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  1. 3621
  2. 3622

    Predicting errors in accident hotspots and investigating satiotemporal, weather, and behavioral factors using interpretable machine learning: An analysis of telematics big data. by Ali Golestani, Nazila Rezaei, Mohammad-Reza Malekpour, Naser Ahmadi, Seyed Mohammad-Navid Ataei, Sepehr Khosravi, Ayyoob Jafari, Saeid Shahraz, Farshad Farzadfar

    Published 2025-01-01
    “…Merging this data with a weather-related dataset resulted in a comprehensive dataset containing location, time, weather, and error type variables. After preprocessing, 619,988 records without any missing values were used to train and compare the performance of six machine learning models including logistic regression, K-nearest neighbors, random forest, Extreme Gradient Boosting (XGBoost), Naïve Bayes, and support vector machine. …”
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    Article
  3. 3623

    Artificial Neural Network Modelling of Photodegradation in Suspension of Manganese Doped Zinc Oxide Nanoparticles under Visible-Light Irradiation by Yadollah Abdollahi, Azmi Zakaria, Nor Asrina Sairi, Khamirul Amin Matori, Hamid Reza Fard Masoumi, Amir Reza Sadrolhosseini, Hossein Jahangirian

    Published 2014-01-01
    “…The artificial neural network (ANN) modeling of m-cresol photodegradation was carried out for determination of the optimum and importance values of the effective variables to achieve the maximum efficiency. …”
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    Article
  4. 3624

    Statistical Model for Polarization Mode Dispersion in Single Mode Fibers by Baghdad Science Journal

    Published 2010-09-01
    “…This phenomenon contributes effectively to: increasing pulse width, power decreasing, time jittering, and shape distortion. The time jittering means that the pulse center will shift to left or right. …”
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    Article
  5. 3625

    TEMPORAL TREND IN DAILY RAINFALL INTENSITY IN A CHANGING CLIMATE IN THE MIDDLE BELT REGION OF NIGERIA by Johnson O. MAGE, Bernard T. TYUBEE

    Published 2017-12-01
    “…Trend in the series of the six daily rainfall intensity classes is analyzed using Mann Kendall’s test statistics (τ) and the values obtained are plotted to show the temporal variability in the region. …”
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    Article
  6. 3626

    Sеlf-similar solutions of hydrodynamic equations of non-local physics by B. V. Аlexeev, I. V. Ovchinnikova

    Published 2014-12-01
    “…Namely, in the quasi-stationary Hubble regime only the implicit dependence on time for the unknown values exists. It means that for the intermediate (Hubble) regime the complicated PDE set can be transformed in the set ODE. …”
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    Article
  7. 3627

    Correlations between depressive symptoms, verbal working memory, and physical activity in university students: evidence based on resting EEG by Yuxi Ren, Shufan Li, Shuqi Jia, Xing Wang, Haiyan Wen

    Published 2025-05-01
    “…EEG indicators in the frontal regions of the brain, including beta2 power values for (FP1, FP2) and delta power values for (F3, F4) and (F7, F8), were negatively correlated with depressive symptom scores and verbal working memory reaction time and positively correlated with the level of physical activity (P < 0.05). …”
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    Article
  8. 3628

    An Analysis of Transportation Mode Choice in Bitung City Using Structural Equation Modeling by Lucia Ingrid Regina Lefrandt, Charles S. C. Punuhsingon

    Published 2024-12-01
    “…The research involved distributing an online questionnaire to 200 respondents and gathering data on various latent variables, including Travel Cost, Travel Time, Vehicle Condition, and Comfort Level. …”
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    Article
  9. 3629

    Prediction of Atmospheric Refractivity From Clutter Power Images Using a Convolutional Neural Network and a Trilinear Atmospheric Model by Taekyeong Jin, Doyoung Jang, Hosung Choo

    Published 2025-01-01
    “…The proposed RFC method outputs values for these four variables, which can be used to predict the current atmospheric conditions in a short time. …”
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    Article
  10. 3630

    Contractile and mechanical properties of hamstring muscles measured by the method of tensiomyography (TMG) in professional soccer players: A systematic review, meta-analysis and me... by Daniel Fernández-Baeza, Cristina González-Millán, Germán Díaz-Ureña

    Published 2025-01-01
    “…The main findings of the study are that of the six parameters analysed, three variables were found to differ significantly. Furthermore, the weighted mean values founded were biceps femoris (Tc 27.88, Dm 5.2, Td 23.72) and in semitendinosus (Dm 8.72, Td 25.25). …”
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    Article
  11. 3631

    A Stochastic Approach to the Analysis of Pollutant Emissions and Fuel Consumption of Motor Vehicles Driven in Real Traffic by Monika Andrych-Zalewska, Zdzisław Chłopek, Jakub Lasocki, Jerzy Merkisz, Jacek Pielecha

    Published 2024-12-01
    “…Under such conditions, significant time variability in the values describing engine operations is observed, especially in terms of rotational speed and torque. …”
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    Article
  12. 3632

    INTRA-INDUSTRY TRADE IN AGRICULTURAL AND FOOD PRODUCTS: THE CASE OF MOLDOVA by Liliana CIMPOIES, Cornel COSER

    Published 2017-01-01
    “…For most commodity groups the GL values present average high variability over time, fact which reflects the structural changes in Moldavian agri-food trade. …”
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  13. 3633

    Removal of Cr(VI) from Aqueous Solution Using Modified Pomegranate Peel : Equilibrium and Kinetic Studies by Tariq S. Najim, Suhad A. Yassin

    Published 2009-01-01
    “…A series of experiments were conducted in a batch system to evaluate the effect of system variables. The effect of pH, initial Cr(VI) concentration, contact time, adsorbent dosage and temperature were considered. …”
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  14. 3634

    Optimization of Ultrasound-Assisted Extraction of Morphine from Capsules of Papaver somniferum by Response Surface Methodology by Ibrahim Bulduk, Bahdışen Gezer, Mustafa Cengiz

    Published 2015-01-01
    “…For this purpose, solvent/solid ratio (10–20 mL/500 mg sample), pH (1–13), time (30–60 min), and temperature (30–50°C) were chosen as experimental variables. …”
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    Article
  15. 3635

    A hybrid long short-term memory with generalized additive model and post-hoc explainable artificial intelligence with causal inference for air pollutants prediction in Kimberley, S... by Israel Edem Agbehadji, Ibidun Christiana Obagbuwa

    Published 2025-08-01
    “…Though the causal effect analysis show no p-values (&gt;0.88) for variables, the experiment results show that LSTM-GAM-xAI guaranteed the lowest MSE values across different time-steps.…”
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  16. 3636

    Sky Image-Based Localized, Short-Term Solar Irradiance Forecasting for Multiple PV Sites via Cloud Motion Tracking by Lasanthika H. Dissawa, Roshan I. Godaliyadda, Parakrama B. Ekanayake, Ashish P. Agalgaonkar, Duane Robinson, Janaka B. Ekanayake, Sarath Perera

    Published 2021-01-01
    “…Two inexpensive sky camera systems were developed and placed in two different locations to obtain sky images for cloud tracking and cloud-based heights. Then, irradiance values for onsite and for a PV site located with a distance of 2 km from the main camera were forecasted for 1 minute, 5 minutes, and 15 minutes ahead of real-time. …”
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    Article
  17. 3637

    Alkaline fusion approach to Zeolite Y synthesis from Ahoko Metakaolin: computer-aided simulation, response surface and ANFIS modelling with uncertainty quantification by Kazeem K. Salam, Olusola E. Oke, Dauda O. Araromi, Mujidat O. Aremu, Idayat A. Olowonyo, Monsuru O. Dauda, Akinola D. Ogunsola

    Published 2025-03-01
    “…Comparison of RSM and ANFIS models for the prediction of the utility, and the ratios of WWG and SM show that both model types can predict the responses with R2 values ranging between 0.998 and 1. The uncertainty analysis values obtained from the MCS for the three responses showed that the obtained uncertainty values are negligible to developed models. …”
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    Article
  18. 3638

    EFFECT OF THE C:N RATIO ON Daphnia magna (Straus, 1820) PRODUCTION USING TILAPIA FARMING WASTEWATER by Géssica Cavalcanti Pereira MOTA, Clarissa Vilela Figueiredo da Silva CAMPOS, Laenne Barbara Silva de MORAES, David Nunes Aguiar BRUZACA, Luís Otávio BRITO, Alfredo Olivera GÁLVEZ

    Published 2019-09-01
    “…The following growth variables of the Daphnia were also evaluated: Maximum average density (MAD), Maximum density day (MDD), Specific growth rate (SGR), Doubling time (DT) and yield (Y). …”
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  19. 3639

    Mathematical Modelling with the Exact Solution of Three Different Bioheat Conduction Models of a Skin Tissue Shocked by Thermoelectrical Effect by Eman A. N. Al-Lehaibi

    Published 2023-01-01
    “…The numerical results demonstrate the values of the voltage, resistance, electric shock time, and dual-phase-lag time parameters which have significant influences on the distributions of the dynamic and conductive temperature rise through the skin tissue.…”
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  20. 3640

    Advancing Mg/Ca Analysis of Coralline Algae as a Climate Proxy by Assessing LA‐ICP‐OES Sampling and Coupled Mg/Ca‐δ18O Analysis by Tricia Light, Branwen Williams, Jochen Halfar, Alicia Hou, Zoltan Zajacz, Alexandra Tsay, Walter Adey

    Published 2018-09-01
    “…While Mg/Ca data across all specimens captured seasonal sea surface temperature (SST) variability, Mg/Ca values differed in replicate transects within skeleton formed at the same time regardless of technique used. …”
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