Formulation of Foundation Makeup (Liquid) Using D-Optimal Mixture Design

Formulation of foundation makeup (liquid) was performed using Doptimal mixture design. Design expert software 7.0 was used to set up D-optimal mixture design and 15 formulations were conducted. Each formulation was judged its properties of pH, viscosity, and skin irritation to obtain the most appropriate composition. The optimum formulation of foundation makeup (liquid) was 227.43 ml of deionized water (DI), 1.40 g of carboxy methyl cellulose (CMC), 4.37 g of triethanolamine (TEA), 20.94 g of propanediol (PD), 31.84 g of titanium dioxide (TiO2), 5.25 g of iron oxide (Fe3O4), 7.0 g of kaolin (Kao), 1.40 g of methyl paraben (MP), 34.97 ml of mineral oil (MO), 5.25 g of stearic acid (SA), 8.75 g of glyceryl monosterate (GMS) and 1.40 g of propyl paraben (PP) based on its properties of pH 6.93, 1722.3cP of viscosity and 0 of skin irritation. Regarding the evaluation sheet performed by the Hedonic scale test, satisfactory scores of foundation makeup (liquid) was 7.4 out of 9

Applications of complexometry and polarography to continuous analysis

Imperial Users onl

Myanmar news summarization using different word representations

There is enormous amount information available in different forms of sources and genres. In order to extract useful information from a massive amount of data, automatic mechanism is required. The text summarization systems assist with content reduction keeping the important information and filtering the non-important parts of the text. Good document representation is really important in text summarization to get relevant information. Bag-of-words cannot give word similarity on syntactic and semantic relationship. Word embedding can give good document representation to capture and encode the semantic relation between words. Therefore, centroid based on word embedding representation is employed in this paper. Myanmar news summarization based on different word embedding is proposed. In this paper, Myanmar local and international news are summarized using centroid-based word embedding summarizer using the effectiveness of word representation approach, word embedding. Experiments were done on Myanmar local and international news dataset using different word embedding models and the results are compared with performance of bag-of-words summarization. Centroid summarization using word embedding performs comprehensively better than centroid summarization using bag-of-words

Collaborative Learning and IT-Supported Organizational Memory

An exploratory study of class email and discussion database postings in two advanced IS undergraduate classes looks at the extent to which the students use these collaborative tools for organizational memory purposes. The instructor was trying to move communication away from email onto an Internet-based Lotus Notes discussion database (Domino) in order to provide a shared organizational memory that would benefit a greater number of students. Students working on group projects used both email and Domino for both teamwork and topical contributions to organizational memory at much higher levels then students working on individual projects

Interview with Valerie Soe

Valerie Soe is a fourth generation Asian American woman from the San Francisco/Berkeley area. She is a documentary and experimental filmmaker, known for her films Love Boat: Taiwan and Radical Care: The Auntie Sewing Squad. Additionally, she is a Asian American Studies professor at San Francisco State University. She is an original member of the Auntie Sewing Squad since March of 2019.https://digitalcommons.csumb.edu/auntiesewing_interviews/1028/thumbnail.jp