Educational Semantic Networks and their Applications

Size: px
Start display at page:

Download "Educational Semantic Networks and their Applications"

Transcription

1 BUIU Unverstăţ Petrol Gaze dn Ploeşt Vol. X o. / Sera atematcă - Informatcă - Fzcă ducatonal Semantc etwors and ther Alcatons Gabrela ose vu Ionţă Unverstatea Petrol-Gaze dn Ploeşt Bd. Bucureşt 39 Ploeşt e-mal: gmose@ug-loest.ro Abstract In ths aer the authors resents an algebrac structure about educatonal semantc networs. he structure could be used to model the content of an electroncal course. hs structure enables to erform oeratons to combne more electroncal courses and to obtan a new course to defne a edagogcal technque to teach a course to ursue the evoluton of students durng the nstructon rocess. he educatonal semantc networs could be used n the software develoment n the feld of comuter asssted nstructon and to desgn software based on edagogcal agent. ey words: educatonal semantc networ algebrac structure nowledge reresentaton e-course e-learnng Introducton A semantc networ s a grahcal notaton to nowledge reresentaton n a structure wth nodes nterconnected by arcs. he nodes are rmtves to reresent concets events states and the arcs are rmtves whch abstract the relatons between nodes. he frst mlementaton of semantc networs n comuter systems was develoed n the artfcal ntellgence feld and translaton machnes. he roles of the semantc networs n the educaton rocess were stressed by Jonassen []. he human memory s organzed accordng to the relatons exstng between deas so structurng the nformaton accordng to semantc networs allows an actve nstructon rocess. he semantc networs rovde an effcent mode to navgate n an electronc course. he semantc networs force the teacher to organze the edagogcal materals n a logcal mode so that the students can understand better the educatonal materals. he new concets of the course wll be ntegrated n an exstng concetual structure. o use the educatonal semantc networs n the e-learnng software the author rooses some defntons about educatonal semantc networs [] oeratons wth them and an algebrac structure.

2 78 Gabrela ose vu Ionţă Problem Formulaton Defnton. We call an educatonal semantc networ noted a nowledge reresentaton n the form: where are nodes labeled wth and these nodes has attached educatonal resources n multmeda format noted wth and reresents a relaton from node to node labeled wth. Defnton. he educatonal semantc networ wth a sngle node s called the sngular educatonal semantc networ and t s resented n the form:. Defnton. We call an emty semantc networ the semantc networ wthout any node or relaton. he Oeratons wth ducatonal Semantc etwors he reunon of two educatonal semantc networs noted s defned n ths way [3]: ase no. he two semantc networs and have n common at least one node. et consder: where node s a common node. { } c.... xamle: et consder two educatonal semantc networs wth one node n common. he reunon of them s resented n the fgure no.. ase no.. he two semantc networs and have not any node n common. { }... ew c

3 ducatonal Semantc etwors and ther Alcatons 79 Fg.. he reunon of two educatonal semantc networ wth one common node he reunon could be realzed f and only f we can draw a relaton between two nodes from each networ. emar. In an educatonal semantc networ solated nodes don t exst. xamle: et consder two educatonal semantc networs wthout any node n common. he reunon of them s resented n the fgure no.. Fg.. he reunon of two educatonal semantc networ wthout any common node

4 80 Gabrela ose vu Ionţă emar. A concet could be added to a networ usng the reunon oeraton between a networ and a sngle networ. he ntersecton of two educatonal semantc networs s a semantc networ noted defned n ths way [3]: he two semantc networs and have at least one common node. et consder: { { }} card. emar. he result of the ntersecton of two educatonal semantc networs wthout any common node s the emty networ. he dfference between two educatonal semantc networs s a semantc networ noted : { { }} card. xamle: et consder two educatonal semantc networs. he dfference between the two educatonal semantc networs s resented n the fgure no. 3. he selecton of an educatonal semantc networ after a set of nodes loos le that [3]: et consder a semantc networ and a set of nodes. { } S

5 ducatonal Semantc etwors and ther Alcatons 8 Fg. 3. he dfference between two educatonal semantc networ xamle: he selecton oeraton s resented n the fgure no. 4. he set of nodes s. A B D Fg. 4. he selecton of an educatonal semantc networ after a set of nodes

6 8 Gabrela ose vu Ionţă he onod of ducatonal Semantc etwors Prooston. We note wth the set of all educatonal semantc networs. s a monod consderng the reunon oeraton. Proof. o roof that the set of all educatonal semantc networs s a monod we have to roof that the oeratons of reunon s assocatve and the emty semantc networ s an dentty element.. et s consder the reunon oeraton. 3 3 he roerty s evdence whle the reunon of the sets of obects s assocatve.. he emty educatonal semantc networ s the dentty element for reunon oeraton. { } { } { } } hs monod s a commutatve monod whle the reunon oeraton s commutatve. Defnton. et s consder an educatonal semantc networ. { } { } { } { }. We call the set of arts of and we noted wth Ρ : Ρ { Ρ { } } Ρ { } Ρ { } Ρ { } Prooston. et s consder an educatonal semantc networ and followng roertes are true:. Ρ 3 3. Ρ 3. ; Ρ Ρ Analog Ρ s a commutatve monod.. 3 ; s a commutatve monod where the dentty element s. Ρ the set of arts. he

7 ducatonal Semantc etwors and ther Alcatons 83 Alcaton odellng e-ourses he educatonal semantc networs can be used to model the e-courses. onsder a course. he course has O O On n nstructonal obectves. For each obectve we could buld an educatonal semantc networ. O { } { } { } { } where are labeled nodes and each node s assocated wth a edagogcal resource called content. means a relaton from node to node labeled wth. he educatonal semantc networ assocated to the course s obtaned usng the reunon oeraton n. odelng the Obect Orented Programmng ourse o buld the e-course wth ttle Obect Orented Programmng we could use a set of educatonal semantc networ. Some of them are resented n the followng fgures. Data Abstract data tye Abstract data rogrammng Imlementaton abstract data tye Fg. 5. he educatonal semantc networ for the obectve data Programmng technques estng rograms Unstructured rogrammng Obect orented rogrammng Debuggng Programs Proflng Procedural rogrammng odular rogrammng Fg. 5. he educatonal semantc networ for the obectve rogrammng technques

8 84 Gabrela ose vu Ionţă he effcency of the algorthm he analyss of the algorthm Algorthms 3 he concet of algorthm he elaboraton of the algorthm Fg. 6. he educatonal semantc networ for the obectve algorthm Inhertance Overloaded functons 4 Base class Herarchy of Derved class classes Fg. 7. he educatonal semantc networ for the obectve nhertance Statc Dynamc 5 nng Fg. 8. he educatonal semantc networ for the obectve lnng 6 he concet of olymorhsm Polymorhsm Vrtual functons 7 Fg. 9. he educatonal semantc networ for the obectve olymorhsm Abstract class Fg. 0. he educatonal semantc networ for the obectve abstract class Destructor 8 he class concet omosed class Instance onstructor he class concet Obect ethods he obect concet Proertes vents Fg.. he educatonal semantc networ for the obectve class obect he semantc networ could be stored n the comuter usng databases. ach node has attached more fles reresentng the educatonal resources n the multmeda format. Alyng the

9 ducatonal Semantc etwors and ther Alcatons 85 reunon oeraton results the educatonal semantc networ of the course Obect Orented Programmng o teach only the module wth ttle estng rograms we have to aly the selecton oerator to semantc networ after the node wth the same ttle. he advantages of usng ths nd of structure for the edagogcal resources are [4]:. -courses could be managed more easy;. the ossblty of buldng new courses based on the exstng courses; 3. ossblty of usng teachng and learnng strateges esecally accordng to the rofle learnng of each student. onclusons he evoluton of nformaton technologes enables to teach accordng to a varety of the nstructon strateges. he great maorty of the software rograms dedcated to comuter asssted nstructon resent the edagogcal resources n one format. So the students regardless of the learnng style of them have to learn n the same way. he structure resented n the aer s a base structure for the e-courses. he structure was used n the software system develoment based on edagogcal agent resented n PhD thess and confrms that students learn better f the teachers use a strategy based on learnng styles [5 6]. eferences. Jonassen D.H. - Desgnng structured hyertext and structurng access to hyertext ducatonal echnology ose G. - A software system for onlne learnng aled to dstance unversty nstructon n the feld of comuter scence unublshed manuscrt Petroleum-Gas Unversty Ploest ose G. - odellng e-courses based on educatonal semantc networ Petroleum-Gas Unversty of Ploest Bulletn Vol. VII no ose G. - A new aroach to manage contents of edagogcal resources Scentfc Bulletn of Poltehnca Unversty of msoara Wel Joyce B. alhoun. - odels of eachng Pearson ducaton ose G. - A Software System for Onlne earnng Aled n the Feld of omuter Scence Internatonal Journal of omuters ommuncatons & ontrol II o. 007 avalable at htt://ournal.unvagora.ro/ 007 ezumat eţele semantce educaţonale ş alcaţle lor În acest artcol autor rezntă structura algebrcă a reţelelor semantce educaţonale. Structura rousă în lucrare oate f utlzată entru modelarea conţnuturlor cursurlor electronc: ermte oeraţ de generare de no cursur electronce defnrea de tehnc edagogce entru redarea cursurlor tehnc de evaluare a studenţlor.

THE CONDENSED FUZZY K-NEAREST NEIGHBOR RULE BASED ON SAMPLE FUZZY ENTROPY

THE CONDENSED FUZZY K-NEAREST NEIGHBOR RULE BASED ON SAMPLE FUZZY ENTROPY Proceedngs of the 20 Internatonal Conference on Machne Learnng and Cybernetcs, Guln, 0-3 July, 20 THE CONDENSED FUZZY K-NEAREST NEIGHBOR RULE BASED ON SAMPLE FUZZY ENTROPY JUN-HAI ZHAI, NA LI, MENG-YAO

More information

Ontology based data warehouses federation management system

Ontology based data warehouses federation management system Ontolog based data warehouses federaton management sstem Naoual MOUHNI 1, Abderrafaa EL KALAY 2 1 Deartment of mathematcs and comuter scences, Unverst Cad Aad, Facult of scences and technologes Marrakesh,

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

A note on Schema Equivalence

A note on Schema Equivalence note on Schema Equvalence.H.M. ter Hofstede and H.. Proer and Th.P. van der Wede E.Proer@acm.org PUBLISHED S:.H.M. ter Hofstede, H.. Proer, and Th.P. van der Wede. Note on Schema Equvalence. Techncal Reort

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

Security Enhanced Dynamic ID based Remote User Authentication Scheme for Multi-Server Environments

Security Enhanced Dynamic ID based Remote User Authentication Scheme for Multi-Server Environments Internatonal Journal of u- and e- ervce, cence and Technology Vol8, o 7 0), pp7-6 http://dxdoorg/07/unesst087 ecurty Enhanced Dynamc ID based Remote ser Authentcaton cheme for ult-erver Envronments Jun-ub

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

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

A Scheduling Algorithm of Periodic Messages for Hard Real-time Communications on a Switched Ethernet

A Scheduling Algorithm of Periodic Messages for Hard Real-time Communications on a Switched Ethernet IJCSNS Internatonal Journal of Comuter Scence and Networ Securty VOL.6 No.5B May 26 A Schedulng Algorthm of Perodc Messages for Hard eal-tme Communcatons on a Swtched Ethernet Hee Chan Lee and Myung Kyun

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

A Topology-aware Random Walk

A Topology-aware Random Walk A Topology-aware Random Walk Inkwan Yu, Rchard Newman Dept. of CISE, Unversty of Florda, Ganesvlle, Florda, USA Abstract When a graph can be decomposed nto clusters of well connected subgraphs, t s possble

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

An Improved Image Segmentation Algorithm Based on the Otsu Method

An Improved Image Segmentation Algorithm Based on the Otsu Method 3th ACIS Internatonal Conference on Software Engneerng, Artfcal Intellgence, Networkng arallel/dstrbuted Computng An Improved Image Segmentaton Algorthm Based on the Otsu Method Mengxng Huang, enjao Yu,

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

A Method of Line Matching Based on Feature Points

A Method of Line Matching Based on Feature Points JOURNAL OF SOFTWARE, VOL. 7, NO. 7, JULY 2012 1539 A Method of Lne Matchng Based on Feature Ponts Yanxa Wang and Yan Ma College of Comuter and Informaton Scence, Chongqng Normal Unversty, Chongqng, 400047,

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

Application of Genetic Algorithms in Graph Theory and Optimization. Qiaoyan Yang, Qinghong Zeng

Application of Genetic Algorithms in Graph Theory and Optimization. Qiaoyan Yang, Qinghong Zeng 3rd Internatonal Conference on Materals Engneerng, Manufacturng Technology and Control (ICMEMTC 206) Alcaton of Genetc Algorthms n Grah Theory and Otmzaton Qaoyan Yang, Qnghong Zeng College of Mathematcs,

More information

Recognition of Identifiers from Shipping Container Images Using Fuzzy Binarization and Enhanced Fuzzy Neural Network

Recognition of Identifiers from Shipping Container Images Using Fuzzy Binarization and Enhanced Fuzzy Neural Network Recognton of Identfers from Shng Contaner Images Usng uzzy Bnarzaton and Enhanced uzzy Neural Networ Kwang-Bae Km Det. of Comuter Engneerng, Slla Unversty, Korea gbm@slla.ac.r Abstract. In ths aer, we

More information

Multilayer Neural Networks and Nearest Neighbor Classifier Performances for Image Annotation

Multilayer Neural Networks and Nearest Neighbor Classifier Performances for Image Annotation (IJACSA) Internatonal Journal of Advanced Comuter Scence and Alcatons, Vol. 3, No. 11, 01 Multlayer Neural Networs and Nearest Neghbor Classfer erformances for Image Annotaton Mustaha OUJAOURA Laboratory

More information

AN ALGEBRAIC APPROACH TO CONSISTENCY CHECKING BETWEEN CLASS DIAGRAMS

AN ALGEBRAIC APPROACH TO CONSISTENCY CHECKING BETWEEN CLASS DIAGRAMS AN ALGEBRAIC AROACH TO CONSISTENC CHECKING BETWEEN CLASS DIAGRAMS HIDEKAZU ENJO, MOTONARI TANABU, JUNICHI IIJIMA NTT DATA Corporaton, okohama Natonal Unversty, Tokyo Insttute of Technology enouh@nttdata.co.p,

More information

Semantic Image Retrieval Using Region Based Inverted File

Semantic Image Retrieval Using Region Based Inverted File Semantc Image Retreval Usng Regon Based Inverted Fle Dengsheng Zhang, Md Monrul Islam, Guoun Lu and Jn Hou 2 Gppsland School of Informaton Technology, Monash Unversty Churchll, VIC 3842, Australa E-mal:

More information

High-Boost Mesh Filtering for 3-D Shape Enhancement

High-Boost Mesh Filtering for 3-D Shape Enhancement Hgh-Boost Mesh Flterng for 3-D Shape Enhancement Hrokazu Yagou Λ Alexander Belyaev y Damng We z Λ y z ; ; Shape Modelng Laboratory, Unversty of Azu, Azu-Wakamatsu 965-8580 Japan y Computer Graphcs Group,

More information

MINING OF CONCEPTUAL COST ESTIMATION KNOWLEDGE WITH A NEURO FUZZY SYSTEM

MINING OF CONCEPTUAL COST ESTIMATION KNOWLEDGE WITH A NEURO FUZZY SYSTEM MINING OF CONCEPTUAL COST ESTIMATION KNOWLEDGE WITH A NEURO FUZZY SYSTEM Wen-der Yu and Yu-ru Lee Insttute of Constructon Management, Chung Hua Unversty, Tawan Abstract: Concetual cost estmaton durng the

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

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

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

Six-axis Robot Manipulator Numerical Control Programming and Motion Simulation

Six-axis Robot Manipulator Numerical Control Programming and Motion Simulation 2016 Internatonal Conference on Appled Mechancs, Mechancal and Materals Engneerng (AMMME 2016) ISBN: 978-1-60595-409-7 S-as Robot Manpulator Numercal Control Programmng and Moton Smulaton Chen-hua SHE

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

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

A Fuzzy Image Matching Algorithm with Linguistic Spatial Queries

A Fuzzy Image Matching Algorithm with Linguistic Spatial Queries Fuzzy Matchng lgorthm wth Lngustc Spatal Queres TZUNG-PEI HONG, SZU-PO WNG, TIEN-HIN WNG, EEN-HIN HIEN epartment of Electrcal Engneerng, Natonal Unversty of Kaohsung Insttute of Informaton Management,

More information

Adaptive Energy and Location Aware Routing in Wireless Sensor Network

Adaptive Energy and Location Aware Routing in Wireless Sensor Network Adaptve Energy and Locaton Aware Routng n Wreless Sensor Network Hong Fu 1,1, Xaomng Wang 1, Yngshu L 1 Department of Computer Scence, Shaanx Normal Unversty, X an, Chna, 71006 fuhong433@gmal.com {wangxmsnnu@hotmal.cn}

More information

SLAM Summer School 2006 Practical 2: SLAM using Monocular Vision

SLAM Summer School 2006 Practical 2: SLAM using Monocular Vision SLAM Summer School 2006 Practcal 2: SLAM usng Monocular Vson Javer Cvera, Unversty of Zaragoza Andrew J. Davson, Imperal College London J.M.M Montel, Unversty of Zaragoza. josemar@unzar.es, jcvera@unzar.es,

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

Available online at ScienceDirect. Procedia Computer Science 94 (2016 )

Available online at  ScienceDirect. Procedia Computer Science 94 (2016 ) Avalable onlne at www.scencedrect.com ScenceDrect Proceda Comuter Scence 94 (2016 ) 176 182 The 13th Internatonal Conference on Moble Systems and Pervasve Comutng (MobSPC 2016) An Effcent QoS-aware Web

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

Discovering User Access Pattern Based on Probabilistic Latent Factor Model

Discovering User Access Pattern Based on Probabilistic Latent Factor Model Dscoverng User Access Pattern Based on Probablstc Latent Factor Model Guandong Xu, Yanchun Zhang, Jangang Ma School of Comuter Scence and Mathematcs Vctora Unversty PO Box 14428, VIC 8001, Australa {xu,yzhang,ma}@csm.vu.edu.au

More information

A MULTILEVEL DECISION MAKING MODEL FOR THE SUPPLIER SELECTION PROBLEM IN A FUZZY SITUATION

A MULTILEVEL DECISION MAKING MODEL FOR THE SUPPLIER SELECTION PROBLEM IN A FUZZY SITUATION OPERATIONS RESEARCH AND DECISIONS No. 4 2017 DOI: 10.5277/ord170401 Ahmad Yusuf ADHAMI 1 Syed Mohd MUNEEB 1 Mohammad Asm NOMANI 2 A MULTILEVEL DECISION MAKING MODEL FOR THE SUPPLIER SELECTION PROBLEM IN

More information

Advanced LEACH: A Static Clustering-based Heteroneous Routing Protocol for WSNs

Advanced LEACH: A Static Clustering-based Heteroneous Routing Protocol for WSNs Advanced LEACH: A Statc Clusterng-based Heteroneous Routng Protocol for WSNs A. Iqbal 1, M. Akbar 1, N. Javad 1, S. H. Bouk 1, M. Ilah 1, R. D. Khan 2 1 COMSATS Insttute of Informaton Technology, Islamabad,

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

Learning-Based Top-N Selection Query Evaluation over Relational Databases

Learning-Based Top-N Selection Query Evaluation over Relational Databases Learnng-Based Top-N Selecton Query Evaluaton over Relatonal Databases Lang Zhu *, Wey Meng ** * School of Mathematcs and Computer Scence, Hebe Unversty, Baodng, Hebe 071002, Chna, zhu@mal.hbu.edu.cn **

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

Design of an interactive Web-based e-learning course with simulation lab: a case study of a fuzzy expert system course

Design of an interactive Web-based e-learning course with simulation lab: a case study of a fuzzy expert system course World Transactons on Engneerng and Technology Educaton Vol.8, No.3, 2010 2010 WIETE Desgn of an nteractve Web-based e-learnng course wth smulaton lab: a case study of a fuzzy expert system course Che-Chern

More information

QoS-Based Service Provision Schemes and Plan Durability in Service Composition

QoS-Based Service Provision Schemes and Plan Durability in Service Composition QoS-Based Servce Provson Schemes and Plan Durablty n Servce Comoston Koramt Pchanaharee and Twtte Senvongse Deartment of Comuter Engneerng, Faculty of Engneerng, Chulalongkorn Unversty Phyatha Road, Pathumwan,

More information

Classifier Selection Based on Data Complexity Measures *

Classifier Selection Based on Data Complexity Measures * Classfer Selecton Based on Data Complexty Measures * Edth Hernández-Reyes, J.A. Carrasco-Ochoa, and J.Fco. Martínez-Trndad Natonal Insttute for Astrophyscs, Optcs and Electroncs, Lus Enrque Erro No.1 Sta.

More information

TIME-EFFICIENT NURBS CURVE EVALUATION ALGORITHMS

TIME-EFFICIENT NURBS CURVE EVALUATION ALGORITHMS TIME-EFFICIENT NURBS CURVE EVALUATION ALGORITHMS Kestuts Jankauskas Kaunas Unversty of Technology, Deartment of Multmeda Engneerng, Studentu st. 5, LT-5368 Kaunas, Lthuana, kestuts.jankauskas@ktu.lt Abstract:

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

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

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

Contour Error of the 3-DoF Hydraulic Translational Parallel Manipulator. Ryszard Dindorf 1,a, Piotr Wos 2,b

Contour Error of the 3-DoF Hydraulic Translational Parallel Manipulator. Ryszard Dindorf 1,a, Piotr Wos 2,b Advanced Materals Research Vol. 874 (2014) 57-62 Onlne avalable snce 2014/Jan/08 at www.scentfc.net (2014) rans ech Publcatons, Swtzerland do:10.4028/www.scentfc.net/amr.874.57 Contour Error of the 3-DoF

More information

Algorithm for Computer Aided Design Curve Shape Form Generation of Knitting Patterns

Algorithm for Computer Aided Design Curve Shape Form Generation of Knitting Patterns Algorth for Couter Aded Desgn Curve Shae For Generaton of Knttng Patterns Elena Zahareva-Stoyanova Techncal Unversty of Gabrovo 4 H. Drat str. 500 Gabrovo, ulgara, hone +59 59 Abstract - The knttng ndustry

More information

Visual research topic discovery with MULTI-SOM model of analysis

Visual research topic discovery with MULTI-SOM model of analysis Vsual research toc dscovery wth MULTI-SOM model of analyss Xaver Polanco and Martal Hoffmann Unté de Recherche et Innovaton (URI) Insttut de l Informaton Scentfque et Technque (INIST- CNRS) 2, allée du

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

Alignment Results of SOBOM for OAEI 2010

Alignment Results of SOBOM for OAEI 2010 Algnment Results of SOBOM for OAEI 2010 Pegang Xu, Yadong Wang, Lang Cheng, Tany Zang School of Computer Scence and Technology Harbn Insttute of Technology, Harbn, Chna pegang.xu@gmal.com, ydwang@ht.edu.cn,

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

Determining the Optimal Bandwidth Based on Multi-criterion Fusion

Determining the Optimal Bandwidth Based on Multi-criterion Fusion Proceedngs of 01 4th Internatonal Conference on Machne Learnng and Computng IPCSIT vol. 5 (01) (01) IACSIT Press, Sngapore Determnng the Optmal Bandwdth Based on Mult-crteron Fuson Ha-L Lang 1+, Xan-Mn

More information

Risk Assessment Using Functional Modeling based on Object Behavior and Interaction

Risk Assessment Using Functional Modeling based on Object Behavior and Interaction Rsk Assessment Usng Functonal Modelng based on Object Behavor and Interacton Akekacha Tangsuksant, Nakornth Promoon Software Engneerng Lab, Center of Ecellence n Software Engneerng Deartment of Comuter

More information

Type-2 Fuzzy Non-uniform Rational B-spline Model with Type-2 Fuzzy Data

Type-2 Fuzzy Non-uniform Rational B-spline Model with Type-2 Fuzzy Data Malaysan Journal of Mathematcal Scences 11(S) Aprl : 35 46 (2017) Specal Issue: The 2nd Internatonal Conference and Workshop on Mathematcal Analyss (ICWOMA 2016) MALAYSIAN JOURNAL OF MATHEMATICAL SCIENCES

More information

Force-Directed Method in Mirror Frames for Graph Drawing

Force-Directed Method in Mirror Frames for Graph Drawing I.J. Intellgent Systems and lcatons, 2010, 1, 8-14 Publshed Onlne November 2010 n MES (htt://www.mecs-ress.org/) Force-Drected Method n Mrror Frames for Grah Drawng Jng Lee and *hng-hsng Pe Deartment of

More information

Arabic Text Classification Using N-Gram Frequency Statistics A Comparative Study

Arabic Text Classification Using N-Gram Frequency Statistics A Comparative Study Arabc Text Classfcaton Usng N-Gram Frequency Statstcs A Comparatve Study Lala Khresat Dept. of Computer Scence, Math and Physcs Farlegh Dcknson Unversty 285 Madson Ave, Madson NJ 07940 Khresat@fdu.edu

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

Study of Data Stream Clustering Based on Bio-inspired Model

Study of Data Stream Clustering Based on Bio-inspired Model , pp.412-418 http://dx.do.org/10.14257/astl.2014.53.86 Study of Data Stream lusterng Based on Bo-nspred Model Yngme L, Mn L, Jngbo Shao, Gaoyang Wang ollege of omputer Scence and Informaton Engneerng,

More information

Privacy Models for RFID Authentication Protocols

Privacy Models for RFID Authentication Protocols Prvacy Models for RFID Authentcaton Protocols Jan Shen 1,2, Jn Wang 1,2, Yuan Me 1,2, Ilyong Chung 3 1 Jangsu Engneerng Center of Network Montorng, Nanjng Unversty of Informaton Scence &echnology, Nanjng,210044,Chna

More information

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

Control strategies for network efficiency and resilience with route choice

Control strategies for network efficiency and resilience with route choice Control strateges for networ effcency and reslence wth route choce Andy Chow Ru Sha Centre for Transport Studes Unversty College London, UK Centralsed strateges UK 1 Centralsed strateges Some effectve

More information

Finite Element Analysis of Rubber Sealing Ring Resilience Behavior Qu Jia 1,a, Chen Geng 1,b and Yang Yuwei 2,c

Finite Element Analysis of Rubber Sealing Ring Resilience Behavior Qu Jia 1,a, Chen Geng 1,b and Yang Yuwei 2,c Advanced Materals Research Onlne: 03-06-3 ISSN: 66-8985, Vol. 705, pp 40-44 do:0.408/www.scentfc.net/amr.705.40 03 Trans Tech Publcatons, Swtzerland Fnte Element Analyss of Rubber Sealng Rng Reslence Behavor

More information

Bayesian Networks: Independencies and Inference. What Independencies does a Bayes Net Model?

Bayesian Networks: Independencies and Inference. What Independencies does a Bayes Net Model? Bayesan Networks: Indeendences and Inference Scott Daves and Andrew Moore Note to other teachers and users of these sldes. Andrew and Scott would be delghted f you found ths source materal useful n gvng

More information

Private Information Retrieval (PIR)

Private Information Retrieval (PIR) 2 Levente Buttyán Problem formulaton Alce wants to obtan nformaton from a database, but she does not want the database to learn whch nformaton she wanted e.g., Alce s an nvestor queryng a stock-market

More information

Broadcast Time Synchronization Algorithm for Wireless Sensor Networks Chaonong Xu 1)2)3), Lei Zhao 1)2), Yongjun Xu 1)2) and Xiaowei Li 1)2)

Broadcast Time Synchronization Algorithm for Wireless Sensor Networks Chaonong Xu 1)2)3), Lei Zhao 1)2), Yongjun Xu 1)2) and Xiaowei Li 1)2) Broadcast Tme Synchronzaton Algorthm for Wreless Sensor Networs Chaonong Xu )2)3), Le Zhao )2), Yongun Xu )2) and Xaowe L )2) ) Key Laboratory of Comuter Archtecture, Insttute of Comutng Technology Chnese

More information

Rational Ruled surfaces construction by interpolating dual unit vectors representing lines

Rational Ruled surfaces construction by interpolating dual unit vectors representing lines Ratonal Ruled surfaces constructon by nterolatng dual unt vectors reresentng lnes Stavros G. Paageorgou Robotcs Grou, Deartment of Mechancal and Aeronautcal Engneerng, Unversty of Patras 265 Patra, Greece

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

Image Segmentation. Image Segmentation

Image Segmentation. Image Segmentation Image Segmentaton REGION ORIENTED SEGMENTATION Let R reresent the entre mage regon. Segmentaton may be vewed as a rocess that arttons R nto n subregons, R, R,, Rn,such that n= R = R.e., the every xel must

More information

FAHP and Modified GRA Based Network Selection in Heterogeneous Wireless Networks

FAHP and Modified GRA Based Network Selection in Heterogeneous Wireless Networks 2017 2nd Internatonal Semnar on Appled Physcs, Optoelectroncs and Photoncs (APOP 2017) ISBN: 978-1-60595-522-3 FAHP and Modfed GRA Based Network Selecton n Heterogeneous Wreless Networks Xaohan DU, Zhqng

More information

View-Dependent Multiresolution Representation for a Height Map

View-Dependent Multiresolution Representation for a Height Map Internatonal Journal of Innovaton, Management and echnology, Vol. 4, No. 1, February 013 Vew-Deendent Multresoluton Reresentaton for a Heght Ma Yong H. Chung, Won K. Hwam, Dae S. Chang, Jung-Ju Cho, and

More information

A Robust Webpage Information Hiding Method Based on the Slash of Tag

A Robust Webpage Information Hiding Method Based on the Slash of Tag Advanced Engneerng Forum Onlne: 2012-09-26 ISSN: 2234-991X, Vols. 6-7, pp 361-366 do:10.4028/www.scentfc.net/aef.6-7.361 2012 Trans Tech Publcatons, Swtzerland A Robust Webpage Informaton Hdng Method Based

More information

A high precision collaborative vision measurement of gear chamfering profile

A high precision collaborative vision measurement of gear chamfering profile Internatonal Conference on Advances n Mechancal Engneerng and Industral Informatcs (AMEII 05) A hgh precson collaboratve vson measurement of gear chamferng profle Conglng Zhou, a, Zengpu Xu, b, Chunmng

More information

A New Feature of Uniformity of Image Texture Directions Coinciding with the Human Eyes Perception 1

A New Feature of Uniformity of Image Texture Directions Coinciding with the Human Eyes Perception 1 A New Feature of Unformty of Image Texture Drectons Concdng wth the Human Eyes Percepton Xng-Jan He, De-Shuang Huang, Yue Zhang, Tat-Mng Lo 2, and Mchael R. Lyu 3 Intellgent Computng Lab, Insttute of Intellgent

More information

A Hierarchical Skeleton-based Implicit Model

A Hierarchical Skeleton-based Implicit Model A Herarchcal Skeleton-based Imlct Model MARCELO DE GOMENSORO MALHEIROS WU, SHIN-TING Gruo de Comutação de Imagens (GCI-DCA-FEEC) Unversdade Estadual de Camnas (UNICAMP) fmalhero,tngg@dca.fee.uncam.br Abstract.

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

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

Sums of exponential functions and their new fundamental properties

Sums of exponential functions and their new fundamental properties Sus of exonental functons and ther new fundaental roertes Yur K. Shestoaloff Abstract hs aer dscovers and roves the fundaental roertes of sus of exonental functon n the for of а heore that s stated as

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

Semi-Supervised Biased Maximum Margin Analysis for Interactive Image Retrieval

Semi-Supervised Biased Maximum Margin Analysis for Interactive Image Retrieval IP-06850-00.R3 Sem-Suervsed Based Maxmum Margn Analyss for Interactve Image Retreval Lnng Zhang,, Student Member, IEEE, Lo Wang, Senor Member, IEEE and Wes Ln 3, Senor Member, IEEE School of Electrcal

More information

Fuzzy C-Means Initialized by Fixed Threshold Clustering for Improving Image Retrieval

Fuzzy C-Means Initialized by Fixed Threshold Clustering for Improving Image Retrieval Fuzzy -Means Intalzed by Fxed Threshold lusterng for Improvng Image Retreval NAWARA HANSIRI, SIRIPORN SUPRATID,HOM KIMPAN 3 Faculty of Informaton Technology Rangst Unversty Muang-Ake, Paholyotn Road, Patumtan,

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

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

Index Terms-Software effort estimation, principle component analysis, datasets, neural networks, and radial basis functions.

Index Terms-Software effort estimation, principle component analysis, datasets, neural networks, and radial basis functions. ISO 9001:2008 Certfed Internatonal Journal of Engneerng and Innovatve Technology (IJEIT The Effect of Dmensonalty Reducton on the Performance of Software Cost Estmaton Models Ryadh A.K. Mehd College of

More information

NOVEL APPROACH FOR MOVING HUMAN DETECTION AND TRACKING IN STATIC CAMERA VIDEO SEQUENCES

NOVEL APPROACH FOR MOVING HUMAN DETECTION AND TRACKING IN STATIC CAMERA VIDEO SEQUENCES THE PUBLIHING HOUE PROCEEDING OF THE ROMANIAN ACADEMY, eres A, OF THE ROMANIAN ACADEMY Volume 3, Number 3/202,. 269 277 NOVEL APPROACH FOR MOVING HUMAN DETECTION AND TRACKING IN TATIC CAMERA VIDEO EQUENCE

More information

Oracle Database: SQL and PL/SQL Fundamentals Certification Course

Oracle Database: SQL and PL/SQL Fundamentals Certification Course Oracle Database: SQL and PL/SQL Fundamentals Certfcaton Course 1 Duraton: 5 Days (30 hours) What you wll learn: Ths Oracle Database: SQL and PL/SQL Fundamentals tranng delvers the fundamentals of SQL and

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

E-DEEC- Enhanced Distributed Energy Efficient Clustering Scheme for heterogeneous WSN

E-DEEC- Enhanced Distributed Energy Efficient Clustering Scheme for heterogeneous WSN 21 1st Internatonal Conference on Parallel, Dstrbuted and Grd Comutng (PDGC - 21) E-DEEC- Enhanced Dstrbuted Energy Effcent Clusterng Scheme for heterogeneous WSN Parul San Deartment of Comuter Scence

More information

A Unified Framework for Semantics and Feature Based Relevance Feedback in Image Retrieval Systems

A Unified Framework for Semantics and Feature Based Relevance Feedback in Image Retrieval Systems A Unfed Framework for Semantcs and Feature Based Relevance Feedback n Image Retreval Systems Ye Lu *, Chunhu Hu 2, Xngquan Zhu 3*, HongJang Zhang 2, Qang Yang * School of Computng Scence Smon Fraser Unversty

More information

Resource and Virtual Function Status Monitoring in Network Function Virtualization Environment

Resource and Virtual Function Status Monitoring in Network Function Virtualization Environment Journal of Physcs: Conference Seres PAPER OPEN ACCESS Resource and Vrtual Functon Status Montorng n Network Functon Vrtualzaton Envronment To cte ths artcle: MS Ha et al 2018 J. Phys.: Conf. Ser. 1087

More information

A Clustering Algorithm for Chinese Adjectives and Nouns 1

A Clustering Algorithm for Chinese Adjectives and Nouns 1 Clusterng lgorthm for Chnese dectves and ouns Yang Wen, Chunfa Yuan, Changnng Huang 2 State Key aboratory of Intellgent Technology and System Deptartment of Computer Scence & Technology, Tsnghua Unversty,

More information

Analytical Performance Analysis of Network- Processor-Based Application Designs

Analytical Performance Analysis of Network- Processor-Based Application Designs Analytcal Performance Analyss of Networ- Processor-Based Alcaton Desgns e Lu BMC Software Inc. Waltham, MA e Wang Unversty of Massachusetts Lowell, MA Abstract Networ rocessors (NP) are desgned to rovde

More information

A Model for System Resources in Flexible Time-Triggered Middleware Architectures

A Model for System Resources in Flexible Time-Triggered Middleware Architectures A Model for System Resources n Flexble Tme-Trggered Mddleware Archtectures Adran Noguero 1, Isdro Calvo 2, Lus Almeda 3, and Una Gangot 2 1 Tecnala, Software Systems Engneerng Unt, Parque Tecnológco de

More information

Hermite Splines in Lie Groups as Products of Geodesics

Hermite Splines in Lie Groups as Products of Geodesics Hermte Splnes n Le Groups as Products of Geodescs Ethan Eade Updated May 28, 2017 1 Introducton 1.1 Goal Ths document defnes a curve n the Le group G parametrzed by tme and by structural parameters n the

More information

A new Algorithm for Lossless Compression applied to two-dimensional Static Images

A new Algorithm for Lossless Compression applied to two-dimensional Static Images A new Algorthm for Lossless Comresson aled to two-dmensonal Statc Images JUAN IGNACIO LARRAURI Deartment of Technology Industral Unversty of Deusto Avda. Unversdades, 4. 48007 Blbao SPAIN larrau@deusto.es

More information

Support Vector Machines

Support Vector Machines /9/207 MIST.6060 Busness Intellgence and Data Mnng What are Support Vector Machnes? Support Vector Machnes Support Vector Machnes (SVMs) are supervsed learnng technques that analyze data and recognze patterns.

More information

Outline. Type of Machine Learning. Examples of Application. Unsupervised Learning

Outline. Type of Machine Learning. Examples of Application. Unsupervised Learning Outlne Artfcal Intellgence and ts applcatons Lecture 8 Unsupervsed Learnng Professor Danel Yeung danyeung@eee.org Dr. Patrck Chan patrckchan@eee.org South Chna Unversty of Technology, Chna Introducton

More information

Analysis of Continuous Beams in General

Analysis of Continuous Beams in General Analyss of Contnuous Beams n General Contnuous beams consdered here are prsmatc, rgdly connected to each beam segment and supported at varous ponts along the beam. onts are selected at ponts of support,

More information