LEADER 01396nas0-2200385---450- 001 990001108280203316 005 20021125140453.0 035 $a000110828 035 $aUSA01000110828 035 $a(ALEPH)000110828USA01 035 $a000110828 100 $a20021125b1999----km-y0ITAy0103----ba 101 $afre 101 $aeng 102 $aFR 110 $aafri---|||| 200 1 $aMonthly statistics of foreign trade$fOECD Department of economics and statistics$dStatistiques mensuelles du commerce extérieur / Department des affaires économiques et statistiques, OCDE 210 $aParis$cOrganization for economic cooperation and development$d-Dec.1999 215 $a17 v.$cill.$d27 cm 225 $aOECD statistics 300 $aComincia nel 1983 e cessa nel 1999 300 $aDescrizione basata su: Dec. 1999 326 $aMensile 430 1$1001$12001$aStatistics of foreign trade. Monthly bulletin 440 1$1001000110823$12001$aMonthly statistics of international trade 606 0 $aStatistiche commerciali$xPeriodici 676 $a382.0212 801 0$aIT$bsalbc$gISBD 912 $a990001108280203316 958 $aECO$bSala OCDE$c1983-1999; scompleti 1983,1986,1990. 959 $aSE 979 $aANNAPIA$b90$c20021125$lUSA01$h1404 979 $aPATRY$b90$c20040406$lUSA01$h1717 996 $aMonthly statistics of foreign trade$9981003 997 $aUNISA LEADER 00991cam a2200277 i 4500 001 991003789759707536 008 080711t2003 gw 00 eng d 020 $a3540401539 035 $ab13752303-39ule_inst 040 $aSet. Economia$bita 082 $a332 100 1 $aRao, P. K$0149190 245 10$aDevelopment finance /$cP. K. Rao 260 $aBerlin [etc.] :$bSpringer,$cc2003 300 $axvi, 209 p. ;$c25 cm 504 $aCon bibliografia 650 04$aCredito$zPaesi in via di sviluppo 650 04$aFinanza e sviluppo economico 650 4$aPaesi in via di sviluppo$xFinanziamenti 650 04$aDebito estero$zPaesi in via di sviluppo 907 $a.b13752303$b18-05-18$c11-07-08 912 $a991003789759707536 945 $aLE025 ECO 332 RAO01.01$g1$i2025000112391$lle025$nCatalogato 2018$o-$pE0.00$q-$rl$s- $t0$u0$v0$w0$x0$y.i14800445$z11-07-08 996 $aDevelopment finance$91226868 997 $aUNISALENTO 998 $ale025$b11-07-08$cm$da $e-$feng$ggw $h0$i0 LEADER 05520nam 22005175 450 001 9910874665903321 005 20251225202113.0 010 $a3-031-63989-8 024 7 $a10.1007/978-3-031-63989-0 035 $a(MiAaPQ)EBC31534741 035 $a(Au-PeEL)EBL31534741 035 $a(CKB)33063733800041 035 $a(DE-He213)978-3-031-63989-0 035 $a(EXLCZ)9933063733800041 100 $a20240719d2024 u| 0 101 0 $aeng 135 $aurcnu|||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aMobile and Ubiquitous Systems: Computing, Networking and Services $e20th EAI International Conference, MobiQuitous 2023, Melbourne, VIC, Australia, November 14?17, 2023, Proceedings, Part I /$fedited by Arkady Zaslavsky, Zhaolong Ning, Vana Kalogeraki, Dimitrios Georgakopoulos, Panos K. Chrysanthis 205 $a1st ed. 2024. 210 1$aCham :$cSpringer Nature Switzerland :$cImprint: Springer,$d2024. 215 $a1 online resource (559 pages) 225 1 $aLecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering,$x1867-822X ;$v593 311 08$a3-031-63988-X 327 $a -- Tracking and Detection. -- NoD: Lightweight Continuous Neighbor Discovery on Everyday Devices. -- Decentralized Collaborative Inertial Tracking. -- High-Performance Features in Generalizable Fingerprint- based Indoor Positioning. -- SCORE: Scalable Contact Tracing Over Uncertain Trajectories. -- IoT. -- FaultBit : Generic and E?icient Wireless Fault Detection Using the Internet of Things. -- DeepHeteroIoT: Deep Local and Global Learning over Heterogeneous IoT Sensor Data. -- Federated Reinforcement Learning for Automated LoRaWAN Management in Industrial IoT. -- A Hybrid Approach to Monitor Context Parameters for Optimising Caching for Context-Aware IoT Applications. -- LOADHoC: Towards the Automatic local Distribution of Computation using Existing IoT Devices. -- E-Go Bicycle Intelligent Speed Adaptation System for Catching the Green Light. -- Federated Learning. -- FedGCS: Addressing Class Imbalance in Long-Tail Federated Learning. -- FedRC: Representational Consistency Guided Model Uploading Mechanism for Asynchronous Federated Learning. -- RADEAN: A Resource Allocation Model Based on Deep Reinforcement Learning and Generative Adversarial Networks in Edge Computing. -- Networks. -- A Stream Data Service Framework for Real-time Vehicle Companion Discovery. -- KS-Autoformer: An Autoformer-based SOC Prediction Framework for Electric Vehicles. -- Deep Reinforcement Learning-based Multi-Node Collaborative Task Offloading Optimization in 6G Space-Air-Ground Integrated Networks. -- Securing Wireless Communication in Critical Infrastructure: Challenges and Opportunities. -- Activity Recognition. -- Cross-user activity recognition via temporal relation optimal transport. -- SelfAct: Personalized Activity Recognition based on Self-Supervised and Active Learning. -- A Novel Method for Wearable Activity Recognition with Feature Evolvable Streams. -- Let?s Vibrate with Vibration: Augmenting Structural Engineering with Low-Cost Vibration Sensing. -- Security Management. -- Research on Data Drift and Class Imbalance in Android Malware detection. -- Reputation-based Dissemination of Trustworthy Information in VANETs. -- Reputation Systems for Supply Chains: The Challenge of Achieving Privacy Preservation. -- Data Management in Appendable-block Blockchains: A Case Study for IT Life-cycle Management. -- Exploiting the Potential Anomaly Detection in Automobile Safety Data with Multi-type Neural Network. -- Urban/Mobile Crowdsensing. -- HAUM3: A Height Aware Urban Map Matching Mechanism. -- A resource-e?icient approach of GNSS activation for pedestrian monitoring. 330 $aThese two-volume proceedings constitute the refereed post-conference proceedings of the 20th EAI International Conference on Mobile and Ubiquitous Systems: Computing, Networking and Services, MobiQuitous 2023, held in Melbourne, Australia, during November 14-17, 2023. The 65 papers presented in these proceedings were carefully reviewed and selected from 161 submissions. The conference papers are organized in topical sections on: Part I - Tracking and Detection; IoT; Federated learning; Networks; Activity recognition; Security Management; Urban/Mobile Crowdsensing. Part II - Urban/Mobile Crowdsensing; Edge computing; Crowdsourcing, Platforms and localization; Activity recognition and prediction; AI and machine learning; Mobile edge and fog computing; Mobile augmented reality and applications for mobile computing; interaction technologies; AutoQuitous workshop. 410 0$aLecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering,$x1867-822X ;$v593 606 $aComputer networks 606 $aComputer Communication Networks 615 0$aComputer networks. 615 14$aComputer Communication Networks. 676 $a004.6 700 $aZaslavsky$b Arkady$0858779 701 $aNing$b Zhaolong$01749248 701 $aKalogeraki$b Vana$01749249 701 $aGeorgakopoulos$b Dimitrios$01711768 701 $aChrysanthis$b Panos K$0963731 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910874665903321 996 $aMobile and Ubiquitous Systems: Computing, Networking and Services$94253429 997 $aUNINA