Learning-based wildfire tracking with unmanned aerial vehicles

This project attempts to design a path planning algorithm for a group of unmanned aerial vehicles (UAVs) to track multiple spreading wildfire zones on a wildland. Due to the physical limitations of UAVs, the wildland is partially observable. Thus, the fire spreading is difficult to model. An online training regression neural network using real-time UAV observation data is implemented for fire front positions prediction. The wildfire tracking with UAVs path planning algorithm is proposed by Q-learning. Various practical factors are considered by designing an appropriate cost function which can describe the tracking problem, such as importance of the moving targets, field of view of UAVs, spreading speed of fire zones, collision avoidance between UAVs, obstacle avoidance, and maximum information collection. To improve the computation efficiency, a vertices-based fire line feature extraction is used to reduce the fire line targets. Simulation results under various wind conditions validate the fire prediction accuracy and UAV tracking performance.Includes bibliographical references

How Does Word of Mouth from Different Components Systems Influence Product Sales differently?

Online word-of-mouth (WOM) has become an important reference for customers’ online purchase decisions. However, current studies ignore the various effects of WOM in different components, i.e., online reviews and the replies in the question and answer (Q &A) discussion area. To fill such a research gap, this study explores the relationship between WOM in two different forms and product sales. We measure the semantic features and thematic consistency of two forms of WOM and product sales. The findings show that the review component and Q&A component differ significantly in terms of quantity and content richness, with the review component being richer and more voluminous and the Q&A section having less content and relatively less quantity in comparison. Besides, the OLS results suggest that topic consistency has a negative impact on product sales, while the richness characteristics of both have a positive impact on product sales, and that the content richness of the Q&A component has a greater impact on sales than the review component

Exploring Crowdfunding Success in Cross-Culture Framework

With the rapid development of reward-based crowdfunding, how to make creative projects stand out is of great significance to entrepreneurs and other stakeholders. This study tends to explore the impact of the number of projects within the same category on crowdfunding success and the impact of spatial clustering effect on crowdfunding success. We draw upon a sample of 11,576,590 daily observations of 331,104 projects from Kickstarter, finding a negative association exists between the number of projects within the same category (NPSC) and crowdfunding success, which means that the concurrent impact of the number of projects within the same category (NPSC) on crowdfunding success displays the much larger competitive effects. The preliminary findings are discussed, and it is hoped that this work can be used to explore the key factors influencing the fundraising success of reward-based crowdfunding projects

Research on Image Perception of Luxury Hotels in Dalian Based on Text Analysis

In recent years, with the development of mobile Internet and smartphones, more and more consumers will share their feelings and thoughts after staying in the hotel on the website, thus forming many online comments. These online comments reflect consumers\u27 perception of the hotel image to a certain extent. This paper uses Python to collect 35977 online comment data of luxury hotels in Dalian. Through the analysis of high-frequency words, characteristic words, and comment emotion, it is found that the main factors affecting the perception of hotel image are: hotel location, room condition, environmental sanitation, service attitude, and professional ability of receptionist and other service personnel. Finally, according to the research conclusions, provide personalized suggestions for the hotel to improve its image

Automatic Recognition of Knowledge Characteristics of Scientific and Technological Literature from the Perspective of Text Structure

This paper independently explores the chapter structure of scientific and technological literature in the field of shipbuilding in the natural sciences and the field of library and information in the social sciences. The chapter structure model of previous studies, namely \u27background, purpose, method, result, conclusion, demonstration,\u27 is quoted as the verification object of the document chapter structure in the field of exploration. In order to verify the rationality of the structure, this paper uses the deep learning models TextCNN, DPCNN, TextRCNN, and BiLSTM-Attention as experimental tools, and designs 5-fold cross-validation experiment and normal experiment, and finally verifies the rationality of the model structure, and It is concluded that the BiLSTM-Attention model can better identify the chapter structure in this field

The Impact of Platform Social Responsibility on Consumer Trust

The concept of social responsibility has been widely applied incorporates business philosophy to gain the trust of consumers. With the rise of two-side platforms, platforms have popped up the limelight along with the hot topic of the sharing economy. Despite this, we do not know much about the underlying mechanisms of consumer trust. A questionnaire survey was conducted with 263 consumers from China to explore the consequences of platform social responsibility on consumer trust. The results demonstrate that the implementation of social responsibility by platforms significantly increases consumer trust. Additionally, consumer confusion plays a mediating effect, and platform network externality plays a moderating role. Briefly, the platform does not play a dominant role in regulating supply and demand as we might think since the consciousness of consumer groups is rising. Their autonomy to collect information and make decisions after perception cannot be ignored. The study shows that sharing economy platforms should take their social responsibilities into consideration, rather than taking them as a subsidiary role. Platforms should see consumer trust as a key end rather than a means to promote profits

The Impact of Employment Discrimination on Job Search Performance

This study is to explore the impact of perceived employment discrimination on job search performance. Based on the trait activation theory, this article proposes that people’s perceived employment discrimination when searching jobs online has a direct effect on job search performance, moderated by self-efficacy of job applicants. A total of 97 valid questionnaires were collected in this study. Through data analysis, we have concluded that the perceived impact of employment discrimination on job search performance is significantly negatively correlated, and job applicants’ self-efficacy is not significant. Such results have implications for the human resource managers and job applicants to adopt positive attitudes to deal with the possible facing discrimination generated during searching a job in the internet era