How generativity affects organic dining intention: Case study of Shanghai.

With people's concerns about the environment growing, the demand for organic food has increased. However, few studies have focused on organic dining intention. Therefore, this study examined generativity, which is defined as the direction and care for the growth of future generations through self-expanding forms, and its influence on attitude toward organic food, environment concern and dining intention.

Perception Research of Artificial Intelligence in Environmental Public Health Physiotherapy Nursing for the Elderly.

This perceptual study focuses on developing artificial intelligence for elderly care design. It analyses and discusses the role of artificial intelligence in elderly care and its application to physiotherapy care. Artificial intelligence, as an emerging disruptive technology, is releasing the enormous energy accumulated in the technological and industrial revolutions, profoundly transforming how humans produce, live, and think about the world.

The relationship between phubbing and green hotel consumption: the roles of need for uniqueness, social value perception, and gender difference.

Green hotel serves as an effective way of achieving sustainable development in hospitality industry, few studies have tested the association between social relationships and green hotel consumption. Since the emerging of phubbing has changed social interaction norm, the association between phubbing and green hotel consumption remains unknown. Drawing upon optimal distinctiveness theory (ODT), the present study aims to address this research gap by examining the relationship between peer phubbing and green hotel booking intention.

Ameliorated New Media Literacy Model Based on an Esthetic Model: The Ability of a College Student Audience to Enter the Field of Digital Art.

In the current digital environment, people can visit every corner of the world without leaving their homes. New media technology compresses distance and time, but it also subverts the traditional mode of audience presence. Many traditional, offline content expression modes are also moving toward the digital field, and digital art is among them.

Research on the Influence of DNN-Based Cross-Media Data Analysis on College Students' New Media Literacy.

New media has gradually become the mainstream media that college students rely on, and new media has also brought about subversive changes and has become an essential medium for college students to receive and disseminate information, such as learning, interpersonal communication, and entertainment. Young college students have become the most enthusiastic recipients and users of new media. College students need to have the ability to recognize, understand, and criticize new media.

Synthesis and Luminescence Properties of Eu-Doped SrMgSiO Blue Light-Emitting Phosphor for Application in Near-Ultraviolet Excitable White Light-Emitting Diodes.

In this study, [SrEu]MgSiO phosphors were sintered at 1200-1400 °C for 1-5 h by using the solid-state reaction method. The crystallinity and morphology of these phosphors were characterized through X-ray diffraction analysis and field-emission scanning electron microscopy, respectively, to determine their luminescence. The photoluminescence properties, including the excitation and emission properties, of the prepared phosphors were investigated through fluorescence spectrophotometry.

The impact of high economic growth and technology advancement on extensive energy production in China: evidence using NARDL model.

High energy production is the global requirement that is the demand of high economic growth in the country and needs regulators and recent researchers' emphasis. Therefore, the current study examines the impact of economic factors such as gross domestic product (GDP), national income, employment rate, foreign direct investment (FDI), and inflation and technological advancement on energy production in China. The present article has used the secondary data extracted from World Development Indicators (WDIs) from 1976 to 2020.

Diamond Model of Green Commitment and Low-Carbon Travel Motivation, Constraint, and Intention.

Although consumers generally accept and care about environmental issues, consumers have not adjusted their behavior accordingly. Based on the diamond model theory, this study proposes and tests the direct impact of personal green commitments on low-carbon travel motivation and constraint, and the possibility of subsequent low-carbon travel intention. According to the results of 358 valid questionnaire surveys, this study shows that green commitments positively affect the low-carbon travel motivation and intention, while negatively affecting the low-carbon travel constraint.

Unreferenced English articles' translation quality-oriented automatic evaluation technology using sparse autoencoder under the background of deep learning.

Currently, both manual and automatic evaluation technology can evaluate the translation quality of unreferenced English articles, playing a particular role in detecting translation results. Still, their deficiency is the lack of a close or noticeable relationship between evaluation time and evaluation theory. Thereupon, to realize the automatic Translation Quality Assessment (TQA) of unreferenced English articles, this paper proposes an automatic TQA model based on Sparse AutoEncoder (SAE) under the background of Deep Learning (DL).

Emotion Recognition of Online Education Learners by Convolutional Neural Networks.

At present, the facial expression recognition model in video communication has problems such as weak network generalization ability and complex model structure, which leads to a large amount of computation. Firstly, the Inception architecture is adopted as a design philosophy. The Visual Geometry Group Network (VGGNet) model is improved.

The Role of Relational Embeddedness in Enhancing Absorptive Capacity and Relational Performance of Internationalized SMEs: Evidence From Mainland China.

The social network in the organizational learning process is a critical knowledge source to realize superior performance. The purpose of this study is to examine the relationship between relational memory, relational embeddedness, and absorptive capacity, and their impact on the relational performance of small and middle enterprises (SMEs). This study empirically verifies the research framework from 223 Chinese internationalized SMEs.

Application of Adaptive Neural Network Algorithm Model in English Text Analysis.

Based on the existing optimization neural network algorithm, this paper introduces a simple and computationally efficient adaptive mechanism (adaptive exponential decay rate). By applying the adaptive mechanism to the Adadelta algorithm, it can be seen that AEDR-Adadelta acquires the learning rate dynamically and adaptively. At the same time, by proposing an adaptive exponential decay rate, the number and method of configuring hyperparameters can be reduced, and different learning rates can be effectively obtained for different parameters.

Investigations of a Statistical and Analytical Method to Find the Relationship between the Morphological and Optical Properties of ZnO Nanoflower Arrays.

In this study, a sapphire substrate with a patterned concave structure was used to prepare ZnO film/A-B glue, and the ZnO film/A-B glue with a patterned convex matrix was transferred onto a silicon wafer using the lift-off technology as the seed layer. Then, the hydrothermal method with different Zn(CHCOO) and CHN concentrations as precursors was used to synthesize ZnO nanoflower arrays on the patterned convex ZnO seed layer. XRD pattern, FESEM, FIB, and photoluminescence (PL) spectrometry were employed to observe and analyze the properties of the synthesized ZnO nanoflower arrays.

Construction of an Artificial Intelligence Writing Model for English Based on Fusion Neural Network Model.

This paper presents an in-depth study and analysis of the model of English writing using artificial intelligence algorithms of neural networks. Based on word vectors, the unsupervised disambiguation, and clustering of multimedia contexts extracted from massive online videos, the disambiguation accuracy reaches over 0.7, and the resulting small-scale multimedia context set can cover up to 90% of vocabulary learning tasks; user experiments show that the multimedia context learning system based on this method can improve the effectiveness and experience of ESL vocabulary learning, as well as the long-term word sense memory of learners.

A Study of DNN-Based Media Literacy and Distance Education Management System in the Context of Participatory Culture.

Through an in-depth study and analysis of the integration of media literacy with distance education management using the DNN algorithm in the context of participatory culture, and the design of a distance education management system for application in actual teaching, the word embedding model is used to embed the ratings and tags, respectively; then, the self-encoder is used to extract textual features for item tags, while DNN is used to extract features for user tagging behaviors; finally, the fully connected neural network is used to predict ratings for the fused user and item features. The experimental results show that the optimized recommendation model effectively reduces the user rating prediction error while alleviating the cold start problem. A blockchain-based learning platform is designed.

Invading the dynamics of economic growth and CO emission: panel data error correction model (ECM) approach.

This paper examined the impact of green finance and financial technology on economic growth by utilizing statistics between 1990 to 2000 gathered from 50 US states and regions. A two-step generalized GMM was used to analyze the link between green finance, financial technology, and continued economic growth using panel regression analysis. We found that the US green finance sector had grown significantly and such growth was accompanied by an increase in the usage of non-combustible energy and an advancement in the green finance economic forum.

A Multicriteria English Teaching Decision Model Based on Deep Learning.

In any stage of the teaching process, the teaching behavior depends on the decision of teachers. For English teachers, the English teaching decision level directly determines the course quality and the mining of learner potential. The existing studies only focus on a single teaching stage and involve one decision maker.

Low-Carbon Travel Motivation and Constraint: Scales Development and Validation.

Low-carbon travel has emerged as a topic of interest in tourism and academia. Studies have offered reasons tourists may engage in low-carbon travel; however, these explanations are scattered throughout the literature and have yet to be integrated into low-carbon travel motivation and constraint constructs. This study develops a low-carbon travel motivation scale (LCTMS) and a low-carbon travel constraint scale (LCTCS).

How green finance and financial development promote green economic growth: deployment of clean energy sources in South Asia.

A major issue for governments in the past few decades has been environmental deterioration caused by economic activity. Researchers are increasingly interested in the factors that contribute to environmental deterioration. This research fills the empirical gaps by looking at the influence of carbon footprints of growth and R&D investment on green finance development of renewable energy.

Effects of tourism and eco-innovation on environmental quality in selected ASEAN countries.

Environmental issues have gained the attention of regulators and researchers worldwide. This present study empirically examines the validation of the environmental Kuznets curve (EKC) in the selected ASEAN economies for the period 1995-2018 in the presence of eco-innovations and tourism. This study assesses the short-run and long-run relationship between carbon dioxide emission, tourism, eco-innovations, and economic growth in ASEAN countries.

Study on the university students' satisfaction of the wisdom tree massive open online course platform based on parameter optimization intelligent algorithm.

Introduction: Curriculum learning through the wisdom tree massive open online course platform not only gets rid of the limitations of specialty, school and region, eliminates the limitations of time and space in traditional teaching, but also effectively solves the problem of educational equity.

Objectives: This paper proposes an intelligent algorithm combining decision tree, support vector machine, and simulated annealing to obtain the best classification accuracy and decision rules for university students' satisfaction with the wisdom tree massive open online course platform.

Methods: This study takes the university students in Fuzhou city information management department as the survey object, and adopts the electronic questionnaire survey method.

Role of tourism development in environmental degradation: A step towards emission reduction.

Globally, the interaction and vulnerability of tourism and climate change have recently been in focus. This study examines how carbon dioxide emissions respond to changes in the tourism development. Panel data from 2000 to 2017 for 70 countries are analyzed using spatial econometric method to investigate the spatial spillover effect of tourism development on environmental pollution.

Dynamic nexus between transportation, urbanization, economic growth and environmental pollution in ASEAN countries: does environmental regulations matter?

Prior studies on environmental standards have highlighted the significance of urbanization and transportation in affecting environmental sustainability worldwide. As the empirical and theoretical debates are still unresolved and divisive, the argument of whether urbanization, transportation and economic growth in Association of Southeast Asian Nations (ASEAN) countries cause greenhouse gas (GHG) emissions remains unclear. This study aim is to examine dynamic linkage between transportation, urbanization, economic growth and GHG emissions, as well as the impact of environmental regulations on GHG emission reduction in ASEAN countries over the years 1995-2018.

Discussion of Teaching With Multiple Intelligences to Corporate Employees' Learning Achievement and Learning Motivation.

The development of multiple intelligences used to focus on kindergartens and elementary schools as educational experts and officials considered that the development of students' multiple intelligences should be cultivated from childhood and slowly promoted to other levels. Nevertheless, the framework of multiple intelligences should not be simply promoted in kindergartens and elementary schools, but was also suitable in high schools, universities, and even graduate schools or in-service training. Taking employees in Southern Taiwan Science Park as the research subjects, total 314 employees in high-tech industry are preceded the 16-week (3 h per week for total 48 h) experimental teaching research.