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This study aims to explore the success factors of tourism performing arts (TPA) programs by analyzing a large data set of online reviews.

A total of 195,230 reviews from Ctrip.com were collected and preprocessed. A deep learning method was leveraged to estimate the similarity between words. Then, regression analysis was conducted to determine success factors.

This study extracted four positive and two negative factors affecting tourist satisfaction with tourism performance arts. The results demonstrate that the tourists paid the most attention to the traditional Chinese cultural aspects, audiovisual effects and the actors’ performing enthusiasm.

Despite this study’s large data set, the focused was only on Chinese reviews. It would be useful and interesting to compare the success factors of tourism performance arts programs offered in different countries.

The study findings can contribute to the development of TPA programs to attract tourists to travel destinations.

This study demonstrates that analyzing online reviews of TPA through text mining technology is an effective method of understanding tourist satisfaction.

在线点评分析探析旅游演艺成功因素

本研究旨在通过分析大型在线评论数据集来探索旅游表演艺术项目的成功因素。

共收集和预处理来自携程网的 195,230 条评论。利用深度学习方法来估计单词之间的相似性。然后, 进行回归分析以确定成功因素。

本研究提取了影响游客对旅游表演艺术满意度的四个积极因素和两个消极因素。结果表明, 游客最关注中国传统文化方面、视听效果和演员的表演热情。

尽管我们的数据集很大, 但它只关注中文评论。比较不同国家提供的旅游表演艺术项目的成功因素将是有用和有趣的未来研究方向。

研究结果有助于发展旅游表演艺术项目, 以吸引游客前往旅游目的地。

研究表明, 通过文本挖掘技术分析旅游表演艺术的在线评论是了解游客满意度的有效方法。

Under the constraints of given passenger service level and coupling travel demand with train departure time, this study optimizes the train operational plan in an urban rail corridor to minimize the numbers of train trips and rolling stocks considering the time-varying demand of urban rail passenger flow.

The authors optimize the train operational plan in a special network layout, i.e. an urban rail corridor with dead-end terminal yard, by decomposing it into two sub-problems: train timetable optimization and rolling stock circulation optimization. As for train timetable optimization, the authors propose a schedule-based passenger flow assignment method, construct the corresponding timetabling optimization model and design the bi-directional coordinated sequential optimization algorithm. For the optimization of rolling stock circulation, the authors construct the corresponding optimization assignment model and adopt the Hungary algorithm for solving the model.

The case study shows that the train operational plan developed by the study's approach meets requirements on the passenger service quality and reduces the operational cost to the maximum by minimizing the numbers of train trips and rolling stocks.

The example verifies the efficiency of the model and algorithm.

This paper aims to propose a medium-term forecast model for the daily passenger volume of High Speed Railway (HSR) systems to predict the daily the Origin-Destination (OD) daily volume for multiple consecutive days (e.g. 120 days).

By analyzing the characteristics of the historical data on daily passenger volume of HSR systems, the date and holiday labels were designed with determined value ranges. In accordance to the autoregressive characteristics of the daily passenger volume of HSR, the Double Layer Parallel Wavelet Neural Network (DLP-WNN) model suitable for the medium-term (about 120 d) forecast of the daily passenger volume of HSR was established. The DLP-WNN model obtains the daily forecast result by weighed summation of the daily output values of the two subnets. Subnet 1 reflects the overall trend of daily passenger volumes in the recent period, and subnet 2 the daily fluctuation of the daily passenger volume to ensure the accuracy of medium-term forecast.

According to the example application, in which the DLP-WNN model was used for the medium-term forecast of the daily passenger volumes for 120 days for typical O-D pairs at 4 different distances, the average absolute percentage error is 7%-12%, obviously lower than the results measured by the Back Propagation (BP) neural network, the ELM (extreme learning machine), the ELMAN neural network, the GRNN (generalized regression neural network) and the VMD-GA-BP. The DLP-WNN model was verified to be suitable for the medium-term forecast of the daily passenger volume of HSR.

This study proposed a Double Layer Parallel structure forecast model for medium-term daily passenger volume (about 120 days) of HSR systems by using the date and holiday labels and Wavelet Neural Network. The predict results are important input data for supporting the line planning, scheduling and other decisions in operation and management in HSR systems.

The fractal and fractional calculus have obtained considerable attention in the electrical and electronic engineering since they can model many complex phenomena that the traditional integer-order calculus cannot. The purpose of this paper is to develop a new fractional pulse narrowing nonlinear transmission lines model within the local fractional calculus for the first time and derive a novel method, namely, the direct mapping method, to seek for the nondifferentiable (ND) exact solutions.

By defining some special functions via the Mittag–Leffler function on the Cantor sets, a novel approach, namely, the direct mapping method is derived via constructing a group of the nonlinear local fractional ordinary differential equations. With the aid of the direct mapping method, four groups of the ND exact solutions are obtained in just one step. The dynamic behaviors of the ND exact solutions on the Cantor sets are also described through the 3D graphical illustration.

It is found that the proposed method is simple but effective and can construct four sets of the ND exact solutions in just one step. In addition, one of the ND exact solutions becomes the exact solution of the classic pulse narrowing nonlinear transmission lines model for the special case 9 = 1, which strongly proves the correctness and effectiveness of the method. The ideas in the paper can be used to study the other fractal partial differential equations (PDEs) within the local fractional derivative (LFD) arising in electrical and electronic engineering.

The fractional pulse narrowing nonlinear transmission lines model within the LFD is proposed for the first time in this paper. The proposed method in the work can be used to study the other fractal PDEs arising in electrical and electronic engineering. The findings in this work are expected to shed a light on the study of the fractal PDEs arising in electrical and electronic engineering.

This paper aims to identify computational thinking (CT) in 4th to 6th grade students in the context of project-based problem-solving while engaged in an after-school program.

This case study approach was selected due to its suitability for answering “how” or “why” questions about real-world phenomena within a set context (Creswell and Poth, 2018; Yin, 2018). This was an appropriate fit given the context of an after-school program and the research question asked how to identify learners’ demonstrated CT through project-based learning hands-on activities and problem-solving in a naturalistic environment.

Results show that heuristics, algorithms and conditional logic were observed more than other components of CT such as data collection, simulations and modeling. Descriptions of common activities in a naturalistic learning environment are presented to illustrate how the students practiced CT over time, which could help readers develop an understanding of CT in conjunction with hands-on problem-solving activities in elementary students. Identifying and classifying CT in this study focused on students’ learning process.

This study contributes to the challenging field of evaluating CT while focusing on observable behaviors and problem-solving activities with various degrees of teacher’s facilitation instead of final artifacts. Implications for researchers and educators interested in integrating CT in K-12 learning and its assessment are discussed.

The purpose of this paper is to model the aircraft-cargo’s coupling dynamics during ultra-low altitude heavy cargo airdrop and to design the aircraft’s robust flight control law counteracting its aerodynamic coefficients perturbation induced by ground effect and the disturbance from the sliding cargo inside.

Aircraft-cargo system coupling dynamics model in vertical plane is derived using the Kane method. Trimmed point is calculated when the cargo fixed in the cabin and then the approximate linearized motion equation of the aircraft upon it is derived. The robust stability and robust H_∞ optimal disturbance restraint flight control law are designed countering the aircraft’s aerodynamic coefficients perturbation and the disturbance moment, respectively.

Numerical simulation shows the effectiveness of the proposed control law with elevator deflection as a unique control input.

The model derived and control law designed in the paper can be applied to heavy cargo airdrop integrated design and relevant parameters choice.

The dynamics model derived is closed, namely, the model can be called in numerical simulation free of assuming the values of parachute’s extraction force or cargo’s relative sliding acceleration or velocity as seen in many literatures. The modeling is simplified using Kane method rather than Newton’s laws. The robust control law proposed is effective in guaranteeing the aircraft’s flight stability and disturbance restraint performance in the presence of aerodynamic coefficients perturbation.

The relationship between debt and happiness is an emerging research topic with significant implications for both theory and practice in economics and business. In China, where the consumer credit market is at an early stage of development, the topic remains under-investigated and the evidence on the debt–well-being link is scarce. The purpose of this study is to examine the association between debt holding and happiness and the moderating role of income in it.

Data used in the study were from three waves (2013, 2015 and 2017) of the China Household Finance Survey. Fixed-effect regressions on panel data were used for data analyses.

The results show that any type of debt holding is negatively associated with happiness. Among seven specific types of debts, four types show negative associations with happiness, which in the order from higher to lower associations, are medical, education, other and housing debt. In addition, negative associations between debt holding and happiness vary among income groups. The results suggest that any debt holding potentially decreases happiness for low- and middle-income consumers only. In addition, holdings of three specific types of debts (medical, education and housing debt) may decrease happiness for both low- and middle-income consumers, and holding two types of debts (business and other debt) may decrease happiness for middle-income consumers only.

Data used in this study originate from one country only. It limits the generalizability of findings to other countries with different institutional backgrounds and different socio-economic characteristics of populations. The results have implications for researchers who study consumer debt behavior and business practitioners who do businesses with Chinese companies and consumers.

China is an emerging economy that is at the early stage of credit market development. The results of this study provide helpful information and insights for business practitioners to explore credit markets and serve credit product clients with various income levels in China.

The results of this study are informative for public policies. When introducing credit market-related policies, policymakers should pay attention to people's happiness and to differential welfare effects of holdings of different types of debts and among consumers with various levels of incomes.

Unique contributions of this study include using data from the most recently available waves of the China Household Finance Survey (2013, 2015 and 2017) to study the associations between debt holding and happiness. In addition, the findings of this study enrich the literature of debt and happiness by adding evidence from China, the largest emerging economy in the world, which is helpful for future theory building and business practice on the relationship between debt holding and happiness.

Bedroom Feng Shui practices have been criticized as myth over the years but in fact having its scientific origin that is not purely superstitious. This paper aims to examine whether the architects' design practice for bedroom interior arrangement is concurring with the recommended bedroom Feng Shui practices. The study has successfully interviewed 16 architects from diverse backgrounds to avoid bias, seeking their design perspectives in bedroom interior configuration. Subsequently, the interviewees submitted sketches of ideal bedroom layout based on their expertise, with pre-set requirements. Data from semi-structured interviews were analyzed using mixed method approach. In agreement with our expectations, majority of the interviewees have matching thoughts that “bed arrangement” is the primary consideration in bedroom interior configuration. Most of the design outputs were highly attached to favorable Feng Shui conditions. The overall findings implied that bedroom Feng Shui is not merely superstitious but most components are practical design references for architects from diverse backgrounds.

The purpose of this paper is to provide the historical background of genealogical records and analyze the value of Chinese genealogical research through the study of names and genealogical resources.

The paper examines the historical evolution and value of Chinese genealogical records, with the focus on researching the Islamic Chinese names used by the people living in Guilin. The highlight of this paper includes the analysis and evolution of the Islamic Chinese names commonly adopted by the local people in Guilin. It concludes with the recommendations on emphasizing and making the best use of genealogical records to enhance the research value of Chinese overseas studies.

The paper covers the history of Islam and describes how the religion was introduced into China, as well as Muslims' ethnicity and identity. It also places focus on the importance of building a research collection in Asian history and Chinese genealogy.

This research study has a strong subject focus on Chinese genealogy, Asian history, and Islamic Chinese surnames. It is a narrow field that few researchers have delved into.

The results of this study will assist students, researchers, and the general public in tracing the origin of their surnames and developing their interest in the social and historical value of Chinese local history and genealogies.

The study of Chinese surnames is, by itself, a particular field for researching the social and political implications of contemporary Chinese society during the time the family members lived.

Very little research has been done in the area of Chinese local history and genealogy. The paper would be of value to researchers such as historians, sociologists, ethnologists and archaeologists, as well as students and anyone interested in researching a surname origin, its history and evolution.

Despite big data analytics capability (BDAC) has received extensive attention, how and under what conditions BDAC influences green supply chain integration (GSCI) remains unclear. This study draws on organizational information processing theory to examine the mediating effect of supply chain visibility in the BDAC–GSCI link and the moderating effects of flexibility- and control-oriented culture.

The authors examined the research model using two-waved survey data gathered from 317 Chinese firms. The authors employed hierarchical regression analysis and bootstrapping method to test hypotheses and assessed the robust of theoretical model using structural model.

The authors found that BDAC facilitates all three dimensions of GSCI. Supply visibility mediates the relationship between BDAC and all three dimensions of GSCI, whereas demand visibility only mediates the positive effects of BDAC on green internal and customer integration. In addition, control-oriented culture strengthens the positive impacts of BDAC on supply and demand visibility, while the moderating effects of flexibility-oriented culture are insignificant.

This research contributes to opening the “black box” of how BDAC affects GSCI and provides novel guidelines for firms enhancing the degree of GSCI.