In the diagnosis of reinforced concrete, investigating the size and cover thickness of the reinforcement is important. Electromagnetic radar, which conducts surveys by identifying scattered waveforms, is highly valued for its efficiency and convenience in these investigations. Recently, the use of Artificial Neural Networks (ANN) for identifying electromagnetic waveforms has been reported. While these reports mainly focus on void detection within concrete, the potential and accuracy of reinforcement detection using ANN are not examined in detail. In this paper, we explore the possibilities of estimating reinforcement size and cover thickness using ANN in a model of two-dimensional homogenous reinforced concrete. Furthermore, this paper reports on investigations conducted in cases where noise is introduced into the observed data and when multiple reinforcements are present.

Nanosecond pulse electric field (nsPEF) therapy has attracted attention in recent years as a non-invasive cancer treatment with minimal side effects. However, the relationship between the electrical stress induced in cells by the external electric field and the biological response has not been fully investigated quantitatively. We investigated the effects of nsPEF therapy on cancer cells using microgap electrodes under low voltage conditions. We developed an equivalent circuit model using intracellular components to determine the amount of stimulation of cellular components and performed frequency analysis of nsPEF. nsPEF applied to Jurkat cells activated caspase-3 and induced apoptosis at shorter pulse widths. nsPEF induced biological responses and apoptosis in cancer cells. The relationship between the biological response induced by nsPEF and the amount of electrical stimulation was investigated by comparing the experimental results with frequency analysis. Using quantitative values for each cellular element, the relationship between the biological response and the amount of electrical stimulation can be integrated.