• Journal of Digital Convergence
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• v.17 no.1
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• pp.239-247
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• 2019

An accurate prediction of emotion is a very important issue for the sake of patient-centered medical device development and emotion-related psychology fields. Although there have been many studies on emotion prediction, no studies have applied the heart rate variability and neuro-fuzzy approach to emotion prediction. We propose ANFEP(Adaptive Neuro Fuzzy System for Emotion Prediction) HRV. The ANFEP bases its core functions on an ANFIS(Adaptive Neuro-Fuzzy Inference System) which integrates neural networks with fuzzy systems as a vehicle for training predictive models. To prove the proposed model, 50 participants were invited to join the experiment and Heart rate variability was obtained and used to input the ANFEP model. The ANFEP model with STDRR and RMSSD as inputs and two membership functions per input variable showed the best results. The result out of applying the ANFEP to the HRV metrics proved to be significantly robust when compared with benchmarking methods like linear regression, support vector regression, neural network, and random forest. The results show that reliable prediction of emotion is possible with less input and it is necessary to develop a more accurate and reliable emotion recognition system.

• Journal of Radiation Protection and Research
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• v.47 no.4
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• pp.195-203
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• 2022

Background: The aim of the present study was to determine radioactive concentrations in fertilizers known to contain essential nutrients. Results of this study could be used as basic data to monitor the impact of chemical fertilizers on the environment and public health. Nitrogen fertilizers, calcium fertilizers, sulfur fertilizers, phosphate acid fertilizers, and potassium chloride fertilizers were used in this study. Materials and Methods: Five chemical fertilizers were pulverized, placed in polyethylene containers, and weighed. The time to measure each specimen was set to be 3,600 seconds for a scintillator-based gamma-ray spectroscopy system. Concentration of gamma radionuclide was analyzed based on obtained spectra. At the end of the measurement, the spectrum file was stored and used to calculate radioactive concentrations using a gamma-ray spectrometer software. Results and Discussion: In the nitrogen fertilizer, 3.49 ± 5.71 Bq/kg of ¹³⁷Cs, 34.43 ± 7.61 Bq/kg of ¹³⁴Cs, and 569.16 ± 91.15 of ⁴⁰K were detected whereas ¹³¹I was not detected. In the calcium fertilizer, 5.74 ± 4.40 Bq/kg of ¹³⁷Cs (the highest concentration among all fertilizers), 22.37 ± 5.39 Bq/kg of ¹³⁴Cs, and 433.67 ± 64.24 Bq/kg of ⁴⁰K were detected whereas ¹³¹I was not detected. In the sulfur fertilizer, 347.31 ± 55.73 Bq/kg of ⁴⁰K, 19.42 ± 4.53 Bq/kg of ¹³⁴Cs, 2.21 ± 3.49 of ¹³⁷Cs, and 0.04 ± 0.22 Bq/Kg of ¹³¹I were detected. In the phosphoric acid fertilizer, 70,007.34 ± 844.18 Bq/kg of ⁴⁰K (the highest concentration among all fertilizers) and 46.07 ± 70.40 Bq/kg of ¹³⁴Cs were detected whereas neither ¹³⁷Cs nor ¹³¹I was detected. In the potassium chloride fertilizer, 12,827.92 ± 1542.19 Bq/kg of ⁴⁰K was and 94.76 ± 128.79 Bq/kg of ¹³⁴Cs were detected whereas neither ¹³⁷Cs nor ¹³¹I was detected. The present study examined inorganic fertilizers produced by a single manufacturer. There might be different results according to the country and area from which fertilizers are imported. Further studies about inorganic fertilizers in more detail are needed to create measures to reduce ⁴⁰K. Conclusion: Measures are needed to reduce radiation exposure to ⁴⁰K contained in fertilizers including phosphoric acid and potassium chloride fertilizers.