{"id":24265983,"url":"https://github.com/lukehackett/clusteranalysistool","last_synced_at":"2025-03-05T01:26:06.575Z","repository":{"id":4578253,"uuid":"5719982","full_name":"LukeHackett/ClusterAnalysisTool","owner":"LukeHackett","description":null,"archived":false,"fork":false,"pushed_at":"2013-04-24T19:38:03.000Z","size":16284,"stargazers_count":0,"open_issues_count":0,"forks_count":1,"subscribers_count":2,"default_branch":"master","last_synced_at":"2025-01-15T11:30:21.029Z","etag":null,"topics":[],"latest_commit_sha":null,"homepage":null,"language":"C#","has_issues":false,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":null,"status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/LukeHackett.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":null,"code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null}},"created_at":"2012-09-07T17:21:47.000Z","updated_at":"2014-06-06T18:02:07.000Z","dependencies_parsed_at":"2022-09-21T18:20:18.792Z","dependency_job_id":null,"html_url":"https://github.com/LukeHackett/ClusterAnalysisTool","commit_stats":null,"previous_names":[],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/LukeHackett%2FClusterAnalysisTool","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/LukeHackett%2FClusterAnalysisTool/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/LukeHackett%2FClusterAnalysisTool/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/LukeHackett%2FClusterAnalysisTool/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/LukeHackett","download_url":"https://codeload.github.com/LukeHackett/ClusterAnalysisTool/tar.gz/refs/heads/master","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":241947309,"owners_count":20047166,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":[],"created_at":"2025-01-15T10:58:47.750Z","updated_at":"2025-03-05T01:26:06.556Z","avatar_url":"https://github.com/LukeHackett.png","language":"C#","readme":"Cluster Analysis Tool\r\n===================\r\n\r\n###Problem\r\nConsider a wireless product consistently dropping calls within a one mile radius \r\nat a particular point upon a drive test. Currently, RIM is able debug this \r\nproduct within the test field laboratory to find out if there is a hardware and/or \r\nsoftware bug associated with the error. However if the results of the laboratory \r\ntests came back as a pass, it would have to be assumed that there is an issue \r\nwith the mobile network. \r\nIt is this assumption that can cause frustration for RIM's third parties (e.g. \r\ncustomers and mobile network operators), even more so if other wireless devices \r\nwithin the same area are able to communicate perfectly fine.\r\n\r\n\r\n###Solution\r\nTo design, implement and test one (or more) clustering algorithms in order to \r\ncluster coordinates that are generated by cellular devices. A further comparison \r\nof the various devices' meta-data will be required in order to allow for a more \r\nspecific, in depth analysis.\r\n\r\n\r\n###User Requirements\r\nThe following objectives have been set directly by the client, RIM. These objectives \r\nhave been outlined using the MoSCoW prioritisation technique, and are outlined \r\nbelow:\r\n\r\n**MUST**\r\n* Design and develop an algorithm to cluster GPS coordinates.\r\n* Compare RAT footprints of two data sets (products or pins) with each set being \r\nN weeks' worth of data and highlight differences in the RAT usage/drop/fails \r\nalong the route.\r\n* Compare MIX_BAND (Frequency bands) footprints of two data sets and highlight \r\ndifferences in usage/drops/fails between sets.\r\n\r\n**SHOULD**\r\n* Compare two sets of data for call its drop/failure clusters and highlight \r\ndifferences. \r\n* Ability to tag drops/fails with classification attributes and even compare \r\nbased on attributes.\r\n* Produce a web-based interface to the results, with a map plugin allowing the \r\nuser to view the data.\r\n\r\n**COULD**\r\n* Velocity differences along route.\r\n* Plot a map for all call attempts and call ends (success/fail) for a given \r\nperiod of time, for different devices.\r\n* Allow the user to filter the clustering down (e.g. show only call drops).\r\n\r\n**WON'T**\r\n* Integration with current internal RIM testing systems.","funding_links":[],"categories":[],"sub_categories":[],"project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Flukehackett%2Fclusteranalysistool","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Flukehackett%2Fclusteranalysistool","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Flukehackett%2Fclusteranalysistool/lists"}