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Portal-Plataforma De Cultura Musical" Enero 2016 Óscar Cuevas Lanchares
PFC "PORTAL-PLATAFORMA DE CULTURA MUSICAL" ENERO 2016 ÓSCAR CUEVAS LANCHARES Departamento de Informática PROYECTO FIN DE CARRERA PORTAL-PLATAFORMA DE CULTURA MUSICAL Autor: ÓSCAR CUEVAS LANCHARES Tutor: JESÚS HERNANDO CORROCHANO Leganés, Enero de 2016 PFC "PORTAL-PLATAFORMA DE CULTURA MUSICAL" ENERO 2016 ÓSCAR CUEVAS LANCHARES Título: PORTAL-PLATAFORMA DE CULTURA MUSICAL Autor: Óscar Cuevas Lanchares Director: EL TRIBUNAL Presidente: Vocal: Secretario: Realizado el acto de defensa y lectura del Proyecto Fin de Carrera el día __ de _______ de 20__ en Leganés, en la Escuela Politécnica Superior de la Universidad Carlos III de Madrid, acuerda otorgarle la CALIFICACIÓN de VOCAL SECRETARIO PRESIDENTE PFC "PORTAL-PLATAFORMA DE CULTURA MUSICAL" ENERO 2016 ÓSCAR CUEVAS LANCHARES ÍNDICE PÁG. AGRADECIMIENTOS 1 RESUMEN 2 PALABRAS CLAVE 3 ABSTRACT 4 ESTRUCTURA DE LA MEMORIA 5 GLOSARIO DE TÉRMINOS 6 CAPÍTULO 1: MOTIVACIÓN Y OBJETIVOS 8 1.1 MOTIVACIÓN 8 1.2 OBJETIVOS 8 1.3 QUÉ SE ESPERA DE ESTE PROYECTO 9 1.4 MEDIOS EMPLEADOS 10 CAPÍTULO 2: ESTADO DEL ARTE 12 2.1 TECNOLOGÍA 12 2.1.1 J2EE 13 2.1.2 PHP 15 2.1.3 .NET 16 2.1.4 COMPUTACIÓN EN LA NUBE (CLOUD COMPUTING) 18 2.1.5 BLUEMIX 21 2.1.6 DOCKER 21 2.1.7 BASES DE DATOS NO-SQL 21 2.1.8 BIG DATA 23 2.1.9 VERTX 25 2.1.10 NODE.JS 25 2.1.11 JAVASCRIPT 26 2.1.12 SOAP 26 2.1.13 API REST 27 2.1.14 BOOTSTRAP 30 2.1.15 JSF 30 2.1.16 JPA 32 2.2 METODOLOGÍA 32 2.2.1 METODOLOGÍA EN CASCADA 33 2.2.2 METODOLOGÍA EN V 34 2.2.3 METODOLOGÍA EN ESPIRAL 35 2.2.4 METODOLOGÍA TRADICIONAL 36 2.2.5 METODOLOGÍA ÁGIL 37 2.3. -
Version 19.0.2 Plixer
Scrutinizer Documentation Version 19.0.2 Plixer January 15, 2021 Scrutinizer 1 Deployment guides3 1.1 Virtual Appliance deployment guide............................3 1.2 AMI deployment guide................................... 34 2 System administration 41 2.1 Database backups..................................... 41 2.2 Changelog......................................... 45 2.3 Check vulnerabilities.................................... 59 2.4 Data aggregation...................................... 60 2.5 Support for distributed collectors............................. 64 2.6 Configuring Scrutinizer for dual/multi-homing...................... 65 2.7 Functional IDs....................................... 67 2.8 Getting started....................................... 69 2.9 Interactive CLI....................................... 69 2.10 Language translations................................... 91 2.11 Licensing.......................................... 92 2.12 Replicator load balancing................................. 93 2.13 Meta data collection.................................... 94 2.14 Predicting disk needs.................................... 95 2.15 Interactive CLI....................................... 96 2.16 Security updates...................................... 115 2.17 Sizing your environment.................................. 116 2.18 Configuring SSL in Scrutinizer.............................. 121 2.19 Streaming support for customer data lakes........................ 124 2.20 System LEDs........................................ 124 2.21 Third-party -
From Toolkit to Framework - the Past and Future Evolution of Phedex
From toolkit to framework - the past and future evolution of PhEDEx A Sanchez-Hernandez,a R Egelandb 1, C-H Huangc, N Ratnikovad, N Maginie and T Wildishf a Centro Invest. Estudios Avanz IPN b University of Minnesota, Twin Cities c Fermi National Accelerator Laboratory d KIT (Karlsruhe Institute of Technology) and ITEP (Institute for Theoretical and Experimental Physics, Moscow, Russia) e CERN f Princeton University E-mail: [email protected] Abstract. PhEDEx is the data-movement solution for CMS at the LHC. Created in 2004, it is now one of the longest-lived components of the CMS dataflow/workflow world. As such, it has undergone significant evolution over time, and continues to evolve today, despite being a fully mature system. Originally a toolkit of agents and utilities dedicated to specific tasks, it is becoming a more open framework that can be used in several ways, both within and beyond its original problem domain. In this talk we describe how a combination of refactoring and adoption of new technologies that have become available over the years have made PhEDEx more flexible, maintainable, and scaleable. 1. Introduction PhEDEx[1] (Physics Experiment Data Export) is the data-placement management system developed by CMS for managing the experiments’ data on the grid. It uses grid-level transfer tools (FTS[2], SRM[3], etc) to transfer files according to the CMS data placement policy. It was originally implemented in 2004, and consists of a set of agents and a few ancilliary command-line tools, and a website for presenting information to users. The agents are used for repetitive tasks, scheduling them at regular intervals, such as scheduling transfers according to priorities and link performance, processing the transfer queues for a site, and updating the bookkeeping based on recent activity. -
Introduction to Perl
Introduction to Perl #!/usr/bin/perl −w # find−a−func use strict; $_=’$;="per l";map{map {s}^\s+}} ;$_{$_}++unless(/[^a− z]/)}split(/ [\s,]+/)i f(/alpha. *$;/i../w ait/)}‘$; doc\040$; toc‘;;;@[=k eys%_;$; =20;$:=15;;for(0..($;*$:−1 )){$;[$_]="_" ;}until($%++>3*$;||@]>2*$:−3){@_=split(//,splice(@[,rand( @[),1));if(3>@_){next;}$~=int(rand($;));$^=int(rand($:)); $−=$~+$^*$;;my$Erudil=0;{if($Erudil++>2*$:){next;}$a=(−1, 0,1)[rand(3)];$b=(−1,0,1)[rand(3)];unless(($a||$b)&&$~ +$a*@_<=$;&&$~+$a*@_>=0&&$^+$b*@_<=$:&&$^+$b*@_>=0){re do;;}my$llama=0;;for(0..$#_){unless($;[$−+$a*$_+$b* $;*$_]eq$_[$_]||$;[$−+$a*$_+$b*$;*$_]eq"_"){$llam a++;last;}}if($llama){redo;}push@],join("",@_);f or(0..$#_){$;[$−+$a*$_+$b*$;*$_]=$_[$_];}}}@_ =sort@];unshift@_ ,"Find:","−"x5;for$a(0. .$:−1){for$b(0. .$;−1){$~=("a".."z") [rand(26)];$_ ="$;[$a*$;+$b]". $";s;_;$~; ;print;}$_=s hift@_|| $";;print$ ",$", $_,$ /;$_ =shi ft@_ ||$ ";pr int $"x $;, $"x $;, $", $", $_ ,$/;; ;}’ ;;; s[\s+] $$g; eval; Kirrily Robert Paul Fenwick Jacinta Richardson Introduction to Perl by Kirrily Robert, Paul Fenwick, and Jacinta Richardson Copyright © 1999-2000 Netizen Pty Ltd Copyright © 2000 Kirrily Robert Copyright © 2001 Obsidian Consulting Group Pty Ltd Copyright © 2001-2005 Paul Fenwick ([email protected]) Copyright © 2001-2005 Jacinta Richardson ([email protected]) Copyright © 2001-2005 Perl Training Australia Open Publications License 1.0 Cover artwork Copyright (c) 2000 by Stephen B. Jenkins. Used with permission. The use of a llama image with the topic of Perl is a trademark of O’Reilly & Associates, Inc. -
STATE ENGINEERING UNIVERSITY of ARMENIA Department of Computer Systems and Informatics Development of Resource Sharing System Co
STATE ENGINEERING UNIVERSITY OF ARMENIA Department of Computer Systems and Informatics Artem T. HARUTYUNYAN Development of Resource Sharing System Components for AliEn Grid Infrastructure Ph.D. Thesis CERN-THESIS-2010-084 07/05/2010 Scientific adviser: Prof. Ara A. GRIGORYAN Yerevan-2010 CONTENTS INTRODUCTION .............................................................................................. 4 ACKNOWLEDGEMENTS .................................................................................. 10 CHAPTER 1. GRID COMPUTING AND CLOUD COMPUTING ............................. 12 1.1 Grid computing concepts ...................................................................... 12 1.2 The architecture of the Grid .................................................................. 15 1.2.1 End systems....................................................................................... 15 1.2.2 Clusters ............................................................................................. 16 1.2.3 Intranets ........................................................................................... 17 1.2.4 Internets ........................................................................................... 18 1.2.5 Core Grid services ............................................................................... 19 1.3 Implementations of Grid infrastructures and projects ............................... 20 1.3.1 Grid projects worldwide ....................................................................... 20 1.3.2 National Grid -
Universidad Mayor De San Andrés Facultad De Ciencias Puras Y Naturales Carrera De Informática
UNIVERSIDAD MAYOR DE SAN ANDRÉS FACULTAD DE CIENCIAS PURAS Y NATURALES CARRERA DE INFORMÁTICA TESIS DE GRADO “APLICACIÓN MÓVIL COLABORATIVA PARA CALCULAR EL TIEMPO MÁS ÓPTIMO EN RUTAS DEL TRANSPORTE PÚBLICO” PARA OPTAR AL TÍTULO DE LICENCIATURA EN INFORMÁTICA MENCIÓN: INGENIERIA DE SISTEMAS INFORMÁTICOS POSTULANTE: ELIZABETH OROZCO APAZA TUTORA METODOLÓGICA: LIC. MENFY MORALES RÍOS ASESORA: LIC. BRÍGIDA ALEXANDRA CARVAJAL BLANCO LA PAZ – BOLIVIA 2015 UNIVERSIDAD MAYOR DE SAN ANDRÉS FACULTAD DE CIENCIAS PURAS Y NATURALES CARRERA DE INFORMÁTICA LA CARRERA DE INFORMÁTICA DE LA FACULTAD DE CIENCIAS PURAS Y NATURALES PERTENECIENTE A LA UNIVERSIDAD MAYOR DE SAN ANDRÉS AUTORIZA EL USO DE LA INFORMACIÓN CONTENIDA EN ESTE DOCUMENTO SI LOS PROPÓSITOS SON ESTRICTAMENTE ACADÉMICOS. LICENCIA DE USO El usuario está autorizado a: a) visualizar el documento mediante el uso de un ordenador o dispositivo móvil. b) copiar, almacenar o imprimir si ha de ser de uso exclusivamente personal y privado. c) copiar textualmente parte(s) de su contenido mencionando la fuente y/o haciendo la referencia correspondiente respetando normas de redacción e investigación. El usuario no puede publicar, distribuir o realizar emisión o exhibición alguna de este material, sin la autorización correspondiente. TODOS LOS DERECHOS RESERVADOS. EL USO NO AUTORIZADO DE LOS CONTENIDOS PUBLICADOS EN ESTE SITIO DERIVARA EN EL INICIO DE ACCIONES LEGALES CONTEMPLADOS EN LA LEY DE DERECHOS DE AUTOR. DEDICATORIA A mi mamita Alicia Apaza Vda. de Orozco por ser ejemplo de esfuerzo y perseverancia. A mis queridos hermanos: Ricardo, Edgar, Roxana y Dora. A mis sobrinos Diana, Ian, Fernanda, Gustavo, Carolina y Brandom. Al hombre que me dio la vida, el cual a pesar de haberlo perdido a muy temprana edad, ha estado siempre cuidándome y guiándome desde el cielo. -
KOS.Content 01 | 2014
KOS.content 01 | 2014 Ergebnisse der Untersuchungen des Kompetenzzentrum Open Source der DHBW-Stuttgart Frühjahr 2014 band.2 KOS.content 01 | 2014 Editorial Lieber Leser, vor Ihnen liegt der erste Ergebnisband mit studen- Fragestellungen werden dann in Seminaren an der tischen Ausarbeitungen, die im Rahmen des For- DHBW von studentischen Arbeitsgruppen analy- schungsprojekt KOS entstanden sind. KOS steht siert, wobei nicht nur die Dozenten, sondern auch für Kompetenzzentrum Open Source und bezeich- Fachexperten der dualen Partner die Studierenden net ein kooperatives Forschungsprojekt im Studi- wissenschaftlich leiten. engang Wirtschaftsinformatik der DHBW Stutt- gart, das in Zusammenarbeit mit den dualen Am Ende eines jeden Seminars präsentieren die Partnern Allianz Deutschland, HALLESCHE Kran- Studierenden die Untersuchungsergebnisse vor kenversicherung und Deutsche Rentenversiche- den Vertretern der beteiligten Unternehmen. Meist rung Baden-Württemberg den Einsatz von Open geht dabei um generische Lösungskonzepte, die Source Software/Techniken zur Optimierung von von den beteiligten dualen Partnern in konkrete Geschäftsprozessen in Versicherungsunterneh- Lösungen für das eigene Unternehmen umgesetzt men untersucht. werden können. Diese Abschlusspräsentationen sind nicht nur für die Unternehmen, sondern auch Die Ursprünge des Forschungsprojekts KOS gehen für die Studierenden etwas Besonderes, da sie ihre auf das Jahr 2009 zurück, in dem die Duale Hoch- Seminarergebnisse vor einem recht großen fach- schule Baden-Württemberg (DHBW) nicht -
Scrutinizer Documentation Version 18.18 Plixer
Scrutinizer Documentation Version 18.18 Plixer February 18, 2020 Scrutinizer 1 Deployment guides3 1.1 Virtual Appliance deployment guide............................3 1.2 AMI deployment guide................................... 42 2 System administration 51 2.1 Getting started....................................... 51 2.2 Changelog......................................... 52 2.3 Licensing.......................................... 61 2.4 Meta data collection.................................... 62 2.5 System LEDs........................................ 63 2.6 Functional IDs....................................... 66 2.7 Data aggregation...................................... 68 2.8 Configuring SSL in Scrutinizer.............................. 71 2.9 Database backups..................................... 73 2.10 Upgrade instructions.................................... 77 2.11 Interactive scrut_util.................................... 80 2.12 Configuring Scrutinizer for dual/multi-homing...................... 101 2.13 Support for distributed collectors............................. 103 2.14 Check vulnerabilities.................................... 104 2.15 Security updates...................................... 105 2.16 Language translations................................... 106 2.17 Third-party licenses.................................... 107 3 Integration guides 129 3.1 Configuring Amazon Web Services Flow Logs...................... 129 3.2 Cisco’s FireSIGHT eStreamer client............................ 131 i 3.3 Elasticsearch / Kibana (ELK) integration........................ -
Converting Network Media Data Into Human Readable Form a Study on Deep Packet Inspection with with Real- Time Visualization
Degree project Converting Network Media Data into Human Readable Form A study on deep packet inspection with with real- time visualization. Author: Steffen-Marc Förderer Date: 2011-05-25 Subject: Computer Science Level: Bachelor Course code: 2DV00E Converting Network Media Data into Human Readable Form A Study on deep packet inspection with real-time visualization. by c Steffen-Marc F¨orderer A thesis submitted to the School of Graduate Studies in partial fulfilment of the requirements for the degree of Bachelor of Computer Science Matematiska och systemtekniska institutionen Linn´euniversitetet 05 2011 V¨axj¨o Sverige Abstract A proof of concept study into the working of network media capture and visual- ization through the use of Packet Capture in realtime. An application was developed that is able to capture tcp network packets; identify and display images in raw HTTP network traffic through the use of search, sort, error detection, timeout failsafe al- gorithms in real time. The application was designed for network administrators to visualize raw network media content together with its relevant network source & ad- dress identifiers. Different approaches were tried and tested such as using Perl with GTK+ and Visual Studio C# .Net. Furthermore two different types of image identi- fication methods were used: raw magic string identification in pure tcp network traffic and HTTP Mime type identification. The latter being more accurate and faster. C# was seen as vastly superior in both speed of prototyping and final performance eval- uation. The study presents a novel new way of monitoring networks on the basis of their media content through deep packet inspection. -
Scrutinizer Documentation Version 19.0.2 Plixer
Scrutinizer Documentation Version 19.0.2 Plixer May 26, 2021 Contents 1 Deployment guides1 1.1 Virtual Appliance deployment guide............................1 1.2 AMI deployment guide................................... 32 2 System administration 39 2.1 Changelog......................................... 39 2.2 Checking for vulnerabilities................................ 53 2.3 Data aggregation...................................... 54 2.4 Support for distributed collectors............................. 58 2.5 Functional IDs....................................... 59 2.6 Interactive CLI....................................... 61 2.7 Language translations................................... 83 2.8 Licensing.......................................... 84 2.9 Predicting disk needs.................................... 85 2.10 Replicator load balancing................................. 86 2.11 Security updates...................................... 87 2.12 Sharing meta data with Plixer............................... 88 2.13 Sizing your environment.................................. 90 2.14 SSL configuration..................................... 95 2.15 Streaming support for customer data lakes........................ 98 2.16 Third-party licenses.................................... 98 2.17 Upgrade guide....................................... 119 3 Integration guides 121 3.1 Advanced Threat Intelligence Feed............................ 121 3.2 Amazon Web Services flow logs.............................. 122 i 3.3 Elasticsearch / Kibana (ELK) integration........................ -
Still Doing Evolutionary Algorithms with Perl
Still doing evolutionary algorithms with Perl Juan Juli´an Merelo Guerv´os Depto. Arquitectura y Tecnolog´ıa de Computadores, ETS Ingenier´ıa Inform´atica y Telecomunicaciones, Universidad de Granada (Spain) and Granada Perl Monger and Free Software Office, UGR http://osl.ugr.es Tel.: +34-958-243162, Email: [email protected] http://search.cpan.org/~jmerelo/ October 8, 2018 Abstract Algorithm::Evolutionary (A::E from now on) was introduced in 2002, after a talk in YAPC::EU in M¨unich. 7 years later, A::E is in its 0.67 version (past its ”number of the beast” 0.666), and has been used extensively, to the point of being the foundation of much of the (computer) science being done by our research group (and, admittedly, not many others). All is not done, however; now A::E is being integrated with POE so that evolutionary algorithms (EAs) can be combined with all kinds of servers and used in client, servers, and anything in between. In this companion to the talk I will explain what arXiv:0908.0516v1 [cs.NE] 4 Aug 2009 evolutionary algorithms are, what they are being used for, how to do them with Perl (using these or other fine modules found in CPAN) and what evolutionary algorithms can do for Perl at large. 1 Don’t talk no evolution, I believe in intel- ligent design! Right-on, buddy, but while you’re at it think about this very simple exper- iment. You’ve probably never done a chili con carne, right? Well, if you 1 Table 1: Scores given by Y. -
Programming Perl
Programming Perl #!/usr/bin/perl −w use strict; $_=’ev al("seek\040D ATA,0, 0;");foreach(1..2) {<DATA>;}my @camel1hump;my$camel; my$Camel ;while( <DATA>){$_=sprintf("%−6 9s",$_);my@dromedary 1=split(//);if(defined($ _=<DATA>)){@camel1hum p=split(//);}while(@dromeda ry1){my$camel1hump=0 ;my$CAMEL=3;if(defined($_=shif t(@dromedary1 ))&&/\S/){$camel1hump+=1<<$CAMEL;} $CAMEL−−;if(d efined($_=shift(@dromedary1))&&/\S/){ $camel1hump+=1 <<$CAMEL;}$CAMEL−−;if(defined($_=shift( @camel1hump))&&/\S/){$camel1hump+=1<<$CAMEL;}$CAMEL−−;if( defined($_=shift(@camel1hump))&&/\S/){$camel1hump+=1<<$CAME L;;}$camel.=(split(//,"\040..m‘{/J\047\134}L^7FX"))[$camel1h ump];}$camel.="\n";}@camel1hump=split(/\n/,$camel);foreach(@ camel1hump){chomp;$Camel=$_;tr/LJF7\173\175‘\047/\061\062\063 45678/;tr/12345678/JL7F\175\173\047‘/;$_=reverse;print"$_\040 $Camel\n";}foreach(@camel1hump){chomp;$Camel=$_;y/LJF7\173\17 5‘\047/12345678/;tr/12345678/JL7F\175\173\047‘/;$_=reverse;p rint"\040$_$Camel\n";}#japh−Erudil’;;s;\s*;;g;;eval; eval ("seek\040DATA,0,0;");undef$/;$_=<DATA>;s$\s*$$g;( );;s ;^.*_;;;map{eval"print\"$_\"";}/.{4}/g; __DATA__ \124 \1 50\145\040\165\163\145\040\157\1 46\040\1 41\0 40\143\141 \155\145\1 54\040\1 51\155\ 141 \147\145\0 40\151\156 \040\141 \163\16 3\ 157\143\ 151\141\16 4\151\1 57\156 \040\167 \151\164\1 50\040\ 120\1 45\162\ 154\040\15 1\163\ 040\14 1\040\1 64\162\1 41\144 \145\ 155\14 1\162\ 153\04 0\157 \146\ 040\11 7\047\ 122\1 45\15 1\154\1 54\171 \040 \046\ 012\101\16 3\16 3\15 7\143\15 1\14 1\16 4\145\163 \054 \040 \111\156\14 3\056 \040\