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AbstractPurpose -Aims to investigate medical rapid prototyping (medical RP) technology applications and methods based on reverse engineering (RE) and medical imaging data. Design/methodology/approach -Medical image processing and RE are applied to construct three-dimensional models of anatomical structures, from which custom-made (personalized) medical applications are developed. Findings -The investigated methods were successfully used for design and manufacturing of biomodels, surgical aid tools, implants, medical devices and surgical training models. More than 40 medical RP applications were implemented in Europe and Asia since 1999. Research limitations/implications -Medical RP is a multi-discipline area. It involves in many human resources and requires high skills and knowhow in both engineering and medicine. In addition, medical RP applications are expensive, especially for low-income countries. These practically limit its benefits and applications in hospitals. Practical implications -In order to transfer medical RP into hospitals successfully, a good link and close collaboration between medical and engineering sites should be established. Moreover, new medical applications should be developed in the way that does not change the traditional approaches that medical doctors (MD) were trained, but provides solutions to improve the diagnosis and treatment quality. Originality/value -The presented state-of-the-art medical RP is applied for diagnosis and treatment in the following medical areas: craniomaxillofacial and dental surgery, neurosurgery, orthopedics, orthosis and tissue engineering. The paper is useful for MD (radiologists and surgeons), biomedical and RP/CAD/CAM engineers.
The power output of photovoltaic modules operating under certain field conditions decreases over the time. The photovoltaic module degradation factor depends not only by the physical properties of the material but also by the change of parameters of the environment where the P V panels operate. The change of the P V modules degradation factor over the time reflects on the power output which is in a close relation with revenues from the purchased electricity produced by the modules.The process of PV modules degradation is a normal process accompanying the operation of the panels. This process is a result of increased losses in linear connections; increased relative humidity of the ambient air, and the process of moisture evaporation; limitation of possibilities of the p-n junction; and destruction of protective coating. The first abovementioned of losses generally depends on the local atmospheric conditions where the panels operate. At higher local values of the average temperature and relative humidity of the air the rate of degradation increases. An analysis about the degradation rate of the P V modules operating under specific field conditions here is made.
4The naturally occurring wildfires and the peoplerelated forest fires are events, which in many cases have significant impact on the environment, the wildlife and the human population. The most devastating among these events usually start in unpopulated remote areas, which are difficult to inspect or are not constantly being monitored or observed. This gives the local small-sized fires enough time to evolve into fullscale wide-area disasters, which in turn makes their suppression and extinguishing very difficult.In this paper, we present an autonomous system for early detection of forest fires, named THEASIS-M. The presented system represents a solution that is based on a combination of innovative technologies, including computer vision algorithms, artificial intelligence and unmanned aerial vehicles.In the first part of the study, we provide an overview on the present applications of the UAVs in the forestry domain. The paper then introduces the general architecture of the THEASIS-M system and its components. The system itself is fully autonomous and is based on several different types of UAVs, including a fixedwing drone, which provides the overall forest monitoring capabilities of the proposed solution, and a rotary-wing UAV that is used for confirmation and monitoring of the detected fire event. The widely used technologies for computer vision and image processing, which are used for the detection of fire and smoke in the realtime video streams sent from the UAVs to the ground control station, are highlighted in the next section of this study. Finally, the experimental tests and demonstrations of the proposed THEASIS-M system are presented and briefly discussed.Index Terms4Unmanned aerial vehicles, computer vision, artificial intelligence, early detection of forest fires, autonomous system for fire detections
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