The detection of epileptic seizures by electroencephalography (EEG) signals has become a standard method in recent years for the diagnosis of epilepsy. Accurate and automatic detection of epileptic seizures is needed since manual identification of epileptic seizures by specialist neurologists is a time-consuming and labor-intensive process, which also leads to various errors. For this purpose, frequency-based features were extracted from the EEG signal and various classifiers based on ensemble learning were used to detect epileptic seizures automatically. The performance of the proposed method was tested using cross-validation and cross-patient experiments. According to the experimental results, sensitivity, specificity, and accuracy rates were obtained 94%, 93% and 93% for cross-validation and 76%, 90% and 90% for cross-patients, respectively.

This work examines the production of nanoparticles using exploding wire method (EWM). It is applied by the sudden discharge of a high voltage energy, stored on a power source, through a thin wire. The required high voltage energy was obtained with the use a voltage multiplier circuit which was first designed in the simulation environment. Then the circuit realized by the circuit elements' parameters obtained through the simulation. Kanthal-D (FeCrAl alloy) wire was chosen as the thin metal, and all wire exploding experiments were carried out in air environment. The obtained nanoparticles were examined by SEM, and point analysis was applied to a target area on the SEM image. It is observed that the dimensions of obtained Kanthal-D nanoparticles in this study vary between 0-250 nm. In addition, EDS chemical microanalysis was performed to reveal obtained nanoparticles' composition. Fe (71-7-74-7%), Al (4.8%) and Cr (20.5-23.5%) atoms were detected in the exploded nanoparticles. With this study, it has been shown for the first time in the literature that the stored energy obtained by a voltage multiplier circuit can be used in the EWM to produce nanoparticles in appropriate sizes