AN ALGORITHM FOR GENERATING

example, reason that one constraint makes another un- satisfiable. Because agents involved in collaboration dedicate a significant portion of their time to discussing the ac- tions they need to perform, an algorithm for rood- 37 elling plan recognition in discourse must model re[r]

AN ALGORITHM FOR GENERATING NON-REDUNDANT QUANTIFIER SCOPINGS Espen J. Vestre Department of Mathematics University of Oslo P.O. Box 1053 Blindern N-0316 OSLO 3, Norway Internet: espen@math.uio.no ABSTRACT This paper describes an algorithm for generat-[r]

communicative goals to pursue, expressed by Describe(r,v) property p ascribed to referent r referents already processed properties whose images on the lexical level are likely to fill empty slots in FD property-referent combinations that cannot be verbalized in the given context Table 1: Variables u[r]

of the held-out. We collect statistics on how well theoutput of the system matches the target side of theheld-out. The matching scores on the held-out dataoften make large jumps from iteration to iteration.We take the median of the results from 9 consecutiveiterations (the 4 iterations before, the c[r]

2IntroductionAn independent set, or a stable set, in a graph is a set of mutually nonadjacent vertices. The problem of finding a maximum independent set in a graph,IndSet, is one of most fundamental combinatorial NP-hard problem. It servesalso as the primary representative for the family of s[r]

but also basically “designs”. A software framework is a reusable architecture, which providesthe skeleton and basic behavior of a certain kind of software product. In general, a frameworkis a collection of tightly related classes whose interrelation is usually given by the designpatterns that the fr[r]

Faculty of Computer Science and Engineering Department of Computer Science Released on 03/09/2012 10:09:56 1/5 DATA STRUCTURES & ALGORITHMS Tutorial 1 Questions COMPUTATIONAL COMPLEXITY Required Questions Question 1. Reorder the following efficiencies from the smallest to the largest: a.[r]

fact that stage interleaving given in [8]isaspecialcaseofamore general class of MD quantizers. In MD-MSVQ, eachstage consists of a set of multiple description codebooks withan associated index assignment (IA) matrix [2]. The inter-leaving scheme considered in [8] essentially corresponds toan MD-MSVQ[r]

EURASIP Journal on Applied Signal Processing 2004:6, 913–922c 2004 Hindawi Publishing CorporationMAP Estimation of Chin and Cheek Contoursin Video SequencesMarkus KampmannEricsson Research, Ericsson Allee 1, 52134 Herzogenrath, GermanyEmail: markus.kampmann@ericsson.comReceived 28 December 2002; Re[r]

Hindawi Publishing CorporationEURASIP Journal on Advances in Signal ProcessingVolume 2008, Article ID 360912, 10 pagesdoi:10.1155/2008/360912Research ArticleTracking Objects with Networked ScatteredDirectional SensorsKurt Plarre1and P. R. Kumar21Department of Mechanical Engineer ing and Center fo[r]

(1992) reported that their system required around1,500 person-hours of expert labour to modify fora new extraction task. One approach to this problemis to use machine learning to automatically learn thedomain-specific information required to port a sys-tem (Riloff, 1996). Yangarber et al. (2000) prop[r]

De-novo algorithms work for truly unknown structuresSee Oscar and FragLibSee GlySpySource: Congruent Strategies for Carbohydrate Sequencing.3. OSCAR: An Algorithm for Assigning Oligosaccharide Topology from MSn Datahttp://www.pubmedcentral.nih.gov/articlerender.fcg[r]

Faculty of Computer Science and Engineering Department of Computer Science Released on 03/09/2012 10:09:56 1/5 DATA STRUCTURES & ALGORITHMS Tutorial 1 Questions COMPUTATIONAL COMPLEXITY Required Questions Question 1. Reorder the following efficiencies from the smallest to the largest: a.[r]

True value of the coefficientFigure 4: Genetic adaptive algorithm tracking performance in arapidly varying environment (d = 1.6).tion to rapid small-scale excursions resulting from the use ofblocked input-output data, the extent to which the unknownsystem is correctly identified fluctuates on a m[r]

r= 91◦.The inequality constraint for the case of broadbandsources was considered in [14, 16]. Using the same approx-imation method, the result for a narrowband source will beextended to broadband sources.REFERENCES[1] O. L. Frost III, “An algorithm for linearly con[r]

vert the tuple (v, f) to a string by adding prepositions and articles where needed. For exam-ple, for (element, <project, pcomp_of, 1>) gener-ate the corresponding string “element of the project” and search the web for exact matches of the string. Then validate the[r]

bounces off the surface, resulting from a combination of secondarywavefronts, will not propagate just in the specular direction withrespect to the exciting wave.3. Mathematical Models of Diffractionand DiffusionIn this section we investigate some mathematical modelsused in the literature to quantitat[r]

whether a or a' was read is retrieved from the stack, but this information is merely popped without investigation. Thereby, the algorithm fails to perform the necessary matching of the elementary tree with regard to the part to the "north-west" of the adjunction. Our new algorithm reco[r]

−2The proposed method, source 1The proposed method, source 2Figure 7: The RMSE of the estimated frequency over 500 MonteCarlo runs versus the number of snapshots; 14 sensors are used andthe SNR is fixed at 15dB. Two equi-power sources approach the ar-ray from 38◦and 20◦,respectively.estimation accura[r]

Authors’ contributionsBoth authors contributed equally to this work. All authors read and approved the final manuscript.Competing interestsThe authors declare that they have no competing interests.Received: 13 March 2011 Accepted: 25 August 2011 Published: 25 August 2011References1. Rockafellar, RT:[r]