A Novel Voronoi-Driven Optimization Approach for Point-Based Sensor Network Deployment by Saeid Doodman, Mir-Abolfazl Mostafavi, Raja Sengupta, Ali Afghantoloee

“…Both algorithms performed significantly better with Kriging and TPS than with IDW.…”
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OS-PSO: A Modified Ratio of Exponentially Weighted Averages-Based Optical and SAR Image Registration by Hui Zhang, Yu Song, Jingfang Hu, Yansheng Li, Yang Li, Guowei Gao

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Application of a geostatistical algorithm for correcting well logging data when modelling complex hydrocarbon deposits at the stage of additional field exploration by V. L. Shuster, O. V. Tjukavkina, I. S. Permyakova, I. L. Kapitonova

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Understanding Clinician Knowledge About Race Adjustment in the Vaginal Birth After Cesarean Calculator by Julia Cron, Amelia A. Shapiro, Laura Carasimu, Julia Iyasere, Johanna M. Schisler, Szilvia Nagy, Sandra Angus, Anna Burgansky, Ashlesha K. Dayal, Tracy Bohn Hemmerdinger, Denise Howard, Corrina Oxford-Horrey, Donald C. Phillibert, Jean-Ju Sheen, Dena Goffman

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Damage Detection for Offshore Wind Turbines Subjected to Non-Stationary Ambient Excitations: A Noise-Robust Algorithm Using Partial Measurements by Ning Yang, Peng Huang, Hongning Ye, Wuhua Zeng, Yusen Liu, Juhuan Zheng, En Lin

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Enhanced Unmanned Surface Vehicle Path Planning Based on the Pair Barracuda Swarm Optimization Algorithm: Implementation and Performance in Thousand Island Lake by Binghua Shi, Zeyu Liu, Zhou He, Chen Wang, Jia Guo

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Optimal parameter extraction of equivalent circuits for single- and three- phase Power transformers based on arctic puffin algorithm accomplished with experimental verification by Amlak Abaza, Ragab A. El-Sehiemy, Mohamed Assaad Hamida, Raphael Chenouard, Ahmed Bayomyi

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Methodology for Evaluating the Performance of a New Pulse Oximeter Model and Pulse Oximetry Algorithm in Neonates in a Clinical Trial (Exploratory Study) by T. S. Adylov, E. V. Shestak, V. Yu. Starkov

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Development of a grape-harvesting robot using a multi-step detection method based on AI and a position-estimation algorithm by Weiguo Wang, Liangliang Yang, Noboru Noguchi

“…The insights and methodologies elucidated in this study can serve as valuable references for researchers delving into the realms of crop identification and harvesting.…”
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Ghostly Encounters on Google by Samuel Collins

“…In so doing, spirit photography anticipates the challenges digitization, manipulation and algorithmically generated images raise to the indexical truth-value of the image. …”
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A Framework for Generating S-Box Circuits with Boyer–Peralta Algorithm-Based Heuristics, and Its Applications to AES, SNOW3G, and Saturnin by Yongjin Jeon, Seungjun Baek, Giyoon Kim, Jongsung Kim

“…Many optimization strategies have been developed for the linear layer, led by the Boyer–Peralta (BP) algorithm. The Advanced Encryption Standard (AES) has been a focus of extensive research in this area. …”
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Predicting Surface Roughness and Grinding Forces in UNS S34700 Steel Grinding: A Machine Learning and Genetic Algorithm Approach to Coolant Effects by Mohsen Dehghanpour Abyaneh, Parviz Narimani, Mohammad Sadegh Javadi, Marzieh Golabchi, Samareh Attarsharghi, Mohammadjafar Hadad

“…In today’s tech world of digitalization, engineers are leveraging tools such as artificial intelligence for analyzing data in order to enhance their capability in evaluating product quality effectively. This research study adds value by applying algorithms and various machine learning techniques—such as support vector regression, Gaussian process regression, and artificial neural networks—on a dataset related to the grinding process of UNS S34700 steel. …”
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Walking detection for Parkinson’s disease patients and healthy control subjects measured with a smartphone accelerometer using mean amplitude deviation algorithm by Milla Juutinen, Jari Ruokolainen, Juha Puustinen, Anu Holm, Mark van Gils, Antti Vehkaoja

“…The sensitivity of the algorithm in a controlled measurement setting was 100% and 98.7% for healthy adults and a combined dataset of Parkinson’s disease patients and control subjects, respectively. …”
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A Practical Method for Red-Edge Band Reconstruction for Landsat Image by Synergizing Sentinel-2 Data with Machine Learning Regression Algorithms by Yuan Zhang, Zhekui Fan, Wenjia Yan, Chentian Ge, Huasheng Sun

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Application of Real-Time Palm Imaging with Nelder–Mead Particle Swarm Optimization/Regression Algorithms for Non-Contact Blood Pressure Detection by Te-Jen Su, Ya-Chung Hung, Wei-Hong Lin, Wen-Rong Yang, Qian-Yi Zhuang, Yan-Xiang Fei, Shih-Ming Wang

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Redefining Trauma Triage for Elderly Adults: Development of Age-Specific Guidelines for Improved Patient Outcomes Based on a Machine-Learning Algorithm by Ji Yeon Lim, Yongho Jee, Seong Gyu Choi, Yoon Hee Choi, Sam S. Torbati, Carl T. Berdahl, Sun Hwa Lee

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Extracting Knowledge From Scientific Texts on Patient-Derived Cancer Models Using Large Language Models: Algorithm Development and Validation Study by Jiarui Yao, Zinaida Perova, Tushar Mandloi, Elizabeth Lewis, Helen Parkinson, Guergana Savova

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A study of government regulation’s strategy for solving the algorithmic black-box puzzle of digital platforms: a complex network-based perspective by Gehui Zhu, Mingliang Tang, Xiao Jian, Tong Mu

“…In addition, small-world models can be used to assess the robustness of regulatory measures in different scenarios, and to study the stability and information flow capability of the network in the face of node failure or attacks, reflecting the interaction between users and platforms. The research results and relevant discussion are as follows: First, the simulation results of government regulatory intensity indicate the government’s regulatory strength for the algorithmic black-box problem needs to be kept at an appropriate standard. …”
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Dholes Hunting—A Multi-Local Search Algorithm Using Gradient Approximation and Its Application for Blockchain Consensus Problem by Binh Minh Nguyen, Thieu Nguyen, Quoc-Hien Vu, Tran Huy Hung, Tran Hoang Hai, Huynh Thi Thanh Binh, Van-Dang Tran

“…We compare the achieved results with several previous research from various well-known algorithms. The comparisons demonstrate that DhoH is better than other meta-heuristic algorithms in most cases and determines high-quality solutions with fewer control parameters. …”
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An Empirical Model-Based Algorithm for Removing Motion-Caused Artifacts in Motor Imagery EEG Data for Classification Using an Optimized CNN Model by Rajesh Kannan Megalingam, Kariparambil Sudheesh Sankardas, Sakthiprasad Kuttankulangara Manoharan

“…In this research study, we propose an empirical error model-based artifact removal approach for the cross-subject classification of motor imagery (MI) EEG data using a modified CNN-based deep learning algorithm, designed to assist wheelchair users with severe mobility issues. …”
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