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Automation of logistics enhances efficiency, reduces costs, and minimizes human error. Image processing—particularly vision-based AI—enables real-time tracking, object recognition, and intelligent decision-making, thereby improving supply chain resilience. This study addresses the challenge of deploying deep learning-based object detection on resource-constrained embedded platforms, such as NVIDIA Jetson devices on UAVs and ground robots, for real-time logistics applications. Specifically, we provide a comprehensive comparative analysis of YOLOv5 and YOLOv8, evaluating their performance in terms of inference speed, accuracy, and dataset-specific metrics using both the Common Objects in Context (COCO) dataset and a novel, custom logistics dataset tailored for aerial and ground-based logistics scenarios. A key contribution is the development of a user-friendly graphical user interface (GUI) for selective object visualization, enabling dynamic interaction and real-time filtering of detection results—significantly enhancing practical usability. Furthermore, we investigate and compare deployment strategies in both Python 3.9 and C# (ML. NET v3 and .NET Framework 7) environments, highlighting their respective impacts on performance and scalability. This research offers valuable insights and practical guidelines for optimizing real-time object detection deployment on embedded platforms in UAV- and ground robot-based logistics, with a focus on efficient resource utilization and enhanced operational effectiveness.

In this paper, we aimed to identify the dynamics of a crude distillation unit (CDU) using closed-loop data with NARX−NN and the Koopman operator in both linear (KL) and bilinear (KB) forms. A comparative analysis was conducted to assess the performance of each method under different experimental conditions, such as the gain, a delay and time constant mismatch, tight constraints, nonlinearities, and poor tuning. Although NARX−NN showed good training performance with the lowest Mean Squared Error (MSE), the KB demonstrated better generalization and robustness, outperforming the other methods. The KL observed a significant decline in performance in the presence of nonlinearities in inputs, yet it remained competitive with the KB under other circumstances. The use of the bilinear form proved to be crucial, as it offered a more accurate representation of CDU dynamics, resulting in enhanced performance.

Some chemical reactors exhibit coupled dynamics with multiple equilibrium points and strong nonlinearities. The accurate modeling of these dynamics is crucial to optimal control and increasing the reactor’s economic performance. While neural networks can effectively handle complex nonlinearities, they sacrifice interpretability. Alternatively, block-oriented Hammerstein–Wiener models and Koopman operator-based linear predictors combine nonlinear representation with linear dynamics, offering a gray-box identification approach. This paper comprehensively reviews recent advancements in both the Hammerstein–Wiener and Koopman operator methods and benchmarks their accuracy against neural network-based approaches to modeling a large-scale industrial Fluid Catalytic Cracking fractionator. Furthermore, Monte Carlo simulations are employed to validate performance under varying signal-to-noise ratios. The results demonstrate that the Koopman bilinear model significantly outperforms the other methods in terms of accuracy and robustness.

La problématique de cette présente étude s'articule autour de l'intégration des procédés servant à l'évaluation et la gestion des coûts produits par les établissements hospitaliers publics dans le projet de contractualisation entre les bailleurs de fonds ; les prestataires et les consommateurs de service. Le mode d'organisation de l'institution publique hospitalière Algérienne est-il en mesure d'adopter les outils et méthodes de gestion modernes propres au management hospitalier. Pour concrétiser le projet de la contractualisation avec les différents partenaires du système de santé ; Il s'agit à travers cette étude de présenter un modèle d'évaluation du coût de prise en charge en milieu chirurgical, en procédant avec la méthode des sections homogènes et quelques indicateurs de mesure comptable utilisés dans la méthode Activity Based Costing (A.B.C).

Cette étude propose une méthode d'évaluation du Coût unitaire des épisodes de soins produits au niveau de l'unité des Urgences Médico-chirurgicales d'un hôpital public. L'étude a été réalisée en 2021sur un échantillon de 785 passages opérés au niveau des urgences. Le constat qui a été établi concernant le mode de calcul que nous avons adopté détermine, que la charge de travail quantifiée en fonction de l'inducteur « horaire »peut être utilisée comme méthode de calcul plus ou moins rationnelle pour estimer le coût de revient de prise en charge des patients.

A travers cette étude nous tenterons de proposer une procédure de calcul du cout de séjour hospitalier dans un hôpital public en se basant sur un procédé qui consiste à annexer deux de calcul relevant de la comptabilité analytique (la méthode traditionnelle des sections homogènes et la méthode A.B.C. de calcul des coûts basée sur l'usage des inducteurs d'activités. La comptabilité analytique, jusqu'ici ignorée ne s'applique que difficilement, dans une institution telle l'hôpital ; étant donné la particularité des produits de soins. Dans le secteur public, la gestion financière des organisations obéit à des règles qui respectent simplement les dépenses d'un budget.

A partir du début des années 2000, la priorité de l'Etat était axée sur l'amélioration des services publics, la promotion du bien-être collectif ainsi que le développement des infrastructures économiques et sociales notamment ; par la mise en oeuvre d'une stratégie d'impulsion budgétaire à la croissance économique, profitant de l'augmentation des recettes fiscales provenant des hydrocarbures. L'amélioration des indicateurs économiques et sociaux fut la principale quête inscrite dans les programmes de l'Etat. Le présent article se préoccupe de mesurer l'impact des dépenses publiques sur le bien-être social propre à l'Algérie.

Considerable attention has been given to the study of the propagation of surface waves in order to improve the efficiency and lifetime of the surface acoustic wave devices such as transducers. In this paper, an investigation of the Rayleigh waves in functionally graded piezoelectric material is presented. The Rayleigh surface wave propagation is assumed to take place in a transversely isotropic graded piezoelectric half-space with material properties varying continuously along the thickness direction. The obtained results have shown that dispersive Rayleigh waves can propagate on the surface of the FGPM half-space with characteristics that depend on the graded variation of the material parameters. Based on the dispersion relations, the phase velocity for both the electrically open and shorted cases at the free surface is deduced. The displacement magnitudes and the corresponding decay variations are plotted and discussed.

This paper presents an implementation of a robust control LQG-Kalman model applied to composite Kirchhoff plate dynamics. A reduced model of a finite element method and control procedure is considered in the modeling of a structure because of the important number of piezoelectric patches used in control. Replacing the full model with a short model reduces the computational and time costs, especially when the number of degrees of freedom is significant. In robust control, the measurement of all states is not necessary and the observability and estimability criteria can be exploited, while conventional LQR control assumes that the data accessibility of all states is available. For this reason, robust control is proposed to control the random external disturbances and is compared to LQR control to illustrate its practicability and efficiency. The sensors and actuators in the thermo-piezoelectric material are randomly distributed on both sides of the plate to establish the control procedure. A Monte Carlo simulation is used in the selection of the degrees of freedom of sensors presenting high electrical outputs. Numerical simulations are performed to demonstrate the effectiveness of the proposed control procedure in a reduced model and under mechanical and thermal disturbances in comparison with the LQR control.