Full-chain comprehensive assessment and multi-scenario simulation of geological disaster vulnerability based on the VSD framework: a case study of Yunnan province in China by Li Xu, Shucheng Tan, Runyang Li

“…Thus, scientifically assessing and predicting geological disasters and formulating disaster prevention and mitigation policies are of critical importance for promoting regional sustainable development. However, current evaluations of geological disasters often overlook the adaptive capacity of the disaster-bearing body and focus primarily on cross-sectional comparisons across different regions at specific time points, with insufficient attention to spatiotemporal dynamics. …”
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Investigating the impact of fatty acid profiles on biodiesel lubricity using artificial intelligence techniques by Atthaphon Maneedaeng, Attasit Wiangkham, Atthaphon Ariyarit, Anupap Pumpuang, Ekarong Sukjit

“…To further analyze the impact of fatty acid composition on lubricity, an artificial intelligence (AI)-based approach using the Adaptive Boosting (AdaBoost) algorithm was implemented. …”
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Rolling Bearing Fault Diagnosis Method Based on Improved Variational Mode Decomposition and Information Entropy by Wen FAN, Lian GE, Xiaoting XIAO, Fangji GAN, Xin LAI, Hongxia DENG, Qi HUANG

“…A new fitness function combining differential evolution (DE) algorithm with gray wolf optimization (GWO) algorithm is proposed to form a new hybrid optimization algorithm, named DEGWO. …”
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Full Information Numerical Simulation of Two-Dimensional Steady Ground Temperature Field by Fan Jiang, Shikun Dai, Ying Zhang, Hongjun Tian

“…The equations under different wavenumbers are independent of each other and highly parallel, while retaining vertical spatial domain, with strict upper and lower boundary conditions, which can adapt to the needs of complex terrain simulation. …”
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LuViRA Dataset Validation and Discussion: Comparing Vision, Radio, and Audio Sensors for Indoor Localization by Ilayda Yaman, Guoda Tian, Erik Tegler, Jens Gulin, Nikhil Challa, Fredrik Tufvesson, Ove Edfors, Kalle Astrom, Steffen Malkowsky, Liang Liu

“…Each sensor is paired with a current state-of-the-art localization algorithm and evaluated for different aspects: localization accuracy, reliability and sensitivity to environment changes, calibration requirements, and potential system complexity. …”
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Wavelet Transform-Based 3D Landscape Design and Optimization for Digital Cities by Yang Chen, Xiaolin Wang, Chang Zhang

“…The algorithm extracts mixed feature information of local long path and local short path based on the information retention module, and decomposes the information by combining wavelet transform, inputs the different components obtained from the decomposition into the network for training, and removes the noise by subsequent feature screening of the network structure. …”
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The Macroalgae Ecological Quality Index (MEQI) in the Basin of Mexico: a proposal of aquatic bioindicators for peri-urban rivers by Javier Carmona-Jiménez, Victor Hugo Salinas-Camarillo, Angela Caro-Borrero

“…By assigning an indicator value to each group of species, we calculated the MEQI using the formula adapted from Pantle and Buck, indicating five different ecological quality classes. …”
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Impact of dimensionality reduction techniques on student performance prediction using machine learning by Koushik Roy, Huu-Hoa Nguyen, Dewan Md. Farid

“…This reduction in dimensionality enhances the performance of predictive models and provides valuable insights into the key factors influencing student performance. The study evaluates ADRA using four different student performance datasets and six machine learning algorithms, comparing it to three existing dimensionality reduction methods. …”
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Prediction of Moisture Content in Kiwi (Actinidia deliciosa) Dried Using Machine Learning Approaches by Halil Nusret BULUS, Soner CELEN

“…In this study, kiwi slices of three different thicknesses were dried using 90 W microwave power. …”
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Two-Timescale Cross-Layer Design for URLLC Over Parallel Fading Channels With Imperfect CSI by Hongsen Peng, Meixia Tao

“…Based on the small timescale optimization method, we adopt the ternary search algorithm to optimize the pilot length and pilot power through Monte Carlo evaluations in the large timescale. …”
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Opportunities, Challenges, and Future Directions for Generative Artificial Intelligence in Library Information Literacy Education: A Scoping Review by Fan YUAN, Jia LI

“…Future research directions should focus on conducting empirical studies in different educational contexts, developing adaptive teaching frameworks that balance technological innovation with traditional educational values, and investigating the long-term impact of GenAI integration on learning outcomes. …”
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Parallel Simulation Multi-Sample Task Scheduling Approach Based on Deep Reinforcement Learning in Cloud Computing Environment by Yuhao Xiao, Yping Yao, Feng Zhu

“…Complex scenario analysis and evaluation simulations often involve multiple sets of simulation applications with different combinations of parameters, thus resulting in high computing power consumption, which is one of the factors that limits the efficiency of multi-sample parallel simulations. …”
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Predicting Landslide Deposit Zones: Insights from Advanced Sampling Strategies in the Ilopango Caldera, El Salvador by Laura Paola Calderon-Cucunuba, Abel Alexei Argueta-Platero, Tomás Fernández, Claudio Mercurio, Chiara Martinello, Edoardo Rotigliano, Christian Conoscenti

“…Additionally, the Multivariate Adaptive Regression Splines (MARS) algorithm was used for modeling. …”
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Trusted Energy-Aware Hierarchical Routing (TEAHR) for Wireless Sensor Networks by Vikas, Charu Wahi, Bharat Bhushan Sagar, Manisha Manjul

“…The mechanism in TEAHR overcomes these challenges by placing an adaptive trust assessment mechanism that adapts to the background network conditions and real-time activities of the nodes. …”
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Impact of dimensionality reduction techniques on student performance prediction using machine learning by Koushik Roy, Huu-Hoa Nguyen, Dewan Md. Farid

“…This reduction in dimensionality enhances the performance of predictive models and provides valuable insights into the key factors influencing student performance. The study evaluates ADRA using four different student performance datasets and six machine learning algorithms, comparing it to three existing dimensionality reduction methods. …”
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Research on Hyperspectral Inversion of Soil Organic Carbon in Agricultural Fields of the Southern Shaanxi Mountain Area by Yunhao Han, Bin Wang, Jingyi Yang, Fang Yin, Linsen He

“…For feature band selection, three methods were utilized: Variable Importance Projection (VIP), Competitive Adaptive Reweighted Sampling (CARS), and Stepwise Projection Algorithm (SPA). …”
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End-Edge Collaborative Lightweight Secure Federated Learning for Anomaly Detection of Wireless Industrial Control Systems by Chi Xu, Xinyi Du, Lin Li, Xinchun Li, Haibin Yu

“…Furthermore, to ensure the parameter security during wireless transmission in the open radio environment, we propose an adaptive key generation algorithm for parameter encryption. …”
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A Study on the Impact of Obstacle Size on Training Models Based on DQN and DDQN by Lu Siyu, Tao Ye, Zeng Junwei, Zuo Qihuan

“…Various parameters such as obstacle size and complexity influence the agent's performance, promoting efficient learning and policy optimization using both DQN and DDQN algorithms under different configurations. After our experiment, comparing with DQN, we found that DDQN could be a better algorithm in car racing scenarios as in some extreme environments, DQN would not very accurately estimate future reward, therefore, agent could not make better decisions because of the misguided evaluation. …”
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Genome-Wide Tool for Sensitive de novo Identification and Visualisation of Interspersed and Tandem Repeats by Ruslan Kalendar, Ulykbek Kairov

“…Studying these repeats of different origins is essential for understanding the evolution and adaptation of a given organism. …”
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Symbiotic Learning Grey Wolf Optimizer for Engineering and Power Flow Optimization Problems by Aala Kalananda Vamsi Krishna Reddy, Komanapalli Venkata Lakshmi Narayana

“…SL-GWO’s symbiotic hunting strategies provide a major overhaul to the exiting hierarchical hunting through population sub-grouping into attacking hunters and experienced hunters with individually crafted dynamic adaptive tuning. The hunting mechanisms are implemented through the inclusion of random omega wolves from the wolfpack thereby reducing the algorithm’s excessive dependence on the three dominant wolves and enhancing the population diversity. …”
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