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This paper aims to propose a robust and efficient method for vanishing point detection in unstructured road scenes.

The proposed method includes two main stages: drivable region estimation and vanishing point detection. In drivable region estimation stage, the road image is segmented into a set of patches; then the drivable region is estimated by the patch-wise manifold ranking. In vanishing point detection stage, the LSD method is used to extract the straight lines; then a series of principles are proposed to remove the noise lines. Finally, the vanishing point is detected by a novel voting strategy.

The proposed method is validated on various unstructured road images collected from the real world. It is more robust and more efficient than the state-of-the-art method and the other three recent methods. Experimental results demonstrate that the detected vanishing point is practical for vision-sensor-based navigation in complex unstructured road scenes.

This paper proposes a patch-wise manifold ranking method to estimate the drivable region that contains most of the informative clues for vanishing point detection. Based on the removal of the noise lines through a series of principles, a novel voting strategy is proposed to detect the vanishing point.

This paper aims to introduce a novel structure for the physical internet (PI)–enabled sustainable supplier selection and inventory management problem under uncertain environments.

To address hybrid uncertainty both in the objective function and constraints, a novel interactive hybrid multi-objective optimization solution approach combining Me-based fuzzy possibilistic programming and interval programming approaches is tailored.

Various numerical experiments are introduced to validate the feasibility of the established model and the proposed solution method.

Due to its interconnectedness, the PI has the opportunity to support firms in addressing sustainability challenges and reducing initial impact. The sustainable supplier selection and inventory management have become critical operational challenges in PI-enabled supply chain problems. This is the first attempt on this issue, which uses the presented novel interactive possibilistic programming method.

This paper aims to develop a dynamic two-sided stable matching method based on preference information of the matching objects in uncertain environments, so as to solve the matching problem of cloud manufacturing tasks and services with load balancing.

For dynamic two-sided matching, due to the complexity of social environment and the limitation of human cognition, hesitation and fuzziness always exist in the process of multi-criteria assessment. First, in order to obtain the accurate preference information of each matching object, uncertain linguistic variables, uncertain preference ordinal and incomplete complementary matrices are used to evaluate multi-criteria preference information. This process is undertaken by considering the probability of each possible matching pair. Second, the preference information at different times is integrated by using the time-series weight to obtain the comprehensive satisfaction degree matrices of the matching objects. Further, the load adjustment parameter is used to increase the satisfaction degree of the matching objects. Afterward, a dynamic two-sided stable matching optimization model is constructed by considering stable matching conditions. The model aims to maximize the satisfaction degree and minimizes the difference in the satisfaction degree of matching objects. The optimal stable matching results can be obtained by solving the optimization model. Finally, a numerical example and comparative analysis are presented to demonstrate the characteristics of the proposed method.

Uncertain linguistic variables, uncertain preference orders and incomplete complementary matrices are used to describe multi-criteria preference information of the matching objects in uncertain environments. A dynamic two-sided stable matching method is proposed, based on which a DTSMDM (dynamic two-sided matching decision-making) model of cloud manufacturing with load balancing can be constructed. The study proved that the authors can use the proposed method to obtain stable matching pairs and higher matching objective value through comparative analysis and the sensitivity analysis.

A new method for the two-sided matching decision-making problem of cloud manufacturing with load balancing is proposed in this paper, which allows the matching objects to elicit language evaluation under uncertain environment more flexibly to implement dynamic two-sided matching based on preference information at different times. This method is suitable for dealing with a variety of TSMDM (two-sided matching decision-making) problems.

People continue to become more liberated and individualised day by day. They look for ways to somehow get out of any situation that restricts them, tend to get rid of their typical holiday patterns and travel alone, without being stuck within anyone else's borders, precisely as they want. In addition, people can travel alone to discover themselves, meet different cultures, relieve stress and learn new skills. Women travel alone more than men, although they face more difficulties than men. The experiences of women solo travellers suggest that this form of travel can provide a meaningful foundation for advancing gender equality. By challenging gender roles and expectations, empowering women to assert their autonomy and agency and creating opportunities for community-building and solidarity, solo travel can help to transform social norms and promote gender equity.

This chapter aims to build a body of knowledge that will have a widespread impact based on available data on the relationship of women solo travellers to gender equality. It also examines the effects of women solo travellers on gender equality based on secondary data sources. This chapter, designed as conceptual research with descriptive analysis and document analysis, is important in revealing what the indirect gains of women solo travellers can be for gender equality, the fifth of the United Nations Development Programme (UNDP) Sustainable Development Goals.

This study examines the effect of employees' perceptions of political connections on performance measurement systems (PMS) design choice and firm performance. In addition, this study explores the moderating effect of social networking, a very common and widely used factor by domestic and foreign multinational firms operating in China, and its joint effect with political connections or PMS design choice on firm performance. We collected survey responses from a sample of 110 managers from manufacturing firms in China. Our results reveal that highly politically connected managers use nonfinancial measures, leading to improved firm performance. Our results suggest that social networking interacts significantly with political connections, and nonfinancial and financial measures on firm performance. The theoretical and practical implications of our findings are discussed.

Distance is the core concept in tourism. However, previous studies focused on single distance dimensions and generated contradictory findings due to omitted variable biases. This paper aims to introduce the well-established CAGE (cultural, administrative, geographical, and economic) distance framework into international tourism research to measure the comprehensive distance and explore its impact on inbound tourist satisfaction.

The comprehensive distance was calculated based on the Mahalanobis formula. Combining tourist review data from TripAdvisor, this study used ordinary least square regressions to explore the influence of the comprehensive distance on inbound tourist satisfaction and the mediating role of inbound tourist emotion.

Results show that CAGE distance effectively describes the dynamic change in distance. The comprehensive distance also positively impacts tourist satisfaction, and tourist emotion plays a mediating role in this impact.

This paper advances knowledge about distance in international tourism by introducing the CAGE distance framework and addresses the contradictory findings with specific distance dimensions by the comprehensive distance.

距离是旅游的核心概念。然而, 以前的研究集中在单一的距离维度上, 并且由于遗漏变量偏差而产生了相互矛盾的结果。 本文旨在将成熟的 CAGE 距离框架引入国际旅游研究中, 以衡量综合距离并探讨其对入境游客满意度的影响。

综合距离根据马氏距离公式计算。 结合TripAdvisor网站的游客评论数据, 采用普通最小二乘（OLS）回归分析综合距离对入境游客满意度的影响以及入境游客情绪的中介作用。

结果表明, CAGE距离有效地描述了距离的动态变化。 综合距离也正向影响游客满意度, 游客情绪在此影响中起中介作用。

本文通过引入 CAGE 距离框架来提升国际旅游中的距离知识。 本研究还通过综合距离解决了特定距离维度的矛盾发现。

La distancia es el concepto central en el turismo. Sin embargo, estudios previos se han centrado en dimensiones de una sola distancia, generando resultados contradictorios debido a los sesgos por la omisión de variables. Este trabajo tiene como objetivo introducir el marco de distancia CAGE, establecido en la investigación turística internacional, con la intención de medir la distancia integral y explorar su impacto en la satisfacción del turista receptor.

La distancia integral se calculó con base en la fórmula de Mahalanobis. Combinando los datos de reseñas turísticas de TripAdvisor, se utilizaron regresiones de mínimos cuadrados ordinarios (OLS) para explorar la influencia de la distancia integral en la satisfacción del turista receptor y el papel mediador de la emoción del turista receptor.

Los resultados muestran que el modelo CAGE describe el cambio dinámico en la distancia de una forma efectiva. La distancia integral también impacta positivamente en la satisfacción del turista, y la emoción del turista juega un papel mediador en este impacto.

Este documento avanza en el conocimiento sobre la distancia en el turismo internacional mediante la introducción del marco de distancia CAGE. Además, aborda resultados contradictorios con las dimensiones de distancia específicas mediante la distancia integral.