Machine learning based multi-stage intrusion detection system and feature selection ensemble security in cloud assisted vehicular ad hoc networks by C. Christy, A. Nirmala, A. Mary Odilya Teena, A. Isabella Amali

“…A multi-step approach is employed by the proposed system, with each stage dedicated to accurately detecting specific types of attacks. …”
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Elucidating the Role of the Mixing Entropy in Equilibrated Nanoconfined Reactions by Leonid Rubinovich, Micha Polak

“…To obtain the time dependence of the instantaneous mixing entropy following equilibration, the Stochastic Simulation (Gillespie) Algorithm is employed. In particular, the smallest nanosystems exhibit a step-like behavior that deviates significantly from the smooth mean values and is associated with the discrete probability distribution of the reaction extent. …”
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Full Vector Inversion of Magnetic Microscopy Images Using Euler Deconvolution as Prior Information by Gelson F. Souza‐Junior, Leonardo Uieda, Ricardo I. F. Trindade, Janine Carmo, Roger Fu

“…The algorithm follows a three‐step process: (a) employ image processing techniques to identify and isolate data windows for each magnetic source; (b) use Euler Deconvolution to estimate the position of each source; (c) solve a linear inverse problem to estimate the dipole moment of each source. …”
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Cludoop: An Efficient Distributed Density-Based Clustering for Big Data Using Hadoop by Yanwei Yu, Jindong Zhao, Xiaodong Wang, Qin Wang, Yonggang Zhang

“…This paper proposes Cludoop algorithm, an efficient distributed density-based clustering for big data using Hadoop. …”
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FFTL-Net: a network for the classification of skin diseases based on feature fusion and transfer learning by Xiaowei Song, Yurong Mei, Zhilei Zhao, Hao Chang, Lina Han, Hui Wang, Xinyi Zhang, Guoqiang Wang

“…The integration of prior knowledge into the deep network is a critical step in addressing the challenges of overfitting and data imbalance in skin disease classification. …”
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Parallel Primal-Dual Method with Linearization for Structured Convex Optimization by Xiayang Zhang, Weiye Tang, Jiayue Wang, Shiyu Zhang, Kangqun Zhang

“…In contrast to most primal-dual approaches that employ a fixed step size constrained by a global upper limit throughout all iterations, the adaptive step size is typically greater and may result in faster convergence. …”
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A Multi-Level Speed Guidance Cooperative Approach Based on Bidirectional Periodic Green Wave Coordination Under Intelligent and Connected Environment by Luxi Dong, Xiaolan Xie, Lieping Zhang, Shuiwang Li, Zhiqian Yang

“…A bi-level combinatorial optimization method is constructed through a combinatorial deep Q learning method, named Deep Q Network-Genetic Algorithm (DQNGA), with the objective of obtaining the global optimal solution. …”
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Identifying common disease trajectories of Alzheimer’s disease with electronic health recordsResearch in context by Mingzhou Fu, Sriram Sankararaman, Bogdan Pasaniuc, Keith Vossel, Timothy S. Chang

“…In this study, we sought to identify multi-step trajectories culminating in AD by analysing longitudinal electronic health records (EHRs). …”
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Interpretable machine learning for depression recognition with spatiotemporal gait features among older adults: a cross-sectional study in Xiamen, China by Shaowu Lin, Sicheng Li, Ya Fang

“…The five most important gait parameters in the optimal model were left step height, walking speed, right step height, body sway, and step width. …”
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Research on Ship Heave Motion Compensation Control Under Complex Sea State Environment Based on Improved Reinforcement Learning by ZHANG Qin, ZHOU Jingyi, WANG Xingyue, HU Xiong

“…This algorithm surpasses step control methods optimized through particle swarm optimization and outperforms traditional TD3 reinforcement learning methodologies. …”
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Detailed Time-resolved Spectral and Temporal Investigations of SGR J1550–5418 Bursts Detected with Fermi Gamma-Ray Burst Monitor by Mustafa Demirer, Ersin Göğüş, Yuki Kaneko, Özge Keskin, Sinem Şaşmaz, Shotaro Yamasaki

“…Subsequently, we obtained nonoverlapping time segments with varying lengths based on their spectral evolution patterns, employing a machine learning algorithm called k -means clustering. …”
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Experimental acoustic study of small horizontal axis wind turbines based on computational fluid dynamics and artificial intelligence approaches by M. Sadeghi malekabadi, A.R. Davari

“…In conducting multi-objective optimization for both the airfoil and serration shapes, the study demonstrates notable improvements: a 5 to 7% enhancement in aerodynamic performance alongside a simultaneous 1-4% reduction in noise compared to benchmark airfoils. Then, in the second step, experimental methodology is employed to investigate the aeroacoustic attributes of a small horizontal-axis wind turbine with optimized blades. …”
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Study on Dust Distribution Law in Open-Pit Coal Mines Based on Depth Variation by Dongmei Tian, Xiyao Wu, Jian Yao, Weiyu Qu, Jimao Shi, Kaishuo Yang, Jiayun Wang

“…The research team developed a three-dimensional geological model updating algorithm with depth gradient as the characteristic parameter, enabling dynamic monitoring of mining depth with a model iteration accuracy of 0.5 m per update. …”
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Tidal tail identification and detailed analysis of the open star cluster King 13 using Gaia DR3 and 2MASS by Nasser M. Ahmed, Mohamed S. Darwish

“…To assess membership, we employed the pyUPMASK Python package with the HDBSCAN algorithm. …”
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AI-powered literature search: some observations and concerns by Farooq Azam Rathore, Fareeha Farooq

“…The algorithms behind AI tools may inherently approve of a certain type of content or styles of writing, which can affect the summaries produced.7 This data and algorithmic bias may be problematic for seasoned researchers who need to understand the basis for the information being generated by these AI tools. …”
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Evolved Motor Design Process to Reduce the Design Expense of Axial Flux Permanent Magnet Motor by Jong-Min Ahn, Dong-Kuk Lim, Min-Mo Koo

“…Design variables with significant impact on performance are selected, and an optimal design is conducted using a multi-objective optimization algorithm. The analytical method employs the space harmonic method to calculate the motor’s magnetic field distribution using Fourier series, while the conformal mapping method considers the slot effect by incorporating it into the air gap flux density. …”
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Multi-strategy enhanced artificial rabbits optimization for prediction of grades in tourism service communication courses by Xiaodan Qu, Zhuyin Jia

“…To address this issue, a Multi-Strategy Enhanced Artificial Rabbits Optimization Algorithm (MEARO) is introduced. MEARO first employs a Nonlinear Exploration and Exploitation Transition Factor (NL) to improve the balance between exploration and exploitation. …”
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Wideband Beam-Steering Flat Dielectric Lens Antenna for 5G Communications by Zahra Rahimian Omam, Saeideh Shad, Bahram Khalichi, Hani Mehrpouyan, Mohsen Khalily, Ahmed A. Kishk

“…In the feed network, an array of probe-fed rectangular waveguides, each accompanied by a symmetric E-plane step discontinuity and a partial-height conducting post, is employed to enable the launch of multiple beams over a wide operating frequency band. …”
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Decision Support System to Solve Single-Container Loading Problem Considering Practical Constraints by Natalia Romero-Olarte , Santiago Amézquita-Ortiz, John Willmer Escobar, David Álvarez-Martínez

“…We propose an open-source decision support system (DSS) implemented on a widely used platform (MS Excel®), which employs a heuristic algorithm to find efficient loading solutions under these constraints. …”
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The Development of Digital Twin Baby Incubators for Fault Detection and Performance Analysis by Hatice Kabaoğlu, Emine Uçar, Fecir Duran

“…This study focuses on developing a digital twin for baby incubators in neonatal intensive care units to enhance monitoring and care for premature infants. The digital twin employs a hybrid model integrating Long Short-Term Memory (LSTM) and Random Forest (RF) algorithms to predict potential errors and alarms. …”
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