Validation of Novel Metrics from the Accommodative Dynamic Profile

Objective and subjective methods of assessing time taken for accommodative change (ToAC) include accommodative dynamics (AD) and accommodative facility (AF). This study investigates the validity of novel metrics derived from the AD-profile and explores their relationship with AF. AD were assessed using a modified open-field autorefractor in 43 healthy adults. Non-linear regression curves were fitted to the data to derive: latency-of-accommodation (nLoA) and -disaccomodation (nLoD), Time-for-accommodation (ToA) and -disaccommodation (ToD), and objective-ToAC (oToAC). Latencies were also calculated through visual inspection of the AD data as in previous studies (pLoA and pLoD). AF was used to assess subjective-ToAC. Statistical analysis explored the relationships between the AD-metrics and AF. Subjects were assessed on three visits to examine intra- and inter-observer repeatability. nLoA and nLoD were greater than pLoA (p = 0.001) and pLoD (p = 0.004) respectively. nLoA and nLoD also demonstrated greater intra- and inter-observer repeatability than pLoA and pLoD. AF demonstrated a moderate, inverse correlation with ToA (p = 0.02), ToD (p = 0.007), and oToAC (p = 0.007). ToD was the single best accommodative predictor of AF (p = 0.011). The novel method for deriving latency was more repeatable, but not interchangeable with the techniques used in previous studies. ToD was the most repeatable metric with the greatest association with AF.

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Improved conditional imputation for linear regression with a randomly censored predictor

Statistical Methods in Medical Research ◽

10.1177/0962280217727033 ◽

2017 ◽

Vol 28 (2) ◽

pp. 432-444 ◽

Cited By ~ 5

Author(s):

Folefac D Atem ◽

Emmanuel Sampene ◽

Thomas J Greene

Keyword(s):

Cardiovascular Disease ◽

Linear Regression ◽

Limit Of Detection ◽

Analytic Method ◽

The Novel ◽

Complete Case ◽

Parental History ◽

History Of ◽

Novel Method ◽

Randomly Censored

This article describes a nonparametric conditional imputation analytic method for randomly censored covariates in linear regression. While some existing methods make assumptions about the distribution of covariates or underestimate standard error due to lack of imputation error, the proposed approach is distribution-free and utilizes resampling to correct for variance underestimation. The performance of the novel method is assessed using simulations, and results are contrasted with methods currently used for a limit of detection censored design, including the complete case approach and other nonparametric approaches. Theoretical justifications for the proposed method are provided, and its application is demonstrated through a study of association between lipoprotein cholesterol in offspring and parental history of cardiovascular disease.

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Novel method for determining 234U-238U ages of Devils Hole 2 cave calcite (Nevada)

10.5194/egusphere-egu21-1955 ◽

2021 ◽

Author(s):

Xianglei Li ◽

Kathleen A. Wendt ◽

Yuri Dublyansky ◽

Gina E. Moseley ◽

Christoph Spötl ◽

...

Keyword(s):

Linear Regression ◽

The Novel ◽

Time Intervals ◽

Devils Hole ◽

Calcite Deposition ◽

Dating Method ◽

Novel Method ◽

Multi Linear Regression ◽

Over Time

Uranium-uranium (234U-238U) disequilibrium dating can determine the age of secondary carbonates over greater time intervals than the well-established 230Th-234U dating method. Yet it is rarely applied due to unknowns in the initial d234U (d234Ui) value, which result in significant age uncertainties. In order to understand the d234Ui in Devils Hole 2 cave, Nevada, we have determined 110 d234Ui values from phreatic calcite using 230Th-234U disequilibrium dating. The sampled calcite was deposited in Devils Hole 2 between 4 and 590 ka, providing a long-term look at d234Ui variability over time. We then performed multi-linear regression among the d234Ui values and correlative d18O and d13C values. The regression can be used to estimate the d234Ui value of Devils Hole calcite based upon its measured d18O and d13C values. Using this approach and the measured present-day d234U values of Devils Hole 2 calcite, we calculated 110 independent 234U-238U ages. In addition, we used newly measured d18O, d13C, and present-day d234U values to calculate 10 234U-238U ages that range between 676 and 731 ka, thus allowing us to extend the Devils Hole chronology beyond the 230Th-234U-dated chronology while maintaining an age precision of ~2 %. Our results indicate that calcite deposition at Devils Hole 2 cave began no later than 736 &#177; 11 kyr ago. The novel method presented here may be applied to future speleothem studies in similar hydrogeological settings, given appropriate calibration studies.

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A novel method for the determination of linting propensity of paper

TAPPI Journal ◽

10.32964/tj11.10.9 ◽

2012 ◽

Vol 11 (10) ◽

pp. 9-17

Author(s):

ALESSANDRA GERLI ◽

LEENDERT C. EIGENBROOD

Keyword(s):

Ash Content ◽

The Novel ◽

Offset Printing ◽

Excellent Correlation ◽

End Conditions ◽

Bottom Side ◽

Novel Method ◽

Total Fraction

A novel method was developed for the determination of linting propensity of paper based on printing with an IGT printability tester and image analysis of the printed strips. On average, the total fraction of the surface removed as lint during printing is 0.01%-0.1%. This value is lower than those reported in most laboratory printing tests, and more representative of commercial offset printing applications. Newsprint paper produced on a roll/blade former machine was evaluated for linting propensity using the novel method and also printed on a commercial coldset offset press. Laboratory and commercial printing results matched well, showing that linting was higher for the bottom side of paper than for the top side, and that linting could be reduced on both sides by application of a dry-strength additive. In a second case study, varying wet-end conditions were used on a hybrid former machine to produce four paper reels, with the goal of matching the low linting propensity of the paper produced on a machine with gap former configuration. We found that the retention program, by improving fiber fines retention, substantially reduced the linting propensity of the paper produced on the hybrid former machine. The papers were also printed on a commercial coldset offset press. An excellent correlation was found between the total lint area removed from the bottom side of the paper samples during laboratory printing and lint collected on halftone areas of the first upper printing unit after 45000 copies. Finally, the method was applied to determine the linting propensity of highly filled supercalendered paper produced on a hybrid former machine. In this case, the linting propensity of the bottom side of paper correlated with its ash content.

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Detection of Leukemia Using Image Processing

International Journal of Advanced Research in Computer Science and Software Engineering ◽

10.23956/ijarcsse.v8i4.632 ◽

2018 ◽

Vol 8 (4) ◽

pp. 61

Author(s):

A. Sivasangari ◽

G. Sasikumar

Keyword(s):

Image Processing ◽

Statistical Analysis ◽

Early Detection ◽

Visual Inspection ◽

Causes Of Death ◽

Cure Rate ◽

Blood Disorders ◽

Detection And Diagnosis ◽

The Moment ◽

Early Detection And Diagnosis

Leukemia disease is one of the leading causes of death among human. Its cure rate and prognosis depends mainly on the early detection and diagnosis of the disease. At the moment, identification of blood disorders is through visual inspection of microscopic images by examining changes like texture, geometry, colour and statistical analysis of images . This project aims to preliminary of developing a detection of leukemia types using microscopic blood sample using MATLAB. Images are used as they are cheap and do not expensive for testing and lab equipment.

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The ground-level ozone concentration is inversely correlated with the number of COVID-19 cases in Warsaw, Poland

Air Quality Atmosphere & Health ◽

10.1007/s11869-021-01009-7 ◽

2021 ◽

Author(s):

Oskar Wiśniewski ◽

Wiesław Kozak ◽

Maciej Wiśniewski

Keyword(s):

Wind Speed ◽

Ozone Concentration ◽

Inverse Correlation ◽

Ground Level ◽

Viral Agent ◽

The Novel ◽

Weather Factors ◽

Ground Level Ozone ◽

The Many ◽

The Impact

AbstractCOVID-19, which is a consequence of infection with the novel viral agent SARS-CoV-2, first identified in China (Hubei Province), has been declared a pandemic by the WHO. As of September 10, 2020, over 70,000 cases and over 2000 deaths have been recorded in Poland. Of the many factors contributing to the level of transmission of the virus, the weather appears to be significant. In this work, we analyze the impact of weather factors such as temperature, relative humidity, wind speed, and ground-level ozone concentration on the number of COVID-19 cases in Warsaw, Poland. The obtained results show an inverse correlation between ground-level ozone concentration and the daily number of COVID-19 cases.

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REMAXINT: a two-mode clustering-based method for statistical inference on two-way interaction

Advances in Data Analysis and Classification ◽

10.1007/s11634-021-00441-y ◽

2021 ◽

Author(s):

Zaheer Ahmed ◽

Alberto Cassese ◽

Gerard van Breukelen ◽

Jan Schepers

Keyword(s):

Null Hypothesis ◽

Type I Error ◽

Type I ◽

The Novel ◽

Simulation Studies ◽

Test Statistic ◽

Clustering Model ◽

Novel Method ◽

Main Effects ◽

Empirical Case Studies

AbstractWe present a novel method, REMAXINT, that captures the gist of two-way interaction in row by column (i.e., two-mode) data, with one observation per cell. REMAXINT is a probabilistic two-mode clustering model that yields two-mode partitions with maximal interaction between row and column clusters. For estimation of the parameters of REMAXINT, we maximize a conditional classification likelihood in which the random row (or column) main effects are conditioned out. For testing the null hypothesis of no interaction between row and column clusters, we propose a $$max-F$$ m a x - F test statistic and discuss its properties. We develop a Monte Carlo approach to obtain its sampling distribution under the null hypothesis. We evaluate the performance of the method through simulation studies. Specifically, for selected values of data size and (true) numbers of clusters, we obtain critical values of the $$max-F$$ m a x - F statistic, determine empirical Type I error rate of the proposed inferential procedure and study its power to reject the null hypothesis. Next, we show that the novel method is useful in a variety of applications by presenting two empirical case studies and end with some concluding remarks.

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A Novel Method Based on Linear Regression Model for Identify the Sensitivity of Quantitative Trait in ADNI Cohort

Proceedings of the 2nd International Conference on Vision, Image and Signal Processing - ICVISP 2018 ◽

10.1145/3271553.3271558 ◽

2018 ◽

Author(s):

Zhang Qiushi ◽

Li Jin ◽

Chen Dandan

Keyword(s):

Linear Regression ◽

Regression Model ◽

Linear Regression Model ◽

Quantitative Trait ◽

Novel Method

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Interrogating the Egypto-Sudanic Arabic Connection

Languages ◽

10.3390/languages6030123 ◽

2021 ◽

Vol 6 (3) ◽

pp. 123

Author(s):

Thomas A. Leddy-Cecere

Keyword(s):

The Novel ◽

Present Contribution ◽

Phonological Processes ◽

Verbal Inflection ◽

Segmental Phonology ◽

Language Data ◽

History Of ◽

Novel Method ◽

Dialect Classification ◽

Arabic Speaking

The Arabic dialectology literature repeatedly asserts the existence of a macro-level classificatory relationship binding the Arabic speech varieties of the combined Egypto-Sudanic area. This proposal, though oft-encountered, has not previously been formulated in reference to extensive linguistic criteria, but is instead framed primarily on the nonlinguistic premise of historical demographic and genealogical relationships joining the Arabic-speaking communities of the region. The present contribution provides a linguistically based evaluation of this proposed dialectal grouping, to assess whether the postulated dialectal unity is meaningfully borne out by available language data. Isoglosses from the domains of segmental phonology, phonological processes, pronominal morphology, verbal inflection, and syntax are analyzed across six dialects representing Arabic speech in the region. These are shown to offer minimal support for a unified Egypto-Sudanic dialect classification, but instead to indicate a significant north–south differentiation within the sample—a finding further qualified via application of the novel method of Historical Glottometry developed by François and Kalyan. The investigation concludes with reflection on the implications of these results on the understandings of the correspondence between linguistic and human genealogical relationships in the history of Arabic and in dialectological practice more broadly.

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Suspended Sediment Modeling Using a Heuristic Regression Method Hybridized with Kmeans Clustering

Sustainability ◽

10.3390/su13094648 ◽

2021 ◽

Vol 13 (9) ◽

pp. 4648

Author(s):

Rana Muhammad Adnan ◽

Kulwinder Singh Parmar ◽

Salim Heddam ◽

Shamsuddin Shahid ◽

Ozgur Kisi

Keyword(s):

Clustering Algorithm ◽

Suspended Sediments ◽

Ecological Impacts ◽

Accurate Estimation ◽

Data Sets ◽

The Novel ◽

Neuro Fuzzy ◽

Adaptive Regression ◽

Novel Method ◽

Model Training

The accurate estimation of suspended sediments (SSs) carries significance in determining the volume of dam storage, river carrying capacity, pollution susceptibility, soil erosion potential, aquatic ecological impacts, and the design and operation of hydraulic structures. The presented study proposes a new method for accurately estimating daily SSs using antecedent discharge and sediment information. The novel method is developed by hybridizing the multivariate adaptive regression spline (MARS) and the Kmeans clustering algorithm (MARS–KM). The proposed method’s efficacy is established by comparing its performance with the adaptive neuro-fuzzy system (ANFIS), MARS, and M5 tree (M5Tree) models in predicting SSs at two stations situated on the Yangtze River of China, according to the three assessment measurements, RMSE, MAE, and NSE. Two modeling scenarios are employed; data are divided into 50–50% for model training and testing in the first scenario, and the training and test data sets are swapped in the second scenario. In Guangyuan Station, the MARS–KM showed a performance improvement compared to ANFIS, MARS, and M5Tree methods in term of RMSE by 39%, 30%, and 18% in the first scenario and by 24%, 22%, and 8% in the second scenario, respectively, while the improvement in RMSE of ANFIS, MARS, and M5Tree was 34%, 26%, and 27% in the first scenario and 7%, 16%, and 6% in the second scenario, respectively, at Beibei Station. Additionally, the MARS–KM models provided much more satisfactory estimates using only discharge values as inputs.

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