Information is traditionally confined to paper or digitally to a screen. In this paper, we introduce WUW, a wearable gestural interface, which attempts to bring information out into the tangible world. By using a tiny projector and a camera mounted on a hat or coupled in a pendant like wearable device, WUW sees what the user sees and visually augments surfaces or physical objects the user is interacting with. WUW projects information onto surfaces, walls, and physical objects around us, and lets the user interact with the projected information through natural hand gestures, arm movements, or interaction with the object itself.

Carboxyl‐containing polysiloxane (LCCP) has been successfully applied in the flame retardancy of polycarbonate (PC). The LCCP was synthesized by hydrosilylation and condensation reaction. The presence of carboxyl groups has been demonstrated to be crucial to provide high flame retardant effectiveness. The flame retardancy of LCCP–PC composites is investigated by limiting oxygen index (LOI), vertical burning tests (UL‐94). At the mole ratio of diethoxymethyl (1‐propionyloxy) silane/diethoxydimethylsilane = 8/100 in LCCP(3), the best flame retardant performance of LCCP‐PC composites was obtained. The LOI value of the composites is 38.5 and the UL‐94 rating reaches V‐0 when the content of LCCP(3) is as low as 0.5 wt %. Evolution of the thermal behaviors of the composites tested by thermogravimetric analysis shows that addition of LCCP(3) in PC can reduce the degradation speed of PC and induce a reduction of the initiated decomposition temperature of PC. © 2013 Wiley Periodicals, Inc. J. Appl. Polym. Sci., 2014, 131, 39814.

The high volume of increasingly sophisticated cyber threats is drawing growing attention to cybersecurity, where many challenges remain unresolved. Namely, for intrusion detection, new algorithms that are more robust, effective, and able to use more information are needed. Moreover, the intrusion detection task faces a serious challenge associated with the extreme class imbalance between normal and malicious traffics. Recently, graph-neural network (GNN) achieved state-of-the-art performance to model the network topology in cybersecurity tasks. However, only a few works exist using GNNs to tackle the intrusion detection problem. Besides, other promising avenues such as applying the attention mechanism are still under-explored.This paper presents two novel graph-based solutions for intrusion detection, the modified E-GraphSAGE and E-ResGAT algorithms, which rely on the established GraphSAGE and graph attention network (GAT), respectively. The key idea is to integrate residual learning into the GNN leveraging the available graph information. Residual connections are added as a strategy to deal with the high class imbalance, aiming at retaining the original information and improving the minority classes' performance. An extensive experimental evaluation on four recent intrusion detection datasets shows the excellent performance of our approaches, especially when predicting minority classes.

BackgroundAffected by the COVID-19, many colleges have adopted online teaching. Meanwhile, the digital transformation of academic journals has shifted readers’ reading habits from traditional paper media to digital media. Digital academic reading has become the main reading method of college students during the COVID-19 pandemic.PurposeThe purpose of this study was to investigate the behavioral characteristics of college students’ digital academic reading and explore the internal factors and external environmental factors affecting the Intention and Use behavior of digital academic reading. At the same time this study provide recommendations to address these influencing factors in terms of the individual, the environment and library resources.MethodsBased on UTAUT2 model and digital academic reading theories, this paper constructs a digital academic reading information behavior (DARB) model of college students to examine college students’ digital academic reading behavior and intention. College students with digital academic reading behavior were recruited as research participants. A multi-stage sampling technique was used to collect representative samples from universities in Nanjing. 239 respondents participated in the questionnaire, with 189 providing valid data. Results: Effort expectancy (EE), social influence (SI), price value (PV), perceived risk (PR) and habit (BH) have a significant impact on behavioral intention (BI), and behavioral intention (BI) and habit (BH) have a significant impact on use behavior (B). However, performance expectancy (PE) and facilitating conditions (FC) have no significant influence on behavioral intention (BI).Originality/valueThe findings of this study will help fill the gap in previous research on the relationship between the influencing factors of digital academic reading and college students’ reading intentions and behaviors, so as to provide a basis for improving the academic reading literacy program in colleges and optimizing the current digital academic reading environment.

BackgroundShort videos play a key role in the process of tourism destination promotion, and attractive short videos can bring tourist flow and economic income growth to tourist attractions. Many tourist attractions in China have achieved remarkable success through short video promotion.PurposeThe purpose of this study was to investigate the behavioral characteristics of short video users browsing short tourism videos and explore what factors of short video affected users’ tourism intention. This study also compared which factors were most important in triggering users’ tourism intention in marketing communication via short tourism videos in order to shed light on tourism destination strategy and facilitate adaptation to market development trends.MethodsThis study developed a conceptual model by extending the stimulus-organism-response (SOR) model with technology acceptance factors (perceived usefulness, perceived ease of use) and short video factors (perceived enjoyment, perceived professionalism, perceived interactivity) to examine users’ tourism intention. A convenience random sampling technique was used to distribute the questionnaire in Chinese city of Nanjing. Four hundred twenty-one respondents participated in the questionnaire, with 395 providing valid data.ResultsThe results of the SEM analysis show that all posed hypotheses (Perceived professionalism - > Telepresence, Perceived interactivity - > Telepresence, Perceived enjoyment - > Telepresence, Perceived ease of use - > Telepresence, Perceived enjoyment - > Flow experience, Perceived ease of use - > Flow experience, Telepresence - > Flow experience, Telepresence - > Tourism intention, Flow experience - > Tourism intention) are confirmed except for (Perceived usefulness - > Tourism intention), which is not confirmed.ConclusionThe findings of this study will help fill the gap in previous research on the relationship between short video influencing factors and users’ tourism intention, thus contributing to the academic research on emerging short videos and the endorsement of destinations promoted by technological innovation.