Demonstration of Emulator-Based Bayesian Calibration of Safety Analysis Codes: Theory and Formulation by Joseph P. Yurko, Jacopo Buongiorno, Robert Youngblood

“…The key innovation has come from development of code surrogate model (or code emulator) construction and prediction algorithms. Use of a fast emulator makes the calibration processes used here with Markov Chain Monte Carlo (MCMC) sampling feasible. …”
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Enhancing Driving Safety and Environmental Consciousness through Automated Road Sign Recognition Using Convolutional Neural Networks by M. H. F. Md Fauadi, M. F. H. Mohd Zan, M. A. M Ali, L. Abdullah, S. N. Yaakop and A. Z. M. Noor

“…CNNs, as deep learning algorithms, possess the ability to process and classify visual data, making them well-suited for image-based tasks such as road sign recognition. …”
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Convergence of nanotechnology and artificial intelligence in the fight against liver cancer: a comprehensive review by Manjusha Bhange, Darshan Telange

“…We highlight how AI-powered algorithms can optimize nanocarrier design, facilitate real-time monitoring of treatment efficacy, and enhance clinical decision-making. …”
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An Improved Feature Selection Based on Effective Range for Classification by Jianzhong Wang, Shuang Zhou, Yugen Yi, Jun Kong

“…Therefore, IFSER outperforms the original ERGS and some other state-of-the-art algorithms. Experiments on several well-known databases are performed to demonstrate the effectiveness of the proposed method.…”
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Application of an Improved TF-IDF Method in Literary Text Classification by Lin Xiang

“…In the realm of text classification, the TF-IDF algorithm is a widely used classification algorithm. …”
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Custom YOLO Object Detection Model for COVID-19 Diagnosis by Noor Najah Ali, Aseel Hameed, Asanka G. Perera, Ali Al_Naji

“…Clinical staff can benefit from Computer Aided Diagnostics (CAD) systems that combine deep learning algorithms and image processing technologies as diagnostic tools for COVID-19. …”
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Combining non-Monotone trust rregion method with a new adaptive radius for unconstrained optimization problems by Seyed Hamzeh Mirzaei, Ali Ashrafi

“…In addition, it significantly reduces computational costs compared to traditional algorithms. On the other hand, the new adaptive radius avoids the ineffectiveness of the trust region close to the solution.…”
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Toward secure and accountable data transmission in Narrow Band Internet of Things based on blockchain by Hanshu Hong, Bing Hu, Zhixin Sun

“…We describe the interaction processes between each layer in detail and construct the algorithms which are used to conduct data authentication and blockchain generation. …”
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Classification in Networked Data with Heterophily by Zhenwen Wang, Fengjing Yin, Wentang Tan, Weidong Xiao

“…In empirical study, we apply the proposed algorithm to the real-world datasets, compared with some other algorithms. …”
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Rolling Bearing Diagnosis Based on Adaptive Probabilistic PCA and the Enhanced Morphological Filter by Yuanqing Luo, Changzheng Chen, Siyu Zhao, Xiangxi Kong, Zhong Wang

“…To solve this problem, a parameter adaptive PPCA method based on grasshopper optimization algorithm (GOA) is proposed. Finally, combining the advantages of the above algorithms, a comprehensive rolling bearing fault diagnosis method named APPCA-EMDF is proposed in this paper. …”
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Latency Improvement Strategies for Reliability-Aware Scheduling in Industrial Wireless Sensor Networks by Felix Dobslaw, Tingting Zhang, Mikael Gidlund

“…Moreover, SchedEx executes orders of magnitude faster than recent algorithms in the literature while producing schedules with competitive latencies. …”
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Anomaly Detection in IoMT Environment Based on Machine Learning: An Overview by Peyman Vafadoost Sabzevar, Hamidreza Rokhsati, Alireza Chamansara, Ahmad Hajipour

“…In this article, the isolation forest algorithm was used for training on 80% of the dataset related to the data of the Internet of Medical Things network, and then this model was tested and evaluated on the remaining 20%. …”
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A Bionic Social Learning Strategy Pigeon-Inspired Optimization for Multi-Unmanned Aerial Vehicle Cooperative Path Planning by Yankai Shen, Xinan Liu, Xiao Ma, Hong Du, Long Xin

“…The paper also proves the algorithm’s convergence and provides complexity analysis. …”
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Risk Assessment of Biological Asset Mortgage Loans of China’s New Agricultural Business Entities by Shuzhen Zhu, Yutao Chen, Wenwen Wang

“…Based on 1249 production and operation data samples of new agricultural entities in Zhejiang, Henan, and Shandong provinces, this study constructs an XGBoost model for empirical analysis and compares it with logical regression, support vector machine, and random forest algorithms to obtain the optimal model and feature importance value. …”
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Deep Learning Methods for Arabic Autoencoder Speech Recognition System for Electro-Larynx Device by Zinah J. Mohammed Ameen, Abdulkareem Abdulrahman Kadhim

“…Artificial intelligence algorithms have shown promising capabilities for Arabic speech recognition. …”
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Face presentation attack detection. A comprehensive evaluation of the generalisation problem by Artur Costa‐Pazo, Daniel Pérez‐Cabo, David Jiménez‐Cabello, José Luis Alba‐Castro, Esteban Vazquez‐Fernandez

“…Besides, a new fine‐grained categorisation of presentation attacks and instruments is provided, enabling higher flexibility in assessing the generalisation of different algorithms under a common framework. As a result, GRAD‐GPAD v2, a comprehensive and modular framework is presented to evaluate the performance of face‐PAD approaches in realistic settings, enabling accountability and fair comparison of most face‐PAD approaches in the literature.…”
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Robust Face Detection and Identification under Occlusion using MTCNN and RESNET50 by Eiman Wahab, Wajeeha Shafique, Habiba Amir, Sameena Javed, Muhammad Marouf

“…We used the face detector algorithm called Multi-Task Cascaded Convolutional Neural Network (MTCNN) for face detection with 99.8% accuracy. …”
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Cognitive Driven Multilayer Self-Paced Learning with Misclassified Samples by Qi Zhu, Ning Yuan, Donghai Guan

“…In recent years, self-paced learning (SPL) has attracted much attention due to its improvement to nonconvex optimization based machine learning algorithms. As a methodology introduced from human learning, SPL dynamically evaluates the learning difficulty of each sample and provides the weighted learning model against the negative effects from hard-learning samples. …”
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Intelligent Topical Sentiment Analysis for the Classification of E-Learners and Their Topics of Interest by M. Ravichandran, G. Kulanthaivel, T. Chellatamilan

“…In this paper, rather than using the opinion polarity of each message relevant to the topic, authors focus on sentence level opinion classification upon using the unsupervised algorithm named bigram item response theory (BIRT). …”
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Computing four-point functions with integrability, bootstrap and parity symmetry by Andrea Cavaglià, Nikolay Gromov, Michelangelo Preti

“…As this could be a clear obstacle in restoring higher point functions, we studied the problem of bounding directly a 4-point function at generic cross ratio, showing how to adapt for this purpose the numerical bootstrap algorithms based on semidefinite programming. Another tool we are using to further narrow the bounds is a parity symmetry descending from the N $$ \mathcal{N} $$ =4 SYM theory, which allowed us to reduce the number of parameters. …”
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