Virtual organization with fusion knowledge in odor classification
E-nose systems are becoming increasingly important instruments across all industries, especially the fields of food and beverages and biomedicine. Given the inaccurate, unsafe and unreliable dependency on the human nose to detect smells that are highly risky and hazardous to human health, e-nose sys...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Villarrubia, Gabriel [verfasserIn] |
|---|
| Format: |
E-Artikel |
|---|---|
| Sprache: |
Englisch |
| Erschienen: |
2017transfer abstract |
|---|
| Schlagwörter: |
|---|
| Umfang: |
8 |
|---|
| Übergeordnetes Werk: |
Enthalten in: The TORC1 signaling pathway regulates respiration-induced mitophagy in yeast - Liu, Yang ELSEVIER, 2018, an international journal, Amsterdam |
|---|---|
| Übergeordnetes Werk: |
volume:231 ; year:2017 ; day:29 ; month:03 ; pages:3-10 ; extent:8 |
| Links: |
|---|
| DOI / URN: |
10.1016/j.neucom.2016.05.106 |
|---|
| Katalog-ID: |
ELV030576520 |
|---|
| LEADER | 01000caa a22002652 4500 | ||
|---|---|---|---|
| 001 | ELV030576520 | ||
| 003 | DE-627 | ||
| 005 | 20230625182042.0 | ||
| 007 | cr uuu---uuuuu | ||
| 008 | 180603s2017 xx |||||o 00| ||eng c | ||
| 024 | 7 | |a 10.1016/j.neucom.2016.05.106 |2 doi | |
| 028 | 5 | 2 | |a GBVA2017014000007.pica |
| 035 | |a (DE-627)ELV030576520 | ||
| 035 | |a (ELSEVIER)S0925-2312(16)31162-6 | ||
| 040 | |a DE-627 |b ger |c DE-627 |e rakwb | ||
| 041 | |a eng | ||
| 082 | 0 | |a 610 | |
| 082 | 0 | 4 | |a 610 |q DE-600 |
| 082 | 0 | 4 | |a 570 |q VZ |
| 084 | |a BIODIV |q DE-30 |2 fid | ||
| 084 | |a 35.70 |2 bkl | ||
| 084 | |a 42.12 |2 bkl | ||
| 100 | 1 | |a Villarrubia, Gabriel |e verfasserin |4 aut | |
| 245 | 1 | 0 | |a Virtual organization with fusion knowledge in odor classification |
| 264 | 1 | |c 2017transfer abstract | |
| 300 | |a 8 | ||
| 336 | |a nicht spezifiziert |b zzz |2 rdacontent | ||
| 337 | |a nicht spezifiziert |b z |2 rdamedia | ||
| 338 | |a nicht spezifiziert |b zu |2 rdacarrier | ||
| 520 | |a E-nose systems are becoming increasingly important instruments across all industries, especially the fields of food and beverages and biomedicine. Given the inaccurate, unsafe and unreliable dependency on the human nose to detect smells that are highly risky and hazardous to human health, e-nose systems offer a tremendous advantage. E-noses are convenient, highly efficient and can be used in real life to detect various types of odors. This paper presents a virtual organization of agents that integrates different classification techniques and neural networks to perform information fusion from parameters retrieved by the E-nose. The integral brain in e-noses is the data processing system, which classifies odors that have been detected by the detection part of its system. The system mimics how a human brain classifies odors. | ||
| 520 | |a E-nose systems are becoming increasingly important instruments across all industries, especially the fields of food and beverages and biomedicine. Given the inaccurate, unsafe and unreliable dependency on the human nose to detect smells that are highly risky and hazardous to human health, e-nose systems offer a tremendous advantage. E-noses are convenient, highly efficient and can be used in real life to detect various types of odors. This paper presents a virtual organization of agents that integrates different classification techniques and neural networks to perform information fusion from parameters retrieved by the E-nose. The integral brain in e-noses is the data processing system, which classifies odors that have been detected by the detection part of its system. The system mimics how a human brain classifies odors. | ||
| 650 | 7 | |a Classifiers |2 Elsevier | |
| 650 | 7 | |a Neural networks |2 Elsevier | |
| 650 | 7 | |a E-nose |2 Elsevier | |
| 650 | 7 | |a Virtual organization |2 Elsevier | |
| 700 | 1 | |a De Paz, Juan F. |4 oth | |
| 700 | 1 | |a Pelki, Dechen |4 oth | |
| 700 | 1 | |a de la Prieta, Fernando |4 oth | |
| 700 | 1 | |a Omatu, Sigeru |4 oth | |
| 773 | 0 | 8 | |i Enthalten in |n Elsevier |a Liu, Yang ELSEVIER |t The TORC1 signaling pathway regulates respiration-induced mitophagy in yeast |d 2018 |d an international journal |g Amsterdam |w (DE-627)ELV002603926 |
| 773 | 1 | 8 | |g volume:231 |g year:2017 |g day:29 |g month:03 |g pages:3-10 |g extent:8 |
| 856 | 4 | 0 | |u https://doi.org/10.1016/j.neucom.2016.05.106 |3 Volltext |
| 912 | |a GBV_USEFLAG_U | ||
| 912 | |a GBV_ELV | ||
| 912 | |a SYSFLAG_U | ||
| 912 | |a FID-BIODIV | ||
| 912 | |a SSG-OLC-PHA | ||
| 936 | b | k | |a 35.70 |j Biochemie: Allgemeines |q VZ |
| 936 | b | k | |a 42.12 |j Biophysik |q VZ |
| 951 | |a AR | ||
| 952 | |d 231 |j 2017 |b 29 |c 0329 |h 3-10 |g 8 | ||
| 953 | |2 045F |a 610 | ||
| author_variant |
g v gv |
|---|---|
| matchkey_str |
villarrubiagabrieldepazjuanfpelkidechend:2017----:itaognztowtfsokoldend |
| hierarchy_sort_str |
2017transfer abstract |
| bklnumber |
35.70 42.12 |
| publishDate |
2017 |
| allfields |
10.1016/j.neucom.2016.05.106 doi GBVA2017014000007.pica (DE-627)ELV030576520 (ELSEVIER)S0925-2312(16)31162-6 DE-627 ger DE-627 rakwb eng 610 610 DE-600 570 VZ BIODIV DE-30 fid 35.70 bkl 42.12 bkl Villarrubia, Gabriel verfasserin aut Virtual organization with fusion knowledge in odor classification 2017transfer abstract 8 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier E-nose systems are becoming increasingly important instruments across all industries, especially the fields of food and beverages and biomedicine. Given the inaccurate, unsafe and unreliable dependency on the human nose to detect smells that are highly risky and hazardous to human health, e-nose systems offer a tremendous advantage. E-noses are convenient, highly efficient and can be used in real life to detect various types of odors. This paper presents a virtual organization of agents that integrates different classification techniques and neural networks to perform information fusion from parameters retrieved by the E-nose. The integral brain in e-noses is the data processing system, which classifies odors that have been detected by the detection part of its system. The system mimics how a human brain classifies odors. E-nose systems are becoming increasingly important instruments across all industries, especially the fields of food and beverages and biomedicine. Given the inaccurate, unsafe and unreliable dependency on the human nose to detect smells that are highly risky and hazardous to human health, e-nose systems offer a tremendous advantage. E-noses are convenient, highly efficient and can be used in real life to detect various types of odors. This paper presents a virtual organization of agents that integrates different classification techniques and neural networks to perform information fusion from parameters retrieved by the E-nose. The integral brain in e-noses is the data processing system, which classifies odors that have been detected by the detection part of its system. The system mimics how a human brain classifies odors. Classifiers Elsevier Neural networks Elsevier E-nose Elsevier Virtual organization Elsevier De Paz, Juan F. oth Pelki, Dechen oth de la Prieta, Fernando oth Omatu, Sigeru oth Enthalten in Elsevier Liu, Yang ELSEVIER The TORC1 signaling pathway regulates respiration-induced mitophagy in yeast 2018 an international journal Amsterdam (DE-627)ELV002603926 volume:231 year:2017 day:29 month:03 pages:3-10 extent:8 https://doi.org/10.1016/j.neucom.2016.05.106 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U FID-BIODIV SSG-OLC-PHA 35.70 Biochemie: Allgemeines VZ 42.12 Biophysik VZ AR 231 2017 29 0329 3-10 8 045F 610 |
| spelling |
10.1016/j.neucom.2016.05.106 doi GBVA2017014000007.pica (DE-627)ELV030576520 (ELSEVIER)S0925-2312(16)31162-6 DE-627 ger DE-627 rakwb eng 610 610 DE-600 570 VZ BIODIV DE-30 fid 35.70 bkl 42.12 bkl Villarrubia, Gabriel verfasserin aut Virtual organization with fusion knowledge in odor classification 2017transfer abstract 8 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier E-nose systems are becoming increasingly important instruments across all industries, especially the fields of food and beverages and biomedicine. Given the inaccurate, unsafe and unreliable dependency on the human nose to detect smells that are highly risky and hazardous to human health, e-nose systems offer a tremendous advantage. E-noses are convenient, highly efficient and can be used in real life to detect various types of odors. This paper presents a virtual organization of agents that integrates different classification techniques and neural networks to perform information fusion from parameters retrieved by the E-nose. The integral brain in e-noses is the data processing system, which classifies odors that have been detected by the detection part of its system. The system mimics how a human brain classifies odors. E-nose systems are becoming increasingly important instruments across all industries, especially the fields of food and beverages and biomedicine. Given the inaccurate, unsafe and unreliable dependency on the human nose to detect smells that are highly risky and hazardous to human health, e-nose systems offer a tremendous advantage. E-noses are convenient, highly efficient and can be used in real life to detect various types of odors. This paper presents a virtual organization of agents that integrates different classification techniques and neural networks to perform information fusion from parameters retrieved by the E-nose. The integral brain in e-noses is the data processing system, which classifies odors that have been detected by the detection part of its system. The system mimics how a human brain classifies odors. Classifiers Elsevier Neural networks Elsevier E-nose Elsevier Virtual organization Elsevier De Paz, Juan F. oth Pelki, Dechen oth de la Prieta, Fernando oth Omatu, Sigeru oth Enthalten in Elsevier Liu, Yang ELSEVIER The TORC1 signaling pathway regulates respiration-induced mitophagy in yeast 2018 an international journal Amsterdam (DE-627)ELV002603926 volume:231 year:2017 day:29 month:03 pages:3-10 extent:8 https://doi.org/10.1016/j.neucom.2016.05.106 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U FID-BIODIV SSG-OLC-PHA 35.70 Biochemie: Allgemeines VZ 42.12 Biophysik VZ AR 231 2017 29 0329 3-10 8 045F 610 |
| allfields_unstemmed |
10.1016/j.neucom.2016.05.106 doi GBVA2017014000007.pica (DE-627)ELV030576520 (ELSEVIER)S0925-2312(16)31162-6 DE-627 ger DE-627 rakwb eng 610 610 DE-600 570 VZ BIODIV DE-30 fid 35.70 bkl 42.12 bkl Villarrubia, Gabriel verfasserin aut Virtual organization with fusion knowledge in odor classification 2017transfer abstract 8 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier E-nose systems are becoming increasingly important instruments across all industries, especially the fields of food and beverages and biomedicine. Given the inaccurate, unsafe and unreliable dependency on the human nose to detect smells that are highly risky and hazardous to human health, e-nose systems offer a tremendous advantage. E-noses are convenient, highly efficient and can be used in real life to detect various types of odors. This paper presents a virtual organization of agents that integrates different classification techniques and neural networks to perform information fusion from parameters retrieved by the E-nose. The integral brain in e-noses is the data processing system, which classifies odors that have been detected by the detection part of its system. The system mimics how a human brain classifies odors. E-nose systems are becoming increasingly important instruments across all industries, especially the fields of food and beverages and biomedicine. Given the inaccurate, unsafe and unreliable dependency on the human nose to detect smells that are highly risky and hazardous to human health, e-nose systems offer a tremendous advantage. E-noses are convenient, highly efficient and can be used in real life to detect various types of odors. This paper presents a virtual organization of agents that integrates different classification techniques and neural networks to perform information fusion from parameters retrieved by the E-nose. The integral brain in e-noses is the data processing system, which classifies odors that have been detected by the detection part of its system. The system mimics how a human brain classifies odors. Classifiers Elsevier Neural networks Elsevier E-nose Elsevier Virtual organization Elsevier De Paz, Juan F. oth Pelki, Dechen oth de la Prieta, Fernando oth Omatu, Sigeru oth Enthalten in Elsevier Liu, Yang ELSEVIER The TORC1 signaling pathway regulates respiration-induced mitophagy in yeast 2018 an international journal Amsterdam (DE-627)ELV002603926 volume:231 year:2017 day:29 month:03 pages:3-10 extent:8 https://doi.org/10.1016/j.neucom.2016.05.106 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U FID-BIODIV SSG-OLC-PHA 35.70 Biochemie: Allgemeines VZ 42.12 Biophysik VZ AR 231 2017 29 0329 3-10 8 045F 610 |
| allfieldsGer |
10.1016/j.neucom.2016.05.106 doi GBVA2017014000007.pica (DE-627)ELV030576520 (ELSEVIER)S0925-2312(16)31162-6 DE-627 ger DE-627 rakwb eng 610 610 DE-600 570 VZ BIODIV DE-30 fid 35.70 bkl 42.12 bkl Villarrubia, Gabriel verfasserin aut Virtual organization with fusion knowledge in odor classification 2017transfer abstract 8 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier E-nose systems are becoming increasingly important instruments across all industries, especially the fields of food and beverages and biomedicine. Given the inaccurate, unsafe and unreliable dependency on the human nose to detect smells that are highly risky and hazardous to human health, e-nose systems offer a tremendous advantage. E-noses are convenient, highly efficient and can be used in real life to detect various types of odors. This paper presents a virtual organization of agents that integrates different classification techniques and neural networks to perform information fusion from parameters retrieved by the E-nose. The integral brain in e-noses is the data processing system, which classifies odors that have been detected by the detection part of its system. The system mimics how a human brain classifies odors. E-nose systems are becoming increasingly important instruments across all industries, especially the fields of food and beverages and biomedicine. Given the inaccurate, unsafe and unreliable dependency on the human nose to detect smells that are highly risky and hazardous to human health, e-nose systems offer a tremendous advantage. E-noses are convenient, highly efficient and can be used in real life to detect various types of odors. This paper presents a virtual organization of agents that integrates different classification techniques and neural networks to perform information fusion from parameters retrieved by the E-nose. The integral brain in e-noses is the data processing system, which classifies odors that have been detected by the detection part of its system. The system mimics how a human brain classifies odors. Classifiers Elsevier Neural networks Elsevier E-nose Elsevier Virtual organization Elsevier De Paz, Juan F. oth Pelki, Dechen oth de la Prieta, Fernando oth Omatu, Sigeru oth Enthalten in Elsevier Liu, Yang ELSEVIER The TORC1 signaling pathway regulates respiration-induced mitophagy in yeast 2018 an international journal Amsterdam (DE-627)ELV002603926 volume:231 year:2017 day:29 month:03 pages:3-10 extent:8 https://doi.org/10.1016/j.neucom.2016.05.106 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U FID-BIODIV SSG-OLC-PHA 35.70 Biochemie: Allgemeines VZ 42.12 Biophysik VZ AR 231 2017 29 0329 3-10 8 045F 610 |
| allfieldsSound |
10.1016/j.neucom.2016.05.106 doi GBVA2017014000007.pica (DE-627)ELV030576520 (ELSEVIER)S0925-2312(16)31162-6 DE-627 ger DE-627 rakwb eng 610 610 DE-600 570 VZ BIODIV DE-30 fid 35.70 bkl 42.12 bkl Villarrubia, Gabriel verfasserin aut Virtual organization with fusion knowledge in odor classification 2017transfer abstract 8 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier E-nose systems are becoming increasingly important instruments across all industries, especially the fields of food and beverages and biomedicine. Given the inaccurate, unsafe and unreliable dependency on the human nose to detect smells that are highly risky and hazardous to human health, e-nose systems offer a tremendous advantage. E-noses are convenient, highly efficient and can be used in real life to detect various types of odors. This paper presents a virtual organization of agents that integrates different classification techniques and neural networks to perform information fusion from parameters retrieved by the E-nose. The integral brain in e-noses is the data processing system, which classifies odors that have been detected by the detection part of its system. The system mimics how a human brain classifies odors. E-nose systems are becoming increasingly important instruments across all industries, especially the fields of food and beverages and biomedicine. Given the inaccurate, unsafe and unreliable dependency on the human nose to detect smells that are highly risky and hazardous to human health, e-nose systems offer a tremendous advantage. E-noses are convenient, highly efficient and can be used in real life to detect various types of odors. This paper presents a virtual organization of agents that integrates different classification techniques and neural networks to perform information fusion from parameters retrieved by the E-nose. The integral brain in e-noses is the data processing system, which classifies odors that have been detected by the detection part of its system. The system mimics how a human brain classifies odors. Classifiers Elsevier Neural networks Elsevier E-nose Elsevier Virtual organization Elsevier De Paz, Juan F. oth Pelki, Dechen oth de la Prieta, Fernando oth Omatu, Sigeru oth Enthalten in Elsevier Liu, Yang ELSEVIER The TORC1 signaling pathway regulates respiration-induced mitophagy in yeast 2018 an international journal Amsterdam (DE-627)ELV002603926 volume:231 year:2017 day:29 month:03 pages:3-10 extent:8 https://doi.org/10.1016/j.neucom.2016.05.106 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U FID-BIODIV SSG-OLC-PHA 35.70 Biochemie: Allgemeines VZ 42.12 Biophysik VZ AR 231 2017 29 0329 3-10 8 045F 610 |
| language |
English |
| source |
Enthalten in The TORC1 signaling pathway regulates respiration-induced mitophagy in yeast Amsterdam volume:231 year:2017 day:29 month:03 pages:3-10 extent:8 |
| sourceStr |
Enthalten in The TORC1 signaling pathway regulates respiration-induced mitophagy in yeast Amsterdam volume:231 year:2017 day:29 month:03 pages:3-10 extent:8 |
| format_phy_str_mv |
Article |
| bklname |
Biochemie: Allgemeines Biophysik |
| institution |
findex.gbv.de |
| topic_facet |
Classifiers Neural networks E-nose Virtual organization |
| dewey-raw |
610 |
| isfreeaccess_bool |
false |
| container_title |
The TORC1 signaling pathway regulates respiration-induced mitophagy in yeast |
| authorswithroles_txt_mv |
Villarrubia, Gabriel @@aut@@ De Paz, Juan F. @@oth@@ Pelki, Dechen @@oth@@ de la Prieta, Fernando @@oth@@ Omatu, Sigeru @@oth@@ |
| publishDateDaySort_date |
2017-01-29T00:00:00Z |
| hierarchy_top_id |
ELV002603926 |
| dewey-sort |
3610 |
| id |
ELV030576520 |
| language_de |
englisch |
| fullrecord |
<?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>01000caa a22002652 4500</leader><controlfield tag="001">ELV030576520</controlfield><controlfield tag="003">DE-627</controlfield><controlfield tag="005">20230625182042.0</controlfield><controlfield tag="007">cr uuu---uuuuu</controlfield><controlfield tag="008">180603s2017 xx |||||o 00| ||eng c</controlfield><datafield tag="024" ind1="7" ind2=" "><subfield code="a">10.1016/j.neucom.2016.05.106</subfield><subfield code="2">doi</subfield></datafield><datafield tag="028" ind1="5" ind2="2"><subfield code="a">GBVA2017014000007.pica</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-627)ELV030576520</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(ELSEVIER)S0925-2312(16)31162-6</subfield></datafield><datafield tag="040" ind1=" " ind2=" "><subfield code="a">DE-627</subfield><subfield code="b">ger</subfield><subfield code="c">DE-627</subfield><subfield code="e">rakwb</subfield></datafield><datafield tag="041" ind1=" " ind2=" "><subfield code="a">eng</subfield></datafield><datafield tag="082" ind1="0" ind2=" "><subfield code="a">610</subfield></datafield><datafield tag="082" ind1="0" ind2="4"><subfield code="a">610</subfield><subfield code="q">DE-600</subfield></datafield><datafield tag="082" ind1="0" ind2="4"><subfield code="a">570</subfield><subfield code="q">VZ</subfield></datafield><datafield tag="084" ind1=" " ind2=" "><subfield code="a">BIODIV</subfield><subfield code="q">DE-30</subfield><subfield code="2">fid</subfield></datafield><datafield tag="084" ind1=" " ind2=" "><subfield code="a">35.70</subfield><subfield code="2">bkl</subfield></datafield><datafield tag="084" ind1=" " ind2=" "><subfield code="a">42.12</subfield><subfield code="2">bkl</subfield></datafield><datafield tag="100" ind1="1" ind2=" "><subfield code="a">Villarrubia, Gabriel</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">Virtual organization with fusion knowledge in odor classification</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="c">2017transfer abstract</subfield></datafield><datafield tag="300" ind1=" " ind2=" "><subfield code="a">8</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="a">nicht spezifiziert</subfield><subfield code="b">zzz</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="a">nicht spezifiziert</subfield><subfield code="b">z</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="a">nicht spezifiziert</subfield><subfield code="b">zu</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">E-nose systems are becoming increasingly important instruments across all industries, especially the fields of food and beverages and biomedicine. Given the inaccurate, unsafe and unreliable dependency on the human nose to detect smells that are highly risky and hazardous to human health, e-nose systems offer a tremendous advantage. E-noses are convenient, highly efficient and can be used in real life to detect various types of odors. This paper presents a virtual organization of agents that integrates different classification techniques and neural networks to perform information fusion from parameters retrieved by the E-nose. The integral brain in e-noses is the data processing system, which classifies odors that have been detected by the detection part of its system. The system mimics how a human brain classifies odors.</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">E-nose systems are becoming increasingly important instruments across all industries, especially the fields of food and beverages and biomedicine. Given the inaccurate, unsafe and unreliable dependency on the human nose to detect smells that are highly risky and hazardous to human health, e-nose systems offer a tremendous advantage. E-noses are convenient, highly efficient and can be used in real life to detect various types of odors. This paper presents a virtual organization of agents that integrates different classification techniques and neural networks to perform information fusion from parameters retrieved by the E-nose. The integral brain in e-noses is the data processing system, which classifies odors that have been detected by the detection part of its system. The system mimics how a human brain classifies odors.</subfield></datafield><datafield tag="650" ind1=" " ind2="7"><subfield code="a">Classifiers</subfield><subfield code="2">Elsevier</subfield></datafield><datafield tag="650" ind1=" " ind2="7"><subfield code="a">Neural networks</subfield><subfield code="2">Elsevier</subfield></datafield><datafield tag="650" ind1=" " ind2="7"><subfield code="a">E-nose</subfield><subfield code="2">Elsevier</subfield></datafield><datafield tag="650" ind1=" " ind2="7"><subfield code="a">Virtual organization</subfield><subfield code="2">Elsevier</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">De Paz, Juan F.</subfield><subfield code="4">oth</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Pelki, Dechen</subfield><subfield code="4">oth</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">de la Prieta, Fernando</subfield><subfield code="4">oth</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Omatu, Sigeru</subfield><subfield code="4">oth</subfield></datafield><datafield tag="773" ind1="0" ind2="8"><subfield code="i">Enthalten in</subfield><subfield code="n">Elsevier</subfield><subfield code="a">Liu, Yang ELSEVIER</subfield><subfield code="t">The TORC1 signaling pathway regulates respiration-induced mitophagy in yeast</subfield><subfield code="d">2018</subfield><subfield code="d">an international journal</subfield><subfield code="g">Amsterdam</subfield><subfield code="w">(DE-627)ELV002603926</subfield></datafield><datafield tag="773" ind1="1" ind2="8"><subfield code="g">volume:231</subfield><subfield code="g">year:2017</subfield><subfield code="g">day:29</subfield><subfield code="g">month:03</subfield><subfield code="g">pages:3-10</subfield><subfield code="g">extent:8</subfield></datafield><datafield tag="856" ind1="4" ind2="0"><subfield code="u">https://doi.org/10.1016/j.neucom.2016.05.106</subfield><subfield code="3">Volltext</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_USEFLAG_U</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ELV</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">SYSFLAG_U</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">FID-BIODIV</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">SSG-OLC-PHA</subfield></datafield><datafield tag="936" ind1="b" ind2="k"><subfield code="a">35.70</subfield><subfield code="j">Biochemie: Allgemeines</subfield><subfield code="q">VZ</subfield></datafield><datafield tag="936" ind1="b" ind2="k"><subfield code="a">42.12</subfield><subfield code="j">Biophysik</subfield><subfield code="q">VZ</subfield></datafield><datafield tag="951" ind1=" " ind2=" "><subfield code="a">AR</subfield></datafield><datafield tag="952" ind1=" " ind2=" "><subfield code="d">231</subfield><subfield code="j">2017</subfield><subfield code="b">29</subfield><subfield code="c">0329</subfield><subfield code="h">3-10</subfield><subfield code="g">8</subfield></datafield><datafield tag="953" ind1=" " ind2=" "><subfield code="2">045F</subfield><subfield code="a">610</subfield></datafield></record></collection>
|
| author |
Villarrubia, Gabriel |
| spellingShingle |
Villarrubia, Gabriel ddc 610 ddc 570 fid BIODIV bkl 35.70 bkl 42.12 Elsevier Classifiers Elsevier Neural networks Elsevier E-nose Elsevier Virtual organization Virtual organization with fusion knowledge in odor classification |
| authorStr |
Villarrubia, Gabriel |
| ppnlink_with_tag_str_mv |
@@773@@(DE-627)ELV002603926 |
| format |
electronic Article |
| dewey-ones |
610 - Medicine & health 570 - Life sciences; biology |
| delete_txt_mv |
keep |
| author_role |
aut |
| collection |
elsevier |
| remote_str |
true |
| illustrated |
Not Illustrated |
| topic_title |
610 610 DE-600 570 VZ BIODIV DE-30 fid 35.70 bkl 42.12 bkl Virtual organization with fusion knowledge in odor classification Classifiers Elsevier Neural networks Elsevier E-nose Elsevier Virtual organization Elsevier |
| topic |
ddc 610 ddc 570 fid BIODIV bkl 35.70 bkl 42.12 Elsevier Classifiers Elsevier Neural networks Elsevier E-nose Elsevier Virtual organization |
| topic_unstemmed |
ddc 610 ddc 570 fid BIODIV bkl 35.70 bkl 42.12 Elsevier Classifiers Elsevier Neural networks Elsevier E-nose Elsevier Virtual organization |
| topic_browse |
ddc 610 ddc 570 fid BIODIV bkl 35.70 bkl 42.12 Elsevier Classifiers Elsevier Neural networks Elsevier E-nose Elsevier Virtual organization |
| format_facet |
Elektronische Aufsätze Aufsätze Elektronische Ressource |
| format_main_str_mv |
Text Zeitschrift/Artikel |
| carriertype_str_mv |
zu |
| author2_variant |
p j f d pjf pjfd d p dp l p f d lpf lpfd s o so |
| hierarchy_parent_title |
The TORC1 signaling pathway regulates respiration-induced mitophagy in yeast |
| hierarchy_parent_id |
ELV002603926 |
| dewey-tens |
610 - Medicine & health 570 - Life sciences; biology |
| hierarchy_top_title |
The TORC1 signaling pathway regulates respiration-induced mitophagy in yeast |
| isfreeaccess_txt |
false |
| familylinks_str_mv |
(DE-627)ELV002603926 |
| title |
Virtual organization with fusion knowledge in odor classification |
| ctrlnum |
(DE-627)ELV030576520 (ELSEVIER)S0925-2312(16)31162-6 |
| title_full |
Virtual organization with fusion knowledge in odor classification |
| author_sort |
Villarrubia, Gabriel |
| journal |
The TORC1 signaling pathway regulates respiration-induced mitophagy in yeast |
| journalStr |
The TORC1 signaling pathway regulates respiration-induced mitophagy in yeast |
| lang_code |
eng |
| isOA_bool |
false |
| dewey-hundreds |
600 - Technology 500 - Science |
| recordtype |
marc |
| publishDateSort |
2017 |
| contenttype_str_mv |
zzz |
| container_start_page |
3 |
| author_browse |
Villarrubia, Gabriel |
| container_volume |
231 |
| physical |
8 |
| class |
610 610 DE-600 570 VZ BIODIV DE-30 fid 35.70 bkl 42.12 bkl |
| format_se |
Elektronische Aufsätze |
| author-letter |
Villarrubia, Gabriel |
| doi_str_mv |
10.1016/j.neucom.2016.05.106 |
| dewey-full |
610 570 |
| title_sort |
virtual organization with fusion knowledge in odor classification |
| title_auth |
Virtual organization with fusion knowledge in odor classification |
| abstract |
E-nose systems are becoming increasingly important instruments across all industries, especially the fields of food and beverages and biomedicine. Given the inaccurate, unsafe and unreliable dependency on the human nose to detect smells that are highly risky and hazardous to human health, e-nose systems offer a tremendous advantage. E-noses are convenient, highly efficient and can be used in real life to detect various types of odors. This paper presents a virtual organization of agents that integrates different classification techniques and neural networks to perform information fusion from parameters retrieved by the E-nose. The integral brain in e-noses is the data processing system, which classifies odors that have been detected by the detection part of its system. The system mimics how a human brain classifies odors. |
| abstractGer |
E-nose systems are becoming increasingly important instruments across all industries, especially the fields of food and beverages and biomedicine. Given the inaccurate, unsafe and unreliable dependency on the human nose to detect smells that are highly risky and hazardous to human health, e-nose systems offer a tremendous advantage. E-noses are convenient, highly efficient and can be used in real life to detect various types of odors. This paper presents a virtual organization of agents that integrates different classification techniques and neural networks to perform information fusion from parameters retrieved by the E-nose. The integral brain in e-noses is the data processing system, which classifies odors that have been detected by the detection part of its system. The system mimics how a human brain classifies odors. |
| abstract_unstemmed |
E-nose systems are becoming increasingly important instruments across all industries, especially the fields of food and beverages and biomedicine. Given the inaccurate, unsafe and unreliable dependency on the human nose to detect smells that are highly risky and hazardous to human health, e-nose systems offer a tremendous advantage. E-noses are convenient, highly efficient and can be used in real life to detect various types of odors. This paper presents a virtual organization of agents that integrates different classification techniques and neural networks to perform information fusion from parameters retrieved by the E-nose. The integral brain in e-noses is the data processing system, which classifies odors that have been detected by the detection part of its system. The system mimics how a human brain classifies odors. |
| collection_details |
GBV_USEFLAG_U GBV_ELV SYSFLAG_U FID-BIODIV SSG-OLC-PHA |
| title_short |
Virtual organization with fusion knowledge in odor classification |
| url |
https://doi.org/10.1016/j.neucom.2016.05.106 |
| remote_bool |
true |
| author2 |
De Paz, Juan F. Pelki, Dechen de la Prieta, Fernando Omatu, Sigeru |
| author2Str |
De Paz, Juan F. Pelki, Dechen de la Prieta, Fernando Omatu, Sigeru |
| ppnlink |
ELV002603926 |
| mediatype_str_mv |
z |
| isOA_txt |
false |
| hochschulschrift_bool |
false |
| author2_role |
oth oth oth oth |
| doi_str |
10.1016/j.neucom.2016.05.106 |
| up_date |
2024-07-06T17:56:02.352Z |
| _version_ |
1803853299558907904 |
| fullrecord_marcxml |
<?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>01000caa a22002652 4500</leader><controlfield tag="001">ELV030576520</controlfield><controlfield tag="003">DE-627</controlfield><controlfield tag="005">20230625182042.0</controlfield><controlfield tag="007">cr uuu---uuuuu</controlfield><controlfield tag="008">180603s2017 xx |||||o 00| ||eng c</controlfield><datafield tag="024" ind1="7" ind2=" "><subfield code="a">10.1016/j.neucom.2016.05.106</subfield><subfield code="2">doi</subfield></datafield><datafield tag="028" ind1="5" ind2="2"><subfield code="a">GBVA2017014000007.pica</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-627)ELV030576520</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(ELSEVIER)S0925-2312(16)31162-6</subfield></datafield><datafield tag="040" ind1=" " ind2=" "><subfield code="a">DE-627</subfield><subfield code="b">ger</subfield><subfield code="c">DE-627</subfield><subfield code="e">rakwb</subfield></datafield><datafield tag="041" ind1=" " ind2=" "><subfield code="a">eng</subfield></datafield><datafield tag="082" ind1="0" ind2=" "><subfield code="a">610</subfield></datafield><datafield tag="082" ind1="0" ind2="4"><subfield code="a">610</subfield><subfield code="q">DE-600</subfield></datafield><datafield tag="082" ind1="0" ind2="4"><subfield code="a">570</subfield><subfield code="q">VZ</subfield></datafield><datafield tag="084" ind1=" " ind2=" "><subfield code="a">BIODIV</subfield><subfield code="q">DE-30</subfield><subfield code="2">fid</subfield></datafield><datafield tag="084" ind1=" " ind2=" "><subfield code="a">35.70</subfield><subfield code="2">bkl</subfield></datafield><datafield tag="084" ind1=" " ind2=" "><subfield code="a">42.12</subfield><subfield code="2">bkl</subfield></datafield><datafield tag="100" ind1="1" ind2=" "><subfield code="a">Villarrubia, Gabriel</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">Virtual organization with fusion knowledge in odor classification</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="c">2017transfer abstract</subfield></datafield><datafield tag="300" ind1=" " ind2=" "><subfield code="a">8</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="a">nicht spezifiziert</subfield><subfield code="b">zzz</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="a">nicht spezifiziert</subfield><subfield code="b">z</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="a">nicht spezifiziert</subfield><subfield code="b">zu</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">E-nose systems are becoming increasingly important instruments across all industries, especially the fields of food and beverages and biomedicine. Given the inaccurate, unsafe and unreliable dependency on the human nose to detect smells that are highly risky and hazardous to human health, e-nose systems offer a tremendous advantage. E-noses are convenient, highly efficient and can be used in real life to detect various types of odors. This paper presents a virtual organization of agents that integrates different classification techniques and neural networks to perform information fusion from parameters retrieved by the E-nose. The integral brain in e-noses is the data processing system, which classifies odors that have been detected by the detection part of its system. The system mimics how a human brain classifies odors.</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">E-nose systems are becoming increasingly important instruments across all industries, especially the fields of food and beverages and biomedicine. Given the inaccurate, unsafe and unreliable dependency on the human nose to detect smells that are highly risky and hazardous to human health, e-nose systems offer a tremendous advantage. E-noses are convenient, highly efficient and can be used in real life to detect various types of odors. This paper presents a virtual organization of agents that integrates different classification techniques and neural networks to perform information fusion from parameters retrieved by the E-nose. The integral brain in e-noses is the data processing system, which classifies odors that have been detected by the detection part of its system. The system mimics how a human brain classifies odors.</subfield></datafield><datafield tag="650" ind1=" " ind2="7"><subfield code="a">Classifiers</subfield><subfield code="2">Elsevier</subfield></datafield><datafield tag="650" ind1=" " ind2="7"><subfield code="a">Neural networks</subfield><subfield code="2">Elsevier</subfield></datafield><datafield tag="650" ind1=" " ind2="7"><subfield code="a">E-nose</subfield><subfield code="2">Elsevier</subfield></datafield><datafield tag="650" ind1=" " ind2="7"><subfield code="a">Virtual organization</subfield><subfield code="2">Elsevier</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">De Paz, Juan F.</subfield><subfield code="4">oth</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Pelki, Dechen</subfield><subfield code="4">oth</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">de la Prieta, Fernando</subfield><subfield code="4">oth</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Omatu, Sigeru</subfield><subfield code="4">oth</subfield></datafield><datafield tag="773" ind1="0" ind2="8"><subfield code="i">Enthalten in</subfield><subfield code="n">Elsevier</subfield><subfield code="a">Liu, Yang ELSEVIER</subfield><subfield code="t">The TORC1 signaling pathway regulates respiration-induced mitophagy in yeast</subfield><subfield code="d">2018</subfield><subfield code="d">an international journal</subfield><subfield code="g">Amsterdam</subfield><subfield code="w">(DE-627)ELV002603926</subfield></datafield><datafield tag="773" ind1="1" ind2="8"><subfield code="g">volume:231</subfield><subfield code="g">year:2017</subfield><subfield code="g">day:29</subfield><subfield code="g">month:03</subfield><subfield code="g">pages:3-10</subfield><subfield code="g">extent:8</subfield></datafield><datafield tag="856" ind1="4" ind2="0"><subfield code="u">https://doi.org/10.1016/j.neucom.2016.05.106</subfield><subfield code="3">Volltext</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_USEFLAG_U</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ELV</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">SYSFLAG_U</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">FID-BIODIV</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">SSG-OLC-PHA</subfield></datafield><datafield tag="936" ind1="b" ind2="k"><subfield code="a">35.70</subfield><subfield code="j">Biochemie: Allgemeines</subfield><subfield code="q">VZ</subfield></datafield><datafield tag="936" ind1="b" ind2="k"><subfield code="a">42.12</subfield><subfield code="j">Biophysik</subfield><subfield code="q">VZ</subfield></datafield><datafield tag="951" ind1=" " ind2=" "><subfield code="a">AR</subfield></datafield><datafield tag="952" ind1=" " ind2=" "><subfield code="d">231</subfield><subfield code="j">2017</subfield><subfield code="b">29</subfield><subfield code="c">0329</subfield><subfield code="h">3-10</subfield><subfield code="g">8</subfield></datafield><datafield tag="953" ind1=" " ind2=" "><subfield code="2">045F</subfield><subfield code="a">610</subfield></datafield></record></collection>
|
| score |
7.401457 |