Proposes a coarse-to-fine optimization of a recommending system based on deep-neural networks using 'tensorflow'.

Provides tools for using the API of 'e-Stat' (<https://www.e-stat.go.jp/>), a portal site for Japanese government statistics.
    Includes functions for automatic query generation, data collection and formatting.

Provides a function collection to extract metadata, sectioned text and study characteristics from scientific articles in 'NISO-JATS' format. Articles in PDF format can be converted to 'NISO-JATS' with the 'Content ExtRactor and MINEr' ('CERMINE', <https://github.com/CeON/CERMINE>). For convenience, two functions bundle the extraction heuristics: JATSdecoder() converts 'NISO-JATS'-tagged XML files to a structured list with elements title, author, journal, history, 'DOI', abstract, sectioned text and reference list. study.character() extracts multiple study characteristics like number of included studies, statistical methods used, alpha error, power, statistical results, correction method for multiple testing, software used. An estimation of the involved sample size is performed based on reports within the abstract and the reported degrees of freedom within statistical results. In addition, the package contains some useful functions to process text (text2sentences(), text2num(), ngram(), strsplit2(), grep2()). See Böschen, I. (2021) <doi:10.1007/s11192-021-04162-z> Böschen, I. (2021) <doi:10.1038/s41598-021-98782-3> and Böschen, I (2023) <doi:10.1038/s41598-022-27085-y>.

Graphics device routing all graphics commands to a Java
	     program. The actual functionality of the JavaGD depends
	     on the Java-side implementation. Simple AWT and Swing
	     implementations are included.

Maximization or Minimization of a fitness function using Jaya Algorithm (JA).
   A population based method which repeatedly modifies a population of individual solutions.
   Capable of solving both constrained and unconstrained optimization problems.
   It does not contain any hyperparameters. 
   For further details: R.V. Rao (2016) <doi:10.5267/j.ijiec.2015.8.004> .