A Robust Fuzzy Neural Network Model for Soil Lead Estimation from Spectral Features

Soil lead content is an important parameter in environmental and industrial applications. Chemical analysis, the most commonly method for studying soil samples, are costly, however application of soil spectroscopy presents a more viable alternative. The first step in the method is usually to extract some appropriate spectral features and then regression models are applied to these extracted features. The aim of this paper was to design an accurate and robust regression technique to estimate soil lead contents from laboratory observed spectra. Three appropriate spectral features were selected according to information from other research as well as the spectrum interpretation of field collected soil samples containing lead. These features were then applied to common Multiple Linear Regression (MLR), Partial Least Square Regression (PLSR) and Neural Network (NN) regression models. Results showed that although NN had adequate accuracy, it produced unstable results (i.e., variation of response in different runs). This problem was addressed with application of a Fuzzy Neural Network (FNN) with a least square training strategy. In addition to the stabilized and unique response, the capability of the proposed FNN was proved in terms of regression accuracy where a Ratio of Performance to Deviation (RPD) of 8.76 was achieved for test samples

The Epidemiology of Injuries and Accidents in Children Under one Year of Age, during (2009-2016) in Hamadan Province, Iran

Background Injuries and accidents are the first cause of death in the first 5 years of children life in the world; the present study was conducted to investigate the extent and distribution of accidents in the infants under one year in Hamadan Province, Iran. Materials and Methods:This cross-sectional descriptive-analytic study was carried out using of   data of injuries and accidents related to children under one year for Hamadan province in seven years period from March 2009 to March 2016. In this study we used data according national injuries and accidents recorded program. The data were analyzed using descriptive statistics as well as analytical statistics including the Chi-square test. Data were analyzed using Stata software version 12. Results:In this 7 year periods, 3,200 accidents were registered among children under one year. The highest occurrence of accidents was in the spring 1,029 (31.15% of cases). 1,890 (59.1%) of accidents occurred in the urban area and only 429 (13.4%) of them were in rural area. In total, car accidents (53.4%), trauma (12.6%) and fall from altitude (8.8%) had most frequency from all accidents. There was a significant difference between gender and place of accident with type of accident (