Accurate total consumer price index forecasting with data augmentation, multivariate features, and sentiment analysis: A case study in Korea. by Injae Seo, Minkyoung Kim, Jong Wook Kim, Beakcheol Jang

“…Experimental results demonstrate that the proposed model outperforms existing approaches in CPI prediction, as evidenced by lower RMSE values. This improved accuracy has the potential to support the development of more timely and effective economic policies.…”
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Predicting mass transfer activation energy and physicochemical properties of dried onion using numerical modeling and artificial intelligence by Fangfang Liu, Hany S. El-Mesery, Ahmed H. ElMesiry, Zicheng Hu, Ali Salem

“…Abstract The quality of the onion slices was statistically evaluated based on the variables of drying conditions, considering the following characteristics: drying time, color, shrinkage, water activity, and rehydration ratio, critical parameters in evaluating food processing and preservation methods. …”
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Post-Processing of AM-EBM Ti6Al4V for Biomedical Applications: Evolution of Mechanical Properties as a Function of Surface Roughness by Andrea Valencia-Cadena, Ude Hangen, Joan Josep Roa Rovira

“…Post-processing, and particularly the dry electropolishing process, is essential for improving the surface quality of 3D-printed Ti6Al4V samples, with specific emphasis on reducing roughness over extended polishing times while preserving mechanical properties. Reducing surface roughness enhances the reliability of hardness measurements and improves the consistency of elastic modulus measurements, as prolonged polishing time stabilizes the full width at half maximum values, thereby minimizing variability due to uniaxial indentation. …”
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Energy Management and Edge-Driven Trading in Fractal-Structured Microgrids: A Machine Learning Approach by Mostafa Pasandideh, Jason Kurz, Mark Apperley

“…The integration of renewable energy into residential microgrids presents significant challenges due to solar generation intermittency and variability in household electricity demand. Traditional forecasting methods, reliant on historical data, fail to adapt effectively in dynamic scenarios, leading to inefficient energy management. …”
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Transmission of systemic Risk between the banking systems of Asia-Pacific Countries and Russia by S. A. Dzuba, V. S. Tishkovetz, M. A. Shchepeleva

“…As a result of the application the algorithm, we get two networks —simultaneous interconnections and using the values of the lagged variables. The networks were constructed for the 2005–2020 time period and separately for sub-periods including the global financial crisis (2005– 2013) and the COVID-19 pandemic period (2014–2020).Based on the results obtained, the networks over the entire time period seem to be quite susceptible to external risks. …”
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Interpretable prognostic modeling for long-term survival of Type A aortic dissection patients using support vector machine algorithm by Hao Cai, Yue Shao, Xuan-yu Liu, Chang-ying Li, Hao-yu Ran, Hao-ming Shi, Cheng Zhang, Qing-chen Wu

“…In the training set, the model achieved an AUC of 0.9137 (95% CI 0.9081–0.9203) and in the internal and external testing set, 0.8533 (95% CI 0.8503–0.8624) and 0.8770 (95% CI 0.8698–0.8982), respectively. The accuracy values were 0.8366, 0.8481 and 0.8030; precision values were 0.8696, 0.8374 and 0.8235; recall values were 0.8421, 0.7933 and 0.7651; F1 scores were 0.8290, 0.8148 and 0.7928; Brier scores were 0.1213, 0.1417 and 0.1323; average precision (AP) values were 0.9019, 0.8789 and 0.8548, respectively. …”
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Assessing and Forecasting Natural Regeneration in Mediterranean Landscapes After Wildfires by Paraskevi Oikonomou, Vassilia Karathanassi, Vassilis Andronis, Ioannis Papoutsis

“…Comparing pre-fire and post-fire values highlighted the recovery rate, while the trendline slope indicated the regeneration rate. …”
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Implant-Prosthetic Rehabilitation with Immediately Loaded Post-Extractive Implants: Retrospective Clinical Cohort Study at 18-Month Follow-Up by Matteo Nagni, Bianca D’Orto, Renato De Cunto, Francesca Cattoni, Raffaele Vinci

“…Marginal bone loss increased over time, with higher values in posterior regions and in patients with systemic conditions or smoking habits. …”
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Recurrent Neuronal Networks for the Prediction of the Temperature of a Synchronous Machine During Its Operation by Rubén Pascual, Marcos Esteban, José M. Guerrero, Carlos A. Platero

“…Its inputs include electrical variables and the inlet and outlet air temperatures of the SM’s cooling system. …”
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Aortic Pressure Control Based on Deep Reinforcement Learning for <i>Ex Vivo</i> Heart Perfusion by Shangting Wang, Ming Yang, Yuan Liu, Junwen Yu

“…The control performance of the proposed DDPG method, the traditional proportional–integral–derivative (PID) method, and the fuzzy PID method are compared by simulating single and mixed changes in mean aortic pressure target values and coronary resistance. The proposed method exhibits superior performance compared to the PID and fuzzy PID methods under mixed factors, with 68.6% and 66.4% lower settling times and 70.3% and 54.1% lower overshoot values, respectively. …”
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Analisis Penerapan Mutual Information pada Klasifikasi Status Studi Mahasiswa Menggunakan Naïve Bayes by Sulfayanti Situju, Nahya Nur, Nursan Halal

“… Early identification of Student Study Status is essential for higher education institutions to implement proactive and strategic measures that facilitate timely completion of studies and mitigate dropout rates. …”
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WEATHER RISKS AS DRIVERS OF STRUCTURAL SHIFTS IN AGRICULTURE IN THE RUSSIAN FEDERATION by Marina Yevgenievna KADOMTSEVA, Andrej Vladimirovich BOGDANOV

“…The relationship between climatic variables and economic efficiency of the crop production sub-sector is determined. …”
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Artificial intelligence-assisted optimization of Eichhornia crassipes extracts and evaluation of their biological activities by Nuh Korkmaz

“…The optimization focused on three key variables: extraction temperature, duration, and the ethanol-to-water solvent ratio. …”
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Evaluating an Artificial Intelligence (AI) Model Designed for Education to Identify Its Accuracy: Establishing the Need for Continuous AI Model Updates by Navdeep Verma, Seyum Getenet, Christopher Dann, Thanveer Shaik

“…Bland–Altman analysis showed moderate variability with substantial differences in results, and both Pearson and Spearman correlations revealed weak relationships, with values close to zero. …”
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Voltage unbalance assessment in a distribution system incorporated with renewable‐based sources and electric vehicles in an uncertain environment by Nandini K. K., Jayalakshmi N. Sabhahit, Vinay Kumar Jadoun

“…The modified WOA outperforms the other optimization method and the existing literature in minimizing the % VUF and VRP index in case 2 operation, with values of 1.7 and 8.89 respectively. Case 3 also achieves low objective function values, but the VUF and VRP index are 11.76% and 9.67% higher than case 2 by modified WOA. …”
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Gait data generation using generative adversarial network based on human dynamics by Ryoya OBA, Yusuke OSAWA, Keiichi WATANUKI, Kazunori KAEDE

“…Various training techniques have been devised to capture motion data during real-time walking and provide feedback to trainees, allowing them to adjust their gait to align the measured gait parameters with target values. …”
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Anthropometric and physical indicators among Jordanian female soccer according to playing position by Ghazi El-kalana, Sofia Akroush, Salem Al-qarra, Osama Abdel Fattah, Mousa Ahmad

“…Objective: This study aimed to explore the anthropometric and physical measurement values among Jordanian female soccer players and to identify differences in these values according to playing position. …”
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Assessment of Multi-Depth Water Quality Dynamics in an Artificial Lake: A Case Study of the Ribnica Reservoir in Serbia by Dragana Milijašević Joksimović, Dejana Jakovljević, Dejan Doljak

“…The SWQI results indicated a general improvement in water quality over time, with values ranging from medium (82) to excellent (95) in 2021 and increasing from good (89) to excellent (98) in 2022. …”
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Dynamics of the borders of phenological seasons in the east of the Russian Plain (Kirov, Russia) by T.G. Shikhova, A.N. Soloviev

“…Using the phenological database covering the period of 1961–2019 for Kirov (58°36' N, 49°40' E), the regional features of changes in the seasonal rhythms were analyzed. Mean values were calculated for 1981–2010. Additional types of seasonal rhythms with parameters deviating from the mean values by more than ±2σ were identified. …”
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Changes in neurobiological markers of reactivity to alcohol-related stimuli in alcohol-dependent patients after two years of treatment by Gabriel Rubio, Gabriel Rubio, Gabriel Rubio, Gabriel Rubio, Marta Marín, Marta Marín, Marta Marín, Marta Marín, Cristina Martín-Arriscado Arroba, Enrique Rubio-Escobar, Francisco Arias, Francisco Arias, Francisco Arias, Francisco Arias, Abraham B. Torregrosa, Abraham B. Torregrosa, Abraham B. Torregrosa, Jorge Manzanares, Jorge Manzanares, Jorge Manzanares

“…A repeated measures variance model (RMMM) was also fitted to the logarithmic values ​​over time.ResultsStartle reflex response and salivary cortisol levels before and after ARS viewing did not change significantly in men or women between T0 and T2. …”
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