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  1. 1161

    Development of data-driven machine learning models and their potential role in predicting dengue outbreak by Bushra Mazhar, Nazish Mazhar Ali, Farkhanda Manzoor, Muhammad Kamran Khan, Muhammad Nasir, Muhammad Ramzan

    Published 2024-11-01
    “…This involves gathering data on various climatic factors, including temperature, rainfall, relative humidity, and wind speed, along with monthly records of dengue cases. The study functions as an efficient warning system, enabling the anticipation of dengue outbreaks. …”
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  2. 1162

    Two Weighted Fuzzy Goal Programming Methods to Solve Multiobjective Goal Programming Problem by Mousumi Gupta, Debasish Bhattacharjee

    Published 2012-01-01
    “…Here, the relative weights represent the relative importance of the objective functions. The proposed methods involve one additional goal constraint by introducing only underdeviation variables to the fuzzy operator λ (resp., 1-λ), which is more efficient than some well-known existing methods such as those proposed by Zimmermann, Hannan, Tiwari, and Mohamed. …”
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  3. 1163

    Evaluating the level of digitalization of the innovation process with artificial intelligence approach in the digital transformation of knowledge-based companies by ali Bagheri, reza radfar, sepehr ghazinoory

    Published 2025-02-01
    “…In this method, the number of membership functions is 5 functions representing very low, low, medium, high and very high. …”
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  4. 1164

    An enhanced buck-boost converter for photovoltaic diagnosis application: Accurate MPP tracker and I-V tracer by Yassine Chouay, Mohammed Ouassaid

    Published 2025-03-01
    “…In normal operation, the converter is controlled by neural network (NN) controller to efficiently extract maximum power point (MPP). However, in the event of a system failure, the converter automatically transitions to variable load mode to capture different points on the current-voltage (I-V) curve. …”
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  5. 1165

    Fuzzy System for the Quality Assessment of Educational Multimedia Edition Design by Vsevolod Senkivskyy, Liubomyr Sikora, Nataliia Lysa, Alona Kudriashova, Iryna Pikh

    Published 2025-04-01
    “…A multilevel model of fuzzy logical inference is constructed, representing the dependency between quality factors. Membership functions for linguistic variables are formed and their weight coefficients are determined using pairwise comparison matrices. …”
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  6. 1166

    Improved Sliding Mode Active Disturbance Rejection Control for Single-inductance Dual-output Buck Converter by HUANG Jinfeng, ZHOU Jie

    Published 2025-07-01
    “…ObjectiveThe single-inductance dual-output (SIDO) converter has gained increasing attention due to its reduced magnetic component count, compact size, low cost, and high efficiency. However, because both output branches share a single inductor, significant cross-coupling arises during input voltage transients and load disturbances, degrading output voltage performance. …”
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  7. 1167

    Study of the possibility of controlling the production of low-molecular-weight heparin preparations by domestic test systems (review) by A. L. Berkovsky, E. V. Sergeeva, A. V. Suvorov

    Published 2024-09-01
    “…The data on the wide clinical use of low-molecular-weight heparin (LMWH) preparations are presented, necessitating the need for efficient and high-quality production of appropriate pharmaceuticals. …”
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  8. 1168

    The Analysis of the Effective Factors on Urban Blight in District 3, Region 12, Tehran City by Hossein Mansourian, Ahmad Pour Ahmad, Hasan Ashouri

    Published 2019-09-01
    “…Since the old city or the central part of today’s cities has not been able to upgrade its previous efficient, dynamic, and satisfactory structure to today’s conditions, it has experienced a reduction in environmental quality and, in the broad sense, decay, deterioration, and blight. …”
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  9. 1169

    Explainable AI-driven assessment of hydro climatic interactions shaping river discharge dynamics in a monsoonal basin by Prashant Parasar, Akhouri Pramod Krishna

    Published 2025-07-01
    “…The main findings of this study are (1) KAN demonstrated high predictive performance with root mean squared error (RMSE) values ranging from 42.7 to 58.3 m3/s, Nash–Sutcliffe efficiency (NSE) between 0.80 and 0.87, mean absolute error (MAE) between 28.9 to 52.7 and R2 values between 0.84 and 0.90 across stations. (2) SHAP based feature contribution analysis identified Relative humidity (hurs), specific humidity (huss), and temperature (tas) as key predictors, while (pr) showed limited contribution due to spatial inherent inconsistencies in GCM precipitation data. (3) The bootstrapped SHAP distributions highlighted substantial variability in feature importance, particularly for humidity variables, revealing station specific uncertainty patterns in model interpretation. (4) The KAN framework results indicate strong temporal alignment and physical realism, confirming KAN’s robustness in capturing seasonal discharge dynamics and extreme flow events under monsoon influence environments. (5) In this study KAN with SHAP (SHapley additive exPlanations) is implemented for hydrological modeling under monsoon-influenced and data-limited regions such as SRB, offering improved accuracy, functional precision and efficiency compared to traditional models. …”
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  10. 1170
  11. 1171

    The Hydrodynamic Performance of a Vertical-Axis Hydro Turbine with an Airfoil Designed Based on the Outline of a Sailfish by Aiping Wu, Shiming Wang, Chenglin Ding

    Published 2025-06-01
    “…Results indicated the centrifugal subsystem demonstrated peak hydrodynamic efficiency at a 25° installation angle, whereas the axial-flow module achieves optimal performance at 35° blade orientation. …”
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  12. 1172

    A Comparative Study of Deep Reinforcement Learning Algorithms for Urban Autonomous Driving: Addressing the Geographic and Regulatory Challenges in CARLA by Yechan Park, Woomin Jun, Sungjin Lee

    Published 2025-06-01
    “…To evaluate the adaptability of each algorithm to geographical variability and complex traffic laws, scenario-specific reward and penalty functions were carefully designed and incorporated. …”
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  13. 1173

    ASSESSING THE FARMERS’ SATISFACTION WITH THE PARTICIPATORY COCONUT PLANTING PROJECT (PCPP) USING REGRESSION ANALYSIS by Leomarich F. CASINILLO

    Published 2023-01-01
    “…The data were summarized through descriptive calculations and determine the association of variables with the aid of regression analysis. Results of the study have depicted that coconut farmers, on average, are satisfied with the different functions of PCPP in regard to their farming activities. …”
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  14. 1174

    Combined analysis of 16S rRNA gene sequencing data reveals core vaginal bacteria across livestock species by Lucille C. Jonas, Lucille C. Jonas, Curtis R. Youngs, Stephan Schmitz-Esser, Stephan Schmitz-Esser

    Published 2025-02-01
    “…Recent publications have uncovered a high degree of variability of the livestock vaginal microbiota, making it difficult to focus functional research on individual microorganisms. …”
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  15. 1175

    Decarbonisation pathways for industrial clusters through multi-energy systems by Ugochukwu Ngwaka, Yousaf Khalid, Janie Ling-Chin, John Counsell, Ruben Pinedo-Cuenca, Huda Dawood, Andrew J. Smallbone, Nashwan Dawood, Anthony P. Roskilly

    Published 2025-06-01
    “…Given the complex and nonlinear interconnections among systems within a multi-energy cluster, this study extends the dynamic multi-vector methodology to multi-energy system clusters, representing variables as nodes and converting them into transfer functions for system integration. …”
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  16. 1176

    Eco-engineered remediation: Microbial and rhizosphere-based strategies for heavy metal detoxification by Arun Karnwal, Gaurav Kumar, Alaa El Din Mahmoud, Joydeep Dutta, Rattandeep Singh, Abdel Rahman Mohammad Said Al-Tawaha, Tabarak Malik

    Published 2025-01-01
    “…Moreover, a detailed understanding of plant–microbe interactions and the role of secondary metabolite signalling in the rhizosphere is essential to improve remediation efficiency. Future strategies should prioritize the application of functional genomics, developing bioinoculants tailored to specific environmental conditions, and implementing robust ecological risk assessments for GEMs. …”
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  17. 1177

    Mathematical crystal chemistry II: Random search for ionic crystals and analysis on oxide crystals registered in ICSD by Ryotaro Koshoji

    Published 2025-07-01
    “…Additionally, discrete variables and constraint functions, which give a choice of creatable types of geometrical constraints depending on the spatial order of atoms, are implemented to formalize the feasible atomic environment, such as the composition of coordination polyhedra, resulting in acceleration of structure search and decrease of the number of local minima. …”
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  18. 1178

    A transient homotypic interaction model for the influenza A virus NS1 protein effector domain. by Philip S Kerry, Juan Ayllon, Margaret A Taylor, Claudia Hass, Andrew Lewis, Adolfo García-Sastre, Richard E Randall, Benjamin G Hale, Rupert J Russell

    Published 2011-03-01
    “…While RBD dimerization seems functionally conserved, two possible apo ED dimers have been proposed (helix-helix and strand-strand). …”
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  19. 1179

    Analysis of Surface Roughness and Machine Learning-Based Modeling in Dry Turning of Super Duplex Stainless Steel Using Textured Tools by Shailendra Pawanr, Kapil Gupta

    Published 2025-06-01
    “…One of the most critical aspects of turning, and machining in general, is the surface roughness of the finished product, which directly influences the performance, functionality, and longevity of machined components. …”
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  20. 1180

    Building electrical consumption patterns forecasting based on a novel hybrid deep learning model by Nasser Shahsavari-Pour, Azim Heydari, Farshid Keynia, Afef Fekih, Aylar Shahsavari-Pour

    Published 2025-06-01
    “…Specifically, the proposed model comprises three key components: (i) a mutual information-based feature selection method to identify the most significant input variables influencing energy consumption; (ii) a variational mode decomposition (VMD) approach to decompose the original energy consumption signal into intrinsic mode functions (IMFs), capturing relevant trends and eliminating noise; and (iii) a long short-term memory (LSTM) neural network to perform time-series forecasting of the target energy consumption values. …”
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