Motor imagery EEG signal classification using novel deep learning algorithm by Sathish Mathiyazhagan, M. S. Geetha Devasena

“…To attain enhanced performance the parameters of the classifier network are optimized using the Far and near optimization (FNO) algorithm. …”
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Nodal Carbon Emission Factor Prediction for Power Systems Based on MDBO-CNN-LSTM by Lihua Zhong, Feng Pan, Yuyao Yang, Lei Feng, Haiming Shao, Jiafu Wang

“…Current carbon emission prediction methods for power systems exhibit limited computational efficiency and inadequate noise immunity under complex operating conditions. …”
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FAST Drift Scan Survey for H i Intensity Mapping. II. Stacking-based Beam Construction of the 19-feed Array at 1.4 GHz by Xinyang Zhao, Yichao Li, Wenxiu Yang, Furen Deng, Yougang Wang, Fengquan Wu, Xin Wang, Xiaohui Sun, Xin Zhang, Xuelei Chen

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Distributionally Robust Operation for Flexible Distribution Networks Considering Multi-correlation of Renewable Power Generation by Zhiwei LIU, Yue MA, Zhicheng SHA, Yunshu SHAO, Yuanfang NIU, Xiaoming DONG, Chengfu WANG

“…Firstly, aiming to minimize active power loss and voltage deviation in the distribution network, an optimal power flow model for flexible distribution networks is derived and constructed, incorporating various coordinated control measures for sources, grids and loads. …”
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Impacts of Phenolic Compounds and Their Benefits on Human Health: Germination by Jonathan Hernández-Miranda, Karen Argelia Reyes-Portillo, Abigail García-Castro, Esther Ramírez-Moreno, Alma Delia Román-Gutiérrez

“…Furthermore, the nutritional profile can naturally be maximized and optimized through the germination process through two key methods: degradation of macromolecules and biosynthesis of metabolites, which favors an increase in the concentration of bioactive compounds, such as phenolic compounds. …”
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Early Detection of Multiwavelength Blazar Variability by Hermann Stolte, Jonas Sinapius, Iftach Sadeh, Elisa Pueschel, Matthias Weidlich, David Berge

“…Based on unsupervised anomaly detection and clustering methods, we differentiate source variability from noisy background activity, without the need for a labeled training data set of flaring states. …”
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Modern approaches to cervical cancer screening (a review) by M. I. Pavliuchenko, Yu. Ya. Krut, V. H. Siusiuka, O. V. Deinichenko

“…The aim – systematization of data from modern scientific sources and own knowledge and experience regarding the problems, advantages and prospects of the development of various methods of diagnosing pathological conditions of the cervix. …”
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Analysis of the Effectiveness of the Pricing Policy of the Organization: Practical Aspect (on the Example of JSC “Verkhnebakansky Cement Plant”) by I. P. Kovaleva

“…This is especially true in conditions of instability, when commercial organizations are forced to look for various ways and methods to optimize their activities. One of such methods is the study of the financial results of the organization’s activities when applying various pricing tactics, for example, using discounts and without them for regular customers. …”
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UAV Path Planning: A Dual-Population Cooperative Honey Badger Algorithm for Staged Fusion of Multiple Differential Evolutionary Strategies by Xiaojie Tang, Chengfen Jia, Zhengyang He

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Sensitivity of biological sewage disposal efficiency functional to parameters of biogen concentration dynamics model by Е. S. Zhmenya, N. S. Buzalo

“…A practical example of the method application for the optimal control problem for an aeration tank (an element of the sewage treatment plant for the biological sewage treatment) is considered.Discussion and Conclusions. …”
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Robust machine learning models for calculating the carbon dioxide desublimation point within natural gas mixtures at low temperature conditions by Walid Abdelfattah, Munthar Kadhim Abosaoda, Dharmesh Sur, Menon Soumya V, Prabhat Kumar Sahu, Kamred Udham Singh, R. Sivaranjani, Rohit Chauhan, Siya Singla, Fereydoon Ranjbar

“…Desublimation at low temperatures offers an efficient method for removing CO2 from gas streams. Accurate prediction of the carbon dioxide desublimation temperature (CDDT) is essential for applying this method in natural gas processing. …”
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Improving Energy Efficiency with Energy Recovery for Propylene Production by Andi Nadhif Athallah Hurairah, Danu Pasa Arkajaya, Tenisyah Ramadhani, Virgi Achmad Fahrezi

“…This study focuses on optimizing energy consumption by integrating heat recovery and reducing the reliance on external energy sources. …”
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The Capital’s Election Criteria Used in the Financial Management of a Company’s Financing Decision by Camelia OPREAN, Constantin OPREAN

“…For this consideration, the capital�s structure and their medium cost is an important profit source for the company, so the profit comes from this source, and not from the exploitation activity or other financial sources or traditional exceptive. …”
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Fractional-Order Swarming Intelligence Heuristics for Nonlinear Sliding-Mode Control System Design in Fuel Cell Hybrid Electric Vehicles by Nabeeha Qayyum, Laiq Khan, Mudasir Wahab, Sidra Mumtaz, Naghmash Ali, Babar Sattar Khan

“…This paper presents a DSMC strategy enhanced with Robust Uniform Exact Differentiators for FCHEV energy management. To optimally tune DSMC parameters, reduce chattering, and address the limitations of conventional methods, a hybrid metaheuristic framework is proposed. …”
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Spatio-Temporal Characteristics and Driving Forces of Landscape Ecological Risks in Highly Urbanized Areas: A Case Study of Suzhou City by Lingyue LU, Dawei SHAO, Dianming WU

“…The formation mechanism, spatio-temporal heterogeneous driving effect and scale response law of LER in highly urbanized areas still need to be systematically explored.MethodsUtilizing multi-source data spanning the period from 1995 to 2020, including Landsat TM/ETM imagery, digital elevation model (DEM) and NASA datasets, this research focuses on exploring the characteristics of spatio-temporal variability of LER and corresponding drivers in Suzhou at the optimal scale, utilizing the LER evaluation model and the geographically and temporally weighted regression (GTWR) framework.Results1) The landscape pattern of Suzhou City is scale-dependent, with significant variations in the landscape pattern index for each land type at the optimal scale. …”
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A Holistic Approach to the Efficient Estimation of Operational Flexibility From Distributed Resources by Nikolaos Savvopoulos, Nikos Hatziargyriou, Hannu Laaksonen

“…This paper presents a novel optimization-based method to estimate the time-dependent flexibility at a primary distribution substation while accounting for the uncertainty of renewable generation. …”
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Synthesis and hydrogen storage application of innovated ternary-based NiFe2O4/Fe2O3/g-C3N4 nanocomposites by facile Pechini sol–gel method by Fatemeh Sadat Razavi, Hanieh Ansarinejad, Safaa Mustafa Hameed, Forat H. Alsultany, Hadil Hussain Hamza, Masoud Salavati-Niasari

“…Abstract Nowadays, renewable and clean energy sources, such as hydrogen, play a key role in the development of societies. …”
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Geometric Accuracy Design and Tolerance Allocation of Precision Horizontal Machining Centers by Lina Wang, Xingxing Liu, Wenjie Tian, Dawei Zhang

“…This paper conducts a comprehensive investigation into the tolerance optimization allocation method for geometric accuracy in precision horizontal machining centers utilizing interval theory. …”
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Dual Function Radar and Communication Waveform Design Based on Sub-pulse Hybrid Modulation by Yu LIU, Junhao ZHANG, Xue YAO, Xianxiang YU, Guolong CUI

“…The proposed SHM method utilizes time-, spectral-, and polarization-domain features from inter-subpulse and intra-subpulse sources to convey information. …”
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Data-Driven Multi-Scale Channel-Aligned Transformer for Low-Carbon Autonomous Vessel Operations: Enhancing CO₂ Emission Prediction and Green Autonomous Shipping Efficien... by Jiahao Ni, Hongjun Tian, Kaijie Zhang, Yihong Xue, Yang Xiong

“…The accurate prediction of autonomous vessel CO₂ emissions is critical for achieving IMO 2050 carbon neutrality and optimizing low-carbon maritime operations. Traditional models face limitations in real-time multi-source data analysis and dynamic cross-variable dependency modeling, hindering data-driven decision-making for sustainable autonomous shipping. …”
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