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Relevant bibliographies by topics / Ambiguity selection

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Academic literature on the topic 'Ambiguity selection'

Author: Grafiati

Published: 4 June 2021

Last updated: 17 February 2022

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Journal articles on the topic "Ambiguity selection"

1

Pflug, Georg, and David Wozabal. "Ambiguity in portfolio selection." Quantitative Finance 7, no. 4 (August 2007): 435–42. http://dx.doi.org/10.1080/14697680701455410.

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Mengle, Saket S. R., and Nazli Goharian. "Ambiguity measure feature-selection algorithm." Journal of the American Society for Information Science and Technology 60, no. 5 (May 2009): 1037–50. http://dx.doi.org/10.1002/asi.21023.

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Jin, Hanqing, and Xun Yu Zhou. "Continuous-time portfolio selection under ambiguity." Mathematical Control & Related Fields 5, no. 3 (2015): 475–88. http://dx.doi.org/10.3934/mcrf.2015.5.475.

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Draper, D. W., and D. G. Long. "An advanced ambiguity selection algorithm for seawinds." IEEE Transactions on Geoscience and Remote Sensing 41, no. 3 (March 2003): 538–47. http://dx.doi.org/10.1109/tgrs.2003.810228.

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Gupta, Ashok Kumar Gupta, and Aziz Deraman. "A framework for software requirement ambiguity avoidance." International Journal of Electrical and Computer Engineering (IJECE) 9, no. 6 (December 1, 2019): 5436. http://dx.doi.org/10.11591/ijece.v9i6.pp5436-5445.

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This research deals with software requirements ambiguity problems. Among these are incomplete, incorrect, improper, inaccurate and unambiguous requirements. Interestingly, published material related to Software Requirements Specifications (SRS) problems discusses ambiguity as one of the most conversed problems. This paper proposes a Software Requirement Ambiguity Avoidance Framework (SRAAF) to assist and support requirement engineers to write unambiguous requirements, by selecting correct elicitation technique based on the evaluation of various attributes and by applying the W6H technique. We explored existing theories and the outcomes of experimental research to construct the framework. On the basis of existing and inferred knowledge, we tried to justify proposed frameworks components. Our selection process focuses on various situational attributes. We added various situational attributes related to project, stakeholders and requirement engineer for the selection process. Newly devised approach chooses techniques other than traditional techniques or most common techniques and deals with ambiguity to capture the correct requirements information from stakeholders. The framework will be able to address the selection and ambiguity issues in a more effective way and can handle vagueness. New evidence related to attributes and adequacy matrix can be easily added to the framework without any inconvenience.

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Hasuike, Takashi, and Hiroaki Ishii. "Probability maximization models for portfolio selection under ambiguity." Central European Journal of Operations Research 17, no. 2 (January 8, 2009): 159–80. http://dx.doi.org/10.1007/s10100-008-0082-y.

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Koufopoulos, Kostas, and Roman Kozhan. "Optimal insurance under adverse selection and ambiguity aversion." Economic Theory 62, no. 4 (October 19, 2015): 659–87. http://dx.doi.org/10.1007/s00199-015-0926-3.

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Giraud, Raphaël, and Lionel Thomas. "Ambiguity, optimism, and pessimism in adverse selection models." Journal of Economic Theory 171 (September 2017): 64–100. http://dx.doi.org/10.1016/j.jet.2017.06.004.

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Yi, Bo, Frederi Viens, Baron Law, and Zhongfei Li. "Dynamic portfolio selection with mispricing and model ambiguity." Annals of Finance 11, no. 1 (June 8, 2014): 37–75. http://dx.doi.org/10.1007/s10436-014-0252-y.

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Ji, Shaolin, and Xiaomin Shi. "Reaching goals under ambiguity: Continuous-time optimal portfolio selection." Statistics & Probability Letters 137 (June 2018): 63–69. http://dx.doi.org/10.1016/j.spl.2018.01.010.

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Dissertations / Theses on the topic "Ambiguity selection"

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Draper, David. "Wind scatterometry with improved ambiguity selection and rain modeling /." Diss., CLICK HERE for online access, 2003. http://contentdm.lib.byu.edu/ETD/image/etd327.pdf.

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Draper, David W. "Wind Scatterometry with Improved Ambiguity Selection and Rain Modeling." BYU ScholarsArchive, 2003. https://scholarsarchive.byu.edu/etd/117.

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Although generally accurate, the quality of SeaWinds on QuikSCAT scatterometer ocean vector winds is compromised by certain natural phenomena and retrieval algorithm limitations. This dissertation addresses three main contributers to scatterometer estimate error: poor ambiguity selection, estimate uncertainty at low wind speeds, and rain corruption. A quality assurance (QA) analysis performed on SeaWinds data suggests that about 5% of SeaWinds data contain ambiguity selection errors and that scatterometer estimation error is correlated with low wind speeds and rain events. Ambiguity selection errors are partly due to the "nudging" step (initialization from outside data). A sophisticated new non-nudging ambiguity selection approach produces generally more consistent wind than the nudging method in moderate wind conditions. The non-nudging method selects 93% of the same ambiguities as the nudged data, validating both techniques, and indicating that ambiguity selection can be accomplished without nudging. Variability at low wind speeds is analyzed using tower-mounted scatterometer data. According to theory, below a threshold wind speed, the wind fails to generate the surface roughness necessary for wind measurement. A simple analysis suggests the existence of the threshold in much of the tower-mounted scatterometer data. However, the backscatter does not "go to zero" beneath the threshold in an uncontrolled environment as theory suggests, but rather has a mean drop and higher variability below the threshold. Rain is the largest weather-related contributer to scatterometer error, affecting approximately 4% to 10% of SeaWinds data. A simple model formed via comparison of co-located TRMM PR and SeaWinds measurements characterizes the average effect of rain on SeaWinds backscatter. The model is generally accurate to within 3 dB over the tropics. The rain/wind backscatter model is used to simultaneously retrieve wind and rain from SeaWinds measurements. The simultaneous wind/rain (SWR) estimation procedure can improve wind estimates during rain, while providing a scatterometer-based rain rate estimate. SWR also affords improved rain flagging for low to moderate rain rates. QuikSCAT-retrieved rain rates correlate well with TRMM PR instantaneous measurements and TMI monthly rain averages. SeaWinds rain measurements can be used to supplement data from other rain-measuring instruments, filling spatial and temporal gaps in coverage.

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Richards, Stephen L. "A Field-Wise Retrieval Algorithm for SeaWinds." BYU ScholarsArchive, 2003. https://scholarsarchive.byu.edu/etd/74.

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In the spring of 1999 NASA will launch the scatterometer SeaWinds, beginning a 3 year mission to measure the ocean winds. SeaWinds is different from previous spaceborne scatterometers in that it employs a rotating pencil-beam antenna as opposed to fixed fan-beam antennas. The scanning beam provides greater coverage but causes the wind retrieval accuracy to vary across the swath. This thesis develops a filed-wise wind retrieval algorithm to improve the overall wind retrieval accuracy for use with SeaWinds data. In order to test the field-wise wind retrieval algorithm, methods for simulating wind fields are developed. A realistic approach interpolates the NASA Scatterometer (NSCAT) estimates to fill a SeaWinds swath using optimal interpolation along with linear wind filed models. The two stages of the field-wise wind retrieval algorithm are filed-wise estimation and field-wise ambiguity selection. Field-wise estimation is implemented using a 22 parameter Karhunen-Loeve (KL) wind field model in conjunction with a maximum likelihood objective function. An augmented multi-start global optimization is developed which uses information from the point-wise estimates to aid in a global search of the objective function. The local minima in the objective function are located using the augmented multi-start search techniques and are stored as field-wise ambiguities. The ambiguity selection algorithm uses a field-wise median filter to select the field-wise ambiguity closest to the true wind in each region. Point-wise nudging is used to further improve the filed-wise estimate using information from the point-wise estimates. Combined, these two techniques select a good estimate of the wind 95% of the time. The overall performance of the field-wise wind retrieval algorithm is compared with the performance of the current point-wise techniques. Field-wise estimation techniques are shown to be potentially better than point-wise techniques. The field-wise estimates are also shown to be very useful tools in point-wise ambiguity selection since 95.8%-96.6% of the point-wise estimates closest to the field-wise estimates are the correct aliases.

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Williams, Brent A. "Signal Processing Methods for Ultra-High Resolution Scatterometry." Diss., CLICK HERE for online access, 2010. http://contentdm.lib.byu.edu/ETD/image/etd3529.pdf.

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Books on the topic "Ambiguity selection"

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Gorfein, David S., ed. On the consequences of meaning selection: Perspectives on resolving lexical ambiguity. Washington: American Psychological Association, 2001. http://dx.doi.org/10.1037/10459-000.

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D'Amico, Stefania. Density selection and combination under model ambiguity: An application to stock returns. Washington, D.C: Federal Reserve Board, 2005.

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Hristea, Florentina T. The Naïve Bayes Model for Unsupervised Word Sense Disambiguation: Aspects Concerning Feature Selection. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013.

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On the Consequences of Meaning Selection: Perspectives on Resolving Lexical Ambiguity. American Psychological Association (APA), 2002.

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1952-, Koslowski Peter, and Schenk Richard, eds. Ambivalenz, Ambiguität, Postmodernität: Begrenzt eindeutiges Denken. Stuttgart: Frommann-Holzboog, 2004.

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Hristea, Florentina T. The Naïve Bayes Model for Unsupervised Word Sense Disambiguation: Aspects Concerning Feature Selection. Springer, 2012.

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Harms, Mackenzie, Victoria Kennel, and Roni Reiter-Palmon. Team Creativity. Oxford University Press, 2017. http://dx.doi.org/10.1093/oso/9780190222093.003.0004.

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Creative cognition is a critical aspect of creative problem solving for both teams and individuals, but the cognitive processes underlying creativity have received more attention at the individual than the team level. This chapter focuses on early- and late-stage cognitive processes that have currently received less attention in the team creativity literature: problem construction and idea evaluation and selection. Problem construction aims to clarify problem ambiguity through restating and redefining a problem and identifying goals and parameters for consideration prior to solution generation. Idea evaluation and selection occurs after idea generation and refers to the evaluation of ideas with respect to specific standards, goals, or ideals, and the selection of ideas for pursuit in implementation. Additional research for team problem construction and team idea evaluation and selection is proposed.

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Streiner, David L., Geoffrey R. Norman, and John Cairney. Selecting the items. Oxford University Press, 2015. http://dx.doi.org/10.1093/med/9780199685219.003.0005.

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Not all of the items that have been generated will prove to be useful. This chapter discusses the criteria of a good item, such as its reading level, lack of ambiguity, asking only a single question, freedom from jargon, being worded in a positive direction, and length. Another consideration is the distribution of responses, whether all response alternatives have been used by at least some of the respondents, and when items with very low endorsement frequencies may actually be useful. It also discusses the homogeneity of the scale and the various ways of measuring it (e.g. KR-20, split-halves, and Cronbach’s alpha). Finally, it discusses when homogeneity is and is not important, and which statistical tests should not be used when homogeneity is not required.

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Sterne, Laurence. A Sentimental Journey and Other Writings. Edited by Tim Parnell and Ian Jack. Oxford University Press, 2008. http://dx.doi.org/10.1093/owc/9780199537181.001.0001.

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Love is nothing without feeling. And feeling is still less without love.' Celebrated in its own day as the progenitor of 'a school of sentimental writers', A Sentimental Journey (1768) has outlasted its many imitators because of the humour and mischievous eroticism that inform Mr Yorick's travels. Setting out to journey to France and Italy he gets little further than Lyons but finds much to appreciate, in contrast to contemporary travel writers whom Sterne satirizes in the figures of Smelfungus and Mundungus. A master of ambiguity and double entendre, Sterne is nevertheless as concerned as his peers with exploring the nature of virtue; unlike other writers of sentimental fiction Sterne insists on the inseparability of desire and feeling. This new edition includes a selection from The Sermons of Mr Yorick, which shed light on the concerns of the Journey, The Journal to Eliza, which records Sterne's feelings as he languishes for the company of Eliza Draper, and A Political Romance, the satire on a local ecclesiastical squabble that was the catalyst for Sterne's literary career.

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Jamieson, Kathleen Hall. The Need for a Science of Science Communication. Edited by Kathleen Hall Jamieson, Dan M. Kahan, and Dietram A. Scheufele. Oxford University Press, 2017. http://dx.doi.org/10.1093/oxfordhb/9780190497620.013.2.

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Communicating within and about science in a fashion that honors its norms and ways of knowing plays a role in warranting the ability of science to serve as a privileged source of premises, evidence, and conclusions in public and policy debates and decisions. Unlike political communication, in which selective uses of evidence, categorical assertion, and calculated ambiguity are stocks in trade, science’s distinctive norms and structures of enforcement entail forms of communication that take into account the available relevant evidence, specify the level of certainty attached to a claim, and precisely specifying the phenomena being analyzed or reported. This chapter discusses these issues and suggests future ways forward for science communicators.

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Book chapters on the topic "Ambiguity selection"

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Kireev, Maxim, Alexander Korotkov, Maya Zheltyakova, Denis Cherednichenko, Valeria Gershkovich, Nadezhda Moroshkina, Victor Allakhverdov, and Tatiana Chernigovskaya. "Psychophysiological Interactions Underlying Meaning Selection in Ambiguity Resolution." In Advances in Cognitive Research, Artificial Intelligence and Neuroinformatics, 213–21. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-71637-0_25.

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Wen, Zhibo, Patrick Henkel, and Christoph Günther. "Precise Point Positioning with Partial Ambiguity Fixing and Optimal Subset Selection." In International Association of Geodesy Symposia, 783–89. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/1345_2015_110.

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Antonini, Paride, Davide Petturiti, and Barbara Vantaggi. "Dynamic Portfolio Selection Under Ambiguity in the $$\epsilon $$-Contaminated Binomial Model." In Information Processing and Management of Uncertainty in Knowledge-Based Systems, 210–23. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-50143-3_16.

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Wang, Jun, and Yanming Feng. "A Satellite Selection Algorithm for Achieving High Reliability of Ambiguity Resolution with GPS and Beidou Constellations." In Lecture Notes in Electrical Engineering, 3–20. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-37407-4_1.

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Goo, S. H., and Anne Carver. "Low Structure, High Ambiguity: Selective Adaptation of International Norms of Corporate Governance Mechanisms in China." In Changing Corporate Governance Practices in China and Japan, 206–34. London: Palgrave Macmillan UK, 2008. http://dx.doi.org/10.1057/9780230595156_10.

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"Ambiguity in Portfolio Selection." In Chapman & Hall/CRC Financial Mathematics Series, 377–92. Chapman and Hall/CRC, 2008. http://dx.doi.org/10.1201/9781420081923.ch18.

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Santesteban, Mikel, and John W. Schwieter. "Lexical Selection and Competition in Bilinguals." In Bilingual Lexical Ambiguity Resolution, 126–56. Cambridge University Press, 2020. http://dx.doi.org/10.1017/9781316535967.007.

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Curry, William Sims. "Single-Score Best-Value Selection Process Eliminates Ambiguity." In Government Abuse, 145–63. Routledge, 2017. http://dx.doi.org/10.4324/9780203790472-8.

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Annesley, Claire, Karen Beckwith, and Susan Franceschet. "Institutionalist Approaches to Cabinet Appointments." In Cabinets, Ministers, and Gender, 25–59. Oxford University Press, 2019. http://dx.doi.org/10.1093/oso/9780190069018.003.0002.

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Chapter 2 sets out the book’s theoretical, conceptual, and methodological approaches for explaining gendered patterns and processes of cabinet formation. Employing a feminist institutionalist approach, the chapter explains how formal and informal rules create and maintain gendered hierarchies that have historically advantaged men in the cabinet appointment process. The chapter also shows how rules change over time, emphasizing the importance of agency, ambiguity, and ideas. The chapter offers a model of the relationship among sets of rules to produce cabinets that include women. The chapter provides justification of the case selection, methods of data collection and organization, and a description of each country case.

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Clark, Ian D. "Dissonance surrounding the Aboriginal origin of a selection of placenames in Victoria, Australia: Lessons in lexical ambiguity." In Indigenous and Minority Placenames: Australian and International Perspectives. ANU Press, 2014. http://dx.doi.org/10.22459/imp.04.2014.14.

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Conference papers on the topic "Ambiguity selection"

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Villeval, Shahar, Joseph Tabrikian, and Igal Bilik. "Ambiguity function for sequential antenna selection." In 2016 IEEE Sensor Array and Multichannel Signal Processing Workshop (SAM). IEEE, 2016. http://dx.doi.org/10.1109/sam.2016.7569753.

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Yang, Jieming, and Zhiying Liu. "Ambiguity measure-based feature selection for text categorization." In 2012 Third International Conference on Intelligent Control and Information Processing (ICICIP). IEEE, 2012. http://dx.doi.org/10.1109/icicip.2012.6391414.

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dos Santos, Eulanda M., Robert Sabourin, and Patrick Maupin. "Ambiguity-guided dynamic selection of ensemble of classifiers." In 2007 10th International Conference on Information Fusion. IEEE, 2007. http://dx.doi.org/10.1109/icif.2007.4408123.

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Liu, Zhiying, and Jieming Yang. "An Improved Ambiguity Measure Feature Selection for Text Categorization." In 2012 4th International Conference on Intelligent Human-Machine Systems and Cybernetics (IHMSC). IEEE, 2012. http://dx.doi.org/10.1109/ihmsc.2012.62.

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Kenyon, C. M., and N. A. Goodman. "Range-Doppler ambiguity mitigation via closed-loop, adaptive PRF selection." In 2010 International Conference on Electromagnetics in Advanced Applications (ICEAA). IEEE, 2010. http://dx.doi.org/10.1109/iceaa.2010.5652265.

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Mohanta, Bhagyashree, Pragyan Nanda, and Srikanta Patnaik. "Uncertainty and Ambiguity Management in Supplier Selection using Fuzzy Analytical Model." In 2019 3rd International Conference on Data Science and Business Analytics (ICDSBA). IEEE, 2019. http://dx.doi.org/10.1109/icdsba48748.2019.00044.

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Mengle, Saket S. R., and Nazli Goharian. "Using ambiguity measure feature selection algorithm for support vector machine classifier." In the 2008 ACM symposium. New York, New York, USA: ACM Press, 2008. http://dx.doi.org/10.1145/1363686.1363896.

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August, J. K., Krishna Vasudevan, and W. H. Magninie. "Effective Maintenance PM Task Selection Requirements." In International Joint Power Generation Conference collocated with TurboExpo 2003. ASMEDC, 2003. http://dx.doi.org/10.1115/ijpgc2003-40091.

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Developing an effective scheduled maintenance program requires a profound awareness of risk tolerance, dominant failure modes, failure symptoms, diagnostic methods, and work practices. Effective PM task selection is hard work. Identifying applicable and effective tasks quickly and consistently for critical equipment is the first step towards reliable, cost-effective operations. Automating the PM task selection process by using relational database software removes developmental ambiguity, which speeds up analysis, but poses practical problems. Preventive maintenance (PM) work order development can be standardized and automated to achieve this objective.

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Bradaric, Ivan, Gerard T. Capraro, and Michael C. Wicks. "Multistatic ambiguity function - A tool for waveform selection in distributed radar systems." In 2009 International Waveform Diversity and Design Conference. IEEE, 2009. http://dx.doi.org/10.1109/wddc.2009.4800311.

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Bradaric, I., G. T. Capraro, and M. C. Wicks. "Multistatic ambiguity function — A tool for waveform selection in distributed radar systems." In 2008 IEEE Antennas and Propagation Society International Symposium and USNC/URSI National Radio Science Meeting. IEEE, 2008. http://dx.doi.org/10.1109/aps.2008.4619986.

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