Journal of Global Economics

Foreign Direct Investment (FDI) has become a key driver of economic development in the globalized world. This article explores the various aspects of FDI and its impact on global economies. It examines the benefits and challenges associated with FDI, as well as the strategies employed by governments and businesses to attract and manage foreign investments. The article also discusses the importance of FDI in fostering economic growth, technology transfer, and employment generation. Keywords: Foreign Direct Investment, Global Economies, Economic Development, Investment Strategies, Technology Transfer. FDI refers to the investment made by a firm or an individual in one country into business interests located in another country, which implies a significant degree of influence or control by the investor. FDI has gained prominence as a means for multinational enterprises to expand their operations, gain access to new markets, and tap into resources not available in their home countries.

Blockchain technology has gained attention as a powerful tool for governments seeking to enhance transparency, efficiency, and digital governance. This article explores the applications of block chain in government, its potential benefits, and the challenges it poses. We examine use cases, security concerns, and the role of block chain in reshaping the public sector. By leveraging block chain, governments can create a more accountable and streamlined administration that serves citizens more effectively. Blockchain's inherent security features make it an ideal technology for government use. It ensures that data remains tamper-proof and auditable, enhancing government accountability. In an era where trust in government institutions is often eroded, blockchain can help rebuild that trust by providing transparent and immutable records of government actions.

Interdisciplinary research is pivotal in addressing complex challenges. A bibliometric analysis reveals key trends and challenges in this field. Utilizing data integration, citation patterns, and network analysis, it uncovers the growth and impact of interdisciplinary research. Challenges lie in data integration and accurate representation of interdisciplinary work in databases. Findings indicate a consistent increase in interdisciplinary research, with broad societal impact and unique citation patterns. Interdisciplinary research networks have been mapped, facilitating collaboration. As the boundaries between disciplines blur, bibliometric analysis remains essential in understanding this evolving research landscape.

Medical image analysis has witnessed significant advancements with the introduction of Convolutional Neural Networks (CNNs). This paper explores the application of CNNs in the field of medical image analysis, highlighting their potential, challenges, and key contributions. CNNs have shown remarkable results in tasks such as image classification, segmentation, and disease detection, making them a powerful tool for healthcare professionals and researchers. In this article, we delve into the architecture of CNNs, discuss their training and fine-tuning techniques, and provide insights into their use in various medical imaging modalities. Furthermore, we address the ethical and privacy concerns associated with the use of CNNs in medical image analysis.