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This paper presents a compact analog system-on-chip (SoC) implementation of a spiking neural network (SNN) for low-power Internet of Things (IoT) applications. The low-power implementation of an SNN SoC requires the optimization of not only the SNN model but also the architecture and circuit designs. In this work, the SNN has been constituted from the analog neuron and synaptic circuits, which are designed to optimize both the chip area and power consumption. The proposed synapse circuit is based on a current multiplier charge injector (CMCI) circuit, which can significantly reduce power consumption and chip area compared with the previous work while allowing for design scalability for higher resolutions. The proposed neuron circuit employs an asynchronous structure, which makes it highly sensitive to input synaptic currents and enables it to achieve higher energy efficiency. To compare the performance of the proposed SoC in its area and power consumption, we implemented a digital SoC for the same SNN model in FPGA. The proposed SNN chip, when trained using the MNIST dataset, achieves a classification accuracy of 96.56%. The presented SNN chip has been implemented using a 65 nm CMOS process for fabrication. The entire chip occupies 0.96 mm2 and consumes an average power of 530 μW, which is 200 times lower than its digital counterpart.

This work represents the set of measurements of radon and thoron concentrations levels of soil-gas in Al-Kufa city in Iraq using electric Radon meter (RAD-7). Radon and thoron concentration were measured in soil-gas in 20 location for three depth of (50, 100 and 150) cm. The results show that the emanation rate of radon and thoron gas varied from location to anther, depending on the geological formation. The Radon concentration in soil has been found to vary from (12775±400) Bq/m3 at 150 cm depth in location (sample K2) to (41.45±17) Bq/m3, for depth 150 cm in location (sample K20). The thoron concentration in soil has been found to vary from (198±8.5) Bq/m3 at 150 cm depth in location samples (K1 & K2) to undetected in the most location. These concentrations values are well below the allowed levels which it is range (0.4-40) KBq/m3.

In this research, radon concentrations in some types of healthy drinking water samples available in Iraq's market were measured using a technique called Durridge RAD-7-H2O with closed loop. Then the rate of annual effective dose in human taken this water is determined. It was found that, radon concentrations in studied samples ranged between 1.2 Bq.m-3 to 142 Bq.m-3. The results of the radon concentrations and the rate of annual effective dose for drinking water samples were significantly lower than the USEPA and WHO recommended limits that equal 500 Bq/m3 and 1 mSv/y respectively.

Measurement of radon concentration level was carried out in 40 houses in Al – Najaf city during summer season of 2012. Long term measurement of indoor of old building radon concentrations have been taken, using a previously calibrated passive diffusion dosimeters containing CR – 39 solid state nuclear track detectors which are very sensitive for alpha particles. The measurement of the indoor radon concentration obtained in summer in these regions ranged from 11.654±4.216 Bq.m-3 to 53.610±8.777 Bq.m-3. The results were within universally permitted levels.