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The performance of behavioral targeting (BT) mainly relies on the effectiveness of user classification since advertisers always want to target their advertisements to the most relevant users. In this paper, the authors frame the BT as a user classification problem and describe a machine learning–based approach for solving it.

To perform such a study, two major research questions are investigated: the first question is how to represent a user’s online behavior. A good representation strategy should be able to effectively classify users based on their online activities. The second question is how different representation strategies affect the targeting performance. The authors propose three user behavior representation methods and compare them empirically using the area under the receiver operating characteristic curve (AUC) as a performance measure.

The experimental results indicate that ad campaign effectiveness can be significantly improved by combining user search queries, clicked URLs and clicked ads as a user profile. In addition, the authors also explore the temporal aspect of user behavior history by investigating the effect of history length on targeting performance. The authors note that an improvement of approximately 6.5% in AUC is achieved when user history is extended from 1 day to 14 days, which is substantial in targeting performance.

This paper confirms the effectiveness of BT on user classification and provides a validation of BT for Internet advertising.

The aim of this study was to investigate the themes related to the achievement of Sustainable Development Goal (SDG) 12 in relation to tourism, and specifically to explore how the emotional psyche affects tourists’ environmentally responsible behaviors.

Based on the value-belief-norm theory, a research framework was developed to examine the serial mediation effects of environmental emotions in predicting tourists’ environmentally responsible behaviors. A total of 741 responses was collected from an online survey. Data were analyzed by the partial least squares structural equation modeling.

Environmental concern does not directly predict tourists’ environmentally responsible behaviors. Instead, environmental awe and environmental worry serially mediate the relationship between environmental concern and tourists’ environmentally responsible behaviors.

This study extends the value-belief-norm theory by integrating environmental emotions and empirically tests the effect of multiple psyches on responsible consumption, contributing to the achievement of SDG 12 in UN Agenda 2030.

本研究的目的是探究与旅游相关的可持续发展目标12的实现, 特别是探讨环境情感如何影响旅游者的环境责任行为。

基于价值信念-规范理论, 构建了环境情感预测旅游者环境责任行为的链式中介模型。研究共收集741份有效样本, 并采用偏最小二乘结构方程模型进行分析。

环境关心并不能直接预测旅游者的环境责任行为。但是, 环境敬畏和环境忧虑在环境关心与环境责任行为之间起链式中介作用。

本研究将环境情感扩展到价值信念规范理论中, 并实证检验了环境敬畏和环境忧虑两种环境情感对旅游者的负责任消费行为的影响, 呼应了联合国2030年议程中的可持续发展目标12。

el objetivo de este estudio fue investigar los temas relacionados con el logro del Objetivo de Desarrollo Sostenible 12 en relación con el turismo, y específicamente explorar cómo la psique emocional afecta los comportamientos ambientalmente responsables de los turistas.

Basado en la teoría del valor-creencia-norma, se desarrolló un marco de investigación para examinar los efectos de mediación en serie de las emociones ambientales en la predicción de los comportamientos ambientalmente responsables de los turistas. Se recopiló un total de 741 respuestas de una encuesta en línea. Los datos se analizaron mediante el modelo de ecuaciones estructurales de mínimos cuadrados parciales.

la preocupación ambiental no predice directamente los comportamientos ambientalmente responsables de los turistas. En cambio, el temor ambiental y la preocupación ambiental median en serie la relación entre la preocupación ambiental y los comportamientos ambientalmente responsables de los turistas.

este estudio amplía la teoría del valor-creencia-norma al integrar las emociones ambientales y prueba empíricamente el efecto de múltiples psiques en el consumo responsable, contribuyendo al logro del ODS 12 en la Agenda 2030 de la ONU.

This paper aims to improve the performance of the autonomous optical navigation using relativistic perturbation of starlight, which is a promising technique for future space missions. Through measuring the change in inter-star angle due to the stellar aberration and the gravitational deflection of light with space-based optical instruments, the position and velocity vectors of the spacecraft can be estimated iteratively.

To enhance the navigation performance, an integrated optical navigation (ION) method based on the fusion of both the inter-star angle and the inter-satellite line-of-sight measurements is presented. A Q-learning extended Kalman filter (QLEKF) is designed to optimize the state estimate.

Simulations illustrate that the integrated optical navigation outperforms the existing method using only inter-star angle measurement. Moreover, the QLEKF is superior to the traditional extended Kalman filter in navigation accuracy.

A novel ION method is presented, and an effective QLEKF algorithm is designed for information fusion.

In this study, a modeling method for a clamped deformable cable simulation based on Kirchhoff theory is proposed. This methodology can be used to describe the physical deformation configuration of any constrained flexible cable in a computer-aided design/manufacturing system. The modeling method, solution algorithm, simulation and experimental results are presented to prove the feasibility of the proposed methodology. The paper aims to discuss these issues.

First, Kirchhoff equations for deformable cables are proposed based on the nonlinear mechanics of thin elastic rods, and the general solution of the equations described by the Euler angles is given in the arc coordinate system. The parametric form solution of the Kirchhoff equations, which is easy to use, is then obtained in a cylindrical coordinate form based on Saint Venant’s theory. Finally, mathematical expressions that reflect the clamped cable configuration are given, and the deformable process is simulated based on an open source geometry kernel and is then tested by a 3D laser scanning technology.

The method presented in this paper can be adapted to any boundary condition for constrained cables as long as the external force and torque are known. The experimental results indicate that both the model and algorithm are efficient and accurate.

A more comprehensive study must be executed for the physical simulation of more complicated constrained cables, such as the helical spring and asymmetric constraint. The influence of the material properties of the cable on the calculation efficiency must be considered in future analysis.

The semi-analytical algorithm of the cable simulation in cylindrical coordinates is a novel topic and is more accurate and efficient than the common numerical solution.

In this paper, a novel and unified method for geometry configuration simulation of flexible cable under certain boundary conditions is presented. This methodology can be used to realize cable assembly verification in any computer-aided design/manufacturing system. The modeling method, solution algorithm, geometry configuration simulation and experimental results are presented to prove the feasibility of this proposed methodology. The paper aims to discuss these issues.

Considering the gravity, bending and torsion, modeling of cable follows the Kirchhoff theory. For this purpose, Euler quaternions are used to describe its spatial geometry configuration by a carefully chosen set of coordinates. Then the cable is discretized by the FEM, and the equilibrium condition per element is computed. In this way, the global static behavior is independent of the discretization. The static evolution of the cable is obtained by numerical integration of the resulting Kirchhoff equations. Then the manner is demonstrated, in which this system of equations can be decoupled and efficiently solved. Geometry configuration simulation examples with different boundary conditions are presented. Finally, experiment validation are given to describe the effectiveness of the models and algorithms.

The method presented in this paper can be adapted to computer-aided assembly verification of flexible cable. The experimental results indicate that both of the model and algorithm are efficient and accurate.

The method should be extended to flexible cables with multiple branches and more complex constraints (holes, curved surfaces and clamps) and non-circular sections. Dynamic assembly process simulation based on the Kirchhoff theory must be considered in the future.

Unlike in previous approaches, the cable behavior was independent of the underlying discretization, and the finite element approach enables physically plausible cable assembly verification.

The prediction of by-product gas is an important guarantee for the full utilization of resources. The purpose of this research is to predict gas consumption to provide a basis for gas dispatch and reduce the production cost of enterprises.

In this paper, a new method using the ensemble empirical mode decomposition (EEMD) and the back propagation neural network is proposed. Unfortunately, this method does not achieve the ideal prediction. Further, using the advantages of long short-term memory (LSTM) neural network for long-term dependence, a prediction method based on EEMD and LSTM is proposed. In this model, the gas consumption series is decomposed into several intrinsic mode functions and a residual term (r(t)) by EEMD. Second, each component is predicted by LSTM. The predicted values of all components are added together to get the final prediction result.

The results show that the root mean square error is reduced to 0.35%, the average absolute error is reduced to 1.852 and the R-squared is reached to 0.963.

A new gas consumption prediction method is proposed in this paper. The production data collected in the actual production process is non-linear, unstable and contains a lot of noise. But the EEMD method has the unique superiority in the analysis data aspect and may solve these questions well. The prediction of gas consumption is the result of long-term training and needs a lot of prior knowledge. Relying on LSTM can solve the problem of long-term dependence.

The purpose of the paper is to predict the erosion rate of the components of centrifugal pump under certain operating condition to identify the maximum erosion area and to discuss the factors affecting them. This helps to optimize design and estimate service life.

In the paper, the Eulerian–Lagrangian approach method coupled with the erosion model to investigate the mixed sand characteristics on erosion characteristics of centrifugal pump flow-through wall. The hydraulic performance and wear characteristics experiment of the pump is used to verify the accuracy of the numerical simulation.

The blade erosion area mainly occurs near the blade inlet and the trailing edge of the pressure surface, the main erosion area of the impeller back shroud is near the outlet of the flow passage and the main erosion area of the volute is near the tongue and the I section. With the change of the average diameter and density of sand particles, the average erosion rate on different flow-through walls is positively correlated with the average mass concentration to a certain extent. However, for different sand shape factors, there is little correlation between the average erosion rate and the average mass concentration. In addition, compared with other erosion areas, the increase of average sand particle diameter and density has the greatest impact on the total erosion rate of blade pressure surface, while the shape of sand particles has a greater impact on the total erosion rate of each flow-through wall of centrifugal pump.

In this work, according to the characteristics of the mixed distribution of different sand diameters in the Yellow River Basin, the erosion characteristics of centrifugal pumps used in the Yellow River Basin are studied. The numerical calculation method for predicting the wall erosion of centrifugal pump is established and compared with the experimental results. The results can provide reference for optimizing design and increasing service life.

Cables are widely used, and they play a key role in complex electromechanical products such as vehicles, ships, aircraft and satellites. Cable design and assembly significantly impact the development cycle and assembly quality, which is be-coming a key element affecting the function of a product. However, there are various kinds of cables, with complex geo-metric configurations and a narrow assembly space, which can easily result in improper or missed assembly, an unreasonable layout or interference. Traditional serial design methods are inefficient and costly, and they cannot predict problems in installation and use. Based on physical modeling, computer-aided cable design and assembly can effectively solve these problems. This paper aims to address virtual assembly (VA) of flexible cables based on physical modeling.

Much research has focused recently on virtual design and assembly-process planning for cables. This paper systematically reviews the research progress and the current state of mechanical models, virtual design, assembly-process planning, collision detection and geometric configuration and proposes areas for further research.

In the first instance, the main research groups and typical systems are investigated, followed by extensive exploration of the major research issues. The latter can be reviewed from five perspectives: the current state of mechanical models, virtual design, assembly-process planning, collision detection and geometric configuration. Finally, the barriers that prevent successful application of VA are also discussed, and the future research directions are summarized.

This paper presents a comprehensive survey of the topics of VA of flexible cables based on physical modeling and investigates some new ideas and recent advances in the area.

Feelings about conflict in labor relations are determined by both the objective conditions surrounding the dimension of labor relations and their subjective evaluation. This study aims to examine features of the subjective evaluation factors in labor relations for new generation employees born in the post-1980s, transitional China, and to explore the conflict reduction strategies in labor relations.

This study designed items and a scale to measure employees’ subjective evaluation bias regarding labor relations, and conducted a survey of 1,500 employees in 80 Chinese enterprises. It conducted a principal components analysis of the subjective evaluation biases, and a covariance analysis to explore differences in the common factors between employees of two generations. Comparing the subjective bias with the objective status of labor relations, as well as with employers’ expectations, this study analyzed the feelings toward conflict and conflict management strategies.

There are eight common factors in the subjective evaluation bias toward labor relations, four of which show significant differences between employees of two generations. Employers should study these differences, and apply conflict reduction measures to manage labor relations.

This is one of the first studies to propose the concept of a subjective evaluation bias regarding labor relations, and examine the common factors and features among new generation employees. It establishes a model for feelings toward conflict through four combinations of the subjective preferences and objective status dimensions. This study offers new insights for reducing workplace conflict.

Traditional simulation research of geological and similar engineering models, such as landslides or other natural disaster scenarios, usually focuses on the change of stress and the state of the model before and after destruction. However, the transition of the inner change is usually invisible. To optimize and make models more intelligent, this paper aims to propose a perceptible design to detect the internal temperature change transformed by other energy versions like stress or torsion.

In this paper, micron diamond particles were embedded in 3D printed geopolymers as a potential thermal sensor material to detect the inner heat change. The authors use synthetic micron diamond powder to reinforced the anti-corrosion properties and thermal conductivity of geopolymer and apply this novel geopolymer slurry in the direct ink writing (DIW) technique.

As a result, the addition of micron diamond powder can greatly influence the rheology of geopolymer slurry and make the geopolymer slurry extrudable and suitable for DIW by reducing the slope of the viscosity of this inorganic colloid. The heat transfer coefficient of the micron diamond (15 Wt.%)/geopolymer was 50% higher than the pure geopolymer, which could be detected by the infrared thermal imager. Besides, the addition of diamond particles also increased the porous rates of geopolymer.

In conclusion, DIW slurry deposition of micron diamond-embedded geopolymer (MDG) composites could be used to manufacture the multi-functional geological model for thermal imaging and defect detection, which need the characteristic of lightweight, isolation, heat transfer and wave absorption.