Current Tasks in Identifying Invalid Events in Critical Information Infrastructure by D. A. Evdokimova, A. A. Mikryukov

“…Problems related to large data volumes, the complexity of event processing, the considerable time required for their detection, and technological limitations were considered. …”
Get full text

Unsupervised clustering of temporal patterns in high-dimensional neuronal ensembles using a novel dissimilarity measure. by Lukas Grossberger, Francesco P Battaglia, Martin Vinck

“…SPOTDisClust does not require binning and can detect complex patterns (beyond sequential activation) even when high levels of out-of-pattern "noise" spiking are present. …”
Get full text

Obstacle Avoidance Control of Autonomous Undersea Vehicle Based on DVFH+ in Ocean Current Environment by Zhongben ZHU, Jiahao ZHANG, Yifan XUE, Hongde QIN

“…This enabled the calculation of the planning instructions based on environmental characteristics around AUVs, ensuring the efficiency and safety of navigation. Simulation experiments using the REMUS 100 AUV model show that DVFH+ can provide a smoother and more feasible obstacle avoidance route, making it suitable for AUV obstacle avoidance in complex environments while effectively preventing issues such as detouring and planning failure caused by improper threshold settings in the original algorithm.…”
Get full text

Enhanced futures price-spread forecasting based on an attention-driven optimized LSTM network: integrating an improved grey wolf optimizer algorithm for enhanced accuracy by Yongli Tang, Zhenlun Gao, Zhongqi Cai, Jinxia Yu, Panke Qin

“…Financial market prediction faces significant challenges due to the complex temporal dependencies and heterogeneous data relationships inherent in futures price-spread data. …”
Get full text

Iridium porphyrin-catalysed asymmetric carbene insertion into primary N-adjacent C–H bonds with TON over 1000000 by Zong-Rui Li, Kun Zhan, Yi-Jie Wang, Liang-Liang Wu, Guo-Lin Lu, Hao-Yang Wang, Xiao-Long Wan, Zhen-Jiang Xu, Kam-Hung Low, Chi-Ming Che

“…Abstract Selective functionalization of ubiquitous C-H bonds in organic molecules provides a straightforward and efficient approach to construct complex molecules with fewer synthetic steps and high atom economy, thus promoting more sustainable and economical chemical synthesis. …”
Get full text

SP-RF-ARIMA: A sparse random forest and ARIMA hybrid model for electric load forecasting by Kamran Hassanpouri Baesmat, Farhad Shokoohi, Zeinab Farrokhi

“…Accurate Electric Load Forecasting (ELF) is crucial for optimizing production capacity, improving operational efficiency, and managing energy resources effectively. …”
Get full text

Toward Trustworthy Machine Learning for Daily Sediment Modeling in the Riverine Systems: An Integrated Framework With Enhanced Uncertainty Quantification and Interpretability by Z. J. Yue, N. N. Wang, B. D. Xu, X. Huang, D. M. Yang, H. B. Xiao, Z. H. Shi

“…To achieve trustworthy ML for riverine sediment timeseries predictions, this study proposes an integrated ML framework, enhancing key steps: feature selection, UQ, and interpretation. Lagged hydro‐environmental variables are incorporated via rigorous feature selection. …”
Get full text

Prioritizing simulation-based stress tests to assess the resilience of transport systems: a computation-free methodology by Hossein Nasrazadani, Maria Nogal, Bryan T. Adey, Stergios A. Mitoulis

“…It enables infrastructure managers to efficiently screen and rank stress tests, optimizing the selection process to maximize insights into system resilience while minimizing computational demands. …”
Get full text

An Adaptive Signal Denoising Method Based on Reweighted SVD for the Fault Diagnosis of Rolling Bearings by Baoxiang Wang, Chuancang Ding

“…Due to the harsh and complex operating conditions, rolling element bearings (REBs) are prone to failures, which can result in significant economic losses and catastrophic breakdowns. …”
Get full text

Elite leader dwarf mongoose optimization algorithm by Anping Lin, Yong Liao, Chengfeng Peng, Xiang Li, Xing Zhang

“…Abstract Dwarf mongoose optimization algorithm (DMOA) is a recently proposed meta-heuristics, it attracts widely attention due to its effectiveness in solving complex optimization. However, DMOA utilizes roulette wheel selection to evolve the individual, this method may cause the swarm evolving unevenly and the swarm diversity losing rapidly. …”
Get full text

NORMALISATION OF THE DRIVE PRECISION OF METAL-CUTTING MACHINES by Irina A. Klenova, Dmitry A. Rudikov, Svetlana N. Kholodova

“…Conclusion The use of the proposed methodology expands the scientific basis for the development of algorithms and programs facilitating the selection of the optimal number of gear teeth for multiplying groups and structures and guaranteeing high accuracy of the gained series.…”
Get full text

The evolving role of programming and LLMs in the development of self-driving laboratories by John R. Kitchin

“…Machine learning and automation are transforming scientific research, yet the implementation of self-driving laboratories (SDLs) remains costly and complex, and it remains difficult to learn how to use these facilities. …”
Get full text

Diagnostics of the enterprise’s business potential by A.A.

“…The grouping of diagnostic methods was carried out in accordance with the goals of the diagnosis (diagnostics of the strategic perspective of development; diagnostics of competitiveness; diagnostics of the components of business potential; diagnostics of the possibility of the onset of a financial crisis), which contributes to increasing the efficiency of its implementation. It has been proven that achieving the goal and solving the tasks of diagnosing business potential is possible due to: the formation of reliable information support; successful selection of diagnostic methods; analytical substantiation of the conclusion regarding the state and opportunities of business potential; development and implementation of measures to improve the existing situation; conducting control over the implementation of measures.…”
Get full text

Neuro-Evolution of Augmenting Topologies for Dynamic Scheduling of Flexible Job Shop Problem by Jian Huang, Yarong Chen, Jabir Mumtaz, Liuyan Zhong

“…The NEAT algorithm harnesses the features of dynamic flexible job shop scheduling problems (DFJSPs) to devise heuristic rules for job selection and machine allocation, synthesizing these rules into coherent scheduling strategies. …”
Get full text

Comparative analysis of convolutional neural networks and transformer architectures for breast cancer histopathological image classification by Bo Yuan, Yudie Hu, Yan Liang, Yutong Zhu, Lingyu Zhang, Shimin Cai, Rui Peng, Xianbin Wang, Zheng Yang, Jinhui Hu

“…This indicates that with minimal adaptation, foundation models can be valuable tools in digital pathology, especially in complex multi-class scenarios.…”
Get full text

Chitosan-encapsulated linoleic acid from Leucaena leucocephala (Lam.) de Wit. inhibits FOXL2 mutation in MNU-induced ovarian granulosa cell tumors in Wistar rats by Cletus Anes Ukwubile, Hassan Braimah Yesufu, Roland Nnaemeka Okoro, Ahamefula Anslem Ahuchaogu, Blessing Ogechukwu Umeokoli, Matthew Onyema Agu, Nnamdi David Menkiti, Patrick Akoji Ida

“…Gel retardation assay showed efficient complexation between LACS2 and FOXL2 gene, with maximum complex formation (86.22 ± 2.04 %) observed at 32 mg chitosan and 8 mg FOXL2. …”
Get full text

Enhancing education quality with hybrid clustering and evolutionary neural networks in a multi phase framework by Saleem Malik, Chandrakanta Mahanty, Jnanaranjan Mohanty, Krunal Vaghela, T. Narmadha, R. Sivaranjani, Javed Khan Bhutto, Saiful Islam, Anwar Khan, Amanuel Zewdie

“…This algorithm’s strong feature selection and clustering help target educational interventions by revealing student learning behaviors. …”
Get full text

An Effective Method for Borehole Imaging of Buried Tunnels by Loreto Di Donato, Rosa Scapaticci, Tommaso Isernia, Ilaria Catapano, Lorenzo Crocco

“…Since this requires to drill holes in the soil wherein the transmitting and receiving antennas have to be positioned, low complexity of the involved apparatus is important. On the other hand, to effectively image the surveyed area, there is the need for adopting efficient and reliable imaging methods. …”
Get full text

Soil moisture retrieval and spatiotemporal variation analysis based on deep learning by Zihan Zhang, Jinjie Wang, Jianli Ding, Jinming Zhang, Liya Shi, Wen Ma

“…We demonstrate that the design of efficient neural network architectures is essential for soil moisture inversion, and provides valuable insights for deep learning applications in hydrological parameter estimation and other challenges in complex environmental contexts.…”
Get full text

Multiradar Collaborative Task Scheduling Algorithm Based on Graph Neural Networks with Model Knowledge Embedding by Haoqing LI, Dian YU, Changchun PAN, Wenxian YU, Dongying LI

“…Modern radar systems face increasingly complex challenges in tasks such as detection, tracking, and identification. …”
Get full text