Статті в журналах: "Interval"

1

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.

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2

Lodwick, 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.

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3

Kleinman, 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.

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Accurate timing is critical for a wide range of cognitive processes and behaviors. In addition, complex environments frequently necessitate the simultaneous timing of multiple intervals, and behavioral performance in concurrent timing can constrain formal models of timing behavior and provide important insights into the corresponding neural mechanisms. However, the accuracy of such concurrent timing has not been rigorously examined. We developed a novel behavioral paradigm in which rhesus monkeys were incentivized to time two independent intervals. The onset asynchrony of two overlapping intervals varied randomly, thereby discouraging the animals from adopting any habitual responses. We found that only the first response for each interval was strongly indicative of the internal timing of that interval, consistent with previous findings and a two-stage model. In addition, the temporal precision of the first response was comparable in the single-interval and concurrent-interval conditions, although the first saccade to the second interval tended to occur sooner than in the single-interval condition. Finally, behavioral responses during concurrent timing could be well accounted for by a race between two independent stochastic processes resembling those in the single-interval condition. The fact that monkeys can simultaneously monitor and respond to multiple temporal intervals indicates that the neural mechanisms for interval timing must be sufficiently flexible for concurrent timing.

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4

Perlman, 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.

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Six Javanese and six Western musicians performed a magnitude-estimation task using 36 melodic intervals ranging from 60 to 760 cents at 20-cent increments. Several musicians displayed well-defined regions of confusion in which a range of intervals was assigned approximately equal magnitude estimates. The results suggest that these listeners assimilate the intervals to a set of internal interval standards. No evidence for assimilation was found for other musicians in both groups, some of whom made highly accurate estimates. For the Javanese musicians who showed assimilation to internal interval standards, the regions corresponded to the two Javanese tuning systems, slendro and pelog. For the Western musicians, the regions corresponded to the equal-tempered scale. The relatively wider regions of confusion for the Javanese musicians may reflect the greater variability of intonation in Java. In addition, the Javanese musicians seemed able to choose between internal interval standards based on the two tuning systems.

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5

Kahraman, 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.

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Abstract Confidence intervals are useful tools for statistical decision-making purposes. In case of incomplete and vague data, fuzzy confidence intervals can be used for decision making under uncertainty. In this paper, we develop interval-valued intuitionistic fuzzy (IVIF) confidence intervals for population mean, population proportion, differences in means of two populations, and differences in proportions of two populations. The developed IVIF intervals can be used in cases of both finite and infinite population sizes. The developed fuzzy confidence intervals are equivalent decision-making tools to fuzzy hypothesis tests. We apply the proposed confidence intervals to the differences in the mean lives and failure proportions of two types of radiators used in automobiles, and a sensitivity analysis is given to check the robustness of the decisions.

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6

Blokh, 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.

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7

McClaskey, 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.

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8

Cui, 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.

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This paper compares classic (continuous) fatigue tests and fatigue tests carried out with time intervals of no stress in rock salt using a multifunctional testing machine and acoustic emission equipment. The results show that time intervals of no stress have a strong impact on the fatigue activity of rock salt. In fatigue tests with intervals, the residual strain in circles following an interval (α circles) is generally larger than that in circles before the intervals (β circles). The insertion of a time interval with no stress in the fatigue process accelerates the accumulation of residual strain: the longer the interval, the faster the residual strain accumulates during the fatigue process and the shorter the fatigue life of the rock salt. α circles produce a greater number of acoustic emission counts than β circles, which demonstrates that residual stress leads to internal structural adjustment of rock salt on a mesoscopic scale. During intervals of no stress, acoustic emission activity becomes more active in α circles because of reverse softening caused by the Bauschinger effect, which accelerates the accumulation of plastic deformation. A qualitative relationship between the accumulated damage variable and the time interval is established. A threshold in the duration of the time interval exists (around 900 s).

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9

Repp, 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.

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Several interesting studies in the literature have demonstrated that a temporal interval coinciding with or following a rapid sequence of auditory stimuli is subjectively lengthened relative to a baseline interval without such rapid auditory stimulation (RAS). It has also been found that an interval preceding RAS is subjectively shortened. These effects have been attributed to acceleration of an internal pacemaker by RAS. The present study used musically trained participants in two experiments, similar to some reported in the literature. In Experiment 1, rapid chromatic scales preceded, followed, or intervened between two empty intervals that had to be compared. In Experiment 2, a series of comparison intervals, each preceded by a series of rapidly repeated tones, had to be compared to a memorized standard interval. Neither experiment yielded any effects of RAS relative to a control condition without RAS. These negative results raise questions about the conditions under which RAS affects interval judgment, and whether pacemaker acceleration is the correct explanation for these effects when they do occur.

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10

Bhattacharya, 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.

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11

CAMELIER, RICARDO, and CARLOS GUTIERREZ. "Affine interval exchange transformations with wandering intervals." Ergodic Theory and Dynamical Systems 17, no. 6 (December 1997): 1315–38. http://dx.doi.org/10.1017/s0143385797097666.

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12

Kurniaman, Otang, and Muhammad Nailul Huda. "PENERAPAN STRATEGI BERCERITA UNTUK MENINGKATKAN KETERAMPILAN MENYIMAK SISWA KELAS III SD MUHAMADIYAH 6 PEKANBARU." Primary: Jurnal Pendidikan Guru Sekolah Dasar 7, no. 2 (October 30, 2018): 249. http://dx.doi.org/10.33578/jpfkip.v7i2.6284.

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The background of this study is the low listening skills of third-grade students of SD Muhammadiyah 6 Pekanbaru. This researchis a classroom action research, which is carried out by applying storytelling strategies. The results of the study stated that thelistening skills of students had increased in cycle 1 meeting 1 number of students who scored between 80-100 totaling 12students, on the internal score 60-79 totaled 3 students, at an interval of 40-59 amounted to 4 students, at intervals of 20 -39numbered 2 students and in the interval 0-29 there were 0 students. Whereas in cycle 1 meeting 2, the number of students whoobtained grades between 80-100 totaled 13 students, in the internal score 60-79 totaled 10 students, at intervals of 40-59amounted to 0 students, at intervals of 20-39 amounted to 0 students and at interval 0-29 contains 0 students. In cycle 2 meeting1 listening skills increased the number of students who got grades between 80-100 totaling 15 students, in the internal score 60-79 totaled 8 students, at intervals of 40-59 amounted to 0 students, at intervals of 20-39 amounted to 0 students and in theinterval 0-29 there are 0 students. Whereas in the second cycle of meeting 2 the number of students who got a score between 80-100 totaled 19 students, in the internal score 60-79 totaled 4 students, at intervals of 40-59 amounted to 0 students, at intervalsof 20-39 amounted to 0 students and at intervals 0-29 consists of 0 students. Based on these values, it can be concluded that thestorytelling strategy can improve the listening skills of third-grade students of SD Muhammadiyah 6 Pekanbaru

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13

Styra, Dmitrijus, Algirdas Čiučelis, Ana Usovaitė та Jovita Damauskaitė. "ON POSSIBILITY OF SHORT‐TERM PROGNOSIS OF CYCLONIC ACTIVITY AFTER‐EFFECTS IN VILNIUS BY VARIATION OF HARD COSMIC RAY FLUX/CIKLONŲ AKTYVUMO PASEKMIŲ TRUMPALAIKĖS PROGNOZĖS GALIMYBĖS VILNIAUS MIESTE PAGAL KIETOSIOS KOSMINĖS SPINDULIUOTĖS SRAUTO VARIACIJAS/ О ВОЗМОЖНОСТИ КРАТКОВРЕМЕННОГО ПРОГНОЗА ПОСЛЕДСТВИЙ ЦИКЛОНИЧЕСКОЙ АКТИВНОСТИ В ВИЛЬНЮСЕ ПО КОЛЕБАНИЯМ ПОТОКА ЖЕСТКОГО ИЗЛУЧЕНИЯ". JOURNAL OF ENVIRONMENTAL ENGINEERING AND LANDSCAPE MANAGEMENT 16, № 4 (31 грудня 2008): 159–67. http://dx.doi.org/10.3846/1648-6897.2008.16.159-167.

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Analysis of hard cosmic ray flux (HCRF) variation at an energy interval 1.2—1.6 MeV was carried out in Vilnius. Connection between HCRF decrease at the mentioned energy interval and the minimum atmospheric pressure in 3–6 days is defined. This phenomenon is registered from 8 up to 13 hours. According to the time interval of HCRF decrease, for instance 8–9 and 9–10 hours, the minimum pressure in Vilnius takes place in 3^1 days, and at time intervals 11–12, and 12–13 hours ‐ in 5–6 days. Realization of this prognosis at one of the presented time intervals was 56–67% in 2002–2003. The same investigation results, with the assumption of atmospheric pressure decrease from 1005 hPa and less, showed a high efficiency of prognosis of the minimum pressure in Vilnius at all the time intervals during 6 days ‐ 92%, and 82% in 2002 and 2003, correspondingly. Santrauka Atlikta kietosios kosminės spinduliuotės srauto variacijų analizė energijų intervale 1,2–1,6 MeV Vilniaus mieste. Nustatytas ryšis tarp kietosios kosminės spinduliuotės srauto (KKSS) sumažėjimo šiame intervale ir atmosferos slėgio kitimo, kuris įvyks per 3–4 paras. Toks ryšis registruojamas tik nuo 8 val. iki 13 val. KKSS mažėjimas Vilniaus mieste priklauso nuo laiko intervalo, pvz., nuo 8–9 ir 9–10 val. slėgis sumažėja po 3–4 dienų; 11–12 ir 12–13 val. slėgis sumažėja po 5–6 dienų. Prognozės efektyvumas viename iš laiko intervalų buvo nuo 56–67 % 2002–2003 m. atitinkamai. To paties tyrimo rezultatai, įskaitant ir atmosferos slėgio mažėjimą nuo 1005 hPa ir mažiau, parodė aukštą prognozės efektyvumą visuose laiko intervaluose per 6 dienas – 92 % ir 82 % 2002–2003 metais atitinkamai. Резюме Проведен анализ колебаний потока жесткого космического излучения (ПЖКИ) в энергетическом интервале 1,2– 1,6 МэВ в г. Вильнюсе. Установлена связь между падением ПЖКИ в этом энергетическом интервале и изменением атмосферного давления, которое произойдет через 3–6 суток. Такая связь регистрируется только с 8 час. до 13 часов. В зависимости от интервала времени регистрации падения ПЖКИ, в частности, 8–9 часов, 9–10 часов – наименьшее давление в г. Вильнюсе образуется через 3–4 суток, а 11–12 часов и 12–13 часов – через 5–6 суток. Выполнимость такого прогноза по падению ПЖКИ в одном временном интервале в среднем соответствовала 56– 67% в 2002–2003 гг. Результаты аналогичного исследования с учетом того, что атмосферное давление уменьшается, начиная с 1005 гПа и ниже, показали высокую эффективность прогноза формирования наименьшего давления в г. Вильнюсе по падению ПЖКИ во всех временных интервалах в течение 6 суток – 92% и 82% в 2002 и 2003 гг. соответственно.

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14

Ingham, Roger J., Anne K. Cordes, and Merrilyn L. Gow. "Time-Interval Measurement of Stuttering." Journal of Speech, Language, and Hearing Research 36, no. 3 (June 1993): 503–15. http://dx.doi.org/10.1044/jshr.3603.503.

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This paper reports the results of two experiments that investigated interval-by-interval inter and intrajudge agreement for stuttered and nonstuttered speech intervals (4.0 sec). The first experiment demonstrated that interval-by-interval interjudge agreement could be significantly improved, and to satisfactory levels, by training judges to discriminate between experimenter-agreed intervals of stuttered and nonstuttered speech. The findings also showed that, independent of training, judges with relatively high intrajudge agreement also showed relatively higher interjudge agreement. The second experiment showed that interval-by-interval interjudge agreement was not significantly different if judges rated 4-sec speech intervals from different samples under three conditions: in random order, separated by 5-sec recording intervals; in correct order, also separated by 5-sec recording intervals; or after brief judgment signals that occurred every 4 sec during continuous samples. The implications of these findings for stuttering measurement are discussed.

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15

Campbell, Jack P., Matthew C. Gratton, Joseph A. Salomone, Daniel J. Lindholm, and William A. Watson. "System Implications of the Ambulance Arrival-to-Patient Contact Interval on Response Interval Compliance." Prehospital and Disaster Medicine 9, no. 4 (December 1994): 230–32. http://dx.doi.org/10.1017/s1049023x00041455.

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AbstractBackground:Background: In some emergency medical services (EMS) system designs, response time intervals are mandated with monetary penalties for noncompliance. These times are set with the goal of providing rapid, definitive patient care. The time interval of vehicle at scene-to-patient access (VSPA) has been measured, but its effect on response time interval compliance has not been determined.Purpose:To determine the effect of the VSPA interval on the mandated code 1 (<9 min) and code 2 (<13 min) response time interval compliance in an urban, public-utility model system.Methods:A prospective, observational study used independent third-party riders to collect the VSPA interval for emergency life-threatening (code 1) and emergency nonlife-threatening (code 2) calls. The VSPA interval was added to the 9-1-1 call-to-dispatch and vehicle dispatch-to-scene intervals to determine the total time interval from call received until paramedic access to the patient (9-1-1 call-to-patient access). Compliance with the man dated response time intervals was determined using the traditional time intervals (9-1-1 call-to-scene) plus the VSPA time intervals (9-1-1 call-to-patient access). Chi-square was used to determine statistical significance.Results:Of the 216 observed calls, 198 were matched to the traditional time intervals. Sixty three were code 1, and 135 were code 2. Of the code 1 calls, 90.5% were compliant using 9-1-1 call-to-scene intervals dropping to 63.5% using 9-1-1 call-to-patient access intervals (p<0.0005). Of the code 2 calls, 94.1% were compliant using 9-1-1 call-to-scene intervals. Compliance decreased to 83.7% using 9-1-1 call-to-patient access intervals (p = 0.012).Conclusion:The addition of the VSPA interval to the traditional time intervals impacts system response time compliance. Using 9-1-1 call-to-scene compliance as a basis for measuring system performance underestimates the time for the delivery of definitive care. This must be considered when response time interval compliances are defined.

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16

Yost, William A., and William P. Shofner. "Regular interval stimuli: Are higher‐order intervals necessary?" Journal of the Acoustical Society of America 102, no. 5 (November 1997): 3162. http://dx.doi.org/10.1121/1.420753.

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17

Kee, F., D. Gorman, and W. Odling-Smee. "Confidence intervals and interval cancers … needles and haystacks?" Public Health 106, no. 1 (January 1992): 29–35. http://dx.doi.org/10.1016/s0033-3506(05)80326-9.

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18

Aggarwal, Alok, and Takeshi Tokuyama. "Consecutive interval query and dynamic programming on intervals." Discrete Applied Mathematics 85, no. 1 (June 1998): 1–24. http://dx.doi.org/10.1016/s0166-218x(98)00021-3.

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19

Hinton, Sean C., and Warren H. Meck. "The ‘internal clocks’ of circadian and interval timing." Endeavour 21, no. 1 (January 1997): 3–8. http://dx.doi.org/10.1016/s0160-9327(96)10022-3.

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20

Balcı, Fuat. "Interval Timing: Stopping the Internal Stopwatch by Photostimulation." Current Biology 27, no. 24 (December 2017): R1312—R1314. http://dx.doi.org/10.1016/j.cub.2017.10.072.

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21

Shuchat, Alan, Randy Shull, and Ann N. Trenk. "Unit Interval Orders of Open and Closed Intervals." Order 33, no. 1 (May 7, 2015): 85–99. http://dx.doi.org/10.1007/s11083-015-9354-z.

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22

Severini, Thomas A. "Bayesian Interval Estimates Which are Also Confidence Intervals." Journal of the Royal Statistical Society: Series B (Methodological) 55, no. 2 (January 1993): 533–40. http://dx.doi.org/10.1111/j.2517-6161.1993.tb01921.x.

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23

Rautenbach, Dieter, and Jayme L. Szwarcfiter. "Unit Interval Graphs of Open and Closed Intervals." Journal of Graph Theory 72, no. 4 (June 18, 2012): 418–29. http://dx.doi.org/10.1002/jgt.21650.

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24

Jian, Yuan. "Extremal eigenvalue intervals of symmetric tridiagonal interval matrices." Numerical Linear Algebra with Applications 24, no. 2 (January 16, 2017): e2083. http://dx.doi.org/10.1002/nla.2083.

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25

Fishburn, Peter C. "Interval graphs and interval orders." Discrete Mathematics 55, no. 2 (July 1985): 135–49. http://dx.doi.org/10.1016/0012-365x(85)90042-1.

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26

Batanero, Carmen, and Mª del Mar López-Martín. "Conocimiento del Intervalo de Confianza por Futuros Profesores de Bachillerato." Jornal Internacional de Estudos em Educação Matemática 13, no. 4 (February 11, 2021): 363–73. http://dx.doi.org/10.17921/2176-5634.2020v13n4p363-373.

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ResumenEl objetivo de este trabajo fue evaluar el conocimiento común y especializado del contenido de los futuros profesores españoles de bachillerato sobre el intervalo de confianza. Para lograr tal fin se propuso a un grupo de 73 futuros profesores un problema abierto sobre intervalo de confianza, similar a los propuestos en cursos anteriores a los estudiantes de Bachillerato en las pruebas de acceso a la universidad. Además, se les preguntó cómo explicarían a un estudiante el significado del intervalo de confianza y sus propiedades. Utilizando una metodología cualitativa de análisis de contenido, se estudia el planteamiento, cálculo, interpretación y definición del intervalo y las propiedades que recuerdan. Aunque la mayor parte de los participantes en el estudio plantea y calcula correctamente el intervalo, sólo el 28,8% de los futuros profesores lo interpreta correctamente. Se encuentran interpretaciones deterministas o propias a la metodología bayesiana, similares a las descritas en investigaciones con estudiantes. Otros o no proporcionan una interpretación. Pocos participantes fueron capaces de definir correctamente el intervalo de confianza cuando se les pide explicar a un estudiante su significado y recuerdan pocas propiedades del mismo. Se concluye la necesidad de reforzar el conocimiento del contenido sobre intervalo de confianza en estos futuros profesores. Palabras-clave: Intervalo de Confianza. Conocimiento del Contenido. Futuros Profesores. Bachillerato. Evaluación. AbstractThe aim of this research was to assess prospective high school teachers’ common and specialized content knowledge of confidence intervals. To achieve this aim, we proposed to 73 prospective teachers an open problem similar to those proposed to high school students in the previous years at the entrance to university tests. Besides, participants were asked to describe how they would explain the concept and its properties to a student. Using the qualitative methodology of content analysis we study the setting, computation, interpretation and definition of confidence interval and its properties. Although most participants correctly set and computed the confidence interval, only 28.8% of them made a correct interpretation of the same. Deterministic and Bayesian interpretations, similar to those described in previous research with students arose or there was no interpretation. Few participants defined correctly the interval when asked how they would explain the topic to a student; additionally, only a few properties of the interval were remembered. We conclude the need to reinforce the content knowledge of confidence intervals in prospective teachers. Keywords: Confidence Interval. Content Knowledge. Prospective Teachers. High School. Assessment.

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27

Zhao, Zhi Li, Wei Li, Chong Yang Deng, and Hu Ping Wang. "A Generalized Cholesky Decomposition for Interval Matrix." Advanced Materials Research 479-481 (February 2012): 825–28. http://dx.doi.org/10.4028/www.scientific.net/amr.479-481.825.

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Using the generalized interval arithmetic we give a generalized cholesky decomposition. Generalized intervals (intervals whose bounds are not constrained to be increasingly ordered) extend classical intervals providing better algebraic properties. In particular, the generalized interval arithmetic is a group for addition and for multiplication of zero free intervals. These properties allow one constructing a cholesky decomposition of a generalized interval matrix A: the computed generalized interval matrix L satisfy A=LLTwith equality instead of the weaker inclusion obtained in the context of classical intervals.

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28

muzaki, muzaki, herman afrian, and Lalu Erpan Suryadi. "Pengaruh Latihan Interval (Interval Training) Terhadap Peningkatan Vo2max Tim Gama Fc Pancor 2017." Jurnal Porkes 1, no. 1 (June 30, 2018): 1–6. http://dx.doi.org/10.29408/porkes.v1i1.1080.

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29

Cordes, Anne K., and Roger J. Ingham. "Time-Interval Measurement of Stuttering." Journal of Speech, Language, and Hearing Research 37, no. 4 (August 1994): 779–88. http://dx.doi.org/10.1044/jshr.3704.779.

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The study reported in this article used a binary forced-choice judgment procedure to investigate the effects of sample duration on observers’ judgments of stuttering. Two groups of judges, differing in their previous experience with stuttering, categorized 270 speech intervals as stuttered or nonstuttered; the intervals were drawn from 30 persons who stuttered and ranged from 1 sec to 15 sec in duration. Results showed that judgments were consistently related to interval duration, with shorter intervals significantly more likely than longer intervals to be labeled nonstuttered. Interjudge agreement levels, however, were largely unaffected by the different interval durations for most speakers and for both judge groups, with the exception of the longest and shortest intervals drawn from speakers evidencing the mildest and most severe stuttering. An interval duration in the 3- to 5-sec region appeared to attract the most satisfactory level of agreement. The implications of these findings for interval-based clinical and experimental measurements of stuttering are discussed.

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30

Choi, Jae. "Interval." Iowa Review 40, no. 3 (December 2010): 74. http://dx.doi.org/10.17077/0021-065x.6946.

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31

Finkel, Donald. "Interval." Grand Street 8, no. 1 (1988): 45. http://dx.doi.org/10.2307/25007164.

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32

Stobb, William. "Interval." Colorado Review 42, no. 1 (2015): 158–59. http://dx.doi.org/10.1353/col.2015.0004.

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33

Goodyer, Allan V. N. "The abnormal mechanical strength–interval curve of hypoxic rabbit papillary muscle." Canadian Journal of Physiology and Pharmacology 66, no. 7 (July 1, 1988): 907–16. http://dx.doi.org/10.1139/y88-148.

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The effect of hypoxic injury on the mechanical strength–interval curve of rabbit myocardium was studied, using an isolated left ventricular thick papillary muscle preparation. Histochemical staining disclosed a central core of injured tissue enveloped by viable muscle which was sustained by aerobic metabolism, being unaffected by iodoacetate. Mechanical strength–interval curves were derived by measurement of developed isometric tension during various pacing protocols. The phasic recovery of contractile tension, described by the strength–internal curve, was markedly prolonged and partly responsible for reduced tension development. Parameters of the strength–interval curve were determined by linear and monoexponential curve-fitting procedures during various experimental interventions. These parameters indicated that the contractility recovery rate was not altered by acidosis or propranolol, but the early phase of the strength–interval curve (at short test intervals) was augmented by propranolol, and the plateau of the full curve was depressed by acidosis. These observations emphasize that the strength–interval curve must be considered in any study of the effect of a drug or other intervention on the contractility of hypoxic myocardium.

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34

Polyak, B. T., and S. A. Nazin. "Interval solutions for interval algebraic equations." Mathematics and Computers in Simulation 66, no. 2-3 (June 2004): 207–17. http://dx.doi.org/10.1016/j.matcom.2003.11.006.

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35

Coffman, Jr, Leopold Flatto, and Predrag Jelenković. "Interval packing: the vacant interval distribution." Annals of Applied Probability 10, no. 1 (February 2000): 240–57. http://dx.doi.org/10.1214/aoap/1019737671.

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36

Boyadzhiyska, Simona, Garth Isaak, and Ann N. Trenk. "Interval orders with two interval lengths." Discrete Applied Mathematics 267 (August 2019): 52–63. http://dx.doi.org/10.1016/j.dam.2019.06.021.

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37

Zhang, Shu Guang, and Su Huan Chen. "Static Interval Optimization for Structures with Interval Parameters and Interval Loading." Advanced Materials Research 443-444 (January 2012): 738–44. http://dx.doi.org/10.4028/www.scientific.net/amr.443-444.738.

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A static interval optimization method for structures was developed. The matrices of structures with interval parameters are given. Combining the interval extension of functions with the perturbation theory of static analysis, the method for interval static analysis of the structure with interval parameters and interval loading was derived. The Interval optimization problem was transformed into a corresponding deterministic one. Because the mid-values and the uncertainties of the interval parameters can be selected as the design variables, more information of the optimization results can be obtained by the present method than that obtained by the deterministic one. The numerical results show that the present method is valid.

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38

Dimuro, Graçaliz Pereira, Benjamín Callejas Bedregal, Regivan Hugo Nunes Santiago, and Renata Hax Sander Reiser. "Interval additive generators of interval t-norms and interval t-conorms." Information Sciences 181, no. 18 (September 2011): 3898–916. http://dx.doi.org/10.1016/j.ins.2011.05.003.

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39

Gao, Zuo Feng, Chao Han, and Jing Wu. "Interval Banzhaf Value for Cooperative Interval Games on Augmenting Systems." Advanced Materials Research 1030-1032 (September 2014): 1726–32. http://dx.doi.org/10.4028/www.scientific.net/amr.1030-1032.1726.

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This paper focuses on the Banzhaf value for cooperative games where the set of players is restraint on augmenting systems and the coalition values are compact intervals of real numbers. The interval Banzhaf value for cooperative interval games on augmenting systems is put forward on the basis of corresponding axiomatic system and operations of interval numbers. Moreover, some properties of the interval Banzhaf value are given. Finally, a practical example is offered to illustrate the validity and feasibility of this method on these kinds of cooperative interval games.

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40

Chaika, Jon, and Alex Eskin. "Möbius disjointness for interval exchange transformations on three intervals." Journal of Modern Dynamics 14, no. 1 (2019): 55–86. http://dx.doi.org/10.3934/jmd.2019003.

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41

Sinova, Beatriz, and Stefan Van Aelst. "A spatial-type interval-valued median for random intervals." Statistics 52, no. 3 (May 4, 2018): 479–502. http://dx.doi.org/10.1080/02331888.2018.1435658.

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42

Ferrari, Luca. "Dyck Algebras, Interval Temporal Logic, and Posets of Intervals." SIAM Journal on Discrete Mathematics 30, no. 4 (January 2016): 1918–37. http://dx.doi.org/10.1137/15m1016904.

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43

Gutierrez, C., S. Lloyd, and B. Pires. "Affine interval exchange transformations with flips and wandering intervals." Proceedings of the American Mathematical Society 137, no. 04 (November 3, 2008): 1439–45. http://dx.doi.org/10.1090/s0002-9939-08-09718-9.

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44

Chen, Ke, Yuanyuan Wang, Xiaopeng Yu, Haishuo Wang, Rui Wu, and Hongmei Zheng. "Electrical internal quantum efficiency improved by interval doping method." Applied Optics 57, no. 34 (November 30, 2018): 10072. http://dx.doi.org/10.1364/ao.57.010072.

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45

Hinton, Sean C., and Warren H. Meck. "The ‘internal clocks’ of circadian and interval timing ( erratum )." Endeavour 21, no. 2 (1997): 82–87. http://dx.doi.org/10.1016/s0160-9327(97)01043-0.

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46

Diamond, Phil. "Interval-valued random functions and the kriging of intervals." Mathematical Geology 20, no. 3 (April 1988): 145–65. http://dx.doi.org/10.1007/bf00890251.

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47

Levin, V. I. "Ordering of Intervals and Optimization Problems with Interval Parameters." Cybernetics and Systems Analysis 40, no. 3 (May 2004): 316–24. http://dx.doi.org/10.1023/b:casa.0000041988.20251.d7.

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48

Inuiguchi, Masahiro, and Yasufumi Kume. "Goal programming problems with interval coefficients and target intervals." European Journal of Operational Research 52, no. 3 (June 1991): 345–60. http://dx.doi.org/10.1016/0377-2217(91)90169-v.

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49

Santiago, Regivan, Flaulles Bergamaschi, Humberto Bustince, Graçaliz Dimuro, Tiago Asmus, and José Antonio Sanz. "On the Normalization of Interval Data." Mathematics 8, no. 11 (November 23, 2020): 2092. http://dx.doi.org/10.3390/math8112092.

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The impreciseness of numeric input data can be expressed by intervals. On the other hand, the normalization of numeric data is a usual process in many applications. How do we match the normalization with impreciseness on numeric data? A straightforward answer is that it is enough to apply a correct interval arithmetic, since the normalized exact value will be enclosed in the resulting “normalized” interval. This paper shows that this approach is not enough since the resulting “normalized” interval can be even wider than the input intervals. So, we propose a pair of axioms that must be satisfied by an interval arithmetic in order to be applied in the normalization of intervals. We show how some known interval arithmetics behave with respect to these axioms. The paper ends with a discussion about the current paradigm of interval computations.

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50

BRANZEI, R., S. TIJS, and S. Z. ALPARSLAN GÖK. "HOW TO HANDLE INTERVAL SOLUTIONS FOR COOPERATIVE INTERVAL GAMES." International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems 18, no. 02 (April 2010): 123–32. http://dx.doi.org/10.1142/s0218488510006441.

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Uncertainty accompanies almost every situation in our lives and it influences our decisions. On many occasions uncertainty is so severe that we can only predict some upper and lower bounds for the outcome of our (collaborative) actions, i.e., payoffs lie in some intervals. Cooperative interval games have been proved useful for solving reward/cost sharing problems in situations with interval data in a cooperative environment. In this paper we propose two procedures for cooperative interval games. Both transform an interval allocation, i.e., a payoff vector whose components are compact intervals of real numbers, into a payoff vector (whose components are real numbers) when the value of the grand coalition becomes known (at once or in multiple stages). The research question addressed here is: How to determine for each player his/her/its payoff generated by cooperation within the grand coalition – in the promised range of payoffs to establish such cooperation – after the uncertainty on the payoff for the grand coalition is resolved? This question is an important one that deserves attention both in the literature and in game practice.

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