Article
Engineering, Multidisciplinary
Huiying Zhang, Runbo Zhao, Zuguo Yang
Summary: This paper investigates the evolutionary paths of blockchain technology from a technology management perspective, including topic identification, topic evolution analysis, and topic prediction. The findings include five major application fields, several emerging and lasting technical topics, and the two longest evolutionary paths.
INTERNATIONAL JOURNAL OF TECHNOLOGY MANAGEMENT
(2023)
Article
Chemistry, Multidisciplinary
Monika Tanwar, Hyunseok Park, Nagarajan Raghavan
Summary: This study introduces a state-based diagnostic and prognostic methodology for lubricating oil degradation using the sticky hierarchical Dirichlet process-hidden Markov model (HDP-HMM). By considering multiple states in the wear-out phase of LCM data, the proposed framework improves the precision and accuracy of diagnostics and prognostics, providing guidance for maintenance decision making.
APPLIED SCIENCES-BASEL
(2021)
Article
Computer Science, Information Systems
Jingru Sun, Mu Peng, Hongbo Jiang, Qinghui Hong, Yichuang Sun
Summary: With the proposal of the HMIAN model, it aims to better predict short-term traffic flow by considering the spatial and temporal features and effectively fusing traffic data with external factors. Experimental results demonstrate the effectiveness of the hierarchical mapping structure and the influence of different external factors on traffic prediction, providing valuable insights for future research in this area.
IEEE INTERNET OF THINGS JOURNAL
(2022)
Article
Energy & Fuels
Xiao Chen, Chad Zanocco, June Flora, Ram Rajagopal
Summary: This research proposes and tests a new framework that utilizes a dynamic energy lifestyles approach to understand residential electricity demand. By extracting latent household energy attributes using the Latent Dirichlet Allocation method, six distinct energy lifestyle profiles are derived using clustering techniques. The study finds that approximately 73% of households exhibit multiple lifestyle patterns within a year.
Article
Computer Science, Artificial Intelligence
Wanyin Xu, Yun Li, Jipeng Qiang
Summary: DCSS is a dynamic clustering algorithm based on the Dirichlet process, which can automatically learn the number of topics in documents and solve the topic drift problem of short text streams. By considering the correlation of topic distribution at neighbouring time points and utilizing the prior distribution, DCSS outperforms existing methods and exhibits better stability in experiments on two widely used datasets.
APPLIED INTELLIGENCE
(2022)
Article
Business
Junhan Kim, Youngjung Geum
Summary: This study proposes a systematic and concrete framework to develop data-driven technology roadmaps, consisting of three phases: layer mapping, contents mapping, and opportunity finding. This contributes to the field by providing a systematic method for data-driven roadmapping and offering data-driven evidence for more reasonable decision-making by experts.
TECHNOLOGICAL FORECASTING AND SOCIAL CHANGE
(2021)
Review
Statistics & Probability
Kuhwan Jeong, Yongdai Kim
Summary: The paper introduces a dynamic HDP topic model and its updating algorithm, which simplifies the updating process by combining variational inference algorithm and power prior approach without requiring a complicated dynamic generative model. Analysis on real datasets shows that the proposed algorithm is a useful alternative approach for dynamic HDP topic identification.
JOURNAL OF THE KOREAN STATISTICAL SOCIETY
(2021)
Review
Business
Susanne Adler, Marko Sarstedt
Summary: The study reveals that a stable core group of prominent authors has shaped and expanded CLT research, with topic modeling showing an expansion into interdisciplinary and applied contexts. While CLT's relevance in consumer research has increased, traditional areas of CLT research like planning fallacy and impulse control have shown a decline in momentum. The findings suggest the need for a more comprehensive societal focus in future CLT-related research.
PSYCHOLOGY & MARKETING
(2021)
Article
Neurosciences
Lin Jiang, Fali Li, Zhaojin Chen, Bin Zhu, Chanlin Yi, Yuqin Li, Tao Zhang, Yueheng Peng, Yajing Si, Zehong Cao, Antao Chen, Dezhong Yao, Xun Chen, Peng Xu
Summary: In this study, a new scheme combining EEG and DTI was developed to quantify the ITV and map the ITVN in the human brain. The ITVN revealed bottom-up and top-down interactions during P300 generation, with high velocity exchange between visual and attention-activated regions. The inter-individual variability in P300 was found to be related to differences in information transmission efficiency, providing new insight into cognitive degenerations.
Article
Computer Science, Artificial Intelligence
Haobo Xiong, Shuting Wang, Mingrong Tang, Liping Wang, Xuemin Lin
Summary: The paper presents a comprehensive approach for complex question answering over KG, addressing challenges in topic entity recognition, candidate path ranking, and answer fusion.
KNOWLEDGE-BASED SYSTEMS
(2021)
Article
Computer Science, Artificial Intelligence
Yitang Wang, Kunpeng Li, Qingye Li, Yong Pang, Liye Lv, Wei Sun, Xueguan Song
Summary: Multi-fidelity information fusion has attracted increasing attention for its promising in engineering design and optimization. In order to improve the approximation performance, a feature mapping-based hierarchical surrogate model for the fusion of LF and HF information is developed. The experiments demonstrate that our method outperforms other methods in 97.436% of the thirteen test problems under three different quantitative evaluations.
KNOWLEDGE-BASED SYSTEMS
(2023)
Article
Medical Informatics
Guanglei Yu, Linlin Zhang, Ying Zhang, Jiaqi Zhou, Tao Zhang, Xuehua Bi
Summary: This study proposed an improved four-layer supervised latent Dirichlet allocation (sLDA) approach, Hierarchical sLDA model, to categorize patient features in HDRs about CHD. By combining RFs and SMOTE methods to address data missing and imbalance issues, utilizing TF-IDF processing of datasets, applying variational Bayes expectation-maximization method and generalized linear model to recognize the latent clinical state of a patient, i.e., risk stratification, and predict CHD.
Our proposed approach was shown to enhance training time by 59.74% and testing time by 25.58% compared to the Multi-class sLDA model, with almost no loss of average prediction accuracy on the datasets. The results demonstrate that the Hierarchical sLDA model is competitive in time performance and accuracy, and hierarchical processing of patient features can significantly improve the efficiency and time-consuming nature of the sLDA model.
BMC MEDICAL INFORMATICS AND DECISION MAKING
(2022)
Article
Education & Educational Research
Marta F. Arroyabe, Martin Schumann, Carlos F. A. Arranz
Summary: This paper provides a comprehensive review and analysis of the literature on the entrepreneurial university, using text-mining techniques. The study finds that the research in this field is diverse and covers various topics, with a focus on academic entrepreneurship, commercialization of research, and university-industry alliances. Traditional case-study research is losing momentum, while emerging areas such as entrepreneurial capability and university-industry alliances are gaining popularity.
STUDIES IN HIGHER EDUCATION
(2022)
Article
Robotics
Ran Long, Christian Rauch, Tianwei Zhang, Vladimir Ivan, Sethu Vijayakumar
Summary: This work proposes a novel RGB-D SLAM approach to handle static background and large dynamic rigid objects simultaneously, addressing the issue of dynamic objects occluding major portions of the camera view. By treating all dynamic parts as one rigid body, it achieves simultaneous segmentation and tracking of static and dynamic components without requiring prior knowledge of dynamic object shape and appearance.
IEEE ROBOTICS AND AUTOMATION LETTERS
(2021)
Article
Mathematics
Dongfen Li, Yundan Zheng, Xiaofang Liu, Jie Zhou, Yuqiao Tan, Xiaolong Yang, Mingzhe Liu
Summary: This paper solves the problem of channel particle allocation in quantum communication by combining the decision tree algorithm of machine learning with quantum communication. A hierarchical quantum information splitting scheme based on the multi-particle state is proposed, and experimental verification shows that the scheme is reliable and has high security and efficiency.
Article
Green & Sustainable Science & Technology
Jihong Chen, Kai Zhang, Yuan Zhou, Yufei Liu, Lingfeng Li, Zheng Chen, Li Yin
Article
Green & Sustainable Science & Technology
Huanyong Ji, Guannan Xu, Yuan Zhou, Zhongzhen Miao
Article
Computer Science, Artificial Intelligence
Jihong Chen, Kai Zhang, Yuan Zhou, Zheng Chen, Yufei Liu, Zhuo Tang, Li Yin
Article
Chemistry, Physical
Xin Li, Mingjie Fan, Yuan Zhou, Jing Fu, Fei Yuan, Lucheng Huang
Article
Computer Science, Interdisciplinary Applications
Guannan Xu, Weijie Hu, Yuanyuan Qiao, Yuan Zhou
Article
Business
Yuan Zhou, Zhaofu Li, Yufei Liu, Fankang Deng
Summary: The study proposes a three-layered framework using multisource heterogeneous data and network methods to measure cluster-proximity in innovation clusters, aiming to better understand the combined proximity between organizations within network communities. Findings from a case study show that machine-tool firms/organizations with high cluster proximity within geographic communities enriched by business connections, highlighting the importance of knowledge linkages in across-community proximity.
IEEE TRANSACTIONS ON ENGINEERING MANAGEMENT
(2021)
Article
Business
Yuan Zhou, Rong Zhou, Luyi Chen, Yun Zhao, Qintian Zhang
Summary: This article examines the impacts of municipal-level environmental policy mixes on the textile industry in China. The results show that these policy mixes can promote green performance without compromising productivity growth, and the impacts vary in different cities.
IEEE TRANSACTIONS ON ENGINEERING MANAGEMENT
(2022)
Article
Chemistry, Multidisciplinary
Yufei Liu, Guan Wang, Yuan Zhou, Yuhan Liu
Summary: This study proposes a novel framework for analyzing the evolutionary pathways of advanced technologies in the emerging field of nanogenerators. By calculating the similarity between clusters of different layers, the evolutionary pathways from grants to papers and then to patents are drawn, monitoring the development of established technologies and identifying emerging technologies under research.
Article
Business
Guannan Xu, Yuan Zhou, Huanyong Ji
Summary: The traditional technology diffusion literature focuses on the diffusion of technologies within the existing manufacturing paradigm, while few studies have explored the determinants and mechanisms of technology diffusion when moving across manufacturing paradigms. This article aims to explore the intrinsic and institutional factors, as well as the impact mechanism on technology diffusion in the context of manufacturing paradigm shift. The study reveals that government interventions, especially indirect ones, have significant moderating effects on the influential mechanism of technology diffusion in a manufacturing paradigm shift.
IEEE TRANSACTIONS ON ENGINEERING MANAGEMENT
(2023)
Article
Computer Science, Information Systems
Rongjia Zhang, Wenqin Zhong, Na Wang, Ruxu Sheng, Yiqi Wang, Yuan Zhou
Summary: This paper compares the intelligent connected vehicle policies of the U.S., the EU, Japan, and China, and analyzes the local industrial policies of intelligent connected vehicles issued by major cities in China since 2016. The results show that cities like Beijing, Shanghai, and Guangzhou have implemented intelligent connected vehicle policies that significantly promote industrial innovation. These cities have chosen environment-oriented industrial policies, represented by target planning and legal regulation, to make the industrial development more comprehensive and systematic.
Article
Environmental Studies
Peichao Dai, Ruxu Sheng, Zhongzhen Miao, Zanxu Chen, Yuan Zhou
Summary: Based on China's industrial land transfer data from 2010 to 2019, this study quantitatively analyzed the transfer structure and spatial distribution characteristics. The research showed significant differences in transfer scale among provinces, with Western China having smaller scales compared to Eastern and Central regions. The study identified hotspots in industrial land transfer, such as mineral-rich Western regions and modern manufacturing and high-tech industries in Eastern coastal areas.
Article
Business
Yuan Zhou, Zhongzhen Miao, Frauke Urban
Summary: This paper proposes a framework combining natural language processing methods with experts' knowledge to detect abrupt changes (turbulences) and analyzes how institutional turbulences interact with other turbulences to form Green WoOs in China's hydropower sector.
INDUSTRIAL AND CORPORATE CHANGE
(2020)
Article
Business
Xin Li, Qianqian Xie, Jiaojiao Jiang, Yuan Zhou, Lucheng Huang
TECHNOLOGICAL FORECASTING AND SOCIAL CHANGE
(2019)
Article
Business
Yuan Zhou, Fang Dong, Dejing Kong, Yufei Liu
TECHNOLOGICAL FORECASTING AND SOCIAL CHANGE
(2019)