Intelligent Turning Tool Monitoring with Neural Network Adaptive Learning by Maohua Du, Peixin Wang, Junhua Wang, Zheng Cheng, Shensong Wang

“…., (a) through distinctively designed experimental technique with comprehensive consideration of cutting parameters and tool wear values as variables, (b) through bisensor fusion for simultaneous measurements of low and high frequency signals, (c) through multitheory fusion of wavelet decomposition and the Relief-F algorithm for performing dual feature extraction and feature dimension reduction to achieve more accurate state identification using neural network, and (d) through an innovative programming technique of MATLAB-nested labVIEW. …”
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Endoscopic ultrasonography-based intratumoral and peritumoral machine learning ultrasomics model for predicting the pathological grading of pancreatic neuroendocrine tumors by Shuangyang Mo, Cheng Huang, Yingwei Wang, Shanyu Qin

“…Subsequently, the dimensionality of these radiomics features was reduced using the least absolute shrinkage and selection operator (LASSO) algorithm. A machine learning algorithm, namely multilayer perception (MLP), was employed to construct prediction models using only the nonzero coefficient features and retained clinical features, respectively. …”
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Enhancing the Hybrid Microgrid Performance with Jellyfish Optimization for Efficient MPPT and THD Estimation by the Unscented Kalman Filter by Nivedita Singh, M. A. Ansari, Manoj Tripathy, Pratiksha Gupta, Ikbal Ali, Adel Saleh Rawea

“…The contribution of the jellyfish optimization (JF) algorithm lies in its ability to efficiently and effectively maximize power generation from the PV system, regardless of normal or partial shading conditions. …”
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Application of GA-BP Neural Network Optimized by Grey Verhulst Model around Settlement Prediction of Foundation Pit by C. Y. Liu, Y. Wang, X. M. Hu, Y. L. Han, X. P. Zhang, L. Z. Du

“…Due to the limitation in the prediction of the foundation pit settlement, this paper proposed a new methodology which takes advantage of the grey Verhulst model and a genetic algorithm. In the previous study, excavation times are often the only factor to predict the settlement, which is mainly because the correspondence between real-time excavation depth and the excavation time is hard to determine. …”
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Assessing machine learning for fair prediction of ADHD in school pupils using a retrospective cohort study of linked education and healthcare data by Johnny Downs, Robert Stewart, Alice Wickersham, Sumithra Velupillai, Lucile Ter-Minassian, Natalia Viani, Lauren Cross

“…Sociodemographic biases were effectively reduced by a fair pre-processing algorithm without loss of accuracy.Conclusions ML approaches using linked routinely collected education and health data offer accurate, low-cost and scalable prediction models of ADHD. …”
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Circle chaotic map tuna swarm optimization (CCMTSO) based feature selection and deep learning approach for air quality prediction by Aradhyamatada Swamy, Rohitha U.M.

“…Utilizing LSTM and FCNN, this algorithm can extract the temporal and spatial components of the information with good precision and reliability.…”
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Continuous and Discrete Similarity Coefficient for Identifying Essential Proteins Using Gene Expression Data by Jiancheng Zhong, Zuohang Qu, Ying Zhong, Chao Tang, Yi Pan

“…Using the graph theory as the basis, we fused the newly proposed similarity coefficient with the existing network topology prediction algorithm at each protein node to recognize essential proteins. …”
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Single-cell landscape of dynamic changes in CD8+ T cells, CD4+ T cells and exhausted T cells in hepatocellular carcinoma by Rongqiang Liu, Jing Ye, Jianguo Wang, Wangbin Ma, Zhendong Qiu, Jia Yu, Weixing Wang

“…Altered signaling pathway activity in exhausted T cells was uncovered by the AUCell algorithm. xCELL, TIMER, QUANTISEQ, CIBERSORT and CIBERSORT-abs were performed to explore immune cell infiltration. …”
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Multiobjective Optimization of Surface Roughness and Tool Wear in High-Speed Milling of AA6061 by Machine Learning and NSGA-II by Anh-Tu Nguyen, Van-Hai Nguyen, Tien-Thinh Le, Nhu-Tung Nguyen

“…We applied a two-pronged approach that combines machine learning (ML) and a Nondominated Sorting Genetic Algorithm (NSGA-II) to model and optimize Ra and Vbmax. …”
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Environmental Covariates for Sampling Optimization and Pest Prediction in Soybean Crops by Cenneya Lopes Martins, Maiara Pusch, Wesley Augusto Conde Godoy, Lucas Rios do Amaral

“…In the 2022–2023 crop season, sample designs were optimized using the iterative algorithm optimization of sample configurations using spatial simulated annealing (SPSANN) using the selected covariates, resulting in two optimized designs that were compared to a regular grid. …”
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Soil-Rock Slope Stability Analysis under Top Loading considering the Nonuniformity of Rocks by Huang Xian-Wen, Zhi-Shu Yao, Wang Bing-Hui, Zhou Ai-Zhao, Peng-Ming Jiang

“…To obtain better estimation results, a new rock contour establishing algorithm was developed, capable of considering interlock effect between rocks. …”
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A Collaborative Control Framework: Achieving Emergency Vehicle Priority While Minimizing Negative Impact on Ordinary Vehicles at Signalized Intersection by Ke-jun Long, Zhong-gen Zhang, Zhi-bo Gao, Si-qi Zhong, Jian Gu

“…Finally, our collaborative control framework also employs an Eco-Driving algorithm for the optimization of OV speed to reduce fuel consumption. …”
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Face Recognition Method for Underground Engineering Based on Dual-Target Domain Adaptation and Discriminative Feature Learning by Yongqiang Yu, Cong Guo, Lidan Fan, Jiyun Zhang, Liwei Yu, Peitao Li

“…Although various methods to improve algorithm robustness can enhance the overall model performance, the face recognition accuracy remains insufficient for the large number of blurred and NIR images generated during underground engineering. …”
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Prediction of COD Degradation in Fenton Oxidation Treatment of Kitchen Anaerobic Wastewater Based on IPSO-BP Neural Network by Tianpeng Zhang, Pengfei Ji, Dayong Tian, Rui Xu

“…The improved particle swarm optimization (IPSO) algorithm is used to optimize the back propagation (BP) neural network, and a prediction model of COD degradation is established based on IPSO-BP neural network. …”
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Implementasi Sistem Administrasi di Unit Pelaksana Teknis Pusat Pengembangan Publikasi Ilmiah Dosen Universitas Semarang berbasis Website by Muhamamd Surya Jati Pradana, Aria Hendrawan, B.Very Christioko, Agusta Praba Ristadi Pinem

“…The search process equipped with sequential search algorithm can also display the results searched based on the subject keyword. …”
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A privacy-enhanced framework with deep learning for botnet detection by Guangli Wu, Xingyue Wang

“…We design a privacy confrontation algorithm based on a mutual information calculation mechanism. …”
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An improved SPWM control approach with aid of ant lion optimization for minimizing the THD in multilevel inverters by Alaa M. Abdel-hamed, Abdelrahman M. Nasser, Hamdy Shatla, Amr Refky

“…The ant lion optimization (ALO) algorithm was implemented to optimize the switching control to reduce the total harmonic distortion (THD) and improve power quality. …”
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Optimization Configuration Method of Energy Storage Considering Photovoltaic Power Consumption and Source-Load Uncertainty by Junjie Qiao, Xiaofang Meng, Weigang Zheng, Pengxue Huang, Tiefeng Xu, Yupeng Xu

“…The representative scenarios are obtained after the combination is cut down by the K-means clustering algorithm. The poor operation scenarios are identified by using the variation of the maximum total node voltage deviation. …”
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Fast and accurate imputation of genotypes from noisy low-coverage sequencing data in bi-parental populations. by Cécile Triay, Alice Boizet, Christopher Fragoso, Anestis Gkanogiannis, Jean-François Rami, Mathias Lorieux

“…Here, we present a new algorithm for imputation of LC-NGS data that eliminates the need of complex pre-filtering of noisy data, accurately types heterozygous chromosomal regions, precisely estimates crossover positions, corrects erroneous data, and imputes missing data. …”
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Explainable deep learning approach for recognizing “Egyptian Cobra” bite in real-time by Elhoseny Mohamed, Hassan Ahmed, Shehata Marwa H., Kayed Mohammed

“…We deploy IoT-enabled wearable devices equipped with sensors capable of detecting snake bites, whereas these sensors measure changes in physiological parameters indicative of a snakebite, such as heart rate, blood pressure, and temperature sensors based on our proposed mathematical algorithm. Also, we present a real case study in which we used our mathematical algorithm to determine based on its sensor readings whether the victim was exposed to a snake bite or not in the real-time. …”
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