Studies in Big Data

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Studies in Big Data

Vol. 65: Data Management and Analysis. Switzerland : Springer, 2019.

Under the general editorship: M. M. Pour, R. Alhajj, B. Far

In press

Data management and analysis is one of the fastest growing and most challenging areas of research and development in both academia and industry. Numerous types of applications and services have been studied and re-examined in this field resulting in this edited volume which includes chapters on effective approaches for dealing with the inherent complexity within data management and analysis. This edited volume contains practical case studies, and will appeal to students, researchers and professionals working in data management and analysis in the business, education, healthcare, and bioinformatics areas.

Prediction Model for Prevalence of Type-2 Diabetes Mellitus Complications Using Machine Learning Approach

Ahmed Munna M. T., , in: Studies in Big DataVol. 65: Data Management and Analysis.: Switzerland: Springer, 2019. P. 103–116.

Nowadays, most of the people are suffering from the attack of chronic diseases because of their lifestyle, food habits, and reduction in physical activities. Diabetes is one of the most common chronic diseases being suffered by the people of all ages. As a result, the healthcare sector is generating extensive data containing huge volume, enormous ...

Added: December 29, 2019

Research target: Computer Science Health Studies Medical and Health Sciences

Priority areas: IT and mathematics

Language: English

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Non-linear in-band interference cancellation on base of conjugate gradients method

Degtyarev A., Bakhurin S., Yudin N., DSPA 2026 P. 1–6

This paper investigates one possible solution to the problem of self-interference cancellation (SIC) arising in the design of in-band full-duplex (IBFD) communication systems. Self-interference cancellation is performed in the digital domain using multilayer nonlinear models adapted via gradient-based optimization. The presence of local minima and saddle points during the adaptation of multilayer models limits the ...

Added: May 26, 2026

Comparative Study of Training Methods and Architectures of Echo State Networks

Androsov I., Proceedings of the Institute for System Programming of the RAS 2026 Vol. 38 No. 3 P. 87–114

This paper examines echo state networks (ESNs), one of the most prevalent approaches to implementing reservoir computing. An ESN consists of a recurrent neural network with fixed (untrained) weights and a readout layer that is typically linear and trainable. This approach enables the creation of energyefficient and computationally efficient neural networks capable of real-time learning. However, since ...

Added: May 26, 2026

Menstrual health as a public concern in Ghana: A conceptual review of symbolic and structural ownership

Вохойие Х., Anikin V. A., Tomsk State University Journal of Philosophy, Sociology and Political Science 2026 Vol. 90 P. 204–211

Menstrual health serves as a critical litmus test for state intervention in contexts where women’s bodily experiences are historically shaped by stigma, cultural taboos, and structural violence. Drawing on Joseph Gusfield’s theory of social problems, this review traces the moral passage of menstruation in Ghana (1992–2025) from a privately managed, stigmatized phenomenon to a matter ...

Added: May 26, 2026

Рефакторинг исходного кода на основе LLM и расширения UML

Караваева Е. А., Кулигин Л. А., Rezunik L. et al., Труды Института системного программирования РАН 2026 Т. 38 № 3 С. 67–94

В статье представлен метод рефакторинга исходного кода на основе интеграции большой языковой модели (LLM) и расширенной UML-модели программного кода. Предложенный подход позволяет выявлять проблемные участки кода с использованием функций тревожности и структурных метрик классов, а затем выполнять автоматизированный рефакторинг. Ключевой особенностью метода является использование LLM для генерации формальных спецификаций на языке OCL (Object Constraint Language), ...

Added: May 24, 2026

Coping with AI errors with provable guarantees

Tyukin I., Tyukina T., van Helden D. P. et al., Information Sciences 2024 Vol. 678 Article 120856

AI errors pose a significant challenge, hindering real-world applications. This work introduces a novel approach to cope with AI errors using weakly supervised error correctors that guarantee a specific level of error reduction. Our correctors have low computational cost and can be used to decide whether to abstain from making an unsafe classification. We provide ...

Added: May 23, 2026

Overcoming the Curse of Dimensionality with Synolitic AI

Zaikin A., Sviridov I., Sosedka A. et al., Technologies 2026 Vol. 14 No. 2 Article 84

High-dimensional tabular data are common in biomedical and clinical research, yet conventional machine learning methods often struggle in such settings due to data scarcity, feature redundancy, and limited generalization. In this study, we systematically evaluate Synolitic Graph Neural Networks (SGNNs), a framework that transforms high-dimensional samples into sample-specific graphs by training ensembles of low-dimensional pairwise ...

Added: May 23, 2026

Stable On-the-Fly Learning for Dynamic Neural Networks With Delayed Inputs

Kibkalo Vladislav, Chertopolokhov V., Mukhamedov A. et al., IEEE Access 2026 Vol. 14 P. 14369–14392

This study presents on-the-fly identification and multi-step prediction of nonlinear systems with delayed inputs using a dynamic neural network combined with a smooth projection onto ellipsoids. The projection enforces parameter constraints that guarantee stability, while a Lyapunov–Krasovskii analysis yields computable ultimate error bounds. Riccati-type matrix inequalities are derived, providing an efficient vectorization–projection–devectorization implementation suitable for ...

Added: May 22, 2026

Опыт применения сетевого анализа (SNA) в историческом нарративе полисубъектного региона (на примере валлийской хроники Brut y Tywysogyon)

Loshkareva M. E., Matveeva N., Вестник Томского государственного университета. История 2026 № 100 С. 112–118

This research is an endeavor to apply social network analysis (SNA) to the study of a medieval narrative source. The authors suppose that the use of network analysis may offer new possibilities in the study of the history of regions characterized by some political fragmentation. Authors tried to construct networks of historical interactions from 1193 ...

Added: May 22, 2026

Технологии генетического секвенирования как средство профилактики рождения детей с генетическими аномалиями

Plotnikov S., ЯКУБЕНКО Т. В., Ratio et Natura 2024 № 3 (11) Статья 10

The article presents the results of our own research aimed at studying the prospects of using genetic sequencing technologies to identify the risk of having children with genetic abnormalities. ...

Added: May 21, 2026

ML-based Fast Simulation of FARICH Responses

Shipilov F., Barnyakov A., Ivanov A. et al., / Series Physics "arxiv.org". 2026.

A fast simulation of the detector response is a vital task in high-energy physics (HEP). Traditional Monte-Carlo methods form the backbone of modern particle physics simulation software but are computationally expensive. We present a machine-learning-based approach to fast simulation of the Focusing Aerogel Ring Imaging Cherenkov (FARICH) detector response. Given a particle track and momentum, ...

Added: May 19, 2026

Proceedings of the 19th Conference of the European Chapter of the Association for Computational Linguistics (Volume 3: System Demonstrations)

Rabat: Association for Computational Linguistics, 2026.

Added: May 19, 2026

Dataset of solubility values for organic compounds in binary mixtures of solvents at various temperatures

Bezzubov S., Malikov D., Krasnov L. et al., Scientific data 2026 Vol. 13 Article 727

Solubility is a crucial property of organic compounds, impacting their potential applications in synthetic chemistry, materials science and drug design. Moreover, in technological processes mixtures of solvents are often utilized, making the solubility assessment more complicated. Predicting solubility values in mixtures of solvents from a molecular structure can help to address this issue, although a ...

Added: May 19, 2026

Aerokinesis: An IoT-Based Vision-Driven Gesture Control System for Quadcopter Navigation Using Deep Learning and ROS2

Pikalov V., Meshcheryakov V., Kondratev S. et al., Technologies 2026 Vol. 14 No. 1 P. 1–27

This paper presents Aerokinesis, an IoT-based software–hardware system for intuitive gesture-driven control of quadcopter unmanned aerial vehicles (UAVs), developed within the Robot Operating System 2 (ROS2) framework. The proposed system addresses the challenge of providing an accessible human–drone interaction interface for operators in scenarios where traditional remote controllers are impractical or unavailable. The architecture comprises ...

Added: May 19, 2026

Aerokinesis: An IoT-Based Vision-Driven Gesture Control System for Quadcopter Navigation Using Deep Learning and ROS2

Kondratev S., Yulia Dyrchenkova, Georgiy Nikitin et al., Technologies 2026 Vol. 14 No. 1 Article 69

Added: May 19, 2026

Применение методик кортикальной и субкортикальной стимуляции у пациентов с глиальными опухолями различной степени злокачественности доминантного по речи полушария головного мозга в условиях хирургии с пробуждением.

Андрушкевич О. М., Калиновский А. В., Гаврюшин А. В. et al., Нейрохирургия 2026 Т. 28 № 1 С. 33–42

Background. The application of cortical and subcortical stimulation during awake craniotomy mitigates the risk of persistent postoperative speech deficits. However, the functions of some white matter pathways remain inadequately understood, particularly the frontal aslant tract (FAT) of the dominant hemisphere. Aim. To evaluate the efficacy of cortical and subcortical stimulation techniques in the localization of glial tumors near ...

Added: May 18, 2026

Parallel Computational Technologies. PCT 2025

Springer, 2025.

This book constitutes the refereed proceedings of the 19th International Conference on Parallel Computational Technologies, PCT 2025, held in Moscow, Russia, during April 8–10, 2025. The 31 full papers included in this volume were carefully reviewed and selected from 122 submissions. These papers were organized under the following topical sections: High Performance Architectures, Tools and Technologies; ...

Added: May 18, 2026

KMHCR: A Key-Controlled Signal-Domain Transformation for 5G IoT Security

Ronglin Z., Wei L., Jiahong C. et al., Journal of Signal Processing Systems 2026 Vol. 98 Article 31

To address the need for lightweight and low-latency protection in massive resource-constrained 5G Internet of Things (IoT) systems, this paper proposes Key-Controlled Modulation Hopping and Constellation Rotation (KMHCR). KMHCR is designed as a physical-layer confidentiality-enhancement mechanism that avoids bit-wise full-payload encryption in the protection pipeline. It uses a shared key derived from channel-reciprocity secret key ...

Added: May 16, 2026

DPN Verifier: A Toolkit for Faster Soundness Verification and Repair of Process Models with Data

Suvorov N. M., Proceedings of the Institute for System Programming of the RAS 2026 Vol. 38 No. 3(2) P. 49–66

Data Petri Nets (DPNs) extend classical Petri nets to model processes where data directly influences control-flow, enabling a comprehensive view of system behavior and possibility to detect failure points that could otherwise be hidden. Soundness is a correctness criterion that captures such failure points as deadlocks and livelocks as well as model boundedness and absence ...

Added: May 16, 2026

QGKM: A Quantum Fidelity-Based Graph Clustering Framework for Robust Data Pattern Recognition in Education Social Networks

Xiong N., Long W., He D. et al., Algorithms 2026 Vol. 19 No. 5 Article 386

In the era of data-driven education, educational social networks generate large volumes of high-dimensional and complex-structured data through learner interactions, collaborative activities, and resource-sharing behaviors, posing significant challenges to traditional unsupervised learning methods. Such data often exhibit non-convex distributions, heterogeneity, and noise sensitivity, making conventional clustering approaches insufficient for capturing their intrinsic structural relationships. To ...

Added: May 13, 2026

Proceedings of the 9th Student Research Workshop associated with the International Conference Recent Advances in Natural Language Processing

Velichkov B., Nikolova-Koleva I., Slavcheva M., Shumen: INCOMA Ltd, 2025.

The RANLP 2025 Student Research Workshop (RANLPStud’2025) is a special track of the established international conference Recent Advances in Natural Language Processing (RANLP’2025). The RANLPStud is being organised for the 9th time and this year is running in parallel with the other tracks of the main RANLP 2025 conference. The target of RANLPStud’25 is to be a ...

Added: May 12, 2026

Natural hazard database from Internet publications: text mining with a large language model

Derkacheva A., Sakirkina M., Kraev G. et al., /. 2026.

Comprehensive data on natural hazards and their consequences are crucial for effective for risk assessment, adaptation planning, and emergency response. However, many countries face challenges with fragmented, inconsistent, and inaccessible data, particularly regarding local-scale events. To address this data gap in Russia, we developed an end-to-end processing pipeline that scrapes news from various online sources, ...

Added: April 28, 2026

WWW '26: Proceedings of the ACM Web Conference 2026

NY: Association for Computing Machinery (ACM), 2026.

It is our great pleasure to welcome you to the 35th edition of the Web Conference to be held on June 29 – July 3, 2026, in Dubai, United Arab Emirates. Following discussions with our partners and key stakeholders, we have taken the decision to postpone the ACM Web Conference 2026, initially planned for April 2026. ...

Added: April 23, 2026

Machine Learning Approach to Anticancer Activity Prediction of Transition-Metal Complexes Based on a Large-Scale Experimental Database

Krasnov L., Malikov D., Kiseleva M. et al., Journal of Medicinal Chemistry 2026 Vol. 69 No. 8 P. 8838–8851

In this work, we developed a straightforward data-driven approach to predict the cytotoxicity of metal complexes based entirely on their (metal + ligands) composition. To this end, we have manually curated MetalCytoToxDB─a comprehensive experimental database comprising 26,500 IC50 values for 7050 metal complexes against 754 cell lines from 1921 articles. Based on these, machine learning ...

Added: April 23, 2026

Algorithmic overlaps as thermodynamic variables: from local to cluster Monte Carlo dynamics in critical phenomena

Pilé I., Deng Y., Shchur L., / Series arXiv "math". 2026. No. 2604.10254.

We investigate the spatial overlap of successive spin configurations in Markov chain Monte Carlo simulations using the local Metropolis algorithm and the Svendsen-Wang and Wolff cluster algorithms. We examine the dynamics of these algorithms for two models in different universality classes: the Ising model and the Potts model with three components. The overlap of two ...

Added: April 20, 2026