Unlocking ecological insights from sub‐seasonal visible‐to‐shortwave infrared imaging spectroscopy: The SHIFT campaign by K. Dana Chadwick, Frank Davis, Kimberley R. Miner, Ryan Pavlick, Mark Reynolds, Philip A. Townsend, Philip G. Brodrick, Christiana Ade, Jean Allen, Leander Anderegg, Yoseline Angel, Indra Boving, Kristin B. Byrd, Petya Campbell, Luke Carberry, Katherine C. Cavanaugh, Kyle C. Cavanaugh, Kelly Easterday, Regina Eckert, Michelle Gierach, Kaitlin Gold, Erin Hestir, Fred Huemmrich, Maggie Klope, Raymond F Kokaly, Piper Lovegreen, Kelly Luis, Conor McMahon, Nicholas Nidzieko, Francisco Ochoa, Anna Jiselle Ongjoco, Elsa Ordway, Madeleine Pascolini‐Campbell, Natalie Queally, Dar A. Roberts, Clare M. Saiki, Fabian D. Schneider, Alexey N. Shiklomanov, Germán D. Silva, Jordan Snyder, Michele Thornton, Anna T. Trugman, Nidhi Vinod, Ting Zheng, Dulcinea M. Avouris, Brianna Baker, Latha Baskaran, Tom Bell, Megan Berg, Michael Bernas, Niklas Bohn, Renato K. Braghiere, Zach Breuer, Andrew J. Brooks, Nolan Burkard, Julia Burmistrova, Kerry Cawse‐Nicholson, John Chapman, Johana Chazaro‐Haraksin, Joel Cryer, K. C. Cushman, Kyla Dahlin, Phuong D. Dao, Athena DiBartolo, Michael Eastwood, Clayton D. Elder, Angela Giordani, Kathleen Grant, Robert O. Green, Alexa Hanson, Brendan Heberlein, Mark Helmlinger, Simon Hook, Daniel Jensen, Emma Johnson, Marie Johnson, Michael Kiper, Christopher Kibler, Jennifer Y. King, Kyle R. Kovach, Aaron Kreisberg, Daniel Lacey, Evan Lang, Christine Lee, Amanda M. Lopez, Brittany Lopez Barreto, Andrew Maguire, Elliott Marsh, Charles Miller, Dieu My T. Nguyen, Cassandra Nickles, Jonathan P. Ocón, Elijah P. Papen, Maria Park, Benjamin Poulter, Ann Raiho, Porter Reim, Timothy H. Robinson, Fernando E. Romero Galvan, Ethan Shafron, Brenen R. Skalitzky, Sydney Stroschein, Niky C. Taylor, David R. Thompson, Kate Thompson, Cecily Tye, Joelie Van Beek, Cecilia Vanden Heuvel, Jonathan Vellanoweth, Evert Vermeer, Claire Villanueva‐Weeks, Kristen Zumdahl, David Schimel

“…SHIFT, designed to support NASA's SBG mission, addressed mission scoping, scientific advancement, applications development, and community building. …”
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Rough Set Theory and Soft Computing Methods for Building Explainable and Interpretable AI/ML Models by Sami Naouali, Oussama El Othmani

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Electric Vehicle and Soft Open Points Co-Planning for Active Distribution Grid Flexibility Enhancement by Jie Fang, Wenwu Li, Dunchu Chen

“…This paper proposes co-planning of electric vehicles (EVs) and soft opening points (SOPs) to improve the flexibility of the active distribution network, thereby improving the economics and flexibility of the distribution network. …”
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Joining Application of Unmanned Aerial Vehicle Imagery with GIS for Monitoring of Soft Cliff Linear Habitats by Egidijus Jurkus, Julius Taminskas, Ramūnas Povilanskas, Arvydas Urbis, Jovita Mėžinė, Domantas Urbis

“…The study’s main objective was to assess short-term behavior of soft cliffs as littoral linear habitats during calm season storm events in the example of the Olandų Kepurė cliff, located on a peri-urban protected seashore (Baltic Sea, Lithuania). …”
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A state-of-the-art review of soft computing-based monitoring and control in the machining of hard alloys by Lokesh Kumar, Ashish Goyal, Vimal Kumar Pathak, Abhijit Bhowmik

“…To address these limitations, the manufacturing industry has increasingly shifted towards non-traditional machining methods. …”
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Improved Motion Correction in Dynamic Contrast-Enhanced MRI Using Low Rank With Soft Weighting by Jichang Zhang, Faisal Najeeb, Yulin Wang, Xinpei Wang, Pengfei Xu, Hammad Omer, Jianjun Zheng, Jingfeng Zhang, Sue Francis, Paul Glover, Richard Bowtell, Thomas Meersmann, Chengbo Wang

“…This paper introduces a motion-corrected, free-breathing dynamic contrast-enhanced (DCE) MRI reconstruction method, termed low-rank plus sparse (L+S) with soft weighting. We designed a soft weighting matrix that smoothly transitions spokes between the target and other motion states to suppress motion blurring. …”
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Development of an interpretable model for foot soft tissue stiffness based on gait plantar pressure analysis by Xiaotian Bai, Xiao Hou, Dazhi Lv, Dazhi Lv, Jialin Wei, Jialin Wei, Yiling Song, Zhengyan Tang, Hongfeng Huo, Hongfeng Huo, Jingmin Liu

“…A backpropagation neural network, optimized by integrating particle swarm optimization and genetic algorithm, was constructed to predict foot soft tissue stiffness using plantar pressure data collected during walking. …”
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A study on plant root apex morphology as a model for soft robots moving in soil. by Anand Kumar Mishra, Francesca Tramacere, Roberto Guarino, Nicola Maria Pugno, Barbara Mazzolai

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Learning to suppress tremors: a deep reinforcement learning-enabled soft exoskeleton for Parkinson’s patients by Tamás Endrei, Tamás Endrei, Sándor Földi, Sándor Földi, Ádám Makk, György Cserey, György Cserey

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Soft Sensor Modeling of Key Effluent Parameters in Wastewater Treatment Process Based on SAE-NN by Yousuf Babiker M. Osman, Wei Li

“…In this research work, we propose a soft sensor model based on deep learning which combines stacked autoencoders with neural network (SAE-NN). …”
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Complex q-Rung Orthopair Fuzzy N-Soft Sets: A New Model with Applications by Muhammad Akram, Faiza Wasim, Ahmad N. Al-Kenani

“…To that purpose, the proposed theory integrates complex q-rung orthopair fuzzy sets with the parametric structure of N-soft sets. The framework that arises captures information beyond the confined space of complex intuitionistic fuzzy N-soft sets and complex Pythagorean fuzzy N-soft sets, with the assistance of a parameter q. …”
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Local Community Detection Algorithm Based on Minimal Cluster by Yong Zhou, Guibin Sun, Yan Xing, Ranran Zhou, Zhixiao Wang

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Student Performance Prediction Using Machine Learning Algorithms by Esmael Ahmed

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Nonlinear Correction Methods of Temperature-Caused Peak Shift for a NaI(Tl) Gamma-Ray Spectrometer by Jinfei Wu, Juan Zhai, Wanchang Lai, Hongjian Lin, Chenhao Zeng, Runqiu Gu, Shaoqin Li, Yunrui Jiang, Jie Shi, Bo Zhang

“…Two easy-to-implement methodologies are proposed to stabilize the measured spectrum without the necessity of adjusting the gain, which are a correction algorithm for temperature-caused peak-shift based on multiple characteristic peak area weighting factors and an interpolation correction algorithm based on multicharacteristic peak sequence. …”
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EEG-Based Emotion Recognition Using Deep Learning Network with Principal Component Based Covariate Shift Adaptation by Suwicha Jirayucharoensak, Setha Pan-Ngum, Pasin Israsena

“…To detect emotion from nonstationary EEG signals, a sophisticated learning algorithm that can represent high-level abstraction is required. …”
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RLS Beamforming Algorithm Based on Wavelet Transform by Jihong Zhao, Pei Lei, Weihua Wang, Hua Qu, Dan He

“…This algorithm uses soft thresholding wavelet transform for signal denoising, solves the problem that the traditional Adaptive beamforming algorithm is sensitive to noise and the steady-state error is big under the environment of the low signal to noise ratio（SNR）and small forgetting factor. …”
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Using Evolving Algorithms to Cryptanalysis Nonlinear Cryptosystems by Riyam Noori Jawad, Faez Hassan Ali

“…In this paper, new method have been investigated using evolving algorithms (EA's) to cryptanalysis one of the nonlinear stream cipher cryptosystems which depends on the Linear Feedback Shift Register (LFSR) unit by using cipher text-only attack. …”
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Research on Particle Filter Video Tracking Algorithms by YU Shuchun, TONG Xiaoyu

“…Aiming at the problem of insufficient robustness of moving target tracking in complex scenes, a particle filter target tracking algorithm based on CNN feature extraction is proposed CNN selflearning mechanism is used to extract highlevel semantic features of objects in images Chaotic sequence variable scale firefly algorithm is introduced to improve the accuracy of target recognition A particle filter tracking algorithm combining mean shift and weight optimization is constructed to optimize the weight of particles, improve the diversity of particle sets and make video tracking more accurate The simulation results show that the proposed algorithm can effectively adapt to occlusion, illumination, violent motion and other scenes, and has good adaptability and high realtime performance to illumination change, scale change, occlusion and so on The results of comparison with seven other methods show that under the same experimental conditions, the tracking success rate and tracking accuracy of this method are 5%~40% higher than those of other methods…”
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Ventricular segmentation algorithm for echocardiography based on transfer learning and GAN by Jin Wang, Xiaoning Bo, Guoqin Li, Yanli Tan

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Posture detection of athletes in sports based on posture solving algorithms by Huan Zhang

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