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This paper describes a FADC Readout system developed for the tap water $\alpha/\beta$ dose monitoring system which is based on EJ444 phoswich scintillation detector and wavelength shifting fiber readout. The Readout system contains dual sampling channels that can supply sampling rate up to 1 GSPS, 14-Bit vertical resolution and adequate effective number of bits (9.7 Bits at 10 MHz), which is optimum for the discrimination of the minimal difference between alpha/beta signals. Moreover, the system is based on a ZYNQ SoC which provides high data throughput speed, low latency and excellent flexibility. As for the discrimination algorithms, a simple least-square classification method is used to discriminate the $\alpha/\beta$ signals and shows high discrimination capability. Besides, the front-end electronics and high voltage supply modules are also briefly introduced in the paper.

The monitoring of Cs-137 in seawater using scintillation detector relies on the spectrum analysis method to extract the Cs-137 concentration. And when in poor statistic situation, the calculation result of the traditional net peak area (NPA) method has a large uncertainty. We present a machine learning based method to better analyze the gamma-ray spectrum with low Cs-137 concentration. We apply multilayer perceptron (MLP) to analyze the 662 keV full energy peak of Cs-137 in the seawater spectrum. And the MLP can be trained with a few measured background spectrums by combining the simulated Cs-137 signal with measured background spectrums. Thus, it can save the time of preparing and measuring the standard samples for generating the training dataset. To validate the MLP-based method, we use Geant4 and background gamma-ray spectrums measured by a seaborne monitoring device to generate an independent test dataset to test the result by our method and the traditional NPA method. We find that the MLP-based method achieves a root mean squared error of 0.159, 2.3 times lower than that of the traditional net peak area method, indicating the MLP-based method improves the precision of Cs-137 concentration calculation, Comment: 13 pages, 11 figures