SIMPLIFYING THE BUREAUCRACY THROUGH TRANSACTION COST THEORY

Simplifying the Bureaucracy Through Transaction Cost Theory

The policy of simplifying the bureaucracy aims to simplify, but in its preparation, it produces many regulations that also cost a lot of money.The Ministry of Finance publishes an average cost incurred for the preparation of one ministerial regulation of up to Rp232 million, not including other costs that do not look like the formulation time.This

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Genetic Diversity, Population Structure, and Genetic Correlation with Climatic Variation in Chickpea (Cicer arietinum) Landraces from Pakistan

AMINO ENERGY GRAPE Chickpea ( L.) production in arid regions, such as those predominant in Pakistan, faces immense challenges of drought and heat stress.Addressing these challenges is made more difficult by the lack of genetic and phenotypic characterization of available cultivated varieties and breeding materials.Genotyping-by-sequencing offers a

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Reduction of Embodied Energy and Construction Cost of Affordable Houses through Efficient Architectural Design: A Case Study in Indian Scenario

Embodied energy and cost of construction of any building depends upon the consumption of resources, more specifically construction materials.In housing clusters, the spaces provided for horizontal and vertical circulation of occupants such as corridors and contribute in the built-up area of individual unit without any increase in the usable/carpet

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Exploring Quality Differences in Telemedicine Between Hospital Outpatient Departments and Community Clinics: Cross-sectional Study

BackgroundTelemedicine is a care delivery modality that has the potential to broaden the reach and flexibility of health care services.In the United Arab Emirates, telemedicine services are mainly delivered through either integrated hospital outpatient department (OPDs) or community clinics.However, it is unknown if patients’ perceptions of, and

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Category-Level Adversaries for Semantic Domain Adaptation

Recent advances in deep learning, especially deep convolutional neural networks, have led to great performance improvement over semantic segmentation systems.Unfortunately, training deep neural networks (DNNs) requires a humongous amount of labeled data, which is laborious and costly to collect and annotate.Thus, plenty of works have proposed an al

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