGMS and GRIP,from the viewpoint of robust ranking of multi-criteria alternatives.In these methods,the preference information provided by a single or multiple Decision Makers(DMs)is composed of holistic judgements of some selected alternatives,called reference alternatives.The judgements express pairwise comparisons of some reference alternatives(in UTAGMS),and comparisons of selected pairs of reference alternatives from the viewpoint of intensity of preference(in GRIP).Ordinal regression is used to find additive value functions compatible with this preference information.The whole set of compatible value functions is then used in Linear Programming(LP)to calculate a necessary and possible weak preference relations in the set of all alternatives,and in the set of all pairs of alternatives.While the necessary relation is true for all compatible value functions,the possible relation is true for at least one compatible value function.The necessary relation is a partial preorder and the possible relation is a complete and negatively transitive relation.The necessary relations show consequences of the given preference information which are robust because "always true".We illustrate this methodology with an example.展开更多
We present the AS-Index, a new index structure for exact string search in disk resident databases. AS-Index relies on a classical inverted file structure, whose main innovation is a probabilistic search based on the p...We present the AS-Index, a new index structure for exact string search in disk resident databases. AS-Index relies on a classical inverted file structure, whose main innovation is a probabilistic search based on the properties of algebraic signatures used for both n-grams hashing and pattern search. Specifically, the properties of our signatures allow to carry out a search by inspecting only two of the posting lists. The algorithm thus enjoys the unique feature of requiring a constant number of disk accesses, independently from both the pattern size and the database size. We conduct extensive experiments on large datasets to evaluate our index behavior. They confirm that it steadily provides a search performance proportional to the two disk accesses necessary to obtain the posting lists. This makes our structure a choice of interest for the class of applications that require very fast lookups in large textual databases. We describe the index structure, our use of algebraic signatures, and the search algorithm. We discuss the operational trade-offs based on the parameters that affect the behavior of our structure, and present the theoretical and experimental performance analysis. We next compare the AS-Index with the state-of-the-art alternatives and show that 1） its construction time matches that of its competitors, due to the similarity of structures, 2） as for search time, it constantly outperforms the standard approach, thanks to the economical access to data complemented by signature calculations, which is at the core of our search method.展开更多
Plants diseases have a detrimental effect on the quality but also on the quantity of agricultural production.However,the prediction of these diseases is proving the effect on crop quality and on reducing the risk of p...Plants diseases have a detrimental effect on the quality but also on the quantity of agricultural production.However,the prediction of these diseases is proving the effect on crop quality and on reducing the risk of production losses.Indeed,the detection of plant diseases-either with a naked eye or using traditional methods-is largely a cumbersome process in terms of time,availability and results with a high-risk error.The present work introduces a depth study of various CNN architectures with different optimization algorithms carried out for olive disease detection using classification techniques that recommend the best model for constructing an effective disease detector.This study presents a dataset of 5571 olive leaf images collected manually on real conditions from different regions of Morocco,that also includes healthy class to detect olive diseases.Further,one of the goals of this research was to study the correlation effects between CNN architectures and optimization algorithms evaluated by the accuracy and other performance metrics.The highest rate in trained models was 100%,while the highest rate in experiments without data augmentation was 92,59%.Another subject of this study is the influence of the optimization algorithms on neuronal network performance.As a result of the experiments carried out,the MobileNet architecture using Rmsprop algorithms outperformed the others combinations in terms of performance and efficiency of disease detector.展开更多
基金supported in part by the CNRST Morocco,the Volkswagen Foundation:Grant number I/79315Hydromed project
文摘In the present work, we investigate the inverse problem of reconstructing the parameter of an integro-differential parabolic equation, which comes from pollution problems in porous media, when the final observation is given. We use the optimal control framework to establish both the existence and necessary condition of the minimizer for the cost func- tional. Furthermore, we prove the stability and the local uniqueness of the minimizer. Some numerical results will be presented and discussed.
文摘We present two recent methods,called UTAGMS and GRIP,from the viewpoint of robust ranking of multi-criteria alternatives.In these methods,the preference information provided by a single or multiple Decision Makers(DMs)is composed of holistic judgements of some selected alternatives,called reference alternatives.The judgements express pairwise comparisons of some reference alternatives(in UTAGMS),and comparisons of selected pairs of reference alternatives from the viewpoint of intensity of preference(in GRIP).Ordinal regression is used to find additive value functions compatible with this preference information.The whole set of compatible value functions is then used in Linear Programming(LP)to calculate a necessary and possible weak preference relations in the set of all alternatives,and in the set of all pairs of alternatives.While the necessary relation is true for all compatible value functions,the possible relation is true for at least one compatible value function.The necessary relation is a partial preorder and the possible relation is a complete and negatively transitive relation.The necessary relations show consequences of the given preference information which are robust because "always true".We illustrate this methodology with an example.
文摘We present the AS-Index, a new index structure for exact string search in disk resident databases. AS-Index relies on a classical inverted file structure, whose main innovation is a probabilistic search based on the properties of algebraic signatures used for both n-grams hashing and pattern search. Specifically, the properties of our signatures allow to carry out a search by inspecting only two of the posting lists. The algorithm thus enjoys the unique feature of requiring a constant number of disk accesses, independently from both the pattern size and the database size. We conduct extensive experiments on large datasets to evaluate our index behavior. They confirm that it steadily provides a search performance proportional to the two disk accesses necessary to obtain the posting lists. This makes our structure a choice of interest for the class of applications that require very fast lookups in large textual databases. We describe the index structure, our use of algebraic signatures, and the search algorithm. We discuss the operational trade-offs based on the parameters that affect the behavior of our structure, and present the theoretical and experimental performance analysis. We next compare the AS-Index with the state-of-the-art alternatives and show that 1） its construction time matches that of its competitors, due to the similarity of structures, 2） as for search time, it constantly outperforms the standard approach, thanks to the economical access to data complemented by signature calculations, which is at the core of our search method.
文摘Plants diseases have a detrimental effect on the quality but also on the quantity of agricultural production.However,the prediction of these diseases is proving the effect on crop quality and on reducing the risk of production losses.Indeed,the detection of plant diseases-either with a naked eye or using traditional methods-is largely a cumbersome process in terms of time,availability and results with a high-risk error.The present work introduces a depth study of various CNN architectures with different optimization algorithms carried out for olive disease detection using classification techniques that recommend the best model for constructing an effective disease detector.This study presents a dataset of 5571 olive leaf images collected manually on real conditions from different regions of Morocco,that also includes healthy class to detect olive diseases.Further,one of the goals of this research was to study the correlation effects between CNN architectures and optimization algorithms evaluated by the accuracy and other performance metrics.The highest rate in trained models was 100%,while the highest rate in experiments without data augmentation was 92,59%.Another subject of this study is the influence of the optimization algorithms on neuronal network performance.As a result of the experiments carried out,the MobileNet architecture using Rmsprop algorithms outperformed the others combinations in terms of performance and efficiency of disease detector.
