Wavelet Based Simulation and Analysis of Single and Multiple Power Quality Disturbances

Improving power quality disturbance (PQD) detection and automatic classification has been a major concern ever since the emergence of sensitive non-linear devices. The role of distributed generation in a power system is the main source of PQDs. Short-term and long-term duration single and multiple complex PQDs are difficult to monitor and need higher accuracy and time. This paper presents the analysis of different and distinctive combinations of PQDs. Variety of single and multiple PQD samples are generated using Matlab environment conferring to IEEE STD 1159-2009. Such disturbance samples are accurately detected and analyzed from waveform patterns using multi resolution analysis based discrete wavelet transform. The generation of samples and detection lies in fact that it can allow the feature extraction process for the training/testing sample features for machine learning based automatic recognition of disturbance types

Assessment of dental students′ psychomotor skills using oral surgery simulation models

Aim: The aim of this study was to determine the validity of using oral surgery simulation models as a tool to assess the psychomotor skills of dental students. Materials and Methods: All students in the 4 th year of a 6 years dental program were enrolled in the study. 23 dental students were asked to display their competency in the injection of local anesthesia and dental extraction in two summative testing environments namely; in the simulation and in the outpatient clinic. A panel of four experts assessed the students′ performance during the injection of local anesthesia and tooth extraction on patients and simulation using a pre-validated checklist. Students′ scores were compared in both settings. Results: The results showed no significant correlation between the scores on patients and simulation in the two settings (P = 0.759). Conclusion: The study revealed that the real patient remains the gold standard in summative assessment of dental students′ psychomotor skills