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Global digitalization has given birth to the explosion of digital services in approximately every sector of contemporary life. Applications of artificial intelligence, blockchain technologies, and internet of things are promising to…
As geopolitical, organizational, and technological fragmentation deepens, resilient digital collaboration becomes imperative. This paper develops a spectrum framework of polycentric digital ecosystems-nested socio-technical systems spanning…
With the emergence of new methodologies and technologies it has now become possible to manage large amounts of environmental sensing data and apply new integrated computing models to acquire information intelligence. This paper advocates…
Our machines, products, utilities, and environments have long been monitored by embedded software systems. Our professional, commercial, social and personal lives are also subject to monitoring as they are mediated by software systems. Data…
Finite mixture models have been a very important tool for exploring complex data structures in many scientific areas, for example, economics, epidemiology, finance. In the past decade, semiparametric techniques have been popularly…
Small and Medium size Enterprises (SME) are considered as a backbone of many developing and developed economies of the world; they are the driving force to any major economy across the globe. Through Cloud Computing firms outsource their…
Fair graph clustering is crucial for ensuring equitable representation and treatment of diverse communities in network analysis. Traditional methods often ignore disparities among social, economic, and demographic groups, perpetuating…
The advancement of various research sectors such as Internet of Things (IoT), Machine Learning, Data Mining, Big Data, and Communication Technology has shed some light in transforming an urban city integrating the aforementioned techniques…
The integration of blockchain technology with data analytics is essential for extracting insights in the cryptocurrency space. Although academic literature on blockchain data analytics is limited, various industry solutions have emerged to…
In recent years, `fake news' has become a global issue that raises unprecedented challenges for human society and democracy. This problem has arisen due to the emergence of various concomitant phenomena such as (1) the digitization of human…
Blockchain technology is referred to as a very secure decentralized, distributed ledger that records the history of any digital asset. It is being used in numerous governmental and private sector organizations across numerous nations.…
Federated Learning (FL) is an evolving distributed machine learning approach that safeguards client privacy by keeping data on edge devices. However, the variation in data among clients poses challenges in training models that excel across…
The growth of local data annually implies extra charges for the customers, which makes their business slowing down. Cloud computing paradigm comes with new technologies that offer a very economic and cost-effective solution, but the…
With the exponentially increasing demand for performance and scalability in cloud applications and systems, data center architectures evolved to integrate heterogeneous computing fabrics that leverage CPUs, GPUs, and FPGAs. FPGAs differ…
Usual formulations of the clustering coefficient can be shown to be insufficient in the task of describing the local topology of very simple networks. Motivated by this, we review some alternatives in order to present an extension, the…
Recent measurement studies show that there are massively distributed hosting and computing infrastructures deployed in the Internet. Such infrastructures include large data centers and organizations' computing clusters. When idle, these…
The task of stock earnings forecasting has received considerable attention due to the demand investors in real-world scenarios. However, compared with financial institutions, it is not easy for ordinary investors to mine factors and analyze…
Security is becoming a pivotal point in cloud platforms. Several divisions, such as business organisations, health care, government, etc., have experienced cyber-attacks on their infrastructures. This research focuses on security issues…
Machine learning is critical for innovation and efficiency in financial markets, offering predictive models and data-driven decision-making. However, challenges such as missing data, lack of transparency, untimely updates, insecurity, and…
Time series clustering promises to uncover hidden structural patterns in data with applications across healthcare, finance, industrial systems, and other critical domains. However, without validated ground truth information, researchers…