# Failure Behavior Analysis for Reliable Distributed Embedded Systems

Save this PDF as:

Size: px
Start display at page:

## Transcription

6 Pressure Sensor 1 Pressure Sensor 2 Pressure Sensor 3 Average Filter Moving Average Filter Hysteresis Switch Fig. 9. Structure of ressure control system. tionally, a moving average filter is alied in the next ste. After that, a hysteresis switch decides when the valve has to be oened or closed. The formulae defining the digital filters are shown in figure 10. The average filter weights all of the three ressure values equally to calculate the actual overall ressure value. The moving average filter uses the last five actual ressure values to calculate the smoothed average ressure value, whereby again all values are weighted equally. i[k]: ressure i at time k [k] : average ressure at time k a[k]: smoothed average ressure at time k average filter moving average filter k [ ] a[ k] The hysteresis loo of the switch is shown in figure 11. Although a ressure between 480 and 520 bar is otimal, the threshold values of the hysteresis have been set to 490 and 510 bar in order to have a 10 bar reserve at both ends. As the target ressure is 500 bar, a tolerance interval of +/- 10 bar has been established, before the valve is oened or closed, resectively Failure Behavior. In the next ste, the failure behavior must be defined. Therefore, the failure modes of the three comonents, that can be considered as tasks of the system, are secified. As it has been exlained earlier, we use extended etri nets to describe the failure behavior. Average Filter The failure behavior model of the average filter is shown in figure 12. The general structure illustrated in figure 5 has been used to model the failure behavior of that task. The qualities of the three ressure values 1, 2, and 3 are considered as inut. If any of these values has a relative error different from zero, the task is set to the failure mode Error, otherwise the task remains in the mode Normal. If the task is in the normal mode, the outut value has no error, therefore, the error attribute is set to 0 (The setting Valve 1 = -- ( 1[ k] + 2[ k] + 3[ k] ) = -- k [ i] 3 i = 0 Fig. 10. Formulae describing the digital filters. switch command [oen/close] oen close ressure [bar] Fig. 11. Hysteresis loo used for the hysteresis switch. enter Guards: g1 : 1.error>0 or 2.error>0 or 3.error>0 g2 : 1.error==0 and 2.error==0 and 3.error==0 Actions: a1 :.error = 1/3 (1.error + 2.error + 3.error) a2 :.error = currentfailuremode Error g1 [1,2,3] g2 Normal [1,2,3] Error Normal [1,2,3] a1 [1,2,3] getstate Fig. 12. Petri net secifying the failure behavior of the average filter. of the attribute validity has been neglected to kee the examle simle). In the failure mode Error the relative error of the outut ressure is calculated using the relative errors of the inut values, as it is secified by the formula shown in figure 13. The current failure mode is reresented by an additional token on the lace currentfailuremode, asithas been mentioned earlier. The transitions outside the box are required as interface and will be connected to transitions in the suerordinated net, as it has been exlained in section error = -- ( 3 1.error + 2.error + 3.error) Fig. 13. formula secifying error roagation of the average filter Moving Average Filter The moving average filter uses the last five values of the average filter, whereby every 2 milliseconds a new value is samled. The error roagation can be secified, in general, deending on the amount of regarded samles N and the samle eriod T, as it is shown in figure 14. The w = min 1, (.MTTC) N T a.error = w.error Fig. 14. Formula secifying error roagation of an moving average filter. quotient of the MTTC over the eriod T defines how many samles can be influenced by a fault. All other samles have no error (It is assumed that MTTO» N T ). Therefore, the ratio between the number of influenced samles and the number of all samles defines the weight w of the relative error. The according etri net for the filter is shown in figure 15. Again, the failure modes Normal and Error are defined. The normal mode is valid when the inut is correct, otherwise, the task is set to the error mode. In the normal mode, again, the error attribute of the outut quality is set to zero. In the error mode, the relative error of the outut value is calculated according to the formula shown in figure 14. To exress a ersistent error with the MTTC, the latter is set to the maximal ossible integer value (MAX- INT). If an error is ersistent, all samles are faulty, therefore, a must have the same relative error as. This fm a2 exit - 6 -

7 enter Guards: g1 :.error>0 g2 :.error==0 Actions: a1 : a.error = min(1, 1/5 * floor(.mttc / 2)) *.error a2 : a.error = 0 Error CurrentFailureMode g1 Normal g2 Normal getstate exit a Fig. 15. Petri net secifying the failure behavior of the moving average filter. requirement is met if the MTTC is set to MAXINT, asin that case the weight w always evaluates to 1, i.e. the error of is assigned to the error attribute of a. Error fm a1 a a2 a value of a is lower than the actual ressure: 520( 1 x) 510 => x = 1.9% value of a is higher than the actual ressure: 480( 1 + x) 510 => x = 6.25% Fig. 16. Maximal relative error for the uer threshold value Hysteresis Switch Before we define the etri net for the hysteresis switch, we examine its failure behavior. The hysteresis loo is illustrated in figure 11 and the consequences of too low or too high a ressure are shown in figure 8. Besides the normal oeration, wrong ressure values can result in a roblematic or dangerous situation, resectively. Obviously, it is reasonable to define the three failure modes Normal, Problem, and Danger. Now, we must examine which errors result in which failure mode. At first sight, it seems quite simle to define guards like.currentvalue > 520. However, our aroach is aliable at early stages of the develoment rocess, therefore, we do not assume to have absolute values or absolute errors available. For this reason, we regard the threshold values and use the available relative errors to obtain the absolute values. This is sufficient, as it is only necessary to consider the worst case. We must regard both threshold values and, since the relative error does not exress if the faulty value is higher or lower than the actual value, it is also necessary to cover both cases in the consideration. We want to calculate exemlarily the maximal relative error that is allowed to remain in the normal mode for the uer threshold value. The uer threshold value is 510 bar. Actually, it is only necessary to oen the valve when the ressure is higher than 520 bar. If the faulty value of a is lower than the actual ressure in the tank, it must be ensured, nevertheless, that the valve is oened at latest when the ressure is higher than 520 bar. That means, if the ressure is 520 bar, the current, faulty value of a must be at least 510 bar. According to the uer formula shown in figure 16, the relative error must therefore be lower than or equal to 1.9%. If the value of a is higher than the actual ressure, the valve might be oened too early. We demand that the ressure must be at least 480 bar before the valve is oened. The according maximal relative error is calculated using the lower formula of figure 16. The remaining maximal relative errors can be calculated in the same way. The etri net reresenting the resulting failure behavior of the hysteresis switch is shown in figure 17. As the outut of this task is a direct system outut (the command for the valve), it is only necessary to outreach the failure mode to obtain the influence on the system behavior. (a.error>1.9) and (a.error<=3.8) a a.error>3.8 a.error<=1.9 Problem Danger Normal currentfailuremode Fig. 17. Petri net secifying the failure behavior of the hysteresis switch Interdeendencies of tasks. So far, the failure behavior of three single tasks has been described. Now, it is necessary to combine the single etri nets in a suerordinated etri net to obtain the system failure behavior. The overall etri net secifying the failure behavior of the ressure control system is shown in figure 18. Mainly the system structure has been rebuilt. First, an instance of the etri net reresenting the average filter is created and three qualities of the ressure values can be injected, as it has been exlained in section 3.5. The current failure mode and the quality of the average ressure value are requested from the sub net describing the average filter. The quality of the average ressure value is used as inut for an instance of the etri net secifying the failure behavior of the moving average filter. The outut of this sub net is its current failure mode and the quality of the smoothed average ressure value, which, in turn, is used as inut for the hysteresis switch. As the outut of the hysteresis switch is a direct system outut, it is reasonable not to use an information quality as outut, but only the current failure mode. An analysis can be started by simulating the etri net. Errors can be injected using the injection transitions. We create an information quality object, which is referenced by a token, and ut this token on the lace leading to the resective transition. These information quality tokens can be either defined and laced manually on the inut laces, or automatically by a searate software. The injection and the roagation of the information qualities is then done automatically by a etri net simulator [10]. Placing the tokens manually has the disadvantage that the etri net simulator requires to create and to lace new information quality tokens for each analysis run. Furthermore, it is not ossible to change the injections during an analysis. However, it is one major advantage of our aroach that the exit getstate - 7 -

9 Created tokens: 1.valid=false; 1.error = 15%; 1.MTTC=4; 2.valid=false; 2.error = 6%; 2.MTTC=4; 3.valid=true; Error average filter Injection-Interfaces Inut Places moving average filter.error=7% hysteresis switch Fig. 20. Analysis of the influences of a transient sensor fault. the smoothed ressure value a is reduced to 2.8%. That means, the efficiency of the deending machines is reduced (see figure 17). It is obviously necessary to imrove the behavior. In the next scenario, we assume that the engineers of the lant roose two ossible imrovements: First, it is ossible to reduce the maximal time of ersistence of the radiation from 4 to 3.5 milliseconds. Second, it is ossible to shield the sensors, in consequence, the relative errors could be reduced to 12% and 4.8%, resectively, that means a reduction of the disturbance by 20%. If we use these values as inut for the analysis, we obtain the result, that the reduction of the time of disturbance to 3.5 milliseconds is sufficient to hold u the normal mode. A ersistence of the radiation of less than 4 milliseconds means that at most one samle is influenced. For that reason, the moving average filter comensates the relative error Ṡhielding the sensors as assumed above, however, is not sufficient. Desite the reduced relative errors, the overall ressure has still a relative error of 5.6%. The moving average filter only reduces the error to 2.24%, what is not sufficient to remain in the normal mode. 5 Conclusion: Analyzing large distributed systems Error a a.error= 2.8% Problem In this aer, we introduced a flexible, scalable, and extendable aroach for failure behavior analysis. In comarison to existing analyses, like FTA or FMEA, our analysis yields more sohisticated results which enable the analyst to understand the system behavior in the case of faults. In the alication examle, we demonstrated the alicability of our analysis. However, we limited the comlexity of the examle to revent going beyond the scoe of a aer. Our research focuses on large, distributed embedded systems. Therefore, our analysis has been develoed for those systems. Mastering the comlexity of those systems is one major roblem. For that reason, the scalability of our aroach is of crucial imortance. A further essential asect is the ossibility to automatically generate major arts of the etri nets. For examle, it is even ossible to generate a simle failure behavior that sets the validity attribute of the outut information qualities to false, if any inut quality is invalid. For that reason, similar results as they are obtained by FMEA are yielded automatically without any additional effort of the analyst. Although the generated etri nets define only a very coarse aroximation of the actual failure behavior, it is, in contrast to a common FMEA, ossible to examine the effects of fault combinations very easily or even automatically. A further asect that is imortant for the analysis of large systems is reuse. If tasks or comonents are reused in other rojects, the etri nets defining their failure behavior, can be reused, too. If distributed systems ought to be analyzed, our aroach has two further advantages. First, the artitioning of the system is suorted, as one can examine which tasks should be assigned to which artition so that a failure of one artition has the least influence on the overall system behavior. Second, the effects of missing or delayed information, interchanged between system artitions, can be analyzed. The delay of an information can be assigned to its quality and the effects on single tasks can be modelled exlicitly with etri nets. The effect on the overall system behavior is obtained automatically, as the error roagation is rovided by the etri net simulator. 6 References [1] G. Booch, I. Jacobson, J. Rumbaugh, The Unified Modelling Language User Guide, Addison Wesley Longman, Reading, MA [2] A. Metzger, S. Queins, A Reuse- and Prototying-based Aroach for the Secification of Building Automation Systems, OMER-2 Worksho, Hersching, Germany, 2001 [3] IEC ( ), Fault Tree Analysis, International Electrotechnical Commission, Geneva, Switzerland, 1990 [4] K. Yang, C. K. Kaur, Customer Driven Reliability: Integration Of QFD And Robust Desing, Proceedings IEEE Annual Reliability and Maintainability Symosium, 1997 [5] C. J. Price, N. S. Taylor, FMEA For Multile Failures, Proceedings IEEE Annual Reliability and Maintainability Symosium, 1998 [6] B. Berard, M. Bidoit, A. Finkel, F. Laroussinie, A. Petit, L.Petrucci, Ph. Schnoebelen, P. McKenzie, Systems and Software Verification, Sringer Verlag, Berlin, 2001 [7] H. Hermanns, Construction and Verification of Performance and Reliability Models, in Bulletin of the Euroean Association for Theoretical Comuter Science (EATCS), 2001 [8] H. Hermanns, J.P. Katoen, J. Meyer-Kayser and M. Siegle, A Markov chain model checker, Proceedings of Six International Conference on Tools and Algorithms for the Construction and Analysis of Systems (TACAS), Sringer Verlag, Berlin, 2001 [9] Olaf Kummer, Simulating Synchronous Channels and Net Instances, 5. Worksho on Algorithms and Tools for Petri Nets, 1998 [10]Olaf Kummer, Frank Wienberg, RENEW - The Reference Net Worksho, Petri Net Newsletter, No. 56,

### Concurrent Program Synthesis Based on Supervisory Control

010 American Control Conference Marriott Waterfront, Baltimore, MD, USA June 30-July 0, 010 ThB07.5 Concurrent Program Synthesis Based on Suervisory Control Marian V. Iordache and Panos J. Antsaklis Abstract

### ENFORCING SAFETY PROPERTIES IN WEB APPLICATIONS USING PETRI NETS

ENFORCING SAFETY PROPERTIES IN WEB APPLICATIONS USING PETRI NETS Liviu Grigore Comuter Science Deartment University of Illinois at Chicago Chicago, IL, 60607 lgrigore@cs.uic.edu Ugo Buy Comuter Science

### The Online Freeze-tag Problem

The Online Freeze-tag Problem Mikael Hammar, Bengt J. Nilsson, and Mia Persson Atus Technologies AB, IDEON, SE-3 70 Lund, Sweden mikael.hammar@atus.com School of Technology and Society, Malmö University,

### One-Chip Linear Control IPS, F5106H

One-Chi Linear Control IPS, F5106H NAKAGAWA Sho OE Takatoshi IWAMOTO Motomitsu ABSTRACT In the fi eld of vehicle electrical comonents, the increasing demands for miniaturization, reliability imrovement

### Leak Test of Sensors with the Test Medium compressed Air

DOI 10.516/sensor013/B7.3 Leak Test of Sensors with the Test Medium comressed Air Dr. Joachim Lasien CETA Testsysteme GmbH, Marie-Curie-Str. 35-37, 4071 Hilden, GERMANY, E-Mail: joachim.lasien@cetatest.com

### Monitoring Frequency of Change By Li Qin

Monitoring Frequency of Change By Li Qin Abstract Control charts are widely used in rocess monitoring roblems. This aer gives a brief review of control charts for monitoring a roortion and some initial

### TOWARDS REAL-TIME METADATA FOR SENSOR-BASED NETWORKS AND GEOGRAPHIC DATABASES

TOWARDS REAL-TIME METADATA FOR SENSOR-BASED NETWORKS AND GEOGRAPHIC DATABASES C. Gutiérrez, S. Servigne, R. Laurini LIRIS, INSA Lyon, Bât. Blaise Pascal, 20 av. Albert Einstein 69621 Villeurbanne, France

### SQUARE GRID POINTS COVERAGED BY CONNECTED SOURCES WITH COVERAGE RADIUS OF ONE ON A TWO-DIMENSIONAL GRID

International Journal of Comuter Science & Information Technology (IJCSIT) Vol 6, No 4, August 014 SQUARE GRID POINTS COVERAGED BY CONNECTED SOURCES WITH COVERAGE RADIUS OF ONE ON A TWO-DIMENSIONAL GRID

### Simulation and Verification of Coupled Heat and Moisture Modeling

Simulation and Verification of Couled Heat and Moisture Modeling N. Williams Portal 1, M.A.P. van Aarle 2 and A.W.M. van Schijndel *,3 1 Deartment of Civil and Environmental Engineering, Chalmers University

### Problem Set 6 Solutions

( Introduction to Algorithms Aril 16, 2004 Massachusetts Institute of Technology 6046J/18410J Professors Erik Demaine and Shafi Goldwasser Handout 21 Problem Set 6 Solutions This roblem set is due in recitation

### C-Bus Voltage Calculation

D E S I G N E R N O T E S C-Bus Voltage Calculation Designer note number: 3-12-1256 Designer: Darren Snodgrass Contact Person: Darren Snodgrass Aroved: Date: Synosis: The guidelines used by installers

### Software Cognitive Complexity Measure Based on Scope of Variables

Software Cognitive Comlexity Measure Based on Scoe of Variables Kwangmyong Rim and Yonghua Choe Faculty of Mathematics, Kim Il Sung University, D.P.R.K mathchoeyh@yahoo.com Abstract In this aer, we define

### Comparing Dissimilarity Measures for Symbolic Data Analysis

Comaring Dissimilarity Measures for Symbolic Data Analysis Donato MALERBA, Floriana ESPOSITO, Vincenzo GIOVIALE and Valentina TAMMA Diartimento di Informatica, University of Bari Via Orabona 4 76 Bari,

### D.Sailaja, K.Nasaramma, M.Sumender Roy, Venkateswarlu Bondu

Predictive Modeling of Customers in Personalization Alications with Context D.Sailaja, K.Nasaramma, M.Sumender Roy, Venkateswarlu Bondu Nasaramma.K is currently ursuing her M.Tech in Godavari Institute

### Confidence Intervals for Capture-Recapture Data With Matching

Confidence Intervals for Cature-Recature Data With Matching Executive summary Cature-recature data is often used to estimate oulations The classical alication for animal oulations is to take two samles

### Load Balancing Mechanism in Agent-based Grid

Communications on Advanced Comutational Science with Alications 2016 No. 1 (2016) 57-62 Available online at www.isacs.com/cacsa Volume 2016, Issue 1, Year 2016 Article ID cacsa-00042, 6 Pages doi:10.5899/2016/cacsa-00042

### Web Application Scalability: A Model-Based Approach

Coyright 24, Software Engineering Research and Performance Engineering Services. All rights reserved. Web Alication Scalability: A Model-Based Aroach Lloyd G. Williams, Ph.D. Software Engineering Research

### An inventory control system for spare parts at a refinery: An empirical comparison of different reorder point methods

An inventory control system for sare arts at a refinery: An emirical comarison of different reorder oint methods Eric Porras a*, Rommert Dekker b a Instituto Tecnológico y de Estudios Sueriores de Monterrey,

### An Efficient Method for Improving Backfill Job Scheduling Algorithm in Cluster Computing Systems

The International ournal of Soft Comuting and Software Engineering [SCSE], Vol., No., Secial Issue: The Proceeding of International Conference on Soft Comuting and Software Engineering 0 [SCSE ], San Francisco

### FIArch Workshop. Towards Future Internet Architecture. Brussels 22 nd February 2012

FIrch Worksho Brussels 22 nd February 2012 Towards Future Internet rchitecture lex Galis University College London a.galis@ee.ucl.ac.uk www.ee.ucl.ac.uk/~agalis FIrch Worksho Brussels 22 nd February 2012

### A Modified Measure of Covert Network Performance

A Modified Measure of Covert Network Performance LYNNE L DOTY Marist College Deartment of Mathematics Poughkeesie, NY UNITED STATES lynnedoty@maristedu Abstract: In a covert network the need for secrecy

### Synopsys RURAL ELECTRICATION PLANNING SOFTWARE (LAPER) Rainer Fronius Marc Gratton Electricité de France Research and Development FRANCE

RURAL ELECTRICATION PLANNING SOFTWARE (LAPER) Rainer Fronius Marc Gratton Electricité de France Research and Develoment FRANCE Synosys There is no doubt left about the benefit of electrication and subsequently

### Topology of the Prism Model for 3D Indoor Spatial Objects

Toology of the Prism Model for 3D Indoor Satial Objects Joon-Seok Kim, Hye-Young Kang, Tae-Hoon Lee, Ki-Joune Li Deartment of Comuter Engineering Pusan National University joonseok@nu.edu, hyezero@nu.edu,

### Storage Basics Architecting the Storage Supplemental Handout

Storage Basics Architecting the Storage Sulemental Handout INTRODUCTION With digital data growing at an exonential rate it has become a requirement for the modern business to store data and analyze it

### HYPOTHESIS TESTING FOR THE PROCESS CAPABILITY RATIO. A thesis presented to. the faculty of

HYPOTHESIS TESTING FOR THE PROESS APABILITY RATIO A thesis resented to the faculty of the Russ ollege of Engineering and Technology of Ohio University In artial fulfillment of the requirement for the degree

### Operational Amplifiers Rail to Rail Input Stages Using Complementary Differential Pairs

Oerational Amlifiers Rail to Rail Inut Stages Using Comlementary Differential Pairs Submitted to: Dr. Khoman Phang Submitted by: Ahmed Gharbiya Date: November 15, 2002 Abstract A rail to rail inut common

### 2.1 Simple & Compound Propositions

2.1 Simle & Comound Proositions 1 2.1 Simle & Comound Proositions Proositional Logic can be used to analyse, simlify and establish the equivalence of statements. A knowledge of logic is essential to the

### Time-Cost Trade-Offs in Resource-Constraint Project Scheduling Problems with Overlapping Modes

Time-Cost Trade-Offs in Resource-Constraint Proect Scheduling Problems with Overlaing Modes François Berthaut Robert Pellerin Nathalie Perrier Adnène Hai February 2011 CIRRELT-2011-10 Bureaux de Montréal

### A Brief Introduction to Design of Experiments

J. K. TELFORD D A Brief Introduction to Design of Exeriments Jacqueline K. Telford esign of exeriments is a series of tests in which uroseful changes are made to the inut variables of a system or rocess

### Service Network Design with Asset Management: Formulations and Comparative Analyzes

Service Network Design with Asset Management: Formulations and Comarative Analyzes Jardar Andersen Teodor Gabriel Crainic Marielle Christiansen October 2007 CIRRELT-2007-40 Service Network Design with

### A Virtual Machine Dynamic Migration Scheduling Model Based on MBFD Algorithm

International Journal of Comuter Theory and Engineering, Vol. 7, No. 4, August 2015 A Virtual Machine Dynamic Migration Scheduling Model Based on MBFD Algorithm Xin Lu and Zhuanzhuan Zhang Abstract This

### A MOST PROBABLE POINT-BASED METHOD FOR RELIABILITY ANALYSIS, SENSITIVITY ANALYSIS AND DESIGN OPTIMIZATION

9 th ASCE Secialty Conference on Probabilistic Mechanics and Structural Reliability PMC2004 Abstract A MOST PROBABLE POINT-BASED METHOD FOR RELIABILITY ANALYSIS, SENSITIVITY ANALYSIS AND DESIGN OPTIMIZATION

### Static and Dynamic Properties of Small-world Connection Topologies Based on Transit-stub Networks

Static and Dynamic Proerties of Small-world Connection Toologies Based on Transit-stub Networks Carlos Aguirre Fernando Corbacho Ramón Huerta Comuter Engineering Deartment, Universidad Autónoma de Madrid,

### Risk in Revenue Management and Dynamic Pricing

OPERATIONS RESEARCH Vol. 56, No. 2, March Aril 2008,. 326 343 issn 0030-364X eissn 1526-5463 08 5602 0326 informs doi 10.1287/ore.1070.0438 2008 INFORMS Risk in Revenue Management and Dynamic Pricing Yuri

### On the predictive content of the PPI on CPI inflation: the case of Mexico

On the redictive content of the PPI on inflation: the case of Mexico José Sidaoui, Carlos Caistrán, Daniel Chiquiar and Manuel Ramos-Francia 1 1. Introduction It would be natural to exect that shocks to

### CABRS CELLULAR AUTOMATON BASED MRI BRAIN SEGMENTATION

XI Conference "Medical Informatics & Technologies" - 2006 Rafał Henryk KARTASZYŃSKI *, Paweł MIKOŁAJCZAK ** MRI brain segmentation, CT tissue segmentation, Cellular Automaton, image rocessing, medical

### Int. J. Advanced Networking and Applications Volume: 6 Issue: 4 Pages: 2386-2392 (2015) ISSN: 0975-0290

2386 Survey: Biological Insired Comuting in the Network Security V Venkata Ramana Associate Professor, Deartment of CSE, CBIT, Proddatur, Y.S.R (dist), A.P-516360 Email: ramanacsecbit@gmail.com Y.Subba

### Solutions to Problem Set 3

Massachusetts Institute of Technology 6.042J/18.062J, Fall 05: Mathematics for Comuter Science October 3 Prof. Albert R. Meyer and Prof. Ronitt Rubinfeld revised October 8, 2005, 979 minutes Solutions

### Buffer Capacity Allocation: A method to QoS support on MPLS networks**

Buffer Caacity Allocation: A method to QoS suort on MPLS networks** M. K. Huerta * J. J. Padilla X. Hesselbach ϒ R. Fabregat O. Ravelo Abstract This aer describes an otimized model to suort QoS by mean

### THE REVISED CONSUMER PRICE INDEX IN ZAMBIA

THE REVISED CONSUMER PRICE INDEX IN ZAMBIA Submitted by the Central Statistical office of Zambia Abstract This aer discusses the Revised Consumer Price Index (CPI) in Zambia, based on revised weights,

### CRITICAL AVIATION INFRASTRUCTURES VULNERABILITY ASSESSMENT TO TERRORIST THREATS

Review of the Air Force Academy No (23) 203 CRITICAL AVIATION INFRASTRUCTURES VULNERABILITY ASSESSMENT TO TERRORIST THREATS Cătălin CIOACĂ Henri Coandă Air Force Academy, Braşov, Romania Abstract: The

### Safety evaluation of digital post-release environment sensor data interface for distributed fuzing systems

Safety evaluation of digital ost-release environment sensor data interface for distributed fuzing systems 57 th Fuze Conference, Newark, NJ Wednesday, July 30 th, 2014 Oen Session IIIA, 3:20 PM S. Ebenhöch,

### Decision-Making on-board an Autonomous Agile Earth-Observing Satellite

Decision-Making on-board an Automous Agile Earth-Observing Satellite Grégory Beaumet and Gérard Verfaillie ONERA, Toulouse, France {Gregory.Beaumet, Gerard.Verfaillie}@onera.fr Marie-Claire Charmeau CNES,

NAVAL POSTGRADUATE SCHOOL MONTEREY CALIFORNIA THESIS SYMMETRICAL RESIDUE-TO-BINARY CONVERSION ALGORITHM PIPELINED FPGA IMPLEMENTATION AND TESTING LOGIC FOR USE IN HIGH-SPEED FOLDING DIGITIZERS by Ross

### 1 Gambler s Ruin Problem

Coyright c 2009 by Karl Sigman 1 Gambler s Ruin Problem Let N 2 be an integer and let 1 i N 1. Consider a gambler who starts with an initial fortune of \$i and then on each successive gamble either wins

### GAS TURBINE PERFORMANCE WHAT MAKES THE MAP?

GAS TURBINE PERFORMANCE WHAT MAKES THE MAP? by Rainer Kurz Manager of Systems Analysis and Field Testing and Klaus Brun Senior Sales Engineer Solar Turbines Incororated San Diego, California Rainer Kurz

### Automatic Search for Correlated Alarms

Automatic Search for Correlated Alarms Klaus-Dieter Tuchs, Peter Tondl, Markus Radimirsch, Klaus Jobmann Institut für Allgemeine Nachrichtentechnik, Universität Hannover Aelstraße 9a, 0167 Hanover, Germany

### Design of A Knowledge Based Trouble Call System with Colored Petri Net Models

2005 IEEE/PES Transmission and Distribution Conference & Exhibition: Asia and Pacific Dalian, China Design of A Knowledge Based Trouble Call System with Colored Petri Net Models Hui-Jen Chuang, Chia-Hung

### http://www.ualberta.ca/~mlipsett/engm541/engm541.htm

ENGM 670 & MECE 758 Modeling and Simulation of Engineering Systems (Advanced Toics) Winter 011 Lecture 9: Extra Material M.G. Lisett University of Alberta htt://www.ualberta.ca/~mlisett/engm541/engm541.htm

### Memory management. Chapter 4: Memory Management. Memory hierarchy. In an ideal world. Basic memory management. Fixed partitions: multiple programs

Memory management Chater : Memory Management Part : Mechanisms for Managing Memory asic management Swaing Virtual Page relacement algorithms Modeling age relacement algorithms Design issues for aging systems

### A Simple Model of Pricing, Markups and Market. Power Under Demand Fluctuations

A Simle Model of Pricing, Markus and Market Power Under Demand Fluctuations Stanley S. Reynolds Deartment of Economics; University of Arizona; Tucson, AZ 85721 Bart J. Wilson Economic Science Laboratory;

### A New Method for Eye Detection in Color Images

Journal of Comuter Engineering 1 (009) 3-11 A New Method for Eye Detection in Color Images Mohammadreza Ramezanour Deartment of Comuter Science & Research Branch Azad University, Arak.Iran E-mail: Mr.ramezanoor@gmail.com

### Large-Scale IP Traceback in High-Speed Internet: Practical Techniques and Theoretical Foundation

Large-Scale IP Traceback in High-Seed Internet: Practical Techniques and Theoretical Foundation Jun Li Minho Sung Jun (Jim) Xu College of Comuting Georgia Institute of Technology {junli,mhsung,jx}@cc.gatech.edu

### FDA CFR PART 11 ELECTRONIC RECORDS, ELECTRONIC SIGNATURES

Document: MRM-1004-GAPCFR11 (0005) Page: 1 / 18 FDA CFR PART 11 ELECTRONIC RECORDS, ELECTRONIC SIGNATURES AUDIT TRAIL ECO # Version Change Descrition MATRIX- 449 A Ga Analysis after adding controlled documents

### A NONLINEAR SWITCHING CONTROL METHOD FOR MAGNETIC BEARING SYSTEMS MINIMIZING THE POWER CONSUMPTION

Coyright IFAC 5th Triennial World Congress, Barcelona, Sain A NONLINEAR SWITCHING CONTROL METHOD FOR MAGNETIC BEARING SYSTEMS MINIMIZING THE POWER CONSUMPTION Kang-Zhi Liu Λ; Akihiro Ikai Λ Akihiro Ogata

### The risk of using the Q heterogeneity estimator for software engineering experiments

Dieste, O., Fernández, E., García-Martínez, R., Juristo, N. 11. The risk of using the Q heterogeneity estimator for software engineering exeriments. The risk of using the Q heterogeneity estimator for

### It is important to be very clear about our definitions of probabilities.

Use Bookmarks for electronic content links 7.6 Bayesian odds 7.6.1 Introduction The basic ideas of robability have been introduced in Unit 7.3 in the book, leading to the concet of conditional robability.

### STUDIES ON DYNAMIC VISCOSITY CHANGES OF THE ENGINE S LUBRICATION OIL DEPENDING ON THE PRESSURE

Journal of KONES Powertrain and Transort, Vol. 20, No. 4 2013 STUDIES ON DYNAMIC VISCOSITY CHANGES OF THE ENGINE S LUBRICATION OIL DEPENDING ON THE PRESSURE Grzegorz Sikora Gdynia Maritime University Deartment

### Theoretical comparisons of average normalized gain calculations

PHYSICS EDUCATIO RESEARCH All submissions to PERS should be sent referably electronically to the Editorial Office of AJP, and then they will be forwarded to the PERS editor for consideration. Theoretical

### POISSON PROCESSES. Chapter 2. 2.1 Introduction. 2.1.1 Arrival processes

Chater 2 POISSON PROCESSES 2.1 Introduction A Poisson rocess is a simle and widely used stochastic rocess for modeling the times at which arrivals enter a system. It is in many ways the continuous-time

### An Associative Memory Readout in ESN for Neural Action Potential Detection

g An Associative Memory Readout in ESN for Neural Action Potential Detection Nicolas J. Dedual, Mustafa C. Ozturk, Justin C. Sanchez and José C. Princie Abstract This aer describes how Echo State Networks

### 4 Perceptron Learning Rule

Percetron Learning Rule Objectives Objectives - Theory and Examles - Learning Rules - Percetron Architecture -3 Single-Neuron Percetron -5 Multile-Neuron Percetron -8 Percetron Learning Rule -8 Test Problem

### COST CALCULATION IN COMPLEX TRANSPORT SYSTEMS

OST ALULATION IN OMLEX TRANSORT SYSTEMS Zoltán BOKOR 1 Introduction Determining the real oeration and service costs is essential if transort systems are to be lanned and controlled effectively. ost information

### The Fundamental Incompatibility of Scalable Hamiltonian Monte Carlo and Naive Data Subsampling

The Fundamental Incomatibility of Scalable Hamiltonian Monte Carlo and Naive Data Subsamling Michael Betancourt Deartment of Statistics, University of Warwick, Coventry, UK CV4 7A BETANAPHA@GMAI.COM Abstract

### Re-Dispatch Approach for Congestion Relief in Deregulated Power Systems

Re-Disatch Aroach for Congestion Relief in Deregulated ower Systems Ch. Naga Raja Kumari #1, M. Anitha 2 #1, 2 Assistant rofessor, Det. of Electrical Engineering RVR & JC College of Engineering, Guntur-522019,

### From Simulation to Experiment: A Case Study on Multiprocessor Task Scheduling

From to Exeriment: A Case Study on Multirocessor Task Scheduling Sascha Hunold CNRS / LIG Laboratory Grenoble, France sascha.hunold@imag.fr Henri Casanova Det. of Information and Comuter Sciences University

### Point Location. Preprocess a planar, polygonal subdivision for point location queries. p = (18, 11)

Point Location Prerocess a lanar, olygonal subdivision for oint location ueries. = (18, 11) Inut is a subdivision S of comlexity n, say, number of edges. uild a data structure on S so that for a uery oint

### X How to Schedule a Cascade in an Arbitrary Graph

X How to Schedule a Cascade in an Arbitrary Grah Flavio Chierichetti, Cornell University Jon Kleinberg, Cornell University Alessandro Panconesi, Saienza University When individuals in a social network

### Moving Objects Tracking in Video by Graph Cuts and Parameter Motion Model

International Journal of Comuter Alications (0975 8887) Moving Objects Tracking in Video by Grah Cuts and Parameter Motion Model Khalid Housni, Driss Mammass IRF SIC laboratory, Faculty of sciences Agadir

### Overview of Lecture 3. Model Checking with SPIN. First attempt (revisited) Linear Temporal Logic (LTL) CDP #3

Concurrent and Distributed Programming htt://fmt.cs.utwente.nl/courses/cd/ Mel Checking with SPIN CDP #3 Overview of Lecture 3 Ch. 4 - Verification of Concurrent Programs linear temoral logic (LTL) deductive

### MODELLING AND SIMULATION OF A DISH STIRLING SOLAR ENGINE. Sergio Bittanti Antonio De Marco Marcello Farina Silvano Spelta

MODELLING AND SIMULATION OF A DISH STIRLING SOLAR ENGINE Sergio Bittanti Antonio De Marco Marcello Farina Silvano Selta Diartimento di Elettronica e Informazione, Politecnico di Milano, Via Ponzio 34,

### 17609: Continuous Data Protection Transforms the Game

17609: Continuous Data Protection Transforms the Game Wednesday, August 12, 2015: 8:30 AM-9:30 AM Southern Hemishere 5 (Walt Disney World Dolhin) Tony Negro - EMC Rebecca Levesque 21 st Century Software

### Learning Human Behavior from Analyzing Activities in Virtual Environments

Learning Human Behavior from Analyzing Activities in Virtual Environments C. BAUCKHAGE 1, B. GORMAN 2, C. THURAU 3 & M. HUMPHRYS 2 1) Deutsche Telekom Laboratories, Berlin, Germany 2) Dublin City University,

### The Magnus-Derek Game

The Magnus-Derek Game Z. Nedev S. Muthukrishnan Abstract We introduce a new combinatorial game between two layers: Magnus and Derek. Initially, a token is laced at osition 0 on a round table with n ositions.

### Software Model Checking: Theory and Practice

Software Model Checking: Theory and Practice Lecture: Secification Checking - Temoral Logic Coyright 2004, Matt Dwyer, John Hatcliff, and Robby. The syllabus and all lectures for this course are coyrighted

### An Analysis of Reliable Classifiers through ROC Isometrics

An Analysis of Reliable Classifiers through ROC Isometrics Stijn Vanderlooy s.vanderlooy@cs.unimaas.nl Ida G. Srinkhuizen-Kuyer kuyer@cs.unimaas.nl Evgueni N. Smirnov smirnov@cs.unimaas.nl MICC-IKAT, Universiteit

### Branch-and-Price for Service Network Design with Asset Management Constraints

Branch-and-Price for Servicee Network Design with Asset Management Constraints Jardar Andersen Roar Grønhaug Mariellee Christiansen Teodor Gabriel Crainic December 2007 CIRRELT-2007-55 Branch-and-Price

### START Selected Topics in Assurance

START Selected Toics in Assurance Related Technologies Table of Contents Understanding Binomial Sequential Testing Introduction Double Samling (Two Stage) Testing Procedures The Sequential Probability

### Drinking water systems are vulnerable to

34 UNIVERSITIES COUNCIL ON WATER RESOURCES ISSUE 129 PAGES 34-4 OCTOBER 24 Use of Systems Analysis to Assess and Minimize Water Security Risks James Uber Regan Murray and Robert Janke U. S. Environmental

### Simulink Implementation of a CDMA Smart Antenna System

Simulink Imlementation of a CDMA Smart Antenna System MOSTAFA HEFNAWI Deartment of Electrical and Comuter Engineering Royal Military College of Canada Kingston, Ontario, K7K 7B4 CANADA Abstract: - The

### The Graphical Method. Lecture 1

References: Anderson, Sweeney, Williams: An Introduction to Management Science - quantitative aroaches to decision maing 7 th ed Hamdy A Taha: Oerations Research, An Introduction 5 th ed Daellenbach, George,

### Softmax Model as Generalization upon Logistic Discrimination Suffers from Overfitting

Journal of Data Science 12(2014),563-574 Softmax Model as Generalization uon Logistic Discrimination Suffers from Overfitting F. Mohammadi Basatini 1 and Rahim Chiniardaz 2 1 Deartment of Statistics, Shoushtar

### Variations on the Gambler s Ruin Problem

Variations on the Gambler s Ruin Problem Mat Willmott December 6, 2002 Abstract. This aer covers the history and solution to the Gambler s Ruin Problem, and then exlores the odds for each layer to win

### The impact of metadata implementation on webpage visibility in search engine results (Part II) q

Information Processing and Management 41 (2005) 691 715 www.elsevier.com/locate/inforoman The imact of metadata imlementation on webage visibility in search engine results (Part II) q Jin Zhang *, Alexandra

### Shunt Active Power Filter with Dynamic Output Current Limitation

Shunt Active Power Filter with Dynamic Outut Current Limitation R. Pregitzer, J. G. Pinto, Luís F.C. Monteiro, João L. Afonso Industrial Electronics Deartment University of Minho Guimarães, Portugal Email:

### Interaction Expressions A Powerful Formalism for Describing Inter-Workflow Dependencies

Interaction Exressions A Powerful Formalism for Describing Inter-Workflow Deendencies Christian Heinlein, Peter Dadam Det. Databases and Information Systems University of Ulm, Germany {heinlein,dadam}@informatik.uni-ulm.de

### A Study of Active Queue Management for Congestion Control

In IEEE INFOCOM 2 A Study of Active Queue Management for Congestion Control Victor Firoiu Marty Borden 1 vfiroiu@nortelnetworks.com mborden@tollbridgetech.com Nortel Networks TollBridge Technologies 6

### Stochastic Derivation of an Integral Equation for Probability Generating Functions

Journal of Informatics and Mathematical Sciences Volume 5 (2013), Number 3,. 157 163 RGN Publications htt://www.rgnublications.com Stochastic Derivation of an Integral Equation for Probability Generating

### IEEM 101: Inventory control

IEEM 101: Inventory control Outline of this series of lectures: 1. Definition of inventory. Examles of where inventory can imrove things in a system 3. Deterministic Inventory Models 3.1. Continuous review:

### A Framework to Schedule Parametric Dataflow Applications on Many-Core Platforms

A Framework to Schedule Parametric Dataflow Alications on Many-Core Platforms Vagelis ebelis Pascal Fradet Alain Girault INRIA Univ. Grenoble Ales, F-38000, Grenoble, France STMicroelectronics first.last@inria.fr

### Computational Finance The Martingale Measure and Pricing of Derivatives

1 The Martingale Measure 1 Comutational Finance The Martingale Measure and Pricing of Derivatives 1 The Martingale Measure The Martingale measure or the Risk Neutral robabilities are a fundamental concet

### Provable Ownership of File in De-duplication Cloud Storage

1 Provable Ownershi of File in De-dulication Cloud Storage Chao Yang, Jian Ren and Jianfeng Ma School of CS, Xidian University Xi an, Shaanxi, 710071. Email: {chaoyang, jfma}@mail.xidian.edu.cn Deartment

### Migration to Object Oriented Platforms: A State Transformation Approach

Migration to Object Oriented Platforms: A State Transformation Aroach Ying Zou, Kostas Kontogiannis Det. of Electrical & Comuter Engineering University of Waterloo Waterloo, ON, N2L 3G1, Canada {yzou,

### Improved Symmetric Lists

Imroved Symmetric Lists Technical Reort MIP-49 October, 24 Christian Bachmaier and Marcus Raitner University of Passau, 943 Passau, Germany Fax: +49 85 59 332 {bachmaier,raitner}@fmi.uni-assau.de Abstract.

### Pressure Drop in Air Piping Systems Series of Technical White Papers from Ohio Medical Corporation

Pressure Dro in Air Piing Systems Series of Technical White Paers from Ohio Medical Cororation Ohio Medical Cororation Lakeside Drive Gurnee, IL 600 Phone: (800) 448-0770 Fax: (847) 855-604 info@ohiomedical.com

### NOISE ANALYSIS OF NIKON D40 DIGITAL STILL CAMERA

NOISE ANALYSIS OF NIKON D40 DIGITAL STILL CAMERA F. Mojžíš, J. Švihlík Detartment of Comuting and Control Engineering, ICT Prague Abstract This aer is devoted to statistical analysis of Nikon D40 digital

### Pinhole Optics. OBJECTIVES To study the formation of an image without use of a lens.

Pinhole Otics Science, at bottom, is really anti-intellectual. It always distrusts ure reason and demands the roduction of the objective fact. H. L. Mencken (1880-1956) OBJECTIVES To study the formation

### Butterfly: Privacy Preserving Publishing on Multiple Quasi-Identifiers

Butterfly: Privacy Preserving Publishing on Multile Quasi-Identifiers Technical Reort TR 2008-18 School of Comuting Science, Simon Fraser University Jian Pei Simon Fraser University jei@cs.sfu.ca Yufei