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IPUMS International provides individual-level data with labor incomes and worker characteristics which can be used to estimate the empirical distribution of within-group worker wages.
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Quality-adjusted trade prices, as done by Robert Feenstra and John Romalis, “International Prices and Endogenous Quality” , The Quarterly Journal of Economics, May 1, 2014, vol.129 (No.2) pp. 477-527.
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  • Software/Code
  • Dataset
PVC and glass T junction with different diameters are used to estimate split of phases and check with Shoham et al.'s model of 1987
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PWT version 8.1 is a database with information on relative levels of income, output, input and productivity across the world between 1950 and 2011.
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IPUMS International provides information on individual characteristics and sector of work, which can be used to calibrate the comparative advantage of different labor groups across sectors.
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World Input-Output Tables, Release 2013. The table provides world Input-output tables (WIOT) in current prices, denoted in millions of dollars for the period from 1995 to 2011.
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HealthAidKB, a Knowledge Base, is the result of an automatic extraction and clustering pipeline of common procedural knowledge in the domain of health. Our goal is to construct domain targeted high precision procedural knowledge base containing task frames. We developed a pipeline of methods leveraging Open IE to extract procedural knowledge by tapping in to on-line communities. In addition, we devise a mechanism to canonicalize the task frames in to clusters based on the similarity of the problems they intend to solve. The resulting knowledge base shows high precision based on an evaluation by human experts in the domain. We extracted the procedural knowledge by tapping in to health category of wiki how (https://www.wikihow.com/Category:Health ) and how to cure (https://howtocure.com/).
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We represented a new Bangla dataset with a Hybrid Recurrent Neural Network model which generated Bangla natural language description of images. This dataset achieved by a large number of images with classification and containing natural language process of images. We conducted experiments on our self-made Bangla Natural Language Image to Text (BNLIT) dataset. Our dataset contained 8,743 images. We made this dataset using Bangladesh perspective images. We used one annotation for each image. In our repository, we added two types of pre-processed data which is 224 × 224 and 500 × 375 respectively alongside annotations of full dataset. We also added CNN features file of whole dataset in our repository which is features.pkl.
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The data in SPSS contains cases of mathematics teachers self-efficacy with regard to technology integration. the self-efficacy was rated on a Likert scale while some background information were categorical.
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The functions used to carry out this work are found in the files provided, "k-Prototypes Clustering" and "clustMixType modified functions". These algorithms carry out the operations of obtaining and manipulating the data matrix, descriptive statistics of the data, determining the best number of clusters, clustering with the k-prototypes method, and statistical validation of the generated clusters with MANOVA. An example is also presented using the Iris database, contained in the R software library, and widely used to exemplify and validate algorithms developed in R language. The functions modified for this work are found in the files "clustMixType modified functions". The modified functions are called in the algorithm of the file "k-Prototypes Clustering", on line 41, by the file "k-Prototypes Clustering.R". The kproto.modif (), clprofiles.modif () and summary.kproto.modif () functions were modified from the kproto (), clprofiles () and summary.kproto () functions, respectively, of the clustMixType package, developed by SZEPANNEK (2018). The dist.binary () function of the ade4 package, developed by DRAY & DUFOUR (2017), was also used in the development of the kproto.modif () function, that now can use a variety of similarity functions. The relationship between the variables is expressed by the squared Euclidean distance, to quantify the distance between numerical variables, and for the nominal variables, the distance can be obtained from a variety of coefficients of similarity. The fviz_cluster.modif () function was modified from the fviz_cluster () function of the factoextra package, developed by KASSAMBARA & MUNDT (2017). REFERENCES: - DRAY, S.; DUFOUR, A.-B. The ade4 Package: Implementing the Duality Diagram for Ecologists. Journal of Statistical Software, v.22, n.4, p.1-20, set. 2017. R Package version 1.7-13. Available at: https://CRAN.R-project.org/package=ade4. https://www.doi.org/10.18637/jss.v022.i04. - KASSAMBARA, A.; MUNDT, F. factoextra: Extract and Visualize the Results of Multivariate Data Analyses. 2017. R Package version 1.0.5. Available at: https://CRAN.R-project.org/package=factoextra. - SZEPANNEK, G. clustMixType: User-Friendly Clustering of Mixed-Type Data in R. The R Journal, v.10, n.2, p.200-208, 2018. R Package version 0.2-1. Available at: https://CRAN.R-project.org/package=clustMixType. https://www.doi.org/10.32614/RJ-2018-048.
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