Genetic Pattern Recognition using Intelligent Techniques by Basil Thanoon, Omar Qasim

“…Some comparisons have been made between particularly Artificial Neural Network, Fuzzy Logic and Genetic Algorithms for discovering the powerful and the week ones in particle way. …”
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Recovering Pulsar Periodicity from Time-of-arrival Data by Finding the Shortest Vector in a Lattice by Dotan Gazith, Aaron B. Pearlman, Barak Zackay

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Search for gamma-ray spectral lines from dark-matter annihilation with the DAMPE satellite by Frieden Jennifer Maria

“…In this contribution, the search for spectral lines in the gamma-ray spectrum, using eight years of data collected with the space-borne Dark Matter Particle Explorer is presented. To improve the event selection, two machine-learning algorithms were developed and proved to outperform all the standard methods. …”
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Application of Energy Dispersive X-ray Fluorescence Spectroscopy in Analysis of Heavy Metals in Soil: A Review by Aosong JIANG, Longhua WU, Zhu LI

“…Therefore, the current mainstream focus is on combining the advantages of different algorithms for the preprocessing analysis of ED-XRF spectroscopy and the establishment of quantitative analysis models to improve the accuracy of ED-XRF detection. …”
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Performance of quantum approximate optimization with quantum error detection by Zichang He, David Amaro, Ruslan Shaydulin, Marco Pistoia

“…To the best of our knowledge, our results demonstrate the largest universal quantum computing algorithm protected by partially fault-tolerant quantum error detection on practical applications to date.…”
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An adaptive continuous threshold wavelet denoising method for LiDAR echo signal by Dezhi Zheng, Tianchi Qu, Chun Hu, Shijia Lu, Zhongxiang Li, Guanyu Yang, Xiaojun Yang

“…In this paper, a novel adaptive continuous threshold wavelet denoising algorithm is proposed to filter out the noise. The algorithm features an adaptive threshold and a continuous threshold function. …”
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Geographic origin discrimination and quantification of phenolic compounds and moisture in Artemisia argyi folium using NIRS and chemometrics by Lifei Hu, Yifan Wang, Xin Wu, Yuanyuan Shan, Fengxiao Zhu, Fan Zhang, Qiang Yang, Mingxing Liu

“…Multivariate statistical analysis (four methods) and six machine learning algorithms were employed for origin discrimination. …”
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Learning Quantum Processes with Quantum Statistical Queries by Chirag Wadhwa, Mina Doosti

“…Finally, we demonstrate the practical relevance of our access model by applying our learning algorithm to attack an authentication protocol using Classical-Readout Quantum Physically Unclonable Functions, partially addressing an important open question in quantum hardware security.…”
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Associations of VEGF-D levels with clinical manifestations in lymphangioleiomyomatosis: a cross-sectional analysis of 631 cases by Luning Yang, Hanghang Wang, Chongsheng Cheng, Miaoyan Zhang, Danjing Hu, Yani Wang, Tengyue Zhang, Xiaoxin Zhang, Song Liu, Wenshuai Xu, Junya Liu, Jinrong Dai, Shuzhen Meng, Yanli Yang, Shao-Ting Wang, Xinlun Tian, Kai-Feng Xu

“…VEGF-D is a valuable biomarker in evaluation of LAM and improve the efficiency of diagnostic algorithm.…”
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Peptide receptor radionuclide therapy for ectopic Cushing’s syndrome caused by metastatic neuroendocrine neoplasms by Emma Boehm, Terry Hung, Tim Akhurst, Ramin Alipour, Cherie Chiang, Rodney J Hicks, Michael S Hofman, Aravind S Ravi Kumar, Nirupa Sachithanandan, Javad Saghebi, Michael Michael, Grace Kong

“…Conclusion: PRRT can be effective for ECS caused by metastatic SSTR-positive GEPNEN and should be considered in its treatment algorithm.…”
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Context-Aware Deep Learning Model for Yield Prediction in Potato Using Time-Series UAS Multispectral Data by Suraj A. Yadav, Xin Zhang, Nuwan K. Wijewardane, Max Feldman, Ruijun Qin, Yanbo Huang, Sathishkumar Samiappan, Wyatt Young, Francisco G. Tapia

“…The proposed feature engineering and prediction model followed a two-fold approach: first, adoption of partial least squares regression (PLSR) algorithm to extract features relevant to yield, and second, a novel context-aware attention and residual connection convolution-bidirectional gated recurrent unit bidirectional long short-term memory-network (CAR Conv1D-BiGRU-BiLSTM-Net) to exploit time-series multifeatures information to predict final yield. …”
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High-throughput untargeted metabolomics reveals metabolites and metabolic pathways that differentiate two divergent pig breeds by S. Bovo, M. Bolner, G. Schiavo, G. Galimberti, F. Bertolini, S. Dall’Olio, A. Ribani, P. Zambonelli, M. Gallo, L. Fontanesi

“…The molecular data were analysed using a bioinformatics pipeline specifically designed for identifying differentially abundant metabolites between the two breeds in a robust and statistically significant manner, including the Boruta algorithm, which is a Random Forest wrapper, and sparse Partial Least Squares Discriminant Analysis (sPLS-DA) for feature selection. …”
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DEVELOPMENT OF PRACTICAL SKILLS IN FOREIGN STUDENTS DURING EDUCATION AT THE DEPARTMENT OF PROPEDEUTICS OF SURGICAL DENTISTRY by I.A. Kolisnyk, A.I. Pankevych, A.M. Hohol, V.M. Novikov, E.Yu. Rezvina, M.A. Korostashova

“…Unfortunately, teachers are only able to visualize and comment in detail on the performing of certain manipulations. However, even a partial solution of this component in the form of justification and demonstration of the algorithm creates a stable argument for further study of surgical stomatology, and achievement of the ultimate goals of training a dentist. …”
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Hyperspectral and LiDAR space-borne data for assessing mountain forest volume and biomass by Rodolfo Ceriani, Sebastian Brocco, Monica Pepe, Silvio Oggioni, Giorgio Vacchiano, Renzo Motta, Roberta Berretti, Davide Ascoli, Matteo Garbarino, Donato Morresi, Francesco Bassi, Francesco Fava

“…We compared EMIT with Sentinel-2 (S2) multispectral data as model inputs, with and without GEDI data integration, using five Machine Learning (ML) algorithms: Partial Least Squares Regression (PLSR), Boosted Regression Trees (BRT), Support Vector Machines (SVM), Artificial Neural Networks (ANN), and Gaussian Process Regression (GPR). …”
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Research on Gamma Image Reconstruction Method Based on Multi-distance System Matrix Superposition by WU Yuan1, 2, , XU Feng1, 2, , ZHOU Yicong1, 2, XIAO Yufeng1, 2, ZHENG Yulai3

“…In order to enable the gamma camera to accurately locate multiple radioactive sources in the unknown radiation field at the same time, this paper proposed a multi-distance system matrix superposition gamma image reconstruction algorithm based on the maximum likelihood expectation maximization (MLEM) algorithm. …”
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Maternal antibody and the maintenance of a lyssavirus in populations of seasonally breeding African bats. by David T S Hayman, Angela D Luis, Olivier Restif, Kate S Baker, Anthony R Fooks, Clint Leach, Daniel L Horton, Richard Suu-Ire, Andrew A Cunningham, James L N Wood, Colleen T Webb

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Nitrous oxide prediction through machine learning and field-based experimentation: A novel strategy for data-driven insights by Muhammad Hassan, Khabat Khosravi, Travis J. Esau, Gurjit S. Randhawa, Aitazaz A. Farooque, Seyyed Ebrahim Hashemi Garmdareh, Yulin Hu, Nauman Yaqoob, Asad T. Jappa

“…Feature selection and optimization of input scenarios were achieved using a combination of particle swarm optimization (PSO) and manual methods. …”
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The role of intracellular signaling in the stripe formation in engineered Escherichia coli populations. by Xiaoru Xue, Chuan Xue, Min Tang

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PSO-Based Support Vector Machine with Cuckoo Search Technique for Clinical Disease Diagnoses by Xiaoyong Liu, Hui Fu

“…Therefore, we can conclude that our proposed method is very efficient compared to the previously reported algorithms.…”
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Asymmetries of thermal processes in open quantum systems by Álvaro Tejero, Rafael Sánchez, Laiachi El Kaoutit, Daniel Manzano, Antonio Lasanta

“…Relaxation to thermal equilibrium is the most important dissipative process, being a key concept for the design of heat engines and refrigerators, contributing to the study of foundational questions of thermodynamics, and being relevant for quantum computing through the process of algorithmic cooling. Despite their importance, the dynamics of these processes are far from being understood. …”
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