Denoising of acoustic emission signals from rock failure processes through ICEEMDAN combined with multiple criteria and wavelet transform by Tao Wang, Weiwei Ye, Liyuan Liu, Zhihui Zhao, Wei Huang

“…Quantitative analysis of denoising effects on typical rock uniaxial compression fracture AE signals reveals that the optimized method has a positive impact on high-frequency noise reduction. The peak frequency range is unaffected before and after optimization, while the main amplitude reduction is concentrated in the high-frequency range. …”
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An artificial intelligence model integrating culprit lesion diagnosis and risk assessment for acute coronary syndromeResearch in context by Peng Peng Xu, Bin Hu, Fan Zhou, Zhi Han Xu, Qian Chen, Tong Yuan Liu, Bang Jun Guo, Chang Sheng Zhou, Xin Wei Tao, Hong Yan Qiao, Jia Ni Zou, Xiang Ming Fang, Wen Cai Huang, Long Jiang Zhang

“…Summary: Background: An integrated machine learning (ML) approach capable of both diagnosing acute coronary syndrome (ACS, encompassing myocardial infarction and unstable angina) and predicting future ACS risk within defined optimal timeframes remains an unmet need in cardiovascular risk stratification. …”
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Adaptive WSN Scheduling for Lifetime Extension in Environmental Monitoring Applications by Jong Chern Lim, Chris Bleakley

“…For two-tier networks, the proposed algorithm outperforms a highly cited previously published algorithm by up to 512% in terms of lifetime and by up to 30% in terms of prediction accuracy. …”
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Automatic speech signal segmentation with chosen parametrization method by Cz. BASZTURA, T. SAWCZYN

“…The usability of three different parametrization methods - based on the analysis of zero-crossings, spectral analysis and linear prediction coding - was analyzed. No significant differences were observed in the efficiency of investigated parameters.…”
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Statistical Evaluation of Smartphone-Based Automated Grading System for Ocular Redness Associated with Dry Eye Disease and Implications for Clinical Trials by Rodriguez JD, Hamm A, Bensinger E, Kerti SJ, Gomes PJ, Ousler III GW, Gupta P, De Moraes CG, Abelson MB

“…The model utilizes the DeepLabV3 architecture for image segmentation, extracting two key features—horizontality and redness. The algorithm then uses these features to predict eye redness, validated by comparison with expert grader scores.Results: The bivariate model using both redness and horizontality performed best, with a Mean Absolute Error (MAE) of 0.450 points (SD=0.334) on the redness scale relative to expert scores. …”
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Forecasting Financial Crashes: Revisit to Log-Periodic Power Law by Bingcun Dai, Fan Zhang, Domenico Tarzia, Kwangwon Ahn

“…We aim to provide an algorithm to predict the distribution of the critical times of financial bubbles employing a log-periodic power law. …”
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Fast and resource efficient method for indoor localization based on fingerprint with varied scales by Yanfen LE, Zhuo TANG, Cunbao SHENG, Weibin SHI

“…To improve the prediction speed in indoor localization,a novel algorithm based on fingerprint with varied scales was proposed.It divided the region of interest into distinct zones with distinctive coverage indicators,and reference positions with different distribution density were set in the region.According the time relevance and strength vary of the RSS from the anchors,the grids-matching process was greatly sped up for the usage of coverage indictors and the features of the location fingerprint extracted with the PCA,which made the proposed method fit the demand of application with limited power and memory.Experimental results indicate that accuracy of the positioning is ensured with the reduced energy-consuming,and more flexible about the number of anchors and the grid distribution.…”
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NeuralConstraints: integrating a neural generative model with constraint-based composition by Juan S. Vassallo, Örjan Sandred, Julien Vincenot

“…‘NeuralConstraints’ combines the predictive generative abilities of neural networks trained on symbolic musical data with an advanced backtracking constraint algorithm. …”
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RATIONALE FOR PREVENTION OF CARDIO-CEREBRAL COMPLICATIONS IN THE METABOLIC SYNDROME BASED ON MATHEMATICAL FORECASTING TECHNIQUES by S. V. Chernavskii, A. N. Fursov, N. P. Potekhin, V. N. Yakovlev

“…A discriminant analysis of clinical and instrumental data of patients with MS.Results of this study allow the early (prenosological) stages of the metabolic syndrome using the linear discriminant equations to predict thedevelopment of myocardial infarction up to 89.3 %, stroke — up to 87.8 %.Conclusion. …”
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Evaluation of Nonlinear Autoregressive Network with Exogenous Inputs Architectures for Wind Speed forecasting by Kacimi Houda, Fennane Sara, Mabchour Hamza, ALtalqi Fatehi, Echchelh Adil

“…Predictive performance was assessed using RMSE to measure the gap between predicted and actual values. …”
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Potential geographical distribution of Carob tree (Ceratonia siliqua L., Leguminosae) in Morocco under climate change by Jalal Kassout, Soufian Chakkour, Abdeltif El Ouahrani, Younes Hmimsa, Salama El Fatehi, Yanzheng Yan, Rachid Hadria, Mohammed Ater

“…Our hypothesis suggests a reduction in suitable habitats for the carob tree under climate change scenarios. …”
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Artificial intelligence for smart irrigation: Reducing water consumption and improving agricultural output by Arlanova A. A., Hojamkuliyeva B. A., Babanazarov N. Sh., Arlanov M. S.

“…A mathematical model based on machine learning algorithms is developed to predict the optimal water volume required for irrigation of agricultural crops. …”
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A Synergistic CNN-DF Method for Landslide Susceptibility Assessment by Jiangang Lu, Yi He, Lifeng Zhang, Qing Zhang, Jiapeng Tang, Tianbao Huo, Yunhao Zhang

“…In addition, the SHAP algorithm was used to quantify the contribution of features to the prediction results both globally and locally, further explaining the model. …”
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Exploring qubit-ADAPT-VQE for materials discovery in direct air capture by Marco Antonio Barroca, Rodrigo Neumann Barros Ferreira, Mathias Steiner

“…Quantum computing can potentially accelerate the discovery of solid sorbents for DAC by predicting molecular binding energies. In this work, we explore algorithms for predicting gas adsorption in metal–organic frameworks using a quantum computer. …”
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An improved model accuracy for forecasting risk measures: application of ensemble methods by Katleho Makatjane, Kesaobaka Mmelesi

“…Statistical-based predictions with extreme value theory improve the performance of the risk model not by choosing the model structure that is expected to predict the best but by developing a model whose results are a combination of models with different shapes. …”
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Quantum Neural Networks Approach for Water Discharge Forecast by Liu Zhen, Alina Bărbulescu

“…The lower error between the recorded values and the predicted ones in the evaluation of maxima compared to the case of the competitors mentioned shows that the algorithm best fits the extremes. …”
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Hybrid GOA and PSO optimization for load frequency control in renewable multi source dual area power systems by Muhammad Zubair Yameen, Abdul Khalique Junejo, Zhigang Lu, Rizwan Aziz Siddiqui, Fayez F. M. El-Sousy, Ibtisam Naveed

“…Similarly, in the dual-area IPS, it provides a 76.73% reduction in overshoot, an 87.62% reduction in undershoot, and a 75.68% improvement in rise time. …”
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MACAW: a method for semi-automatic detection of errors in genome-scale metabolic models by Devlin C. Moyer, Justin Reimertz, Daniel Segrè, Juan I. Fuxman Bass

“…Abstract Genome-scale metabolic models (GSMMs) are used to predict metabolic fluxes, with applications ranging from identifying novel drug targets to engineering microbial metabolism. …”
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Machine learning approaches for modelling of molecular polarizability in gold nanoclusters by Abhishek Ojha, Satya S. Bulusu, Arup Banerjee

“…Our results demonstrate the efficacy of machine-learning in accurately predicting the polarizability of gold nanoclusters. …”
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Mapping the ADDQoL to the EQ-5D-5L and SF-6Dv2 among Chinese patients with type 2 diabetes mellitus by Haoran Fang, Tianqi Hong, Xinran Liu, Chang Luo, Yuanyuan Hou, Shitong Xie

“…This study developed mapping algorithms to predict EQ-5D-5L and SF-6Dv2 utility values from ADDQoL scores in T2DM patients in China. …”
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