Estimation of excess volume and density of ternary liquid mixtures of non-electrolytes from binary data

1982 ◽  
Vol 47 (5) ◽  
pp. 1414-1419 ◽  
Author(s):  
Ivan Cibulka
Keyword(s):  
Density Estimation ◽  
Binary Data ◽  
Excess Volume ◽  
Maximum Error ◽  
Liquid Mixtures ◽  
Volume Estimation ◽  
Ternary Mixtures ◽  
Data Sets ◽  
Mean Error ◽  
The Mean

Several methods for estimating the excess volume and density of ternary liquid mixtures of non-electrolytes from binary data are tested using 27 sets of data from the literature. The mean error of the excess volume estimation is lower than 0.1 cm3 mol-1. The use of the tested methods for estimating the density of ternary mixtures results in a significant reduction of the error compared to the stimation when the mixture is considered to be ideal. In decisive majority of the data sets, the maximum error in the density estimation is lower than 0.1%.

Measurements of the excess volume of benzene-methanol, benzene-acetonitrile and methanol-acetonitrile mixtures by a vibrating-tube densimeter

1979 ◽  
Vol 44 (2) ◽  
pp. 295-306 ◽  
Author(s):  
Ivan Cibulka ◽  
Vladimír Hynek ◽  
Robert Holub ◽  
Jiří Pick
Keyword(s):  
Excess Volume ◽  
Density Measurement ◽  
Indirect Measurement ◽  
Measuring System ◽  
Mean Error ◽  
Shaped Tube ◽  
Underlying Principle ◽  
The Mean ◽  
Vibrating Tube Densimeter

A digital vibrating-tube densimeter was constructed for measuring the density of liquids at several temperatures. The underlying principle of the apparatus is the measurement of the period of eigen-vibrations of a V-shaped tube; the second power of the period of the vibrations is proportional to the density of the liquid in the tube. The temperature of the measuring system is controlled by an electronic regulator. The mean error in the density measurement is approximately ±1 . 10-5 g cm-3 at 25 °C and ±2 . 10-5 g cm-3 at 40 °C. The apparatus was used for an indirect measurement of the excess volume, tested with the benzene-cyclohexane system and further used for determining the excess volume of the benzene-methanol, benzene-acetonitrile and methanol-acetonitrile systems at 25 and 40 °C.

Electrode-Skin Impedance Component Estimation in the Time-Domain

2019 ◽  
Author(s):  
Benjamin C. Fortune ◽  
Lachlan R. McKenzie ◽  
Logan T. Chatfield ◽  
Christopher G. Pretty
Keyword(s):  
Human Subject ◽  
Simulated Data ◽  
Maximum Error ◽  
Exponential Model ◽  
Skin Impedance ◽  
Bipolar Electrode ◽  
Passive Component ◽  
Data Sets ◽  
Mean Error ◽  
The Individual

Abstract This paper presents a method to estimate the individual component values of a bipolar electrode-skin interface, with future intent of applying compensatory electrode-skin impedance balancing prior recording bio-signals with electromyography. The electrode-skin interface was stimulated by a step input and the output behaviour was characterised using a single exponential model per electrode. The method was applied to simulated circuitry, passive component circuitry and a human subject. The accuracy of the method was determined using the known values that comprised the simulated and passive component circuitry. Nine of ten simulated data sets resulted in accurate estimations, with a maximum error of 0.763% and a mean error of 0.076% per component. The method also produced successful estimates for nine of the ten physical circuitry data sets, with a maximum error of 10.2% and a mean error of 3.49% per component. The method was unsuccessful in estimating the individual electrode-skin impedance components for the human subject: this was due to the system failing to reach steady state during the stimulation period. The authors suspect a DC offset caused by the half-cell potentials associated with the electrode-skin interface were the cause of the unexpected behaviour.

scholarly journals Tractable Multivariate Binary Density Estimation and the Restricted Boltzmann Forest

2010 ◽  
Vol 22 (9) ◽  
pp. 2285-2307 ◽  
Author(s):  
Hugo Larochelle ◽  
Yoshua Bengio ◽  
Joseph Turian
Keyword(s):  
Density Estimation ◽  
Binary Data ◽  
Mixture Modeling ◽  
Data Sets ◽  
Boltzmann Machine ◽  
Binary Variables ◽  
Multivariate Binary Data ◽  
Hidden Layer ◽  
Binary Density ◽  
Density Modeling

We investigate the problem of estimating the density function of multivariate binary data. In particular, we focus on models for which computing the estimated probability of any data point is tractable. In such a setting, previous work has mostly concentrated on mixture modeling approaches. We argue that for the problem of tractable density estimation, the restricted Boltzmann machine (RBM) provides a competitive framework for multivariate binary density modeling. With this in mind, we also generalize the RBM framework and present the restricted Boltzmann forest (RBForest), which replaces the binary variables in the hidden layer of RBMs with groups of tree-structured binary variables. This extension allows us to obtain models that have more modeling capacity but remain tractable. In experiments on several data sets, we demonstrate the competitiveness of this approach and study some of its properties.

The Age of Nonsynonymous and Synonymous Mutations in Animal mtDNA and Implications for the Mildly Deleterious Theory

Genetics ◽  
1999 ◽  
Vol 153 (1) ◽  
pp. 497-506 ◽  
Author(s):  
Rasmus Nielsen ◽  
Daniel M Weinreich
Keyword(s):  
Dna Sequences ◽  
Purifying Selection ◽  
Data Sets ◽  
Deleterious Mutations ◽  
Synonymous Mutations ◽  
Weak Evidence ◽  
Mitochondrial Data ◽  
The Mean ◽  
Excess Number ◽  
Neutral Mutations

Abstract McDonald/Kreitman tests performed on animal mtDNA consistently reveal significant deviations from strict neutrality in the direction of an excess number of polymorphic nonsynonymous sites, which is consistent with purifying selection acting on nonsynonymous sites. We show that under models of recurrent neutral and deleterious mutations, the mean age of segregating neutral mutations is greater than the mean age of segregating selected mutations, even in the absence of recombination. We develop a test of the hypothesis that the mean age of segregating synonymous mutations equals the mean age of segregating nonsynonymous mutations in a sample of DNA sequences. The power of this age-of-mutation test and the power of the McDonald/Kreitman test are explored by computer simulations. We apply the new test to 25 previously published mitochondrial data sets and find weak evidence for selection against nonsynonymous mutations.

scholarly journals New Methodology for Computing the Aircraft’s Position Based on the PPP Method in GPS and GLONASS Systems

Energies ◽  
2021 ◽  
Vol 14 (9) ◽  
pp. 2525
Author(s):  
Kamil Krasuski ◽  
Damian Wierzbicki
Keyword(s):  
Linear Combination ◽  
Research Method ◽  
High Efficiency ◽  
Satellite System ◽  
Weighting Scheme ◽  
Measurement Technology ◽  
Dual Frequency ◽  
Weighted Mean ◽  
Mean Error ◽  
The Mean

In the field of air navigation, there is a constant pursuit for new navigation solutions for precise GNSS (Global Navigation Satellite System) positioning of aircraft. This study aims to present the results of research on the development of a new method for improving the performance of PPP (Precise Point Positioning) positioning in the GPS (Global Positioning System) and GLONASS (Globalnaja Nawigacionnaja Sputnikovaya Sistema) systems for air navigation. The research method is based on a linear combination of individual position solutions from the GPS and GLONASS systems. The paper shows a computational scheme based on the linear combination for geocentric XYZ coordinates of an aircraft. The algorithm of the new research method uses the weighted mean method to determine the resultant aircraft position. The research method was tested on GPS and GLONASS kinematic data from an airborne experiment carried out with a Seneca Piper PA34-200T aircraft at the Mielec airport. A dual-frequency dual-system GPS/GLONASS receiver was placed on-board the plane, which made it possible to record GNSS observations, which were then used to calculate the aircraft’s position in CSRS-PPP software. The calculated XYZ position coordinates from the CSRS-PPP software were then used in the weighted mean model’s developed optimization algorithm. The measurement weights are a function of the number of GPS and GLONASS satellites and the inverse of the mean error square. The obtained coordinates of aircraft from the research model were verified with the RTK-OTF solution. As a result of the research, the presented solution’s accuracy is better by 11–87% for the model with a weighting scheme as a function of the inverse of the mean error square. Moreover, using the XYZ position from the RTKLIB program, the research method’s accuracy increases from 45% to 82% for the model with a weighting scheme as a function of the inverse of the square of mean error. The developed method demonstrates high efficiency for improving the performance of GPS and GLONASS solutions for the PPP measurement technology in air navigation.

scholarly journals Assessment of necessity of neuronavigation in localization of calvarial extra-axial lesions in the setting of limited resources

2021 ◽  
Vol 7 (1) ◽  
Author(s):  
Hussein Soffar ◽  
Mohamed F. Alsawy
Keyword(s):  
Conventional Method ◽  
Linear Measurement ◽  
Limited Resources ◽  
Linear Measurements ◽  
Surgical Interventions ◽  
Localization Method ◽  
Mean Error ◽  
Significant Difference ◽  
The Mean ◽  
Mean Time

Abstract Background Neuronavigation is a very beneficial tool in modern neurosurgical practice. However, the neuronavigation is not available in most of the hospitals in our country raising the question about its importance in localizing the calvarial extra-axial lesions and to what extent it is safe to operate without it. Methods We studied twenty patients with calvarial extra-axial lesions who underwent surgical interventions. All lesions were preoperatively located with both neuronavigation and the usual linear measurements. Both methods were compared regarding the time consumed to localize the tumor and the accuracy of each method to anticipate the actual center of the tumor. Results The mean error of distance between the planned center of the tumor and the actual was 6.50 ± 1.762 mm in conventional method, whereas the error was 3.85 ± 1.309 mm in IGS method. Much more time was consumed during the neuronavigation method including booting, registration, and positioning. A statistically significant difference was found between the mean time passed in the conventional method and IGS method (2.05 ± 0.826, 24.90 ± 1.334, respectively), P-value < 0.001. Conclusion In the setting of limited resources, the linear measurement localization method seems to have an accepted accuracy in the localization of calvarial extra-axial lesions and it saves more time than neuronavigation method.

scholarly journals Critical Aspects of Person Counting and Density Estimation

2021 ◽  
Vol 7 (2) ◽  
pp. 21
Author(s):  
Roland Perko ◽  
Manfred Klopschitz ◽  
Alexander Almer ◽  
Peter M. Roth
Keyword(s):  
Density Estimation ◽  
Network Architecture ◽  
Reference Data ◽  
State Of The Art ◽  
Limit State ◽  
Ground Truth ◽  
Data Sets ◽  
Ground Truth Generation ◽  
Baseline Approach ◽  
Critical Aspects

Many scientific studies deal with person counting and density estimation from single images. Recently, convolutional neural networks (CNNs) have been applied for these tasks. Even though often better results are reported, it is often not clear where the improvements are resulting from, and if the proposed approaches would generalize. Thus, the main goal of this paper was to identify the critical aspects of these tasks and to show how these limit state-of-the-art approaches. Based on these findings, we show how to mitigate these limitations. To this end, we implemented a CNN-based baseline approach, which we extended to deal with identified problems. These include the discovery of bias in the reference data sets, ambiguity in ground truth generation, and mismatching of evaluation metrics w.r.t. the training loss function. The experimental results show that our modifications allow for significantly outperforming the baseline in terms of the accuracy of person counts and density estimation. In this way, we get a deeper understanding of CNN-based person density estimation beyond the network architecture. Furthermore, our insights would allow to advance the field of person density estimation in general by highlighting current limitations in the evaluation protocols.

POSTPARTUM AMENORRHOEA IN RURAL EASTERN UTTAR PRADESH, INDIA

1998 ◽  
Vol 30 (2) ◽  
pp. 227-243
Author(s):  
K. N. S. YADAVA ◽  
S. K. JAIN
Keyword(s):  
Higher Education ◽  
Uttar Pradesh ◽  
Current Status Data ◽  
North India ◽  
Current Status ◽  
Data Sets ◽  
Survival Status ◽  
The Mean ◽  
The Difference ◽  
Using Data

This paper calculates the mean duration of the postpartum amenorrhoea (PPA) and examines its demographic, and socioeconomic correlates in rural north India, using data collected through 'retrospective' (last but one child) as well as 'current status' (last child) reporting of the duration of PPA.The mean duration of PPA was higher in the current status than in the retrospective data;n the difference being statistically significant. However, for the same mothers who gave PPA information in both the data sets, the difference in mean duration of PPA was not statistically significant. The correlates were identical in both the data sets. The current status data were more complete in terms of the coverage, and perhaps less distorted by reporting errors caused by recall lapse.A positive relationship of the mean duration of PPA was found with longer breast-feeding, higher parity and age of mother at the birth of the child, and the survival status of the child. An inverse relationship was found with higher education of a woman, higher education of her husband and higher socioeconomic status of her household, these variables possibly acting as proxies for women's better nutritional status.

Consistency of long-term marketable yield of carrot and onion cultivars in muck (organic) soil in relation to seasonal weather

2010 ◽  
Vol 90 (5) ◽  
pp. 755-765 ◽  
Author(s):  
M. T. Tesfaendrias ◽  
M. R. McDonald ◽  
J. Warland
Keyword(s):  
Allium Cepa ◽  
Daucus Carota ◽  
Organic Soil ◽  
Data Sets ◽  
Fresh Market ◽  
Marketable Yield ◽  
Daucus Carota L ◽  
Weather Patterns ◽  
The Mean

To identify carrot and onion cultivars that provide consistent marketable yields, we tracked the yields of five fresh market carrot [(Daucus carota L. subsp. sativus (Hoffm.) Arcang.] and six onion (Allium cepa L.) cultivars for at least 13 yr. Relationships between long-term weather variables and marketable yields were also investigated. The effects of cultivar, year and cultivar × year interactions on yield of carrots and onions were assessed. Cultivar and year had significant effects on carrot and onion yields, while the interaction was significant in only one of four data sets of carrot yield. Carrot cv. Cellobunch (95.4 t ha–1) and onion cv. Corona (74.1 t ha–1) had the highest mean marketable yields over the years studied. There was a slight positive correlation between mean yield of the assessed carrots and maximum temperatures in September (r = 0.44). Mean carrot yield was also somewhat negatively correlated with total rainfall in July (r = –0.43) and with number of days with rain in August (r = –0.43) and September (r = –0.44). Most onion cultivars showed stronger relationships between marketable yield and various weather patterns. Marketable yield of onions increased with an increase in the number of days with rainfall in June (r = 0.57). The mean marketable yield of the six onion cultivars decreased in relation to temperatures ≥30°C in June (r = –0.55) and August (r = –0.53). The mean yield of all the onions in the trials was negatively correlated (r = –0.78) with growing degree days (base 5°C, May to August). The results indicated that the data from long-term cultivar trials can be used to identify cultivars that yield well despite seasonal variations in weather. Key words: Daucus carota, Allium cepa, temperature, rainfall

scholarly journals Density Estimation for Positron Emission Tomography

2005 ◽  
Vol 4 (2) ◽  
pp. 131-141 ◽  
Author(s):  
Barbara Pawlak ◽  
Richard Gordon
Keyword(s):  
Positron Emission Tomography ◽  
Density Estimation ◽  
3D Imaging ◽  
Diagnostic Techniques ◽  
Emission Tomography ◽  
Experimental Phase ◽  
Positron Emission ◽  
Coincidence Event ◽  
The Mean ◽  
Traditional Approaches

PET (positron emission tomography) scans are still in the experimental phase, as one of the newest breast cancer diagnostic techniques. There are two traditional approaches to the computation of images from data collected in PET. In the first, standard CT (computed tomography) algorithms are used on rays designated by pairs of detectors receiving coincidence events. The problem generated by this approach is that generally only the mean can be used by such algorithms. With the relatively small numbers of events in PET, and with Poisson statistics for which variance equals the mean, the noise sensivity of standard CT algorithms becomes limiting. This is exasperated further by 3D imaging with cylindrical arrays of detectors. Statistical CT algorithms take the variance into account. As in the list-mode approach, we consider each coincidence event individually. However, we estimate the location of the annihilation event that caused each coincidence event, one by one, based on the previously assigned location of events processed earlier. The estimated annihilation locations form the image. To accomplish this, we construct a probability distribution along each coincidence line. This is generated from previous annihilation points by density estimation. In this paper we present our density estimation approach to positron emission tomography. Nonparametric methods of density estimation are overviewed followed by numerical examples. Our goal here is to determine which density estimation approach is most suitable for PET.

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