The Role of Short Videos in Medical Training: Student Feedback and an Experiential Learning Perspective by DEEPIKA VELUSAMI, SHIVAYOGAPPA TELI, KRISHNAMURTHY SOUNDARIYA, SENTHAMIL K, MANGANI S

“…A pre-designed 10 questions, Likert scale questionnaire, based on Kirkpatrick’s Model (Level 1), was used to collect data about the students’ learning experience. …”
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EVALUATION OF THE MBKM INTERNSHIP PROGRAM ON THE LEVEL OF STUDENT SATISFACTION IN ACHIEVING LEARNING OBJECTIVES by Patricia Sulaowady, Samuel Elmer Limputra, Maichal Maichal

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CITIZEN SCIENCE PROJECT'S CONTRIBUTION TO SCIENCE LEARNING OUTCOME: SYSTEMATIC LITERATURE REVIEW by Ipin Aripin, Topik Hidayat, Nuryani Y. Rustaman, Riandi Riandi

“…The contributions of CSPs to these measured indicators of science learning outcomes show positive and significant results. …”
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Sequential learning on a tensor network Born machine with trainable token embedding by Wanda Hou, Miao Li, Yi-Zhuang You

“…Quantum-inspired generative models, such as Born machines based on the matrix product state (MPS) framework, have demonstrated remarkable capabilities in unsupervised learning tasks. …”
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PENINGKATAN KUALITAS PEMBELAJARAN STUDI KELAYAKAN BISNIS MELALUI METODE LEARNING CYCLE by Syamsu Hadi

“…That score was the average of all aspects investigated on three cycles. Based on result of study, it was suggested that for lecturers of Business Feasibility Study subject to apply Learning Cycle method in teaching-learning process. …”
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Mathematics e-comic in cultural context to improve student motivation and learning outcomes by Dani Farhan, M Ikhsan, Elizar Elizar

“…Method: The research used a development method based on the Plomp model, which consists of an initial investigation, design, and assessment stage. …”
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Integrating Color and Contour Analysis with Deep Learning for Robust Fire and Smoke Detection by Abror Shavkatovich Buriboev, Akmal Abduvaitov, Heung Seok Jeon

“…This study suggests a unique concatenated convolutional neural network (CNN) model that combines deep learning with hybrid preprocessing methods, such as contour-based algorithms and color characteristics analysis, to provide reliable and accurate fire and smoke detection. …”
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The Correlation Between Teachers' Emotional Intelligence and Students' Learning Engagement in EFL Class by Wahyu Satya Gumelar, Sri Fitri Wulandari, Tyara Sucia Lestari, Riki Ruswandi

“…There was a moderate level of students’ learning engagement, with a mean score of 12.46. Hypothesis analysis also found that there is a positive and significant relationship between teacher emotional intelligence and student learning engagement with a fairly strong correlation level. …”
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A burst-dependent algorithm for neuromorphic on-chip learning of spiking neural networks by Michael Stuck, Xingyun Wang, Richard Naud

“…Approaches based on burst-dependent plasticity have been proposed to address this requirement, but their ability to learn complex tasks has remained unproven. …”
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Estimating latent heat flux of subtropical forests using machine learning algorithms by Harekrushna Sahu, Pramit Kumar Deb Burman, Palingamoorthy Gnanamoorthy, Qinghai Song, Yiping Zhang, Huimin Wang, Yaoliang Chen, Shusen Wang

“…An analysis of the annual water budget, based on ERA5 precipitation data, highlights net positive water balances across the study sites. …”
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Machine learning and discriminant analysis model for predicting benign and malignant pulmonary nodules by Zhi Li, Wenjing Zhang, Jinyi Huang, Ling Lu, Dongming Xie, Jinrong Zhang, Jiamin Liang, Yuepeng Sui, Linyuan Liu, Jianjun Zou, Ao Lin, Lei Yang, Fuman Qiu, Zhaoting Hu, Mei Wu, Yibin Deng, Xin Zhang, Jiachun Lu

“…The GMU_D model constructed by discriminative analysis based on machine learning screening features had an excellent discriminative performance (AUC = 0.866, 95% CI: 0.858–0.874), and higher accuracy than the PKUPH model (AUC = 0.559, 95% CI: 0.552–0.567) and the Block model (AUC = 0.823, 95% CI: 0.814–0.833). …”
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Leveraging paired mammogram views with deep learning for comprehensive breast cancer detection by Jae Won Seo, Young Jae Kim, Kwang Gi Kim

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Multi-Sensor Fusion and Machine Learning for Forest Age Mapping in Southeastern Tibet by Zelong Chi, Kaipeng Xu

“…Forest age is a key factor in determining the carbon sequestration capacity and trends of forests. Based on the Google Earth Engine platform and using the topographically complex and climatically diverse Southeastern Tibet as the study area, we propose a new method for forest age estimation that integrates multi-source remote-sensing data with machine learning. …”
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Machine learning prediction model for lateral lymph node metastasis in rectal cancer by Longchun Dong, Shiyong Du, Hongjie Yang, Hongjie Yang, Hongjie Yang, Hongjie Yang, Xipeng Zhang, Xipeng Zhang, Xipeng Zhang, Xipeng Zhang, Zhichun Zhang, Zhichun Zhang, Zhichun Zhang, Zhichun Zhang, Shuan Geng, Shuan Geng, Shuan Geng, Shuan Geng, Yuanda Zhou, Yuanda Zhou, Yuanda Zhou, Yuanda Zhou, Peng Li, Peng Li, Peng Li, Peng Li, Qingsheng Zeng, Qingsheng Zeng, Qingsheng Zeng, Qingsheng Zeng, Yi Sun, Yi Sun, Yi Sun, Yi Sun, Peishi Jiang

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Machine Learning-Driven Acoustic Feature Classification and Pronunciation Assessment for Mandarin Learners by Gulnur Arkin, Tangnur Abdukelim, Hankiz Yilahun, Askar Hamdulla

“…This study confirms the effectiveness of objective assessment methods based on formant analysis in speech acquisition research, provides a theoretical basis for algorithm optimization in speech evaluation systems, and holds significant application value for the development of Computer-Assisted Language Learning (CALL) systems and the improvement of multi-ethnic Mandarin speech recognition technology.…”
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Deep Learning with Dual-Channel Feature Fusion for Epileptic EEG Signal Classification by Bingbing Yu, Mingliang Zuo, Li Sui

“…Developing lightweight and accurate models for real-time epilepsy detection remains a key challenge. Methods: This study proposes a novel dual-channel deep learning model to classify epileptic EEG signals into three categories: normal, ictal, and interictal states. …”
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Comparison of cardiovascular risk prediction models developed using machine learning based on data from a Sri Lankan cohort with World Health Organization risk charts for predictin... by Anuradhani Kasturiratne, Hithanadura Janaka de Silva, Chamila Mettananda, Anuradha Supun Dassanayake, Norihiro Kato, Rajitha Wickremasinghe, Maheeka Solangaarachchige, Prasanna Haddela

“…Introduction Models derived from non-Sri Lankan cohorts are used for cardiovascular (CV) risk stratification of Sri Lankans.Objective To develop a CV risk prediction model using machine learning (ML) based on data from a Sri Lankan cohort followed up for 10 years, and to compare the predictions with WHO risk charts.Design Cohort study.Setting The Ragama Health Study (RHS), an ongoing, prospective, population-based cohort study of patients randomly selected from the Ragama Medical Office of Heath area, Sri Lanka, focusing on the epidemiology of non-communicable diseases, was used to develop the model. …”
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Multi-RIS-Assisted 3D Localization and Synchronization via Deep Learning by Alireza Fadakar, Maryam Sabbaghian, Henk Wymeersch

“…Then, a hybrid asynchronous AOD time-of-arrival-based approach is proposed in the first stage to estimate an initial guess of the position of the user equipment (UE). …”
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Autonomous learning and creative cognition: the mediating effect of gifted students’ self-efficacy by Şenol Orakcı

“…In this regard, the study examined the role of gifted students’ self-efficacy (SE) as a mediator on the relationship between autonomous learning (AL) and creative cognition (CC).MethodsA proposed conceptual model was tested using a cross-sectional survey design. …”
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Quantum Machine Learning for Identifying Transient Events in X-Ray Light Curves by Taiki Kawamuro, Shinya Yamada, Shigehiro Nagataki, Shunji Matsuura, Yusuke Sakai, Satoshi Yamada

“…We investigate whether a novel method of quantum machine learning can identify anomalous events in X-ray light curves as transient events and apply it to detect such events from the XMM-Newton 4XMM-DR14 catalog. …”
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