LEADER 01093nam a2200289 a 4500 001 991003554269707536 008 180423s1995 nyua b 001 0 eng d 020 $a0471009733 035 $ab14351274-39ule_inst 040 $aBibl. Dip.le Aggr. Matematica e Fisica - Sez. Fisica$beng 082 04$a515/.078$220 084 $aLC QA303.5.D37 100 1 $aHarris, Kent$0785649 245 10$aDiscovering calculus with Maple /$cKent Harris, Robert J. Lopez 250 $a2nd ed. 260 $aNew York :$bJ. Wiley,$cc1995 300 $a344 p. :$bill. ;$c26 cm 504 $aIncludes bibliographical references (p. 341) and index 650 4$aCalculus$xData processing 650 4$aMaple (Computer file) 700 1 $aLopez, Robert J. 907 $a.b14351274$b08-10-18$c08-10-18 912 $a991003554269707536 945 $aLE006 Fondo Soliani 109$cEx libris Giulio Soliani$g1$i2006000180627$lle006$og$pE37.50$q-$rn$s- $t1$u0$v0$w0$x0$y.i15863220$z08-10-18 996 $aDiscovering calculus with Maple$91749127 997 $aUNISALENTO 998 $ale006$b23-04-18$cm$da $e $feng$gnyu$h0$i0 LEADER 01446nam a22003011i 4500 001 991002081329707536 005 20040126133510.0 008 040407s1977 it a||||||||||||||||ita 035 $ab12867913-39ule_inst 035 $aARCHE-084753$9ExL 040 $aDip.to Scienze Storiche$bita$cA.t.i. Arché s.c.r.l. Pandora Sicilia s.r.l. 082 04$a325 100 1 $aBellencin Meneghel, Giovanna$0129737 245 10$aContributi geografici allo studio dei fenomeni migratori in Italia :$banalisi di due comuni campione delle Prealpi Giulie : Lusevera e Savogna /$cGiovanna Bellencin Meneghel, Franca Battigelli ; prefazione di Giorgio Valussi 260 $aPisa :$bPacini,$c1977 300 $a182 p. :$bill. ;$c25 cm 500 $aIn testa al front.: Facoltà di lingue e letterature straniere della Università di Trieste, sede di Udine 650 4$aEmigrazione$xLusevera 650 4$aEmigrazione$xSavogna 650 4$aEmigrazione$zUdine 700 1 $aBattigelli, Franca$eauthor$4http://id.loc.gov/vocabulary/relators/aut$0271918 700 1 $aValussi, Giorgio 907 $a.b12867913$b02-04-14$c16-04-04 912 $a991002081329707536 945 $aLE009 GEOG.14.414-66$g1$i2009000161481$lle009$o-$pE0.00$q-$rl$s- $t0$u0$v0$w0$x0$y.i13428767$z16-04-04 996 $aContributi geografici allo studio dei fenomeni migratori in Italia$91448601 997 $aUNISALENTO 998 $ale009$b16-04-04$cm$da $e-$fita$git $h0$i1 LEADER 04583nam 2201345z- 450 001 9910557613103321 005 20220321 035 $a(CKB)5400000000045271 035 $a(oapen)https://directory.doabooks.org/handle/20.500.12854/79603 035 $a(oapen)doab79603 035 $a(EXLCZ)995400000000045271 100 $a20202203d2022 |y 0 101 0 $aeng 135 $aurmn|---annan 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 00$aAdvances in Computational Intelligence Applications in the Mining Industry 210 $aBasel$cMDPI - Multidisciplinary Digital Publishing Institute$d2022 215 $a1 online resource (324 p.) 311 08$a3-0365-3159-9 311 08$a3-0365-3158-0 330 $aThis book captures advancements in the applications of computational intelligence (artificial intelligence, machine learning, etc.) to problems in the mineral and mining industries. The papers present the state of the art in four broad categories: mine operations, mine planning, mine safety, and advances in the sciences, primarily in image processing applications. Authors in the book include both researchers and industry practitioners. 606 $aHistory of engineering & technology$2bicssc 606 $aTechnology: general issues$2bicssc 610 $aaccidents 610 $aartificial intelligence 610 $aball mill throughput 610 $aBayesian network 610 $aBayesian Network Structure Learning (BNSL) 610 $abitumen extraction 610 $abitumen processability 610 $ablast impact 610 $abluetooth beacon 610 $aclassification and regression tree 610 $acoal 610 $aconvolutional neural networks 610 $adamage risk analysis 610 $adata analytics in mining 610 $adecision trees 610 $adigital twin 610 $adimensionality reduction 610 $adiscrete event simulation 610 $aempirical model 610 $aepithermal gold 610 $afragmentation 610 $afragmentation size analysis 610 $agaussian nai?ve bayes 610 $ageological uncertainty 610 $ageostatistics 610 $agrinding circuits 610 $ahealth and safety management 610 $ahyperspectral imaging 610 $aimage analysis 610 $ak-nearest neighbors 610 $aknowledge discovery 610 $amacerals 610 $amachine learning 610 $amasonry buildings 610 $ameasurement while drilling 610 $amine optimization 610 $amine safety and health 610 $amine worker fatigue 610 $amine-to-mill 610 $amineral prospectivity mapping 610 $aminerals processing 610 $amining 610 $amining equipment uncertainties 610 $amining exploitation 610 $amining geology 610 $amodes of operation 610 $amultispectral imaging 610 $amultivariate statistics 610 $an/a 610 $aNaive Bayes 610 $anarratives 610 $anatural language processing 610 $aneighbourhood component analysis 610 $anon-additivity 610 $aoil sands 610 $aoperational data 610 $aore control 610 $aorebody uncertainty 610 $apartial least squares regression 610 $apetrographic analysis 610 $apoint cloud scaling 610 $aQ-learning 610 $arandom forest 610 $arandom forest algorithm 610 $arandom forest classification 610 $arandom forest model 610 $arock type 610 $asemantic segmentation 610 $astockpiles 610 $astructure from motion 610 $asupport vector machine 610 $atactical geometallurgy 610 $atransport route 610 $atransport time 610 $atruck dispatching 610 $aunderground mine 610 $aunstructured data 610 $avariable importance 615 7$aHistory of engineering & technology 615 7$aTechnology: general issues 700 $aGanguli$b Rajive$4edt$01314875 702 $aDessureault$b Sean$4edt 702 $aRogers$b Pratt$4edt 702 $aGanguli$b Rajive$4oth 702 $aDessureault$b Sean$4oth 702 $aRogers$b Pratt$4oth 906 $aBOOK 912 $a9910557613103321 996 $aAdvances in Computational Intelligence Applications in the Mining Industry$93032078 997 $aUNINA