LEADER 03625nam 2200349 450 001 9910412272203321 005 20230830152541.0 024 7 $a10.5555/1065226 035 $a(CKB)5280000000244240 035 $a(NjHacI)995280000000244240 035 $a(EXLCZ)995280000000244240 100 $a20230830d2005 uy 0 101 0 $aeng 135 $aur||||||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aProceedings of the 2005 national conference on Digital government research /$fLois Delcambre, Genevieve Giuliano 210 1$aMarina Del Rey, CA :$cDigital Government Society of North America,$d2005. 215 $a1 online resource (346 pages) $cillustrations (some color) 330 $aIt is a pleasure to welcome you to 2005 National Digital Government Research Conference, dg.o2005. dg.o brings together computer and social science researchers, government professionals, representatives of industry, and members of the public to discuss how research in information strategies, policies, and technologies can improve government operations and public services.This year we were very pleased to host two keynote talks and one keynote panel. Our opening keynote speaker on Monday morning is Neil Eisner, the Assistant General Counsel for Regulation and Enforcement at the U.S. Department of Transportation. His talk, entitled "Digital Dreams: The Future of E-Government," focuses on government's use of technology and how future research can contribute to even more effective digital government.Our keynote panel in the opening session on Tuesday morning is entitled "Digital Government Research in the Academy." It discusses issues regarding applied and interdisciplinary research in academia, including how faculty are evaluated in the promotion and tenure processes, the extent to which digital government represents an emerging field of interdisciplinary research, the role of applied research, and the challenges of promoting interdisciplinary research in the academy.This year we continue the NSF Project Highlights track, where NSF-funded digital government research projects are presented. The NSF Project Highlight presentations are interspersed with accepted research papers, grouped by application domain.Monday evening we have our poster and demonstration sessions, continuing our tradition of indepth informal discussion of demos and posters accompanied by informal conversation and good food. This has become a very successful venue to showcase the potential of digital government research in a wide variety of areas and to encourage new research projects and partnerships.The conference continues to grow as evidenced by submissions, which this year include 45 Project Highlights, 10 demonstrations, 11 poster submissions, and 40 research papers, of which 15 regular research papers and 3 student research papers were accepted. The program is complemented by 3 invited demonstrations and talks, 50 posters and demonstrations, and 5 Birds of a Feather Meetings. Conference presentations feature both information technology and social science perspectives, as they contribute to pressing public sector challenges. 606 $aElectronic government information$vCongresses 615 0$aElectronic government information 676 $a352.3802854678 700 $aDelcambre$b Lois$01421487 702 $aGiuliano$b Genevieve 801 0$bNjHacI 801 1$bNjHacl 906 $aBOOK 912 $a9910412272203321 996 $aProceedings of the 2005 national conference on Digital government research$93542893 997 $aUNINA LEADER 04535nam 2201165z- 450 001 9910580212403321 005 20220706 035 $a(CKB)5690000000011964 035 $a(oapen)https://directory.doabooks.org/handle/20.500.12854/87527 035 $a(oapen)doab87527 035 $a(EXLCZ)995690000000011964 100 $a20202207d2022 |y 0 101 0 $aeng 135 $aurmn|---annan 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 00$aAdvances in Artificial Intelligence: Models, Optimization, and Machine Learning 210 $aBasel$cMDPI - Multidisciplinary Digital Publishing Institute$d2022 215 $a1 online resource (362 p.) 311 08$a3-0365-4515-8 311 08$a3-0365-4516-6 330 $aThe present book contains all the articles accepted and published in the Special Issue "Advances in Artificial Intelligence: Models, Optimization, and Machine Learning" of the MDPI Mathematics journal, which covers a wide range of topics connected to the theory and applications of artificial intelligence and its subfields. These topics include, among others, deep learning and classic machine learning algorithms, neural modelling, architectures and learning algorithms, biologically inspired optimization algorithms, algorithms for autonomous driving, probabilistic models and Bayesian reasoning, intelligent agents and multiagent systems. We hope that the scientific results presented in this book will serve as valuable sources of documentation and inspiration for anyone willing to pursue research in artificial intelligence, machine learning and their widespread applications. 517 $aAdvances in Artificial Intelligence 606 $aMathematics and Science$2bicssc 606 $aResearch and information: general$2bicssc 610 $a.NET framework 610 $aadaptive sampling 610 $aagent algorithms 610 $aagent-based systems 610 $aanimal-inspired 610 $aapplied machine learning 610 $aapproximate differential optimization 610 $aautonomous driving 610 $aclass imbalance 610 $aclassification 610 $aclassification and regression 610 $acombinatorics 610 $acomputational complexity 610 $adata mining 610 $adeep learning 610 $adeep neural networks 610 $aDeepFKTNet 610 $adefect classification 610 $adistance metrics 610 $adistributed W-learning 610 $adynamic programming algorithm 610 $aengineering informatics 610 $aensemble model 610 $aevolutionary algorithm 610 $aexploitation 610 $aexploration 610 $afree radical polymerization 610 $agender-based violence in Mexico 610 $agenerative adversarial networks 610 $agraph neural network 610 $ahot rolled strip steel 610 $ahyperparameters 610 $aimage classification 610 $ainference 610 $ainstance-based learning 610 $aintelligent transport systems 610 $ainteroperability 610 $ak-nearest neighbor 610 $aknockout tournament 610 $alarge margin nearest neighbor regression 610 $amachine learning 610 $ametaheuristics 610 $amulti-agent framework 610 $amulti-agent systems 610 $amultiple point hill climbing 610 $amultisensory fingerprint 610 $an/a 610 $aobject tracking 610 $aoptimization 610 $aplastic bottle 610 $aprototypes 610 $areinforcement learning 610 $asimulations 610 $asoftware design 610 $aspatial-temporal variable speed limit 610 $astochastic methods 610 $asurface defects 610 $atraffic control 610 $atrajectory prediction 610 $atransfer learning 610 $atwitter messages 610 $aurban motorways 615 7$aMathematics and Science 615 7$aResearch and information: general 700 $aLeon$b Florin$4edt$01297586 702 $aHulea$b Mircea$4edt 702 $aGavrilescu$b Marius$4edt 702 $aLeon$b Florin$4oth 702 $aHulea$b Mircea$4oth 702 $aGavrilescu$b Marius$4oth 906 $aBOOK 912 $a9910580212403321 996 $aAdvances in Artificial Intelligence: Models, Optimization, and Machine Learning$93024578 997 $aUNINA