Enhancing Machine Learning Models Through PCA, SMOTE-ENN, and Stochastic Weighted Averaging by Youngjin Han, Inwhee Joe

“…By integrating Principal Component Analysis (PCA)<i>,</i> hyperparameter optimization, and resampling methods, as well as combining Edited Nearest Neighbors (<i>ENN</i>) with the Synthetic Minority Oversampling Technique (SMOTE), the model significantly improves predictive accuracy and model generalization. …”
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A Dataset of Real and Synthetic Speech in Ukrainian by Khrystyna Lipianina-Honcharenko, Hennadii Bohuta, Adam Ivaniush, Mariana Soia

“…The dataset contains a unique collection of audio recordings that include both real and synthesized Ukrainian speech, providing unprecedented opportunities for improving machine learning algorithms aimed at speech recognition and analysis. …”
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Overbounding of Near Real-Time Estimated Ionospheric Gradient Slope in Low-Latitude Regions by Maria Caamano, Jose Miguel Juan, Jaume Sanz, Sam Pullen

“…This paper proposes to expand this approach by including the derivation of an uncertainty model for the estimated gradient slope, allowing the threat model to be substituted with the near real-time estimated and overbounded gradient slope in current GBAS algorithms. Evaluations with simulated and real anomalous gradients produced by equatorial plasma bubbles demonstrate the efficacy of this methodology, indicating its potential to enhance GBASs by dynamically detecting, estimating, and overbounding the estimated anomalous gradients instead of relying solely on worst-case models, thus improving system availability and continuity.…”
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Applying Extensions of Evidence Theory to Detect Frauds in Financial Infrastructures by Luigi Coppolino, Salvatore D'Antonio, Valerio Formicola, Luigi Romano

“…Results show substantial improvements of the performance in terms of true positive and false positive rates with respect to the classical DS theory.…”
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Solving the RNA design problem with reinforcement learning. by Peter Eastman, Jade Shi, Bharath Ramsundar, Vijay S Pande

“…This suggests the possibility that future improvements to the training protocol may yield further gains in performance.…”
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Cache replacement strategy based on content value by Dan HUANG, Rongfang SONG

“…The cache replacement mechanism is one of the important research issues of the content center network.Considering the limited cache space,the reasonable replacement of the cache content becomes a key factor affecting the overall performance of the network.Therefore,a cache replacement scheme based on content value was designed.Considering the dynamic popularity of content,the cost of caching,and the time of the most recently requested,a more realistic content value function was built,and an effective content storage and replacement scheme was designed based on the content value function.Specifically,when the cache space was insufficient,the existing cache contents were replaced according to the value from small to large.Simulation results show that compared with the traditional replacement algorithms LRU,LFU and FIFO,the proposed scheme effectively improves the content cache hit rate of network nodes and reduces the average hops of users’ content acquisition.…”
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Enhanced Neutrosophic Set and Machine Learning Approach for Breast Cancer Prediction by Ashika T, Hannah Grace, Nivetha Martin, Florentin Smarandache

“…When trained on the N-dataset instead of traditional datasets, ML algorithms such as Decision Tree (DT), Random Forest (RF), and Adaptive Boosting (AdaBoost) perform better. …”
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Exploring Artificial Intelligence for Enhanced Endodontic Practice: Applications, Challenges, and Future Directions by Santosh R. Patil, Mohmed Isaqali Karobari

“…Key findings demonstrate that AI improves the precision of diagnostics, facilitates personalized treatment planning, and supports clinical decision-making, ultimately enhancing efficiency and patient care. …”
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AI frontiers in emergency care: the next evolution of nursing interventions by Zakaria Mani, Bander Albagawi, Bander Albagawi

“…The review notes that AI in emergency healthcare can lead to more efficient care and timely, data-driven actions, but also highlights significant issues such as safeguarding patient data, the necessity for dependable infrastructure, and concerns over discriminatory algorithms. The promise of AI in improving emergency healthcare practices and patient care is clear, yet the identified challenges must be carefully navigated to promote safe and ethical use. …”
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Collision Avoidance for Wheeled Mobile Robots in Smart Agricultural Systems Using Control Barrier Function Quadratic Programming by Sairoel Amertet, Girma Gebresenbet

“…The entire system was simulated in the MATLAB/Simulink environment, and the results demonstrated a <b>93% improvement in steady-state error over</b> rapidly exploring random tree (RRT). …”
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Application of neural network technology for public opinion analysis by Kyrylo Perevoznyk, Yurii Parzhyn

“…They may be of great practical importance for improving methods of analyzing public opinion and making informed decisions based on a deep understanding of global feedback.…”
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Advancements in epilepsy classification: Current trends and future directions by Rajani Rai B, Karunakara Rai B, Mamatha A S, Kavitha Sooda

“…The paper synthesizes cutting-edge techniques with the focus on the application of hybrid models that combine traditional signal processing techniques with machine learning algorithms. By highlighting key breakthroughs in the field, the paper aims to propose novel directions for improving classification precision. …”
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Key Role and Optimization Dispatch Research of Technical Virtual Power Plants in the New Energy Era by Weigang Jin, Peihua Wang, Jiaxin Yuan

“…For each method, this review presents its mathematical models and solution algorithms. This review highlights the significance of TVPPs in enhancing power system flexibility, improving renewable energy integration, and providing ancillary services. …”
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Development and Validation of a Reduced DME Mechanism Applicable to Various Combustion Modes in Internal Combustion Engines by Gregory T. Chin, J.-Y. Chen, Vi H. Rapp, R. W. Dibble

“…The construction of reduced chemistry was carried out with automatic algorithms incorporating newly developed strategies. …”
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Automatic Navigation and Self-Driving Technology in Agricultural Machinery: A State-of-the-Art Systematic Review by Md. Sabbir Hossain, Mostafijur Rahman, Ashifur Rahman, Md. Mohsin Kabir, M. F. Mridha, Jie Huang, Jungpil Shin

“…Key applications of self-driving machinery in planting, harvesting, and field monitoring were explored, with findings showing improvements in farm productivity, reduced operational costs, and enhanced worker safety. …”
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Distributed Acoustic Sensing of Sounds in Audible Spectrum in Realistic Optical Cable Infrastructure by Petr Dejdar, Ondrej Mokry, Petr Munster, Tomas Horvath, Jiri Schimmel

“…The dataset offers the possibility to develop and test algorithms aimed at enhancing signal-to-noise ratio (SNR), detecting anomalies, and improving speech intelligibility. …”
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Optimized hybrid SVM-RF multi-biometric framework for enhanced authentication using fingerprint, iris, and face recognition by Sonal, Ajit Singh, Chander Kant

“…The integration of support vector machine (SVM) and random forest (RF) classifiers, along with optimization techniques like bacterial foraging optimization (BFO) and genetic algorithms (GA), improves efficiency and robustness. …”
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Machine‐Learning Research in the Space Weather Journal: Prospects, Scope, and Limitations by Noé Lugaz, Huixin Liu, Mike Hapgood, Steven Morley

“…We discuss which manuscripts are within the journal's scope and emphasize that manuscripts focusing purely on a forecasting technique (rather than on understanding and forecasting a phenomenon) must correspond to a substantial improvement over the current state‐of‐the‐art techniques and present this comparison. …”
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Advancing Gamma Knife Radiosurgery with Artificial Intelligence: A New Era of Precision and Efficacy by Kavin K. Devani, Subhas K. Konar, Vikas V. Vazhayil, Arun Thimmarayappa, Nishanth Sadashiva

“…The recent surge in artificial intelligence (AI) applications is revolutionizing the medical field by offering astute data analysis and decision-making advancements. AI, via its algorithmic techniques, improves its performance over time by analyzing the data continuously and learning, identifying, and implementing subtle changes in the data presented to it. …”
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New directions in mapping the Earth’s surface with citizen science and generative AI by Linda See, Qingqing Chen, Andrew Crooks, Juan Carlos Laso Bayas, Dilek Fraisl, Steffen Fritz, Ivelina Georgieva, Gerid Hager, Martin Hofer, Myroslava Lesiv, Žiga Malek, Milutin Milenković, Inian Moorthy, Fernando Orduña-Cabrera, Katya Pérez-Guzmán, Dmitry Schepaschenko, Maria Shchepashchenko, Jan Steinhauser, Ian McCallum

“…This paper discusses how generative AI could be harnessed for land cover/land use mapping by enhancing citizen science approaches with multi-modal large language models (MLLMs), including improvements to the spatial awareness of AI.…”
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