LEADER 05927nam 22008535 450 001 996466234203316 005 20200629172326.0 010 $a3-540-25929-5 024 7 $a10.1007/b97961 035 $a(CKB)1000000000212395 035 $a(DE-He213)978-3-540-25929-9 035 $a(SSID)ssj0000239677 035 $a(PQKBManifestationID)11174008 035 $a(PQKBTitleCode)TC0000239677 035 $a(PQKBWorkID)10240407 035 $a(PQKB)10632446 035 $a(MiAaPQ)EBC3087816 035 $a(PPN)155199870 035 $a(EXLCZ)991000000000212395 100 $a20121227d2004 u| 0 101 0 $aeng 135 $aurnn#008mamaa 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aRough Sets and Current Trends in Computing$b[electronic resource] $e4th International Conference, RSCTC 2004, Uppsala, Sweden, June 1-5, 2004, Proceedings /$fedited by Shusaku Tsumoto, Roman Slowi?ski, Jan Komorowski, Jerzy W. Grzymala-Busse 205 $a1st ed. 2004. 210 1$aBerlin, Heidelberg :$cSpringer Berlin Heidelberg :$cImprint: Springer,$d2004. 215 $a1 online resource (XX, 860 p.) 225 1 $aLecture Notes in Artificial Intelligence ;$v3066 300 $aBibliographic Level Mode of Issuance: Monograph 311 $a3-540-22117-4 320 $aIncludes bibliographical references and index. 327 $aPlenary Papers -- Theory -- Logic and Rough Sets -- Granular Computing -- Rough and Fuzzy Relations -- Foundations of Data Mining -- Incomplete Information Systems -- Interestingness -- Multiagents and Information Systems -- Fuzzy Logic and Modeling -- Rough Classification -- Rough Sets and Probabilities -- Variable Precision Rough Set Model -- Spatial Reasoning -- Reduction -- Rule Induction -- Rough Sets and Neural Network -- Clustering -- Data Mining -- Image and Signal Recognition -- Information Retrieval -- Decision Support -- Adaptive and Opminization Methods -- Bioinformatics -- Medical Applications -- Bibliography Project of International Rough Set Society. 330 $aIn recent years rough set theory has attracted the attention of many researchers and practitioners all over the world, who have contributed essentially to its development and applications. Weareobservingagrowingresearchinterestinthefoundationsofroughsets, including the various logical, mathematical and philosophical aspects of rough sets. Some relationships have already been established between rough sets and other approaches, and also with a wide range of hybrid systems. As a result, rough sets are linked with decision system modeling and analysis of complex systems, fuzzy sets, neural networks, evolutionary computing, data mining and knowledge discovery, pattern recognition, machine learning, and approximate reasoning. In particular, rough sets are used in probabilistic reasoning, granular computing (including information granule calculi based on rough mereology), intelligent control, intelligent agent modeling, identi?cation of autonomous s- tems, and process speci?cation. Methods based on rough set theory alone or in combination with other - proacheshavebeendiscoveredwith awide rangeofapplicationsinsuchareasas: acoustics, bioinformatics, business and ?nance, chemistry, computer engineering (e.g., data compression, digital image processing, digital signal processing, p- allel and distributed computer systems, sensor fusion, fractal engineering), de- sion analysis and systems, economics, electrical engineering (e.g., control, signal analysis, power systems), environmental studies, informatics, medicine, mole- lar biology, musicology, neurology, robotics, social science, software engineering, spatial visualization, Web engineering, and Web mining. 410 0$aLecture Notes in Artificial Intelligence ;$v3066 606 $aComputers 606 $aArtificial intelligence 606 $aMathematical logic 606 $aOptical data processing 606 $aDatabase management 606 $aApplication software 606 $aTheory of Computation$3https://scigraph.springernature.com/ontologies/product-market-codes/I16005 606 $aArtificial Intelligence$3https://scigraph.springernature.com/ontologies/product-market-codes/I21000 606 $aMathematical Logic and Formal Languages$3https://scigraph.springernature.com/ontologies/product-market-codes/I16048 606 $aImage Processing and Computer Vision$3https://scigraph.springernature.com/ontologies/product-market-codes/I22021 606 $aDatabase Management$3https://scigraph.springernature.com/ontologies/product-market-codes/I18024 606 $aInformation Systems Applications (incl. Internet)$3https://scigraph.springernature.com/ontologies/product-market-codes/I18040 615 0$aComputers. 615 0$aArtificial intelligence. 615 0$aMathematical logic. 615 0$aOptical data processing. 615 0$aDatabase management. 615 0$aApplication software. 615 14$aTheory of Computation. 615 24$aArtificial Intelligence. 615 24$aMathematical Logic and Formal Languages. 615 24$aImage Processing and Computer Vision. 615 24$aDatabase Management. 615 24$aInformation Systems Applications (incl. Internet). 676 $a004 702 $aTsumoto$b Shusaku$4edt$4http://id.loc.gov/vocabulary/relators/edt 702 $aSlowi?ski$b Roman$4edt$4http://id.loc.gov/vocabulary/relators/edt 702 $aKomorowski$b Jan$4edt$4http://id.loc.gov/vocabulary/relators/edt 702 $aGrzymala-Busse$b Jerzy W$4edt$4http://id.loc.gov/vocabulary/relators/edt 712 02$aLINK (Online service) 712 12$aRSCTC 2004 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a996466234203316 996 $aRough Sets and Current Trends in Computing$9772414 997 $aUNISA LEADER 04080nam 22009493a 450 001 9910367752103321 005 20250203235429.0 010 $a9783039215959 010 $a3039215957 024 8 $a10.3390/books978-3-03921-595-9 035 $a(CKB)4100000010106196 035 $a(oapen)https://directory.doabooks.org/handle/20.500.12854/53374 035 $a(ScCtBLL)a74b933b-ebd3-4ac3-92ff-f2ec721cac3e 035 $a(OCoLC)1163850973 035 $a(oapen)doab53374 035 $a(EXLCZ)994100000010106196 100 $a20250203i20192019 uu 101 0 $aeng 135 $aurmn|---annan 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 00$aMicro- and Nanofluidics for Bionanoparticle Analysis$fYong Zeng, Xuanhong Cheng 210 $cMDPI - Multidisciplinary Digital Publishing Institute$d2019 210 1$aBasel, Switzerland :$cMDPI,$d2019. 215 $a1 electronic resource (138 p.) 311 08$a9783039215942 311 08$a3039215949 330 $aBionanoparticles such as microorganisms and exosomes are recoganized as important targets for clinical applications, food safety, and environmental monitoring. Other nanoscale biological particles, includeing liposomes, micelles, and functionalized polymeric particles are widely used in nanomedicines. The recent deveopment of microfluidic and nanofluidic technologies has enabled the separation and anslysis of these species in a lab-on-a-chip platform, while there are still many challenges to address before these analytical tools can be adopted in practice. For example, the complex matrices within which these species reside in create a high background for their detection. Their small dimension and often low concentration demand creative strategies to amplify the sensing signal and enhance the detection speed. This Special Issue aims to recruit recent discoveries and developments of micro- and nanofluidic strategies for the processing and analysis of biological nanoparticles. The collection of papers will hopefully bring out more innovative ideas and fundamental insights to overcome the hurdles faced in the separation and detection of bionanoparticles. 606 $aHistory of engineering and technology$2bicssc 610 $amagnetic field 610 $amicrofluidic device 610 $aballpoint pen printing 610 $apaper-based microfluidic device 610 $aonline analysis 610 $ananoporous membrane 610 $adielectric film 610 $adigital microfluidic chip 610 $aHIV diagnostics 610 $aprecipitation 610 $aoptically induced dielectrophoresis (ODEP) 610 $adigital microfluidic device 610 $afluorescence 610 $aferrofluids 610 $acancer metastasis 610 $aflow focusing 610 $aimage processing 610 $aelectrowetting 610 $alight diffraction 610 $alensfree 610 $ananoparticle characterization 610 $amulti-step assay 610 $acell isolation 610 $abiomarker detection 610 $amicroparticles 610 $aconductive electrode 610 $asingle particle analysis 610 $aplastic wrap 610 $asecond-hand smoke 610 $aflow control 610 $asurface acoustic wave 610 $adroplet actuation 610 $acirculating tumour cells (CTCs) 610 $alipid nanoparticles 610 $acrop disease 610 $across-flow filtration 610 $aoxidized hollow mesoporous carbon nanosphere 610 $amicrofluidic systems 610 $a3-ethenylpyridine 610 $amicrofluidic 610 $amicrofluidics 610 $aCOMSOL 610 $aplug flow mixer 615 7$aHistory of engineering and technology 700 $aZeng$b Yong$01309854 702 $aCheng$b Xuanhong 801 0$bScCtBLL 801 1$bScCtBLL 906 $aBOOK 912 $a9910367752103321 996 $aMicro- and Nanofluidics for Bionanoparticle Analysis$93029656 997 $aUNINA