Artículos de revistas: "Two way classification"

1

Balakrishnan, N., M. L. Tiku y A. H. El Shaarawi. "Robust Univariate Two-Way Classification". Biometrical Journal 27, n.º 2 (1985): 123–38. http://dx.doi.org/10.1002/bimj.4710270202.

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2

Singh, Vaishali y Sanjay K. Dwivedi. "Two Way Question Classification in Higher Education Domain". International Journal of Modern Education and Computer Science 7, n.º 9 (8 de septiembre de 2015): 59–65. http://dx.doi.org/10.5815/ijmecs.2015.09.08.

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3

Celardo, Livia y Martin G. Everett. "Network text analysis: A two-way classification approach". International Journal of Information Management 51 (abril de 2020): 102009. http://dx.doi.org/10.1016/j.ijinfomgt.2019.09.005.

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4

Lin, C. S. y G. Butler. "Cluster Analyses for Analyzing Two‐Way Classification Data". Agronomy Journal 82, n.º 2 (marzo de 1990): 344–48. http://dx.doi.org/10.2134/agronj1990.00021962008200020034x.

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5

Piepho, Hans-Peter. "Distribution-Free Tests for One-Way Homoscedasticity in a Two-Way Classification". Biometrics 53, n.º 1 (marzo de 1997): 340. http://dx.doi.org/10.2307/2533119.

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6

Qiao, Mu y Jia Li. "Two-way Gaussian mixture models for high dimensional classification". Statistical Analysis and Data Mining: The ASA Data Science Journal 3, n.º 4 (13 de julio de 2010): 259–71. http://dx.doi.org/10.1002/sam.10082.

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7

Zhang, Qinghua, Deyou Xia y Guoyin Wang. "Three-way decision model with two types of classification errors". Information Sciences 420 (diciembre de 2017): 431–53. http://dx.doi.org/10.1016/j.ins.2017.08.066.

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8

Wei, Laisheng y Jiahua Chen. "Empirical Bayes estimation and its superiority for two-way classification model". Statistics & Probability Letters 63, n.º 2 (junio de 2003): 165–75. http://dx.doi.org/10.1016/s0167-7152(03)00079-8.

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9

Brzeskwiniewicz, Henryk y Wiesław Wagner. "Error Normality Testing in a Model of Two-Way Nested Classification". Biometrical Journal 36, n.º 1 (1994): 87–94. http://dx.doi.org/10.1002/bimj.4710360112.

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10

Samadi, Hossein, Iman Aghayan, Amir Saman Abdollahzadeh Nasiri, Omid Rahmani y Mehrzad Hasanvand. "Platoon-Based Assessment of Two-Way Two-Lane Roads Performance Measure: A Classification Method". Journal of Advanced Transportation 2023 (24 de julio de 2023): 1–13. http://dx.doi.org/10.1155/2023/5054427.

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Two-way two-lane roads have a significant impact on road transportation infrastructure. Platoon formation on two-lane roads is one of the factors that affect the quality of traffic flow on two-lane roads. More specifically, the creation of a platoon increases the density of vehicles and the number of overtaking maneuvers and decreases the traffic performance of two-lane roads. The present study made an effort to investigate the effect of the platoon characteristics on the traffic flow of vehicles on two-lane roads. Moreover, it strived to develop the nonlinear regression model with a new approach to capacity calculation. Finally, a method for estimating the level of service (LOS) based on the number of followers per capacity (NFPC) and LOS classification using the KNN method was presented. Considering these aims, first, the relevant variables (which were related to platoon) including time headway (Ht), average travel speed (ATS), platoon size (PS), average platoon speed (APS), percentage of heavy vehicles (HV), percent time spent following (PTSF), number of overtaking (NO), density (ρ), and traffic flow were investigated on the examined roads. The results showed that the speed and the Ht were the most effective and the least effective platoon characteristics, respectively. Moreover, it was accompanied by the increase in PTSF which resulted in the increase in overtaking maneuver. Finally, the results regarding the developed model showed that the NFPC measure was able to predict the traffic flow of two-lane roads in a more satisfactory way compared to the two criteria, namely, PTSF and ATS in the Highway Capacity Manual (2016) since it increased ATS by 65% and decreased the capacity of two-lane roads by 21%.

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11

Kooch, Yahya, Hamid Jalilvand, Mohammad Ali Bahman y Mohammad Reza Porma. "Application of Two Way Indicator Species Analysis in Lowland Plant Types Classification". Pakistan Journal of Biological Sciences 11, n.º 5 (15 de febrero de 2008): 752–57. http://dx.doi.org/10.3923/pjbs.2008.752.757.

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12

van de Wiel, M. A. "Exact null distributions of quadratic distribution-free statistics for two-way classification". Journal of Statistical Planning and Inference 120, n.º 1-2 (febrero de 2004): 29–40. http://dx.doi.org/10.1016/s0378-3758(02)00498-6.

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13

Silva, Adenilton C. da, Sófacles F. C. Soares, Matías Insausti, Roberto K. H. Galvão, Beatriz S. F. Band y Mário César U. de Araújo. "Two-dimensional linear discriminant analysis for classification of three-way chemical data". Analytica Chimica Acta 938 (septiembre de 2016): 53–62. http://dx.doi.org/10.1016/j.aca.2016.08.009.

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14

P, Sinthia y Malathi M. "An Effective Two Way Classification of Breast Cancer Images: A Detailed Review". Asian Pacific Journal of Cancer Prevention 19, n.º 12 (1 de diciembre de 2018): 3335–39. http://dx.doi.org/10.31557/apjcp.2018.19.12.3335.

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15

Li, Jia y Hongyuan Zha. "Two-way Poisson mixture models for simultaneous document classification and word clustering". Computational Statistics & Data Analysis 50, n.º 1 (enero de 2006): 163–80. http://dx.doi.org/10.1016/j.csda.2004.07.013.

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16

Wagner, Wieslaw y H. Brzeskwiniewicz. "Normality Testing in a Mixed Model of a Two-way Nested Classification". Biometrical Journal 37, n.º 7 (1995): 889–95. http://dx.doi.org/10.1002/bimj.4710370711.

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17

Ahn, Hongshik, James J. Chen y Tsae-Yun D. Lin. "A Two-Way Analysis of Covariance Model for Classification of Stability Data". Biometrical Journal 39, n.º 5 (1997): 559–76. http://dx.doi.org/10.1002/bimj.4710390505.

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18

Leenen, Iwin y Eva Ceulemans. "Three-way Hierarchical Classes: A Comparison of the Indclas and Tucker3-Hiclas Models". Applied Multivariate Research 13, n.º 2 (19 de agosto de 2009): 43. http://dx.doi.org/10.22329/amr.v13i1.2834.

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Hierarchical classes (HICLAS) models for multi-way multi-mode data constitute a unique family of classification models in that (a) they simultaneously induce a hierarchical classification (of the elements) of each mode and (b) they link the hierarchical classifications together by an association relation that yieldsa predicted (or reconstructed) value for each cell in the data array. For the case of three-way three-mode binary data, the most prominent HICLAS models include INDCLAS and Tucker3-HICLAS. In this paper, we compare the latter two models, introducing the underlying theory of both in substantive terms and showing how a Tucker3-HICLAS analysis may result in a simpler model than that yielded by INDCLAS, although the former is mathematically more complex than the latter (which it includes as a special case). We illustrate by two applications: astudy on anger responses in frustrating situations and a case-study on emotions in interpersonal relations.

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19

Piepho, H. P. "Comment on Shukla's test for homogeneity of variances in a two-way classification". Journal of Animal Science 70, n.º 5 (1 de mayo de 1992): 1644–45. http://dx.doi.org/10.2527/1992.7051644x.

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20

Aggarwal, Apeksha, Vibhav Sharma, Anshul Trivedi, Mayank Yadav, Chirag Agrawal, Dilbag Singh, Vipul Mishra y Hassène Gritli. "Two-Way Feature Extraction Using Sequential and Multimodal Approach for Hateful Meme Classification". Complexity 2021 (17 de abril de 2021): 1–7. http://dx.doi.org/10.1155/2021/5510253.

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Millions of memes are created and shared every day on social media platforms. Memes are a great tool to spread humour. However, some people use it to target an individual or a group generating offensive content in a polite and sarcastic way. Lack of moderation of such memes spreads hatred and can lead to depression like psychological conditions. Many successful studies related to analysis of language such as sentiment analysis and analysis of images such as image classification have been performed. However, most of these studies rely only upon either one of these components. As classifying meme is one problem which cannot be solved by relying upon only any one of these aspects, the present work identifies, addresses, and ensembles both the aspects for analyzing such data. In this research, we propose a solution to the problems in which the classification depends on more than one model. This paper proposes two different approaches to solve the problem of identifying hate memes. The first approach uses sentiment analysis based on image captioning and text written on the meme. The second approach is to combine features from different modalities. These approaches utilize a combination of glove, encoder-decoder, and OCR with Adamax optimizer deep learning algorithms. Facebook Challenge Hateful Meme Dataset is utilized which contains approximately 8500 meme images. Both the approaches are implemented on the live challenge competition by Facebook and predicted quite acceptable results. Both approaches are tested on the validation dataset, and results are found to be promising for both models.

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21

Ben Chikha, Haithem y Ahmad Almadhor. "Automatic Classification of Superimposed Modulations for 5G MIMO Two-Way Cognitive Relay Networks". Computers, Materials & Continua 70, n.º 1 (2022): 1799–814. http://dx.doi.org/10.32604/cmc.2022.018819.

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22

Bolla, Marianna, Katalin Friedl y András Krámli. "Singular value decomposition of large random matrices (for two-way classification of microarrays)". Journal of Multivariate Analysis 101, n.º 2 (febrero de 2010): 434–46. http://dx.doi.org/10.1016/j.jmva.2009.09.006.

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23

Shinzawa, Hideyuki, Shigeaki Morita, Yukihiro Ozaki y Roumiana Tsenkova. "New Method for Spectral Data Classification: Two-Way Moving Window Principal Component Analysis". Applied Spectroscopy 60, n.º 8 (agosto de 2006): 884–91. http://dx.doi.org/10.1366/000370206778062020.

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24

Sklar, Michael G. y Ronald D. Armstrong. "Robust estimation procedures and visual display techniques for a two-way classification model". Quality & Quantity 28, n.º 3 (agosto de 1994): 283–304. http://dx.doi.org/10.1007/bf01098945.

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25

Gupta, A. K. y D. G. Kabe. "One-Way Classification ANOVA Model for the Mixture of Two Multivariate Normal Populations". Biometrical Journal 33, n.º 3 (1991): 361–67. http://dx.doi.org/10.1002/bimj.4710330320.

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26

Wu, Yejun. "Organization of Complex Topics in Comprehensive Classification Schemes: Case Studies of Disaster and Security". KNOWLEDGE ORGANIZATION 50, n.º 2 (2023): 99–110. http://dx.doi.org/10.5771/0943-7444-2023-2-99.

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This research investigates how comprehensive classifications and home-grown classifications organize complex topics. Two comprehensive classifications and two home-grown taxonomies are used to examine two complex topics: disaster and security. The two comprehensive classifications are the Library of Congress Classification and the Classification Scheme for Chinese Libraries. The two home-grown taxonomies are AIRS 211 LA County Taxonomy of Human Services – Disaster Services, and the Human Security Taxonomy. It is found that a comprehensive classification may provide many subclasses of a complex topic, which are scattered in various classes. Occasionally the classification scheme may provide several small taxonomies that organize the terms of a subclass of the complex topic that are pulled from multiple classes. However, the comprehensive classification provides no organization of the major subclasses of the complex topic. The lack of organization of the major subclasses of the complex topic may prevent users from understanding the complex topic systematically, and so preventing them from selecting an appropriate classification term for the complex topic. Ideally a comprehensive classification should provide a high-level conceptual framework for the complex topic, or at least organize the major subclasses in a way that help users understand the complex topic systematically.

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27

Leonard, Tom y Melvin R. Novick. "Bayesian Full Rank Marginalization for Two-Way Contingency Tables". Journal of Educational Statistics 11, n.º 1 (marzo de 1986): 33–56. http://dx.doi.org/10.3102/10769986011001033.

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A general approach is proposed for modeling the structure of an r × s contingency table and for drawing marginal inferences about all parameters (e.g., interaction effects) in the model. The main approach is relevant whenever rs − r − s + 1≥5. The approach may also be used to check the adequacy of Rasch’s multiplicative Poisson model. In general, the posterior estimates of the cell probabilities compromise between the cell frequencies and the fitted values obtained under the reduced model in the spirit of Leonard (1975) . It is also possible to compute reasonable approximations to the full posterior densities of many parameters of interest, following Leonard (1982) and Tierney and Kadane (1984) . All prior parameters are evaluated with the assistance of the data via a hierarchical Bayes procedure, thus reducing the subjectivity involved in the analysis. An r × s cross classification of 5,648 Marine Corps clerical students by school and test grade is analyzed in detail, and the posterior densities of the 96 possible interactions are used to suggest a simplified structure partitioning and collapsing the table into a meaningful 3 × 2 table.

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28

Darghan, Aquiles, Sinha Surendra y Julio Monroy. "A score test for the agronomical overlap effect in a two-way classification model". Agronomía Colombiana 32, n.º 3 (1 de septiembre de 2014): 417–22. http://dx.doi.org/10.15446/agron.colomb.v32n3.46086.

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In some agricultural research, a treatment applied to an experimental unit may affect the response in the neighboring experimental units. This phenomenon is known as overlap. In this article, a test to evaluate this effect in the Draper and Guttman model was developed by imposing side conditions on the parameters of a two-way classification model to obtain a re-parameterized model which can be used in different neighboring patterns of experimental units, usually plants within a crop, whenever the nearest neighbor is considered a directly affected experimental unit and the two-way model is used. Three methods, namely maximum likelihood, least squares with side conditions and generalized inverse, were used to estimate the parameters of the original model in order to calculate the value of the test statistics for the null hypothesis associated with the absence of the overlapping effect. The three alternatives were invariant with respect to the use of test. The proposed test is simple to adopt and can be implemented in agronomy since its asymptotic nature is in agreement with the large number of experimental units which generally exist in this type of research, where each plant represents the experimental unit being assessed.

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29

Ye, Ren-dao, Na An, Kun Luo y Ya Lin. "Bootstrap inference of the skew-normal two-way classification random effects model with interaction". Applied Mathematics-A Journal of Chinese Universities 37, n.º 3 (septiembre de 2022): 435–52. http://dx.doi.org/10.1007/s11766-022-4320-1.

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30

Liang, Decui y Bochun Yi. "Two-stage three-way enhanced technique for ensemble learning in inclusive policy text classification". Information Sciences 547 (febrero de 2021): 271–88. http://dx.doi.org/10.1016/j.ins.2020.08.051.

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31

Kashani, Ali Tavakoli y Afshin Shariat Mohaymany. "Analysis of the traffic injury severity on two-lane, two-way rural roads based on classification tree models". Safety Science 49, n.º 10 (diciembre de 2011): 1314–20. http://dx.doi.org/10.1016/j.ssci.2011.04.019.

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32

Ojeda, Mario Miguel y Hardeo Sahai. "A mixed-effects model for growth curves analysis in a two-way crossed classification layout". Revista de Matemática: Teoría y Aplicaciones 11, n.º 2 (20 de febrero de 2009): 87. http://dx.doi.org/10.15517/rmta.v11i2.245.

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33

ALEXANDER, G. J. "THE USE OF A MULTIVARIATE METHOD OF CLASSIFICATION (TWO-WAY INDICATOR SPECIES ANALYSIS) IN BIOGEOGRAPHY". Journal of the Herpetological Association of Africa 36, n.º 1 (agosto de 1989): 7–10. http://dx.doi.org/10.1080/04416651.1989.9650216.

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34

Campbell, Nancy L., Linda J. Young y George A. Capuano. "Analyzing over-dispersed count data in two-way cross-classification problems using generalized linear models". Journal of Statistical Computation and Simulation 63, n.º 3 (junio de 1999): 263–81. http://dx.doi.org/10.1080/00949659908811956.

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35

Abdel-Magid, Shaban. "MINQUE and PSD-MINQMBE in the two way cross classification random effect model without interaction". Microelectronics Reliability 35, n.º 1 (enero de 1995): 97–99. http://dx.doi.org/10.1016/0026-2714(93)e0004-s.

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36

Hu, Junhua, Wanying Cao y Pei Liang. "A Novel Sequential Three-Way Decision Model for Medical Diagnosis". Symmetry 14, n.º 5 (15 de mayo de 2022): 1004. http://dx.doi.org/10.3390/sym14051004.

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In the sequential three-way decision model (S3WD), conditional probability and decision threshold pair are two key elements affecting the classification results. The classical model calculates the conditional probability based on the strict equivalence relationship, which limits its application in reality. In addition, little research has studied the relationship between the threshold change and its cause at different granularity levels. To deal with these deficiencies, we propose a novel sequential three-way decision model and apply it to medical diagnosis. Firstly, we propose two methods of calculating conditional probability based on similarity relation, which satisfies the property of symmetry. Then, we construct an S3WD model for a medical information system and use three different kinds of cost functions as the basis for modifying the threshold pair at each level. Subsequently, the rule of the decision threshold pair change is explored. Furthermore, two algorithms used for implementing the proposed S3WD model are introduced. Finally, extensive experiments are carried out to validate the feasibility and effectiveness of the proposed model, and the results show that the model can achieve better classification performance.

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37

Grazioli, J., D. Tuia, S. Monhart, M. Schneebeli, T. Raupach y A. Berne. "Hydrometeor classification from two-dimensional video disdrometer data". Atmospheric Measurement Techniques 7, n.º 9 (9 de septiembre de 2014): 2869–82. http://dx.doi.org/10.5194/amt-7-2869-2014.

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Abstract. The first hydrometeor classification technique based on two-dimensional video disdrometer (2DVD) data is presented. The method provides an estimate of the dominant hydrometeor type falling over time intervals of 60 s during precipitation, using the statistical behavior of a set of particle descriptors as input, calculated for each particle image. The employed supervised algorithm is a support vector machine (SVM), trained over 60 s precipitation time steps labeled by visual inspection. In this way, eight dominant hydrometeor classes can be discriminated. The algorithm achieved high classification performances, with median overall accuracies (Cohen's K) of 90% (0.88), and with accuracies higher than 84% for each hydrometeor class.

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38

Effati, Meysam, Mohammd Ali Rajabi, Farshad Hakimpour y Shahin Shabani. "Prediction of Crash Severity on Two-Lane, Two-Way Roads Based on Fuzzy Classification and Regression Tree Using Geospatial Analysis". Journal of Computing in Civil Engineering 29, n.º 6 (noviembre de 2015): 04014099. http://dx.doi.org/10.1061/(asce)cp.1943-5487.0000432.

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39

Wen-Jing, ZHANG, ZHANG Qin-Di, WANG Jing, FENG Fei y BI Run-Cheng. "A comparison of multivariate regression tree and two-way indicator species analysis in plant community classification". Chinese Journal of Plant Ecology 39, n.º 6 (2015): 586–92. http://dx.doi.org/10.17521/cjpe.2015.0056.

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40

Kolář, Jakub, Jan Sýkora y Petr Hron. "Update-Based Machine Learning Classification of Hierarchical Symbols in a Slowly Varying Two-Way Relay Channel". Mathematics 8, n.º 11 (11 de noviembre de 2020): 2007. http://dx.doi.org/10.3390/math8112007.

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This paper presents a stochastic inference problem suited to a classification approach in a time-varying observation model with continuous-valued unknown parameterization. The utilization of an artificial neural network (ANN)-based classifier is considered, and the concept of a training process via the backpropagation algorithm is used. The main objective is the minimization of resources required for the training of the classifier in the parametric observation model. To reach this, it is proposed that the weights of the ANN classifier vary continuously with the change of the observation model parameters. This behavior is then used in an update-based backpropagation algorithm. This proposed idea is demonstrated on several procedures, which re-use previously trained weights as prior information when updating the classifier after a channel phase change. This approach successfully saves resources needed for re-training the ANN. The new approach is verified via a simulation on an example communication system with the two-way relay slowly fading channel.

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41

Pacheco, Fernando António Leal y Paulo Milton Barbosa Landim. "Two-Way Regionalized Classification of Multivariate Datasets and its Application to the Assessment of Hydrodynamic Dispersion". Mathematical Geology 37, n.º 4 (mayo de 2005): 393–417. http://dx.doi.org/10.1007/s11004-005-5955-1.

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42

Huang, Lei y Jialiang Li. "Weighted volume under the three-way receiver operating characteristic surface". Statistical Methods in Medical Research 28, n.º 12 (20 de noviembre de 2018): 3627–48. http://dx.doi.org/10.1177/0962280218812211.

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It is often necessary to differentiate subjects from multiple categories using medical tests. We may then adopt statistical measures to characterize the performance of these tests. The three-way ROC analysis has been proposed to evaluate the diagnostic accuracy of medical tests with three categories, reflecting the correct classification probabilities across all possible decision thresholds. The geometry of the ROC surface is carefully studied, leading to numerical summary measures such as the volume under the surface. This paper generalizes the global volume under the surface of three-way ROC analysis to the weighted volume under the surface (WVUS) by introducing a weight function emphasizing particular regions of correct classification probabilities. This generalization practically allows researchers to calculate the diagnostic accuracy for a medical or clinical biomarker while satisfactorily high probabilities of correct classification for one or two classes are conditionally ensured. We provide the asymptotic properties of the proposed nonparametric and parametric estimators of WVUS, which could easily lend support to statistical inferences. Some simulations have been conducted to assess the proposed estimators and also to demonstrate the necessity of WVUS. A real data analysis about liver cancer illustrates our methodology.

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43

Shah, Kiriti R. y Aloke Dey. "An Approach to the Analysis of Nonorthogonal Three-Way Designs". Calcutta Statistical Association Bulletin 44, n.º 1-2 (marzo de 1994): 49–56. http://dx.doi.org/10.1177/0008068319940105.

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A method of analysis of designs eliminating heterogeneity in two directions (three-way designs) is proposed for situations where the row versus column classification is nonorthogonal. The method appears to be simpler than the existing ones when the number of “missing” cells is small relative to the number of treatments and the total number of possible cells. A numerical example is given.

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44

YANG Ren-jie, 杨仁杰, 刘蓉 LIU Rong, 杨延荣 YANG Yan-rong y 张伟玉 ZHANG Wei-yu. "Classification of adulterated milk by two-dimensional correlation near-infrared spectroscopy and multi-way principal component analysis". Optics and Precision Engineering 22, n.º 9 (2014): 2352–58. http://dx.doi.org/10.3788/ope.20142209.2352.

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45

Gallo, Jose y Andre I. Khuri. "Exact Tests for the Random and Fixed Effects in an Unbalanced Mixed Two-Way Cross-Classification Model". Biometrics 46, n.º 4 (diciembre de 1990): 1087. http://dx.doi.org/10.2307/2532450.

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46

Sahai, Hardeo y Anwer Khurshid. "A comparison of estimators of variance components in a two–way balanced crossed classification random effects model". Statistics 23, n.º 2 (enero de 1992): 129–43. http://dx.doi.org/10.1080/02331889208802359.

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47

Gnanasekar, Sharon Priya y Elangannan Arunan. "A Detailed Classification of Three-Centre Two-Electron Bonds". Australian Journal of Chemistry 73, n.º 8 (2020): 767. http://dx.doi.org/10.1071/ch19557.

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We evaluate the three-centre two-electron (3c-2e) bonds using atoms in molecules (AIM) and natural bond orbital (NBO) theoretical analyses. They have been classified as ‘open (V)’ or ‘closed (Δ)’, depending on how the three centres were bonded. Herein, we show that they could be classified as V, L, Δ, Y, T and I (linear) arrangements depending on the way the three centres are bonded. These different structures are found in B2H6 (V), CH5+ (V), Me-C2H2+ (L), B3+ (Δ), C3H3+ (Δ), H3+ (Y), 2-norbornyl+ (T), SiH5+ (T), and Al2H7− (I). Our results suggest that CH3Li2+ does not contain a 3c-2e bond according to NBO analysis. Therefore, we propose that 3c-2e bonds are classified more accurately as V, L, Δ, Y, T, or I, based on the electron density topology.

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48

Hussin, Hamzah y Mohd Hariri Arifin. "Rock mass classification for rock mass in tunnelling and underground excavation - Development, limitation and way forward". Bulletin of the Geological Society of Malaysia 75 (26 de mayo de 2023): 13–23. http://dx.doi.org/10.7186/bgsm75202303.

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In the last few decades, rock mass classification had been used intensively in engineering design. The concern arises for the potential occurrence of localized or global rock mass failure due to geological (such as discontinuities, water, weathering) and non-geological (such as construction load, vibration) factors should be taken into consideration. The ability of a classification system to represent the rock mass condition in a straightforward and effective way can assist in engineering works. Two classification systems can be applied in underground construction such as tunneling and mining. In tunnel construction, the Rock Mass Rating (RMR), Q System, Japanese Highway (JH) Method, Geological Strength Index (GSI) and Rock Mass Quality Rating (RMQR) are commonly used. However, these systems cannot be applied for rock mass covered by shotcrete due to difficulty in observing the discontinuity planes. Therefore, a new investigation method and rock mass classification for rock mass covered by shotcrete is vital to overcome this limitation.

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49

Yang, Su y Farzin Deravi. "Re-Engineered Word Embeddings for Improved Document-Level Sentiment Analysis". Applied Sciences 12, n.º 18 (16 de septiembre de 2022): 9287. http://dx.doi.org/10.3390/app12189287.

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In this paper, a novel re-engineering mechanism for the generation of word embeddings is proposed for document-level sentiment analysis. Current approaches to sentiment analysis often integrate feature engineering with classification, without optimizing the feature vectors explicitly. Engineering feature vectors to match the data between the training set and query sample as proposed in this paper could be a promising way for boosting the classification performance in machine learning applications. The proposed mechanism is designed to re-engineer the feature components from a set of embedding vectors for greatly increased between-class separation, hence better leveraging the informative content of the documents. The proposed mechanism was evaluated using four public benchmarking datasets for both two-way and five-way semantic classifications. The resulting embeddings have demonstrated substantially improved performance for a range of sentiment analysis tasks. Tests using all the four datasets achieved by far the best classification results compared with the state-of-the-art.

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Dupuy-McCauley, K., H. V. Mudrakola y T. I. Morgenthaler. "0698 A Comparison Of Two Visual Hypopnea Classification Methods". Sleep 43, Supplement_1 (abril de 2020): A266. http://dx.doi.org/10.1093/sleep/zsaa056.694.

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Abstract Introduction The rules for classifying apneas as either obstructive or central using usual polysomnography (PSG) channels are well established, but classification of hypopneas is less straightforward without special sensors. Visual scoring methods have been proposed by the American Academy of Sleep Medicine (AASM) and by Randerath, et al. These two scoring methods have never been compared. We evaluated these two scoring methods for clinical use. Methods We selected 50 hypopnea segments from patient’s PSGs with very clear obstructive physiology (average total AHI 48.6, central AI 0), assumed to be obstructive hypopneas, and from patient’s PSGs with very clear central physiologies (average total AHI 34.3, obstructive AI 0.3), assumed to be central hypopneas. These 100 hypopnea-containing PSG segments (HCPS) were deidentified, placed in randomized order, and sent to two groups of 6 PSG scorers (2 RPSGTs, 2 sleep medicine fellows, 2 sleep medicine specialists). One group scored using the AASM criteria and the other used the Randerath algorithm. After a washout period, re-randomized HCPS were sent to be scored using the alternative method. We used Fleiss’ kappa to determine inter-rater reliability—i.e., how consistently multiple scorers came to the same conclusion about a given hypopnea segment using each method, and accuracy—how often the scorers rated the HCPS in a manner consistent with the assumed physiology. We also recorded the time it took to score. Results Overall accuracy of both methods was 68%. Among 12 scorers, Fleiss’ Kappa coefficient was 0.32 and 0.27 for the AASM and Randerath scoring methods, respectively. Average scoring time (24.3 minutes for AASM and 26.2 minutes for Randerath) was similar (p=0.79). Conclusion Inter-rater agreement was only fair using these methods, and accuracy was only 68%. More work is needed to discover a convenient, non-invasive way to reproducibly and accurately characterize hypopneas. Support This project does not have any funding support.

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