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Journal articles on the topic 'Matching factors'

Author: Grafiati

Published: 4 June 2021

Last updated: 9 February 2022

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1

de Fez, M. D., P. Capilla, M. J. Luque, J. Pérez-Carpinell, and J. C. del Pozo. "Asymmetric colour matching: Memory matching versus simultaneous matching." Color Research & Application 26, no. 6 (October 8, 2001): 458–68. http://dx.doi.org/10.1002/col.1066.

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2

Nishimura, Tsuyoshi. "On 1-factors and matching extension." Discrete Mathematics 222, no. 1-3 (July 2000): 285–90. http://dx.doi.org/10.1016/s0012-365x(00)00057-1.

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3

Gabow, Harold N. "Data Structures for Weighted Matching and Extensions to b -matching and f -factors." ACM Transactions on Algorithms 14, no. 3 (July 16, 2018): 1–80. http://dx.doi.org/10.1145/3183369.

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4

Gabow, Harold N., and Piotr Sankowski. "Algorithms for Weighted Matching Generalizations I: Bipartite Graphs, b-matching, and Unweighted f-factors." SIAM Journal on Computing 50, no. 2 (January 2021): 440–86. http://dx.doi.org/10.1137/16m1106195.

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5

Kaushal, Kanica. "Matching for risk factors in case control studies." Indian Journal of Medical Research 141, no. 2 (2015): 245. http://dx.doi.org/10.4103/0971-5916.155597.

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6

Blough, Donald S. "Error factors in pigeon discrimination and delayed matching." Journal of Experimental Psychology: Animal Behavior Processes 22, no. 1 (1996): 118–31. http://dx.doi.org/10.1037/0097-7403.22.1.118.

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7

P�rez-Carpinell, Joaqu�n, Rosa Baldov�, M. Dolores de Fez, and Jos� Castro. "Color memory matching: Time effect and other factors." Color Research & Application 23, no. 4 (August 1998): 234–47. http://dx.doi.org/10.1002/(sici)1520-6378(199808)23:4<234::aid-col8>3.0.co;2-p.

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8

Demorest, Steven M., and Ann Clements. "Factors Influencing the Pitch-Matching of Junior High Boys." Journal of Research in Music Education 55, no. 3 (October 2007): 190–203. http://dx.doi.org/10.1177/002242940705500302.

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The skill of pitch-matching is a prerequisite for even the most casual musical participation. While singing accuracy has been carefully researched at the elementary level, there has been comparatively less research done with adolescents. The purpose of the study described here was to examine the influence of perceptual ability, task demands, and singing range on the pitch-matching performance of adolescent boys in various stages of the voice change. We found significant differences between certain, inconsistent, and uncertain singers in their perceptual skills and found that a contextual pitch-matching condition was significantly easier than a single-pitch condition. There was no difference by singing range. Future research should explore the progression of these skills longitudinally and continue to examine performance related to different task demands.

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9

kitchel, Tracy, and Robert Torres. "Possible Factors In Matching Student Teachers With Cooperating Teachers." Journal of Agricultural Education 48, no. 3 (September 1, 2007): 13–24. http://dx.doi.org/10.5032/jae.2007.03013.

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10

Salameh, Z. M., B. S. Borowy, and A. R. A. Amin. "Photovoltaic module-site matching based on the capacity factors." IEEE Transactions on Energy Conversion 10, no. 2 (June 1995): 326–32. http://dx.doi.org/10.1109/60.391899.

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11

Siskind, Victor, Judith P. Kelly, and David W. Kaufman. "Estimating risks for matching factors in case-control studies." Journal of Clinical Epidemiology 53, no. 3 (March 2000): 251–56. http://dx.doi.org/10.1016/s0895-4356(99)00159-6.

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12

BELL, J. R., I. GAILEY, and S. OGLESBY. "Analysis of Factors Influencing Colour Matching in Package Dyeing." Journal of the Society of Dyers and Colourists 87, no. 12 (October 22, 2008): 432–37. http://dx.doi.org/10.1111/j.1478-4408.1971.tb02985.x.

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13

Körner, Jürgen G. "The helicity matching approach to heavy hadron form factors." Nuclear Physics B - Proceedings Supplements 21 (June 1991): 366–77. http://dx.doi.org/10.1016/0920-5632(91)90278-m.

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14

Nevin, John A. "Stimulus factors in addiction." Behavioral and Brain Sciences 19, no. 4 (December 1996): 590–91. http://dx.doi.org/10.1017/s0140525x00043193.

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AbstractHeyman's analysis of addiction in terms of matching to local relative value can be supplemented by stimulus-control processes. Stimulus equivalence can broaden the set of situations that occasion addictive behavior, and the situation-reinforcer correlation can enhance its persistence. The joint effects of stimulus-control and reinforcement processes may complicate treatment.

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15

Lucas, Hannah B., Ian McKnight, Regan Raines, Abdullah Hijazi, Christoph Hart, Chan Lee, Do-Gyoon Kim, Wei Li, Peter H. U. Lee, and Joon W. Shim. "Factors Associated with Mutations: Their Matching Rates to Cardiovascular and Neurological Diseases." International Journal of Molecular Sciences 22, no. 10 (May 11, 2021): 5057. http://dx.doi.org/10.3390/ijms22105057.

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Monogenic hypertension is rare and caused by genetic mutations, but whether factors associated with mutations are disease-specific remains uncertain. Given two factors associated with high mutation rates, we tested how many previously known genes match with (i) proximity to telomeres or (ii) high adenine and thymine content in cardiovascular diseases (CVDs) related to vascular stiffening. We extracted genomic information using a genome data viewer. In human chromosomes, 64 of 79 genetic loci involving >25 rare mutations and single nucleotide polymorphisms satisfied (i) or (ii), resulting in an 81% matching rate. However, this high matching rate was no longer observed as we checked the two factors in genes associated with essential hypertension (EH), thoracic aortic aneurysm (TAA), and congenital heart disease (CHD), resulting in matching rates of 53%, 70%, and 75%, respectively. A matching of telomere proximity or high adenine and thymine content projects the list of loci involving rare mutations of monogenic hypertension better than those of other CVDs, likely due to adoption of rigorous criteria for true-positive signals. Our data suggest that the factor–disease matching rate is an accurate tool that can explain deleterious mutations of monogenic hypertension at a >80% match—unlike the relatively lower matching rates found in human genes of EH, TAA, CHD, and familial Parkinson’s disease.

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16

Thornton, William A. "Intersections of matching spectra: Applications." Color Research & Application 18, no. 6 (December 1993): 412–21. http://dx.doi.org/10.1002/col.5080180609.

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17

Hu, Xin, and Kevin W. Houser. "Large-field color matching functions." Color Research & Application 31, no. 1 (2005): 18–29. http://dx.doi.org/10.1002/col.20170.

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18

Zhu, Juan, Xinyi Niu, and Cheng Shi. "The Influencing Factors of a Polycentric Employment System on Jobs-Housing Matching—A Case Study of Hangzhou, China." Sustainability 11, no. 20 (October 17, 2019): 5752. http://dx.doi.org/10.3390/su11205752.

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This paper discusses the relationship between the polycentric spatial structure and jobs-housing matching and its influencing factors in the urbanized area of Hangzhou City in China. First, 42 employment centers are identified while using the method of the threshold value of employment density and employment to residence ratio based on the places of employment and residence that were identified from cellphone signaling data. This study found that Hangzhou have remarkable features of a polycentric system. Second, we use the jobs-housing matching rate index to measure the jobs-housing matching characteristics of employment centers. We found that the polycentric structure does not guarantee jobs-housing matching of all centers, although nearly half of the employment centers had good jobs-housing matching and 14.29% do not achieve jobs-housing matching, which indicates the uncertainty of “co-location hypothesis” in China. Employment centers of different levels, industry types, and locations also display certain regularity in their jobs-housing matching level. Third, by using correlation analysis and stepwise multiple regression analysis, we found that, besides the polycentric factor, the spatial and industrial factors also exert a certain effect on jobs-housing matching, reasonable control of the employment center size, employment to resident ratio, and industrial diversity are the determinants that affect the jobs-housing matching level.

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19

Nithipatikom, Kasem, and Linda B. McGown. "Factors Affecting Calibration for Phase-Modulation Fluorescence Lifetime Determinations." Applied Spectroscopy 40, no. 4 (May 1986): 549–53. http://dx.doi.org/10.1366/0003702864508854.

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The effects of several instrumental and experimental factors on phase-modulation fluorescence lifetime determinations of dimethyl POPOP, 9,10-diphenylanthracene, and benzo(a)pyrene were evaluated with the use of both a scattering solution and dimethylPOPOP as references for phase and modulation calibration. For the scattering solution reference, best results were obtained when the scatterer was measured within a few nanometers of the resonance peak corresponding to the excitation wavelength used for measuring the sample. Intensity matching of the reference (either scatterer or dimethylPOPOP) to the sample solution does not appear to be required as long as the sample solution exhibits lifetime homogeneity and the sample and reference are measured with the same voltage applied to the photomultiplier tube detector. Intensity matching to within 10–20% does appear to be indicated for samples with lifetime heterogeneity. When intensity matching is used, the intensities should be matched by adjustment of the reference solution concentration rather than by changing the wavelengths used to measure the reference.

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20

Khalid, Mariya, and Mohammad Ali Chughtai. "Art and Science of Shade Matching." Dental Update 47, no. 3 (March 2, 2020): 238–45. http://dx.doi.org/10.12968/denu.2020.47.3.238.

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Shade selection is an important step in restorative procedures. The objective of this step is to provide aesthetically pleasing restorations which blend in with the existing dentition of the patient. This article highlights clinical difficulties which may hinder proper shade selection and a number of factors causing these difficulties. For ease of understanding, these factors have been divided into four categories. These are factors related to the dentist, the shade matching environment, the material used for shade selection and the patient. Because shade selection is an important step, it is recommended that this step should be given sufficient time. A checklist and a form for shade selection have also been devised to avoid any oversights during shade selection. This will help improve dentist laboratory communication which can result in an improved and aesthetically pleasing restoration. CPD/Clinical Relevance: Shade selection is a crucial step in the process of fabricating an aesthetically pleasing restoration.

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21

Do, Myungsik, Wanhee Byun, Doh Kyoum Shin, and Hyeryun Jin. "Factors Influencing Matching of Ride-Hailing Service Using Machine Learning Method." Sustainability 11, no. 20 (October 12, 2019): 5615. http://dx.doi.org/10.3390/su11205615.

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It is common to call a taxi by taxi-apps in Korea and it was believed that an app-taxi service would provide customers with more convenience. However, customers’ requests can often be denied, as taxi drivers can decide whether to take calls from customers or not. Therefore, studies on factors that determine whether taxi drivers refuse or accept calls from customers are needed. This study investigated why taxi drivers might refuse calls from customers and factors that influence the success of matching within the service. This study used origin-destination data in Seoul and Daejeon obtained from T-map Taxis, which was analyzed via a decision tree using machine learning. Cross-validation was also performed. Results showed that distance, socio-economic features, and land uses affected matching success rate. Furthermore, distance was the most important factor in both Seoul and Daejeon. The matching success rate in Seoul was lowest for trips shorter than the average at midnight. In Daejeon, the rate was lowest when the calls were made for trips either shorter or longer than the average distance. This study showed that the matching success for ride-hailing services can be differentiated particularly by the distance of the requested trip depending on the size of the city.

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22

McCoy, Claire Wehr. "Factors Relating to Pitch-Matching Skills of Elementary Education Majors." Journal of Research in Music Education 45, no. 3 (October 1997): 356–66. http://dx.doi.org/10.2307/3345531.

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23

Liu, Gong-shen, and Sheng-jun Zhu. "The factors analysis and algorithm implementation of single-pattern matching." Journal of Shanghai Jiaotong University (Science) 14, no. 3 (June 2009): 331–37. http://dx.doi.org/10.1007/s12204-009-0331-9.

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24

Hill, Jacquelyne L. "Perceptions of Factors Affecting Student-Patient Matching in Clinical Experiences." Journal of Nursing Education 32, no. 3 (March 1993): 133–34. http://dx.doi.org/10.3928/0148-4834-19930301-09.

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25

Jeang, Angus, Chang Pu Ko, Chien-Ping Chung, Francois Liang, and Guan-Ying Chen. "Experimental design and analysis of matching design." International Journal of Quality & Reliability Management 36, no. 7 (August 5, 2019): 1078–87. http://dx.doi.org/10.1108/ijqrm-07-2018-0200.

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Purpose This study considers the five factors of a car rotation system: angle (F1), arm length (F2), toe in and out (F3), width (F4) and length (F5). The purpose of this paper is to fine tune the design so it produces the smoothest response to various rotation angles. Design/methodology/approach In the case of Ackerman’s principle, the response surface methodology (RSM) was used to analyze data when encountering different quality characteristics at various rotation angles. Findings In this study, RSM was used to obtain the best factor and the best reaction value for the five factors of a car rotation system. Practical implications In this study, the four-wheel steering of a car is taken as an example. When the current wheel is turned, the intersection of the left and right wheels of the front axle falls on the extension line of the rear wheel. In this case, the steering will be the smoothest. In this example, we selected angle (F1), arm length (F2), toe in and out (F3), width (F4) and length (F5) as experimental factors, hoping to satisfy the Ackerman principle. Social implications Traditionally, when dealing with four-wheel steering problems, solutions may be based on past experience or on new information used to formulate R&D plans. In this study, the combination of statistical factors and optimization is used to find the optimal combination of factors and the relationship between factors. Originality/value In the past, most literature relied on kinematics to study the car rotation system due to a lack of experimental design and analysis concepts. However, this study aims to achieve the above goals in finding the solution, which can be used to predict reaction values.

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26

Zimmerman, Barret J., and Alyson J. McGregor. "Sex- and Gender-Related Factors in Blood Product Transfusions." Gender and the Genome 4 (January 1, 2020): 247028972094806. http://dx.doi.org/10.1177/2470289720948064.

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Blood products are indicated for a plethora of conditions in several settings, with a variety of products available for transfusion, from highly processed specific components to whole blood. Matching the donor product to the recipient is crucial in avoiding serious transfusion reactions, with the extent of matching depending on the physiological need, setting, and product. There are important factors related to sex and gender differences in donated blood products, adverse reactions to those products, interplay with underlying pathology, as well as sociocultural differences in the collection. This article will review key sex- and gender-specific research related to the use of blood products with an emphasis on the acute care setting.

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27

North, Amy D., and Mark D. Fairchild. "Measuring color-matching functions. Part I." Color Research & Application 18, no. 3 (June 1993): 155–62. http://dx.doi.org/10.1002/col.5080180305.

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28

Borbély, Ákos, and János Schanda. "Colour matching using LEDs as primaries." Color Research & Application 29, no. 5 (July 26, 2004): 360–64. http://dx.doi.org/10.1002/col.20044.

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29

Nadasdi, Terry. "Subject NP doubling, matching, and minority French." Language Variation and Change 7, no. 1 (March 1995): 1–14. http://dx.doi.org/10.1017/s0954394500000879.

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ABSTRACTOur study presents a variationist analysis of subject doubling in the French of Ontario, Canada. Two principal variants are distinguished: a non-doubled variant and a doubled variant containing a clitic agreement marker. In our analyses, both linguistic and social factors are taken into account and analyzed usinggoldvarb2. It is proposed that subject clitics are marked for default features, and that the doubled variant is favored when the clitic's default features match those of the subject NP; lack of matching favors the non-doubled variant. Discussion of linguistic factors for the present study, therefore, is limited to those factors which can be explained in terms matching. The principal social factor studied is restricted language use (cf. Mougeon & Beniak, 1991). Our results show that the greater the restriction, the fewer doubled subjects one finds.

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30

Zhang, Yuan. "Influence of Teacher-Student Matching on Knowledge Innovation of College Students." International Journal of Emerging Technologies in Learning (iJET) 16, no. 01 (January 12, 2021): 262. http://dx.doi.org/10.3991/ijet.v16i01.19721.

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The relationship between teacher-student matching and knowledge innovation of college students is constrained by multiple factors. Considering the multiple constraints, this paper explores deep into the influence of teacher-student matching on knowledge innovation of college students. Firstly, the internal correlation between the two factors was identified through analysis. Next, the detailed contents of the two factors were examined, and used to set up an analysis model to improve knowledge innovation of college students based on teacher-student matching. Grey system theory and analytic hierarchy process (AHP) were implemented in the modeling process. Finally, several strategies were put forward to promote knowledge innovation among college students, from the perspective of teacher-student matching. The research results provide a strong support to knowledge innovation in colleges.

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31

Price, Harry E. "Interval Matching by Undergraduate Nonmusic Majors." Journal of Research in Music Education 48, no. 4 (December 2000): 360–72. http://dx.doi.org/10.2307/3345369.

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This article describes the sixth in a series of studies designed to gain a better understanding of factors that may affect pitch matching. Undergraduate nonmusic majors ( N = 141) enrolled in a music fundamentals class were classified as uncertain, modulating, or certain singers. They listened to a stimulus tape of descending minor thirds, sung by men in their normal and falsetto registers (G3-E3 and G4-E4, respectively, with G3 (middle C being C4), and to two sine-wave stimuli in the same octaves and attempted to sing back the interval they heard. There were no significant differences in the accuracy of responses to male and sine-wave stimuli or between men and women participants. There were significant differences among singer types, with inaccurate singers being less in tune than either modulating or certain singers. There was a significant interaction of response accuracy between participant sex and stimulus octave. These results differ somewhat from previous research with children, in which stimulus timbre and participant sex were factors.

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32

Kim, Sung Han, Eun Young Park, Jungnam Joo, Jae Young Joung, Ho Kyung Seo, Jinsoo Chung, and Kang Hyun Lee. "Effect of Neoadjuvant Hormone Therapy on Resection Margin and Survival Prognoses in Locally Advanced Prostate Cancer after Prostatectomy Using Propensity-Score Matching." BioMed Research International 2018 (December 6, 2018): 1–7. http://dx.doi.org/10.1155/2018/4307207.

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This study aimed to investigate the effect of neoadjuvant hormone therapy (NHT) on resection margin positivity, biochemical-recurrence- (BCR-) free survival, and overall survival (OS) in 176 patients with locally advanced prostate cancer (LAPC) treated with radical prostatectomy using propensity-score matching, including 79 (44.9%) patients treated with the NHT. Fifty pairs of one-to-one propensity-score matching were matched to investigate the pure effect of NHT on resection margin positivity, BCR, and OS with a statistical significance of p<0.050. Before matching, NHT, tumor volume percentage, and extracapsular extension were significant factors for resection margin positivity (p≤0.001); however, after matching, NHT became insignificant in the multivariate analysis (p=0.084). In the survival analysis, NHT was not associated with BCR or OS before and after matching (BCR: hazard ratio, 1.35 and 0.84, respectively; OS: hazard ratio, 1.05 and 0.77, respectively; p≥0.539 for all). Conversely, PSA level (HR, 2.23), extracapsular extension (HR, 2.10), and lymphovascular invasion (HR, 1.85) were significant factors for BCR (p≤0.001 for all), but none were significant factors for OS in the propensity-score matching analysis (p≥0.948). Therefore, NHT was not a significant factor for resection margin positivity, BCR-free survival, and OS before and after propensity-score matching in patients with LAPC.

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Sullivan Pepe, Margaret, Jing Fan, Christopher W. Seymour, Christopher Li, Ying Huang, and Ziding Feng. "Biases Introduced by Choosing Controls to Match Risk Factors of Cases in Biomarker Research." Clinical Chemistry 58, no. 8 (August 1, 2012): 1242–51. http://dx.doi.org/10.1373/clinchem.2012.186007.

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Abstract BACKGROUND Selecting controls that match cases on risk factors for the outcome is a pervasive practice in biomarker research studies. Such matching, however, biases estimates of biomarker prediction performance. The magnitudes of these biases are unknown. METHODS We examined the prediction performance of biomarkers and improvements in prediction gained by adding biomarkers to risk factor information. Data simulated from bivariate normal statistical models and data from a study to identify critically ill patients were used. We compared true performance with that estimated from case control studies that do or do not use matching. ROC curves were used to quantify performance. We propose a new statistical method to estimate prediction performance from matched studies for which data on the matching factors are available for subjects in the population. RESULTS Performance estimated with standard analyses can be grossly biased by matching, especially when biomarkers are highly correlated with matching risk factors. In our studies, the performance of the biomarker alone was underestimated whereas the improvement in performance gained by adding the marker to risk factors was overestimated by 2–10-fold. We found examples for which the relative ranking of 2 biomarkers for prediction was inappropriately reversed by use of a matched design. The new approach to estimation corrected for bias in matched studies. CONCLUSIONS To properly gauge prediction performance in the population or the improvement gained by adding a biomarker to known risk factors, matched case control studies must be supplemented with risk factor information from the population and must be analyzed with nonstandard statistical methods.

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34

Zhou, M., L. S. Chen, J. H. Wang, G. E. Teng, C. R. Li, Q. Q. Yao, and J. Y. Chen. "ANALYSIS OF INFLUENCING FACTORS OF CURVE MATCHING BASED GEOMETRIC CALIBRATION FOR ZY3-02 ALTIMETER DATA." ISPRS Annals of Photogrammetry, Remote Sensing and Spatial Information Sciences IV-2/W7 (September 16, 2019): 221–26. http://dx.doi.org/10.5194/isprs-annals-iv-2-w7-221-2019.

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<p><strong>Abstract.</strong> High-precision on-orbit geometric calibration of spaceborne laser altimetry data is essential to its effective applications. Firstly, the existing calibration methods for laser altimeter data are analyzed. Then, a geometric calibration method based on curve matching is proposed. Compared to the existing methods, the proposed method does not rely on ground calibration field. Thus, it is efficiency in expense and time. Notably, three factors, i.e. matching method, initial control point selection and the step size of matching step, which significantly affect the results of calibration are analyzed respectively. The analysis was validated based on the original laser altimetry data obtained by ZY3-02 satellite. According to the results, the following conclusions can be drawn preliminarily: (1) Both the correlation coefficient maximum (COR) criterion and the mean square error minimum (MSD) criterion in the curve matching can be used to correct the systematic error in altimetry data. (2) The initial control points of the selected track should have a significant change trend and the slope within the laser footprints should be less than 15&deg;. (3) Current experimental data show that the best step size for matching search is 10&thinsp;m. The relevant conclusions can provide reference for the research of geometrical calibration and data processing of the same type of laser altimetry satellite.</p>

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Huang, Xu, Xue Wan, and Daifeng Peng. "Robust Feature Matching with Spatial Smoothness Constraints." Remote Sensing 12, no. 19 (September 26, 2020): 3158. http://dx.doi.org/10.3390/rs12193158.

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Feature matching is to detect and match corresponding feature points in stereo pairs, which is one of the key techniques in accurate camera orientations. However, several factors limit the feature matching accuracy, e.g., image textures, viewing angles of stereo cameras, and resolutions of stereo pairs. To improve the feature matching accuracy against these limiting factors, this paper imposes spatial smoothness constraints over the whole feature point sets with the underlying assumption that feature points should have similar matching results with their surrounding high-confidence points and proposes a robust feature matching method with the spatial smoothness constraints (RMSS). The core algorithm constructs a graph structure from the feature point sets and then formulates the feature matching problem as the optimization of a global energy function with first-order, spatial smoothness constraints based on the graph. For computational purposes, the global optimization of the energy function is then broken into sub-optimizations of each feature point, and an approximate solution of the energy function is iteratively derived as the matching results of the whole feature point sets. Experiments on close-range datasets with some above limiting factors show that the proposed method was capable of greatly improving the matching robustness and matching accuracy of some feature descriptors (e.g., scale-invariant feature transform (SIFT) and Speeded Up Robust Features (SURF)). After the optimization of the proposed method, the inlier number of SIFT and SURF was increased by average 131.9% and 113.5%, the inlier percentages between the inlier number and the total matches number of SIFT and SURF were increased by average 259.0% and 307.2%, and the absolute matching accuracy of SIFT and SURF was improved by average 80.6% and 70.2%.

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Sineshaw, Helmneh M., Kimmie Ng, W. Dana Flanders, Otis W. Brawley, and Ahmedin Jemal. "Factors contributing to the black/white colorectal cancer survival disparity in nonelderly patients." Journal of Clinical Oncology 35, no. 15_suppl (May 20, 2017): 3587. http://dx.doi.org/10.1200/jco.2017.35.15_suppl.3587.

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3587 Background: Previous studies reported that black/white survival disparities among elderly colorectal cancer (CRC) patients largely reflect differences in tumor presentation rather than differences in treatment. We sought to determine the contribution of differences in tumor presentation and receipt of treatment to the black/white survival disparity among nonelderly CRC patients. Methods: We selected non-Hispanic black (black) and Non-Hispanic white (white) patients aged 18-64 years, and diagnosed between 2004-2012 with single or first primary invasive stage I-IV CRC in the National Cancer Data Base. Blacks were sequentially matched with three white comparison cohorts, using propensity score and greedy matching algorithm, by demographics (age, sex, diagnosis year, region), tumor presentation (stage, grade, margin, tumor location, node status, comorbidity score), and treatment (surgery, chemotherapy, radiotherapy, metastatectomy) characteristics. We used Kaplan-Meier method to estimate 5-year survival for blacks compared with whites in the entire cohort and in the three sequentially matched cohorts. Results: In the entire cohort, 5-year survival was 9.2% lower in nonelderly blacks than whites (57.3% vs 66.5%). The survival difference remained unchanged after demographic matching, but it decreased to 3.3% (5.9% absolute and 64% relative reductions) after tumor presentation matching, and to 2.6% (0.7% absolute and 7.6% relative reductions) after treatment matching. By anatomic subsite, treatment matching reduced the black/white 5-year survival difference by 26% (3%/11.5%) for rectal cancer, only by 5.6% (0.5%/9%) for left colon cancer, and no change for right colon cancer. Conclusions: Differences in tumor presentation characteristics explained about two-thirds of the black/white survival disparity in nonelderly CRC patients, while treatment explained less than ten percent of the disparity. Future research should explore the biological mechanisms underlying these observed differences in tumor presentation and implications for treatment.

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37

Abidin, Zainal, Indra Gita Anugrah, and Ryco Puji Setyono. "Maksimalisasi Penggunaan Metode Profile Matching dalam Menentukan Kandidat Terbaik." Jurnal Informatika Universitas Pamulang 4, no. 3 (September 30, 2019): 95. http://dx.doi.org/10.32493/informatika.v4i3.3249.

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Determine the best candidate in a company is something that is natural. There are several methods to determine the best candidate. One of them using the "Profile Matching" method. The method will rate employees from the highest to the lowest value, the assessment is carried out with several aspects of assessment which are categorized into two categories, namely core factors and scondary factors. Core factor is an assessment of the main factors in an assessment and the scondary factor is the supporting factors in an assessment. In weight determining the core factor and scondary factors greatly influence the results of the assessment. With the use of the "Profile Matching" method, it is expected that employee assessment can be maximized and provide results as expected. But in the calculation, there are several factors that are very influential so that the results obtained are unsuitable. Normal calculation using the Profile Matching method with standard values is the middle value produces the best candidate that is not appropriate. Requires modification of the weighting gap table so that the results produced can be maximized and appropriate.

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Li, Qiang, and Guan Nan Li. "The Method of Automatic Counting of Circular Objects Based on the Matching Method of Fuzzy Circular Template." Advanced Materials Research 490-495 (March 2012): 2609–13. http://dx.doi.org/10.4028/www.scientific.net/amr.490-495.2609.

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Importing ideas of Geometry and Fuzzy into traditional matching method of template, generates the matching method of fuzzy circular template. The template of this method is data of a circle with fixed radius and width of line by fuzzy function, its matching is judging the extent of similarity of the object of matching bitmap and fuzzy circular of template. This method utilizes efficiently the shape of matching object and overcome disadvantageous influence of the factors of bitmap noise and unequal size and irregular shape of matching object.

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39

Zammit, Michael D., Thomas P. Davis, and Kevin G. Suddaby. "Factors influencing detector matching in multidetector SEC: solvent and concentration effects." Polymer 39, no. 23 (November 1998): 5789–98. http://dx.doi.org/10.1016/s0032-3861(97)10373-1.

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Chhabra, Ekta Seth, and Henry N. Higgs. "The many faces of actin: matching assembly factors with cellular structures." Nature Cell Biology 9, no. 10 (October 2007): 1110–21. http://dx.doi.org/10.1038/ncb1007-1110.

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Wycherley, Ian Michael, and Elaine Cox. "Factors in the selection and matching of executive coaches in organisations." Coaching: An International Journal of Theory, Research and Practice 1, no. 1 (March 2008): 39–53. http://dx.doi.org/10.1080/17521880701878075.

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Rantanen, Esa M., Douglas A. Wiegmann, Brent O. Palmer, and Kevin M. Musiorski. "A Human Factors Database for Matching Human Errors and Technological Interventions." Proceedings of the Human Factors and Ergonomics Society Annual Meeting 47, no. 4 (October 2003): 782–86. http://dx.doi.org/10.1177/154193120304700426.

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Liu, T., and RB Altman. "Identifying Druggable Targets by Protein Microenvironments Matching: Application to Transcription Factors." CPT: Pharmacometrics & Systems Pharmacology 3, no. 1 (January 2014): 93. http://dx.doi.org/10.1038/psp.2013.66.

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Wang, Fuhong, Hannah Ji, and Peiyan Zhou. "Inference of Mobile Matching Factors on Accounting and Finance Job Performance." International Journal of Mobile Communications 19, no. 1 (2021): 1. http://dx.doi.org/10.1504/ijmc.2021.10034215.

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45

Han, Yutong, Bin Wang, Xiaochun Yang, Tao Qiu, and Huaijie Zhu. "Efficient regular expression matching on LZ77 compressed strings using negative factors." World Wide Web 22, no. 6 (March 23, 2019): 2519–43. http://dx.doi.org/10.1007/s11280-019-00667-z.

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HAGLIN, DAVID J. "BIPARTITE EXPANDER MATCHING IS IN NC." Parallel Processing Letters 05, no. 03 (September 1995): 413–20. http://dx.doi.org/10.1142/s0129626495000382.

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A work-efficient deterministic [Formula: see text] algorithm is presented for finding a maximum matching in a bipartite expander graph with any expansion factor β > 1. This improves upon a recently presented deterministic [Formula: see text] maximum matching algorithm which is restricted to those bipartite expanders with large expansion factors (β ≥ Δ∊, ∊ > 0), and is not work-efficient [1].

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Pierce, Percy E., and Robert T. Marcus. "Radiative transfer theory solid color-matching calculations." Color Research & Application 22, no. 2 (April 1997): 72–87. http://dx.doi.org/10.1002/(sici)1520-6378(199704)22:2<72::aid-col3>3.0.co;2-0.

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Sluban, Boris, and James H. Nobbs. "Colour correctability of a colour-matching recipe." Color Research & Application 22, no. 2 (April 1997): 88–95. http://dx.doi.org/10.1002/(sici)1520-6378(199704)22:2<88::aid-col4>3.0.co;2-#.

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Cogno, J. A. "Recursive quadratic programming algorithm for color matching." Color Research & Application 13, no. 2 (April 1988): 124–26. http://dx.doi.org/10.1002/col.5080130211.

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Oleari, Claudio. "Inter-observer comparison of color-matching functions." Color Research & Application 24, no. 3 (June 1999): 177–84. http://dx.doi.org/10.1002/(sici)1520-6378(199906)24:3<177::aid-col4>3.0.co;2-#.

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