A LINGUISTIC MODEL OF AGGREGATION IN VIRTUAL MANUFACTURING PROCESSES

Size: px
Start display at page:

Download "A LINGUISTIC MODEL OF AGGREGATION IN VIRTUAL MANUFACTURING PROCESSES"

Transcription

1 A LINGUISTIC MODEL OF AGGREGATION IN VIRTUAL MANUFACTURING PROCESSES Vasle CRĂCIUNEAN 1 ABSTRACT: The current objectves to ncrease the standards of qualty and effcency n manufacturng processes can be acheved only through the best combnaton of nputs, ndependent of spatal dstance between them. Electronc communcaton solves the problem of the dstance between resources. As a natural consequence, achevng these objectves s solved by vrtual producton processes. Due to the complexty of these producton processes they cannot be mastered wthout the help of accurate and complex models that reflect real-tme evoluton and breakdown of aggregate physcal and logcal actons focused on goals. Ths paper proposes a lngustc model for buldng vrtual producton systems by assemblng ntellgent elementary actons wth a hgh degree of ndependence. Thus from a lot of ndependent actons whch we call actons of aggregaton, we defne an aggregaton system of actons capable of generatng aggregate producton processes. In our model the aggregated producton process s a word n a language over the alphabet consstng of actons of aggregaton. KEY WORDS: acton of aggregaton, aggregaton system of actons, aggregated producton process, applcaton of aggregaton, applcaton of dsaggregaton. 1 INTRODUCTION Through the producton process we understand the transformaton of a gven set of resources (raw materals, sem-fnshed goods, energy, labor, equpment) nto fnshed products by aggregatng specfc actons accordng to ther manufacturng recpes. The techncal and technologcal progress has contrbuted to ncreased communcaton capacty and optmal use of the resources and actvtes regardless of ther dstrbuton n space leadng to the possblty of managng them vrtual. It s clear that technology s essental to manage vrtual actons but on the other hand the real need of collaboraton n vrtual organzatons creates the mpetus for the creaton of approprate technologes. Software and hardware technologes open opportuntes for developng new better ways of coordnaton and synchronzaton of the actons nvolved n producton processes. It s a fact that vrtual organzatons based on the archtecture of a dstrbuted manufacturng system, well organzed, can brng a sgnfcant ncrease n effcency and product qualty. Ths paper proposes a model for buldng vrtual producton systems by assemblng actons wth a hgh degree of ndependence. 1 Lucan Blaga Unversty of Sbu, Engneerng Faculty, Romana E-mal: cracunean@sln.ro 124 Constructon of an aggregate producton process from actons nvolves two dstnct actvtes: create new actons and creatng producton processes by aggregatng exstng actons. Therefore when we want to develop a producton process wll have to frst try to buld on exstng actons and just after that to buld new actons needed for our producton process requrement. Ths actons wll enlarge our base of actons. Our base of actons, on whch we buld producton process, together wth facltes for acton constructon and management s the actons nfrastructure. The actons nfrastructure conssts of three dstnct models: a standard acton model, an actons connecton model, and an acton deployment model. A standard acton model defnes what a vald acton s, and how to create a new acton n the actons nfrastructure. All reusable actons wll be bult, thus, accordng to the model of the standard acton. Each actons nfrastructure has a lbrary of reusable actons conformng to the standard acton model. The actons connecton model defnes a collecton of connectors and support facltes for actons aggregaton. Therefore, the connecton model determnes how to buld a producton process or a larger acton from exstng actons. The acton deployment model descrbes how the actons wll be mplemented n a work envronment. ACADEMIC JOURNAL OF MANUFACTURING ENGINEERING, VOL. 12, ISSUE 3/2014

2 Based on ths realty and the belef that ths s the evoluton of producton processes, ths paper proposes a lngustc model for buldng complex producton processes startng from actons. Smplfyng thngs, n ths paper a producton process s a word n a language. All the actons of a producton process are desgned to operate n a parallel and dstrbuted envronment. In 3 we ntroduce the noton of an aggregaton system of actons (S) and the language L(S,f) assocated wth t. The aggregaton system of actons s a general framework that defnes a set of producton processes. In 4. we ntroduce the noton of aggregated producton process and functonal aggregated producton process. We beleve that the present paper provdes the necessary mechansms to buld statc or dynamc optmal producton processes by assemblng ndependent actons. 2 PRELIMINARY NOTIONS AND NOTATIONS Let X be a set. The famly of subsets of X s denoted by Ƥ(X). The cardnalty of X s denoted by X. The set of natural numbers, {0, 1, 2,....} s denoted by N. The empty set s denoted by Ø. An alphabet s a fnte nonempty set of abstract symbols. For an alphabet V we denote by V * the set of all strngs of symbols n V. The empty strng s denoted by λ. The set of nonempty strngs over V, that s V * -{λ}, s denoted by V +. Let Sub(w) denote the set of subwords of w. Each subset of V * s called a language over V. The length of a strng x V* (the number of symbol occurrences n X) s denoted by x. The number of occurrences of a gven symbol a V n x V * s denoted by x a. Let Symb(w) denote the set of symbol occurrences n w. 3 AGGREGATION SYSTEM OF ACTIONS In ths paper we consder that the atomc producton unt of the process s the acton. The actons and the resources on whch the actons are produced, are dstrbuted n a vrtual network of companes workng together. Actons are very nhomogeneous begnnng wth actons of desgn, procurement, logstcs, manufacturng, qualty control etc. There wll be software actons that wll store and dynamcally process all data on the evoluton of the producton process. Therefor we begn by defnng the noton of acton of aggregaton on wtch our model s based. Defnton 3.1. An acton of aggregaton a s a construct of the form a = (I,O,M) I={(r,c,e ) =1,2,...m ; r s a resource, c s the quantty of that resource, e s an event}; The resource r s called an nput resource and represents the necessary resource n the c quantty for the acton a, and e s called an nput event. O={(r o,c o,e o ) o=1,2,...n ; r o s a resource or a fnal product, c o s the quantty of the resource, e o s an event}; If r o s the resource then t s called the output resource and c o s the quantty of that resource, else r o s the fnal output product. The event e o s the output event. M s a set of data and assocated metadata such as duraton of acton, the mnmum allowed stock, costs, techncal data about the acton, software components, etc. Although vrtual producton processes are words n a language that are strngs of actons, the executon order s not strctly that from the word of aggregate producton process. Each component embeds n t a certan degree of ntellgence. It wll know how to check f t has provded the necessary context for startng, for example t wll know to check f t has the necessary resources for the smooth conduct. If ths condtons are not satsfed t wll wat untl these condtons are met. The wat wll last untl t gets a message about updatng the nput resources and then t wll restart the process wth context verfcaton. The acton wll know how to decrement stock, for example, wth consumed resources and ncrement the stock wth the resource created by t and also sendng the correspondng event. An acton of aggregaton also does a very mportant thng that s real-tme update of developments related to varous data such as start tme, the actual length, watng tme, costs, etc. We consder the set A of actons of aggregaton nvolved n a producton process, then we defne the precedence actons by two functons, namely: a bottom-up functon of precedence f: A Ƥ(A), defned as follows: f(a) = {b A O a ϵ I b }, ( ) a A and a top-down functon of precedence g:a Ƥ(A), defned as follows: g(b) = {a A O a ϵ I b }, ( ) b A. In the followng we defne some useful languages over the set A. The symbols from the A set, represent real elementary actons and therefore ACADEMIC JOURNAL OF MANUFACTURING ENGINEERING, VOL. 12,ISSUE 3/

3 the semantc load of the elements of the vocabulary s well defned. Defnton 3.2. An aggregaton system of actons s a construct of the form A s a fnte set of actons called acton of aggregaton; f s a functon f: A Ƥ(A) named bottom-up functon of precedence; g s a functon g: A Ƥ(A) named top-down functon of precedence; L X s a language over A, ( ) X Ƥ(A). It s obvous that L X can be an empty language for some X Ƥ(A). Based on the functon f we defne the applcaton of aggregaton φ as follows: Defnton 3.3. An applcaton of aggregaton s an applcaton φ: Ƥ(A) Ƥ(A) defned as follows: φ X = x X f(x) X Ƥ A. In ths condtons φ n (X) can be defned as: φ 0 (X) = X ( ) X Ƥ(A); φ n (X) = φ(φ n-1 (X)). We observe that φ n (X) Ƥ(A) ( ) n N and ( ) X Ƥ(A), and therefore over the set φ n (X) we have the language L φ n (X) as defned n Defnton 3.2. The set {φ n (X); n 0, X Ƥ(A)} s fnte, because A s a fnte set. Smlarly, we defne the applcaton of dsaggregaton ψ: Defnton 3.4. An applcaton of dsaggregaton s an applcaton ψ: Ƥ(A) Ƥ(A) defned as follows: ψ X = x X g x X Ƥ A. Smlarly, ψ n (X) can be defned as: ψ 0 (X) = X ( ) X Ƥ(A); ψ n (X) = ψ (ψ n-1 (X)). We observe that ψ n (X) Ƥ(A) ( ) n N and ( ) X Ƥ(A), and therefore over the set ψ n (X) we have the language L ψ n (X) as defned n Defnton 3.2. The set {ψ n (X); n 0, X Ƥ(A)} s fnte, because A s a fnte set. In the followng we defne the language specfed by the aggregaton system S. We must pont out that one can defne two mportant languages specfed by the aggregaton system S, namely one startng from the bottom-up precedence functon f wtch we denote by L(S,f) and the other startng from the top-down precedence functon g wtch we denote by L(S,g). In ths paper we wll deal only wth the L(S,f) language, whch s why we use the aggregaton applcaton φ:ƥ(a) Ƥ(A) as defned above, by the bottom-up precedence functon f. Defnton 3.5. Let be an aggregaton system of actons. Then the language L(S,f) specfed by the aggregaton system of actons S s: L S, f = Lemma 3.1. Let X Ƥ(A) =0 be an aggregaton system of actons and the language then R(X) = =0 R(X) = R 1 (X) R 2 (X)(R 3 (X)) * R 4 (X) R 1 X = R 2 X = R 3 X = 1 1 = k= ACADEMIC JOURNAL OF MANUFACTURING ENGINEERING, VOL. 12, ISSUE 3/2014

4 R 4 X = 2 2 = 1 k= 1 Proof. For X Ƥ(A) we consder the followng sequence: X, φ(x), φ 2 (X),, φ k (X), Because the set X A s fnte, t s obvous that ( ) and j such that φ (X) = φ j (X) and therefore L φ X = L φ j (X). Let 1 and 2 ( 1 < 2 ) be the smallest such values for and j. If we denote produces as output a resource or a fnal product and a specfc event. If we have a strng of actons of aggregaton α=a 1 a 2...a m a Symb(α) s of the form a = (I a,o a,m a ) then we denote and wth I α = I a a Symb (α) O α = O a a Symb (α) R 1 X = R 2 X = R 3 X = R 4 X = 1 1 = k= = 1 k= 1 then the Lemma 3.1 s proved. We have a prefx from 0 to 1 whch s not repeated, followed by R 3 whch can repeat from 0 to nfnte and then we have a remander (a part from a perod). Theorem 3.1. Let be an aggregaton system of actons. If all languages L X, X Ƥ(A) are of type {0,1,2,3} n the Chomsky herarchy, then the language L(S,f) s of type n the Chomsky herarchy. Proof. It follows mmedately from closng the languages from the Chomsky herarchy at unon, catenaton, catenaton closure and from Lemma AGGREGATED PRODUCTION PROCESS We wll further look at an acton of aggregaton as a basc producton process whch allows as nput a set of resources n specfed quanttes and a specfed type of event and Defnton 4.1. An acton of aggregaton block of level k ntated by X s a construct of the form: Ɓ k (X) = (I k, O k, L k (X), B k ) L k (X)= I k = I a αε B k X O k = O a αε B k (X) B k s an object, named block-board, that can store nformaton of the form (resource, quantty, event). B k s used by the actons of aggregaton for communcaton. Defnton 4.2. Let be an aggregaton system of actons and X Ƥ(A). Then the language R X = ACADEMIC JOURNAL OF MANUFACTURING ENGINEERING, VOL. 12,ISSUE 3/ =0 s called an aggregated producton network generated by X. Defnton 4.3. Let S be an aggregaton system of actons and R X = =0 be an aggregated producton network generated by X Ƥ(A). Then the aggregated producton network R(X) s a functonal aggregated producton network f for all,1,2 we have the acton of aggregaton block Ɓ k (X) = (I k, O k, L k (X), B k ) and I k+1 =O k. Lemma 4.1. Let

5 be an aggregaton system of actons and X Ƥ(A). If R X = =0 s a functonal aggregated producton network then: ) φ (ψ(x))=x ( )X Ƥ(A), ) ) ψ (φ (X))=X ( )X Ƥ(A), φ n (ψ n (X))=X ( )X Ƥ(A). v) ψ n (φ n (X))=X ( )X Ƥ(A). Proof. Ponts ) and ) are obvous from the defntons of φ and ψ. Statements ) and v) are proved by nducton. We prove only the asserton ) because v) has the same demonstraton. For n=1 we have the asserton ). We assume the statement s true for n,.e. φ n (ψ n (X))=X. We replace X wth ψ(x) and obtan φ n (ψ n (ψ(x)))= ψ(x). We apply φ on ths relatonshp and get φ n+1 (ψ n+1 (X)) = φ(ψ(x)) = X. Thus n each block, two control loops of the aggregated producton process close, one downward and one upward. Each block receves through breakdown a partcular path to follow by the ascendng block and reports back ts progress by aggregaton. Defnton 4.4. Let be an aggregaton system of actons, R(X) an aggregated producton network generated by X and α=α 1 α 2 α n, α L φ (X) a fnte word from R X. Therefore, A= (I, O, α, φ, ψ, B) s called an aggregated producton process : I = I α1 O = O α R X, n = n, n N s called an aggregated producton network generated by X and length n. We remark that R(X, n) contans all aggregated producton processes generated by X and length n, namely all aggregated producton processes of the form: A= (I, O, α, φ, ψ, B) : I = a X I a O = a φ k (X) α R(X,n), B s lke n the Defnton 4.2. In practce we are nterested n an aggregated producton processes that has a lot of nputs I and plenty of outputs O. Obvously, we need to search for our producton process n a subset of R(X, n), whch we denote R(X, Y, n) : X s a mnmal subset Z wth the property a Z I a n = mn O = I n a φ k (X) Y = {a φ n (X) O a O Ø} n R X, Y, n = L (φ k X ψ n k Y ) O a O a, n N α The φ and ψ applcatons are the restrctons of the φ and ψ applcatons from 3.3 and 3.4 defntons. B s an object, called process-board, that can store nformaton of the form (resource, quantty, event). B s used by the actons of aggregaton for communcaton. Defnton 4.5. Let S be an aggregaton system of actons and A=(I,O,α,φ,ψ,B) an aggregated producton process α=α 1 α 2 α n, α Lφ(X).Then the aggregated producton process A s a functonal aggregated producton process f ( ) =1,, n-1 we have I α+1 = O α. 128 Defnton 4.6. Let be an aggregaton system of actons. Then Defnton 4.7. The language R(X, Y, n) s called a network of acceptable aggregated producton process. As can be seen from the above there are a lot of equvalent acceptable producton processes n the sense that they make the same products. You should therefore choose the optmal aggregated producton process, problem whch wll be the subjects of future papers. Also, buldng generatve grammars for languages assocated wth an aggregaton system of actons wll be treated n future papers. 5 CONCLUSION The purpose of ths model s to generate aggregated producton processes by combnng ndependent actons. ACADEMIC JOURNAL OF MANUFACTURING ENGINEERING, VOL. 12, ISSUE 3/2014

6 A process as defned, wll run n a parallel and dstrbuted envronment. Startng the process mples parallel actvaton of all actons of aggregaton. Each acton wll get ts nput data from the block-board and wrte all ts output data also on the block-board. Of course, these operatons wll synchronze dynamcally. We note that we can get more functonal aggregated producton processes that do the same from the perspectve of the process, namely aggregated processes that have the same nputs and outputs. It s natural to ask the queston of choosng the best soluton for our process, optmal n terms of executon tme and cost. The problem of fndng the optmal aggregate can be put n two ways: statc determnaton of an optmum aggregated process or buldng an aggregated process that evolves over tme by changng hs actons accordng to ther effcency. 6 REFERENCES Mowshowtz A., Vrtual Organzaton: A vson of Management n the Informaton Age, The Informaton, 1994 Matthas Dehmer, Abbe Mowshowtz, and Frank Emmert-Streb - Advances n Network Complexty Wley-VCH Verlag GmbH & Co. KGaA, Boschstr. 12, Wenhem, Germany Păun Gh., Mecansme generatve ale proceselor economce, Ed Tehncă, Bucureşt, 1988 Dassow J., Păun Gh., On the power of membrane computng, J. Unversal Computer Sc., 5, 2 (1999), 33-49, ( Calude Ch. S., Păun Gh., Computng wth Cells and Atoms an ntroducton to quantum, DNA and membrane computng, Taylor & Francs, 2001 Alfred V. Aho, Rav Seth, Jeffrey D. Ullman, Complers: Prncples, Technques, and Tools, Addson Wesley, Salomaa, A., Formal Languages, New York, Academc Press, Crăcunean, V., Proectarea Translatoarelor, Sbu, Edtura Unverstăț Lucan Blaga Sbu, 2014, ISBN Crăcunean, V., Stochastc grammars for ntellgent software systems modellng, Proceedngs of the 8 th WSEAS Internatonal Conference, Mathematcal Methods and Computatonal Technques n Electrcal Engneerng (MMACTEE), Bucharest, Romana 2006, pag , ISSN , ISBN Crăcunean, V., Stochastc Grammars n Smulaton Models WSEAS Transactons on Computers, Issue 2, Volume 6, February 2007, pag , ISSN Faban R., Crăcunean, V., Popa E. M., Intellgent system modelng wth total fuzzy grammars, Proceedngs of the 8 th WSEAS Internatonal Conference, Mathematcal Methods and Computatonal Technques n Electrcal Engneerng (MMACTEE), Bucharest, Romana 2006, pag , ISSN , ISBN Crăcunean, V., Faban R., Popa E. M., Package archtecture optmzaton n software applcaton desgn Proceedngs of the 8 th WSEAS Internatonal Conference, Mathematcal Methods and Computatonal Technques n Electrcal Engneerng (MMACTEE), Bucharest, Romana 2006, pag , ISSN , ISBN Crăcunean, V., Faban R., Popa E. M.,Total Fuzzy Grammar Drven Archtecture for Intellgent Software Sytems WSEAS Transactons on Computers, Issue 2, Volume 6, February 2007, pag , ISSN Crăcunean, V., Faban R., Popa E. M.,Algorthm for Optmal Decomposton of Software Applcatons WSEAS Transactons on Computers, Issue 2, Volume 6, February 2007, pag , ISSN Crăcunean, V., Aron C.E., Faban R., Hunyad I.D., Mult Level Recursve Specfcatons for Context Free Grammars - Proceedngs of the 11 th WSEAS Internatonal Conference on COMPUTERS, Agos Nkolaos, Crete Island, Greece, 2007, pag , ISSN , ISBN Crăcunean, V., Faban R., Hunyad I.D, Popa E. M.,Fx pont nternal herarchy specfcaton for context free grammars - Proceedngs of the 11 th WSEAS Internatonal Conference on COMPUTERS, Agos Nkolaos, Crete Island, Greece, 2007, pag , ISSN , ISBN ACADEMIC JOURNAL OF MANUFACTURING ENGINEERING, VOL. 12,ISSUE 3/

Sum of Linear and Fractional Multiobjective Programming Problem under Fuzzy Rules Constraints

Sum of Linear and Fractional Multiobjective Programming Problem under Fuzzy Rules Constraints Australan Journal of Basc and Appled Scences, 2(4): 1204-1208, 2008 ISSN 1991-8178 Sum of Lnear and Fractonal Multobjectve Programmng Problem under Fuzzy Rules Constrants 1 2 Sanjay Jan and Kalash Lachhwan

More information

An Optimal Algorithm for Prufer Codes *

An Optimal Algorithm for Prufer Codes * J. Software Engneerng & Applcatons, 2009, 2: 111-115 do:10.4236/jsea.2009.22016 Publshed Onlne July 2009 (www.scrp.org/journal/jsea) An Optmal Algorthm for Prufer Codes * Xaodong Wang 1, 2, Le Wang 3,

More information

For instance, ; the five basic number-sets are increasingly more n A B & B A A = B (1)

For instance, ; the five basic number-sets are increasingly more n A B & B A A = B (1) Secton 1.2 Subsets and the Boolean operatons on sets If every element of the set A s an element of the set B, we say that A s a subset of B, or that A s contaned n B, or that B contans A, and we wrte A

More information

Module Management Tool in Software Development Organizations

Module Management Tool in Software Development Organizations Journal of Computer Scence (5): 8-, 7 ISSN 59-66 7 Scence Publcatons Management Tool n Software Development Organzatons Ahmad A. Al-Rababah and Mohammad A. Al-Rababah Faculty of IT, Al-Ahlyyah Amman Unversty,

More information

A mathematical programming approach to the analysis, design and scheduling of offshore oilfields

A mathematical programming approach to the analysis, design and scheduling of offshore oilfields 17 th European Symposum on Computer Aded Process Engneerng ESCAPE17 V. Plesu and P.S. Agach (Edtors) 2007 Elsever B.V. All rghts reserved. 1 A mathematcal programmng approach to the analyss, desgn and

More information

Parallelism for Nested Loops with Non-uniform and Flow Dependences

Parallelism for Nested Loops with Non-uniform and Flow Dependences Parallelsm for Nested Loops wth Non-unform and Flow Dependences Sam-Jn Jeong Dept. of Informaton & Communcaton Engneerng, Cheonan Unversty, 5, Anseo-dong, Cheonan, Chungnam, 330-80, Korea. seong@cheonan.ac.kr

More information

NUMERICAL SOLVING OPTIMAL CONTROL PROBLEMS BY THE METHOD OF VARIATIONS

NUMERICAL SOLVING OPTIMAL CONTROL PROBLEMS BY THE METHOD OF VARIATIONS ARPN Journal of Engneerng and Appled Scences 006-017 Asan Research Publshng Network (ARPN). All rghts reserved. NUMERICAL SOLVING OPTIMAL CONTROL PROBLEMS BY THE METHOD OF VARIATIONS Igor Grgoryev, Svetlana

More information

6.854 Advanced Algorithms Petar Maymounkov Problem Set 11 (November 23, 2005) With: Benjamin Rossman, Oren Weimann, and Pouya Kheradpour

6.854 Advanced Algorithms Petar Maymounkov Problem Set 11 (November 23, 2005) With: Benjamin Rossman, Oren Weimann, and Pouya Kheradpour 6.854 Advanced Algorthms Petar Maymounkov Problem Set 11 (November 23, 2005) Wth: Benjamn Rossman, Oren Wemann, and Pouya Kheradpour Problem 1. We reduce vertex cover to MAX-SAT wth weghts, such that the

More information

Virtual Memory. Background. No. 10. Virtual Memory: concept. Logical Memory Space (review) Demand Paging(1) Virtual Memory

Virtual Memory. Background. No. 10. Virtual Memory: concept. Logical Memory Space (review) Demand Paging(1) Virtual Memory Background EECS. Operatng System Fundamentals No. Vrtual Memory Prof. Hu Jang Department of Electrcal Engneerng and Computer Scence, York Unversty Memory-management methods normally requres the entre process

More information

On Some Entertaining Applications of the Concept of Set in Computer Science Course

On Some Entertaining Applications of the Concept of Set in Computer Science Course On Some Entertanng Applcatons of the Concept of Set n Computer Scence Course Krasmr Yordzhev *, Hrstna Kostadnova ** * Assocate Professor Krasmr Yordzhev, Ph.D., Faculty of Mathematcs and Natural Scences,

More information

Solving two-person zero-sum game by Matlab

Solving two-person zero-sum game by Matlab Appled Mechancs and Materals Onlne: 2011-02-02 ISSN: 1662-7482, Vols. 50-51, pp 262-265 do:10.4028/www.scentfc.net/amm.50-51.262 2011 Trans Tech Publcatons, Swtzerland Solvng two-person zero-sum game by

More information

A NOTE ON FUZZY CLOSURE OF A FUZZY SET

A NOTE ON FUZZY CLOSURE OF A FUZZY SET (JPMNT) Journal of Process Management New Technologes, Internatonal A NOTE ON FUZZY CLOSURE OF A FUZZY SET Bhmraj Basumatary Department of Mathematcal Scences, Bodoland Unversty, Kokrajhar, Assam, Inda,

More information

Non-Split Restrained Dominating Set of an Interval Graph Using an Algorithm

Non-Split Restrained Dominating Set of an Interval Graph Using an Algorithm Internatonal Journal of Advancements n Research & Technology, Volume, Issue, July- ISS - on-splt Restraned Domnatng Set of an Interval Graph Usng an Algorthm ABSTRACT Dr.A.Sudhakaraah *, E. Gnana Deepka,

More information

Research of Dynamic Access to Cloud Database Based on Improved Pheromone Algorithm

Research of Dynamic Access to Cloud Database Based on Improved Pheromone Algorithm , pp.197-202 http://dx.do.org/10.14257/dta.2016.9.5.20 Research of Dynamc Access to Cloud Database Based on Improved Pheromone Algorthm Yongqang L 1 and Jn Pan 2 1 (Software Technology Vocatonal College,

More information

AADL : about scheduling analysis

AADL : about scheduling analysis AADL : about schedulng analyss Schedulng analyss, what s t? Embedded real-tme crtcal systems have temporal constrants to meet (e.g. deadlne). Many systems are bult wth operatng systems provdng multtaskng

More information

Assembler. Shimon Schocken. Spring Elements of Computing Systems 1 Assembler (Ch. 6) Compiler. abstract interface.

Assembler. Shimon Schocken. Spring Elements of Computing Systems 1 Assembler (Ch. 6) Compiler. abstract interface. IDC Herzlya Shmon Schocken Assembler Shmon Schocken Sprng 2005 Elements of Computng Systems 1 Assembler (Ch. 6) Where we are at: Human Thought Abstract desgn Chapters 9, 12 abstract nterface H.L. Language

More information

A New Approach For the Ranking of Fuzzy Sets With Different Heights

A New Approach For the Ranking of Fuzzy Sets With Different Heights New pproach For the ankng of Fuzzy Sets Wth Dfferent Heghts Pushpnder Sngh School of Mathematcs Computer pplcatons Thapar Unversty, Patala-7 00 Inda pushpndersnl@gmalcom STCT ankng of fuzzy sets plays

More information

MODELING THE RELIABILITY OF INFORMATION MANAGEMENT SYSTEMS BASED ON MISSION SPECIFIC TOOLS SET SOFTWARE

MODELING THE RELIABILITY OF INFORMATION MANAGEMENT SYSTEMS BASED ON MISSION SPECIFIC TOOLS SET SOFTWARE Knowledge Dynamcs MODELING THE ELIABILITY OF INFOMATION MANAGEMENT SYSTEMS BASED ON MISSION SPECIFIC TOOLS SET SOFTWAE Cezar VASILESCU Assocate Professor, egonal Department of Defense esources Management

More information

Problem Definitions and Evaluation Criteria for Computational Expensive Optimization

Problem Definitions and Evaluation Criteria for Computational Expensive Optimization Problem efntons and Evaluaton Crtera for Computatonal Expensve Optmzaton B. Lu 1, Q. Chen and Q. Zhang 3, J. J. Lang 4, P. N. Suganthan, B. Y. Qu 6 1 epartment of Computng, Glyndwr Unversty, UK Faclty

More information

Multiblock method for database generation in finite element programs

Multiblock method for database generation in finite element programs Proc. of the 9th WSEAS Int. Conf. on Mathematcal Methods and Computatonal Technques n Electrcal Engneerng, Arcachon, October 13-15, 2007 53 Multblock method for database generaton n fnte element programs

More information

Cluster Analysis of Electrical Behavior

Cluster Analysis of Electrical Behavior Journal of Computer and Communcatons, 205, 3, 88-93 Publshed Onlne May 205 n ScRes. http://www.scrp.org/ournal/cc http://dx.do.org/0.4236/cc.205.350 Cluster Analyss of Electrcal Behavor Ln Lu Ln Lu, School

More information

MODULE DESIGN BASED ON INTERFACE INTEGRATION TO MAXIMIZE PRODUCT VARIETY AND MINIMIZE FAMILY COST

MODULE DESIGN BASED ON INTERFACE INTEGRATION TO MAXIMIZE PRODUCT VARIETY AND MINIMIZE FAMILY COST INTERNATIONAL CONFERENCE ON ENGINEERING DESIGN, ICED 07 28-31 AUGUST 2007, CITE DES SCIENCES ET DE L'INDUSTRIE, PARIS, FRANCE MODULE DESIGN BASED ON INTERFACE INTEGRATION TO MAIMIZE PRODUCT VARIETY AND

More information

APPLICATION OF MULTIVARIATE LOSS FUNCTION FOR ASSESSMENT OF THE QUALITY OF TECHNOLOGICAL PROCESS MANAGEMENT

APPLICATION OF MULTIVARIATE LOSS FUNCTION FOR ASSESSMENT OF THE QUALITY OF TECHNOLOGICAL PROCESS MANAGEMENT 3. - 5. 5., Brno, Czech Republc, EU APPLICATION OF MULTIVARIATE LOSS FUNCTION FOR ASSESSMENT OF THE QUALITY OF TECHNOLOGICAL PROCESS MANAGEMENT Abstract Josef TOŠENOVSKÝ ) Lenka MONSPORTOVÁ ) Flp TOŠENOVSKÝ

More information

Harvard University CS 101 Fall 2005, Shimon Schocken. Assembler. Elements of Computing Systems 1 Assembler (Ch. 6)

Harvard University CS 101 Fall 2005, Shimon Schocken. Assembler. Elements of Computing Systems 1 Assembler (Ch. 6) Harvard Unversty CS 101 Fall 2005, Shmon Schocken Assembler Elements of Computng Systems 1 Assembler (Ch. 6) Why care about assemblers? Because Assemblers employ some nfty trcks Assemblers are the frst

More information

Optimal planning of selective waste collection

Optimal planning of selective waste collection Sustanable Development and Plannng V 78 Optmal plannng of selectve aste collecton S. Racu, D. Costescu, E. Roşca & M. Popa Unversty Poltehnca of Bucharest, Romana Abstract The paper presents an optmsaton

More information

ON SOME ENTERTAINING APPLICATIONS OF THE CONCEPT OF SET IN COMPUTER SCIENCE COURSE

ON SOME ENTERTAINING APPLICATIONS OF THE CONCEPT OF SET IN COMPUTER SCIENCE COURSE Yordzhev K., Kostadnova H. Інформаційні технології в освіті ON SOME ENTERTAINING APPLICATIONS OF THE CONCEPT OF SET IN COMPUTER SCIENCE COURSE Yordzhev K., Kostadnova H. Some aspects of programmng educaton

More information

Scheduling Remote Access to Scientific Instruments in Cyberinfrastructure for Education and Research

Scheduling Remote Access to Scientific Instruments in Cyberinfrastructure for Education and Research Schedulng Remote Access to Scentfc Instruments n Cybernfrastructure for Educaton and Research Je Yn 1, Junwe Cao 2,3,*, Yuexuan Wang 4, Lanchen Lu 1,3 and Cheng Wu 1,3 1 Natonal CIMS Engneerng and Research

More information

Overview. Basic Setup [9] Motivation and Tasks. Modularization 2008/2/20 IMPROVED COVERAGE CONTROL USING ONLY LOCAL INFORMATION

Overview. Basic Setup [9] Motivation and Tasks. Modularization 2008/2/20 IMPROVED COVERAGE CONTROL USING ONLY LOCAL INFORMATION Overvew 2 IMPROVED COVERAGE CONTROL USING ONLY LOCAL INFORMATION Introducton Mult- Smulator MASIM Theoretcal Work and Smulaton Results Concluson Jay Wagenpfel, Adran Trachte Motvaton and Tasks Basc Setup

More information

Load Balancing for Hex-Cell Interconnection Network

Load Balancing for Hex-Cell Interconnection Network Int. J. Communcatons, Network and System Scences,,, - Publshed Onlne Aprl n ScRes. http://www.scrp.org/journal/jcns http://dx.do.org/./jcns.. Load Balancng for Hex-Cell Interconnecton Network Saher Manaseer,

More information

Compiler Design. Spring Register Allocation. Sample Exercises and Solutions. Prof. Pedro C. Diniz

Compiler Design. Spring Register Allocation. Sample Exercises and Solutions. Prof. Pedro C. Diniz Compler Desgn Sprng 2014 Regster Allocaton Sample Exercses and Solutons Prof. Pedro C. Dnz USC / Informaton Scences Insttute 4676 Admralty Way, Sute 1001 Marna del Rey, Calforna 90292 pedro@s.edu Regster

More information

TECHNIQUE OF FORMATION HOMOGENEOUS SAMPLE SAME OBJECTS. Muradaliyev A.Z.

TECHNIQUE OF FORMATION HOMOGENEOUS SAMPLE SAME OBJECTS. Muradaliyev A.Z. TECHNIQUE OF FORMATION HOMOGENEOUS SAMPLE SAME OBJECTS Muradalyev AZ Azerbajan Scentfc-Research and Desgn-Prospectng Insttute of Energetc AZ1012, Ave HZardab-94 E-mal:aydn_murad@yahoocom Importance of

More information

Behavioral Model Extraction of Search Engines Used in an Intelligent Meta Search Engine

Behavioral Model Extraction of Search Engines Used in an Intelligent Meta Search Engine Behavoral Model Extracton of Search Engnes Used n an Intellgent Meta Search Engne AVEH AVOUSI Computer Department, Azad Unversty, Garmsar Branch BEHZAD MOSHIRI Electrcal and Computer department, Faculty

More information

TWO DIAGNOSTIC MODELS FOR PLC CONTROLLED FLEXIBLE MANUFACTURING SYSTEMS. W. HU*, A. G. STARR* and A. Y. T. LEUNG*

TWO DIAGNOSTIC MODELS FOR PLC CONTROLLED FLEXIBLE MANUFACTURING SYSTEMS. W. HU*, A. G. STARR* and A. Y. T. LEUNG* TWO DIAGNOSTIC MODELS FOR PLC CONTROLLED FLEXIBLE MANUFACTURING SYSTEMS W. HU*, A. G. STARR* and A. Y. T. LEUNG* * Manchester School of Engneerng, The Unversty of Manchester, Manchester M13 9PL, UK To

More information

PHYSICS-ENHANCED L-SYSTEMS

PHYSICS-ENHANCED L-SYSTEMS PHYSICS-ENHANCED L-SYSTEMS Hansrud Noser 1, Stephan Rudolph 2, Peter Stuck 1 1 Department of Informatcs Unversty of Zurch, Wnterthurerstr. 190 CH-8057 Zurch Swtzerland noser(stuck)@f.unzh.ch, http://www.f.unzh.ch/~noser(~stuck)

More information

A FINITE-CAPACITY BEAM-SEARCH-ALGORITHM FOR PRODUCTION SCHEDULING IN SEMICONDUCTOR MANUFACTURING. Ilka Habenicht Lars Mönch

A FINITE-CAPACITY BEAM-SEARCH-ALGORITHM FOR PRODUCTION SCHEDULING IN SEMICONDUCTOR MANUFACTURING. Ilka Habenicht Lars Mönch Proceedngs of the 2002 Wnter Smulaton Conference E. Yücesan, C.-H. Chen, J. L. Snowdon, and J. M. Charnes, eds. A FINITE-CAPACITY BEAM-SEARCH-ALGORITHM FOR PRODUCTION SCHEDULING IN SEMICONDUCTOR MANUFACTURING

More information

An Application of the Dulmage-Mendelsohn Decomposition to Sparse Null Space Bases of Full Row Rank Matrices

An Application of the Dulmage-Mendelsohn Decomposition to Sparse Null Space Bases of Full Row Rank Matrices Internatonal Mathematcal Forum, Vol 7, 2012, no 52, 2549-2554 An Applcaton of the Dulmage-Mendelsohn Decomposton to Sparse Null Space Bases of Full Row Rank Matrces Mostafa Khorramzadeh Department of Mathematcal

More information

Virtual Machine Migration based on Trust Measurement of Computer Node

Virtual Machine Migration based on Trust Measurement of Computer Node Appled Mechancs and Materals Onlne: 2014-04-04 ISSN: 1662-7482, Vols. 536-537, pp 678-682 do:10.4028/www.scentfc.net/amm.536-537.678 2014 Trans Tech Publcatons, Swtzerland Vrtual Machne Mgraton based on

More information

The Codesign Challenge

The Codesign Challenge ECE 4530 Codesgn Challenge Fall 2007 Hardware/Software Codesgn The Codesgn Challenge Objectves In the codesgn challenge, your task s to accelerate a gven software reference mplementaton as fast as possble.

More information

Cordial and 3-Equitable Labeling for Some Star Related Graphs

Cordial and 3-Equitable Labeling for Some Star Related Graphs Internatonal Mathematcal Forum, 4, 009, no. 31, 1543-1553 Cordal and 3-Equtable Labelng for Some Star Related Graphs S. K. Vadya Department of Mathematcs, Saurashtra Unversty Rajkot - 360005, Gujarat,

More information

Assembler. Building a Modern Computer From First Principles.

Assembler. Building a Modern Computer From First Principles. Assembler Buldng a Modern Computer From Frst Prncples www.nand2tetrs.org Elements of Computng Systems, Nsan & Schocken, MIT Press, www.nand2tetrs.org, Chapter 6: Assembler slde Where we are at: Human Thought

More information

Concurrent Apriori Data Mining Algorithms

Concurrent Apriori Data Mining Algorithms Concurrent Apror Data Mnng Algorthms Vassl Halatchev Department of Electrcal Engneerng and Computer Scence York Unversty, Toronto October 8, 2015 Outlne Why t s mportant Introducton to Assocaton Rule Mnng

More information

Data Representation in Digital Design, a Single Conversion Equation and a Formal Languages Approach

Data Representation in Digital Design, a Single Conversion Equation and a Formal Languages Approach Data Representaton n Dgtal Desgn, a Sngle Converson Equaton and a Formal Languages Approach Hassan Farhat Unversty of Nebraska at Omaha Abstract- In the study of data representaton n dgtal desgn and computer

More information

Chapter 6 Programmng the fnte element method Inow turn to the man subject of ths book: The mplementaton of the fnte element algorthm n computer programs. In order to make my dscusson as straghtforward

More information

Kent State University CS 4/ Design and Analysis of Algorithms. Dept. of Math & Computer Science LECT-16. Dynamic Programming

Kent State University CS 4/ Design and Analysis of Algorithms. Dept. of Math & Computer Science LECT-16. Dynamic Programming CS 4/560 Desgn and Analyss of Algorthms Kent State Unversty Dept. of Math & Computer Scence LECT-6 Dynamc Programmng 2 Dynamc Programmng Dynamc Programmng, lke the dvde-and-conquer method, solves problems

More information

Notes on Organizing Java Code: Packages, Visibility, and Scope

Notes on Organizing Java Code: Packages, Visibility, and Scope Notes on Organzng Java Code: Packages, Vsblty, and Scope CS 112 Wayne Snyder Java programmng n large measure s a process of defnng enttes (.e., packages, classes, methods, or felds) by name and then usng

More information

A MOVING MESH APPROACH FOR SIMULATION BUDGET ALLOCATION ON CONTINUOUS DOMAINS

A MOVING MESH APPROACH FOR SIMULATION BUDGET ALLOCATION ON CONTINUOUS DOMAINS Proceedngs of the Wnter Smulaton Conference M E Kuhl, N M Steger, F B Armstrong, and J A Jones, eds A MOVING MESH APPROACH FOR SIMULATION BUDGET ALLOCATION ON CONTINUOUS DOMAINS Mark W Brantley Chun-Hung

More information

CMPS 10 Introduction to Computer Science Lecture Notes

CMPS 10 Introduction to Computer Science Lecture Notes CPS 0 Introducton to Computer Scence Lecture Notes Chapter : Algorthm Desgn How should we present algorthms? Natural languages lke Englsh, Spansh, or French whch are rch n nterpretaton and meanng are not

More information

Outline. Self-Organizing Maps (SOM) US Hebbian Learning, Cntd. The learning rule is Hebbian like:

Outline. Self-Organizing Maps (SOM) US Hebbian Learning, Cntd. The learning rule is Hebbian like: Self-Organzng Maps (SOM) Turgay İBRİKÇİ, PhD. Outlne Introducton Structures of SOM SOM Archtecture Neghborhoods SOM Algorthm Examples Summary 1 2 Unsupervsed Hebban Learnng US Hebban Learnng, Cntd 3 A

More information

Transaction-Consistent Global Checkpoints in a Distributed Database System

Transaction-Consistent Global Checkpoints in a Distributed Database System Proceedngs of the World Congress on Engneerng 2008 Vol I Transacton-Consstent Global Checkponts n a Dstrbuted Database System Jang Wu, D. Manvannan and Bhavan Thurasngham Abstract Checkpontng and rollback

More information

Reliability and Performance Models for Grid Computing

Reliability and Performance Models for Grid Computing Relablty and Performance Models for Grd Computng Yuan-Shun Da,2, Jack Dongarra,3,4 Department of Electrcal Engneerng and Computer Scence, Unversty of Tennessee, Knoxvlle 2 Department of Industral and Informaton

More information

The Greedy Method. Outline and Reading. Change Money Problem. Greedy Algorithms. Applications of the Greedy Strategy. The Greedy Method Technique

The Greedy Method. Outline and Reading. Change Money Problem. Greedy Algorithms. Applications of the Greedy Strategy. The Greedy Method Technique //00 :0 AM Outlne and Readng The Greedy Method The Greedy Method Technque (secton.) Fractonal Knapsack Problem (secton..) Task Schedulng (secton..) Mnmum Spannng Trees (secton.) Change Money Problem Greedy

More information

CHAPTER 2 DECOMPOSITION OF GRAPHS

CHAPTER 2 DECOMPOSITION OF GRAPHS CHAPTER DECOMPOSITION OF GRAPHS. INTRODUCTION A graph H s called a Supersubdvson of a graph G f H s obtaned from G by replacng every edge uv of G by a bpartte graph,m (m may vary for each edge by dentfyng

More information

b * -Open Sets in Bispaces

b * -Open Sets in Bispaces Internatonal Journal of Mathematcs and Statstcs Inventon (IJMSI) E-ISSN: 2321 4767 P-ISSN: 2321-4759 wwwjmsorg Volume 4 Issue 6 August 2016 PP- 39-43 b * -Open Sets n Bspaces Amar Kumar Banerjee 1 and

More information

DEVELOPMENT AND RESEARCH OF OPEN-LOOP MODELS THE SUBSYSTEM "PROCESSOR-MEMORY" OF MULTIPROCESSOR SYSTEMS ARCHITECTURES UMA, NUMA AND SUMA

DEVELOPMENT AND RESEARCH OF OPEN-LOOP MODELS THE SUBSYSTEM PROCESSOR-MEMORY OF MULTIPROCESSOR SYSTEMS ARCHITECTURES UMA, NUMA AND SUMA DEVELOPMENT AND RESEARCH OF OPEN-LOOP MODELS THE SUBSYSTEM "PROCESSOR-MEMORY" OF MULTIPROCESSOR SYSTEMS ARCHITECTURES UMA, NUMA AND SUMA A. I. Martyshkn Penza State Technologcal Unversty, Baydukov Proyezd

More information

Simulation Based Analysis of FAST TCP using OMNET++

Simulation Based Analysis of FAST TCP using OMNET++ Smulaton Based Analyss of FAST TCP usng OMNET++ Umar ul Hassan 04030038@lums.edu.pk Md Term Report CS678 Topcs n Internet Research Sprng, 2006 Introducton Internet traffc s doublng roughly every 3 months

More information

Course Introduction. Algorithm 8/31/2017. COSC 320 Advanced Data Structures and Algorithms. COSC 320 Advanced Data Structures and Algorithms

Course Introduction. Algorithm 8/31/2017. COSC 320 Advanced Data Structures and Algorithms. COSC 320 Advanced Data Structures and Algorithms Course Introducton Course Topcs Exams, abs, Proects A quc loo at a few algorthms 1 Advanced Data Structures and Algorthms Descrpton: We are gong to dscuss algorthm complexty analyss, algorthm desgn technques

More information

Application of Improved Fish Swarm Algorithm in Cloud Computing Resource Scheduling

Application of Improved Fish Swarm Algorithm in Cloud Computing Resource Scheduling , pp.40-45 http://dx.do.org/10.14257/astl.2017.143.08 Applcaton of Improved Fsh Swarm Algorthm n Cloud Computng Resource Schedulng Yu Lu, Fangtao Lu School of Informaton Engneerng, Chongqng Vocatonal Insttute

More information

Efficient Distributed File System (EDFS)

Efficient Distributed File System (EDFS) Effcent Dstrbuted Fle System (EDFS) (Sem-Centralzed) Debessay(Debsh) Fesehaye, Rahul Malk & Klara Naherstedt Unversty of Illnos-Urbana Champagn Contents Problem Statement, Related Work, EDFS Desgn Rate

More information

an assocated logc allows the proof of safety and lveness propertes. The Unty model nvolves on the one hand a programmng language and, on the other han

an assocated logc allows the proof of safety and lveness propertes. The Unty model nvolves on the one hand a programmng language and, on the other han UNITY as a Tool for Desgn and Valdaton of a Data Replcaton System Phlppe Quennec Gerard Padou CENA IRIT-ENSEEIHT y Nnth Internatonal Conference on Systems Engneerng Unversty of Nevada, Las Vegas { 14-16

More information

A Resources Virtualization Approach Supporting Uniform Access to Heterogeneous Grid Resources 1

A Resources Virtualization Approach Supporting Uniform Access to Heterogeneous Grid Resources 1 A Resources Vrtualzaton Approach Supportng Unform Access to Heterogeneous Grd Resources 1 Cunhao Fang 1, Yaoxue Zhang 2, Song Cao 3 1 Tsnghua Natonal Labatory of Inforamaton Scence and Technology 2 Department

More information

Subspace clustering. Clustering. Fundamental to all clustering techniques is the choice of distance measure between data points;

Subspace clustering. Clustering. Fundamental to all clustering techniques is the choice of distance measure between data points; Subspace clusterng Clusterng Fundamental to all clusterng technques s the choce of dstance measure between data ponts; D q ( ) ( ) 2 x x = x x, j k = 1 k jk Squared Eucldean dstance Assumpton: All features

More information

Imperialist Competitive Algorithm with Variable Parameters to Determine the Global Minimum of Functions with Several Arguments

Imperialist Competitive Algorithm with Variable Parameters to Determine the Global Minimum of Functions with Several Arguments Fourth Internatonal Conference Modellng and Development of Intellgent Systems October 8 - November, 05 Lucan Blaga Unversty Sbu - Romana Imperalst Compettve Algorthm wth Varable Parameters to Determne

More information

Remote Sensing Image Retrieval Algorithm based on MapReduce and Characteristic Information

Remote Sensing Image Retrieval Algorithm based on MapReduce and Characteristic Information Remote Sensng Image Retreval Algorthm based on MapReduce and Characterstc Informaton Zhang Meng 1, 1 Computer School, Wuhan Unversty Hube, Wuhan430097 Informaton Center, Wuhan Unversty Hube, Wuhan430097

More information

Convex Fuzzy Set, Balanced Fuzzy Set, and Absolute Convex Fuzzy Set in a Fuzzy Vector Space

Convex Fuzzy Set, Balanced Fuzzy Set, and Absolute Convex Fuzzy Set in a Fuzzy Vector Space IOSR Journal of Mathematcs (IOSR-JM) e-issn: 2278-5728, p-issn: 239-765X. Volume 2, Issue 2 Ver. VI (Mar. - pr. 206), PP 7-24 www.osrjournals.org Conve Fuzzy Set, alanced Fuzzy Set, and bsolute Conve Fuzzy

More information

A Binarization Algorithm specialized on Document Images and Photos

A Binarization Algorithm specialized on Document Images and Photos A Bnarzaton Algorthm specalzed on Document mages and Photos Ergna Kavalleratou Dept. of nformaton and Communcaton Systems Engneerng Unversty of the Aegean kavalleratou@aegean.gr Abstract n ths paper, a

More information

A protocol for mixed-criticality management in switched Ethernet networks

A protocol for mixed-criticality management in switched Ethernet networks A protocol for mxed-crtcalty management n swtched Ethernet networks Olver CROS, Laurent GEORGE Unversté Pars-Est, LIGM / ESIEE, France cros@ece.fr,lgeorge@eee.org Xaotng LI ECE Pars / LACSC, France xaotng.l@ece.fr

More information

VRT012 User s guide V0.1. Address: Žirmūnų g. 27, Vilnius LT-09105, Phone: (370-5) , Fax: (370-5) ,

VRT012 User s guide V0.1. Address: Žirmūnų g. 27, Vilnius LT-09105, Phone: (370-5) , Fax: (370-5) , VRT012 User s gude V0.1 Thank you for purchasng our product. We hope ths user-frendly devce wll be helpful n realsng your deas and brngng comfort to your lfe. Please take few mnutes to read ths manual

More information

Outline. Digital Systems. C.2: Gates, Truth Tables and Logic Equations. Truth Tables. Logic Gates 9/8/2011

Outline. Digital Systems. C.2: Gates, Truth Tables and Logic Equations. Truth Tables. Logic Gates 9/8/2011 9/8/2 2 Outlne Appendx C: The Bascs of Logc Desgn TDT4255 Computer Desgn Case Study: TDT4255 Communcaton Module Lecture 2 Magnus Jahre 3 4 Dgtal Systems C.2: Gates, Truth Tables and Logc Equatons All sgnals

More information

A PATTERN RECOGNITION APPROACH TO IMAGE SEGMENTATION

A PATTERN RECOGNITION APPROACH TO IMAGE SEGMENTATION 1 THE PUBLISHING HOUSE PROCEEDINGS OF THE ROMANIAN ACADEMY, Seres A, OF THE ROMANIAN ACADEMY Volume 4, Number 2/2003, pp.000-000 A PATTERN RECOGNITION APPROACH TO IMAGE SEGMENTATION Tudor BARBU Insttute

More information

Tsinghua University at TAC 2009: Summarizing Multi-documents by Information Distance

Tsinghua University at TAC 2009: Summarizing Multi-documents by Information Distance Tsnghua Unversty at TAC 2009: Summarzng Mult-documents by Informaton Dstance Chong Long, Mnle Huang, Xaoyan Zhu State Key Laboratory of Intellgent Technology and Systems, Tsnghua Natonal Laboratory for

More information

Pose, Posture, Formation and Contortion in Kinematic Systems

Pose, Posture, Formation and Contortion in Kinematic Systems Pose, Posture, Formaton and Contorton n Knematc Systems J. Rooney and T. K. Tanev Department of Desgn and Innovaton, Faculty of Technology, The Open Unversty, Unted Kngdom Abstract. The concepts of pose,

More information

Modelling a Queuing System for a Virtual Agricultural Call Center

Modelling a Queuing System for a Virtual Agricultural Call Center 25-28 July 2005, Vla Real, Portugal Modellng a Queung System for a Vrtual Agrcultural Call Center İnc Şentarlı, a, Arf Orçun Sakarya b a, Çankaya Unversty, Department of Management,06550, Balgat, Ankara,

More information

Ontology Generator from Relational Database Based on Jena

Ontology Generator from Relational Database Based on Jena Computer and Informaton Scence Vol. 3, No. 2; May 2010 Ontology Generator from Relatonal Database Based on Jena Shufeng Zhou (Correspondng author) College of Mathematcs Scence, Laocheng Unversty No.34

More information

Bridges and cut-vertices of Intuitionistic Fuzzy Graph Structure

Bridges and cut-vertices of Intuitionistic Fuzzy Graph Structure Internatonal Journal of Engneerng, Scence and Mathematcs (UGC Approved) Journal Homepage: http://www.jesm.co.n, Emal: jesmj@gmal.com Double-Blnd Peer Revewed Refereed Open Access Internatonal Journal -

More information

Evaluation of Parallel Processing Systems through Queuing Model

Evaluation of Parallel Processing Systems through Queuing Model ISSN 2278-309 Vkas Shnde, Internatonal Journal of Advanced Volume Trends 4, n Computer No.2, March Scence - and Aprl Engneerng, 205 4(2), March - Aprl 205, 36-43 Internatonal Journal of Advanced Trends

More information

Polyhedral Compilation Foundations

Polyhedral Compilation Foundations Polyhedral Complaton Foundatons Lous-Noël Pouchet pouchet@cse.oho-state.edu Dept. of Computer Scence and Engneerng, the Oho State Unversty Feb 8, 200 888., Class # Introducton: Polyhedral Complaton Foundatons

More information

Specifying Database Updates Using A Subschema

Specifying Database Updates Using A Subschema Specfyng Database Updates Usng A Subschema Sona Rstć, Pavle Mogn 2, Ivan Luovć 3 Busness College, V. Perća 4, 2000 Nov Sad, Yugoslava sdrstc@uns.ns.ac.yu 2 Vctora Unversty of Wellngton, School of Mathematcal

More information

Mathematics 256 a course in differential equations for engineering students

Mathematics 256 a course in differential equations for engineering students Mathematcs 56 a course n dfferental equatons for engneerng students Chapter 5. More effcent methods of numercal soluton Euler s method s qute neffcent. Because the error s essentally proportonal to the

More information

Positive Semi-definite Programming Localization in Wireless Sensor Networks

Positive Semi-definite Programming Localization in Wireless Sensor Networks Postve Sem-defnte Programmng Localzaton n Wreless Sensor etworks Shengdong Xe 1,, Jn Wang, Aqun Hu 1, Yunl Gu, Jang Xu, 1 School of Informaton Scence and Engneerng, Southeast Unversty, 10096, anjng Computer

More information

AGGREGATED MODELS TECHNIQUE FOR INTEGRATING PLANNING AND SCHEDULING OF PRODUCTION TASKS

AGGREGATED MODELS TECHNIQUE FOR INTEGRATING PLANNING AND SCHEDULING OF PRODUCTION TASKS Internatonal Journal of Modern Manufacturng Technologes ISSN 2067 3604, Vol III, No 1 / 2011 39 AGGREGATED MODELS TECHNIQUE FOR INTEGRATING PLANNING AND SCHEDULING OF PRODUCTION TASKS Ştefan Dumbravă Gheorghe

More information

Lobachevsky State University of Nizhni Novgorod. Polyhedron. Quick Start Guide

Lobachevsky State University of Nizhni Novgorod. Polyhedron. Quick Start Guide Lobachevsky State Unversty of Nzhn Novgorod Polyhedron Quck Start Gude Nzhn Novgorod 2016 Contents Specfcaton of Polyhedron software... 3 Theoretcal background... 4 1. Interface of Polyhedron... 6 1.1.

More information

On Correctness of Nonserializable Executions

On Correctness of Nonserializable Executions Journal of Computer and System Scences 56, 688 (1998) Artcle No. SS971536 On Correctness of Nonseralzable Executons Rajeev Rastog,* Sharad Mehrotra, - Yur Bretbart, [,1 Henry F. Korth,* and Av Slberschatz*

More information

Using Simulation Modeling for IT Cost Analysis

Using Simulation Modeling for IT Cost Analysis Usng Smulaton Modelng for IT Cost Analyss Tmofe Popkov (tm@xjtek.com), Yur Karpov (karpov@xjtek.com), Maxm Garfulln (maxm@xjtek.com) http://www.xjtek.com/ http://www.xjlabs.com/ St.Petersburg State Techncal

More information

Constructing Minimum Connected Dominating Set: Algorithmic approach

Constructing Minimum Connected Dominating Set: Algorithmic approach Constructng Mnmum Connected Domnatng Set: Algorthmc approach G.N. Puroht and Usha Sharma Centre for Mathematcal Scences, Banasthal Unversty, Rajasthan 304022 usha.sharma94@yahoo.com Abstract: Connected

More information

Learning the Kernel Parameters in Kernel Minimum Distance Classifier

Learning the Kernel Parameters in Kernel Minimum Distance Classifier Learnng the Kernel Parameters n Kernel Mnmum Dstance Classfer Daoqang Zhang 1,, Songcan Chen and Zh-Hua Zhou 1* 1 Natonal Laboratory for Novel Software Technology Nanjng Unversty, Nanjng 193, Chna Department

More information

Lecture 5: Multilayer Perceptrons

Lecture 5: Multilayer Perceptrons Lecture 5: Multlayer Perceptrons Roger Grosse 1 Introducton So far, we ve only talked about lnear models: lnear regresson and lnear bnary classfers. We noted that there are functons that can t be represented

More information

Parallel matrix-vector multiplication

Parallel matrix-vector multiplication Appendx A Parallel matrx-vector multplcaton The reduced transton matrx of the three-dmensonal cage model for gel electrophoress, descrbed n secton 3.2, becomes excessvely large for polymer lengths more

More information

Load-Balanced Anycast Routing

Load-Balanced Anycast Routing Load-Balanced Anycast Routng Chng-Yu Ln, Jung-Hua Lo, and Sy-Yen Kuo Department of Electrcal Engneerng atonal Tawan Unversty, Tape, Tawan sykuo@cc.ee.ntu.edu.tw Abstract For fault-tolerance and load-balance

More information

Semi - - Connectedness in Bitopological Spaces

Semi - - Connectedness in Bitopological Spaces Journal of AL-Qadsyah for computer scence an mathematcs A specal Issue Researches of the fourth Internatonal scentfc Conference/Second صفحة 45-53 Sem - - Connectedness n Btopologcal Spaces By Qays Hatem

More information

EECS 730 Introduction to Bioinformatics Sequence Alignment. Luke Huan Electrical Engineering and Computer Science

EECS 730 Introduction to Bioinformatics Sequence Alignment. Luke Huan Electrical Engineering and Computer Science EECS 730 Introducton to Bonformatcs Sequence Algnment Luke Huan Electrcal Engneerng and Computer Scence http://people.eecs.ku.edu/~huan/ HMM Π s a set of states Transton Probabltes a kl Pr( l 1 k Probablty

More information

Report on On-line Graph Coloring

Report on On-line Graph Coloring 2003 Fall Semester Comp 670K Onlne Algorthm Report on LO Yuet Me (00086365) cndylo@ust.hk Abstract Onlne algorthm deals wth data that has no future nformaton. Lots of examples demonstrate that onlne algorthm

More information

Hierarchical clustering for gene expression data analysis

Hierarchical clustering for gene expression data analysis Herarchcal clusterng for gene expresson data analyss Gorgo Valentn e-mal: valentn@ds.unm.t Clusterng of Mcroarray Data. Clusterng of gene expresson profles (rows) => dscovery of co-regulated and functonally

More information

Cracking of the Merkle Hellman Cryptosystem Using Genetic Algorithm

Cracking of the Merkle Hellman Cryptosystem Using Genetic Algorithm Crackng of the Merkle Hellman Cryptosystem Usng Genetc Algorthm Zurab Kochladze 1 * & Lal Besela 2 1 Ivane Javakhshvl Tbls State Unversty, 1, I.Chavchavadze av 1, 0128, Tbls, Georga 2 Sokhum State Unversty,

More information

Introduction. Leslie Lamports Time, Clocks & the Ordering of Events in a Distributed System. Overview. Introduction Concepts: Time

Introduction. Leslie Lamports Time, Clocks & the Ordering of Events in a Distributed System. Overview. Introduction Concepts: Time Lesle Laports e, locks & the Orderng of Events n a Dstrbuted Syste Joseph Sprng Departent of oputer Scence Dstrbuted Systes and Securty Overvew Introducton he artal Orderng Logcal locks Orderng the Events

More information

Sequential search. Building Java Programs Chapter 13. Sequential search. Sequential search

Sequential search. Building Java Programs Chapter 13. Sequential search. Sequential search Sequental search Buldng Java Programs Chapter 13 Searchng and Sortng sequental search: Locates a target value n an array/lst by examnng each element from start to fnsh. How many elements wll t need to

More information

Investigations of Topology and Shape of Multi-material Optimum Design of Structures

Investigations of Topology and Shape of Multi-material Optimum Design of Structures Advanced Scence and Tecnology Letters Vol.141 (GST 2016), pp.241-245 ttp://dx.do.org/10.14257/astl.2016.141.52 Investgatons of Topology and Sape of Mult-materal Optmum Desgn of Structures Quoc Hoan Doan

More information

Evaluation of an Enhanced Scheme for High-level Nested Network Mobility

Evaluation of an Enhanced Scheme for High-level Nested Network Mobility IJCSNS Internatonal Journal of Computer Scence and Network Securty, VOL.15 No.10, October 2015 1 Evaluaton of an Enhanced Scheme for Hgh-level Nested Network Moblty Mohammed Babker Al Mohammed, Asha Hassan.

More information

A Novel Approach for an Early Test Case Generation using Genetic Algorithm and Dominance Concept based on Use cases

A Novel Approach for an Early Test Case Generation using Genetic Algorithm and Dominance Concept based on Use cases Alekhya Varkut et al, / (IJCSIT) Internatonal Journal of Computer Scence and Informaton Technologes, Vol. 3 (3), 2012,4218-4224 A Novel Approach for an Early Test Case Generaton usng Genetc Algorthm and

More information

Study on Fuzzy Models of Wind Turbine Power Curve

Study on Fuzzy Models of Wind Turbine Power Curve Proceedngs of the 006 IASME/WSEAS Internatonal Conference on Energy & Envronmental Systems, Chalkda, Greece, May 8-0, 006 (pp-7) Study on Fuzzy Models of Wnd Turbne Power Curve SHU-CHEN WANG PEI-HWA HUANG

More information

Using the Multiple-Clue approach for system testing on AIRBUS FAL (Final Assembly Line)

Using the Multiple-Clue approach for system testing on AIRBUS FAL (Final Assembly Line) Usng the Multple-Clue approach for system testng on AIRBUS FAL (Fnal Assembly Lne) Fassely Doumba, Odle Laurent, Dder Atger AIRBUS France 316 route de Bayonne 31060 Toulouse Cedex 09 {Frstname.Name}@arbus.com

More information