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2022 ◽  
Vol 30 (6) ◽  
pp. 1-21
Author(s):  
Lei Li ◽  
Shaojun Ma ◽  
Runqi Wang ◽  
Yiping Wang ◽  
Yilin Zheng

Abundant natural resources are the basis of urbanisation and industrialisation. Citizens are the key factor in promoting a sustainable supply of natural resources and the high-quality development of urban areas. This study focuses on the co-production behaviours of citizens regarding urban natural resource assets in the age of big data, and uses the latent Dirichlet allocation algorithm and the stepwise regression analysis method to evaluate citizens’ experiences and feelings related to the urban capitalisation of natural resources. Results show that, firstly, the machine learning algorithm based on natural language processing can effectively identify and deal with the demands of urban natural resource assets. Secondly, in the experience of urban natural resources, citizens pay more attention to the combination of history, culture, infrastructure and natural landscape. Unique natural resource can enhance citizens’ sense of participation. Finally, the scenery, entertainment and quality and value of urban natural resources are the influencing factors of citizens’ satisfaction.


2022 ◽  
Vol 8 ◽  
pp. 500-513
Author(s):  
Ammar Mebarki ◽  
Adel Sekhri ◽  
Abdelhalim Assassi ◽  
Abdelhakim Hanafi ◽  
Belkacem Marir

The United Nations Sustainable Development Goals (SDGs) are universally seen to be global in their nature and reach, but there is a growing acceptance that they have an important local dimension. At the same time, there is an increasing recognition of the need for appropriate Information and Communication Technologies (ICTs) to support and monitor the SDGs. This article adopts a qualitative inductive research approach in examining a range of public authority and academic source material, and framework analysis is used to record, categorise and critique this material. The findings provide an overview of the role of the SDGs at the local level and an assessment of how the localisation of the SDGs is being addressed in some urban areas within Western Europe. The findings also indicate how ICTs are being deployed to support the localisation process in Western Europe and the wider world. This is followed by a discussion of some emergent issues related to the localisation of the SDGs, including the increasingly important role of ICTs.


2022 ◽  
Vol 2 ◽  
pp. 100012
Author(s):  
Amita Singh ◽  
Jannicke Baalsrud Hauge ◽  
Magnus Wiktorsson ◽  
Utkarsh Upadhyay

2022 ◽  
Vol 8 (1) ◽  
pp. 1-22
Author(s):  
Asif Iqbal Middya ◽  
Sarbani Roy ◽  
Debjani Chattopadhyay

Adequate nighttime lighting of city streets is necessary for safe vehicle and pedestrian movement, deterrent of crime, improvement of the citizens’ perceptions of safety, and so on. However, monitoring and mapping of illumination levels in city streets during the nighttime is a tedious activity that is usually based on manual inspection reports. The advancement in smartphone technology comes up with a better way to monitor city illumination using a rich set of smartphone-equipped inexpensive but powerful sensors (e.g., light sensor, GPS, etc). In this context, the main objective of this work is to use the power of smartphone sensors and IoT-cloud-based framework to collect, store, and analyze nighttime illumination data from citizens to generate high granular city illumination map. The development of high granular illumination map is an effective way of visualizing and assessing the illumination of city streets during nighttime. In this article, an illumination mapping algorithm called Street Illumination Mapping is proposed that works on participatory sensing-based illumination data collected using smartphones as IoT devices to generate city illumination map. The proposed method is evaluated on a real-world illumination dataset collected by participants in two different urban areas of city Kolkata. The results are also compared with the baseline mapping techniques, namely, Spatial k-Nearest Neighbors, Inverse Distance Weighting, Random Forest Regressor, Support Vector Regressor, and Artificial Neural Network.


2022 ◽  
Vol 129 ◽  
pp. 1-11
Author(s):  
Elena Di Pirro ◽  
Lorenzo Sallustio ◽  
Gregorio Sgrigna ◽  
Marco Marchetti ◽  
Bruno Lasserre

2023 ◽  
Vol 83 ◽  
Author(s):  
S. Ali ◽  
S. Khan ◽  
S. N. Khan ◽  
M. Rauf ◽  
M. F. Khan ◽  
...  

Abstract Rotavirus is the main infective agent of acute gastroenteritis (AGE) in children under the age of five years and causing significant morbidity as well as mortality throughout the world. The study was carried out to detect the prevalence rate, genotypes strain and risk factors of Rotavirus among the children of rural and urban areas of district Bannu Khyber Pakhtunkhwa Pakistan. A total of 180 stool samples were collected from children under the age of 5 years from two major hospitals of Bannu from January to December (2015). The samples were analyzed by Reverse-transcriptase Polymerase Chain Reaction (RT-PCR) for the detection of Rotavirus, positive samples were further processed for genotyping (G and P type) through specific PCR. Of the total, 41 (23%) samples were positive for Rotavirus. The most prevalent G genotypes found were: G3, G8, G9 (each 29%), followed by G10 (15%), and G11 (10%). Whereas the prevalent P genotypes were: P-8 (25%), P-4 and P-10 (each 20%), P-9 (15%), followed by P-6 and P-11 (each 10%). Moreover, Rotavirus infection was more prevalent in summer (23.73%) and winter (22.7%) than spring (20%) and autumn (21.4%). Rotavirus infection exhibited high frequency in June (14%), October (8%) and November (6%). It is concluded that Rotavirus is more prevalent in children and various genotypes (G and P) of Rotavirus are present in the study area. Lack of studies, awareness and rarer testing of Rotavirus are the principal reasons of virus prevalence in district Bannu, Pakistan.


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