An Echo State Network Approach for Parameter Variation Robustness Enhancement in FCS-MPC for PMSM Drives by Xiao Zeng, Jing Li, Pengcheng Yang, Hongda Cai, Yongzhi Zhou, Daren Li

“…Initially, the ESN is trained offline using data derived from a PMSM-MPC control environment. …”
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Effectiveness of time-varying echo information for target geometry identification in bat-inspired human echolocation. by Miwa Sumiya, Kaoru Ashihara, Hiroki Watanabe, Tsutomu Terada, Shizuko Hiryu, Hiroshi Ando

“…The results suggest that using time-varying patterns in echo intensity, timbre, and/or pitch enables humans to identify target geometries. …”
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An echo state network based on enhanced intersecting cortical model for discrete chaotic system prediction by Xubin Wang, Pei Ma, Jing Lian, Jizhao Liu, Yide Ma

“…Deep learning models, while effective, are associated with high computational costs and large data requirements. As an alternative, Echo State Networks (ESNs) are more computationally efficient, but their predictive accuracy can be constrained by the use of simplistic neuron models and a dependency on hyperparameter tuning.MethodsThis paper proposes a framework, the Echo State Network based on an Enhanced Intersecting Cortical Model (ESN-EICM). …”
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Biased echoes: Large language models reinforce investment biases and increase portfolio risks of private investors. by Philipp Winder, Christian Hildebrand, Jochen Hartmann

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A Deep Learning-Based Echo Extrapolation Method by Fusing Radar Mosaic and RMAPS-NOW Data by Shanhao Wang, Zhiqun Hu, Fuzeng Wang, Ruiting Liu, Lirong Wang, Jiexin Chen

“…In summary, the model trained with the MR-DCGAN architecture effectively enhances the accuracy of radar echo extrapolation.…”
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Adaptive Echo State Network for crop yield prediction incorporating Fall Armyworm dynamicsMendeley Data by Mulima Chibuye, Jackson Phiri, Phillip Nkunika

“…To support precision pest management, we developed an adaptive Echo State Network (ESN) that predicts annual maize yield while accounting for FAW pressure. …”
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Demonstrating Feasibility of Point of Care Ultrasound (POCUS)-Guided Inpatient Transthoracic Echo Triage Decision Pathway by Stephanie Conner, Mustafa Husaini, Maya Fiore, Mohamad Ramadan, Benjamin Hoemann, Nicholas Arnold, Farhan Katchi, Crystal Atwood, Carol Faulk, Karl Wallenkampf, Jing Li

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A Forecast-Refinement Neural Network Based on DyConvGRU and U-Net for Radar Echo Extrapolation by Jinliang Yao, Feifan Xu, Zheng Qian, Zhipeng Cai

“…One of the challenges of precipitation nowcasting is radar echo extrapolation which predicts the radar echo images accurately. …”
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Early prediction of CKD from time series data using adaptive PSO optimized echo state networks by Thangadurai Anbazhagan, Balamurugan Rangaswamy

“…This study introduces a novel Adaptive Particle Swarm Optimization (APSO)-optimized Echo State Network (ESN) model designed to overcome key limitations of existing methods. …”
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Piloting the Extension for Community Healthcare Outcomes (ECHO) Pediatric Oncology Telehealth Education Program in Western Kenya: Implementation Study by Tyler Severance, Gilbert Olbara, Festus Njuguna, Martha Kipng'etich, Sandra Lang'at, Maureen Kugo, Jesse Lemmen, Marjorie Treff, Patrick Loehrer, Terry Vik

“…We implemented Project ECHO (Extension for Community Healthcare Outcomes)—a validated virtual guided practice and telementoring model—to connect multidisciplinary specialists at MTRH with staff in medically underserved communities in western Kenya for training, technical assistance, and mentorship. …”
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Analysis of a Pilot Study Delivering Cancer Survivorship Education to Community Healthcare Professionals Utilizing the Project ECHO Model by Ashley Pariser Davenport, Kevin Johns, Dena Champion, Andrea Roberts, Susan Fugett, Erin Holley, Candice Schreiber, Carolyn J. Presley, Jalyn Todd, Andrew Honeychuck, Katherine Hunt, Yurong Lu, Bhuvaneswari Ramaswamy, Seuli Bose Brill

“…All 22 participants rated the Cancer Survivorship ECHO pilot experience as having a positive (greater than neutral) result on their training. …”
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Reservoir computing with generalized readout based on generalized synchronization by Akane Ohkubo, Masanobu Inubushi

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A Radio Frequency Interference Screening Framework—From Quick-Look Detection Using Statistics-Assisted Network to Raw Echo Tracing by Jiayuan Shen, Bing Han, Yang Li, Zongxu Pan, Di Yin, Yugang Feng, Guangzuo Li

“…The possible distribution of the RFI in the corresponding raw echo is further inferred, which is one of the first attempts to use spaceborne SAR data to elucidate the RFI location mapping relationship between image data and raw echo. …”
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Trauma has an echo: a mixed methods study exploring barriers to routine healthcare for survivors of sexual violence in a UK higher education setting by Jane Meyrick, Laura Hooper

“…Survivor-led reforms called for survivor-centred practices and encouraged systemic reflection on how healthcare systems may contribute to the broader marginalisation of survivors. Findings echo policy recommendations for co-produced services led by minoritised/marginalised patients and operationalise trauma-informed training for healthcare professionals. …”
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Pre-post feasibility trial of a telephone-delivered exercise intervention for patients during chemotherapy for recurrent ovarian cancer: the ECHO-R trial protocol by Andreas Obermair, Monika Janda, Sandra C Hayes, Elizabeth Eakin, Marcelo Nascimento, Dimitrios Vagenas, Jermaine Coward, Louisa G Gordon, Catherine Shannon, James Nicklin, Jeffrey Goh, Vanessa L Beesley, Penny Webb, Merran Williams, Sheree Rye, Rosalind R Spence, Helene O’Neill, Melissa J Newton, Sara Baniahmadi, Andrea Garret

“…The exercise intervention comprises 12 telephone sessions over a 6-month period delivered by trial-trained exercise professionals and supplemented (where feasible) by five sessions face to face. …”
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End-to-End Interrupted Sampling Repeater Jamming Countermeasure Network Under Low Signal-to-Noise Ratio by Gane Dai, Xiaoxuan Yang, Sha Huan, Ziyang Chen, Cong Peng, Yuanqin Xu

“…A multi-domain combined loss function integrates the waveform and range-pulse-compression information to ensure the amplitude and phase integrity of the reconstructed echo waveform during the training process. The effectiveness of the proposed method was validated in terms of its jamming suppression capability, echo fidelity, and detection performance indicators under low-SNR conditions compared to conventional methods.…”
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Identifying Criteria and Indicators and Determining the Alternative Scenario for Transforming Industrial Towns into Eco-industrial Parks by Ahmad Nohegar, Hamid Asadbeigi

“…The results indicated executive guidelines and standards should be compiled to manage environmental problems in industrial towns and transform towns into echo-industrial parks. It is hoped that decision-makers in this field will take an important step to transform industrial towns into echo-industrial parks, minimize environmental problems and manage waste by developing executive guidelines and updated and advanced standards.…”
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Support for young people who are distressed by hearing voices: protocol for an uncontrolled feasibility evaluation of a psychological intervention package delivered within secondar... by Mark Hayward, Mary John, Sarah Parry, Anna-Marie Bibby-Jones, Faith Orchard, Fiona Malpass, Clare Dixon, Akira Naito

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External validation of CLOTS-AF score in patients with atrial fibrillation undergoing transesophageal echocardiography by Koray Kalenderoglu, Mert Ilker Hayiroglu, Lale Dinc Asarcikli, Tufan Cinar, Melih Oz, Gunseli Miray Ozdemir, Kivanc Keskin, Kadir Gurkan

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ELECTROCARDIOGRAPHIC CONTROL FOR CARDIOVASCULAR SYSTEM IN SPORTSMEN AT PRECOMPETITION TRAINING by N. P. Garganeeva, I. F. Taminova, I. N. Vorozhtsova

“…Study methods were electrocardiography (ECG), Holter monitoring of ECG, echocardiography (EchoCG), veloergometry (VEM).Results. During the preparation period of training-competition process, ECG changes, including cardiac rhythm disorders (CRD), were found in 93 of 136, that is 86 (63,2%) of quality sportsmen and 7 (5,1%) of controls (p=0,00001); during competition period — in 104 (76,5%) and 8 (5,9%) (p=0,00001), respectively. …”
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