Support Provided by Public Health Nurses for Fathers Who Have Abused Their Children—As Observed in Cases of Child Neglect and Physical or Psychological Abuse

This study aims to identify the support to provide to fathers who have abused children as reported by public health nurses (PHNs). In this study, a qualitative descriptive design was applied to the data analysis. Interviewees were 10 public health nurses (PHNs) in charge of child abuse services for at least 5 years at public health centers. The study analyzed 13 cases reported in the interviews. Measures to support fathers who abuse their children as suggested by PHNs were classified into direct support to the father, support to other family members, and support to be provided by others involved including related organizations. The direct support to the father includes “gaining an in-depth understanding of the abusive situation and psychological states of those involved”, “refraining from involvement in areas where it is difficult to understand the personality of the father”, and others. Support of other family members includes “understanding the marital relationship and assessing the qualities of the relationship”, “refraining from matters that will involve divorce”, and others. Support to be provided by others including related organizations includes “understanding the value of social exchange and assessment of the ability to create and maintain interpersonal relationships”, “establishing support arrangements to enable intervention when necessary”, and others. The interviews report that PHNs arrange support measures that enable intervention as it becomes required, and that this enables learning about child-abuse preventing activities.

Soft measurement for component content based on adaptive model of Pr/Nd color features

For measurement of component content in the extraction and separation process of praseodymium/neodymium(Pr/Nd), a soft measurement method was proposed based on modeling of ion color features, which is suitable for fast estimation of component content in production field. Feature analysis on images of the solution is conducted,which are captured from Pr/Nd extraction/separation field. H/S components in the HSI color space are selected as model inputs, so as to establish the least squares support vector machine(LSSVM) model for Nd(Pr) content,while the model parameters are determined with the GA algorithm. To improve the adaptability of the model,the adaptive iteration algorithm is used to correct parameters of the LSSVM model, on the basis of model correction strategy and new sample data. Using the field data collected from rare earth extraction production, predictive methods for component content and comparisons are given. The results indicate that the proposed method presents good adaptability and high prediction precision, so it is applicable to the fast detection of element content in the rare earth extraction.