Parameter estimation and control design of solar maximum power point tracking

Parameters evaluation, design, and intelligent control of the solar photovoltaic model are presented in this work. The parameters of zeta converters such as a rating of an inductor, capacitor, and switches for a particular load are evaluated its values to compare the trade of the existing model and promoted to research in the proposed area. The zeta converter is pulsed through intelligent controller-based maximum power point tracking (intelligent-MPPT). The intelligent controller is a fuzzy logic controller (FLC) which extracts maximum power from the solar panel using the zeta converter. The performance of evaluated parameters based on the solar system and zeta converter is seen by an intelligent control algorithm. Moreover, evaluated parameters of solar photovoltaic (PV) and zeta converter can be examined the performance of fuzzy based intelligent MPPT under transient and steady-state conditions with different solar insolation. The brushless direct current motor-based water pump is used as the direct control (DC) load of the proposed model. The proposed model can enhance the research and assist to develop a new configuration of the present system

RuSTL: Runtime Verification using Signal Temporal Logic

A system is classified to be a safety-critical system if its failure and/or malfunction of these devices may result in severe injuries or in extreme cases loss of human life. Such systems are all around us, examples of which include pacemakers, respiratory equipment, electrical locks, fire sprinklers and cars among many others. Runtime Verification (RV) is used to monitor the execution of such systems either while running or after execution to ensure that the system under observation does not violate any safety constraints. RV employs formal specification languages to evaluate a real-world systems. Pnueli introduced the formal specification for Linear Temporal Logic (LTL) in 1977 for specifying propositional time properties of reactive and concurrent systems. Signal Temporal Logic (STL) is a popular extension of LTL, which analyzes dense-time real-valued signal properties with quantitative timing constraints. In this thesis, we introduce Runtime Verification using Signal Temporal Logic (RuSTL), an offline qualitative semantic tool for monitoring STL properties. RuSTL is designed to parse any valid STL formula ’ and create a stand-alone executable monitor program, which checks the property against a given trace σ. RuSTL also take in as input structured English text and convert it into an equivalent STL formula. The application also has the capability to automatically generate diagnostic plots that help the user visually inspect the results of the monitor against a given trace. We prove that the monitor program generated by RuSTL is sound and it terminates for any given valid STL property. Furthermore, we prove that the parsing algorithm used to create the monitor program is complete. We evaluated RuSTL’s performance over traces collected from an autonomous self-driving vehicle. The experimental results for our RV monitor show that the execution time of the monitor grows linearly with respect to the length of the signal trace provided

Hyperparameters analysis of long short-term memory architecture for crop classification

Deep learning (DL) has seen a massive rise in popularity for remote sensing (RS) based applications over the past few years. However, the performance of DL algorithms is dependent on the optimization of various hyperparameters since the hyperparameters have a huge impact on the performance of deep neural networks. The impact of hyperparameters on the accuracy and reliability of DL models is a significant area for investigation. In this study, the grid Search algorithm is used for hyperparameters optimization of long short-term memory (LSTM) network for the RS-based classification. The hyperparameters considered for this study are, optimizer, activation function, batch size, and the number of LSTM layers. In this study, over 1,000 hyperparameter sets are evaluated and the result of all the sets are analyzed to see the effects of various combinations of hyperparameters as well the individual parameter effect on the performance of the LSTM model. The performance of the LSTM model is evaluated using the performance metric of minimum loss and average loss and it was found that classification can be highly affected by the choice of optimizer; however, other parameters such as the number of LSTM layers have less influence

Role of Waqf in poverty mitigation: A study from South Punjab Pakistan

This study investigated the mediating role of family well-being in the relationship between waqf and poverty mitigation. Using a cross-sectional design, data was collected from 350 respondents in a Malaysian context. The results showed that waqf practices have a direct positive effect on poverty mitigation and family well-being. Family well-being, in turn, partially mediates the relationship between waqf and poverty mitigation. The study provides evidence for the potential of waqf practices to improve family well-being, which can ultimately contribute to poverty reduction. The findings have important implications for policymakers, organizations, and Islamic philanthropists involved in poverty reduction efforts. Policymakers can promote and support waqf practices to mitigate poverty, while organizations can focus on initiatives that improve family well-being. The study highlights the importance of family well-being in poverty reduction efforts and provides valuable insights for poverty reduction strategies and initiatives

An optimal clustering algorithm based distance-aware routing protocol for wireless sensor networks

Wireless Sensors Networks (WSN) consist of low power devices that are deployed at different geographical isolated areas to monitor physical event. Sensors are arranged in clusters. Each cluster assigns a specific and vital node which is known as a cluster head (CH). Each CH collects the useful information from its sensor member to be transmitted to a sink or Base Station (BS). Sensor have implemented with limited batteries (1.5V) that cannot have replaced. To resolve this issue and improve network stability, the proposed scheme adjust the transmission range between CHs and their members. The proposed approach is evaluated via simulation experiments and compared with some references existing algorithms. Our protocol seemed improved performance in terms of extended lifetime and achieved more than 35% improvements in terms of energy consumptio

Virtual reality (VR)-based environmental enrichment in older adults with mild cognitive impairment (MCI) and mild dementia

Background: Despite an alarming rise in the global prevalence of dementia, the available modalities for improving cognition and mental wellbeing of dementia patients remain limited. Environmental enrichment is an experimental paradigm that has shown promising anti-depressive and memory-enhancing effects in pre-clinical studies. However, its clinical utility has remained limited due to the lack of effective implementation strategies.Objective: The primary objective of this study was to evaluate the usability (tolerability and interactivity) of a long-term virtual reality (VR)- based environmental enrichment training program in older adults with mild cognitive impairment (MCI) and mild dementia. A secondary objective was to assess the effect of VR-based environmental enrichment on stabilization of cognitive functioning and improvement of mental wellbeing in older adults with MCI and mild dementia.Methods: A total of seven participants (four patients with MCI and three with mild dementia) received biweekly VR-based environmental enrichment over a course of 6 months. The tolerability and interactivity of the participants in the VR training was serially assessed via virtual reality sickness questionnaire (VRSQ) and recording of input-error ratio. Cognitive functioning was assessed through Montreal cognitive assessment (MoCA) before and after the study. Mental wellbeing was assessed through Warwick-Edinburgh Mental Well Being Scale (WEMWBS).Results: VR-based environmental enrichment was well-tolerated by the patients with significant decrease in VRSQ scores (p \u3c 0.01) and input-error ratio (p \u3c 0.001) overtime. VR training was also effective in stabilization of MoCA scores over the course of therapy (non-significant difference in the MoCA scores before and after the therapy) and was associated with a trend (p \u3c 0.1) towards improvement in WEMWBS scores between the first and the last assessments. Qualitative observations by the care-givers further corroborated a noticeable improvement in mental wellbeing of patients.Conclusions: This pilot study shows that VR can be a feasible, tolerable, and potentially effective tool in long-term support of older adults with MCI and mild dementia