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Artículos de revistas sobre el tema "Incomplete approaches"

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Publicado: 6 de julio de 2024

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1

Ansótegui, Carlos, Felip Manyà, Jesus Ojeda, Josep M. Salvia y Eduard Torres. "Incomplete MaxSAT approaches for combinatorial testing". Journal of Heuristics 28, n.º 4 (agosto de 2022): 377–431. http://dx.doi.org/10.1007/s10732-022-09495-3.

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AbstractWe present a Satisfiability (SAT)-based approach for building Mixed Covering Arrays with Constraints of minimum length, referred to as the Covering Array Number problem. This problem is central in Combinatorial Testing for the detection of system failures. In particular, we show how to apply Maximum Satisfiability (MaxSAT) technology by describing efficient encodings for different classes of complete and incomplete MaxSAT solvers to compute optimal and suboptimal solutions, respectively. Similarly, we show how to solve through MaxSAT technology a closely related problem, the Tuple Number problem, which we extend to incorporate constraints. For this problem, we additionally provide a new MaxSAT-based incomplete algorithm. The extensive experimental evaluation we carry out on the available Mixed Covering Arrays with Constraints benchmarks and the comparison with state-of-the-art tools confirm the good performance of our approaches.
2

Putnam, Michael T. y Liliana Sánchez. "What’s so incomplete about incomplete acquisition?" Linguistic Approaches to Bilingualism 3, n.º 4 (11 de octubre de 2013): 478–508. http://dx.doi.org/10.1075/lab.3.4.04put.

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Modeling the competence grammar of heritage speakers who exhibit low proficiency in their L1 represents a significant challenge for generative and experimental approaches to bilingual linguistic research. In this paper we revisit the core tenets of the incomplete acquisition hypothesis as developed in recent scholarship (in particular by Montrul (2002 et seq.) and Polinsky (1997, 2006)). Although we adopt many of these fundamental aspects of this research program, in this article we develop an alternative model that provides a more accurate depiction of the process that leads to what these scholars describe as the (later) effects of incomplete acquisition, thus improving the predictive power of this research program.
3

Erikson, Truls y Mirjam Knockaert. "Negotiating incomplete contracts". Journal of Strategic Contracting and Negotiation 5, n.º 3 (septiembre de 2021): 153–69. http://dx.doi.org/10.1177/20555636211042093.

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When planning is possible, as in predictive environments, comprehensive contracting is not only desirable, but also useful. However, under conditions of fundamental uncertainty, as is the case in non-predictive environments, incomplete contracting approaches likely prevail. In this study, we explore how trust in such environments affects the way in which venturing professionals negotiate, and how the outcome subsequently manifests itself in the negotiated agreement. In particular, building upon a sample of Norwegian firms, we find that stewardship relationships are more prone to incomplete contracting approaches than agency relationships, paving the way for a relational approach to contracting when uncertainty is high. Implications for theory and practice are discussed.
4

Li, Zhaowen, Shimin Liao, Liangdong Qu y Yan Song. "Attribute selection approaches for incomplete interval-value data". Journal of Intelligent & Fuzzy Systems 40, n.º 5 (22 de abril de 2021): 8775–92. http://dx.doi.org/10.3233/jifs-200394.

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Attribute selection in an information system (IS) is an important issue when dealing with a large amount of data. An IS with incomplete interval-value data is called an incomplete interval-valued information system (IIVIS). This paper proposes attribute selection approaches for an IIVIS. Firstly, the similarity degree between two information values of a given attribute in an IIVIS is proposed. Then, the tolerance relation on the object set with respect to a given attribute subset is obtained. Next, θ-reduction in an IIVIS is studied. What is more, connections between the proposed reduction and information entropy are revealed. Lastly, three reduction algorithms base on θ-discernibility matrix, θ-information entropy and θ-significance in an IIVIS are given.
5

Timm, Heiko, Christian Döring y Rudolf Kruse. "Different approaches to fuzzy clustering of incomplete datasets". International Journal of Approximate Reasoning 35, n.º 3 (marzo de 2004): 239–49. http://dx.doi.org/10.1016/j.ijar.2003.08.004.

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6

Kim, Seung-Jun, Young-hwan Lee y Kwang Y. Lee. "Robust Subspace Approaches for Analyzing Incomplete Synchrophasor Measurements". IFAC-PapersOnLine 48, n.º 30 (2015): 120–25. http://dx.doi.org/10.1016/j.ifacol.2015.12.364.

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7

Zou, Yan y Zhi Xiao. "Data analysis approaches of soft sets under incomplete information". Knowledge-Based Systems 21, n.º 8 (diciembre de 2008): 941–45. http://dx.doi.org/10.1016/j.knosys.2008.04.004.

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8

Sarabando, Paula, Luís C. Dias y Rudolf Vetschera. "Mediation with Incomplete Information: Approaches to Suggest Potential Agreements". Group Decision and Negotiation 22, n.º 3 (10 de febrero de 2012): 561–97. http://dx.doi.org/10.1007/s10726-012-9283-9.

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9

Rueda, David Rodríguez, Carlos Cotta y Antonio J. Fernández-Leiva. "Memetic collaborative approaches for finding balanced incomplete block designs". Computers & Operations Research 114 (febrero de 2020): 104804. http://dx.doi.org/10.1016/j.cor.2019.104804.

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10

Yan, Tao y Chongzhao Han. "A Novel Approach of Rough Conditional Entropy-Based Attribute Selection for Incomplete Decision System". Mathematical Problems in Engineering 2014 (2014): 1–15. http://dx.doi.org/10.1155/2014/728923.

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Pawlak's classical rough set theory has been applied in analyzing ordinary information systems and decision systems. However, few studies have been carried out on the attribute selection problem in incomplete decision systems because of its complexity. It is therefore necessary to investigate effective algorithms to deal with this issue. In this paper, a new rough conditional entropy-based uncertainty measure is introduced to evaluate the significance of subsets of attributes in incomplete decision systems. Furthermore, some important properties of rough conditional entropy are derived and three attribute selection approaches are constructed, including an exhaustive search strategy approach, a heuristic search strategy approach, and a probabilistic search strategy approach for incomplete decision systems. Moreover, several experiments on real-life incomplete data sets are conducted to assess the efficiency of the proposed approaches. The final experimental results indicate that two of these approaches can give satisfying performances in the process of attribute selection in incomplete decision systems.
11

Goldfarb, David S. "Refining Diagnostic Approaches in Nephrolithiasis: Incomplete Distal Renal Tubular Acidosis". Clinical Journal of the American Society of Nephrology 12, n.º 9 (3 de agosto de 2017): 1380–82. http://dx.doi.org/10.2215/cjn.07160717.

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12

Pratibha, Gaur. "Bio-informatics approaches in liver disease: Incomplete without experimental validation". Archives of Hepatitis Research 8, n.º 1 (27 de septiembre de 2022): 012–13. http://dx.doi.org/10.17352/ahr.000033.

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In the search for the treatment of hepatic diseases, multiple approaches have been used frequently such as bioinformatics and algorithm-based systems biology for the screening of already published data that leads to the identification of promising drug candidates at molecular levels. These studies provide a large data set of information and claim to identify many genes, which could be targeted for the cure. However, it is important to note that the identified compounds are only predictions and the potential of these suggested molecules or genes should be well confirmed by adopting robust and critical experimental approaches to satisfy all possible aspects to use them safely for therapeutic purposes. Therefore, I put forward the opinion that these predicted markers whether prognostic, diagnostic, or molecular must be evaluated critically through a well-defined experimental pipeline.
13

Van Steen, K., N. M. Laird, P. Markel y G. Molenberghs. "Approaches to Handling Incomplete Data in Family-based Association Testing". Annals of Human Genetics 71, n.º 2 (marzo de 2007): 141–51. http://dx.doi.org/10.1111/j.1469-1809.2006.00325.x.

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14

Liu, Yaya, Keyun Qin, Chang Rao y Mahamuda Alhaji Mahamadu. "Object–Parameter Approaches to Predicting Unknown Data in an Incomplete Fuzzy Soft Set". International Journal of Applied Mathematics and Computer Science 27, n.º 1 (28 de marzo de 2017): 157–67. http://dx.doi.org/10.1515/amcs-2017-0011.

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Abstract The research on incomplete fuzzy soft sets is an integral part of the research on fuzzy soft sets and has been initiated recently. In this work, we first point out that an existing approach to predicting unknown data in an incomplete fuzzy soft set suffers from some limitations and then we propose an improved method. The hidden information between both objects and parameters revealed in our approach is more comprehensive. Furthermore, based on the similarity measures of fuzzy sets, a new adjustable object-parameter approach is proposed to predict unknown data in incomplete fuzzy soft sets. Data predicting converts an incomplete fuzzy soft set into a complete one, which makes the fuzzy soft set applicable not only to decision making but also to other areas. The compared results elaborated through rate exchange data sets illustrate that both our improved approach and the new adjustable object-parameter one outperform the existing method with respect to forecasting accuracy.
15

Yan, Tao y Chong Zhao Han. "A Novel Approach Based on Rough Conditional Entropy for Attribute Reduction". Applied Mechanics and Materials 644-650 (septiembre de 2014): 1607–19. http://dx.doi.org/10.4028/www.scientific.net/amm.644-650.1607.

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Z. Pawlak’s rough set theory has been widely applied in analyzing ordinary information systems and decision tables. While few studies have been conducted on attribute selection problem in incomplete decision systems because of its complexity. Therefore, it is necessary to investigate effective algorithms to tackle this issue. In this paper, In this paper, a new rough conditional entropy based uncertainty measure is introduced to evaluate the significance of subsets of attributes in incomplete decision systems. Moreover, some important properties of rough conditional entropy are derived and three attribute selection approaches are constructed, including an exhaustive approach, a heuristic approach, and a probabilistic approach. In the end, a series of experiments on practical incomplete data sets are carried out to assess the proposed approaches. The final experimental results indicate that two of these approaches perform satisfyingly in the process of attribute selection in incomplete decision systems.
16

Shishkina, T. Yu y V. B. Aksenova. "Ultrasound diagnosis of interstitial ectopic pregnancy. Current approaches". Voprosy ginekologii, akušerstva i perinatologii 21, n.º 1 (2022): 144–49. http://dx.doi.org/10.20953/1726-1678-2022-1-144-149.

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The analysis of ultrasound elastography and three-dimensional (3D) ultrasound imaging of suspected pregnancy in the interstitial part of the fallopian tube in three patients is presented. The following diagnoses were confirmed: interstitial pregnancy; first identified myomatous node with impaired trophism in the interstitial part of the fallopian tube in combination with menstrual disorders; incomplete miscarriage combined with a presence of myomatous node in the interstitial part of the fallopian tube simulating ectopic nidation. According to elastography, both the fertilized egg and myomatous nodes in the interstitial part of the fallopian tube appeared as stiff relative to the myometrium with clearly visualized contours. Three-dimensional ultrasound imaging with modalities including multiplanar reconstruction, tomography, omni-view, and “niche” contributed to verifying the diagnosis. Laparoscopy was performed in all patients. Interstitial pregnancy and incomplete miscarriage were histologically confirmed. Key words: compression elastography, ectopic pregnancy, pregnancy in the interstitial part of the fallopian tube, elastographic patterns, three-dimensional ultrasound imaging, ultrasound elastography
17

Öztürk, Cihat, Gülfem Tuzkaya y Serol Bulkan. "Centrality based solution approaches for median-type incomplete hub location problems". Computers & Industrial Engineering 156 (junio de 2021): 107275. http://dx.doi.org/10.1016/j.cie.2021.107275.

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18

Glebova, P. A. "Approaches to Calculating Loads on Interchamber Pillars under Incomplete Undermined Conditions". Journal of Physics: Conference Series 1945, n.º 1 (1 de junio de 2021): 012008. http://dx.doi.org/10.1088/1742-6596/1945/1/012008.

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19

Granberg-Rademacker, J. Scott. "A Comparison of Three Approaches to Handling Incomplete State-Level Data". State Politics & Policy Quarterly 7, n.º 3 (septiembre de 2007): 325–38. http://dx.doi.org/10.1177/153244000700700306.

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This article compares three approaches to handling missing data at the state level under three distinct conditions. Using Monte Carlo simulation experiments, I compare the results from a linear model using listwise deletion (LD), Markov Chain Monte Carlo with the Gibbs sampler algorithm (MCMC), and multiple imputation by chained equations (MICE) as approaches to dealing with different severity levels of missing data: missing completely at random (MCAR), missing at random (MAR), and nonignorable missingness (NI). I compare the results from each of these approaches under each condition for missing data to the results from the fully observed dataset. I conclude that the MICE algorithm performs best under most missing data conditions, MCMC provides the most stable parameter estimates across the missing data conditions (but often produced estimates that were moderately biased), and LD performs worst under most missing data conditions. I conclude with recommendations for handling missing data in state-level analysis.
20

Heath, David, Eckhard Platen y Martin Schweizer. "A Comparison of Two Quadratic Approaches to Hedging in Incomplete Markets". Mathematical Finance 11, n.º 4 (octubre de 2001): 385–413. http://dx.doi.org/10.1111/1467-9965.00122.

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21

Ikeme, Jekwu. "Equity, environmental justice and sustainability: incomplete approaches in climate change politics". Global Environmental Change 13, n.º 3 (octubre de 2003): 195–206. http://dx.doi.org/10.1016/s0959-3780(03)00047-5.

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22

Tang, Xiao-Song, Dian-Qing Li, Chuang-Bing Zhou y Kok-Kwang Phoon. "Copula-based approaches for evaluating slope reliability under incomplete probability information". Structural Safety 52 (enero de 2015): 90–99. http://dx.doi.org/10.1016/j.strusafe.2014.09.007.

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23

Zeng, Yifu, Kenli Li, Shui Yu, Yantao Zhou y Keqin Li. "Parallel and Progressive Approaches for Skyline Query Over Probabilistic Incomplete Database". IEEE Access 6 (2018): 13289–301. http://dx.doi.org/10.1109/access.2018.2806379.

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24

Vetschera, Rudolf. "Deriving rankings from incomplete preference information: A comparison of different approaches". European Journal of Operational Research 258, n.º 1 (abril de 2017): 244–53. http://dx.doi.org/10.1016/j.ejor.2016.08.031.

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25

HOGAN, JOSEPH W. y NAN M. LAIRD. "MODEL-BASED APPROACHES TO ANALYSING INCOMPLETE LONGITUDINAL AND FAILURE TIME DATA". Statistics in Medicine 16, n.º 3 (15 de febrero de 1997): 259–72. http://dx.doi.org/10.1002/(sici)1097-0258(19970215)16:3<259::aid-sim484>3.0.co;2-s.

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26

Auchmuty, Rosemary. "Feminist Approaches to Sexuality and Law Scholarship". Legal Information Management 15, n.º 1 (marzo de 2015): 4–7. http://dx.doi.org/10.1017/s1472669615000055.

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AbstractSexuality and Law scholarship is a new and developing field but, like most legal scholarship, it is dominated by masculine concerns and methodologies. This article, by Rosemary Auchmuty, explains why research that ignores feminist concerns and methodologies will be incomplete and inaccurate, and suggests questions that should be asked of resources to ensure a complete and accurate coverage of the topic.
27

Zimmerman, D. C., S. W. Smith, H. M. Kim y T. J. Bartkowicz. "An Experimental Study of Structural Health Monitoring Using Incomplete Measurements". Journal of Vibration and Acoustics 118, n.º 4 (1 de octubre de 1996): 543–50. http://dx.doi.org/10.1115/1.2888333.

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In this paper, algorithmic approaches to enhance structural health monitoring capability when faced with incomplete measurements are addressed. The incomplete measurement problem has two aspects: (i) experimental measurement of a lesser number of modes of vibration than that of the analytical model and (ii) experimental measurement of a lesser number of degrees of freedom than that of the analytical model. Studies comparing model reduction, eigenvector expansion, and a hybrid model reduction/eigenvector expansion to address the second contribution are performed using experimental data. These approaches to the incomplete measurement problem are evaluated within the frameworks of multiple-constraint matrix adjustment (both sparsity and nonsparsity preserving algorithms) and minimum rank perturbation theory, which are both applicable for model refinement as well as damage location. Experimental evaluation of the proposed approaches utilize data from the NASA Langley Research Center 8-bay truss and McDonnell Douglas Aerospace 10-bay truss facilities.
28

Dragu, Tiberiu y Michael Laver. "Legislative coalitions with incomplete information". Proceedings of the National Academy of Sciences 114, n.º 11 (27 de febrero de 2017): 2876–80. http://dx.doi.org/10.1073/pnas.1608514114.

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In most parliamentary democracies, proportional representation electoral rules mean that no single party controls a majority of seats in the legislature. This in turn means that the formation of majority legislative coalitions in such settings is of critical political importance. Conventional approaches to modeling the formation of such legislative coalitions typically make the “common knowledge” assumption that the preferences of all politicians are public information. In this paper, we develop a theoretical framework to investigate which legislative coalitions form when politicians’ policy preferences are private information, not known with certainty by the other politicians with whom they are negotiating over what policies to implement. The model we develop has distinctive implications. It suggests that legislative coalitions should typically be either of the center left or the center right. In other words our model, distinctively, predicts only center-left or center-right policy coalitions, not coalitions comprising the median party plus parties both to its left and to its right.
29

Tabakhi, Atena M. "Parameterized Heuristics for Incomplete Weighted CSPs". Proceedings of the AAAI Conference on Artificial Intelligence 33 (17 de julio de 2019): 10045–46. http://dx.doi.org/10.1609/aaai.v33i01.330110045.

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The key assumption in Weighted Constraint Satisfaction Problems (WCSPs) is that all constraints are specified a priori. This assumption does not hold in some applications that involve users preferences. Incomplete WCSPs (IWCSPs) extend WCSPs by allowing some constraints to be partially specified. Unfortunately, existing IWCSP approaches either guarantee to return optimal solutions or not provide any quality guarantees on solutions found. To bridge the two extremes, we propose a number of parameterized heuristics that allow users to find boundedly-suboptimal solutions, where the error bound depends on user-defined parameters. These heuristics thus allow users to trade off solution quality for fewer elicited preferences and faster computation times.
30

Tabakhi, Atena M. "Parameterized Heuristics for Incomplete Weighted CSPs". Proceedings of the AAAI Conference on Artificial Intelligence 33 (17 de julio de 2019): 9898–99. http://dx.doi.org/10.1609/aaai.v33i01.33019898.

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The key assumption in Weighted Constraint Satisfaction Problems (WCSPs) is that all constraints are specified a priori. This assumption does not hold in some applications that involve users preferences. Incomplete WCSPs (IWCSPs) extend WCSPs by allowing some constraints to be partially specified. Unfortunately, existing IWCSP approaches either guarantee to return optimal solutions or not provide any quality guarantees on solutions found. To bridge the two extremes, we propose a number of parameterized heuristics that allow users to find boundedly-suboptimal solutions, where the error bound depends on user-defined parameters. These heuristics thus allow users to trade off solution quality for fewer elicited preferences and faster computation times.
31

Niskanen, Andreas, Daniel Neugebauer, Matti Järvisalo y Jörg Rothe. "Deciding Acceptance in Incomplete Argumentation Frameworks". Proceedings of the AAAI Conference on Artificial Intelligence 34, n.º 03 (3 de abril de 2020): 2942–49. http://dx.doi.org/10.1609/aaai.v34i03.5686.

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Expressing incomplete knowledge in abstract argumentation frameworks (AFs) through incomplete AFs has recently received noticeable attention. However, algorithmic aspects of deciding acceptance in incomplete AFs are still under-developed. We address this current shortcoming by developing algorithms for NP-hard and coNP-hard variants of acceptance problems over incomplete AFs via harnessing Boolean satisfiability (SAT) solvers. Focusing on nonempty conflict-free or admissible sets and on stable extensions, we also provide new complexity results for a refined variant of skeptical acceptance in incomplete AFs, ranging from polynomial-time computability to hardness for the second level of the polynomial hierarchy. Furthermore, central to the proposed SAT-based counterexample-guided abstraction refinement approach for the second-level problem variants, we establish conditions for redundant atomic changes to incomplete AFs from the perspective of preserving extensions. We show empirically that the resulting SAT-based approach for incomplete AFs scales at least as well as existing SAT-based approaches to deciding acceptance in AFs.
32

Wei, Guiwu, Hongjun Wang, Xiaofei Zhao y Rui Lin. "Approaches to hesitant fuzzy multiple attribute decision making with incomplete weight information". Journal of Intelligent & Fuzzy Systems 26, n.º 1 (2014): 259–66. http://dx.doi.org/10.3233/ifs-120734.

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33

Qin, Hongwu y Xiuqin Ma. "Data Analysis Approaches of Interval-Valued Fuzzy Soft Sets Under Incomplete Information". IEEE Access 7 (2019): 3561–71. http://dx.doi.org/10.1109/access.2018.2886215.

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34

Rajagopal, D. "A synthesis of unilateral approaches to mitigating emissions leakage under incomplete policies". Climate Policy 17, n.º 5 (10 de marzo de 2016): 573–90. http://dx.doi.org/10.1080/14693062.2016.1150249.

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35

De Cicco, Maristella, Gianfranco Mamone, Luigia Di Stasio, Pasquale Ferranti, Francesco Addeo y Gianluca Picariello. "Hidden “Digestome”: Current Analytical Approaches Provide Incomplete Peptide Inventories of Food Digests". Journal of Agricultural and Food Chemistry 67, n.º 27 (15 de mayo de 2019): 7775–82. http://dx.doi.org/10.1021/acs.jafc.9b02342.

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36

Pedretti, Daniele y Roger D. Beckie. "Stochastic evaluation of simple pairing approaches to reconstruct incomplete rainfall time series". Stochastic Environmental Research and Risk Assessment 30, n.º 7 (14 de diciembre de 2015): 1933–46. http://dx.doi.org/10.1007/s00477-015-1195-1.

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37

Pereira, Ramon Fraga, Andre Grahl Pereira y Felipe Meneguzzi. "Landmark-Enhanced Heuristics for Goal Recognition in Incomplete Domain Models". Proceedings of the International Conference on Automated Planning and Scheduling 29 (25 de mayo de 2021): 329–37. http://dx.doi.org/10.1609/icaps.v29i1.3495.

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Recent approaches to goal recognition have progressively relaxed the assumptions about the amount and correctness of domain knowledge and available observations, yielding accurate and efficient algorithms. These approaches, however, assume completeness and correctness of the domain theory against which their algorithms match observations: this is too strong for most real-world domains. In this paper, we develop goal recognition techniques that are capable of recognizing goals using incomplete domain theories by considering different notions of planning landmarks in such domains. We evaluate the resulting techniques empirically in a large dataset of incomplete domains, and perform an ablation study to understand their effect on recognition performance.
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Benallou, Oualid y Rajae Aboulaich. "Improving Capital Budgeting Through Probabilistic Approaches". Review of Pacific Basin Financial Markets and Policies 20, n.º 03 (14 de agosto de 2017): 1750018. http://dx.doi.org/10.1142/s0219091517500187.

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This article advocates the multiple benefits of applying probabilistic approaches to capital budgeting through enriching the deterministic framework with a stochastic modeling of main impacting inputs (including a methodology for selecting the most important inputs to be modeled stochastically). The essential limitations of the deterministic capital budgeting methodology are presented: behavioral biases (optimism, asymmetric probability distribution, etc.), incomplete view of the risk return profile, neglecting real options (be it to evaluate a project or to reshape it in a value creation perspective), portfolio diversification impact, etc. Through some selected examples, we illustrate how each of these limitations can be mitigated thanks to probabilistic approaches leading to a better decision-making process and ultimately more value creation.
39

Goel, Sonia y Meena Tushir. "Different Approaches for Missing Data Handling in Fuzzy Clustering: A Review". Recent Advances in Electrical & Electronic Engineering (Formerly Recent Patents on Electrical & Electronic Engineering) 13, n.º 6 (4 de noviembre de 2020): 833–46. http://dx.doi.org/10.2174/2352096512666191127121710.

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Introduction: Incomplete data sets containing some missing attributes is a prevailing problem in many research areas. The reasons for the lack of missing attributes may be several; human error in tabulating/recording the data, machine failure, errors in data acquisition or refusal of a patient/customer to answer few questions in a questionnaire or survey. Further, clustering of such data sets becomes a challenge. Objective: In this paper, we presented a critical review of various methodologies proposed for handling missing data in clustering. The focus of this paper is the comparison of various imputation techniques based FCM clustering and the four clustering strategies proposed by Hathway and Bezdek. Methods: In this paper, we imputed the missing values in incomplete datasets by various imputation/ non-imputation techniques to complete the data set and then conventional fuzzy clustering algorithm is applied to get the clustering results. Results: Experiments on various synthetic data sets and real data sets from UCI repository are carried out. To evaluate the performance of the various imputation/ non-imputation based FCM clustering algorithm, several performance criteria and statistical tests are considered. Experimental results on various data sets show that the linear interpolation based FCM clustering performs significantly better than other imputation as well as non-imputation techniques. Conclusion: It is concluded that the clustering algorithm is data specific, no clustering technique can give good results on all data sets. It depends upon both the data type and the percentage of missing attributes in the dataset. Through this study, we have shown that the linear interpolation based FCM clustering algorithm can be used effectively for clustering of incomplete data set.
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G, Tsoucalas. "Anatomy Image Series: Persistent Metopic Sutures in a Series of Dry Skulls of Hellenic Origin". Journal of Human Anatomy 5, n.º 1 (26 de enero de 2021): 1–3. http://dx.doi.org/10.23880/jhua-16000158.

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The persistence of a complete metopic suture in adulthood is called metopism. Numerous studies report wide variations concerning the prevalence of metopic sutures in adult crania. Metopic suture lies to the midline of the forehead and extends from the frontal bone to the root of the nose. However various types of incomplete sutures do exist. A series of 126 dry skulls is examined. A total of 15 metopic sutures were revealed, 2 complete (1 combined) and 13 incompletes. The localization and suture types are important for clinical approaches, as during the evaluation of head traumas in the emergency department.
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Gerken, Thomas A. "Biophysical Approaches to Salivary Mucin Structure, Conformation and Dynamics". Critical Reviews in Oral Biology & Medicine 4, n.º 3 (abril de 1993): 261–70. http://dx.doi.org/10.1177/10454411930040030201.

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Our understanding of the origins of the physical and biochemical properties of mucous glycoproteins is incomplete and not with out controversy. Recent molecular biological and biophysical studies revealing the architecture and solution structure and dynamics of a series of salivary mucins, invaluable toward resolving many of these questions, are discussed. Mucins are very large, structurally heterogeneous, and highly expanded molecules with the carbohydrate playing a key role in maintaining the extended mucin conformation.
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Stumpf, Michael P. H. y Thomas Thorne. "Multi-model inference of network properties from incomplete data". Journal of Integrative Bioinformatics 3, n.º 2 (1 de diciembre de 2006): 123–36. http://dx.doi.org/10.1515/jib-2006-32.

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Summary It has previously been shown that subnets differ from global networks from which they are sampled for all but a very limited number of theoretical network models. These differences are of qualitative as well as quantitative nature, and the properties of subnets may be very different from the corresponding properties in the true, unobserved network. Here we propose a novel approach which allows us to infer aspects of the true network from incomplete network data in a multi-model inference framework. We develop the basic theoretical framework, including procedures for assessing confidence intervals of our estimates and evaluate the performance of this approach in simulation studies and against subnets drawn from the presently available PIN network data in Saccaromyces cerevisiae. We then illustrate the potential power of this new approach by estimating the number of interactions that will be detectable with present experimental approaches in sfour eukaryotic species, inlcuding humans. Encouragingly, where independent datasets are available we obtain consistent estimates from different partial protein interaction networks. We conclude with a discussion of the scope of this approaches and areas for further research
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Shekhovtsov, Andrii, Joanna Kołodziejczyk y Wojciech Sałabun. "Fuzzy Model Identification Using Monolithic and Structured Approaches in Decision Problems with Partially Incomplete Data". Symmetry 12, n.º 9 (18 de septiembre de 2020): 1541. http://dx.doi.org/10.3390/sym12091541.

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A significant challenge in the current trend in decision-making methods is the problem’s class in which the decision-maker makes decisions based on partially incomplete data. Classic methods of multicriteria decision analysis are used to analyze alternatives described by using numerical values. At the same time, fuzzy set modifications are usually used to include uncertain data in the decision-making process. However, data incompleteness is something else. In this paper, we show two approaches to identify fuzzy models with partially incomplete data. The monolithic approach assumes creating one model that requires many queries to the expert. In the structured approach, the problem is decomposed into several interrelated models. The main aim of the work is to compare their accuracy empirically and to determine the sensitivity of the obtained model to the used criteria. For this purpose, a study case will be presented. In order to compare the proposed approaches and analyze the significance of the decision criteria, we use two ranking similarity coefficients, i.e., symmetric rw and asymmetric WS. In this work, the limitations of each approach are presented, and the results show great similarity despite the use of two structurally different approaches. Finally, we show an example of calculations performed for alternatives with partially incomplete data.
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Hu, Menglei y Songcan Chen. "One-Pass Incomplete Multi-View Clustering". Proceedings of the AAAI Conference on Artificial Intelligence 33 (17 de julio de 2019): 3838–45. http://dx.doi.org/10.1609/aaai.v33i01.33013838.

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Real data are often with multiple modalities or from multiple heterogeneous sources, thus forming so-called multi-view data, which receives more and more attentions in machine learning. Multi-view clustering (MVC) becomes its important paradigm. In real-world applications, some views often suffer from instances missing. Clustering on such multi-view datasets is called incomplete multi-view clustering (IMC) and quite challenging. To date, though many approaches have been developed, most of them are offline and have high computational and memory costs especially for large scale datasets. To address this problem, in this paper, we propose an One-Pass Incomplete Multi-view Clustering framework (OPIMC). With the help of regularized matrix factorization and weighted matrix factorization, OPIMC can relatively easily deal with such problem. Different from the existing and sole online IMC method, OPIMC can directly get clustering results and effectively determine the termination of iteration process by introducing two global statistics. Finally, extensive experiments conducted on four real datasets demonstrate the efficiency and effectiveness of the proposed OPIMC method.
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Liu, Deshan, Dapeng Wang, Deqin Yan y Yu Sang. "Approximate Accuracy Approaches to Attribute Reduction for Information Systems". Abstract and Applied Analysis 2014 (2014): 1–6. http://dx.doi.org/10.1155/2014/382967.

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The key problem for attribute reduction to information systems is how to evaluate the importance of an attribute. The algorithms are challenged by the variety of data forms in information system. Based on rough sets theory we present a new approach to attribute reduction for incomplete information systems and fuzzy valued information systems. In order to evaluate the importance of an attribute effectively, a novel algorithm with rigorous theorem is proposed. Experiments show the effect of proposed algorithm.
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Goryachev, D. V., N. E. Uvarova y G. V. Shukshina. "Marketing Authorisation Based on Incomplete Clinical Data: International Experience and Prospects". Bulletin of the Scientific Centre for Expert Evaluation of Medicinal Products 10, n.º 3 (18 de septiembre de 2020): 152–63. http://dx.doi.org/10.30895/1991-2919-2020-10-3-152-163.

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No new drug can be used in clinical practice without marketing authorisation. Acquisition of the necessary amount of clinical data may take several years, which is especially critical for pernicious diseases for which no alternative therapy is available. Lack of treatment options creates conditions in which early introduction of efficacious therapy into clinical practice is becoming crucial. This need resulted in the development of new regulatory approaches aimed at accelerated approval of drugs both by reducing the time frame and by fulfilling post-authorisation requirements. The aim of the study was to review regulatory approaches to the accelerated authorisation procedure based on incomplete clinical data, and analyse their potential use in the Russian Federation. The paper presents an overview of authorisation pathways based on incomplete clinical data, which are used by different regulatory authorities, as well as regulatory approaches used in the Eurasian Economic Union (EAEU) and as part of the Russian national authorisation procedure. It was demonstrated that the approaches used by the US, European, and Japanese regulatory authorities, despite some differences, share a common objective of accelerated approval of drugs that fill an unmet medical need. The EAEU also has a conditional approval procedure, but the proposed criteria do not make it possible to use this approach in a real clinical situation of an unmet medical need. A similar national procedure would make it possible to reach a compromise between the needs of the healthcare system and the sound basis for informed decisions of the regulatory authority. Accelerated introduction of novel drugs that address unmet medical needs would set the national regulation in the area of drug circulation on the right track.
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Atnafu, Asmamaw, Gashaw Andargie, Mezgebu Yitayal, Tadesse Awoke Ayele, Kassahun Alemu, Getu Debalkie Demissie, Haileab Fekadu Wolde et al. "Prevalence and determinants of incomplete or not at all vaccination among children aged 12–36 months in Dabat and Gondar districts, northwest of Ethiopia: findings from the primary health care project". BMJ Open 10, n.º 12 (diciembre de 2020): e041163. http://dx.doi.org/10.1136/bmjopen-2020-041163.

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ObjectiveEthiopia is one of the Africa’s signatory countries for implementation of the primary healthcare strategy including immunisation. In Ethiopia, however, 16% of child death is due to vaccine-preventable disease. Thus, this study aimed to assess the prevalence and determinants of incomplete or not at all vaccination among children aged 12–36 months in Dabat and Gondar districts, Northwest Ethiopia.Study designThe study is community-based cross-sectional study.Study settingDabat and Gondar Zuria districts, Northwest Ethiopia.ParticipantsMothers/caregivers with children aged 12–36 months were enrolled in the study. Participants were randomly selected through systematic sampling and a total of 603 participants were included in the analysis.MethodsA binary logistic regression analysis was done. In the multivariable logistic regression analysis, a p value of <0.05 and adjusted OR (AOR) with 95% CI were used to identify statistically associated factors with incomplete or not at all vaccination.OutcomesIncomplete or not at all vaccination.ResultsThe prevalence of incomplete or not at all vaccinated children was 23.10% (95% CI 16.50 to 29.70). The multivariable analysis revealed that the odds of incomplete or not at all vaccination were higher among mothers who had no antenatal care (ANC) visit (AOR: 1.81, 95% CI 1.21 to 4.03) and no postnatal care (PNC) visit (AOR=1.52, 95% CI 1.05 to 2.25).ConclusionsIn the study area, nearly one-fourth of children are incompletely or not at all vaccinated. Our finding suggests that ANC and PNC visits are key determinants of incomplete or not at all vaccination. Thus, in low-resource settings like Ethiopia, the health system approaches to improved ANC and PNC services should be intensified with more effective advice on child immunisation to reduce vaccine preventable disease.
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Zheng, Shurong, Jianhua Guo, Ning-Zhong Shi y Guo-Liang Tian. "Likelihood-based approaches for multivariate linear models under inequality constraints for incomplete data". Journal of Statistical Planning and Inference 142, n.º 11 (noviembre de 2012): 2926–42. http://dx.doi.org/10.1016/j.jspi.2012.04.018.

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YENDURI, SUMANTH y S. S. IYENGAR. "PERFORMANCE EVALUATION OF IMPUTATION METHODS FOR INCOMPLETE DATASETS". International Journal of Software Engineering and Knowledge Engineering 17, n.º 01 (febrero de 2007): 127–52. http://dx.doi.org/10.1142/s0218194007003173.

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In this study, we compare the performance of four different imputation strategies ranging from the commonly used Listwise Deletion to model based approaches such as the Maximum Likelihood on enhancing completeness in incomplete software project data sets. We evaluate the impact of each of these methods by implementing them on six different real-time software project data sets which are classified into different categories based on their inherent properties. The reliability of the constructed data sets using these techniques are further tested by building prediction models using stepwise regression. The experimental results are noted and the findings are finally discussed.
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Clements, Lily, Alan C. Kimber y Stefanie Biedermann. "Multiple Imputation of Composite Covariates in Survival Studies". Stats 5, n.º 2 (29 de marzo de 2022): 358–70. http://dx.doi.org/10.3390/stats5020020.

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Missing covariate values are a common problem in survival studies, and the method of choice when handling such incomplete data is often multiple imputation. However, it is not obvious how this can be used most effectively when an incomplete covariate is a function of other covariates. For example, body mass index (BMI) is the ratio of weight and height-squared. In this situation, the following question arises: Should a composite covariate such as BMI be imputed directly, or is it advantageous to impute its constituents, weight and height, first and to construct BMI afterwards? We address this question through a carefully designed simulation study that compares various approaches to multiple imputation of composite covariates in a survival context. We discuss advantages and limitations of these approaches for various types of missingness and imputation models. Our results are a first step towards providing much needed guidance to practitioners for analysing their incomplete survival data effectively.
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