"... In PAGE 2: ... The four databases are General Motors (GM) cars, Japanese cars, Mercedes cars, and Motorsport cars. Table1 shows the vir- tual database combining all four databases. The columns are the car model, car make, number of doors, number of seats, driving range on a tank of gas, and the manufacturers... ..."

"... In PAGE 2: ... The four databases are General Motors #28GM#29 cars, Japanese cars, Mercedes cars, and Motorsport cars. Table1 shows the vir- tual database combining all four databases. The columns are the car model, car make, number of doors, number of seats, driving range on a tank of gas, and the manufacturers... ..."

"... In PAGE 2: ...3 Databases and data curation Data from various public data sources were collected into our local database. Table1 lists the data sources utilized in the examples of this paper. In order to add a specific bioinformatics database into our system, it has to be passed first through a curation stage.... In PAGE 3: ... It is the task of the curator to cap- ture its relevant subparts as well as to define appropriate semantics for the integrated database. Table1 shows the XML Document Classes captured from databases used in this paper. In the course of implementing the above steps we make use of XMLSPY software (Altova, Inc.... ..."

"... In PAGE 43: ... Almost all students of the courses study computer science as their minor; students of computer science curriculum have a programming course of their own. The results are shown in Table1 . Light PBL students of L1 have statistically signi cantly better results (less drop out) than students of Standard L1 course.... In PAGE 43: ... However, the di erences were not statistically signi cant. Table1 : Results of the L1/Y1 course and L1/Y1 light PBL versions. The Y1 control group had equal requirements as the standard Y1 group.... In PAGE 57: ...Kolin Kolistelut - Koli Calling 2002 Table1 : Generality. System Rank Language Speciality Animal n/a any JAWAA any any Jeliot EJava code and algorithm animation Matrix Java algorithm animation Table 2: Presentation Style.... In PAGE 57: ... However, this has no e ect on the ranking that follows. The evaluation is summarized in Table1 . The most discriminating characteristic is Ani- mal apos;s and JAWAA apos;s capability of visualizing (almost) anything.... In PAGE 75: ... Here TCP is the result of decisions taken by a committee. Table1 : Aspects of the di erent categories of description of TCP (Berglund, 2002). As what is TCP experienced? As a part of which framework is TCP experienced? What is the technical character of TCP? How is TCP described? 1.... In PAGE 87: ... High school students need more speci c instructions for what to do. In Table1 we can see the amounts of participants in Virtual Approbatur during years 2000- 2001. In Table 1 is also seeing the relative part of female and male students in each control date.... In PAGE 87: ... In Table 1 we can see the amounts of participants in Virtual Approbatur during years 2000- 2001. In Table1 is also seeing the relative part of female and male students in each control date.... ..."

"... In PAGE 16: ...7%. The main results on the MNIST set are summarized in Table3 . Prior to the present work, the best system on the MNIST set was a boosted ensemble of LeNet4 neural networks, trained on a huge database of artificially generated virtual examples.... ..."

"... In PAGE 5: ...storing the temporally explicit data in a RDBMS and maintaining appropriate links from a GIS layer to the RDBMS tables. Table1 summarizes the GWRAPPS data storage. 3.... ..."

"... In PAGE 16: ...7%. The main results on the MNIST set are summarized in Table3 . Prior to the present work, the best system on the MNIST set was a boosted ensemble of LeNet4 neural networks, trained on a huge database of arti cially generated virtual examples.... ..."

"... In PAGE 7: ...nd air pollutants to form acidic compounds...........................................................4 Table2 : Actors of Virtual School Lab.... In PAGE 21: ... A complete set of use- cases specifies all the different ways to use the system, and therefore defines all behavior required of the system, bounding the scope of the system. Table2 presents the actors who interact with Sensor Data Management System. Table 3 specifies a set of use-cases that are used to represent the behavior of the system.... ..."

"... In PAGE 30: ... All system characteristics which are contained in the classification framework are explicitly chosen by the system or protocol designer. Table3 -1 classifies these protocols. A different classification for replica update protocols, which concentrates on relationships between the protocols, is presented in [CHKS94].... In PAGE 34: ...Chapter 3: State of the art Table3 -1: Classification of replication protocols. Replication transparency Transparent Non-trans- parent Not applicable 2PC, 3PC, QC, ROWA, MW, VP, AE, TSAE, LR, IUIA, DP, MC, TU, Re, QCP, PT, ES, BI, Esc, VC Consistency Strong 2PC, 3PC, QC, ROWA, MW, VP, Re, VC1 Weak AE, TSAE, LR, IUIA, DP, MC, TU, QCP, PT, ES, BI, Esc, VC2 Replica syn- chronization Synchronous 2PC, 3PC, QC, ROWA, MW, VP, MC3, Re5, VC1 As soon as possible AE, TSAE, LR, IUIA, MC4, BI, Esc Temporal event QCP10, PT, ES11, VC2 Non-tempo- ral event DP7, TU8, Re6, QCP10, ES11 Update rights Master-slave TU, QCP, VC8 Peer-to-peer 2PC, 3PC, QC, ROWA, MW, VP, AE, TSAE, LR, IUIA, DP, MC, TU, Re, PT, ES, BI, Esc Conflicts Conflicts can occur AE, TSAE9, LR9, IUIA, DP, MC, TU, PT, ES11, BI12 No conflicts occur 2PC, 3PC, QC, ROWA, MW, VP, TSAE9, LR9, Re, QCP, Esc, VC, ES11, BI12 Implicit replica- tion of refer- enced objects Yes No Not applicable 2PC, 3PC, QC, ROWA, MW, VP, AE, TSAE, LR, IUIA, DP, MC, TU, Re, QCP, PT, ES, BI, Esc, VC Implicit schema replication Yes Partial No Not applicable 2PC, 3PC, QC, ROWA, MW, VP, AE, TSAE, LR, IUIA, DP, MC, TU, Re, QCP, PT, ES, BI, Esc, VC Dynamic allo- cation of repli- cas Yes No Not applicable 2PC, 3PC, QC, ROWA, MW, VP, AE, TSAE, LR, IUIA, DP, MC, TU, Re, QCP, PT, ES, BI, Esc, VC Data model Object- oriented Rela- tional Files Other data model Not applicable or open 2PC, 3PC, QC, ROWA, MW, VP, AE, TSAE, LR, IUIA, DP, MC, TU, Re, QCP, PT, ES, BI, Esc, VC 3.... In PAGE 34: ... Replication transparency Transparent Non-trans- parent Not applicable 2PC, 3PC, QC, ROWA, MW, VP, AE, TSAE, LR, IUIA, DP, MC, TU, Re, QCP, PT, ES, BI, Esc, VC Consistency Strong 2PC, 3PC, QC, ROWA, MW, VP, Re, VC1 Weak AE, TSAE, LR, IUIA, DP, MC, TU, QCP, PT, ES, BI, Esc, VC2 Replica syn- chronization Synchronous 2PC, 3PC, QC, ROWA, MW, VP, MC3, Re5, VC1 As soon as possible AE, TSAE, LR, IUIA, MC4, BI, Esc Temporal event QCP10, PT, ES11, VC2 Non-tempo- ral event DP7, TU8, Re6, QCP10, ES11 Update rights Master-slave TU, QCP, VC8 Peer-to-peer 2PC, 3PC, QC, ROWA, MW, VP, AE, TSAE, LR, IUIA, DP, MC, TU, Re, PT, ES, BI, Esc Conflicts Conflicts can occur AE, TSAE9, LR9, IUIA, DP, MC, TU, PT, ES11, BI12 No conflicts occur 2PC, 3PC, QC, ROWA, MW, VP, TSAE9, LR9, Re, QCP, Esc, VC, ES11, BI12 Implicit replica- tion of refer- enced objects Yes No Not applicable 2PC, 3PC, QC, ROWA, MW, VP, AE, TSAE, LR, IUIA, DP, MC, TU, Re, QCP, PT, ES, BI, Esc, VC Implicit schema replication Yes Partial No Not applicable 2PC, 3PC, QC, ROWA, MW, VP, AE, TSAE, LR, IUIA, DP, MC, TU, Re, QCP, PT, ES, BI, Esc, VC Dynamic allo- cation of repli- cas Yes No Not applicable 2PC, 3PC, QC, ROWA, MW, VP, AE, TSAE, LR, IUIA, DP, MC, TU, Re, QCP, PT, ES, BI, Esc, VC Data model Object- oriented Rela- tional Files Other data model Not applicable or open 2PC, 3PC, QC, ROWA, MW, VP, AE, TSAE, LR, IUIA, DP, MC, TU, Re, QCP, PT, ES, BI, Esc, VC 3.1 Replication protocols 41 Table3 -2: Legend to table 3-1. 2PC Two-phase commit MW Missing writes 3PC Three-phase commit PT Polytransaction AE Anti-entropy QC Quorum consensus BI Bounded ignorance QCP Quasi-copy DP Data-patch Re Referee ES Epsilon-serializability ROW A Read-One-Write-All Esc Escrow TSAE Timestamped anti-entropy IUIA Independent updates and in- cremental agreement TU Tentative update LR Lazy Replication VC Virtual primary copy MC mc-compatibility VP Virtual partition 1 Within virtual primary copy 7 Initiated by database adminis- trator 2 Outside virtual primary copy 8 Update requests of weak repli- cas are redirected to the virtual primary copy 3 For commutative transactions 9 Depending on update ordering 4 For non-commutative transac- tions 10 Depending on coherency conditions 5 Within CSCR 11 Depending on replica control protocol 6 Outside CSCR 12 Depending on the global and local consistency constraints 3.... In PAGE 40: ...Chapter 3: State of the art Table3 -3: Classification of replication in distributed systems. Replication transparency Transparent Is, FW, RG, OT, IB, AFS, Co10, Fi, Fr, Hu, Ru, MI, Ar, El, Ro, Go, Ha, SOM, ARO, DV, GI, RMS Non-trans- parent Ca, Ba, Co11 Not ap- plicable Consistency Strong Is1,2, Fr3,4, Hu, Ar, El1,2, Ro9, Go, Ha, SOM, ARO12, DV19, RMS Weak Is1,2, FW, RG, OT, IB, AFS, Co, Fi, Fr4, Ru, MI, Ca, El1,2, Ro9, ARO12, DV19, GI, Ba Replica syn- chronization Synchronous Is1,2, Fr3,4, Hu, Ar, El1,2, Ro9, Go, Ha, SOM, ARO12, DV19, RMS As soon as pos- sible Is1,2, FW, RG, AFS, Co10, Fi, Fr4, El1,2, Ro9, ARO12, DV19, GI22 Temporal event Fr4, Ca, ARO12 Non-temporal event OT14, IB14, Co11, Fr4, Ru8, MI7, ARO12, GI23, Ba Update rights Master- slave Ca, SOM13 Peer-to-peer Is, FW, RG, OT, IB, AFS, Co, Fi, Fr, Hu, Ru, MI, Ar, El, Ro, Go, Ha, SOM13, ARO, DV, GI, RMS, Ba Conflicts Conflicts can occur Is1,2, FW1, RG1, OT16, IB18, AFS, Co, Fi, Fr4, Ru, El1,2, Ro9, GI, Ba No conflicts occur Is1,2, FW1, RG1, OT20, IB15, Fr3, Hu, MI, Ca, Ar, El1,2, Ro9, Go, Ha, SOM, ARO5, DV17, RMS Implicit replica- tion of refer- enced objects Yes DV21 No OT, IB, Ar, El, Ro, Go, Ha, SOM, ARO, GI, RMS Not applicable Is, Fw, RG, AFS, Co, Fi, Fr, Hu, Ru, MI, Ca, Ba Implicit schema replication Yes Partial OT6, IB6 No Ar, El, Ro, Go, Ha, SOM, ARO, DV, GI, RMS Not applicable Is, FW, RG, AFS, Co, Fi, Fr, Hu, Ru, MI, Ca, Ba Dynamic allo- cation of repli- cas Yes RMS No Is, FW, RG, OT, IB, AFS, Co, Fi, Fr, Hu, Ru, MI, Ca, Ar, El, Ro, Go, Ha, SOM, ARO, DV, GI, Ba Not appli- cable Data model Object-ori- ented OT, IB, Ar, El, Ro, Go, Ha, SOM, ARO, DV, GI, RMS Rela- tional Files AFS, Co, Fi, Fr, Hu, Ru, MI, Ca Other data model Not applicable or open Is, FW, RG, Ba 3.... In PAGE 40: ... Replication transparency Transparent Is, FW, RG, OT, IB, AFS, Co10, Fi, Fr, Hu, Ru, MI, Ar, El, Ro, Go, Ha, SOM, ARO, DV, GI, RMS Non-trans- parent Ca, Ba, Co11 Not ap- plicable Consistency Strong Is1,2, Fr3,4, Hu, Ar, El1,2, Ro9, Go, Ha, SOM, ARO12, DV19, RMS Weak Is1,2, FW, RG, OT, IB, AFS, Co, Fi, Fr4, Ru, MI, Ca, El1,2, Ro9, ARO12, DV19, GI, Ba Replica syn- chronization Synchronous Is1,2, Fr3,4, Hu, Ar, El1,2, Ro9, Go, Ha, SOM, ARO12, DV19, RMS As soon as pos- sible Is1,2, FW, RG, AFS, Co10, Fi, Fr4, El1,2, Ro9, ARO12, DV19, GI22 Temporal event Fr4, Ca, ARO12 Non-temporal event OT14, IB14, Co11, Fr4, Ru8, MI7, ARO12, GI23, Ba Update rights Master- slave Ca, SOM13 Peer-to-peer Is, FW, RG, OT, IB, AFS, Co, Fi, Fr, Hu, Ru, MI, Ar, El, Ro, Go, Ha, SOM13, ARO, DV, GI, RMS, Ba Conflicts Conflicts can occur Is1,2, FW1, RG1, OT16, IB18, AFS, Co, Fi, Fr4, Ru, El1,2, Ro9, GI, Ba No conflicts occur Is1,2, FW1, RG1, OT20, IB15, Fr3, Hu, MI, Ca, Ar, El1,2, Ro9, Go, Ha, SOM, ARO5, DV17, RMS Implicit replica- tion of refer- enced objects Yes DV21 No OT, IB, Ar, El, Ro, Go, Ha, SOM, ARO, GI, RMS Not applicable Is, Fw, RG, AFS, Co, Fi, Fr, Hu, Ru, MI, Ca, Ba Implicit schema replication Yes Partial OT6, IB6 No Ar, El, Ro, Go, Ha, SOM, ARO, DV, GI, RMS Not applicable Is, FW, RG, AFS, Co, Fi, Fr, Hu, Ru, MI, Ca, Ba Dynamic allo- cation of repli- cas Yes RMS No Is, FW, RG, OT, IB, AFS, Co, Fi, Fr, Hu, Ru, MI, Ca, Ar, El, Ro, Go, Ha, SOM, ARO, DV, GI, Ba Not appli- cable Data model Object-ori- ented OT, IB, Ar, El, Ro, Go, Ha, SOM, ARO, DV, GI, RMS Rela- tional Files AFS, Co, Fi, Fr, Hu, Ru, MI, Ca Other data model Not applicable or open Is, FW, RG, Ba 3.2 Replication in distributed systems 53 Table3 -4: Legend to table 3-3. AFS Andrew File System Go GOOFY Ar Arjuna Ha Hawk ARO Adaptable replicated objects Hu Huygens Ba Bayou IB Information Bus Ca Castanet Is Isis Co Coda MI MIo-NFS DV DistView OT OrbixTalk El ELECTRA RG Replication group Fi Ficus RMS Replica Management System Fr Frolic Ro ROMANCE FW Framework for group com- munication systems Ru Rumor GI GINA SOM SOM Replication Framework 1 Depending on update ordering 13 Depending on the number of writable replicas 2 Depending on reply collection 14 Pull- and push-actions are explicitly initiated 3 Between clusters 15 With guaranteed message de- livery 4 Within cluster: Depending on replica control strategy 16 Without persistent event chan- nels 5 If consistency manager disal- lows asynchronous peer-to- peer replication for conflicting updates 17 If lock object disallows asyn- chronous peer-to-peer replica- tion for conflicting updates 6 Implicit by self-describing format 18 Without guaranteed message delivery 7 On token passing 19 Depending on replica control strategy of the lock object 8 Reconciliation is explicitly initiated 20 With persistent event channels 9 Depending on replica control strategy 21 Only at replication setup time 10 In connected mode 22 With tight or loose coupling 11 In disconnected mode 23 In decoupled mode 12 Depends on consistency man-... In PAGE 44: ...3.3 Replication in database systems 61 Table3 -6: Legend to table 3-5. CA CA-OpenIngres/Replicator OR OmniReplicator ER Informix Enterprise Replica- tion Ora Oracle replication facility DRO Objectivity/DB Data Replica- tion Option OSAR ObjectStore Asynchronous Replication Gem GemEnterprise OSC OSCAR IBM IBM DataPropagator SQLS Microsoft SQL Server repli- cation facility IP InfoPump SR SQL Remote Jet Microsoft Jet Database Engine Sy Sybase Replication Server LN Lotus Notes replication facil- ity VR Versant Replication 1 With peer-to-peer replication 3 Schema 2 With master-slave replication 4 Data 3.... ..."

"... In PAGE 6: ... In order to investigate this, we have implemented the system in both ways, with generic programming techniques and using inheritance and virtual functions. Table3 presents the performance comparison for the sequential applica-... In PAGE 7: ...From Table3 we can see that the code generated by the system using generic pro- gramming techniques is faster. This is because the generic programming relies on static polymorphism, which resolves interfaces at compile time.... ..."