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  1. 981

    Energy Management of Industrial Energy Systems via Rolling Horizon and Hybrid Optimization: A Real-Plant Application in Germany by Loukas Kyriakidis, Rushit Kansara, Maria Isabel Roldán Serrano

    Published 2025-07-01
    “…Industrial energy systems are increasingly required to reduce operating costs and CO<sub>2</sub> emissions while integrating variable renewable energy sources. Managing these objectives under uncertainty requires advanced optimization strategies capable of delivering reliable and real-time decisions. …”
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    Article
  2. 982

    Notice of Violation of IEEE Publication Principles: VVC/H.266 Intra Mode QTMT Based CU Partition Using CNN by Sameena Javaid, Safdar Rizvi, Muhammad Talha Ubaid, Abdullah Tariq

    Published 2022-01-01
    “…Finally, a variable threshold decision system is established to achieve the targeted low complexity and RD performance. …”
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    Article
  3. 983

    Multi-period optimisation of flexible natural gas production network infrastructure with an operational perspective: A mixed integer linear programming approach by Noor Yusuf, Roberto Baldacci, Ahmed AlNouss, Tareq Al-Ansari

    Published 2024-10-01
    “…Notably, the case considering fixed and operating cost variables together as a single cost variable in the objective function, referred to as annualised cost (case C), offered optimal cost quantification with relaxed technical constraints. …”
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  4. 984

    Impact of municipal wastewater use on urban and peri‑urban agricultural productivity: the endogenous treatment-effects approach by Mohammed Abdulai, Mohammed Tanko, Alhassan Andani

    Published 2025-06-01
    “…Using survey data from 416 vegetable farmers, we employed a semi-log production function augmented with an endogenous binary-treatment effect equation to estimate the drivers and impact of MWW use on value of vegetable output, accounting for selection bias and omitted variable problem. …”
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  5. 985

    Machine learning with hyperparameter optimization applied in facies-supported permeability modeling in carbonate oil reservoirs by Watheq J. Al-Mudhafar, Alqassim A. Hasan, Mohammed A. Abbas, David A. Wood

    Published 2025-04-01
    “…On the other hand, highly permeable fractures function as the main flow conduits within such reservoirs. …”
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  6. 986

    PileBetaGR: An R-based integrative tool for predicting the geometric reliability index of piles using load-displacement curves by Xing Zheng Wu

    Published 2025-05-01
    “…The application compiles a series of functions for analyzing load-displacement data: (i) a power law regression is used to fit each load-displacement curve, yielding a set of regression parameters for the site; (ii) a normal copula model is established to fit the joint distribution of these regression variables, allowing a geometric reliability index to be computed; (iii) the critical environmental contour is determined based on the joint probability density function and the limit state function. …”
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  7. 987

    The Effect of Hydraulic Partitioning on Prediction the Rate of Bed Load Transport in Gravel-bed Rivers using Support Vector Machine by Kiyoumars Roushangar, Mohammad Hosseini, Saman Shahnazi

    Published 2019-03-01
    “…After optimization of parameters for kernel function, the bed load transport rate was predicted and obtained results from different models were investigated in terms of correlation coefficient (R), Root mean square error (RMSE) and Nash-Sutcliffe (NSE). in order to assess the capability of SVM in quantification of bed load under varied hydraulic conditions, Froude number (Fr) and bed slope of channel (S0) were selected as a parameters describing the hydraulic conditions and median diameter of the sediment particles (D50) and shear Reynolds number (Re*) were considered as a representative of sediment characteristic. …”
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  8. 988

    Optimal Control Problem of Converter Steelmaking Production Process Based on Operation Optimization Method by Jun Zhang

    Published 2015-01-01
    “…The optimal control indicator is determined via current state of converter smelting production process, and the set values of operation variable would control converter production. Relationship between various operating variables, current temperature, and carbon content is constructed through operation analysis of a great deal of actual production data; then, the dynamic optimal control indicator is derived from historical excellent smelting data; finally, the dynamic operation optimization model is built by taking the minimum deviation between the current data—molten steel temperature and carbon content—and optimal data which are determined by the optimal control indicator as objective function. …”
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    Article
  9. 989

    Response Surface Optimization of CuS Photocatalytic Process Using UV‐vis Irradiation for Wastewater Treatment by Caressa Munien, Emmanuel Kweinor Tetteh, Sudesh Rathilal

    Published 2025-06-01
    “…Thus, this study aimed to optimize the operating parameters of the photocatalytic degradation process using copper sulphide (CuS) and UV‐visible irradiation via response surface methodology (RSM) to determine the relationship that exists between the most significant factors and the water quality parameters. The efficiency of the CuS photocatalyst was evaluated as a function of three input variables viz. …”
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  10. 990

    The effects of IT capability and distribution competence on business performance of retailers in Omnichannel by Anh T.D. Nguyen

    Published 2025-03-01
    “…Results: Information technology capability and distribution competence have a direct impact on business performance, with beta coefficients of 0.198 and 0.271, respectively. Meanwhile, the regression coefficients of indirect relationships through mediating variables are 0.204 and 0.097, respectively. …”
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    Article
  11. 991

    Extreme combination of wind effects and analysis of wind load characteristics for low-rise buildings by Haiwei Guan, Yuji Tian, Yuliang Qi, Weihu Chen

    Published 2025-06-01
    “…Based on transcendental probability theory, the probability density functions of two non-Gaussian scalar sums of wind effects are derived from the relationship between the probability density of the sum of random variables and the joint probability density function of sub-random variables by Hermite polynomial transformation. …”
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  12. 992

    The Fuzzy Response Surface Reliability Analysis Method of Turbine Blades by PAN Cheng-yi, WEI Wen-long, ZHANG Chun-yi

    Published 2019-08-01
    “…The analysis result shows that the blade reliability indexes decrease with the increase of fuzzy coefficient. Compared with the traditional method based on random variables, this method is more reasonable for the description of uncertainty, and the evaluation of reliability is more accurate theoretically.…”
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  13. 993

    Creating Balance on Bandwidth Consumption using Network Coding in Wireless Sensor Networks by Ehsan Kharati

    Published 2024-02-01
    “…For this purpose, we need to calculate the derivative of the Lagrangian function relative to its variables, in order to determine the condition as a multi-excited multi-equation device. …”
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  14. 994

    Fusion of Multimodal Audio Data for Enhanced Speaker Identification Using Kolmogorov-Arnold Networks by Aryaman Tamotia, Dhruv Shantu Karmokar, Rethi Komal, K. Khadar Nawas, A. Shahina, A. Nayeemulla Khan

    Published 2025-01-01
    “…One of the critical innovations within this design is a class of trainable activation functions that eliminate the need for traditional weight parameters, thereby providing scalable and computationally efficient solutions. …”
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  15. 995

    Fast 3D localization of nano-objects in wide-field interferometric scattering microscopy via vectorial diffraction model-derived analytical fitting by Liaoliao Wei, Caroline Livan Anyi, Huakun Li, Haitao Nie, Bihan Wen, Tong Ling

    Published 2025-05-01
    “…The simplified analytic function includes a quadratically scaling amplitude term and a linearly scaling phase term, both of which change with the nano-object’s axial position. …”
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  16. 996

    Bayesian inference for peak feature extraction and prediction of material property in X-ray diffraction data by Ryo Murakami, Taisuke T. Sasaki, Hideki Yoshikawa, Yoshitaka Matsushita, Keitaro Sodeyama, Tadakatsu Ohkubo, Hiroshi Shinotsuka, Kenji Nagata

    Published 2024-12-01
    “…We challenge peak feature extraction in the situation where only the peak function profile is known a priori, without knowledge of the measurement material or crystal structure factor. …”
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  17. 997

    THE PROPOSAL MODEL OF RATIONAL WORKFORCE ASSIGNMENT IN DOKUZ EYLUL UNIVERSITY BY ANALYTIC HIERARCHY PROCESS BASED 0-1 INTEGER PROGRAMMING by Yılmaz GÖKŞEN, Hakan AŞAN, Onur DOĞAN, Mustafa ÜNLÜ, Osman PALA

    Published 2016-11-01
    “…The Assignment model of the type of linear programming models is a mathematical method used to match the right person for the right job. The coefficients of the variables in the objective function of the assignment model constitute potential contributions of employees. …”
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  18. 998

    Estimating Daily Rice Crop Evapotranspiration in Limited Climatic Data and Utilizing the Soft Computing Algorithms MLP, RBF, GRNN, and GMDH by Pouya Aghelpour, Hadigheh Bahrami-Pichaghchi, Farzaneh Karimpour

    Published 2022-01-01
    “…The ETc rates were calculated by seven meteorological variables, the FAO-56 Penman-Monteith equation, and the regional calibrated rice crop coefficient and considered as the reference data. …”
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  19. 999

    On the Nonlinear Forced Vibration of the Magnetostrictive Laminated Beam in a Complex Environment by Nicolae Herisanu, Bogdan Marinca, Vasile Marinca

    Published 2024-12-01
    “…The nonlinear differential equations were studied using an original, explicit, and very efficient technique, namely the optimal auxiliary functions method (OAFM). …”
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  20. 1000

    The Relationship between Optimism and Mindfulness with Cognitive Performance in Older Adults by Sanaz Ghannadi, Morteza Tarkhan

    Published 2025-04-01
    “…Furthermore, 34% of the variance in cognitive function was explained by optimism and mindfulness.Conclusion: Therefore, based on the findings of the present study, it can be concluded that optimism and mindfulness are important variables in predicting cognitive function (p < 0.05).…”
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