• Català
  • Castellano
  • English
Logo Catalònica
  • Búsqueda
  • Colecciones
  • Conócenos
  • Ayuda
  • Directorio
  • Profesionales
Está en:  › Datos de registro
Linked Open Data
Abnormal Behavior Identification through Deep Learning: TensorFlow
Identificadores del recurso
http://hdl.handle.net/20.500.12367/2164
Procedencia
(Repositori Digital del TecnoCampus)

Ficha

Título:
Abnormal Behavior Identification through Deep Learning: TensorFlow
Tema:
Indústria manufacturera, manteniment predictiu, intel·ligència artificial
Descripción:
Treball de fi de grau - Curs 2021-2022
Aplicar efectivament a l´industria de la manufacturació el manteniment predictiu, es a dir, poder esbrinar quan, on i com tindrem fallades en un sistema de la cadena de producció pot resultar molt beneficiós. Per a aplicar el manteniment predictiu, es desenvoluparan models d’intel·ligència artificial. Es posaran a prova aquests diversos models estadístics, d’aprenentatge automàtic i d’aprenentatge profund per a comprendre quines tècniques ens ofereixen els millors resultats davant aquest problema.
Idioma:
Spanish; Castilian
Autor/Productor:
Torrell Belzach, Robert
Otros colaboradores/productores:
TecnoCampus. Escola Superior Politècnica (ESUPT)
Font Aragonès, Xavier
Derechos:
Attribution 4.0 International
http://creativecommons.org/licenses/by/4.0/
info:eu-repo/semantics/openAccess
Fecha:
2023-01-31T13:52:11Z
2022
Tipo de recurso:
info:eu-repo/semantics/bachelorThesis
Formato:
49, 7 p.
application/pdf

oai_dc

Descargar XML

    <?xml version="1.0" encoding="UTF-8" ?>

  1. < oai_dc:dc schemaLocation =" http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd " >

    1. < dc:title > Abnormal Behavior Identification through Deep Learning: TensorFlow </ dc:title >

    2. < dc:creator > Torrell Belzach, Robert </ dc:creator >

    3. < dc:contributor > TecnoCampus. Escola Superior Politècnica (ESUPT) </ dc:contributor >

    4. < dc:contributor > Font Aragonès, Xavier </ dc:contributor >

    5. < dc:subject > Indústria manufacturera, manteniment predictiu, intel·ligència artificial </ dc:subject >

    6. < dc:description > Treball de fi de grau - Curs 2021-2022 </ dc:description >

    7. < dc:description > Aplicar efectivament a l´industria de la manufacturació el manteniment predictiu, es a dir, poder esbrinar quan, on i com tindrem fallades en un sistema de la cadena de producció pot resultar molt beneficiós. Per a aplicar el manteniment predictiu, es desenvoluparan models d’intel·ligència artificial. Es posaran a prova aquests diversos models estadístics, d’aprenentatge automàtic i d’aprenentatge profund per a comprendre quines tècniques ens ofereixen els millors resultats davant aquest problema. </ dc:description >

    8. < dc:date > 2023-01-31T13:52:11Z </ dc:date >

    9. < dc:date > 2023-01-31T13:52:11Z </ dc:date >

    10. < dc:date > 2022 </ dc:date >

    11. < dc:type > info:eu-repo/semantics/bachelorThesis </ dc:type >

    12. < dc:identifier > http://hdl.handle.net/20.500.12367/2164 </ dc:identifier >

    13. < dc:language > spa </ dc:language >

    14. < dc:rights > Attribution 4.0 International </ dc:rights >

    15. < dc:rights > http://creativecommons.org/licenses/by/4.0/ </ dc:rights >

    16. < dc:rights > info:eu-repo/semantics/openAccess </ dc:rights >

    17. < dc:format > 49, 7 p. </ dc:format >

    18. < dc:format > application/pdf </ dc:format >

    19. < dc:format > application/pdf </ dc:format >

    </ oai_dc:dc >

didl

Descargar XML

    <?xml version="1.0" encoding="UTF-8" ?>

  1. < d:DIDL schemaLocation =" urn:mpeg:mpeg21:2002:02-DIDL-NS http://standards.iso.org/ittf/PubliclyAvailableStandards/MPEG-21_schema_files/did/didl.xsd " >

    1. < d:DIDLInfo >

      1. < dcterms:created schemaLocation =" http://purl.org/dc/terms/ http://dublincore.org/schemas/xmls/qdc/dcterms.xsd " > 2023-01-31T13:52:11Z </ dcterms:created >

      </ d:DIDLInfo >

    2. < d:Item id =" hdl_20.500.12367_2164 " >

      1. < d:Descriptor >

        1. < d:Statement mimeType =" application/xml; charset=utf-8 " >

          1. < dii:Identifier schemaLocation =" urn:mpeg:mpeg21:2002:01-DII-NS http://standards.iso.org/ittf/PubliclyAvailableStandards/MPEG-21_schema_files/dii/dii.xsd " > urn:hdl:20.500.12367/2164 </ dii:Identifier >

          </ d:Statement >

        </ d:Descriptor >

      2. < d:Descriptor >

        1. < d:Statement mimeType =" application/xml; charset=utf-8 " >

          1. < oai_dc:dc schemaLocation =" http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd " >

            1. < dc:title > Abnormal Behavior Identification through Deep Learning: TensorFlow </ dc:title >

            2. < dc:creator > Torrell Belzach, Robert </ dc:creator >

            3. < dc:contributor > TecnoCampus. Escola Superior Politècnica (ESUPT) </ dc:contributor >

            4. < dc:contributor > Font Aragonès, Xavier </ dc:contributor >

            5. < dc:description > Treball de fi de grau - Curs 2021-2022 </ dc:description >

            6. < dc:description > Aplicar efectivament a l´industria de la manufacturació el manteniment predictiu, es a dir, poder esbrinar quan, on i com tindrem fallades en un sistema de la cadena de producció pot resultar molt beneficiós. Per a aplicar el manteniment predictiu, es desenvoluparan models d’intel·ligència artificial. Es posaran a prova aquests diversos models estadístics, d’aprenentatge automàtic i d’aprenentatge profund per a comprendre quines tècniques ens ofereixen els millors resultats davant aquest problema. </ dc:description >

            7. < dc:date > 2023-01-31T13:52:11Z </ dc:date >

            8. < dc:date > 2023-01-31T13:52:11Z </ dc:date >

            9. < dc:date > 2022 </ dc:date >

            10. < dc:type > info:eu-repo/semantics/bachelorThesis </ dc:type >

            11. < dc:identifier > http://hdl.handle.net/20.500.12367/2164 </ dc:identifier >

            12. < dc:language > spa </ dc:language >

            13. < dc:rights > http://creativecommons.org/licenses/by/4.0/ </ dc:rights >

            14. < dc:rights > info:eu-repo/semantics/openAccess </ dc:rights >

            15. < dc:rights > Attribution 4.0 International </ dc:rights >

            </ oai_dc:dc >

          </ d:Statement >

        </ d:Descriptor >

      3. < d:Component id =" 20.500.12367_2164_1 " >

        1. < d:Resource mimeType =" application/pdf " ref =" https://repositori.tecnocampus.cat/bitstream/20.500.12367/2164/1/TFG_TorrellBelzach_Memoria.pdf " />

        </ d:Component >

      4. < d:Component id =" 20.500.12367_2164_2 " >

        1. < d:Resource mimeType =" application/pdf " ref =" https://repositori.tecnocampus.cat/bitstream/20.500.12367/2164/2/TFG_TorrellBelzach_EstudiViabilitat.pdf " />

        </ d:Component >

      </ d:Item >

    </ d:DIDL >

edm

Descargar XML

    <?xml version="1.0" encoding="UTF-8" ?>

  1. < rdf:RDF schemaLocation =" http://www.w3.org/1999/02/22-rdf-syntax-ns# http://www.europeana.eu/schemas/edm/EDM.xsd " >

    1. < edm:ProvidedCHO about =" https://catalonica.bnc.cat/catalonicahub/lod/oai:repositori.tecnocampus.cat:20.500.12367_--_2164#ent0 " >

      1. < dc:contributor > TecnoCampus. Escola Superior Politècnica (ESUPT) </ dc:contributor >

      2. < dc:contributor > Font Aragonès, Xavier </ dc:contributor >

      3. < dc:creator > Torrell Belzach, Robert </ dc:creator >

      4. < dc:date > 2023-01-31T13:52:11Z </ dc:date >

      5. < dc:date > 2023-01-31T13:52:11Z </ dc:date >

      6. < dc:date > 2022 </ dc:date >

      7. < dc:description > Treball de fi de grau - Curs 2021-2022 </ dc:description >

      8. < dc:description > Aplicar efectivament a l´industria de la manufacturació el manteniment predictiu, es a dir, poder esbrinar quan, on i com tindrem fallades en un sistema de la cadena de producció pot resultar molt beneficiós. Per a aplicar el manteniment predictiu, es desenvoluparan models d’intel·ligència artificial. Es posaran a prova aquests diversos models estadístics, d’aprenentatge automàtic i d’aprenentatge profund per a comprendre quines tècniques ens ofereixen els millors resultats davant aquest problema. </ dc:description >

      9. < dc:identifier > http://hdl.handle.net/20.500.12367/2164 </ dc:identifier >

      10. < dc:language > spa </ dc:language >

      11. < dc:rights > Attribution 4.0 International </ dc:rights >

      12. < dc:rights > http://creativecommons.org/licenses/by/4.0/ </ dc:rights >

      13. < dc:rights > info:eu-repo/semantics/openAccess </ dc:rights >

      14. < dc:subject > Indústria manufacturera, manteniment predictiu, intel·ligència artificial </ dc:subject >

      15. < dc:title > Abnormal Behavior Identification through Deep Learning: TensorFlow </ dc:title >

      16. < dc:type > info:eu-repo/semantics/bachelorThesis </ dc:type >

      17. < edm:type > TEXT </ edm:type >

      </ edm:ProvidedCHO >

    2. < ore:Aggregation about =" https://catalonica.bnc.cat/catalonicahub/lod/oai:repositori.tecnocampus.cat:20.500.12367_--_2164#ent1 " >

      1. < edm:aggregatedCHO resource =" https://catalonica.bnc.cat/catalonicahub/lod/oai:repositori.tecnocampus.cat:20.500.12367_--_2164#ent0 " />
      2. < edm:dataProvider > Repositori Digital del TecnoCampus </ edm:dataProvider >

      3. < edm:isShownAt resource =" http://hdl.handle.net/20.500.12367/2164 " />
      4. < edm:isShownBy resource =" https://repositori.tecnocampus.cat/bitstream/20.500.12367/2164/1/TFG_TorrellBelzach_Memoria.pdf " />
      5. < edm:provider > Catalònica </ edm:provider >

      6. < edm:rights resource =" http://creativecommons.org/licenses/by/4.0/ " />

      </ ore:Aggregation >

    </ rdf:RDF >

etdms

Descargar XML

    <?xml version="1.0" encoding="UTF-8" ?>

  1. < thesis schemaLocation =" http://www.ndltd.org/standards/metadata/etdms/1.0/ http://www.ndltd.org/standards/metadata/etdms/1.0/etdms.xsd " >

    1. < title > Abnormal Behavior Identification through Deep Learning: TensorFlow </ title >

    2. < creator > Torrell Belzach, Robert </ creator >

    3. < contributor > TecnoCampus. Escola Superior Politècnica (ESUPT) </ contributor >

    4. < contributor > Font Aragonès, Xavier </ contributor >

    5. < description > Treball de fi de grau - Curs 2021-2022 </ description >

    6. < description > Aplicar efectivament a l´industria de la manufacturació el manteniment predictiu, es a dir, poder esbrinar quan, on i com tindrem fallades en un sistema de la cadena de producció pot resultar molt beneficiós. Per a aplicar el manteniment predictiu, es desenvoluparan models d’intel·ligència artificial. Es posaran a prova aquests diversos models estadístics, d’aprenentatge automàtic i d’aprenentatge profund per a comprendre quines tècniques ens ofereixen els millors resultats davant aquest problema. </ description >

    7. < date > 2023-01-31 </ date >

    8. < date > 2023-01-31 </ date >

    9. < date > 2022 </ date >

    10. < type > info:eu-repo/semantics/bachelorThesis </ type >

    11. < identifier > http://hdl.handle.net/20.500.12367/2164 </ identifier >

    12. < language > spa </ language >

    13. < rights > http://creativecommons.org/licenses/by/4.0/ </ rights >

    14. < rights > info:eu-repo/semantics/openAccess </ rights >

    15. < rights > Attribution 4.0 International </ rights >

    </ thesis >

marc

Descargar XML

    <?xml version="1.0" encoding="UTF-8" ?>

  1. < record schemaLocation =" http://www.loc.gov/MARC21/slim http://www.loc.gov/standards/marcxml/schema/MARC21slim.xsd " >

    1. < leader > 00925njm 22002777a 4500 </ leader >

    2. < datafield ind1 =" " ind2 =" " tag =" 042 " >

      1. < subfield code =" a " > dc </ subfield >

      </ datafield >

    3. < datafield ind1 =" " ind2 =" " tag =" 720 " >

      1. < subfield code =" a " > Torrell Belzach, Robert </ subfield >

      2. < subfield code =" e " > author </ subfield >

      </ datafield >

    4. < datafield ind1 =" " ind2 =" " tag =" 260 " >

      1. < subfield code =" c " > 2022 </ subfield >

      </ datafield >

    5. < datafield ind1 =" " ind2 =" " tag =" 520 " >

      1. < subfield code =" a " > Aplicar efectivament a l´industria de la manufacturació el manteniment predictiu, es a dir, poder esbrinar quan, on i com tindrem fallades en un sistema de la cadena de producció pot resultar molt beneficiós. Per a aplicar el manteniment predictiu, es desenvoluparan models d’intel·ligència artificial. Es posaran a prova aquests diversos models estadístics, d’aprenentatge automàtic i d’aprenentatge profund per a comprendre quines tècniques ens ofereixen els millors resultats davant aquest problema. </ subfield >

      </ datafield >

    6. < datafield ind1 =" 8 " ind2 =" " tag =" 024 " >

      1. < subfield code =" a " > http://hdl.handle.net/20.500.12367/2164 </ subfield >

      </ datafield >

    7. < datafield ind1 =" 0 " ind2 =" 0 " tag =" 245 " >

      1. < subfield code =" a " > Abnormal Behavior Identification through Deep Learning: TensorFlow </ subfield >

      </ datafield >

    </ record >

mets

Descargar XML

    <?xml version="1.0" encoding="UTF-8" ?>

  1. < mets ID =" DSpace_ITEM_20.500.12367-2164 " OBJID =" hdl:20.500.12367/2164 " PROFILE =" DSpace METS SIP Profile 1.0 " TYPE =" DSpace ITEM " schemaLocation =" http://www.loc.gov/METS/ http://www.loc.gov/standards/mets/mets.xsd " >

    1. < metsHdr CREATEDATE =" 2023-10-08T01:02:44Z " >

      1. < agent ROLE =" CUSTODIAN " TYPE =" ORGANIZATION " >

        1. < name > TECNOCAMPUS </ name >

        </ agent >

      </ metsHdr >

    2. < dmdSec ID =" DMD_20.500.12367_2164 " >

      1. < mdWrap MDTYPE =" MODS " >

        1. < xmlData schemaLocation =" http://www.loc.gov/mods/v3 http://www.loc.gov/standards/mods/v3/mods-3-1.xsd " >

          1. < mods:mods schemaLocation =" http://www.loc.gov/mods/v3 http://www.loc.gov/standards/mods/v3/mods-3-1.xsd " >

            1. < mods:name >

              1. < mods:role >

                1. < mods:roleTerm type =" text " > author </ mods:roleTerm >

                </ mods:role >

              2. < mods:namePart > Torrell Belzach, Robert </ mods:namePart >

              </ mods:name >

            2. < mods:name >

              1. < mods:role >

                1. < mods:roleTerm type =" text " > other </ mods:roleTerm >

                </ mods:role >

              2. < mods:namePart > TecnoCampus. Escola Superior Politècnica (ESUPT) </ mods:namePart >

              </ mods:name >

            3. < mods:name >

              1. < mods:role >

                1. < mods:roleTerm type =" text " > tutor </ mods:roleTerm >

                </ mods:role >

              2. < mods:namePart > Font Aragonès, Xavier </ mods:namePart >

              </ mods:name >

            4. < mods:extension >

              1. < mods:dateAccessioned encoding =" iso8601 " > 2023-01-31T13:52:11Z </ mods:dateAccessioned >

              </ mods:extension >

            5. < mods:extension >

              1. < mods:dateAvailable encoding =" iso8601 " > 2023-01-31T13:52:11Z </ mods:dateAvailable >

              </ mods:extension >

            6. < mods:originInfo >

              1. < mods:dateIssued encoding =" iso8601 " > 2022 </ mods:dateIssued >

              </ mods:originInfo >

            7. < mods:identifier type =" uri " > http://hdl.handle.net/20.500.12367/2164 </ mods:identifier >

            8. < mods:abstract > Aplicar efectivament a l´industria de la manufacturació el manteniment predictiu, es a dir, poder esbrinar quan, on i com tindrem fallades en un sistema de la cadena de producció pot resultar molt beneficiós. Per a aplicar el manteniment predictiu, es desenvoluparan models d’intel·ligència artificial. Es posaran a prova aquests diversos models estadístics, d’aprenentatge automàtic i d’aprenentatge profund per a comprendre quines tècniques ens ofereixen els millors resultats davant aquest problema. </ mods:abstract >

            9. < mods:language >

              1. < mods:languageTerm authority =" rfc3066 " > spa </ mods:languageTerm >

              </ mods:language >

            10. < mods:accessCondition type =" useAndReproduction " > Attribution 4.0 International </ mods:accessCondition >

            11. < mods:titleInfo >

              1. < mods:title > Abnormal Behavior Identification through Deep Learning: TensorFlow </ mods:title >

              </ mods:titleInfo >

            12. < mods:genre > info:eu-repo/semantics/bachelorThesis </ mods:genre >

            </ mods:mods >

          </ xmlData >

        </ mdWrap >

      </ dmdSec >

    3. < amdSec ID =" FO_20.500.12367_2164_1 " >

      1. < techMD ID =" TECH_O_20.500.12367_2164_1 " >

        1. < mdWrap MDTYPE =" PREMIS " >

          1. < xmlData schemaLocation =" http://www.loc.gov/standards/premis http://www.loc.gov/standards/premis/PREMIS-v1-0.xsd " >

            1. < premis:premis >

              1. < premis:object >

                1. < premis:objectIdentifier >

                  1. < premis:objectIdentifierType > URL </ premis:objectIdentifierType >

                  2. < premis:objectIdentifierValue > https://repositori.tecnocampus.cat/bitstream/20.500.12367/2164/1/TFG_TorrellBelzach_Memoria.pdf </ premis:objectIdentifierValue >

                  </ premis:objectIdentifier >

                2. < premis:objectCategory > File </ premis:objectCategory >

                3. < premis:objectCharacteristics >

                  1. < premis:fixity >

                    1. < premis:messageDigestAlgorithm > MD5 </ premis:messageDigestAlgorithm >

                    2. < premis:messageDigest > 0280fdc9e92dca6d2d12da3a2c3b47a6 </ premis:messageDigest >

                    </ premis:fixity >

                  2. < premis:size > 982842 </ premis:size >

                  3. < premis:format >

                    1. < premis:formatDesignation >

                      1. < premis:formatName > application/pdf </ premis:formatName >

                      </ premis:formatDesignation >

                    </ premis:format >

                  </ premis:objectCharacteristics >

                4. < premis:originalName > TFG_TorrellBelzach_Memoria.pdf </ premis:originalName >

                </ premis:object >

              </ premis:premis >

            </ xmlData >

          </ mdWrap >

        </ techMD >

      </ amdSec >

    4. < amdSec ID =" FO_20.500.12367_2164_2 " >

      1. < techMD ID =" TECH_O_20.500.12367_2164_2 " >

        1. < mdWrap MDTYPE =" PREMIS " >

          1. < xmlData schemaLocation =" http://www.loc.gov/standards/premis http://www.loc.gov/standards/premis/PREMIS-v1-0.xsd " >

            1. < premis:premis >

              1. < premis:object >

                1. < premis:objectIdentifier >

                  1. < premis:objectIdentifierType > URL </ premis:objectIdentifierType >

                  2. < premis:objectIdentifierValue > https://repositori.tecnocampus.cat/bitstream/20.500.12367/2164/2/TFG_TorrellBelzach_EstudiViabilitat.pdf </ premis:objectIdentifierValue >

                  </ premis:objectIdentifier >

                2. < premis:objectCategory > File </ premis:objectCategory >

                3. < premis:objectCharacteristics >

                  1. < premis:fixity >

                    1. < premis:messageDigestAlgorithm > MD5 </ premis:messageDigestAlgorithm >

                    2. < premis:messageDigest > b57c59543abecff84694fcf21116397b </ premis:messageDigest >

                    </ premis:fixity >

                  2. < premis:size > 216799 </ premis:size >

                  3. < premis:format >

                    1. < premis:formatDesignation >

                      1. < premis:formatName > application/pdf </ premis:formatName >

                      </ premis:formatDesignation >

                    </ premis:format >

                  </ premis:objectCharacteristics >

                4. < premis:originalName > TFG_TorrellBelzach_EstudiViabilitat.pdf </ premis:originalName >

                </ premis:object >

              </ premis:premis >

            </ xmlData >

          </ mdWrap >

        </ techMD >

      </ amdSec >

    5. < amdSec ID =" FT_20.500.12367_2164_4 " >

      1. < techMD ID =" TECH_T_20.500.12367_2164_4 " >

        1. < mdWrap MDTYPE =" PREMIS " >

          1. < xmlData schemaLocation =" http://www.loc.gov/standards/premis http://www.loc.gov/standards/premis/PREMIS-v1-0.xsd " >

            1. < premis:premis >

              1. < premis:object >

                1. < premis:objectIdentifier >

                  1. < premis:objectIdentifierType > URL </ premis:objectIdentifierType >

                  2. < premis:objectIdentifierValue > https://repositori.tecnocampus.cat/bitstream/20.500.12367/2164/4/TFG_TorrellBelzach_EstudiViabilitat.pdf.txt </ premis:objectIdentifierValue >

                  </ premis:objectIdentifier >

                2. < premis:objectCategory > File </ premis:objectCategory >

                3. < premis:objectCharacteristics >

                  1. < premis:fixity >

                    1. < premis:messageDigestAlgorithm > MD5 </ premis:messageDigestAlgorithm >

                    2. < premis:messageDigest > 6434912d73bdbf78a92a823a4cba03f5 </ premis:messageDigest >

                    </ premis:fixity >

                  2. < premis:size > 7755 </ premis:size >

                  3. < premis:format >

                    1. < premis:formatDesignation >

                      1. < premis:formatName > text/plain </ premis:formatName >

                      </ premis:formatDesignation >

                    </ premis:format >

                  </ premis:objectCharacteristics >

                4. < premis:originalName > TFG_TorrellBelzach_EstudiViabilitat.pdf.txt </ premis:originalName >

                </ premis:object >

              </ premis:premis >

            </ xmlData >

          </ mdWrap >

        </ techMD >

      </ amdSec >

    6. < amdSec ID =" FT_20.500.12367_2164_5 " >

      1. < techMD ID =" TECH_T_20.500.12367_2164_5 " >

        1. < mdWrap MDTYPE =" PREMIS " >

          1. < xmlData schemaLocation =" http://www.loc.gov/standards/premis http://www.loc.gov/standards/premis/PREMIS-v1-0.xsd " >

            1. < premis:premis >

              1. < premis:object >

                1. < premis:objectIdentifier >

                  1. < premis:objectIdentifierType > URL </ premis:objectIdentifierType >

                  2. < premis:objectIdentifierValue > https://repositori.tecnocampus.cat/bitstream/20.500.12367/2164/5/TFG_TorrellBelzach_Memoria.pdf.txt </ premis:objectIdentifierValue >

                  </ premis:objectIdentifier >

                2. < premis:objectCategory > File </ premis:objectCategory >

                3. < premis:objectCharacteristics >

                  1. < premis:fixity >

                    1. < premis:messageDigestAlgorithm > MD5 </ premis:messageDigestAlgorithm >

                    2. < premis:messageDigest > 7b7490d067c13677c4c6a8dc7a308007 </ premis:messageDigest >

                    </ premis:fixity >

                  2. < premis:size > 68699 </ premis:size >

                  3. < premis:format >

                    1. < premis:formatDesignation >

                      1. < premis:formatName > text/plain </ premis:formatName >

                      </ premis:formatDesignation >

                    </ premis:format >

                  </ premis:objectCharacteristics >

                4. < premis:originalName > TFG_TorrellBelzach_Memoria.pdf.txt </ premis:originalName >

                </ premis:object >

              </ premis:premis >

            </ xmlData >

          </ mdWrap >

        </ techMD >

      </ amdSec >

    7. < fileSec >

      1. < fileGrp USE =" ORIGINAL " >

        1. < file ADMID =" FO_20.500.12367_2164_1 " CHECKSUM =" 0280fdc9e92dca6d2d12da3a2c3b47a6 " CHECKSUMTYPE =" MD5 " GROUPID =" GROUP_BITSTREAM_20.500.12367_2164_1 " ID =" BITSTREAM_ORIGINAL_20.500.12367_2164_1 " MIMETYPE =" application/pdf " SEQ =" 1 " SIZE =" 982842 " >

          1. < FLocat LOCTYPE =" URL " href =" https://repositori.tecnocampus.cat/bitstream/20.500.12367/2164/1/TFG_TorrellBelzach_Memoria.pdf " type =" simple " />

          </ file >

        2. < file ADMID =" FO_20.500.12367_2164_2 " CHECKSUM =" b57c59543abecff84694fcf21116397b " CHECKSUMTYPE =" MD5 " GROUPID =" GROUP_BITSTREAM_20.500.12367_2164_2 " ID =" BITSTREAM_ORIGINAL_20.500.12367_2164_2 " MIMETYPE =" application/pdf " SEQ =" 2 " SIZE =" 216799 " >

          1. < FLocat LOCTYPE =" URL " href =" https://repositori.tecnocampus.cat/bitstream/20.500.12367/2164/2/TFG_TorrellBelzach_EstudiViabilitat.pdf " type =" simple " />

          </ file >

        </ fileGrp >

      2. < fileGrp USE =" TEXT " >

        1. < file ADMID =" FT_20.500.12367_2164_4 " CHECKSUM =" 6434912d73bdbf78a92a823a4cba03f5 " CHECKSUMTYPE =" MD5 " GROUPID =" GROUP_BITSTREAM_20.500.12367_2164_4 " ID =" BITSTREAM_TEXT_20.500.12367_2164_4 " MIMETYPE =" text/plain " SEQ =" 4 " SIZE =" 7755 " >

          1. < FLocat LOCTYPE =" URL " href =" https://repositori.tecnocampus.cat/bitstream/20.500.12367/2164/4/TFG_TorrellBelzach_EstudiViabilitat.pdf.txt " type =" simple " />

          </ file >

        2. < file ADMID =" FT_20.500.12367_2164_5 " CHECKSUM =" 7b7490d067c13677c4c6a8dc7a308007 " CHECKSUMTYPE =" MD5 " GROUPID =" GROUP_BITSTREAM_20.500.12367_2164_5 " ID =" BITSTREAM_TEXT_20.500.12367_2164_5 " MIMETYPE =" text/plain " SEQ =" 5 " SIZE =" 68699 " >

          1. < FLocat LOCTYPE =" URL " href =" https://repositori.tecnocampus.cat/bitstream/20.500.12367/2164/5/TFG_TorrellBelzach_Memoria.pdf.txt " type =" simple " />

          </ file >

        </ fileGrp >

      </ fileSec >

    8. < structMap LABEL =" DSpace Object " TYPE =" LOGICAL " >

      1. < div ADMID =" DMD_20.500.12367_2164 " TYPE =" DSpace Object Contents " >

        1. < div TYPE =" DSpace BITSTREAM " >

          1. < fptr FILEID =" BITSTREAM_ORIGINAL_20.500.12367_2164_1 " />

          </ div >

        2. < div TYPE =" DSpace BITSTREAM " >

          1. < fptr FILEID =" BITSTREAM_ORIGINAL_20.500.12367_2164_2 " />

          </ div >

        </ div >

      </ structMap >

    </ mets >

mods

Descargar XML

    <?xml version="1.0" encoding="UTF-8" ?>

  1. < mods:mods schemaLocation =" http://www.loc.gov/mods/v3 http://www.loc.gov/standards/mods/v3/mods-3-1.xsd " >

    1. < mods:name >

      1. < mods:namePart > Torrell Belzach, Robert </ mods:namePart >

      </ mods:name >

    2. < mods:extension >

      1. < mods:dateAvailable encoding =" iso8601 " > 2023-01-31T13:52:11Z </ mods:dateAvailable >

      </ mods:extension >

    3. < mods:extension >

      1. < mods:dateAccessioned encoding =" iso8601 " > 2023-01-31T13:52:11Z </ mods:dateAccessioned >

      </ mods:extension >

    4. < mods:originInfo >

      1. < mods:dateIssued encoding =" iso8601 " > 2022 </ mods:dateIssued >

      </ mods:originInfo >

    5. < mods:identifier type =" uri " > http://hdl.handle.net/20.500.12367/2164 </ mods:identifier >

    6. < mods:abstract > Aplicar efectivament a l´industria de la manufacturació el manteniment predictiu, es a dir, poder esbrinar quan, on i com tindrem fallades en un sistema de la cadena de producció pot resultar molt beneficiós. Per a aplicar el manteniment predictiu, es desenvoluparan models d’intel·ligència artificial. Es posaran a prova aquests diversos models estadístics, d’aprenentatge automàtic i d’aprenentatge profund per a comprendre quines tècniques ens ofereixen els millors resultats davant aquest problema. </ mods:abstract >

    7. < mods:language >

      1. < mods:languageTerm > spa </ mods:languageTerm >

      </ mods:language >

    8. < mods:accessCondition type =" useAndReproduction " > http://creativecommons.org/licenses/by/4.0/ </ mods:accessCondition >

    9. < mods:accessCondition type =" useAndReproduction " > info:eu-repo/semantics/openAccess </ mods:accessCondition >

    10. < mods:accessCondition type =" useAndReproduction " > Attribution 4.0 International </ mods:accessCondition >

    11. < mods:titleInfo >

      1. < mods:title > Abnormal Behavior Identification through Deep Learning: TensorFlow </ mods:title >

      </ mods:titleInfo >

    12. < mods:genre > info:eu-repo/semantics/bachelorThesis </ mods:genre >

    </ mods:mods >

oaire

Descargar XML

    <?xml version="1.0" encoding="UTF-8" ?>

  1. < oaire:record schemaLocation =" http://namespaceopenaire.eu/schema/oaire/ " >

    1. < dc:title > Abnormal Behavior Identification through Deep Learning: TensorFlow </ dc:title >

    2. < datacite:creator >

      1. < datacite:creatorName > Torrell Belzach, Robert </ datacite:creatorName >

      </ datacite:creator >

    3. < datacite:contributor > TecnoCampus. Escola Superior Politècnica (ESUPT) </ datacite:contributor >

    4. < datacite:contributor > Font Aragonès, Xavier </ datacite:contributor >

    5. < dc:subject > Indústria manufacturera, manteniment predictiu, intel·ligència artificial </ dc:subject >

    6. < dc:description > Treball de fi de grau - Curs 2021-2022 </ dc:description >

    7. < dc:description > Aplicar efectivament a l´industria de la manufacturació el manteniment predictiu, es a dir, poder esbrinar quan, on i com tindrem fallades en un sistema de la cadena de producció pot resultar molt beneficiós. Per a aplicar el manteniment predictiu, es desenvoluparan models d’intel·ligència artificial. Es posaran a prova aquests diversos models estadístics, d’aprenentatge automàtic i d’aprenentatge profund per a comprendre quines tècniques ens ofereixen els millors resultats davant aquest problema. </ dc:description >

    8. < dc:date > 2023-01-31T13:52:11Z </ dc:date >

    9. < dc:date > 2023-01-31T13:52:11Z </ dc:date >

    10. < dc:date > 2022 </ dc:date >

    11. < dc:type > info:eu-repo/semantics/bachelorThesis </ dc:type >

    12. < datacite:alternateIdentifier > http://hdl.handle.net/20.500.12367/2164 </ datacite:alternateIdentifier >

    13. < dc:language > spa </ dc:language >

    14. < dc:rights > Attribution 4.0 International </ dc:rights >

    15. < dc:rights > http://creativecommons.org/licenses/by/4.0/ </ dc:rights >

    16. < dc:rights > info:eu-repo/semantics/openAccess </ dc:rights >

    17. < dc:format > 49, 7 p. </ dc:format >

    18. < dc:format > application/pdf </ dc:format >

    19. < dc:format > application/pdf </ dc:format >

    20. < oaire:file > https://repositori.tecnocampus.cat/bitstream/20.500.12367/2164/1/TFG_TorrellBelzach_Memoria.pdf </ oaire:file >

    </ oaire:record >

qdc

Descargar XML

    <?xml version="1.0" encoding="UTF-8" ?>

  1. < qdc:qualifieddc schemaLocation =" http://purl.org/dc/elements/1.1/ http://dublincore.org/schemas/xmls/qdc/2006/01/06/dc.xsd http://purl.org/dc/terms/ http://dublincore.org/schemas/xmls/qdc/2006/01/06/dcterms.xsd http://dspace.org/qualifieddc/ http://www.ukoln.ac.uk/metadata/dcmi/xmlschema/qualifieddc.xsd " >

    1. < dc:title > Abnormal Behavior Identification through Deep Learning: TensorFlow </ dc:title >

    2. < dc:creator > Torrell Belzach, Robert </ dc:creator >

    3. < dc:contributor > TecnoCampus. Escola Superior Politècnica (ESUPT) </ dc:contributor >

    4. < dc:contributor > Font Aragonès, Xavier </ dc:contributor >

    5. < dcterms:abstract > Aplicar efectivament a l´industria de la manufacturació el manteniment predictiu, es a dir, poder esbrinar quan, on i com tindrem fallades en un sistema de la cadena de producció pot resultar molt beneficiós. Per a aplicar el manteniment predictiu, es desenvoluparan models d’intel·ligència artificial. Es posaran a prova aquests diversos models estadístics, d’aprenentatge automàtic i d’aprenentatge profund per a comprendre quines tècniques ens ofereixen els millors resultats davant aquest problema. </ dcterms:abstract >

    6. < dcterms:dateAccepted > 2023-01-31T13:52:11Z </ dcterms:dateAccepted >

    7. < dcterms:available > 2023-01-31T13:52:11Z </ dcterms:available >

    8. < dcterms:created > 2023-01-31T13:52:11Z </ dcterms:created >

    9. < dcterms:issued > 2022 </ dcterms:issued >

    10. < dc:type > info:eu-repo/semantics/bachelorThesis </ dc:type >

    11. < dc:identifier > http://hdl.handle.net/20.500.12367/2164 </ dc:identifier >

    12. < dc:language > spa </ dc:language >

    13. < dc:rights > http://creativecommons.org/licenses/by/4.0/ </ dc:rights >

    14. < dc:rights > info:eu-repo/semantics/openAccess </ dc:rights >

    15. < dc:rights > Attribution 4.0 International </ dc:rights >

    </ qdc:qualifieddc >

rdf

Descargar XML

    <?xml version="1.0" encoding="UTF-8" ?>

  1. < rdf:RDF schemaLocation =" http://www.openarchives.org/OAI/2.0/rdf/ http://www.openarchives.org/OAI/2.0/rdf.xsd " >

    1. < ow:Publication about =" oai:repositori.tecnocampus.cat:20.500.12367/2164 " >

      1. < dc:title > Abnormal Behavior Identification through Deep Learning: TensorFlow </ dc:title >

      2. < dc:creator > Torrell Belzach, Robert </ dc:creator >

      3. < dc:contributor > TecnoCampus. Escola Superior Politècnica (ESUPT) </ dc:contributor >

      4. < dc:contributor > Font Aragonès, Xavier </ dc:contributor >

      5. < dc:description > Treball de fi de grau - Curs 2021-2022 </ dc:description >

      6. < dc:description > Aplicar efectivament a l´industria de la manufacturació el manteniment predictiu, es a dir, poder esbrinar quan, on i com tindrem fallades en un sistema de la cadena de producció pot resultar molt beneficiós. Per a aplicar el manteniment predictiu, es desenvoluparan models d’intel·ligència artificial. Es posaran a prova aquests diversos models estadístics, d’aprenentatge automàtic i d’aprenentatge profund per a comprendre quines tècniques ens ofereixen els millors resultats davant aquest problema. </ dc:description >

      7. < dc:date > 2023-01-31T13:52:11Z </ dc:date >

      8. < dc:date > 2023-01-31T13:52:11Z </ dc:date >

      9. < dc:date > 2022 </ dc:date >

      10. < dc:type > info:eu-repo/semantics/bachelorThesis </ dc:type >

      11. < dc:identifier > http://hdl.handle.net/20.500.12367/2164 </ dc:identifier >

      12. < dc:language > spa </ dc:language >

      13. < dc:rights > http://creativecommons.org/licenses/by/4.0/ </ dc:rights >

      14. < dc:rights > info:eu-repo/semantics/openAccess </ dc:rights >

      15. < dc:rights > Attribution 4.0 International </ dc:rights >

      </ ow:Publication >

    </ rdf:RDF >

xoai

Descargar XML

    <?xml version="1.0" encoding="UTF-8" ?>

  1. < metadata schemaLocation =" http://www.lyncode.com/xoai http://www.lyncode.com/xsd/xoai.xsd " >

    1. < element name =" dc " >

      1. < element name =" contributor " >

        1. < element name =" author " >

          1. < element name =" none " >

            1. < field name =" value " > Torrell Belzach, Robert </ field >

            2. < field name =" authority " > 010ef51f-844d-4a1b-b529-91c7641161e9 </ field >

            3. < field name =" confidence " > -1 </ field >

            </ element >

          </ element >

        2. < element name =" other " >

          1. < element name =" ca " >

            1. < field name =" value " > TecnoCampus. Escola Superior Politècnica (ESUPT) </ field >

            </ element >

          </ element >

        3. < element name =" tutor " >

          1. < element name =" none " >

            1. < field name =" value " > Font Aragonès, Xavier </ field >

            2. < field name =" authority " > 78e5ba59-f06f-47e0-9154-cf897af416ee </ field >

            3. < field name =" confidence " > -1 </ field >

            </ element >

          </ element >

        </ element >

      2. < element name =" date " >

        1. < element name =" accessioned " >

          1. < element name =" none " >

            1. < field name =" value " > 2023-01-31T13:52:11Z </ field >

            </ element >

          </ element >

        2. < element name =" available " >

          1. < element name =" none " >

            1. < field name =" value " > 2023-01-31T13:52:11Z </ field >

            </ element >

          </ element >

        3. < element name =" issued " >

          1. < element name =" none " >

            1. < field name =" value " > 2022 </ field >

            </ element >

          </ element >

        </ element >

      3. < element name =" identifier " >

        1. < element name =" uri " >

          1. < element name =" none " >

            1. < field name =" value " > http://hdl.handle.net/20.500.12367/2164 </ field >

            </ element >

          </ element >

        </ element >

      4. < element name =" description " >

        1. < element name =" ca " >

          1. < field name =" value " > Treball de fi de grau - Curs 2021-2022 </ field >

          </ element >

        2. < element name =" abstract " >

          1. < element name =" ca " >

            1. < field name =" value " > Aplicar efectivament a l´industria de la manufacturació el manteniment predictiu, es a dir, poder esbrinar quan, on i com tindrem fallades en un sistema de la cadena de producció pot resultar molt beneficiós. Per a aplicar el manteniment predictiu, es desenvoluparan models d’intel·ligència artificial. Es posaran a prova aquests diversos models estadístics, d’aprenentatge automàtic i d’aprenentatge profund per a comprendre quines tècniques ens ofereixen els millors resultats davant aquest problema. </ field >

            </ element >

          </ element >

        </ element >

      5. < element name =" format " >

        1. < element name =" extent " >

          1. < element name =" ca " >

            1. < field name =" value " > 49, 7 p. </ field >

            </ element >

          </ element >

        </ element >

      6. < element name =" language " >

        1. < element name =" iso " >

          1. < element name =" ca " >

            1. < field name =" value " > spa </ field >

            </ element >

          </ element >

        </ element >

      7. < element name =" rights " >

        1. < element name =" * " >

          1. < field name =" value " > Attribution 4.0 International </ field >

          </ element >

        2. < element name =" uri " >

          1. < element name =" * " >

            1. < field name =" value " > http://creativecommons.org/licenses/by/4.0/ </ field >

            </ element >

          </ element >

        3. < element name =" accessLevel " >

          1. < element name =" none " >

            1. < field name =" value " > info:eu-repo/semantics/openAccess </ field >

            </ element >

          </ element >

        </ element >

      8. < element name =" subject " >

        1. < element name =" other " >

          1. < element name =" ca " >

            1. < field name =" value " > Indústria manufacturera, manteniment predictiu, intel·ligència artificial </ field >

            </ element >

          </ element >

        </ element >

      9. < element name =" title " >

        1. < element name =" ca " >

          1. < field name =" value " > Abnormal Behavior Identification through Deep Learning: TensorFlow </ field >

          </ element >

        </ element >

      10. < element name =" type " >

        1. < element name =" ca " >

          1. < field name =" value " > info:eu-repo/semantics/bachelorThesis </ field >

          </ element >

        </ element >

      11. < element name =" embargo " >

        1. < element name =" terms " >

          1. < element name =" ca " >

            1. < field name =" value " > cap </ field >

            </ element >

          </ element >

        </ element >

      </ element >

    2. < element name =" bundles " >

      1. < element name =" bundle " >

        1. < field name =" name " > ORIGINAL </ field >

        2. < element name =" bitstreams " >

          1. < element name =" bitstream " >

            1. < field name =" name " > TFG_TorrellBelzach_Memoria.pdf </ field >

            2. < field name =" originalName " > TFG_TorrellBelzach_Memoria.pdf </ field >

            3. < field name =" description " />
            4. < field name =" format " > application/pdf </ field >

            5. < field name =" size " > 982842 </ field >

            6. < field name =" url " > https://repositori.tecnocampus.cat/bitstream/20.500.12367/2164/1/TFG_TorrellBelzach_Memoria.pdf </ field >

            7. < field name =" checksum " > 0280fdc9e92dca6d2d12da3a2c3b47a6 </ field >

            8. < field name =" checksumAlgorithm " > MD5 </ field >

            9. < field name =" sid " > 1 </ field >

            10. < field name =" drm " > open access </ field >

            </ element >

          2. < element name =" bitstream " >

            1. < field name =" name " > TFG_TorrellBelzach_EstudiViabilitat.pdf </ field >

            2. < field name =" originalName " > TFG_TorrellBelzach_EstudiViabilitat.pdf </ field >

            3. < field name =" description " />
            4. < field name =" format " > application/pdf </ field >

            5. < field name =" size " > 216799 </ field >

            6. < field name =" url " > https://repositori.tecnocampus.cat/bitstream/20.500.12367/2164/2/TFG_TorrellBelzach_EstudiViabilitat.pdf </ field >

            7. < field name =" checksum " > b57c59543abecff84694fcf21116397b </ field >

            8. < field name =" checksumAlgorithm " > MD5 </ field >

            9. < field name =" sid " > 2 </ field >

            10. < field name =" drm " > open access </ field >

            </ element >

          </ element >

        </ element >

      2. < element name =" bundle " >

        1. < field name =" name " > CC-LICENSE </ field >

        2. < element name =" bitstreams " >

          1. < element name =" bitstream " >

            1. < field name =" name " > license_rdf </ field >

            2. < field name =" originalName " > license_rdf </ field >

            3. < field name =" format " > application/rdf+xml; charset=utf-8 </ field >

            4. < field name =" size " > 908 </ field >

            5. < field name =" url " > https://repositori.tecnocampus.cat/bitstream/20.500.12367/2164/3/license_rdf </ field >

            6. < field name =" checksum " > 0175ea4a2d4caec4bbcc37e300941108 </ field >

            7. < field name =" checksumAlgorithm " > MD5 </ field >

            8. < field name =" sid " > 3 </ field >

            9. < field name =" drm " > open access </ field >

            </ element >

          </ element >

        </ element >

      3. < element name =" bundle " >

        1. < field name =" name " > TEXT </ field >

        2. < element name =" bitstreams " >

          1. < element name =" bitstream " >

            1. < field name =" name " > TFG_TorrellBelzach_EstudiViabilitat.pdf.txt </ field >

            2. < field name =" originalName " > TFG_TorrellBelzach_EstudiViabilitat.pdf.txt </ field >

            3. < field name =" description " > Extracted text </ field >

            4. < field name =" format " > text/plain </ field >

            5. < field name =" size " > 7755 </ field >

            6. < field name =" url " > https://repositori.tecnocampus.cat/bitstream/20.500.12367/2164/4/TFG_TorrellBelzach_EstudiViabilitat.pdf.txt </ field >

            7. < field name =" checksum " > 6434912d73bdbf78a92a823a4cba03f5 </ field >

            8. < field name =" checksumAlgorithm " > MD5 </ field >

            9. < field name =" sid " > 4 </ field >

            10. < field name =" drm " > open access </ field >

            </ element >

          2. < element name =" bitstream " >

            1. < field name =" name " > TFG_TorrellBelzach_Memoria.pdf.txt </ field >

            2. < field name =" originalName " > TFG_TorrellBelzach_Memoria.pdf.txt </ field >

            3. < field name =" description " > Extracted text </ field >

            4. < field name =" format " > text/plain </ field >

            5. < field name =" size " > 68699 </ field >

            6. < field name =" url " > https://repositori.tecnocampus.cat/bitstream/20.500.12367/2164/5/TFG_TorrellBelzach_Memoria.pdf.txt </ field >

            7. < field name =" checksum " > 7b7490d067c13677c4c6a8dc7a308007 </ field >

            8. < field name =" checksumAlgorithm " > MD5 </ field >

            9. < field name =" sid " > 5 </ field >

            10. < field name =" drm " > open access </ field >

            </ element >

          </ element >

        </ element >

      </ element >

    3. < element name =" others " >

      1. < field name =" handle " > 20.500.12367/2164 </ field >

      2. < field name =" identifier " > oai:repositori.tecnocampus.cat:20.500.12367/2164 </ field >

      3. < field name =" lastModifyDate " > 2023-06-27 01:45:37.808 </ field >

      4. < field name =" drm " > open access </ field >

      </ element >

    4. < element name =" repository " >

      1. < field name =" name " > TECNOCAMPUS </ field >

      2. < field name =" mail " > pir@csuc.cat </ field >

      </ element >

    </ metadata >

Biblioteca de Catalunya Carrer de l'Hospital, 56. 08001 Barcelona Email: catalonica@bnc.cat Tlf.: +34 932 702 300
  • Logotipo de Biblioteca de Catalunya
  • Logotipo de la Generalitat de Catalunya
  • Nota técnica
  • Aviso legal
  • Repositorio OAI