Results 151 to 160 of about 197,254 (306)

Computational linguistics for design, maintenance, and manufacturing [PDF]

, 2007
Nicole Segers, Pierre Leclercq
openalex   +1 more source

DeepSeek in Education: Exploring the Transformative Potential of AI‐Driven Educational Intelligence

Future in Educational Research, EarlyView.
ABSTRACT The integration of artificial intelligence into education remains challenged by issues of scalability, interpretability, and multimodal adaptability. DeepSeek's AI‐driven educational tools show potential to improve educational applications through advances in reasoning efficiency, lightweight deployment, and multimodal fusion.
Jian Liao, Fan Sun, Yajie Liu, Yuli Hu
wiley   +1 more source

Proceedings of the 2018 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 1 (Long Papers)

, 2018

openalex   +1 more source

Reflective Pathways: Integrating Empathy Into the STEM Student Experiences

Future in Educational Research, EarlyView.
ABSTRACT The growing demand for a globally competent STEM workforce showcases the importance of embedding empathy into undergraduate education. As a core dimension of global competence, empathy enables individuals to engage diverse perspectives and navigate collaborative challenges.
Aparajita Jaiswal, Nathan S. Bitner, Gaurav Nanda, Muna Sapkota   +3 more
wiley   +1 more source

Implementation of Federal and State Policies for Students Identified With or at‐Risk for Dyslexia in Ohio

Future in Educational Research, EarlyView.
ABSTRACT This study reveals constructs that determine how federal and state policies for identification of and services for students with dyslexia are implemented in three Ohio suburban public schools. The research questions guiding this study were: (a) How do K–12 public educators interpret federal and state policies for the identification of students
Rebecca Tolson
wiley   +1 more source

Proceedings of 52nd Annual Meeting of the Association for Computational Linguistics: System Demonstrations [PDF]

, 2014
Kalina Bontcheva, Beatrice Alex, Omar Alonso, Thierry Declerck, Dirk Hovy, Degen Huang, Brigitte Kren, Ofai Oi, Yee Kwong, Maggie Li, Wenjie Li, Nicolas Nicolov, Patrick Paroubek, Stelios Limsi, Athena Piperidis, Barbara Rc/Ilsp, Plank, John Tait, Yih Su, Le Sun, Marc Vilain, Leo Wanner, Derek Wong, Wei Xu, Liang-Chih Yu, Yuan Ze University, Jiajun Zhang, Tiejun Zhao, Chung-Chi Huang, Maxine Eskenazi, Jaime Carbonell, Lun-Wei Ku, Ping-Che Yang, Markus Grtner, Anders Bjrkelund, Gregor Thiele, Wolfgang Seeker, Jonas Kuhn, Jana Strakov, Milan Straka, Jan Haji, Jianyi Liu, Wenbin Liu, Cong Yao, Wang, Zhiyuan Liu, Wenyi Huang, Yabin Zheng, Maosong Sun, Wei-Yun Ma, Keh-Jiann Chen, Rada Mihalcea, Paul Tarau, Josef Franz, Hermann Och, Ney, Yoshimasa Tsuruoka, Jun'ichi Tsujii, D Peter, Turney, Wei Wu, Bin Zhang, Mari Ostendorf, Jing Wayne Xin Zhao, Jing Jiang, Yang He, Palakorn Song, Ee-Peng Achananuparp, Xiaoming Lim, Li, Rie Kubota, Ando, Tong Zhang, Donald Knuth, Michal Konkol, Miloslav Konopk, Michal Konkol, Miloslav Konopk, Jana Kravalov, Zdenk abokrtsk, Mitchell Marcus, Beatrice Santorini, Mary Marcinkiewicz, Lev Ratinov, Dan Roth, Libin Shen, Giorgio Satta, Aravind Joshi, Jan Spoustov, Jan Haji, Miroslav Raab, Spousta, Jana Strakov, Milan Straka, Jan Haji, Jun Suzuki, Hideki Isozaki, Erik Tjong, Kim Sang, Fien De   +99 more
openalex   +1 more source

Machine Learning Approaches for GC–MS Data Interpretation in Flavour and Fragrance Analysis

Flavour and Fragrance Journal, EarlyView.
The review explores machine learning integration in GC‐MS data analysis for the fragrance and flavour industry, highlighting recent advances and techniques in a context constrained by data scarcity and intellectual property concerns. ABSTRACT This review explores the integration of machine learning (ML) in the analysis of mass spectrometry data ...
Jean‐Baptiste Coffin, Romain Krafft, Sylvain Antoniotti, Sébastien Fiorucci   +3 more
wiley   +1 more source

A Fuzzy Framework for Realized Volatility Prediction: Empirical Evidence From Equity Markets

Journal of Forecasting, EarlyView.
ABSTRACT This study introduces a realized volatility fuzzy time series (RV‐FTS) model that applies a fuzzy c‐means clustering algorithm to estimate time‐varying c$$ c $$ latent volatility states and their corresponding membership degrees. These memberships are used to construct a fuzzified volatility estimate as a weighted average of cluster centroids.
Shafqat Iqbal, Štefan Lyócsa
wiley   +1 more source

Health adaptation policy for climate vulnerable groups: a 'critical computational linguistics' analysis. [PDF]

BMC Public Health, 2014
Seidel BM, Bell E.
europepmc   +1 more source