Intuition-guided Reinforcement Learning for Soft Tissue Manipulation with Unknown Constraints by Xian He, Shuai Zhang, Jian Chu, Tongyu Jia, Lantao Yu, Bo Ouyang

“…Compared with the SAC algorithm, the proposed framework can markedly increase the robotic soft tissue manipulation ability by automatically adjusting the regulator factors.…”
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Human-in-the-Loop Modeling and Bilateral Skill Transfer Control of Soft Exoskeleton by Jiajun Xu, Kaizhen Huang, Mengcheng Zhao, Jinfu Liu

“…Soft exoskeletons (exosuits) are expected to provide a comfortable wearing experience and compliant assistance compared with traditional rigid exoskeleton robots. …”
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Design and Dimension Optimization of Rigid–Soft Hand Function Rehabilitation Robots by Rui Zhang, Meng Ning, Yuqian Wang, Jun Yang

“…This study develops a rigid–soft coupling rehabilitation robot integrating linkage mechanisms with soft components. …”
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Soft Actor-Critic Approach to Self-Adaptive Particle Swarm Optimisation by Daniel von Eschwege, Andries Engelbrecht

“…Particle swarm optimisation (PSO) is a swarm intelligence algorithm that finds candidate solutions by iteratively updating the positions of particles in a swarm. …”
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Development and evaluation of a soft pneumatic muscle for elbow joint rehabilitation by Mostafa Orban, Mostafa Orban, Mostafa Orban, Kai Guo, Kai Guo, Caijun Luo, Caijun Luo, Hongbo Yang, Hongbo Yang, Karim Badr, Karim Badr, Mahmoud Elsamanty, Mahmoud Elsamanty

“…In this study, the design, fabrication and systematic evaluation of a soft pneumatic muscle for elbow rehabilitation are presented. …”
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Study of spectral overlap and heterogeneity in agriculture based on soft classification techniques by Shubham Rana, Salvatore Gerbino, Petronia Carillo

“…The analysis involves preprocessing the image data, calculating the vegetation indices, and applying the MPCM algorithm to perform soft classification, allowing pixels to belong to multiple classes with varying degrees of membership. …”
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A Hybridization of Modified Rough Bipolar Soft Sets and TOPSIS for MCGDM by Saba Ayub, Muhammad Shabir, Rizwan Gul

“…In this technique, we first introduce an aggregated parameter matrix with the help of modified bipolar soft lower and upper matrices to identify the positive and negative ideal solutions. …”
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Isotopic Properties of Neutrosophic Soft Quasigroup and Its Application in Decision-making by Benard Osoba, Oyebo Tunde Yakub, Abdulkareem Abdulafeez Olalekan, Oyewole Oluwapamilerin, Adenibuyan Micheal Tokunbo, Oluwatobi Balogun, Adekola Lanrewaju Olumide

“…This research expands the concept of the Q-set to a groupoid, which facilitates the development of an algorithm for Q-neutrosophic soft quasigroups. The definitions of isotopism and homomorphism for Q-neutrosophic soft quasigroups are introduced, revealing that every isotope of a Qneutrosophic soft quasigroup is indeed a Q-neutrosophic soft quasigroup. …”
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A New Approach to the Criteria-Weighted Fuzzy Soft Max-Min Decision-Making Method and Its Application to a Performance-Based Value Assignment Problem by Samet Memiş, Serdar Enginoğlu

“…A., Mohamad, D., A decision making method using fuzzy soft sets, Malaysian Journal of Fundamental and Applied Sciences, 2013, 9(2), 99-104] has been configured to operate in the fuzzy parameterized fuzzy soft matrices (fpfs-matrices) space by Enginoğlu and Memiş [A configuration of some soft decision-making algorithms via fpfs-matrices, Cumhuriyet Science Journal, 2018, 39(4), 871-881] faithfully to the original. …”
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A New Approach to Group Decision-Making Method Based on TOPSIS Under Fuzzy Soft Environment by Faruk Karaaslan, Samet Memiş, Serdar Enginoğlu

“…In 2015, the group decision-making method based on TOPSIS under fuzzy soft environment was defined and applied to a decision-making problem by Eraslan and Karaaslan. …”
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New Topological Approaches to Generalized Soft Rough Approximations with Medical Applications by Mostafa K. El-Bably, Muhammad I. Ali, El-Sayed A. Abo-Tabl

“…There are many approaches to deal with vagueness and ambiguity including soft sets and rough sets. Feng et al. initiated the concept of possible hybridization of soft sets and rough sets. …”
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A hybrid elastic-hyperelastic approach for simulating soft tactile sensors by Berith Atemoztli De la Cruz Sánchez, Jean-Philippe Roberge

“…A significant challenge for simulating tactile sensors is balancing the trade-off between accuracy and processing time in simulation algorithms and models. To address this, we propose a hybrid approach that combines elastic and hyperelastic finite element simulations, complemented by convolutional neural networks (CNNs), to generate synthetic tactile maps of a soft capacitive tactile sensor. …”
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Soft voting ensemble model to improve Parkinson’s disease prediction with SMOTE by Jumanto Unjung, Rofik Rofik, Endang Sugiharti, Alamsyah Alamsyah, Riza Arifudin, Budi Prasetiyo, Much Aziz Muslim

“…This study demonstrates that implementing the soft-voting ensemble-SMOTE method can enhance the model's predictive accuracy.…”
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Optimizing Cardiovascular Risk Assessment with a Soft Voting Classifier Ensemble by Ammar Oad, Zulfikar Ahmed Maher, Imtiaz Hussain Koondhar, Karishima Kumari, Hammad Bacha

“…The proposed ensemble soft voting classifier employs an ensemble of seven machine learning algorithms to provide binary classification, the Naïve Bayes K Nearest Neighbor SVM Kernel Decision Tree Random Forest Logistic Regression and Support Vector Classifier. …”
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Reinforcement learning-based multi-model ensemble for ocean waves forecasting by Weinan Huang, Xiangrong Wu, Xiangrong Wu, Haofeng Xia, Haofeng Xia, Haofeng Xia, Xiaowen Zhu, Yijie Gong, Xuehai Sun

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Modelling Enterprise’s Coordinated Development Strategy with a Soft Fuzzy Rough Set by Tongtong Wang, Jianing Cui

“…Furthermore, we use training methods and soft fuzzy rough sets’ learning algorithm to calculate, and the evaluating indicator rough set is constructed with a three-tier model structure. …”
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Reduced complexity hard‐ and soft‐input BCH decoding with applications in concatenated codes by Jürgen Freudenberger, Daniel Nicolas Bailon, Malek Safieh

“…For the algebraic decoding we demonstrate that Peterson's algorithm can be more efficient than the Berlekamp–Massey algorithm for single, double, and triple error correcting BCH codes. …”
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Metallic Artifacts’ Reduction in Microtomography Using the Bone- and Soft-Tissue Decomposition Method by Jan Juszczyk, Jakub Pałachniak, Ewa Piętka

“…This paper proposes a new method for eliminating metallic artifacts, applying a bone- and soft-tissue decomposition (BSTD) algorithm to microtomography raw data before the reconstruction process. …”
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Development and Verification of Control Strategy to Avoid Soft Tower Resonance for Wind Turbine by LIU Hongwen, WANG Dian, JIANG Tao, WAN Yubing, ZHAI Dayong, LU Shixin

“…However, because of the intersection of tower first-order natural frequency with rotor speed 1P, there is a risk of resonance. Therefore, a soft tower control algorithm named speed exclusion zone controller is designed relying on the H125 high tower of 2MW D121 type wind turbine, which can realize speed crossing through adaptive control. …”
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Fault recovery strategy for urban distribution networks using soft open points by Liangsheng Lan, Guangqi Liu, Sitong Zhu, Min Hou, Xinrui Liu

“…By employing a binary particle swarm optimisation algorithm, this method effectively improves load recovery, reduces the number of switching operations, and minimises network loss. …”
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