This paper presents the implementation and evaluation of Leo Breiman’s Random Forest algorithm within the Weka data mining environment, with a particular focus on addressing imbalanced datasets that hinder machine learning performance in domains such as...
Cloud computing services have quickly proven to be one of the primary technologies that can meet the dynamic needs of an organization, regarding IT resources distribution. But the problem of efficient resource provisioning is still considered quite...
Community financial institutions — community banks, credit unions, and small savings institutions — face the same two loss-generating problems as large, well-capitalized institutions: transaction and account fraud that erodes customer trust and capital, and...
Growth Potential at the Crossroads of Artificial Intelligence, Robotics, and Synthetic Biology. Biomedical and bioengineering advancements are impeded by our incapacity to foretell how biological systems will act. We are unable to extrapolate behaviour on a...
Computerization in medical services is rapidly transforming the landscape of modern healthcare, particularly within critical environments such as the Operating Room (OR) and Intensive Care Unit (ICU). The integration of advanced digital technologies has led...
Volunteer engagement and retention represent persistent challenges in citizen science, with many projects struggling to recruit and sustain active participants despite growing public interest in scientific participation. While citizen science has...
Transaction monitoring, fraud detection, and financial early-warning are typically built, staffed, and evaluated as three separate functions inside a financial institution, even though all three share the same underlying task: deciding, under time pressure...
Biodiversity conservation depends on accurate, timely, and comprehensive data on species distributions, populations, and ecological interactions. Citizen science has emerged as a powerful tool for biodiversity monitoring, mobilizing millions of volunteers...
The area of high-tech robots has been utterly transformed by AI, ML, and DL in the last several years. The use of AI, ML, and DL is revolutionizing the area of advanced robotics, allowing for more capable, efficient, and adaptive robots that can handle...
Due to the overwhelming number of solutions for Big Data processing during the last few years, distributed data engineering frameworks have become one of the most effective tools for real-time analyses and decision-making in numerous domains. However, these...
On April 17, 2026, the Federal Reserve, OCC, and FDIC jointly issued SR 26-2, Revised Guidance on Model Risk Management, which supersedes both the foundational 2011 guidance (SR 11-7 / OCC Bulletin 2011-12) and the 2021 interagency statement on BSA/AML...
Contemporary businesses are progressively implementing an AI-centric product design approach, integrating machine learning (ML) intelligence into the foundation of new products and functionalities. This paper offers an extensive examination of scalable...
Brainy is a recently made cross-stage machine learning library written in Java. It characterizes interfaces for regular kinds of AI errands, what's more, executions of the most well-known calculations. Smart uses a complex numerical framework which is...
Estimates put the amount of new healthcare data at 2,314,000 gigabytes in 2022, according to the global trend towards digitising health care systems. Better reasoning and more effective utilisation of obtained data are continuous goals of intelligent system...
AI consciousness (computer based intelligence) and ML is a promising field of cardiovascular medication. Numerous AI devices have been demonstrated to be effective with an elevated degree of precision. However, their utilization, in actuality, isn't deeply...
Community Development Financial Institutions (CDFIs) now represent a $452 billion industry of 1,487 Treasury-certified institutions as of the first quarter of 2023, having grown rapidly, industry assets nearly tripled and the certified-institution count...
Cloud computing has become the backbone of modern digital infrastructure, enabling businesses to leverage scalable, on-demand resources for storage, computation, and data management. However, the dynamic nature of cloud environments introduces challenges in...
The rapid growth of data across scientific, industrial, and social domains has created an increasing demand for professionals skilled in data mining and knowledge discovery. This proposal presents a structured and comprehensive data mining curriculum...
Rule-based transaction monitoring systems remain the default anti-money-laundering (AML) control at most deposit-taking institutions, yet they are widely reported to generate false-positive alert rates in excess of 95 percent. For large banks this...
Higher education institutions are increasingly adopting data analytics to improve student outcomes, optimize financial planning, and enhance operational efficiency. Oracle Analytics offers a comprehensive suite of business intelligence tools that facilitate...
Small and Medium Enterprises (SMEs) form the backbone of most emerging economies, yet lending institutions continue to struggle with two interlinked risks when serving this segment: the gradual build-up of financial distress in a borrower's cash-flow...
Suspicious-activity monitoring in community and mid-sized financial institutions still leans heavily on static, rule-based alerting engines that generate overwhelming volumes of false-positive alerts, straining investigative teams and slowing the production...
he exponential adoption of distributed cloud systems has imposed heretofore unseen demands as to data dependability, redundancy, and process performance. The conventional failure detection techniques can only provide a partial solution to the dynamic nature...
Financial organisations increasingly use artificial intelligence to detect fraud, assess creditworthiness, forecast investment conditions, monitor portfolios, and automate regulatory reporting. This critical narrative review examines the decision...
The rapid advancement of machine learning (ML) has transformed industries by enabling sophisticated data-driven decision-making, yet it has also introduced critical ethical challenges. Ethical data governance frameworks are essential to ensure that ML...
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