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The purpose of this study is to compare the spatial distribution of Airbnb and hotels in London and examine the relationship between demographic, socioeconomic and environmental factors and the supply of these two types of lodging supply.

Local information of Airbnb listings in London was collected through Insideairbnb.com. Gathered data were examined using geo-spatial auto-correlation analysis and spatial econometric models.

The results indicate that Airbnb predominates in the areas around popular tourist attractions and the peripheral areas of the city, while in the downtown area Airbnb and hotels are in the state of coexistence. The mono-centric model and the agglomeration model could be extended to the context of peer-to-peer accommodation. The location of Airbnb and traditional hotels capitalizes on different factors.

The study is based on secondary data due to data availability. And, it is based on the case of London, so the findings may not reflect the situation of small cities and rural destinations.

This study not only gives suggestions for local councils to regulate the location of hotels and Airbnb but also provides professional landlords with reference to choosing Airbnb location.

This study extends the hotel location theoretical models into the context of Airbnb and sheds lights on the distinction between these two business models in terms of location factors.

爱彼迎和酒店的位置：空间分布和关系

本研究旨在比较伦敦Airbnb和酒店的空间分布, 并探讨人口、社会经济和环境因素与这两类住宿供给的关系。

伦敦Airbnb房源信息通过Insideairbnb.com网站收集, 采用地理空间自相关分析和空间经济计量模型进行分析。

结果表明Airbnb主要集中在旅游景点周边和城市周边地区, 在市中心地区, Airbnb与酒店处于共存状态。单中心模型和聚集模型适用于共享住宿情境。Airbnb和传统酒店的空间分布影响因素的重要性存在差异。

本研究将酒店区位理论模型扩展到Airbnb情境下, 并揭示了这两种商业模式在区位因素方面的区别。

本研究采用二手数据。案例地为伦敦, 因此研究结果可能无法反映小城市和乡村旅游目的地的情况。

地方政府应更加重视专业公司的劳动力保障并限制旅游景点周边的短期租赁。

Ubicación de los hoteles y preferencias: distribución espacial y relaciones

El propósito de este estudio es comparar la distribución espacial de Airbnb y los hoteles en Londres y examinar la relación entre los factores demográficos, socioeconómicos y ambientales y la oferta de estos dos tipos de oferta de alojamiento.

La información local de los anuncios de Airbnb en Londres se recopiló a través de Insideairbnb.com. Los datos recopilados se examinaron mediante análisis de autocorrelación geoespacial y modelos econométricos espaciales.

Los resultados indican que Airbnb predomina en las zonas aledañas a los atractivos turísticos populares y las zonas periféricas de la ciudad, mientras que en la zona centro Airbnb y los hoteles se encuentran en estado de convivencia. El modelo monocéntrico y el modelo de aglomeración podrían extenderse al contexto de la acomodación entre pares. La ubicación de Airbnb y los hoteles tradicionales se basa en diferentes factores.

Este estudio amplía los modelos teóricos de ubicación de hoteles en el contexto de Airbnb y arroja luz sobre la distinción entre estos dos modelos comerciales en términos de factores de ubicación.

El estudio se basa en datos secundarios debido a la disponibilidad de datos. Y se basa en el caso de Londres, por lo que los hallazgos pueden no reflejar la situación de las ciudades pequeñas y los destinos rurales.

Los hallazgos sugieren que las autoridades locales deberían prestar más atención a la seguridad laboral de las empresas profesionales y restringir los alquileres a corto plazo alrededor de las atracciones turísticas.

The microcutting performance of the ¹⁰B/Al composite is significantly poor because of the existence of hard boron particles. The effects of cutting parameters, including uncut chip thickness and cutting speed, on the material removal mechanism and surface generation are investigated to improve the surface quality.

The 2D finite element model, which includes a rigid cutting tool, a reinforced phase, a matrix and a dense layer, is established. The effects of uncut chip thickness on material removal mechanism and surface generation are analyzed from a probabilistic perspective. The relationship between the uncut chip thickness and the probability in which the machined surface will have a better surface quality is constructed. A Gaussian distribution formula is applied to describe the machined surface quality.

Two representative particle-removal modes, namely, cutting-through and pulling-out modes, are observed. For cutting-through mode, when the relative cutting location is small, better surface quality is obtained. For pulling-out mode, the quality of the machined surface gradually improves because the further increase of the relative cutting location reduces the height of the generated pit and scratches. The microcutting at high cutting speed tends to suppress the scratch phenomenon. The best surface quality will be obtained at small uncut chip thickness and high cutting speed.

The surface quality generated in microcutting of the ¹⁰B/Al composite can be improved by optimizing the cutting parameters and controlling the particle-removal modes based on the proposed Gaussian distribution formula.

Targeting the common functions of the Zhejiang Library website, elderly individuals were invited to complete six experimental tasks on the improved website interfaces, and subjective data (PAD emotion scale and usability evaluation) and objective data (eye movement data) were recorded to verify the effects of graphic layout and navigation position on the information-seeking experience of elderly individuals.

This study analyzes the effect of the graphic layout and navigation position of the Zhejiang Library’s website interface on the emotional state, perceived usability and information-seeking time of elderly individuals, with the aim of providing guidance and suggestions for the elderly-oriented reform of the public library website.

The experimental results show that the graphic layout has a significant effect on the emotional state and perceived usability of elderly individuals, and the navigation position has a significant effect on the information-seeking time; the interaction between graphic layout and navigation position exerts a significant effect on the information-seeking time of elderly individuals. The eye movement data show that elderly individuals have a better information-seeking experience when the top navigation bar and image-text matched arrangement are used for the interface layout.

This study adopts a new approach combining subjective data and eye movement data to evaluate the effect of the public library website’s interface layout on the information-seeking experience for older people. The findings can provide a theoretical basis and methodological support for the elderly-oriented reform of public library websites. They can also provide scientific design suggestions for age-friendly interface layouts of other Internet products and service applications.

Opaque selling has become popular among service providers in recent years. Although many researchers have investigated the optimality of opaque selling for service providers focusing on heterogeneous consumers, one question remaining unexplored is how the service providers’ optimal decisions are impacted by competitive intensity in a heterogeneous market. This paper aims to determine the conditions under which opaque selling is optimal for competing service providers.

The paper takes a Hotelling model to characterize the competition between two service providers. The authors also consider the interaction between the service providers and intermediary. Service providers act as game leaders and determine whether they should cooperate with the intermediary to introduce the opaque service.

The authors find that two competing service providers do not always benefit from opaque selling in a heterogeneous market consisting of leisure and business consumers, and the competitive intensity plays a significant role in the service providers’ decision optimization. Opaque selling allows service providers to acquire more profit in a highly competitive market or when the market contains a large proportion of leisure consumers. Otherwise, it is optimal for service providers without introducing the opaque selling.

The paper examines the optimality of opaque selling for competing service providers, and provides the suggestions to optimize the service providers’ decisions.

The paper investigates how the service providers’ optimal decisions are impacted by competitive intensity, considering the interaction between the service providers and intermediary.

Robotic arms’ interactions with the external environment are growing more intricate, demanding higher control precision. This study aims to enhance control precision by establishing a dynamic model through the identification of the dynamic parameters of a self-designed robotic arm.

This study proposes an improved particle swarm optimization (IPSO) method for parameter identification, which comprehensively improves particle initialization diversity, dynamic adjustment of inertia weight, dynamic adjustment of local and global learning factors and global search capabilities. To reduce the number of particles and improve identification accuracy, a step-by-step dynamic parameter identification method was also proposed. Simultaneously, to fully unleash the dynamic characteristics of a robotic arm, and satisfy boundary conditions, a combination of high-order differentiable natural exponential functions and traditional Fourier series is used to develop an excitation trajectory. Finally, an arbitrary verification trajectory was planned using the IPSO to verify the accuracy of the dynamical parameter identification.

Experiments conducted on a self-designed robotic arm validate the proposed parameter identification method. By comparing it with IPSO1, IPSO2, IPSOd and least-square algorithms using the criteria of torque error and root mean square for each joint, the superiority of the IPSO algorithm in parameter identification becomes evident. In this case, the dynamic parameter results of each link are significantly improved.

A new parameter identification model was proposed and validated. Based on the experimental results, the stability of the identification results was improved, providing more accurate parameter identification for further applications.

This study aims to reveal the room-temperature effect of a superconducting gravimeter prototype, which will guide its subsequent optimization to improve its gravimetric measurement accuracy.

Without leveling, the prototype output signal, tilt data and room temperature were measured under steady operating conditions. After analyzing the correlations of the three data sets, the residuals of the prototype’s output signal were compensated using the tilt data and the geodynamic effects (ocean tide loading, atmospheric loading and the gravitational effect of polar motion) were then corrected.

The remaining residuals after correction may be caused by small tilt variations that are due to the sensor chamber temperature and radiation shield temperature changes. These small tilt variations were submerged in the tilt signal noise. Although the peak-to-peak noise of the tiltmeter does not exceed 15 µrad, it can still produce gravimetric deviations above 60 µGal when the prototype is significantly tilted.

This study analyzes in detail the room-temperature effect of a superconducting gravimeter prototype, introduces the tilt effect of the relative gravimeters to compensate for the gravimetric deviations and emphasizes that the improvement of fine leveling and the accuracy of the tiltmeter are key requirements for the prototype to perform high-accuracy gravity measurement tasks.

The purpose of this paper is to solve the problem that the location of the initiation point cannot be measured accurately in the shallow underground space, this paper proposes a method, which is based on fusion of multidimensional vibration sensor information, to locate single shallow underground sources.

First, in this paper, using the characteristics of low multipath interference and good P-wave polarization in the near field, the adaptive covariance matrix algorithm is used to extract the polarization angle information of the P-wave and the short term averaging/long term averaging algorithm is used to extract the first break travel time information. Second, a hybrid positioning model based on travel time and polarization angle is constructed. Third, the positioning model is taken as the particle update fitness function of quantum-behaved particle swarm optimization and calculation is performed in the hybrid positioning model. Finally, the experiment verification is carried out in the field.

The experimental results show that, with root mean square error, spherical error probable and fitness value as evaluation indicators, the positioning performance of this method is better than that without speed prediction. And the positioning accuracy of this method has been improved by nearly 30%, giving all of the three tests a positioning error within 0.5 m and a fitness less than 1.

This method provides a new idea for high-precision positioning of shallow underground single source. It has a certain engineering application value in the fields of directional demolition of engineering blasting, water inrush and burst mud prediction, fuze position measurement, underground initiation point positioning of ammunition, mine blasting monitoring and so on.

The purpose of this paper is to present a method which enables a robot to learn both motion skills and stiffness profiles from humans through kinesthetic human-robot cooperation.

Admittance control is applied to allow robot-compliant behaviors when following the reference trajectories. By extending the dynamical movement primitives (DMP) model, a new concept of DMP and stiffness primitives is introduced to encode a kinesthetic demonstration as a combination of trajectories and stiffness profiles, which are subsequently transferred to the robot. Electromyographic signals are extracted from a human’s upper limbs to obtain target stiffness profiles. By monitoring vibrations of the end-effector velocities, a stability observer is developed. The virtual damping coefficient of admittance controller is adjusted accordingly to eliminate the vibrations.

The performance of the proposed methods is evaluated experimentally. The result shows that the robot can perform tasks in a variable stiffness mode as like the human dose in the teaching phase.

DMP has been widely used as a teaching by demonstration method to represent movements of humans and robots. The proposed method extends the DMP framework to allow a robot to learn not only motion skills but also stiffness profiles. Additionally, the authors proposed a stability observer to eliminate vibrations when the robot is disturbed by environment.