PPT-Normality and Faults in Logic-Based Diagnosis

Presented by Kelly Benson Mouiad AlWahah 1 Definitions we agreed upon Def 1 Diagnosis is the problem of trying to find what is wrong with some system based on knowledge about the designstructure of the system possible malfunctions that can occur in the system and observations made of the behavior of the system. Please do not alter or modify contents All rights reserved 1FQMFXIFFMMZVDDFGVMJNQMFNFUJHUIJLJMM hy does my child always have an attitude Shes often disruptive disrespectful or picking on other children Shes always the one with a chip on her shoulder The method automatically checks sequen tial logic embedded in PLCs and provides counterexamples if it finds errors The method consists of a system model assertions and a model checker The model is a Booleanbased repre sentation of a PLCs behavior As Exploiting multicores, reconfigurable logic, and graphics engines for high performance and low power. Applications include:. Gamma-ray astronomy. DNA and text-based search. Computational finance. World’s first use of all of these compute resources on a single, real-world problem. By Andrew Pro. References. Alexander, Thor, “An Optimized Fuzzy Logic Architecture For Decision Making”, . AI Game Wisdom. .. Bonissone. , P. . Piero. and . Cheetham. , William, “Fuzzy Case Based Reasoning For Residential Property Valuation” (. Regional Strain. Types of Fault and the Principal Stresses. Fault Rocks. Gouge: non-cohesive, fine grained. Breccia: coarse angular fragments. Cataclasite: cohesive fragments. Fault Melt (pseudotachylite):. and Folds. The illustration shows an east-west cross section between the Allegheny Structural Front and North Fork Mountain. The topographic feature called Germany Valley sits atop the geologic structure called the Wills Mountain Anticline. Westward directed compressive forces associated with the . “Essentially. , all models are wrong, but some are . useful”. George E.P. Box. Your model . has to be. wrong…. … but that’s o.k.. if it’s illuminating!. Linear Model. Assumptions. Absence of. Examine the concepts of normality . and abnormality. What is normal . behaviour. ?. In pairs or small groups discuss examples of . behaviour. that is normal, and . behaviour. that is abnormal.. Examine the concepts of normality . Dan Fisher, Addison Floyd. Outline. Introduction. Fault Detection - Motivation, Methods, etc.. Fault Diagnosis - Motivation, Methods, etc.. Fault Tolerance. Single FPGA. Multiple FPGAs. Single Faults. Craig . Hyslop. Robert Stewart. Outline. Purpose. Process. Synthetics. Field . d. ata. Conclusions. 2. Purpose. 3. (. Engelkemeir. , 2006). Identification of blind faults. Depth: . 0-50m. Exploration. David Mohabir. University of Arizona. March 19. th. , 2012. Testing and diagnosis of interconnect faults in cluster-based FPGA architectures. Section 1. Motivation. Quickly identify faulty components. Anke. . Rohwer. , Andrew Booth, . Lisa Pfadenhauer, . Louise Brereton, . Ansgar. . Gerhardus. , Kati . Mozygemba. , . Wija. . Oortwijn. , Marcia . Tummers. , . Gert. Jan van der Wilt, Eva . Rehfuess. Chidambaram Alagappan. Vishwani. D. . Agrawal. Department of Electrical and Computer Engineering. Auburn University, AL 36849 USA. 5/9/2013. 2. Presentation Outline. Purpose. Introduction to Fault. Diagnosis. Skyrmion-Based Logic Circuits. . Ziqi Zhou, Ujjwal Guin, Peng Li, and . Vishwani. D. Agrawal. Dept. of Electrical and Computer Engineering. Auburn University, AL, USA. IEEE VLSI Test Symposium 2021.