Finite element-based nonlinear dynamic optimization of nanomechanical resonators by Zichao Li, Farbod Alijani, Ali Sarafraz, Minxing Xu, Richard A. Norte, Alejandro M. Aragón, Peter G. Steeneken

“…Here, we integrate an FE-based nonlinear ROM technique with a derivative-free optimization algorithm to enable the design of nonlinear mechanical resonators. …”
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A Group-Based Signal Timing Optimization Model Considering Safety for Signalized Intersections with Mixed Traffic Flows by Fen Wang, Keshuang Tang, Keping Li, Zhigang Liu, Lin Zhu

“…Then, the multiobjective optimization issue was formulated as a nonlinear program and solved by a Nondominated Sorting Genetic Algorithm. A numerical study was performed to demonstrate the applicability and performance of the proposed model. …”
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Age group classification based on optical measurement of brain pulsation using machine learning by Martti Ilvesmäki, Hany Ferdinando, Kai Noponen, Tapio Seppänen, Vesa Korhonen, Vesa Kiviniemi, Teemu Myllylä

“…Four feature sets were derived from log-normal parameters estimated by pulse decomposition algorithm. ML experiments utilized support vector machines and random forest learners, along with maximum relevance minimum redundancy and principal component analysis for feature selection. …”
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Large language models for causal hypothesis generation in science by Kai-Hendrik Cohrs, Emiliano Diaz, Vasileios Sitokonstantinou, Gherardo Varando, Gustau Camps-Valls

“…As an example, our hybrid (LLM + data) causal discovery algorithm illustrates ways for deeper integration. …”
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Predicting Earthquake Casualties and Emergency Supplies Needs Based on PCA-BO-SVM by Fuyu Wang, Huiying Xu, Huifen Ye, Yan Li, Yibo Wang

“…Subsequently, the optimal hyperparameters for the SVM model are obtained using the Bayesian Optimization algorithm. This approach results in the development of an earthquake casualty prediction model based on PCA-BO-SVM. …”
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Analysis of Techno–Economic and Social Impacts of Electric Vehicle Charging Ecosystem in the Distribution Network Integrated with Solar DG and DSTATCOM by Ramesh Bonela, Sriparna Roy Ghatak, Sarat Chandra Swain, Fernando Lopes, Sharmistha Nandi, Surajit Sannigrahi, Parimal Acharjee

“…The optimal locations and capacities of the EVCE, solar DG, and DSTATCOM are determined using an improved particle swarm optimization algorithm based on the success rate technique. The study aims to maximize the technical, financial, and social benefits while ensuring that all security constraints are met. …”
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Biological samples for examination: concepts, conditions, sampling tactics by M. H. Shcherbakovskyi, A. M. Protsenko, A. E. Volkova

“…The author proposes a general algorithm for the tactics of obtaining biological samples for examination at the stage of pre-trial investigation, which includes the preparatory, working and final stages.…”
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Modeling and simulation for toxicity assessment by Cristina Anton, Jian Deng, Yau Shu Wong, Yile Zhang, Weiping Zhang, Stephan Gabos, Dorothy Yu Huang, Can Jin

“…To efficiently estimate the model's parameters, we design an Expectation Maximization algorithm. The model is validated by showing that it accurately represents the information provided by the TCRCs recorded after the experiments. …”
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On the Effect of the Patient Table on Attenuation in Myocardial Perfusion Imaging SPECT by Tamino Huxohl, Gopesh Patel, Wolfgang Burchert

“…Methods Jaszczak phantom scans are acquired according to quality control and MPI procedures. An algorithm is developed to automatically remove the patient table from the CT for attenuation correction. …”
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A Real-Time Timetable Rescheduling Method for Metro System Energy Optimization under Dwell-Time Disturbances by Guang Yang, Junjie Wang, Feng Zhang, Shiwen Zhang, Cheng Gong

“…The real-time feature and self-adaptability of the method are attributed to the combinational use of Genetic Algorithm (GA) and Deep Neural Network (DNN). The decision system for proposing solutions, which contains multiple DNN cells with same structures, is trained by GA results. …”
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Combined Oriented Data Augmentation Method for Brain MRI Images by Ahmeed Suliman Farhan, Muhammad Khalid, Umar Manzoor

“…Both thresholds are adjustable, initially set by the user and automatically fine-tuned by the algorithm to control the number of images produced for each class, thus helping to address the data imbalance problem. …”
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XAI-Enhanced Machine Learning for Obesity Risk Classification: A Stacking Approach With LIME Explanations by Mohammad Azad, Md Faraz Kabir Khan, Sameh Abd El-Ghany

“…Our proposed model employs an ensemble approach, specifically a stacking algorithm, where the base estimators include the Light Gradient Boosting Machine (LGBM) classifier, the Logistic Regression (LR) classifier, and the Random Forest (RF) Classifier, and the Stochastic Gradient Descent (SGD) classifier is selected as the final estimator. …”
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A Simplified Method of Flexible Conductors Mechanic Calculation in Switchgears without Restrictions on the Number of Taps by Yu. V. Bladyko, E. G. Ponomarenko, P. I. Klimkovich

“…The most accurate methods of mechanical calculation of flexible conductors include methods based on the numerical solution of the equation of wires in the form of a flexible elastic thread. Such an algorithm is implemented in the author's computer program MR21. …”
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Optimization and modeling of sulfur removal from liquid fuel using carbon-based adsorbents through synergistic application of RSM and machine learning by Karim Maghfour Sarkarabad, Mohsen Shayanmehr, Ahad Ghaemi

“…We employed radial basis function (RBF) and multilayer perceptron (MLP) algorithms for ANN modeling. The optimal MLP configuration, utilizing the Levenberg–Marquardt (Trainlm) algorithm, consisted of three hidden layers with 20, 17, and 9 neurons, respectively, while the optimal RBF network contained 43 neurons. …”
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AI based predictive acceptability model for effective vaccine delivery in healthcare systems by Muhammad Shuaib Qureshi, Muhammad Bilal Qureshi, Urooj Iqrar, Ali Raza, Yazeed Yasin Ghadi, Nisreen Innab, Masoud Alajmi, Ayman Qahmash

“…A sample dataset containing 7150 data records with 31 demographic and socioeconomic attributes from PDHS (2017–2018) is used in this paper. Using the LightGBM algorithm, the proposed model constructed on the basis of different machine-learning procedures achieved 98% accuracy to accurately predict the acceptability of vaccines included in the immunization program. …”
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Crashworthiness Design and Multiobjective Optimization for Hexagon Honeycomb Structure with Functionally Graded Thickness by Ruixian Qin, Junxian Zhou, Bingzhi Chen

“…In addition, three surrogate models, including radial basis function (RBF), response surface method (RSM), and kriging (KRG), are compared in the accuracy of predicting SEA and PCF and capacity for optimization design of FGT honeycomb structure; the Nondominated Sorting Genetic Algorithm (NSGA-II) is applied to obtain the Pareto optimal solutions for the maximum thickness, minimum thickness, and thickness variation gradient exponent of a honeycomb wall. …”
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Automated Computer Vision System for Urine Color Detection by Ban Shamil Abdulwahed, Ali Al-Naji, Izzat Al-Rayahi, Ammar Yahya, Asanka G. Perera

“…The proposed system uses a web camera to capture an image in real-time, analyze it, and then classify the color of urine by using the random forest (RF) algorithm and show the result via the Graphical User Interface (GUI). …”
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Zero-TCE: Zero Reference Tri-Curve Enhancement for Low-Light Images by Chengkang Yu, Guangliang Han, Mengyang Pan, Xiaotian Wu, Anping Deng

“…We compare our proposed method against ten other advanced algorithms based on multiple datasets, including LOL, DICM, MEF, NPE, and ExDark, that encompass complex illumination variations. …”
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Fusion of multi-scale attention for aerial images small-target detection model based on PARE-YOLO by Huiying Zhang, Pan Xiao, Feifan Yao, Qinghua Zhang, Yifei Gong

“…Abstract In view of the complex environments and varying object scales in drone-captured imagery, a novel PARE-YOLO algorithm based on YOLOv8 for small object detection is proposed. …”
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Earthquake Disaster Rescue Model Based on Complex Adaptive System Theory by Fujiang Chen, Jingang Liu, Junying Chen

“…The experimental results show that the model used in this paper is better than the other two models in terms of algorithm convergence, rescue number, and overall score; in different scenarios, the relative survival probability of the model in this paper is 58.92%, 67.85%, and 77.46%, and the proportion of the wounded rescued is 66.31%, 76.45%, and 83.06%, which were higher than those of the other two models. …”
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