Microseismic Monitoring, Positioning Principle, and Sensor Layout Strategy of Rock Mass Engineering by Tianhui Ma, Daoyuan Lin, Chun’an Tang, Kedar Prasad Yadav, Zhiqiang Feng, Ke Ma

“…Thus, the scientific nature of monitoring work is greatly promoted, and the accuracy and advance of the prediction of engineering and geological disasters are improved. …”
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Distinct cortico-striatal compartments drive competition between adaptive and automatized behavior. by William H Barnett, Alexey Kuznetsov, Christopher C Lapish

“…The model accomplishes this by distinguishing learning processes in the dorsomedial striatum (DMS) that rely on reward prediction error signals as distinct from the dorsolateral striatum (DLS) where learning is supported by salience signals. …”
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Solutions to improve the energy efficiency of non-residential buildings: Evidence from Romania by Ioan Bitir-Istrate, Laura-Alexandra Doroftei, Gheorghe Militaru

“…The results showed that the platform allows analysing various measures for increasing energy efficiency and displays an approximate prediction as a result of these measures. By performing simulations in the platform, it is possible to check and choose the best measures leading to maximizing the energy efficiency of the building and to plan the investments. …”
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Monitoring and Simulation of Dynamic Spatiotemporal Land Use/Cover Changes by Andong Guo, Yuqing Zhang, Qing Hao

“…By comparing the FoM and Kappa coefficients, we concluded that the prediction accuracy of partitioned MLP-MC is better than that of unpartitioned MLP-MC. …”
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Harmonization and Verification of Three National European Icing Forecast Models Using Pilot Reports by Christoph Knigge, Katie Bennett, Christine Le Bot, Mara Gehlen-Zeller, Svenja Koos

“…In this study, several methods with varying complexities are analyzed for combining three individual in-flight icing forecasts based on numerical weather prediction models from Deutscher Wetterdienst, Météo-France, and Met Office. …”
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MAGEB2-Mediated Degradation of EGR1 Regulates the Proliferation and Apoptosis of Human Spermatogonial Stem Cell Lines by Xueheng Zhao, Zenghui Huang, Yongzhe Chen, Qianyin Zhou, Fang Zhu, Huan Zhang, Dai Zhou

“…Further, using protein interaction prediction, molecular docking, and immunoprecipitation, we found that MAGEB2 interacted with early growth response protein 1 (EGR1) in SSC lines. …”
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Research of the Backfill Body Compaction Ratio Based on Upward Backfill Safety Mining of the Close-Distance Coal Seam Group by Xingping Lai, Leiming Zhang, Yun Zhang, Pengfei Shan, Peifeng Wan, Kaiwen Mu

“…Based on that, a layer spacing-BBCR-mining height (L-R-H) prediction model based on multiple linear regression analysis was established and the BBCR of close-distance coal seam group safe upward mining was determined combined with the engineering background. …”
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Evaluating Proton Intensities for the SMILE Mission by Simon Mischel, Elena A. Kronberg, C. P. Escoubet

“…Abstract This study introduces five linear regression models developed to accurately predict proton intensities in the critical energy range of 92.2–159.7 keV. …”
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IMPLEMENTATION OF GENOME-WIDE SELECTION IN WHEAT by G. Charmet, E. Storlie

“…In such conditions, uncharacterized markers can be used to predict the breeding value of a trait without referring to actual QTLs. …”
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Failure Mechanism of Anchored Rock under Constant Resistance Values of Cable Based on Particle Flow Code by Xiaoming Sun, Li Cui, Yong Zhang, Zuoxun Jiang, Lei Wang

“…The research results provide a reference for the design of a CRV and collapse prediction of the anchored surrounding rock.…”
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Statistical Downscaling of ERA-Interim Forecast Precipitation Data in Complex Terrain Using LASSO Algorithm by Lu Gao, Karsten Schulz, Matthias Bernhardt

“…Compared to other three downscaling methods, LASSO shows the best performances in precipitation occurrence and precipitation amount prediction on average. Furthermore, LASSO could reduce the error for certain sites, where no improvement could be seen when LOCI and QM were used. …”
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Graph-based two-level indicator system construction method for smart city information security risk assessment by Li Yang, Kai Zou, Yuxuan Zou

“…For the simulation of risk level prediction, we compared our method with some machine learning algorithms, such as ridge regression, Lasso regression, support vector regression, decision trees, and multi-layer perceptron. …”
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Federated Learning-Based Credit Card Fraud Detection: A Comparative Analysis of Advanced Machine Learning Models by Zheng Han

“…Because of the privacy concerns about the transaction data, it is essential not to leak it when training prediction models for credit card fraud analysis. Challenges for credit card fraud monitoring include highly imbalanced datasets and the need for advanced models to detect fraud patterns. …”
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The correlation between on-farm biosecurity and animal welfare indices in large-scale turkey production by László Kovács, Christopher René Klaucke, Máté Farkas, Mikolt Bakony, Viktor Jurkovich, László Könyves

“…The association between biosecurity and welfare indicators was investigated by correlation testing and prediction accuracy using random forest classification. …”
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Nondata-aided error vector magnitude performance analysis over κ−μ shadowed fading channel by Fan YANG, Xiaoping ZENG, Haiwei MAO, Xin JIAN, Derong DU, Xiaoheng TAN, Yiwen GAO

“…The performance prediction of wireless system over κ−μ shadowed fading channels was a challenging problem of wireless communications,which affects transmission scheme design seriously.To solve this problem,a novel method of quantifying the κ−μ shadowed fading channels performance based on nondata-aided error vector magnitude (NDA-EVM) was proposed.NDA-EVM was considered as a new metric to evaluate the change of the channels.The unified model to calculate different modulation order of NDA-EVM was analytically derived by maximum likelihood criterion.Moreover,the relationship between the κ−μ distribution and the NDA-EVM was built by using the attenuation factor of the channel as intermediate variable.Thereafter,the lower bounds of the NDA-EVM over the κ−μ shadowed fading channels were formulated,which was also simplified for various typical channels.The theoretical analysis was taken,moreover,numerical results were also conducted to verify the effectiveness of the derived formulation.It shows that NDA-EVM estimation has the lest root mean square error than data-aided signal to noise ratio (DA-SNR) estimation and error vector magnitude (DA-EVM) estimation over the κ−μ shadowed fading channels.The derived lower bounds closely match the theoretical values,especially at low SNR.In addition,the lower bounds are negatively related to all of the parameters of the κ−μ shadowed fading channels,which make it sensitive to the change of the fading channels.…”
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Acoustic Echo Cancellation Embedded in Smart Transcoding Algorithm between 3GPP AMR-NB Modes by Emmanuel Rossignol Thepie Fapi, Dominique Pastor, Christophe Beaugeant, Hervé Taddei

“…We propose in this paper a coded domain AEC integrated in a smart transcoding strategy which directly modifies the Code Excited Linear Prediction (CELP) parameters. The proposed system addresses simultaneously problems due to network interoperability and network voice quality enhancement. …”
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Optimization of Mix Proportions for Novel Dry Stack Interlocking Concrete Blocks Using ANN by Krishna Prakash A, Jane Helena H, Paul Oluwaseun Awoyera

“…In the second phase, the identified mix proportions were analysed using ANN to predict the compressive strength of interlocking blocks. …”
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Beyond detection and correction: Fake news’ «news-ness» and «shareworthiness» as alternative ways to tackle disinformation by Raúl Rodríguez-Ferrándiz

“…In this work we problematize critically the research questions formulated on fakeness detection and specifically we address two significant alternative (though complementary) approaches: 1) What formal traits and news values do fake news best imitate, which sheds light on what “news” means (irrespective of falsity) since the rise of social media as news source (news-ness assessment), and 2) what factors explain fake news sharing (shareworthiness prediction), which explains why it is shared with a higher intensity than real news, even in the case of awareness that a falsity is being shared. …”
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Self- versus clinician-collected swabs in anal cancer screening: A clinical trial. by Clare E F Dyer, Fengyi Jin, Jennifer M Roberts, I Mary Poynten, Annabelle Farnsworth, Leon P McNally, Philip H Cunningham, Andrew E Grulich, Richard J Hillman

“…Concordance for cytologic prediction was 88.2% for any cytologic abnormality. …”
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Machine learning optimized design of THz piezoelectric perovskite-based biosensor for the detection of formalin in aqueous environments by Jacob Wekalao, Shobhit K. Patel, Om Prakash Kumar, Fahad Ahmed Al-zahrani

“…The integration of LWLR-based optimization protocols substantially enhances prediction accuracy while reducing computational time by ≥ 85% as well as cutting down the required resources. …”
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