Advanced Network Traffic Prediction Using Deep Learning Techniques: A Comparative Study of SVR, LSTM, GRU, and Bidirectional LSTM Models by Wang Yuxin

“…These findings underscore the significant potential of deep learning models, particularly GRU and Bidirectional LSTM, in improving the precision and reliability of network traffic predictions. …”
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Learning to Listen to Non-spoken Voices. Including Young People With Intellectual Disabilities Who are Non-speaking as Primary Participants in Qualitative Research by Beverley Samways, Pauline Heslop

“…The paper concludes with some brief learnings and reflections on the research journey. …”
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Penerapan Model Problem Based Learning dengan Socioscientific Issues untuk Meningkatkan Keterampilan Berpikir Kritis pada Pembelajaran Biologi SMA by Rif'atin Khoirunnisa, Anwari Adi Nugroho, Nur Rokhimah Hanik

Subjects: “…problem based learning…”
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Machine learning analysis of pathological images to predict 1-year progression-free survival of immunotherapy in patients with small-cell lung cancer by Hirotaka Matsumoto, Hiroaki Akamatsu, Nobuyuki Yamamoto, Yuki Sato, Daichi Fujimoto, Yoshihiko Taniguchi, Motohiro Tamiya, Yasuhiro Koh, Junya Fukuoka, Hisashi Tanaka, Naoki Furuya, Ryota Shibaki, Tsukasa Nozawa, Akira Sano, Yuka Kitamura, Takashi Kijima, Toshihide Yokoyama, Satoru Miura, Akito Hata, Jun Sugisaka

“…The primary outcome was the mean area under the curve (AUC) of machine learning models in predicting the 1-year PFS.Results We analyzed 100,544 patches of pathological images from 78 patients. …”
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Rethinking the measurements and predictors of environmental degradation in Ethiopia: Predicting long-term impacts using a kernel-based machine learning approach by Tesfaye Etensa, Tekie Alemu, Mengesha Yayo

Subjects: “…Kernel-based machine learning…”
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Deep Outer‐Rise Faults in the Southern Mariana Subduction Zone Indicated by a Machine‐Learning‐Based High‐Resolution Earthquake Catalog by Han Chen, Hongfeng Yang, Gaohua Zhu, Min Xu, Jian Lin, Qingyu You

“…We applied a machine‐learning phase detector (EQTransformer) to the OBS data and found more than 1,975 earthquakes. …”
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Optimization and modeling of sulfur removal from liquid fuel using carbon-based adsorbents through synergistic application of RSM and machine learning by Karim Maghfour Sarkarabad, Mohsen Shayanmehr, Ahad Ghaemi

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DeepGenMon: A Novel Framework for Monkeypox Classification Integrating Lightweight Attention-Based Deep Learning and a Genetic Algorithm by Abdulqader M. Almars

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Improved Error Reduction and Hybrid Input Output Algorithms for Phase Retrieval by including a Sparse Dictionary Learning-Based Inpainting Method by Jian-Jia Su, Chung-Hao Tien

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A Novel Data-Driven Terminal Iterative Learning Control with Iteration Prediction Algorithm for a Class of Discrete-Time Nonlinear Systems by Shangtai Jin, Zhongsheng Hou, Ronghu Chi

“…The proposed DDPTILC scheme consists of an iterative learning control law, an iterative parameter estimation law, and an iterative parameter prediction law. …”
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Penerapan Model Pembelajaran Penemuan Terbimbing (Guided Discovery Learning) untuk Meningkatkan Hasil Belajar dan Keterampilan Proses Sains Siswa by Hanis Destrini, Nirwana Nirwana, Indra Sakti

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A New Video-Based Crash Detection Method: Balancing Speed and Accuracy Using a Feature Fusion Deep Learning Framework by Zhenbo Lu, Wei Zhou, Shixiang Zhang, Chen Wang

“…In this paper, a feature fusion-based deep learning framework was developed for video-based urban traffic crash detection task, aiming at achieving a balance between detection speed and accuracy with limited computing resource. …”
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Interpretation of COVID-19 Epidemiological Trends in Mexico Through Wastewater Surveillance Using Simple Machine Learning Algorithms for Rapid Decision-Making by Arnoldo Armenta-Castro, Orlando de la Rosa, Alberto Aguayo-Acosta, Mariel Araceli Oyervides-Muñoz, Antonio Flores-Tlacuahuac, Roberto Parra-Saldívar, Juan Eduardo Sosa-Hernández

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Enhancing Arabic text-to-speech synthesis for emotional expression in visually impaired individuals using the artificial hummingbird and hybrid deep learning model by Mahmoud M. Selim, Mohammed S. Assiri

“…Natural Language Processing (NLP) and machine learning (ML) techniques provide powerful tools for analysing social media text data, helping detect emotional distress and providing timely support. …”
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Mediating Role of Time Pressure on the Relationship between Organizational Psychology Safety and Motivation of Learning from Failure in Large-Scale Construction Project by Lingna Lin, Xiaowei Luo, Sainan Cheng, Min Xu, Lianbo Zhu

“…Large-scale construction projects are characterized by the temporary cooperation of different parties with objectives, making it challenging to learn from failure under great time pressures. Learning from failure in such multiparties projects must overcome the fear of speaking out the “failure,” reflected by organizational psychology safety. …”
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Embedding research capacity strengthening in multi-country studies in low-and middle-income countries: learnings from sexual and reproductive health research by Anne M. Khisa, Hesborn Wao, Vanessa Brizuela, Rachidatou Compaoré, Adama Baguiya, Alejandra López Gómez, Mercedes Bonet, Seni Kouanda, Anna Thorson, Evelyn Gitau

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Practical Hybrid Machine Learning Approach for Estimation of Ultimate Load of Elliptical Concrete-Filled Steel Tubular Columns under Axial Loading by Tien-Thinh Le

“…In this study, a hybrid machine learning (ML) technique was proposed to predict the bearing capacity of elliptical CFST columns under axial load. …”
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RETRACTED ARTICLE: A prospective diagnostic model for breast cancer utilizing machine learning to examine the molecular immune infiltrate in HSPB6 by Lizhe Wang, Yu Wang, Yueyang Li, Li Zhou, Sihan Liu, Yongyi Cao, Yuzhi Li, Shenting Liu, Jiahui Du, Jin Wang, Ting Zhu

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Model Analisis Aktivitas Tutor Dalam Learning Management System Berdasarkan Data Log Menggunakan K-Means Dan Deteksi Outlier by Agusriandi Agusriandi, Elihami Elihami, Irman Syarif, Ita Sarmita Samad

“…Another fact showed who were tutors rarely provided feedback both in narrative and assessment when giving assignments so that the tutors in doing online learning has not met the standard process in online learning. …”
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Q‐scheduler: A temperature and energy‐aware deep Q‐learning technique to schedule tasks in real‐time multiprocessor embedded systems by Mahsa Mohammadi, Hakem Beitollahi

“…This paper proposes Q‐scheduler, a novel technique based on the deep Q‐learning technology, to dispatch tasks between processors in a real‐time MPSoC. …”
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