{"version":"1.0","provider_name":"JITA -Journal of Information Technology and Application","provider_url":"https:\/\/jita-au.com","author_name":"admin","author_url":"https:\/\/jita-au.com\/index.php\/author\/jita-au-com\/","title":"Measuring the Characteristics of DG CAC Algorithm - JITA -Journal of Information Technology and Application","type":"rich","width":600,"height":338,"html":"<blockquote class=\"wp-embedded-content\" data-secret=\"cdg82VoujC\"><a href=\"https:\/\/jita-au.com\/index.php\/2024\/04\/12\/measuring-the-characteristics-of-dg-cac-algorithm\/\">Measuring the Characteristics of DG CAC Algorithm<\/a><\/blockquote><iframe sandbox=\"allow-scripts\" security=\"restricted\" src=\"https:\/\/jita-au.com\/index.php\/2024\/04\/12\/measuring-the-characteristics-of-dg-cac-algorithm\/embed\/#?secret=cdg82VoujC\" width=\"600\" height=\"338\" title=\"&#8220;Measuring the Characteristics of DG CAC Algorithm&#8221; &#8212; JITA -Journal of Information Technology and Application\" data-secret=\"cdg82VoujC\" frameborder=\"0\" marginwidth=\"0\" marginheight=\"0\" scrolling=\"no\" class=\"wp-embedded-content\"><\/iframe><script>\n\/*! This file is auto-generated *\/\n!function(d,l){\"use strict\";l.querySelector&&d.addEventListener&&\"undefined\"!=typeof URL&&(d.wp=d.wp||{},d.wp.receiveEmbedMessage||(d.wp.receiveEmbedMessage=function(e){var t=e.data;if((t||t.secret||t.message||t.value)&&!\/[^a-zA-Z0-9]\/.test(t.secret)){for(var s,r,n,a=l.querySelectorAll('iframe[data-secret=\"'+t.secret+'\"]'),o=l.querySelectorAll('blockquote[data-secret=\"'+t.secret+'\"]'),c=new RegExp(\"^https?:$\",\"i\"),i=0;i<o.length;i++)o[i].style.display=\"none\";for(i=0;i<a.length;i++)s=a[i],e.source===s.contentWindow&&(s.removeAttribute(\"style\"),\"height\"===t.message?(1e3<(r=parseInt(t.value,10))?r=1e3:~~r<200&&(r=200),s.height=r):\"link\"===t.message&&(r=new URL(s.getAttribute(\"src\")),n=new URL(t.value),c.test(n.protocol))&&n.host===r.host&&l.activeElement===s&&(d.top.location.href=t.value))}},d.addEventListener(\"message\",d.wp.receiveEmbedMessage,!1),l.addEventListener(\"DOMContentLoaded\",function(){for(var e,t,s=l.querySelectorAll(\"iframe.wp-embedded-content\"),r=0;r<s.length;r++)(t=(e=s[r]).getAttribute(\"data-secret\"))||(t=Math.random().toString(36).substring(2,12),e.src+=\"#?secret=\"+t,e.setAttribute(\"data-secret\",t)),e.contentWindow.postMessage({message:\"ready\",secret:t},\"*\")},!1)))}(window,document);\n\/\/# sourceURL=https:\/\/jita-au.com\/wp-includes\/js\/wp-embed.min.js\n<\/script>\n","thumbnail_url":"https:\/\/jita-au.com\/wp-content\/uploads\/2024\/03\/cover_issue_949_en_US.jpg","thumbnail_width":595,"thumbnail_height":793,"description":"Vol. 1 No. 1 (2011): JITA &#8211; APEIRON Goran \u0110ukanovi\u0107, Milan \u0160unjevari\u0107, Nata\u0161a Gospi\u0107 Measuring the Characteristics of DG CAC Algorithm Original scientific paper DOI: https:\/\/doi.org\/10.7251\/JIT1101060DJ Download Article PDF Abstract Users today expect email and instant messaging access, surf, video games and other services through mobile broadband access networks. In order to support this increasing data traffic, advanced resource management has to be implemented. As CAC (Call Admission Control) algorithm plays an important role in this resource management, comparing of two proposed call admission control algorithms has been done in this paper. Algorithms are tested in simulation environment, for two different periods of time. They showed expected characteristics in both 1000 and 10000 seconds periods, and newly proposed DG CAC algorithm showed better results than other algorithm, in number of handover requests, and in the way of returning resources to degraded connections. Keywords: CAC, QoS, UMTS, Wireless. Vol. 26 No. 2 (2023): JITA &#8211; APEIRON Igor Shubinsky, Alexey Ozerov Application of Artificial Intelligence Methods for the Prediction of Hazardous Failures Original scientific paper DOI: https:\/\/doi.org\/10.7251\/JIT2302061S Download Article PDF Abstract The availability of real-time data on the state of railway facilities and the state-of-the art technologies for data collection and analysis allow transition to the fourth generation maintenance. It is based on the prediction of the facility functional safety and dependability and the risk-oriented facility management. The article describes an approach to assessing the risks of hazardous facility failures using the latest digital data processing methods. The implementation of this approach will help set maintenance objectives and contribute to the efficient use of resources and the reduction of railway facility managers\u2019 expenditures. Keywords: predictive analysis, maintenance, functional safety, Big Data, Data Science, risk indicators. Vol. 26 No. 2 (2023): JITA &#8211; APEIRON Igor Shubinsky, Alexey Ozerov Application of Artificial Intelligence Methods for the Prediction of Hazardous Failures Original scientific paper DOI: https:\/\/doi.org\/10.7251\/JIT2302061S Download Article PDF Abstract The availability of real-time data on the state of railway facilities and the state-of-the art technologies for data collection and analysis allow transition to the fourth generation maintenance. It is based on the prediction of the facility functional safety and dependability and the risk-oriented facility management. The article describes an approach to assessing the risks of hazardous facility failures using the latest digital data processing methods. The implementation of this approach will help set maintenance objectives and contribute to the efficient use of resources and the reduction of railway facility managers\u2019 expenditures. Keywords: predictive analysis, maintenance, functional safety, Big Data, Data Science, risk indicators."}