LEADER 05321nam 2200661 a 450 001 9910830999903321 005 20230829010331.0 010 $a3-527-66037-2 010 $a1-280-66351-0 010 $a9786613640444 010 $a3-527-66095-X 010 $a3-527-60902-4 035 $a(CKB)1000000000376057 035 $a(EBL)865038 035 $a(SSID)ssj0000354489 035 $a(PQKBManifestationID)11249036 035 $a(PQKBTitleCode)TC0000354489 035 $a(PQKBWorkID)10314032 035 $a(PQKB)10376186 035 $a(MiAaPQ)EBC865038 035 $a(OCoLC)85820795 035 $a(EXLCZ)991000000000376057 100 $a20120206d2006 uy 0 101 0 $ager 135 $aur|n|---||||| 181 $ctxt 182 $cc 183 $acr 200 00$aMiniplant-technik$b[electronic resource] $ein der Prozessindustrie /$fLudwig Deibele, Ralf Dohrn (Hrsg.) 210 $aWeinheim $cWiley-VCH$d2006 215 $a1 online resource (452 p.) 300 $aDescription based upon print version of record. 311 $a3-527-30739-7 320 $aIncludes bibliographical references and index. 327 $aTitlePage; Inhaltsverzeichnis; Vorwort; 1 Der Weg zur Miniplant-Technik - ein historischer Uumalberblick; 2 Grundsaumaltze der Miniplant-Technik; 2.1 Gruumalnde fuumalr Laborversuche; 2.2 Anforderungen an die Miniplant-Technik; 2.3 Vorteile von Miniplant-Anlagen gegenuumlaber Technikumsanlagen; 2.4 Apparate- und Verfahrens-Scale-up; 3 Voraussetzungen zum Bau von Anlagen der Miniplant-Technik; 3.1 Arbeitsumfeld; 3.1.1 Arbeitsraum; 3.1.2 Einrichtung und Ausstattung; 3.1.3 Be- und Entluumalftung; 3.1.4 Energieversorgung; 3.1.5 Nebenraumalume; 3.1.6 Lager; 3.2 Werkstoffe 327 $a3.2.1 Grundwerkstoff Borosilicatglas 3.33.2.1.1 Chemische Bestaumalndigkeit; 3.2.1.2 Physikalische Eigenschaften; 3.2.1.3 Mechanische Eigenschaften; 3.2.1.4 Optische Eigenschaften; 3.2.1.5 Zulaumalssige Betriebsdaten; 3.2.2 Kombinationswerkstoffe; 3.2.2.1 Chrom-Nickel-Legierungen; 3.2.2.2 Sondermetalle; 3.2.2.3 Stahl/Emaille; 3.2.2.4 Stahl/PTFE; 3.2.2.5 Quarzglas; 3.2.2.6 Keramik; 3.2.2.7 Grafit; 3.2.2.8 Fluorkunststoffe und technische Kunststoffe; 3.2.3. Dichtungs- und Lagerwerkstoffe; 3.2.3.1 Fluorierte Kunststoffe; 3.2.3.2 Keramik; 3.2.3.3 Grafit; 3.2.3.4 Metalle 327 $a3.2.4. Beschichtungs- und Faumalrbewerkstoffe3.3 Baukastenprinzip fuumalr Miniplant-Anlagen; 3.3.1 Technische Merkmale; 3.3.1.1 Verbindungselemente; 3.3.1.2 Armaturen; 3.3.1.3 Konstruktionsmerkmale fuumalr Bauteile; 3.3.2 Bauteile; 3.3.2.1 Produkt- und Betriebsmittelleitungen; 3.3.2.2 Armaturen; 3.3.2.3 Gefaumalbe/Ruumalhrwerke; 3.3.2.4 Waumalrmeuumalbertrager; 3.3.2.5 Kolonnenbauteile; 3.3.2.6 Pumpen und Ventile; 3.3.2.7 Mess- und Regelgeraumalte; 3.3.2.8 Verbindungen; 3.3.2.9 Gestelle und Halterungen; 3.3.3 Baugruppen; 3.3.3.1 Verdampfer; 3.3.3.2 Mischer-Scheide-Stufe 327 $a3.3.3.3 Absorptionsapparatur3.3.4 Module; 3.4 Steuerung und Regelung; 3.4.1 Anforderungen an die Automatisierung der Miniplant; 3.4.1.1 Einleitung; 3.4.1.2 Aufgaben; 3.4.1.3 Praxis der Automatisierungstechnik in F&E; 3.4.1.4 Einteilung der Geraumaltetechnik in Musterkategorien; 3.4.1.5 Besondere Anforderungen; 3.4.1.6 Verfahrenstechnische Anlage und Automatisierungssystem; 3.4.1.7 Fahrweisen; 3.4.1.8 Struktur des Automatisierungssystems; 3.4.2 Anforderungen an Systeme zur Rezeptfahrweise; 3.4.2.1 Die Elemente der Rezeptsteuerung; 3.4.3 Ein Automatisierungssystem fuumalr die Miniplant 327 $a3.4.3.1 Schnittstellen3.4.3.2 Automatisierungstechnische Grundfunktionen; 3.4.3.3 Rezeptursteuerung; 3.4.3.4 Instrumentierung; 3.4.3.5 Anwendungsorientierte Geraumaltebausteine; 3.4.3.6 Regler; 3.4.3.7 Sicherheit; 3.4.3.8 Das ABK-Betriebsprogramm; 3.4.4 Ein Anwendungsbeispiel; 3.5 Messdatenaufnehmer; 3.5.1 Einleitung; 3.5.2 Temperaturmessung; 3.5.3 Druckmessung; 3.5.4 Gewichtsmessung; 3.5.5 Fuumalllstandsund Grenzschichtmessung; 3.5.6 Durchflussmessung; 3.5.6.1 Massenfluss; 3.5.6.2 Volumenfluss; 3.5.7 Ruumalhrerdrehmoment; 3.5.8 Spezielle Messgroumalben 327 $a3.6 Sicherheitskonzept bei Miniplant-Versuchsanlagen 330 $aNur in Ausnahmefa?llen lassen sich technische Anlagen fu?r neue Produktionsverfahren der chemischen Industrie an Hand von Literaturdaten und rechnerischer Simulation entwickeln und auslegen. Der u?bliche Weg des Scale-up fu?hrt u?ber den Laborversuch und den anschließenden Aufbau einer Technikumsanlage zur technischen Großanlage.Die Miniplanttechnik ermo?glicht die Entwicklung technischer Anlagen in nur einem Schritt vom Labor zur funktionierenden Großanlage. Dabei werden alle Verfahrensschritte im kleinstmo?glichen Maßstab, der noch einen reproduzierbaren Dauerbetrieb erlaubt, als Gesamtverf 606 $aPlant engineering 606 $aManufacturing processes 606 $aProduction engineering 615 0$aPlant engineering. 615 0$aManufacturing processes. 615 0$aProduction engineering. 676 $a660.28 676 $a660/.28 701 $aDeibele$b Ludwig$01680020 701 $aDohrn$b Ralf$01680021 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910830999903321 996 $aMiniplant-technik$94048672 997 $aUNINA LEADER 09705nam 22007215 450 001 9910483361303321 005 20251226202438.0 010 $a3-642-04441-7 024 7 $a10.1007/978-3-642-04441-0 035 $a(MiAaPQ)EBC3064694 035 $a(PPN)139958762 035 $a(CKB)1000000000798297 035 $a(BIP)37160352 035 $a(DE-He213)978-3-642-04441-0 035 $a(EXLCZ)991000000000798297 100 $a20100301d2009 u| 0 101 0 $aeng 135 $aurnn#||8mamaa 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aComputational Collective Intelligence. Semantic Web, Social Networks and Multiagent Systems $eFirst International Conference, ICCCI 2009, Wroclaw, Poland, October 5-7, 2009, Proceedings /$fedited by Ryszard Kowalczyk 205 $a1st ed. 2009. 210 1$aBerlin, Heidelberg :$cSpringer Berlin Heidelberg :$cImprint: Springer,$d2009. 215 $axvii, 860p 225 1 $aLecture Notes in Artificial Intelligence,$x2945-9141 ;$v5796 320 $aIncludes bibliographical references and index. 327 $aKeynote Speeches -- Rough Set Approach to Knowledge Discovery about Preferences -- Toward a Self-referential Collective Intelligence Some Philosophical Background of the IEML Research Program -- A-Teams and Their Applications -- Collective Decision Making -- Local Search Algorithms for Core Checking in Hedonic Coalition Games -- Information Foraging Theory as a Form of Collective Intelligence for Social Search -- SAM: Semantic Argumentation Based Model for Collaborative Knowledge Creation and Sharing System -- A Conception for Modification of Learning Scenario in an Intelligent E-learning System -- Firefly Algorithm for Continuous Constrained Optimization Tasks -- Distributed Data Mining Methodology with Classification Model Example -- A Token-Based Mutual Exclusion Approach to Improve Collaboration in Distributed Environments -- Discovering Medical Knowledge from Data in Patients? Files -- Towards an Increase of Collective Intelligence within Organizations Using Trust and Reputation Models -- A New Ant Colony Optimization Algorithm with an Escape Mechanism for Scheduling Problems -- Recognizing Team Formations in Multiagent Systems: Applications in Robotic Soccer -- Semi-traces and Their Application in Concurrency Control Problem -- Design of the Directory Facilitator Supporting Fault-Tolerance in Multi-OSGi Agent System -- Multiagent Systems -- Agent-Based Provisioning of Group-Oriented Non-linear Telecommunication Services -- A Multi-agent Model of Deceit and Trust in Intercultural Trade -- Implementation of Epistemic Operators for Model Checking Multi-agent Systems -- Meta-game HOLOS as a Multi-agent Decision-Making Laboratory -- Agent-Based Computational Modeling of Emergent Collective Intelligence -- Fuzzy Cognitive and Social Negotiation Agent Strategy for Computational CollectiveIntelligence -- A Multi-agent Architecture for Multi-robot Surveillance -- Designing Social Agents with Empathic Understanding -- Multi-agent Systems in Pedestrian Dynamics Modeling -- Towards a Model for Extraction of Possible Worlds and Accessibility Relation from Cognitive Agent?s Experience -- Social Networks -- On Deriving Tagsonomies: Keyword Relations Coming from Crowd -- d 2 isco: Distributed Deliberative CBR Systems with jCOLIBRI -- Model of a Collaboration Environment for Knowledge Management in Competence-Based Learning -- PlWiki ? A Generic Semantic Wiki Architecture -- Properties of Bridge Nodes in Social Networks -- Semantic Web -- Use of Semantic Principles in a Collaborative System in Order to Support Effective Information Retrieval -- Assessing Semantic Quality of Web Directory Structure -- Computer Aided Requirements Management -- BizKB: A Conceptual Framework for Dynamic Cross-Enterprise Collaboration -- A Simple Parallel Reasoning System for the Description Logic -- SemCards: A New Representation for Realizing the Semantic Web -- ExpTime Tableaux for Checking Satisfiability of a Knowledge Base in the Description Logic -- Semantically Enhanced Intellectual Property Protection System - SEIPro2S -- Semantic Knowledge Representation in Terrorist Threat Analysis for Crisis Management Systems -- Consensus Choice for Reconciling Social Collaborations on Semantic Wikis -- Ontology Management -- Ontology Mapping Composition for Query Transformation in Distributed Environment -- Algebra of Ontology Modules for Semantic Agents -- Grouping Results of Queries to Ontological Knowledge Bases by Conceptual Clustering -- Applying the c.DnS Design Pattern to Obtain an Ontology for Investigation Management System -- Ontology Applications for Achieving Situation Awareness inMilitary Decision Support Systems -- A Collaborative Ontology-Based User Profiles System -- Ontology-Based Intelligent Agent for Grid Resource Management -- Special Session: Dynamics of Real-World Social Networks -- The Norm Game on a Model Network: A Critical Line -- Model for Trust Dynamics in Service Oriented Information Systems -- Collective Prisoner?s Dilemma Model of Artificial Society -- Special Session: Nature-Inspired Collective Intelligence -- DES Control Synthesis and Cooperation of Agents -- Parameter Tuning for the Artificial Bee Colony Algorithm -- A Modified Ant-Based Approach to Edge Detection -- A Hybrid Evolutionary Approach for the Protein Classification Problem -- A Family of GEP-Induced Ensemble Classifiers -- Handling Dynamic Networks Using Ant Colony Optimization on a Distributed Architecture -- Modelling Shortest Path Search Techniques by Colonies of Cooperating Agents -- Natural Scene Retrieval Based on Graph Semantic Similarity for Adaptive Scene Classification -- Special Session: Web Systems Analysis -- A Hybrid Architecture for E-Procurement -- Localization by Wireless Technologies for Managing of Large Scale Data Artifacts on Mobile Devices -- Avoiding Threats Using Multi Agent System Planning for Web Based Systems -- Using WordNet to Measure the Similarity of Link Texts -- Mining Frequent Purchase Behavior Patterns for Commercial Websites -- Block Map Technique for the Usability Evaluation of a Website -- Global Distribution of HTTP Requests Using the Fuzzy-Neural Decision-Making Mechanism -- Deterministic Processing of WWW Pages by the Web Service -- Special Session: Collective Intelligence for Economic Data Analysis -- Comparative Analysis of Regression Tree Models for Premises Valuation Using Statistica Data Miner -- Electronic Trading on Electricity Marketswithin a Multi-agent Framework -- Comparative Analysis of Premises Valuation Models Using KEEL, RapidMiner, and WEKA -- A Multi-agent System to Assist with Real Estate Appraisals Using Bagging Ensembles -- Reputation Tracking Procurement Auctions -- Comparative Analysis of Evolutionary Fuzzy Models for Premises Valuation Using KEEL -- Hybrid Repayment Prediction for Debt Portfolio. 330 $aComputational collective intelligence (CCI) is most often understood as a subfield of artificial intelligence (AI) dealing with soft computing methods that enable group decisions to be made or knowledge to be processed among autonomous units acting in distributed environments. The needs for CCI techniques and tools have grown signi- cantly recently as many information systems work in distributed environments and use distributed resources. Web-based systems, social networks and multi-agent systems very often need these tools for working out consistent knowledge states, resolving conflicts and making decisions. Therefore, CCI is of great importance for today?s and future distributed systems. Methodological, theoretical and practical aspects of computational collective int- ligence, such as group decision making, collective action coordination, and knowledge integration, are considered as the form of intelligence that emerges from the collabo- tion and competition of many individuals (artificial and/or natural). The application of multiple computational intelligence technologies such as fuzzy systems, evolutionary computation, neural systems, consensus theory, etc. , can support human and other collective intelligence and create new forms of CCI in natural and/or artificial s- tems. 410 0$aLecture Notes in Artificial Intelligence,$x2945-9141 ;$v5796 606 $aArtificial intelligence 606 $aUser interfaces (Computer systems) 606 $aHuman-computer interaction 606 $aSoftware engineering 606 $aComputer science 606 $aData mining 606 $aArtificial Intelligence 606 $aUser Interfaces and Human Computer Interaction 606 $aSoftware Engineering 606 $aTheory of Computation 606 $aData Mining and Knowledge Discovery 615 0$aArtificial intelligence. 615 0$aUser interfaces (Computer systems). 615 0$aHuman-computer interaction. 615 0$aSoftware engineering. 615 0$aComputer science. 615 0$aData mining. 615 14$aArtificial Intelligence. 615 24$aUser Interfaces and Human Computer Interaction. 615 24$aSoftware Engineering. 615 24$aTheory of Computation. 615 24$aData Mining and Knowledge Discovery. 676 $a006.3 701 $aNguyen$b Ngoc Thanh$cD. Sc.$0601234 701 $aKowalczyk$b Ryszard$f1961-$01240245 701 $aChen$b Shyi-Ming$01423979 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910483361303321 996 $aComputational Collective Intelligence. Semantic Web, Social Networks and Multiagent Systems$94521378 997 $aUNINA