The demand for lottery expenditure in Taiwan: a quantile regression approach

This paper is a pioneering attempt to apply the quantile regression method (QRM) to the demand for lottery expenditure in order to consider the extreme behavior of lottery expenditure as well as clarify the diverse results obtained from previous studies on lottery expenditure. The results of this study reveal that there exists a complementary correlation both between benevolent donations and lottery expenditure, and between entertainment expenditure and lottery expenditure. By contrast, the results from using OLS reveal that benevolent donations do not have a significant impact on lottery expenditure and that entertainment expenditure does not have a negative impact on lottery expenditure. Besides, expenditure on cigarettes and alcohol is found to have a positive impact on lottery expenditure, which coincides with the results of Balabanis (2002).

Fabrication of a microresonator-fiber assembly maintaining a high-quality factor by CO2 laser welding

We demonstrate fabrication of a microtoroid resonator of a high-quality (high-Q) factor using femtosecond laser three-dimensional (3D) micromachining. A fiber taper is reliably assembled to the microtoroid using CO2 laser welding. Specifically, we achieve a high Q-factor of 2.12*10^6 in the microresonator-fiber assembly by optimizing the contact position between the fiber taper and the microtoroid.Comment: 7 pages, 5 figure

Toward Robust Long Range Policy Transfer

Humans can master a new task within a few trials by drawing upon skills acquired through prior experience. To mimic this capability, hierarchical models combining primitive policies learned from prior tasks have been proposed. However, these methods fall short comparing to the human's range of transferability. We propose a method, which leverages the hierarchical structure to train the combination function and adapt the set of diverse primitive polices alternatively, to efficiently produce a range of complex behaviors on challenging new tasks. We also design two regularization terms to improve the diversity and utilization rate of the primitives in the pre-training phase. We demonstrate that our method outperforms other recent policy transfer methods by combining and adapting these reusable primitives in tasks with continuous action space. The experiment results further show that our approach provides a broader transferring range. The ablation study also shows the regularization terms are critical for long range policy transfer. Finally, we show that our method consistently outperforms other methods when the quality of the primitives varies.Comment: Accepted by AAAI 202

Analysis on Parameters of Regeneration Subsystem in Liquid Desiccant Dehumidification Systems

Along with the widely use in industries and lives, the dehumidification systems have consumed a large amount of energy. Fortunately, the application of liquid desiccant dehumidification system can greatly reduce the consumption of high-grade energies. To improve the advantages of liquid desiccant system compared with the conventional dehumidification system, one of the key measures is to increase the efficiency of the regeneration sub-system. In this study, models for the regeneration tower and counter-current heat exchanger, which are recognized by previous experiments, are employed and the corresponding VC++ computer program modules are used to describe the heat and mass transfer processes between the liquid desiccant solution and moist air in the regenerator and the heat transfer process in heat exchanger respectively. The orthogonal design is used to arrange the numerical experiment. The results are analyzed by the method of variance analysis to determine the relative significance of operating parameters and the interactions between them. The analysis on the influence factors shows that for the evaporation rate of water vapor in the regenerator, the important parameters are the inlet temperature and concentration of the solution, the mass flow ratio of dry air to dehydrated desiccant, and the NTU of the regenerator. For the regeneration efficiency, the mass flow ratio of dry air to dehydrated desiccant, the NTU of the regenerator and inlet temperature of solution are important parameters. There is no interaction that influences the evaporation rate of water vapor and the regeneration efficiency significantly

Data preprocessing for artificial neural network applications in prioritizing railroad projects â a practical experience in Taiwan

[[abstract]]Financial constraints necessitate the tradeoff among proposed railroad projects, so that the project priorities for implementation and budget allocation need to be determined by the ranking mechanisms in the government. At present, the Taiwan central government prioritizes funding allocations primarily using the analytic hierarchy process (AHP), a methodology that permits the synthesizing of subjective judgments systematically and logically into objective consensus. However, due to the coopetition and heterogeneity of railway projects, the proper priorities of railroad projects could not be always evaluated by the AHP. The decision makers prefer subjective judgments to referring to the AHP evaluation re- sults. This circumstance not only decreased the AHP advantages, but also raised the risk of the policies. A method to con- sider both objective measures and subjective judgments of project attributes can help reduce this problem. Accordingly, combining the AHP with the artificial neural network (ANN) methodologies would theoretically be a proper solution to bring a ranking predication model by creating the obscure relations between objective measures by the AHP and subjec- tive judgments. However, the inconsistency between the AHP evaluation and subjective judgments resulted in the inferior soundness of the AHP/ANN ranking forecast model. To overcome this problem, this study proposes the data prepro- cessing method (DPM) to calculate the correlation coefficient value using the subjective and objective ranking incidence matrixes; according to the correlation coefficient value, the consistency between the AHP rankings and subjective judg- ments of railroad projects can be evaluated and improved, so that the forecast accuracy of the AHP/ANN ranking forecast model can also be enhanced. Based on this concept, a practical railroad project ranking experience derived from the Insti- tute of Transportation of Taiwan is illustrated in this paper to reveal the feasibility of applying the DPM to the AHP/ANN ranking prediction model.[[notice]]補正完畢[[journaltype]]國外[[incitationindex]]SCI[[ispeerreviewed]]Y[[booktype]]電子版[[countrycodes]]LT