A Novel Two-Stage Learning-Based Phase Unwrapping Algorithm via Multimodel Fusion by Chao Yan, Tao Li, Yandong Gao, Shijin Li, Xiang Zhang, Xuefei Zhang, Di Zhang, Huiqin Liu

“…Deep learning phase unwrapping (DLPU) can better solve this problem. …”
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Evaluating the Lifelong Learning Approach to Demand-Oriented Research in Student Theses Using the ADDIE Model by Abolghasem Rahmani, Pooria Gill, Siavash Moradi, Atefeh Zabihi Zazoly, Fattane Amuei, adele Rafati

“…This study utilized components of the lifelong learning approach and the steps of the Analysis, Design, Development, Implementation, and Evaluation (ADDIE) model for educational design. …”
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Extended VGG16 Deep-Learning Detects COVID-19 from Chest CT Images by abolfazl karimiyan abdar, seyyed mostafa sadjadi, ali bashirgonbadi, mehran naghibi, Hamid Soltanian-Zadeh

“…Coronavirus disease 2019 (COVID-19), is a rapidly spreading disease that has infected millions of people worldwide. One of the essential steps to prevent spreading COVID-19 is an effective screening of infected individuals. …”
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Learning styles and academic performance among nursing and midwifery students: A cross-sectional study by Mohammadreza Rajabloo, Hamideh Mancheri, Ali Kavosi, Zahra Sabzi

“…Given the significant role of learning styles in education and their potential impact on student’s academic performance, this study aims to determine the relationship between learning styles and academic performance among nursing and midwifery students. …”
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The Learning Curve for Laparoscopic Sacrocolpopexy Based on Dissection Skills if Structured Teaching and Standardized Surgery are Applied by Studer AM, Krebs J, Brambs C, Christmann-Schmid C

“…The aim of this study was to evaluate if dry-lab suture and knotting training lead to stable theater performance. Consequently, the learning curve is supposed to be ascribed to only on-patient trainable skills like tissue preparation.Patients and Methods: To test this hypothesis, a structured training and stepwise surgical program were implemented to perform laparoscopic sacrocolpopexy (SCP) for urogynecological fellows adapting existing literature.The program was structured and recorded as following: dry-lab training weekly for knotting and suturing skills, assisting 20 SCP, stepwise overtaking defined steps under supervision including preparation of the dissecting planes anteriorly, posteriorly and at the level of the promontory, mesh fixation and retroperitoneal closure. …”
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A Deep Learning Enabled Chest X-Ray Abnormality Detection Model for Radiology Assistance. by Ssempeebwa, Phillip, Ainembabazi, Patience

“…The main objective of this study is to develop and implement a Deep Learning-Enabled Chest X-ray Abnormality Detection model with automated report generation. …”
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Empowering Sustainability: The Crucial Role of IoT-Enabled Distributed Learning Systems in Reducing Carbon Footprints by Anjana M S, Aryadevi Remanidevi Devidas, Maneesha Vinodini Ramesh

“…Transitioning to cleaner energy sources and improving energy efficiency are essential steps to reduce the environmental impact of electricity generation. …”
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Colorectal cancer detection with enhanced precision using a hybrid supervised and unsupervised learning approach by Akella S. Narasimha Raju, K. Venkatesh, Ranjith Kumar Gatla, Eswara Prasad Konakalla, Marwa M. Eid, Nataliia Titova, Sherif S. M. Ghoneim, Ramy N. R. Ghaly

“…The method entails several steps with CNN models: ADa-22 and AD-22, transformer networks, and an SVM classifier, all inbuilt. …”
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Real-World Parkinson’s Hand Tremor Detection Using Ensemble Learning Techniques by Sungwook Hur, Jieming Zhang, Moon-Hyun Kim, Tai-Myoung Chung

“…In this paper, we propose a novel approach to detect Parkinsonian hand tremor at walking state by exploiting the periodic synchronization between arm swings and leg steps that is observed in natural walking, specifically by using a wrist-worn sensor to capture the characteristic hand tremor that is induced during walking in Parkinson’s patients. …”
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Objective assessment of gait and posture symptoms in Parkinson’s disease using wearable sensors and machine learning by Lingyan Ma, Lingyan Ma, Shinuan Lin, Shinuan Lin, Jianing Jin, Jianing Jin, Zhan Wang, Zhan Wang, Xuemei Wang, Xuemei Wang, Zhonglue Chen, Zhonglue Chen, Yun Ling, Yun Ling, Fei Zhang, Fei Zhang, Kang Ren, Kang Ren, Tao Feng, Tao Feng, Tao Feng

“…In addition, 180° Turn—Steps – mean (R = 0.482, p < 0.001) had a positive correlation with scores on item #3.11. …”
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Spatial analysis of air pollutant exposure and its association with metabolic diseases using machine learning by Jingjing Liu, Chang Liu, Zhangdaihong Liu, Yibin Zhou, Xiaoguang Li, Yang Yang

“…Methods The ASEMD pipeline comprises three main steps: (i) Spatial autocorrelation between APs and MDs is evaluated using Moran’s I statistic and Local Indicators of Spatial Association (LISA) maps. …”
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Novel Fuzzy Multi-Criteria Decision Framework for Maritime Infrastructure Maintenance by Ehidiame Ibazebo, Vimal Savsani, Arti Siddhpura, Milind Siddhpura, Poonam Savsani

“…The proposed framework incorporates three distinct multi-criteria decision-making tools Step-wise Weight Assessment Ratio Analysis, Weighted Aggregate Sum Product Assessment, and Technique for Order of Preference by Similarity to Ideal Solution. …”
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Capabilities of the Canva web service for creating educational videos to improve the effectiveness of the educational process in flipped learning by Inna I. Kovtaniuk, Olena Yu. Tarasova, Iryna S. Zakarliuka

“…The paper provides a comprehensive analysis of Canva's features for educational video creation, compares it with alternative tools, and offers step-by-step guidance for implementing Canva videos in Ukrainian educational contexts. …”
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Learing Visual Fox Pro Language with Audio, Video and Sharing by Turfa Hamed

“…Two learning methods are used in this research: Enumeration  learning where the user plays a video file containing the lecture while the user is listening, and the Interactive learning which instructs the user to build the application by himself by  sound and pictures step-by-step until the application is finished. …”
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El Ciclo del Aprendizaje Cooperativo: una guía para implementar de manera efectiva el aprendizaje cooperativo en educación física (The Cooperative Learning Cycle: a guide to effect... by Javier Fernández-Río

“…Each of these phases is composed by several sub-phases and/or techniques that help understanding the whole process. The Cooperative Learning Cycle represents a step forward, because it provides teachers with a stable framework that allows them and their students to understand, learn, use, and integrate progressively cooperative learning in their classes. …”
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“Sensing, learning but forgetting”: the inability of strawberry plants to transmit the infochemically-mediated stress priming under salinity by Costanza Ceccanti, Giulia Lauria, Fabrizio Araniti, Ermes Lo Piccolo, Ylenia Pieracci, Guido Flamini, Lucia Guidi, Marco Landi

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FOLU-Net: A novel framework using long short-term memory networks to predict future forestry and other land use by Sanchali Banerjee, Paige T. Williams, Randolph H. Wynne

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Frontal plane mechanical leg alignment estimation from knee x-rays using deep learning by Kenneth Chen, Christoph Stotter, Christopher Lepenik, Thomas Klestil, Christoph Salzlechner, Stefan Nehrer

“…The model's evaluation involved two steps: In step 1, the model's predictions on knee images cropped from LLRs were compared against the ground truth from the original LLRs. …”
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Resilience, Confidence-Building, and Performance: by Audrey Ricke

“…Such an analysis, which considers mediating factors not previously analyzed together in adaptive digital learning studies, such as individual rather than aggregate performance, digital learning platform design differences, resiliency factors, and in-class activities, is an important step in clarifying some of the previously mixed results. …”
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Resilience, Confidence-Building, and Performance: by Audrey Ricke

“…Such an analysis, which considers mediating factors not previously analyzed together in adaptive digital learning studies, such as individual rather than aggregate performance, digital learning platform design differences, resiliency factors, and in-class activities, is an important step in clarifying some of the previously mixed results. …”
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