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Journal articles on the topic 'Comparative methods'

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Published: 4 June 2021

Last updated: 31 January 2023

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1

Yusupov, Azamat, Muyassar Khamitovna Karimova, and Mastona Zakirkhodzhayeva. "COMPARATIVE ANALYSIS OF TONOMETRY METHODS." UZBEK MEDICAL JOURNAL Special issue, no. 3 (September 30, 2021): 21–24. http://dx.doi.org/10.26739/2181-0664-2021-si-3-4.

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The principles of glaucoma diagnostics are based on the triad of symptoms -the excess of IOP over the tolerant level, changes in the visual field, primarily in the Bjerrum zone, and also on glaucomatous excavation of the optic nerve head. It should be recognized that the IOP level is the only proven risk factor for the progression of glaucomatous optic nerve atrophy and, at the same time, the only factor that we can influence. That is why the determination of IOP is of great importance in diagnosis and is the basis for evaluating the effectiveness of glaucoma treatment.Keywords: IOP (intraocular pressure), tonometry, glaucoma, primary open-angle glaucoma, glaucomatous optic neuropathy, tonometer, pneumotonometer

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2

Yusupov, Azamat, Muyassar Khamitovna Karimova, and Mastona Zakirkhodzhayeva. "COMPARATIVE ANALYSIS OF TONOMETRY METHODS." UZBEK MEDICAL JOURNAL Special issue, no. 3 (September 30, 2021): 21–24. http://dx.doi.org/10.26739/2181-0664-2021-si-3-4.

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The principles of glaucoma diagnostics are based on the triad of symptoms -the excess of IOP over the tolerant level, changes in the visual field, primarily in the Bjerrum zone, and also on glaucomatous excavation of the optic nerve head. It should be recognized that the IOP level is the only proven risk factor for the progression of glaucomatous optic nerve atrophy and, at the same time, the only factor that we can influence. That is why the determination of IOP is of great importance in diagnosis and is the basis for evaluating the effectiveness of glaucoma treatment.Keywords: IOP (intraocular pressure), tonometry, glaucoma, primary open-angle glaucoma, glaucomatous optic neuropathy, tonometer, pneumotonometer

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3

Fitzgerald, Tanya. "Comparative historical methods." History of Education 44, no. 3 (March 5, 2015): 400–402. http://dx.doi.org/10.1080/0046760x.2015.1015629.

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4

Cornwell, Will, and Shinichi Nakagawa. "Phylogenetic comparative methods." Current Biology 27, no. 9 (May 2017): R333—R336. http://dx.doi.org/10.1016/j.cub.2017.03.049.

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5

Kim, Tae-Woong. "Comparative Analysis of Estimation Methods for Basin Averaged Effective Rainfall Using NRCS-CN Method." Journal of the Korean Society of Civil Engineers 34, no. 2 (2014): 493. http://dx.doi.org/10.12652/ksce.2014.34.2.0493.

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6

Lohr, Kathleen N. "Comparative Effectiveness Research Methods." Medical Care 48 (June 2010): S3—S6. http://dx.doi.org/10.1097/mlr.0b013e3181e10434.

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7

Bolbakov, R. G., A. V. Sinitsyn, and V. Ya Tsvetkov. "Methods of comparative analysis." Journal of Physics: Conference Series 1679 (November 2020): 052047. http://dx.doi.org/10.1088/1742-6596/1679/5/052047.

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8

Thiem, Alrik. "Unifying Configurational Comparative Methods." Sociological Methods & Research 43, no. 2 (October 30, 2013): 313–37. http://dx.doi.org/10.1177/0049124113500481.

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9

Uyeda, Josef C., Rosana Zenil-Ferguson, and Matthew W. Pennell. "Rethinking phylogenetic comparative methods." Systematic Biology 67, no. 6 (April 25, 2018): 1091–109. http://dx.doi.org/10.1093/sysbio/syy031.

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10

Gittleman, J. L., and H. Luh. "On Comparing Comparative Methods." Annual Review of Ecology and Systematics 23, no. 1 (November 1992): 383–404. http://dx.doi.org/10.1146/annurev.es.23.110192.002123.

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11

Paine, Jack. "Set-Theoretic Comparative Methods." Comparative Political Studies 49, no. 6 (January 18, 2015): 703–41. http://dx.doi.org/10.1177/0010414014564851.

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12

Williams, Lloyd G. "Comparative software methods: Introduction." Journal of Systems and Software 9, no. 2 (February 1989): 79–80. http://dx.doi.org/10.1016/0164-1212(89)90011-3.

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13

vikram, Dr Archana, Dr Vikram S. Dr.Vikram S, Dr Rajalakshmi T. N. Dr.Rajalakshmi T N, Dr Ajith S. Dr.Ajith S, and Dr Rajagopal K. Dr.Rajagopal.K. "Comparative Study of Mechanical Methods for Cervical Ripening." Global Journal For Research Analysis 3, no. 2 (June 15, 2012): 172–74. http://dx.doi.org/10.15373/22778160/february2014/56.

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14

Björklund, Mats, and Mats Bjorklund. "Are 'Comparative Methods' Always Necessary?" Oikos 80, no. 3 (December 1997): 607. http://dx.doi.org/10.2307/3546637.

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15

K.Saritha, S., and R. K Pateriya. "Methods for Identifying Comparative Sentences." International Journal of Computer Applications 108, no. 19 (December 18, 2014): 23–26. http://dx.doi.org/10.5120/19020-0504.

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16

Saxena, Abhineet, Lalit Mohan Goyal, and Mamta Mittal. "Comparative Analysis of Clustering Methods." International Journal of Computer Applications 118, no. 21 (May 20, 2015): 30–35. http://dx.doi.org/10.5120/20873-3452.

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17

DeFELICE, E. GENE. "Causal Inference and Comparative Methods." Comparative Political Studies 19, no. 3 (October 1986): 415–37. http://dx.doi.org/10.1177/0010414086019003005.

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Various ways are considered to infer causality from a relatively small number of cases that can be selected but not manipulated. The development of the “comparable-cases strategy” is examined first, together with the claim that it constitutes the comparative method. Mill's “method of agreement” is then presented as an alternative method of comparison, a method that not only can and has been used quite effectively with survey research in comparative politics, but one that is completely free from the methodological short-comings attributed to it. Cases, in short, may be selected for their similarity or their contrast. But because both of these qualitative methods of comparison (even when used jointly) are considerably less powerful than the “method of concomitant variation,” a third strategy is proffered to comparativists. It is a strategy employed extensively by Durkheim, but apparently lost sight of in attempts to reduce it—as well as the method of agreement—to a single comparative method based upon comparable cases.

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18

Armstrong, Katrina. "Methods in Comparative Effectiveness Research." Journal of Clinical Oncology 30, no. 34 (December 1, 2012): 4208–14. http://dx.doi.org/10.1200/jco.2012.42.2659.

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Comparative effectiveness research (CER) seeks to assist consumers, clinicians, purchasers, and policy makers to make informed decisions to improve health care at both the individual and population levels. CER includes evidence generation and evidence synthesis. Randomized controlled trials are central to CER because of the lack of selection bias, with the recent development of adaptive and pragmatic trials increasing their relevance to real-world decision making. Observational studies comprise a growing proportion of CER because of their efficiency, generalizability to clinical practice, and ability to examine differences in effectiveness across patient subgroups. Concerns about selection bias in observational studies can be mitigated by measuring potential confounders and analytic approaches, including multivariable regression, propensity score analysis, and instrumental variable analysis. Evidence synthesis methods include systematic reviews and decision models. Systematic reviews are a major component of evidence-based medicine and can be adapted to CER by broadening the types of studies included and examining the full range of benefits and harms of alternative interventions. Decision models are particularly suited to CER, because they make quantitative estimates of expected outcomes based on data from a range of sources. These estimates can be tailored to patient characteristics and can include economic outcomes to assess cost effectiveness. The choice of method for CER is driven by the relative weight placed on concerns about selection bias and generalizability, as well as pragmatic concerns related to data availability and timing. Value of information methods can identify priority areas for investigation and inform research methods.

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19

Yee, K. F. "Comparative precision of laboratory methods." Journal of Automatic Chemistry 9, no. 2 (1987): 100–101. http://dx.doi.org/10.1155/s1463924687000221.

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20

Harvey, Paul H., and Andy Purvis. "Comparative methods for explaining adaptations." Nature 351, no. 6328 (June 1991): 619–24. http://dx.doi.org/10.1038/351619a0.

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21

EAVESIII, F., F. BARTONJR, D. KNIZE, and M. PAUL. "Comparative methods for brow lift*." Aesthetic Surgery Journal 17, no. 6 (November 1997): 397–403. http://dx.doi.org/10.1016/s1090-820x(97)80057-x.

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22

Esposito Vinzi, Vincenzo. "Explanatory methods for comparative analyses." Chemometrics and Intelligent Laboratory Systems 58, no. 2 (October 2001): 275–86. http://dx.doi.org/10.1016/s0169-7439(01)00166-6.

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23

Anykeyev, V. B., A. A. Spiridonov, and V. P. Zhigunov. "Comparative investigation of unfolding methods." Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment 303, no. 2 (June 1991): 350–69. http://dx.doi.org/10.1016/0168-9002(91)90802-w.

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24

Huggett, A. C., B. Schilter, M. Roberfroid, E. Antignac, and J. H. Koeman. "Comparative methods of toxicity testing." Food and Chemical Toxicology 34, no. 2 (February 1996): 183–92. http://dx.doi.org/10.1016/0278-6915(95)00098-4.

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25

Munck, Gerardo L. "Assessing Set-Theoretic Comparative Methods." Comparative Political Studies 49, no. 6 (January 24, 2016): 775–80. http://dx.doi.org/10.1177/0010414015626453.

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26

Smith, Michael E., Barbara L. Stark, Wen-Ching Chuang, Timothy J. Dennehy, Sharon L. Harlan, April Kamp-Whittaker, Benjamin W. Stanley, and Abigail M. York. "Comparative Methods for Premodern Cities." Cross-Cultural Research 50, no. 5 (September 23, 2016): 415–51. http://dx.doi.org/10.1177/1069397116665824.

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27

Richardson, Michael K., Jonathan E. Jeffery, M. I. Coates, and Olaf R. P. Bininda-Emonds. "Comparative methods in developmental biology." Zoology 104, no. 3-4 (January 2001): 278–83. http://dx.doi.org/10.1078/0944-2006-00033.

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28

Walker, S. "Comparative underground coal mining methods." Fuel and Energy Abstracts 37, no. 3 (May 1996): 170. http://dx.doi.org/10.1016/0140-6701(96)88326-3.

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29

Rihoux, Benoît. "Qualitative Comparative Analysis (QCA) and Related Systematic Comparative Methods." International Sociology 21, no. 5 (September 2006): 679–706. http://dx.doi.org/10.1177/0268580906067836.

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30

Romer, M. "Comparative test—Part I—Comparative test of ‘penetrability’ methods." Materials and Structures 38, no. 10 (December 2005): 895–906. http://dx.doi.org/10.1007/bf02482256.

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31

Lim, Hyun-Il. "Comparative Analysis of Technical Methods for Detecting Software Thefts." Journal of Computers 11, no. 1 (January 2016): 26–32. http://dx.doi.org/10.17706/jcp.11.1.26-32.

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32

GEORGIEV, Rumen, and Kolyo KOLEV. "COMPARATIVE ANALYSIS OF TUNING MISSILE AUTOPILOTS USING INTELLIGENT METHODS." SCIENTIFIC RESEARCH AND EDUCATION IN THE AIR FORCE 18, no. 1 (June 24, 2016): 251–58. http://dx.doi.org/10.19062/2247-3173.2016.18.1.34.

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33

Devadoss, Michael Kamaraj, and Balakrishnan Ganesan. "Comparative analysis of multiple target tracking methods." International Journal of Advances in Intelligent Informatics 2, no. 2 (July 31, 2016): 65. http://dx.doi.org/10.26555/ijain.v2i2.55.

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Many applications such as intelligent transportation, video surveillance, robotics of computer vision mainly depend on task of multiple object tracking. It includes the process of detection, classifications and tracking. The main focus of the study is to develop an efficient and effective multiple target tracking methods to solve the issues of illumination changes, occlusions and affinity matching. Accordingly, the various multiple target tracking methods are tested and evaluated using the metrics on publicly available datasets from which it is obvious that the outcome of the global energy minimization and optimization techniques is comparatively better than any other existing techniques in all aspects. This comparative study work will also help in better understanding of the problem, knowledge of the methods and experimental evaluation skill for further research works.

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34

Smith, Cindy J. "Comparative Methods: Going beyond Incorporating International Research Methods with Traditional Methods." International Journal of Comparative and Applied Criminal Justice 33, no. 2 (September 1, 2009): 211–28. http://dx.doi.org/10.1080/01924036.2009.9678806.

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35

Kashyap, Yashwant, Ankit Bansal, Anil K. Sao, and Satyanarayan Patel. "Comparative Study of Parameter Estimation Methods for Solar Irradiation Forecasting." Journal of Clean Energy Technologies 4, no. 3 (2015): 192–96. http://dx.doi.org/10.7763/jocet.2016.v4.278.

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36

Pharande, Ms Damini, and S. R. Suryawanshi. "Comparative Study of Aluminum Formwork Design Using Various Codal Methods." Journal of Advances and Scholarly Researches in Allied Education 15, no. 2 (April 1, 2018): 370–74. http://dx.doi.org/10.29070/15/56849.

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37

Fleming, Jesse. "Comparative Philosophy: Its Aims and Methods." Journal of Chinese Philosophy 30, no. 2 (February 1, 2003): 259–70. http://dx.doi.org/10.1163/15406253-03002008.

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38

Shahi, Mandira, Megh Raj Banjara, Jeny Kayastha, Amrita Chaulagain, Suni Pradhan, and Rikesh Pradhan. "Effectiveness of Teaching Methods : Comparative Outcomes." Journal of Ayurveda Campus 1, no. 1 (October 19, 2020): 16–25. http://dx.doi.org/10.51648/jac.4.

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Background: Instructional methods play an important role in developing nursing education. The objective of this study was to compare the effectiveness of lecture, small group discussion and mixed method to teach childhood diarrhea topic among 2nd year Proficiency Certificate Level (PCL) nursing students. Methods: Over a one year period, 60 2nd year PCL nursing students were divided into three groups and provided educational sessions on childhood diarrhoea. Three methods; a lecture, small group discussions and mixed methods (lecture+ small group discussion) were used separately. At the beginning, students were informed about a research study with process and questionnaires on the content of childhood diarrhea were administered to each student for pre-test. After the completion of sessions, post-test was done. They also completed a session evaluation ranged from 1(Strongly Disagree) to 5 (Strongly Agree). Classroom observation result was collected by using "A 5-Point Likert Scale" ranging from 1(poor) to 5 (excellent) by the observer with feedback. The collected data were entered in MS Excel and analyzed using latest version of SPSS. Results: Lecture method was most significantly effective for gaining factual knowledge while small group discussion was most significantly effective for gaining insightful knowledge. However mixed method is most significantly effective for learning both the procedural and insightful knowledge. Conclusion: Nursing students learning about childhood diarrhoea preferred a mixed method of lecture and small group discussions (SGDs) over traditional lecture or discussion in groups.

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39

Jia, Qi, Xu Liang Lv, Wei Dong Xu, Jiang Hua Hu, and Xian Hui Rong. "Comparative Experiment of Color Reproduction Methods." Advanced Materials Research 1051 (October 2014): 967–70. http://dx.doi.org/10.4028/www.scientific.net/amr.1051.967.

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Digital camera which has the advantage of real-time image transferring and easily processing is more and more widely used in the packaging and printing industry with the rapid development of high-tech electronics industry. However, the color in digital camera is not accurate which affect the application. To minimize the color difference between the color in the digital camera and the real color, the color reproduction methods is developing. The field comparative experiment is carried out to compare the performance of color reproduction methods, such as polynomial regression algorithm in different color space, and color checker passport. The results show that fourth order polynomial regression color reproduction in XYZ color space has the best performance.

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40

Kalambet, Y. A., Y. P. Kozmin, and A. S. Samokhin. "Noise filtering. Comparative analysis of methods." Analytics, no. 5 (2017): 88–101. http://dx.doi.org/10.22184/2227-572x.2017.36.5.88.101.

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41

Kaur, Sumit, and R. K. Bansal. "COMPARATIVE ANALYSIS OF SUPERPIXEL SEGMENTATION METHODS." International Journal of Engineering Technologies and Management Research 5, no. 3 (February 10, 2020): 1–9. http://dx.doi.org/10.29121/ijetmr.v5.i3.2018.172.

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Superpixel segmentation showed to be a useful preprocessing step in many computer vision applications. Superpixel’s purpose is to reduce the redundancy in the image and increase efficiency from the point of view of the next processing task. This led to a variety of algorithms to compute superpixel segmentations, each with individual strengths and weaknesses. Many methods for the computation of superpixels were already presented. A drawback of most of these methods is their high computational complexity and hence high computational time consumption. K mean based SLIC method shows better performance as compare to other while evaluating on the bases of under segmentation error and boundary recall, etc parameters.

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42

Bagawade, Mr Ramdas Pandurang. "Comparative Study of Object Classification Methods." International Journal for Research in Applied Science and Engineering Technology 6, no. 3 (March 31, 2018): 1498–505. http://dx.doi.org/10.22214/ijraset.2018.3232.

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43

Barbour, Rosaline S. "Using qualitative methods in comparative research." SALUTE E SOCIETÀ, no. 2 (July 2010): 65–79. http://dx.doi.org/10.3280/ses2010-su1005.

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Although quantitative and qualitative approaches are sometimes presented as being in opposition to each other, it is argued that they can, more usefully, be viewed as complementary. Qualitative work can make an important contribution both to pan-European and country-specific comparative research. Most studies have capitalized on qualitative methods at the outset of projects (principally for their ability to develop survey instruments) and, perhaps, less frequently, in order to enhance cultural sensitivity of such tools. However, more imaginative sequencing of methods can pay enormous dividends. Qualitative methods can also furnish hypotheses for investigation in quantitative phases of research studies, and can also be employed in order to better understand the mechanisms linking variables as identified by quantitative work. In particular, qualitative methods can be used to advantage in exploring surprising or anomalous findings. Stand-alone qualitative studies are also valuable, and can address comparison, since they can be harnessed to study change over time or, even, cross-country comparisons. If we are to realize the full potential of qualitative studies in comparative research, however, we need to pay attention to research design issues, seeking to be more imaginative in our sequencing of methods and appreciating the potential of purposive sampling to illuminate comparisons.

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44

Mahmood, Mo A. "System Development Methods-A Comparative Investigation." MIS Quarterly 11, no. 3 (September 1987): 293. http://dx.doi.org/10.2307/248674.

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45

Munot, Nikita, and Sharvari S. Govilkar. "Comparative Study of Text Summarization Methods." International Journal of Computer Applications 102, no. 12 (September 18, 2014): 33–37. http://dx.doi.org/10.5120/17870-8810.

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46

Smith, Scott R. "Advancing Methods for Comparative Effectiveness Research." Medical Care 48 (June 2010): S1—S2. http://dx.doi.org/10.1097/mlr.0b013e3181e1cde5.

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47

Sox, Harold C., and Steven N. Goodman. "The Methods of Comparative Effectiveness Research." Annual Review of Public Health 33, no. 1 (April 21, 2012): 425–45. http://dx.doi.org/10.1146/annurev-publhealth-031811-124610.

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48

Patrignani, Emma. "Book Review: Methods of Comparative Law." Maastricht Journal of European and Comparative Law 19, no. 4 (December 2012): 549–53. http://dx.doi.org/10.1177/1023263x1201900405.

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49

Darintsev, O. V., and A. B. Migranov. "Comparative analysis of intelligent planning methods." Proceedings of the Mavlyutov Institute of Mechanics 9, no. 2 (2012): 53–57. http://dx.doi.org/10.21662/uim2012.2.048.

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The main stages of solving the problem of planning movements by mobile robots in a non-stationary working environment based on neural networks, genetic algorithms and fuzzy logic are considered. The features common to the considered intellectual algorithms are singled out and their comparative analysis is carried out. Recommendations are given on the use of this or that method depending on the type of problem being solved and the requirements for the speed of the algorithm, the quality of the trajectory, the availability (volume) of sensory information, etc.

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50

Pang, J., R. Dukkipati, W. N. Patten, and G. Sheng. "Comparative analysis of model-reduction methods." International Journal of Heavy Vehicle Systems 10, no. 3 (2003): 224. http://dx.doi.org/10.1504/ijhvs.2003.003208.

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