PANI, CLAUDIA
Distribuzione geografica
| Continente | # |
|---|---|
| EU - Europa | 414 |
| AS - Asia | 213 |
| NA - Nord America | 180 |
| AF - Africa | 28 |
| SA - Sud America | 21 |
| OC - Oceania | 9 |
| Continente sconosciuto - Info sul continente non disponibili | 2 |
| Totale | 867 |
| Nazione | # |
|---|---|
| IT - Italia | 183 |
| US - Stati Uniti d'America | 176 |
| DE - Germania | 86 |
| CN - Cina | 51 |
| GB - Regno Unito | 43 |
| HK - Hong Kong | 28 |
| NL - Olanda | 28 |
| IN - India | 21 |
| SG - Singapore | 20 |
| FR - Francia | 18 |
| KR - Corea | 18 |
| JP - Giappone | 17 |
| TW - Taiwan | 14 |
| ES - Italia | 11 |
| EG - Egitto | 10 |
| VN - Vietnam | 10 |
| ZA - Sudafrica | 10 |
| PE - Perù | 9 |
| TR - Turchia | 8 |
| RU - Federazione Russa | 7 |
| MA - Marocco | 6 |
| MY - Malesia | 6 |
| SE - Svezia | 6 |
| BR - Brasile | 5 |
| GR - Grecia | 5 |
| IR - Iran | 5 |
| LK - Sri Lanka | 5 |
| NZ - Nuova Zelanda | 5 |
| PL - Polonia | 5 |
| AU - Australia | 4 |
| BE - Belgio | 4 |
| CL - Cile | 4 |
| DK - Danimarca | 4 |
| ID - Indonesia | 4 |
| RO - Romania | 4 |
| CO - Colombia | 3 |
| FI - Finlandia | 3 |
| PT - Portogallo | 3 |
| TH - Thailandia | 3 |
| CA - Canada | 2 |
| CZ - Repubblica Ceca | 2 |
| EU - Europa | 2 |
| MX - Messico | 2 |
| RS - Serbia | 2 |
| AE - Emirati Arabi Uniti | 1 |
| LB - Libano | 1 |
| LY - Libia | 1 |
| PH - Filippine | 1 |
| TN - Tunisia | 1 |
| Totale | 867 |
| Città | # |
|---|---|
| Cagliari | 145 |
| Hamburg | 34 |
| Beijing | 14 |
| Shanghai | 13 |
| Tokyo | 13 |
| Goole | 12 |
| Duncan | 11 |
| San Jose | 11 |
| Seattle | 11 |
| Gurgaon | 10 |
| Lima | 9 |
| Central | 8 |
| Herzogenrath | 8 |
| Norwalk | 8 |
| San Francisco | 8 |
| Santa Cruz | 8 |
| Woodbridge | 8 |
| Dong Ket | 7 |
| Ashburn | 6 |
| Berlin | 6 |
| Bryanston | 6 |
| Chulmleigh | 6 |
| Clarks Summit | 6 |
| Hsinchu | 6 |
| Leicester | 6 |
| University Park | 6 |
| Fairfield | 5 |
| Houston | 5 |
| Mountain View | 5 |
| Sheffield | 5 |
| Singapore | 5 |
| Cambridge | 4 |
| Genoa | 4 |
| Santiago | 4 |
| Taipei | 4 |
| Wuhan | 4 |
| Auckland | 3 |
| Barcelona | 3 |
| Bogotá | 3 |
| Buffalo | 3 |
| Central District | 3 |
| Columbia | 3 |
| Durban | 3 |
| Frankfurt am Main | 3 |
| Gladwin | 3 |
| Izmir | 3 |
| Jakarta | 3 |
| Karlsruhe | 3 |
| Krakow | 3 |
| London | 3 |
| Los Angeles | 3 |
| Meknès | 3 |
| Nottingham | 3 |
| Putignano | 3 |
| Saint-Ouen-du-Tilleul | 3 |
| San Martino Buon Albergo | 3 |
| Taichung | 3 |
| Valencia | 3 |
| Amsterdam | 2 |
| Bangkok | 2 |
| Belgrade | 2 |
| Birmingham | 2 |
| Bornova | 2 |
| Bremen | 2 |
| Cluj-napoca | 2 |
| Dongjak-gu | 2 |
| Florianópolis | 2 |
| Frankenthal | 2 |
| Gandra | 2 |
| Genova | 2 |
| Hebei | 2 |
| Hefei | 2 |
| Hellevoetsluis | 2 |
| Helsinki | 2 |
| Ho Chi Minh City | 2 |
| Juan-les-pins | 2 |
| Kota Kinabalu | 2 |
| Kumar | 2 |
| Lake Forest | 2 |
| Liverpool | 2 |
| Memphis | 2 |
| Milan | 2 |
| Mumbai | 2 |
| Mérignac | 2 |
| Osaka | 2 |
| Richmond | 2 |
| Rotterdam | 2 |
| Seoul | 2 |
| Shenyang | 2 |
| Shenzhen | 2 |
| Tianjin | 2 |
| Wilmington | 2 |
| Zaventem | 2 |
| Aachen | 1 |
| Adelaide | 1 |
| Alessandria | 1 |
| Ann Arbor | 1 |
| Athens | 1 |
| Atlanta | 1 |
| Bangalore | 1 |
| Totale | 574 |
| Nome | # |
|---|---|
| Prediction of late/early arrivals in container terminals - A qualitative approach, file e2f56ed5-ae75-3eaf-e053-3a05fe0a5d97 | 387 |
| Managing vessel arrival uncertainty in container terminals: a machine learning approach, file e2f56ed8-499b-3eaf-e053-3a05fe0a5d97 | 324 |
| Port Cooperation Policies in the Mediterranean Basin: an Experimental Approach using Cluster Analysis, file e2f56ed5-ab97-3eaf-e053-3a05fe0a5d97 | 165 |
| Design and optimisation of an innovative two-hub-and-spoke network for the Mediterranean short-sea-shipping market, file e2f56ed9-71b9-3eaf-e053-3a05fe0a5d97 | 12 |
| A data mining approach to forecast late arrivals in a transhipment container terminal, file e2f56ed5-a253-3eaf-e053-3a05fe0a5d97 | 8 |
| Prediction of arrival times and human resources allocation for container terminal, file e2f56ed3-c520-3eaf-e053-3a05fe0a5d97 | 3 |
| A bus allocation model for major industrial disasters, file e2f56ed6-8b27-3eaf-e053-3a05fe0a5d97 | 2 |
| Totale | 901 |
| Categoria | # |
|---|---|
| all - tutte | 1.878 |
| article - articoli | 0 |
| book - libri | 0 |
| conference - conferenze | 0 |
| curatela - curatele | 0 |
| other - altro | 0 |
| patent - brevetti | 0 |
| selected - selezionate | 0 |
| volume - volumi | 0 |
| Totale | 1.878 |
| Totale | Lug | Ago | Sett | Ott | Nov | Dic | Gen | Feb | Mar | Apr | Mag | Giu | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 2018/2019 | 3 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 2 | 1 |
| 2019/2020 | 58 | 3 | 3 | 1 | 3 | 4 | 5 | 5 | 6 | 7 | 10 | 6 | 5 |
| 2020/2021 | 222 | 3 | 10 | 3 | 44 | 43 | 16 | 18 | 14 | 12 | 18 | 15 | 26 |
| 2021/2022 | 237 | 11 | 8 | 25 | 14 | 41 | 27 | 13 | 15 | 25 | 15 | 15 | 28 |
| 2022/2023 | 130 | 26 | 10 | 29 | 2 | 1 | 4 | 10 | 0 | 9 | 8 | 23 | 8 |
| 2023/2024 | 105 | 4 | 8 | 18 | 4 | 4 | 21 | 7 | 14 | 5 | 10 | 10 | 0 |
| Totale | 901 | ||||||||||||