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  1. Article ; Online: A Study on the Trends of the Global Cruise Tourism Industry, Sustainable Development, and the Impacts of the COVID-19 Pandemic

    Li-Ying Lin / Chang-Ching Tsai / Jen-Yao Lee

    Sustainability, Vol 14, Iss 6890, p

    2022  Volume 6890

    Abstract: Stable financial operation is the essential factor for the sustainable development of the cruise tourism industry. The cruise industry was one of the fastest growing before the COVID-19 pandemic. The industry is capital intensive, has an enormous supply ... ...

    Abstract Stable financial operation is the essential factor for the sustainable development of the cruise tourism industry. The cruise industry was one of the fastest growing before the COVID-19 pandemic. The industry is capital intensive, has an enormous supply chain, serves to improve many ports-of-call economies, hires an immense quantity of people worldwide, and has a substantial economic contribution worldwide, especially in coastal countries or areas. COVID-19 has disrupted what had been an unending development of growth and success for the cruise industry. This study aims to analyze the financial performance of the worldwide cruise industry and realize the trends in the cruise tourism industry. The study examines the statistical data of the top three cruise companies that account for nearly 74.6–91.8% of the worldwide cruise tourism for 2015–2021. The financial analysis includes economic structure, solvency, operating ability, profitability, and financial leverage. We also analyze the economic indicators of the top three cruise companies with frequency analysis, correlation analysis, regression analysis, and the financial management risks of the top three cruise companies with the Z-Score Model. In addition, the study organizes and summarizes the impact of the COVID-19 pandemic on global cruise tourism. The study found that from mid-March 2020 until July 2021, the temporary suspension decreased passenger numbers, operating losses, and stock price losses. The research results confirm that the COVID-19 pandemic has caused the suspension of cruise ships worldwide. The break has led to a sharp drop in the number of cruise passengers, resulting in a significant decrease in operating income and profits of cruise companies, and the debt-to-assets ratio and leverage ratio have increased significantly. The excessive debt ratio will affect the sustainable operation of cruise companies and the sustainable development of the cruise industry. Because of the enormous impact and damage caused to the cruise industry by the ...
    Keywords cruise tourism industry ; sustainable development ; financial management ; Coronavirus disease (COVID-19) ; Environmental effects of industries and plants ; TD194-195 ; Renewable energy sources ; TJ807-830 ; Environmental sciences ; GE1-350
    Subject code 380
    Language English
    Publishing date 2022-06-01T00:00:00Z
    Publisher MDPI AG
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  2. Article ; Online: Analysis of Taiwan’s Mask Collection and Plan Evasion during the COVID-19 Pandemic

    Po-Sheng Ko / Jen-Yao Lee

    International Journal of Environmental Research and Public Health, Vol 18, Iss 4137, p

    2021  Volume 4137

    Abstract: This study established a two-stage dynamic game strategy to analyze how the planned quota and price of masks were set and why mask manufacturing firms on the national mask team (NMT) in Taiwan evaded the plan. Plan evasion occurred when the NMT decided ... ...

    Abstract This study established a two-stage dynamic game strategy to analyze how the planned quota and price of masks were set and why mask manufacturing firms on the national mask team (NMT) in Taiwan evaded the plan. Plan evasion occurred when the NMT decided to produce less than the quota set by the government, even though they were incentivized and able to produce more. Taiwan’s experience shows that through the collection of masks and the Name-Based Mask Rationing System, the people’s right to procure masks can be guaranteed; however, to promote market transaction efficiency, the government should adopt a lower quota for the collection of masks and allow firms to freely sell them in the market after they complete their plans. The self-interest of the government played a key role in inducing plan evasion.
    Keywords mask shortage ; planned quota ; plan evasion ; Medicine ; R
    Language English
    Publishing date 2021-04-01T00:00:00Z
    Publisher MDPI AG
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  3. Article ; Online: Asymmetric Hydroarylation of Enones via Nickel-Catalyzed 5-

    Qin, Xurong / Yao Lee, Marcus Wen / Zhou, Jianrong Steve

    Organic letters

    2019  Volume 21, Issue 15, Page(s) 5990–5994

    Abstract: A nickel-catalyzed reductive cyclization of enones affords a wide array of indanones in high enantiomeric induction. The reaction is featured with an unprecedented broad scope of substrates. The versatility of the new method is demonstrated in several ... ...

    Abstract A nickel-catalyzed reductive cyclization of enones affords a wide array of indanones in high enantiomeric induction. The reaction is featured with an unprecedented broad scope of substrates. The versatility of the new method is demonstrated in several short stereoselective syntheses of medically valuable (
    Language English
    Publishing date 2019-07-24
    Publishing country United States
    Document type Journal Article ; Research Support, Non-U.S. Gov't
    ISSN 1523-7052
    ISSN (online) 1523-7052
    DOI 10.1021/acs.orglett.9b02130
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  4. Article ; Online: Induction Motor Fault Classification Based on FCBF-PSO Feature Selection Method

    Chun-Yao Lee / Wen-Cheng Lin

    Applied Sciences, Vol 10, Iss 5383, p

    2020  Volume 5383

    Abstract: This study proposes a fast correlation-based filter with particle-swarm optimization method. In FCBF–PSO, the weights of the features selected by the fast correlation-based filter are optimized and combined with backpropagation neural network as a ... ...

    Abstract This study proposes a fast correlation-based filter with particle-swarm optimization method. In FCBF–PSO, the weights of the features selected by the fast correlation-based filter are optimized and combined with backpropagation neural network as a classifier to identify the faults of induction motors. Three significant parts were applied to support the FCBF–PSO. First, Hilbert–Huang transforms were used to analyze the current signals of motor normal, bearing damage, broken rotor bars and short circuits in stator windings. Second, ReliefF, symmetrical uncertainty and FCBF three feature-selection methods were applied to select the important features after the feature was captured. Moreover, the accuracy comparison was performed. Third, particle-swarm optimization (PSO) was combined to optimize the selected feature weights which were used to obtain the best solution. The results showed excellent performance of the FCBF–PSO for the induction motor fault classification such as had fewer feature numbers and better identification ability. In addition, the analyzed of the induction motor fault in this study was applied with the different operating environments, namely, SNR = 40 dB, SNR = 30 dB and SNR = 20 dB. The FCBF–PSO proposed by this research could also get the higher accuracy than typical feature-selection methods of ReliefF, SU and FCBF.
    Keywords fast correlation-based filter (FCBF) ; back propagation neural network (BPNN) ; Hilbert–Huang transform (HHT) ; motor failure ; ReliefF ; symmetrical uncertainty (SU) ; Technology ; T ; Engineering (General). Civil engineering (General) ; TA1-2040 ; Biology (General) ; QH301-705.5 ; Physics ; QC1-999 ; Chemistry ; QD1-999
    Subject code 620
    Language English
    Publishing date 2020-08-01T00:00:00Z
    Publisher MDPI AG
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  5. Article ; Online: Establish Induction Motor Fault Diagnosis System Based on Feature Selection Approaches with MRA

    Chun-Yao Lee / Meng-Syun Wen

    Processes, Vol 8, Iss 1055, p

    2020  Volume 1055

    Abstract: This paper proposes a feature selection (FS) approach, namely, correlation and fitness value-based feature selection (CFFS). CFFS is an improvement feature selection approach of correlation-based feature selection (CFS) for the common failure cases of ... ...

    Abstract This paper proposes a feature selection (FS) approach, namely, correlation and fitness value-based feature selection (CFFS). CFFS is an improvement feature selection approach of correlation-based feature selection (CFS) for the common failure cases of the induction motor. CFFS establishes the induction motor fault detection (FD) system with artificial neural network (ANN). This study analyzes the current signal of the induction motor with multiresolution analysis (MRA), extracts the features, and uses feature selection approaches (ReliefF, CFS, and CFFS) to reduce the number of features and maintain the accuracy of the induction motor fault detection system. Finally, the induction motor fault detection system is trained by the feature selection approaches selected features. The best induction motor fault detection system will be established through the comparison of the efficiency of these FS approaches.
    Keywords fault detection ; feature selection ; multiresolution analysis ; correlation-based feature selection ; correlation and fitness value-based feature selection ; artificial neural network ; Chemical technology ; TP1-1185 ; Chemistry ; QD1-999
    Subject code 004
    Language English
    Publishing date 2020-08-01T00:00:00Z
    Publisher MDPI AG
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  6. Article ; Online: Motor Fault Detection Using Wavelet Transform and Improved PSO-BP Neural Network

    Chun-Yao Lee / Yi-Hsin Cheng

    Processes, Vol 8, Iss 1322, p

    2020  Volume 1322

    Abstract: This paper proposes a motor fault detection method based on wavelet transform (WT) and improved PSO-BP neural network which is combined with improved particle swarm optimization (PSO) and a back propagation (BP) neural network with linearly increasing ... ...

    Abstract This paper proposes a motor fault detection method based on wavelet transform (WT) and improved PSO-BP neural network which is combined with improved particle swarm optimization (PSO) and a back propagation (BP) neural network with linearly increasing inertia weight. First, this research used WT to analyze the current signals of the healthy motor, bearing damage motor, stator winding inter-turn short circuit motor, and broken rotor bar motor. Second, features after completing the signal analysis were extracted, and three types of classifiers were used to classify. The results show that the improved PSO-BP neural network can effectively detect the cause of failure. In addition, in order to simulate the actual operating environment of the motor, this study added white noise with signal noise ratios of 30 dB, 25 dB, and 20 dB to verify that this model has a better anti-noise ability.
    Keywords induction motors ; back propagation neural network ; fault detection ; particle swarm optimization wavelet transform ; Chemical technology ; TP1-1185 ; Chemistry ; QD1-999
    Subject code 629
    Language English
    Publishing date 2020-10-01T00:00:00Z
    Publisher MDPI AG
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  7. Article ; Online: The consumer price index prediction using machine learning approaches

    Tien-Thinh Nguyen / Hong-Giang Nguyen / Jen-Yao Lee / Yu-Lin Wang / Chien-Shu Tsai

    Heliyon, Vol 9, Iss 10, Pp e20730- (2023)

    Evidence from the United States

    2023  

    Abstract: The consumer price index (CPI) is one of the most important macroeconomic indicators for determining inflation, and accurate predictions of CPI changes are important for a country's economic development. This study uses multivariate linear regression ( ... ...

    Abstract The consumer price index (CPI) is one of the most important macroeconomic indicators for determining inflation, and accurate predictions of CPI changes are important for a country's economic development. This study uses multivariate linear regression (MLR), support vector regression (SVR), autoregressive distributed lag (ARDL), and multivariate adaptive regression splines (MARS) to predict the CPI of the United States. Data from January 2017 to February 2022 were randomly selected and divided into two stages: 80 % for training and 20% for testing. The US CPI was modeled for the observed period and relied on a mix of elements, including crude oil price, world gold price, and federal fund effective rate. Evaluation metrics—mean absolute percentage value, mean absolute error, root mean square error, R-squared, and correlation of determination—were employed to estimate forecasted values. The MLR, SVR, ARDL, and MARS models attained high accuracy parameters, while the MARS algorithm generated higher accuracy in US CPI forecasts than the others in the testing phase. These outputs could support the US government in overseeing economic policies, sectors, and social security, thereby boosting national economic development.
    Keywords Consumer price index ; Forecasting ; Multivariate linear regression model ; Support vector regression model ; Autoregressive distributed lag model ; Multivariate adaptive regression splines model ; Science (General) ; Q1-390 ; Social sciences (General) ; H1-99
    Subject code 338
    Language English
    Publishing date 2023-10-01T00:00:00Z
    Publisher Elsevier
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  8. Article ; Online: Priority Weights for Predicting the Success of Hotel Sustainable Business Models

    Tien-Chin Wang / Chin-Ying Huang / Shu-Li Huang / Jen-Yao Lee

    Sustainability, Vol 13, Iss 14032, p

    2021  Volume 14032

    Abstract: This study proposes the use of consistent fuzzy preference relations to evaluate the structure of hotel sustainable business model (HSBM) dimensions and the corresponding hierarchy of evaluation indicators, and predict the overall probability of success. ...

    Abstract This study proposes the use of consistent fuzzy preference relations to evaluate the structure of hotel sustainable business model (HSBM) dimensions and the corresponding hierarchy of evaluation indicators, and predict the overall probability of success. As fuzzy preference relations require, a group of hotel professionals in Taiwan was asked to process pairwise comparisons using linguistic variables to determine the weights of dimensions and indicators. According to the results, finances were found to be the most important dimension, followed by human capital. The number of local cultural events in the hotel was identified as the most important indicator. The predictive values revealed the possibility for successful HSBM implementation, shedding light on the vision of sustainability for the hotel industry. The results of the present study contribute to the literature on sustainability by determining the importance and weights of dimensions and indicators for hotel business models, providing an example of the use of this strategic tool in generating and modifying sustainable business models for the hotel industry.
    Keywords sustainable business model ; consistent fuzzy preference relations ; hotel industry ; sustainability ; Environmental effects of industries and plants ; TD194-195 ; Renewable energy sources ; TJ807-830 ; Environmental sciences ; GE1-350
    Subject code 910
    Language English
    Publishing date 2021-12-01T00:00:00Z
    Publisher MDPI AG
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  9. Article ; Online: An alarm system of carbamazepine‐induced toxic effects highly associated with HLA‐B*1502 allele

    Ying‐Hao Lu / Wen‐Chin Hsu / Li‐Yao Lee / Chen‐Chun Kuo

    Kaohsiung Journal of Medical Sciences, Vol 37, Iss 2, Pp 156-

    2021  Volume 157

    Keywords Medicine (General) ; R5-920
    Language English
    Publishing date 2021-02-01T00:00:00Z
    Publisher Wiley
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  10. Article ; Online: Inward Foreign Direct Investment and Trade Openness in Vietnam

    Jen-Yao Lee / Ya-Chuan Hsiao / Ngochien Bui / Tien-Thinh Nguyen

    Economies, Vol 9, Iss 120, p

    A Nonlinear Autoregressive Distributed Lag Approach

    2021  Volume 120

    Abstract: This study aims to examine the asymmetric relationship between trade openness and FDI (foreign direct investment) inflows to Vietnam by using NARDL (nonlinear autoregressive distributed lag) during the period from 1997 to 2019. Our findings show that the ...

    Abstract This study aims to examine the asymmetric relationship between trade openness and FDI (foreign direct investment) inflows to Vietnam by using NARDL (nonlinear autoregressive distributed lag) during the period from 1997 to 2019. Our findings show that the influence of FDI on trade openness is asymmetric in the short-run and long-run. But the influence of trade openness on FDI is symmetric in the short-run and asymmetric in the long run.
    Keywords ARDL model ; NARDL model ; foreign direct investment ; trade openness ; tax rate ; political stability ; Economics as a science ; HB71-74
    Language English
    Publishing date 2021-08-01T00:00:00Z
    Publisher MDPI AG
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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