Patents related to artificial intelligence-assisted pathology were searched and collected from the Derwent Innovation Index (DII), which were imported into Derwent Data Analyzer (DDA, Clarivate Derwent, New York, NY, USA) for authority control, and imported into the freely available computer program Ucinet 6 for drawing the patent citation network. The patent citation network according to the citation relationship could describe the technology development context in the field of artificial intelligence-assisted pathology. The patent citations were extracted from the collected patent data, selected highly cited patents to form a co-occurrence matrix, and built a patent citation network based on the co-occurrence matrix in each period. Text clustering is an unsupervised learning method, an important method in text mining, where similar documents are grouped into clusters. The similarity between documents are determined by calculating the distance between them, and the two documents with the closest distance are combined. The method of text clustering was used to identify the technology frontiers based on the patent citation network, which was according to co-word analysis of the title and abstract of the patents in this field.
For FULL-TEXT https://doi.org/10.1371/journal.pone.0273355
Author(s): Ting Zhang,Juan Chen,Yan Lu,Xiaoyi Yang,Zhaolian Ouyang
Organization(s):Institute of Medical Information & Library, Chinese Academy of Medical Sciences and Peking Union Medical College
This paper introduces a new measure of patent value – Maintenance Renewal Score (MRSc) – reflecting assignee valuing the patent by paying successive renewal fees. We generate MRSc’s for nanotechnology patents issued by the US Patent Office from 1999 through 2009, with US assignees and US inventors. Patenting increases over this period, coincident with increased US funding of nanotechnology R&D. We compare maintenance rates over the period, and against a comparison set of all 1999 USPTO grants to US inventors/assignees. We find differences in propensity to maintain the nanopatents by institution type, technological sector, and patent complexity.
- We introduce a new measure of patent quality – Maintenance Renewal Score.
- We report differences in propensity to maintain US patents.
- The US National Nanotechnology Initiative (NNI) begins in 2003.
- US Nanotechnology patenting increases from 1999 to 2009 as NNI takes place.
- 52.5% of 1999 US patents maintain to full term; 1999–2009 US nanopatents, 40.5%.
For FULL-TEXT https://doi.org/10.1016/j.wpi.2023.102178
Author(s): Alan L. Porter, Mark Markley, Richard Snead, Nils C. Newman
Organization: Search Technology, Inc.
Source: World Patent Information
Profitable organisations that applied data analytics have obtained a double-digit improvement in reducing costs, predicting demands, and enhancing decision-making. However, in nonprofit organisations (NPOs), applying data analysis can interpret and discover more patterns of donors, volunteers, and forecasting future funds, gifts and grants. To uncover the usage of data analytics in different NPOs and understand its contribution, this article presents a bibliometric analysis of 2673 related publications to reveal the research landscape of data analytics applied in NPOs. Through a co-term analysis and scientific evolutionary pathways analysis, we profile the associations between data analysis techniques and NPOs and additionally identify the research topic changes in this field over time. The results yield us three major insights: (1) Robust and classic statistical methods-based data analysis techniques are dominantly prevalent in the NPOs field through all the time; (2) Healthcare and public affairs are two crucial sectors that involve data analytics to support decision-making and problem-solving; (3) Artificial Intelligence (AI)-based data analytics is a recently emerging trending, especially in the healthcare-related sector; however, it is still at an immature stage, and more efforts are needed to nourish its development.
Author(s): Idrees Alsolbi, Mengjia Wu, Yi Zhang, Siamak Tafavogh, Ashish Sinha, Mukesh Prasad
Organization(s): University of Technology Sydney
Source: Pattern Recognition and Data Analysis with Applications. Lecture Notes in Electrical Engineering
Author: Tausif A. Bordoloi
Organization: University of Manchester
Source: A thesis submitted to the University of Manchester for the degree of Doctor of Philosophy (Ph.D.) in the Faculty of Humanities, Alliance Manchester Business School
For FULL-TEXT https://www.research.manchester.ac.uk/portal/files/234004561/FULL_TEXT.PDF
The notion of cyber-physical convergence, which indicates the pervasive integration of digital
technologies in manufacturing, has rapidly gained prominence around the world because of its
potential to accelerate economic productivity gains. A question of significance but relatively
little empirical scrutiny is how cyber-physical convergence is characterised and realised in
innovation generation, innovation adoption and innovation policy. These issues are addressed
in this doctoral thesis, resulting in three journal-format papers.
The first paper characterises and operationalises the notion of cyber-physical convergence, and
then measures the growth and trajectories of scholarly research associated with the notion by
employing text-mining and bibliometric approaches. The second paper is an inductive case
study on the relative influences of geographical and non-geographical proximity factors in the
adoption of digital technologies by small- and medium-sized automotive and aerospace firms
(SMEs) co-localised in North West England. The third paper is an integrative literature review
of three industrial policy initiatives – Germany’s Industrie 4.0, Smart Manufacturing in the
U.S. and the High Value Manufacturing in the U.K., to analyse the framing and execution of
policy vision to support specific types of technologies underpinning convergence.
There are three main contributions of this thesis: first, it systematically delineates the cyberphysical convergence research domain into five data-centric capabilities – namely, Monitoring, Analytics, Modelling and Simulation, Transmission and Security, and sheds light on national research performance indicators for the period 2010–2019; second, it provides micro-level evidence indicating that geographical proximity among automotive and aerospace SMEs and also other types of economic actors is not the leading factor in technology adoption, rather
institutional and cognitive (knowledge) factors play a more prominent role; and third, it offers
insights pertaining to policy design and implementation, with Industrie 4.0 being more explicit
and comprehensive than Smart Manufacturing and High Value Manufacturing in its framing,
usage and implementation of a vision to support specific types of technologies. These contributions allow deriving policy and managerial implications regarding: the significance of data in manufacturing and funding data-centric capabilities, including questions of trade-offs between funding specific capabilities; the importance of interactions with non-
localised actors for the purpose of technology adoption; and the consideration and systematic
execution of policy vision to support and accelerate the realisation of cyber-physical
The recent outbreak of one of the RNA viruses (2019-nCoV) has affected most of the population and the fatalities reported may label it as a modern-day scourge. Active research on RNA virus infections and vaccine development had more commercial impact which leads to an increase in patent filings. Patents are a goldmine of information whose mining yields crucial technological inputs for further research. In this research article, we have investigated both the patent applications and granted patents, to identify the technological trends and their impact on 2019-nCoV infection using biotechnology-related keywords such as genes, proteins, nucleic acid etc. related to the RNA virus infection. In our research, patent analysis was majorly focused on prospecting for patent data related to the RNA virus infections. Our patent analysis specifically identified spike protein (S protein) and nucleocapsid proteins (N proteins) as the most actively researched macromolecules for vaccine and/or drug development for diagnosis and treatment of RNA virus based infectious diseases. The outcomes of this patent intelligence study will be useful for the researchers who are actively working in the area of vaccine or drug development for RNA virus-based infections including 2019-nCoV and other emerging and re-emerging viral infections in the near future.
For FULL-TEXT https://doi.org/10.1016/j.ijbiomac.2022.08.169
Author(s): Pratap Devarapalli, Pragati Kumari, Seema Soni, Vandana Mishra, Saurabh Yadav
Organization(s): University of Tasmania, Queensland University of Technology, H.N.B. Garhwal University
Source: International Journal of Biological Macromolecules
Supply chain management (SCM), which generally refers to horizontal integration management, has steadily become the core competitiveness of company rivalry and an essential approach to developing national comprehensive and national strength since the end of the 20th century due to the numerous needs arising from a competitive international economy. Manufacturers develop a community of interest by forming long-term strategic partnerships with suppliers and vendors throughout the supply chain. This paper defines supply chain management by reviewing the existing literature and discusses the current state of supply chain management research, as well as prospective research directions. Specifically, we conducted a bibliometric analysis of the influential studies of SCM in terms of various aspects, such as research areas, journals, countries/regions, institutions, authors and corresponding authors, most cited publications, and author keywords, based on the 8998 reviews and articles collected from the SCI and SSCI database of the Web of Science (WoS) between 2010 and 2020. The results show that the major research areas were Management (3071, 34.13%), Operations Research & Management Science (2680, 29.78%), and Engineering, Industrial (1854, 20.60%) with TP and TPR%. The most productive journal and institution were J. Clean Prod and Hong Kong Polytech Univ with a TP of 554 and 238, respectively. China, USA, and UK were the top three contributing countries. Furthermore, “sustainability”, “green supply chain (management)”, and “sustainable supply chain (management)” were the most popular author keywords in recent three years and since 2010, apart from the author keywords of SCM. When combined with the most cited articles in recent years, the application of block chain and Industry 4.0 in supply chain management increased rapidly and generated great attention
FOR FULL-TEXT https://doi.org/10.3390/pr10091681
Author(s): Hui Fang, Fei Fang, Qiang Hu, Yuehua Wan
Organization(s): Zhejiang University of Technology, Shanghai University of Finance and Economics
A clearer understanding of research streams and players involved in efforts to address the sustainability of global food and agricultural systems is needed to clarify the current state of scientific knowledge and form collaborations to pursue future research directions. This study presents new insights into this issue through a scientometric process involving a case study of technologies for extending fruit shelf-life. The text mining software was utilized to analyze 3,131 Web of Science-indexed articles published between 2000 and 2020 as a means to glean the conceptual structure of current knowledge and conduct a social network analysis to explore scientific and publication activity. The findings were mapped onto a strategic diagram of research productivity and collaboration between players at the national, organizational, and individual levels. This research’s main findings highlight that research on shelf-life technology is in continuous development, and academic institutions from China, Spain, and the U.S. are the core national players in this field. The results provide insights for further investigation to strengthen co-research and technological development programs in other fields. Researchers who are exploring networking opportunities can use the model and process presented as a guideline for identifying emerging and future research trends and formulating strategies.
For FULL-TEXT see https://doi.org/10.1155/2022/7120662
Author(s): Jakkrit Thavorn ,Veera Muangsi, Chupun Gowanit, Nongnuj Muangsin
Organization(s): Chulalongkorn University
Source: The Scientific World Journal
In order to reveal the status and trends of chemical treatment for wastewater, the patents analysis from both structured and unstructured data was performed in this study. 35,838 patents recorded in the Derwent Innovation Index database were adopted. The results showed that China was the country with the largest number of patents in the field, and the United States was the main exporter of international technology flows. Chemical processes combined with biological and physical processes was the mainstream, and ozonation and electrochemical treatment were the major single technologies. Technology evolution path generally showed the transition from biological process-combined chemical treatment to electrochemical treatment and finally to physical process-combined chemical treatment. Furthermore, future trends were revealed from both patents and papers. It demonstrated that efficient removal of ammonia nitrogen, green water treatment agents and resourcezation of wastewater were the key innovation directions, and technologies with regard to efficient use of energy (including photocatalytic technology and microbial fuel cell) were the main research hotspots. Overall, this study provided a comprehensive understanding for the research and application of chemical treatment for wastewater technologies.
Author(s): Xiangzhou Sun, Lili Jin, Fengyao Zhou, Kai Jin, Laichun Wang, Xuxiang Zhang, Hongqiang Ren, Hui Huang
Organization(s): Nanjing University
Profitable companies that used data analytics have a double gain in cost reduction, demand prediction, and decision-making. However, using data analysis in non-profit organisations (NPOs) can help understand and identify more patterns of donors, volunteers, and anticipated future cash, gifts, and grants. This article presents a bibliometric study of 2673 to discover the use of data analytics in different NPOs and understand its contribution. We characterise the associations between data analysis techniques and NPOs using, Bibliometrics R tool, a co-term analysis and scientific evolutionary pathways analysis, as well as identify the research topic changes in this field throughout time. The findings revealed three key conclusions may be drawn from the findings: (1) In the sphere of NPOs, robust and conventional statistical methods-based data analysis procedures are dominantly common at all times; (2) Healthcare and public affairs are two crucial sectors that involve data analytics to support decision-making and problem-solving; (3) Artificial Intelligence (AI) based data analytics is a recently emerging trending, especially in the healthcare-related sector; however, it is still at an immature stage, and more efforts are needed to nourish its development. The research findings can leverage future research and add value to the existing literature on the subject of data analytics.
For FULL-TEXT https://doi.org/10.20517/jsegc.2022.09
Author(s): Idrees Alsolbi, Mengjia Wu, Yi Zhang, Sudhanshu Joshi, Manu Sharma, Siamak Tafavogh, Ashish Sinha, Mukesh Prasad
Organization(s): University of Technology Sydney, Commonwealth Bank Health Society
Source: Journal of Smart Environments and Green Computing
The intervention of hydrogen of renewable origin, green H2, in the energy mix of a country is a topic of great interest today as it is emerging as an energy vector conducive to the decarbonization of the economy and the energy transition from a fossil energy system to one based on renewable energies . Thus, in the context of the Hydrogen Economy, green H2 is produced, stored, transported and distributed for use as energy vector or chemical input. The diversity of pathways of production, with different levels of scientific advancement and technological maturity, motivates the realization of this work, which proposes to carry out a systematic bibliographic review, supported by bibliometric methods, of the scientific literature and the registration of patents on the production of green H2, in the period 2010-
For EXTENDED ABSTRACT https://hyceltec2022.com.ar/wp-content/uploads/2022/07/O-4H-Posso.pdf
Author(s): F. Posso1, A. Aguilera, M. Galeano
Organization(s): Universidad de Santander, Universidad Nacional de Asunción
Source: 8th Symposium on Hydrogen, Fuel Cells and Advanced Batteries (HYCELTEC 2022)