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This paper aims to design a composite, aiming to improve the static puncture resistance through polyurethane impregnated treatment with five concentration gradients.

The relationship between polyurethane concentration, the number of polyester nonwovens, component fiber type (filament or staple) and the static puncture resistance is explored respectively and elaborately.

This study provides a new perspective to design flexible composites with better static puncture resistance, feasible preparation process as well as low cost.

The results show that the static puncture resistance of nonwovens impregnated by polyurethane is improved obviously. Meanwhile the puncture strength-T of nonwovens increases first and then decreases with the increase of the number of layers, and the maximum puncture strength-T is found at 20 layers. Moreover, the composite with filaments illustrates better mechanical resistance.

This paper aims to propose a constant-gain Kalman Filter algorithm based on the projection method and constant dimension projection, which ensures that the dimension of the observation matrix obtained is maintained when there is a satellite with multiple sensors.

First, a time-invariant observation matrix is determined with the projection method, which does not require the Jacobi matrix to be calculated. Second, the constant-gain matrix replaces the EKF (extended Kalman filter) gain matrix, which requires online computation, considerably improving the stability and real-time properties of the algorithm.

The simulation results indicate that compared to the EKF algorithm, the constant-gain Kalman filter algorithm has a considerably lower computational burden and improved real-time properties and stability without a significant loss of accuracy. The algorithm based on the constant dimension projection has better real-time properties, simpler computations and greater fault tolerance than the conventional EKF algorithm when handling an attitude determination system with three or more star trackers.

In satellite attitude determination systems, the constant-gain Kalman Filter algorithm based on the projection method reduces the large computational burden and improve the real-time properties of the EKF algorithm.

This paper aims to examine the optimal promotion strategy of an e-retailer, who may advertise, or launch rebates initiative to encourage consumers' disseminating electronic word-of-mouth (eWOM) messages, with an aim to boost product sales.

This paper analyzes the decisions of the e-retailer in a two-period model, using utility function approach and backward induction method, and obtains the optimal solutions in four promotion strategies.

The study finds that rebate scheme greatly impacts the timing of advertising, and neither lower nor higher consumers' eWOM effort invariably benefits the retailer, rather, a medium level is the best choice for the retailer. When eWOM impact power is at a relatively high level, it can supplement advertising effect to attract more consumers' purchase. Otherwise, eWOM may counteract the role of advertising.

Different from the extant literature focusing on advertising or eWOM without rebates, the paper studies the issue of advertising and eWOM with rebates in two- period model which seldom addresses before the authors examine the optimal timing of advertising and eWOM with/without rebates in four promotion strategies i.e. the A-NE model the NE-A model the A-ER model and the ER-A model.

There is a growing interest in brand formation and brand valuation among global firms today, but global marketers typically ignore one of the key factors of brand building – corporation ability association (CAA). This paper aims to explore the structural relationship between CAA and consumer‐based brand equity variables and its product‐market outcomes.

Utilizing Aaker and Keller's theoretical framework of brand equity, this paper develops a brand equity model combining customer‐based brand equity with product‐market outcome approaches. A set of scales are developed and tested on a national sample of Chinese consumers.

The data provide support for ten of the 12 hypotheses. The results indicate that CAA is an important factor in building and preserving brand equity. CAA and brand awareness have impact on quality perception, which has positive impact on brand resonance, brand extensibility, and price flexibility. Brand resonance has positive influence on brand extensibility and the intention to repurchase.

For global marketers operating in China, brand equity is a cultural market‐based asset and global companies must focus on building corporation ability association in China in order to enjoy the substantial competitive and economic advantages provided by brand equity. Theoretically, the proposed brand equity model is an extension of the model proposed by Keller.

For the first time, CAA is integrated into fhe brand equity model. This may provide a theoretical base for further research in the endorsement role of company ability in brand equity building.

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.

As organizations increasingly engage with consumers over mobile devices, there is a growing need to understand how consumers react to impression management over platforms with limited textual content. The purpose of this paper is to empirically assess how different impression management tactics can be used in mobile media to enhance consumer perception-attitude-intentions toward a corporate brand.

We surveyed 670 consumers and estimate structural equation models and repeated-measures ANOVAs to determine how short passages employing alternate impression management tactics influence consumers’ perceptions, attitudes and purchase intentions.

Results reveal that each impressions management tactic (i.e. ingratiation, intimidation, organizational promotion, supplication and exemplification) influences consumer perceptions, attitudes and intentions. The authors compare differences in how the impressions management tactics influence each stage of the perception-attitude-intentions model and find evidence that initial differences in perceptions favoring ingratiation and exemplification appeals become magnified for purchase intentions.

Recent calls for research focus on an understanding of how consumers process information on reduced-content platforms of small-screened mobile devices. These results provide empirical evidence of the use of impression management and the difference between five impression management tactics on enhancing consumer perception-attitude-intentions model.

The results of this study will provide marketers with insights to optimize communications and corporate brands with consumers over mobile media.

This paper adds to the nascent yet vital literature on mobile marketing by focusing on how impression management tactics influence perceptions, attitudes and intentions through the short message characteristic of mobile platforms. The authors develop a framework for how corporate brand management can strategically use impressions management tactics in this novel domain.

The purpose of this paper is to provide an overview of smart agriculture systems and monitor and identify the technologies which can be used for deriving traditional agriculture system to modern agriculture system. It also provides the reader a broad area to work for the advancement in the field of agriculture and also explains the use of advanced technologies such as spectral imaging, robotics and artificial intelligence (AI) in the field of agriculture.

Smart uses of modern technologies were reviewed in the field of agriculture, which helps to monitor stress levels of plants and perform operations according to requirements. Operations can be irrigation, pests spray, monitoring crops, monitoring yield production, etc. Based on the literature review, a smart agriculture system is suggested. The parameters studied were spectral image processing, AI, unmanned aerial vehicle (UAVs) (fixed and rotatory), water or soil moisture, nutrients and pesticides.

The use of autonomous vehicles and AI techniques has been suggested through which the agriculture system becomes much more efficient. The world will switch to the smart agriculture system in the upcoming era completely. The authors conclude that autonomous vehicle in the field of science is time-saving and health efficient for both plants and workers in the fields. The suggested system increases the productivity of crops and saves the assets as well.

This review paper discusses the various contemporary technologies used in the field of agriculture and it will help future researchers to build on this research. This paper reveals that the UAVs along with multispectral, hyperspectral or red, green and blue camera (depends on the need) and AI are more suitable for the advancement of agriculture and increasing yield rate.

The purpose of this paper is to examine current gender differences in job expectations among Chinese college students, how current job expectations across gender differ from an earlier study, and how they might impact organizational practices such as recruitment and retention.

Using Manhardt’s 25-item measure of job expectations, this study asked Chinese college students to rate the importance of various job characteristics on a five-point Likert scale (5=very important to 1=very unimportant). Male and female responses were compared for 430 college students.

Results of the current study found that males and females differed in their ratings on 23 of 25 items, with females rating all 23 of these items to be of higher importance. These findings differ significantly from an earlier study so they are compared and discussed.

This paper is limited in that it focusses solely on college students and only examines gender as a basis for comparison. Future studies should examine employees and consider other factors such as Chinese ethnicity as a basis for comparison.

Organizations may choose to change/improve aspects of certain jobs to more closely align with job candidates’ interests and/or choose to differently implement tools such as realistic job previews in order to improve retention.

This paper provides an updated status on gender differences in job expectations of China’s soon-to-be emerging workforce. Findings provide organizations with insight on how to develop human resource tools to hold on to talent.

This paper advances on previous work by drawing on a much larger sample and by utilizing a structured forward-translation, back-translation process for its survey.

Previous studies have mainly focused on public opinions regarding genetically modified (GM) technology and GM food. The purpose of this paper is to assess scientists’ attitudes on whether China needs to develop its national agricultural GM technology and their willingness to buy GM food.

A stratified sampling method was used to select and interview 806 scientists from six major agricultural universities and 20 research institutes under two national academies in China in 2013. Based on these data, the authors use both descriptive statistics and multivariate regression analysis to examine scientists’ attitudes toward agricultural GM technology and food, using GM soybean oil as an example of GM foods.

The survey results show that nearly three-quarters of scientists agree that China needs to develop its agricultural GM technology, but their attitudes differ largely. Only 29 percent of scientists are willing to buy GM soybean oil, similar to urban consumers (25 percent) in China. The knowledge of biology is extensive for some scientists but varies significant among scientists and correlates positively with their attitudes toward agricultural GM technology and GM soybean oil. Younger and male scientists with higher professional titles, and those involved in GM research are more in favor of China’s GM technology compared to other scientists. Female scientists, scientists with lower professional titles, those that have never engaged in GM research or are from non-agricultural scientific disciplines are less willing to buy GM soybean oil. Interestingly, their low willingness to buy GM soybean oil is inconsistent with the fact that it is the most common edible oil in China.

This study is the first to examine scientists’ attitudes toward GM technology and food in China. The results of this study contribute to understanding the current debates on GM technology and the relevance of research, based on the willingness to buy GM food, for decision making regarding the commercialization of GM technology.