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Big Data and Cognitive Computing, Volume 9, Issue 6

2025 June - 21 articles

Cover Story: Rainfall is a novel framework for rapid prototyping of data mining pipelines, aligned with the Cross-Industry Standard Process for Data Mining. It offers a low-code, visual environment where non-technical users can build, run, and monitor complex pipelines. The framework supports standard data mining algorithms like machine learning, deep learning and process mining, and allows on-the-fly integration of custom techniques. Thanks to its modular, container-based architecture, Rainfall scales range from local to enterprise deployments. Its applicability, scalability, and usability were validated through real-world industrial collaborations, a computational study, and a user evaluation involving over 85 participants. Rainfall bridges the gap between experimentation and production, helping organizations turn data into insights efficiently. View this paper
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Articles (21)

  • Article
  • Open Access
7 Citations
11,106 Views
29 Pages

This paper proposes a comprehensive deep-learning framework, SentiStack, for Bitcoin price forecasting and trading strategy evaluation by integrating multimodal data sources, including market indicators, macroeconomic variables, and sentiment informa...

  • Article
  • Open Access
1 Citations
2,782 Views
56 Pages

Semantic Reasoning Using Standard Attention-Based Models: An Application to Chronic Disease Literature

  • Yalbi Itzel Balderas-Martínez,
  • José Armando Sánchez-Rojas,
  • Arturo Téllez-Velázquez,
  • Flavio Juárez Martínez,
  • Raúl Cruz-Barbosa,
  • Enrique Guzmán-Ramírez,
  • Iván García-Pacheco and
  • Ignacio Arroyo-Fernández

Large-language-model (LLM) APIs demonstrate impressive reasoning capabilities, but their size, cost, and closed weights limit the deployment of knowledge-aware AI within biomedical research groups. At the other extreme, standard attention-based neura...

  • Article
  • Open Access
1 Citations
2,648 Views
23 Pages

With the demand for workflow processing driven by edge computing in the Internet of Things (IoT) and cloud computing growing at an exponential rate, task scheduling in heterogeneous distributed systems has become a key challenge to meet real-time con...

  • Article
  • Open Access
2 Citations
1,627 Views
19 Pages

Time Series Prediction Method of Clean Coal Ash Content in Dense Medium Separation Based on the Improved EMD-LSTM Model

  • Kai Cheng,
  • Xiaokang Zhang,
  • Keping Zhou,
  • Chenao Zhou,
  • Jielin Li,
  • Chun Yang,
  • Yurong Guo and
  • Ranfeng Wang

Real-time ash content control in dense medium coal separation is challenged by time lags between detection and density adjustment, along with nonlinear/noisy signals. This study proposes a hybrid model for clean coal ash content in dense medium separ...

  • Article
  • Open Access
1 Citations
1,824 Views
18 Pages

Steel plays a fundamental role in modern smart city development, where its surface structural integrity is decisive for operational safety and long-term sustainability. While deep learning approaches show promise, their effectiveness remains limited...

  • Article
  • Open Access
1 Citations
3,986 Views
10 Pages

Analysis of Shots Trajectory and Effectiveness in Women’s and Men’s Football European Championship Matches

  • Blanca De-la-Cruz-Torres,
  • Miguel Navarro-Castro and
  • Anselmo Ruiz-de-Alarcón-Quintero

Shots on target are a crucial factor in football performance, yet the impact of categorizing shots as low or ground-level and high or parabolic has not been fully explored. The objective of this study was to analyze whether there are differences in t...

  • Article
  • Open Access
1 Citations
6,737 Views
20 Pages

Decentralized blockchains have grown into massive and Internet-scale ecosystems, collectively securing hundreds of billions of dollars in value. The complex interplay of technology and economic incentives within blockchain systems creates a delicate...

  • Article
  • Open Access
2 Citations
3,477 Views
25 Pages

Machine Learning-Based Analysis of Travel Mode Preferences: Neural and Boosting Model Comparison Using Stated Preference Data from Thailand’s Emerging High-Speed Rail Network

  • Chinnakrit Banyong,
  • Natthaporn Hantanong,
  • Supanida Nanthawong,
  • Chamroeun Se,
  • Panuwat Wisutwattanasak,
  • Thanapong Champahom,
  • Vatanavongs Ratanavaraha and
  • Sajjakaj Jomnonkwao

This study examines travel mode choice behavior within the context of Thailand’s emerging high-speed rail (HSR) development. It conducts a comparative assessment of predictive capabilities between the conventional Multinomial Logit (MNL) framew...

  • Article
  • Open Access
2 Citations
1,722 Views
18 Pages

Image Visual Quality: Sharpness Evaluation in the Logarithmic Image Processing Framework

  • Arnaud Pauwelyn,
  • Maxime Carré,
  • Michel Jourlin,
  • Dominique Ginhac and
  • Fabrice Meriaudeau

In image processing, the acquisition step plays a fundamental role because it determines image quality. The present paper focuses on the issue of blur and suggests ways of assessing contrast. The logic of this work consists in evaluating the sharpnes...

  • Article
  • Open Access
10 Citations
3,247 Views
19 Pages

Real-Time Algal Monitoring Using Novel Machine Learning Approaches

  • Seyit Uguz,
  • Yavuz Selim Sahin,
  • Pradeep Kumar,
  • Xufei Yang and
  • Gary Anderson

Monitoring algal growth rates and estimating microalgae concentration in photobioreactor systems are critical for optimizing production efficiency. Traditional methods—such as microscopy, fluorescence, flow cytometry, spectroscopy, and macrosco...

  • Article
  • Open Access
2 Citations
3,853 Views
16 Pages

To improve the performance of the image semantic segmentation algorithm and make the algorithm achieve a better balance between accuracy and real-time performance when segmenting images, this paper proposes a real-time image semantic segmentation mod...

  • Review
  • Open Access
3 Citations
3,585 Views
32 Pages

The Use of Large Language Models in Ophthalmology: A Scoping Review on Current Use-Cases and Considerations for Future Works in This Field

  • Ye King Clarence See,
  • Khai Shin Alva Lim,
  • Wei Yung Au,
  • Si Yin Charlene Chia,
  • Xiuyi Fan and
  • Zhenghao Kelvin Li

The advancement of generative artificial intelligence (AI) has resulted in its use permeating many areas of life. Amidst this eruption of scientific output, a wide range of research regarding the usage of Large Language Models (LLMs) in ophthalmology...

  • Article
  • Open Access
2,579 Views
28 Pages

A Framework for Rapidly Prototyping Data Mining Pipelines

  • Flavio Corradini,
  • Luca Mozzoni,
  • Marco Piangerelli,
  • Barbara Re and
  • Lorenzo Rossi

With the advent of Big Data, data mining techniques have become crucial for improving decision-making across diverse sectors, yet their employment demands significant resources and time. Time is critical in industrial contexts, as delays can lead to...

  • Article
  • Open Access
1 Citations
3,265 Views
34 Pages

Our study investigates how the sequencing of text and image inputs within multi-modal prompts affects the reasoning performance of Large Language Models (LLMs). Through empirical evaluations of three major commercial LLM vendors—OpenAI, Google,...

  • Article
  • Open Access
2 Citations
1,651 Views
32 Pages

The early detection of dementia, a condition affecting both individuals and society, is essential for its effective management. However, reliance on advanced laboratory tests and specialized expertise limits accessibility, hindering timely diagnosis....

  • Review
  • Open Access
8 Citations
12,540 Views
44 Pages

The Importance of AI Data Governance in Large Language Models

  • Saurabh Pahune,
  • Zahid Akhtar,
  • Venkatesh Mandapati and
  • Kamran Siddique

AI data governance is a crucial framework for ensuring that data are utilized in the lifecycle of large language model (LLM) activity, from the development process to the end-to-end testing process, model validation, secure deployment, and operations...

  • Article
  • Open Access
2,156 Views
15 Pages

Bone segmentation in magnetic resonance imaging (MRI) is crucial for clinical and research applications, including diagnosis, surgical planning, and treatment monitoring. However, it remains challenging due to anatomical variability and complex bone...

  • Article
  • Open Access
1 Citations
2,307 Views
18 Pages

No-Code Edge Artificial Intelligence Frameworks Comparison Using a Multi-Sensor Predictive Maintenance Dataset

  • Juan M. Montes-Sánchez,
  • Plácido Fernández-Cuevas,
  • Francisco Luna-Perejón,
  • Saturnino Vicente-Diaz and
  • Ángel Jiménez-Fernández

Edge Computing (EC) is one of the proposed solutions to address the problems that the industry is facing when implementing Predictive Maintenance (PdM) implementations that can benefit from Edge Artificial Intelligence (Edge AI) systems. In this work...

  • Article
  • Open Access
3 Citations
9,477 Views
33 Pages

The Impact of Blockchain Technology and Dynamic Capabilities on Banks’ Performance

  • Abayomi Ogunrinde,
  • Carmen De-Pablos-Heredero,
  • José-Luis Montes-Botella and
  • Luis Fernández-Sanz

Blockchain technology has sparked significant interest and is currently being researched by academics and practitioners due to its potential to reduce transaction costs, improve the security of transactions, increase transparency, etc. However, there...

  • Article
  • Open Access
1 Citations
2,021 Views
34 Pages

Ship Typhoon Avoidance Route Planning Method Under Uncertain Typhoon Forecasts

  • Zhengwei He,
  • Junhong Guo,
  • Weihao Ma and
  • Jinfeng Zhang

Formulating effective typhoon avoidance routes is crucial for ensuring the safe navigation of ocean-going vessels. From a maritime safety perspective, this paper investigates ship route optimization under typhoon forecast uncertainty. Initially, the...

  • Article
  • Open Access
1 Citations
2,420 Views
20 Pages

Predicting the Damage of Urban Fires with Grammatical Evolution

  • Constantina Kopitsa,
  • Ioannis G. Tsoulos,
  • Andreas Miltiadous and
  • Vasileios Charilogis

Fire, whether wild or urban, depends on the triad of oxygen, fuel, and heat. Urban fires, although smaller in scale, have devastating impacts, as evidenced by the 2018 wildfire in Mati, Attica (Greece), which claimed 104 lives. The elderly and childr...

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Big Data Cogn. Comput. - ISSN 2504-2289