Statistical learning-driven parameter tuning in injection molding using modified simplex method by Pongchanun Luangpaiboon, Walailak Atthirawong, Anucha Hirunwat, Pasura Aungkulanon

“…Nonlinear interactions and quality inconsistencies are frequently encountered by existing methods. The Statistical Learning-Driven Modified Simplex Method (SLMSM) is a novel hybrid optimization framework that is introduced to resolve this gap. …”
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A Rapid Computational Method for Quantifying Inter-Regional Air Pollutant Transport Dynamics by Luoqi Yang, Guangjie Wang, YeGui Wang, Yibai Wang, Yongjing Ma, Xi Zhang

“…The model integrates high-resolution numerical simulations, Geographic Information System (GIS) capabilities, and advanced statistical evaluation metrics with boundary pixel decomposition methods to effectively characterize complex pollutant transport dynamics while ensuring computational efficiency. …”
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SGM-EMA: Speech Enhancement Method Score-Based Diffusion Model and EMA Mechanism by Yuezhou Wu, Zhiri Li, Hua Huang

“…Especially when processing out-of-dataset noisy speech, the proposed method achieved excellent speech enhancement results compared to other methods, demonstrating the model’s strong generalization capability. …”
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Design of an Iterative Method for Malware Detection Using Autoencoders and Hybrid Machine Learning Models by Rijvan Beg, R. K. Pateriya, Deepak Singh Tomar

“…Traditional detection and analysis methods face threats of data high-dimensionality, lack of strength against adversarial attacks, and non-efficient use of unlabeled data samples. …”
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Fast Reflectance Spectral Profile Reconstruction Method for Full-waveform Hyperspectral LiDAR by Hui SHAO, Hulong ZHANG, Hui DAI, Yuwei CHEN, Long SUN, Heng XU, Xingyun LI

“…The direct transmission of information from the full-waveform signals to the reconstruction of the reflectance spectral profiles is a more efficient approach. Therefore, we propose an echo intensity correction method based on HSL full-waveform data for the rapid generation of reflectance spectral profiles of targets. …”
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Implementation of the Prototype Method in Developing a Questionnaire Information System for Integrated Survey Services by Rhoedy Setiawan, Zainur Romadhon, Alvin Rainaldy Hakim

“…This study aims to design and develop a centralized questionnaire information system to improve survey management efficiency. Using the prototype method, the system was developed in two cycles: the first cycle included core features such as a dashboard, questionnaire management, reporting, and a login system, while the second cycle refined functionalities, including input validation, answer variations, search filters, and report export capabilities. …”
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Optimization of Domestic Wastewater Treatment with Biological Aerated Filter (BAF) Method Based on Bioball by Khalimatus Sa'diyah, Mochammad Agung Indra Iswara, Listiyana Candra Dewi, Febby Anisa Putri

“…Obtaining higher process efficiency required a combination of wastewater treatment methods.…”
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Novel Dynamic Chord Reference Method in Railway Track Irregularity Measurement Based on Vehicle by Yan Wang, Wenbo Zhao, Shibin Wei, Jiyou Fei, Fei Yang, Peng Dai

“…The proposed method aims to improve the accuracy and efficiency of CRM assessments, particularly those requiring real-time or continuous inspection. …”
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Stabilized Discretization in Spline Element Method for Solution of Two-Dimensional Navier-Stokes Problems by Neng Wan, Ke Du, Tao Chen, Sentang Zhang, Gongnan Xie

“…In terms of the poor geometric adaptability of spline element method, a geometric precision spline method, which uses the rational Bezier patches to indicate the solution domain, is proposed for two-dimensional viscous uncompressed Navier-Stokes equation. …”
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Analytical approximate solutions of some fractional nonlinear evolution equations through AFVI method by Md. Asaduzzaman, Faruk Özger, Md. Zulfikar Ali

“…In this article, we construct and investigate a new fractional variational iteration technique which is named as AFVI method. …”
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A temporal fusion method for modeling the rate of penetration during deep geological drilling by Yang ZHOU, Chengda LU, Min WU, Xin CHEN, Ningping YAO, Haitao SONG, Youzhen ZHANG

“…However, deep geological drilling faces challenges such as nonlinearity, non-convex optimization, multiple operating conditions, and temporal variations. Consequently, traditional modeling methods are difficult to adapt to complex geologic environments. …”
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Point-Symmetric Extension-Based Interval Shannon-Cosine Spectral Method for Fractional PDEs by Ruyi Xing, Yanqiao Li, Qing Wang, Yangyang Wu, Shu-Li Mei

“…Compared with Shannon and Shannon-Gabor wavelet quasi-spectral methods, the novel scheme has stronger applicability to the shockwave appeared in the solution besides the higher numerical accuracy and efficiency.…”
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Necessary reporting of reaction yield for method evaluation: Considering Knoevenagel synthesis of ferulic acid by Hanah T. Rheay, David L. Compton, Korey J. Brownstein, Christopher D. Skory

“…The initial goal of identifying a Knoevenagel reaction method to adapt toward continuous production of ferulic acid was hindered by the inconsistent reporting of yield metrics across relevant literature. …”
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A New Customized Measurement System for a Non-Contact, Enhanced Thermometric Method by Luca Evangelisti, Edoardo De Cristo, Salvatore Monteleone, Claudia Guattari, Paola Gori, Ivan Pini, Tullio de Rubeis, Dario Ambrosini

“…This study introduces a novel, low-cost, non-contact measurement system for heat flux estimation based on an enhanced thermometric method. The customized system was designed and assembled to implement a non-contact, indirect approach for heat flux assessment. …”
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Finite Element Method Stress Analysis of Kammprofile Gasket Defects and Evaluation of the Sealing Performance by Muhammad Afiq Azmansah, Ahmad Majdi A Rani, Fudhail Abd Munir

“…Therefore, the Finite Element Method (FEM) analysis using static structural was developed to analyse the influence of dimension variations and defects, specifically on pitch, serration depth and thickness of the Kammprofile gasket that drive the leakage in the flange gasketed joints by finding the compressive strains, maximum and average contact stresses. …”
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Vehicle detection method based on multi-layer selective feature for UAV aerial images by Yinbao Ma, Yuyu Meng, Jiuyuan Huo

“…For the detection head, a Generalized Wasserstein Distance Loss (GWDLoss) function is proposed to quantify positional and scale discrepancies, improving the adaptability of bounding box regression to geometric variations. Extensive experiments on the VisDrone and Vehicle datasets demonstrate that the proposed method reduces the number of parameters by 22.9% and achieves mAP@50–95 improvements of 4.5% and 7.3%, respectively, over YOLO11n. …”
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TOPSIS model with combination weight for demand assessment of flood emergency material supplies by Bingbing Xu, Wenguang Yang, Lanxiang Yi, Dekun Kong, Ruitian Liu

“…The objective weights and subjective weights of the evaluation indicators are calculated using the coefficient of variation method and the order relation analysis method, respectively. …”
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A comparison of tissue preparation methods for protein extraction of cocoa (Theobroma cacao L.) pod by Ascensión Martínez-Márquez, Jaime Alfredo Morante-Carriel, Roque Bru-Martínez

“…Cocoa has a very high level of interfering substances, such as polysaccharides and phenolic compounds that could prevent the isolation of suitable protein. Efficient methods of protein extraction are a priority to successfully apply proteomic analyses. …”
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Improving genomic prediction accuracy for methane emission and feed efficiency in sheep: integrating rumen microbial PCA with host genomic variation using neural network GBLUP (NN-... by Setegn Worku Alemu, Timothy P. Bilton, Patricia L. Johnson, Benjamin J. Perry, Hannah Henry, Ken G. Dodds, John C. McEwan, Suzanne J. Rowe

“…For the second objective, the NN-GBLUP model incorporating PCA-reduced RMC data improved prediction accuracy compared to standard GBLUP methods. Prediction accuracy for methane emissions increased from 0.09 to 0.30 in train-test validation and from 0.15 to 0.27 in five-fold cross-validation using PCA components explaining 25% of total RMC variation. …”
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A Comprehensive Investigation of Anomaly Detection Methods in Deep Learning and Machine Learning: 2019–2023 by Shalini Kumari, Chander Prabha, Asif Karim, Md. Mehedi Hassan, Sami Azam

“…Many researchers have proposed numerous methods and worked in the area of AD. Multiple anomalies and considerable intraclass variation make industrial datasets tough. …”
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