Revealing the potential of Netzwerk neu A1: A comparative study using Funk’s criteria and Mukundan et al.’s framework by Nurvi Alvi Laili Rohmatin Yuwono, Primardiana Hermilia Wijayati

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The Effectiveness of the Learning Module Cooperative Learning Student Facilitator and Explaining by Ramadhani Rahmatullah, Syahril Syahril, Rijal Abdullah

“… Low understanding of students impacts low student learning outcomes in subjects due to teacher-centered learning orientation. …”
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Automatic Receiver Function Picking Using Fuzzy C‐Means Clustering by Neng Xiong, Fenglin Niu, Hongrui Qiu, Yuyan Liu, Wenpei Miao

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AI, machine learning and deep learning in cyber risk management by Ishrag Hamid, M. M. Hafizur Rahman

“…Abstract The integration of Artificial Intelligence (AI) and Machine Learning (ML) in both climate change and cyber risk management has significantly bolstered their effectiveness. …”
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Analysis of Wind–Wave Relationship in Taiwan Waters by Kai-Ho Cheng, Chih-Hsun Chang, Yi-Chung Yang, Yu-Hao Tseng, Chung-Ru Ho, Tai-Wen Hsu, Dong-Jiing Doong

“…The relationship between wind speed and significant wave height (SWH) was examined using regression analysis. Additionally, machine learning techniques were employed to assess the relative importance of features contributing to SWH growth. …”
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Integrated approach of extreme learning machines and locally weighted linear regression for improved discharge coefficient prediction by Mohammed Majeed Hameed, Mohamed Khalid Alomar, Siti Fatin Mohd Razali, Ali Salem

“…Additionally, sensitivity analysis identified the ratio of weir height to length and dimensionless length as critical factors affecting Cd estimation. …”
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Opinion Mining and Perceptions of Self-Determination in Videoconference Classrooms Using Machine Learning and Multidimensional Sentiment Frameworks by Bosede Iyiade Edwards

“… This study provides a comprehensive analysis of learner sentiments regarding learning in videoconference (VC) environments, highlighting critical areas for improving digital education. …”
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IER-SMCEM: An Implicit Expression Recognition Model of Emojis in Social Media Comments Based on Prompt Learning by Jun Zhang, Chaobin Wang, Ziyu Liu, Hongli Deng, Qinru Li, Bochuan Zheng

“…Therefore, the model can be effectively applied to sentiment analysis or quantitative analysis.…”
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Analysis of drug crystallization by evaluation of pharmaceutical solubility in various solvents by optimization of artificial intelligence models by Wael A. Mahdi, Adel Alhowyan, Ahmad J. Obaidullah

“…In this investigation, the solubility of salicylic acid as drug model in a variety of solvents is predicted through the utilization of multiple machine learning techniques. The dataset consists of 217 data points, each of which contains 15 input features, including pressure, temperature, and a variety of solvents. …”
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How deep learning identifies and learns aspects of plant for classification by Devi V. Sowmya, Pooja Govu, Ramya Sande, Priya Nakka Vishnu

“…By merging classical structural approach with innovative machine learning methods. We gathered data from diverse plants highlighting mainly on leaves, fruits, flowers and vegetables. …”
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Desentiment: A New Method to Control Sentimental Tendency During Summary Generation by Hongyu Cao, Jinlong Li

“…Due to a scarcity of labeled data for sentiment-supervised summarization, we utilize sentiment sentences from original texts as positive samples in the training process, augmented with a prompt learning method. …”
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MEETING ESP NEEDS OF NURSING STUDENTS: PERSPECTIVES FROM STUDENTS AND PROFESSIONAL by Noni Agustina, Ratnawati Susanto, Mira Asmirajanti, Adam Astrada, Gisely Vionalita

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Novel cancer subtyping method guided by tumor-normal sample in latent space of transcriptomic variational autoencoder by Hongzhi Wang, Yu Zhang, Dandan Zhang, Min Luo

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FOUR DOMINANT FACTORS INFLUENCING STUDENTS' MATHEMATICAL CURIOSITY by Dadang Juandi, Nurul Farida, Saddam Al Aziz, Welli Meinarni

“…This study aims to develop and validate a measurement instrument for students' mathematical curiosity through an exploratory factor analysis (EFA) approach. The background of this study is based on the importance of curiosity in mathematics learning, which plays a role in encouraging exploration, and deep understanding, and improving students' learning performance. …”
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Data-driven insights into the electronic and thermoelectric properties of 1T-Li2O: A combined DFT and ML investigation by S. Chellaiya Thomas Rueshwin, R.D. Eithiraj

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Medical data security and effective organization using integrated Blockchain principles in AI-based healthcare 6.0 infrastructures by Mohammad Gouse Galety, Kuan Tak Tan, Pravin R. Kshirsagar, Subba Rao Polamuri

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Can AI-Based Video Analysis Help Evaluate the Performance of the Items in the Bayley Scales of Infant Development? by Dong Hyun Ye, Tae Won Kim, Su Min Kim, Ji Won Seo, Jongyoon Chang, June-Goo Lee, Eun Jae Ko

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Hierarchical clustering of the pre-exam anxiety levels in physically inactive and active adolescent students from 56 countries: an observational study using PISA program data by Samuel Encarnação, Samuel Encarnação, Samuel Encarnação, José Eduardo Teixeira, José Eduardo Teixeira, José Eduardo Teixeira, José Eduardo Teixeira, José Eduardo Teixeira, José Eduardo Teixeira, Pedro Forte, Pedro Forte, Pedro Forte, Luciano Bernardes Leite, Luciano Bernardes Leite, Andrew Sortwell, Andrew Sortwell, Luís Branquinho, Luís Branquinho, Luís Branquinho, Luís Branquinho, Ricardo Ferraz, Ricardo Ferraz, Pedro Afonso, Pedro Afonso, Paula Vaz, Paula Vaz, António Miguel Monteiro, António Miguel Monteiro

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Integrating bulk and single cell sequencing data to identify prognostic biomarkers and drug candidates in HBV associated hepatocellular carcinoma by Yanjie Zhong, Antony Stalin, Yushi Dai, Zhiqiang He, Siqi Yang, Ruiqi Zou, Aoqiang Zhai, Fuyu Li, Haijie Hu

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Coastal Urban Ecological Security Pattern Identification Integrating Land Subsidence Factors: A Deep Learning-Based Case Study of Zhuhai City by Yuan Shaoxiong, Gong Qinghua, Ye Yuyao, Wang Jun, Hao Yinlei, Zhang Yaze, Liu Bowen

“…This study proposes a framework that integrates land subsidence into ESP construction through machine learning and multi-source data fusion methods. Using Zhuhai City as a case study, we analyzed 30 environmental variables, including historical land subsidence data, topography, soil distribution, land use, climatic factors, and human activity indicators. …”
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