Academic literature on the topic 'Interval'
Create a spot-on reference in APA, MLA, Chicago, Harvard, and other styles
Consult the lists of relevant articles, books, theses, conference reports, and other scholarly sources on the topic 'Interval.'
Next to every source in the list of references, there is an 'Add to bibliography' button. Press on it, and we will generate automatically the bibliographic reference to the chosen work in the citation style you need: APA, MLA, Harvard, Chicago, Vancouver, etc.
You can also download the full text of the academic publication as pdf and read online its abstract whenever available in the metadata.
Journal articles on the topic "Interval"
Rohn, Jiří. "Interval solutions of linear interval equations." Applications of Mathematics 35, no. 3 (1990): 220–24. http://dx.doi.org/10.21136/am.1990.104406.
Full textLodwick, Weldon A., and Oscar A. Jenkins. "Constrained intervals and interval spaces." Soft Computing 17, no. 8 (February 19, 2013): 1393–402. http://dx.doi.org/10.1007/s00500-013-1006-x.
Full textKleinman, Matthew R., Hansem Sohn, and Daeyeol Lee. "A two-stage model of concurrent interval timing in monkeys." Journal of Neurophysiology 116, no. 3 (September 1, 2016): 1068–81. http://dx.doi.org/10.1152/jn.00375.2016.
Full textPerlman, Marc, and Carol L. Krumhansl. "An Experimental Study of Internal Interval Standards in Javanese and Western Musicians." Music Perception 14, no. 2 (1996): 95–116. http://dx.doi.org/10.2307/40285714.
Full textKahraman, Cengiz, Basar Oztaysi, and Sezi Cevik Onar. "Interval-Valued Intuitionistic Fuzzy Confidence Intervals." Journal of Intelligent Systems 28, no. 2 (April 24, 2019): 307–19. http://dx.doi.org/10.1515/jisys-2017-0139.
Full textBlokh, A. M. "On rotation intervals for interval maps." Nonlinearity 7, no. 5 (September 1, 1994): 1395–417. http://dx.doi.org/10.1088/0951-7715/7/5/008.
Full textMcClaskey, Carolyn M. "Standard-interval size affects interval-discrimination thresholds for pure-tone melodic pitch intervals." Hearing Research 355 (November 2017): 64–69. http://dx.doi.org/10.1016/j.heares.2017.09.008.
Full textCui, Yao, Changjun Liu, Nan Qiao, Siyu Qi, Xuanyi Chen, Pengyu Zhu, and Yongneng Feng. "Characteristics of Acoustic Emission Caused by Intermittent Fatigue of Rock Salt." Applied Sciences 12, no. 11 (May 29, 2022): 5528. http://dx.doi.org/10.3390/app12115528.
Full textRepp, Bruno H., Hannah B. Mendlowitz, and Michael J. Hove. "Does Rapid Auditory Stimulation Accelerate an Internal Pacemaker? Don’t Bet on It." Timing & Time Perception 1, no. 1 (2013): 65–76. http://dx.doi.org/10.1163/22134468-00002001.
Full textBhattacharya, Sourav, and Alexander Blokh. "Over-rotation intervals of bimodal interval maps." Journal of Difference Equations and Applications 26, no. 8 (February 17, 2020): 1085–113. http://dx.doi.org/10.1080/10236198.2020.1725495.
Full textDissertations / Theses on the topic "Interval"
Korzenowski, Heidi. "Estudo sobre resolucao de equacoes de coeficientes intervalares." reponame:Biblioteca Digital de Teses e Dissertações da UFRGS, 1994. http://hdl.handle.net/10183/25863.
Full textThe aim of this work is to determine the solution set of some Equations of Interval Coefficients. The study use a Theory of Interval Approximation. The begining of this theory was described by [ACI91]. In this theory the equality for intervals is replaced by an approximation relation. When we make use of that relation to solve interval equations, it's possible to obtain an optimal solution, i.e., to get an interval solution that contain all of real solutions of the real equations envolved in the interval equation. By using the equality of Classical Interval Theory for solving interval equations we can not get an optimal solution, that is, the interval solution in the most of equations not consider some real solutions of real equations that belong to the interval equation. We present some basic concepts and analyse some properties at the interval space (1(R), E, -a x , 1). Different kind of functions are showed in this space in order to obtain the range, the solution caracterization and the graphic identification of the optimal and external solution region, for each kind of function. The representation of intervals in /(R) is determined in a half plane of axes X - , X+, where X - represent the lower endpoint and X+ represent the upper endpoint of the intervals. The nonregular intervals are defined in /(R), which are determined in an other half plane. In this interval space are presenting some specific concepts, as well as arithmetical operations and some remarks about nonregular intervals. The interval space (1(R), +, •, C, Ex , 1) have a similar structure to a field, so it's possible to solve interval coefficients equations analogously as to solve real equations in the real space. We present the solution of linear interval equations and we determine an interval formula to solve square interval equation. We present some intervals iterated methods for functions that have degree greater than 2 that allow to get an interval solution of interval functions. Finally we show some basic concepts about the interval matrix space Af,„„(IR)) and present direct methods for the resolution of linear interval sistems.
Taga, Marcel Frederico de Lima. "Regressão linear com medidas censuradas." Universidade de São Paulo, 2008. http://www.teses.usp.br/teses/disponiveis/45/45133/tde-05122008-005901/.
Full textWe consider a simple linear regression model in which both variables are interval censored. To motivate the problem we use data from an audiometric study designed to evaluate the possibility of prediction of behavioral thresholds from physiological thresholds. We develop prediction intervals for the response variable, obtain the maximum likelihood estimators of the proposed model and compare their performance with that of estimators obtained under ordinary linear regression models.
Holbig, Carlos Amaral. "Métodos intervalares para a resolução de sistemas de equações lineares." reponame:Biblioteca Digital de Teses e Dissertações da UFRGS, 1996. http://hdl.handle.net/10183/23432.
Full textThe study of interval methods is important for resolution of linear equation systems, because such methods produce results into reliable bounds and prove the existence or not existence of solutions, therefore they produce reliable results that, the punctual methods can non present,save that there is an exhaustive analysis of errors. Another aspect to emphasize is the field of utilization of linear equation systems in engineering problems and other sciences, in which is showed the applicability of that methods and, consequently, the necessity of tools elaboration that make possible the implementation of that interval methods. The goal of this work is not the elaboration of new interval methods, but to accomplish a description and implementation of some interval methods found in the searched bibliography. The interval version of punctual methods is not simple, and the calculus by interval methods can be expensive, respecting is treats of vectors and matrices of intervals. The implementation of interval methods was only possible due to the existence of tools, as the Pascal-XSC compiler, which incorporates to their features, important aspects such as the interval arithmetic, the automatic verification of the result, the optimal scalar product and arithmetic of high accuracy. This work is divided in two stages. The first presents a study of the interval methods for resolution of linear equation systems, in which are characterized the methodologies of development of that methods. These methodologies were divided in three method groups: interval methods based in interval algebraic operations or direct methods, interval methods based in refinament or hybrid methods, and interval methods based in iterations, in which are determined the features, the methods that compose them, and the applicability of those methods in the resolution of linear equation systems. The second stage is characterized for the elaboration of the algorithms relating to the interval methods studied and their respective implementation, originating a interval applied library for resolution of linear equation systems, selintp, implemented in PC-486 and making use of Pascal-XSC compiler. For this development was previously accomplished a study about compiler and avaiable libraries that are used in the inplementation of the interval applied library. The library selintp is organized in four modules: the dirint module (regarding to the direct methods); the refint module (regarding to the methods based in refinament); the itrint module (regarding to the iterative methods) and equalg module(for equation systems of order 1). At last, throu gh this library, comparisons were developed among the results obtained (punctual, interval, sequential and vectorial results) in order to be accomplished an analysis of quantitative performance (accuracy) and a comparison among the results obtained with libselint a library, that is been developed for the Cray Y-MP supercomputer environment of CESUP/UFRGS, as part of the Interval Vectorial Arithmetic project of Group of Computational Mathematics of UFRGS.
Villanueva, Fabiola Roxana. "Contributions in interval optimization and interval optimal control /." São José do Rio Preto, 2020. http://hdl.handle.net/11449/192795.
Full textResumo: Neste trabalho, primeiramente, serão apresentados problemas de otimização nos quais a função objetivo é de múltiplas variáveis e de valor intervalar e as restrições de desigualdade são dadas por funcionais clássicos, isto é, de valor real. Serão dadas as condições de otimalidade usando a E−diferenciabilidade e, depois, a gH−diferenciabilidade total das funções com valor intervalar de várias variáveis. As condições necessárias de otimalidade usando a gH−diferenciabilidade total são do tipo KKT e as suficientes são do tipo de convexidade generalizada. Em seguida, serão estabelecidos problemas de controle ótimo nos quais a funçãao objetivo também é com valor intervalar de múltiplas variáveis e as restrições estão na forma de desigualdades e igualdades clássicas. Serão fornecidas as condições de otimalidade usando o conceito de Lipschitz para funções intervalares de várias variáveis e, logo, a gH−diferenciabilidade total das funções com valor intervalar de várias variáveis. As condições necessárias de otimalidade, usando a gH−diferenciabilidade total, estão na forma do célebre Princípio do Máximo de Pontryagin, mas desta vez na versão intervalar.
Abstract: In this work, firstly, it will be presented optimization problems in which the objective function is interval−valued of multiple variables and the inequality constraints are given by classical functionals, that is, real−valued ones. It will be given the optimality conditions using the E−differentiability and then the total gH−differentiability of interval−valued functions of several variables. The necessary optimality conditions using the total gH−differentiability are of KKT−type and the sufficient ones are of generalized convexity type. Next, it will be established optimal control problems in which the objective function is also interval−valued of multiple variables and the constraints are in the form of classical inequalities and equalities. It will be furnished the optimality conditions using the Lipschitz concept for interval−valued functions of several variables and then the total gH−differentiability of interval−valued functions of several variables. The necessary optimality conditions using the total gH−differentiability is in the form of the celebrated local Pontryagin Maximum Principle, but this time in the intervalar version.
Doutor
Yang, Joyce C. "Interval Graphs." Scholarship @ Claremont, 2016. https://scholarship.claremont.edu/hmc_theses/83.
Full textFranciosi, Beatriz Regina Tavares. "Representação geométrica de intervalos." reponame:Biblioteca Digital de Teses e Dissertações da UFRGS, 1999. http://hdl.handle.net/10183/17751.
Full textThis thesis presents a framework enabling the visual analysis of intervals, obtained by mapping geometric properties of the cartesian plane into interval sets to obtain a graphical representation. This new approach makes possible a dual interval representation and the immediate visual analysis of several relationships in (IR, <=) and (IR, C). In this sense, the set of degenerated intervals is a special case of this approach as they are represented by the straight line y=x. In turn, the order relation in (IR, C) is represented through the half-plane above the straight line y = x, denoted IR plane. Applying this framework, the visual interpretation of most interval operations is obtained directly from the graphical representation of the operands and the operations being studied. On the other hand, some experiments on interval visual analysis were developed with good final results. Thus, new properties and unusual interpretations for known operations can be developed with rather small effort. Moreover, this representation can be easily embedded into a running algorithm, to observe convergence and behavior of interval iterations, as one can easily see how intervals change with respect to midpoint and radius, as well as with respect to each other. The validation of this new approach was carried through the geometric solution of linear interval equations. This result was analyzed in order to verify the effective contribution of this geometrical representation in the context of interval arithmetic.
Santana, Fabiana Trist?o de. "Uma fundamenta??o para sinais e sistemas intervalares." Universidade Federal do Rio Grande do Norte, 2011. http://repositorio.ufrn.br:8080/jspui/handle/123456789/15158.
Full textCoordena??o de Aperfei?oamento de Pessoal de N?vel Superior
In this work we use Interval Mathematics to establish interval counterparts for the main tools used in digital signal processing. More specifically, the approach developed here is oriented to signals, systems, sampling, quantization, coding and Fourier transforms. A detailed study for some interval arithmetics which handle with complex numbers is provided; they are: complex interval arithmetic (or rectangular), circular complex arithmetic, and interval arithmetic for polar sectors. This lead us to investigate some properties that are relevant for the development of a theory of interval digital signal processing. It is shown that the sets IR and R(C) endowed with any correct arithmetic is not an algebraic field, meaning that those sets do not behave like real and complex numbers. An alternative to the notion of interval complex width is also provided and the Kulisch- Miranker order is used in order to write complex numbers in the interval form enabling operations on endpoints. The use of interval signals and systems is possible thanks to the representation of complex values into floating point systems. That is, if a number x 2 R is not representable in a floating point system F then it is mapped to an interval [x;x], such that x is the largest number in F which is smaller than x and x is the smallest one in F which is greater than x. This interval representation is the starting point for definitions like interval signals and systems which take real or complex values. It provides the extension for notions like: causality, stability, time invariance, homogeneity, additivity and linearity to interval systems. The process of quantization is extended to its interval counterpart. Thereafter the interval versions for: quantization levels, quantization error and encoded signal are provided. It is shown that the interval levels of quantization represent complex quantization levels and the classical quantization error ranges over the interval quantization error. An estimation for the interval quantization error and an interval version for Z-transform (and hence Fourier transform) is provided. Finally, the results of an Matlab implementation is given
Neste trabalho utiliza-se a matem?tica intervalar para estabelecer os conceitos intervalares das principais ferramentas utilizadas em processamento digital de sinais. Mais especificamente, foram desenvolvidos aqui as abordagens intervalares para sinais, sistemas, amostragem, quantiza??o, codifica??o, transformada Z e transformada de Fourier. ? feito um estudo de algumas aritm?ticas que lidam com n?meros complexos sujeitos ? imprecis?es, tais como: aritm?tica complexa intervalar (ou retangular), aritm?tica complexa circular, aritm?tica setorial e aritm?tica intervalar polar. A partir da?, investiga-se algumas propriedades que ser?o relevantes para o desenvolvimento e aplica??o no processamento de sinais discretos intervalares. Mostra-se que nos conjuntos IR e R(C), seja qual for a aritm?tica correta adotada, n?o se tem um corpo, isto ?, os elementos desses conjuntos n?o se comportam como os n?meros reais ou complexos com suas aritm?ticas cl?ssicas e que isso ir? requerer uma avalia??o matem?tica dos conceitos necess?rios ? teoria de sinais e a rela??o desses com as aritm?ticas intervalares. Tamb?m tanto ? introduzido o conceito de amplitude intervalar complexa, como alternativa ? defini??o cl?ssica quanto utiliza-se a ordem de Kulisch-Miranker para n?meros complexos afim de que se escreva n?meros complexos intervalares na forma de intervalos, o que torna poss?vel as opera??es atrav?s dos extremos. Essa rela??o ? utilizada em propriedades de somas de intervalos de n?meros complexos. O uso de sinais e sistemas intervalares foi motivado pela representa??o intervalar num sistema de ponto flutuante abstrato. Isto ?, se um n?mero x 2 R n?o ? represent?vel em um sistema de ponto flutuante F, ele ? mapeado para um intervalo [x;x], tal que x ? o maior dos n?meros menores que x represent?vel em F e x ? o menor dos n?meros maiores que x represent?vel em F. A representa??o intervalar ? importante em processamento digital de sinais, pois a imprecis?o em dados ocorre tanto no momento da medi??o de determinado sinal, quanto no momento de process?-los computacionalmente. A partir da?, define-se sinais e sistemas intervalares que assumem tanto valores reais quanto complexos. Para isso, utiliza-se o estudo feito a respeito das aritm?ticas complexas intervalares e mostram-se algumas propriedades dos sistemas intervalares, tais como: causalidade, estabilidade, invari?ncia no tempo, homogeneidade, aditividade e linearidade. Al?m disso, foi definida a representa??o intervalar de fun??es complexas. Tal fun??o estende sistemas cl?ssicos a sistemas intervalares preservando as principais propriedades. Um conceito muito importante no processamento digital de sinais ? a quantiza??o, uma vez que a maioria dos sinais ? de natureza cont?nua e para process?-los ? necess?rio convert?-los em sinais discretos. Aqui, este processo ? descrito detalhadamente com o uso da matem?tica intervalar, onde se prop?em, inicialmente, uma amostragem intervalar utilizando as id?ias de representa??o no sistema de ponto flutuante. Posteriormente, s?o definidos n?veis de quantiza??o intervalares e, a partir da?, ? descrito o processo para se obter o sinal quantizado intervalar e s?o definidos o erro de quantiza??o intervalar e o sinal codificado intervalar. ? mostrado que os n?veis de quantiza??o intervalares representam os n?veis de quantiza??o cl?ssicos e o erro de quantiza??o intervalar representa o e erro de quantiza??o cl?ssico. Uma estimativa para o erro de quantiza??o intervalar ? apresentada. Utilizando a aritm?tica retangular e as defini??es e propriedades de sinais e sistemas intervalares, ? introduzida a transformada Z intervalar e s?o analisadas as condi??es de converg?ncia e as principais propriedades. Em particular, quando a vari?vel complexa z ? unit?ria, define-se a transformada de Fourier intervalar para sinais discretos no tempo, al?m de suas propriedades. Por fim, foram apresentadas as implementa??es dos resultados que foram feitas no software Matlab
Alparslan, Gok Sirma Zeynep. "Cooperative Interval Games." Phd thesis, METU, 2009. http://etd.lib.metu.edu.tr/upload/3/12610337/index.pdf.
Full textSainudiin, R. "Machine Interval Experiments." Thesis, University of Canterbury. Mathematics and Statistics, 2005. http://hdl.handle.net/10092/2833.
Full textAlshammery, Hafiz Jaman 1971. "Interval attenuation estimation." Thesis, Massachusetts Institute of Technology, 1998. http://hdl.handle.net/1721.1/9877.
Full textIncludes bibliographical references (leaves 55-56).
by Hafiz Jaman Alshammery.
S.M.
Books on the topic "Interval"
Stavinoha, Jan. Interval. Amsterdam: Van Oorschot, 1987.
Find full textClief-Stefanon, Lyrae Van. Open interval. Pittsburgh: University of Pittsburgh Press, 2009.
Find full textFlorentin, Smarandache, and Chetry Moon Kumar, eds. Interval groupoids. Ann Arbor: Infolearnquest, 2010.
Find full textMirigan, David. Interval studies. Hayward,CA: Fivenote Music Publishing, 1990.
Find full textSnepp, Frank. Decent interval. Aldbourne: Orbis, 1988.
Find full textOpen interval. Pittsburgh: University of Pittsburgh Press, 2009.
Find full textCinema interval. New York: Routledge, 1999.
Find full textCissik, John. Maximum interval training. Champaign, IL: Human Kinetics, 2015.
Find full textInterval in Africa. Canterbury, Conn: Protea Pub. Co., 1988.
Find full textRoceric, Alexandra. Interval: Opal, ocean. Washington D.C: Moonfall Press, 1997.
Find full textBook chapters on the topic "Interval"
Krawczyk, R. "Interval operators and fixed intervals." In Interval Mathematics 1985, 81–94. Berlin, Heidelberg: Springer Berlin Heidelberg, 1986. http://dx.doi.org/10.1007/3-540-16437-5_8.
Full textGooch, Jan W. "Interval." In Encyclopedic Dictionary of Polymers, 984. New York, NY: Springer New York, 2011. http://dx.doi.org/10.1007/978-1-4419-6247-8_15261.
Full textWeik, Martin H. "interval." In Computer Science and Communications Dictionary, 831. Boston, MA: Springer US, 2000. http://dx.doi.org/10.1007/1-4020-0613-6_9524.
Full textBolles, Dylan, and Peter Lichtenfels. "Interval." In Performance Studies, 57–64. London: Macmillan Education UK, 2014. http://dx.doi.org/10.1007/978-1-137-46315-9_7.
Full textKoncilia, Christian, Tadeusz Morzy, Robert Wrembel, and Johann Eder. "Interval OLAP: Analyzing Interval Data." In Data Warehousing and Knowledge Discovery, 233–44. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-10160-6_21.
Full textSkalna, Iwona. "Interval and Parametric Interval Matrices." In Parametric Interval Algebraic Systems, 51–83. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-75187-0_3.
Full textPontius, Robert Gilmore. "Interval Variable Versus Interval Variable." In Advances in Geographic Information Science, 71–78. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-70765-1_8.
Full textBöhmová, Kateřina, Yann Disser, Matúš Mihalák, and Peter Widmayer. "Interval Selection with Machine-Dependent Intervals." In Lecture Notes in Computer Science, 170–81. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-40104-6_15.
Full textMudelsee, Manfred. "Bootstrap Confidence Intervals Confidence interval,Bootstrap." In Atmospheric and Oceanographic Sciences Library, 61–104. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-04450-7_3.
Full textBiasi, Glenn. "Recurrence Interval." In Encyclopedia of Natural Hazards, 824–25. Dordrecht: Springer Netherlands, 2013. http://dx.doi.org/10.1007/978-1-4020-4399-4_286.
Full textConference papers on the topic "Interval"
Trudel, André. "Interval Algebra Networks with Infinite Intervals." In 2009 16th International Symposium on Temporal Representation and Reasoning (TIME). IEEE, 2009. http://dx.doi.org/10.1109/time.2009.20.
Full textRoman-Flores, Heriberto, and Yurilev Chalco-Cano. "Transitivity of interval and fuzzy-interval extensions of interval functions." In 2015 Conference of the International Fuzzy Systems Association and the European Society for Fuzzy Logic and Technology (IFSA-EUSFLAT-15). Paris, France: Atlantis Press, 2015. http://dx.doi.org/10.2991/ifsa-eusflat-15.2015.203.
Full textYao, Yiyu. "Interval sets and interval-set algebras." In 2009 8th IEEE International Conference on Cognitive Informatics (ICCI). IEEE, 2009. http://dx.doi.org/10.1109/coginf.2009.5250723.
Full textKwon, Junseok, and Kyoung Mu Lee. "Interval Tracker: Tracking by Interval Analysis." In 2014 IEEE Conference on Computer Vision and Pattern Recognition (CVPR). IEEE, 2014. http://dx.doi.org/10.1109/cvpr.2014.447.
Full textLi, Xiu-hai. "Interval Cloud Model and Interval Cloud Generator." In 2010 Second Global Congress on Intelligent Systems (GCIS). IEEE, 2010. http://dx.doi.org/10.1109/gcis.2010.174.
Full textChuang, Chen-Chia, Chin-Wen Li, Chih-Ching Hsiao, Shun-Feng Su, and Jin-Tsong Jeng. "Robust interval support vector interval regression networks for interval-valued data with outliers." In 2014 Joint 7th International Conference on Soft Computing and Intelligent Systems (SCIS) and 15th International Symposium on Advanced Intelligent Systems (ISIS). IEEE, 2014. http://dx.doi.org/10.1109/scis-isis.2014.7044510.
Full textPinhanez, Claudio S., Kenji Mase, and Aaron Bobick. "Interval scripts." In the SIGCHI conference. New York, New York, USA: ACM Press, 1997. http://dx.doi.org/10.1145/258549.258758.
Full textPeschlow, Patrick, Peter Martini, and Jason Liu. "Interval Branching." In 2008 ACM/IEEE/SCS Workshop on Principles of Advanced and Distributed Simulation ( PADS). IEEE, 2008. http://dx.doi.org/10.1109/pads.2008.8.
Full textChou, Pai, and Gaetano Borriello. "Interval scheduling." In the 32nd ACM/IEEE conference. New York, New York, USA: ACM Press, 1995. http://dx.doi.org/10.1145/217474.217571.
Full textMockus, Audris, and David Weiss. "Interval quality." In the 13th international conference. New York, New York, USA: ACM Press, 2008. http://dx.doi.org/10.1145/1368088.1368190.
Full textReports on the topic "Interval"
Chiaro, P. J. Jr. Calibration interval technical basis document. Office of Scientific and Technical Information (OSTI), September 1998. http://dx.doi.org/10.2172/304106.
Full textABDURRAHAM, N. M. Interval estimation for statistical control. Office of Scientific and Technical Information (OSTI), August 2002. http://dx.doi.org/10.2172/808232.
Full textThompson, Andrew A. Interval Scales From Paired Comparisons. Fort Belvoir, VA: Defense Technical Information Center, May 2012. http://dx.doi.org/10.21236/ada568737.
Full textS. Kuzio. Probability Distribution for Flowing Interval Spacing. Office of Scientific and Technical Information (OSTI), May 2001. http://dx.doi.org/10.2172/837138.
Full textS. Kuzio. Probability Distribution for Flowing Interval Spacing. Office of Scientific and Technical Information (OSTI), September 2004. http://dx.doi.org/10.2172/838653.
Full textLoui, Ronald, Jerome Feldman, Henry Kyburg, and Jr. Interval-Based Decisions for Reasoning Systems. Fort Belvoir, VA: Defense Technical Information Center, January 1989. http://dx.doi.org/10.21236/ada250540.
Full textMcAllester, David A., Pascal Van Hentenryck, and Deepak Kapur. Three Cuts for Accelerated Interval Propagation. Fort Belvoir, VA: Defense Technical Information Center, May 1995. http://dx.doi.org/10.21236/ada298215.
Full textParks, A. D. Interval Graphs and Hypergraph Acyclicity Degree. Fort Belvoir, VA: Defense Technical Information Center, June 1991. http://dx.doi.org/10.21236/ada241458.
Full textMorozov. METHOD OF INTERVAL EXOGENOUS RESPIRATORY HYPOXIC TRAINING. Federal State Budgetary Educational Establishment of Higher Vocational Education "Povolzhskaya State Academy of Physical Culture, Sports and Tourism" Naberezhnye Chelny, December 2013. http://dx.doi.org/10.14526/42_2013_14.
Full textMalkin, G., and A. Harkin. TFTP Timeout Interval and Transfer Size Options. RFC Editor, March 1995. http://dx.doi.org/10.17487/rfc1784.
Full text