MingDao University

About: MingDao University is a education organization based out in Bitou, Taiwan. It is known for research contribution in the topics: Thin film & Coating. The organization has 557 authors who have published 903 publications receiving 17915 citations.

High-brightness LEDs—Energy efficient lighting sources and their potential in indoor plant cultivation

Abstract: The rapid development of optoelectronic technology since mid-1980 has significantly enhanced the brightness and efficiency of light-emitting diodes (LEDs). LEDs have long been proposed as a primary light source for space-based plant research chamber or bioregenerative life support systems. The raising cost of energy also makes the use of LEDs in commercial crop culture imminent. With their energy efficiency, LEDs have opened new perspectives for optimizing the energy conversion and the nutrient supply both on and off Earth. The potentials of LED as an effective light source for indoor agricultural production have been explored to a great extent. There are many researches that use LEDs to support plant growth in controlled environments such as plant tissue culture room and growth chamber. This paper provides a brief development history of LEDs and a broad base review on LED applications in indoor plant cultivation since 1990.

A causal and effect decision making model of service quality expectation using grey-fuzzy DEMATEL approach

Abstract: This research uses a solution based on a combined grey-fuzzy DEMATEL method to deal with the objective of the study. This study is aimed to present a perception approach to deal with real estate agent service quality expectation ranking with uncertainty. The ranking of best top five real estate agents might be a key strategic direction of other real estate agents prior to service quality expectation. The solving procedure is as follows: (i) the weights of criteria and alternatives are described in triangular fuzzy numbers; (ii) a grey possibility degree is used to result the ranking order for all alternatives; (iii) DEMATEL is used to resolve interdependency relationships among the criteria and (iv) an empirical example of real estate agent service quality ranking problem in customer expectation is used to resolve with this proposed method approach indicating that real estate agent R1 (CY real estate agent) is the best selection in terms of service quality in customer expectation.

Forecasting stock markets using wavelet transforms and recurrent neural networks: An integrated system based on artificial bee colony algorithm

Abstract: This study presents an integrated system where wavelet transforms and recurrent neural network (RNN) based on artificial bee colony (abc) algorithm (called ABC-RNN) are combined for stock price forecasting. The system comprises three stages. First, the wavelet transform using the Haar wavelet is applied to decompose the stock price time series and thus eliminate noise. Second, the RNN, which has a simple architecture and uses numerous fundamental and technical indicators, is applied to construct the input features chosen via Stepwise Regression-Correlation Selection (SRCS). Third, the Artificial Bee Colony algorithm (ABC) is utilized to optimize the RNN weights and biases under a parameter space design. For illustration and evaluation purposes, this study refers to the simulation results of several international stock markets, including the Dow Jones Industrial Average Index (DJIA), London FTSE-100 Index (FTSE), Tokyo Nikkei-225 Index (Nikkei), and Taiwan Stock Exchange Capitalization Weighted Stock Index (TAIEX). As these simulation results demonstrate, the proposed system is highly promising and can be implemented in a real-time trading system for forecasting stock prices and maximizing profits.