String-to-Dependency Statistical Machine Translation by Libin Shen, Jinxi Xu, Ralph Weischedel

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Real-Time Stringing Detection for Additive Manufacturing by Oumaima Charia, Hayat Rajani, Inés Ferrer Real, Miquel Domingo-Espin, Nuno Gracias

“…This study explores the implementation of traditional computer vision, image processing, and machine learning techniques to enable real-time error detection, specifically focusing on stringing-related anomalies. …”
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Measurement and Application of Track Long String Based on Fixed Points by LIU Tiejun

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<p><strong>The underwater survival of adult and larval stages of <em>Argas persicus</em></strong><strong><em> </em></strong><strong>(Acari: Argasidae)</strong></p> by Mousa Tavassoli, Zahra Rezanejad Sabeghi, Behnaz Ghorbanzadeh, Shokoofeh Shamsi, Jafar Arjmand, Mostafa Golabi

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Assessing concordance between RNA-Seq and NanoString technologies in Ebola-infected nonhuman primates using machine learning by Mostafa Rezapour, Aarthi Narayanan, Wyatt H. Mowery, Metin Nafi Gurcan

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Adaptation of deep learning models to distinguish species with strongly overlapping characteristics: the example of spores of the genus Riccia by Stefan Herdy, Martina Pöltl, Christian Berg, Bettina Weber

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Partner relationships, hopelessness, and health status strongly predict maternal well-being: an approach using light gradient boosting machine by Hikaru Ooba, Jota Maki, Takahiro Tabuchi, Hisashi Masuyama

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Machine learning revealed giant thermal conductivity reduction by strong phonon localization in two-angle disordered twisted multilayer graphene by Jingwen Wang, Zheng Zhu, Tianran Jiang, Ke Chen

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Investigation of Obtaining Highly-Strong Wire of 12X18H10T-Steei by Drawing Method with Electrolyte-Plasma Surface Machining by L. A. Isaevich, Yu. G. Aliakseyeu, A. Yu. Korolyov

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Numerical Polynomial Homotopy Continuation Method and String Vacua by Dhagash Mehta

“…Finding vacua for the four-dimensional effective theories for supergravity which descend from flux compactifications and analyzing them according to their stability is one of the central problems in string phenomenology. Except for some simple toy models, it is, however, difficult to find all the vacua analytically. …”
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Analysis on the difference of volatile flavor components in strong-flavor Baijiu base liquor with different grades by YUE Xiaolin, XIANG Shuangquan, QIAN Yu, LIAN Shengqiang, YANG Guorui, LAN Xiaoqin, TAN Wenyuan

Subjects: “…strong-flavor baijiu|base liquor|volatile flavor component|chemometrics|machine learning|difference analysis…”
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Development of intelligent traction machine for tensioning and paying off construction of transmission lines by Xiaobin Li, Shuo Wang, Feng Wang, Riping Zheng, Zixin Li, Hongbing Wen

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Real-time lithology identification while drilling based on drilling parameters analysis with machine learning by Kun Li, Ting Ren, Ningping Yao, Jon Roberts, Haitao Song, Zhongbei Li, Chunmiao Liang

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Aeroelastic Simulation of Full-Machine Wind Turbines Using a Two-Way Fluid-Structure Interaction Approach by Nan-You Lu, Jia Kai Lam, Yu Lin, Shiu-Wu Chau

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Autoencoder-driven clustering of intersecting D-brane models via tadpole charge by Keiya Ishiguro, Satsuki Nishimura, Hajime Otsuka

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NanoCMSer: a consensus molecular subtype stratification tool for fresh‐frozen and paraffin‐embedded colorectal cancer samples by Arezo Torang, Simone van deWeerd, Veerle Lammers, Sander vanHooff, Inge van denBerg, Saskia van denBergh, Miriam Koopman, Jan N. IJzermans, Jeanine M. L. Roodhart, Jan Koster, Jan Paul Medema

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Leveraging snow probe data, lidar, and machine learning for snow depth estimation in complex-terrain environments by D. Liljestrand, R. Johnson, B. Neilson, P. Strong, E. Cotter

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Beyond N-Grams: Enhancing String Kernels With Transformer-Guided Semantic Insights by Nazar Zaki, Reem Alderei, Mahra Alketbi, Alia Alkaabi, Fatima Alneyadi, Nadeen Zaki

“…This study presents a novel hybrid framework that effectively integrates string kernel approaches with deep contextual embeddings from state-of-the-art transformers for robust AI-generated text detection. …”
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LRS Bianchi Type-I String Cosmological Models in fQ Gravity by Mukesh Kumar, Manvinder Singh, Mohit Bajaj, Hossam Kotb, Djeudjo Temene Hermann

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Dextrosinistral reading of SMILES notation: Investigation into origin of non-sense code from string manipulations by Anup Paul

“…The SMILES notation provides a digital way to represent any chemical structure in the form of a string of ASCII characters, therefore, a preferred data medium for machine learning models. …”
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