2025-08-01 13:32:13 info: [Puppeteer Page] Got cookies, applying... 1 :XOh!8/ -XYh3@h/@W8 VW' +Wp!%? >j/Z2%Z%/VU+ 3dTW7Jzu.iꇸ[iiꑸn.Ƹx.I.ik.|iϺ\Qbyhc~kWq Ƚ2025-08-01 13:32:13 info: [Puppeteer Page] Attempting direct fetch of https://isis.vanderbilt.edu/bibcite/export/bibtex/bibcite_reference/65 LtG3\3R%P34Nt"RtsptZ3V1 tB&C3R C"G"PvE30T>QvC&y^%V8E4CxByU5RyG94C3U?^"E3E3Ry+7Vε2025-08-01 13:32:13 info: [Puppeteer File-Downloader] Attempting to download asset directly... zq܃#jdfܕ#x#děEFқl`;tu!dv`\uu!em!dhu/|@proceedings{65, author = {Saideep Nannapaneni and Abhishek Dubey and Sankaran Mahadevan}, title = {Performance Evaluation of Smart Systems under Uncertainty}, abstract = {This paper develops a model-based framework for the quantification and propagation of multiple uncertainty sources affecting the performance of a smart system. A smart system, in general, performs sensing, control and actuation for proper functioning of a physical subsystem (also referred to as a plant). With strong feedback coupling between several subsystems, the uncertainty in the quantities of interest (QoI) amplifies over time. The coupling in a generic smart system occurs at two levels: (1) coupling between individual subsystems (plant, cyber, actuation, sensors), and (2) coupling between nodes in a distributed computational subsystem. In this paper, a coupled smart system is decoupled and considered as a feed-forward system over time and modeled using a two-level Dynamic Bayesian Network (DBN), one at each level of coupling (between subsystems and between nodes). A DBN can aggregate uncertainty from multiple sources within a time step and across time steps. The DBN associated with a smart system can be learned using available system models, physics models and data. The proposed methodology is demonstrated for the design of a smart indoor heating system (identification of sensors and a wireless network) within cost constraints that enables room-by-room temperature control. We observe that sensor uncertainty has a higher impact on the performance of the heating system compared to the uncertainty in the wireless network.}, year = {2017}, journal = {IEEE Smart World Congress}, month = {08/2017}, publisher = {IEEE}, } ÍʩʩݍɀЖߏƴ۫񰘂喚掚긯ws@ABC@@{.@Y__A]XW_P?h?#Ҥ]Qe ֟ X?   !"#$%&'()*+,-./01234X Pwj?6_4@96` 7@@@@P@T_qB@e17_/ioP@AT_X a)PKo? Ԡ@@ @[!Pj?֮_1ioP@AT_X a)PKo? Ԡ]X Pwj?֡ @["Pj?֮_qB@51_/ioP@AT_X a)PKo? Ԡ]X Pwj?֡ @["Pj?֮_0ioP@AT_X a)PKo? Ԡ]X!Pwj?֡ @[#Pj?֮_oioP@AT_X a)PKo? Ԡ_DP@AT_X a)PKo? Ԡ@X#Pwj?֠ZAҮZO@;Pd?֡ @[$Pj?֮_pioP@AT_X a)PKo? Ԡ_DP@AT_X a)PKo? Ԡ@X%Pwj?֠ZAҮZO@;Pd?֡ @[&Pj?֮_qioP@AT_X a)PKo? Ԡ@XPwj?}BPk?aPkl?ցPkl?֡ @[D'Pj?֡ @X'Pwj?֠X_vio[a ҮZZ @;Pd?֮_kio`Ү @O@;Pd?@@ @XD)Pj?X @X)Pj?֡ @X@*Pwj?PWv?_qB@1l@X*Pwj?֠@@[`T@@@@P@T_qB@1V@X@+Pwj?PWv?_qB@}1+ @X+Pwj?֠@@[XD,Pj?֡ @X,Pwj?֠[X@-Pwj?֠[!Ү[Pd?@@ @XD.Pj?֮_qB@I1@X.Pwj?PWv?_qB@11 @X@/Pwj?֠Ҡ[AҮZ @;Pd?֡@X@0Pwj?PWv?_qB@!1_io`Ү@ @O@;Pd?@@ @XD1Pj?@@ @X1Pj?֮_mioP@AT_X a)PKo? Ԡҡ @[D2Pj?֮_nioP@AT_X a)PKo? Ԡҡ @[2Pj?@@CҤuQe 37P47`S`S`Pp`SP @SP@SSSSS`S`SS`S`S(,3S`S0SSPSpS`@SSpS`pSSP`0SP`SpS P`0SP`SS`P@PS SS`SPSpp83S`SSSSS`SS0SPS0