A FASTER EXTERNAL SORTING ALGORITHM USING NO ADDITIONAL DISK SPACE
|
|
- Shannon Dalton
- 7 years ago
- Views:
Transcription
1 47 A FASTER EXTERAL SORTIG ALGORITHM USIG O ADDITIOAL DISK SPACE Md. Rafqul Islam +, Mohd. oor Md. Sap ++, Md. Sumon Sarker +, Sk. Razbul Islam + + Computer Scence and Engneerng Dscplne, Khulna Unversty, Khulna-908, Bangladesh. ++ Faculty of Computer Scence and Informaton System, Unversty of Technology Malaysa, Skuda, Johor Bahru, Malaysa dmr978@yahoo.com, mohdnoor@fsksm.utm.my, sumonsrkr@yahoo.com, optmst_95@yahoo.com Abstract The effectve performance of the external sortng s analyzed n terms of both tme and I/O complextes. Ths paper s concerned wth a more effcent external sortng algorthm, where both the tme and I/O (read and wrte) complextes have been reduced. The proposed method s a hybrd technque that uses quck sort and merge sort n two dstnct phases. Both the tme and I/O complextes of the proposed algorthm are analyzed here and compared wth the complextes of the exstng smlar algorthms. The proposed algorthm uses specal n-place mergng technque, whch creates no extra backup fle for manpulatng huge records. For ths, the algorthm saves huge dsk space, whch s needed to hold the large fle. Ths also reduces tme complexty and makes the algorthm faster. Keywords: complexty, external sortng, n-place mergng, quck sort, runs.. ITRODUCTIO Sortng means to arrange records or data n an ascendng or descendng order. But when the sze of the records become so much larger than the nternal memory can hold at a tme, then the stuaton arse to use external sortng. It s qute dfferent nternal sortng, even though the problem n both cases s to sort a gven fle nto ncreasng or decreasng order. The most common external sortng algorthm stll uses the merge sort as descrbed by Knuth []. In balanced two-way merge, runs (sorted records whch can ft nto the nternal memory) are dstrbuted over two external fles and another two external fles are used to hold the merged runs of the prevous external fles. After each merge the length of runs becomes double. When all the runs are merged nto a sngle run, the process stops. The key drawback of ths process s that t requres extra dsk space. Dufrene and Ln [] and M. R. Islam et al. [3] proposed ther algorthms n whch no external fle s needed; only the orgnal fle s used. M. R. Islam et al. [4][5] proposed an algorthm that uses no extra dsk space and faster than both the algorthms proposed by Dufrene and Ln [] and M. R. Islam et al. [3]. Here we have proposed an effcent external sortng algorthm wth no addtonal dsk space based on the algorthms proposed by Dufrene and Ln [], M. R. Islam et al. [4] and M. R. Islam et al. Jld 8, Bl. (Dsember 006) Jurnal Teknolog Maklumat
2 48 [3][6]. The proposed algorthm wll reduce both the tme and I/O complextes of the algorthm proposed by M. R. Islam et al. [4][7].. ALGORITHM REVIEW The proposed algorthm s based on the algorthms proposed by Dufrene and Ln [], M. R. Islam et al. [4] and M. R. Islam et al. [3][7]. Among these algorthms, the overall performance of M. R. Islam et al. [4] s better than others. So, we wll only revew M. R. Islam et al. [4] algorthm n the next subsecton.. A ew External Sortng Algorthm wth o Addtonal Dsk Space wth Specal Inplace Mergng Technque Ths algorthm proposed by M. R. Islam et al. [4], whch works n two phases. In the frst phase the algorthm works same as Dufrene and Ln s [] algorthm wth the only dfference that at the last teraton of frst phase, lower half of man memory s wrtten to the poston of Block_ of the external fle keepng Block_ n the upper half of man memory. In the second phase, the records of Block_S are read nto lower half of man memory. Then the records of lower and upper half of memory are merged usng specal In-place mergng technque whch requres no extra space. After sortng n the memory usng In-place mergng, records of the upper half of memory are wrtten to Block_S and records of Block_S- are read nto upper half of man memory. When the last block Block_3 has been processed, the lower half of man memory contans lowest sorted data among Block_ to Block_S. Then the records of lower half of memory are wrtten n the poston of Block_. Ths process contnues untl Block_S- and Block_S are processed. The I/O complexty of the algorthm s less than that of algorthm proposed by M. R. Islam et al. [3]. 3. A FASTER EXTERAL SORTIG ALGORITHM USIG O ADDITIOAL DISK SPACE The proposed algorthm works n several phases. In the frst phase, the external fle s dvded nto equal szed blocks, where the sze of each block s approxmately equal to the avalable man memory (RAM) of the computer. If the sze of the avalable nternal memory s M then the sze of each block s M and f the sze of external fle s then the number of block, S = /M. Block_ s read nto memory. Then the records of the man memory are sorted usng quck sort and agan wrtten to Block_. The process contnues untl the last block, Block_S, has been processed. After ths the proposed algorthm swtches to ts next phase. Each sorted block s dvded nto two sub-blocks, B_ and B_. The sub block B_ of Block_ and sub block B_ of Block_ are read nto the lower half and upper half of the memory array respectvely. Then the records of the lower half and the upper half of the man Jld 8, Bl. (Dsember 006) Jurnal Teknolog Maklumat
3 49 memory, whch are ndvdually sorted are merged usng specal In-place mergng technque [4]. After sortng, the records of the upper half of the man memory are wrtten to B_ of Block_ and the records of the sub block B_ of Block_3 are read nto the upper half of the man memory. Then the records of the man memory are agan merged usng specal In-place mergng technque and the records of the upper half of the man memory are wrtten n the poston of B_ of Block_3 and read the records of sub block B_ of Block_4 to the upper half of the man memory. Repeat ths process untl the records of sub block B_ of Block_S are read nto the upper half of the man memory and processed. ow the lower half of the man memory contans the lowest sorted records among the records Block_ to Block_S and s wrtten n the poston of B_ of Block_. External Fle Block_ Block_ Block_S- Block_S Sorted Records Sorted Records Sorted Records (a) Sorted Records Block_ Block_ Block_S B_ B_ B_ B_ B_ B_ B_ B_ Sub Block (b) Block_ Block_ Block_S B_ B_ B_ B_ B_ B_ Lowest Sorted Records (c) Hghest Sorted Records Block_ Block_ Block_S B_ B_ B_ B_ B_ B_ B_ (d) Fgure. External fle after (a) applyng quck sort (b) splttng each block nto sub blocks, (c) frst teraton (d) renamng the blocks and sub blocks except frst and last sub block. ow sub block B_ of Block_S and sub block B_ of Block_S- are read nto the upper and lower half of the memory array respectvely. Then the records of the lower half and upper half of the man memory are merged usng specal In-place mergng technque. After mergng, the records of the lower half of the man memory are wrtten to B_ of Block_S- and the records of the sub block B_ of Block_S- are read nto the lower half of the man memory. Then the records of the man memory are agan merged usng specal In-place mergng technque and Jld 8, Bl. (Dsember 006) Jurnal Teknolog Maklumat
4 50 the records of the lower half of the man memory are wrtten n the poston of B_ of Block_S- and read the records of sub block B_ of Block_S-3 to the lower half of man memory. Repeat ths process untl the records of the sub block B_ of Block_ are read nto the lower half of the man memory and processed. ow the upper half of the man memory contans the hghest sorted records among the records Block_ to Block_S and s wrtten n the poston of B_ of Block_S. At ths pont sub block B_ of Block_ and sub block B_ of Block_S contans the lowest and hghest sorted records respectvely. ow, read B_ of Block_ and B_ of Block_ n the man memory and after mergng, wrte lower and upper half at the poston of B_ of Block_ and B_ of Block_ respectvely. ow rename B_ of Block_ as B_ and B_ of Block_ as B_ and let both B_ and B_ are under Block_. Smlarly merge B_ of Block_ and B_ of Block_3 and after renamng, let they are under Block_. Repeat ths technque untl B_ of Block_S has been processed. Let the last new Block be Block_S. Then apply the above procedure for the new blocks, Block_ to Block_S, to get the next lowest and hghest sorted records. After each teraton the sze of the external fle s decreased by one sub block. Completng all teratons we get the entre fle sorted. Algorthm 3. n Fgure brngs out the whole procedure.. Declare blocks n the external fle to be equal of the avalable man memory. Let the blocks be Block_, Block_,, Block_(S-), Block_S. set P =.. Read Block_P to the man memory. 3. Sort the data of the man memory usng quck sort, wrte the sorted data to Block_P and set P = P +, f P S read Block_P to the man memory and repeat ths step. 4. Dvde each block nto two sub blocks B_ and B_. Here each sub block equals the half of the avalable man memory. 5. Read sub block B_ of Block_ to the lower half of the avalable man memory. Set Q =. 6. Read sub block B_ of Block_Q to the upper half of the avalable man memory. 7. Merge the data of the man memory usng specal In-place mergng [3], wrte upper half to B_ of Block_Q and set Q = Q +, f Q S, read B_ of Block_Q to upper half of the avalable man memory and repeat ths step. 8. Wrte the lower half to B_ of Block_. Fgure. External Sortng Algorthm Jld 8, Bl. (Dsember 006) Jurnal Teknolog Maklumat
5 5 9. Read B_ of Block_S to the upper half of the avalable man memory. Set Q = S. 0. Read B_ of Block_Q to the lower half of the avalable man memory.. Merge the data of the man memory usng specal In-place mergng [4], wrte lower half to B_ of Block_Q and set Q = Q. If Q read B_ of Block_Q to lower half of the man memory and repeat ths step.. Wrte the upper half to B_ of Block_S. 3. From B_ of Block_ to B_ of Block_S, declare new blocks n the external fle to be equal of the avalable memory and agan gve the number Block_ to Block_S. Dvde each block nto two sub blocks B_ and B_. Here each sub block equals the half of the avalable man memory. Set P =. 4. Read B_ and B_ of Block_P to the man memory. Merge lower and upper half of Block_P. Wrte the sorted data to Block_P n the external fle and set P = P +. If P S, repeat ths step. 5. If S >, go to step 5. Fgure. External Sortng Algorthm (cont.) 4. COMPLEXITIES AALYSIS OF THE PROPOSED ALGORITHM In ths secton we wll deduce the dsk I/Os and the tme complextes of the proposed algorthm. 4. Input Complexty In the frst phase /M blocks wll have to be processed by quck sort, so t wll take /M read (nput) operatons n the frst phase. In the next phase to obtan the frst lowest sorted sub block t wll take /M read operatons and to obtan the frst hghest sorted sub block t wll also take /M read operatons. ext (/M ) blocks wll have to be processed by specal Inplace mergng to generate the new blocks. So t wll take (/M ) read operatons. Then, to obtan the next lowest and hghest sorted sub blocks t wll take (/M ) read operatons n both cases and so on. So total dsk nput s Jld 8, Bl. (Dsember 006) Jurnal Teknolog Maklumat
6 5 ( M + M + M ) + {( M ) + ( M ) + ( M )} { + + } + 3 ( M ) + 3 ( M ) () + 3{ M + ( M ) } + / M + 3 () 4. Output Complexty In the frst phase the proposed algorthm wll take /M wrte (output) operatons. In the next phase to obtan the frst lowest sorted sub block t wll take /M wrte operatons and to obtan the frst hghest sorted sub block t wll take /M wrte operaton. ext (/M ) blocks wll have to be processed to generate the new blocks. So t wll requre (/M ) wrte operatons. Then, to obtan the next lowest and hghest sorted sub block t wll take (/M ) wrte operatons n both cases and so on. So the total output operaton s { M + M + M } + {( M ) + ( M ) + ( M )} { + + } + 3 ( M ) + 3 ( M ) () + 3{ M + ( M ) } + / M + 3 () 4.3 Tme Complexty The tme complexty of the nternal quck sort s O(n log e n) n average case (as gven by Knuth []). Here n s the number of records to be sorted. So, the tme complexty of the frst phase of the proposed algorthm s (/M)(n log e n). In the next phase, the algorthm uses specal In-place mergng technque. The tme complexty of the mergng technque depends on the number of comparson (as gven by Knuth []). To merge n data usng specal In-place mergng technque t wll need n comparsons. So the tme complexty to obtan the frst lowest and hghest sorted sub block s (/M ) n + (/M ) n = (/M ) n. As, after each teraton the fle sze s decreased by one sub block, so the total tme complexty s Jld 8, Bl. (Dsember 006) Jurnal Teknolog Maklumat
7 53 {( (n loge n) + ( )n} + [( ) n + {( ) }n] [n + ( ) n] + n M M M M / M / M ( ) (n loge n) + n M + n / M ( ) (n loge n) + 3n M (3) 5. COMPARISO AD DISCUSSIO For smplcty of dscusson we shall use the followng notatons for the algorthms (exstng algorthms) to pont out n ths paper. (a) Dufrene and Ln, An effcent sortng algorthm wth no addtonal dsk space, [], (Algorthm ) (b) M. R. Islam et al., A ew External Sortng Algorthm wth o Addtonal Dsk Space wth Specal In-place Mergng Technque, [4], (Algorthm ) (c) Proposed Algorthm, A Faster External Sortng Algorthm Usng o Addtonal Dsk Space, (Algorthm 3) The I/O and tme complextes of the algorthms proposed by Algorthm, Algorthm and Algorthm 3 are shown n Table. Table : Complextes of the Algorthms proposed by Algorthm, Algorthm and Algorthm 3 Complexty Algorthm Algorthm Algorthm 3 Input Output B B + B + B B B B B + / M + 3 / M + 3 Tme n log n e / B ( ) nlog B e n + n / B / M ( ) (n loge n) +3n M Here the I/O and tme complexty of Algorthm s better than that of Algorthm. So the overall performance of Algorthm s better than Algorthm. So we shall compare and dscuss the complextes of Algorthm and the Algorthm 3. Moreover, the value of M n the Algorthm 3 equals to B n the Algorthm. So, whle performng comparson M has been replaced by B. Jld 8, Bl. (Dsember 006) Jurnal Teknolog Maklumat
8 54 5. Comparson of Input Complextes Let, the nput complexty of Algorthm, I = + and B B / B the Algorthm 3, I = + 3 ow, I I = + 3 B B / B = B / B 3 B = Here, for > 6B, (I I ) > 0 or I > I. So, the nput complexty of the Algorthm 3 s less than that of Algorthm for > 6B. 5. Comparson of Output Complextes Let, the output complexty of Algorthm, O = and B B / B the Algorthm 3, O = + 3 ow, O O / B = B 3 B = B / B 3 B Here, for 0B, (O O ) > 0 or O > O. So, the output complexty of the Algorthm 3 s less than that of Algorthm for 0B. Jld 8, Bl. (Dsember 006) Jurnal Teknolog Maklumat
9 Comparson of Tme Complextes Let, the tme complexty of Algorthm, T = ( B ) n log e n + n / B and / B the Algorthm 3, T = ( B ) (n log e n) + 3n ow, T T B = ( ) n loge n + n B / / B ( B ) (n log e n) 3n / B = ( ) n log e n + B B n 3n / B / B = ( ) n log e n + n { B B 3 } / B B = ( ) nlog e n B / B / B + n { 3 } Here, for > B, (T T ) > 0 or T > T. So, the tme complexty of the Algorthm 3 s less than that of Algorthm for > B. 6. THEORETICAL RESULTS: The theoretcal results of Algorthm, Algorthm and Algorthm 3 have been shown n tabular format: Table : Reducton of nput Complexty of Algorthm 3 Algorthm and Algorthm External fle sze RAM sze Rato (Algorthm 3 / Algorthm ) Reducton Algorthm Rato (Algorthm 3 / Algorthm ) Reducton Algorthm (%) (%) Jld 8, Bl. (Dsember 006) Jurnal Teknolog Maklumat
10 56 Form the Table we see that n case of Algorthm f External Fle 00MB and n case of Algorthm f External Fle > 600MB, reducton of readng nput of Algorthm 3 n percentage s gradually ncreasng. Table 3: Reducton of Output Complexty of Algorthm 3 Algorthm and Algorthm External fle sze RAM sze Rato (Algorthm 3 / Algorthm ) Reducton Algorthm Rato (Algorthm 3 / Algorthm ) Reducton Algorthm (%) (%) Form the Table 3 we see that n case of Algorthm f External Fle 00MB and n case of Algorthm f External Fle 000MB, reducton of wrtng output of Algorthm 3 n percentage s gradually ncreasng. Table 4: Reducton of Tme Complexty of Algorthm 3 Algorthm and Algorthm External fle sze RAM sze Rato (Algorthm 3 / Algorthm ) Reducton Algorthm (%) Rato (Algorthm 3 / Algorthm ) Reducton Algorthm (%) From Table 4 we see that n case of both Algorthm and Algorthm, f External fle sze 00MB, reducton of executon tme of Algorthm 3 n percentage s gradually ncreasng. Jld 8, Bl. (Dsember 006) Jurnal Teknolog Maklumat
11 57 7. EXPERIMETAL RESULTS The expermental results of Algorthm, Algorthm and Algorthm 3 have been shown n tabular format below: The confguraton of the system where we have performed the experment: Operatng System : Mcrosoft Wndows XP Professonal, Verson 00, Servce Pack. Processor : Intel (R) Pentum(R) 4 CPU.80GHz Memory : 56MB RD RAM Envronment : Vsual C++.et 003 Table 5: Expermental Results for Input Externa l Fle sze RAM Sze Input for Algorth m () Input for Algorthm () Input for Algorth m (3) Reducton Algorthm (%) Reducton Algorthm (%) Table 6: Expermental Results for Output External Fle sze RAM Sze Output for Algorth m () Output for Algorth m () Output for Algorth m (3) Reducton Algorthm (%) Reducton Algorthm (%) Jld 8, Bl. (Dsember 006) Jurnal Teknolog Maklumat
12 58 Table 7: Expermental Results for Executon Tme External Fle sze RAM Sze Tme for Algorthm () n mnutes Tme for Algorthm () n mnutes Tme for Algorthm (3) n mnutes Reducton Algorthm (%) Reducton Algorthm (%) COCLUSIOS We have mproved the performance of the external sortng n the proposed algorthm n terms of both I/O and tme complextes. The algorthm uses quck sort and In-place mergng technque [4] and reduces comparsons to generate mnmum and maxmum sorted sub blocks of records and uses no extra fle. Moreover, the dscusson n the prevous secton, we get the followng results:. The tme complexty of the Algorthm 3 s less than that of Algorthm.. The nput complexty of the Algorthm 3 s less than that of Algorthm for > 6B. 3. The output complexty of Algorthm 3 s less than that of Algorthm for 0B. So, the overall performance of the Algorthm 3 s better than that of Algorthm n terms of both I/O and tme complextes. REFERECES [] D. E. Knuth, Sortng and Searchng, The art of computer programmng Vol. 3, Addson- Wesley, Readng, MA, nd edton, 998. [] W. R. Dufrene, F. C. Ln, An effcent sortng algorthm wth no addtonal space, Compute. J. 35(3) (99). [3] M. R. Islam, S. M. R. Uddn, C. Roy, Computatonal complextes of the external sortng algorthm wth no addtonal dsk space, Internatonal Journal of Computer, Internet and Management (IJCIM), Thaland, Vol. 3, Issue 3, September - December, 005. Jld 8, Bl. (Dsember 006) Jurnal Teknolog Maklumat
13 59 [4] M. R. Islam, W. usrat, M. Hossan, S.M.M. Rana, A ew External Sortng Algorthm wth o Addtonal Dsk Space wth Specal In-place Mergng Technque, Presented at Internatonal Conference on Computer and Informaton Technology (ICCIT), 6-8 December 004, (Dhaka, Bangladesh). [5] M. R. Islam,. Adnan,. Islam, S. Hossen, A new external sortng algorthm wth no addtonal dsk space, Informaton Processng Letters 86(003), [6]. Adnan, R. Islam,. Islam, S. Hossen, A faster hybrd external sortng algorthm wth no addtonal dsk space publshed n the proceedngs of Internatonal Conference on Computer and Informaton Technology (ICCIT), 7-8 December 00 (Dhaka, Bangladesh) [7] S. M. Raqub Uddn, Md. Rafqul Islam, Chnmoy Roy, Complextes of an effcent external sortng algorthm wth specal cases publshed n the proceedngs of Conference on Computer and Informaton Technology (ICCIT), 9- December, 003 (Dhaka, Bangladesh). Jld 8, Bl. (Dsember 006) Jurnal Teknolog Maklumat
Logical Development Of Vogel s Approximation Method (LD-VAM): An Approach To Find Basic Feasible Solution Of Transportation Problem
INTERNATIONAL JOURNAL OF SCIENTIFIC & TECHNOLOGY RESEARCH VOLUME, ISSUE, FEBRUARY ISSN 77-866 Logcal Development Of Vogel s Approxmaton Method (LD- An Approach To Fnd Basc Feasble Soluton Of Transportaton
More information1 Example 1: Axis-aligned rectangles
COS 511: Theoretcal Machne Learnng Lecturer: Rob Schapre Lecture # 6 Scrbe: Aaron Schld February 21, 2013 Last class, we dscussed an analogue for Occam s Razor for nfnte hypothess spaces that, n conjuncton
More informationThe Development of Web Log Mining Based on Improve-K-Means Clustering Analysis
The Development of Web Log Mnng Based on Improve-K-Means Clusterng Analyss TngZhong Wang * College of Informaton Technology, Luoyang Normal Unversty, Luoyang, 471022, Chna wangtngzhong2@sna.cn Abstract.
More informationThe Load Balancing of Database Allocation in the Cloud
, March 3-5, 23, Hong Kong The Load Balancng of Database Allocaton n the Cloud Yu-lung Lo and Mn-Shan La Abstract Each database host n the cloud platform often has to servce more than one database applcaton
More informationVRT012 User s guide V0.1. Address: Žirmūnų g. 27, Vilnius LT-09105, Phone: (370-5) 2127472, Fax: (370-5) 276 1380, Email: info@teltonika.
VRT012 User s gude V0.1 Thank you for purchasng our product. We hope ths user-frendly devce wll be helpful n realsng your deas and brngng comfort to your lfe. Please take few mnutes to read ths manual
More informationMining Multiple Large Data Sources
The Internatonal Arab Journal of Informaton Technology, Vol. 7, No. 3, July 2 24 Mnng Multple Large Data Sources Anmesh Adhkar, Pralhad Ramachandrarao 2, Bhanu Prasad 3, and Jhml Adhkar 4 Department of
More informationAn Analysis of Central Processor Scheduling in Multiprogrammed Computer Systems
STAN-CS-73-355 I SU-SE-73-013 An Analyss of Central Processor Schedulng n Multprogrammed Computer Systems (Dgest Edton) by Thomas G. Prce October 1972 Techncal Report No. 57 Reproducton n whole or n part
More informationModule 2 LOSSLESS IMAGE COMPRESSION SYSTEMS. Version 2 ECE IIT, Kharagpur
Module LOSSLESS IMAGE COMPRESSION SYSTEMS Lesson 3 Lossless Compresson: Huffman Codng Instructonal Objectves At the end of ths lesson, the students should be able to:. Defne and measure source entropy..
More informationA Secure Password-Authenticated Key Agreement Using Smart Cards
A Secure Password-Authentcated Key Agreement Usng Smart Cards Ka Chan 1, Wen-Chung Kuo 2 and Jn-Chou Cheng 3 1 Department of Computer and Informaton Scence, R.O.C. Mltary Academy, Kaohsung 83059, Tawan,
More informationA hybrid global optimization algorithm based on parallel chaos optimization and outlook algorithm
Avalable onlne www.ocpr.com Journal of Chemcal and Pharmaceutcal Research, 2014, 6(7):1884-1889 Research Artcle ISSN : 0975-7384 CODEN(USA) : JCPRC5 A hybrd global optmzaton algorthm based on parallel
More informationVision Mouse. Saurabh Sarkar a* University of Cincinnati, Cincinnati, USA ABSTRACT 1. INTRODUCTION
Vson Mouse Saurabh Sarkar a* a Unversty of Cncnnat, Cncnnat, USA ABSTRACT The report dscusses a vson based approach towards trackng of eyes and fngers. The report descrbes the process of locatng the possble
More informationWhat is Candidate Sampling
What s Canddate Samplng Say we have a multclass or mult label problem where each tranng example ( x, T ) conssts of a context x a small (mult)set of target classes T out of a large unverse L of possble
More informationAn Enhanced Super-Resolution System with Improved Image Registration, Automatic Image Selection, and Image Enhancement
An Enhanced Super-Resoluton System wth Improved Image Regstraton, Automatc Image Selecton, and Image Enhancement Yu-Chuan Kuo ( ), Chen-Yu Chen ( ), and Chou-Shann Fuh ( ) Department of Computer Scence
More informationProject Networks With Mixed-Time Constraints
Project Networs Wth Mxed-Tme Constrants L Caccetta and B Wattananon Western Australan Centre of Excellence n Industral Optmsaton (WACEIO) Curtn Unversty of Technology GPO Box U1987 Perth Western Australa
More informationJ. Parallel Distrib. Comput.
J. Parallel Dstrb. Comput. 71 (2011) 62 76 Contents lsts avalable at ScenceDrect J. Parallel Dstrb. Comput. journal homepage: www.elsever.com/locate/jpdc Optmzng server placement n dstrbuted systems n
More informationELM for Exchange version 5.5 Exchange Server Migration
ELM for Exchange verson 5.5 Exchange Server Mgraton Copyrght 06 Lexmark. All rghts reserved. Lexmark s a trademark of Lexmark Internatonal, Inc., regstered n the U.S. and/or other countres. All other trademarks
More informationData Broadcast on a Multi-System Heterogeneous Overlayed Wireless Network *
JOURNAL OF INFORMATION SCIENCE AND ENGINEERING 24, 819-840 (2008) Data Broadcast on a Mult-System Heterogeneous Overlayed Wreless Network * Department of Computer Scence Natonal Chao Tung Unversty Hsnchu,
More informationAPPLICATION OF PROBE DATA COLLECTED VIA INFRARED BEACONS TO TRAFFIC MANEGEMENT
APPLICATION OF PROBE DATA COLLECTED VIA INFRARED BEACONS TO TRAFFIC MANEGEMENT Toshhko Oda (1), Kochro Iwaoka (2) (1), (2) Infrastructure Systems Busness Unt, Panasonc System Networks Co., Ltd. Saedo-cho
More informationOn the Optimal Control of a Cascade of Hydro-Electric Power Stations
On the Optmal Control of a Cascade of Hydro-Electrc Power Statons M.C.M. Guedes a, A.F. Rbero a, G.V. Smrnov b and S. Vlela c a Department of Mathematcs, School of Scences, Unversty of Porto, Portugal;
More informationImplementation of Boolean Functions through Multiplexers with the Help of Shannon Expansion Theorem
Internatonal Journal o Computer pplcatons (975 8887) Volume 62 No.6, January 23 Implementaton o Boolean Functons through Multplexers wth the Help o Shannon Expanson Theorem Saurabh Rawat Graphc Era Unversty.
More informationA Dynamic Load Balancing for Massive Multiplayer Online Game Server
A Dynamc Load Balancng for Massve Multplayer Onlne Game Server Jungyoul Lm, Jaeyong Chung, Jnryong Km and Kwanghyun Shm Dgtal Content Research Dvson Electroncs and Telecommuncatons Research Insttute Daejeon,
More informationCalculating the high frequency transmission line parameters of power cables
< ' Calculatng the hgh frequency transmsson lne parameters of power cables Authors: Dr. John Dcknson, Laboratory Servces Manager, N 0 RW E B Communcatons Mr. Peter J. Ncholson, Project Assgnment Manager,
More informationNPAR TESTS. One-Sample Chi-Square Test. Cell Specification. Observed Frequencies 1O i 6. Expected Frequencies 1EXP i 6
PAR TESTS If a WEIGHT varable s specfed, t s used to replcate a case as many tmes as ndcated by the weght value rounded to the nearest nteger. If the workspace requrements are exceeded and samplng has
More informationImproved SVM in Cloud Computing Information Mining
Internatonal Journal of Grd Dstrbuton Computng Vol.8, No.1 (015), pp.33-40 http://dx.do.org/10.1457/jgdc.015.8.1.04 Improved n Cloud Computng Informaton Mnng Lvshuhong (ZhengDe polytechnc college JangSu
More informationRate Monotonic (RM) Disadvantages of cyclic. TDDB47 Real Time Systems. Lecture 2: RM & EDF. Priority-based scheduling. States of a process
Dsadvantages of cyclc TDDB47 Real Tme Systems Manual scheduler constructon Cannot deal wth any runtme changes What happens f we add a task to the set? Real-Tme Systems Laboratory Department of Computer
More informationDEFINING %COMPLETE IN MICROSOFT PROJECT
CelersSystems DEFINING %COMPLETE IN MICROSOFT PROJECT PREPARED BY James E Aksel, PMP, PMI-SP, MVP For Addtonal Informaton about Earned Value Management Systems and reportng, please contact: CelersSystems,
More informationHollinger Canadian Publishing Holdings Co. ( HCPH ) proceeding under the Companies Creditors Arrangement Act ( CCAA )
February 17, 2011 Andrew J. Hatnay ahatnay@kmlaw.ca Dear Sr/Madam: Re: Re: Hollnger Canadan Publshng Holdngs Co. ( HCPH ) proceedng under the Companes Credtors Arrangement Act ( CCAA ) Update on CCAA Proceedngs
More informationThe Greedy Method. Introduction. 0/1 Knapsack Problem
The Greedy Method Introducton We have completed data structures. We now are gong to look at algorthm desgn methods. Often we are lookng at optmzaton problems whose performance s exponental. For an optmzaton
More informationAdaptive Fractal Image Coding in the Frequency Domain
PROCEEDINGS OF INTERNATIONAL WORKSHOP ON IMAGE PROCESSING: THEORY, METHODOLOGY, SYSTEMS AND APPLICATIONS 2-22 JUNE,1994 BUDAPEST,HUNGARY Adaptve Fractal Image Codng n the Frequency Doman K AI UWE BARTHEL
More informationPolitecnico di Torino. Porto Institutional Repository
Poltecnco d Torno Porto Insttutonal Repostory [Artcle] A cost-effectve cloud computng framework for acceleratng multmeda communcaton smulatons Orgnal Ctaton: D. Angel, E. Masala (2012). A cost-effectve
More informationLaddered Multilevel DC/AC Inverters used in Solar Panel Energy Systems
Proceedngs of the nd Internatonal Conference on Computer Scence and Electroncs Engneerng (ICCSEE 03) Laddered Multlevel DC/AC Inverters used n Solar Panel Energy Systems Fang Ln Luo, Senor Member IEEE
More information+ + + - - This circuit than can be reduced to a planar circuit
MeshCurrent Method The meshcurrent s analog of the nodeoltage method. We sole for a new set of arables, mesh currents, that automatcally satsfy KCLs. As such, meshcurrent method reduces crcut soluton to
More informationBatch Scheduling for a Single Deteriorating Machine to Minimize Total Actual Flow Time
Proceedngs of the 2014 Internatonal Conference on Industral Engneerng and Operatons Management Bal, Indonesa, January 7 9, 2014 Batch Schedulng for a Sngle Deteroratng Machne to Mnmze Total Actual Flow
More informationAn Interest-Oriented Network Evolution Mechanism for Online Communities
An Interest-Orented Network Evoluton Mechansm for Onlne Communtes Cahong Sun and Xaopng Yang School of Informaton, Renmn Unversty of Chna, Bejng 100872, P.R. Chna {chsun,yang}@ruc.edu.cn Abstract. Onlne
More informationRing structure of splines on triangulations
www.oeaw.ac.at Rng structure of splnes on trangulatons N. Vllamzar RICAM-Report 2014-48 www.rcam.oeaw.ac.at RING STRUCTURE OF SPLINES ON TRIANGULATIONS NELLY VILLAMIZAR Introducton For a trangulated regon
More informationAn ILP Formulation for Task Mapping and Scheduling on Multi-core Architectures
An ILP Formulaton for Task Mappng and Schedulng on Mult-core Archtectures Yng Y, We Han, Xn Zhao, Ahmet T. Erdogan and Tughrul Arslan Unversty of Ednburgh, The Kng's Buldngs, Mayfeld Road, Ednburgh, EH9
More information"Research Note" APPLICATION OF CHARGE SIMULATION METHOD TO ELECTRIC FIELD CALCULATION IN THE POWER CABLES *
Iranan Journal of Scence & Technology, Transacton B, Engneerng, ol. 30, No. B6, 789-794 rnted n The Islamc Republc of Iran, 006 Shraz Unversty "Research Note" ALICATION OF CHARGE SIMULATION METHOD TO ELECTRIC
More informationA Performance Analysis of View Maintenance Techniques for Data Warehouses
A Performance Analyss of Vew Mantenance Technques for Data Warehouses Xng Wang Dell Computer Corporaton Round Roc, Texas Le Gruenwald The nversty of Olahoma School of Computer Scence orman, OK 739 Guangtao
More informationForecasting the Direction and Strength of Stock Market Movement
Forecastng the Drecton and Strength of Stock Market Movement Jngwe Chen Mng Chen Nan Ye cjngwe@stanford.edu mchen5@stanford.edu nanye@stanford.edu Abstract - Stock market s one of the most complcated systems
More informationInvoicing and Financial Forecasting of Time and Amount of Corresponding Cash Inflow
Dragan Smć Svetlana Smć Vasa Svrčevć Invocng and Fnancal Forecastng of Tme and Amount of Correspondng Cash Inflow Artcle Info:, Vol. 6 (2011), No. 3, pp. 014-021 Receved 13 Janyary 2011 Accepted 20 Aprl
More information8 Algorithm for Binary Searching in Trees
8 Algorthm for Bnary Searchng n Trees In ths secton we present our algorthm for bnary searchng n trees. A crucal observaton employed by the algorthm s that ths problem can be effcently solved when the
More informationSurvey on Virtual Machine Placement Techniques in Cloud Computing Environment
Survey on Vrtual Machne Placement Technques n Cloud Computng Envronment Rajeev Kumar Gupta and R. K. Paterya Department of Computer Scence & Engneerng, MANIT, Bhopal, Inda ABSTRACT In tradtonal data center
More informationA Multi-Camera System on PC-Cluster for Real-time 3-D Tracking
The 23 rd Conference of the Mechancal Engneerng Network of Thaland November 4 7, 2009, Chang Ma A Mult-Camera System on PC-Cluster for Real-tme 3-D Trackng Vboon Sangveraphunsr*, Krtsana Uttamang, and
More informationFeature selection for intrusion detection. Slobodan Petrović NISlab, Gjøvik University College
Feature selecton for ntruson detecton Slobodan Petrovć NISlab, Gjøvk Unversty College Contents The feature selecton problem Intruson detecton Traffc features relevant for IDS The CFS measure The mrmr measure
More informationLuby s Alg. for Maximal Independent Sets using Pairwise Independence
Lecture Notes for Randomzed Algorthms Luby s Alg. for Maxmal Independent Sets usng Parwse Independence Last Updated by Erc Vgoda on February, 006 8. Maxmal Independent Sets For a graph G = (V, E), an ndependent
More informationJoint Scheduling of Processing and Shuffle Phases in MapReduce Systems
Jont Schedulng of Processng and Shuffle Phases n MapReduce Systems Fangfe Chen, Mural Kodalam, T. V. Lakshman Department of Computer Scence and Engneerng, The Penn State Unversty Bell Laboratores, Alcatel-Lucent
More informationA Programming Model for the Cloud Platform
Internatonal Journal of Advanced Scence and Technology A Programmng Model for the Cloud Platform Xaodong Lu School of Computer Engneerng and Scence Shangha Unversty, Shangha 200072, Chna luxaodongxht@qq.com
More informationIWFMS: An Internal Workflow Management System/Optimizer for Hadoop
IWFMS: An Internal Workflow Management System/Optmzer for Hadoop Lan Lu, Yao Shen Department of Computer Scence and Engneerng Shangha JaoTong Unversty Shangha, Chna lustrve@gmal.com, yshen@cs.sjtu.edu.cn
More informationDocument Clustering Analysis Based on Hybrid PSO+K-means Algorithm
Document Clusterng Analyss Based on Hybrd PSO+K-means Algorthm Xaohu Cu, Thomas E. Potok Appled Software Engneerng Research Group, Computatonal Scences and Engneerng Dvson, Oak Rdge Natonal Laboratory,
More informationAutomated Mobile ph Reader on a Camera Phone
Automated Moble ph Reader on a Camera Phone B.Y. Loh, N.K. Vuong, S. Chan and C.. Lau AbstractA robust classfcaton algorthm that apples color scence and mage processng technques s developed to automatcally
More informationAn Energy-Efficient Data Placement Algorithm and Node Scheduling Strategies in Cloud Computing Systems
2nd Internatonal Conference on Advances n Computer Scence and Engneerng (CSE 2013) An Energy-Effcent Data Placement Algorthm and Node Schedulng Strateges n Cloud Computng Systems Yanwen Xao Massve Data
More information8.5 UNITARY AND HERMITIAN MATRICES. The conjugate transpose of a complex matrix A, denoted by A*, is given by
6 CHAPTER 8 COMPLEX VECTOR SPACES 5. Fnd the kernel of the lnear transformaton gven n Exercse 5. In Exercses 55 and 56, fnd the mage of v, for the ndcated composton, where and are gven by the followng
More informationLITERATURE REVIEW: VARIOUS PRIORITY BASED TASK SCHEDULING ALGORITHMS IN CLOUD COMPUTING
LITERATURE REVIEW: VARIOUS PRIORITY BASED TASK SCHEDULING ALGORITHMS IN CLOUD COMPUTING 1 MS. POOJA.P.VASANI, 2 MR. NISHANT.S. SANGHANI 1 M.Tech. [Software Systems] Student, Patel College of Scence and
More informationA Fast Incremental Spectral Clustering for Large Data Sets
2011 12th Internatonal Conference on Parallel and Dstrbuted Computng, Applcatons and Technologes A Fast Incremental Spectral Clusterng for Large Data Sets Tengteng Kong 1,YeTan 1, Hong Shen 1,2 1 School
More informationLinear Circuits Analysis. Superposition, Thevenin /Norton Equivalent circuits
Lnear Crcuts Analyss. Superposton, Theenn /Norton Equalent crcuts So far we hae explored tmendependent (resste) elements that are also lnear. A tmendependent elements s one for whch we can plot an / cure.
More informationA Prefix Code Matching Parallel Load-Balancing Method for Solution-Adaptive Unstructured Finite Element Graphs on Distributed Memory Multicomputers
Ž. The Journal of Supercomputng, 15, 25 49 2000 2000 Kluwer Academc Publshers. Manufactured n The Netherlands. A Prefx Code Matchng Parallel Load-Balancng Method for Soluton-Adaptve Unstructured Fnte Element
More informationSTANDING WAVE TUBE TECHNIQUES FOR MEASURING THE NORMAL INCIDENCE ABSORPTION COEFFICIENT: COMPARISON OF DIFFERENT EXPERIMENTAL SETUPS.
STADIG WAVE TUBE TECHIQUES FOR MEASURIG THE ORMAL ICIDECE ABSORPTIO COEFFICIET: COMPARISO OF DIFFERET EXPERIMETAL SETUPS. Angelo Farna (*), Patrzo Faust (**) (*) Dpart. d Ing. Industrale, Unverstà d Parma,
More informationThe University of Texas at Austin. Austin, Texas 78712. December 1987. Abstract. programs in which operations of dierent processes mayoverlap.
Atomc Semantcs of Nonatomc Programs James H. Anderson Mohamed G. Gouda Department of Computer Scences The Unversty of Texas at Austn Austn, Texas 78712 December 1987 Abstract We argue that t s possble,
More informationNetwork Aware Load-Balancing via Parallel VM Migration for Data Centers
Network Aware Load-Balancng va Parallel VM Mgraton for Data Centers Kun-Tng Chen 2, Chen Chen 12, Po-Hsang Wang 2 1 Informaton Technology Servce Center, 2 Department of Computer Scence Natonal Chao Tung
More informationCHOLESTEROL REFERENCE METHOD LABORATORY NETWORK. Sample Stability Protocol
CHOLESTEROL REFERENCE METHOD LABORATORY NETWORK Sample Stablty Protocol Background The Cholesterol Reference Method Laboratory Network (CRMLN) developed certfcaton protocols for total cholesterol, HDL
More informationA New Task Scheduling Algorithm Based on Improved Genetic Algorithm
A New Task Schedulng Algorthm Based on Improved Genetc Algorthm n Cloud Computng Envronment Congcong Xong, Long Feng, Lxan Chen A New Task Schedulng Algorthm Based on Improved Genetc Algorthm n Cloud Computng
More informationConferencing protocols and Petri net analysis
Conferencng protocols and Petr net analyss E. ANTONIDAKIS Department of Electroncs, Technologcal Educatonal Insttute of Crete, GREECE ena@chana.tecrete.gr Abstract: Durng a computer conference, users desre
More informationStatistical Approach for Offline Handwritten Signature Verification
Journal of Computer Scence 4 (3): 181-185, 2008 ISSN 1549-3636 2008 Scence Publcatons Statstcal Approach for Offlne Handwrtten Sgnature Verfcaton 2 Debnath Bhattacharyya, 1 Samr Kumar Bandyopadhyay, 2
More informationConversion between the vector and raster data structures using Fuzzy Geographical Entities
Converson between the vector and raster data structures usng Fuzzy Geographcal Enttes Cdála Fonte Department of Mathematcs Faculty of Scences and Technology Unversty of Combra, Apartado 38, 3 454 Combra,
More informationAn MILP model for planning of batch plants operating in a campaign-mode
An MILP model for plannng of batch plants operatng n a campagn-mode Yanna Fumero Insttuto de Desarrollo y Dseño CONICET UTN yfumero@santafe-concet.gov.ar Gabrela Corsano Insttuto de Desarrollo y Dseño
More informationFast degree elevation and knot insertion for B-spline curves
Computer Aded Geometrc Desgn 22 (2005) 183 197 www.elsever.com/locate/cagd Fast degree elevaton and knot nserton for B-splne curves Q-Xng Huang a,sh-mnhu a,, Ralph R. Martn b a Department of Computer Scence
More informationVehicle Routing Problem with Time Windows for Reducing Fuel Consumption
3020 JOURNAL OF COMPUTERS, VOL. 7, NO. 12, DECEMBER 2012 Vehcle Routng Problem wth Tme Wndows for Reducng Fuel Consumpton Jn L School of Computer and Informaton Engneerng, Zhejang Gongshang Unversty, Hangzhou,
More informationA Cost-Effective Strategy for Intermediate Data Storage in Scientific Cloud Workflow Systems
A Cost-Effectve Strategy for Intermedate Data Storage n Scentfc Cloud Workflow Systems Dong Yuan, Yun Yang, Xao Lu, Jnjun Chen Faculty of Informaton and Communcaton Technologes, Swnburne Unversty of Technology
More informationLoop Parallelization
- - Loop Parallelzaton C-52 Complaton steps: nested loops operatng on arrays, sequentell executon of teraton space DECLARE B[..,..+] FOR I :=.. FOR J :=.. I B[I,J] := B[I-,J]+B[I-,J-] ED FOR ED FOR analyze
More informationPricing Model of Cloud Computing Service with Partial Multihoming
Prcng Model of Cloud Computng Servce wth Partal Multhomng Zhang Ru 1 Tang Bng-yong 1 1.Glorous Sun School of Busness and Managment Donghua Unversty Shangha 251 Chna E-mal:ru528369@mal.dhu.edu.cn Abstract
More informationFREQUENCY OF OCCURRENCE OF CERTAIN CHEMICAL CLASSES OF GSR FROM VARIOUS AMMUNITION TYPES
FREQUENCY OF OCCURRENCE OF CERTAIN CHEMICAL CLASSES OF GSR FROM VARIOUS AMMUNITION TYPES Zuzanna BRO EK-MUCHA, Grzegorz ZADORA, 2 Insttute of Forensc Research, Cracow, Poland 2 Faculty of Chemstry, Jagellonan
More informationForecasting the Demand of Emergency Supplies: Based on the CBR Theory and BP Neural Network
700 Proceedngs of the 8th Internatonal Conference on Innovaton & Management Forecastng the Demand of Emergency Supples: Based on the CBR Theory and BP Neural Network Fu Deqang, Lu Yun, L Changbng School
More informationSingle and multiple stage classifiers implementing logistic discrimination
Sngle and multple stage classfers mplementng logstc dscrmnaton Hélo Radke Bttencourt 1 Dens Alter de Olvera Moraes 2 Vctor Haertel 2 1 Pontfíca Unversdade Católca do Ro Grande do Sul - PUCRS Av. Ipranga,
More informationTexas Instruments 30X IIS Calculator
Texas Instruments 30X IIS Calculator Keystrokes for the TI-30X IIS are shown for a few topcs n whch keystrokes are unque. Start by readng the Quk Start secton. Then, before begnnng a specfc unt of the
More information1. Fundamentals of probability theory 2. Emergence of communication traffic 3. Stochastic & Markovian Processes (SP & MP)
6.3 / -- Communcaton Networks II (Görg) SS20 -- www.comnets.un-bremen.de Communcaton Networks II Contents. Fundamentals of probablty theory 2. Emergence of communcaton traffc 3. Stochastc & Markovan Processes
More informationA Novel Scalable Architecture of Cloud Storage System for Small Files based on P2P
2012 IEEE Internatonal Conference on Cluster Computng Workshops A Novel Scalable Archtecture of Cloud Storage System for Small Fles based on P2P ZHANG Q-fe, PAN Xue-zeng, SHEN Yan College of Computer Scence
More informationPower Low Modified Dual Priority in Hard Real Time Systems with Resource Requirements
Power Low Modfed Dual Prorty n Hard Real Tme Systems wth Resource Requrements M.Angels Moncusí, Alex Arenas {amoncus,aarenas}@etse.urv.es Dpt d'engnyera Informàtca Matemàtques Unverstat Rovra Vrgl Campus
More informationResearch Article A Time Scheduling Model of Logistics Service Supply Chain with Mass Customized Logistics Service
Hndaw Publshng Corporaton Dscrete Dynamcs n Nature and Socety Volume 01, Artcle ID 48978, 18 pages do:10.1155/01/48978 Research Artcle A Tme Schedulng Model of Logstcs Servce Supply Chan wth Mass Customzed
More informationEnergy Efficient Routing in Ad Hoc Disaster Recovery Networks
Energy Effcent Routng n Ad Hoc Dsaster Recovery Networks Gl Zussman and Adran Segall Department of Electrcal Engneerng Technon Israel Insttute of Technology Hafa 32000, Israel {glz@tx, segall@ee}.technon.ac.l
More informationLogistic Regression. Lecture 4: More classifiers and classes. Logistic regression. Adaboost. Optimization. Multiple class classification
Lecture 4: More classfers and classes C4B Machne Learnng Hlary 20 A. Zsserman Logstc regresson Loss functons revsted Adaboost Loss functons revsted Optmzaton Multple class classfcaton Logstc Regresson
More informationSIMPLIFYING NDA PROGRAMMING WITH PROt SQL
SIMPLIFYING NDA PROGRAMMING WITH PROt SQL Aeen L. Yam, Besseaar Assocates, Prnceton, NJ ABSRACf The programmng of New Drug Appcaton (NDA) Integrated Summary of Safety (ISS) usuay nvoves obtanng patent
More informationAll Roads Lead to Rome: Optimistic Recovery for Distributed Iterative Data Processing
All Roads Lead to Rome: Optmstc Recovery for Dstrbuted Iteratve Data Processng Sebastan Schelter Stephan Ewen Kostas Tzoumas Volker Markl Technsche Unverstät Berln, Germany frstname.lastname@tu-berln.de
More informationOpen Access A Load Balancing Strategy with Bandwidth Constraint in Cloud Computing. Jing Deng 1,*, Ping Guo 2, Qi Li 3, Haizhu Chen 1
Send Orders for Reprnts to reprnts@benthamscence.ae The Open Cybernetcs & Systemcs Journal, 2014, 8, 115-121 115 Open Access A Load Balancng Strategy wth Bandwdth Constrant n Cloud Computng Jng Deng 1,*,
More informationThe Effect of Mean Stress on Damage Predictions for Spectral Loading of Fiberglass Composite Coupons 1
EWEA, Specal Topc Conference 24: The Scence of Makng Torque from the Wnd, Delft, Aprl 9-2, 24, pp. 546-555. The Effect of Mean Stress on Damage Predctons for Spectral Loadng of Fberglass Composte Coupons
More informationInstitute of Informatics, Faculty of Business and Management, Brno University of Technology,Czech Republic
Lagrange Multplers as Quanttatve Indcators n Economcs Ivan Mezník Insttute of Informatcs, Faculty of Busness and Management, Brno Unversty of TechnologCzech Republc Abstract The quanttatve role of Lagrange
More informationHALL EFFECT SENSORS AND COMMUTATION
OEM770 5 Hall Effect ensors H P T E R 5 Hall Effect ensors The OEM770 works wth three-phase brushless motors equpped wth Hall effect sensors or equvalent feedback sgnals. In ths chapter we wll explan how
More informationDocument image template matching based on component block list
Pattern Recognton Letters 22 2001) 1033±1042 www.elsever.nl/locate/patrec Document mage template matchng based on component block lst Hanchuan Peng a,b,c, *, Fuhu Long b, Zheru Ch b, Wan-Ch Su b a Department
More informationEfficient Bandwidth Management in Broadband Wireless Access Systems Using CAC-based Dynamic Pricing
Effcent Bandwdth Management n Broadband Wreless Access Systems Usng CAC-based Dynamc Prcng Bader Al-Manthar, Ndal Nasser 2, Najah Abu Al 3, Hossam Hassanen Telecommuncatons Research Laboratory School of
More informationPRACTICE 1: MUTUAL FUNDS EVALUATION USING MATLAB.
PRACTICE 1: MUTUAL FUNDS EVALUATION USING MATLAB. INDEX 1. Load data usng the Edtor wndow and m-fle 2. Learnng to save results from the Edtor wndow. 3. Computng the Sharpe Rato 4. Obtanng the Treynor Rato
More informationWISE-Integrator: An Automatic Integrator of Web Search Interfaces for E-Commerce
WSE-ntegrator: An Automatc ntegrator of Web Search nterfaces for E-Commerce Ha He, Wey Meng Dept. of Computer Scence SUNY at Bnghamton Bnghamton, NY 13902 {hahe,meng}@cs.bnghamton.edu Clement Yu Dept.
More information320 The Internatonal Arab Journal of Informaton Technology, Vol. 5, No. 3, July 2008 Comparsons Between Data Clusterng Algorthms Osama Abu Abbas Computer Scence Department, Yarmouk Unversty, Jordan Abstract:
More informationOptimal Choice of Random Variables in D-ITG Traffic Generating Tool using Evolutionary Algorithms
Optmal Choce of Random Varables n D-ITG Traffc Generatng Tool usng Evolutonary Algorthms M. R. Mosav* (C.A.), F. Farab* and S. Karam* Abstract: Impressve development of computer networks has been requred
More informationJoint Optimization of Bid and Budget Allocation in Sponsored Search
Jont Optmzaton of Bd and Budget Allocaton n Sponsored Search Wenan Zhang Shangha Jao Tong Unversty Shangha, 224, P. R. Chna wnzhang@apex.sjtu.edu.cn Yong Yu Shangha Jao Tong Unversty Shangha, 224, P. R.
More informationUpdating the E5810B firmware
Updatng the E5810B frmware NOTE Do not update your E5810B frmware unless you have a specfc need to do so, such as defect repar or nstrument enhancements. If the frmware update fals, the E5810B wll revert
More informationDescriptive Models. Cluster Analysis. Example. General Applications of Clustering. Examples of Clustering Applications
CMSC828G Prncples of Data Mnng Lecture #9 Today s Readng: HMS, chapter 9 Today s Lecture: Descrptve Modelng Clusterng Algorthms Descrptve Models model presents the man features of the data, a global summary
More informationMATHEMATICAL ENGINEERING TECHNICAL REPORTS. Sequential Optimizing Investing Strategy with Neural Networks
MATHEMATICAL ENGINEERING TECHNICAL REPORTS Sequental Optmzng Investng Strategy wth Neural Networks Ryo ADACHI and Akmch TAKEMURA METR 2010 03 February 2010 DEPARTMENT OF MATHEMATICAL INFORMATICS GRADUATE
More informationTIGER:Thermal-Aware File Assignment in Storage Clusters
TIGER:Thermal-Aware Fle Assgnment n Storage Clusters Ajt Chavan, Xunfe Jang, Mohemmad I. Alghamd, Xao Qn,Mnghua Jang, and Jfu Zhang Department of Computer Scence and Software Engneerng, Auburn Unversty,
More informationResource Scheduling in Desktop Grid by Grid-JQA
The 3rd Internatonal Conference on Grd and Pervasve Computng - Worshops esource Schedulng n Destop Grd by Grd-JQA L. Mohammad Khanl M. Analou Assstant professor Assstant professor C.S. Dept.Tabrz Unversty
More informationINVESTIGATION OF VEHICULAR USERS FAIRNESS IN CDMA-HDR NETWORKS
21 22 September 2007, BULGARIA 119 Proceedngs of the Internatonal Conference on Informaton Technologes (InfoTech-2007) 21 st 22 nd September 2007, Bulgara vol. 2 INVESTIGATION OF VEHICULAR USERS FAIRNESS
More informationTraffic State Estimation in the Traffic Management Center of Berlin
Traffc State Estmaton n the Traffc Management Center of Berln Authors: Peter Vortsch, PTV AG, Stumpfstrasse, D-763 Karlsruhe, Germany phone ++49/72/965/35, emal peter.vortsch@ptv.de Peter Möhl, PTV AG,
More information