ACQR: A Novel Framework to Identify and Predict Influential Users in Micro-Blogging

As key roles of online social networks, influential users in micro-blogging have the ability to influence the attitudes or behaviour of others. When it comes to marketing, the users’ influence should be associated with a certain topic or field on which people have different levels of preference and expertise. In order to identify and predict influential users in a specific topic more effectively, users’ actual influential capability on a certain topic and potential influence unlimited by topics is combined into a novel comprehensive framework named “ACQR” in this research. ACQR framework depicts the attributes of the influentials from four aspects, including activeness (A), centrality (C), quality of post (Q) and reputation (R). Based on this framework, a data mining method is developed for discovering and forecasting the top influentials. Empirical results reveal that our ACQR framework and the data mining method by TOPSIS and SVMs (with polynomial and RBF kernels) can perform very well in identifying and predicting influential users in a certain topic (such as iPhone 5). Furthermore, the dynamic change processes of users’ influence from longitudinal perspective are analysed and suggestions to the sales managers are provided

A Survey and Study on the Current Status of Mathematics Study Habits of Rural Junior High School Students in China

The research is supported by the research project of higher education reform in Jiangsu Province. Nos. 2019JSJG257, 2017JSJG212, Special research project on Rural Education in Yancheng City. No. XCZX21090, and Yancheng educational science planning project in 2021. No. 2021-L-136. (Sponsoring information) Abstract Based on the relevant theories, the article adopts literature research, questionnaire survey, and interview records to first analyze and summarize the research related to " mathematics study habits" and to define and classify the concepts related to "mathematics study habits." Take rural junior high school students in a school in China as the target group, and analyze the current situation of mathematics study habits of rural junior high school students in this school through a questionnaire survey based on the results. Furthermore, through personal interviews with rural junior high school students, teachers, and parents in the region, we completed the analysis of the factors that contribute to the formation of good mathematics study habits in rural junior high school students from the perspectives of students, teachers, and parents. Finally, combined with the current situation and influencing factors of mathematics learning habits of rural junior high school students in the region, corresponding countermeasures are proposed for the cultivation of good mathematical learning habits from the three perspectives of students, teachers and parents. Keywords: Rural junior high school students, Mathematics study habits, Influence factors, Habit development measures DOI: 10.7176/JEP/13-29-04 Publication date:October 31st 202

Hierarchical Sarsa Learning Based Route Guidance Algorithm

In modern society, route guidance problems can be found everywhere. Reinforcement learning models can be normally used to solve such kind of problems; particularly, Sarsa Learning is suitable for tackling with dynamic route guidance problem. But how to solve the large state space of digital road network is a challenge for Sarsa Learning, which is very common due to the large scale of modern road network. In this study, the hierarchical Sarsa learning based route guidance algorithm (HSLRG) is proposed to guide vehicles in the large scale road network, in which, by decomposing the route guidance task, the state space of route guidance system can be reduced. In this method, Multilevel Network method is introduced, and Differential Evolution based clustering method is adopted to optimize the multilevel road network structure. The proposed algorithm was simulated with several different scale road networks; the experiment results show that, in the large scale road networks, the proposed method can greatly enhance the efficiency of the dynamic route guidance system. Document type: Articl

Performance of supersonic steam ejectors considering the nonequilibrium condensation phenomenon for efficient energy utilisation

Supersonic ejectors are of great interest for various industries as they can improve the quality of the low-grade heat source in an eco-friendly and sustainable way. However, the impact of steam condensation on the supersonic ejector performances is not fully understood and is usually neglected by using the dry gas assumptions. The non-equilibrium condensation occurs during the expansion and mixing process and is tightly coupled with the high turbulence, oblique and expansion waves in supersonic flows. In this paper, we develop a wet steam model based on the computational fluid dynamics to understand the intricate feature of the steam condensation in the supersonic ejector. The numerical results show that the dry gas model exaggerates the expansion characteristics of the primary nozzle by 21.95%, which predicts the Mach number of 2.00 at the nozzle exit compared to 1.64 for the wet steam model. The dry gas model computes the static temperature lower to 196 K, whereas the wet steam model predicts the static temperature should above the triple point due to the phase change process. The liquid fraction can reach 7.2% of the total mass based on the prediction of the wet steam model. The performance analysis indicates that the dry gas model over-estimates a higher entrainment ratio by 11.71% than the wet steam model for the steam ejector

Range-only Collaborative Localization for Ground Vehicles

High-accuracy absolute localization for a team of vehicles is essential when accomplishing various kinds of tasks. As a promising approach, collaborative localization fuses the individual motion measurements and the inter-vehicle measurements to collaboratively estimate the states. In this paper, we focus on the range-only collaborative localization, which specifies the inter-vehicle measurements as inter-vehicle ranging measurements. We first investigate the observability properties of the system and derive that to achieve bounded localization errors, two vehicles are required to remain static like external infrastructures. Under the guide of the observability analysis, we then propose our range-only collaborative localization system which categorize the ground vehicles into two static vehicles and dynamic vehicles. The vehicles are connected utilizing a UWB network that is capable of both producing inter-vehicle ranging measurements and communication. Simulation results validate the observability analysis and demonstrate that collaborative localization is capable of achieving higher accuracy when utilizing the inter-vehicle measurements. Extensive experimental results are performed for a team of 3 and 5 vehicles. The real-world results illustrate that our proposed system enables accurate and real-time estimation of all vehicles' absolute poses.Comment: Proceedings of the 32nd International Technical Meeting of the Satellite Division of The Institute of Navigation (ION GNSS+ 2019