Bibliografie tematiche / Interaction analysis

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Letteratura scientifica selezionata sul tema "Interaction analysis"

Autore: Grafiati
Pubblicato: 4 giugno 2021
Ultima modifica: 25 luglio 2025

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Articoli di riviste sul tema "Interaction analysis"

1

Bataeva, Ekaterina V. "Аction-analysis and interaction-analysis of cybercommunication". Sociological Journal 21, № 1 (2015): 6–22. http://dx.doi.org/10.19181/socjour.2015.21.1.1247.

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Han, Ying, Liang Cheng, and Weiju Sun. "Analysis of Protein-Protein Interaction Networks through Computational Approaches." Protein & Peptide Letters 27, no. 4 (2020): 265–78. http://dx.doi.org/10.2174/0929866526666191105142034.

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Abstract (sommario):
The interactions among proteins and genes are extremely important for cellular functions. Molecular interactions at protein or gene levels can be used to construct interaction networks in which the interacting species are categorized based on direct interactions or functional similarities. Compared with the limited experimental techniques, various computational tools make it possible to analyze, filter, and combine the interaction data to get comprehensive information about the biological pathways. By the efficient way of integrating experimental findings in discovering PPIs and computational
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Lin, C. Y., and C. S. Lin. "Investigation of genotype-environment interaction by cluster analysis in animal experiments." Canadian Journal of Animal Science 74, no. 4 (1994): 607–12. http://dx.doi.org/10.4141/cjas94-089.

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The conventional ANOVA (F ratio of GE interaction mean squares to error mean square) provides a means to test if GE interaction is significant, but it does not tell us which factor levels are significantly different or how they are interacting. To answer the latter question, plant researchers developed a technique to group genotypes for similarity of GE interactions and through the resulting groups to explore the GE interaction structure. The basic idea of the technique is to stratify genotypes (or environments) into subgroups such that GE interactions among genotypes (or environments) are hom
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Alqaseer, Ahlam Mohammed. "Interaction Analysis of Smoking with Liver Function Tests." International Journal Of Pharmaceutical And Bio-Medical Science 02, no. 11 (2022): 513–17. http://dx.doi.org/10.47191/ijpbms/v2-i11-07.

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Introduction: Smoking has been linked to harmful health impacts on several body organs including the cardiovascular system. Study objectives: The primary goal of the current study is to assess how smoking models affect the level of liver enzymes. Methods: Thirty male albino rats served as the subjects for this experimental study. We used male albino rats (Rattusratas) that were 6–8 weeks old and weighed 50–180 g. Rats were randomly allocated to one of three groups (n = 10): group 1 served as a negative control and was solely exposed to fresh air; group 2 was exposed to the most popular cigaret
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Bublyk, Yevhen, Olena Borzenko, and Anna Hlazova. "Cryptocurrency energy consumption: Analysis, global trends and interaction." Environmental Economics 14, no. 2 (2023): 49–59. http://dx.doi.org/10.21511/ee.14(2).2023.04.

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The rapid spread of cryptocurrencies is one of the most relevant trends today. One of the significant risks of their spread is the increase in energy consumption, which has a negative impact on the environment due to carbon emissions. This requires the development of a scientific toolkit for assessing relationships and predicting the impact of cryptocurrencies on energy consumption, which is the aim of this paper.With the correlational regression analysis, the model of the dependence of spending on IT sector, energy consumption of Bitcoin, Ethereum and global capitalization of the cryptocurren
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Curtis, Aaron A., Yajun Yu, Megan Carey, Yildiz E. Yilmaz, and Sevtap Savas. "A genome-wide SNP-SNP interaction analysis exploring novel interacting loci associated with the risk of recurrence in colorectal cancer." PLOS One 20, no. 6 (2025): e0321967. https://doi.org/10.1371/journal.pone.0321967.

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Background Genetic factors can influence and predict patient outcomes. The association of interactions of germline SNPs with patient outcomes is an understudied area of prognostic research. In this study, we applied the first genome-wide SNP-SNP interaction analysis in relation to colorectal cancer outcomes. Objectives Our objective was to explore interacting SNP loci at the genome-wide level that predict the risk of local or distant recurrence (RMFS) in a cohort of stage I-III colorectal cancer patients from the Canadian province of Newfoundland and Labrador. Methods The patient cohort consis
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HAYASHI, YOSHIHARU, MIME KOBAYASHI, KATSUYOSHI SAKAGUCHI, et al. "PROTEIN CLASSIFICATION USING COMPARATIVE MOLECULAR INTERACTION PROFILE ANALYSIS SYSTEM." Journal of Bioinformatics and Computational Biology 02, no. 03 (2004): 497–510. http://dx.doi.org/10.1142/s0219720004000703.

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We recently introduced a new molecular description factor, interaction profile Factor (IPF) that is useful for evaluating molecular interactions. IPF is a data set of interaction energies calculated by the Comparative Molecular Interaction Profile Analysis system (CoMIPA). CoMIPA utilizes AutoDock 3.0 docking program, and the system has shown to be a powerful tool in clustering the interacting properties between small molecules and proteins. In this report, we describe the application of CoMIPA for protein clustering. A sample set of 15 proteins that share less than 20% homology and have no co
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Sainyakit, Paulus, and Yan Imam Santoso. "A Classroom Interaction Analysis of Teacher and Students by Using FIACS." Acitya: Journal of Teaching and Education 6, no. 1 (2024): 157–67. http://dx.doi.org/10.30650/ajte.v6i1.3825.

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Classroom interaction plays an important role in the teaching and learning process. It is because it involves the interaction between teacher, student and student-student in which they influence each other in the classroom interaction. It is also said that classroom interaction gives a chance to ask, to guess, to think even to the course material in order to make interaction between the teacher and students their selves in the classroom. This research is aimed to analyze the classroom interaction by using FIACS. This research is included as a quantitative content analysis design. This research
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Kulharia, Mahesh. "Geometrical and electro-static determinants of protein-protein interactions." Bioinformation 17, no. 10 (2021): 851–60. http://dx.doi.org/10.6026/97320630017851.

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Protein-protein interactions (PPI) are pivotal to the numerous processes in the cell. Therefore, it is of interest to document the analysis of these interactions in terms of binding sites, topology of the interacting structures and physiochemical properties of interacting interfaces and the of forces interactions. The interaction interface of obligatory protein-protein complexes differs from that of the transient interactions. We have created a large database of protein-protein interactions containing over100 thousand interfaces. The structural redundancy was eliminated to obtain a non-redunda
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JOHNSTON, RICHARD D., and GEOFFREY W. BARTON. "Structural interaction analysis." International Journal of Control 41, no. 4 (1985): 1005–13. http://dx.doi.org/10.1080/0020718508961179.

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Tesi sul tema "Interaction analysis"

1

Telliskivi, Tanel. "Wheel-rail Interaction Analysis." Doctoral thesis, KTH, Machine Design, 2003. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-3532.

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<p>A general approach to numerically simulating wear in rollingand sliding contacts is presented in this thesis. A simulationscheme is developed that calculates the wear at a detailedlevel. The removal of material follows Archard’s wear law,which states that the reduction of volume is linearlyproportional to the sliding distance, the normal load and thewear coefficient. The target application is the wheel-railcontact.</p><p>Careful attention is paid to stress properties in the normaldirection of the contact. A Winkler method is used to calculatethe normal pressure. The model is calibrated eith
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Hanook, Sharoon. "Analysis of Removable Interaction." Case Western Reserve University School of Graduate Studies / OhioLINK, 2014. http://rave.ohiolink.edu/etdc/view?acc_num=case1413761250.

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Dowling, Michelle Veronica. "Semantic Interaction for Symmetrical Analysis and Automated Foraging of Documents and Terms." Diss., Virginia Tech, 2020. http://hdl.handle.net/10919/104682.

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Sensemaking tasks, such as reading many news articles to determine the truthfulness of a given claim, are difficult. These tasks require a series of iterative steps to first forage for relevant information and then synthesize this information into a final hypothesis. To assist with such tasks, visual analytics systems provide interactive visualizations of data to enable faster, more accurate, or more thorough analyses. For example, semantic interaction techniques leverage natural or intuitive interactions, like highlighting text, to automatically update the visualization parameters using machi
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Sarker, Biswajit. "Organized Chaos! : Untangling multigenerational group interactions in a gamified science center." Thesis, Uppsala universitet, Människa-datorinteraktion, 2015. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-263555.

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This inductive study investigates interactions within groups of visitors during a science center visit. Using simplified interaction analysis of recorded videos; I explore the group dynamics in terms of what determines who takes the lead while multigenerational groups interact with different types of experiments. From the observations, I suggest that the age of different group members and specific design aspects of the experiments play the most important roles in the emergence of leadership. Teenagers in a group tend to take the leadership and dominate during a group interaction, while young c
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Lan, Chinchun. "Analysis of soil-root interaction." Connect to resource, 1985. http://rave.ohiolink.edu/etdc/view?acc%5Fnum=osu1119365654.

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Khouly, Mohamed A. "Analysis of soil-reinforcement interaction /." The Ohio State University, 1995. http://rave.ohiolink.edu/etdc/view?acc_num=osu1487863429092366.

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Ralph, Alan. "The verbal interaction analysis system: A valid measure of competence in interpersonal interactions." Thesis, Ralph, Alan (1988) The verbal interaction analysis system: A valid measure of competence in interpersonal interactions. PhD thesis, Murdoch University, 1988. https://researchrepository.murdoch.edu.au/id/eprint/50427/.

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This thesis proposes a novel approach to the assessment of persons experiencing difficulties with interpersonal interactions. Conversation skills were selected as the focus of the research, these being an important element in such interactions. A broad review of psychological research associated with 4 different perspectives on this topic indicated a variety of approaches to defining, assessing and remediating problems Social, developmental, with interpersonal interactions. educational and clinical perspectives were explored. Clinically useful measurement procedures either evaluated the global
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Campagna, Anne. "Structural analysis of protein interaction networks." Doctoral thesis, Universitat Pompeu Fabra, 2012. http://hdl.handle.net/10803/84111.

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Abstract (sommario):
Interactions between proteins give rise to many functions in cells. In the lastdecade, highthroughput experiments have identified thousands of protein interactions, which are often represented together as large protein interaction networks. However, the classical way of representing interaction networks, as nodes and edges, is too limited to take dynamic properties such as compatible and mutually exclusive interactions into account. In this work, we study protein interaction networks using structural information. More specifically, the analysis of protein interfaces in threedimensional protein
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Thorpe, Christopher John. "Structural analysis of MHC : peptide interaction." Thesis, Birkbeck (University of London), 1996. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.321649.

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Greville-Harris, G. "Child-infant interaction : A micro-analysis." Thesis, Open University, 1985. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.371040.

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Libri sul tema "Interaction analysis"

1

Milnes, Peter D. Cultural interaction analysis. 2nd ed. Belco Consulting, 2008.

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Quasthoff, Uta M. Narrative interaction. John Benjamins Pub., 2005.

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Norris, Sigrid. Identity in interaction: Introducing multimodal interaction analysis. Walter de Gruyter, 2011.

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Robert, Englebretson, ed. Stancetaking in discourse: Subjectivity, evaluation, interaction. John Benjamins Pub., 2007.

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H, Blumberg Herbert, ed. Dramaturgical analysis of social interaction. Praeger, 1988.

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Hare, A. Paul. Dramaturgical analysis of social interaction. Praeger, 1988.

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1953-, Vidmar Thomas J., and McKean Joseph W. 1944-, eds. Drug interaction and lethality analysis. CRC Press, 1988.

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1946-, Kalton Nigel J., Saab E. 1946-, and Montgomery-Smith Stephen 1963-, eds. Interaction between functional analysis, harmonic analysis, and probability. Marcel Dekker, 1996.

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Georgakopoulou, Alexandra. Small stories, interaction, and identities. John Benjamins Pub. Co., 2007.

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Kerbrat-Orecchioni, Catherine. Le discours en interaction. A. Colin, 2005.

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Capitoli di libri sul tema "Interaction analysis"

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Jones, Rodney H. "Strategic Interaction." In Discourse Analysis, 3rd ed. Routledge, 2024. http://dx.doi.org/10.4324/9781003377405-7.

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Miller, Elizabeth R. "Interaction Analysis." In The Palgrave Handbook of Applied Linguistics Research Methodology. Palgrave Macmillan UK, 2018. http://dx.doi.org/10.1057/978-1-137-59900-1_27.

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Jin, Ying. "Interaction analysis." In Doctor–patient Communication in Chinese and Western Medicine. Routledge, 2022. http://dx.doi.org/10.4324/9781003161929-3.

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Cleophas, Ton J., and Aeilko H. Zwinderman. "Interaction." In Clinical Data Analysis on a Pocket Calculator. Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-27104-0_25.

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Cleophas, Ton J., and Aeilko H. Zwinderman. "Interaction." In Clinical Data Analysis on a Pocket Calculator. Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-27104-0_41.

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Shi, Dan. "Multimodal interaction analysis." In Multimodality and Classroom Languaging Dynamics. Routledge, 2021. http://dx.doi.org/10.4324/9781003183457-3.

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Bainbridge, William Sims. "Text Analysis." In Human–Computer Interaction Series. Springer London, 2013. http://dx.doi.org/10.1007/978-1-4471-5604-8_7.

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Clift, Rebecca, Paul Drew, and Ian Hutchby. "Conversation analysis." In The Pragmatics of Interaction. John Benjamins Publishing Company, 2009. http://dx.doi.org/10.1075/hoph.4.02cli.

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Cleophas, Ton J., and Aeilko H. Zwinderman. "Interaction." In Statistical Analysis of Clinical Data on a Pocket Calculator. Springer Netherlands, 2011. http://dx.doi.org/10.1007/978-94-007-1211-9_18.

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Eriksson, Kjell-Ove, and Makonnen Belew. "Hydrophobic Interaction Chromatography." In Methods of Biochemical Analysis. John Wiley & Sons, Inc., 2011. http://dx.doi.org/10.1002/9780470939932.ch6.

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Atti di convegni sul tema "Interaction analysis"

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Lettner, Florian, Christian Grossauer, and Clemens Holzmann. "Mobile interaction analysis." In the 16th international conference. ACM Press, 2014. http://dx.doi.org/10.1145/2628363.2628384.

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Shiri, Maryam Shiri, Jameleddine Hassine Hassine, and Juergen Rilling. "Feature interaction analysis." In the twenty-second IEEE/ACM international conference. ACM Press, 2007. http://dx.doi.org/10.1145/1321631.1321703.

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Cakir, Murat Perit, and Gerry Stahl. "Interaction analysis of dual-interaction CSCL environments." In the 9th international conference. Association for Computational Linguistics, 2009. http://dx.doi.org/10.3115/1600053.1600055.

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Browne, Jeffrey, Bongshin Lee, Sheelagh Carpendale, Nathalie Riche, and Timothy Sherwood. "Data analysis on interactive whiteboards through sketch-based interaction." In the ACM International Conference. ACM Press, 2011. http://dx.doi.org/10.1145/2076354.2076383.

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Basilio, Samuel da Costa Alves, Marcelo Ferreira Moreno, and Eduardo Barrére. "Interaction and audience analysis in interactive digital TV systems." In the 18th Brazilian symposium. ACM Press, 2012. http://dx.doi.org/10.1145/2382636.2382712.

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Basilio, Samuel da Costa Alves, Marcelo Ferreira Moreno, and Eduardo Barrére. "Supporting interaction and audience analysis in interactive TV systems." In the 11th european conference. ACM Press, 2013. http://dx.doi.org/10.1145/2465958.2465977.

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Chu, Sidney K., Samuel Guanglin Xu, Feng Xu, and Nelson L. S. Tang. "Gene-gene Interaction Analysis by IAC (Interaction Analysis by Chi-Square) - A Novel Biological Constraint-based Interaction Analysis Framework." In 7th International Conference on Bioinformatics Models, Methods and Algorithms. SCITEPRESS - Science and and Technology Publications, 2016. http://dx.doi.org/10.5220/0005654601420150.

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Viccione, Giacomo, Vittorio Bovolin, and Eugenio Pugliese Carratelli. "Simulating fluid-structure interaction with SPH." In NUMERICAL ANALYSIS AND APPLIED MATHEMATICS ICNAAM 2012: International Conference of Numerical Analysis and Applied Mathematics. AIP, 2012. http://dx.doi.org/10.1063/1.4756099.

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Ramos, Paulo, João T. Mexia, Francisco Carvalho, et al. "Interaction in Balanced Cross Nested Designs." In NUMERICAL ANALYSIS AND APPLIED MATHEMATICS ICNAAM 2011: International Conference on Numerical Analysis and Applied Mathematics. AIP, 2011. http://dx.doi.org/10.1063/1.3636918.

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"ISS Plasma Interaction Analysis." In 55th International Astronautical Congress of the International Astronautical Federation, the International Academy of Astronautics, and the International Institute of Space Law. American Institute of Aeronautics and Astronautics, 2004. http://dx.doi.org/10.2514/6.iac-04-t.2.03.

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Rapporti di organizzazioni sul tema "Interaction analysis"

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Isaac, Daron, and Michael Iverson. Automated Fluid-Structure Interaction Analysis. Defense Technical Information Center, 2003. http://dx.doi.org/10.21236/ada435321.

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Wood, Sheila J., Russ Granzow, William Petri, and Jr. Recognition Using Biospecific Interaction Analysis. Defense Technical Information Center, 1991. http://dx.doi.org/10.21236/ada241879.

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Zhenkun, Lou. Functional Analysis of Chk2-Kiaa0170 Interaction. Defense Technical Information Center, 2005. http://dx.doi.org/10.21236/ada449840.

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Lou, Zhenkun. Functional Analysis of Chk2-Kiaa0170 Interaction. Defense Technical Information Center, 2004. http://dx.doi.org/10.21236/ada429482.

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Liu, Antony K. Wavelet Analysis of Air-sea Interaction. Defense Technical Information Center, 1997. http://dx.doi.org/10.21236/ada629299.

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Terrill, Eric J. CBLAST Data Analysis: Air-Sea Interaction Floats. Defense Technical Information Center, 2009. http://dx.doi.org/10.21236/ada495437.

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J. Keifer and M. Taylor. PERMANENT ROCKBOLT AND TEMPORARY CHANNEL INTERACTION ANALYSIS. Office of Scientific and Technical Information (OSTI), 1995. http://dx.doi.org/10.2172/883422.

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SIbert, Linda E., James N. Templeman, and Robert J. Jacob. Evaluation and Analysis of Eye Gaze Interaction. Defense Technical Information Center, 2001. http://dx.doi.org/10.21236/ada389984.

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Liu, Wing K. Multiresolution Analysis of Compressible Viscous Flow-Structure Interaction. Defense Technical Information Center, 2000. http://dx.doi.org/10.21236/ada377739.

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Briscoe, William John, Igor I. Strakovsky, and Ronald L. Workman. A Data Analysis Center for Electromagnetic and Hadronic Interaction. Office of Scientific and Technical Information (OSTI), 2015. http://dx.doi.org/10.2172/1213477.

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