Data fusion-based improvements in empirical regression and machine learning for global daily ∼ 8 km resolution sea surface nitrate estimation and interpretation by Aifen Zhong, Difeng Wang, Fang Gong, Jingjing Huang, Zhuoqi Zheng, Xianqiang He, Qing Zhang, Qiankun Zhu

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Using machine learning to develop a stacking ensemble learning model for the CT radiomics classification of brain metastases by Huai-wen Zhang, Yi-ren Wang, Bo Hu, Bo Song, Zhong-jian Wen, Lei Su, Xiao-man Chen, Xi Wang, Ping Zhou, Xiao-ming Zhong, Hao-wen Pang, You-hua Wang

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Tracking Sumatran Tiger (Panthera tigris sumatrae Pocock, 1929) distribution in Gunung Leuser National Park: The influence of prey presence and environmental variables on habitat s... by M Hadi Saputra, Salmah Widyastuti, Wanda Kuswanda, R. Taufiq Purna Nugraha, Hendra Helmanto, Nunu Anugrah, U Mamat Rahmat, Rudianto Saragih Napitu, Andrinaldi Adnan, Iskandarrudin, Agus Purwoko, Pindi Patana

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Comparative study on Functional Machine learning and Statistical Methods in Disease detection and Weed Removal for Enhanced Agricultural Yield by Sudha D., Menaga D.

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N-SOFT SETS ASSOCIATION RULE AND ITS APPLICATION FOR PROMOTION STRATEGY IN DISTANCE EDUCATION by Fatia Fatimah, Selly Anastassia Amellia Kharis, Fauzan Ihza Fajar

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Differentiation of Soybean Genotypes Concerning Seed Physiological Quality Using Hyperspectral Bands by Izabela Cristina de Oliveira, Dthenifer Cordeiro Santana, Victoria Toledo Romancini, Ana Carina da Silva Cândido Seron, Charline Zaratin Alves, Paulo Carteri Coradi, Carlos Antônio da Silva Júnior, Regimar Garcia dos Santos, Fábio Henrique Rojo Baio, Paulo Eduardo Teodoro, Larissa Ribeiro Teodoro

“…The experiment was conducted during the 2021/2022 harvest at the Federal University of Mato Grosso do Sul in a randomized block design with four replicates and 10 F3 soybean populations (G1, G8, G12, G15, G19, G21, G24, G27, G31, and G36). …”
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Evaluating Recycling Initiatives for Landfill Diversion in Developing Economies Using Integrated Machine Learning Techniques by Muyiwa Lawrence Adedara, Ridwan Taiwo, Olusola Olaitan Ayeleru, Hans-Rudolf Bork

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A toolkit for quantifying individual response to herbal extracts in metabolic and inflammatory stress by Soo-yeon Park, Oran Kwon, Tim van den Broek, Jildau Bouwman, Ji Yeon Kim

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Incorporating food plant distributions as important predictors in the habitat suitability model of sumatran orangutan (Pongo abelii) in Gunung Leuser National Park, Indonesia by Salmah Widyastuti, Wanda Kuswanda, M. Hadi Saputra, Hendra Helmanto, Nunu Anugrah, U. Mamat Rahmat, Rudianto Saragih Napitu, Andrinaldi Adnan, Iskandarrudin

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A secure medical image encryption technique based on DNA cryptography with elliptic curves by V. N. Senthil Kumaran, T. Manikandan, Rajesh Kumar Dhanaraj, Taher Al-Shehari, Nasser A. Alsadhan, Shitharth Selvarajan

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The application of blockchain with a comparative approach and its impact on risk, flexibility and internal control evaluation by mohammadsadegh aminipoor, HamidReza GholamniaRoshan, azadeh kiapour, Iman Dadashi

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Artificial intelligence in psychiatry: A systematic review and meta-analysis of diagnostic and therapeutic efficacy by Moustaq Karim Khan Rony, Dipak Chandra Das, Most. Tahmina Khatun, Silvia Ferdousi, Mosammat Ruma Akter, Mst. Amena Khatun, Most. Hasina Begum, Md Ibrahim Khalil, Mst. Rina Parvin, Daifallah M Alrazeeni, Fazila Akter

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Digital Self-Management Intervention Paths for Early Breast Cancer Patients: Results of a Pilot Study by Paula Poikonen-Saksela, Evangelos Karademas, Leena Vehmanen, Meri Utriainen, Haridimos Kondylakis, Konstadina Kourou, Georgios C. Manikis, Eleni Kolokotroni, Panagiotis Argyropaidas, Berta Sousa, Ruth Pat Horenczyk, Ketti Mazzocco, Johanna Mattson

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Residential Electricity Load Model Construction in District Scale by Jieyan XU, Wenyang XU, Yuan CHU, Yuan JIN, Xuyuan KANG, Zheng CHEN

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Predicting chronic pain using wearable devices: a scoping review of sensor capabilities, data security, and standards compliance by Johannes C. Ayena, Johannes C. Ayena, Amina Bouayed, Amina Bouayed, Myriam Ben Arous, Myriam Ben Arous, Youssef Ouakrim, Youssef Ouakrim, Karim Loulou, Karim Loulou, Darine Ameyed, Isabelle Savard, Leila El Kamel, Neila Mezghani, Neila Mezghani

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The Impact of Integrated Project-Based Learning and Flipped Classroom on Students’ Computational Thinking Skills: Embedded Mixed Methods by Muh Fitrah, Anastasia Sofroniou, Caly Setiawan, Widihastuti Widihastuti, Novi Yarmanetti, Melinda Puspita Sari Jaya, Jontas Gayuh Panuntun, Arfaton Arfaton, Septrisno Beteno, Ika Susianti

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Lessons from the PROTECT-CH COVID-19 platform trial in care homes by Philip M Bath, Jonathan Ball, Matthew Boyd, Heather Gage, Matthew Glover, Maureen Godfrey, Bruce Guthrie, Jonathan Hewitt, Robert Howard, Thomas Jaki, Edmund Juszczak, Daniel Lasserson, Paul Leighton, Val Leyland, Wei Shen Lim, Pip Logan, Garry Meakin, Alan Montgomery, Reuben Ogollah, Peter Passmore, Philip Quinlan, Caroline Rick, Simon Royal, Susan D Shenkin, Clare Upton, Adam L Gordon

“…Multiple delays significantly delayed the start date, such as: (1) reduced prioritisation of pandemic trials in 2021; (2) cumbersome mechanisms for choosing the investigational medicinal products; (3) contracting between National Institute for Health and Care Research and the investigational medicinal product manufacturers; (4) publicising the investigational medicinal products; (5) identification of sufficient numbers of care homes; (6) identification and contracting with several thousand general practitioners; (7) limited research nurse availability and (8) identification of adequate insurance to cover care homes for research. …”
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Reinforcement learning for vehicle-to-grid: A review by Hongbin Xie, Ge Song, Zhuoran Shi, Jingyuan Zhang, Zhenjia Lin, Qing Yu, Hongdi Fu, Xuan Song, Haoran Zhang

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RICE AlgebraBot: Lessons learned from designing and developing responsible conversational AI using induction, concretization, and exemplification to support algebra learning by Chenglu Li, Wanli Xing, Yukyeong Song, Bailing Lyu

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Exploring Transfer Learning for Anthropogenic Geomorphic Feature Extraction from Land Surface Parameters Using UNet by Aaron E. Maxwell, Sarah Farhadpour, Muhammad Ali

“…Semantic segmentation algorithms, such as UNet, that rely on convolutional neural network (CNN)-based architectures, due to their ability to capture local textures and spatial context, have shown promise for anthropogenic geomorphic feature extraction when using land surface parameters (LSPs) derived from digital terrain models (DTMs) as input predictor variables. …”
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