Rock blasting evaluation - image recognition method based on deep learning by Haibao YI, Aixiang Wu, Xiliang Zhang

“…And a segmented function R-R block size distribution correction model was proposed, which can better characterize the characteristics of blasting block size distribution and serves as a guide for accurate prediction of block size distribution. Overall, image recognition technology can significantly improve the efficiency and accuracy of blasting evaluation, solve many drawbacks of traditional manual analysis methods, and holds great application prospects in blasting quality evaluation.…”
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HIDS-RPL: A Hybrid Deep Learning-Based Intrusion Detection System for RPL in Internet of Medical Things Network by Abdelwahed Berguiga, Ahlem Harchay, Ayman Massaoudi

“…The suggested model, designated HIDS-RPL, results from the hybridization of the Convolutional Neural Network (CNN) for feature extraction and the Long Short Term Memory neural network (LSTM), typically employed for sequence data prediction. We evaluate the proposed algorithm to detect intrusions using the benchmark CIC-DDoS2019 dataset. …”
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Object Detection in High-Resolution UAV Aerial Remote Sensing Images of Blueberry Canopy Fruits by Yun Zhao, Yang Li, Xing Xu

“…Blueberries, as one of the more economically rewarding fruits in the fruit industry, play a significant role in fruit detection during their growing season, which is crucial for orchard farmers’ later harvesting and yield prediction. Due to the small size and dense growth of blueberry fruits, manual detection is both time-consuming and labor-intensive. …”
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An object-based and Lagrangian view on an intense hailstorm day in Switzerland as represented in COSMO-1E ensemble hindcast simulations by K. P. Brennan, M. Sprenger, A. Walser, M. Arpagaus, H. Wernli

“…To this end, we investigate ensemble hindcast simulations using the COSMO-1E numerical weather prediction model that includes the HAILCAST hail growth parameterization. …”
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Synergistic Matching and Influencing Factors of Grain Production and Cropland Net Primary Productivity in the Black Soil Region of Northeast China by Quanxi Wang, Jun Ren, Maomao Zhang, Hongjun Sui, Xiaodan Li

“…This study analyzed the spatial–temporal mismatch characteristics of grain production and cropland net primary productivity (CNPP) using the gravity center model, spatial autocorrelation analysis, and spatial mismatch index (SMI), and identified the spatial heterogeneity and prediction–response relationships of influencing factors based on a geographically and temporally weighted regression (GTWR) model and boosted regression tree (BRT) machine learning algorithm. …”
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Aerodynamic Optimization of Morphing Airfoil by PCA and Optimization-Guided Data Augmentation by Ao Guo, Jing Wang, Miao Zhang, Han Wang

“…A Multi-Island Genetic Algorithm (MIGA) efficiently explores the reduced design space, while iterative retraining of the surrogate model enhances prediction accuracy, particularly in high-performance regions. …”
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A combined improved dung beetle optimization and extreme learning machine framework for precise SOC estimation by Kaihua Yao, Xinyu Yan, Xiling Mao, Mengwei Li, Xiao Li, Ziyu Lian, Yuxiang Han

“…This effectively resolves the problems of inconsistent performance and instability arising from randomly initialized hidden layer weights and biases in ELM, resulting in enhanced prediction accuracy. The proposed IDBO-ELM method is validated in the context of five parameters, namely, different ambient temperatures, operating conditions, battery materials, initial SOC values, and running time. …”
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THE TASK OF MINIMAX ADAPTIVE MANAGEMENT OF INNOVATIVE PROCESSES AT AN ENTERPRISE WITH RISK ASSESSMENT by Vitalina Babenko, Elena Alisejko, Zoya Kochuyeva

“…The results demonstrated in the work can be used for economic and mathematical modelling and solving other tasks of optimizing processes of data prediction and management under the lack of information and under risks as well as for developing corresponding software and hardware complexes to support efficient managerial decisions in practice.…”
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Uncovering Antibiotic Resistance Genes in Marmara Sea Mucilage via Shotgun Metagenome Sequencing by Gizem Karış, Herdem Aslan, Mehmet Hora, Aycan Gundogdu

“…The DNA data was analyzed using a de novo approach with IDBA-UD assembler, BWA-mem2, and Prodigal gene prediction algorithm. For ARG profiling, gene clusters were aligned to the CARD (The Comprehensive Antibiotic Resistance Database) using BlastX. …”
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Multimodal Fusion Multi-Task Learning Network Based on Federated Averaging for SDB Severity Diagnosis by Songlu Lin, Renzheng Tang, Yuzhe Wang, Zhihong Wang

“…Accurate sleep staging and sleep-disordered breathing (SDB) severity prediction are critical for the early diagnosis and management of sleep disorders. …”
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Personalized machine learning models for noninvasive hypoglycemia detection in people with type 1 diabetes using a smartwatch: Insights into feature importance during waking and sl... by Yasmine M Mohamed, José Mancera, Andreas Brandenberg, Stefan Fischli, Michael M Havranek

“…Therefore, we explored the potential of a consumer-grade wearable for hypoglycemia prediction and investigated differing feature importance during waking and sleeping times. …”
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Smart indoor monitoring for disabled individuals using an ensemble of deep learning models in an IoT environment by Faisal S. Alsubaei, Abdulrahman A. Alshdadi, Mohammed Rizwanullah

“…Internet of Things (IoT) based health systems have an important part in medical assistance and help in enhancing data processing and its prediction. Communicating data or reports requires more time and energy, in addition to causing energy problems and greater latency. …”
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Analyzing the applicability of psychometric QoE modeling for projection-based point cloud video quality assessment by Sam Van Damme, Jeroen van der Hooft, Filip De Turck, Maria Torres Vega

“…Thus, real-time quality monitoring and prediction mechanisms are key to allow for fast countermeasures in case of QoE decrease. …”
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Comprehensive bioinformatics analysis uncover molecular pathways shared between osteoarthritis and atherosclerosis by Yingchao Jin, Hua Zhang

“…After identifying shared differentially expressed genes (DEGs) and hub genes, we performed multifaceted bioinformatics analyses, including functional annotation, co-expression analysis, TF-mRNA and ceRNA regulatory network construction, pharmacogenetic prediction, and receiver operator characteristic (ROC) curve assessment. …”
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ISEE: Industrial Internet of Things perception in solar cell detection based on edge computing by Meiya Dong, Jumin Zhao, Deng-ao Li, Biaokai Zhu, Sihai An, Zhaobin Liu

“…In this article, due to the three core pain points in traditional electroluminescence detection: low efficiency of offline identification, low accuracy and accuracy of data detection, and no online diagnosis and prediction, we carry out ISEE research based on edge computing unit. …”
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Integrating Experimental Analysis and Gradient Boosting for the Durability Assessment of Lime-Based Mortar in Acidic Environment by Ali Taheri, Nima Azimi, Daniel V. Oliveira, Joaquim Tinoco, Paulo B. Lourenço

“…In the modeling phase, the extreme gradient boosting (XGBoost) algorithm was deployed to predict the mechanical properties of the lime-based mortar by 1000, 3000, and 5000 h of exposure. …”
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Flow cytometry for screening and prioritisation of urine samples: a retrospective comparison with culture by Vicky Sender, John Kerr White, Ludvig Bolinder, Karin Amilon, Mirja Hägg, Karin Haij Bhattarai, Niklas K. Björkström, Baharak Saeedi

“…Receiver operating characteristic (ROC) curve analyses assessed method agreement across different patient subpopulations. Predictive values were calculated for the total population and the ten different subpopulations at different cut-offs. …”
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Electronic nose and machine learning for modern meat inspection by Ivan Shtepliuk, Guillem Domènech-Gil, Viktor Almqvist, Arja Helena Kautto, Ivar Vågsholm, Sofia Boqvist, Jens Eriksson, Donatella Puglisi

“…The model demonstrated robust predictive performance with a Kappa value of approximately 0.926, indicating near-perfect agreement between the predictions and actual classifications. …”
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Identification and functional analysis of energy metabolism and pyroptosis-related genes in diabetic nephropathy by Shan He, Jian Ye, Yu Wang, Lu yang Xie, Si Yi Liu, Qin kai Chen

“…PPI network analysis highlighted the central role of these genes within the relevant pathways. Predictive modeling demonstrated interactions between EMAPRDEGs, 69 miRNAs, and 117 TFs. …”
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Significance of Immune-Related Genes in the Diagnosis and Classification of Intervertebral Disc Degeneration by Bo Wu, Xinzhou Huang, Mu Zhang, Wei Chu

“…Then, we utilized a random forest (RF) model to screen six candidate IRGs to predict the risk of IDD. A nomogram was developed on the basis of six candidate IRGs, and DCA showed that patients could benefit from the nomogram. …”
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