LensNet: Enhancing Real-time Microlensing Event Discovery with Recurrent Neural Networks in the Korea Microlensing Telescope Network by Javier Viaña, Kyu-Ha Hwang, Zoë de Beurs, Jennifer C. Yee, Andrew Vanderburg, Michael D. Albrow, Sun-Ju Chung, Andrew Gould, Cheongho Han, Youn Kil Jung, Yoon-Hyun Ryu, In-Gu Shin, Yossi Shvartzvald, Hongjing Yang, Weicheng Zang, Sang-Mok Cha, Dong-Jin Kim, Seung-Lee Kim, Chung-Uk Lee, Dong-Joo Lee, Yongseok Lee, Byeong-Gon Park, Richard W. Pogge

“…We demonstrate a classification accuracy above 87.5% and anticipate further improvements as we expand our training set and continue to refine the algorithm.…”
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Machine Learning Applications in Road Pavement Management: A Review, Challenges and Future Directions by Tiago Tamagusko, Matheus Gomes Correia, Adelino Ferreira

“…We discuss the limitations of conventional PMS and explore how Artificial Intelligence (AI) algorithms can overcome these shortcomings by improving the accuracy of pavement condition assessments, enhancing performance prediction, and optimizing maintenance and rehabilitation decisions. …”
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Secure and efficient batch authentication scheme based on dynamic revocation mechanism in space information network by Yinghui ZHANG, Lingyun HU, Yixin LI, Jianting NING, Dong ZHENG

“…A secure and efficient batch authentication scheme based on dynamic revocation mechanism was proposed for the problem of cross-domain authentication of a large number of mobile users in space information networks.Early key negotiation was achieved by predicting the satellite trajectory and updating the session key in real time.Algorithms were designed for a single as well as a large number of mobile terminals to perform signing and verification, which effectively reduce the computational burden of satellites.Cuckoo filters were adopted by the new scheme to achieve dynamic revocation and malicious access control of mobile terminals.Finally, under the Diffie-Hellman assumption, the proposed scheme was proved to be resistant to replay and man-in-the-middle attacks based on a random oracle model and automated validation of internet security protocols and applications.Security goals such as traceability and revocability were achieved by the scheme, thus improving the efficiency of transmission and computation by more than 80% and 20%, respectively, compared with the existing optimal scheme.…”
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An upgraded high-precision gridded precipitation dataset for the Chinese mainland considering spatial autocorrelation and covariates by J. Hu, C. Miao, J. Su, Q. Zhang, J. Gou, J. Gou, Q. Sun, Q. Sun

“…Specifically, it achieves a mean absolute error of 1.48 mm d<span class="inline-formula">⁻¹</span> and a Kling-Gupta efficiency of 0.88, representing improvements of 12.84 % and 12.86 %, respectively, compared to the previously optimal dataset. …”
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The application of blockchain with a comparative approach and its impact on risk, flexibility and internal control evaluation by mohammadsadegh aminipoor, HamidReza GholamniaRoshan, azadeh kiapour, Iman Dadashi

“…Overall, blockchain can help improve risk, flexibility and internal control assessment. …”
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Graph Based Cooperative Forwarding in Information Centric Vehicular Networks by Beri Surya Samantha, Nitul Dutta, Rajesh Mahadeva, Shashikant P. Patole, Gheorghita Ghinea

“…The prime objective of the algorithm is to reduce content retrieval time and optimize network overhead and throughput. …”
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Heterogeneous Graph Attention Networks for Scheduling in Cloud Manufacturing and Logistics by Dmitrii Fomin, Ilya Makarov, Mariia Voronina, Anna Strimovskaya, Vitaliy Pozdnyakov

“…Our model minimizes both manufacturing and logistics costs, achieving significant performance improvements over greedy algorithms and comparable results to strong genetic algorithms in large-scale scenarios with up to 20 locations. …”
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Development and Training of a Neural Network Filter for Satellite Images Processing by N. Andriyanov, A. Kim

“…As part of the study, the architecture of the autoencoder was developed, optimal hyperparameters were selected and the resulting neural network model was trained. …”
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Pertinence of contact duration as edge feature for epidemic spread analysis by Ramya D. Shetty, Shrutilipi Bhattacharjee

“…In this study, we mainly aim to generate weighted networks to model the pathogen spread by optimal calculation of the edge weight in terms of contact duration (time spent) between individual contacts. …”
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What factors enhance students' achievement? A machine learning and interpretable methods approach. by Hui Mao, Ribesh Khanal, ChengZhang Qu, HuaFeng Kong, TingYao Jiang

“…This study addresses these limitations by employing an ensemble of five machine learning algorithms (SVM, DT, ANN, RF, and XGBoost) to model multivariate relationships between four behavioral and six instructional predictors, using final exam performance as our outcome variable. …”
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Comparative Analysis of Facial Expression Recognition Methods by Denys - Florin COT

“…The integration of such solutions can contribute to the development of decision support systems in psychiatry, optimizing therapeutic strategies, and improving the quality of care for patients with neuropsychological conditions. …”
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PERSONALIZED APPROACH TO THYROTOXICOSIS TREATMENT: THE HISTORY OF DOSIMETRIC CONCEPTS DEVELOPMENT by P. O. Rumyantsev, A. A. Trukhin, M. V. Degtyarev

“…Historically there were developed several methods for calculating effective therapeutic activity: prescription of standard activities (fixed activities) and personalized assessment of effective activity based on evaluation of individual radiobiokinetics, followed by the mathematical modeling. Accumulated variety of approaches to dosimetric planning of radionuclide therapy demonstrates that an optimal algorithm for calculation has not been developed so far. …”
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Research on image generation technology based on deep learning by Li Jinchen

“…Based on the above problems, this paper analyzes the methods of improving and optimizing the mainstream image generation algorithm from the perspectives of improving and optimizing the loss function, improving the space modeling, revising the structure of both the generator and discriminator, while speeding up the training process. …”
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Advancing Stability in Robot Manipulators: A Review of Recent Progress and Parameters by Shabnom Mustary, Mohammod Abul Kashem, Jannatul Mawya Sony, Nayem Hossain, Mohammad Asaduzzaman Chowdhury

“…Uses of Lyapunov and Passivity‐Based Control for key stability improvements incorporate robust solutions to nonlinear dynamics and uncertainties. …”
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Convolutional neural networks and vision transformers for Plankton Classification by Loris Nanni, Alessandra Lumini, Leonardo Barcellona, Stefano Ghidoni

“…The study considers the creation of ensembles combining different Convolutional Neural Network (CNN) models and transformer architectures to understand whether different optimization algorithms can result in more robust and efficient classification across various plankton datasets. …”
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AI-Driven Robotics: Innovations in Design, Perception, and Decision-Making by Lei Li, Li Li, Mantian Li, Ke Liang

“…Artificial intelligence (AI), driven by large datasets and advanced algorithms, plays a pivotal role in addressing these challenges and advancing robotics. …”
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Integrating holographic counterparts for intelligent IoT consumer devices by M. Rajesh, M. Usha, Sathishkumar Veerappampalayam Easwaramoorthy

“…Advancements in quantum algorithms for predictive learning, self-optimization through more integrated machine learning models, and the development of standardised interoperability protocols to facilitate wider industrial usage are all areas that will be investigated in future research.…”
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Recent Advances in Multi-Agent Reinforcement Learning for Intelligent Automation and Control of Water Environment Systems by Lei Jia, Yan Pei

“…From the perspective of cooperative control, this paper investigates the modeling mechanisms and policy coordination strategies of MARL in key tasks such as water supply scheduling, hydro-energy co-regulation, and autonomous monitoring. …”
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AEM-D3QN: A Graph-Based Deep Reinforcement Learning Framework for Dynamic Earth Observation Satellite Mission Planning by Shuo Li, Gang Wang, Jinyong Chen

“…These features are then encoded into a reinforcement learning model that dynamically optimizes scheduling policies under multiple resource constraints. …”
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Fully automated multicolour structured illumination module for super-resolution microscopy with two excitation colours by Haoran Wang, Peter T. Brown, Jessica Ullom, Douglas P. Shepherd, Rainer Heintzmann, Benedict Diederich

“…To optimize DMD diffraction, we developed a model for tilt and roll pixel configurations, enabling use with various low-cost projectors in SIM setups. …”
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