Machine learning-based authentication of banknotes: a comprehensive analysis by Nadia Ghasem Abadi

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Psychological fitness for work: do we still have a long way to go? by Giuseppe Ferrari

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Un essai de typologie à l’appui de l’utilisation des jeux par les aînés by Louise Sauvé, Lise Renaud, David Kaufman, Emmanuel Duplàa

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Forecasting mental states in schizophrenia using digital phenotyping data. by Thierry Jean, Rose Guay Hottin, Pierre Orban

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Efisiensi Big Data Menggunakan Improved Nearest Neighbor by Aditya Hari Bawono, Ahmad Afif Supianto

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Polariton lattices as binarized neuromorphic networks by Evgeny Sedov, Alexey Kavokin

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CBCT analysis of the incidence of maxillary lateral incisor dens invaginatus and its impact on periodontal supporting tissues by Yanhua Wang, Sha Su, Xing Chen, Xueting Jia

“…The incidence of coronal invaginatus is 12.3%, and the incidence of radicular dens invaginatus is 14.6%. …”
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Advanced Mineral Deposit Mapping via Deep Learning and SVM Integration With Remote Sensing Imaging Data by Nazir Jan, Nasru Minallah, Madiha Sher, Muhammad Wasim, Shahid Khan, Amal Al‐Rasheed, Hazrat Ali

“…The results indicate that the SVM with a degree of 12 achieved the highest classification accuracy, followed by degrees 9, 6, and 3. …”
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Detection of Viable but Nonculturable E. coli Induced by Low-Level Antimicrobials Using AI-Enabled Hyperspectral Microscopy by MeiLi Papa, Aarham Wasit, Justin Pecora, Teresa M. Bergholz, Jiyoon Yi

“…The objectives were to (i) induce the VBNC state in Escherichia coli K-12 by exposure to selected antimicrobial stressors, (ii) obtain HMI data capturing physiological changes in VBNC cells, and (iii) automate the classification of normal and VBNC cells using deep learning image classification. …”
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Legume content estimation from UAV image in grass-legume meadows: comparison methods based on the UAV coverage vs. field biomass by Kensuke Kawamura, Tsuneki Tanaka, Taisuke Yasuda, Shoji Okoshi, Masaaki Hanada, Kazuya Doi, Toshiya Saigusa, Takanori Yagi, Kenji Sudo, Kenji Okumura, Jihyun Lim

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An effective feature selection approach based on hybrid Grey Wolf Optimizer and Genetic Algorithm for hyperspectral image by Yiqun Shang, Minrui Zheng, Jiayang Li, Xinqi Zheng

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An Artificial Intelligence-Based Hybrid Approach to Detect the Type of Buried Objects with Broad Frequency Band Antenna Systems by Ebru Efeoğlu

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Computed Tomography Evaluation of Morphological Types of Femoral Trochlear Dysplasia in Small-Breed Dogs—A Retrospective Study by Radka S. Garnoeva

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Predictive models for the implementation of targeted reproductive management in multiparous cows on automatic milking systems by Fergus P. Hannon, Martin J. Green, Luke O'Grady, Chris Hudson, Anneke Gouw, Laura V. Randall

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Reinforcement Learning Based Artificial Immune Classifier by Mehmet Karakose

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Interactions entre gestion personnelle de l’information et connaissances professionnelles des enseignants. Le cas de l’informatique et sciences du numérique (ISN) by Béatrice Drot-Delange

“…PIM is studied through operations of classificatory documentarization, that is, the classification, naming and indexing of resources (Zacklad et al., 2011). …”
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Antenna azimuth diagnosis based on multi-layer perceptron model by Xiangrong CHEN

“…Antenna azimuth was seen as a key factor in the quality of mobile communications, and its accuracy will directly affect the quality of network optimization.An antenna azimuth diagnosis method was proposed based on multi-layer perceptron.The azimuth was divided into 12 interval classes, each class covered a range of 30°, that was,[0, 30°) was recorded as class 0, …,[330°, 360°) was recorded as class 11.The multi-layer perceptron algorithm was used to identify the range of the antenna azimuth angle and automatically identify the angle range of the antenna azimuth angle, which provided effective data support for the network optimization engineer to determine the actual network coverage problem, and greatly reduced workload and labor cost in verifying antenna performance.Experimental results show that the method can effectively and quickly discriminate the antenna azimuth interval class, and the recognition accuracy reaches 92.6%, which is higher than the classification accuracy of random forest and logistic regression classification algorithms.…”
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Real structures on primary Hopf surfaces by Khaled Zahraa

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FAULT DIAGNOSIS OF WIND TURBINE BEARING BASED ON SENET-RESNEXT-LSTM by DU HaoFei, ZHANG Chao, LI JianJun

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Blind recognition of STBC-OFDM signals based on modified K-S test by Qing LING, Li-min ZHANG, Wen-jun YAN

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