Showing 161 - 180 results of 2,509 for search '(shift OR soft) algorithm', query time: 0.18s Refine Results
  1. 161

    Ultrasensitive bionic photonic-electronic skin with wide red-shift mechanochromic response by Tianqi Wang, Lei Chen, Haogeng Liu, Haoran Zhu, Zijie Zeng, Yixin Lu, Ping Zhang, Yaofei Chen, Yue Huang, Gui-Shi Liu, Yunhan Luo, Zhe Chen

    Published 2025-08-01
    “…These advantages have been confirmed in the detection of full-range human motions, such as speech recognition, using a deep neural network algorithm. The red-shift stretchable PC demonstrates a new paradigm for artificial chameleon skins, and the bionic PC crack bilayer structure extends the design concept for visually interactive e-skins.…”
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  2. 162

    Energy-Efficient Soft Real-Time Scheduling for Parameter Estimation in WSNs by Senlin Zhang, Zixiang Wang, Meikang Qiu, Meiqin Liu

    Published 2013-04-01
    “…However, this kind of approaches does not take full advantage of the soft real-time property. In this paper, we proposed an energy-efficient scheduling algorithm especially for the soft real-time estimations in WSNs. …”
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  3. 163

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

    Published 2025-01-01
    “…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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    Article
  4. 164

    Human-in-the-Loop Modeling and Bilateral Skill Transfer Control of Soft Exoskeleton by Jiajun Xu, Kaizhen Huang, Mengcheng Zhao, Jinfu Liu

    Published 2024-12-01
    “…Soft exoskeletons (exosuits) are expected to provide a comfortable wearing experience and compliant assistance compared with traditional rigid exoskeleton robots. …”
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    Article
  5. 165

    Design and Dimension Optimization of Rigid–Soft Hand Function Rehabilitation Robots by Rui Zhang, Meng Ning, Yuqian Wang, Jun Yang

    Published 2025-04-01
    “…This study develops a rigid–soft coupling rehabilitation robot integrating linkage mechanisms with soft components. …”
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    Article
  6. 166

    Soft Actor-Critic Approach to Self-Adaptive Particle Swarm Optimisation by Daniel von Eschwege, Andries Engelbrecht

    Published 2024-11-01
    “…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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  7. 167

    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

    Published 2024-10-01
    “…In this study, the design, fabrication and systematic evaluation of a soft pneumatic muscle for elbow rehabilitation are presented. …”
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    Article
  8. 168

    Study of spectral overlap and heterogeneity in agriculture based on soft classification techniques by Shubham Rana, Salvatore Gerbino, Petronia Carillo

    Published 2025-06-01
    “…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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    Article
  9. 169

    A Hybridization of Modified Rough Bipolar Soft Sets and TOPSIS for MCGDM by Saba Ayub, Muhammad Shabir, Rizwan Gul

    Published 2023-03-01
    “…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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    Article
  10. 170

    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

    Published 2025-04-01
    “…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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    Article
  11. 171
  12. 172

    General Framework of Reversible Watermarking Based on Asymmetric Histogram Shifting of Prediction Error by Sheng Chen, Xianyi Chen, Huijuan Fu

    Published 2017-01-01
    “…This paper presents a general framework for the reversible watermarking based on asymmetric histogram shifting of prediction error, which is inspired by reversible watermarking of prediction error. …”
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  13. 173

    State Estimation for a Class of Singular Systems Using Shifted Legendre Polynomials by Zahra Razavinasab, Mohammad Ali Vali, Mahmoud Samavat

    Published 2024-02-01
    “…Furthermore, the proposed algorithms can be easily implemented in a digital computer and the solutions can be obtained for any length of time. …”
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    Article
  14. 174

    Vibrational Resonance with Self-adaptive Frequency-Shifted and Scaling for Fault Detection of Bearings by MAO Cheng;SHEN Chunhe;CUI Yue;LI Linfeng;CHEN Manhua;CHEN Hui;XIE Zhanshan

    Published 2020-06-01
    “…Moreover, the frequency-shifted and scaling is used to transform the bearing fault characteristic frequencies into small parameter detection condition of vibrational resonance. …”
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  15. 175

    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

    Published 2020-05-01
    “…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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  16. 176

    A New Approach to Group Decision-Making Method Based on TOPSIS Under Fuzzy Soft Environment by Faruk Karaaslan, Samet Memiş, Serdar Enginoğlu

    Published 2019-12-01
    “…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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  17. 177

    New Topological Approaches to Generalized Soft Rough Approximations with Medical Applications by Mostafa K. El-Bably, Muhammad I. Ali, El-Sayed A. Abo-Tabl

    Published 2021-01-01
    “…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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  18. 178

    A hybrid elastic-hyperelastic approach for simulating soft tactile sensors by Berith Atemoztli De la Cruz Sánchez, Jean-Philippe Roberge

    Published 2025-07-01
    “…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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  19. 179

    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

    Published 2025-02-01
    “…This study demonstrates that implementing the soft-voting ensemble-SMOTE method can enhance the model's predictive accuracy.…”
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  20. 180

    Optimizing Cardiovascular Risk Assessment with a Soft Voting Classifier Ensemble by Ammar Oad, Zulfikar Ahmed Maher, Imtiaz Hussain Koondhar, Karishima Kumari, Hammad Bacha

    Published 2024-12-01
    “…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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