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(9:00$B!A(B10:00)$B!!(B($B:BD9(B $BIM8}(B $B9';J(B)
9:00$B!A(B 9:20Q101$B%5%$%P!<%;%-%e%j%F%#$r9MN8$7$?%W%i%s%H$N0BA4@_7W(B
($BL>9)Bg(B) $B!{(B($B3X(B)$BM?8l(B $B=$0l(B $B!&(B $BK-Eh(B $B9d;K(B $B!&(B $BB9(B $B>=(B $B!&(B $B1[Eg(B $B0lO:(B $B!&(B ($B@5(B)$B66K\(B $BK'9((B
Cyber Terrorism
Plant
Control System
S-15730
9:20$B!A(B 9:40Q102$BBg5,LO%W%i%s%H$N@)8f7O9=@.$K$*$1$k@09g@-$NI>2A%7%9%F%`$N3+H/(B
($BL>9)Bg(B) $B!{(B($B3X(B)$BFbF#(B $BM:2p(B $B!&(B ($B@5(B)$B66K\(B $BK'9((B
plant control
large scale
systematic estimation
S-15806
9:40$B!A(B 10:00Q103$B>r7o!?;v>]%M%C%H:G>.
($BL>Bg9)(B) $B!{(B($B@5(B)$B66D^(B $B?J(B $B!&(B ($B3X(B)$B66D^(B $B8g(B $B!&(B ($B@5(B)$BLpV:(B $BCRG7(B $B!&(B ($B@5(B)$B>.LnLZ(B $B9nL@(B
condition/event net
minimal realization
batch control system
S-15991
(10:00$B!A(B11:00)$B!!(B($B:BD9(B $B66K\(B $BK'9((B)
10:00$B!A(B 10:20Q104$B%Y%$%8%"%s%M%C%H%o!<%/$K$h$kF0E*%7%9%F%`$N5sF0M=B,(B
($BL>Bg9)(B) $B!{(B($B3X(B)$BE:ED(B $B9,9((B $B!&(B ($B@5(B)$BLpV:(B $BCRG7(B $B!&(B ($B@5(B)$B66D^(B $B?J(B $B!&(B ($B@5(B)$B>.LnLZ(B $B9nL@(B
Bayesian network
dynamical system
probabilistic model
S-15888
10:20$B!A(B 10:40Q105Projected unscented Kalman filter$B$rMQ$$$?4I7?%^%$%/%m%j%"%/%?$N%b%K%?%j%s%0(B
($B5~Bg9)(B) $B!{(B($B3X(B)$B5\NS(B $B7=Je(B $B!&(B ($B@5(B)$BEBB<(B $B=$(B $B!&(B ($B@5(B)$B2CG<(B $B3X(B $B!&(B ($B@5(B)$BD9C+It(B $B?-<#(B
microreactor
channel blockage
projected unscented Kalman filter
S-15158
10:40$B!A(B 11:00Q106$B%$%Y%s%HAj4X2r@O$rMQ$$$?%"%i!<%`%7%9%F%`$N%Q%U%)!<%^%s%9%b%K%?%j%s%0(B
($BF`NI@hC $B!&(B ($B@5(B)$BLnED(B $B8-(B
Alarm Management
Event correlation analysis
Key Performance Indicator
S-1594
(11:00$B!A(B11:40)$B!!(B($B:BD9(B $B9u2,(B $BIp=S(B)
11:00$B!A(B 11:20Q107$BG.7O%W%i%s%H$KBP$9$kA`6H%G!<%?$+$i$NF1Dj$K4X$9$k8&5f(B
($BL>9)Bg(B) $B!{(B($B3X(B)$BK\ED(B $B7CM}(B $B!&(B ($B@5(B)$BJFC+(B $B>
identification
process control
S-1589
11:20$B!A(B 11:40Q108FIR$B%U%#%k%?$rMQ$$$?M=8+@)8f$K4X$9$k0l9M;!(B
($BL>9)Bg(B) $B!{(B($B3X(B)$BEDCf(B $BBg;K(B $B!&(B ($B@5(B)$BJFC+(B $B>
process control
preview control
S-1558

(13:00$B!A(B13:20)$B!!(B($B;J2q(B $BDS?"(B $B5AJ8(B)
13:00$B!A(B 13:20Q113[$BM%=(O@J8>^(B] Multiobjective Process Synthesis for Dimethyl Ether Production from Various Feedstock and Technologies
(National Energy Tech. Lab. (NETL)) Kim Hosoo $B!&(B (Seoul National U. (SNU)) Han Kyusang $B!&(B $B!{(BYoon En Sup
Multiobjective Optimization
Mixed-integer non-linear programming
DME Production
S-15114
(13:20$B!A(B14:00)$B!!(B($B:BD9(B $B9u2,(B $BIp=S(B)
13:20$B!A(B 13:40Q114Economically and energetically optimal synthesis of complex distillation sequences
($B5~Bg9)(B) $B!{(B($B3X(B)Alcantara-Avila J. R. $B!&(B ($B@5(B)$B2CG<(B $B3X(B $B!&(B ($B@5(B)$BD9C+It(B $B?-<#(B
Heat integration
Compressor addition
Multiobjective optimization
S-15169
13:40$B!A(B 14:00Q115$B%W%m%;%9%$%s%F%0%l!<%7%g%s$K$h$k>J%(%M%k%.!<0F7oNc(B
(PIL) $B!{(B($B@5(B)$BJ?ED(B $B8-B@O:(B $B!&(B (U. Manchester) Smith Robin
Ethylene
Process Integration
Energy saving
S-15535
(14:00$B!A(B15:00)$B!!(B($B:BD9(B $B;32<(B $BA1G7(B)
14:00$B!A(B 14:20Q116$B%a%s%F%J%s%9%U%j!<$J(BPAT$B
($B5~Bg9)(B) $B!{(B($B3X(B)$B6b(B $B>090(B $B!&(B ($B@5(B)$B2CG<(B $B3X(B $B!&(B ($BBh0l;06&(B) ($B@5(B)$BCf@n(B $B90;J(B $B!&(B ($B5~Bg9)(B) ($B@5(B)$BD9C+It(B $B?-<#(B
Locally weighted partial least squares regression
Adaptive model
Soft-sensor
S-15121
14:20$B!A(B 14:40Q117$B6I=j(BPLS$B$K$*$1$k%G!<%?4VN`;wEY$N7hDj
($B5~Bg9)(B) $B!{(B($B3X(B)$B2,Eg(B $BN $B!&(B ($B3X(B)$B6b(B $B>090(B $B!&(B ($B@5(B)$B2CG<(B $B3X(B $B!&(B ($B@5(B)$BD9C+It(B $B?-<#(B
locally weighted PLS
similarity
statistical modeling
S-15191
14:40$B!A(B 15:00Q118PLS$B$*$h$S6I=j(BPLS$B$KE,$7$?%P%.%s%07?JQ?tA*Br
($B5~Bg2=9)(B) $B!{(B($B3X(B)$B0BF#(B $BN40l(B $B!&(B ($B3X(B)$B6b(B $B>090(B $B!&(B ($B@5(B)$B2CG<(B $B3X(B $B!&(B ($B@5(B)$BD9C+It(B $B?-<#(B
variable selection
locally weighted PLS
statistical modeling
S-15239
(15:00$B!A(B16:00)$B!!(B($B:BD9(B $B66D^(B $B?J(B)
15:00$B!A(B 15:20Q119$B%W%m%;%9$NF0FC@-$r9MN8$KF~$l$?JQ?tA*Br
($BElBg1!9)(B) $B!{(B($B3X(B)$B6b;R(B $B90>;(B $B!&(B ($B@5(B)$BA%DE(B $B8x?M(B
soft sensor
process dynamics
variable selection
S-157
15:20$B!A(B 15:40Q120$B%b%G%k$N?.Mj@-$r9MN8$7$?%=%U%H%;%s%5!<
($BElBg1!9)(B) $B!{(B($B3X(B)$B2,ED(B $B9d;L(B $B!&(B ($B3X(B)$B6b;R(B $B90>;(B $B!&(B ($B@5(B)$BA%DE(B $B8x?M(B
soft sensor
process control
model selection
S-15218
15:40$B!A(B 16:00Q121$BHs@~7AF0E*%b%G%k$K4p$E$/0[>o$N8!=P!&F1Dj
($BElG@9)Bg1!9)(B) $B!{(B($B3X(B)$Bib86(B $BM:B@(B $B!&(B ($B3X(B)$B9b8+(B $B=S2p(B $B!&(B ($B@5(B)$B;32<(B $BA1G7(B
Fault detection and isolation
Nonlinear dynamic model
State and parameter estimation
S-15856

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(C) 2011 $B8x1W
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