Evaluation of Sociopreneur-Based Curriculum Implementation in Santa Maria Vocational School with Iluminative Models by Margareta Dwi Wahyu Utari, Juwintar Febriani Arwan, Said Hamid Hasan, Zainal Arifin

“…The obstacles that occur indicate the internal motivation of students and they still need training related to social entrepreneur integration in subjects and their development in learning activities. Overall, this evaluation explains that the process of implementing a social entrepreneur-based curriculum can run well and receive positive responses from students and teachers.…”
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Impacto de la gamificación en el aprendizaje y satisfacción de estudiantes de odontología de una universidad peruana by Sheila Trigo-Cano, Peggy Griselda Coa-Serrano, Sonia Caroll Macedo-Valdivia, Fernando Amilcar Chávez-Fernandez

“…Conclusions: Gamification, in general, and escape rooms, in particular, have been shown to have a positive impact on the learning and satisfaction of dentistry students, so they should be considered as a complementary tool to traditional teaching methods.…”
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Classification of Lung Nodule Using Hybridized Deep Feature Technique by Malin Bruntha, Immanuel Alex Pandian, Siril Sam Abraham

“…The hybridization has been carried out between handcrafted features and deep features. The machine learning algorithms such as SVM and Logistic Regression have been used to classify the nodules based on the features. …”
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Fusion Text Representations to Enhance Contextual Meaning in Sentiment Classification by Komang Wahyu Trisna, Jinjie Huang, Hengyu Liang, Eddy Muntina Dharma

“…Automating sentiment classification involves text classification processes, commonly performed using deep learning methods. The classification process using deep learning models is closely tied to text representation. …”
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Improving EEG based brain computer interface emotion detection with EKO ALSTM model by R. Kishore Kanna, Preety Shoran, Meenakshi Yadav, Mohammad Nadeem Ahmed, Shrikant Burje, Garima Shukla, Anurag Sinha, Mohammad Rashid Hussain, Saifullah Khalid

“…The proposed system and existing algorithms are compared using a variety of evaluation criteria, including specificity, F1 score, accuracy, recall or sensitivity, and positive predictive values or precision. The results demonstrated that the proposed method achieved better performance in EEG-based BCI emotion detection with an accuracy of 97.93%, a positive predictive value of 96.24%, a sensitivity of 97.81%, and a specificity of 97.75%. …”
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Enhancing Arabic Writing Skills Through the Genre-Based Approach in Senior High School by M Yahya Ashari, Mokhammad Miftakhul Huda, Rifatul Mahfudhoh

“…The learning process was also rated positively by observers. …”
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An Explainable LSTM-Based Intrusion Detection System Optimized by Firefly Algorithm for IoT Networks by Taiwo Blessing Ogunseyi, Gogulakrishan Thiyagarajan

“…Specifically, we employ a hybrid approach using statistical methods and a metaheuristic algorithm for feature selection to identify the most relevant features and limit the overall feature set while building an LSTM-based model for intrusion detection. …”
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An integrated machine learning model of transcriptomic genes in multi-center chronic obstructive pulmonary disease reveals the causal role of TIMP4 in airway epithelial cell by Erkang Yi, Haiqing Li, Yu Liu, Qingyang Li, Chengshu Xie, Ruining Sun, Fan Wu, Zhishan Deng, Kunning Zhou, Hairong Wang, Xinru Ran, Yumin Zhou, Pixin Ran

“…Additionally, a gene-based model was constructed to distinguish COPD at the molecular level and validated in independent cohorts. …”
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MRI-based risk factors for intensive care unit admissions in acute neck infections by Jari-Pekka Vierula, Harri Merisaari, Jaakko Heikkinen, Tatu Happonen, Aapo Sirén, Jarno Velhonoja, Heikki Irjala, Tero Soukka, Kimmo Mattila, Mikko Nyman, Janne Nurminen, Jussi Hirvonen

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Identification of sepsis biomarkers through glutamine metabolism-mediated immune regulation: a comprehensive analysis employing mendelian randomization, multi-omics integration, an... by Zhuang’e Shi, Fuping Wang, Lishun Yang, Lishun Yang, Couwen Li, Bing Gong, Ruanxian Dai, Guobing Chen

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Origin centric and part based pose decomposition for 3D human pose estimation by Zhijie Lin, Jinxin Yao, Juan Huang, Jingjing Chen, Yingying Xu, Lu Yang, Lei Zhao, Wei Xing

“…Existing methods typically either consider the entire 2D skeleton for global features extraction or break it into independent parts for local features learning. …”
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A dataset for surface defect detection on complex structured parts based on photometric stereo by Lin Wu, Yu Ran, Li Yan, Yixing Liu, You Song, Dongran Han

“…To address these issues, a novel defect detection technique based on deep learning and photometric stereo vision was proposed, along with the creation of the Metal Surface Defect Dataset (MSDD). …”
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Fully Automated Assessment of Cardiac Chamber Volumes and Myocardial Mass on Non-Contrast Chest CT with a Deep Learning Model: Validation Against Cardiac MR by Ramona Schmitt, Christopher L. Schlett, Jonathan I. Sperl, Saikiran Rapaka, Athira J. Jacob, Manuel Hein, Muhammad Taha Hagar, Philipp Ruile, Dirk Westermann, Martin Soschynski, Fabian Bamberg, Christopher Schuppert

“…<b>Results</b>: The deep learning model generated CT measurements for 52 of the 53 patients (98%). …”
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The role of endothelial cell-related gene COL1A1 in prostate cancer diagnosis and immunotherapy: insights from machine learning and single-cell analysis by Gujun Cong, Jingjing Shao, Feng Xiao, Haixia Zhu, Peipei Kang

“…Furthermore, based on patients’ prognostic information, multiple machine learning analyses highlighted the critical role of COL1A1. …”
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Prediction of the risk of transplant rejection based on RNA sequencing data of PBMCs before transplantation by Yu Gong, Yuan Wang, Kazuyoshi Takeda, Saori Hirota, Yui Maehara, Ko Okumura, Koichiro Uchida

“…Abstract Novel methods for detecting transplant rejection are craved, since conventional methods can detect ongoing rejection that may sometimes have already caused irreversible damage in transplanted organs. …”
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Research Trends and Hotspots in eDNA-Based Surveys of Macroinvertebrates: A Bibliometric Analysis by Xinyu Ge, Junyu Zhang, Ziming Shao, Lu Chai, Jiaxin Nie, Dan Yin, Haoran Zhang, Wenbin Liu, Chuncai Yan

“…In this study, we systematically analyzed 322 articles in the Web of Science Core Collection from 2010 to 2024 using bibliometric methods to reveal the research trends and technological advances in the field of macroinvertebrate surveys based on eDNA metabarcoding technology. …”
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Intelligent Recognition and Parameter Estimation of Radar Active Jamming Based on Oriented Object Detection by Jiawei Lu, Yiduo Guo, Weike Feng, Xiaowei Hu, Jian Gong, Yu Zhang

“…To enhance the perception capability of radar in complex electromagnetic environments, this paper proposes an intelligent jamming recognition and parameter estimation method based on deep learning. The core idea of the method is to reformulate the jamming perception problem as an object detection task in computer vision, and we pioneer the application of oriented object detection to this problem, enabling simultaneous jamming classification and key parameter estimation. …”
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The Emotional Component of Teaching RFL to Iranian Studentsas a Goal and Means of Achieving Optimal Results by Vajihe Rezvani, Alina A. Shuldishova

“…According to the survey results, 85.9% of students expressed dissatisfaction with the virtual learning process. 53% positively assessed the combined use of the above-mentioned methods.…”
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Representation Enhancement-Based Proximal Policy Optimization for UAV Path Planning and Obstacle Avoidance by Xiangxiang Huang, Wei Wang, Zhaokang Ji, Bin Cheng

“…Currently, reinforcement learning (RL) has become increasingly popular in UAV decision-making. …”
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Remaining useful life prediction of li-ion batteries based on an improved transformer model by Qingsong Wang, Annuo Yu, Hao Ding, Ming Cheng, Giuseppe Buja

“…Under the development of artificial intelligence technology, physical methods no longer meet the needs of industrial Li-ion battery RUL prediction, so the data-driven model based on deep learning has become a hot spot. …”
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