London’s Geographic Knowledge Network and the Anson Account (1748)

2017 ◽  
pp. 23-46
Author(s):  
Katherine Parker
Keyword(s):  
Knowledge Network ◽  
Geographic Knowledge

TheOrvosi Hetilap (Hungarian Medical Journal)in the network of medical journals

2014 ◽  
Vol 155 (22) ◽  
pp. 876-879
Author(s):  
András Schubert
Keyword(s):  
Medical Journal ◽  
Scientific Knowledge ◽  
Knowledge Network ◽  
Scientific Journals ◽  
Scientific Enterprise ◽  
Medical Journals ◽  
The Subject

The role of networks is swiftly increasing in the production and communication of scientific knowledge. Network aspects have, therefore, an ever growing importance in the analysis of the scientific enterprise, as well. The present paper demonstrates some techniques of studying the network of scientific journals on the subject of seeking the position of Orvosi Hetilap (Hungarian Medical Journal) in the international journal network. Orv. Hetil., 2014, 155(22), 876–879.

scholarly journals QALY league table of Iran: a practical method for better resource allocation

2021 ◽  
Vol 19 (1) ◽  
Author(s):  
Reza Hashempour ◽  
Behzad Raei ◽  
Majid Safaei Lari ◽  
Nasrin Abolhasanbeigi Gallezan ◽  
Ali AkbariSari
Keyword(s):  
Heart Diseases ◽  
Evaluation Studies ◽  
Final Analysis ◽  
Practical Method ◽  
Cost Utility ◽  
Cost Utility Analysis ◽  
Knowledge Network ◽  
Cochrane Library ◽  
League Table ◽  
Utility Analysis

Abstract Background The limited health care resources cannot meet all the demands of the society. Thus, decision makers have to choose feasible interventions and reject the others. We aimed to collect and summarize the results of all cost utility analysis studies that were conducted in Iran and develop a Quality Adjusted Life Year (QALY) league table. Methods A systematic mapping review was conducted to identify all cost utility analysis studies done in Iran and then map them in a table. PubMed, Embase, Cochrane library, Web of Science, as well as Iranian databases like Iran Medex, SID, Magiran, and Barakat Knowledge Network System were all searched for articles published from the inception of the databases to January 2020. Additionally, Cost per QALY or Incremental Cost Utility Ratio (ICUR) were collected from all studies. The Joanna Briggs checklist was used to assess quality appraisal. Results In total, 51 cost-utility studies were included in the final analysis, out of which 14 studies were on cancer, six studies on coronary heart diseases. Two studies, each on hemophilia, multiple sclerosis and rheumatoid arthritis. The rest were on various other diseases. Markov model was the commonest one which has been applied to in 45% of the reviewed studies. Discount rates ranged from zero to 7.2%. The cost per QALY ranged from $ 0.144 in radiography costs for patients with some orthopedic problems to $ 4,551,521 for immune tolerance induction (ITI) therapy in hemophilia patients. High heterogeneity was revealed; therefore, it would be biased to rank interventions based on reported cost per QALY or ICUR. Conclusions However, it is instructive and informative to collect all economic evaluation studies and summarize them in a table. The information on the table would in turn be used to redirect resources for efficient allocation. in general, it was revealed that preventive programs are cost effective interventions from different perspectives in Iran.

scholarly journals Development of Intelligent Information System for Digital Cultural Contents

Mathematics ◽  
2021 ◽  
Vol 9 (3) ◽  
pp. 238
Author(s):  
Yuna Hur ◽  
Jaechoon Jo
Keyword(s):  
Information System ◽  
User Satisfaction ◽  
Keyword Search ◽  
Relevant Information ◽  
Matter Content ◽  
System Stability ◽  
Knowledge Network ◽  
Intelligent Information ◽  
Subject Matter Content ◽  
Depth Interviews

A significant amount of digital cultural contents is shared online, but learners do not know where subject matter content is or how to find it. Therefore, there is a need for a service to improve educational quality by effectively providing relevant information in response to searches for content that is useful to learners. This study developed and tested the usability and utility of an intelligent information system that effectively searches and visualizes digital cultural contents. The system collects data on digital cultural contents, automatically classifies them, and creates content triple data to automatically display the results with a 3D timeline, knowledge network map, and keyword relation network map through content search, triple search, and keyword search. We also conducted a survey and in-depth interviews to verify users’ satisfaction with respect to the use and utility of the system. For the experiment, we developed survey questions to measure user satisfaction and conducted in-depth interviews regarding the system’s utility with a total of 65 subjects. The results show that the response for satisfaction with regard to the use and utility was generally “satisfied”. In addition, the system stability was evaluated as “high”.

scholarly journals Knowledge Network for Sustainable Local Development

2021 ◽  
Vol 13 (3) ◽  
pp. 1124
Author(s):  
Freddy Marín-González ◽  
Alexa Senior-Naveda ◽  
Mercy Narváez Castro ◽  
Alicia Inciarte González ◽  
Ana Judith Paredes Chacín
Keyword(s):  
Social Capital ◽  
Content Analysis ◽  
Local Development ◽  
Knowledge Exchange ◽  
Knowledge Networks ◽  
Knowledge Network ◽  
Deductive Inference ◽  
The Government ◽  
Exchange Network ◽  
The Relationship

This article aims to build a network for the exchange of knowledge between the government and production, community and university sectors for sustainable local development. To achieve this, the authors relied on the concepts of sustainable local development, social capital, the relationship between sectors or intersectorality, networks and interdisciplinary and transdisciplinary knowledge. Regarding the methodology, the abductive method was used. Under a documentary design, the research techniques were a content analysis of theoretical documents and the deductive inference technique. The construction of a knowledge exchange network for sustainable local development stands out as the result. It is concluded that knowledge networks for sustainable local development have positive implications in the establishment of alliances and links between the sectors that make up society.

GeoAI 2019 workshop report: The 3nd ACM SIGSPATIAL International Workshop on GeoAI: AI for Geographic Knowledge Discovery

2020 ◽  
Vol 11 (3) ◽  
pp. 23-24
Author(s):  
Song Gao ◽  
Shawn Newsam ◽  
Liang Zhao ◽  
Dalton Lunga ◽  
Yingjie Hu ◽  
...  
Keyword(s):  
Knowledge Discovery ◽  
International Workshop ◽  
Workshop Report ◽  
Geographic Knowledge ◽  
Geographic Knowledge Discovery

scholarly journals Bipartite Network of Interest (BNOI): Extending Co-Word Network with Interest of Researchers Using Sensor Data and Corresponding Applications as an Example

Sensors ◽  
2021 ◽  
Vol 21 (5) ◽  
pp. 1668
Author(s):  
Zongming Dai ◽  
Kai Hu ◽  
Jie Xie ◽  
Shengyu Shen ◽  
Jie Zheng ◽  
...  
Keyword(s):  
Feature Fusion ◽  
Extraction Methods ◽  
Knowledge Network ◽  
Sensor Data ◽  
Support Vector ◽  
Bipartite Network ◽  
Classification Models ◽  
Text Data ◽  
Domain Experts ◽  
Problems And Solutions

Traditional co-word networks do not discriminate keywords of researcher interest from general keywords. Co-word networks are therefore often too general to provide knowledge if interest to domain experts. Inspired by the recent work that uses an automatic method to identify the questions of interest to researchers like “problems” and “solutions”, we try to answer a similar question “what sensors can be used for what kind of applications”, which is great interest in sensor- related fields. By generalizing the specific questions as “questions of interest”, we built a knowledge network considering researcher interest, called bipartite network of interest (BNOI). Different from a co-word approaches using accurate keywords from a list, BNOI uses classification models to find possible entities of interest. A total of nine feature extraction methods including N-grams, Word2Vec, BERT, etc. were used to extract features to train the classification models, including naïve Bayes (NB), support vector machines (SVM) and logistic regression (LR). In addition, a multi-feature fusion strategy and a voting principle (VP) method are applied to assemble the capability of the features and the classification models. Using the abstract text data of 350 remote sensing articles, features are extracted and the models trained. The experiment results show that after removing the biased words and using the ten-fold cross-validation method, the F-measure of “sensors” and “applications” are 93.2% and 85.5%, respectively. It is thus demonstrated that researcher questions of interest can be better answered by the constructed BNOI based on classification results, comparedwith the traditional co-word network approach.

scholarly journals Visualization of clinical teaching citations using social network analysis

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Hakimeh Hazrati ◽  
Shoaleh Bigdeli ◽  
Seyed Kamran Soltani Arabshahi ◽  
Vahideh Zarea Gavgani ◽  
Nafiseh Vahed
Keyword(s):  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Research Collaboration ◽  
Clinical Teaching ◽  
Clustering Coefficient ◽  
Knowledge Network ◽  
Research Network ◽  
Centrality Measures ◽  
The Usa

Abstract Background Analyzing the previous research literature in the field of clinical teaching has potential to show the trend and future direction of this field. This study aimed to visualize the co-authorship networks and scientific map of research outputs of clinical teaching and medical education by Social Network Analysis (SNA). Methods We Identified 1229 publications on clinical teaching through a systematic search strategy in the Scopus (Elsevier), Web of Science (Clarivate Analytics) and Medline (NCBI/NLM) through PubMed from the year 1980 to 2018.The Ravar PreMap, Netdraw, UCINet and VOSviewer software were used for data visualization and analysis. Results Based on the findings of study the network of clinical teaching was weak in term of cohesion and the density in the co-authorship networks of authors (clustering coefficient (CC): 0.749, density: 0.0238) and collaboration of countries (CC: 0.655, density: 0.176). In regard to centrality measures; the most influential authors in the co-authorship network was Rosenbaum ME, from the USA (0.048). More, the USA, the UK, Canada, Australia and the Netherlands have central role in collaboration countries network and has the vertex co-authorship with other that participated in publishing articles in clinical teaching. Analysis of background and affiliation of authors showed that co-authorship between clinical researchers in medicine filed is weak. Nineteen subject clusters were identified in the clinical teaching research network, seven of which were related to the expected competencies of clinical teaching and three related to clinical teaching skills. Conclusions In order to improve the cohesion of the authorship network of clinical teaching, it is essential to improve research collaboration and co-authorship between new researchers and those who have better closeness or geodisk path with others, especially those with the clinical background. To reach to a dense and powerful topology in the knowledge network of this field encouraging policies to be made for international and national collaboration between clinicians and clinical teaching specialists. In addition, humanitarian and clinical reasoning need to be considered in clinical teaching as of new direction in the field from thematic aspects.

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