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Artykuły w czasopismach na temat „Criterion-Based”

Autor: Grafiati

Data publikacji: 3 czerwca 2025

Data aktualizacji: 31 lipca 2025

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1

Shaw, C. D. "Criterion based audit." BMJ 300, no. 6725 (1990): 649–51. http://dx.doi.org/10.1136/bmj.300.6725.649.

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2

Li, Xin. "A new stress-based multiaxial high- cycle fatigue damage criterion." Functional materials 25, no. 2 (2018): 406–12. http://dx.doi.org/10.15407/fm25.02.406.

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3

Maity, Arnab Kumar, Sanjib Basu, and Santu Ghosh. "Bayesian criterion‐based variable selection." Journal of the Royal Statistical Society: Series C (Applied Statistics) 70, no. 4 (2021): 835–57. http://dx.doi.org/10.1111/rssc.12488.

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4

Bayarri, M. J., James O. Berger, Woncheol Jang, Surajit Ray, Luis R. Pericchi, and Ingmar Visser. "Prior-based Bayesian information criterion." Statistical Theory and Related Fields 3, no. 1 (2019): 2–13. http://dx.doi.org/10.1080/24754269.2019.1582126.

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5

Skibicki, Dariusz. "Fatigue Criterion Based on the Novoshilov Criterion for Non-proportional Loadings*." Materials Testing 53, no. 6 (2011): 327–31. http://dx.doi.org/10.3139/120.110232.

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6

Pereira, Anne G., Majka Woods, Andrew P. J. Olson, Suzanne van den Hoogenhof, Briar L. Duffy, and Robert Englander. "Criterion-Based Assessment in a Norm-Based World." Academic Medicine 93, no. 4 (2018): 560–64. http://dx.doi.org/10.1097/acm.0000000000001939.

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7

SuQun Cao, QuanYin Zhu, BoKui Li, Rong Gao, and HaiFei Zhai. "Fuzzy Fisher Criterion based Edge Detection." International Journal of Digital Content Technology and its Applications 5, no. 8 (2011): 381–88. http://dx.doi.org/10.4156/jdcta.vol5.issue8.44.

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8

Packer, M. E., B. J. Scott, and R. M. Watson. "Criterion based audit in prosthetic dentistry." British Dental Journal 174, no. 8 (1993): 285–89. http://dx.doi.org/10.1038/sj.bdj.4808156.

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9

Philpot, Timothy A., Kenneth J. Fridley, and David V. Rosowsky. "Energy‐Based Failure Criterion for Wood." Journal of Materials in Civil Engineering 6, no. 4 (1994): 578–94. http://dx.doi.org/10.1061/(asce)0899-1561(1994)6:4(578).

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10

Fawaz, Kassem, Fadi Zaraket, Wes Masri, and Hamza Harkous. "PBCOV: a property-based coverage criterion." Software Quality Journal 23, no. 1 (2014): 171–202. http://dx.doi.org/10.1007/s11219-014-9237-3.

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11

Nagai, Isamu, Katsuyuki Takahashi, and Hirokazu Yanagihara. "Information criterion-based non-hierarchical clustering." International Journal of Knowledge Engineering and Soft Data Paradigms 6, no. 1 (2017): 1. http://dx.doi.org/10.1504/ijkesdp.2017.089504.

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12

Yanagihara, Hirokazu, Isamu Nagai, and Katsuyuki Takahashi. "Information criterion-based non-hierarchical clustering." International Journal of Knowledge Engineering and Soft Data Paradigms 6, no. 1 (2017): 1. http://dx.doi.org/10.1504/ijkesdp.2017.10010599.

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13

Rahaeifard, M., M. T. Ahmadian, and K. Firoozbakhsh. "A strain gradient based yield criterion." International Journal of Engineering Science 77 (April 2014): 45–54. http://dx.doi.org/10.1016/j.ijengsci.2013.12.008.

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14

Hilsenroth, Mark J., Jocelyn W. Charnas, Jennifer Zodan, and David L. Streiner. "Criterion-based training for Rorschach scoring." Training and Education in Professional Psychology 1, no. 2 (2007): 125–34. http://dx.doi.org/10.1037/1931-3918.1.2.125.

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15

Kumar, Pawan. "Load Characteristics of Electric System for Distributing Power on Locality Based Criterion." Bonfring International Journal of Power Systems and Integrated Circuits 4, no. 4 (2014): 39–42. http://dx.doi.org/10.9756/bijpsic.10335.

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16

Cao, Su Qun, and Yun Feng Bu. "Fuzzy Scatter Matrix Based Class Separability Criterion." Advanced Materials Research 179-180 (January 2011): 409–14. http://dx.doi.org/10.4028/www.scientific.net/amr.179-180.409.

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Scatter matrix based class separability criterion is commonly used in supervised feature extraction. But calculations of scatter matrixes depend on labeled data, so this criterion can not be used in unsupervised pattern. This paper presents a method to extend scatter matrix based class separability criterion to unsupervised pattern by fuzzy theory. The basic idea is to optimize the defined fuzzy Fisher criterion function to figure out fuzzy scatter matrixes in unsupervised pattern. Based on the obtained fuzzy between-class scatter matrix and fuzzy within-class scatter matrix, a novel class sep

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17

Jiang, Hua. "A failure criterion for rocks and concrete based on the Hoek-Brown criterion." International Journal of Rock Mechanics and Mining Sciences 95 (May 2017): 62–72. http://dx.doi.org/10.1016/j.ijrmms.2017.04.003.

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18

Wang, Sui, Zuliang Zhong, and Xinrong Liu. "Development of an Anisotropic Nonlinear Strength Criterion for Geomaterials Based on SMP Criterion." International Journal of Geomechanics 20, no. 3 (2020): 04019183. http://dx.doi.org/10.1061/(asce)gm.1943-5622.0001588.

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19

Cheein, Fernando. "Covariance-Based Measurement Selection Criterion for Gaussian-Based Algorithms." Entropy 15, no. 1 (2013): 287–310. http://dx.doi.org/10.3390/e15010287.

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20

Meyers, G. Douglas. "Using Criterion-Based and Reader-Based Peer-Review Sheets." Bulletin of the Association for Business Communication 51, no. 1 (1988): 35–39. http://dx.doi.org/10.1177/108056998805100114.

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21

Liu, Shi Hua, Xian Gang Liu, and Zhi Jian Sun. "A Skywave OTHR Adaptive Frequency Selection Method Based on Preliminary Criterion and Weighted Criterion." Advanced Materials Research 1061-1062 (December 2014): 974–77. http://dx.doi.org/10.4028/www.scientific.net/amr.1061-1062.974.

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A skywave radar adaptive frequency selection method based on the preliminary criterion and the weighted criterion is presented. In this method, according to the various operational tasks, the frequency selection criterion is divided into the preliminary criterion and the weighted criterion based on the characteristic of the targets. The adaptive frequency selection of the skywave radar is achieved by the weighted computed of the frequency selection criterion. The feasibility and availability is demonstrated by an example.

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22

Raof, Awring Maroof, Tariq Salman AL-Hadithi, and Namir Gh Al-Tawil. "DELIVERY CRITERION–BASED AUDITING SYSTEM AT TWO HEALTH FACILITIES IN ERBIL CITY-IRAQ." Journal of Sulaimani Medical College 2, no. 1 (2012): 9–16. http://dx.doi.org/10.17656/jsmc.10019.

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23

Ivanchenko, Aleхandr. "GRAPH ISOMORPHISM CRITERION BASED ON RESISTANCE DISTANCE." University News. North-Caucasian Region. Technical Sciences Series, no. 2 (June 2020): 13–18. http://dx.doi.org/10.17213/1560-3644-2020-2-13-18.

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24

Asadi, Farzin, and Nurettin Abut. "ITAE criterion based controller for buck converter." International Journal of ADVANCED AND APPLIED SCIENCES 4, no. 1 (2016): 15–22. http://dx.doi.org/10.21833/ijaas.2017.01.003.

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25

SUZUKI, Hideo, and Takao ENKAWA. "A Data Clustering Based on MDL Criterion." Japanese journal of applied statistics 22, no. 3 (1993): 117–32. http://dx.doi.org/10.5023/jappstat.22.117.

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26

Singer, Murray. "Strength-based criterion shifts in recognition memory." Memory & Cognition 37, no. 7 (2009): 976–84. http://dx.doi.org/10.3758/mc.37.7.976.

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27

Cone, Al L. "Low Tech/High Touch Criterion-Based Learning." Psychological Reports 63, no. 1 (1988): 203–7. http://dx.doi.org/10.2466/pr0.1988.63.1.203.

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92 students completed a criterion-based course in general psychology in which they spent 75% of class time teaching one another in small, permanently assigned groups using instructional objectives prepared by the instructor. Testing required 90% correct to avoid an alternative test (Form 2) at the next class. All took a standardized test for seniors majoring in psychology. Course grade was significantly correlated with scores on the standardized test. Students with grades of A achieved the 39th percentile for seniors after one semester of general psychology. Results are discussed in terms of t

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28

Tsallis, Constantino. "Generalized entropy-based criterion for consistent testing." Physical Review E 58, no. 2 (1998): 1442–45. http://dx.doi.org/10.1103/physreve.58.1442.

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29

Ayken, Taylan, and Jun-ichi Imura. "Diffusion Based Stopping Criterion for Distributed Optimization." IFAC Proceedings Volumes 47, no. 3 (2014): 10512–17. http://dx.doi.org/10.3182/20140824-6-za-1003.02730.

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30

Owston, Ronald D., and Curt Dudley-Marling. "A Criterion-Based Approach to Software Evaluation." Journal of Research on Computing in Education 20, no. 3 (1988): 234–44. http://dx.doi.org/10.1080/08886504.1988.10781838.

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31

Anderson, J. B. "Sequential decoding based on an error criterion." IEEE Transactions on Information Theory 38, no. 3 (1992): 987–1001. http://dx.doi.org/10.1109/18.135640.

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32

Liseo, Brunero. "Discussion on prior-based Bayes information criterion." Statistical Theory and Related Fields 3, no. 1 (2019): 22–23. http://dx.doi.org/10.1080/24754269.2019.1583630.

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33

Perreault, Judith A. "Criterion-based practice for the ET nurse." Journal of Wound, Ostomy and Continence Nursing 13, no. 3 (1986): 99–104. http://dx.doi.org/10.1097/00152192-198605000-00031.

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34

Cone, Al L. "Frequency of Testing in Criterion-Based Learning." Psychological Reports 67, no. 2 (1990): 396–98. http://dx.doi.org/10.2466/pr0.1990.67.2.396.

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35

Fensin, Saryu, George Gray, Neil Bourne, and Robert Hixson. "Microstructure Based Failure Criterion For Ductile Materials." EPJ Web of Conferences 183 (2018): 03005. http://dx.doi.org/10.1051/epjconf/201818303005.

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For ductile metals, the process of dynamic fracture occurs through nucleation, growth and coalescence of voids. The stress required to nucleate these voids is inferred from the velocimetry data (using the acoustic approach) and termed as the spall strength. This is a key parameter that is used to evaluate a material’s susceptibility to damage and failure. However, it is also well recognized that the dynamic parameters used to generate the shock state such as pulse duration, tensile strain-rate and peak stress coupled with material microstructure itself affect the material response in a complex

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36

Nihira, Mikio Albert. "The Value of Criterion-Based Surgical Education." Female Pelvic Medicine & Reconstructive Surgery 18, no. 5 (2012): 257–58. http://dx.doi.org/10.1097/spv.0b013e31826d2679.

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37

Schleifer-Kwan, Sarah Joy, Karen Carroll, and Marthe J. Moseley. "Developing criterion-based competencies for tele-ICU." Nursing Critical Care 9, no. 6 (2014): 10–13. http://dx.doi.org/10.1097/01.ccn.0000453473.73080.2c.

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38

Oliferuk, Wiera, and Michał Maj. "Plastic instability criterion based on energy conversion." Materials Science and Engineering: A 462, no. 1-2 (2007): 363–66. http://dx.doi.org/10.1016/j.msea.2006.02.465.

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39

Lu, Gui-Fu, Ganyi Tang, and Jian Zou. "Spare L1-norm-based maximum margin criterion." Journal of Visual Communication and Image Representation 38 (July 2016): 11–17. http://dx.doi.org/10.1016/j.jvcir.2016.02.004.

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40

Yang, Jie, Jiuwen Cao, Tianlei Wang, Anke Xue, and Badong Chen. "Regularized correntropy criterion based semi-supervised ELM." Neural Networks 122 (February 2020): 117–29. http://dx.doi.org/10.1016/j.neunet.2019.09.030.

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41

Schoenfeld, S. E., and T. W. Wright. "A failure criterion based on material instability." International Journal of Solids and Structures 40, no. 12 (2003): 3021–37. http://dx.doi.org/10.1016/s0020-7683(03)00059-3.

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42

Trulsson, Eva, and Lennart Ljung. "Adaptive control based on explicit criterion minimization." Automatica 21, no. 4 (1985): 385–99. http://dx.doi.org/10.1016/0005-1098(85)90075-5.

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43

Barranco-Cicilia, F., E. C. P. Lima, and L. V. S. Sagrilo. "Reliability-based design criterion for TLP tendons." Applied Ocean Research 30, no. 1 (2008): 54–61. http://dx.doi.org/10.1016/j.apor.2008.05.001.

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44

Kononenko, Igor, and Ivan Bratko. "Information-based evaluation criterion for classifier's performance." Machine Learning 6, no. 1 (1991): 67–80. http://dx.doi.org/10.1007/bf00153760.

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45

Van den Hof, P. M. J. "Criterion based equivalence for equation error models." IEEE Transactions on Automatic Control 34, no. 2 (1989): 191–93. http://dx.doi.org/10.1109/9.21096.

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46

XiaoYu, CHEN, and JIANG LiZhen. "Quantum separable criterion based on characteristic function." SCIENTIA SINICA Physica, Mechanica & Astronomica 48, no. 2 (2018): 020302. http://dx.doi.org/10.1360/sspma2017-00203.

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47

CONE, AL L. "FREQUENCY OF TESTING IN CRITERION-BASED LEARNING." Psychological Reports 67, no. 6 (1990): 396. http://dx.doi.org/10.2466/pr0.67.6.396-398.

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48

Wang, Jianfeng, Joseph E. Dove, and Marte S. Gutierrez. "Anisotropy-Based Failure Criterion for Interphase Systems." Journal of Geotechnical and Geoenvironmental Engineering 133, no. 5 (2007): 599–608. http://dx.doi.org/10.1061/(asce)1090-0241(2007)133:5(599).

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49

Tang, Zuqiang, Zhixing Yang, and Yan Yao. "Blind multiuser detector based on LMK criterion." Electronics Letters 35, no. 4 (1999): 267. http://dx.doi.org/10.1049/el:19990243.

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50

Meštrović, Romeo. "A primality criterion based on Lucas’ congruence." International Journal of Number Theory 12, no. 05 (2016): 1365–69. http://dx.doi.org/10.1142/s1793042116500834.

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Let [Formula: see text] be a prime. Back in 1878, Lucas proved that the congruence [Formula: see text] holds for any nonnegative integer [Formula: see text]. The converse statement was given in Problem 1494 of Mathematics Magazine proposed in 1997 by Deutsch and Gessel. In this note, we generalize this converse assertion as follows: If [Formula: see text] and [Formula: see text] are integers such that [Formula: see text] for every integer [Formula: see text], then [Formula: see text] is a prime and [Formula: see text] is a power of [Formula: see text].

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