The paper presents research on the accuracy of measuring illuminance and chromaticity of airport lamps. The impact of the type of DC and AC power supply on measurement was assessed with the use of electronic sensors. ...
The paper presents research on the accuracy of measuring illuminance and chromaticity of airport lamps. The impact of the type of DC and AC power supply on measurement was assessed with the use of electronic sensors. BH1750 and BH1745 type sensors in a microprocessor system with an I 2 C interface were used for the measurements. A professional luxmeter was used for comparison purposes. Experimental tests were carried out under laboratory conditions for three types of halogen lamps: approach system lamps, runway centerline lamps, and touchdown zone lamps.
In order to prevent system failures, fault detection and performance assessment are always essential factors. This article investigates the practical implementation of common faults in a two-tank networked control sys...
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1|INTRODUCTION In Linyi,Shandong,China,researchers used 100%grid-forming(GFM)photovoltaics(PVs)to power the microgrid without the conventional synchronous *** microgrid operates independently and stably supporting the...
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1|INTRODUCTION In Linyi,Shandong,China,researchers used 100%grid-forming(GFM)photovoltaics(PVs)to power the microgrid without the conventional synchronous *** microgrid operates independently and stably supporting the seamless transition between islanded and grid-connected *** to the grid-following(GFL)method,GFM enables renewable sources to behave like voltage sources with the transient frequency and voltage *** is the key technology for the renewable generations to replace the con-ventional generations to maintain the synchronous stability of the ***,most GFM methods are developed for the battery energy storage system(BESS)and focus on the single-machine level to emulate the conventional synchronous machine,such as virtual synchronous machine(VSM)1 and droop control.2 These methods tend to lose the synchronous stability in response to the large disturbances under the multi-machine conditions.
Multi-agent Path Finding (MAPF) is the problem of planning collision-free movements of agents such that they get from where they are to where they need to be. Commonly, agents are located on a graph and can traverse e...
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Rotating machinery is an integral part of many industrial systems. Domain adaptation technique provides a powerful tool to detect faults under different working conditions. However, there is still a challenge: convent...
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The paper presents an analysis of fast selection of neural network for the purpose of visual analysis of mechanical wear on prism lenses of in-pavement airport navigational lighting systems. This issue is particularly...
The paper presents an analysis of fast selection of neural network for the purpose of visual analysis of mechanical wear on prism lenses of in-pavement airport navigational lighting systems. This issue is particularly important in terms of aviation safety and navigational lighting control, regulated by EASA and ICAO. The article is the next stage of the development of the system for the vision control of lamps, in which the concept of using a different neural network with an increased data set prepared by the authors is presented. The Deep Network Designer tool included in the Matlab 2022b environment was used. The solution using the GoogLeNet neural network allows for the classification of lamps with an accuracy of 88.37%.
Gait analysis can provide relevant information about the physical and neurological conditions of individuals. For this reason, several studies have recently been carried out in an attempt to monitor people's gait ...
Gait analysis can provide relevant information about the physical and neurological conditions of individuals. For this reason, several studies have recently been carried out in an attempt to monitor people's gait and automatically detect gait anomalies. Among the various monitoring systems available for gait analysis, wearable sensors are considered the gold standard due to their wide capture range and low cost. However, in the case of people that require assistive devices for walking, some studies have proposed the use of sensorized devices in order to minimize invasiveness. Nevertheless, there is still a lack of comparative works that evaluate the performance of sensorized assistive devices for walking with widely used wearable sensors. Hence, this paper presents a comparison between the performance of accelerometer-based wearable sensors and a sensorized tip developed by the authors to detect gait anomalies. The comparative study has been carried out in a controlled environment with five healthy subjects, in which three different physical states have been simulated. A machine-learning based anomaly detection approach has been implemented based on the data captured by a set of wearable sensors and the sensorized tip, and the overall performance of both monitoring systems has been evaluated. Results show that even if both devices can provide an average accuracy of more than 80% in gait anomaly detection, the sensorized tip provides better performance.
The purpose of this article is to perform a comparison between two identification models: a nonlinear one referred to as HARMAX and a classical linear one, of Box-Jenkins (BJ) type. The first model modifies a classica...
The purpose of this article is to perform a comparison between two identification models: a nonlinear one referred to as HARMAX and a classical linear one, of Box-Jenkins (BJ) type. The first model modifies a classical ARMAX model by applying Hammerstein polynomials on input, output, and noise signals. Identification of models was performed by means of Multi-Step Least Squares Method, as described into the article. The simulations on a real-world plant, namely ASTANK2, a fluidic system with two inputs, two outputs and nonlinear static characteristic, have proven that the HARMAX model performs better than the BJ model and provides more accurate useful models to be integrated into closed loop configurations.
This paper presents an analysis of the effectiveness of blood vessel segmentation in human retinal images. The segmentation process was carried out for three-dimensional optical coherence tomography (OCT) scans using ...
This paper presents an analysis of the effectiveness of blood vessel segmentation in human retinal images. The segmentation process was carried out for three-dimensional optical coherence tomography (OCT) scans using the author’s publicly available CAVRI-C database. A 3D version of the U-Net artificial neural network was used. Various dimensions of the input blocks were investigated to determine their influence on the segmentation process. The effectiveness of the proposed solutions was evaluated using various metrics and the results obtained were compared with the 2D solution, also based on neural networks. The use of the proposed solutions allowed us to improve the segmentation even by 15% (in the case of the F1-score).
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