scholarly journals Adopting incentive mechanisms for large-scale participation in mobile crowdsensing: from literature review to a conceptual framework

2016 ◽  
Vol 6 (1) ◽  
Author(s):  
R. I. Ogie
Keyword(s):  
Literature Review ◽  
Conceptual Framework ◽  
Large Scale ◽  
Incentive Mechanisms ◽  
Mobile Crowdsensing

scholarly journals Designing Incentive Mechanisms for Mobile Crowdsensing with Intermediaries

2019 ◽  
Vol 2019 ◽  
pp. 1-14 ◽  
Author(s):  
Yatong Chen ◽  
Huangxun Chen ◽  
Shuo Yang ◽  
Xiaofeng Gao ◽  
Yunhe Guo ◽  
...  
Keyword(s):  
Network Model ◽  
Large Scale ◽  
Incentive Compatibility ◽  
Rapid Development ◽  
Sensor Technology ◽  
Incentive Mechanisms ◽  
Mobile Crowdsensing ◽  
Network Applications ◽  
Sensing Platform

In the past decade, with the rapid development of wireless communication and sensor technology, ubiquitous smartphones equipped with increasingly rich sensors have more powerful computing and sensing abilities. Thus, mobile crowdsensing has received extensive attentions from both industry and academia. Recently, plenty of mobile crowdsensing applications come forth, such as indoor positioning, environment monitoring, and transportation. However, most existing mobile crowdsensing systems lack vast user bases and thus urgently need appropriate incentive mechanisms to attract mobile users to guarantee the service quality. In this paper, we propose to incorporate sensing platform and social network applications, which already have large user bases to build a three-layer network model. Thus, we can publicize the sensing platform promptly in large scale and provide long-term guarantee of data sources. Based on a three-layer network model, we design incentive mechanisms for both intermediaries and the crowdsensing platform and provide a solution to cope with the problem of user overlapping among intermediaries. We theoretically prove the properties of our proposed incentive mechanisms, including incentive compatibility, individual rationality, and efficiency. Furthermore, we evaluate our incentive mechanisms by extensive simulations. Evaluation results validate the effectiveness and efficiency of our proposed mechanisms.

Investigating Diseases and Chemicals in COVID-19 Literature with Text Mining (Preprint)

2020 ◽  
Author(s):  
Amir Karami ◽  
Brandon Bookstaver ◽  
Melissa Nolan
Keyword(s):  
Text Mining ◽  
Literature Review ◽  
Topic Modeling ◽  
Large Scale ◽  
Clinical Manifestations ◽  
International Health ◽  
Research Papers ◽  
Strategic Plans ◽  
Funding Agencies ◽  
The Relationship

BACKGROUND The COVID-19 pandemic has impacted nearly all aspects of life and has posed significant threats to international health and the economy. Given the rapidly unfolding nature of the current pandemic, there is an urgent need to streamline literature synthesis of the growing scientific research to elucidate targeted solutions. While traditional systematic literature review studies provide valuable insights, these studies have restrictions, including analyzing a limited number of papers, having various biases, being time-consuming and labor-intensive, focusing on a few topics, incapable of trend analysis, and lack of data-driven tools. OBJECTIVE This study fills the mentioned restrictions in the literature and practice by analyzing two biomedical concepts, clinical manifestations of disease and therapeutic chemical compounds, with text mining methods in a corpus containing COVID-19 research papers and find associations between the two biomedical concepts. METHODS This research has collected papers representing COVID-19 pre-prints and peer-reviewed research published in 2020. We used frequency analysis to find highly frequent manifestations and therapeutic chemicals, representing the importance of the two biomedical concepts. This study also applied topic modeling to find the relationship between the two biomedical concepts. RESULTS We analyzed 9,298 research papers published through May 5, 2020 and found 3,645 disease-related and 2,434 chemical-related articles. The most frequent clinical manifestations of disease terminology included COVID-19, SARS, cancer, pneumonia, fever, and cough. The most frequent chemical-related terminology included Lopinavir, Ritonavir, Oxygen, Chloroquine, Remdesivir, and water. Topic modeling provided 25 categories showing relationships between our two overarching categories. These categories represent statistically significant associations between multiple aspects of each category, some connections of which were novel and not previously identified by the scientific community. CONCLUSIONS Appreciation of this context is vital due to the lack of a systematic large-scale literature review survey and the importance of fast literature review during the current COVID-19 pandemic for developing treatments. This study is beneficial to researchers for obtaining a macro-level picture of literature, to educators for knowing the scope of literature, to journals for exploring most discussed disease symptoms and pharmaceutical targets, and to policymakers and funding agencies for creating scientific strategic plans regarding COVID-19.

scholarly journals Human-Centered Artificial Intelligence for Designing Accessible Cultural Heritage

2021 ◽  
Vol 11 (2) ◽  
pp. 870
Author(s):  
Galena Pisoni ◽  
Natalia Díaz-Rodríguez ◽  
Hannie Gijlers ◽  
Linda Tonolli
Keyword(s):  
Artificial Intelligence ◽  
Literature Review ◽  
Cultural Heritage ◽  
Conceptual Framework ◽  
Interaction Design ◽  
Participatory Design ◽  
Future Directions ◽  
Heritage Sites ◽  
Review Analysis

This paper reviews the literature concerning technology used for creating and delivering accessible museum and cultural heritage sites experiences. It highlights the importance of the delivery suited for everyone from different areas of expertise, namely interaction design, pedagogical and participatory design, and it presents how recent and future artificial intelligence (AI) developments can be used for this aim, i.e.,improving and widening online and in situ accessibility. From the literature review analysis, we articulate a conceptual framework that incorporates key elements that constitute museum and cultural heritage online experiences and how these elements are related to each other. Concrete opportunities for future directions empirical research for accessibility of cultural heritage contents are suggested and further discussed.

Design and evaluation of characteristic incentive mechanisms in Mobile Crowdsensing Systems

2015 ◽  
Vol 55 ◽  
pp. 95-106 ◽  
Author(s):  
Constantinos Marios Angelopoulos ◽  
Sotiris Nikoletseas ◽  
Theofanis P. Raptis ◽  
José Rolim
Keyword(s):  
Incentive Mechanisms ◽  
Mobile Crowdsensing

scholarly journals Bridging BIM and building: From a literature review to an integrated conceptual framework

2015 ◽  
Vol 33 (6) ◽  
pp. 1405-1416 ◽  
Author(s):  
Ke Chen ◽  
Weisheng Lu ◽  
Yi Peng ◽  
Steve Rowlinson ◽  
George Q. Huang
Keyword(s):  
Literature Review ◽  
Conceptual Framework

scholarly journals How Tour Guides’ Professional Competencies Influence on Service Quality of Tour Guiding and Tourist Satisfaction: An Exploratory Research

2017 ◽  
Vol 7 (1) ◽  
Author(s):  
Yi-Chien Lin ◽  
Mei-Lan Lin ◽  
Yi-Cheng Chen
Keyword(s):  
Service Quality ◽  
Conceptual Framework ◽  
Least Squares ◽  
Partial Least Squares ◽  
Large Scale ◽  
Online Survey ◽  
Professional Competencies ◽  
Convenience Sample ◽  
Tour Guides ◽  
Tourist Satisfaction

Drawing upon the theoretical perspectives from activity competency model and prior tourism literature, this study propose a conceptual framework to explain the impacts of professional competencies on service quality and tourist satisfaction. Empirical data were gathered from a large-scale online survey with experienced GPT tourists to test the proposed hypotheses and research model. The proposed conceptual framework was validated using the partial least squares (PLS) technique. Data gathered from tourists was based on a convenience sample of 345 respondents to test the proposed plausible hypotheses. The conceptual model was validated using the partial least squares (PLS) technique. The empirical results indicate that tour guides’ professional competencies significantly impact on service quality and tourist satisfaction; and tour guides’ service quality positively influences tourist satisfaction.

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