Majority or Minority: Data Imbalance Learning Method for Named Entity Recognition by Sota Nemoto, Shunsuke Kitada, Hitoshi Iyatomi

“…Evaluation experiments on four NER datasets (Japanese and English) showed that MoM learning improves the prediction performance of the minority classes without sacrificing the performance of the majority class and is more effective than widely known and state-of-the-art methods. …”
Get full text

Short-Term Photovoltaic Power Forecasting Based on the VMD-IDBO-DHKELM Model by Shengli Wang, Xiaolong Guo, Tianle Sun, Lihui Xu, Jinfeng Zhu, Zhicai Li, Jinjiang Zhang

“…A DHKELM-based combined prediction model is developed for each component of the decomposition, tailored to different weather types. …”
Get full text

The core aspects of mother expressed emotions as a predictor of Vocational identity in Pakistani adolescents: A Structural Equation Modeling Approach by Sumara Masood

“…Significant positive prediction was found among mother expressed emotions as positive remarks found 20% and warmth found 45% predictor of vocational identity in adolescents, while emotional-over involvement showed -16% significantly negative predictor of vocational identity among adolescents. …”
Get full text

Hybrid learning in post-pandemic higher education systems: an analysis using SEM and DNN by Alvin Muhammad ‘Ainul Yaqin, Ahmad Kamil Muqoffi, Sigit Rahmat Rizalmi, Faishal Arham Pratikno, Remba Yanuar Efranto

“…Meanwhile, DNN achieved a high prediction accuracy of 82.40%, significantly outperforming logistic regression (baseline) models. …”
Get full text

SSATNet: Spectral-spatial attention transformer for hyperspectral corn image classification by Bin Wang, Gongchao Chen, Juan Wen, Linfang Li, Songlin Jin, Yan Li, Ling Zhou, Weidong Zhang

“…Finally, a classifier generates the prediction results. Compared to existing state-of-the-art classification methods, our model performs better on the hyperspectral corn image dataset, demonstrating its effectiveness.…”
Get full text

Antioxidants and Cognitive-Behavioral Therapy in Patients with Functional Dyspepsia by T. V. Sapozhnikova, S. A. Parfenov, T. E. Yesina, K. V. Sapozhnikov, A. N. Smirnov, A. A. Paulov, D. M. Rizakhanov, O. A. Rizakhanova

“…After comparing it with a threshold, the probability of a positive response to a combination of antioxidant and cognitive-behavioral therapy is estimated. The developed prediction algorithm is valid (sensitivity — 91 %, specificity — 73 %, accuracy — 84.8 %) and allows to optimize the definition of treatment tactics for a patient with functional dyspepsia.…”
Get full text

Mini meta-analysis of anticholinesterase actions of atorvastatin, simvastatin and rosuvastatin, and in silico identification of their protein targets in Mus musculus by Fouad Kasim Mohammad, Rawnaq Faris Al-Shalchi

“…The study aims at conducting a mini meta-analysis on in vivo and in vitro adverse anti-ChE effects of atorvastatin, simvastatin and rosuvastatin in mice, and using the SwissPrediction to identify in silico body target proteins. …”
Get full text

Experimental Research of the Influence of Microfracture Morphology on Permeability of Shale Rock by Xiaohe Huang, Yunqian Long, Yuyi Wang, Ming Yue

“…This research can provide some new insights for the production prediction of shale gas reservoir after fracturing.…”
Get full text

Immediate and short-term effects of neurodynamic techniques on hamstring flexibility: A systematic review with meta-analysis. by Sergio Núñez de Arenas-Arroyo, Vicente Martínez-Vizcaíno, Ana Torres-Costoso, Sara Reina-Gutiérrez, Bruno Bizzozero-Peroni, Iván Cavero-Redondo

“…Furthermore, to reflect the variation in genuine therapy effects in different scenarios, including future patients, we calculated a 95% prediction interval(prI).<h4>Results</h4>Thirteen trials were included, involving 624 participants. …”
Get full text

Enhancing electric vehicle battery lifespan: integrating active balancing and machine learning for precise RUL estimation by Yara A. Sultan, Abdelfattah A. Eladl, Mohamed A. Hassan, Samah A. Gamel

“…Among these, k-nearest Neighbors and Random Forest models deliver the highest accuracy, achieving R2 values of 0.996 and above with low MAE, demonstrating strong predictive capability. The integration of active balancing and RUL prediction enables a feedback loop where balanced SOC levels promote battery health, and RUL predictions inform optimal balancing strategies. …”
Get full text

A Deep Learning Model for the Thermospheric Nitric Oxide Emission by Xuetao Chen, Jiuhou Lei, Dexin Ren, Wenbin Wang

“…An accurate representation of the three‐dimension (3‐D) morphology of NO emission in models is critical for predicting the thermosphere state. Recently, the deep‐learning neural network has been widely used in space weather prediction and forecast. …”
Get full text

Maintenance Scheduling of Wind Units from the Power Plant Owner’s Perspective with the Objective of Minimizing Economic Loss by Amir Allame, Asghar Akbari Foroud

“…The estimation of wind speed in the prediction region is conducted by utilizing wind speed data from the study period and employing the Weibull probability density function. …”
Get full text

Analysis on Emissions and Performance of Ceramic Coated Diesel Engine Fueled with Novel Blends Using Artificial Intelligence by Tarun Kumar Kotteda, Rama Bhadri Raju Chekuri, B. Naga Raju, Prasada Raju Kantheti, S. Balakumar

“…It has been identified that ANN showed an average accuracy of prediction superior than regression analysis.…”
Get full text

Quantitative Analysis of Multicomponents in Qufeng Zhitong Capsule and Application of Network Pharmacology to Explore the Anti-Inflammatory Activity of Focused Compounds by Mengjie Xue, Yuting Zhao, Ying Cui, Jing Yang, Yuefei Wang, Xin Chai

“…Based on the brief prediction results of network pharmacological analysis, ultra-performance liquid chromatography coupled with photodiode array detector method was validated in terms of linearity, limit of detection, limit of quantification, precision, repeatability, stability, and recovery test and was successfully employed to determine 16 compounds in 28 batches of QZCs, which confirmed the feasibility and reliability of the established method for the quantitative analysis of 16 compounds in QZC. …”
Get full text

Mechanism of Permeability Evolution for Reservoir Sandstone with Different Physical Properties by Xianshan Liu, Ming Xu, Ke Wang

“…The results also show that the variation patterns of permeability are similar for two reservoir sandstones under combination of confining pressure and water pressure; however, the strength and permeability are smaller for the sandstone with mud than that without mud, deeply indicating that mud-like materials have a relatively great impact on the mechanical properties and permeability, so mud components cannot be ignored for prediction of reservoir permeability. Furthermore, a statistical damage constitutive model considering hydraulic-mechanical coupling process is presented to calculate the damage variable D, illustrating that larger water pressure will result in a relatively smaller damage variables D and corresponding maximum, which explains that the permeability increases more rapidly and is larger for the sandstone without mud than that with mud, and sandstone damage related to corresponding circumferential crack strain and permeability has been investigated, also implying the evolution mechanism of permeability for two sandstones with different physical properties. …”
Get full text

Analysis and synthesis of images of environmentally oriented innovative technologies of construction production by V. I. Telichenko, A. A. Lapidus, M. Yu. Slesarev

“…The object of research — aspects of automated prediction of promising construction technologies is confirmed. …”
Get full text

A novel model of the cross-section variation effect induced by contraction convection on freckle defects in directional solidification by Yang Liu, Yan Shang, Fu Wang, Dexin Ma, Qiang Yang, Xiaorui Chen, Jiantao Wu

“…After considering CSVE, the positional accuracy in freckle prediction has been improved, and the reasons for this improvement have been further explored. …”
Get full text

Robust Optimization of Alginate-Carbopol 940 Bead Formulations by J. M. López-Cacho, Pedro L. González-R, B. Talero, A. M. Rabasco, M. L. González-Rodríguez

“…Confirmation tests to verify the prediction model were carried out and the obtained results were very similar to those predicted in every profile. …”
Get full text

A Feature-Extraction-Based Lightweight Convolutional and Recurrent Neural Networks Adaptive Computing Model for Container Terminal Liner Handling Volume Forecasting by Bin Li, Yuqing He

“…Subsequently, a feature-extraction-based lightweight convolutional and recurrent neural network adaptive computing model (FEB-LCR-ACM) is presented initially to predict the LHV by the fusion of multiple deep learning algorithms and mechanisms, especially for the specific feature extraction package of tsfresh. …”
Get full text

Temperature dynamics and mechanical properties analysis of carbon fiber epoxy composites radiated by nuclear explosion simulated light source by Lin Yuan, Jun Li, Boyu Wang, Xin Zhang, Weijie Zhu, Yang Liu, Haiyang Zhang, Xiaoxiang Han

“…The insights gained from this comprehensive analysis are essential for the rapid prediction of temperature changes and the formulation of robust light radiation protection strategies for equipment exposed to nuclear explosion environments.…”
Get full text