Microplastic Identification Using Impedance Spectroscopy and Machine Learning Algorithms by Juan Sarmiento, Maribel Anaya, Diego Tibaduiza

“…As a contribution to the solution of this problem, this work presents a microplastic detection and classification methodology that uses an electronic tongue system, impedance spectroscopy, and machine learning algorithms for detecting and classifying microplastics. …”
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Secure federated learning scheme based on adaptive Byzantine defense by ZHOU Yousheng, GAO Jingkun, ZUO Xiangjian, LIU Yuanni

Subjects: “…federated learning…”
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Cyberinfrastructure for machine learning applications in agriculture: experiences, analysis, and vision by Lucas Waltz, Sushma Katari, Chaeun Hong, Adit Anup, Julian Colbert, Anirudh Potlapally, Taylor Dill, Canaan Porter, John Engle, John Engle, Christopher Stewart, Hari Subramoni, Scott Shearer, Raghu Machiraju, Osler Ortez, Laura Lindsey, Arnab Nandi, Sami Khanal

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Psychological determinants of learning activities of academically underachieving university students by E. Yu. Cherniakevich

“…The results of an empirical study aimed at studying the features of the learning activity style, self-organisation processes, academic motivation, personal meaning of learning for academically unsuccessful students are presented. …”
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Participatory Forest Carbon Assessment and REDD+: Learning from Tanzania by Kusaga Mukama, Irmeli Mustalahti, Eliakimu Zahabu

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Comparison of Machine Learning Techniques for the Prediction of Compressive Strength of Concrete by Palika Chopra, Rajendra Kumar Sharma, Maneek Kumar, Tanuj Chopra

“…A comparative analysis for the prediction of compressive strength of concrete at the ages of 28, 56, and 91 days has been carried out using machine learning techniques via “R” software environment. R is digging out a strong foothold in the statistical realm and is becoming an indispensable tool for researchers. …”
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Innovation in Public Libraries :Learning From International Library Practice. by فاطمة محمد الامين

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A Mobile Deep Learning Classification Model for Diabetic Retinopathy by Daniel Rimaru, Antonio Nehme, Musaed Alhussein, Khaled Mahbub, Khusheed Aurangzeb, Anas Khan

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Lessons Learned on the Application of Vibration Absorbers for Enhanced Cannon Stabilization by Eric Kathe

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Federated Learning Approach for Breast Cancer Detection Based on DCNN by Hussain AlSalman, Mabrook S. Al-Rakhami, Taha Alfakih, Mohammad Mehedi Hassan

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Learning to Live Through Loss: Helping Children Understand Death by Carolyn S. Wilken

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Oral cannabidiol did not impair learning and memory in healthy adults by Hanna H. Gebregzi, Joanna S. Zeiger, Jeffrey P. Smith, Libby Stuyt, Luann Cullen, Jim Carsella, Daniel C. Rogers, Jordan Lafebre, Jennah Knalfec, Alfredo Vargas, Moussa M. Diawara

“…Abstract Background The effect of oral Cannabidiol (CBD) on interference during learning and memory (L&M) in healthy human volunteers has not been studied. …”
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Oral English Auxiliary Teaching System Based on Deep Learning by Chenhui Qu, Yuanbo Li

“…In order to solve the problem of the oral English auxiliary teaching system, a research based on Deep Learning was proposed. Based on the theory of Deep Learning, the teaching mode of Deep Learning for college students built on information technology was investigated in the research. …”
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FedDrip: Federated Learning With Diffusion-Generated Synthetic Image by Karin Huangsuwan, Timothy Liu, Simon See, Aik Beng Ng, Peerapon Vateekul

Subjects: “…Federated learning…”
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Deep learning enhanced transmembranous electromyography in the diagnosis of sleep apnea by Ross Mandeville, Hooman Sedghamiz, Perry Mansfield, Geoffrey Sheean, Chris Studer, Derrick Cordice, Ghodsieh Ghanbari, Atul Malhotra, Shamim Nemati, Jejo Koola

Subjects: “…Deep learning in medicine…”
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Bayesian Q learning method with Dyna architecture and prioritized sweeping by Jun YU, Quan LIU, Qi-ming FU, Hong-kun SUN, Gui-xing CHEN

Subjects: “…reinforcement learning…”
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Supervised and Self-Supervised Learning for Assembly Line Action Recognition by Christopher Indris, Fady Ibrahim, Hatem Ibrahem, Götz Bramesfeld, Jie Huo, Hafiz Mughees Ahmad, Syed Khizer Hayat, Guanghui Wang

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Deep Learning Approach for Ascaris lumbricoides Parasite Egg Classification by Narut Butploy, Wanida Kanarkard, Pewpan Maleewong Intapan

“…This research proposes deep learning for A. lumbricoides’s egg image recognition to be used as a prototype tool for parasite egg detection in medical diagnosis. …”
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Predictive Control for Steel Rib Bending Based on Deep Learning by Yijiang Xia, Jinhui Luo, Zhuolin Ou, Xin Han, Junlin Deng, Ning Wu

Subjects: “…machine learning…”
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Instance structure based multi-label learning with missing labels by Tianzhu CHEN, Fenghua LI, Yunchuan GUO, Zifu LI

Subjects: “…multi-label learning…”
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