In this article, a delay-range-dependent approach is put forward to tackle the state estimation problem for delayed impulsive neural networks. A new type of nonlinear function, which is more general ...than the normal sigmoid function and functions constrained by the Lipschitz condition, is adopted as the neuron activation function. To effectively alleviate data collisions and save energy, the round-robin protocol is utilized to mitigate the occurrence of unnecessary network congestion in communication channels from sensors to the estimator. With the aid of the Lyapunov stability theory, a state observer is constructed such that the estimation error dynamics are asymptotically stable. The observer existence is ensured by resorting to a set of delay-range-dependent criteria which is dependent on both the impulsive time instant and a coefficient matrix. In addition, the synthesis of the observer is discussed by using linear matrix inequalities. Simulations are provided to illustrate the reasonability of our delay-range-dependent estimation approach.
Studies have confirmed the ineffectiveness of sentiment expressions generated by sellers in improving guests’ purchasing intentions. However, how sentiment expressions can influence guest behavior ...and host performance remains unclear, given the relative importance of seller-generated content in peer-to-peer rental platforms. After collecting data from Airbnb and developing empirical models, this study confirmed that hosts’ sentiment expressions largely benefit from their online performance. This case is especially true when their properties did not receive high-quality negative reviews. To further reveal the mechanism behind this effect, we further conducted two experiments. Results show that trust plays an intermediary role in the relationship between hosts’ sentiment expressions and guests’ purchasing intentions. This work contributes to tourism literature and property owners on peer-to-peer rental platforms in practice.
This article is devoted to dealing with exponential synchronization for inertial neural networks (INNs) with heterogeneous time-varying delays (HTVDs) under the framework of aperiodic sampling and ...state quantization. First, by taking the effect of aperiodic sampling and state quantization into consideration, a novel quantized sampled-data (QSD) controller with time-varying control gain is designed to tackle the exponential synchronization of INNs. Second, considering the available information of the lower and upper bounds of each HTVD, a refined Lyapunov-Krasovskii functional (LKF) is proposed. Meanwhile, an improved looped-functional method is utilized to fully capture the characteristic of practical sampling patterns and further relax the positive definiteness requirement for LKF. Consequently, less conservative exponential synchronization conditions with extra flexibility are derived. Finally, a numerical example is employed to demonstrate the effectiveness and advantages of the proposed synchronization method.
The sharing economy has gained great market share within the lodging sector by offering cost-effective accommodation solutions. However, it is also troubled by increasing criminal incidents. This ...study examined the global relationship between the density of Airbnb and crimes in Florida, explored how the relationships vary at the county level. The results suggested that crime-lodging associations vary by listing types but not crime types. Only the Shared Room type consistently exhibited positive associations with both property and violent crimes, while Private Room and Entire Home exhibited negative associations. Local variations were identified by geographically weighted regression, which could be explained by the local tourism development and ethnic diversity degree. We suggested equal efforts in preventing both property and violent crimes in home sharing business. Also regional differences need to be considered when responding to shared lodging crimes.
We propose a conceptual framework to investigate factors influencing the supply of Airbnb units in US urban communities. Based on a sample of Airbnb supply data from 1068 zip codes in 28 major US ...cities, we apply a mixed-effects negative binomial model to uncover supply determinants. The results confirm the significance of five supply determinant categories, namely, hotel market demand and supply, housing market demand and supply, and short-term rental regulation. We also highlight the respective impacts of supply determinants on three different Airbnb units: entire houses, private rooms, and shared rooms. Moreover, we examine the unique effects of different types of regulation policies. In general, regulations related to tailored legal framework and hostile enforcement significantly decrease Airbnb unit supply.
New England's Colonial Inns and Taverns explores the history of these institutions and visits those that are still around. For centuries, travelers who have stepped out of the cold and into a tavern ...have found not only hearty Yankee fare, but also a feast for the senses. Centuries ago, taverns offered respites for weary wayfarers on horseback. Today, they remain welcome havens from high-speed lives.
Abstract
The inns, or osterie, of early modern Venice were located at the heart of the city, which was one the most important hubs of mobility and travel between Europe and the Mediterranean. Close ...study of the locations, structures, and interiors of the inns shows how they featured centrally in both the long-range itineraries of travelers and migrants as well as smaller-scale circulations of local residents around the city. The intersection of these various trajectories in the space of the inn led to a rich array of social, economic, and cultural exchanges, but also to moments of tension and conflict. As such, a focus on the osterie illuminates the experience of being on the move in this period as well as demonstrating how mobility fundamentally shaped, and was shaped by, the early modern city and its spaces.
After the outbreak of COVID-19 (especially in the stage of tourism recovery), the bed and breakfast (B&B) tourism industry faced big challenges in improving its health strategies. B&Bs are very ...important for the tourism industry in China and many other countries. However, few studies have studied the impact of B&Bs, under COVID-19, on tourism in China. Our paper is among one of the first studies to investigate the impact of COVID-19 on tourist satisfaction with B&Bs in China. The work/travel restrictions started from 20 January 2020, and work/after travel resumed from 20 February 2020 in Zhejiang, China. Data were collected from 588 tourists (who experienced B&Bs in Zhejiang, China) from a WeChat online survey, from 1 March to 15 March 2020. The current study attempted to fill the gap by studying the changing tourist satisfaction levels with B&Bs before/after COVID-19. Moreover, some suggestions are given to the B&B industry for tourism resumption after COVID-19 by an importance-performance analysis (IPA).
This article addresses the quantized sampled-data (QSD) synchronization for inertial neural networks (INNs) with heterogeneous time-varying delays, in which the sampled-data control and state ...quantization effect have been considered. By utilizing a proper variable substitution to transform the original system into a first-order differential system, choosing a new Lyapunov-Krasovskii functional (LKF) containing both the continuous terms and the discontinuous terms, and applying Jensen inequality and an improved reciprocally convex inequality to estimate the derivative of the LKF, the sufficient conditions for QSD synchronization for INNs are newly obtained in terms of linear matrix inequalities (LMIs), and the desired QSD controllers are designed by solving a set of LMIs. Finally, three numerical examples are provided to validate the effectiveness and benefit of the proposed results.
This article focuses on the synchronization problem of delayed inertial neural networks (INNs) with generally uncertain Markovian jumping and their applications in image encryption. The random ...connection weight strengths and generally uncertain Markovian are discussed in the INNs model. Compared with most existing INNs models that have constant connection weight strengths, our model is more practical because connection weight strengths of INNs may randomly vary due to the external and internal environment and human factor. The delay-range-dependent synchronization conditions (DRDSCs) could be obtained by adopting the delay-product-term Lyapunov-Krasovskii functional (DPTLKF) and higher order polynomial-based relaxed inequality (HOPRII). In addition, the desired controllers are obtained by solving a set of linear matrix inequalities. Finally, two examples are shown to demonstrate the effectiveness of the proposed results.
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