Simultaneous text and gesture generation for social robots with small language models by Alessio Galatolo, Alessio Galatolo, Katie Winkle

Get full text

Regression models for productivity prediction in cactus pear cv. Gigante by Bruno V. C. Guimarães, Sérgio L. R. Donato, Ignacio Aspiazú, Alcinei M. Azevedo, Abner J. de Carvalho

“…ABSTRACT The understanding of plant behavior and its reflexes on yield is essential for rural planning; thus, the biomathematical models are promising in the yield prediction of cactus pear cv. …”
Get full text

Zero-Shot Prediction of Conversational Derailment With Large Language Models by Kenya Nonaka, Mitsuo Yoshida

“…Secondly, we explored the effect of inserting prior knowledge into the prompts on the behavior of the LLMs. We discovered that this practice does not necessarily improve the performance of LLMs, resulting in unexpected changes in prediction timing. …”
Get full text

Hypernetwork link prediction method based on the SCL-CMM model by REN Yuyuan, MA Hong, LIU Shuxin, WANG Kai

“…This method federated learned the structural characteristics and aggregation attributes of hypernetworks to model the high-order nonlinear behavior of each subgraph, thereby solving the problems of single category and low precision in heterogeneous hypergraphs link prediction. …”
Get full text

Evaluation of early student performance prediction given concept drift by Benedikt Sonnleitner, Tom Madou, Matthias Deceuninck, Filotas Theodosiou, Yves R. Sagaert

“…We investigate the performance of different machine learning pipelines on a data set with change in study behavior during the Covid-19 period. We demonstrate that (i) LASSO, a shrinkage estimator that reduces complexity and overfitting, outperforms several machine learning models under these circumstances, (ii) a linear regression relying on only two handcrafted features achieves higher accuracy and substantially less predictive bias than commonly used, more complex models with large feature sets. …”
Get full text

Photoinduced hydrogen dissociation in thymine predicted by coupled cluster theory by Eirik F. Kjønstad, O. Jonathan Fajen, Alexander C. Paul, Sara Angelico, Dennis Mayer, Markus Gühr, Thomas J. A. Wolf, Todd J. Martínez, Henrik Koch

“…However, conflicting theoretical predictions have made the experimental data difficult to interpret. …”
Get full text

Ada-GCNLSTM: An adaptive urban crime spatiotemporal prediction model by Miaoxuan Shan, Chunlin Ye, Peng Chen, Shufan Peng

“…A major challenge in achieving accurate predictions lies in identifying generalized patterns of criminal behavior from spatiotemporal features in crime data. …”
Get full text

Prediction-Based Tip-Over Prevention for Planetary Exploration Rovers by Siddhant Shete, Raúl Domínguez, Ravisankar Selvaraju, Mariela De Lucas Álvarez, Frank Kirchner

“…This study presents a deep learning-based prediction system with an elevated approach to prevent tip-over incidents on planetary exploration rovers, enhancing their operational safety and reliability. …”
Get full text

Predicting the frost heaving of bottom ash value for road design by A. A. Lunev, D. A. Razuvaev, V. V. Golubenko, M. G. Chakhlov

“…At the same time, the design of roads with embankments of soil materials in the Northern regions requires taking into account the behavior of materials in cold climates.Although ash and slag materials are a typical dispersed soil, it is prone to frost heaving (due to the peculiarities of the internal structure). …”
Get full text

Modeling and Predicting Human Actions in Soccer Using Tensor-SOM by Moeko Tominaga, Yasunori Takemura, Kazuo Ishii

“…In such a cooperative society, robots must possess the ability to predict human behavior. This study investigates a human–robot cooperation system using RoboCup soccer as a testbed, where a robot observes human actions, infers their intentions, and determines its own actions accordingly. …”
Get full text

Gaia: Complex systems prediction for time to adapt to climate shocks by Allen G. Hunt, Muhammad Sahimi, Boris Faybishenko, Markus Egli, Zbigniew J. Kabala, Behzad Ghanbarian, Fang Yu

“…Extrapolation of the same relationship over less than three additional orders of magnitude of time yields a continental‐scale transport time of 80 Myr, similar to the time scale for recovery from Paleozoic ice ages. We interpret this prediction in terms of Margulis’ understanding of emergent behavior of coupled (soil and plant) ecosystems responding to climate shocks induced by plant innovations that produce renewed steady‐state between wood production and decay at a new equilibrium temperature.…”
Get full text

Application of machine learning techniques for churn prediction in the telecom business by Raji Krishna, D. Jayanthi, D.S. Shylu Sam, K. Kavitha, Naveen Kumar Maurya, T. Benil

“…Telecom managers and analysts investigate why customers cancel their subscriptions and analyze the behavior patterns of customers who have stopped using the services. …”
Get full text

A Platform for Early Class Dropout Prediction of University Students by Guilherme Antonio Borges, Carolina Filipa Dos Santos Pedro, Julio Cesar Santos Dos Anjos, Andre Rodrigues, Fernando Boavida, Jorge Sa Silva

“…The analysis revealed that student performance, re-enrollment behavior, and attendance patterns are strongly correlated with the risk of early dropout. …”
Get full text

Ideological diversity of media consumption predicts COVID-19 vaccination by Marrissa D. Grant, David M. Markowitz, David K. Sherman, Alexandra Flores, Stephan Dickert, Kimin Eom, Gabriela M. Jiga-Boy, Tehila Kogut, Marcus Mayorga, David Oonk, Eric J. Pedersen, Beatriz Pereira, Enrico Rubaltelli, Paul Slovic, Daniel Västfjäll, Leaf Van Boven

“…By incorporating data from an earlier wave of the survey in the summer of 2020, before COVID-19 vaccines were available, we found that a less conservative and more ideologically diverse media diet in 2022 predicted vaccination behavior in 2022, controlling for prior vaccine intentions and media consumption in 2020. …”
Get full text

Modern approaches to predicting vaccine hesitancy: A scoping review by Keshav Gandhi, Sami Alahmadi, Rosie Hanneke, Alexander Gutfraind

“…Areas to pursue include utilizing individual-level data about vaccination behaviors in conjunction with administrative data, solving the challenge of implementing small-area spatiotemporal analysis, using vaccine-agnostic methods that consider data from more than one infectious disease, and assisting causal inference with theoretical frameworks.…”
Get full text

Lymphopenia predicts poor outcomes in newly diagnosed multiple myeloma by Grace M. Ferri, Cenk Yildirim, Nhan V. Do, Mary Brophy, Joseph S. Park, Nikhil C. Munshi, Nathanael R. Fillmore, Camille V. Edwards

Get full text

Radiogenomics and machine learning predict oncogenic signaling pathways in glioblastoma by Abdul Basit Ahanger, Syed Wajid Aalam, Tariq Ahmad Masoodi, Asma Shah, Meraj Alam Khan, Ajaz A. Bhat, Assif Assad, Muzafar Ahmad Macha, Muzafar Rasool Bhat

“…This study explores the utility of radiogenomics and machine learning (ML) in predicting these oncogenic signaling pathways in GBM patients. …”
Get full text

Simulating the Deterioration Behavior of Tunnel Elements Using Amalgamation of Regression Trees and State-of-the-Art Metaheuristics by Eslam Mohammed Abdelkader, Abobakr Al-Sakkaf, Moaaz Elkabalawy, Abdelhady Omar, Ghasan Alfalah

Get full text

Comparative analysis of control methods with predictive models of six-phase permanent magnet synchronous motor by A. A. R. Rahim, S. N. Kladiev, S. Saeidi

“…This article presents a comparison of the performance of the sixphase permanent magnet motor (PMSM) based on two control methods: continuous control set model predictive control (CCSMPC) and a finite control set model predictive control (FCSMPC). …”
Get full text

A dynamic predictive model for evaluating the impact of physical and social factors on energy conservation in buildings by Le Na Tran, Anbang Dai

“…Integrating four intensity levels reduces EUE by 29 %–81 %. This predictive model provides in-depth energy-saving suggestions in extreme environments, unique architecture, and various social behaviors, unveiling practical and specific predictive tools for building energy efficiency strategies across many detailed scenarios.…”
Get full text