the current study investigated and compared data generation methods for groundwater modeling. thesemethods can be divided into two classes; geostatistic and probabilistic. by comparing geostatistic methods,the best method was chosen and the hydraulic conductivity of the aquifer was generated for a study area ina grid (9-cell) format. after observing weak spatial correlation between the data, th...

Abstract Generative adversarial network () models have been successfully utilized in a wide range of machine learning applications, and tabular data generation domain is not an exception. Notably, some state-of-the-art generation, such as , etc. are based on models. Even though these resulted superior performance generating artificial when trained datasets, there lot room (and desire) for impro...

Modern studies from a variety of fields record multiple functional observations according to either multivariate, longitudinal, spatial, or time series designs. We refer such data as second-generation because their analysis—unlike typical analysis, which assumes independence the functions—accounts for complex dependence between and requires more advanced methods. In this article, we provide an ...

The paper is devoted to the problem of generating artificial datasets for data envelopment analysis (DEA), which can be used testing DEA models and methods. In particular, papers that applied big often synthetic generation obtain large-scale because real large size, available in public domain, are extremely rare. This proposes algorithm takes as input some dataset complements it by efficient in...

Sağlık hizmetleri planlaması, klinik deneyler ve araştırma geliştirme çalışmaları gibi sağlık verisi kullanımını gerektiren alanlarda, kişisel verisinin elde edilmesi kullanımında etik, bürokratik operasyonel zorluklar yaşanmaktadır. Elektronik kayıtlarının güvenliği veri mahremiyeti konularındaki kısıtlamalar başta olmak üzere, saha çalışmalarından edilmesinin maliyetli zaman alıcı olması, ger...

This paper introduces the notion of ‘co-testability transformation’. As opposed to traditional testability transformations, which replace the original program in testing, co-testability transformations are designed to be used in conjunction with the original program (and any additional co-transformations as well). Until now, testability transformations have only been used to improve test data g...