Corrections to “Federated Learning Approach for Breast Cancer Detection Based on DCNN” by Hussain Alsalman, Mabrook S. Al-Rakhami, Taha Alfakih, Mohammad Mehedi Hassan

“…Presents corrections to the paper, (Corrections to “Federated Learning Approach for Breast Cancer Detection Based on DCNN”).…”
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An endoscopic ultrasound-based interpretable deep learning model and nomogram for distinguishing pancreatic neuroendocrine tumors from pancreatic cancer by Nan Yi, Shuangyang Mo, Yan Zhang, Qi Jiang, Yingwei Wang, Cheng Huang, Shanyu Qin, Haixing Jiang

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Speech Enhancement Using Joint DNN-NMF Model Learned with Multi-Objective Frequency Differential Spectrum Loss Function by Matin Pashaian, Sanaz Seyedin

“…The use of encoded NMF coefficients as low-dimensional structural features for DNN serves as prior knowledge and helps the learning process. LMO is used beside LFD to take advantage of both the properties of the original and the differential spectrum in the training loss function. …”
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Deep learning-based synthetic CT for dosimetric monitoring of combined conventional radiotherapy and lattice boost in large lung tumors by Hongwei Zeng, Xiangyu E, Minghe Lv, Su Zeng, Yue Feng, Wenhao Shen, Wenhui Guan, Yang Zhang, Ruping Zhao, Jingping Yu

Subjects: “…Deep learning…”
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Closing the loop: establishing an autonomous test-learn cycle to optimize induction of bacterial systems using a robotic platform by Jan Benedict Spannenkrebs, Aron Eiermann, Thomas Zoll, Silke Hackenschmidt, Johannes Kabisch, Johannes Kabisch, Johannes Kabisch

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EFL students’ strategies and obstacles in pronunciation self-regulated learning through TikTok: insights from Indonesian universities by Athiyatul Hidayah

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Retracted: A New Machine Learning Algorithm for Regional Low-Carbon Economic Development Analysis Based on Data Mining by Journal of Function Spaces

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Advanced artificial intelligence with federated learning framework for privacy-preserving cyberthreat detection in IoT-assisted sustainable smart cities by Mahmoud Ragab, Ehab Bahaudien Ashary, Bandar M. Alghamdi, Rania Aboalela, Naif Alsaadi, Louai A. Maghrabi, Khalid H. Allehaibi

Subjects: “…Federated Learning…”
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Freinet and Montessori in practice. A comparative analysis of the meanings attributed to the process of learning by early education teachers – research report by Jarosław Jendza, Joanna Grzanka

“…Understanding constructivism as a metaphor describing process of learning, the authors outline similarities and differences in the conceptions attributed to the processes of learning between the two researched groups of teachers. …”
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Comparative analysis of deep learning and radiomic signatures for overall survival prediction in recurrent high-grade glioma treated with immunotherapy by Qi Wan, Clifford Lindsay, Chenxi Zhang, Jisoo Kim, Xin Chen, Jing Li, Raymond Y. Huang, David A. Reardon, Geoffrey S. Young, Lei Qin

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Pengaruh Model Experiential Learning Dalam Pembelajaran Keterampilan Menulis Teks Negosiasi Pada Siswa Kelas X SMA by Adinda Febry, Sadieli Telaumbanua, Friska Ria Sitorus

Subjects: “…experiential learning…”
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Evolving prognostic paradigms in lung adenocarcinoma with brain metastases: a web-based predictive model enhanced by machine learning by Min Liang, Zhiwen Zhang, Langming Wu, Mafeng Chen, Shifan Tan, Jian Huang

Subjects: “…Machine learning…”
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An Analysis of the Learning Activities Covered in the 5th Grade Science Textbooks Based on 2005 and 2013 Turkish Science Curricula by Cemil Aydogdu, Sahin Idin

“… The aim of this study is to analyze the learning activities covered in 5th grade elementary science textbooks which depend on 2005 and 2013 elementary science curricula. …”
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Mode Optimization and Rule Management of Intellectual Property Rights Protection of Educational Resource Data Based on Machine Learning Algorithm by Jiawei Cao

“…While searching for information in the educational resource database, these resources also have functions such as copying, downloading, reproduction, and dissemination, which raise the issue of expression and protection of intellectual property. Machine learning takes how computers simulate human learning behaviors as the main research content, which can independently determine learning objects, construct their characteristics, perform additional operations beyond the limitations of preset instructions, and discover value from the expression of relative works. …”
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An Approach to Integrating Tactical Decision-Making in Industrial Maintenance Balance Scorecards Using Principal Components Analysis and Machine Learning by Néstor Rodríguez-Padial, Marta Marín, Rosario Domingo

“…In the proposed Custom Balance Scorecard design, an exploratory data phase is integrated with another analysis and prediction phase using Principal Component Analysis algorithms and Machine Learning that uses Artificial Neural Network algorithms. …”
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Summer Research Internship Curriculum to Promote Self-Efficacy, Researcher Identity, and Peer-to-Peer Learning: Retrospective Cohort Study by Yulia A Levites Strekalova, Rachel Liu-Galvin, Samuel Border, Sara Midence, Mishal Khan, Maya VanZanten, John Tomaszewski, Sanjay Jain, Pinaki Sarder

“…The curriculum is intended to support intern self-efficacy, researcher identity development, and peer-to-peer learning. At the end of the internship, students were invited to participate in a web-based survey in which they were asked to rate their academic and research abilities before the internship and as a result of the internship using a modified Entering Research Learning Assessment instrument. …”
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Retracted: Extraction and Analysis of Influencing Factors of Scientific and Technological Ability Improvement of University Teachers Based on Deep Learning Model by Advances in Multimedia

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Exploring sentiment analysis in handwritten and E-text documents using advanced machine learning techniques: a novel approach by Rayees Ahamad, Kamta Nath Mishra

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Intrusion Detection for Wireless Sensor Network Using Particle Swarm Optimization Based Explainable Ensemble Machine Learning Approach by Shaikh Afnan Birahim, Avijit Paul, Fahmida Rahman, Yamina Islam, Tonmoy Roy, Mohammad Asif Hasan, Fariha Haque, Muhammad E. H. Chowdhury

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Hybridize Machine Learning Methods and Optimization Techniques to Analyze and Repair Welding Defects via Digital Twin of Jidoka Simulator by Ahmed M. Abed, Tamer S. Gaafar

“…We are creating a “digital Jidoka twin system” (SQ(R/I/E)) with a controller segment programmed with machine learning (ML) algorithms that use the MFEM’s huge and uneven data to sort defects and their causes. …”
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