Using the ANYLOGIC program for modeling processes using transformer containers by Yurgin I.V.

“…Original algorithms are proposed to optimize loading and unloading, as well as tools for planning routes taking into account the specific use of such containers. …”
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Resilient Transportation Network Design under Uncertain Link Capacity Using a Trilevel Optimization Model by Mohammad Rahdar, Lizhi Wang, Jing Dong, Guiping Hu

“…This study addresses uncertainty in a transportation network by proposing a trilevel optimization model, which improves resiliency against uncertain disruptions. …”
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Impact of imbalanced features on large datasets by Waleed Albattah, Rehan Ullah Khan

“…The exponential growth of image and video data motivates the need for practical real-time content-based searching algorithms. Features play a vital role in identifying objects within images. …”
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Distinguishing Human From Machine: A Review of Advances and Challenges in AI-Generated Text Detection by Serena Fariello, Giuseppe Fenza, Flavia Forte, Mariacristina Gallo, Martina Marotta

“…Results demonstrate that, despite the good delimited performance, the multitude of languages to recognize, hybrid texts, the continuous improvement of algorithms for text generation and the lack of regulation require additional efforts for efficient detection.…”
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MULTILEVEL RESEARCH OF INNOVATIVE AND REPRODUCTION DEVELOPMENT OF REGIONS ON THE BASIS OF THE STATISTICAL ANALYSIS by Yu. A. Dmitriev, D. Yu. Fraymovich, Z. V. Mishchenko

“…The analysis of the approaches to an assessment of innovative development of territories which are available today allows to establish the fact of possibility of their improvement and entering of essentially new non-standard procedures into algorithms of calculation of resultant sizes. …”
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Pioneering the Security of EHRs Using an Immersive Blockchain Conceptual Framework by Rihab Benaich, Youssef Gahi, Saida El Mendili

“…Objectives include strengthening data protection against both traditional and quantum cyber threats, increasing system resilience, and improving user experience and operational efficiency. …”
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Twofold dynamic attention guided deep network and noise-aware mechanism for image denoising by Zihao Chen, Alex Noel Joseph Raj, Vijayarajan Rajangam, Wei Li, Vijayalakshmi G.V. Mahesh, Zhemin Zhuang

“…While employing deeper networks, network performance improves with the cost of additional computational requirements. …”
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Architectural Synthesis of Fixed-Point DSP Datapaths Using FPGAs by Gabriel Caffarena, Juan A. López, Gerardo Leyva, Carlos Carreras, Octavio Nieto-Taladriz

“…The use of a complete fixed-point datapath leads to improvements up to 35%. And, the wise mapping of operations to FPGA resources (logic fabric and embedded blocks), thanks to the proposed resource usage metric, leads to improvements up to 54%.…”
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A Review of Research on Path Planning of Unmanned Surface Vessel Swarm: Deep Reinforcement Learning by Yuli HOU, Ning WANG, Chidong QIU, Yongpeng WENG

“…Secondly, the principle, application scenarios, and improvement directions of various typical DRL algorithms were discussed, and their advantages and disadvantages were analyzed. …”
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GAINSeq: glaucoma pre-symptomatic detection using machine learning models driven by next-generation sequencing data by Muhammad Iqbal, Arshad Iqbal, Humaira Ayub, Maqbool Khan, Naveed Ahmad, Yasir Javed, Mohammed Ali Alshara

“…These algorithms demonstrated outstanding accuracy and resilience. …”
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Scalable reinforcement learning for large-scale coordination of electric vehicles using graph neural networks by Stavros Orfanoudakis, Valentin Robu, E. Mauricio Salazar, Peter Palensky, Pedro P. Vergara

“…Extensive experimental evaluations show that EV-GNN significantly outperforms state-of-the-art RL algorithms in scalability and generalization across diverse EV charging scenarios, delivering notable improvements in both small- and large-scale problems.…”
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A systematic review of deep learning applications in database query execution by Bogdan Milicevic, Zoran Babovic

“…We categorize these approaches into three groups based on how such models are applied: improving performance of index structures and consequently data manipulation algorithms, query optimization tasks, and externally controlling query optimizers through parameter tuning. …”
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Basics of the semantic portal of nuclear knowledge BelNET functioning by S. N. Sytovа, V. V. Haurylavets, A. P. Dunets, A. N. Kavalenka, S. V. Charapitsa

“…The possibility of using semantic technologies for the development and improvement of the content management system of the scientific and educational portal eLab-Science and the Belarusian nuclear knowledge portal BelNET (Belarusian Nuclear Education and Training Portal, https://belnet.by/) created on its basis is being considered.Methods. …”
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Survey on explainable knowledge graph reasoning methods by Yi XIA, Mingjng LAN, Xiaohui CHEN, Junyong LUO, Gang ZHOU, Peng HE

“…In recent years, deep learning models have achieved remarkable progress in the prediction and classification tasks of artificial intelligence systems.However, most of the current deep learning models are black box, which means it is not conducive to human cognitive reasoning process.Meanwhile, with the continuous breakthroughs of artificial intelligence in the researches and applications, high-performance complex algorithms, models and systems generally lack the transparency and interpretability of decision making.This makes it difficult to apply the technologies in a wide range of fields requiring strict interpretability, such as national defense, medical care and cyber security.Therefore, the interpretability of artificial intelligence should be integrated into these algorithms and systems in the process of knowledge reasoning.By means of carrying out explicit explainable intelligence reasoning based on discrete symbolic representation and combining technologies in different fields, a behavior explanation mechanism can be formed which is an important way for artificial intelligence to realize data perception to intelligence perception.A comprehensive review of explainable knowledge graph reasoning was given.The concepts of explainable artificial intelligence and knowledge reasoning were introduced briefly.The latest research progress of explainable knowledge graph reasoning methods based on the three paradigms of artificial intelligence was introduced.Specifically, the ideas and improvement process of the algorithms in different scenarios of explainable knowledge graph reasoning were explained in detail.Moreover, the future research direction and the prospect of explainable knowledge graph reasoning were discussed.…”
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Enhancing Crop Type Mapping in Data-Scarce Regions Through Transfer Learning: A Case Study of the Hexi Corridor by Jingjing Mai, Qisheng Feng, Shuai Fu, Ruijing Wang, Shuhui Zhang, Ruoqi Zhang, Tiangang Liang

“…As target domain data were gradually incorporated, the total accuracy for all models ranged from 0.77 to 0.92, with F1-scores ranging from 0.76 to 0.92, showing a consistent improvement in model performance. This study highlights the feasibility of employing transfer learning for crop mapping in the Hexi Corridor, demonstrating its potential to reduce labeling costs for target domain samples and providing a valuable reference for crop mapping in regions with limited sample availability.…”
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Failure Effects Evaluation for ATC Automation System by Rui Li, Zili Zhou, Yansong Cheng, Jianqiang Wang

“…By analyzing and evaluating the failure modes and their causes and effects, some reasonable improvement measures and preventive maintenance plans can be established. …”
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An objective measure for assessing the quality of contrast enhancement on magnetic resonance images by Simi Venuji Renuka, Damodar Reddy Edla, Justin Joseph

“…Post-processing algorithms like histogram equalization and its variants have been widely employed to enhance the contrast of Magnetic Resonance (MR) images. …”
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Efficiency of neural quantum states in light of the quantum geometric tensor by Sidhartha Dash, Luca Gravina, Filippo Vicentini, Michel Ferrero, Antoine Georges

“…However, the reason behind the practical improvement in their performance with an increase in the number of parameters is not fully understood. …”
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Detection of Fake News Using Deep Learning and Machine Learning by Gabriela CHIRIAC, Ada Maria CATINA

“…Machine Learning and Deep Learning algorithms for detection demand continuous adaptation as disinformation tactics evolve. …”
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A review on multi-fidelity hyperparameter optimization in machine learning by Jonghyeon Won, Hyun-Suk Lee, Jang-Won Lee

“…Tuning hyperparameters effectively is crucial for improving the performance of machine learning models. …”
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