Abstract-In Thailand, nowadays, the planted area, climate and rainfall are changed rapidly effect to unstable of Thai rice production. The decision-making processes often require reliable rice response models. Local governor and farmer need simple and accurate estimation techniques to predict rice yield in the planning process. This study aims to develop the decision support system using Artificial Neural Networks (ANN) by adjust the value of parameters and study about 9 Algorithms training. In predicting rice productions which its study found that each values that was adjusted making high predicting like appropriate number of hidden nodes to model equals to 9, learning rate effects the speed of appropriate learning to the model equals to 0.5, and appropriate momentum to model was 0.5. CGB Algorithm has coefficient decision higher than using regression variable technique by Stepwise multiple method curve of ANN and stepwise multiple regression method was 4,293.70 and 40,160.00, respectively. Index Termsneural networks, stepwise multiple regression method.

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Abstract-The objective of this paper is to present the m-learning for teaching in molding and casting with plaster by using QR Codes (MLM) which offers Thai sign language video correspondence to every contents in learning environment. It was developed as a response to stakeholder at Nakhon Ratchasima Rajabhat University, Thailand. The participations in this study were seven deaf and hard hearing student who faced the problem when study in the classroom. This MLM provided the content and video to demonstrate and showed the technique which student could follow and practice by themselves. This MLM used a Universal Design for learning (UDL) approach to explore the iterative development of mobile to meet stakeholder needs. Koole's FRAME model was used to guide the design process, and evaluated their pedagogical effectiveness. The student can access to the lesson by scanning Quick Response (QR) codes. All relative resource can storage using cloud computing. Participants had a positive response to the m-learning. The students and instructors reported enjoying learning with their mobile devices, and found the MLM easy to access and use.Index Terms-Deaf and hard hearing, mobile learning, QR codes, universal design for learning (UDL).