“高电压技术”课程线上线下混合式教学

本文采用超星学习通线上教学平台，以 “高电压技术”课程为对象，实施了规模为120余人的线上线下混合式教学。基于线上教学和传统教学的优势互补，设计了“高电压技术”多个教学环节。归纳分析了混合式教学在各个教学环节取得的效果和问题，并根据学生反馈提出了持续性的改进措施。     

Picosecond laser trimming of ceramic cores with porous multi-scale particle microstructure

The ceramic core, produced by hot injection molding, is one of the critical components for manufacturing high-performance aircraft engine turbine blades. However, the injection molding process will cause defects such as burrs and flashes in the fine structure of the formed ceramic core. Manual trimming is necessary, but the trimming quality is poor, and the yield is low. In this paper, the online trimming method of ceramic cores is studied. Based on the orthogonal experiment method, the optimal laser parameters for processing the ceramic core's porous multi-scale particle structure material were obtained. Further, the problems of the match head and tail phenomenon and dimensional accuracy improvement in trimming ceramic cores have been studied. A path optimisation method is proposed to improve the quality and accuracy of the trimming profile effectively. Finally, the overall process flow of ceramic core trimming is elaborated, and experimental verification is given. The results show that the ceramic core online trimming method proposed in this paper has advantages of high precision and high yield compared with the manual method, which will have substantial potential application value in the aviation field.     

Modeling online user behaviors with competitive interactions

Online user behaviors are increasingly modulated by social media. Extant literature mainly focuses on investigating how network structures affect user behaviors. However, recent empirical results demonstrate that user behaviors and network structures usually coevolve dynamically, and topological patterns turn out to be inadequate for characterizing real-world user behaviors. In this paper, we present a dynamic model to deal with this challenge. This proposed model is mainly governed by two competing principles: homophily and homeostasis. Empirical evaluations of three online real-world datasets suggest that the proposed dynamic model can well predict long-range online user behaviors.     

面向不平衡数据流的自适应加权在线超限学习机算法

一般的在线学习算法对不平衡数据流的分类识别会遇到较大困难,特别是当数据流发生概念漂移时,对其进行分类会变得更困难.文中提出面向不平衡数据流的自适应加权在线超限学习机算法,自动调整实时到达的训练样本的惩罚参数,达到在线学习不平衡数据流的目的.文中算法可以适用于不同偏斜程度的静态数据流的在线学习和发生概念漂移时数据流的在线学习.理论分析和在多个真实数据流上的实验表明文中算法的正确性和有效性.     

Efficient model selection for real-time adaptive cold start strategy of a fuel cell system on vehicular applications

The PEMFC maximum power is greatly influenced by subfreezing temperature and degradation phenomena. Therefore, a dependable model is required to estimate the power with respect to the variation of the operating conditions and state of health. Semi-empirical models are potent tools in this regard. Nonetheless, there is not much information about their cold environment reliability. This paper comprehensively compares the performance of some models (already tested in normal ambient temperature) in subfreezing condition to introduce the most reliable one for PEMFC cold start-up application. Firstly, seven models are compared regarding voltage losses and precision. Subsequently, the three most dependable ones are selected and experimentally compared at sub-zero temperature in terms of polarization curve estimation for three PEMFCs with different degradation levels. The results of this study indicate that the model introduced by Amphlett et al. has a superior performance compared to other ones regarding the characteristic's estimation in below-zero temperature.     

Digital Extraction Column: Measurement and Modeling Techniques

The digitization of extraction columns requires a profound knowledge of the present hydrodynamics/mass transport interaction as well as appropriate measurement techniques for the detection of relevant input and target values. In this article, the different techniques for droplet size distribution as well as concentration determination are presented and new methods for online evaluation are discussed. In combination with the simulation of droplet size, holdup and solute concentration distribution, an online-capable process tool for controlling and optimizing extraction columns will be obtained.     

Revisiting Linus’s law: Benefits and challenges of open source software peer review

Open source projects leverage a large number of people to review products and improve code quality. Differences among participants are inevitable and important to this collaborative review process—participants with different expertise, experience, resources, and values approach the problems differently, increasing the likelihood of finding more bugs and fixing the particularly difficult ones. To understand the impacts of member differences on the open source software peer review process, we examined bug reports of Mozilla Firefox. These analyses show that the various types of member differences increase workload as well as frustration and conflicts. However, they facilitate situated learning, problem characterization, design review, and boundary spanning. We discuss implications for work performance and community engagement, and suggest several ways to leverage member differences in the open source software peer review process.     

Risk factors associated with online game addiction: A hierarchical model

Online gaming addiction has been increasingly recognized as a mental disorder. However, the predictive factors that lead to online gaming addiction are not well established. The aim of this study was to identify factors that may influence the development of online gaming addiction. A total of 263 patients with problematic online gaming addiction (255 males (97%) and 8 females (3%), age: mean = 20.4 ± 5.8 years) and153 healthy comparison subjects (118 males (77%) and 35 females (23%), age: 21.2 ± 5.5 years, range) were recruited for participation in the current study. Hierarchical logistic regression analyses among each set of variables were conducted. Individual factors (sex and age), cognitive factors (IQ and perseverative errors), psychopathological conditions (ADHD, depression, anxiety, and impulsivity), and social interaction factors (family environment, social anxiety, and self-esteem) were evaluated in a stepwise fashion. All four factors were associated with online gaming addiction, with psychopathological conditions being the strongest risk factors for the addiction. Individual factors, psychological factors, and social interactions were associated with the development of pure online gaming addiction. As before, psychological factors (attention, mood, anxiety and impulsivity) were the strongest risk factors for online gaming addiction in patients with pure online gaming addiction. Psychopathologies, including ADHD and depression, were the strongest factors associated with the development of online gaming addiction in individuals.     

Adolescents’ comments in social media: Why do adolescents receive negative feedback and who is most at risk?

Receiving negative peer feedback in social media may have negative consequences for adolescents’ psychosocial development and well-being. Therefore, the first aim of this study was to investigate online behavior (i.e., online social exploration, risky online self-presentation) that predicts receiving negative online peer feedback. The second aim was to examine three types of precursors that may predict this online behavior and, indirectly, negative feedback: (a) developmental (i.e., sex, age), (b) dispositional (i.e., sensation seeking, inhibitory control), and (c) social precursors (i.e., peer problems, family conflict). We collected survey data among 785 Dutch adolescents (10–15 years old). Our results showed that adolescents who engaged in online social exploration and risky online self-presentation more often, were more likely to receive negative peer feedback. Online social exploration was more prevalent among the older adolescents and adolescents characterized by higher sensation seeking and more family conflict. In addition, risky online self-presentation was more prevalent among adolescents high in sensation seeking. Consequently, these adolescents’ online behavior, indirectly, made them more at risk of receiving negative peer feedback in social media.     

Automatic analysis and identification of verbal aggression and abusive behaviors for online social games

Online multiplayer games create new social platforms, with their own etiquette, social rules of conduct and ways of expression. What counts as aggressive and abusing behavior may change depending on the platform, but most online gaming companies need to deal with aggressive and abusive players explicitly. This usually is tied to a reporting mechanism where the offended player reports an offense. In this paper, we develop tools for validating whether a verbal aggression offense report refers to a real offense or not, in the context of a very popular online social game, called Okey. Our approach relies on the analysis of player behavior and characteristics of offending players. In the proposed system, chat records and other social activities in the game are taken into account, as well as player history. This methodology is sufficiently generic, and it can be applied to similar gaming platforms, thus describing a useful tool for game companies. We report our results on data collected over a six months period, involving 100,000 users and 800,000 game records, and illustrate the viability of such analysis, while providing insights on the factors associated with verbal aggression and abusive behavior for social games.