Regional Geomagnetic Field Modeling Based on Associated Legendre Polynomials by Libo Zhu, Houpu Li, Jineng Ouyang, Bo Zhu, Ming Chang

“…This underscores the potential value of the proposed model in both scientific research and practical applications.…”
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An investigation of the private-attribute leakage in WiFi sensing by Yiding Shi, Xueying Zhang, Lei Fu, Huanle Zhang

“…Our finding calls for research efforts to preserve data privacy while enabling WiFi sensing-based applications.…”
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Enhancing Speed Control of BLDC Motors Using Zeta Converter for Small Electric Vehicles by Muhammad Yusril Hafidh, Unggul Wibawa, Tri Nurwati, Tamunonengi E. Wakama

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A COMPARISON OF FUZZY TIME SERIES CHENG AND CHEN-HSU IN FORECASTING TOTAL AIRPLANE PASSENGERS OF SOEKARNO-HATTA AIRPORT by Latifah Zahra, Maiyastri Maiyastri, Izzati Rahmi

“…To determine the accuracy of the forecast, use three criteria, namely Root Mean Squared Error (RMSE), Mean Absolute Deviation (MAD), and Mean Absolute Percentage Error (MAPE). …”
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Application of a Bi-Mamba Model for Railway Subgrade Settlement Prediction During Pipe-Jacking Tunneling by Yipu Peng, Ning Zhou, Bin Wang, Hongjun Gan

“…Using monitoring data collected using on-site automated monitoring robots as the data foundation, the prediction results of the improved transformer, long short-term memory (LSTM), time-series dense encoder (Tide), and decomposition-linear (Dlinear) neural networks are compared. The research results show that the Mean Squared Error (MSE) and Mean Absolute Error (MAE) of the proposed Bi-Mamba model are 0.279 and 0.276, respectively, demonstrating higher prediction accuracy than comparative models such as iTransformer and LSTM. …”
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Modelling decadal trends and the impact of extreme events on carbon fluxes in a temperate deciduous forest using a terrestrial biosphere model by T. Thum, T. Miinalainen, T. Miinalainen, O. Seppälä, H. Croft, C. Rogers, R. Staebler, S. Caldararu, S. Zaehle

“…In this work, we use in situ measurements of leaf chlorophyll content (Chl<span class="inline-formula">_Leaf</span>, 2013–2016) and the leaf area index (LAI, 1998–2018) to parameterize the seasonal dynamics of the QUINCY (QUantifying Interactions between terrestrial Nutrient CYcles and the climate system) terrestrial biosphere model (TBM) to simulate the carbon fluxes at the Borden Forest Research Station flux tower site, Ontario, Canada, over 22 years from 1996 to 2018. …”
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Personalised selection of medication for newly diagnosed adult epilepsy: study protocol of a first-in-class, double-blind, randomised controlled trial by Mark Howard, Wendyl D’Souza, Emma Foster, Patrick Carney, Zanfina Ademi, Patrick Kwan, David N Vaughan, James Lee, Clare Stapleton, Zongyuan Ge, Zhibin Chen, Natasha A Lannin, Udaya Seneviratne, Robert Sparrow, Piero Perucca, Armin Nikpour, Chong Wong, John-Paul Nicolo, Michelle Kiley, Terence O’Brien, Jacqui-Lyn Saw, Dean Jones, David Reutens, Sandra Reeder, Richard Shek-kwan Chang, Ernest Somerville, Tania Farrar, Daniel Thom, Lata Vadlamudi

“…Introduction Selection of antiseizure medications (ASMs) for newly diagnosed epilepsy remains largely a trial-and-error process. We have developed a machine learning (ML) model using retrospective data collected from five international cohorts that predicts response to different ASMs as the initial treatment for individual adults with new-onset epilepsy. …”
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The CoDiNOS trial protocol: an international randomised controlled trial of intravenous sildenafil versus inhaled nitric oxide for the treatment of pulmonary hypertension in neonat... by Anne Greenough, Thomas Schaible, Neil Patel, Dick Tibboel, Arno van Heijst, Theodore Dassios, Joost van Rosmalen, Viviana Arreo, Yogen Singh, Karel Allegaert, Suzan Cochius-den Otter, Florian Kipfmueller, Maria Dolores Elorza, Ana Sanchez, Leopoldo Martinez, Carlos Labrandero, Pertierra Cortada, Jordi Clotet Caba, Marta Aguar, Ana Gimeno, Raquel Escrig, Irma Capolupo, Pietro Bagolan, Fabrizio Ciralli, Genny Raffaeli, Giacomo Cavallaro, Valentina Condò, Paul D. Losty, Marie Horan, Nimish V. Subhedar, Emma E. Williams, Jennifer B. Brandt, Alexandra Kreissl, Berndt Urlesberger, Carmen Mesas Burgos, Björn Frenckner, Björn Larrson, Carla Pinto, Joana Saldaha, Anne Debeer, Anne Smits, Ragnhild Emblem, Richard Keijzer, Yassar Elsayed, David Tingay, Ulrike Kraemer

“…Different therapies are still mainly based on ‘trial and error’. Inhaled nitric oxide (iNO) is often the drug of first choice. …”
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Enhancing the mechanical properties’ performances coconut fiber and CDW composite in paver block: multiple AI techniques with a Performance analysis by G. Uday Kiran, G. Nakkeeran, Dipankar Roy, Sumant Nivarutti Shinde, George Uwadiegwu Alaneme

“…Abstract The present research incorporates five AI methods to enhance and forecast the characteristics of building envelopes. …”
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A Hybrid Wavelet-Based Deep Learning Model for Accurate Prediction of Daily Surface PM_2.5 Concentrations in Guangzhou City by Zhenfang He, Qingchun Guo, Zhaosheng Wang, Xinzhou Li

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Aquaculture Prediction Model Based on Improved Water Quality Parameter Data Prediction Algorithm under the Background of Big Data by Yuan Jiang, Fei Yan

“…At the same time, GPCA-BP water quality prediction model also has excellent performance in convergence accuracy, prediction accuracy, and MAE error performance test. The research content has important reference value for the application of information technology in modern aquaculture.…”
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Improving Indoor Localization System Using a Partitioning Technique Based on RSS and ToA by Mahmood F . Mosleh, Faeza A. Abed, Zahraa Abbas Hamza

“…In this paper, a case study of a selected building is chosen in order to apply the proposed technique of this research. Such proposal is based on the PT ‎ of the area in the case study into MZ. …”
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Empirical Study of the Impact of Unemployment on Political Stability in Iran (1985-2015) by habib samani, robabeh khilkordi

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Sustainable Cold Chain Management: An Evaluation of Predictive Waste Management Models by Hajar Fatorachian, Kulwant Pawar

“…Both models demonstrated strong predictive accuracy, with low Mean Absolute Error (MAE) and Root Mean Squared Error (RMSE), offering reliable and computationally efficient solutions for mid-sized operations. …”
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A mutual mapping model of cross-sections between the axial and normal planes of ball screws based on the forming of helical ball track by Chaoqun Qian, Yi Ou, Hutian Feng, Jian Wu

“…In 3D modeling tests, it processes 10,000 points in merely 5 ms, with an impressively low maximum relative error of 0.001%. Further testing in product detection confirms the robustness of the model, maintaining a maximum relative error under 0.5%. …”
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Drought Monitoring during Growth Rangeland Coverage, Ardabil Province by saideh eiyni, saeide eini

“…The aim of this research is to investigate drought stress in rangeland rangelands in Ardabil province. …”
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Cloud-based configurable data stream processing architecture in rural economic development by Haohao Chen, Fadi Al-Turjman

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FINANCIAL DISTRESS ANALYSIS AND COMPARISON OF ALTMAN Z-SCORE, SPRINGATE, AND GROVER MODELS AT PT SRITEX FOR THE PERIOD 2019-2023 by Dede Ayu Anisah, Laura Natasha Delilah, Maiyaliza Maiyaliza

“…Despite the fact that the most recent two models provide a more realistic representation of the company's current financial status, the prediction error rate is still substantial (type error 60%). …”
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Enhanced OCR Recognition for Madurese Text Documents: A Genetic Algorithm Approach with Tesseract 5.5 by Muhammad Nazir Arifin, Muhammad Umar Mansyur, Ali Rahman, Nindian Puspa Dewi, Fauzan Prasetyo Eka Putra

“…The GA-optimized preprocessing sequence achieved a 24.32% Word Error Rate (WER) and 7.47% Character Error Rate (CER), marking substantial improvements over the baseline Tesseract implementation. …”
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Application of Machine Learning for Academic Outcome Prediction: A Methodological Comparative Study by Md. Wira Putra Dananjaya, Putu Gita Pujayanti

“…The models were evaluated using Mean Absolute Error (MAE), Root Mean Squared Error (RMSE), and R-squared (R2) metrics. …”
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