Enhancing Critical Thinking Skills of Junior High School Student: Development of Interactive Worksheet Based on Discovery Learning Model by Khumaeroh Dwi Nur'aini, Abdul Rachman Taufik

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Pengembangan Aplikasi E-Learning Edu IT : Pembuatan Aplikasi Ujian Essay Online serta Upload Download Materi Kuliah by Maria Bellaniar Ismiati, Latius Hermawan

“…  Dunia pendidikan sekarang sudah banyak yang menggunakan kecanggihan teknologi dan berbasis internet, seperti proses belajar mengajar secara elektronik atau dikenal dengan e-learning. Salah satu fitur e-learning dalam proses belajar mengajar adalah dapat menampilkan materi, soal latihan, percakapan melalui text/video maupun video, kuis, dan ujian secara elektronik. …”
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A multi-model feature fusion based transfer learning with heuristic search for copy-move video forgery detection by Hessa Alfraihi, Muhammad Swaileh A. Alzaidi, Hamed Alqahtani, Abdulbasit A. Darem, Ali M. Al-Sharafi, Ahmad A. Alzahrani, Menwa Alshammeri, Abdulwhab Alkharashi

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FIRM image analysis: A machine learning workflow for quantifying extracellular matrix components from electron microscopy images. by Nicholas T Gigliotti, Justin Lee, Emily H Mang, Giancarlo R Zambrano, Mitra L Taheri

“…Current imaging techniques allow us to visualize these critical remodeling events and developments in image analysis have employed a combination of analysis software and machine learning techniques to improve the efficiency and accuracy with which features are measured. …”
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Analisis Model Mental Mahasiswa dalam Pengembangan E-Learning Pemrograman Berbasis Gamifikasi Menggunakan Metode Agile UX by Retno Indah Rokhmawati, Fitra Abdurrachman Bachtiar, Fajar Pradana, Kharis Alfian

“…Abstract The purpose of this research is to analyze students' mental models of how their behavior learns programming material. This mental model is then applied to improve the e-learning CodeManiac design. …”
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A hybrid approach for intrusion detection in vehicular networks using feature selection and dimensionality reduction with optimized deep learning. by Fayaz Hassan, Zafi Sherhan Syed, Aftab Ahmed Memon, Saad Said Alqahtany, Nadeem Ahmed, Mana Saleh Al Reshan, Yousef Asiri, Asadullah Shaikh

“…The intended use of CFS and PCA in the machine learning pipeline serves two folds benefit, first is that the resultant feature matrix contains attributes that are most useful for recognizing malicious traffic, and second that after CFS and PCA, the feature matrix has a smaller dimensionality which in turn means that smaller number of weights need to be trained for the dense layers (connections are required for the dense layers) which resulting in smaller model size. …”
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A hybrid machine learning model for intrusion detection in wireless sensor networks leveraging data balancing and dimensionality reduction by Md. Alamin Talukder, Majdi Khalid, Nasrin Sultana

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A NEED ANALYSIS ON ICT-BASED ENGLISH MATERIAL FOR TEACHING AND LEARNING OF READING FOR HIGH SCHOOL STUDENTS IN SOUTH BENGKULU by Margareta Margareta, Safnil Safnil, Irwan Koto

“…This research was aimed to find out ICT media are preferred by high school students in South Bengkulu in learning reading and to describe the reading materials should be used with ICT media. …”
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On the interaction between implicit statistical learning and the alternation advantage: Evidence from manual and oculomotor serial reaction time tasks. by Arianna Compostella, Marta Tagliani, Maria Vender, Denis Delfitto

“…In this study, we examine how implicit statistical learning (ISL) interacts with the cognitive bias of the alternation advantage in serial reaction time (SRT) tasks. …”
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A deep learning-based method for the intelligent identification of the quantity of coals flushed out during borehole hydraulic flushing by Xiaojun LI, Mingyang ZHAO, Miao LI

“…The results of this study provide a technical and practical foundation for the integration of the YOLO series of algorithms with other deep learning techniques and its wide applications. Besides, these results serve as a valuable reference for achieving intelligent advances in complex underground coal mine scenarios such as drilling sites for gas drainage.…”
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Panoramic radiographic features for machine learning based detection of mandibular third molar root and inferior alveolar canal contact by A. Canberk Ulusoy, Tuğçe Toprak, M. Alper Selver, Pelin Güneri, Betül İlhan

Subjects: “…Machine learning…”
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Enhancing drug discovery and patient care through advanced analytics with the power of NLP and machine learning in pharmaceutical data interpretation by Nagalakshmi R, Surbhi Bhatia Khan, Ananthoju Vijay kumar, Mahesh T R, Mohammad Alojail, Saurabh Raj Sangwan, Mo Saraee

“…This study delves into the transformative potential of Machine Learning (ML) and Natural Language Processing (NLP) within the pharmaceutical industry, spotlighting their significant impact on enhancing medical research methodologies and optimizing healthcare service delivery. …”
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Machine learning reveals sex differences in distinguishing between conduct-disordered and neurotypical youth based on emotion processing dysfunction by Gregor Kohls, Erik M. Elster, Peter Tino, Graeme Fairchild, Christina Stadler, Arne Popma, Christine M. Freitag, Stephane A. De Brito, Kerstin Konrad, Ruth Pauli

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Machine learning identifies the association between second primary malignancies and postoperative radiotherapy in young-onset breast cancer patients by Yulin Lai, Peiyuan Huang

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Machine learning-random forest model was used to construct gene signature associated with cuproptosis to predict the prognosis of gastric cancer by Xiaolong Liu, Pengxian Tao, He Su, Yulan Li

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DeepCERES: A deep learning method for cerebellar lobule segmentation using ultra-high resolution multimodal MRI by Sergio Morell-Ortega, Marina Ruiz-Perez, Marien Gadea, Roberto Vivo-Hernando, Gregorio Rubio, Fernando Aparici, Maria de la Iglesia-Vaya, Gwenaelle Catheline, Boris Mansencal, Pierrick Coupé, José V. Manjón

“…We have also integrated deep learning with classical machine learning methods incorporating a priori knowledge from multi-atlas segmentation which improved precision and robustness. …”
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Engaging High Water Users in Water Conservation #3: High Water Users’ Opportunities to Learn about Water Conservation by Pei-wen Huang, Alexa J. Lamm

“…AEC595/WC257: Engaging High Water Users in Water Conservation #3: High Water Users' Opportunities to Learn about Water Conservation (ufl.edu) …”
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ChIMES Carbon 2.0: A transferable machine-learned interatomic model harnessing multifidelity training data by Rebecca K. Lindsey, Sorin Bastea, Sebastien Hamel, Yanjun Lyu, Nir Goldman, Vincenzo Lordi

“…Abstract We present new parameterizations of the ChIMES physics informed machine-learned interatomic model for simulating carbon under conditions ranging from 300 K and 0 GPa to 10,000 K and 100 GPa, along with a new multi-fidelity active learning strategy. …”
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Construction and Validation of a Model for Predicting Fear of Childbirth: A Cross-Sectional Population Study via Machine Learning by Zhang ZL, Chen KJ, Chen H, Zhu MM, Gu JJ, Jiang LS, Zheng L, Zhou SG

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Learn from international recommendations and experiences of countries that have successfully implemented monoclonal antibody prophylaxis for prevention of RSV infection by Sara Manti, Eugenio Baraldi

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