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Select Proceedings of CHSN 2023. High Performance Computing, Smart Devices and Networks
Vol. 1262: Lecture Notes in Electrical Engineering.
Singapore :
Springer, 2024.
Under the general editorship: B. Annappa, W. Hong, D. Haritha, G. Lavanya Devi
This book comprises the proceedings of the 4th International Conference on Computer Vision, High-Performance Computing, Smart Devices, and Networks (CHSN 2023). This book highlights high-quality research articles in machine learning, computer vision, and networks. The content of this volume gives the reader an up-to-date picture of the state-of-the-art connection between computational intelligence, machine learning, and IoT. The papers in this volume are peer-reviewed by experts in related areas. The book serves as a valuable reference resource for academics and researchers across the globe.
Chapters
Alahmid M., Bhimani K. R., Saradva K. et al., , in: Select Proceedings of CHSN 2023. High Performance Computing, Smart Devices and NetworksVol. 1262: Lecture Notes in Electrical Engineering.: Singapore: Springer, 2024. P. 87–100.
To give shift in safety protocols, we have employed advanced deep learning algorithms and frameworks to construct an innovative AI model. The designed model detects the usage of personal protective equipment (PPE) by workers in high-risk industries such as construction and manufacturing. We have used Google’s TensorFlow object detection API to modify and train a model for ...
Added: January 17, 2025
Language:
English
Aleksei Samarin, Nazarenko A., Nazarenko D. et al., Machine Learning and Knowledge Extraction 2026 Vol. 8 No. 10 Article 330
Automated microscopic image analysis is essential for quantitative microbiology, yet manual acquisition and generic recognition models struggle with morphological variability and scene artifacts. We address both ends of this pipeline. First, we present a low-cost, open-source acquisition system, based on an Arduino UNO R3 microcontroller and NEMA 17 stepper motors, that automates focusing, magnification, and ...
Added: October 14, 2026
Mamedov I., Fofanov M., Lukianchenko P. et al., IEEE Access 2026 No. 14 P. 26662–26671
DreamBooth-style personalization, which often relies on one or a few images, can memorize context (background, pose, lighting) rather than learning the subject’s identity, thereby reducing fidelity and limiting prompt-driven edits. P-LoRA (Probability LoRA) is introduced as a training-time modification that biases diffusion timestep sampling and utilizes importance weights, ensuring that the overall objective remains unchanged. ...
Added: October 14, 2026
Parkhomenko V., Kulikova S., Buzmakov A. V., Lobachevskii Journal of Mathematics 2026 Vol. 47 No. 6 P. 2979–2992
The stability of formal concepts and its generalization as robustness are considered in the paper. We use an approximation of stability in the form of Δ-measure for fast calculations. A computationally efficient method for calculating robustness based on subcontexts is presented. We also present a new method to analytically evaluate the number of preimages for ...
Added: October 14, 2026
Kuznetsov A. P., Sedova Y. V., Sataev I. R. et al., Mathematics and Computers in Simulation 2027 Vol. 2 P. 574–592
Universal bifurcation structures on the parameter plane of nonlinear systems, known as shrimps, are discussed. An overview of numerous examples from various fields of science is given. Shrimps are typical for both maps of different dimensions and flows. The varieties of shrimp are discussed and relevant examples are given. The similarity property on the parameter ...
Added: October 14, 2026
Springer, 2026.
This book highlights cutting-edge research in the field of network science, offering scientists, researchers, students and practitioners a unique update on the latest advances in theory and a multitude of applications. It presents the peer-reviewed proceedings of the XIV International Conference on Complex Networks and their Applications (COMPLEX NETWORKS 2025). The carefully selected papers cover ...
Added: October 13, 2026
Springer, 2026.
This book offers a comprehensive overview of the latest research, innovations, and practical applications in the field of sustainability, with a focus on construction materials and their use in building and civil engineering structures. As an outcome of the 3rd International Conference on Sustainability: Developments and Innovations (ICSDI 2026), this book presents a selection of ...
Added: October 13, 2026
Dmitriev A., Kornilov V., Batienkov R., Lecture Notes in Civil Engineering 2026 Vol. 886 P. 249–255
Numerous studies have provided compelling evidence that the probability distribution of avalanche sizes follows a power law, and that 1/f noise is present in the stochastic dynamics of landslides. We present a theoretical explanation of these phenomena within the framework of self-organized criticality theory, proposing a discrete-time model in the form of a sandpile cellular ...
Added: October 13, 2026
Dmitriev A., Shulman I., Lebedev A., Studies in Computational Intelligence 2026 Vol. 1265 P. 266–273
A discrete-time model is presented for the self-organization of the X/Twitter social network to the edge of a phase transition, characterized by avalanche-like propagation of information in the network. The model is based on the analogy between the critical dynamics of the X social network and sandpile cellular automata with Manna rule on the Chung-Lu ...
Added: October 13, 2026
Arutyunov K., Kharitonov I. A., Petrosyants K. O., JETP Letters 2026 Vol. 124 No. 6 P. 1–16
Superconducting properties of metallic micro- and nanowires can be entirely different from those of bulk superconductors. Of particular interest is the nonequilibrium current-induced state of a quasi-one-dimensional superconducting channel. The most interesting phenomenon here is the stepped I–V characteristic, explained by a process known as phase slip center activation. If the origin of such step-like ...
Added: October 13, 2026
Makarov D. M., Kalikin N., Fashchevsky K. A. et al., Electrochimica Acta 2026 Vol. 579 Article 150159
Machine learning (ML) has become a powerful tool for accelerating the development of carbon-based supercapacitors;
however, most published models assume that a single predictive framework can describe both conventional
porous carbons and hybrid carbon electrodes. Here, we test this assumption using a comprehensive
benchmark dataset and an extended literature-curated dataset enriched with synthesis- and electrolyte-related
descriptors. Three ML algorithms ...
Added: October 13, 2026
Zhang Z., Ilvovsky D., Information Processing and Management 2026 Vol. 63 No. 7
Transformer-based Large Language Models (LLMs) rely on Key-Value (KV) cache to accelerate autoregressive decoding, but memory and compute requirements still grow with context length, limiting deployment on resource-constrained devices. Existing training-free KV cache compression methods mainly rely on attention-driven retention heuristics, which may under preserve structurally informative tokens under tight cache budgets, especially when such ...
Added: October 13, 2026
Gusein-Zade S., Campillo A., Delgado F., Mathematische Zeitschrift 2026 Vol. 314 No. 1 P. 1–22
For a subfield $\K$ of the field $\C$ of complex numbers, we consider curve and divisorial valuations on the algebra $\K[[x,y]]$ of formal power series in two variables with the coefficients in $\K$. We compute the semigroup Poincar\'e series and the classical Poincar\'e series of a (discrete, rank one) valuation on it. ...
Added: October 13, 2026
No Species Is an Island, Entire of Itself: Genetic Speciation Algorithm with Interplay among Species
Gromov V., Sohrabi M., Fathollahi-Fard A., International Journal of Engineering, Transactions B: Applications 2027 Vol. 40 No. 5 P. 1437–1460
This paper, with a particular emphasis on Genetic Algorithm (GA), proposes a novel approach that integrates clustering mechanisms, predator-prey dynamics, and a distinctive selection strategy for generating subsequent populations. The proposed evolutionary algorithm, referred to as Genetic Speciation Algorithm with Interplay Among Species (GSAIS), is comprehensively evaluated against several variants of GAs as well as ...
Added: October 12, 2026
Махлуф М., Ozhegov R., Elezov M. et al., Фотоника 2026 Vol. 20 No. 6 P. 414–423
This paper compares the ranging precision of direct time-of-flight (dToF) and non-line-of-sight (NLOS) LiDAR architectures, both using a superconducting nanowire single-photon detector (SNSPD). Both systems operate at 1550 nm with a 50 ps pulsed laser and time-correlated single-photon counting (TCSPC). The dToF configuration achieved approximately 100 µm precision at 10 m, while the NLOS configuration achieved 500 µm precision for ...
Added: October 12, 2026
Mishuris G., Meylan M. H., Pelinovsky E., Journal of Fluid Mechanics 2026 Vol. 1045 Article A4
In this paper, we revisit the classic problem of a wave field on a sloping beach of an arbitrary angle and propose a general approach that allows the computation of regular solutions of the problem regardless of the angle. We use the Mellin-transform technique, reducing the problem to singular integral equations with fixed-point singularities of ...
Added: October 12, 2026
Alexandrov D., Vasilevsky V., Rezunik L. et al., Труды Института системного программирования РАН 2026 Т. 38 № 5 С. 73–90
Large language models demonstrate limitations in tasks that require precise information retrieval from very long input sequences. This limitation affects code generation in large object-oriented systems, where correctness depends on complex inter-class dependencies and the analysis of long execution traces that exceed standard context window sizes. This paper presents JavaCapsule, a technology for automated generation ...
Added: October 12, 2026
Singapore: Springer, 2026.
This volume presents the Proceedings of the 34th IUPAP Conference on Computational Physics (CCP2023), held in Kobe, Japan on August 4–8, 2023. It offers a collection of peer-reviewed articles that highlight recent developments in computational and simulation research across various areas of physics. Key topics include the use of data science, quantum computing, and machine ...
Added: October 12, 2026
Gusein-Zade S., М.: МЦНМО, 2026.
Книга содержит курс лекций по дифференциальной геометрии и топологии, читавшихся автором на механико-математическом факультете МГУ в разные годы. В дополнениях приводятся некоторые сюжеты (связности в расслоениях, теорема Фробениуса, производные Ли и др.), которые были включены в курс в отдельные годы либо содержались в аналогичных курсах лекций в Независимом московском университете.
Для студентов математических и физических специальностей. ...
Added: October 12, 2026
Zykov S. V., Ермаков С. Р., Современные наукоемкие технологии 2026 № 9 С. 43–53
При федеративном обучении с неоднородными клиентскими данными и переменными задержками запоздавшие обновления могут ухудшать качество модели, а обмен параметрами с глобальным сервером увеличивает сетевую нагрузку. Целью исследования является разработка и теоретико-экспериментальное обоснование метода и алгоритмов адаптивного федеративного обучения с учетом распределенного запаздывания клиентских обновлений. Для обоснования разрабатываемых решений использованы событийная и непрерывная модели градиентных обновлений, ...
Added: October 11, 2026
Goncharov A., Chibisov A., Advanced Theory and Simulations 2023 Vol. 12 No. 13 Article 2200816
Designing stable quantum computers with the ability to correct errors responsibly requires a detailed understanding of the physical processes that underlie these devices. In this study, detailed quantum mechanical simulations of the atomic structure, charge distribution of electron density, and distribution and orientation of magnetic and quantum states as a function of applied external pressure ...
Added: October 11, 2026
Chibisov A., Gnidenko A., Chibisova M. et al., FlatChem 2023 Vol. 41 Article 100533
Manufacturing precise quantum computers with small errors in quantum operations, long coherence times, and low power consumption is the most important challenge in modern nanoelectronics. To understand the operating modes of such calculators in detail, both the optimal arrangement of the qubit system within the structure and changes in its magnetic properties must be comprehensively ...
Added: October 11, 2026
Konstantinov A., Elizarova Anastasiya P., Utkin L., Computing, Telecommunications and Control 2026 Vol. 19 No. 1 P. 16–25
Decision trees and their ensemble extensions, such as random forests, are widely used as classification models due to their simplicity and interpretability. However, in many real-world tasks where class labels overlap in the feature space, standard decision trees rely on hard splits that create fragile decision boundaries. In these regions, small perturbations in the input ...
Added: October 2, 2026
International Joint Conferences on Artificial Intelligence, 2026.
Added: October 1, 2026
Lazarev I., Narozniak M., Byrnes T. et al., Physical Review A: Atomic, Molecular, and Optical physics 2025 Vol. 111 No. 012416 Article 012416
Unsupervised machine learning is one of the main techniques employed in artificial intelligence. We introduce an algorithm for quantum-assisted unsupervised data clustering using the self-organizing feature map, a type of artificial neural network. The complexity of our algorithm scales as 𝑂(𝐿𝑁), in comparison to the classical case which scales as 𝑂(𝐿𝑀𝑁), where 𝑁 is the ...
Added: September 14, 2026