<b>The investigation of commonalities in human brain semantic representations across people and across languages</b><br> by Augusto Buchweitz

“…These patterns allow computer algorithms to identify the brain activity associated with a specific word or picture. …”
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Applied of Classification Technique in Data Mining For Credit Scoring by Heriyanto Heriyanto, Ika Kurniawati, Fachri Amsury, Muhammad Rizki Fahdia, Irwansyah Saputra, Nanang Ruhyana, Asrul

“…The best prediction results are nave Bayes with an accuracy of 95.95 % and an AUC of 0.974. …”
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The constrained-disorder principle defines the functions of systems in nature by Yaron Ilan

“…The paper reviews variability-based CDP algorithms and CDP-based second-generation artificial intelligence systems and their potential for improving systems’ prediction and efficiency by using variability.…”
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AI may enable robots to make a clinical impact in total knee arthroplasty, where navigation has not! by Michael T. Hirschmann, Rüdiger vonEisenhart‐Rothe, Heiko Graichen, Stefano Zaffagnini

“…Through the utilization of real‐time data and prediction algorithms, artificial intelligence‐guided robots have the potential to overcome the limits of conventional approaches, thereby establishing a new benchmark for TKA.…”
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Application of Improved WOA in Hammerstein Parameter Resolution Problems under Advanced Mathematical Theory by Lu Zhao, Jiangjun Liu, Yuan Li

“…In identifying Hammerstein model under heavy-tailed noise, the average prediction recognition accuracy of the improved whale algorithm was 92.38%, the determination coefficient was 0.89, the percentage fitting error was 0.03, and the system error was 0.02. …”
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SynergyAI: A Human–AI Pair Programming Tool Based on Dataflow by Le Jiang, Shingo Yamaguchi, Mohd Anuaruddin Bin Ahmadon

“…Additionally, the tool leverages comprehensive prediction algorithms and ensemble learning to simplify the operation of complex dataflows and mitigate overfitting risks. …”
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Pharmacotherapeutic Options for Ophthalmic Conjunctivitis by A. D. van Eyk

“…There is however a challenge in distinguishing between the various types of conjunctivitis due to the similarity in the symptoms and due to a lack of tests and prediction algorithms, thus antibiotic therapy is often incorrectly initiated. …”
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Target Tracking Using a Time-Varying Autoregressive Dynamic Model by Ralph J. Mcdougall, Simon J. Godsill

“…Target tracking algorithms commonly use structured dynamic models which require prior training of fixed model parameters. …”
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Natural Killer (NK) Cell Alloreactivity in Haploidentical Stem Cell Transplantation by Mar Luis-Hidalgo, José Luis Piñana, Carlos Solano, Dolores Planelles

“…These models consider the presence or absence of specific ligands or receptors and/or <i>KIR</i> genes in the donor and recipient to predict alloreactivity. Determining the best model for predicting KIR alloreactivity and its significance in donor selection algorithms for haploidentical transplantation is still under investigation.…”
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A conditional opposition-based particle swarm optimisation for feature selection by Jingwei Too, Ali Safaa Sadiq, Seyed Mohammad Mirjalili

“…Hence, feature selection is a necessary pre-processing stage to select the important features that may considerably increase the efficiency of underlying classification algorithms. As a popular metaheuristic algorithm, particle swarm optimisation has successfully applied to various feature selection approaches. …”
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A Review on Machine Learning Models in Injection Molding Machines by Senthil Kumaran Selvaraj, Aditya Raj, R. Rishikesh Mahadevan, Utkarsh Chadha, Velmurugan Paramasivam

“…Neural networks have considerable applications in the injection molding process consisting of optimization, prediction, identification, classification, controlling, modeling, and monitoring, particularly in manufacturing. …”
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Mapping Antarctic Blue Ice Areas With Sentinel-2A/B Images and LightGBM Model by Xiaolong Teng, Jiahui Xu, Xiangbin Cui, Guitao Shi, Zhengyi Hu, Qingyu Gu, Bailang Yu, Jianping Wu, Yan Huang

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Enhanced EKF and SVSF for state of charge estimation of Li‐ion battery in electric vehicle using a fuzzy parameters model by Meriem Ben Lazreg, Sabeur Jemmali, Bilal Manai, Mahmoud Hamouda

“…The results show that the maximum root mean square error (RMSE) of the estimated SoC is kept within 1.51% with the FP‐EKF and 0.68% with the FP‐SVSF. Moreover, the reduction of the maximum absolute error may reach 0.34% with the FP‐EKF, and 0.82% with the FP‐SVSF, compared to the same algorithms without the proposed FP method. …”
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Improved Synthesis of Global Irradiance with One-Minute Resolution for PV System Simulations by Martin Hofmann, Stefan Riechelmann, Cristian Crisosto, Riyad Mubarak, Gunther Seckmeyer

“…A comparison based on measurements performed in Lindenberg, Germany, and Carpentras, France, shows a reduction of the frequency distribution root mean square errors of more than 60% compared to the two existing synthesizing algorithms.…”
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Exploring Continuous Seismic Data at an Industry Facility Using Unsupervised Machine Learning by Chengping Chai, Omar Marcillo, Monica Maceira, Junghyun Park, Stephen Arrowsmith, James O. Thomas, Joshua Cunningham

“…The Uniform Manifold Approximation and Projection for Dimension Reduction algorithm was used to reduce the dimensionality of the data and generate 2D embeddings. …”
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Uncovering Key Topics in Indonesian Political Discourse Through Twitter Analysis After the 2024 Presidential Inauguration Using Clustering methods by Syarif Hidayatullah, Ulfa Siti Nuraini

“…PCA is used for dimensionality reduction. The clustering algorithms K-means, DBSCAN, PAM, and Agglomerative Hierarchical are employed, with performance evaluated based on the Silhouette Score. …”
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Load recognition method based on convolutional neural network and attention mechanism by ZHAO Yitao, LI Zhao, LIU Xinglong, LUO Zhao, WANG Gang, SHEN Xin

“…Non-intrusive load monitoring (NILM) of residential houses is an important research content of the user demand side of smart grids, and the energy consumption analysis and power consumption management of residential loads are key steps in achieving energy conservation, emission reduction, and sustainable development. Aiming at the problems of poor recognition performance of traditional algorithms and difficulty in adapting to the current complex electricity environment, a NILM load recognition method integrating convolutional neural network (CNN)-self-attention mechanism is proposed from the optimization idea of enhancing the feature extraction performance of classification algorithms. …”
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A YOLOv8n-T and ByteTrack-Based Dual-Area Tracking and Counting Method for Cucumber Flowers by Liyang Su, Shujuan Zhang, Hongtu Zhang, Xiangsen Meng, Xiongkui He

“…Accurate counting of cucumber flowers using intelligent algorithms to monitor their sex ratio is essential for intelligent facility agriculture management. …”
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Optimizing Energy Efficiency in Cloud Data Centers: A Reinforcement Learning-Based Virtual Machine Placement Strategy by Abdelhadi Amahrouch, Youssef Saadi, Said El Kafhali

“…Under the iqr_1.5_mc strategy, the reductions are even more significant: 12.11% compared to PABFD, 15.6% compared to PSO, and 18.67% compared to genetic algorithms. …”
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Hardware Implementation for Triaxial Contact-Force Estimation from Stress Tactile Sensor Arrays: An Efficient Design Approach by María-Luisa Pinto-Salamanca, Wilson-Javier Pérez-Holguín, José A. Hidalgo-López

“…This paper describes the hardware implementation of the proposed sparse algorithm and that of an algorithm previously reported in the literature, comparing the results of both hardware implementations with the software results already validated. …”
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