Artificial intelligence-based personalized diet: A pilot clinical study for irritable bowel syndrome by Tarkan Karakan, Aycan Gundogdu, Hakan Alagözlü, Nergiz Ekmen, Seckin Ozgul, Varol Tunali, Mehmet Hora, Damla Beyazgul, O. Ufuk Nalbantoglu

“…AI-based diet was designed based on optimizing a personalized nutritional strategy by an algorithm regarding individual gut microbiome features. …”
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Precise irrigation of dryland cotton under canal irrigation system constraints based on the CERES-CROPGRO-Cotton model by Lei Wang, Liang He, Weihong Sun, Chen Gao, Zhenxiang Han, Meiwei Lin

“…The results indicate that the intelligent decision-making algorithm outperforms traditional methods under data limitations, reducing the irrigation water consumption-yield ratio (Ui) by 3.99 %, while increasing yield by 8.5 % to 9724 kg/ha, thus achieving both water-saving and yield-enhancing objectives. …”
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Innovative Lightweight Detection for Airborne Remote Sensing: Integrating G-Shuffle and Dynamic Multiscale Pyramid Networks by Ruofei Liang, Yigang Cen, Linna Zhang, Fugui Zhang, Yansen Huang, Fei Gan

“…To address the challenges of significant scale variations and difficulty in extracting discriminative features for small targets in airborne remote sensing object detection, while considering the constraints and efficiency requirements of onboard systems, this article proposes a lightweight detection algorithm. …”
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Track Classification and Characteristics Analysis of Northeast China Cold Vortex During the Warm Season by Jin Tong, Yueming Yu, Qiuping Wang, Xulin Ma, Zhaorong Zhuang

“…This study employed ERA5 reanalysis data over 2012–2022 and the optimized K-means clustering algorithm to classify NCCV tracks into five types: (A) eastward-moving dissipative, (B) eastward-moving retrogressive, (C) short-range eastward-moving offshore, (D) long-range eastward-moving offshore, and (E) long-range southeastward-moving offshore. …”
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Novel method for robust bilateral filtering point cloud denoising by Huan Yang, Wei Wang, Yue Wang, Peng Wang

“…To assess and compare the performance of this algorithm with related ones, the mean square angular error (MSAE) and angular error distribution (AE) were employed to evaluate the accuracy of normal estimation, while the mean square error (MSE) and signal-to-noise ratio (SNR) were employed to assess the denoising performance. …”
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Computer Modelling «Smart Building» by O. Yu. Maryasin, A. S. Kolodkina, A. A. Ogarkov

“…The peculiarity of this model is the use of specialized management and control algorithms which allow providing coordinated interaction of subsystems and optimizing power consumption.…”
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Simulating Argo float trajectories and along-track physical and biogeochemical variability in the California Current System by Xiao Liu, Xiao Liu, John P. Dunne, Elizabeth J. Drenkard, Gregory C. Johnson

“…This study provides new insights to inform optimal float deployment planning, sampling strategies, and data interpretation.…”
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Meigs’ syndrome with elevated CA-125 and HE-4: a case report and literature review by Jichang Seong, Abdusattorov Ravshan, Sametdinov Narkhodzha, Kurbanova Saida, Alimov Jamshid, Alimov Jamshid, Babanov Bahriddin, Sharobidinov Biloliddin

“…Serum CA-125 and HE-4 levels were markedly elevated (1,200 IU/mL and 82.1 pmol/L, respectively), with a Risk of Ovarian Malignancy Algorithm (ROMA) score of 25.63%, suggesting advanced ovarian malignancy. …”
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Unraveling C-to-U RNA editing events from direct RNA sequencing by Adriano Fonzino, Caterina Manzari, Paola Spadavecchia, Uday Munagala, Serena Torrini, Silvestro Conticello, Graziano Pesole, Ernesto Picardi

“…To overcome this issue in direct RNA reads, here we introduce a novel machine learning strategy based on the isolation Forest (iForest) algorithm in which C-to-U editing events are considered as sequencing anomalies. …”
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Classification and Physical Characteristic Analysis of Fermi-GBM Gamma-Ray Bursts Based on Deep Learning by Jia-Ming Chen, Ke-Rui Zhu, Zhao-Yang Peng, Li Zhang

“…Additionally, we apply the optimal model to extract features from the count maps and visualize the extracted GRB features using the t-SNE algorithm, discovering two distinct clusters corresponding to S-type and L-type GRBs. …”
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Artificial Neural Network Modelling of Photodegradation in Suspension of Manganese Doped Zinc Oxide Nanoparticles under Visible-Light Irradiation by Yadollah Abdollahi, Azmi Zakaria, Nor Asrina Sairi, Khamirul Amin Matori, Hamid Reza Fard Masoumi, Amir Reza Sadrolhosseini, Hossein Jahangirian

“…To obtain the optimum topologies, ANN was trained by quick propagation (QP), Incremental Back Propagation (IBP), Batch Back Propagation (BBP), and Levenberg-Marquardt (LM) algorithms for testing data set. The topologies were determined by the indicator of minimized root mean squared error (RMSE) for each algorithm. …”
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Machine learning for Internet of Things (IoT) device identification: a comparative study by Hamid Tahaei, Anqi Liu, Hamid Forooghikian, Mehdi Gheisari, Faiz Zaki, Nor Badrul Anuar, Zhaoxi Fang, Longjun Huang

“…Additionally, we implemented a Binary Green Wolf Optimizer (BGWO) and compared its performance with that of traditional ML classifiers to assess the potential of this binary meta-heuristic algorithm. …”
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Online variational Gaussian process for time series data by Weidong Wang, Mian Muhammad Yasir Khalil, Leta Yobsan Bayisa

“…Unlike traditional methods that rely on a fixed number of inducing points, OLVGP adaptively adjusts the number of inducing points as new data arrives and optimizes them from the model, ensuring that the model remains computationally efficient while maintaining high predictive accuracy. …”
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Parallel boosting neural network with mutual information for day-ahead solar irradiance forecasting by Ubaid Ahmed, Anzar Mahmood, Ahsan Raza Khan, Levin Kuhlmann, Khurram Saleem Alimgeer, Sohail Razzaq, Imran Aziz, Amin Hammad

“…However, DL models often demand substantial computational resources and large datasets, while DT algorithms lack generalizability. To address these limitations, this study proposes a novel parallel boosting neural network (PBNN) framework that integrates boosting algorithms with a feedforward neural network (FFNN). …”
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A Two-Stage Deep Learning Method for Marine Oil Spill Localization and Segmentation From Synthetic Aperture Radar Images by Xudong Huang, Biao Zhang, William Perrie

“…Existing methods for detecting oil spills using synthetic aperture radar (SAR) often face challenges related to algorithm complexity, limited data availability, and practical implementation. …”
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Structural design, modeling and simulation analysis of a cage broiler inspection robot by Yongmin Guo, Xinwei Yu, Wanchao Zhang, Changxi Chen, Liji Yu

“…This design provides the necessary strength and durability while maintaining a lightweight profile. Additionally, the incorporation of a five-axis mechanical arm, integrated with sensors and a gimbal lifting algorithm, ensures adaptability to intricate inspection spaces, with a focus on energy efficiency. …”
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ReliefSeq: a gene-wise adaptive-K nearest-neighbor feature selection tool for finding gene-gene interactions and main effects in mRNA-Seq gene expression data. by Brett A McKinney, Bill C White, Diane E Grill, Peter W Li, Richard B Kennedy, Gregory A Poland, Ann L Oberg

“…The ReliefSeq implementation adapts the number of nearest neighbors (k) for each gene to optimize the Relief-F test statistics (importance scores) for finding both main effects and interactions. …”
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Multi-Level Spectral Attention Network for Hyperspectral BRDF Reconstruction from Multi-Angle Multi-Spectral Images by Liyao Song, Haiwei Li

“…For the multi-level Transformer spectral dimension enhancement algorithm, we added spectral response loss constraints to improve BRDF accuracy. …”
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Estimation of Chlorophyll Content at Stand and Individual Tree Level by UAV Hyperspectral Combined with LiDAR by Zhuonan Meng, Ying Yu, Xiguang Yang, Tao Yang

“…In this study, a total of 36 characteristic variables from hyperspectral image and lidar point cloud data acquired through an unmanned aerial vehicle (UAV) platform were used to evaluate the accuracy of statistical models including multiple stepwise regression, BP neural network, BP neural network optimized by firefly algorithm, random forest, and the mixed data-driven mechanistic model PROSPECT model in estimating chlorophyll content for three different forest types in Maoershan Forest Farm of Northeast Forestry University in Heilongjiang Province, namely coniferous forest, broad-leaved forest, and coniferous–broad-leaved mixed forest. …”
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Preoperative prediction of pulmonary ground-glass nodule infiltration status by CT-based radiomics combined with neural networks by Kun Mei, Zikang Feng, Hui Liu, Min Wang, Chao Ce, Shi Yin, Xiaoying Zhang, Bin Wang

“…Feature selection was performed using the Lasso algorithm to identify the most predictive variables, which were subsequently incorporated into the radiomics-based neural network model. …”
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