Search results

Structural health monitoring (SHM) has gained significant attention due to its capability in providing support for efficient and optimal bridge maintenance activities. However, despite the promising potential, the effectiveness of SHM system might be hindered by unprecedented factors that impact the continuity of data collection. This research presents a framework utilising convolutional neural network (CNN) for estimating structural response using environmental variations.

The CNN framework is validated using monitoring data from the Suramadu bridge monitoring system. Pre-processing is performed to transform the data into data frames, each containing a sequence of data. The data frames are divided into training, validation and testing sets. Both the training and validation sets are employed to train the CNN models while the testing set is utilised for evaluation by calculating error metrics such as mean absolute error (MAE), mean absolute percentage error (MAPE) and root mean square error (RMSE). Comparison with other machine learning approaches is performed to investigate the effectiveness of the CNN framework.

The CNN models are able to learn the trend of cable force sensor measurements with the ranges of MAE between 10.23 kN and 19.82 kN, MAPE between 0.434% and 0.536% and RMSE between 13.38 kN and 25.32 kN. In addition, the investigation discovers that the CNN-based model manages to outperform other machine learning models.

This work investigates, for the first time, how cable stress can be estimated using temperature variations. The study presents the first application of 1-D CNN regressor on data collected from a full-scale bridge. This work also evaluates the comparison between CNN regressor and other techniques, such as artificial neutral network (ANN) and linear regression, in estimating bridge cable stress, which has not been performed previously.

This paper aims to empirically test the influence of fraud awareness, information accountability and capacity for accessing financing on sustainable competitive advantage. Furthermore, this research examines the influence of fraud awareness and information accountability on sustainable competitive advantage through capacity for accessing financing. Finally, this research examines the influence of governance as a moderator of fraud awareness and information accountability on capacity for accessing financing.

This research uses quantitative methods. Researchers collected data by distributing questionnaires to tourism destination operators. This research used tourist destinations in Indonesia and obtained 506 samples. The data analysis technique uses SEM-PLS.

This research finds that fraud awareness, information accountability and the capacity for accessing financing increase sustainable competitive advantage. Furthermore, the capacity for accessing financing can mediate the influence of fraud awareness and information accountability on sustainable competitive advantage. Finally, governance strengthens the influence of fraud awareness and information accountability on the capacity for accessing financing.

Research limitations are the difficulty accessing all tourist destinations in Indonesia and difficulty controlling respondent answer bias.

Practical implications are increasing the ability of tourist destinations to compete, helping to increase funding sources, good governance and information accountability.

Apart from that, the main implication of this research is to increase fraud awareness and reduce fraud so that tourist destinations can achieve their goals.

The gap lies in previous research, which was unaware of the existence of fraud, which could damage the ability of tourist destinations to compete. Therefore, this research adds the fraud awareness variable. Besides, this study develops a different and unique model because it combines mediation and moderation variables into one research model.

The purpose of this paper is to evaluate the institutionalization of an accrual accounting system in the Indonesian public sector.

The authors undertake a case study to gain insights relating to the critical features of the institutionalization process of the accrual accounting system (AAS) in one Indonesian public sector municipality. The data are drawn from official documents of the Indonesian Government and from publicly available information about the accrual adoption processes. The authors also interviewed key actors who were involved in the accrual accounting policy formulation, standards development and implementation. The data under investigation cover the period from 1983 to 2010.

The IPM of Dambrin, Lambert and Sponem is employed to evaluate the process by which an AAS was idealized, standardized, implemented and used in one Indonesian municipality. Scott's pillars of legitimization also inform rationales behind practice. This study reveals how the decision of the Indonesian Government to adopt accrual accounting in 2003 was part of greater political and economic reforms following the financial and political crisis that occurred in 1998. Idealized in the early 1980s by technocrats in the Ministry of Finance, accrual accounting practices were deferred and then enabled by a series of national political events. Their ultimate internalization into our municipality was led by new legislation but also influenced by the habits and histories of the Indonesian local context and was as a result decoupled in many respects from ideals, discourses and techniques established for it.

The findings should be understood in the economic, social and historical context of Indonesia. Findings offered here may differ from other applications due to the nature of the economic, social and political contexts.

Uniquely employing the IPM model, and drawing from a context which has undergone significant political change but which has benefitted from little research, this study contributes to an understanding of the institutionalization and legitimization process of an accrual accounting system in an emerging‐economy public sector. Findings demonstrate how notions of politics and power inform the complexity of institutionalization in this unique political‐economic environment.