Performance Enhancement of GPS/INS Integrated Navigation System Using Wavelet Based De-noising method by narjes davari, Asghar Gholami, mohammad shabani

“…Before using inertial sensors signals in the data fusion algorithm, noise removal method should be performed, in which, wavelet decomposition method is used. …”
Get full text

Utilizing Enhanced Particle Swarm Optimization for Feature Selection in Gender-Emotion Detection From English Speech Signals by Ammar Amjad, Li-Chia Tai, Hsien-Tsung Chang

“…The gender-specific DGA-EBPSO algorithm incorporates a hybrid mutation strategy to improve feature selection efficiency and considers gender-based variations in emotional expression. …”
Get full text

Superficially Plausible Outputs from a Black Box: Problematising GenAI Tools for Analysing Qualitative SoTL Data by Mirjam Sophia Glessmer, Rachel Forsyth

“…We conclude that while results may look plausible initially, digging deeper soon reveals serious problems; the lack of transparency about how analyses are conducted and results are generated means that no reproducible method can be described. …”
Get full text

Poverty‐Armed Conflict Nexus: Can Multidimensional Poverty Data Forecast Intrastate Armed Conflicts? by Çağlar Akar, Doğa Başar Sarıipek, Gökçe Cerev

“…It utilizes a machine‐learning algorithm and annually published fragility data to forecast future intrastate armed conflicts. …”
Get full text

Enhanced Vector Quantization for Embedded Machine Learning: A Post-Training Approach With Incremental Clustering by Thommas K. S. Flores, Morsinaldo Medeiros, Marianne Silva, Daniel G. Costa, Ivanovitch Silva

“…This study introduces a novel method to optimize Post-Training Quantization (PTQ), a widely used technique for reducing model size, by integrating Vector Quantization (VQ) with incremental clustering. While VQ is a technique that reduces model size by grouping similar parameters, incremental clustering, implemented via the AutoCloud K-Fixed algorithm, preserves accuracy during compression. …”
Get full text

Anomaly-Aware Tropical Cyclone Track Prediction Using Multi-Scale Generative Adversarial Networks by He Huang, Difei Deng, Liang Hu, Nan Sun

“…The model is designed to handle diverse inputs, including satellite cloud imagery, vorticity, wind speed, and geopotential height, and it features an advanced center detection algorithm to ensure precise TC center identification. …”
Get full text

Historical changes in the Causal Effect Networks of compound hot and dry extremes in central Europe by Yinglin Tian, Domenico Giaquinto, Giorgia Di Capua, Judith N. Claassen, Javed Ali, Hao Li, Carlo De Michele

“…Here, we use Causal Effect Networks (based on the Peter and Clark momentary conditional independence algorithm) and show that hot extreme events in central Europe are driven primarily by anomalous atmospheric patterns and soil water deficiency. …”
Get full text

DQN-Based Shaped Reward Function Mold for UAV Emergency Communication by Chenhao Ye, Wei Zhu, Shiluo Guo, Jinyin Bai

“…In this paper, we establish a meticulously crafted virtual simulation environment and leverage advanced deep reinforcement learning algorithms to train UAVs agents. Notwithstanding, the development of reinforcement learning algorithms is beset with challenges such as sparse rewards and protracted training durations. …”
Get full text

Influence of Source Shape on Semi-Airborne Transient Electromagnetic Surveys by Lei Liu, Jianghai Xie, Wentao Liu, Jianmei Zhou

“…A three-dimensional (3D) block model is established, and a model order reduction algorithm is applied to calculate the 3D spatial distribution of electromagnetic fields generated by both an ideal linear source and a curved source. …”
Get full text

Sparse DOA Estimation Method Based on Riemann Averaging under Strong Intermittent Jamming by Xiaoyu LAN, Jiyan HU, Mingshen LIANG, Shuang MA

“…Compared with existing subspace algorithms and sparse reconstruction class algorithms, the proposed algorithm has higher estimation accuracy and angular resolution at a smaller number of snapshots, as well as a lower signal-to-noise ratio.…”
Get full text

Hybrid nanofluid flow around a circular cylinder: A coupled ANN and numerical study of MHD, bioconvection, and thermal radiation by Muhammad Fawad Malik

“…This study aims to examine the heat transfer properties of cross-hybrid nanofluid flow around a circular cylinder while accounting for the effects of thermal radiation, tilted magnetohydrodynamics (MHD), activation energy, and bioconvection. …”
Get full text

Log-Based Analysis of Creativity in the Context of Computational Thinking by Rotem Israel-Fishelson, Arnon Hershkovitz

“…We developed a Python algorithm to automatically analyze the logged solutions across four creativity measures. …”
Get full text

RL-Based Vibration-Aware Path Planning for Mobile Robots’ Health and Safety by Sathian Pookkuttath, Braulio Felix Gomez, Mohan Rajesh Elara

“…The results show that it effectively avoids rough areas while maintaining the shortest distance.…”
Get full text

Simplified Model Predictive for Controlling Circulating and Output Currents of a Modular Multilevel Converter by Abolfazl Sheybanifar, Seyed Masoud Barakati

“…In addition, a bilinear mathematical model of the MMC is derived and discretized to predict the states of the MMC for one step ahead. A sorting algorithm is used to retain the balancing capacitor voltage in each SM, while the cost function guarantees the regulation of the output current, and MMC circulating current. …”
Get full text

Parametric study and optimization of energy consumption in batch reverse osmosis for constant permeate flowrate by Abdeljalil Chougradi, Ahmed Abed

“…Batch reverse osmosis configuration has huge potential as an alternative to conventional continuous configuration. While the batch process has many variants, in our work, we study the case of the batch configuration under time-dependent pressure delivering constant permeate flowrate. …”
Get full text

Machine Learning Methods for Predicting Cardiovascular Diseases: A Comparative Analysis by Aiym B. Temirbayeva, Arshyn Altybay

“…The primary research question is to identify which algorithm demonstrates the best predictive performance for heart disease diagnosis. …”
Get full text

Estimating Carbon Stock in Unmanaged Forests Using Field Data and Remote Sensing by Thomas Leditznig, Hermann Klug

“…An overall accuracy of 80.8% with a Cohen’s kappa value of 0.74 was achieved for the land cover classification, while the carbon stock of the living above-ground biomass (AGB) was estimated with an accuracy within 5.9% of field measurements. …”
Get full text

RM-MOCO: A Fast-Solving Model for Neural Multi-Objective Combinatorial Optimization Based on Retention by Huiqing Wei, Fei Han, Qing Liu, Henry Han

“…An industry-standard deep reinforcement learning algorithm is used to train RM-MOCO. Experimental results show that, while ensuring the quality of problem solving,the proposed method significantly outperforms some other methods in terms of the speed of solving MOCO problems.…”
Get full text

Estimation of Current RMS for DC Link Capacitor of S-PMSM Drive System by ZHANG Zhigang, CHANG Jiamian, ZHANG Pengcheng

“…Given the sophisticated processes involved and numerous unresolved integrals while calculating the current RMS value of the capacitor using traditional double Fourier integral algorithm, this paper proposes a method to calculate the current RMS value of the DC capacitor based on polynomial interpolation and quadrature method Cotes. …”
Get full text

Machine learning approach for identifying and forecasting streamflow droughts in data limited basins of South Korea using threshold levels by Young-Ho Seo, Jang Hyun Sung, Byung-Sik Kim, Junehyeong Park

“…Physically based models, while comprehensive, are labor-intensive and inherently uncertain. …”
Get full text