scholarly journals INSIDER UC2: the BR3 biological shield preliminary results and future work

2020 ◽  
Vol 6 ◽  
pp. 14 ◽  
Author(s):  
Wouter Broeckx ◽  
Bart Rogiers ◽  
Nico Mangelschots ◽  
Ronny Vandyck ◽  
Greet Verstrepen ◽  
...  
Keyword(s):  
Current Model ◽  
Secondary Data ◽  
Primary Data ◽  
Full Data ◽  
Data Set ◽  
Clear Cut ◽  
Uncertainty Calculation ◽  
End Stage ◽  
Economical Optimization ◽  
Future Work

Aiming at economical optimization, the characterisation of the biological shield of the Belgian Reactor 3 is one of the three use cases intended to validate the integrated characterization methodology developed within the INSIDER project. Pre-existing data were used to define the sampling design strategy. The additional sampling and analysis program consisted of total gamma measurements at the inner surface of the biological shield (secondary data) and gamma spectrometry measurements on drill core samples (primary data). The newly acquired data is supplemented with the historical available data. The full data set currently consists of a total of 283 secondary and 379 primary data points. Preliminary calculations already provide a clear-cut representation of the three different end-stage classes: unconditional clearance, conditional clearance and radioactive waste. On the short term, the current model will be further refined and completed with proper risk evaluation. On the longer term, we envisage a global uncertainty calculation and sensitivity analysis of the entire process.

Moisture estimation within a mine heap: An application of cokriging with assay data and electrical resistivity

Geophysics ◽  
2010 ◽  
Vol 75 (1) ◽  
pp. B11-B23 ◽  
Author(s):  
Dale Rucker
Keyword(s):  
Electrical Resistivity ◽  
Secondary Data ◽  
Estimation Procedure ◽  
Primary Data ◽  
Low Grade ◽  
Least Squares Regression ◽  
Data Set ◽  
Correlation Scale ◽  
The Mean ◽  
Moisture Estimation

Cokriging has been applied to estimate the distribution of moisture within a rock pile of low-grade gold ore, or heap. Along with the primary data set of gravimetric moisture content obtained from drilling, electrical resistivity was used to supplement the estimation procedure by supplying a secondary data set. The effectiveness of the cokriging method was determined by comparing the results to kriging the moisture data alone and through least-squares regression (LSR) modeling of colocated resistivity and moisture. In general, the wells from which moisture data were derived were separated by distances far greater than the horizontal correlation scale. The kriging results showed that regions generally undersampled by drilling reverted to the mean of the moisture data. The LSR technique, which provides a simpletransformation of resistivity to moisture, converted the low resis-tivity to highmoisture, and vice versa. The sparse well locations created a high degree of uncertainty in the transformed data set. Extreme resistivity values produced nonphysical moisture values, either negative for the linear model or values greater than one for the power model. The cokriging application, which considers the correlation scale and secondary data, produced the best results, as indicated through the cross validation. The mean and variance of the cokriged moisture were closer to the measured moisture, and the bias in the residuals was the lowest. The application likely could be improved through optimal well placement, whereby the resistivity results guide the drilling program through gross target characterization, and the moisture estimation could be updated iteratively.

scholarly journals Embedding to Reference t-SNE Space Addresses Batch Effects in Single-Cell Classification

2019 ◽  
Author(s):  
Pavlin G. Poličar ◽  
Martin Stražar ◽  
Blaž Zupan
Keyword(s):  
Single Cell ◽  
Secondary Data ◽  
Primary Data ◽  
Data Sets ◽  
Batch Effects ◽  
Data Set ◽  
Reduction Techniques ◽  
Straightforward Application ◽  
Cell Gene Expression ◽  
Multiple Data Sets

AbstractDimensionality reduction techniques, such as t-SNE, can construct informative visualizations of high-dimensional data. When working with multiple data sets, a straightforward application of these methods often fails; instead of revealing underlying classes, the resulting visualizations expose data set-specific clusters. To circumvent these batch effects, we propose an embedding procedure that takes a t-SNE visualization constructed on a reference data set and uses it as a scaffold for embedding new data. The new, secondary data is embedded one data-point at the time. This prevents any interactions between instances in the secondary data and implicitly mitigates batch effects. We demonstrate the utility of this approach with an analysis of six recently published single-cell gene expression data sets containing up to tens of thousands of cells and thousands of genes. In these data sets, the batch effects are particularly strong as the data comes from different institutions and was obtained using different experimental protocols. The visualizations constructed by our proposed approach are cleared of batch effects, and the cells from secondary data sets correctly co-cluster with cells from the primary data sharing the same cell type.

scholarly journals Mushroom data creation, curation, and simulation to support classification tasks

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Dennis Wagner ◽  
Dominik Heider ◽  
Georges Hattab
Keyword(s):  
Language Processing ◽  
Binary Classification ◽  
Secondary Data ◽  
Machine Learning Algorithms ◽  
Classification Rule ◽  
Primary Data ◽  
Data Set ◽  
Text Book ◽  
Linear Discriminant ◽  
Classification Tasks

AbstractPredicting if a set of mushrooms is edible or not corresponds to the task of classifying them into two groups—edible or poisonous—on the basis of a classification rule. To support this binary task, we have collected the largest and most comprehensive attribute based data available. In this work, we detail the creation, curation and simulation of a data set for binary classification. Thanks to natural language processing, the primary data are based on a text book for mushroom identification and contain 173 species from 23 families. While the secondary data comprise simulated or hypothetical entries that are structurally comparable to the 1987 data, it serves as pilot data for classification tasks. We evaluated different machine learning algorithms, namely, naive Bayes, logistic regression, and linear discriminant analysis (LDA), and random forests (RF). We found that the RF provided the best results with a five-fold Cross-Validation accuracy and F2-score of 1.0 ($$\mu =1$$ μ = 1 , $$\sigma =0$$ σ = 0 ), respectively. The results of our pilot are conclusive and indicate that our data were not linearly separable. Unlike the 1987 data which showed good results using a linear decision boundary with the LDA. Our data set contains 23 families and is the largest available. We further provide a fully reproducible workflow and provide the data under the FAIR principles.

scholarly journals Survey of fish species from plateau streams of the Miranda River Basin in the Upper Paraguay River Region, Brazil

2017 ◽  
Vol 17 (3) ◽  
Author(s):  
Fabiane Silva Ferreira ◽  
Gabriela Serra do Vale Duarte ◽  
Francisco Severo-Neto ◽  
Otávio Froehlich ◽  
Yzel Rondon Súarez
Keyword(s):  
River Basin ◽  
Fish Fauna ◽  
Secondary Data ◽  
Time Frame ◽  
Primary Data ◽  
Distribution Data ◽  
Data Set ◽  
Number Of Species ◽  
Paraguay River ◽  
River Region

Abstract The objective of this study was to provide a comprehensive list of the fish fauna of headwater streams of the Miranda River in the Upper Paraguay River Basin. Our primary data set was constructed from sampling of fish using a rectangular sieve, trawl, and gill nets from 2004 to 2015. Our secondary data were derived from published reports conducted in the Miranda River Basin, in addition to taxonomic and distribution data from other studies conducted in the basin. All data were compiled, which in the end encompassed a period from 1999 to 2015. The datasets yielded a total of 143 species, 104 from the primary data (72.7%) and 39 from the secondary data (27.3%). Species were distributed among seven orders and 30 families were found in the Miranda River Basin. Characiformes and Siluriformes were the predominant orders, and the families Characidae and Loricariidae had the greatest number of species. Our results indicate a greater number of species compared to other studies of the Upper Paraguay Basin headwaters, likely due to the longer time frame covered by our primary and secondary datasets.

scholarly journals Economic Value of Low Flow Data

1976 ◽  
Vol 7 (1) ◽  
pp. 57-72 ◽  
Author(s):  
Jens Chr Refsgaard ◽  
Eggert Hansen
Keyword(s):  
Regression Model ◽  
Economic Value ◽  
Heuristic Method ◽  
Secondary Data ◽  
Low Flow ◽  
Primary Data ◽  
Bayesian Decision ◽  
Flow Data ◽  
Data Set ◽  
Expected Opportunity Loss

By means of the Bayesian decision approach the economic value of low flow data is considered with special reference to the design of treatment plants for typical Danish conditions. For a specific case the worth of primary data in form of direct observations of low streamflows has been investigated in terms of an expected opportunity loss (EOL). Indirect information concerning the low flow properties of interest may be obtained by means of a secondary data set in combination with a regression model. In this study is suggested a heuristic method for the economic evalution of a secondary set of data taking into account the uncertainty embedded in the regression model.

scholarly journals Embedding to reference t-SNE space addresses batch effects in single-cell classification

2021 ◽  
Author(s):  
Pavlin G. Poličar ◽  
Martin Stražar ◽  
Blaž Zupan
Keyword(s):  
Single Cell ◽  
Single Cells ◽  
Secondary Data ◽  
Machine Learning Techniques ◽  
Primary Data ◽  
Data Sets ◽  
Batch Effects ◽  
Data Set ◽  
Straightforward Application ◽  
Multiple Data Sets

AbstractDimensionality reduction techniques, such as t-SNE, can construct informative visualizations of high-dimensional data. When jointly visualising multiple data sets, a straightforward application of these methods often fails; instead of revealing underlying classes, the resulting visualizations expose dataset-specific clusters. To circumvent these batch effects, we propose an embedding procedure that uses a t-SNE visualization constructed on a reference data set as a scaffold for embedding new data points. Each data instance from a new, unseen, secondary data is embedded independently and does not change the reference embedding. This prevents any interactions between instances in the secondary data and implicitly mitigates batch effects. We demonstrate the utility of this approach by analyzing six recently published single-cell gene expression data sets with up to tens of thousands of cells and thousands of genes. The batch effects in our studies are particularly strong as the data comes from different institutions using different experimental protocols. The visualizations constructed by our proposed approach are clear of batch effects, and the cells from secondary data sets correctly co-cluster with cells of the same type from the primary data. We also show the predictive power of our simple, visual classification approach in t-SNE space matches the accuracy of specialized machine learning techniques that consider the entire compendium of features that profile single cells.

Nilai-Nilai Pendidikan Akhlak dalam Al-Qur’an

2018 ◽  
Vol 10 (2) ◽  
pp. 269-295
Author(s):  
Sri Waluyo
Keyword(s):  
Moral Education ◽  
Primary Source ◽  
Secondary Data ◽  
Primary Data ◽  
The Core ◽  
Primary Data Source ◽  
Before And After ◽  
Data Source

This paper discusses the content of Q.S. al-Baqarah ([2]: 67-73). The data used in the preparation of this paper is the data that is primary and secondary. The primary source is data obtained from the core source. In conducting a study of a verse, it is clear that the primary data source is derived from the Qur'an,precisely on Q.S. al-Baqarah ([2]: 67-73). Secondary data is dataobtained from other sources that are still related to the problemand provide interpretation of the primary source. The method usedin analyzing this paper is the tahlili method. This method describesthe meaning contained by the Qur'an, verse by verse, and letterafter letter according to the order in the Mushaf. The descriptionincludes the various aspects which the interpreted verses contain,such as the meaning of the vocabulary, the connotation of thesentence, the background of the verse down, its relation to otherverses, both before and after. And do not miss the opinion that hasbeen given regarding the interpretation of these verses, whetherdelivered by the Prophet, companions, the tabi'in, as well as othercommentators. This study shows that in Q.S. (2): 67-73) there arevalues of moral education which include: 1) morals in asking, (2)morals to parents, (3) patience of educators, (4) educator honesty,and (5) obedience of learners.

Analisis Pengaruh Kecerdasan Intelektual Terhadap Kemampuan Akuntansi dengan Kecerdasan Emosional dan Spiritual sebagai Pemoderasi

2018 ◽  
Vol 16 (1) ◽  
pp. 1
Author(s):  
Ria Manurung
Keyword(s):  
Data Analysis ◽  
Graduate Program ◽  
Descriptive Analysis ◽  
Research Result ◽  
Secondary Data ◽  
Spiritual Intelligence ◽  
Primary Data ◽  
Moderating Variables ◽  
Use Of Data ◽  
Independent Variable

Research conducted to obtain empirical evidence how the influence of independent variables of intellectual intelligence to accounting with moderating variables of emotional and spiritual intelligence. The research method used is descriptive quantitative with explanatory descriptive or explanatory research. This method is an explanatory research that proves the existence of causal relationship of independent variable (independent variable) that is intellectual intelligence; moderating variable (emotional and spiritual intelligence); and dependent variable (accounted dependent variable). Research begins by conducting library search, followed by primary data collection conducted by using questionnaires and secondary data through data analysis. And for the use of data analysis consists of descriptive analysis, classical assumption test and verification analysis with the method of Moderated Regression Analysis (MRA). This study is a census study with homogeneous and limited population of 92 students, all students of Accounting Graduate Program at UNSOED. Conclusion of research result that is: (1) Intellectual intelligence have influence either positively or signifikan to accountancy. Thus intellectual intelligence can lead students to more easily understand accounting, (2) Intellectual intelligence can be strengthened by emotional intelligence on accounting both positively and significantly. (3) Spiritual intelligence can strengthen the influence of intellectual intelligence on accounting both positively and significantly.

The Design Medan Concert Hall with Metaphor Architecture Approach

2020 ◽  
Vol 4 (1) ◽  
pp. 54-61
Author(s):  
Vinky Rahman ◽  
Muhammad Khairy Humaizy
Keyword(s):  
Secondary Data ◽  
Building Design ◽  
Traditional Music ◽  
Primary Data ◽  
Support Design ◽  
Physical Conditions ◽  
Sound Control ◽  
Strategic Location ◽  
Big City ◽  
Design Ideas

The theater usually has an attractive form to attract the attention of visitors and also has good sound control in the auditorium so as not to cause sound distortion. Performances in Medan are still inadequate to accommodate international performances. Particularly in Medan, the enthusiasm of the community towards art tends to be high, but the facilities of the place lack to accommodate performances. Data collection methods are carried out by collecting primary data through a process of field comparative study and secondary data through literature studies & comparative studies. The design approach used in design studies are analyzing the physical, conditions around the site, potential, the limits that exist on the site, Site and environmental approaches are analysis of site conditions and the best solutions, the user approach is building analysis to meet the need for facilities and quality in accommodating the show, literature studies related to titles and themes and theories that support design ideas. The Metaphor is chosen as a truss design theme to convey the shape of building design by combining metaphorical forms of buildings and the prominence of the same metaphorical theme in the building to those who visit and see buildings to prevent sound distortions by using porous materials. Medan is a big city in Indonesia as a design area with consideration of a strategic location. It is expected that with the presence of this performance center, domestic and foreign tourists and especially Medan people themselves can enjoy the comfort and get to know traditional music and dance in Indonesia.

Kepemimpinan Demokratis Kepala Sekolah dalam Meningkatkan Prestasi di Madrasah Aliyah Negeri Model Palangka Raya

2016 ◽  
Vol 2 (2) ◽  
pp. 6-9
Author(s):  
Shanty Bahar Ising ◽  
Mujiono Mujiono
Keyword(s):  
Secondary Data ◽  
Data Sources ◽  
Primary Data ◽  
Democratic Leadership ◽  
Model State ◽  
Teachers And Students ◽  
Secondary Data Sources ◽  
Conceptual Skills ◽  
To Receive ◽  
Teacher Trainer

This study aims to find out, describe and analyze the democratic leadership of the Principal in improving achievement at the Palangka Raya Model State Madrasah (MAN). The research method used is descriptive qualitative. The researcher wanted to describe the Principal's democratic leadership in improving achievement at the Palangka Raya Model State Islamic Senior High School (MAN). Primary data sources (person) are the Principal, Teachers (Teachers) and Students of MAN Model Palangka Raya. Whereas secondary data sources are the data in the Palangka Raya Model MAN and supporting literature. The results of the study show that the Principal's leadership in improving achievement in the Palangka Raya Model MAN is very democratic, this condition can be seen from: (1) Principals are happy to receive suggestions, opinions and even criticism from subordinates both delivered by students and teachers through suggestion boxes and in the teacher council meeting, (2) the Principal always strives to prioritize teamwork cooperation in an effort to achieve the goal by appointing the instructor teacher, trainer teacher and mentor teacher and conducting deliberation in planning, implementing and evaluating activities, (3) the Principal always tries to make subordinates more success than him, which is realized by including teachers in seminars, workshops, training and competitions so that they get achievements both locally and nationally, and (4) Principals always try to develop their personal capacity as good leaders in conceptual skills, human skill and technical skill.

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