Blended knit with two or more fiber has various dyeing characteristics depending on dyeing method because of different material properties of them. In this paper, newly developed blended knit was used. It was composed by Acrylate fiber and Dyeable polypropylene(DPP) fiber. As result of build-up dyeing test, acid dyes and disperse dyes respectively had good dyeabilities on 1% o.w.f. with Acrylate fiber and DPP fiber. Compatibility of trichromatic of disperse dyes was generally good for most dyes investigated and their critical absorption range were between 120℃ and 130℃. As depending on dyeing methods, there were many differences in dyeability. It was confirmed that 1-bath-1-step dyeing was most suitable when considering dye exhaustion yield and levelling property. Wash, rubbing and light fastness of knits were generally good in most dyes.

In this paper, we implement a system for a fund recommendation based on the investment propensity and for a future fund price prediction. The investment propensity is classified by scoring user responses to series of questions. The proposed system recommends the funds with a suitable risk rating to the investment propensity of the user. The future fund prices are predicted by Prophet model which is one of the machine learning methods for time series data prediction. Prophet model predicts future fund prices by learning the parameters related to trend changes. The prediction by Prophet model is simple and fast because the temporal dependency for predicting the time-series data can be removed. We implement web pages for the fund recommendation and for the future fund price prediction.