Blasting Vibration Control Using an Improved Artificial Neural Network in the Ashele Copper Mine by Shida Xu, Tianxiao Chen, Jiaqi Liu, Chenrui Zhang, Zhiyang Chen

“…In this paper, a genetic algorithm (GA) and an artificial neural network (ANN) algorithm were jointly used to construct a neural network model with a 4-5-1 topology to predict the PPV. …”
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Impact of Public Space in Primary and Secondary Schools Based on Natural Visibility Ratio by Feng Liu, Hao Zhou, Jiangtao Xie, Yue Tang, Shuyu Liu

“…In recent years, the safety of primary and secondary schools has garnered considerable attention from policymakers and architects, necessitating rational design methods to develop effective strategies that optimize the campus environment. This study utilizes algorithmic simulations, spatial analysis, and statistical methods to examine the relationships between the layouts of buildings, public space morphology, and campus safety. …”
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Efficient structure learning of gene regulatory networks with Bayesian active learning by Dániel Sándor, Péter Antal

“…We evaluate scalable structure learning algorithms within an active learning framework to optimize intervention selection. …”
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Ultra-High Spatial Resolution Clinical Positron Emission Tomography (PET) Systems by Myungheon Chin, Muhammad Nasir Ullah, Derek Innes, Craig S. Levin

“…A key strategy involves organ-specific, or loco-regional, scanner configurations that optimize photon detection efficiency (PDE) while balancing the trade-off between spatial resolution and image signal-to-noise ratio (SNR). …”
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Trade-off between gradient measurement efficiency and expressivity in deep quantum neural networks by Koki Chinzei, Shinichiro Yamano, Quoc Hoan Tran, Yasuhiro Endo, Hirotaka Oshima

“…Abstract Quantum neural networks (QNNs) require an efficient training algorithm to achieve practical quantum advantages. …”
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Data-Driven Pavement Performance: Machine Learning-Based Predictive Models by Mohammad Fahad, Nurullah Bektas

“…This study utilizes a range of machine learning algorithms, including linear regression, decision tree, random forest, gradient boosting, K-nearest neighbour, Support Vector Regression, LightGBM and CatBoost, to analyse their effectiveness in predicting pavement performance. …”
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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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Complex Neutrosophic Approach for Uncertainty Management in Employment Competence for Higher Vocational College Students by Shuo Du, Lijuan Zhao

“…The proof-of-concept analysis highlighted the best-ranked alternative while offering intuitions about the sensitivity of the decision process. …”
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A Simulation Based Metaheuristics for Capacitated Vehicle Routing Problem by Tamara Latifah Jasmine, Heru Purboyo Hidayat Putro, Niken Prilandita, Gatot Yudoko

“…The methodology utilizes a simheuristics approach, integrating a Genetic Algorithm (GA) to determine optimal routing solutions, while employing Discrete Event Simulation (DES) to incorporate key economic, environmental, and social variables. …”
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Lightweight YOLOv8s-Based Strawberry Plug Seedling Grading Detection and Localization via Channel Pruning by CHEN Junlin, ZHAO Peng, CAO Xianlin, NING Jifeng, YANG Shuqin

“…Furthermore, a two-stage seedling-hole matching algorithm was introduced based on the pruned YOLOv8s model. …”
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Genotyping Identification of Maize Based on Three-Dimensional Structural Phenotyping and Gaussian Fuzzy Clustering by Bo Xu, Chunjiang Zhao, Guijun Yang, Yuan Zhang, Changbin Liu, Haikuan Feng, Xiaodong Yang, Hao Yang

“…The research results showed that the Gaussian Fuzzy Clustering algorithm was the optimal choice for clustering maize genotypes. …”
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Multi-Feature Long Short-Term Memory Facial Recognition for Real-Time Automated Drowsiness Observation of Automobile Drivers with Raspberry Pi 4 by Michael Julius R. Moredo, James Dion S. Celino, Joseph Bryan G. Ibarra

“…The model was trained on the NTHU-DDD dataset and optimized using long short-term memory (LSTM) deep learning algorithms implemented using TensorFlow version 2.14.0. …”
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HouseGanDi: A Hybrid Approach to Strike a Balance of Sampling Time and Diversity in Floorplan Generation by Azmeraw Bekele Yenew, Beakal Gizachew Assefa, Elefelious Getachew Belay

“…To address these issues, various techniques such as regualrization techniques, architectural modifications, and optimization algorithms, have been employed. However, existing techniques still struggle to balance both sampling time and diversity simultaneously. …”
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Precise application of water and fertilizer to crops: challenges and opportunities by Yingying Xing, Xiukang Wang

“…Precision water and fertilizer application technologies have emerged as crucial innovations in sustainable agriculture, addressing the pressing need to enhance crop yield and quality while optimizing resource use and minimizing environmental impacts. …”
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Fraud Detection in Privacy Preserving Health Insurance System Using Blockchain Technology by Md. Mazharul Islam, Mubasshir Ahmed, Rajesh Palit, Mohammad Shahriar Rahman, Salekul Islam

“…Privacy is preserved using cryptographic techniques such as secure hashing and anonymous credentials, which ensure that sensitive patient information remains confidential throughout the claim process. Smart contract algorithms are utilized in two scenarios: patient‐submitted claims and healthcare provider‐submitted claims, ensuring accurate processing and validation while detecting fraudulent activities such as duplicate claims, inflated medical bills, billing for unprovided services, falsifying patient records, and submitting claims for nonexistent treatments. …”
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A novel Hadamard matrix based hybrid compressive sensing technique for enhancing energy efficiency and network longevity by Balamurali S, Kathirvelu M, SatheeshKumar Palanisamy, Tagrid Abdullah N. Alshalali

“…Such issues complicating protocol design and reducing network efficiency. While various clustering protocols exist, a critical gap still remains in effectively balancing these limitations, to optimize energy consumption, memory efficiency, data accuracy, and network longevity. …”
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Leveraging machine learning techniques to analyze nutritional content in processed foods by K. A. Muthukumar, Soumya Gupta, Doli Saikia

“…The SVR model was optimized to identify the best-fitting hyperplane in high-dimensional space, while the RF model utilized GridSearchCV for hyperparameter tuning and performed a “Feature Importance Analysis” to identify key factors influencing the outcomes. …”
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YOLORM: An Advanced Key Point Detection Method for Accurate and Efficient Rotameter Reading in Low Flow Environments by Huang Yong, Xia Xing, Xiao Shengwang

“…Moreover, YOLORM exhibited significant reductions in parameter count and computational cost while maintaining or enhancing detection performance relative to state-of-the-art algorithms. …”
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DRACO: Decentralized Asynchronous Federated Learning Over Row-Stochastic Wireless Networks by Eunjeong Jeong, Marios Kountouris

“…Through a thorough convergence analysis, we show that DRACO achieves high performance in decentralized optimization while maintaining low variance across users even without predefined scheduling policies. …”
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Distance Estimation with a Stereo Camera and Accuracy Determination by Arnold Zaremba, Szymon Nitkiewicz

“…These results provide valuable information on the capabilities and limitations of the measurement system used, while pointing out directions for its further optimization.…”
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