Cooperative path planning for air–sea heterogeneous unmanned vehicles using search-and-tracking mission
The cooperative path planning problem for air–sea heterogeneous unmanned vehicles using search-and-tracking mission is studied in this paper. Due to the limitations of single unmanned vehicle, the air–sea heterogeneous system, composed of an unmanned aerial–aquatic vehicle (UAAV), an unmanned surfac...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Ke, Can [verfasserIn] |
|---|
| Format: |
E-Artikel |
|---|---|
| Sprache: |
Englisch |
| Erschienen: |
2022transfer abstract |
|---|
| Schlagwörter: |
|---|
| Übergeordnetes Werk: |
Enthalten in: Self-healable hydrogel on tumor cell as drug delivery system for localized and effective therapy - Chang, Guanru ELSEVIER, 2015, Amsterdam [u.a.] |
|---|---|
| Übergeordnetes Werk: |
volume:262 ; year:2022 ; day:15 ; month:10 ; pages:0 |
| Links: |
|---|
| DOI / URN: |
10.1016/j.oceaneng.2022.112020 |
|---|
| Katalog-ID: |
ELV059094141 |
|---|
| LEADER | 01000caa a22002652 4500 | ||
|---|---|---|---|
| 001 | ELV059094141 | ||
| 003 | DE-627 | ||
| 005 | 20230626052220.0 | ||
| 007 | cr uuu---uuuuu | ||
| 008 | 221103s2022 xx |||||o 00| ||eng c | ||
| 024 | 7 | |a 10.1016/j.oceaneng.2022.112020 |2 doi | |
| 028 | 5 | 2 | |a /cbs_pica/cbs_olc/import_discovery/elsevier/einzuspielen/GBV00000000001918.pica |
| 035 | |a (DE-627)ELV059094141 | ||
| 035 | |a (ELSEVIER)S0029-8018(22)01351-8 | ||
| 040 | |a DE-627 |b ger |c DE-627 |e rakwb | ||
| 041 | |a eng | ||
| 082 | 0 | 4 | |a 540 |q VZ |
| 082 | 0 | 4 | |a 660 |q VZ |
| 082 | 0 | 4 | |a 540 |q VZ |
| 084 | |a BIODIV |q DE-30 |2 fid | ||
| 084 | |a 42.13 |2 bkl | ||
| 100 | 1 | |a Ke, Can |e verfasserin |4 aut | |
| 245 | 1 | 0 | |a Cooperative path planning for air–sea heterogeneous unmanned vehicles using search-and-tracking mission |
| 264 | 1 | |c 2022transfer abstract | |
| 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 The cooperative path planning problem for air–sea heterogeneous unmanned vehicles using search-and-tracking mission is studied in this paper. Due to the limitations of single unmanned vehicle, the air–sea heterogeneous system, composed of an unmanned aerial–aquatic vehicle (UAAV), an unmanned surface vehicle (USV) and an autonomous underwater vehicle (AUV), is introduced to compensate for the singleness of unmanned vehicle and complete more complicated marine missions. One search-and-tracking mission containing the search phase and tracking phase is presented to accomplish the underwater target tracking mission with goals of minimizing the search time and finding the shortest tracking path. In the search phase, according to different initial positions of three unmanned vehicles, the corresponding task allocation algorithms are proposed to determine the location of the target efficiently and minimize the search time by allocating different task for three unmanned vehicles. Meanwhile, the unmanned vehicles only know the approximate area containing the target before the task execution and move in the direction of the area for searching target. In the tracking phase, an improved particle swarm optimization algorithm is addressed to solve the path planning problem with obstacles. Simulation results show that the underwater target can be detected using search-and-tracking mission in an air–sea heterogeneous system efficiently and accurately. | ||
| 520 | |a The cooperative path planning problem for air–sea heterogeneous unmanned vehicles using search-and-tracking mission is studied in this paper. Due to the limitations of single unmanned vehicle, the air–sea heterogeneous system, composed of an unmanned aerial–aquatic vehicle (UAAV), an unmanned surface vehicle (USV) and an autonomous underwater vehicle (AUV), is introduced to compensate for the singleness of unmanned vehicle and complete more complicated marine missions. One search-and-tracking mission containing the search phase and tracking phase is presented to accomplish the underwater target tracking mission with goals of minimizing the search time and finding the shortest tracking path. In the search phase, according to different initial positions of three unmanned vehicles, the corresponding task allocation algorithms are proposed to determine the location of the target efficiently and minimize the search time by allocating different task for three unmanned vehicles. Meanwhile, the unmanned vehicles only know the approximate area containing the target before the task execution and move in the direction of the area for searching target. In the tracking phase, an improved particle swarm optimization algorithm is addressed to solve the path planning problem with obstacles. Simulation results show that the underwater target can be detected using search-and-tracking mission in an air–sea heterogeneous system efficiently and accurately. | ||
| 650 | 7 | |a Task allocation |2 Elsevier | |
| 650 | 7 | |a Search-and-tracking mission |2 Elsevier | |
| 650 | 7 | |a Air–sea heterogeneous unmanned vehicles |2 Elsevier | |
| 650 | 7 | |a Path planning |2 Elsevier | |
| 700 | 1 | |a Chen, Huifang |4 oth | |
| 773 | 0 | 8 | |i Enthalten in |n Elsevier Science |a Chang, Guanru ELSEVIER |t Self-healable hydrogel on tumor cell as drug delivery system for localized and effective therapy |d 2015 |g Amsterdam [u.a.] |w (DE-627)ELV01276728X |
| 773 | 1 | 8 | |g volume:262 |g year:2022 |g day:15 |g month:10 |g pages:0 |
| 856 | 4 | 0 | |u https://doi.org/10.1016/j.oceaneng.2022.112020 |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 42.13 |j Molekularbiologie |q VZ |
| 951 | |a AR | ||
| 952 | |d 262 |j 2022 |b 15 |c 1015 |h 0 | ||
| author_variant |
c k ck |
|---|---|
| matchkey_str |
kecanchenhuifang:2022----:oprtvptpannfrisaeeoeeuumnevhceuig |
| hierarchy_sort_str |
2022transfer abstract |
| bklnumber |
42.13 |
| publishDate |
2022 |
| allfields |
10.1016/j.oceaneng.2022.112020 doi /cbs_pica/cbs_olc/import_discovery/elsevier/einzuspielen/GBV00000000001918.pica (DE-627)ELV059094141 (ELSEVIER)S0029-8018(22)01351-8 DE-627 ger DE-627 rakwb eng 540 VZ 660 VZ 540 VZ BIODIV DE-30 fid 42.13 bkl Ke, Can verfasserin aut Cooperative path planning for air–sea heterogeneous unmanned vehicles using search-and-tracking mission 2022transfer abstract nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier The cooperative path planning problem for air–sea heterogeneous unmanned vehicles using search-and-tracking mission is studied in this paper. Due to the limitations of single unmanned vehicle, the air–sea heterogeneous system, composed of an unmanned aerial–aquatic vehicle (UAAV), an unmanned surface vehicle (USV) and an autonomous underwater vehicle (AUV), is introduced to compensate for the singleness of unmanned vehicle and complete more complicated marine missions. One search-and-tracking mission containing the search phase and tracking phase is presented to accomplish the underwater target tracking mission with goals of minimizing the search time and finding the shortest tracking path. In the search phase, according to different initial positions of three unmanned vehicles, the corresponding task allocation algorithms are proposed to determine the location of the target efficiently and minimize the search time by allocating different task for three unmanned vehicles. Meanwhile, the unmanned vehicles only know the approximate area containing the target before the task execution and move in the direction of the area for searching target. In the tracking phase, an improved particle swarm optimization algorithm is addressed to solve the path planning problem with obstacles. Simulation results show that the underwater target can be detected using search-and-tracking mission in an air–sea heterogeneous system efficiently and accurately. The cooperative path planning problem for air–sea heterogeneous unmanned vehicles using search-and-tracking mission is studied in this paper. Due to the limitations of single unmanned vehicle, the air–sea heterogeneous system, composed of an unmanned aerial–aquatic vehicle (UAAV), an unmanned surface vehicle (USV) and an autonomous underwater vehicle (AUV), is introduced to compensate for the singleness of unmanned vehicle and complete more complicated marine missions. One search-and-tracking mission containing the search phase and tracking phase is presented to accomplish the underwater target tracking mission with goals of minimizing the search time and finding the shortest tracking path. In the search phase, according to different initial positions of three unmanned vehicles, the corresponding task allocation algorithms are proposed to determine the location of the target efficiently and minimize the search time by allocating different task for three unmanned vehicles. Meanwhile, the unmanned vehicles only know the approximate area containing the target before the task execution and move in the direction of the area for searching target. In the tracking phase, an improved particle swarm optimization algorithm is addressed to solve the path planning problem with obstacles. Simulation results show that the underwater target can be detected using search-and-tracking mission in an air–sea heterogeneous system efficiently and accurately. Task allocation Elsevier Search-and-tracking mission Elsevier Air–sea heterogeneous unmanned vehicles Elsevier Path planning Elsevier Chen, Huifang oth Enthalten in Elsevier Science Chang, Guanru ELSEVIER Self-healable hydrogel on tumor cell as drug delivery system for localized and effective therapy 2015 Amsterdam [u.a.] (DE-627)ELV01276728X volume:262 year:2022 day:15 month:10 pages:0 https://doi.org/10.1016/j.oceaneng.2022.112020 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U FID-BIODIV SSG-OLC-PHA 42.13 Molekularbiologie VZ AR 262 2022 15 1015 0 |
| spelling |
10.1016/j.oceaneng.2022.112020 doi /cbs_pica/cbs_olc/import_discovery/elsevier/einzuspielen/GBV00000000001918.pica (DE-627)ELV059094141 (ELSEVIER)S0029-8018(22)01351-8 DE-627 ger DE-627 rakwb eng 540 VZ 660 VZ 540 VZ BIODIV DE-30 fid 42.13 bkl Ke, Can verfasserin aut Cooperative path planning for air–sea heterogeneous unmanned vehicles using search-and-tracking mission 2022transfer abstract nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier The cooperative path planning problem for air–sea heterogeneous unmanned vehicles using search-and-tracking mission is studied in this paper. Due to the limitations of single unmanned vehicle, the air–sea heterogeneous system, composed of an unmanned aerial–aquatic vehicle (UAAV), an unmanned surface vehicle (USV) and an autonomous underwater vehicle (AUV), is introduced to compensate for the singleness of unmanned vehicle and complete more complicated marine missions. One search-and-tracking mission containing the search phase and tracking phase is presented to accomplish the underwater target tracking mission with goals of minimizing the search time and finding the shortest tracking path. In the search phase, according to different initial positions of three unmanned vehicles, the corresponding task allocation algorithms are proposed to determine the location of the target efficiently and minimize the search time by allocating different task for three unmanned vehicles. Meanwhile, the unmanned vehicles only know the approximate area containing the target before the task execution and move in the direction of the area for searching target. In the tracking phase, an improved particle swarm optimization algorithm is addressed to solve the path planning problem with obstacles. Simulation results show that the underwater target can be detected using search-and-tracking mission in an air–sea heterogeneous system efficiently and accurately. The cooperative path planning problem for air–sea heterogeneous unmanned vehicles using search-and-tracking mission is studied in this paper. Due to the limitations of single unmanned vehicle, the air–sea heterogeneous system, composed of an unmanned aerial–aquatic vehicle (UAAV), an unmanned surface vehicle (USV) and an autonomous underwater vehicle (AUV), is introduced to compensate for the singleness of unmanned vehicle and complete more complicated marine missions. One search-and-tracking mission containing the search phase and tracking phase is presented to accomplish the underwater target tracking mission with goals of minimizing the search time and finding the shortest tracking path. In the search phase, according to different initial positions of three unmanned vehicles, the corresponding task allocation algorithms are proposed to determine the location of the target efficiently and minimize the search time by allocating different task for three unmanned vehicles. Meanwhile, the unmanned vehicles only know the approximate area containing the target before the task execution and move in the direction of the area for searching target. In the tracking phase, an improved particle swarm optimization algorithm is addressed to solve the path planning problem with obstacles. Simulation results show that the underwater target can be detected using search-and-tracking mission in an air–sea heterogeneous system efficiently and accurately. Task allocation Elsevier Search-and-tracking mission Elsevier Air–sea heterogeneous unmanned vehicles Elsevier Path planning Elsevier Chen, Huifang oth Enthalten in Elsevier Science Chang, Guanru ELSEVIER Self-healable hydrogel on tumor cell as drug delivery system for localized and effective therapy 2015 Amsterdam [u.a.] (DE-627)ELV01276728X volume:262 year:2022 day:15 month:10 pages:0 https://doi.org/10.1016/j.oceaneng.2022.112020 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U FID-BIODIV SSG-OLC-PHA 42.13 Molekularbiologie VZ AR 262 2022 15 1015 0 |
| allfields_unstemmed |
10.1016/j.oceaneng.2022.112020 doi /cbs_pica/cbs_olc/import_discovery/elsevier/einzuspielen/GBV00000000001918.pica (DE-627)ELV059094141 (ELSEVIER)S0029-8018(22)01351-8 DE-627 ger DE-627 rakwb eng 540 VZ 660 VZ 540 VZ BIODIV DE-30 fid 42.13 bkl Ke, Can verfasserin aut Cooperative path planning for air–sea heterogeneous unmanned vehicles using search-and-tracking mission 2022transfer abstract nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier The cooperative path planning problem for air–sea heterogeneous unmanned vehicles using search-and-tracking mission is studied in this paper. Due to the limitations of single unmanned vehicle, the air–sea heterogeneous system, composed of an unmanned aerial–aquatic vehicle (UAAV), an unmanned surface vehicle (USV) and an autonomous underwater vehicle (AUV), is introduced to compensate for the singleness of unmanned vehicle and complete more complicated marine missions. One search-and-tracking mission containing the search phase and tracking phase is presented to accomplish the underwater target tracking mission with goals of minimizing the search time and finding the shortest tracking path. In the search phase, according to different initial positions of three unmanned vehicles, the corresponding task allocation algorithms are proposed to determine the location of the target efficiently and minimize the search time by allocating different task for three unmanned vehicles. Meanwhile, the unmanned vehicles only know the approximate area containing the target before the task execution and move in the direction of the area for searching target. In the tracking phase, an improved particle swarm optimization algorithm is addressed to solve the path planning problem with obstacles. Simulation results show that the underwater target can be detected using search-and-tracking mission in an air–sea heterogeneous system efficiently and accurately. The cooperative path planning problem for air–sea heterogeneous unmanned vehicles using search-and-tracking mission is studied in this paper. Due to the limitations of single unmanned vehicle, the air–sea heterogeneous system, composed of an unmanned aerial–aquatic vehicle (UAAV), an unmanned surface vehicle (USV) and an autonomous underwater vehicle (AUV), is introduced to compensate for the singleness of unmanned vehicle and complete more complicated marine missions. One search-and-tracking mission containing the search phase and tracking phase is presented to accomplish the underwater target tracking mission with goals of minimizing the search time and finding the shortest tracking path. In the search phase, according to different initial positions of three unmanned vehicles, the corresponding task allocation algorithms are proposed to determine the location of the target efficiently and minimize the search time by allocating different task for three unmanned vehicles. Meanwhile, the unmanned vehicles only know the approximate area containing the target before the task execution and move in the direction of the area for searching target. In the tracking phase, an improved particle swarm optimization algorithm is addressed to solve the path planning problem with obstacles. Simulation results show that the underwater target can be detected using search-and-tracking mission in an air–sea heterogeneous system efficiently and accurately. Task allocation Elsevier Search-and-tracking mission Elsevier Air–sea heterogeneous unmanned vehicles Elsevier Path planning Elsevier Chen, Huifang oth Enthalten in Elsevier Science Chang, Guanru ELSEVIER Self-healable hydrogel on tumor cell as drug delivery system for localized and effective therapy 2015 Amsterdam [u.a.] (DE-627)ELV01276728X volume:262 year:2022 day:15 month:10 pages:0 https://doi.org/10.1016/j.oceaneng.2022.112020 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U FID-BIODIV SSG-OLC-PHA 42.13 Molekularbiologie VZ AR 262 2022 15 1015 0 |
| allfieldsGer |
10.1016/j.oceaneng.2022.112020 doi /cbs_pica/cbs_olc/import_discovery/elsevier/einzuspielen/GBV00000000001918.pica (DE-627)ELV059094141 (ELSEVIER)S0029-8018(22)01351-8 DE-627 ger DE-627 rakwb eng 540 VZ 660 VZ 540 VZ BIODIV DE-30 fid 42.13 bkl Ke, Can verfasserin aut Cooperative path planning for air–sea heterogeneous unmanned vehicles using search-and-tracking mission 2022transfer abstract nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier The cooperative path planning problem for air–sea heterogeneous unmanned vehicles using search-and-tracking mission is studied in this paper. Due to the limitations of single unmanned vehicle, the air–sea heterogeneous system, composed of an unmanned aerial–aquatic vehicle (UAAV), an unmanned surface vehicle (USV) and an autonomous underwater vehicle (AUV), is introduced to compensate for the singleness of unmanned vehicle and complete more complicated marine missions. One search-and-tracking mission containing the search phase and tracking phase is presented to accomplish the underwater target tracking mission with goals of minimizing the search time and finding the shortest tracking path. In the search phase, according to different initial positions of three unmanned vehicles, the corresponding task allocation algorithms are proposed to determine the location of the target efficiently and minimize the search time by allocating different task for three unmanned vehicles. Meanwhile, the unmanned vehicles only know the approximate area containing the target before the task execution and move in the direction of the area for searching target. In the tracking phase, an improved particle swarm optimization algorithm is addressed to solve the path planning problem with obstacles. Simulation results show that the underwater target can be detected using search-and-tracking mission in an air–sea heterogeneous system efficiently and accurately. The cooperative path planning problem for air–sea heterogeneous unmanned vehicles using search-and-tracking mission is studied in this paper. Due to the limitations of single unmanned vehicle, the air–sea heterogeneous system, composed of an unmanned aerial–aquatic vehicle (UAAV), an unmanned surface vehicle (USV) and an autonomous underwater vehicle (AUV), is introduced to compensate for the singleness of unmanned vehicle and complete more complicated marine missions. One search-and-tracking mission containing the search phase and tracking phase is presented to accomplish the underwater target tracking mission with goals of minimizing the search time and finding the shortest tracking path. In the search phase, according to different initial positions of three unmanned vehicles, the corresponding task allocation algorithms are proposed to determine the location of the target efficiently and minimize the search time by allocating different task for three unmanned vehicles. Meanwhile, the unmanned vehicles only know the approximate area containing the target before the task execution and move in the direction of the area for searching target. In the tracking phase, an improved particle swarm optimization algorithm is addressed to solve the path planning problem with obstacles. Simulation results show that the underwater target can be detected using search-and-tracking mission in an air–sea heterogeneous system efficiently and accurately. Task allocation Elsevier Search-and-tracking mission Elsevier Air–sea heterogeneous unmanned vehicles Elsevier Path planning Elsevier Chen, Huifang oth Enthalten in Elsevier Science Chang, Guanru ELSEVIER Self-healable hydrogel on tumor cell as drug delivery system for localized and effective therapy 2015 Amsterdam [u.a.] (DE-627)ELV01276728X volume:262 year:2022 day:15 month:10 pages:0 https://doi.org/10.1016/j.oceaneng.2022.112020 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U FID-BIODIV SSG-OLC-PHA 42.13 Molekularbiologie VZ AR 262 2022 15 1015 0 |
| allfieldsSound |
10.1016/j.oceaneng.2022.112020 doi /cbs_pica/cbs_olc/import_discovery/elsevier/einzuspielen/GBV00000000001918.pica (DE-627)ELV059094141 (ELSEVIER)S0029-8018(22)01351-8 DE-627 ger DE-627 rakwb eng 540 VZ 660 VZ 540 VZ BIODIV DE-30 fid 42.13 bkl Ke, Can verfasserin aut Cooperative path planning for air–sea heterogeneous unmanned vehicles using search-and-tracking mission 2022transfer abstract nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier The cooperative path planning problem for air–sea heterogeneous unmanned vehicles using search-and-tracking mission is studied in this paper. Due to the limitations of single unmanned vehicle, the air–sea heterogeneous system, composed of an unmanned aerial–aquatic vehicle (UAAV), an unmanned surface vehicle (USV) and an autonomous underwater vehicle (AUV), is introduced to compensate for the singleness of unmanned vehicle and complete more complicated marine missions. One search-and-tracking mission containing the search phase and tracking phase is presented to accomplish the underwater target tracking mission with goals of minimizing the search time and finding the shortest tracking path. In the search phase, according to different initial positions of three unmanned vehicles, the corresponding task allocation algorithms are proposed to determine the location of the target efficiently and minimize the search time by allocating different task for three unmanned vehicles. Meanwhile, the unmanned vehicles only know the approximate area containing the target before the task execution and move in the direction of the area for searching target. In the tracking phase, an improved particle swarm optimization algorithm is addressed to solve the path planning problem with obstacles. Simulation results show that the underwater target can be detected using search-and-tracking mission in an air–sea heterogeneous system efficiently and accurately. The cooperative path planning problem for air–sea heterogeneous unmanned vehicles using search-and-tracking mission is studied in this paper. Due to the limitations of single unmanned vehicle, the air–sea heterogeneous system, composed of an unmanned aerial–aquatic vehicle (UAAV), an unmanned surface vehicle (USV) and an autonomous underwater vehicle (AUV), is introduced to compensate for the singleness of unmanned vehicle and complete more complicated marine missions. One search-and-tracking mission containing the search phase and tracking phase is presented to accomplish the underwater target tracking mission with goals of minimizing the search time and finding the shortest tracking path. In the search phase, according to different initial positions of three unmanned vehicles, the corresponding task allocation algorithms are proposed to determine the location of the target efficiently and minimize the search time by allocating different task for three unmanned vehicles. Meanwhile, the unmanned vehicles only know the approximate area containing the target before the task execution and move in the direction of the area for searching target. In the tracking phase, an improved particle swarm optimization algorithm is addressed to solve the path planning problem with obstacles. Simulation results show that the underwater target can be detected using search-and-tracking mission in an air–sea heterogeneous system efficiently and accurately. Task allocation Elsevier Search-and-tracking mission Elsevier Air–sea heterogeneous unmanned vehicles Elsevier Path planning Elsevier Chen, Huifang oth Enthalten in Elsevier Science Chang, Guanru ELSEVIER Self-healable hydrogel on tumor cell as drug delivery system for localized and effective therapy 2015 Amsterdam [u.a.] (DE-627)ELV01276728X volume:262 year:2022 day:15 month:10 pages:0 https://doi.org/10.1016/j.oceaneng.2022.112020 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U FID-BIODIV SSG-OLC-PHA 42.13 Molekularbiologie VZ AR 262 2022 15 1015 0 |
| language |
English |
| source |
Enthalten in Self-healable hydrogel on tumor cell as drug delivery system for localized and effective therapy Amsterdam [u.a.] volume:262 year:2022 day:15 month:10 pages:0 |
| sourceStr |
Enthalten in Self-healable hydrogel on tumor cell as drug delivery system for localized and effective therapy Amsterdam [u.a.] volume:262 year:2022 day:15 month:10 pages:0 |
| format_phy_str_mv |
Article |
| bklname |
Molekularbiologie |
| institution |
findex.gbv.de |
| topic_facet |
Task allocation Search-and-tracking mission Air–sea heterogeneous unmanned vehicles Path planning |
| dewey-raw |
540 |
| isfreeaccess_bool |
false |
| container_title |
Self-healable hydrogel on tumor cell as drug delivery system for localized and effective therapy |
| authorswithroles_txt_mv |
Ke, Can @@aut@@ Chen, Huifang @@oth@@ |
| publishDateDaySort_date |
2022-01-15T00:00:00Z |
| hierarchy_top_id |
ELV01276728X |
| dewey-sort |
3540 |
| id |
ELV059094141 |
| 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">ELV059094141</controlfield><controlfield tag="003">DE-627</controlfield><controlfield tag="005">20230626052220.0</controlfield><controlfield tag="007">cr uuu---uuuuu</controlfield><controlfield tag="008">221103s2022 xx |||||o 00| ||eng c</controlfield><datafield tag="024" ind1="7" ind2=" "><subfield code="a">10.1016/j.oceaneng.2022.112020</subfield><subfield code="2">doi</subfield></datafield><datafield tag="028" ind1="5" ind2="2"><subfield code="a">/cbs_pica/cbs_olc/import_discovery/elsevier/einzuspielen/GBV00000000001918.pica</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-627)ELV059094141</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(ELSEVIER)S0029-8018(22)01351-8</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="4"><subfield code="a">540</subfield><subfield code="q">VZ</subfield></datafield><datafield tag="082" ind1="0" ind2="4"><subfield code="a">660</subfield><subfield code="q">VZ</subfield></datafield><datafield tag="082" ind1="0" ind2="4"><subfield code="a">540</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">42.13</subfield><subfield code="2">bkl</subfield></datafield><datafield tag="100" ind1="1" ind2=" "><subfield code="a">Ke, Can</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">Cooperative path planning for air–sea heterogeneous unmanned vehicles using search-and-tracking mission</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="c">2022transfer abstract</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">The cooperative path planning problem for air–sea heterogeneous unmanned vehicles using search-and-tracking mission is studied in this paper. Due to the limitations of single unmanned vehicle, the air–sea heterogeneous system, composed of an unmanned aerial–aquatic vehicle (UAAV), an unmanned surface vehicle (USV) and an autonomous underwater vehicle (AUV), is introduced to compensate for the singleness of unmanned vehicle and complete more complicated marine missions. One search-and-tracking mission containing the search phase and tracking phase is presented to accomplish the underwater target tracking mission with goals of minimizing the search time and finding the shortest tracking path. In the search phase, according to different initial positions of three unmanned vehicles, the corresponding task allocation algorithms are proposed to determine the location of the target efficiently and minimize the search time by allocating different task for three unmanned vehicles. Meanwhile, the unmanned vehicles only know the approximate area containing the target before the task execution and move in the direction of the area for searching target. In the tracking phase, an improved particle swarm optimization algorithm is addressed to solve the path planning problem with obstacles. Simulation results show that the underwater target can be detected using search-and-tracking mission in an air–sea heterogeneous system efficiently and accurately.</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">The cooperative path planning problem for air–sea heterogeneous unmanned vehicles using search-and-tracking mission is studied in this paper. Due to the limitations of single unmanned vehicle, the air–sea heterogeneous system, composed of an unmanned aerial–aquatic vehicle (UAAV), an unmanned surface vehicle (USV) and an autonomous underwater vehicle (AUV), is introduced to compensate for the singleness of unmanned vehicle and complete more complicated marine missions. One search-and-tracking mission containing the search phase and tracking phase is presented to accomplish the underwater target tracking mission with goals of minimizing the search time and finding the shortest tracking path. In the search phase, according to different initial positions of three unmanned vehicles, the corresponding task allocation algorithms are proposed to determine the location of the target efficiently and minimize the search time by allocating different task for three unmanned vehicles. Meanwhile, the unmanned vehicles only know the approximate area containing the target before the task execution and move in the direction of the area for searching target. In the tracking phase, an improved particle swarm optimization algorithm is addressed to solve the path planning problem with obstacles. Simulation results show that the underwater target can be detected using search-and-tracking mission in an air–sea heterogeneous system efficiently and accurately.</subfield></datafield><datafield tag="650" ind1=" " ind2="7"><subfield code="a">Task allocation</subfield><subfield code="2">Elsevier</subfield></datafield><datafield tag="650" ind1=" " ind2="7"><subfield code="a">Search-and-tracking mission</subfield><subfield code="2">Elsevier</subfield></datafield><datafield tag="650" ind1=" " ind2="7"><subfield code="a">Air–sea heterogeneous unmanned vehicles</subfield><subfield code="2">Elsevier</subfield></datafield><datafield tag="650" ind1=" " ind2="7"><subfield code="a">Path planning</subfield><subfield code="2">Elsevier</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Chen, Huifang</subfield><subfield code="4">oth</subfield></datafield><datafield tag="773" ind1="0" ind2="8"><subfield code="i">Enthalten in</subfield><subfield code="n">Elsevier Science</subfield><subfield code="a">Chang, Guanru ELSEVIER</subfield><subfield code="t">Self-healable hydrogel on tumor cell as drug delivery system for localized and effective therapy</subfield><subfield code="d">2015</subfield><subfield code="g">Amsterdam [u.a.]</subfield><subfield code="w">(DE-627)ELV01276728X</subfield></datafield><datafield tag="773" ind1="1" ind2="8"><subfield code="g">volume:262</subfield><subfield code="g">year:2022</subfield><subfield code="g">day:15</subfield><subfield code="g">month:10</subfield><subfield code="g">pages:0</subfield></datafield><datafield tag="856" ind1="4" ind2="0"><subfield code="u">https://doi.org/10.1016/j.oceaneng.2022.112020</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">42.13</subfield><subfield code="j">Molekularbiologie</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">262</subfield><subfield code="j">2022</subfield><subfield code="b">15</subfield><subfield code="c">1015</subfield><subfield code="h">0</subfield></datafield></record></collection>
|
| author |
Ke, Can |
| spellingShingle |
Ke, Can ddc 540 ddc 660 fid BIODIV bkl 42.13 Elsevier Task allocation Elsevier Search-and-tracking mission Elsevier Air–sea heterogeneous unmanned vehicles Elsevier Path planning Cooperative path planning for air–sea heterogeneous unmanned vehicles using search-and-tracking mission |
| authorStr |
Ke, Can |
| ppnlink_with_tag_str_mv |
@@773@@(DE-627)ELV01276728X |
| format |
electronic Article |
| dewey-ones |
540 - Chemistry & allied sciences 660 - Chemical engineering |
| delete_txt_mv |
keep |
| author_role |
aut |
| collection |
elsevier |
| remote_str |
true |
| illustrated |
Not Illustrated |
| topic_title |
540 VZ 660 VZ BIODIV DE-30 fid 42.13 bkl Cooperative path planning for air–sea heterogeneous unmanned vehicles using search-and-tracking mission Task allocation Elsevier Search-and-tracking mission Elsevier Air–sea heterogeneous unmanned vehicles Elsevier Path planning Elsevier |
| topic |
ddc 540 ddc 660 fid BIODIV bkl 42.13 Elsevier Task allocation Elsevier Search-and-tracking mission Elsevier Air–sea heterogeneous unmanned vehicles Elsevier Path planning |
| topic_unstemmed |
ddc 540 ddc 660 fid BIODIV bkl 42.13 Elsevier Task allocation Elsevier Search-and-tracking mission Elsevier Air–sea heterogeneous unmanned vehicles Elsevier Path planning |
| topic_browse |
ddc 540 ddc 660 fid BIODIV bkl 42.13 Elsevier Task allocation Elsevier Search-and-tracking mission Elsevier Air–sea heterogeneous unmanned vehicles Elsevier Path planning |
| format_facet |
Elektronische Aufsätze Aufsätze Elektronische Ressource |
| format_main_str_mv |
Text Zeitschrift/Artikel |
| carriertype_str_mv |
zu |
| author2_variant |
h c hc |
| hierarchy_parent_title |
Self-healable hydrogel on tumor cell as drug delivery system for localized and effective therapy |
| hierarchy_parent_id |
ELV01276728X |
| dewey-tens |
540 - Chemistry 660 - Chemical engineering |
| hierarchy_top_title |
Self-healable hydrogel on tumor cell as drug delivery system for localized and effective therapy |
| isfreeaccess_txt |
false |
| familylinks_str_mv |
(DE-627)ELV01276728X |
| title |
Cooperative path planning for air–sea heterogeneous unmanned vehicles using search-and-tracking mission |
| ctrlnum |
(DE-627)ELV059094141 (ELSEVIER)S0029-8018(22)01351-8 |
| title_full |
Cooperative path planning for air–sea heterogeneous unmanned vehicles using search-and-tracking mission |
| author_sort |
Ke, Can |
| journal |
Self-healable hydrogel on tumor cell as drug delivery system for localized and effective therapy |
| journalStr |
Self-healable hydrogel on tumor cell as drug delivery system for localized and effective therapy |
| lang_code |
eng |
| isOA_bool |
false |
| dewey-hundreds |
500 - Science 600 - Technology |
| recordtype |
marc |
| publishDateSort |
2022 |
| contenttype_str_mv |
zzz |
| container_start_page |
0 |
| author_browse |
Ke, Can |
| container_volume |
262 |
| class |
540 VZ 660 VZ BIODIV DE-30 fid 42.13 bkl |
| format_se |
Elektronische Aufsätze |
| author-letter |
Ke, Can |
| doi_str_mv |
10.1016/j.oceaneng.2022.112020 |
| dewey-full |
540 660 |
| title_sort |
cooperative path planning for air–sea heterogeneous unmanned vehicles using search-and-tracking mission |
| title_auth |
Cooperative path planning for air–sea heterogeneous unmanned vehicles using search-and-tracking mission |
| abstract |
The cooperative path planning problem for air–sea heterogeneous unmanned vehicles using search-and-tracking mission is studied in this paper. Due to the limitations of single unmanned vehicle, the air–sea heterogeneous system, composed of an unmanned aerial–aquatic vehicle (UAAV), an unmanned surface vehicle (USV) and an autonomous underwater vehicle (AUV), is introduced to compensate for the singleness of unmanned vehicle and complete more complicated marine missions. One search-and-tracking mission containing the search phase and tracking phase is presented to accomplish the underwater target tracking mission with goals of minimizing the search time and finding the shortest tracking path. In the search phase, according to different initial positions of three unmanned vehicles, the corresponding task allocation algorithms are proposed to determine the location of the target efficiently and minimize the search time by allocating different task for three unmanned vehicles. Meanwhile, the unmanned vehicles only know the approximate area containing the target before the task execution and move in the direction of the area for searching target. In the tracking phase, an improved particle swarm optimization algorithm is addressed to solve the path planning problem with obstacles. Simulation results show that the underwater target can be detected using search-and-tracking mission in an air–sea heterogeneous system efficiently and accurately. |
| abstractGer |
The cooperative path planning problem for air–sea heterogeneous unmanned vehicles using search-and-tracking mission is studied in this paper. Due to the limitations of single unmanned vehicle, the air–sea heterogeneous system, composed of an unmanned aerial–aquatic vehicle (UAAV), an unmanned surface vehicle (USV) and an autonomous underwater vehicle (AUV), is introduced to compensate for the singleness of unmanned vehicle and complete more complicated marine missions. One search-and-tracking mission containing the search phase and tracking phase is presented to accomplish the underwater target tracking mission with goals of minimizing the search time and finding the shortest tracking path. In the search phase, according to different initial positions of three unmanned vehicles, the corresponding task allocation algorithms are proposed to determine the location of the target efficiently and minimize the search time by allocating different task for three unmanned vehicles. Meanwhile, the unmanned vehicles only know the approximate area containing the target before the task execution and move in the direction of the area for searching target. In the tracking phase, an improved particle swarm optimization algorithm is addressed to solve the path planning problem with obstacles. Simulation results show that the underwater target can be detected using search-and-tracking mission in an air–sea heterogeneous system efficiently and accurately. |
| abstract_unstemmed |
The cooperative path planning problem for air–sea heterogeneous unmanned vehicles using search-and-tracking mission is studied in this paper. Due to the limitations of single unmanned vehicle, the air–sea heterogeneous system, composed of an unmanned aerial–aquatic vehicle (UAAV), an unmanned surface vehicle (USV) and an autonomous underwater vehicle (AUV), is introduced to compensate for the singleness of unmanned vehicle and complete more complicated marine missions. One search-and-tracking mission containing the search phase and tracking phase is presented to accomplish the underwater target tracking mission with goals of minimizing the search time and finding the shortest tracking path. In the search phase, according to different initial positions of three unmanned vehicles, the corresponding task allocation algorithms are proposed to determine the location of the target efficiently and minimize the search time by allocating different task for three unmanned vehicles. Meanwhile, the unmanned vehicles only know the approximate area containing the target before the task execution and move in the direction of the area for searching target. In the tracking phase, an improved particle swarm optimization algorithm is addressed to solve the path planning problem with obstacles. Simulation results show that the underwater target can be detected using search-and-tracking mission in an air–sea heterogeneous system efficiently and accurately. |
| collection_details |
GBV_USEFLAG_U GBV_ELV SYSFLAG_U FID-BIODIV SSG-OLC-PHA |
| title_short |
Cooperative path planning for air–sea heterogeneous unmanned vehicles using search-and-tracking mission |
| url |
https://doi.org/10.1016/j.oceaneng.2022.112020 |
| remote_bool |
true |
| author2 |
Chen, Huifang |
| author2Str |
Chen, Huifang |
| ppnlink |
ELV01276728X |
| mediatype_str_mv |
z |
| isOA_txt |
false |
| hochschulschrift_bool |
false |
| author2_role |
oth |
| doi_str |
10.1016/j.oceaneng.2022.112020 |
| up_date |
2024-07-06T20:57:35.433Z |
| _version_ |
1803864721781161984 |
| 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">ELV059094141</controlfield><controlfield tag="003">DE-627</controlfield><controlfield tag="005">20230626052220.0</controlfield><controlfield tag="007">cr uuu---uuuuu</controlfield><controlfield tag="008">221103s2022 xx |||||o 00| ||eng c</controlfield><datafield tag="024" ind1="7" ind2=" "><subfield code="a">10.1016/j.oceaneng.2022.112020</subfield><subfield code="2">doi</subfield></datafield><datafield tag="028" ind1="5" ind2="2"><subfield code="a">/cbs_pica/cbs_olc/import_discovery/elsevier/einzuspielen/GBV00000000001918.pica</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-627)ELV059094141</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(ELSEVIER)S0029-8018(22)01351-8</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="4"><subfield code="a">540</subfield><subfield code="q">VZ</subfield></datafield><datafield tag="082" ind1="0" ind2="4"><subfield code="a">660</subfield><subfield code="q">VZ</subfield></datafield><datafield tag="082" ind1="0" ind2="4"><subfield code="a">540</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">42.13</subfield><subfield code="2">bkl</subfield></datafield><datafield tag="100" ind1="1" ind2=" "><subfield code="a">Ke, Can</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">Cooperative path planning for air–sea heterogeneous unmanned vehicles using search-and-tracking mission</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="c">2022transfer abstract</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">The cooperative path planning problem for air–sea heterogeneous unmanned vehicles using search-and-tracking mission is studied in this paper. Due to the limitations of single unmanned vehicle, the air–sea heterogeneous system, composed of an unmanned aerial–aquatic vehicle (UAAV), an unmanned surface vehicle (USV) and an autonomous underwater vehicle (AUV), is introduced to compensate for the singleness of unmanned vehicle and complete more complicated marine missions. One search-and-tracking mission containing the search phase and tracking phase is presented to accomplish the underwater target tracking mission with goals of minimizing the search time and finding the shortest tracking path. In the search phase, according to different initial positions of three unmanned vehicles, the corresponding task allocation algorithms are proposed to determine the location of the target efficiently and minimize the search time by allocating different task for three unmanned vehicles. Meanwhile, the unmanned vehicles only know the approximate area containing the target before the task execution and move in the direction of the area for searching target. In the tracking phase, an improved particle swarm optimization algorithm is addressed to solve the path planning problem with obstacles. Simulation results show that the underwater target can be detected using search-and-tracking mission in an air–sea heterogeneous system efficiently and accurately.</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">The cooperative path planning problem for air–sea heterogeneous unmanned vehicles using search-and-tracking mission is studied in this paper. Due to the limitations of single unmanned vehicle, the air–sea heterogeneous system, composed of an unmanned aerial–aquatic vehicle (UAAV), an unmanned surface vehicle (USV) and an autonomous underwater vehicle (AUV), is introduced to compensate for the singleness of unmanned vehicle and complete more complicated marine missions. One search-and-tracking mission containing the search phase and tracking phase is presented to accomplish the underwater target tracking mission with goals of minimizing the search time and finding the shortest tracking path. In the search phase, according to different initial positions of three unmanned vehicles, the corresponding task allocation algorithms are proposed to determine the location of the target efficiently and minimize the search time by allocating different task for three unmanned vehicles. Meanwhile, the unmanned vehicles only know the approximate area containing the target before the task execution and move in the direction of the area for searching target. In the tracking phase, an improved particle swarm optimization algorithm is addressed to solve the path planning problem with obstacles. Simulation results show that the underwater target can be detected using search-and-tracking mission in an air–sea heterogeneous system efficiently and accurately.</subfield></datafield><datafield tag="650" ind1=" " ind2="7"><subfield code="a">Task allocation</subfield><subfield code="2">Elsevier</subfield></datafield><datafield tag="650" ind1=" " ind2="7"><subfield code="a">Search-and-tracking mission</subfield><subfield code="2">Elsevier</subfield></datafield><datafield tag="650" ind1=" " ind2="7"><subfield code="a">Air–sea heterogeneous unmanned vehicles</subfield><subfield code="2">Elsevier</subfield></datafield><datafield tag="650" ind1=" " ind2="7"><subfield code="a">Path planning</subfield><subfield code="2">Elsevier</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Chen, Huifang</subfield><subfield code="4">oth</subfield></datafield><datafield tag="773" ind1="0" ind2="8"><subfield code="i">Enthalten in</subfield><subfield code="n">Elsevier Science</subfield><subfield code="a">Chang, Guanru ELSEVIER</subfield><subfield code="t">Self-healable hydrogel on tumor cell as drug delivery system for localized and effective therapy</subfield><subfield code="d">2015</subfield><subfield code="g">Amsterdam [u.a.]</subfield><subfield code="w">(DE-627)ELV01276728X</subfield></datafield><datafield tag="773" ind1="1" ind2="8"><subfield code="g">volume:262</subfield><subfield code="g">year:2022</subfield><subfield code="g">day:15</subfield><subfield code="g">month:10</subfield><subfield code="g">pages:0</subfield></datafield><datafield tag="856" ind1="4" ind2="0"><subfield code="u">https://doi.org/10.1016/j.oceaneng.2022.112020</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">42.13</subfield><subfield code="j">Molekularbiologie</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">262</subfield><subfield code="j">2022</subfield><subfield code="b">15</subfield><subfield code="c">1015</subfield><subfield code="h">0</subfield></datafield></record></collection>
|
| score |
7.399168 |