A joint three-plane physics-constrained deep learning based polynomial fitting approach for MR electrical properties tomography by Kyu-Jin Jung, Thierry G. Meerbothe, Chuanjiang Cui, Mina Park, Cornelis A.T. van den Berg, Stefano Mandija, Dong-Hyun Kim

“…To estimate tissue electrical properties, various reconstruction algorithms have been proposed. However, physics-based reconstructions are prone to various artifacts such as noise amplification and boundary artifact. …”
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Machine Learning Using Approximate Computing by Padmanabhan Balasubramanian, Syed Mohammed Mosayeeb Al Hady Zaheen, Douglas L. Maskell

“…The design metrics estimated show that NAA achieves a 37% reduction in delay, a 22% reduction in area, and a 31% reduction in power compared to the accurate adder. …”
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Machine learning-based forecasting of ground surface settlement induced by metro shield tunneling construction by Qiankun Wang, Chuxiong Shen, Chao Tang, Zeng Guo, Fangqi Wu, Wenyi Yang

“…The maximum relative error of the prediction based on the data preprocessing method and PSO-BP algorithm is 0.46%, demonstrating a good fitting effect. …”
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Solutions to face and combat disinformation: proposals in scientific literature from the web of science by Jônatas Edison da Silva, Enrique Muriel-Torrado

“…(a) Science and scientific community; (b) States and governments; (c) Media and communications; (d) Platforms and algorithms; (e) Users and education; and (f) Others. …”
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Basics of the semantic portal of nuclear knowledge BelNET functioning by S. N. Sytovа, V. V. Haurylavets, A. P. Dunets, A. N. Kavalenka, S. V. Charapitsa

“…The described basic principles of organization and algorithms based on semantic technologies, which underlie the functioning of the content management system of the scientific and educational portal eLab-Science and the Belarusian nuclear knowledge portal BelNET, created on its basis, make it possible to effectively implement the placement of content records in the portal taxonomy, as well as automatically generate a set of keywords for the resource being created…”
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3D-CNN with Multi-Scale Fusion for Tree Crown Segmentation and Species Classification by Jiayao Wang, Zhen Zhen, Yuting Zhao, Ye Ma, Yinghui Zhao

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Giant pseudoangiomatous stromal hyperplasia of breast: Management challenge of gigantomastia with ptosis by Uma Krishnaswamy, K Balachandar, Thulasilingam Kathirazhagan

“…A pragmatic and individualized approach is the solution in the absence of reliable algorithms for management. This instance of a giant PASH tumor producing gigantomastia with severe ptosis is a case to point. …”
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Electricity nowcasting and forecasting efficiency in blockchain-integrated energy trading platforms by Ameni Boumaiza

“…Experimental results demonstrate a substantial reduction in electricity costs for consumers by an average of 25% and a decrease in carbon dioxide (CO2) emissions by 40 tons annually. …”
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Pengembangan Auto-AI Model Generatif Analisis Kompleksitas Waktu Algoritma Untuk Data Multi-Sensor IoT Pada Node-RED Menggunakan Extreme Learning Machine by Imam Cholissodin, Dahnial Syauqy, Dwi Ady Firmanda, Ibrahim Aji, Edy Rahman, Syazwandy Harahap, Fernando Septino

“…Abstract Initially, algorithms were only used for solving simple mathematical equations such as algebra, arithmetic, probability, and others that were mostly carried out manually and required quite a lot of time and effort as in the case of calculating the value of the time complexity of the algorithm with the formula model of T(n), both for non-recursive and recursive algorithms. …”
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Cross-Technology Interference-Aware Rate Adaptation in Time-Triggered Wireless Local Area Networks by Hanjin Kim, Young-Jin Kim, Won-Tae Kim

“…The rate selection algorithms predict CTI occurrence times and adjust the transmission rate accordingly, enhancing the performance of existing explicit and implicit interference mitigation methods. …”
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Creation of a collection of different biological sample types from elderly patients to study the relationship of clinical, systemic, tissue and cellular biomarkers of accumulation... by A. G. Sorokina, Ya. A. Orlova, O. A. Grigorieva, E. S. Novoseletskaya, N. A. Basalova, N. A. Alexandrushkina, M. A. Vigovsky, K. I. Kirillova, A. V. Balatsky, L. M. Samokhodskaya, N. V. Danilova, U. D. Dyachkova, D. А. Fedotov, A. A. Akopyan, V. V. Kakotkin, D. A. Asratyan, Zh. A. Akopyan, A. Yu. Efimenko

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An introduction to causal discovery by Martin Huber

“…This survey provides an introduction to key concepts, algorithms, and applications of causal discovery from the perspectives of economics and social sciences. …”
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Region-wise landmarks-based feature extraction employing SIFT, SURF, and ORB feature descriptors to recognize Monozygotic twins from 2D/3D Facial Images [version 2; peer review: 2... by Srikanth Prabhu, Vinod Nayak, Aparna Jayakala, Krishna Prakasha K, Gangothri Sanil

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Parallel Implicit Runge-Kutta Methods for Stiff ODEs by Bashir Khalaf, Abdulhabib Murshid

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Surface water quality assessment for drinking and pollution source characterization: A water quality index, GIS approach, and performance evaluation utilizing machine learning anal... by Abhijeet Das

“…Basically, all approaches cumulatively predicted surface WQI with lower accuracy. Overall, the LOR, KNN, ANN, and SVM algorithms were all surpassed by the RF algorithm. …”
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Mitochondrial insights: key biomarkers and potential treatments for diabetic nephropathy and sarcopenia by Yi Wei Chen, Shan He, Yu Wang, Lian Ying Hu, Qin Kai Chen, Si Yi Liu

“…Utilizing four machine learning algorithms (LASSO, SVM, XGBoost, RF), we pinpointed three mitochondrial hub genes. …”
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Determination of Sequential Well Placements Using a Multi-Modal Convolutional Neural Network Integrated with Evolutionary Optimization by Seoyoon Kwon, Minsoo Ji, Min Kim, Juliana Y. Leung, Baehyun Min

“…This complex multi-million-dollar problem involves optimizing multiple parameters using computationally intensive reservoir simulations, often employing advanced algorithms such as optimization algorithms and machine/deep learning techniques to find near-optimal solutions efficiently while accounting for uncertainties and risks. …”
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Research on the Performance Optimization of Turbulent Self-Noise Suppression and Sound Transmission of Acoustic Windows Made from Functionally Graded Material by Bing LI, Fu-Lin ZHOU, Jun FAN, Bin WANG, Liwen TAN

“…The STL, the turbulent self-noise reduction or a weighting function of the STL and turbulent self-noise reduction of FGM acoustic windows is chosen as the optimization objective. …”
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Flexural strengthening of corroded steel beams with CFRP by using the end anchorage: Experimental, numerical, and machine learning methods by Amin Shabani Ammari, Younes Nouri, Habib Ghasemi Jouneghani, Seyed Amin Hosseini, Arash Rayegani, Mehrdad Ebrahimi, Pooria Heydari

“…The ML prediction showed that the CatBoost algorithm had the highest accuracy, with an R2 score of 0.954. …”
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Supervised Learning of Depth Estimation From Imperfect Rectified Stereo Laparoscopic Images of Liver Surface by Chongan Zhang, Ziyi Jin, Xiaoyue Liu, Yuelong Liang, Xiao Liang, Peng Wang, Xiujun Cai, Xuesong Ye

“…A dataset is created for laparoscopic liver depth images, and the ACVNet++ algorithm is tested on this dataset. The experiments demonstrate that, compared to non-learning algorithms based on white light image features, the ACVNet++ algorithm reduces the average absolute error (MAE) and endpoint error (EPE) of depth prediction under white light conditions by 51% and 44%, reaching 2.46 mm and 2.56 pixels, respectively. …”
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