ML-AMPSIT: Machine Learning-based Automated Multi-method Parameter Sensitivity and Importance analysis Tool by D. Di Santo, C. He, F. Chen, L. Giovannini

“…This tool leverages the strengths of multiple regression-based and probabilistic machine learning methods, including LASSO (see the list of abbreviations in Appendix B), support vector machine, classification and regression trees, random forest, extreme gradient boosting, Gaussian process regression, and Bayesian ridge regression. …”
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Robust Adaptive Multiple Backtracking VBKF for In-Motion Alignment of Low-Cost SINS/GNSS by Weiwei Lyu, Yingli Wang, Shuanggen Jin, Haocai Huang, Xiaojuan Tian, Jinling Wang

“…A new observation vector based on the magnitude matching is then constructed to effectively reduce the effect of outliers on the alignment process. …”
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A generalized superposition-based method for loss allocation in active distribution networks: Introducing effective current concept by Mohammad Bayat, Masoud Aghabigloo, Ali Asghar Ghadimi

“…Our method extends the application of the superposition theorem to both loads and generators, streamlining the loss allocation process and eliminating the need for complex Z-bus calculations. …”
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Tuck-KGC: based on tensor decomposition for diabetes knowledge graph completion model integrating Chinese and Western medicine by Jiangtao ZhangSun, Yu Xin Yang, Beiji Zou, Qinghua Peng, Xiao Xia Xiao

“…This method maps the types of medical entities to vectors, which are seamlessly integrated into the knowledge graph representation learning process. …”
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Evaluating soiling effects to optimize solar photovoltaic performance using machine learning algorithms by Muhammad Faizan Tahir, Anthony Tzes, Tarek H.M. El-Fouly, Mohamed Shawky El Moursi, Nauman Ali Larik

“…Additionally, machine learning algorithms such as artificial neural networks, support vector machines, regression trees, ensemble of regression trees, Gaussian process regression, efficient linear regression, and kernel methods are employed to predict power reduction due to soiling and soiling losses across various soiling percentages. …”
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Universal anomaly detection at the LHC: transforming optimal classifiers and the DDD method by Sascha Caron, José Enrique García Navarro, María Moreno Llácer, Polina Moskvitina, Mats Rovers, Adrián Rubio Jímenez, Roberto Ruiz de Austri, Zhongyi Zhang

“…We compare the performance of the DDD method with the Deep Robust One-Class Classification method (DROCC), which incorporates signals in the training process, and the Deep Support Vector Data Description (DeepSVDD) method, a well-established and well-performing method for anomaly detection. …”
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Evaluation of the Electromagnetic Behavior of TiC/Ti3AlC2 Ceramic Matrix Composites Synthesized by in Situ Method by Kh. Zamani, A. Ghasemi, M. Tavoosi, Gh. Gordani

“…In this case, the milling process and secondary heat treatment were used for the synthesis of the composite. …”
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Back to the Family: Rethinking the Role of Parents in Schooling (Сase of the Republic of Guinea) by Katerina V. Fofanova, Adama Conde

“…Passeron which reveals the principles of the educational system, the conditions for the success of the educational process, the influence of the cultural and linguistic capital of the family on the success of the child. …”
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Conceptual analysis of social responsibility of the person and its integration in pharmaceutical practice by N. O. Tkachenko, В. Р. Hromovyk

“…All this determines the multi-vector nature and variety of means of forming its social responsibility.…”
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Random Forest-Based Prediction of the Optimal Solid Ink Density in Offset Lithography by Laihu Peng, Hao Fan, Yubao Qi, Jianqiang Li

“…Solid ink density is an important control parameter in the manufacturing process of offset prints—the size of which has a significant impact on the color performance of the prints—in which the determination of the optimal solid ink density is critical for the pre-press phase of industrial production. …”
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A competency-based framework for preventing blood-borne pathogen occupational exposures in medical students: literature review and Delphi study by Pingping Wang, Minhong Cai, Yu Lv, Qian Xiang

“…Results The literature review initially identified 1,477 records, with 200 articles retained after search and selection process. During the modified Delphi process, a multidisciplinary panel of 25 experts (71.4% initial response rate; 65.7% retention) iteratively refined prevention strategies. …”
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The Development of the Economic Analysis Methodology in the Digital Economy by Nataliya S. Plaskova

“…The study of innovative processes in Russia and abroad showed that their activation is largely determined by the ability to develop and implement a methodical tool for a system of quality information and analytical support of management functions at all stages of the innovation process. …”
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Extension Model for Safety Appraisal of Existing Concrete Members Based on an Improved Comprehensive Weighting Method by Hengyu Zhou, Yongbo Yuan, Chenlong Liu, Chao Wu, Mingyuan Zhang

“…It was found that the subjective weight vector calculated by IAHP consists of interval numbers. …”
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Machine Learning Strategies for Forecasting Mannosylerythritol Lipid Production Through Fermentation: A Proof-of-Concept by Carolina A. Vares, Sofia P. Agostinho, Ana L. N. Fred, Nuno T. Faria, Carlos A. V. Rodrigues

“…Fermentations are complex and often unpredictable processes. However, fermentation-based bioprocesses generate large volumes of data that are currently underexplored. …”
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Autonomous Maneuvering Decision-Making Algorithm for Unmanned Aerial Vehicles Based on Node Clustering and Deep Deterministic Policy Gradient by Xianyong Jing, Fuzhong Cong, Jichuan Huang, Chunyan Tian, Zikang Su

“…The results show that the NC_DDPG algorithm significantly accelerates the autonomous learning and decision-making process under both balanced and disadvantageous conditions, taking only about 77% of the time required by Vector DDPG. …”
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Performance of Sentiment Classification on Tweets of Clothing Brands by Muhammad Shafiq Jalani, Hu Ng, Timothy Tzen Vun Yap, Vik Tor Goh

“…Following that, data pre-processing such as tokenization, filtering, stemming, and case normalization are performed to remove outliers.  …”
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Landslide hazard early warning method for rock slopes using a hybrid LSTM-SARIMA data-driven model. by Yongxin Dai, Zijian Li, Jingbiao Lu

“…This paper proposes a comprehensive technical system for landslide early hazard warning in open-pit mine slopes, encompassing the full process of monitoring data acquisition and processing, analysis of influencing mechanisms, intelligent algorithm-based prediction, and the construction of early hazard warning indicators. …”
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Reconstruction of LDPC code check matrix based on random extraction at high bit error rate by Zhongyong WANG, Zhenghao LI, Kexian GONG, Peng SUN, Qingtao LI

“…In order to improve the performance of the sparse check matrix reconstruction algorithm of LDPC codes at high BER, an open set recognition algorithm of the check matrix with strong fault tolerance under the condition of sufficient and insufficient number of received code words was proposed.Firstly, a new code word space was constructed by randomly extracting part bits of the code words for many times.Gaussian elimination method was used to solve the dual vector and restore the check vector in a lower dimension.Secondly, using the check vector, the proportion of error-free code groups in the received data was continuously increased by using the methods of “eliminating error code words” or“flipping the lowest unreliable bits” for iterative processing.Simulation results show that the proposed algorithm is superior to comparison algorithm under different bit error rates, different code lengths, different code rates and different number of code words.For (648,324) LDPC codes in IEEE 802.11n protocol, when the number of received code words is sufficient, the reconstruction rate of check matrix can reach more than 95% under the condition of bit error rate of 0.003.When the number of received code words is insufficient (the number of code words is 450), the reconstruction rate of check matrix can reach more than 90% under the condition of bit error rate of 0.0015.…”
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Response Relationship Between Runoff and Meteorological Drought and Flood Characteristics in Jialing River Basin by LI Wen-hui, ZHANG Yang, CAO Hui, XING Long, REN Yu-feng, ZHAI Shao-jun, MA Yi-ming, LI Wen-da

“…The findings indicate that emerging machine learning models, such as support vector machines and random forests, can effectively simulate the complex mechanisms through which meteorological drought and flood events affect runoff in the river basin. …”
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Syndrome of system inflammation in the pathogenesis of respiratory syncitial viral infection by I. V. Babachenko, L. A. Alekseeva, A. N. Uskov, T. V. Bessonova, N. S. Tian, N. E. Monakhova, E. V. Makarenkova, S. G. Grigoryev

“…The study revealed a prolonged increase in serum alpha-2 fraction of globulins, immunoregulatory cytokines with pro-inflammatory (IL-6) and anti-inflammatory (IL-10) action and, which may indicate the presence of subacute inflammatory process associated with the persistence of RS-virus. …”
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