APR 1965 Aggregation Methodology
|
|
- Hillary Marshall
- 5 years ago
- Views:
Transcription
1 Sa Joaqu Valley Ar Polluto Cotrol Dstrct APR 1965 Aggregato Methodology Approved By: Sged Date: March 3, 2016 Araud Marjollet, Drector of Permt Servces Backgroud Health rsk modelg ad the collecto of emssos vetory are ecessary for varous Dstrct ad state programs. Emssos vetory reportg ad modelg for small quattes of emssos sources are typcally expedtous compared to projects wth umerous emssos sources. I some cases, facltes or projects ca volve hudreds or thousads of emssos sources or compoets. Due to resource costrats, t may ot be practcal to report ad/or model that may compoets or emsso sources dvdually. I order to maage the reportg ad/or modelg of emssos from a large umber of compoets, aggregato of smlar compoets to a sgle source for reportg ad/or modelg ca be beefcal. Aggregato meas the groupg ad cosoldato of the emssos from ay umber of dvdual compoets or sources to a sgle source. Hstorcally, aalyses assocated wth the AB2588 (Ar Toxc Hot Spots Assessmet Act) program utlzed such a method. Purpose The purpose of ths polcy s to provde gudace o determg f ad how emsso sources may be aggregated for the purposes of performg health rsk modelg for Dstrct Rsk Maagemet Revews (RMR), Calfora Evrometal Qualty Act (CEQA) projects, Emssos Ivetory (EI), ad AB2588 (Ar Toxc Hot Spots Assessmet Act). Applcablty Ths polcy may apply to a faclty or project wth multple fugtve emsso sources or compoets wth fugtve emssos, ad qualfy uder Secto IV.A below. Ths polcy does ot apply to combusto sources, or emssos sources wth stacks, whch should all be reported ad evaluated separately.
2 Gudace (see Appedx B for examples) A. Geeral Requremets ad Qualfcatos To qualfy to be aggregated, each source of emssos must meet all of the followg requremets: 1. Aggregato of compoets should oly occur f there are fve (5) or more of ay sgle compoet (e.g. ppg valves at a olfeld) or source type (e.g. storage taks). Note, there ca be umerous compoets wth a permt ut, ad there ca be umerous compoets that are permt-exempt. 2. The aggregated compoets must have the same Source Classfcato Code (SCC) ad emssos estmato methodology, as well as smlar release parameters. 3. Each aggregated source shall use the same toxc emsso profle(s) for toxc emssos estmato purposes. Aggregated sources that do ot have the same toxc emsso profles requre approval from the Dstrct before proceedg. 4. The locato of the aggregated source must rema wth the same Secto, ¼ Secto, ¼ of a ¼ Secto, or the area whch the actual sources resde. The locato should be determed accordg to Sectos IV. B ad C below. 5. The locato of the aggregated source caot resde a area ot owed or cotrolled by the faclty. 6. Aggregated fugtve compoets should be modeled as area sources. 7. The heght above groud or elevato of the area source wll deped o the sources that have bee aggregated. B. Aggregato of Compoets or Sources wth a Uform Spatal Dstrbuto 1. Compoets that are wth a sgle secto (~1609 x ~1609 meters or 1x1 mle square) ca be aggregated to a sgle source, f: a. The compoets are ot separated by more tha 800 meters ad are equally spread over the etre secto, ad b. The aggregated source locato would be the ceter of the secto. The modeled area source sze should be o greater tha 100 meters by 100 meters. 2. Compoets that are wth a sgle quarter secto (~804 x ~804 meters or ½ x ½ mle) ca be aggregated to a sgle aggregated source, f: APR
3 a. The compoets are ot separated by more tha 400 meters ad are equally spread over the etre quarter secto, ad b. The aggregated source locato would be the ceter of the ¼ secto. The modeled area source sze should be o greater tha 50 meters by 50 meters. 3. Compoets that are wth a sgle quarter of a quarter secto (~402 x ~402 meters or 1/4 x 1/4 mle) ca be aggregated to a sgle aggregated source, f: a. The compoets are ot separated by more tha 200 meters ad are equally spread over the etre quarter of a ¼ secto, ad b. The aggregated source locato would be the ceter of the quarter of the quarter secto. The modeled area source sze should be o greater tha 25 meters by 25 meters. Other aggregato schemes ad szes may be used wth the approval of the Dstrct. C. Aggregato of Compoets or Sources wth a No-Uform Spatal Dstrbuto Compoets that are ot equally dstrbuted over a secto, quarter secto, or sub quarter secto ca stll be aggregated as log as the requremets of sub tem IV.A have bee satsfed. Two methods are descrbed below wth the Weghted Mea Ceter Method cosdered more accurate tha the Coservatve Method. Other methods may be used wth the approval of the Dstrct. 1. Weghted Mea Ceter Method The weghted mea ceter method provdes a procedure by whch geospatal data ca be represeted by a sgle data pot or locato. Ths method takes to accout the locato of each source beg aggregated ad the emssos beg released. I order to use ths techque, three data pots from each source beg aggregated are requred: 1) the toxcty based emsso rate (TBER), 2) UTM North coordate, ad 3) UTM East coordate. A example calculato s cluded Appedx A. a. Toxcty Based Emsso Rate I the early 1990 s, whe the Ar Toxc Hot Spots Act (AB2588) program started to requre HRAs, o system exsted for calculatg a source s exposure to earby receptors. At that tme modelers used what has come to be kow as a toxcty based emsso rate. There are two methods for determg the toxc emsso rates; oe for whe APR
4 carcogec (cacer) mpacts are the most sgfcat ad oe for whe o-carcogec (chroc ad acute) mpacts are the most sgfcat. The carcogec method takes the Ut Rsk Factor (URF) for each toxc ar cotamat (TAC) ad multples t by ts calculated aual emssos lbs/year or g/sec. The the carcogec TBERs for each source are summed. Ths method provdes a sgle emssos rate that represets the overall toxcty of the emssos from a gve source. Ths method s also useful for comparg sources rrespectve of ther dsperso parameters.. To determe the carcogec toxcty based emsso rate of each source, use the followg equato: Eq. 1 Toxcty Based Emsso Factor (Carcogec) w = P T =1 Where: w = Sum of the toxcty based emsso rates P = Source pollutat emssos T = Pollutat toxcty (URF) = Number of pollutats for the source = Represets each pollutat The o-carcogec method takes the calculated max hour (acute) or aual emssos (chroc) for each TAC lbs/hour or lbs/year or g/sec ad dvdes t by ts Relatve Exposure Level (REL) value. The the ocarcogec TBERs for each source are summed. Ths method provdes a sgle emssos rate that represets the overall toxcty of the emssos from a gve source. Ths method s also useful for comparg sources rrespectve of ther dsperso parameters.. To determe the carcogec toxcty based emsso rate of each source, use the followg equato: Eq. 2 Toxcty Based Emsso Factor (No-Carcogec) w = P R =1 Where: w = Sum of the toxcty based emsso rates P = Source pollutat emssos R = Pollutat toxcty (REL) = Number of pollutats for the source = Represets each pollutat APR
5 For the purpose of determg where a aggregated source wll be located ad to mmze the resources eeded, the emssos do ot have to be coverted to grams per secod, but ca be left the uts that wll be reported to the Dstrct. b. To determe the weghted mea ceter locato of the aggregated source, use the followg equatos: Eq. 3. Weghted UTM East coordate Where: X w 1 1 w x Xw = Weghted mea UTM East coordate x = UTM East coordate w = Sum of the toxcty based emsso rates = Number of emssos sources to be aggregated = Represets each source coordate w Eq. 4. Weghted UTM North coordate Where: Y w 1 1 w y Yw = Weghted mea UTM North coordate y = UTM North coordate w = Sum of the toxcty based emsso rates = Number of emssos sources to be aggregated = Represets each source coordate w c. I order to mmze the umber of sources ad resources eeded to perform ths method, sources clustered wth 25 meters of each other may be grouped together ad the ceter locato of the cluster maybe used. 2. Coservatve Method Ths method places the locato of the aggregated source at the locato of the earest source receptor combato. APR
6 Appedx A Weghted Mea Ceter Method The example project has sx tak sources. The coordates for each source are dcated below: Table 1. Source Coordates Source UTM East UTM North Tak Tak Tak Tak Tak Tak Step 1: Calculate the toxcty based emsso rate usg equato 1: Table 2. Example of Toxcty Based Emsso Rates Devce Name CAS Pollutat URF Emsso Rate (lbs/yr) Toxcty Based Emsso Rate Tak H2S 1.79E E+00 Tak Xylees 8.75E E+00 Tak Toluee 4.25E E+00 Tak Bezee 2.90E E E-06 Tak H2S 5.37E E+00 Tak Xylees 2.63E E+00 Tak Toluee 1.28E E+00 Tak Bezee 2.90E E E-06 Tak H2S 2.69E E+00 Tak Xylees 1.31E E+00 Tak Toluee 6.38E E+00 Tak Bezee 2.90E E E-06 Tak H2S 1.07E E+00 Tak Xylees 5.25E E+00 Tak Toluee 2.55E E+00 Tak Bezee 2.90E E E-06 Tak H2S 5.37E E+00 Tak Xylees 2.63E E+00 Tak Toluee 1.28E E+00 Tak Bezee 2.90E E E-06 Tak H2S 1.79E E+00 Tak Xylees 8.75E E+00 Tak Toluee 4.25E E+00 Tak Bezee 2.90E E E-06 APR
7 Step 2: Determe the Weghted Mea Ceter (WMC) UTM Coordates for the Aggregated Source Usg Equato 2: X w = [(1.27E 6) ]+[(8.81E 9) ]+[(1.91E 6) ]+[(7.62E 6) ]+[(3.81E 6) ]+[(1.27E 6) ) (1.27E 6)+(3.81E 6)+(1.91E 6)+(7.62E 6)+(3.81E 6)+(1.27E 6) X w = Usg Equato 3: Y w = [(1.27E 6) ]+[(8.81E 9) ]+[(1.91E 6) ]+[(7.62E 6) ]+[(3.81E 6) ]+[(1.27E 6) ) (1.27E 6)+(3.81E 6)+(1.91E 6)+(7.62E 6)+(3.81E 6)+(1.27E 6) Y w = Fgure 1 dsplays the approxmate locato of the sx fugtve tak sources (T1-T6), ad the weghted mea ceter (WMC) for the aggregated source. Fgure 1. Weghted Mea Ceter (WMC) Source Locato APR
8 Appedx B Examples of Aggregated Source Placemet Example 1: Emssos that are evely dstrbuted across a Secto, ¼ Secto, or ¼ of a ¼ Secto. If the emssos from your sources are evely dstrbuted across the Secto, ¼ Secto, or ¼ of a ¼ Secto, your aggregated source should be placed ear the ceter of the Secto, ¼ Secto, or ¼ of a ¼ Secto, respectvely. Ths s llustrated Fgure 2 below: Fgure 2. Locato of a Aggregated Source for Evely Dstrbuted Sources APR
9 Example 2: Emssos that are ot evely dstrbuted across a Secto, ¼ Secto, or ¼ of a ¼ Secto. If the emssos from your sources are ot evely dstrbuted across a Secto, ¼ Secto, or ¼ of a ¼ Secto, your aggregated source should be placed based o the recommeded weght mea ceter method descrbed Secto IV.C.1 above. Assumg that the sources Fgure 3 are detcal ad wth detcal emssos, your aggregated source would be placed smlarly to what s show below: Fgure 3. Locato of a Aggregated Source for No-Uformly Dstrbuted Sources APR
10 Example 3: Multple clusters of the same source type wth a Secto, ¼ Secto, or ¼ of a ¼ Secto. I Fgure 4, there are two dstct clusters of sources wth the same Secto, ¼ Secto, or ¼ of a ¼ Secto. The two clusters have sources that are detcal ad have detcal emssos, but fall outsde the dstace lmtato(s) lsted Secto IV. I ths case each of the two clusters would ot be combed to a sgle aggregated source, but would be separated to two dstct aggregated sources. Ths would esure that emssos are ot advertetly located mproperly. For ths scearo, the aggregated sources would be placed smlarly to what s show below usg the weghted mea ceter method. Fgure 4. Multple Clusters of Sources APR
Chapter 3 Descriptive Statistics Numerical Summaries
Secto 3.1 Chapter 3 Descrptve Statstcs umercal Summares Measures of Cetral Tedecy 1. Mea (Also called the Arthmetc Mea) The mea of a data set s the sum of the observatos dvded by the umber of observatos.
More informationBezier curves. 1. Defining a Bezier curve. A closed Bezier curve can simply be generated by closing its characteristic polygon
Curve represetato Copyrght@, YZU Optmal Desg Laboratory. All rghts reserved. Last updated: Yeh-Lag Hsu (--). Note: Ths s the course materal for ME55 Geometrc modelg ad computer graphcs, Yua Ze Uversty.
More informationDescriptive Statistics: Measures of Center
Secto 2.3 Descrptve Statstcs: Measures of Ceter Frequec dstrbutos are helpful provdg formato about categorcal data, but wth umercal data we ma wat more formato. Statstc: s a umercal measure calculated
More informationFor all questions, answer choice E) NOTA" means none of the above answers is correct. A) 50,500 B) 500,000 C) 500,500 D) 1,001,000 E) NOTA
For all questos, aswer choce " meas oe of the above aswers s correct.. What s the sum of the frst 000 postve tegers? A) 50,500 B) 500,000 C) 500,500 D),00,000. What s the sum of the tegers betwee 00 ad
More informationA Comparison of Univariate Smoothing Models: Application to Heart Rate Data Marcus Beal, Member, IEEE
A Comparso of Uvarate Smoothg Models: Applcato to Heart Rate Data Marcus Beal, Member, IEEE E-mal: bealm@pdx.edu Abstract There are a umber of uvarate smoothg models that ca be appled to a varety of olear
More informationEight Solved and Eight Open Problems in Elementary Geometry
Eght Solved ad Eght Ope Problems Elemetary Geometry Floret Smaradache Math & Scece Departmet Uversty of New Mexco, Gallup, US I ths paper we revew eght prevous proposed ad solved problems of elemetary
More informationPoint Estimation-III: General Methods for Obtaining Estimators
Pot Estmato-III: Geeral Methods for Obtag Estmators RECAP 0.-0.6 Data: Radom Sample from a Populato of terest o Real valued measuremets: o Assumpto (Hopefully Reasoable) o Model: Specfed Probablty Dstrbuto
More informationITEM ToolKit Technical Support Notes
ITEM ToolKt Notes Fault Tree Mathematcs Revew, Ic. 2875 Mchelle Drve Sute 300 Irve, CA 92606 Phoe: +1.240.297.4442 Fax: +1.240.297.4429 http://www.itemsoft.com Page 1 of 15 6/1/2016 Copyrght, Ic., All
More informationPerformance Impact of Load Balancers on Server Farms
erformace Impact of Load Balacers o Server Farms Ypg Dg BMC Software Server Farms have gaed popularty for provdg scalable ad relable computg / Web servces. A load balacer plays a key role ths archtecture,
More informationEight Solved and Eight Open Problems in Elementary Geometry
Eght Solved ad Eght Ope Problems Elemetary Geometry Floret Smaradache Math & Scece Departmet Uversty of New Mexco, Gallup, US I ths paper we revew eght prevous proposed ad solved problems of elemetary
More information1-D matrix method. U 4 transmitted. incident U 2. reflected U 1 U 5 U 3 L 2 L 3 L 4. EE 439 matrix method 1
-D matrx method We ca expad the smple plae-wave scatterg for -D examples that we ve see to a more versatle matrx approach that ca be used to hadle may terestg -D problems. The basc dea s that we ca break
More informationLP: example of formulations
LP: eample of formulatos Three classcal decso problems OR: Trasportato problem Product-m problem Producto plag problem Operatos Research Massmo Paolucc DIBRIS Uversty of Geova Trasportato problem The decso
More informationMachine Learning: Algorithms and Applications
/03/ Mache Learg: Algorthms ad Applcatos Florao Z Free Uversty of Boze-Bolzao Faculty of Computer Scece Academc Year 0-0 Lecture 3: th March 0 Naïve Bayes classfer ( Problem defto A trag set X, where each
More informationFitting. We ve learned how to detect edges, corners, blobs. Now what? We would like to form a. compact representation of
Fttg Fttg We ve leared how to detect edges, corers, blobs. Now what? We would lke to form a hgher-level, h l more compact represetato of the features the mage b groupg multple features accordg to a smple
More informationCS 2710 Foundations of AI Lecture 22. Machine learning. Machine Learning
CS 7 Foudatos of AI Lecture Mache learg Mlos Hauskrecht mlos@cs.ptt.edu 539 Seott Square Mache Learg The feld of mache learg studes the desg of computer programs (agets) capable of learg from past eperece
More informationRegion Matching by Optimal Fuzzy Dissimilarity
Rego Matchg by Optmal Fuzzy Dssmlarty Zhaggu Zeg, Ala Fu ad Hog Ya School of Electrcal ad formato Egeerg The Uversty of Sydey Phoe: +6--935-6659 Fax: +6--935-3847 Emal: zzeg@ee.usyd.edu.au Abstract: Ths
More informationStatistical Techniques Employed in Atmospheric Sampling
Appedx A Statstcal Techques Employed Atmospherc Samplg A.1 Itroducto Proper use of statstcs ad statstcal techques s ecessary for assessg the qualty of ambet ar samplg data. For a comprehesve dscusso of
More informationReliable Surface Extraction from Point-Clouds using Scanner-Dependent Parameters
1 Relable Surface Extracto from Pot-Clouds usg Scaer-Depedet Parameters Hrosh Masuda 1, Ichro Taaka 2, ad Masakazu Eomoto 3 1 The Uversty of Tokyo, masuda@sys.t.u-tokyo.ac.jp 2 Tokyo Dek Uversty, taaka@cck.deda.ac.jp
More informationDifferentiated Service of Streaming Media Playback Technology
Iteratoal Coferece o Advaced Iformato ad Commucato Techology for Educato (ICAICTE 2013) Dfferetated Servce of Streamg Meda Playback Techology CHENG Z-ao 1 MENG Bo 1 WANG Da-hua 1 ZHAO Yue 1 1 Iformatzato
More informationClustering documents with vector space model using n-grams
Clusterg documets wth vector space model usg -grams Klas Skogmar, d97ksk@efd.lth.se Joha Olsso, d97jo@efd.lth.se Lud Isttute of Techology Supervsed by: Perre Nugues, Perre.Nugues@cs.lth.se Abstract Ths
More informationNEURO FUZZY MODELING OF CONTROL SYSTEMS
NEURO FUZZY MODELING OF CONTROL SYSTEMS Efré Gorrosteta, Carlos Pedraza Cetro de Igeería y Desarrollo Idustral CIDESI, Av Pe de La Cuesta 70. Des. Sa Pablo. Querétaro, Qro, Méxco gorrosteta@teso.mx pedraza@cdes.mx
More informationOffice Hours. COS 341 Discrete Math. Office Hours. Homework 8. Currently, my office hours are on Friday, from 2:30 to 3:30.
Oce Hours Curretly, my oce hours are o Frday, rom :30 to 3:30. COS 31 Dscrete Math 1 Oce Hours Curretly, my oce hours are o Frday, rom :30 to 3:30. Nobody seems to care. Chage oce hours? Tuesday, 8 PM
More informationCOMBINATORIAL METHOD OF POLYNOMIAL EXPANSION OF SYMMETRIC BOOLEAN FUNCTIONS
COMBINATORIAL MTHOD O POLYNOMIAL XPANSION O SYMMTRIC BOOLAN UNCTIONS Dala A. Gorodecky The Uted Isttute of Iformatcs Prolems of Natoal Academy of Sceces of Belarus, Msk,, Belarus, dala.gorodecky@gmal.com.
More informationCOMSC 2613 Summer 2000
Programmg II Fal Exam COMSC 63 Summer Istructos: Name:. Prt your ame the space provded Studet Id:. Prt your studet detfer the space Secto: provded. Date: 3. Prt the secto umber of the secto whch you are
More informationMode Changes in Priority Pre-emptively Scheduled Systems. K. W. Tindell, A. Burns, A. J. Wellings
ode hages rorty re-emptvely Scheduled Systems. W. dell, A. Burs, A.. Wellgs Departmet of omputer Scece, Uversty of York, Eglad Abstract may hard real tme systems the set of fuctos that a system s requred
More informationEstimating Feasibility Using Multiple Surrogates and ROC Curves
Estmatg Feasblty Usg Multple Surrogates ad ROC Curves Arba Chaudhur * Uversty of Florda, Gaesvlle, Florda, 3601 Rodolphe Le Rche École Natoale Supéreure des Mes de Sat-Étee, Sat-Étee, Frace ad CNRS LIMOS
More informationTransistor/Gate Sizing Optimization
Trasstor/Gate Szg Optmzato Gve: Logc etwork wth or wthout cell lbrary Fd: Optmal sze for each trasstor/gate to mmze area or power, both uder delay costrat Statc szg: based o tmg aalyss ad cosder all paths
More informationNine Solved and Nine Open Problems in Elementary Geometry
Ne Solved ad Ne Ope Problems Elemetary Geometry Floret Smaradache Math & Scece Departmet Uversty of New Mexco, Gallup, US I ths paper we revew e prevous proposed ad solved problems of elemetary D geometry
More informationDEEP (Displacement Estimation Error Back-Propagation) Method for Cascaded ViSPs (Visually Servoed Paired Structured Light Systems)
DEEP (Dsplacemet Estmato Error Back-Propagato) Method for Cascaded VSPs (Vsually Servoed Pared Structured Lght Systems) Haem Jeo 1), Jae-Uk Sh 2), Wachoel Myeog 3), Yougja Km 4), ad *Hyu Myug 5) 1), 3),
More informationJournal of Chemical and Pharmaceutical Research, 2015, 7(3): Research Article
Avalable ole www.ocpr.com Joural of Chemcal ad Pharmaceutcal Research, 2015, 73):476-481 Research Artcle ISSN : 0975-7384 CODENUSA) : JCPRC5 Research o cocept smlarty calculato method based o sematc grd
More informationSupporting Capacity Planning for DB2 UDB *
Supportg Capacty Plag for DB2 DB * Hamzeh Zawawy 1,2, Patrck Mart 1 ad Hossam Hassae 1 1 School of Computg Quee's versty Kgsto, Otaro Caada K7L 3N6 2 IBM Toroto Laoratory Toroto, Otaro Caada M3C 1H7 Astract
More informationA MapReduce-Based Multiple Flow Direction Runoff Simulation
A MapReduce-Based Multple Flow Drecto Ruoff Smulato Ahmed Sdahmed ad Gyozo Gdofalv GeoIformatcs, Urba lag ad Evromet, KTH Drottg Krstas väg 30 100 44 Stockholm Telephoe: +46-8-790 8709 Emal:{sdahmed, gyozo}@
More informationFace Recognition using Supervised & Unsupervised Techniques
Natoal Uversty of Sgapore EE5907-Patter recogto-2 NAIONAL UNIVERSIY OF SINGAPORE EE5907 Patter Recogto Project Part-2 Face Recogto usg Supervsed & Usupervsed echques SUBMIED BY: SUDEN NAME: harapa Reddy
More informationReview Statistics review 1: Presenting and summarising data Elise Whitley* and Jonathan Ball
Crtcal Care February Vol 6 No Whtley ad Ball Revew Statstcs revew : Presetg ad summarsg data Else Whtley* ad Joatha Ball *Lecturer Medcal Statstcs, Uversty of Brstol, Brstol, UK Lecturer Itesve Care Medce,
More informationEffects of Exterior Orientation Elements on Direct Georeferencing in POS-Supported Aerial Photogrammetry
Proceedgs of the 8th Iteratoal mposum o patal Accurac Assessmet atural Resources ad Evrometal ceces hagha P. R. Cha Jue 5-7 008 pp. 30-36 Effects of Eteror Oretato Elemets o Drect Georeferecg PO-upported
More informationEinführung in Visual Computing
Eführug Vsual Computg 868 Global Illumato Werer Purgathofer Surface-Rederg Methods polygo rederg methods ray tracg global llumato evromet mappg teture mappg bump mappg Werer Purgathofer Global Illumato
More informationA Disk-Based Join With Probabilistic Guarantees*
A Dsk-Based Jo Wth Probablstc Guaratees* Chrstopher Jermae, Al Dobra, Subramaa Arumugam, Shatau Josh, Abhjt Pol Computer ad Iformato Sceces ad Egeerg Departmet Uversty of Florda, Gaesvlle {cjerma, adobra,
More informationUsing Linear-threshold Algorithms to Combine Multi-class Sub-experts
Usg Lear-threshold Algorthms to Combe Mult-class Sub-experts Chrs Mesterharm MESTERHA@CS.RUTGERS.EDU Rutgers Computer Scece Departmet 110 Frelghuyse Road Pscataway, NJ 08854 USA Abstract We preset a ew
More informationCOMPARISON OF PARAMETERIZATION METHODS USED FOR B-SPLINE CURVE INTERPOLATION
Europea Joural of Techc COMPARISON OF PARAMETERIZATION METHODS USED FOR B-SPLINE CURVE INTERPOLATION Sıtı ÖZTÜRK, Cegz BALTA, Melh KUNCAN 2* Kocael Üverstes, Mühedsl Faültes, Eletro ve Haberleşme Mühedslğ
More informationPreventing Information Leakage in C Applications Using RBAC-Based Model
Proceedgs of the 5th WSEAS It. Cof. o Software Egeerg Parallel ad Dstrbuted Systems Madrd Spa February 5-7 2006 (pp69-73) Prevetg Iformato Leakage C Applcatos Usg RBAC-Based Model SHIH-CHIEN CHOU Departmet
More informationInternational Mathematical Forum, 1, 2006, no. 31, ON JONES POLYNOMIALS OF GRAPHS OF TORUS KNOTS K (2, q ) Tamer UGUR, Abdullah KOPUZLU
Iteratoal Mathematcal Forum,, 6, o., 57-54 ON JONES POLYNOMIALS OF RAPHS OF TORUS KNOTS K (, q ) Tamer UUR, Abdullah KOPUZLU Atatürk Uverst Scece Facult Dept. of. Math. 54 Erzurum, Turkey tugur@atau.edu.tr
More informationA modified Logic Scoring Preference method for dynamic Web services evaluation and selection
A modfed Logc Scorg Preferece method for dyamc Web servces evaluato ad selecto Hog Qg Yu ad Herá Mola 2 Departmet of Computer Scece, Uversty of Lecester, UK hqy@mcs.le.ac.uk 2 Departmet of Iformatcs, School
More informationBlind Steganalysis for Digital Images using Support Vector Machine Method
06 Iteratoal Symposum o Electrocs ad Smart Devces (ISESD) November 9-30, 06 Bld Stegaalyss for Dgtal Images usg Support Vector Mache Method Marcelus Hery Meor School of Electrcal Egeerg ad Iformatcs Badug
More informationGreater Knowledge Extraction Based on Fuzzy Logic And GKPFCM Clustering Algorithm
6th WSEAS It. Coferece o Computatoal Itellgece, Ma-Mache Systems ad Cyberetcs, Teerfe, Spa, December 14-16, 2007 47 Greater Kowledge Extracto Based o uzzy Logc Ad GKPCM Clusterg Algorthm BEJAMÍ OJEDA-MAGAÑA
More informationBODY MEASUREMENT USING 3D HANDHELD SCANNER
Movemet, Health & Exercse, 7(1), 179-187, 2018 BODY MEASUREMENT USING 3D HANDHELD SCANNER Mohamed Najb b Salleh *, Halm b Mad Lazm, ad Hedrk b Lamsal Techology ad Supply Cha Isttute, School of Techology
More informationMINIMIZATION OF THE VALUE OF DAVIES-BOULDIN INDEX
MIIMIZATIO OF THE VALUE OF DAVIES-BOULDI IDEX ISMO ÄRÄIE ad PASI FRÄTI Departmet of Computer Scece, Uversty of Joesuu Box, FI-800 Joesuu, FILAD ABSTRACT We study the clusterg problem whe usg Daves-Bould
More informationArea and Power Efficient Modulo 2^n+1 Multiplier
Iteratoal Joural of Moder Egeerg Research (IJMER) www.jmer.com Vol.3, Issue.3, May-Jue. 013 pp-137-1376 ISSN: 49-6645 Area ad Power Effcet Modulo ^+1 Multpler K. Ptambar Patra, 1 Saket Shrvastava, Sehlata
More informationVanishing Point Detection: Representation Analysis and New Approaches
Publshed the Proceedgs of the th Iteratoal Coferece o Image Aalyss ad Processg (ICIAP ). IEEE. Persoal use of ths materal s permtted. However, permsso to reprt/republsh ths materal for advertsg or promotoal
More informationAPPLICATION OF CLUSTERING METHODS IN BANK S PROPENSITY MODEL
APPLICATION OF CLUSTERING METHODS IN BANK S PROPENSITY MODEL Sergej Srota Haa Řezaková Abstract Bak s propesty models are beg developed for busess support. They should help to choose clets wth a hgher
More informationA Comparison of Heuristics for Scheduling Spatial Clusters to Reduce I/O Cost in Spatial Join Processing
Edth Cowa Uversty Research Ole ECU Publcatos Pre. 20 2006 A Comparso of Heurstcs for Schedulg Spatal Clusters to Reduce I/O Cost Spatal Jo Processg Jta Xao Edth Cowa Uversty 0.09/ICMLC.2006.258779 Ths
More informationAutomated approach for the surface profile measurement of moving objects based on PSP
Uversty of Wollogog Research Ole Faculty of Egeerg ad Iformato Sceces - Papers: Part B Faculty of Egeerg ad Iformato Sceces 207 Automated approach for the surface profle measuremet of movg objects based
More informationClassification Web Pages By Using User Web Navigation Matrix By Mementic Algorithm
Classfcato Web Pages By Usg User Web Navgato Matrx By Memetc Algorthm 1 Parvaeh roustae 2 Mehd sadegh zadeh 1 Studet of Computer Egeerg Software EgeergDepartmet of ComputerEgeerg, Bushehr brach,
More informationEstimation of Co-efficient of Variation in PPS sampling.
It. Statstcal Ist.: Proc. 58th World Statstcal Cogress, 0, Dubl (Sesso CPS00) p.409 Estmato of Co-effcet of Varato PPS samplg. Archaa. V ( st Author) Departmet of Statstcs, Magalore Uverst Magalagagotr,
More informationTDT-2004: ADAPTIVE TOPIC TRACKING AT MARYLAND
TDT-2004: ADAPTIVE TOPIC TRACKING AT MARYLAND Tamer Elsayed, Douglas W. Oard, Davd Doerma Isttute for Advaced r Studes Uversty of Marylad, College Park, MD 20742 Cotact author: telsayed@cs.umd.edu Gary
More informationANALYSIS OF VARIANCE WITH PARETO DATA
Proceedgs of the th Aual Coferece of Asa Pacfc Decso Sceces Isttute Hog Kog, Jue -8, 006, pp. 599-609. ANALYSIS OF VARIANCE WITH PARETO DATA Lakhaa Watthaacheewakul Departmet of Mathematcs ad Statstcs,
More informationTowards Green Cloud Computing: Demand Allocation and Pricing Policies for. Cloud service brokerage.
15 IEEE Iteratoal Coferece o Bg Data (Bg Data) Towards Gree Cloud Computg: Demad Allocato ad Prcg Polces for Cloud Servce Broerage Chex Qu, Hayg She ad Luhua Che Departmet of Electrcal ad Computer Egeerg
More informationOptimal Allocation of Complex Equipment System Maintainability
Optmal Allocato of Complex Equpmet System ataablty X Re Graduate School, Natoal Defese Uversty, Bejg, 100091, Cha edcal Protecto Laboratory, Naval edcal Research Isttute, Shagha, 200433, Cha Emal:rexs841013@163.com
More informationFace Authentication for Multiple Subjects Using Eigenflow
Face Authetcato for Multple Subjects Usg Egeflow Xaomg Lu Tsuha Che ad B.V.K. Vjaya Kumar Advaced Multmeda Processg Lab Techcal Report AMP -5 Aprl 2 Electrcal ad Computer Egeerg Carege Mello Uversty Pttsburgh,
More informationEnumerating XML Data for Dynamic Updating
Eumeratg XML Data for Dyamc Updatg Lau Ho Kt ad Vcet Ng Departmet of Computg, The Hog Kog Polytechc Uversty, Hug Hom, Kowloo, Hog Kog cstyg@comp.polyu.edu.h Abstract I ths paper, a ew mappg model, called
More informationBeijing University of Technology, Beijing , China; Beijing University of Technology, Beijing , China;
d Iteratoal Coferece o Machery, Materals Egeerg, Chemcal Egeerg ad Botechology (MMECEB 5) Research of error detecto ad compesato of CNC mache tools based o laser terferometer Yuemg Zhag, a, Xuxu Chu, b
More informationA Type of Variation of Hamilton Path Problem with Applications
Edth Cowa Uersty Research Ole ECU Publcatos Pre. 20 2008 A Type of Varato of Hamlto Path Problem wth Applcatos Jta Xao Edth Cowa Uersty Ju Wag Wezhou Uersty, Zhejag, Cha 0.09/ICYCS.2008.470 Ths artcle
More informationOn a Sufficient and Necessary Condition for Graph Coloring
Ope Joural of Dscrete Matheatcs, 04, 4, -5 Publshed Ole Jauary 04 (http://wwwscrporg/joural/ojd) http://dxdoorg/0436/ojd04400 O a Suffcet ad Necessary Codto for raph Colorg Maodog Ye Departet of Matheatcs,
More informationHybrid Landmark Routing in Ad Hoc Networks with Heterogeneous Group Mobility
Hybrd Ladmark Routg Ad Hoc Networks wth Heterogeeous Group Moblty Yeg-Zhog Lee, Kax Xu 2, Xaoya Hog 3, Maro Gerla Computer Scece Departmet, Uversty of Calfora, Los Ageles, CA, {yeglee, gerla}@cs.ucla.edu
More informationA New Approach for Reconstructed B-spline Surface Approximating to Scattered Data Points. Xian-guo CHENG
2016 Iteratoal Coferece o Computer, Mechatrocs ad Electroc Egeerg (CMEE 2016 ISBN: 978-1-60595-406-6 A New Approach for Recostructed B-sple Surface Approxmatg to Scattered Data Pots Xa-guo CHENG Ngbo Uversty
More informationTopology Design for Directional Range Extension Networks with Antenna Blockage
Topology Desg for Drectoal Rage Exteso etworks wth Atea Blockage Thomas Shake MIT Lcol Laboratory shake@ll.mt.edu Abstract Extedg the rage of local area surface etworks by usg small arcraft to relay traffc
More informationApplication of Genetic Algorithm for Computing a Global 3D Scene Exploration
Joural of Software Egeerg ad Applcatos, 2011, 4, 253-258 do:10.4236/jsea.2011.44028 Publshed Ole Aprl 2011 (http://www.scrp.org/joural/jsea) 253 Applcato of Geetc Algorthm for Computg a Global 3D Scee
More informationProcess Quality Evaluation based on Maximum Entropy Principle. Yuhong Wang, Chuanliang Zhang, Wei Dai a and Yu Zhao
Appled Mechacs ad Materals Submtted: 204-08-26 ISSN: 662-7482, Vols. 668-669, pp 625-628 Accepted: 204-09-02 do:0.4028/www.scetfc.et/amm.668-669.625 Ole: 204-0-08 204 Tras Tech Publcatos, Swtzerlad Process
More informationCLUSTERING ASSISTED FUNDAMENTAL MATRIX ESTIMATION
CLUSERING ASSISED FUNDAMENAL MARIX ESIMAION Hao Wu ad Y Wa School of Iformato Scece ad Egeerg, Lazhou Uversty, Cha wuhao1195@163com, wayjs@163com ABSRAC I computer vso, the estmato of the fudametal matrx
More informationAuto-Scalability in Cloud: A Surveyof Energy and Sla Efficient Virtual Machine Consolidation
SSRG Iteratoal Joural of Computer Scece ad Egeerg (SSRG-IJCSE volume 3 Issue November 06 Auto-Scalablty Cloud: A Surveyof Eergy ad Sla Effcet Vrtual Mache Cosoldato A.Rchard Wllam, Dr.J.Sethlkumar Asst.
More informationAnalysis of Energy Consumption and Lifetime of Heterogeneous Wireless Sensor Networks
Aalyss of Eergy Cosumpto ad Lfetme of Heterogeeous Wreless Sesor Networks Erque J. Duarte-Melo, Mgya Lu EECS, Uversty of Mchga, A Arbor ejd, mgya @eecs.umch.edu Abstract The paper exames the performace
More informationMATHEMATICAL PROGRAMMING MODEL OF THE CRITICAL CHAIN METHOD
MATHEMATICAL PROGRAMMING MODEL OF THE CRITICAL CHAIN METHOD TOMÁŠ ŠUBRT, PAVLÍNA LANGROVÁ CUA, SLOVAKIA Abstract Curretly there s creasgly dcated that most of classcal project maagemet methods s ot sutable
More informationK-means Based Energy Aware Clustering Algorithm in Wireless Sensor Network Anand Gachhadar, Om Nath Acharya
156 Iteratoal Joural of Scetfc & Egeerg Research, Volume 5, Issue 5, May-2014 K-meas Based Eergy Aware Clusterg Algorthm Wreless Sesor Network Aad Gachhadar, Om Nath Acharya Abstract I ths artcle, a eergy
More informationSoftware Clustering Techniques and the Use of Combined Algorithm
Software Clusterg Techques ad the Use of Combed Algorthm M. Saeed, O. Maqbool, H.A. Babr, S.Z. Hassa, S.M. Sarwar Computer Scece Departmet Lahore Uversty of Maagemet Sceces DHA Lahore, Paksta oaza@lums.edu.pk
More informationABSTRACT Keywords
A Preprocessg Scheme for Hgh-Cardalty Categorcal Attrbutes Classfcato ad Predcto Problems Daele Mcc-Barreca ClearCommerce Corporato 1100 Metrc Blvd. Aust, TX 78732 ABSTRACT Categorcal data felds characterzed
More informationChEn 475 Statistical Analysis of Regression Lesson 1. The Need for Statistical Analysis of Regression
Statstcal-Regresso_hadout.xmcd Statstcal Aalss of Regresso ChE 475 Statstcal Aalss of Regresso Lesso. The Need for Statstcal Aalss of Regresso What do ou do wth dvdual expermetal data pots? How are the
More informationCollaborative Filtering Support for Adaptive Hypermedia
Collaboratve Flterg Support for Adaptve Hypermeda Mart Balík, Iva Jelíek Departmet of Computer Scece ad Egeerg, Faculty of Electrcal Egeerg Czech Techcal Uversty Karlovo áměstí 3, 35 Prague, Czech Republc
More informationEDGE- ODD Gracefulness of the Tripartite Graph
EDGE- ODD Graceuless o the Trpartte Graph C. Vmala, A. Saskala, K. Ruba 3, Asso. Pro, Departmet o Mathematcs, Peryar Maamma Uversty, Vallam, Thajavur Post.. Taml Nadu, Ida. 3 M. Phl Scholar, Departmet
More informationProf. Feng Liu. Winter /24/2019
Prof. Feg Lu Wter 209 http://www.cs.pd.edu/~flu/courses/cs40/ 0/24/209 Last Tme Feature detecto 2 Toda Feature matchg Fttg The followg sldes are largel from Prof. S. Lazebk 3 Wh etract features? Motvato:
More informationDelay based Duplicate Transmission Avoid (DDA) Coordination Scheme for Opportunistic routing
Delay based Duplcate Trasmsso Avod (DDA) Coordato Scheme for Opportustc routg Ng L, Studet Member IEEE, Jose-Fera Martez-Ortega, Vcete Heradez Daz Abstract-Sce the packet s trasmtted to a set of relayg
More informationWeighting Cache Replace Algorithm for Storage System
Weghtg Cache Replace Algorthm for Storage System Yhu Luo 2 Chagsheg Xe 2 Chegfeg Zhag 2 School of mathematcs ad Computer Scece, Hube Uversty, Wuha 430062, P.R. Cha 2 Natoal Storage System Laboratory, School
More informationAn evaluation of the paired comparisons method for software sizing
A evaluato of the pared comparsos method for software szg ABSTRACT Ths paper evaluates the accuracy, precso ad robustess of the pared comparsos method for software szg ad cocludes that the results produced
More informationSoftware reliability is defined as the probability of failure
Evolutoary Regresso Predcto for Software Cumulatve Falure Modelg: a comparatve study M. Beaddy, M. Wakrm & S. Aljahdal 2 : Dept. of Math. & Ifo. Equpe MMS, Ib Zohr Uversty Morocco. beaddym@yahoo.fr 2:
More informationAn Improved Fuzzy C-Means Clustering Algorithm Based on Potential Field
07 d Iteratoal Coferece o Advaces Maagemet Egeerg ad Iformato Techology (AMEIT 07) ISBN: 978--60595-457-8 A Improved Fuzzy C-Meas Clusterg Algorthm Based o Potetal Feld Yua-hag HAO, Zhu-chao YU *, X GAO
More informationNonparametric Comparison of Two Dynamic Parameter Setting Methods in a Meta-Heuristic Approach
Noparametrc Comparso of Two Dyamc Parameter Settg Methods a Meta-Heurstc Approach Seyhu HEPDOGAN, Ph.D. Departmet of Idustral Egeerg ad Maagemet Systems, Uversty of Cetral Florda Orlado, Florda 32816,
More informationGrid Resource Discovery Algorithm Based on Distance
966 JOURNAL OF SOFTWARE, OL. 9, NO., NOEMBER 4 Grd Resource Dscovery Algorthm Based o Dstace Zhogpg Zhag,, Log He, Chao Zhag The School of Iformato Scece ad Egeerg, Yasha Uversty, Qhuagdao, Hebe, 664,
More informationNUMERICAL INTEGRATION BY GENETIC ALGORITHMS. Vladimir Morozenko, Irina Pleshkova
5 Iteratoal Joural Iformato Theores ad Applcatos, Vol., Number 3, 3 NUMERICAL INTEGRATION BY GENETIC ALGORITHMS Vladmr Morozeko, Ira Pleshkova Abstract: It s show that geetc algorthms ca be used successfully
More informationUnsupervised visual learning of three-dimensional objects using a modular network architecture
PERGAMON Neural Networks 12 (1999) 1037 1051 Neural Networks www.elsever.com/locate/euet Usupervsed vsual learg of three-dmesoal objects usg a modular etwork archtecture H. Ado a, *, S. Suzuk a,b, T. Fujta
More informationCubic fuzzy H-ideals in BF-Algebras
OSR Joural of Mathematcs (OSR-JM) e-ssn: 78-578 p-ssn: 39-765X Volume ssue 5 Ver (Sep - Oct06) PP 9-96 wwwosrjouralsorg Cubc fuzzy H-deals F-lgebras Satyaarayaa Esraa Mohammed Waas ad U du Madhav 3 Departmet
More informationClustered Signatures for Modeling and Recognizing 3D Rigid Objects
World Academy of Scece, Egeerg ad Techology 4 008 Clustered Sgatures for Modelg ad Recogzg 3D Rgd Obects H. B. Darbad, M. R. Ito, ad J. Lttle Abstract Ths paper descrbes a probablstc method for three-dmesoal
More informationOMAE HOW TO CARRY OUT METOCEAN STUDIES
Proceedgs of the ASME 20 30th Iteratoal Coferece o Ocea, Offshore ad Arctc Egeerg OMAE20 Jue 9-24, 20, Rotterdam, The Netherlads OMAE20-490 HOW TO CARRY OUT METOCEAN STUDIES Judth va Os Hydraulc Egeerg
More informationToward Undetected Operating System Fingerprinting
Toward Udetected Operatg System Fgerprtg Lloyd G. Greewald ad Tavars J. Thomas LGS Bell Labs Iovatos {lgreewald, tthomas}@lgsovatos.com Abstract Tools for actve remote operatg system fgerprtg geerate may
More informationA Framework for Block-Based Timing Sensitivity Analysis
39.3 Framework for Block-Based Tmg Sestvty alyss Sajay V. Kumar Chadramoul V. Kashyap Sach S. Sapatekar Uversty of Mesota Itel Corporato Uversty of Mesota Meapols MN 55455 Hllsboro OR 973 Meapols MN 55455
More informationImpact of Mobility Prediction on the Temporal Stability of MANET Clustering Algorithms *
Impact of Moblty Predcto o the Temporal Stablty of MANET Clusterg Algorthms * Aravdha Vekateswara, Vekatesh Saraga, Nataraa Gautam 1, Ra Acharya Departmet of Comp. Sc. & Egr. Pesylvaa State Uversty Uversty
More informationImproved MOPSO Algorithm Based on Map-Reduce Model in Cloud Resource Scheduling
Improved MOPSO Algorthm Based o Map-Reduce Model Cloud Resource Schedulg Heg-We ZHANG, Ka NIU *, J-Dog WANG, Na WANG Zhegzhou Isttute of Iformato Scece ad Techology, Zhegzhou 45000, Cha State Key Laboratory
More informationAn Evaluation of Composite Routing and Scheduling Policies for Dynamic Multimedia Environments
A Evaluato o Composte Routg ad Schedulg Polces or Dyamc Multmeda Evromets Zheghua Fu ad Nal Vekatasubramaa Departmet o Iormato ad Computer Scece Uversty o Calora, Irve, Irve CA 92697-3425 {zu,al}@cs.uc.edu
More informationFingerprint Classification Based on Spectral Features
Fgerprt Classfcato Based o Spectral Features Hosse Pourghassem Tarbat Modares Uversty h_poorghasem@modares.ac.r Hassa Ghassema Tarbat Modares Uversty ghassem@modares.ac.r Abstract: Fgerprt s oe of the
More informationAn Energy-Oriented Node Characteristics-Aware Routing Algorithm for Wireless LAN
MM11-74 1 A Eergy-Oreted Node Characterstcs-Aware Routg Algorthm for Wreless LAN Ruq Dg ad Gabrel-Mro Mutea, Member, IEEE Abstract A growg umber of dfferet techologysupported wreless etworks are beg deployed
More informationA Simple Dimensionality Reduction Technique for Fast Similarity Search in Large Time Series Databases
A Smple Dmesoalty Reducto Techque for Fast Smlarty Search Large Tme Seres Databases Eamo J. Keogh ad Mchael J. Pazza Departmet of Iformato ad Computer Scece Uversty of Calfora, Irve, Calfora 92697 USA
More informationA Network Architecture for a Policy-Based Handover Across Heterogeneous Networks
A Networ Archtecture for a Polcy-Based Hadover Across Heterogeeous Networs Rast Pres, Adreas äder, ad Dr Staehle Departmet of Dstrbuted Systems, Isttute of Computer Scece, Uversty of Würzburg Am Hublad,
More informationLaplacian Meshes Deformation Based on the Offset of Sketching
JOURNAL OF SOFTWARE, VOL. 7, NO. 9, SEPTEMBER 202 2083 Laplaca Meshes Deformato Based o the Offset of Sketchg Sha Chemg School of Software, Harb Uversty of Scece ad Techology, Harb, Cha Emal: shachm@63.com
More information