![]() Daar word aangetoon dat hierdie netwerke oorwegend kleinwêreldnetwerke is wat gekenmerk word deur ’n kort gemiddelde pad wat soortgelyk is aan ’n Erdös en Rényi lukrake netwerk (ER- netwerk), maar dat oorganklikheid aansienlik hoër is as vir ekwivalente ER-netwerke. Komplekse netwerkstatistieke word vir hierdie netwerke bereken, insluitend die gemiddelde digtheid, gemiddelde pad en gemiddelde oorganklikheid van hierdie netwerke, en hulle word met mekaar vergelyk. ’n Hutsmerk- of volksonomienetwerk word saamgestel deur hutsmerke as nodusse voor te stel en ’n skakel tussen hutsmerke aan te dui indien hulle in dieselfde plasing voorkom. Die huidige studie ontleed die hutsmerknetwerke van 20 Suid-Afrikaanse maatskappye op Instagram. Die gebruik om self materiaal te ontsluit staan as volksonomie bekend, wat die onderwerp van hierdie studie is. ![]() Een van die maniere hoe hierdie inligting vir latere herwinning ontsluit word, is deur hutsmerke wat gebruikers self aan hul inhoud toeken. Sosiale media is deel van die inligtingsontploffing en verteenwoordig groot hoeveelhede ongestruktureerde data wat deurlopend gegenereer word. These schemas highlight many of the same medium-specific elements absent from RDA, for example, the value of a platform element distinct from system requirements or edition the equal emphasis on developer and publisher or the multifaceted nature of videogame genre. These will be compared to each other and be analyzed in their treatment of RDA core elements and genre classification in order to highlight the ways videogames are challenging and expanding traditional metadata standards. This study will examine videogame metadata schemas designed by information professionals, fan communities, and commercial websites. Until now, online databases developed by fan communities have led the way in creating systems that effectively capture videogame metadata, yet a few groups have recently sprung up in academia that have developed coherent schemas for implementation in libraries and museums. However, widely accepted guidelines for cataloguing videogames are still in the process of being developed. As they have begun to fill museums, archives, and libraries, the need to catalogue them has become more pressing. In the past decade, videogames have grown in cultural importance. Such analysis shall provide an intuitive presentation on the distribution and connections of the game tags, which furthermore suggests a potential way of understanding the important tags that are commonly adopted and the main genres of video games. Hence, in this study, we construct a network of game tags based on the co-occurrence of tags in games on Steam platform and analyze the structure of the network via centrality analysis and community detection. Despite the concern of the quality, the user-generated tags (game tags) provide an opportunity towards an alternative way of understanding video game genres based on the players' collective intelligence. On the other hand, Steam, a popular video game distribution platform, adopts the user-generated tag feature enabling players to describe and annotate video games based on their own understanding of genres. ![]() Despite the commonly acknowledged usefulness of genre classification, scholars in the game studies domain are yet to reach consensus on the game genre classification. By addressing these first, you can start optimizing your plant in no time.Video game genre classification has long been a focusing perspective in game studies domain. We call the measures that can be implemented fastest “QUICK HITS”. This will give you an overview and help you to see which suggestions you can implement quickly. We calculate the energy savings you can expect to achieve from each of our suggestions, as well as the amount of time in which they can be implemented. Within the scope of this analysis, we identify potential plant issues, make corresponding suggestions to resolve those issues and improve plant efficiency and safety. We focus in particular on detecting and preventing water hammer. The duration of the survey depends on the size of the plant, and it can be several days. Together with your technical staff, we carry out a comprehensive survey of the entire steam and condensate system. We make full use of this know-how in our plant inspections. TLV can provide you with expert advice on a wide range of applications, from the steam generator to the heat exchanger to condensate return system. TLV has an extensive knowledge base and deep application expertise that goes well beyond steam traps and valves. At TLV, we are dedicated to optimizing plants’ entire steam and condensate systems.
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