Enhanced Prediction and Evaluation of Hydraulic Concrete Compressive Strength Using Multiple Soft Computing and Metaheuristic Optimization Algorithms by Tianyu Li, Xiamin Hu, Tao Li, Jie Liao, Lidan Mei, Huiwen Tian, Jinlong Gu

“…To address this issue, this study introduces a novel hybrid method for predicting concrete compressive strength by integrating multiple soft computing algorithms and the stacking ensemble learning strategy. …”
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Application of selective ensemble learning soft sensor modeling based on GPR in the solar thermal power collection system by Yalu Sun, Kun Ding, Changhai Yang, Zhuxiu Wang

“…In this paper, the ensemble learning soft sensor model is applied to the outlet temperature control of the solar thermal power collection system. …”
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Just-in-time updated DBN BOF steel-making soft sensor model based on dense connectivity of key features by Lu Zongxu, Liu Hui, Chen FuGang, Li Heng, Xue XiaoJun

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Recognition of cancer mediating genes using MLP-SDAE model by Sougata Sheet, Ranjan Ghosh, Anupam Ghosh

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Shared Mobility for Transport and Its Environmental Impact VeSIPreS: A Vehicular Soft Integrity Preservation Scheme for Shared Mobility by Valaenthin Tratter, Mudassar Aslam, Shahid Raza

“…In this work, a novel vehicle attestation scheme called Vehicular Soft Integrity Preservation Scheme (VeSIPreS) is proposed to detect tampering in the software stack of a vehicle and guarantee the upcoming driver that the previous user has not changed the software of the vehicle. …”
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Stacking classifiers based on integrated machine learning model: fusion of CT radiomics and clinical biomarkers to predict lymph node metastasis in locally advanced gastric cancer... by Tong Ling, Zhichao Zuo, Mingwei Huang, Jie Ma, Liucheng Wu

“…Then, using the rad score and clinical biomarkers as input features, we applied simple statistical strategies (relying on a single ML model) and integrated statistical strategies (including classification model integration techniques, such as hard voting, soft voting, and stacking) to predict LN+ post-NAC. …”
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Identification and susceptibility assessment of landslide disasters in the red bed formation along the Nanjian-Jingdong Expressway by Yifan Cao, Zhifang Zhao, Mingchun Wen, Xin Zhao, Dingyi Zhou, Jingyi Qin, Liu Ouyang, Jingyao Cao

“…The red bed strata region is characterized by distinct interbedded soft and hard water–rock properties and significant water sensitivity, resulting in the frequent occurrence of landslide disasters. …”
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Research on a collaborative platform for teaching English in universities based on an intelligent voice system by Junwei Niu, Lijuan Jiang

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Development of an electrical current stimulator for controlling biohybrid machines by Riccardo Collu, Judith Fuentes, Florencia Lezcano, Maria Crespo-Cuadraro, Andrea Bartolucci, Leonardo Ricotti, Lorenzo Vannozzi, Samuel Sánchez, Stefano Lai, Massimo Barbaro

“…Abstract Soft and flexible robotics is an emerging field that attracts a huge interest due to its ability to produce bioinspired devices that are easily adaptable to the environment. …”
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Scaling CO Electrolyzers for Carbon‐Neutral Chemical Synthesis by Wenzhi Teng, Prof. Yuhang Wang

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TAL-SRX: an intelligent typing evaluation method for KASP primers based on multi-model fusion by Xiaojing Chen, Xiaojing Chen, Jingchao Fan, Jingchao Fan, Shen Yan, Longyu Huang, Longyu Huang, Longyu Huang, Guomin Zhou, Guomin Zhou, Jianhua Zhang, Jianhua Zhang

“…Finally, the two machine learning algorithms are fused through a soft voting integration strategy to output the KASP marker typing effect scores. …”
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Image quality evaluation of imaging skins, a novel stretchable X-ray detector for intraoperative tumour imaging by Solène Dietsch, Harry Allan, Lukas Lindenroth, Robert Moss, Agostino Stilli, Danail Stoyanov

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Improved Anthropomorphic Robotic Hand for Architecture and Construction: Integrating Prestressed Mechanisms with Self-Healing Elastomers by Mijin Kim, Rubaya Yaesmin, Hyungtak Seo, Hwang Yi

“…Soft pneumatic robot-arm end-effectors can facilitate adaptive architectural fabrication and building construction. …”
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An Additively Manufactured Fe-3Si Stator for a High-Performance Electrical Motor by Tej N. Lamichhane, Haobo Wang, Chins Chinnasamy, Latha Sethuraman, Fred A. List, Peeyush Nandwana, Jiaqiang Yan, Zheng Gai, Mariappan Parans Paranthaman

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Advanced Machine Learning Methodology for Earthquake Magnitude Forecasting Using Comprehensive Seismic Data by Subhieh El-Salhi, Bashar Igried, Sari Awwad

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Predicting Residential Energy Consumption in South Africa Using Ensemble Models by David Attipoe, Donatien Koulla Moulla, Ernest Mnkandla, Alain Abran

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Efficient Ensemble Learning-Based Models for Plastic Hinge Length Prediction of Reinforced Concrete Shear Walls by Naser Safaeian Hamzehkolaei, Mohammad Sadegh Barkhordari

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Utilizing Cross-Layer Information to Improve Performance in JPEG2000 Decoding by Hannes Persson, Anna Brunstrom, Tony Ottosson

“…We believe that the proposed decoding method utilizing soft information is suitable for a general IP-based network and that it keeps the principles of a layered structure of the protocol stack intact. …”
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Enhanced Hardrock Seismic Imaging Through Multi‐Scale Information‐Guided Unsupervised Learning by Liuqing Yang, Alireza Malehmir, Magdalena Markovic

“…We use one synthetic and two real pre‐stack seismic data sets from two mineral‐endowed regions in Sweden and Canada to test the effectiveness of the proposed network. …”
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Functional Optical Fibers with Tailored Side Emission from Modified Rod‐in‐Tube Preforms by Jan Schröder, Aaron Reupert, Kilian Pollok, Falko Langenhorst, Lothar Wondraczek

“…This technique enables the accurate radial placement of a longitudinal scattering layer within an otherwise homogeneous fiber, leading to superior robustness and mechanical performance in practical application. Soft borosilicate with an extended optical transmission window and a drawing temperature below 1100 °C serves as the base glass for stack manufacture, providing access to a wide variety of active and passive scattering species to be placed into the scattering layer. …”
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