Fast Computation of Shortest Path for Visiting Segments in the Plane
|
|
- Blanche Thornton
- 6 years ago
- Views:
Transcription
1 Send Orders for Reprnts to 4 The Open Cybernetcs & Systemcs Journal, 04, 8, 4-9 Open Access Fast Computaton of Shortest Path for Vstng Segments n the Plane Ljuan Wang,, Bo Jang *, Ansheng Deng and Q We College of Informaton Scence and Technology, Dalan Martme Unversty, Dalan, Chna, 606; Department of Informaton and Scence, Dalan Insttute of Scence and Technology, Dalan, Chna, 605 Abstract: Let s and t be two ponts n the plane, how to compute the Eucldean shortest path between s and t whch vsts a sequence of segments gven n the plane the problem to be dscussed n ths paper, especally, the stuaton of the adjacent segments ntersect s the focus of our study. In ths paper, we frst analyze the degeneraton applyng rubber-band algorthm to solve the problem and ntroduce the algorthm for computng Eucldean shortest path wth removng suffcently small segments. Then based on rubber-band algorthm, we present a new algorthm for solvng the degeneraton and computng the ESP by crossng over two segments to deal wth ntersecton and n our algorthm the adjacent segments order can be changed when they ntersect. Furthermore, we have mplemented the two algorthms and have appled a large test data to test them. The experments demonstrate that our algorthm s more effcent and effectve, and t has the same tme complexty as the rubber-band algorthm. Keywords: Eucldean shortest path, degeneraton, rubber-band algorthm, test data.. INTRODUCTION Eucldean shortest path (ESP) problem s one of the typcal problems n Computatonal Geometry. Its man am s to fnd the shortest path between two ponts for a gven seres of obstacles n Eucldean space []. In ths paper, we manly study the algorthms for computng the Eucldean shortest path between two ponts s and t of vstng a sequence of segments gven n the plane. Especally, the stuaton of the adjacent segments ntersecton s the focus of our study, but when three or more lne segments ntersect at one pont then t s not the scope of ths paper. The problem can be descrbed as follows. Let be a plane. Assume that there are n> segments s such that s sj sk =, for j k and,j,k =,,,n, see Fg. (), then how to compute the shortest path from s to t that vsts all the gven segments s (at least once) s our study, here, the vstng order needn t to be n the gven order. In Fg. (), the path lnked by dotted lnes s the ESP from s to t whch vsts 4 gven segments, and the vstng order s s 3 4. The ESP problem of vstng a sequence of segments has been ntensvely studed. When the gven segments don t ntersectuch as Funnel algorthm [] proposed by D. T. Lee and F. P. Preparata n 984, and rubber-band algorthm [3, 4] (denoted by R algorthm) proposed by Faje L and Renhard Kettle n 007. R algorthm has the K( ) O(n) tme, where K( )=(L 0 -L)/, L s the true length of the ESP of segment set S, L 0 that of an ntal path, and n s the 874-0X/4 Fg. ( ESP of vstng segments n the plane, for n=4. number of segments of the set S. In 0, Wang and Huo obtaned that the tme complexty of R algorthm s O(n ) when n s larger (.e.,n 500) by the experment. Furthermore, they ntroduced dvde and conquer nto R algorthm and reduced the tme complexty to O(n) [5]. When the gven segment may ntersect, many researchers have been studyng more effectve methods. LI Fa-je and KLETTE Renhard n 008 got an approxmaton soluton by removng suffcently small segments wthn an applcaton of R algorthm [4]. So far, no other effectve method has been reported yet. In ths paper, based on R algorthm, we present a new algorthm for computng the ESP of gven segments by the method of crossng over two segments to deal wth the ntersecton and n our algorthm the adjacent segments order can be changed n order to get the shorter path when they ntersect. The experments show that our algorthm s effcent and accurate for solvng the problem gven above.. THE DEGENERATION APPLYING ALGORITHM TO COMPUTE THE ESP The basc dea of R algorthm s that t computes the shortest path by local optmzaton and contnuous teraton. 04 Bentham Open
2 Fast Computaton of Shortest Path for Vstng Segments n the Plane The Open Cybernetcs & Systemcs Journal, 04, Volume 8 5 Except start pont and end pont, all the path ponts from the frst pont wll be updated one by one by each teraton. The algorthm wll not stop untl the total length of the path between two teratons only dffers by (the chosen accuracy) at most [3, 4]. In R algorthm, the teraton s computed accordng to the gven order of the segments. When any two segments of the segment set S don t ntersect, we can apply R algorthm to compute the ESP between two ponts s and t of vstng a sequence of segments n the gven order easly [3-5], but when they ntersect, t may be hard and even ncorrect to get the shortest path. Takng the Fg. () for example, f the calculated path ponts q on s and q + on s + are at the ntersecton of s and s + n current teraton, t s mpossble to compute new q' and q' + ( q q ', q q ' + + ) that makes q - q' q' + q + shorter than q - q q + q + n the later teraton processes. Because q and q + are both at the crossng of s and s +, the path ponts q and q + do not change n the later teraton process, obvously q - q q + q + sn't the optmal, except q -, q, q +, q + are on the same lne. We call the stuaton n ths example as a degeneraton path of the algorthm [3-5]. When the degeneraton appears, applyng R algorthm wll lead to falure. When the segments ntersect, assume that the segments s and s + ntersect at the pont C - and p + are the path ponts on s - and s + respectvely. Then, there are some cases among the ponts p - and p + and the segments s and s +, whch are as follows. Case p - and p + le on the dfferent sde of s and s + In ths case, the approach n the teraton process s as follows. If p passes through both s + and s +, obvously, p + s the local shortest path, denoted by, = p +, and the vstng order s the order of passng through s and s + ee Fg. (3 Otherwse, for Fg. (3a), there are many cases whch can be seen n Fg. (4 Accordng to R algorthm, we can choose one of the endponts of s as p or one of the endponts of s + as p + such that the local path s the shortest, and the vstng order s the same as above. Smlarly, for Fg. (3b), t can be done as Fg. (3a Snce there are other possble poston relatonshps between s and s +, (.e., they are vertcal), whch also can be done n a smlar way. In addton, n the flowng case and case 3, the method of dealng wth the endponts s the same as that of Fg. (3a (a) Fg. ( The degeneraton wth an applcaton of R algorthm. Removng suffcently small segments from segment s or s + at the ntersecton can avod the degeneraton [4]. Based on ths dea, n reference [6], the mproved R algorthm, denoted by A presented. The degeneraton can be avoded by applyng A when the adjacent segments ntersect, but the shortest path obtaned s only an approxmate because t s possble that the path through the ntersecton of the segments s the shortest. In ths paper, based on R algorthm, we propose the method of crossng over two segments to compute path ponts by analyzng the poston relatonshp between path ponts and segments, and we can change the order of the adjacent segments n order to get the shorter path when they ntersect. The method not only can solve the degeneraton effectvely but also t s more effcent and accurate than A. The experments show that our algorthm s correct and effectve. 3. THE METHOD OF DEALING WITH THE INTER- SECTED SEGMENTS When the segments do not ntersect, references [3-5] has presented the solvng method. (b) Fg. (3 p + passes through both s and s +. Case p - and p + le on the dfferent sde of s (s + ) and on the same sde of s + (s ) In ths case, t needs to compute the reflecton pont r on the lne segment s or s + to fnd the shortest path [7, 8]ee Fg. (5 The approach n the teratve process s as follows. If p p + only ntersects wth one of segments s and s +, the reflecton pont r les on the segment whch does not ntersect wth p, = + p r + rp +, and the vstng order s the order of passng through s and s +.
3 6 The Open Cybernetcs & Systemcs Journal, 04, Volume 8 Wang et al. (a) (b) (a) The reflecton pont les on s (c) (d) Fg. (4 p + does not ntersect wth s or s +. (a) The reflecton pont les on s (b) The reflecton pont les on s + Fg. (5 p - and p + le on the dfferent sde of s (s + ) and on the same sde of s + (s Case 3 p - and p + le on the same sde of s and s + In ths case, there are two cases whch are shown n Fgs. (6) and (7 () the case of computng one reflecton The two segments can be vsted by computng a reflecton pont (see Fg. 6 In ths case, obvously, = p r + rp +. It s worth notng that when passes through s or s + twce, we can select the nearest ntersecton to C as the p or p + n order to deal wth endponts easly. (b) The reflecton pont les on s + Fg. (6 p - and p + le on the same sde of s and s + (One reflecton pont () the case of computng two reflectons It needs to compute two reflectons when the two segments can t be vsted by computng a reflecton pont. The approach s as follows. We make the symmetrc pont of p - on s and the symmetrc pont of p + on s +, denoted by - and + respectvely. In ths case, there are three stuatons when computng the local shortest path (see Fg. 7 f ntersects wth s + and s + at the pont p and p + respectvely, and p and p + are on the same sde of p - and p +, they are the two reflectons and also the path ponts. If p p does not ntersect wth p, the shortest path s = p + + p + pp + + p, and the vstng + + order s the order of passng through s and s + (see Fg. (7a Otherwse, we need to change the vstng order of s and s + n order to get the shortest path, then = p + + p p + + pp + (see Fg. (7b f passes through the ntersecton C, n ths + case, the reflecton ponts concde wth C and they are also the path ponts (p =p + =C), = p C+ Cp +, and the vstng order s the order of passng through s and s +. It easly can be proved by makng two auxlary ponts and + on s and s + (see Fg. (7c f doesn t pass through the ntersecton C + and s dfferent from the sde of + p C and Cp +, = p C+ Cp +, the path ponts p and p + concde wth C, and the vstng order s the order of passng through s
4 Fast Computaton of Shortest Path for Vstng Segments n the Plane and s+ (see Fg. 7d Ths can be proved as follows. In Fg. (7d), we take two ponts and + on s and s+nce p ' p ' + p ' p ' + + p ' + p ' + = p p ' + p ' p ' + + p ' + p + ' C + Cp ' + = p C + Cp +, obvously ' C + Cp ' + < p ' p ' + p ' p ' + + p ' + p ' +, then p C + Cp + < p p ' + p ' p ' + + p ' + p +, = p C + Cp + follows. (a) The Open Cybernetcs & Systemcs Journal, 04, Volume NEW ALGORITHM In ths paper, we adopt the method of crossng over two segments when two segments ntersect. The basc dea s as follows. Assume that s nterests wth s+, we can compute the path pont p on s and the path pont p+ on s+ accordng to the poston relatonshp between the path ponts p- and p+ and the segments s and s+. Next, we judge the poston relatonshp of s+ and s+,, f s + s + =, we compute the path pont p+ on s+ and p+3 on s+3. Otherwse, we compute the path pont p+ on s+ and p+ on s+. The new algorthm s denoted by A, whch conssts of Man procedure, Update procedure, ESPByOne procedure and ESPByTwo procedure. Man procedure s developed based on R algorthm whch s used to calculate the teraton process, Update procedure s used to compute the path ponts n each teraton, ESPByOne s the procedure of crossng over one segment to compute the path ponts, the detal has been presented n reference [7], ESPByTwo s the procedure of crossng two segments to compute the path ponts, whch s the core of ths paper. ESPByTwo procedure can be descrbed as follows. ESPByTwo( p + + ) procedure. Here and s + are two segments and p + are two path ponts on s and s +. The procedure s used to compute the new path ponts p and p + on s and s +. (b) Let s = p p +, L denote the path computed by ESPByOne procedure, and c s the ntersecton of s wth s +. Case p- and p+ le on the dfferent sde of s and s+ f ( s s && s + s ), assume that r and r are the ntersectons of s wth s, and s + wth s respectvely, then let p = r and p + = r, and f ( p r > p r ) then call swap ( s + ) and call swap( p + (c) Case p- and p+ le on the dfferent sde of s (s+) and on the same sde of s+( s) f ( s s s + s ) f ( s s ) then call ESPByOne( p + + ), assume that r and r are the ntersectons of L wth s, and L wth s + respectvely. Let p = r + = r and stemp = r p +, f ( s stemp ) then call swap ( s + ),and call swap ( p + else ESPByOne( p + ), assume that r and r are (d) Fg. (7 p- and p+ le on the same sde of s and s+ (Two reflecton ponts the ntersectons of L wth s, and L wth s + respectvely. Let p = r + = r and stemp = p r.
5 8 The Open Cybernetcs & Systemcs Journal, 04, Volume 8 Wang et al. Table. The Results of 0 Segments Sets by A and A. Segment Sets A Algorthm A Algorthm Iteraton Tmes ESP Iteraton Tmes ESP f ( s + stemp ) then call swap ( s ), and call swap ( p Case 3 p - and p + le on the same sde of s and s + ESPByOne( p + ), let r denotes the ntersecton of L wth s and stemp = p r. f ( s + stemp ), and r s the ntersecton, then let p = r = + r, call swap ( s ) and call swap ( p else ESPByOne( p + ), let r denotes the ntersecton of L wth s, and stemp = p + r. p ( f ( s stemp ), and r s the ntersecton, then let = r = + r, call swap ( s ) and call swap p + p, else we make the symmetrc pont of p - on s and that of p + on s, denoted by - and + respectvely, let stemp = p ' p ' +, r and r denote the ntersecton s wth stemp, and s wth stemp. f ( p and c le on the same sde of stemp ) then let p = p = c. + else let p = r, and p = + r. f ( p r p p call swap ( p + + ) then call swap ( s ) and 5. THE ANALYSIS OF RUNNING RESULT We have mplemented A and A wth C++ program and have appled 0 randomly generated segment sets to test the algorthms, and the sze of segments s 00, 00,,000 respectvely. The experment s results show that our algorthm s correct and effcent, whch can be shown n Table. From the Table, we can see that the ESP of A s shorter than that of A and the teraton tmes of A s less than that of A. Fg. (8 The runnng result of 0 segments of A and A. To make the result clearly vsble, we only present the result of 0 segments (see Fg. 8 The sold lnes are randomly generated segments, the path lnked by the thndotted-lnes from S to T s the ESP obtaned by the A and the path lnked by the thck-dotted-lnes from S to T s the ESP obtaned by the A. It s obvous that the ESP obtaned by A s shorter than ESP obtaned by A. In ths example, s s the ntal gven order of segments. After runnng wth our algorthm, the output s s 4,s,s 3,s,s 6,s 5,s 7,s 9,s 8,s 0. We can see the vstng order has been changed and we can get the shorter path and the faster runnng tme. Furthermore, ths example contaned three poston relatonshps between path ponts and segments ds-
6 Fast Computaton of Shortest Path for Vstng Segments n the Plane The Open Cybernetcs & Systemcs Journal, 04, Volume 8 9 cussed above, for example, (p 3 6 ), (p ) and (p 9,s 8,s 0,T) are the case, case and case3 respectvely. 6. CONCLUSION In ths paper, based on R algorthm, we present a new algorthm for computng the Eucldean shortest path of vstng a sequence of segments gven n the plane. When the adjacent segments ntersect, applyng the method of crossng over two segments to deal wth the ntersecton can effectvely solve the degeneraton caused by R algorthm. Furthermore, our algorthm can effcently and accurately compute the ESP of gven segments. Snce dealng wth degeneraton has not ncreased the tme complexty of R algorthm, t has the same tme complexty as R algorthm. Ths research has made prelmnary results, the stuaton of three or three more lne segments ntersect at one pont s an open problem [9]. CONFLICT OF INTEREST The authors confrm that ths artcle content has no conflct of nterest. ACKNOWLEDGEMENTS Ths work s supported by the Natonal Natural Scence Foundaton of Chna (No , 677) and the General Project of Lao Nng Provnce Scence and Research (No. L0487 REFERENCES [] M. de Berg, O. Cheong, M. van Kreveld, M. Overmars, Computatonal Geometry: Algorths and Applcatons (3 rd Edton), Sprnger-Verlag Publshers: Berln, 009p. 0-. [] D. T. Lee and F. P. Preparata, Eucldean shortest paths n the presence of rectlnear barrers, Networks, vol. 4, no. 3p , September.984. [3] F. L and R. Klette, Exact and approxmate algorthms for the calculaton of shortest paths, IMA J. Manag. Mathem., vol. 7, no.p.34-38, 006. [4] F. L and R. Klette, Shortest path algorthms for sequences of polygons, CAAI Trans. Intell. Syst., vol. 3, no. p. 3-30, 008. [5] L. Wang, L. Huo, and D. He, An mproved algorthm for eucldean shortest paths of vstng lne segments n the plane, J. Conver. Inform. Tech., vol. 6, no. 6p. 9-5, 0. [6] L. Wang, B. Jang, Q. We, D. He, Research on the algorthm for eucldean shortest paths of vstng lne segments n the plane, ICIC Express Lett., vol. 8, no. 6p , 04. [7] X. Tan, Fast computaton of shortest watchman routes n smple polygon, Inform. Process. Lett., vol. 77, no. p. 7-33, 00. [8] A. Dumtrescu, J. S. B. Mtchell and P. yl sk, Watchman Route for Lne and segments, Algorthm. Theory SWAT 0 Lect. Notes Comp. Sc., vol.7357, no. 4p , May. 0. [9] M. Dror, A. Efrat, A. Lubw and J. S. B. Mtchell, Tourng a sequence of polygons, In Proc. 35th Annu. ACM Sympos. Theory Comput., Calforna, USA, 003p Receved: September, 04 Revsed: November 30, 04 Accepted: December 0, 04 Wang et al.; Lcensee Bentham Open. Ths s an open access artcle lcensed under the terms of the Creatve Commons Attrbuton Non-Commercal Lcense ( lcenses/by-nc/3.0/) whch permts unrestrcted, non-commercal use, dstrbuton and reproducton n any medumrovded the work s properly cted.
The Shortest Path of Touring Lines given in the Plane
Send Orders for Reprnts to reprnts@benthamscence.ae 262 The Open Cybernetcs & Systemcs Journal, 2015, 9, 262-267 The Shortest Path of Tourng Lnes gven n the Plane Open Access Ljuan Wang 1,2, Dandan He
More informationOpen Access A New Algorithm for the Shortest Path of Touring Disjoint Convex Polygons
Send Orders for Reprnts to reprnts@benthamscence.ae 1364 The Open Automaton and Control Systems Journal, 2015, 7, 1364-1368 Open Access A New Algorthm for the Shortest Path of Tourng Dsjont Convex Polygons
More informationResearch and Application of Fingerprint Recognition Based on MATLAB
Send Orders for Reprnts to reprnts@benthamscence.ae The Open Automaton and Control Systems Journal, 205, 7, 07-07 Open Access Research and Applcaton of Fngerprnt Recognton Based on MATLAB Nng Lu* Department
More informationAn Optimal Algorithm for Prufer Codes *
J. Software Engneerng & Applcatons, 2009, 2: 111-115 do:10.4236/jsea.2009.22016 Publshed Onlne July 2009 (www.scrp.org/journal/jsea) An Optmal Algorthm for Prufer Codes * Xaodong Wang 1, 2, Le Wang 3,
More informationParallelism for Nested Loops with Non-uniform and Flow Dependences
Parallelsm for Nested Loops wth Non-unform and Flow Dependences Sam-Jn Jeong Dept. of Informaton & Communcaton Engneerng, Cheonan Unversty, 5, Anseo-dong, Cheonan, Chungnam, 330-80, Korea. seong@cheonan.ac.kr
More informationRelated-Mode Attacks on CTR Encryption Mode
Internatonal Journal of Network Securty, Vol.4, No.3, PP.282 287, May 2007 282 Related-Mode Attacks on CTR Encrypton Mode Dayn Wang, Dongda Ln, and Wenlng Wu (Correspondng author: Dayn Wang) Key Laboratory
More informationQuality Improvement Algorithm for Tetrahedral Mesh Based on Optimal Delaunay Triangulation
Intellgent Informaton Management, 013, 5, 191-195 Publshed Onlne November 013 (http://www.scrp.org/journal/m) http://dx.do.org/10.36/m.013.5601 Qualty Improvement Algorthm for Tetrahedral Mesh Based on
More informationA Five-Point Subdivision Scheme with Two Parameters and a Four-Point Shape-Preserving Scheme
Mathematcal and Computatonal Applcatons Artcle A Fve-Pont Subdvson Scheme wth Two Parameters and a Four-Pont Shape-Preservng Scheme Jeqng Tan,2, Bo Wang, * and Jun Sh School of Mathematcs, Hefe Unversty
More informationModule Management Tool in Software Development Organizations
Journal of Computer Scence (5): 8-, 7 ISSN 59-66 7 Scence Publcatons Management Tool n Software Development Organzatons Ahmad A. Al-Rababah and Mohammad A. Al-Rababah Faculty of IT, Al-Ahlyyah Amman Unversty,
More informationSolving two-person zero-sum game by Matlab
Appled Mechancs and Materals Onlne: 2011-02-02 ISSN: 1662-7482, Vols. 50-51, pp 262-265 do:10.4028/www.scentfc.net/amm.50-51.262 2011 Trans Tech Publcatons, Swtzerland Solvng two-person zero-sum game by
More informationNUMERICAL SOLVING OPTIMAL CONTROL PROBLEMS BY THE METHOD OF VARIATIONS
ARPN Journal of Engneerng and Appled Scences 006-017 Asan Research Publshng Network (ARPN). All rghts reserved. NUMERICAL SOLVING OPTIMAL CONTROL PROBLEMS BY THE METHOD OF VARIATIONS Igor Grgoryev, Svetlana
More informationNon-Split Restrained Dominating Set of an Interval Graph Using an Algorithm
Internatonal Journal of Advancements n Research & Technology, Volume, Issue, July- ISS - on-splt Restraned Domnatng Set of an Interval Graph Usng an Algorthm ABSTRACT Dr.A.Sudhakaraah *, E. Gnana Deepka,
More informationKent State University CS 4/ Design and Analysis of Algorithms. Dept. of Math & Computer Science LECT-16. Dynamic Programming
CS 4/560 Desgn and Analyss of Algorthms Kent State Unversty Dept. of Math & Computer Scence LECT-6 Dynamc Programmng 2 Dynamc Programmng Dynamc Programmng, lke the dvde-and-conquer method, solves problems
More informationR s s f. m y s. SPH3UW Unit 7.3 Spherical Concave Mirrors Page 1 of 12. Notes
SPH3UW Unt 7.3 Sphercal Concave Mrrors Page 1 of 1 Notes Physcs Tool box Concave Mrror If the reflectng surface takes place on the nner surface of the sphercal shape so that the centre of the mrror bulges
More informationCSE 326: Data Structures Quicksort Comparison Sorting Bound
CSE 326: Data Structures Qucksort Comparson Sortng Bound Steve Setz Wnter 2009 Qucksort Qucksort uses a dvde and conquer strategy, but does not requre the O(N) extra space that MergeSort does. Here s the
More informationMathematics 256 a course in differential equations for engineering students
Mathematcs 56 a course n dfferental equatons for engneerng students Chapter 5. More effcent methods of numercal soluton Euler s method s qute neffcent. Because the error s essentally proportonal to the
More informationPositive Semi-definite Programming Localization in Wireless Sensor Networks
Postve Sem-defnte Programmng Localzaton n Wreless Sensor etworks Shengdong Xe 1,, Jn Wang, Aqun Hu 1, Yunl Gu, Jang Xu, 1 School of Informaton Scence and Engneerng, Southeast Unversty, 10096, anjng Computer
More informationThe Codesign Challenge
ECE 4530 Codesgn Challenge Fall 2007 Hardware/Software Codesgn The Codesgn Challenge Objectves In the codesgn challenge, your task s to accelerate a gven software reference mplementaton as fast as possble.
More informationCSE 326: Data Structures Quicksort Comparison Sorting Bound
CSE 326: Data Structures Qucksort Comparson Sortng Bound Bran Curless Sprng 2008 Announcements (5/14/08) Homework due at begnnng of class on Frday. Secton tomorrow: Graded homeworks returned More dscusson
More informationDetermining the Optimal Bandwidth Based on Multi-criterion Fusion
Proceedngs of 01 4th Internatonal Conference on Machne Learnng and Computng IPCSIT vol. 5 (01) (01) IACSIT Press, Sngapore Determnng the Optmal Bandwdth Based on Mult-crteron Fuson Ha-L Lang 1+, Xan-Mn
More informationAn Improved Image Segmentation Algorithm Based on the Otsu Method
3th ACIS Internatonal Conference on Software Engneerng, Artfcal Intellgence, Networkng arallel/dstrbuted Computng An Improved Image Segmentaton Algorthm Based on the Otsu Method Mengxng Huang, enjao Yu,
More informationAccounting for the Use of Different Length Scale Factors in x, y and z Directions
1 Accountng for the Use of Dfferent Length Scale Factors n x, y and z Drectons Taha Soch (taha.soch@kcl.ac.uk) Imagng Scences & Bomedcal Engneerng, Kng s College London, The Rayne Insttute, St Thomas Hosptal,
More informationGSLM Operations Research II Fall 13/14
GSLM 58 Operatons Research II Fall /4 6. Separable Programmng Consder a general NLP mn f(x) s.t. g j (x) b j j =. m. Defnton 6.. The NLP s a separable program f ts objectve functon and all constrants are
More informationSolving the large scale knapsack feasibility problem using a distributed computation approach to integer programming
https://do.org/10.1186/s40535-017-0047-0 RESEARCH Open Access Solvng the large scale napsac feasblty problem usng a dstrbuted computaton approach to nteger programmng Zhengtan Wu 1,2*, Fuyuan Hu 1 and
More informationParallel Artificial Bee Colony Algorithm for the Traveling Salesman Problem
Parallel Artfcal Bee Colony Algorthm for the Travelng Salesman Problem Kun Xu, Mngyan Jang, Dongfeng Yuan The School of Informaton Scence and Engneerng Shandong Unversty, Jnan, 250100, Chna E-mal: xukun_sdu@163.com,
More informationCluster Analysis of Electrical Behavior
Journal of Computer and Communcatons, 205, 3, 88-93 Publshed Onlne May 205 n ScRes. http://www.scrp.org/ournal/cc http://dx.do.org/0.4236/cc.205.350 Cluster Analyss of Electrcal Behavor Ln Lu Ln Lu, School
More informationOpen Access Early Fire Smoke Image Segmentation in a Complex Large Space
Send Orders for Reprnts to reprnts@benthamscence.ae The Open Constructon and Buldng Technology Journal, 2015, 9, 27-31 27 Open Access Early Fre Smoke Image Segmentaton n a Complex Large Space Hu Yan 1,2,*,
More informationA New Approach For the Ranking of Fuzzy Sets With Different Heights
New pproach For the ankng of Fuzzy Sets Wth Dfferent Heghts Pushpnder Sngh School of Mathematcs Computer pplcatons Thapar Unversty, Patala-7 00 Inda pushpndersnl@gmalcom STCT ankng of fuzzy sets plays
More informationAP PHYSICS B 2008 SCORING GUIDELINES
AP PHYSICS B 2008 SCORING GUIDELINES General Notes About 2008 AP Physcs Scorng Gudelnes 1. The solutons contan the most common method of solvng the free-response questons and the allocaton of ponts for
More informationCourse Introduction. Algorithm 8/31/2017. COSC 320 Advanced Data Structures and Algorithms. COSC 320 Advanced Data Structures and Algorithms
Course Introducton Course Topcs Exams, abs, Proects A quc loo at a few algorthms 1 Advanced Data Structures and Algorthms Descrpton: We are gong to dscuss algorthm complexty analyss, algorthm desgn technques
More informationA MOVING MESH APPROACH FOR SIMULATION BUDGET ALLOCATION ON CONTINUOUS DOMAINS
Proceedngs of the Wnter Smulaton Conference M E Kuhl, N M Steger, F B Armstrong, and J A Jones, eds A MOVING MESH APPROACH FOR SIMULATION BUDGET ALLOCATION ON CONTINUOUS DOMAINS Mark W Brantley Chun-Hung
More informationAn Application of the Dulmage-Mendelsohn Decomposition to Sparse Null Space Bases of Full Row Rank Matrices
Internatonal Mathematcal Forum, Vol 7, 2012, no 52, 2549-2554 An Applcaton of the Dulmage-Mendelsohn Decomposton to Sparse Null Space Bases of Full Row Rank Matrces Mostafa Khorramzadeh Department of Mathematcal
More informationUNIT 2 : INEQUALITIES AND CONVEX SETS
UNT 2 : NEQUALTES AND CONVEX SETS ' Structure 2. ntroducton Objectves, nequaltes and ther Graphs Convex Sets and ther Geometry Noton of Convex Sets Extreme Ponts of Convex Set Hyper Planes and Half Spaces
More informationLoad Balancing for Hex-Cell Interconnection Network
Int. J. Communcatons, Network and System Scences,,, - Publshed Onlne Aprl n ScRes. http://www.scrp.org/journal/jcns http://dx.do.org/./jcns.. Load Balancng for Hex-Cell Interconnecton Network Saher Manaseer,
More informationResearch on Categorization of Animation Effect Based on Data Mining
MATEC Web of Conferences 22, 0102 0 ( 2015) DOI: 10.1051/ matecconf/ 2015220102 0 C Owned by the authors, publshed by EDP Scences, 2015 Research on Categorzaton of Anmaton Effect Based on Data Mnng Na
More informationAPPLICATION OF IMPROVED K-MEANS ALGORITHM IN THE DELIVERY LOCATION
An Open Access, Onlne Internatonal Journal Avalable at http://www.cbtech.org/pms.htm 2016 Vol. 6 (2) Aprl-June, pp. 11-17/Sh Research Artcle APPLICATION OF IMPROVED K-MEANS ALGORITHM IN THE DELIVERY LOCATION
More informationEmpirical Distributions of Parameter Estimates. in Binary Logistic Regression Using Bootstrap
Int. Journal of Math. Analyss, Vol. 8, 4, no. 5, 7-7 HIKARI Ltd, www.m-hkar.com http://dx.do.org/.988/jma.4.494 Emprcal Dstrbutons of Parameter Estmates n Bnary Logstc Regresson Usng Bootstrap Anwar Ftranto*
More informationOn Some Entertaining Applications of the Concept of Set in Computer Science Course
On Some Entertanng Applcatons of the Concept of Set n Computer Scence Course Krasmr Yordzhev *, Hrstna Kostadnova ** * Assocate Professor Krasmr Yordzhev, Ph.D., Faculty of Mathematcs and Natural Scences,
More informationApplication of Clustering Algorithm in Big Data Sample Set Optimization
Applcaton of Clusterng Algorthm n Bg Data Sample Set Optmzaton Yutang Lu 1, Qn Zhang 2 1 Department of Basc Subjects, Henan Insttute of Technology, Xnxang 453002, Chna 2 School of Mathematcs and Informaton
More informationClassifier Selection Based on Data Complexity Measures *
Classfer Selecton Based on Data Complexty Measures * Edth Hernández-Reyes, J.A. Carrasco-Ochoa, and J.Fco. Martínez-Trndad Natonal Insttute for Astrophyscs, Optcs and Electroncs, Lus Enrque Erro No.1 Sta.
More informationCompiler Design. Spring Register Allocation. Sample Exercises and Solutions. Prof. Pedro C. Diniz
Compler Desgn Sprng 2014 Regster Allocaton Sample Exercses and Solutons Prof. Pedro C. Dnz USC / Informaton Scences Insttute 4676 Admralty Way, Sute 1001 Marna del Rey, Calforna 90292 pedro@s.edu Regster
More informationParallel matrix-vector multiplication
Appendx A Parallel matrx-vector multplcaton The reduced transton matrx of the three-dmensonal cage model for gel electrophoress, descrbed n secton 3.2, becomes excessvely large for polymer lengths more
More informationUnsupervised Learning
Pattern Recognton Lecture 8 Outlne Introducton Unsupervsed Learnng Parametrc VS Non-Parametrc Approach Mxture of Denstes Maxmum-Lkelhood Estmates Clusterng Prof. Danel Yeung School of Computer Scence and
More informationAn Accurate Evaluation of Integrals in Convex and Non convex Polygonal Domain by Twelve Node Quadrilateral Finite Element Method
Internatonal Journal of Computatonal and Appled Mathematcs. ISSN 89-4966 Volume, Number (07), pp. 33-4 Research Inda Publcatons http://www.rpublcaton.com An Accurate Evaluaton of Integrals n Convex and
More informationA Binarization Algorithm specialized on Document Images and Photos
A Bnarzaton Algorthm specalzed on Document mages and Photos Ergna Kavalleratou Dept. of nformaton and Communcaton Systems Engneerng Unversty of the Aegean kavalleratou@aegean.gr Abstract n ths paper, a
More informationSum of Linear and Fractional Multiobjective Programming Problem under Fuzzy Rules Constraints
Australan Journal of Basc and Appled Scences, 2(4): 1204-1208, 2008 ISSN 1991-8178 Sum of Lnear and Fractonal Multobjectve Programmng Problem under Fuzzy Rules Constrants 1 2 Sanjay Jan and Kalash Lachhwan
More informationShadow Elimination of Moving Targets Base on a Novel Two-Step Algorithm
Send Orders for Reprnts to reprnts@benthamscence.ae The Open Cybernetcs & Systemcs Journal 2015 9 761-769 761 Open Access Shadow Elmnaton of Movng Targets Base on a Novel Two-Step Algorthm Lu Yng * Chongqng
More informationON SOME ENTERTAINING APPLICATIONS OF THE CONCEPT OF SET IN COMPUTER SCIENCE COURSE
Yordzhev K., Kostadnova H. Інформаційні технології в освіті ON SOME ENTERTAINING APPLICATIONS OF THE CONCEPT OF SET IN COMPUTER SCIENCE COURSE Yordzhev K., Kostadnova H. Some aspects of programmng educaton
More informationThe Greedy Method. Outline and Reading. Change Money Problem. Greedy Algorithms. Applications of the Greedy Strategy. The Greedy Method Technique
//00 :0 AM Outlne and Readng The Greedy Method The Greedy Method Technque (secton.) Fractonal Knapsack Problem (secton..) Task Schedulng (secton..) Mnmum Spannng Trees (secton.) Change Money Problem Greedy
More informationLine Clipping by Convex and Nonconvex Polyhedra in E 3
Lne Clppng by Convex and Nonconvex Polyhedra n E 3 Václav Skala 1 Department of Informatcs and Computer Scence Unversty of West Bohema Unverztní 22, Box 314, 306 14 Plzeò Czech Republc e-mal: skala@kv.zcu.cz
More informationOutline. Type of Machine Learning. Examples of Application. Unsupervised Learning
Outlne Artfcal Intellgence and ts applcatons Lecture 8 Unsupervsed Learnng Professor Danel Yeung danyeung@eee.org Dr. Patrck Chan patrckchan@eee.org South Chna Unversty of Technology, Chna Introducton
More informationAssignment # 2. Farrukh Jabeen Algorithms 510 Assignment #2 Due Date: June 15, 2009.
Farrukh Jabeen Algorthms 51 Assgnment #2 Due Date: June 15, 29. Assgnment # 2 Chapter 3 Dscrete Fourer Transforms Implement the FFT for the DFT. Descrbed n sectons 3.1 and 3.2. Delverables: 1. Concse descrpton
More informationProblem Set 3 Solutions
Introducton to Algorthms October 4, 2002 Massachusetts Insttute of Technology 6046J/18410J Professors Erk Demane and Shaf Goldwasser Handout 14 Problem Set 3 Solutons (Exercses were not to be turned n,
More informationChapter 6 Programmng the fnte element method Inow turn to the man subject of ths book: The mplementaton of the fnte element algorthm n computer programs. In order to make my dscusson as straghtforward
More informationStraight Line Detection Based on Particle Swarm Optimization
Sensors & ransducers 013 b IFSA http://www.sensorsportal.com Straght Lne Detecton Based on Partcle Swarm Optmzaton Shengzhou XU, Jun IE College of computer scence, South-Central Unverst for Natonaltes,
More informationCE 221 Data Structures and Algorithms
CE 1 ata Structures and Algorthms Chapter 4: Trees BST Text: Read Wess, 4.3 Izmr Unversty of Economcs 1 The Search Tree AT Bnary Search Trees An mportant applcaton of bnary trees s n searchng. Let us assume
More informationA Fast Content-Based Multimedia Retrieval Technique Using Compressed Data
A Fast Content-Based Multmeda Retreval Technque Usng Compressed Data Borko Furht and Pornvt Saksobhavvat NSF Multmeda Laboratory Florda Atlantc Unversty, Boca Raton, Florda 3343 ABSTRACT In ths paper,
More informationSuppression for Luminance Difference of Stereo Image-Pair Based on Improved Histogram Equalization
Suppresson for Lumnance Dfference of Stereo Image-Par Based on Improved Hstogram Equalzaton Zhao Llng,, Zheng Yuhu 3, Sun Quansen, Xa Deshen School of Computer Scence and Technology, NJUST, Nanjng, Chna.School
More informationA fast algorithm for color image segmentation
Unersty of Wollongong Research Onlne Faculty of Informatcs - Papers (Arche) Faculty of Engneerng and Informaton Scences 006 A fast algorthm for color mage segmentaton L. Dong Unersty of Wollongong, lju@uow.edu.au
More informationThe Theory and Application of an Adaptive Moving Least. Squares for Non-uniform Samples
Xanpng Huang, Qng Tan, Janfe Mao, L Jang, Ronghua Lang The Theory and Applcaton of an Adaptve Movng Least Squares for Non-unform Samples Xanpng Huang, Qng Tan, Janfe Mao*, L Jang, Ronghua Lang College
More informationSupport Vector Machines
/9/207 MIST.6060 Busness Intellgence and Data Mnng What are Support Vector Machnes? Support Vector Machnes Support Vector Machnes (SVMs) are supervsed learnng technques that analyze data and recognze patterns.
More informationLearning the Kernel Parameters in Kernel Minimum Distance Classifier
Learnng the Kernel Parameters n Kernel Mnmum Dstance Classfer Daoqang Zhang 1,, Songcan Chen and Zh-Hua Zhou 1* 1 Natonal Laboratory for Novel Software Technology Nanjng Unversty, Nanjng 193, Chna Department
More informationBIN XIA et al: AN IMPROVED K-MEANS ALGORITHM BASED ON CLOUD PLATFORM FOR DATA MINING
An Improved K-means Algorthm based on Cloud Platform for Data Mnng Bn Xa *, Yan Lu 2. School of nformaton and management scence, Henan Agrcultural Unversty, Zhengzhou, Henan 450002, P.R. Chna 2. College
More informationAn Influence of the Noise on the Imaging Algorithm in the Electrical Impedance Tomography *
Open Journal of Bophyscs, 3, 3, 7- http://dx.do.org/.436/ojbphy.3.347 Publshed Onlne October 3 (http://www.scrp.org/journal/ojbphy) An Influence of the Nose on the Imagng Algorthm n the Electrcal Impedance
More informationThe Comparison of Calibration Method of Binocular Stereo Vision System Ke Zhang a *, Zhao Gao b
3rd Internatonal Conference on Materal, Mechancal and Manufacturng Engneerng (IC3ME 2015) The Comparson of Calbraton Method of Bnocular Stereo Vson System Ke Zhang a *, Zhao Gao b College of Engneerng,
More informationFast Feature Value Searching for Face Detection
Vol., No. 2 Computer and Informaton Scence Fast Feature Value Searchng for Face Detecton Yunyang Yan Department of Computer Engneerng Huayn Insttute of Technology Hua an 22300, Chna E-mal: areyyyke@63.com
More informationImprovement of Spatial Resolution Using BlockMatching Based Motion Estimation and Frame. Integration
Improvement of Spatal Resoluton Usng BlockMatchng Based Moton Estmaton and Frame Integraton Danya Suga and Takayuk Hamamoto Graduate School of Engneerng, Tokyo Unversty of Scence, 6-3-1, Nuku, Katsuska-ku,
More informationObstacle-Aware Routing Problem in. a Rectangular Mesh Network
Appled Mathematcal Scences, Vol. 9, 015, no. 14, 653-663 HIKARI Ltd, www.m-hkar.com http://dx.do.org/10.1988/ams.015.411911 Obstacle-Aware Routng Problem n a Rectangular Mesh Network Norazah Adzhar Department
More informationTsinghua University at TAC 2009: Summarizing Multi-documents by Information Distance
Tsnghua Unversty at TAC 2009: Summarzng Mult-documents by Informaton Dstance Chong Long, Mnle Huang, Xaoyan Zhu State Key Laboratory of Intellgent Technology and Systems, Tsnghua Natonal Laboratory for
More informationCracking of the Merkle Hellman Cryptosystem Using Genetic Algorithm
Crackng of the Merkle Hellman Cryptosystem Usng Genetc Algorthm Zurab Kochladze 1 * & Lal Besela 2 1 Ivane Javakhshvl Tbls State Unversty, 1, I.Chavchavadze av 1, 0128, Tbls, Georga 2 Sokhum State Unversty,
More informationA Topology-aware Random Walk
A Topology-aware Random Walk Inkwan Yu, Rchard Newman Dept. of CISE, Unversty of Florda, Ganesvlle, Florda, USA Abstract When a graph can be decomposed nto clusters of well connected subgraphs, t s possble
More informationREFRACTION. a. To study the refraction of light from plane surfaces. b. To determine the index of refraction for Acrylic and Water.
Purpose Theory REFRACTION a. To study the refracton of lght from plane surfaces. b. To determne the ndex of refracton for Acrylc and Water. When a ray of lght passes from one medum nto another one of dfferent
More informationPerformance Evaluation of Information Retrieval Systems
Why System Evaluaton? Performance Evaluaton of Informaton Retreval Systems Many sldes n ths secton are adapted from Prof. Joydeep Ghosh (UT ECE) who n turn adapted them from Prof. Dk Lee (Unv. of Scence
More informationINTEGER PROGRAMMING MODELING FOR THE CHINESE POSTMAN PROBLEMS
INTEGER PROGRAMMING MODELING FOR THE CHINESE POSTMAN PROBLEMS ABSTRACT Feng Junwen School of Economcs and Management, Nanng Unversty of Scence and Technology, Nanng, 2009, Chna As far as the tradtonal
More informationUC Berkeley Working Papers
UC Berkeley Workng Papers Ttle Dscretzaton and Valdaton of the Contnuum Approxmaton Scheme for Termnal System Desgn Permalnk https://escholarshp.org/uc/tem/9dm7v0cn Authors Ouyang, Yanfeng Daganzo, Carlos
More informationTouring a Sequence of Polygons
Tourng a Sequence of Polygon Mohe Dror Alon Efrat Anna Lubw Joe Mtchell Unverty of Arzona Unverty of Arzona Unverty of Waterloo Stony Brook Unverty Tourng Polygon Problem Gven: a equence of convex polygon,
More informationPalmprint Minutia Point Matching Algorithmand GPU Application
Palmprnt Mnuta Pont Matchng Algorthmand GPU Applcaton 1 Beng Crmnal Scence Insttuton, Beng, 100054,Chna E-mal: wucs@sccas.cn Zhgang Lu 2 Publc Securty Bureau of Beng s Dongcheng, Beng, 100061, Chna Cagang
More informationLecture Note 08 EECS 4101/5101 Instructor: Andy Mirzaian. All Nearest Neighbors: The Lifting Method
Lecture Note 08 EECS 4101/5101 Instructor: Andy Mrzaan Introducton All Nearest Neghbors: The Lftng Method Suose we are gven aset P ={ 1, 2,..., n }of n onts n the lane. The gven coordnates of the -th ont
More informationComplex Deformable Objects in Virtual Reality
Complex Deformable Obects n Vrtual Realty Young-Mn Kang Department of Computer Scence Pusan Natonal Unversty ymkang@pearl.cs.pusan.ac.kr Hwan-Gue Cho Department of Computer Scence Pusan Natonal Unversty
More informationMaintaining temporal validity of real-time data on non-continuously executing resources
Mantanng temporal valdty of real-tme data on non-contnuously executng resources Tan Ba, Hong Lu and Juan Yang Hunan Insttute of Scence and Technology, College of Computer Scence, 44, Yueyang, Chna Wuhan
More informationELEC 377 Operating Systems. Week 6 Class 3
ELEC 377 Operatng Systems Week 6 Class 3 Last Class Memory Management Memory Pagng Pagng Structure ELEC 377 Operatng Systems Today Pagng Szes Vrtual Memory Concept Demand Pagng ELEC 377 Operatng Systems
More informationConstructing Minimum Connected Dominating Set: Algorithmic approach
Constructng Mnmum Connected Domnatng Set: Algorthmc approach G.N. Puroht and Usha Sharma Centre for Mathematcal Scences, Banasthal Unversty, Rajasthan 304022 usha.sharma94@yahoo.com Abstract: Connected
More informationCLUSTERING that discovers the relationship among data
Ramp-based Twn Support Vector Clusterng Zhen Wang, Xu Chen, Chun-Na L, and Yuan-Ha Shao arxv:82.0370v [cs.lg] 0 Dec 208 Abstract Tradtonal plane-based clusterng methods measure the cost of wthn-cluster
More informationCS1100 Introduction to Programming
Factoral (n) Recursve Program fact(n) = n*fact(n-) CS00 Introducton to Programmng Recurson and Sortng Madhu Mutyam Department of Computer Scence and Engneerng Indan Insttute of Technology Madras nt fact
More informationType-2 Fuzzy Non-uniform Rational B-spline Model with Type-2 Fuzzy Data
Malaysan Journal of Mathematcal Scences 11(S) Aprl : 35 46 (2017) Specal Issue: The 2nd Internatonal Conference and Workshop on Mathematcal Analyss (ICWOMA 2016) MALAYSIAN JOURNAL OF MATHEMATICAL SCIENCES
More informationResearch of Dynamic Access to Cloud Database Based on Improved Pheromone Algorithm
, pp.197-202 http://dx.do.org/10.14257/dta.2016.9.5.20 Research of Dynamc Access to Cloud Database Based on Improved Pheromone Algorthm Yongqang L 1 and Jn Pan 2 1 (Software Technology Vocatonal College,
More informationScheduling Remote Access to Scientific Instruments in Cyberinfrastructure for Education and Research
Schedulng Remote Access to Scentfc Instruments n Cybernfrastructure for Educaton and Research Je Yn 1, Junwe Cao 2,3,*, Yuexuan Wang 4, Lanchen Lu 1,3 and Cheng Wu 1,3 1 Natonal CIMS Engneerng and Research
More informationMULTISPECTRAL IMAGES CLASSIFICATION BASED ON KLT AND ATR AUTOMATIC TARGET RECOGNITION
MULTISPECTRAL IMAGES CLASSIFICATION BASED ON KLT AND ATR AUTOMATIC TARGET RECOGNITION Paulo Quntlano 1 & Antono Santa-Rosa 1 Federal Polce Department, Brasla, Brazl. E-mals: quntlano.pqs@dpf.gov.br and
More informationAn Efficient Genetic Algorithm with Fuzzy c-means Clustering for Traveling Salesman Problem
An Effcent Genetc Algorthm wth Fuzzy c-means Clusterng for Travelng Salesman Problem Jong-Won Yoon and Sung-Bae Cho Dept. of Computer Scence Yonse Unversty Seoul, Korea jwyoon@sclab.yonse.ac.r, sbcho@cs.yonse.ac.r
More informationA Unified Framework for Semantics and Feature Based Relevance Feedback in Image Retrieval Systems
A Unfed Framework for Semantcs and Feature Based Relevance Feedback n Image Retreval Systems Ye Lu *, Chunhu Hu 2, Xngquan Zhu 3*, HongJang Zhang 2, Qang Yang * School of Computng Scence Smon Fraser Unversty
More informationLearning-Based Top-N Selection Query Evaluation over Relational Databases
Learnng-Based Top-N Selecton Query Evaluaton over Relatonal Databases Lang Zhu *, Wey Meng ** * School of Mathematcs and Computer Scence, Hebe Unversty, Baodng, Hebe 071002, Chna, zhu@mal.hbu.edu.cn **
More informationA Clustering Algorithm for Chinese Adjectives and Nouns 1
Clusterng lgorthm for Chnese dectves and ouns Yang Wen, Chunfa Yuan, Changnng Huang 2 State Key aboratory of Intellgent Technology and System Deptartment of Computer Scence & Technology, Tsnghua Unversty,
More informationVectorization of Image Outlines Using Rational Spline and Genetic Algorithm
01 Internatonal Conference on Image, Vson and Computng (ICIVC 01) IPCSIT vol. 50 (01) (01) IACSIT Press, Sngapore DOI: 10.776/IPCSIT.01.V50.4 Vectorzaton of Image Outlnes Usng Ratonal Splne and Genetc
More informationInsertion Sort. Divide and Conquer Sorting. Divide and Conquer. Mergesort. Mergesort Example. Auxiliary Array
Inserton Sort Dvde and Conquer Sortng CSE 6 Data Structures Lecture 18 What f frst k elements of array are already sorted? 4, 7, 1, 5, 1, 16 We can shft the tal of the sorted elements lst down and then
More informationThe Research of Ellipse Parameter Fitting Algorithm of Ultrasonic Imaging Logging in the Casing Hole
Appled Mathematcs, 04, 5, 37-3 Publshed Onlne May 04 n ScRes. http://www.scrp.org/journal/am http://dx.do.org/0.436/am.04.584 The Research of Ellpse Parameter Fttng Algorthm of Ultrasonc Imagng Loggng
More informationFINDING IMPORTANT NODES IN SOCIAL NETWORKS BASED ON MODIFIED PAGERANK
FINDING IMPORTANT NODES IN SOCIAL NETWORKS BASED ON MODIFIED PAGERANK L-qng Qu, Yong-quan Lang 2, Jng-Chen 3, 2 College of Informaton Scence and Technology, Shandong Unversty of Scence and Technology,
More informationSecurity Vulnerabilities of an Enhanced Remote User Authentication Scheme
Contemporary Engneerng Scences, Vol. 7, 2014, no. 26, 1475-1482 HIKARI Ltd, www.m-hkar.com http://dx.do.org/10.12988/ces.2014.49186 Securty Vulnerabltes of an Enhanced Remote User Authentcaton Scheme Hae-Soon
More informationCan We Beat the Prefix Filtering? An Adaptive Framework for Similarity Join and Search
Can We Beat the Prefx Flterng? An Adaptve Framework for Smlarty Jon and Search Jannan Wang Guolang L Janhua Feng Department of Computer Scence and Technology, Tsnghua Natonal Laboratory for Informaton
More informationLoop Transformations, Dependences, and Parallelization
Loop Transformatons, Dependences, and Parallelzaton Announcements Mdterm s Frday from 3-4:15 n ths room Today Semester long project Data dependence recap Parallelsm and storage tradeoff Scalar expanson
More informationA Saturation Binary Neural Network for Crossbar Switching Problem
A Saturaton Bnary Neural Network for Crossbar Swtchng Problem Cu Zhang 1, L-Qng Zhao 2, and Rong-Long Wang 2 1 Department of Autocontrol, Laonng Insttute of Scence and Technology, Benx, Chna bxlkyzhangcu@163.com
More information