Article
Green & Sustainable Science & Technology
Derek Hungness, Raj Bridgelall
Summary: This paper evaluates the applicability of using vehicle miles of travel (VMT) forecasting and impact assessment in transportation planning for Dane County, Wisconsin. The study finds that exploratory spatial data analysis reveals statistically significant spatial relationships and interactions that are not easily visualized using other methods. Planners can utilize these techniques to identify cost-effective VMT remediation measures for sustainable networks and environments.
Article
Computer Science, Hardware & Architecture
Urvashi Gupta, Rohit Sharma
Summary: This paper explores the crime against women dataset in India from 2001 to 2020 using exploratory data analysis and linear regression. It reveals that the situation of crime against women in India has not improved in recent years and the high population density has contributed to the increase in crime. The proposed predictive model based on CRISP-DM methodology shows promising results in predicting crime rate.
COMPUTERS & ELECTRICAL ENGINEERING
(2023)
Article
Multidisciplinary Sciences
Bjoern Brembs, Philippe Huneman, Felix Schoenbrodt, Gustav Nilsonne, Toma Susi, Renke Siems, Pandelis Perakakis, Varvara Trachana, Lai Ma, Sara Rodriguez-Cuadrado
Summary: We propose replacing traditional journals with a decentralized and resilient network governed by the scholarly community to overcome social dilemmas and prevent corporate takeover. We suggest redirecting funding from legacy publishers to this new network by expanding infrastructure requirements at recipient institutions and realigning financial incentives.
ROYAL SOCIETY OPEN SCIENCE
(2023)
Article
Geography, Physical
Yufeng He, Yehua Sheng, Barbara Hofer, Yi Huang, Jiarui Qin
Summary: This paper introduces a process-event-centred dynamic data model for geographic scenes, formalizing the relationship between geographic processes and events. The model is implemented in the Neo4j graph database to support spatio-temporal reasoning and provides an organizational framework for simulating spatio-temporal dynamics and complex calculations. The capabilities of the data model for spatial reasoning and dynamic modeling are demonstrated through queries to the graph database.
INTERNATIONAL JOURNAL OF DIGITAL EARTH
(2022)
Article
Computer Science, Information Systems
Artemis Psaltoglou, Athena Vakali
Summary: The development of smart cities is enhancing urban planning and data analysis through interactive visualization and game design, improving the city's problem-solving capacity. This research leverages spatial data to generate three-dimensional environments and interactive applications, providing a new approach for accessing and understanding urban data.
MULTIMEDIA TOOLS AND APPLICATIONS
(2021)
Article
Green & Sustainable Science & Technology
Xi Zhang, Yong Geng, Yen Wah Tong, Harn Wei Kua, Xu Tian, Rui Wu, Xingrong Zhao, Anthony S. F. Chiu
Summary: The analysis of patent data shows significant spatial characteristics in China's low-carbon energy technology innovation, with different provinces exhibiting clustering patterns and coastal provinces playing a crucial role in the innovation. The study highlights the importance of technology priority, economic scale, R&D efficiency, and R&D share in driving the increases of low-carbon energy technology innovations in different regions of China.
JOURNAL OF CLEANER PRODUCTION
(2021)
Article
Environmental Studies
Consuelo Calafat-Marzal, Mercedes Sanchez-Garcia, Aurea Gallego-Salguero, Veronica Pineiro
Summary: The frequency of producers opting to abandon agricultural land has increased, emphasizing the importance of this phenomenon in terms of its environmental, landscape, and socio-economic impacts. The decisions of producers on whether to abandon or maintain/improve their farms depend on individual and contextual factors. This research aims to evaluate the influence of neighbors on winegrowers' decisions and to clarify the specific importance of individual and contextual drivers in farmers' decisions using spatial analysis and multilevel models.
Article
Computer Science, Artificial Intelligence
Wanessa W. L. Freitas, Renata M. C. R. de Souza, Getulio J. A. Amaral, Fernanda De Bastiani
Summary: This paper aims to identify the behavior of interval data with its geospatial information within the framework of Symbolic Data Analysis, extending Moran's autocorrelation index. The importance of considering variability present in the interval variable and geographical information is demonstrated through experiments and case studies. The proposed approach shows effectiveness in dealing with spatially correlated data and illustrates the usefulness of incorporating variability into analysis.
EXPERT SYSTEMS WITH APPLICATIONS
(2022)
Article
Engineering, Mechanical
Li Liu, Qian Wang, Zong-Yuan Tan, Ning Cai
Summary: A novel review system is proposed to improve the performance and effectiveness of peer review. The system is based on an analysis of the peer review process for academic journals and uses a parallel model built via the Monte Carlo method. The model can simulate the review, application, and acceptance activities in a distributed manner. Simulation experiments conducted on two different review systems demonstrate the significant advantages of the novel system.
NONLINEAR DYNAMICS
(2023)
Article
Biochemical Research Methods
Xinghu Qin, Charleston W. K. Chiang, Oscar E. Gaggiotti
Summary: The study introduces a new method called KLFDAPC, which uses Kernel Local Fisher Discriminant Analysis of Principal Components to infer individual geographic genetic structure. Compared to traditional methods, KLFDAPC has higher discriminatory power and accuracy, making it suitable for geographic ancestry inference and genome research.
BRIEFINGS IN BIOINFORMATICS
(2022)
Article
Urban Studies
Shuoshuo Shang, Shihong Du, Shouji Du, Shoujie Zhu
Summary: Population distribution data is crucial for social and geographical studies, and this study presents a novel method of estimating building-scale population by integrating urban functional zones data and multi-source geospatial data. The proposed method outperformed state-of-the-art methods in predicting population in the study area of Ningbo, China, demonstrating its effectiveness for urban modernization and resource allocation.
Article
Green & Sustainable Science & Technology
Huihui Wang, Xiaoyong Gao, Tingting Xu, Hanyu Xue, Wanlin He
Summary: The frequent occurrence of drought poses challenges to regional sustainable development. This study constructs a framework to assess drought resilience in China and reveals the spatiotemporal evolution mechanism and spatial autocorrelation of drought resilience. The results show an overall increasing trend in drought resilience, with coastal provinces having higher resilience levels compared to inland northwest regions. Environmental indicators are identified as the main factors causing spatial differentiation in drought resilience, and the interaction among influencing factors is found to be greater than the impact of a single factor.
JOURNAL OF CLEANER PRODUCTION
(2023)
Article
Energy & Fuels
Matteo Rocco, Elena Fumagalli, Chiara Vigone, Ambrogio Miserocchi, Emanuela Colombo
Summary: This research models and contrasts alternative electrification pathways for Tanzania in the time frame 2015-2040, finding that policy goals are achievable but require significant investment. Environmental policies can lower carbon intensity and reduce electricity costs, while achieving universal access to electricity may be possible earlier but may pose challenges in reducing carbon intensity or electricity costs.
ENERGY STRATEGY REVIEWS
(2021)
Article
Green & Sustainable Science & Technology
Eric Vaz
Summary: This study aimed to reveal the spatial characteristics of COVID-19 and key socio-economic features of its distribution in Toronto through a geographical information systems framework and spatial modeling. The findings suggest that COVID-19 exhibits clear spatial characteristics, with social injustice, infrastructure, and neighborhood cohesion being significant factors in the increasing spread and incidence of the disease.
Article
Transportation
Gholam Ali Shafabakhsh, Afshin Famili, Mahdi Akbari
Summary: This paper uses a combination of geographic information system and spatial analysis to study the frequency and severity of traffic accidents. Methods of planar and network statistics are applied to analyze different types of accidents, and it is found that the accidents in the study region are clustered.
TRANSPORTATION LETTERS-THE INTERNATIONAL JOURNAL OF TRANSPORTATION RESEARCH
(2023)
Article
Computer Science, Interdisciplinary Applications
Qi Yu, Qi Wang, Yafei Zhang, Chongyan Chen, Hyeyoung Ryu, Namu Park, Jae-Eun Baek, Keyuan Li, Yifei Wu, Daifeng Li, Jian Xu, Meijun Liu, Jeremy J. Yang, Chenwei Zhang, Chao Lu, Peng Zhang, Xin Li, Baitong Chen, Islam Akef Ebeid, Julia Fensel, Chao Min, Yujia Zhai, Min Song, Ying Ding, Yi Bu
Summary: This paper conducted an entitymetric analysis on COVID-19 literature, revealing ACE-2 and C-reactive protein as significant genes and lopinavir and ritonavir as important chemicals.
Article
Computer Science, Information Systems
Meijun Liu, Yi Bu, Chongyan Chen, Jian Xu, Daifeng Li, Yan Leng, Richard B. Freeman, Eric T. Meyer, Wonjin Yoon, Mujeen Sung, Minbyul Jeong, Jinhyuk Lee, Jaewoo Kang, Chao Min, Min Song, Yujia Zhai, Ying Ding
Summary: Scientific novelty is crucial for inventing new vaccines and solutions during a pandemic. First-time collaboration and international collaboration are essential channels to expand team search activities and generate novel ideas.
JOURNAL OF THE ASSOCIATION FOR INFORMATION SCIENCE AND TECHNOLOGY
(2022)
Letter
Computer Science, Interdisciplinary Applications
Qi Yu, Qi Wang, Yafei Zhang, Chongyan Chen, Hyeyoung Ryu, Namu Park, Jae-Eun Baek, Keyuan Li, Yifei Wu, Daifeng Li, Jian Xu, Meijun Liu, Jeremy J. Yang, Chenwei Zhang, Chao Lu, Peng Zhang, Xin Li, Baitong Chen, Islam Akef Ebeid, Julia Fensel, Chao Min, Yujia Zhai, Min Song, Ying Ding, Yi Bu
Article
Computer Science, Information Systems
Huimin Xu, Yi Bu, Meijun Liu, Chenwei Zhang, Mengyi Sun, Yi Zhang, Eric Meyer, Eduardo Salas, Ying Ding
Summary: Power dynamics play a significant role in scientific collaboration. Team power level and team power hierarchy can be used to measure team power dynamics. Research findings indicate that a flat team structure is associated with higher team impact, particularly when teams have a high level of power.
JOURNAL OF THE ASSOCIATION FOR INFORMATION SCIENCE AND TECHNOLOGY
(2022)
Article
Computer Science, Interdisciplinary Applications
Meijun Liu, Ning Zhang, Xiao Hu, Ajay Jaiswal, Jian Xu, Hong Chen, Ying Ding, Yi Bu
Summary: This study examines the evolution of gender inequalities before and during the COVID-19 pandemic through a difference in differences approach. The findings show that females' leadership in publications as the first author was negatively affected during the pandemic. The gender gaps in the share of authorships have also been strengthened, and there was a decline in mixed-gender collaboration in publications. Furthermore, papers by teams where females play a key role were less cited, and this disadvantage was exacerbated during the pandemic. Gender inequalities regarding authorships and collaboration were enhanced in the initial stage of COVID-19 and widened with the increasing severity of COVID-19, but returned to pre-pandemic levels in September 2020.
JOURNAL OF INFORMETRICS
(2022)
Article
Computer Science, Interdisciplinary Applications
Meijun Liu, Xiao Hu
Summary: The study found that scientists' mobility has a positive impact on their career development, especially for scientists in emerging countries. Mobility does not have an initial negative effect on scientists' productivity and collaboration, and it leads to increased collaboration with new partners.
JOURNAL OF INFORMETRICS
(2022)
Article
Green & Sustainable Science & Technology
Ruifeng Hu, Weiqiao Xu
Summary: This paper analyzes the number and distribution of green agriculture patents in China, and finds an increasing trend in patent numbers and uneven spatial distribution. The research also identifies popular fields, such as seed breeding, planting, and organic fertilizers, in China's green agriculture. These findings provide empirical support for the future development of green agriculture in China and other developing countries.
Article
Computer Science, Interdisciplinary Applications
Meijun Liu, Ajay Jaiswal, Yi Bu, Chao Min, Sijie Yang, Zhibo Liu, Daniel Acuna, Ying Ding
Summary: This study examines the relationship between the freshness of scientific teams and their impact, measured through the citations of their papers. The findings suggest an inverted-U-shaped association between team freshness and citations across disciplines and time periods. Small teams are hindered by team freshness, while medium and large teams can benefit from it until a turning point is reached. These findings have implications for team formation and management in scientific research.
JOURNAL OF INFORMETRICS
(2022)
Article
Environmental Studies
Ruifeng Hu, Weiqiao Xu, Yalin Yang
Summary: This paper reveals the spatiotemporal evolution of electric technology in mainland China through patent analysis. The results show that electric technology has spatial heterogeneity with slower growth in the north and west and faster growth in the south and east. Additionally, the study provides positive evidence that low-carbon policies improve the green innovation capacity of electric technology.
INTERNATIONAL JOURNAL OF CLIMATE CHANGE STRATEGIES AND MANAGEMENT
(2023)
Article
Economics
Ruifeng Hu, Weiqiao Xu, Yalin Yang, Guangxian Ni
Summary: Sustainable development has gained attention due to environmental concerns, leading to increased interest in eco-innovation and a surge in publications. This study examines the evolution of eco-innovation research using extensive data and meta-analysis. The findings show a steady increase in publications, growing interest from developing countries, and the significant influence of innovation capability and environmental regulations on eco-innovation.
JOURNAL OF THE KNOWLEDGE ECONOMY
(2023)
Article
Green & Sustainable Science & Technology
Ruifeng Hu, Weiqiao Xu
Summary: Urban agglomerations are an important spatial form for integrated regional development, but they can also bring about environmental problems. The Chinese government has implemented a green strategy to promote clean transformation and firm green innovation in urban agglomerations. This study collected data on green-granted patents of listed firms in the Chengdu-Chongqing Economic Circle from 2000 to 2021, and analyzed the influence of urban agglomerations on firm green innovation using the difference-in-differences method, as well as explored the mediating effects of green finance and some moderating effects. The results indicate that urban agglomerations significantly enhance firm green innovation, with the mediating role of green finance being positively moderated by firm digitalization. The study also finds that the impact of urban agglomerations varies based on firm size, industry, ownership type, and levels of economic and educational development.
JOURNAL OF CLEANER PRODUCTION
(2023)
Article
Green & Sustainable Science & Technology
Ruifeng Hu, Weiqiao Xu, Lian-feng Liu, Zhiyu Cui, Changyi Zhao
Summary: Urban agglomerations have become the dominant form of regional growth, but they also contribute to a significant portion of global carbon emissions, making it crucial to reduce emissions during China's rapid urbanization. This study investigates the impact of China's urban agglomeration construction on carbon emissions using a time-varying difference-in-differences method, and finds that urban agglomerations can effectively reduce emissions, with an optimal spatial scope of 50-100 km. The study also reveals that the reduction effect varies based on regional economic development and green innovation capability, and suggests policy recommendations for designing urban agglomerations and improving the digital economy to achieve emission reduction.
JOURNAL OF CLEANER PRODUCTION
(2023)
Article
Business
Weiqiao Xu, Ruifeng Hu
Summary: This study examines the impact of top management team's (TMT) academic competence on firm innovation performance and explores the mechanisms behind it. The findings suggest that TMT's academic competence positively contributes to firms' innovation performance, with university-industry collaboration partially mediating this relationship. The mediating effect is enhanced by cognitive proximity, while distance proximity does not diminish it.
MANAGEMENT DECISION
(2023)
Article
Computer Science, Information Systems
Yi Bu, Hanlin Li, Chunli Wei, Meijun Liu, Jiang Li
Summary: This article explores the relationship between supervisor-supervisee gender difference and the scientific impact of doctoral dissertations in the fields of Humanities and Social Sciences in China. The study findings indicate that the rankings of scientific impact are female-female (first), female-male (second), male-male (third), and male-female (fourth) pairs (sequence: student gender and then supervisor gender). This finding has significant implications for science policy and gender inequality.
JOURNAL OF INFORMATION SCIENCE
(2022)
Article
Computer Science, Information Systems
Ruifeng Hu, Xinyi Diao
Summary: This paper reviews current research on open innovation from the perspective of the evolution of participants, theoretically constructs a framework for the open innovation information spillover effect, and verifies the practical existence of this effect among firms using Huawei Technologies Co., Ltd., as an example. The aim is to extend the research boundary of open innovation and provide a theoretical reference for further studies.
Article
Computer Science, Interdisciplinary Applications
Hao Teng, Nan Wang, Hongyu Zhao, Yingtong Hu, Haitao Jin
Summary: In this paper, a new method based on functional semantic knowledge (FOP) is proposed for patent similarity calculation. Furthermore, patent STS datasets are processed and released as benchmarks. Preliminary results show that FOP-based methods are more suitable for STS tasks when combined with IPC codes, weights' assignments, and patent pre-trained vectors.
JOURNAL OF INFORMETRICS
(2024)
Article
Computer Science, Interdisciplinary Applications
Cristina Urdiales, Eduardo Guzman
Summary: Subject categorization of scientific publications is important for evaluating paper quality. Traditional mechanisms for categorization have been questioned, and a new method based on association rules is proposed. The method automatically defines publication categories based on the repetition or absence of relevant descriptors. The empirical study in the field of Physical Sciences and Engineering shows that the proposed method produces consistent and suitable categorization results.
JOURNAL OF INFORMETRICS
(2024)
