scholarly journals Research on quantitative analysis method of street space quality evaluation, Whuan City centre

2020 ◽  
Author(s):  
Huihui Yan ◽  
◽  
Runzhi Huang ◽  
Yunming Cheng ◽  
Keyword(s):  
Artificial Intelligence ◽  
Big Data ◽  
Evaluation System ◽  
Information Technologies ◽  
Quality Evaluation ◽  
Hot Spot ◽  
Central City ◽  
Current Status ◽  
City Centre ◽  
Street Space

ith the continuous development of technical means, information technologies such as big data and artificial intelligence have gradually become one of the core technical means of planning and design. Applying AI and big data to evaluate street space has also become one hot spot in recent years. However, there are few studies on the street space quality of Wuhan based on new technology, and especially there is almost no evaluation system that combines planning technology and information technology. This study employs big data, traditional planning data and current status survey data, combined with artificial intelligence, ArcGIS spatial analysis and spatial syntax and other analytical techniques, to propose a comprehensive system for evaluating street space quality. This paper selects an area in the central city of Wuhan for the case study on the quality evaluation system, and accordingly provides an analytic idea for the planning and construction of streets, so as to guide the implementation of street-related projects and planning.

scholarly journals Artificial intelligence and machine learning: changing paradigm in diagnostics and imaging

2019 ◽  
Vol 8 (1) ◽  
pp. 382
Author(s):  
Rahul Badwaik
Keyword(s):  
Artificial Intelligence ◽  
Machine Learning ◽  
Big Data ◽  
Data Analytics ◽  
Big Data Analytics ◽  
Healthcare Setting ◽  
Digital Transformation ◽  
Current Status ◽  
Healthcare Industry ◽  
Review Of The Literature

Healthcare industry is currently undergoing a digital transformation, and Artificial Intelligence (AI) is the latest buzzword in the healthcare domain. The accuracy and efficiency of AI-based decisions are already been heard across countries. Moreover, the increasing availability of electronic clinical data can be combined with big data analytics to harness the power of AI applications in healthcare. Like other countries, the Indian healthcare industry has also witnessed the growth of AI-based applications. A review of the literature for data on AI and machine learning was conducted. In this article, we discuss AI, the need for AI in healthcare, and its current status. An overview of AI in the Indian healthcare setting has also been discussed.

Big Data- and Artificial Intelligence-Based Hot-Spot Analysis of COVID-19: Gauteng, South Africa, as a case study

2021 ◽  
Author(s):  
Benjamin Lieberman ◽  
Roy Gusinow ◽  
Ali Asgary ◽  
Nicola Luigi Bragazzi ◽  
Nalomotse Choma ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
South Africa ◽  
Big Data ◽  
Hot Spot ◽  
Hot Spot Analysis ◽  
Spot Analysis

Information Technologies in the Work of Municipal Controlling and Counting Bodies

2018 ◽  
Vol 7 (2) ◽  
pp. 4-10
Author(s):  
В. Перов ◽  
V. Perov ◽  
Е. Кличева ◽  
E. Klicheva
Keyword(s):  
Artificial Intelligence ◽  
Big Data ◽  
Information Technologies ◽  
The Other ◽  
Social Stability ◽  
Data Systems ◽  
Management Tools ◽  
Document Flow ◽  
Big Data Systems ◽  
The One

The article explored the practice of applying information technology in controlling and counting of municipal bodies. The information on information systems for automation document flow between control and counting bodies and municipalities; perform supervisory powers control and accounting bodies; process for the preparation of consolidated accounts and audit of procurementis compiled and analyzed. On the one hand, the development of information technologies,including the use of “big data” systems and artificial intelligence allows you to withdraw municipal controlling and counting bodies at a qualitatively new level, going from penalties to prevent violations and application of risk-management tools. On the other hand, it requires the solution of new tasks. The authors give proposals to improve the application of municipal software controlling and counting bodies in order to improve the effectiveness of financial controls, maintaining sustainable economic development and social stability of the municipalities.

scholarly journals EULAR points to consider for the use of big data in rheumatic and musculoskeletal diseases

2019 ◽  
Vol 79 (1) ◽  
pp. 69-76 ◽  
Author(s):  
Laure Gossec ◽  
Joanna Kedra ◽  
Hervé Servy ◽  
Aridaman Pandit ◽  
Simon Stones ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Big Data ◽  
Musculoskeletal Diseases ◽  
Task Force ◽  
Data Interpretation ◽  
Current Status ◽  
Privacy By Design ◽  
Design Data ◽  
European League Against Rheumatism ◽  
International Experts

BackgroundTremendous opportunities for health research have been unlocked by the recent expansion of big data and artificial intelligence. However, this is an emergent area where recommendations for optimal use and implementation are needed. The objective of these European League Against Rheumatism (EULAR) points to consider is to guide the collection, analysis and use of big data in rheumatic and musculoskeletal disorders (RMDs).MethodsA multidisciplinary task force of 14 international experts was assembled with expertise from a range of disciplines including computer science and artificial intelligence. Based on a literature review of the current status of big data in RMDs and in other fields of medicine, points to consider were formulated. Levels of evidence and strengths of recommendations were allocated and mean levels of agreement of the task force members were calculated.ResultsThree overarching principles and 10 points to consider were formulated. The overarching principles address ethical and general principles for dealing with big data in RMDs. The points to consider cover aspects of data sources and data collection, privacy by design, data platforms, data sharing and data analyses, in particular through artificial intelligence and machine learning. Furthermore, the points to consider state that big data is a moving field in need of adequate reporting of methods and benchmarking, careful data interpretation and implementation in clinical practice.ConclusionThese EULAR points to consider discuss essential issues and provide a framework for the use of big data in RMDs.

Sign in / Sign up

Export Citation Format

Share Document