Nanodesigner: resolving the complex-CDR interdependency with iterative refinement by Melissa Maria Rios Zertuche, Şenay Kafkas, Dominik Renn, Magnus Rueping, Robert Hoehndorf

“…NanoDesigner integrates key stages—structure prediction, docking, CDR generation, and side-chain packing—into an iterative framework based on an expectation maximization (EM) algorithm. …”
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Deep Learning-Based Signal Constellation for OFDM Underwater Acoustic Communications by Ammar E. Abdelkareem, Majid Dherar Younus, Emad A. Al-Sabawi

“…The hegemony was depicted in the performance of the bit error rate (BER) of the proposed DL-based signal constellation prediction algorithm, which achieved 100% accuracy and a gain of 10dB and 12dB over minimum mean square error (MMSE) and least square (LS) channel estimation performance, respectively, when CP=0 at N_p=N/4. …”
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Online Meta-Recommendation of CUSUM Hyperparameters for Enhanced Drift Detection by Jessica Fernandes Lopes, Sylvio Barbon Junior, Leonimer Flávio de Melo

“…With the increasing demand for time-series analysis, driven by the proliferation of IoT devices and real-time data-driven systems, detecting change points in time series has become critical for accurate short-term prediction. The variability in patterns necessitates frequent analysis to sustain high performance by acquiring the hyperparameter. …”
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TARNet: An Efficient and Lightweight Trajectory-Based Air-Writing Recognition Model Using a CNN and LSTM Network by Md. Shahinur Alam, Ki-Chul Kwon, Shariar Md Imtiaz, Md Biddut Hossain, Bong-Gyun Kang, Nam Kim

“…LSTM is good for time series prediction yet time-consuming; on the other hand, CNN is superior in feature generation but comparatively faster. …”
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Modelling maintenance scheduling strategies for highway networks. by Bao Tong, Jianwei Wang, Xue Wang, Feihao Zhou, Xinhua Mao, Yaxin Duan

“…A simulated annealing algorithm and augmented Lagrange algorithm are employed to solve the two proposed models, respectively. …”
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Computer Course Design Plan for Film and Television Media Major by Shan Hui, Xiao Zhang, Tian Yang

“…In view of the excellent global optimization ability of GA and the defects of the BP algorithm itself, this work adopts the improved GA algorithm to optimize the BP network, and establishes an IGA-BP network combination model with higher prediction accuracy. …”
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Dynamic scheduling strategies for cloud-based load balancing in parallel and distributed systems by Nasser S. Albalawi

“…The Least Response Time (LRT) technique for the Load Monitoring procedures will be developed once the job scheduling is complete. The Harmony Search Algorithm with Linear Regression (LR-HSA) is then used to do Distributed Computing-based Load Prediction and Adjustment. …”
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Real-Time Accurate Determination of Table Tennis Ball and Evaluation of Player Stroke Effectiveness with Computer Vision-Based Deep Learning by Zilin He, Zeyi Yang, Jiarui Xu, Hongyu Chen, Xuanfeng Li, Anzhe Wang, Jiayi Yang, Gary Chi-Ching Chow, Xihan Chen

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Machine Learning Applied to Near-Infrared Spectra for Chicken Meat Classification by Sylvio Barbon, Ana Paula Ayub da Costa Barbon, Rafael Gomes Mantovani, Douglas Fernandes Barbin

“…Determining wavelengths relevance and selecting subsets for classification and prediction models are mandatory for the development of multispectral systems. …”
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Application of Monte Carlo Simulation (MCS) and Fuzzy Finite Element (FFEM) for Investigating the Uncertainty of Seepage in Homogeneous Earth Dams by Milad Kheiry, Farhoud Kalateh

“…The purpose of this research is to investigate the impact of uncertainty in the prediction of seepage flow through earth dams using the Fuzzy Monte Carlo Simulation (FMCS) new hybrid algorithm, which is implemented with the help of the finite element method and monte carlo simulation. …”
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Backdoor Defence for Voice Print Recognition Model Based on Speech Enhancement and Weight Pruning by Jiawei Zhu, Lin Chen, Dongwei Xu, Wenhong Zhao

“…Firstly, input samples are perturbed by superimposing various speech patterns, and the backdoor samples are determined based on the randomness (entropy value) of the prediction classes with perturbed inputs from a given deployment model (malicious or benign). …”
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Optimization Method for Transit Signal Priority considering Multirequest under Connected Vehicle Environment by Song Xianmin, Yuan Mili, Liang Di, Ma Lin

“…Aiming at reducing per person delay, this paper presents an optimization method for Transit Signal Priority (TSP) considering multirequest under connected vehicle environment, which is based on the travel time prediction model. Conventional arrival time of transit depended on the detection information and the front road state, which restricted the effect of priority seriously. …”
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Offline Single-Polarization Radar Quantitative Precipitation Estimation Based on a Spatiotemporal Deep Fusion Model by Yonghong Zhang, Shiwei Chen, Wei Tian, Guangyi Ma, Shuai Chen

“…Quantitative precipitation estimation (QPE) based on Doppler radar plays an important role in severe weather monitoring, industrial and agricultural production, and natural disaster prediction and prevention. However, the temporal and spatial variability of precipitation leads to large errors in radar estimates of mixed precipitation. …”
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Contrail altitude estimation using GOES-16 ABI data and deep learning by V. R. Meijer, V. R. Meijer, S. D. Eastham, S. D. Eastham, S. D. Eastham, I. A. Waitz, S. R. H. Barrett, S. R. H. Barrett

“…The altitude estimation algorithm outputs probability distributions for the contrail top altitude in order to represent predictive uncertainty. …”
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Multimodal ultrasound deep learning to detect fibrosis in early chronic kidney disease by Xiachuan Qin, Xiaoling Liu, Linlin Xia, Qi Luo, Chaoxue Zhang

“…The AUC of the multimodal US DL model was significantly better than that of the single-mode DL and clinical models. The DL algorithm developed using multimodal US images can effectively predict early fibrosis in patients with CKD with significantly greater accuracy than single-mode DL or clinical models.…”
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Classifying detrital zircon U-Pb age distributions using automated machine learning by Jack W. Fekete, Glenn R. Sharman, Xiao Huang

“…Applied to the North American Cordillera dataset, AutoML achieves an ∼0.91 F1 score when predicting between foreland and forearc basin tectonic settings and an ∼0.71 F1 score when predicting subbasins within these settings, outperforming both RF and R2. …”
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Chlorophyll-a in the Chesapeake Bay Estimated by Extra-Trees Machine Learning Modeling by Nikolay P. Nezlin, SeungHyun Son, Salem I. Salem, Michael E. Ondrusek

“…Our approach leverages the Extra-Trees (ET) algorithm, a tree-based ensemble method that offers predictive accuracy comparable to that of other ensemble models, while significantly improving computational efficiency. …”
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Smart estimation of protective antioxidant enzymes’ activity in savory (Satureja rechingeri L.) under drought stress and soil amendments by Amin Taheri-Garavand, Mojgan Beiranvandi, Abdolreza Ahmadi, Nikolaos Nikoloudakis

“…On the other hand, POX had a lower predictive correlation (R = 0.8737), indicating a lower capacity of the ANN system in forecasting this parameter. …”
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Comparative Analysis of Automated Machine Learning for Hyperparameter Optimization and Explainable Artificial Intelligence Models by Muhammad Salman Khan, Tianbo Peng, Hanzlah Akhlaq, Muhammad Adeel Khan

“…The study focuses on predicting the ultimate moment capacity of Ultra-High-Performance Concrete (UHPC) beams and U-shaped girders. …”
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The BRCA1 variant p.Ser36Tyr abrogates BRCA1 protein function and potentially confers a moderate risk of breast cancer. by Charita M Christou, Andreas Hadjisavvas, Maria Kyratzi, Christina Flouri, Ioanna Neophytou, Violetta Anastasiadou, Maria A Loizidou, Kyriacos Kyriacou

“…PolyPhen algorithm predicted that the BRCA1 p.Ser36Tyr VUS identified in the Cypriot population was damaging, whereas Align-GVGD predicted that it was possibly of no significance. …”
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