One for All: Neural Joint Modeling of Entities and Events

The previous work for event extraction has mainly focused on the predictions for event triggers and argument roles, treating entity mentions as being provided by human annotators. This is unrealistic as entity mentions are usually predicted by some existing toolkits whose errors might be propagated to the event trigger and argument role recognition. Few of the recent work has addressed this problem by jointly predicting entity mentions, event triggers and arguments. However, such work is limited to using discrete engineering features to represent contextual information for the individual tasks and their interactions. In this work, we propose a novel model to jointly perform predictions for entity mentions, event triggers and arguments based on the shared hidden representations from deep learning. The experiments demonstrate the benefits of the proposed method, leading to the state-of-the-art performance for event extraction.Comment: Accepted at The Thirty-Third AAAI Conference on Artificial Intelligence (AAAI-19) (Honolulu, Hawaii, USA

Sequential sampling strategy for the modeling of parameterized microwave and RF components

Accurate modeling of parameterized microwave and RF components often requires a large number of full-wave electromagnetic simulations. In order to reduce the overall simulation cost, a sequential sampling algorithm is proposed that selects a sparse set of data samples which characterize the overall response of the system. The resulting data samples can be fed into existing modeling techniques. The effectiveness of the approach is illustrated by a parameterized H-shaped microwave antenna

The relationship between service quality, customer satisfaction and customer loyalty: An investigation in Vietnamese retail banking sector

This study develops and empirically tests the interrelationships between service quality, customer satisfaction, and customer loyalty in a retail banking context. Increasingly intense competitiveness and fundamental changes in the business environment nowadays are forcing firms to implement a customer-focused strategy which raises the importance of customer-related constructs such as customer satisfaction, service quality, and customer loyalty in explaining a firm’s performance. In particular, they are essential for competitiveness in industries where the exchanges are complex and customers are closely involved in the decision-making process, such as the banking industry. In this study, first, a research model about the interrelationships between service quality, customer satisfaction, and customer loyalty is suggested. Then a survey is conducted with retail banking customers about these constructs, which results in 261 valid respondents. The hypotheses are then proposed and tested using confirmatory factor analysis (CFA) and the structural equation modelling technique (SME). The analysis reveals that service quality and customer satisfaction are important antecedents of customer loyalty and customer satisfaction mediates the effects of service quality on customer loyalty. These findings suggest that there are non-linear relationships between three constructs and emphasize the need to treat customer loyalty management as a process which includes plenty of factors interacting with each other.Internal Grant Agency of Faculty of Management and Economics, Tomas Bata University in Zlin [IGA/FaME/2016/020

DYNAMICS OF PREDATOR-PREY POPULATION WITH MODIFIED LESLIE-GOWER AND HOLLING-TYPE II SCHEMES

Joint Research on Environmental Science and Technology for the Eart