This paper proposes computational models to investigate the effects of dust and ambient temperature on the performance of a photovoltaic system built at the Hashemite University, Jordan. The system is connected on-grid with an azimuth angle of 0° and a tilt angle of 26°. The models have been developed employing optimized architectures of artificial neural network (ANN) and extreme learning machine (ELM) models to estimate conversion efficiency based on experimental data. The methodology of building the models is demonstrated and validated for its accuracy using different metrics. The effect of each parameter was found to be in agreement with the well-known relationship between each parameter and the predicted efficiency. It is found that the optimized ELM model predicts conversion efficiency with the best accuracy, yielding an R2 of 91.4%. Moreover, a recommendation for cleaning frequency of every two weeks is proposed. Finally, different scenarios of electricity tariffs with their sensitivity analyses are illustrated.
Obstructive Sleep Apnea/Hypopnea Syndrome (OSAHS) is the most common form of Sleep Disordered Breathing (SDB) and it is estimated to affect approximately 15% of US adult population. Various methods have been proposed for the development of inexpensive screening methods to detect SDB to reduce the need for costly nocturnal polysomnography (NPSG). In this paper, a description of the ultrasonic transducer design and characterization is presented, followed by the results of a full night sleep study. The findings show a significant difference in the temporal features extracted from the received ultrasonic waveform during apneic breathing, compared to the hyperventilation that follows. Therefore, the findings indicate the feasibility of developing an ultrasonic detection device for low cost diagnosis of SDB.
Obstructive sleep apnea/hypopnea Syndrome (OSAHS) is the most common form of Sleep Disordered Breathing (SDB) and it is estimated to affect approximately 6% of US adult population. Various methods have been proposed for the development of inexpensive screening methods to detect SDB to reduce the need for costly nocturnal polysomnography (NPSG). By using the existing air in the airway as an ultrasonic contrast agent, we propose a method to examine the narrowing or occlusion of the airway associated with OSAHS events. We describe here an in vitro study that approximates the anatomical and acoustic characteristics of the airway and neck. In this experiment, we simulate the fully open airway as well as apnea and hypopnea events. These in vitro studies results show significant differences in the ultrasonic signals acquired from the open airway model versus those from the model depicting apnea and hypopnea events. Therefore, the findings provide a foundation for development of an ultrasound system to detect SDB in vivo.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.