Identification of Papua Cenderawasih Batik Motifs using Local Binary Pattern and K-Nearest Neighbor by Dian Dwi Ariani, Sitti Zuhriyah, Eva Yulia Puspaningrum, Mahabintang Pallawabonang

“…Future research could improve model accuracy by utilizing larger data sets and classification algorithms to make the models more accurate.…”
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Hygrobot: Hydrogen-Powered Mobile Robotic Platform for Rough Terrain: Electro-Mechanical Design, Physical Implementation, and Experimental Testing by Cirilo Delgado Asencio, Francisca Segura Manzano, José Manuel Andújar Márquez

“…Although substantial advancements have been achieved in creating marketable mobile robot designs, including improvements to their physical composition, sensory systems, navigation algorithms, and operational management, their widespread integration is still hindered. …”
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Development of machine learning models for predicting non-remission in early RA highlights the robust predictive importance of the RAID score-evidence from the ARCTIC study by Gaoyang Li, Shrikant S. Kolan, Franco Grimolizzi, Joseph Sexton, Giulia Malachin, Guro Goll, Tore K. Kvien, Tore K. Kvien, Nina Paulshus Sundlisæter, Manuela Zucknick, Siri Lillegraven, Espen A. Haavardsholm, Espen A. Haavardsholm, Bjørn Steen Skålhegg

“…The predictive power of each feature was assessed using a composite measure derived from individual algorithm estimates.ResultsThe model demonstrated a mean AUC-ROC of 0.75-0.76, with mean sensitivity of 0.77-0.81, precision (also referred to as Positive Predictive Value) of 0.77-0.79 and specificity of 0.63-0.66 across the criteria. …”
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Novel therapeutic approaches to correct retinal metabolic abnormalities in primary open-angle glaucoma and age-related macular degeneration by K. A. Mirzabekova

“…Currently, several vitamin and mineral supplements that differ in composition, dosage, and schedule are approved in Russia. …”
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Optimal Coverage Path Planning for Unmanned Surface Vehicles Using Flexible Formation Tracking Control by Minsung Park, Bo Woo Nam

“…Unmanned surface vehicle (USVs) have attracted significant attention in cooperative surveys of marine environments, where efficient coverage path planning (CPP) is crucial. …”
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ANTi-JAM solutions for smart roads: Ant-inspired traffic flow rules under CAVs environment by Marco Guerrieri, Nicola Pugno

“…The macroscopic traffic flow variables of interest were estimated using the deep learning method and the YOLO detection algorithm. The results show that ants adopt specific traffic strategies (platoon formation, quasi-constant speed and no overtaking maneuvers) that help avoid jam phenomena, even at high density. …”
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Game Cross Efficiency for Systems with Two-Stage Structures by Chaoqun Ma, Debin Liu, Zhongbao Zhou, Wei Zhao, Wenbin Liu

“…For systems with two-stage structures, where all the outputs from the first stage are the only inputs to the second stage, the centralized model, which is based on the concept of cooperative game theory, has been widely used to examine the efficiencies of such systems. …”
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The RMaP challenge of predicting RNA modifications by nanopore sequencing by Jannes Spangenberg, Stefan Mündnich, Anne Busch, Stefan Pastore, Anna Wierczeiko, Winfried Goettsch, Vincent Dietrich, Leszek P. Pryszcz, Sonia Cruciani, Eva Maria Novoa, Kandarp Joshi, Ranjan Perera, Salvatore Di Giorgio, Paola Arrubarrena, Irem Tellioglu, Chi-Lam Poon, Yuk Kei Wan, Jonathan Göke, Andreas Hildebrandt, Christoph Dieterich, Mark Helm, Manja Marz, Susanne Gerber, Nicolo Alagna

“…Results demonstrate that a low prediction error and a high prediction accuracy can be achieved on these modifications across different approaches and algorithms. The RMaP challenge marks a substantial step towards improving algorithms’ comparability, reliability, and consistency in RNA modification prediction. …”
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Research on load labeling method for big data in novel power system by ZHANG Ximing, XU Huan, YANG Qiuyong

“…Unique evaluation indicators are also identified to measure the performance of the composite dataset. The synthetic dataset is compared with the real dataset, and the smart grid machine learning algorithm is trained and tested on this basis. …”
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Pollen holographic images and light-induced fluorescence measurements at the species level by Sophie Erb, Alexis Berne, Bernard Clot, Maria Lbadaoui-Darvas, Gian-Duri Lieberherr, Marie-Pierre Meurville, Fiona Tummon, Benoît Crouzy

“…These data are meant to be used as the basis for training new pollen identification algorithms that will make use of fluorescence measurements. …”
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Research on pricing strategy of shared electro-thermal-hydrogen energy storage in integrated energy multi-microgrid based on hybrid game by Huan Zhou, Jie Wei

“…The model is solved using a genetic algorithm (GA) and the alternating direction method of multipliers (ADMM). …”
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Passenger Flow Prediction of Integrated Passenger Terminal Based on K-Means–GRNN by Yifan Tan, Haixu Liu, Yun Pu, Xuemei Wu, Yubo Jiao

“…As the passenger flow distribution center cooperating with various modes of transportation, the comprehensive passenger transport hub brings convenience to passengers. …”
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The Legal Infrastructures of UK Border Control—Cerberus and the Dispositif of Speculative Suspicion by Gavin Sullivan, Dimitri Van Den Meerssche

“…We conclude with reflections on critiquing algorithmic systems like Cerberus through the emergent infrastructural relations they enact.…”
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Machine learning-based model for acute asthma exacerbation detection using routine blood parameters by Youpeng Chen, Junquan Sun, Yabang Chen, Enzhong Li, Jiancai Lu, Huanhua Tang, Yifei Xie, Jiana Zhang, Lesi Peng, Haojie Wu, Zhangkai J. Cheng, Baoqing Sun

“…Results: The Generalized Linear Model Boosting combined with Random Forest (glmBoost + RF) algorithm using 14 variables achieved comparable performance (Area Under the Curve [AUC] = 0.981) to the more complex Least Absolute Shrinkage and Selection Operator combined with Random Forest (Lasso + RF) algorithm using 25 variables (AUC = 0.985). …”
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Nanomodification analysis of pore structure in GO-enhanced CWRB based on metal intrusion and BSE imaging with deep learning by Jiajian Yu, Yi Gong, Yuan Gao, Hao Sui, Xiaoli Xu, Yanming Liu

“…The deep Taylor decomposition (DTD) algorithm successfully locates the reinforced characteristics of the GO modification in CWRB specimens under the resolution of 340 nm. …”
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SILF Dataset: Fault Dataset for Solar Insecticidal Lamp Internet of Things Node by Xing Yang, Liyong Zhang, Lei Shu, Xiaoyuan Jing, Zhijun Zhang

“…The results indicate that machine learning algorithms can achieve high accuracy on the proposed dataset. …”
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A multi-agent reinforcement learning approach for continuous battery cell-level balancing by Yasaman Tavakol-Moghaddam, Mehrdad Boroushaki

“…Trained with the trust region policy optimization (TRPO) algorithm, the approach ensures stability and partial observability. …”
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Bankruptcy rules and sustainable water management: A MODSIM-NSGAII simulation multi-objective optimization framework for equitable transboundary water allocation by Bentolhoda Asl-Rousta, S. Jamshid Mousavi

“…A mechanism based on the rationality principle of cooperative games and the equity concept is designed to identify the most stable solution. …”
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Bio-inspired multi-dimensional deep fusion learning for predicting dynamical aerospace propulsion systems by Michael Qian Vergnolle, Eastman Z. Y. Wu, Yanan Sui, Qian Wang

“…Specifically, a shared parameter fusion algorithm is employed to effectively integrate Fourier and Wavelet analyses, providing full and sliced 1D sequences to form 2D tensors that can be seamlessly processed by parameter-efficient inception blocks. …”
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Conjugate Cellular Automata and Neural Network Approach: Failure Load Prediction of Masonry Panels by Iuliia Glushakova, Qihan Liu, Yu Zhang, Guangchun Zhou

“…The NN uses a backpropagation algorithm and two hidden layers with sigmoid activation functions to predict failure loads. …”
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