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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Sparse Array Mutual Coupling Reduction by C. Larmour, N. Buchanan, V. Fusco, M. Ali Babar Abbasi

“…The paper conducts a comprehensive comparison of multiple array design optimisation techniques, including genetic algorithm, covariance matrix adaptation evolution strategy, particle swarm optimisation, trust-region framework, Nelder-Mead simplex algorithm, interpolated Quasi-Newton, and classic Powell. …”
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The sustainable energy development dilemma in European countries: a time-series cluster analysis by Víctor Dugo, David Gálvez-Ruiz, Pilar Díaz-Cuevas

“…Abstract Background Measuring the evolution of countries in various related dimensions is essential for the evaluation of progress and compliance with the set of sustainable development goals. …”
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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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Computationally expensive constrained problems via surrogate-assisted dynamic population evolutionary optimization by Zan Yang, Chen Jiang, Jiansheng Liu

“…Specifically, the population is dynamically constructed by simultaneously considering the real-time feasibility, convergence, and diversity information of all the previously evaluated solutions. The evolution strategies adapted to dynamic populations are designed to arrange targeted search resources for individuals with different potentials. …”
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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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A Review of Vibration Control Studies of Double-Layered Cylindrical Shells Under Transient Excitation in Water by Zhen Zhang, Yinglong Zhao, Feng Chen

“…Firstly, the vibration response mechanisms of underwater double-layered cylindrical shells are sorted through a bibliometric analysis, and the evolution laws for plate–shell structures and the vibration transmission paths for single–double-shell structures are summarized systematically; secondly, the multi-path vibration transmission characteristics of double-layered cylindrical shells are analyzed based on energy transfer theory, and the contribution to transient noise through different transmission paths is quantitatively evaluated; and thirdly, the vibration transmission characteristics of active control, passive control, and hybrid control are evaluated systematically in terms of the dimensions of the control mechanism. …”
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An echo state network based on enhanced intersecting cortical model for discrete chaotic system prediction by Xubin Wang, Pei Ma, Jing Lian, Jizhao Liu, Yide Ma

“…The performance of the ESN-EICM was compared to that of a standard ESN and a Long Short-Term Memory (LSTM) network. The evaluation used data from three discrete chaotic systems (Logistic, Sine, and Ricker) for both one-step and multi-step prediction tasks.ResultsThe experimental results indicate that the ESN-EICM produced lower error metrics (MSE, RMSE, MAE) compared to the standard ESN and LSTM models across the tested systems, with the performance difference being more pronounced in multi-step forecasting scenarios. …”
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Angle detection method for surface mount components based on weighted clustering by Chunfu ZHANG, Zhiqiang SONG

“…To validate the effectiveness of the proposed method, we conducted experimental tests on eight different types of chip packages and compared the results with those from two state-of-the-art line segment detection algorithms currently in use. …”
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