Overview of Component Search System SPARS-J
|
|
- Antonia Ferguson
- 8 years ago
- Views:
Transcription
1 Overview of omponent Searc System Tetsuo Yamamoto*,Makoto Matsusita**, Katsuro Inoue** *Japan Science and Tecnology gency **Osaka University ac part nalysis part xperiment onclusion and Future work Motivation Reuse of Software omponents is a tecnique of developing new software s by using te s developed in te past. xample of reusable s: source code, document.. improves productivity and quality, and cuts down development cost as a result. However, reuse of s is not utilized effectively. developer doesn t know existence of desirable s. ltoug tere are a lot of s, tese s are not organized. In order to take advantage of reuse, it is required to manage s and searc suitable easily Researc aim We ave built te system wic ave functions as follows ollects software s eagerly witout preserving teir inerent structures Manages te information automatically Provides be suitable for User s request Targets Intranet closed software development inside a company Internet Large open source software development web site SourceForge, Jakarta Project. etc. 4 ac part nalysis part xperiment onclusion and Future work 5 (Software Product rcive analysis and Retrieval System for Java) Java Software Product rciving, analyzing and Retrieving System Many s are analyzed automatically. searc engine is built based on te analysis information. omponent: a source code of class or interface Features Keyword searc Two ranking metods Frequency in use of a word Use relation nalyzed information omponents using/used by a Package ierarcy 6
2 Structure of Library (Java source files) File omponent analysis part extract s from a file store analyzed information to clustering and rank s using nalyzed information omponent information atabase store analyzed information and omponent retrieval part searc s in correspondence wit query from rank s based on frequency in use of a keyword aggregate two rankings User Result Query User interface part deliver query to retrieval part sow searc results Hit s Query 7 Ranking searc results. omponent suited to a user request Ranking based on frequency in use of a word Keyword Rank (KR). omponent used mostly Ranking based on use relation omponent Rank (R) We make it ig ranking tat te bot and are ig Searc results are sown to aggregate two ranks 8 ac part nalysis part xperiment onclusion and Future work omponent analysis part xtract and its information from a Java source file Te process xtract a Index te xtract use relations lustering similar s Rank s based on use relations (R metod) 9 xtract and index a xtracting Find class or interface block in a java source file Location information in te file (start line number, end line number) Indexing xtract index key from te public final class Sort { quicksort private static void quicksort( ) { int pivot; quicksort( ); quicksort( ); word kind Index key a word and te Sort lass name kind of it quicksort omment No reserved words are quicksort Metod name extracted pivot Variable name ount frequency in use of te quicksort Metod call word Index key Science and Tecnology, frequency Software ngineering Laboratory, epartment of omputer Science, Graduate Scool of Information Osaka University xtract use relations xtract use relations among s using semantic analysis Make grap from use relations Node: dge: use relation public class Test extend ata{ public static void main( ) { Sort.quicksort(super.array); ata Inerit Field access Test omponent grap Sort Metod call Inerit Interface implementation Variable type Inst creation Field access Metod call Te kind of use relation
3 Similar Similar is copied or minor modified We merge similar s into single Merged ave use relations tat all before merging ave G F omponent grap F G F G lustered grap lustering s We measure caracteristics metrics to merge s Te difference ratio of eac metrics Metrics complexity Te number of metods, cyclomatic, etc. represent a structural caracteristic Token-composition Te number of appears of eac token represent a surface caracteristic 4 Ranking based on use relation omponent Rank (R) Reusable ave many use relation Te example of use is muc General purpose Sopisticated We measure use relation quantitatively, and rank s Te used by many s is important Te used by important is also important Katsuro Inoue, Reisi Yokomori, Hikaru Fujiwara, Tetsuo Yamamoto, Makoto Matsusita, Sinji Kusumoto: "omponent Rank: Relative Signific Rank for Software omponent Searc", IS, Portland, OR, May 6,. Propagating weigts d-oc weigts are assigned to eac node 5 6 Propagating weigts Propagating weigts Te node weigts are re-defined by te incoming edge weigts We get new node weigts 7 8
4 Propagating weigts We get stable weigt assignment next-step weigts are te same as previous ones omponent Rank : order of nodes sorted by te weigt 9 ac part nalysis part xperiment onclusion and Future work omponent retrieval part Searc s from database, rank s Te process Searc s Ranking suited to a user request ggregate two ranks (R and KR) Searc s Searc query Words a user input Te kind of an index word, package name omponents contain given query are searced from atabase Ranking suited to a user request alculation of KR value Keyword Rank (KR) omponents wic contain words given by a user are searced Rank s using te value calculated from index word weigt Index word weigt Many frequency in use of a word contained particular s word represent te function suc as lass name Sort te sum of all given word weigt TF-IF weigting using full-text searc engine alculate weigt W ct wit c word t TFi Te frequency wit wic a kind i of word t occurs in c IF te total number of s / te number of s containing word t kwiweigt of a kind i allkind w ct = ( kwi TFi) IF KR value is te sum of all word W ct te kind of a word lass name Interface name Metod name Package name Import Metod call Field access Variable type Inst creation Local var access omment oc comment Line comment String weig t
5 ggregate two ranks orda ount metod ggregate two ranks KR and R ggregation metod orda ount metod known a voting system Use for single or multiple-seat elections Tis form of voting is extremely popular in determining awards Rank s bot KR and R Using KR and R, te tat be suitable user s request, reusable and sopisticated Tere are voters and 5 candidates (from to ) ac voter rank candidates point for last place, points for second from last place, and N points for first place st=5points nd=4points =8points 8points 8points points 6points s t s t s t n d r d r d 4t 4t 5t ggregation 5t 5 6 User interface ac part nalysis part xperiment onclusion and Future work Receive a user s query and provide te searc results troug Web browser Microsoft Internet xplore, Mozilla, etc. Te process Parse query word and te searc condition Sow rank ordered results Sow analyzed information of te Used by/using te Metrics 7 8 nalyzed information information are as follows Metrics Te number of metod, variable LO, cyclomatic tc. (measurable metrics in te itself) omponents used by/using te Sow lists of nodes followed use relation omponents tat are similar to te Sow lists of similar s Package browsing Te naming structure for Java packages is ierarcical user can searc lists of s in same package of a easily 9
6 Screensot (top page) Screensot (searc results) Screensot (source code) Screensot (similar s) 4 Screensot (using te ) Screensot (used by te ) 5 6
7 Screensot (package browsing) ac part nalysis part xperiment onclusion and Future work 7 8 xperiment(/) xperiment(/) omparison wit Google Register about, s get from Internet Query words calculator applet and cat server client alculate relev ratio of rank iger : Te is reusable source code Google is a web searc engine dd java source term to te query words Follow one link from te result web page xample calculator applet 9 its 7 suited s xample cat server client 69 its 57 suited s Using, suited is ig order relev ratio = order Te number of relevant rank order xample SPRS-J Ratio Google Ratio xample Ratio Google ratio onclusion and Future work We developed searc engine Using, retrieval of s used well is enabled easily. Future work Morpological analysis of Index keyword ollaborative filtering Investigate best ranking metod Te value of weigt ggregation ranks valuation of Usability 4
Optimized Data Indexing Algorithms for OLAP Systems
Database Systems Journal vol. I, no. 2/200 7 Optimized Data Indexing Algoritms for OLAP Systems Lucian BORNAZ Faculty of Cybernetics, Statistics and Economic Informatics Academy of Economic Studies, Bucarest
More informationResearch on the Anti-perspective Correction Algorithm of QR Barcode
Researc on te Anti-perspective Correction Algoritm of QR Barcode Jianua Li, Yi-Wen Wang, YiJun Wang,Yi Cen, Guoceng Wang Key Laboratory of Electronic Tin Films and Integrated Devices University of Electronic
More informationSAMPLE DESIGN FOR THE TERRORISM RISK INSURANCE PROGRAM SURVEY
ASA Section on Survey Researc Metods SAMPLE DESIG FOR TE TERRORISM RISK ISURACE PROGRAM SURVEY G. ussain Coudry, Westat; Mats yfjäll, Statisticon; and Marianne Winglee, Westat G. ussain Coudry, Westat,
More informationh Understanding the safe operating principles and h Gaining maximum benefit and efficiency from your h Evaluating your testing system's performance
EXTRA TM Instron Services Revolve Around You It is everyting you expect from a global organization Te global training centers offer a complete educational service for users of advanced materials testing
More informationGeometric Stratification of Accounting Data
Stratification of Accounting Data Patricia Gunning * Jane Mary Horgan ** William Yancey *** Abstract: We suggest a new procedure for defining te boundaries of te strata in igly skewed populations, usual
More informationSchedulability Analysis under Graph Routing in WirelessHART Networks
Scedulability Analysis under Grap Routing in WirelessHART Networks Abusayeed Saifulla, Dolvara Gunatilaka, Paras Tiwari, Mo Sa, Cenyang Lu, Bo Li Cengjie Wu, and Yixin Cen Department of Computer Science,
More informationTis Problem and Retail Inventory Management
Optimizing Inventory Replenisment of Retail Fasion Products Marsall Fiser Kumar Rajaram Anant Raman Te Warton Scool, University of Pennsylvania, 3620 Locust Walk, 3207 SH-DH, Piladelpia, Pennsylvania 19104-6366
More informationA system to monitor the quality of automated coding of textual answers to open questions
Researc in Official Statistics Number 2/2001 A system to monitor te quality of automated coding of textual answers to open questions Stefania Maccia * and Marcello D Orazio ** Italian National Statistical
More informationResearch on Risk Assessment of PFI Projects Based on Grid-fuzzy Borda Number
Researc on Risk Assessent of PFI Projects Based on Grid-fuzzy Borda Nuber LI Hailing 1, SHI Bensan 2 1. Scool of Arcitecture and Civil Engineering, Xiua University, Cina, 610039 2. Scool of Econoics and
More informationThe modelling of business rules for dashboard reporting using mutual information
8 t World IMACS / MODSIM Congress, Cairns, Australia 3-7 July 2009 ttp://mssanz.org.au/modsim09 Te modelling of business rules for dasboard reporting using mutual information Gregory Calbert Command, Control,
More informationThe EOQ Inventory Formula
Te EOQ Inventory Formula James M. Cargal Matematics Department Troy University Montgomery Campus A basic problem for businesses and manufacturers is, wen ordering supplies, to determine wat quantity of
More informationInstantaneous Rate of Change:
Instantaneous Rate of Cange: Last section we discovered tat te average rate of cange in F(x) can also be interpreted as te slope of a scant line. Te average rate of cange involves te cange in F(x) over
More informationSHAPE: A NEW BUSINESS ANALYTICS WEB PLATFORM FOR GETTING INSIGHTS ON ELECTRICAL LOAD PATTERNS
CIRED Worksop - Rome, 11-12 June 2014 SAPE: A NEW BUSINESS ANALYTICS WEB PLATFORM FOR GETTING INSIGTS ON ELECTRICAL LOAD PATTERNS Diego Labate Paolo Giubbini Gianfranco Cicco Mario Ettorre Enel Distribuzione-Italy
More informationHow To Ensure That An Eac Edge Program Is Successful
Introduction Te Economic Diversification and Growt Enterprises Act became effective on 1 January 1995. Te creation of tis Act was to encourage new businesses to start or expand in Newfoundland and Labrador.
More informationOPTIMAL FLEET SELECTION FOR EARTHMOVING OPERATIONS
New Developments in Structural Engineering and Construction Yazdani, S. and Sing, A. (eds.) ISEC-7, Honolulu, June 18-23, 2013 OPTIMAL FLEET SELECTION FOR EARTHMOVING OPERATIONS JIALI FU 1, ERIK JENELIUS
More informationTorchmark Corporation 2001 Third Avenue South Birmingham, Alabama 35233 Contact: Joyce Lane 972-569-3627 NYSE Symbol: TMK
News Release Torcmark Corporation 2001 Tird Avenue Sout Birmingam, Alabama 35233 Contact: Joyce Lane 972-569-3627 NYSE Symbol: TMK TORCHMARK CORPORATION REPORTS FOURTH QUARTER AND YEAR-END 2004 RESULTS
More informationM(0) = 1 M(1) = 2 M(h) = M(h 1) + M(h 2) + 1 (h > 1)
Insertion and Deletion in VL Trees Submitted in Partial Fulfillment of te Requirements for Dr. Eric Kaltofen s 66621: nalysis of lgoritms by Robert McCloskey December 14, 1984 1 ackground ccording to Knut
More information2.23 Gambling Rehabilitation Services. Introduction
2.23 Gambling Reabilitation Services Introduction Figure 1 Since 1995 provincial revenues from gambling activities ave increased over 56% from $69.2 million in 1995 to $108 million in 2004. Te majority
More informationUnemployment insurance/severance payments and informality in developing countries
Unemployment insurance/severance payments and informality in developing countries David Bardey y and Fernando Jaramillo z First version: September 2011. Tis version: November 2011. Abstract We analyze
More informationComparison between two approaches to overload control in a Real Server: local or hybrid solutions?
Comparison between two approaces to overload control in a Real Server: local or ybrid solutions? S. Montagna and M. Pignolo Researc and Development Italtel S.p.A. Settimo Milanese, ITALY Abstract Tis wor
More informationDerivatives Math 120 Calculus I D Joyce, Fall 2013
Derivatives Mat 20 Calculus I D Joyce, Fall 203 Since we ave a good understanding of its, we can develop derivatives very quickly. Recall tat we defined te derivative f x of a function f at x to be te
More informationA strong credit score can help you score a lower rate on a mortgage
NET GAIN Scoring points for your financial future AS SEEN IN USA TODAY S MONEY SECTION, JULY 3, 2007 A strong credit score can elp you score a lower rate on a mortgage By Sandra Block Sales of existing
More informationTHE NEISS SAMPLE (DESIGN AND IMPLEMENTATION) 1997 to Present. Prepared for public release by:
THE NEISS SAMPLE (DESIGN AND IMPLEMENTATION) 1997 to Present Prepared for public release by: Tom Scroeder Kimberly Ault Division of Hazard and Injury Data Systems U.S. Consumer Product Safety Commission
More informationVerifying Numerical Convergence Rates
1 Order of accuracy Verifying Numerical Convergence Rates We consider a numerical approximation of an exact value u. Te approximation depends on a small parameter, suc as te grid size or time step, and
More informationQuasi-static Multilayer Electrical Modeling of Human Limb for IBC
Quasi-static Multilayer Electrical Modeling of Human Limb for IBC S H Pun 1,2, Y M Gao 2,3, P U Mak 1,2, M I Vai 1,2,3, and M Du 2,3 1 Department of Electrical and Electronics Engineering, Faculty of Science
More informationPioneer Fund Story. Searching for Value Today and Tomorrow. Pioneer Funds Equities
Pioneer Fund Story Searcing for Value Today and Tomorrow Pioneer Funds Equities Pioneer Fund A Cornerstone of Financial Foundations Since 1928 Te fund s relatively cautious stance as kept it competitive
More informationCan a Lump-Sum Transfer Make Everyone Enjoy the Gains. from Free Trade?
Can a Lump-Sum Transfer Make Everyone Enjoy te Gains from Free Trade? Yasukazu Icino Department of Economics, Konan University June 30, 2010 Abstract I examine lump-sum transfer rules to redistribute te
More informationCollege Planning Using Cash Value Life Insurance
College Planning Using Cas Value Life Insurance CAUTION: Te advisor is urged to be extremely cautious of anoter college funding veicle wic provides a guaranteed return of premium immediately if funded
More informationChapter 10: Refrigeration Cycles
Capter 10: efrigeration Cycles Te vapor compression refrigeration cycle is a common metod for transferring eat from a low temperature to a ig temperature. Te above figure sows te objectives of refrigerators
More informationNew Vocabulary volume
-. Plan Objectives To find te volume of a prism To find te volume of a cylinder Examples Finding Volume of a Rectangular Prism Finding Volume of a Triangular Prism 3 Finding Volume of a Cylinder Finding
More informationLecture 10: What is a Function, definition, piecewise defined functions, difference quotient, domain of a function
Lecture 10: Wat is a Function, definition, piecewise defined functions, difference quotient, domain of a function A function arises wen one quantity depends on anoter. Many everyday relationsips between
More informationSWITCH T F T F SELECT. (b) local schedule of two branches. (a) if-then-else construct A & B MUX. one iteration cycle
768 IEEE RANSACIONS ON COMPUERS, VOL. 46, NO. 7, JULY 997 Compile-ime Sceduling of Dynamic Constructs in Dataæow Program Graps Soonoi Ha, Member, IEEE and Edward A. Lee, Fellow, IEEE Abstract Sceduling
More informationWorking Capital 2013 UK plc s unproductive 69 billion
2013 Executive summary 2. Te level of excess working capital increased 3. UK sectors acieve a mixed performance 4. Size matters in te supply cain 6. Not all companies are overflowing wit cas 8. Excess
More informationAn Intuitive Framework for Real-Time Freeform Modeling
An Intuitive Framework for Real-Time Freeform Modeling Mario Botsc Leif Kobbelt Computer Grapics Group RWTH Aacen University Abstract We present a freeform modeling framework for unstructured triangle
More informationAn inquiry into the multiplier process in IS-LM model
An inquiry into te multiplier process in IS-LM model Autor: Li ziran Address: Li ziran, Room 409, Building 38#, Peing University, Beijing 00.87,PRC. Pone: (86) 00-62763074 Internet Address: jefferson@water.pu.edu.cn
More information1.6. Analyse Optimum Volume and Surface Area. Maximum Volume for a Given Surface Area. Example 1. Solution
1.6 Analyse Optimum Volume and Surface Area Estimation and oter informal metods of optimizing measures suc as surface area and volume often lead to reasonable solutions suc as te design of te tent in tis
More informationChapter 11. Limits and an Introduction to Calculus. Selected Applications
Capter Limits and an Introduction to Calculus. Introduction to Limits. Tecniques for Evaluating Limits. Te Tangent Line Problem. Limits at Infinit and Limits of Sequences.5 Te Area Problem Selected Applications
More informationDesign and Analysis of a Fault-Tolerant Mechanism for a Server-Less Video-On-Demand System
Design and Analysis of a Fault-olerant Mecanism for a Server-Less Video-On-Demand System Jack Y. B. Lee Department of Information Engineering e Cinese University of Hong Kong Satin, N.., Hong Kong Email:
More informationMulti-Project Software Engineering: An Example
Multi-Project Software Engineering: An Example Pankaj K Garg garg@zeesource.net Zee Source 1684 Nightingale Avenue, Suite 201, Sunnyvale, CA 94087, USA Thomas Gschwind tom@infosys.tuwien.ac.at Technische
More informationANALYTICAL REPORT ON THE 2010 URBAN EMPLOYMENT UNEMPLOYMENT SURVEY
THE FEDERAL DEMOCRATIC REPUBLIC OF ETHIOPIA CENTRAL STATISTICAL AGENCY ANALYTICAL REPORT ON THE 2010 URBAN EMPLOYMENT UNEMPLOYMENT SURVEY Addis Ababa December 2010 STATISTICAL BULLETIN TABLE OF CONTENT
More informationTangent Lines and Rates of Change
Tangent Lines and Rates of Cange 9-2-2005 Given a function y = f(x), ow do you find te slope of te tangent line to te grap at te point P(a, f(a))? (I m tinking of te tangent line as a line tat just skims
More information2 Limits and Derivatives
2 Limits and Derivatives 2.7 Tangent Lines, Velocity, and Derivatives A tangent line to a circle is a line tat intersects te circle at exactly one point. We would like to take tis idea of tangent line
More informationStaying in-between Music Technology in Higher Education
Staying in-between Music Tecnology in Higer Education (Post-modern) Callenges and Opportunities for Music Tecnology Education Carola Boem Carola Boem Centre for Music Tecnology Department of Music Department
More informationPressure. Pressure. Atmospheric pressure. Conceptual example 1: Blood pressure. Pressure is force per unit area:
Pressure Pressure is force per unit area: F P = A Pressure Te direction of te force exerted on an object by a fluid is toward te object and perpendicular to its surface. At a microscopic level, te force
More informationAbstract. Introduction
Fast solution of te Sallow Water Equations using GPU tecnology A Crossley, R Lamb, S Waller JBA Consulting, Sout Barn, Brougton Hall, Skipton, Nort Yorksire, BD23 3AE. amanda.crossley@baconsulting.co.uk
More informationCatalogue no. 12-001-XIE. Survey Methodology. December 2004
Catalogue no. 1-001-XIE Survey Metodology December 004 How to obtain more information Specific inquiries about tis product and related statistics or services sould be directed to: Business Survey Metods
More informationEC201 Intermediate Macroeconomics. EC201 Intermediate Macroeconomics Problem set 8 Solution
EC201 Intermediate Macroeconomics EC201 Intermediate Macroeconomics Prolem set 8 Solution 1) Suppose tat te stock of mone in a given econom is given te sum of currenc and demand for current accounts tat
More informationPre-trial Settlement with Imperfect Private Monitoring
Pre-trial Settlement wit Imperfect Private Monitoring Mostafa Beskar University of New Hampsire Jee-Hyeong Park y Seoul National University July 2011 Incomplete, Do Not Circulate Abstract We model pretrial
More informationEffect of Heat and Electricity Storage and Reliability on Microgrid Viability: A Study of Commercial Buildings in California and New York States
LBNL-1334E ERNEST ORLANDO LAWRENCE BERKELEY NATIONAL LABORATORY Effect of Heat and Electricity Storage and Reliability on Microgrid Viability: A Study of Commercial Buildings in California and New York
More informationSAT Math Must-Know Facts & Formulas
SAT Mat Must-Know Facts & Formuas Numbers, Sequences, Factors Integers:..., -3, -2, -1, 0, 1, 2, 3,... Rationas: fractions, tat is, anyting expressabe as a ratio of integers Reas: integers pus rationas
More informationMath 113 HW #5 Solutions
Mat 3 HW #5 Solutions. Exercise.5.6. Suppose f is continuous on [, 5] and te only solutions of te equation f(x) = 6 are x = and x =. If f() = 8, explain wy f(3) > 6. Answer: Suppose we ad tat f(3) 6. Ten
More informationInvesting in Roads: Pricing, Costs and New Capacity
Investing in Roads: Pricing, Costs and New Capacity Cristoper rcer Stepen Glaister Department of Civil and Environmental Engineering Imperial College London November 2006 Researc commissioned by te Independent
More informationWhat is Advanced Corporate Finance? What is finance? What is Corporate Finance? Deciding how to optimally manage a firm s assets and liabilities.
Wat is? Spring 2008 Note: Slides are on te web Wat is finance? Deciding ow to optimally manage a firm s assets and liabilities. Managing te costs and benefits associated wit te timing of cas in- and outflows
More informationFor Sale By Owner Program. We can help with our for sale by owner kit that includes:
Dawn Coen Broker/Owner For Sale By Owner Program If you want to sell your ome By Owner wy not:: For Sale Dawn Coen Broker/Owner YOUR NAME YOUR PHONE # Look as professional as possible Be totally prepared
More informationHaptic Manipulation of Virtual Materials for Medical Application
Haptic Manipulation of Virtual Materials for Medical Application HIDETOSHI WAKAMATSU, SATORU HONMA Graduate Scool of Healt Care Sciences Tokyo Medical and Dental University, JAPAN wakamatsu.bse@tmd.ac.jp
More information- 1 - Handout #22 May 23, 2012 Huffman Encoding and Data Compression. CS106B Spring 2012. Handout by Julie Zelenski with minor edits by Keith Schwarz
CS106B Spring 01 Handout # May 3, 01 Huffman Encoding and Data Compression Handout by Julie Zelenski wit minor edits by Keit Scwarz In te early 1980s, personal computers ad ard disks tat were no larger
More informationStaffing and routing in a two-tier call centre. Sameer Hasija*, Edieal J. Pinker and Robert A. Shumsky
8 Int. J. Operational Researc, Vol. 1, Nos. 1/, 005 Staffing and routing in a two-tier call centre Sameer Hasija*, Edieal J. Pinker and Robert A. Sumsky Simon Scool, University of Rocester, Rocester 1467,
More informationGovernment Debt and Optimal Monetary and Fiscal Policy
Government Debt and Optimal Monetary and Fiscal Policy Klaus Adam Manneim University and CEPR - preliminary version - June 7, 21 Abstract How do di erent levels of government debt a ect te optimal conduct
More informationPredicting the behavior of interacting humans by fusing data from multiple sources
Predicting te beavior of interacting umans by fusing data from multiple sources Erik J. Sclict 1, Ritcie Lee 2, David H. Wolpert 3,4, Mykel J. Kocenderfer 1, and Brendan Tracey 5 1 Lincoln Laboratory,
More informationON LOCAL LIKELIHOOD DENSITY ESTIMATION WHEN THE BANDWIDTH IS LARGE
ON LOCAL LIKELIHOOD DENSITY ESTIMATION WHEN THE BANDWIDTH IS LARGE Byeong U. Park 1 and Young Kyung Lee 2 Department of Statistics, Seoul National University, Seoul, Korea Tae Yoon Kim 3 and Ceolyong Park
More informationTheoretical calculation of the heat capacity
eoretical calculation of te eat capacity Principle of equipartition of energy Heat capacity of ideal and real gases Heat capacity of solids: Dulong-Petit, Einstein, Debye models Heat capacity of metals
More informationHeterogeneous firms and trade costs: a reading of French access to European agrofood
Heterogeneous firms and trade costs: a reading of Frenc access to European agrofood markets Cevassus-Lozza E., Latouce K. INRA, UR 34, F-44000 Nantes, France Abstract Tis article offers a new reading of
More informationSAT Subject Math Level 1 Facts & Formulas
Numbers, Sequences, Factors Integers:..., -3, -2, -1, 0, 1, 2, 3,... Reals: integers plus fractions, decimals, and irrationals ( 2, 3, π, etc.) Order Of Operations: Aritmetic Sequences: PEMDAS (Parenteses
More informationStrategic trading in a dynamic noisy market. Dimitri Vayanos
LSE Researc Online Article (refereed) Strategic trading in a dynamic noisy market Dimitri Vayanos LSE as developed LSE Researc Online so tat users may access researc output of te Scool. Copyrigt and Moral
More informationMath Test Sections. The College Board: Expanding College Opportunity
Taking te SAT I: Reasoning Test Mat Test Sections Te materials in tese files are intended for individual use by students getting ready to take an SAT Program test; permission for any oter use must be sougt
More informationStrategic trading and welfare in a dynamic market. Dimitri Vayanos
LSE Researc Online Article (refereed) Strategic trading and welfare in a dynamic market Dimitri Vayanos LSE as developed LSE Researc Online so tat users may access researc output of te Scool. Copyrigt
More informationFINANCIAL SECTOR INEFFICIENCIES AND THE DEBT LAFFER CURVE
INTERNATIONAL JOURNAL OF FINANCE AND ECONOMICS Int. J. Fin. Econ. 10: 1 13 (2005) Publised online in Wiley InterScience (www.interscience.wiley.com). DOI: 10.1002/ijfe.251 FINANCIAL SECTOR INEFFICIENCIES
More informationCyber Epidemic Models with Dependences
Cyber Epidemic Models wit Dependences Maocao Xu 1, Gaofeng Da 2 and Souuai Xu 3 1 Department of Matematics, Illinois State University mxu2@ilstu.edu 2 Institute for Cyber Security, University of Texas
More informationIndustrial Robot: An International Journal Emerald Article: High-level robot programming based on CAD: dealing with unpredictable environments
Emerald Article: Hig-level robot programming based on CAD: dealing wit unpredictable environments Pedro Neto, Nuno Mendes, Ricardo Araújo, J Norberto Pires, A Paulo Moreira Article information: To cite
More informationA hybrid model of dynamic electricity price forecasting with emphasis on price volatility
all times On a non-liquid market, te accuracy of a price A ybrid model of dynamic electricity price forecasting wit empasis on price volatility Marin Cerjan Abstract-- Accurate forecasting tools are essential
More information1. What are Data Structures? Introduction to Data Structures. 2. What will we Study? CITS2200 Data Structures and Algorithms
1 What are ata Structures? ata Structures and lgorithms ata structures are software artifacts that allow data to be stored, organized and accessed Topic 1 They are more high-level than computer memory
More informationOperation go-live! Mastering the people side of operational readiness
! I 2 London 2012 te ultimate Up to 30% of te value of a capital programme can be destroyed due to operational readiness failures. 1 In te complex interplay between tecnology, infrastructure and process,
More informationLarge-scale Virtual Acoustics Simulation at Audio Rates Using Three Dimensional Finite Difference Time Domain and Multiple GPUs
Large-scale Virtual Acoustics Simulation at Audio Rates Using Tree Dimensional Finite Difference Time Domain and Multiple GPUs Craig J. Webb 1,2 and Alan Gray 2 1 Acoustics Group, University of Edinburg
More informationEPIKOTE TM Resin MGS RIM 235
2.1-1 EPIKOTE TM Resin MGS RIM 235 EPIKURE TM Curing Agent RIM H 235-238 page Caracteristics 1 Application 11 Specifications 12 Processing details 13 Mixing ratios 13 Temperature development 13 Viscosity
More information1. Case description. Best practice description
1. Case description Best practice description Tis case sows ow a large multinational went troug a bottom up organisational cange to become a knowledge-based company. A small community on knowledge Management
More informationThe Dynamics of Movie Purchase and Rental Decisions: Customer Relationship Implications to Movie Studios
Te Dynamics of Movie Purcase and Rental Decisions: Customer Relationsip Implications to Movie Studios Eddie Ree Associate Professor Business Administration Stoneill College 320 Wasington St Easton, MA
More informationFree Shipping and Repeat Buying on the Internet: Theory and Evidence
Free Sipping and Repeat Buying on te Internet: eory and Evidence Yingui Yang, Skander Essegaier and David R. Bell 1 June 13, 2005 1 Graduate Scool of Management, University of California at Davis (yiyang@ucdavis.edu)
More informationNAFN NEWS SPRING2011 ISSUE 7. Welcome to the Spring edition of the NAFN Newsletter! INDEX. Service Updates Follow That Car! Turn Back The Clock
NAFN NEWS ISSUE 7 SPRING2011 Welcome to te Spring edition of te NAFN Newsletter! Spring is in te air at NAFN as we see several new services cropping up. Driving and transport emerged as a natural teme
More informationOnce you have reviewed the bulletin, please
Akron Public Scools OFFICE OF CAREER EDUCATION BULLETIN #5 : Driver Responsibilities 1. Akron Board of Education employees assigned to drive Board-owned or leased veicles MUST BE FAMILIAR wit te Business
More informationWarm medium, T H T T H T L. s Cold medium, T L
Refrigeration Cycle Heat flows in direction of decreasing temperature, i.e., from ig-temperature to low temperature regions. Te transfer of eat from a low-temperature to ig-temperature requires a refrigerator
More informationACT Math Facts & Formulas
Numbers, Sequences, Factors Integers:..., -3, -2, -1, 0, 1, 2, 3,... Rationals: fractions, tat is, anyting expressable as a ratio of integers Reals: integers plus rationals plus special numbers suc as
More informationDigital evolution Where next for the consumer facing business?
Were next for te consumer facing business? Cover 2 Digital tecnologies are powerful enablers and lie beind a combination of disruptive forces. Teir rapid continuous development demands a response from
More informationAn Orientation to the Public Health System for Participants and Spectators
An Orientation to te Public Healt System for Participants and Spectators Presented by TEAM ORANGE CRUSH Pallisa Curtis, Illinois Department of Public Healt Lynn Galloway, Vermillion County Healt Department
More informationWelfare, financial innovation and self insurance in dynamic incomplete markets models
Welfare, financial innovation and self insurance in dynamic incomplete markets models Paul Willen Department of Economics Princeton University First version: April 998 Tis version: July 999 Abstract We
More informationThe Demand for Food Away From Home Full-Service or Fast Food?
United States Department of Agriculture Electronic Report from te Economic Researc Service www.ers.usda.gov Agricultural Economic Report No. 829 January 2004 Te Demand for Food Away From Home Full-Service
More informationMacroeconomic conditions influence consumers attitudes,
Yu Ma, Kusum L. Ailawadi, Dines K. Gauri, & Druv Grewal An Empirical Investigation of te Impact of Gasoline Prices on Grocery Sopping Beavior Te autors empirically examine te effect of gas prices on grocery
More informationKeskustelualoitteita #65 Joensuun yliopisto, Taloustieteet. Market effiency in Finnish harness horse racing. Niko Suhonen
Keskustelualoitteita #65 Joensuun yliopisto, Taloustieteet Market effiency in Finnis arness orse racing Niko Suonen ISBN 978-952-219-283-7 ISSN 1795-7885 no 65 Market Efficiency in Finnis Harness Horse
More informationUsing Intelligent Agents to Discover Energy Saving Opportunities within Data Centers
1 Using Intelligent Agents to Discover Energy Saving Opportunities witin Data Centers Alexandre Mello Ferreira and Barbara Pernici Dipartimento di Elettronica, Informazione e Bioingegneria Politecnico
More informationParallel Smoothers for Matrix-based Multigrid Methods on Unstructured Meshes Using Multicore CPUs and GPUs
Parallel Smooters for Matrix-based Multigrid Metods on Unstructured Meses Using Multicore CPUs and GPUs Vincent Heuveline Dimitar Lukarski Nico Trost Jan-Pilipp Weiss No. 2-9 Preprint Series of te Engineering
More informationNotes: Most of the material in this chapter is taken from Young and Freedman, Chap. 12.
Capter 6. Fluid Mecanics Notes: Most of te material in tis capter is taken from Young and Freedman, Cap. 12. 6.1 Fluid Statics Fluids, i.e., substances tat can flow, are te subjects of tis capter. But
More informationICE FOOD DEPOT COOLED WITH A HEAT PUMP: A PRE-FEASIBILITY STUDY
ICE FOOD DEPOT COOLED WITH A HEAT PUMP: A PRE-FEASIBILITY STUDY S.A. Guly, G.Z. Perlstein Nort-Eastern Researc Station o Permarost Institute, Siberian Branc o Russian Academy o Sciences. 12, Gagarin St.,
More informationShell and Tube Heat Exchanger
Sell and Tube Heat Excanger MECH595 Introduction to Heat Transfer Professor M. Zenouzi Prepared by: Andrew Demedeiros, Ryan Ferguson, Bradford Powers November 19, 2009 1 Abstract 2 Contents Discussion
More informationCHAPTER 7. Di erentiation
CHAPTER 7 Di erentiation 1. Te Derivative at a Point Definition 7.1. Let f be a function defined on a neigborood of x 0. f is di erentiable at x 0, if te following it exists: f 0 fx 0 + ) fx 0 ) x 0 )=.
More informationCHAPTER TWO. f(x) Slope = f (3) = Rate of change of f at 3. x 3. f(1.001) f(1) Average velocity = 1.1 1 1.01 1. s(0.8) s(0) 0.8 0
CHAPTER TWO 2.1 SOLUTIONS 99 Solutions for Section 2.1 1. (a) Te average rate of cange is te slope of te secant line in Figure 2.1, wic sows tat tis slope is positive. (b) Te instantaneous rate of cange
More informationTraining Robust Support Vector Regression via D. C. Program
Journal of Information & Computational Science 7: 12 (2010) 2385 2394 Available at ttp://www.joics.com Training Robust Support Vector Regression via D. C. Program Kuaini Wang, Ping Zong, Yaoong Zao College
More informationMULTY BINARY TURBO CODED WOFDM PERFORMANCE IN FLAT RAYLEIGH FADING CHANNELS
Volume 49, Number 3, 28 MULTY BINARY TURBO CODED WOFDM PERFORMANCE IN FLAT RAYLEIGH FADING CHANNELS Marius OLTEAN Maria KOVACI Horia BALTA Andrei CAMPEANU Faculty of, Timisoara, Romania Bd. V. Parvan,
More informationIn other words the graph of the polynomial should pass through the points
Capter 3 Interpolation Interpolation is te problem of fitting a smoot curve troug a given set of points, generally as te grap of a function. It is useful at least in data analysis (interpolation is a form
More informationMATHEMATICS FOR ENGINEERING DIFFERENTIATION TUTORIAL 1 - BASIC DIFFERENTIATION
MATHEMATICS FOR ENGINEERING DIFFERENTIATION TUTORIAL 1 - BASIC DIFFERENTIATION Tis tutorial is essential pre-requisite material for anyone stuing mecanical engineering. Tis tutorial uses te principle of
More information2.1: The Derivative and the Tangent Line Problem
.1.1.1: Te Derivative and te Tangent Line Problem Wat is te deinition o a tangent line to a curve? To answer te diiculty in writing a clear deinition o a tangent line, we can deine it as te iting position
More informationFactoring Synchronous Grammars By Sorting
Factoring Syncronous Grammars By Sorting Daniel Gildea Computer Science Dept. Uniersity of Rocester Rocester, NY Giorgio Satta Dept. of Information Eng g Uniersity of Padua I- Padua, Italy Hao Zang Computer
More information