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Over the last decade, health information systems (HIS) have undergone significant changes, particularly in embracing flexible frameworks for ongoing development. This evolution underscores the necessity for information technology (IT) infrastructures that rapidly align with clinical processes. The paper investigates the transition of hospital information systems to comprehensive strategies, examining the benefits and challenges involved. It also examines the increasing demands on health data management systems (HDMS) for patient care and biomedical research. The focus is on how the integration of the Internet of Things (IoT) and open-source enterprise resource planning (ERP) systems, such as Odoo, impacts health information management. The study evaluates the effectiveness and implications of combining these technologies. It provides examples of these integrated systems in action, particularly in resource-limited settings, and evaluates their potential to improve care. The document provides a comprehensive review of the current status and evolution of HIS and HDMS, highlighting the importance of integrating IoT and other cutting-edge technologies in healthcare. This is a crucial aspect for developing countries, where these advancements can significantly improve healthcare outcomes. [ABSTRACT FROM AUTHOR]

This paper focuses on the study and the design of an air core magnetorquer model dedicated to the 1U CubeSat (10×10×10 cm3). The objective is to obtain a solution which is able to provide accurate attitude control while having the smallest possible dimensions, electrical power, and total mass. To this end, the first part will provide theoretical mathematical knowledge on the laws of the coil to design an electromagnetic air core actuator. Then, this paper presents comparisons of the performances obtained by varying the type of material and the shape of the coil. Towards the end, the effect of temperature variation in LEO orbit is taken into consideration to predict the generated magnetic moment.

In a three-dimensional environment, the navigation of a vehicle in airspace, terrestrial space, or maritime space presents complex aspects concerning the determination of its position, its orientation, and the stability of the processing of the asynchronous data coming from the various sensors during navigation. In this context, this paper presents an experimental analysis of the position accuracy estimated by a low-cost inertial measurement unit coupled, by the extended Kalman data fusion algorithm, with a system of absolute measurements of a positioning system received from a GPS which designates the global positioning system. The different scenarios of the experimental study carried out during this work concerned three tests in a real environment, such as the navigation in a course inside the city of Rabat/Morocco with a moderate speed, a section on the highway at a speed of 120 Km/h and a circular path around a roundabout. The experimental results proved that the low-cost sensors studied are a good candidate for civil navigation applications.

The objective of this paper is to investigate the ability of analytical wake models to estimate the wake effects between wind turbines (WTs). The interaction of multiple wakes reduces the total power output produced by a large offshore wind farm (LOFWF). This power loss is due to the effect of turbine spacing (WTS), if the WTs are too close, the power loss is very significant. Therefore, the optimization of turbine positions within the offshore wind farm requires an understanding of the interaction of wakes inside the wind farm. To better understand the wake effect, the Horns Rev 1 offshore wind farm has been studied with four wake models, Jensen, Larsen, Ishihara, and Frandsen. A comparative study of the wake models has been performed in several situations and configurations, single and multiple wakes are taken into consideration. Results from the Horns Rev1 offshore wind farm case have been evaluated and compared to observational data, and also with the previous studies. The power output of a row of WTs is sensitive to the wind direction. For example, if a row of ten turbines is aligned with the 270° wind direction, the full wake condition of WTs is reached and the power deficit limit predicted by Jensen model exceeds 70%. When a wind direction changes only of 10° (260° and 280°), the deficit limit reduces to 30%. The obtained results show that a significant power deficit occurs when the turbines are arranged in an aligned manner. The findings also showed that all four models gave acceptable predictions of the total power output. The comparison between the calculated and reported power output of Horns Revs 1 showed that the differences ranged from - 8.27 MW (12.49%) to 15.27 MW (23.06%) for the Larsen and Frandsen models, respectively. [ABSTRACT FROM AUTHOR]

This paper investigates the optimal layout of wind turbines (WTs) within a wind farm. Finding the best placement of WTs in a wind farm is a challenging process due to the existence of multiple wake effects. A biogeography based optimization (BBO) algorithm method is proposed to search for the optimal location of WTs in a wind farm (WF), to maximize the power produced by the WF and improve the annual economic performance of the WF. A wind turbine (WT) that operates in the wake of one or more other turbines is subject to lower flow and therefore produces less power. When designing a wind project, the arrangement of the turbines with each other in a wind farm is a very important factor. The best layout of a wind farm is to achieve the optimal placement of the turbines in relation to each other in a given area to maximize the efficiency of the whole wind farm and reduce its cost. A dense configuration would result in considerable power losses. Each turbine must have a sufficient distance from other turbines in the WF where the optimal number of turbines should be placed. The BBO approach is conducted on a 2 km x 2 km wind farm assuming a constant wind speed of 12 m/s with a fixed wind direction, for solving the wind farm layout optimization problem in two different configurations which include 26 and 30 WTs respectively. A comparison of the results obtained with the previous studies shows that the BBO is more efficient in terms of maximizing power output and economic profitability of the same wind farm model, which validates that BBO performs effectively in optimizing WTs placement within WF. BOO provides the greatest improvement in the optimal layout, for example, in the case of the layout for 30 WTs. The power output reaches 15,383 KW, the agreement between the ideal and the optimal layout is more favorable. The difference in output power is only 169 KW (1%). Knowing that the ideal layout is reached if all WTs receive a wind flow with a maximum wind speed of 12 m/s. Furthermore, a case study of wind turbine layout optimization using the BBO program on the Alta X wind farm has been performed under variable wind speed and variable wind direction. The results indicate that the optimized layout of the Alta X wind farm achieves a 12% increase in the power output for a similar cost when compared to the original layout of Alta X. It is also more appropriate for evaluating the wind farm layout in the Wind Power Project (WPP). [ABSTRACT FROM AUTHOR]