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In many instances, the data exhibits periodic and trend characteristics. However, indices like the Digital Economy Development Index (DEDI), which pertains to science, technology, policy and economy, may occasionally display erratic behaviors due to external influences. Thus, to address the unique attributes of the digital economy, this study integrates the principle of information prioritization with nonlinear processing techniques to accurately forecast rapid and anomalous data.

The proposed method utilizes the new information priority GM(1,1) model alongside an optimized BP neural network model achieved through the gradient descent technique (GD-BP). Initially, the provincial Digital Economic Development Index (DEDI) is derived using the entropy weight approach. Subsequently, the original GM(1,1) time response equation undergoes alteration of the initial value, and the time parameter is fine-tuned using Particle Swarm Optimization (PSO). Next, the GD-BP model addresses the residual error. Ultimately, the prediction outcome of the grey combination forecasting model (GCFM) is derived by merging the findings from both the NIPGM(1,1) model and the GD-BP approach.

Using the DEDI of Jiangsu Province as a case study, researchers demonstrate the effectiveness of the grey combination forecasting model. This model achieves a mean absolute percentage error of 0.33%, outperforming other forecasting methods.

First of all, due to the limited data access, it is impossible to obtain a more comprehensive dataset related to the DEDI of Jiangsu Province. Secondly, according to the test results of the GCFM from 2011 to 2020 and the forecasting results from 2021 to 2023, it can be seen that the results of the GCFM are consistent with the actual development situation, but it cannot guarantee the correctness of the long-term forecasting, so the combination forecasting model is only suitable for short-term forecasting.

This article proposes a grey combination prediction model based on the principles of new information priority and nonlinear processing.

This paper aims to propose that the extent to which activating self-identity increases resource-saving behavior varies across these three levels of self-identities. In particular, the authors hypothesize that activating relational or collective self-identity increases saving behavior more than activating individual self-identity does. Moreover, activating relational self-identity has a stronger impact on workplace saving behavior than activating collective self-identity does. In addition, the authors suggest that prosocial motive mediates the relationship between the three levels of self-identity and saving behavior.

Workplace saving behavior such as office supply savings could help save organizational resources and build more environmentally conscious organizations. Drawing from self-identity theory, the authors examine the influences of three types of self-identities (i.e. individual, relational and collective self-identities) on workplace resource-saving behaviors.

The results obtained from a field experiment conducted in a Chinese company and an online vignette study generally support the proposed hypotheses. The authors also discuss the theoretical and practical implications of the findings.

The authors contribute to the literature on saving behavior in organizations by studying an individual-level predictor from the perspective of self-identity and the research on self-identity and saving behavior by testing the mediating role played by prosocial motive. Based on the findings, the authors also propose some human resource policies to increase workplace saving behavior.

This study aims to build a research model from the perspectives of knowledge hiding and idea implementation to examine what factors influence idea implementation and the cross-level moderating role of team territory climate.

Data were collected from universities, 52 (R&D) teams in China via a two-wave survey. The final sample contained 209 team members and their immediate supervisors. Hierarchical linear modeling was used to test hypotheses.

The results indicated that individuals’ knowledge-hiding behavior had a significantly negative impact on idea implementation and creative process engagement, which played a mediating role. Team territorial climate played a cross-level moderating role between knowledge hiding and idea implementation. If team territorial climate was at a high level, then the negative connection between knowledge hiding and idea implementation would be weaker.

Under the perspective of territorial behavior in Chinese cultural, it can help to distinguish territorial behavior and be preventive at individual and team levels. This study not only enables managers to clearly understand the precipitating factors of idea implementation but also provides constructive strategies for alleviating the negative effects of knowledge territoriality on creative process engagement and idea implementation.

This study constructs a cross-level model to explore the relationship among knowledge hiding, creative process engagement and idea implementation at individual and team levels in the context of Chinese R&D enterprises. Additionally, the study analyzes the influence of territoriality on idea implementation under boundary conditions.

This paper aims to provide a sensor for fast, sensitive and selective ethylene (C₂H₄) concentration measurements.

The paper developed a sensor platform based on tunable laser absorption spectroscopy with a 3,266-nm interband cascade laser (ICL) as an optical source and a hollow waveguide (HWG) as a gas cell. The ICL wavelength was scanned across a C₂H₄ strong fundamental absorption band, and an interference-free C₂H₄ absorption line located at 3,060.76 cm⁻¹ was selected. Wavelength modulation spectroscopy with the second harmonic detection (WMS-2f) technique was used to improve the sensitivity. Furthermore, the HWG gas cell can achieve a long optical path in a very small volume to improve the time response.

The results show excellent linearity of the measured 2f signal and the C₂H₄ concentration with a correlation coefficient of 0.9997. Also, the response time is as short as about 10 s. The Allan variance analysis indicates that the detection limit can achieve 53 ppb with an integration time of 24 s.

The ethylene sensor has many meaningful applications in environmental monitoring, industrial production, national security and the biomedicine field.

The paper provides a novel sensor architecture which can be a versatile sensor platform for fast and sensitive trace-gas detection in the mid-infrared region.

This paper aims to answer the following four research questions: Where do tourists gaze at the destination? What do tourists gaze at the destination? How do tourists gaze differently? Why do tourists gaze differently referring to relevant theory?

With a computer vision approach, this study illustrated a series of maps that reflect where and what do tourists gaze at and compared the differences in the visual perceptions among Asian, European and North American tourists in Hong Kong.

The findings confirm that the “tourist gaze” is influenced by geographical and cultural conditions. The conclusions provided three types of implementations for destination management strategies and advocated a high engagement with computer vision technology.

In theory, this study proves that the “tourist gaze” is influenced by geographical and cultural conditions. The study’s methodological contribution lies in applying advanced technology of visual content analysis for big data relevant to the issue of the tourist gaze. Practically, the finding that has not been achieved via previous questionnaire surveys will serve as a reference for tourism recommendations and precision marketing. In addition, its practical contribution is that it offers a means by which to explore tourists’ perceptions of destinations and understand the attractiveness of destinations to tourists.

研究一方面使用计算机视觉深入学习模型对游客照片内容进行识别, 比较了亚洲、欧洲和北美游客在香港不同空间场景的视觉感知差异。另一方面, 研究借助ArcGIS软件对游客凝视地点和内容差异进行了具体可视化分析。

这项研究有四个研究子问题：

• （1） 游客在哪里凝视？

• （2） 游客凝视了什么？

• （3） 游客凝视内容有什么不同？

  （4） 为什么游客凝视不同？

（1） 游客在哪里凝视？

（2） 游客凝视了什么？

（3） 游客凝视内容有什么不同？

（4） 为什么游客凝视不同？

不同游客在旅游目的地的“凝视”存在差异, 差异表征具体体现在地点选择和内容偏好等维度。同时, 研究结果显示计算机视觉技术在旅游研究领域呈现较好的应用潜力。

理论上, 本研究佐证了”游客凝视”受地理和文化条件影响的理论。技术上, 本研究探索了视觉分析技术在游客凝视议题上应用, 为旅游目的地感知评估提供了新的视角。应用层面, 研究结论为旅游目的地精准营销提供了参考。

Resumen

Con un enfoque de visión artificial, este estudio ilustra una serie de mapas que reflejan dónde y qué miran los turistas, y compara las diferencias en las percepciones visuales entre los turistas asiáticos, europeos y norteamericanos en Hong Kong.

El estudio tiene cuatro preguntas de investigación:

• (1) ¿Dónde miran los turistas en el destino?

• (2) ¿Qué miran los turistas en el destino?

• (3) ¿Cómo miran los turistas de forma diferente?

• (4) ¿Por qué los turistas miran de forma diferente en referencia a la teoría pertinente?

(1) ¿Dónde miran los turistas en el destino?

(2) ¿Qué miran los turistas en el destino?

(3) ¿Cómo miran los turistas de forma diferente?

(4) ¿Por qué los turistas miran de forma diferente en referencia a la teoría pertinente?

Las conclusiones confirman que la “mirada del turista” está influida por las condiciones geográficas y culturales. Las conclusiones aportan tres tipos de aplicaciones para las estrategias de gestión de destinos y abogan por un alto compromiso con la tecnología de visión artificial.

En teoría, este estudio demuestra que la “mirada del turista” está influenciada por las condiciones geográficas y culturales. La contribución metodológica del estudio radica en la aplicación de tecnología avanzada de análisis de contenido visual para big data relevante para el tema de la mirada del turista. En la práctica, los hallazgos que no se han logrado a través de encuestas anteriores servirán de referencia para las recomendaciones turísticas y el marketing de precisión. Además, su contribución práctica es que ofrece un medio para explorar las percepciones de los turistas sobre los destinos, y comprender el atractivo de los mismos para los turistas.

To construct a scientific and reasonable indicator system, it is necessary to design a set of standardized indicator primary selection and optimization inspection process. The purpose of this paper is to provide theoretical guidance and reference standards for the indicator system design process, laying a solid foundation for the application of the indicator system, by systematically exploring the expert evaluation method to optimize the index system to enhance its credibility and reliability, to improve its resolution and accuracy and reduce its objectivity and randomness.

The paper is based on system theory and statistics, and it designs the main line of “relevant theoretical analysis – identification of indicators – expert assignment and quality inspection” to achieve the design and optimization of the indicator system. First, the theoretical basis analysis, relevant factor analysis and physical process description are used to clarify the comprehensive evaluation problem and the correlation mechanism. Second, the system structure analysis, hierarchical decomposition and indicator set identification are used to complete the initial establishment of the indicator system. Third, based on expert assignment method, such as Delphi assignments, statistical analysis, t-test and non-parametric test are used to complete the expert assignment quality diagnosis of a single index, the reliability and validity test is used to perform single-index assignment correction and consistency test is used for KENDALL coordination coefficient and F-test multi-indicator expert assignment quality diagnosis.

Compared with the traditional index system construction method, the optimization process used in the study standardizes the process of index establishment, reduces subjectivity and randomness, and enhances objectivity and scientificity.

The innovation point and value of the paper are embodied in three aspects. First, the system design process of the combined indicator system, the multi-dimensional index screening and system optimization are carried out to ensure that the index system is scientific, reasonable and comprehensive. Second, the experts’ background is comprehensively evaluated. The objectivity and reliability of experts’ assignment are analyzed and improved on the basis of traditional methods. Third, aim at the quality of expert assignment, conduct t-test, non-parametric test of single index, and multi-optimal test of coordination and importance of multiple indicators, enhance experts the practicality of assignment and ensures the quality of expert assignment.

The purpose of this paper is to focus on finding the optimal maintenance interval and the minimum maintenance cost for redundant system, considering environment factors.

The authors propose a decision model with environment-based preventive maintenance for the repairable redundant system. Referring to the k-out-of-n model and Proportional Hazard Model, the reliability analysis is completed for the redundant system affected by internal and external issues. Meanwhile, the maintenance cost for the redundant system is divided into two categories: the fixed maintenance cost involving whole system replacement at the time of system failure, and the cost to replace failure components when the system still functions.

Upon the required reliability analysis, an optimal maintenance interval that minimizes the average maintenance cost per unit time is identified. The simulation results indicate that the optimal maintenance interval with consideration of environmental factors is significantly shorter than that without consideration of these factors, with the maintenance cost increase within 10 percent.

The redundant systems have widely been used in industries including the aero craft control system and warship power system. The model could be applied in the more real case considering the types of components and the operation environment, and help production managers better maintain machines by increasing the safety and reliability of the redundant model with the more frequent inspection.

Previous research of redundant system always focuses on internal degradation, while ignoring the reliability analysis for a redundant system with various multiple components under the influence of environment. However, this work could fill the theoretical gap, i.e. simultaneously consider both environmental and internal factors for a redundant system with non-homogeneous components. Meanwhile, the proposed superior model increases the reliability and safety of the k-out-of-n model with reasonable cost. Production managers could benefit a lot from this as well.

The purpose of this paper is to propose the complementary design rules, give a quantitative comparison and analyze the force production mechanism of two kinds of primary wound field flux-switching linear (PWFFSL) motors.

PWFFSL motors have the merits of no use of rare-earth magnet, low cost and a wide operation range in which the armature windings and the field windings are all located at the short primary mover and the secondary is very robust. Hence, the PWFFSL motor is ideal for rail transportation systems which need a long stator and a wide speed range. To overcome the disadvantages of the existing PWFFSL motors, new complementary design rules will be proposed. Also, to offer a better PWFFSL motor for the rail transportation systems, it is necessary to investigate different structures of PWFFSL motors and give a comprehensive comparison. To predict the force performance of two kinds of PWFFSL motors with different secondary types, their flux density analysis and force production mechanism will be presented and compared.

The comparison result shows that the PWFFSL motor with toothed secondary can offer larger thrust force, higher force density and higher efficiency, whereas the PWFFSL motor with segmented secondary has the merits of lower force ripple, less use of stator iron, higher power factor and less critical saturation.

Many PWFFSL motors with different primary/secondary pole pitches based on the proposed design principle have not been considered in this paper.

This paper has presented the air-gap flux analysis, proposed the complementary design rules for two kinds of PWFFSL motors with different secondary types and compared the electromagnetic performance of the two motors.

The purpose of this paper is to establish mass balance model and predict the concentration and diameter distribution of indoor suspended particulate matters (SPM).

Taking the small offices and residences for a research objective, this paper analyzes the major factors to affect the concentration and diameter distribution of indoor SPM, founds the deposition ratio model, the penetration factor model and the mass balance model to predict the concentration and diameter distribution of indoor SPM. According to the real‐time measuring data, the feature of building defence structure and the concentration and diameter distribution of outdoor SPM, the deposition model, the penetration model and indoor air capacity are used as input parameter of the mass balance model.

The size of defence in natural ventilation, the pressure difference of both sides and the friction velocity have less influence on the concentration and diameter distribution of indoor SPM, but the concentration and diameter distribution of outdoor SPM mainly affects that of indoor SPM. Indoor particle concentration change with outdoor particle concentration, and less than later because of indoor particle deposition. The prediction results are basically in agreement with the measuring data.

Real‐time and accuracy of measuring data of outdoor SPM are the main limitations which the prediction model are simulated.

The prediction results can provide scientific theory basis for making environmental standards of particulate matter and the control of indoor air quality.

A new method to predict the concentration and diameter distribution of indoor SPM.