Community Information Centre in Nagaland

2006 ◽  
Author(s):  
Mangkholien Singson

Currently, the professional construction community information field is largely filled with the topic of creating a comfortable living environment. However, architectural and engineering design that corresponds to the concept of sustainable development is currently hindered due to the lack of a formed conceptual framework that reveals the meaning of the term "comfort", as well as a criteria list that determines the indoor environment quality in the Russian Federation regulatory and technical framework. The article offers some components of a comfortable living environment, within which the parameters of designing the internal environment of premises are highlighted. A comparative analysis of the national standards of the Russian Federation regulating the design of the internal space of residential and public buildings, with international "green" standards for a number of parameters was carried out. It is concluded that it is necessary to update the Russian regulatory and technical base taking into account the international experience of "green" standards.


2020 ◽  
Vol 4 (Supplement_1) ◽  
pp. 341-341
Author(s):  
Ronica Rooks

Abstract Where we live impacts our health, but this is more apt for older adults (aged 55+) aging-in-place in their neighborhoods. Gentrification, i.e. the transformation of neighborhoods from low to high value, can put community-dwelling older adults at risk for residential displacement with limited retirement incomes and financial stressors like increased housing costs and property taxes, residential turnover and changing access to resources. As a place-based stressor, gentrification may exacerbate social vulnerabilities (e.g., lower socioeconomic status and racial/ethnic minority status) related to chronic condition (CC) disparities. But, little gentrification research focuses on these issues. This research examines associations between gentrification and older adults’ CC management related to broader social determinants in Hamilton, Ontario, Canada from health and social service providers’ perspectives. Hamilton, a recovering steel industry city with in-migration from Toronto, is experiencing higher costs of living, income inequality and tension with recent gentrifiers. I conducted key informant interviews with service providers in city government and community-based organizations using thematic analysis. Across providers, food insecurity, social isolation and displacement were the biggest issues associated with gentrification and CC, particularly for older adults with lower incomes and government disability support. Results thus far reveal Hamilton has numerous older adult-focused providers, but older adults often have difficulties accessing services due to a lack of knowledge, not always asking or realizing when they need help and coordinated referral difficulties across providers. To address these challenges, providers consider environmental scans, mapping resources and advertisement in an online community information database from the city’s public library.


2021 ◽  
Vol 15 (4) ◽  
pp. 1-23
Author(s):  
Guojie Song ◽  
Yun Wang ◽  
Lun Du ◽  
Yi Li ◽  
Junshan Wang

Network embedding is a method of learning a low-dimensional vector representation of network vertices under the condition of preserving different types of network properties. Previous studies mainly focus on preserving structural information of vertices at a particular scale, like neighbor information or community information, but cannot preserve the hierarchical community structure, which would enable the network to be easily analyzed at various scales. Inspired by the hierarchical structure of galaxies, we propose the Galaxy Network Embedding (GNE) model, which formulates an optimization problem with spherical constraints to describe the hierarchical community structure preserving network embedding. More specifically, we present an approach of embedding communities into a low-dimensional spherical surface, the center of which represents the parent community they belong to. Our experiments reveal that the representations from GNE preserve the hierarchical community structure and show advantages in several applications such as vertex multi-class classification, network visualization, and link prediction. The source code of GNE is available online.


Sign in / Sign up

Export Citation Format

Share Document