Intracom Holdings is the main shareholder of a group of multinational companies specialized in IT services, construction projects and defense electronics systems..
This paper presents an innovative software interface for the utilization of widely used Machine Learning (ML) algorithms in a unified Python/R programming environment. A novel software model, the Rbox+, is proposed to execute ML algorithms by jointly leveraging the capabilities of the Python and R programming languages. Furthermore, more comprehensive and specialized architecture is made available for integrating ML into enterprise information systems. Unlike conventional ML Application Programming Interfaces (APIs) or isolated Enterprise Resource Planning (ERP) analytics tools, the Rbox+ enables transparent, language-independent execution and validation of ML models while exposing the underlying source code. The proposed approach supports practical applications in enterprise analytics, reproducible research, and enhancing interoperability between ERP systems, analytics platforms, and statistical programming environments. The proposed API has been tested and evaluated using a publicly available benchmark dataset for regression analysis, applying multiple ML models and comparative performance metrics. The obtained results demonstrate improved computational efficiency and scalability.
We are witnessing a plethora of computing and storage resources with various characteristics and technologies that operate in the edge, in the cloud and in high performance computing environments. In parallel, there is a strong move towards the creation of new services in support of diverse applications that span across these environments that interoperate in the form of a continuum. In this work, we present the SERRANO platform for the creation of an Edge-Cloud-HPC continuum in support of highly demanding, dynamic and security-critical applications. We present the platform’s architecture, main components and interactions. We also describe the way the various resources are integrated under the platform and orchestrated.
This study examines four typical cases in NanjingDongge Community in Pukou District, Longshang Village in Jiangning District, Hemujian Village in Gaochun District, and Shitouzhai Village in Lishui Districtto explore how digital empowerment promotes rural governance through comparative analysis. The findings reveal that digital technologies reshape the rural governance landscape by constructing an integrated infrastructureindustryservicesgovernance system. The study concludes that the essence of digital empowerment in rural governance lies in achieving simultaneous improvements in efficiency, industrial transformation, and service optimization through technological integration and data-driven processes, thereby providing a practical model for rural revitalization in the new era.
