► Identify students’ patterns and themes of participations in LVS environments. ► Reveal a disciplinary difference in online LVS participation. ► A combination of using data mining and text mining ...techniques can yield considerable insights.
This study analyses the online questions and chat messages automatically recorded by a live video streaming (LVS) system using data mining and text mining techniques. We apply data mining and text mining techniques to analyze two different datasets and then conducted an in-depth correlation analysis for two educational courses with the most online questions and chat messages respectively. The study found the discrepancies as well as similarities in the students’ patterns and themes of participation between online questions (student–instructor interaction) and online chat messages (student–students interaction or peer interaction). The results also identify disciplinary differences in students’ online participation. A correlation is found between the number of online questions students asked and students’ final grades. The data suggests that a combination of using data mining and text mining techniques for a large amount of online learning data can yield considerable insights and reveal valuable patterns in students’ learning behaviors. Limitations with data and text mining were also revealed and discussed in the paper.
Various technology innovations and applications have been developed to fight the coronavirus pandemic. The pandemic also has implications for the design, development, and use of technologies. There ...is an urgent need for a greater understanding of what roles information systems and technology researchers can play in this global pandemic. This paper examines emerging technologies used to mitigate the threats of COVID-19 and relevant challenges related to technology design, development, and use. It also provides insights and suggestions into how information systems and technology scholars can help fight the COVID-19 pandemic. This paper helps promote future research and technology development to produce better solutions for tackling the COVID-19 pandemic and future pandemics.
Lithium metal anodes suffer from poor cycling stability and potential safety hazards. To alleviate these problems, Li thin‐film anodes prepared on current collectors (CCs) and Li‐free types of anodes ...that involve direct Li plating on CCs have received increasing attention. In this study, the atomic‐scale design of Cu‐CC surface lithiophilicity based on surface lattice matching of the bcc Li(110) and fcc Cu(100) faces as well as electrochemical achievement of Cu(100)‐preferred surfaces for smooth Li deposition with a low nucleation barrier is reported. Additionally, a purposely designed solid–electrolyte interphase is created for Li anodes prepared on CCs. Not only is a smooth planar Li thin film prepared, but a uniform Li plating/stripping on the skeleton of 3D CCs is achieved as well by high utilization of the surface and cavities of the 3D CCs. This work demonstrates surface electrochemistry approaches to construct stable Li metal–electrolyte interphases towards practical applications of Li anodes prepared on CCs.
Get in touch with lithium: The generation of surface lithiophilicity on planar and 3D Cu hosts for Li metal anodes is reported. Enabled by a lattice matching of Cu(100) and Li(110), smooth deposition of Li thin films and the creation of ultra‐smooth ultra‐thin SEI on the Cu hosts is made possible. This allows a high utilization of not only the surface but also cavities of the Cu hosts.
Purpose
Current knowledge management (KM) systems cannot be used effectively for decision-making because of the lack of real-time data. This study aims to discuss how KM can benefit by embedding ...Internet of Things (IoT).
Design/methodology/approach
The paper discusses how IoT can help KM to capture data and convert data into knowledge to improve the parking service in transportation using a case study.
Findings
This case study related to intelligent parking service supported by IoT devices of vehicles shows that KM can play a role in turning the incoming big data collected from IoT devices into useful knowledge more quickly and effectively.
Originality/value
The literature review shows that there are few papers discussing how KM can benefit by embedding IoT and processing incoming big data collected from IoT devices. The case study developed in this study provides evidence to explain how IoT can help KM to capture big data and convert big data into knowledge to improve the parking service in transportation.
Many industrial enterprises acquire disparate systems and applications over the years. The need to integrate these different systems and applications is often prominent for satisfying business ...requirements and needs. In an effort to help researchers in industrial informatics understand the state-of-the-art of the enterprise application integration, we examined the architectures and technologies for integrating distributed enterprise applications, illustrated their strengths and weaknesses, and identified research trends and opportunities in this increasingly important area.
The advances in cloud computing and internet of things (IoT) have provided a promising opportunity to resolve the challenges caused by the increasing transportation issues. We present a novel ...multilayered vehicular data cloud platform by using cloud computing and IoT technologies. Two innovative vehicular data cloud services, an intelligent parking cloud service and a vehicular data mining cloud service, for vehicle warranty analysis in the IoT environment are also presented. Two modified data mining models for the vehicular data mining cloud service, a Naïve Bayes model and a Logistic Regression model, are presented in detail. Challenges and directions for future work are also provided.
Holographic striped superconductor Ling, Yi; Wu, Meng-He
The journal of high energy physics,
03/2021, Letnik:
2021, Številka:
3
Journal Article
Recenzirano
Odprti dostop
A
bstract
We construct a holographic model describing the striped superconductor (SSC), which is characterized by the presence of pair density waves (PDW). We explicitly demonstrate that the SSC ...phase is implemented as the intertwined phase of charge density waves (CDW) order and uniform superconducting (SC) order. The interplay of PDW order, CDW order as well as the uniform SC order in SSC phase is studied. It is found that the PDW order is prominent when both CDW order and uniform SC order are balanced. The critical temperature of CDW becomes higher in the presence of the uniform SC order, but its charge density amplitude is suppressed. On the other hand, the SC order is not sensitive to the presence of CDW order. We also demonstrate that among all the possible solutions, the black hole in SSC phase has the lowest free energy and thus is thermodynamically favored.
► Perform social media competitive analysis for the three largest pizza chains. ► Apply text mining to analyze social media data. ► Reveal new knowledge and themes from social media data.
Social ...media have been adopted by many businesses. More and more companies are using social media tools such as Facebook and Twitter to provide various services and interact with customers. As a result, a large amount of user-generated content is freely available on social media sites. To increase competitive advantage and effectively assess the competitive environment of businesses, companies need to monitor and analyze not only the customer-generated content on their own social media sites, but also the textual information on their competitors’ social media sites. In an effort to help companies understand how to perform a social media competitive analysis and transform social media data into knowledge for decision makers and e-marketers, this paper describes an in-depth case study which applies text mining to analyze unstructured text content on Facebook and Twitter sites of the three largest pizza chains: Pizza Hut, Domino's Pizza and Papa John's Pizza. The results reveal the value of social media competitive analysis and the power of text mining as an effective technique to extract business value from the vast amount of available social media data. Recommendations are also provided to help companies develop their social media competitive analysis strategy.
This research involved two investigations that examined the effects of two types of affect (i.e., mood and emotion) on creativity motivation. Study 1 examined the degree to which noninduced habitual ...mood impacted creativity motivation in the context of a group of junior secondary school students in Hong Kong (
= 588), while Study 2 examined the effect of the experimental manipulation of emotion induction on creativity motivation in the context of a group of undergraduate students in Hong Kong (
= 653). The Chinese version of the Creativity Motivation Scale, the International Positive and Negative Affect Schedule-Short Form, and the Affect Grid were employed to assess creativity motivation, mood, and emotional states, respectively. Interesting findings were obtained. First, both studies consistently demonstrated a facilitating role of positive and negative affect in creativity motivation. Second, both studies consistently showed that the impact of positive affect on creativity motivation was stronger than that of negative affect. While previous affect-creativity research has focused predominantly on the role of affect in the cognitive components of creativity and yielded mixed results, this research adds to the literature by showing that students' motivation to engage in creativity-related behaviors can be influenced by a broad spectrum of affective experiences (i.e., positive and negative affect, stable and enduring moods, and momentary and mutable emotions). The theoretical and educational implications of the findings are highlighted.
The paper describes a study that examines the factors affecting Chinese users' online social media fatigue on WeChat from the perspective of perceived pressure. This study is based on the S-S-O ...(Stressor-Strain-Outcome) theoretical framework and uses the structural equation modeling to analyze the factors affecting Chinese users' online social media fatigue on WeChat. The results show that information overload, privacy concerns and time cost produce a strong positive impact on social media fatigue intention while compulsive use have a negative impact on social media fatigue intention. Fear of missing out (FoMO) affects social media fatigue intention not significantly, but FoMO indirectly affects social media fatigue intention through compulsive use. Intrinsic motivation plays a negatively moderating role between social media fatigue intention and fatigue behavior while extrinsic motivation plays a positively moderating role between them.
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