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Article
Publication date: 19 June 2017

Qi Wang, Pengcheng Zhang, Jianming Wang, Qingliang Chen, Zhijie Lian, Xiuyan Li, Yukuan Sun, Xiaojie Duan, Ziqiang Cui, Benyuan Sun and Huaxiang Wang

Electrical impedance tomography (EIT) is a technique for reconstructing the conductivity distribution by injecting currents at the boundary of a subject and measuring the…

Abstract

Purpose

Electrical impedance tomography (EIT) is a technique for reconstructing the conductivity distribution by injecting currents at the boundary of a subject and measuring the resulting changes in voltage. Image reconstruction for EIT is a nonlinear problem. A generalized inverse operator is usually ill-posed and ill-conditioned. Therefore, the solutions for EIT are not unique and highly sensitive to the measurement noise.

Design/methodology/approach

This paper develops a novel image reconstruction algorithm for EIT based on patch-based sparse representation. The sparsifying dictionary optimization and image reconstruction are performed alternately. Two patch-based sparsity, namely, square-patch sparsity and column-patch sparsity, are discussed and compared with the global sparsity.

Findings

Both simulation and experimental results indicate that the patch based sparsity method can improve the quality of image reconstruction and tolerate a relatively high level of noise in the measured voltages.

Originality/value

EIT image is reconstructed based on patch-based sparse representation. Square-patch sparsity and column-patch sparsity are proposed and compared. Sparse dictionary optimization and image reconstruction are performed alternately. The new method tolerates a relatively high level of noise in measured voltages.

Details

Sensor Review, vol. 37 no. 3
Type: Research Article
ISSN: 0260-2288

Keywords

Article
Publication date: 29 March 2022

Changju Kim, Xiuyan Yan and Soohyun Park

Drawing on the theory of planned behavior, this study aims to conduct an empirical investigation on whether and how psychological and motivational factors (i.e. attitudes…

1208

Abstract

Purpose

Drawing on the theory of planned behavior, this study aims to conduct an empirical investigation on whether and how psychological and motivational factors (i.e. attitudes, subjective norms and perceived behavioral control) affect actual purchase behavior. It does so through the lens of boycott intention and gender differences in the context of boycott campaigns.

Design/methodology/approach

Focusing on the South Korean boycott campaign against Japanese companies, this study employs a structural equation model using survey data from 571 South Korean consumers to test the hypotheses.

Findings

While the three psychological and motivational factors inhibit all three dimensions of actual purchase behavior (i.e. purchase frequency, number of items purchased and purchase amount) through increased boycott intention, perceived behavioral control of boycotts directly curb South Korean consumers from purchasing Japanese products. Additionally, the effect of boycott intention on overall actual purchase behavior is stronger for men than for women, suggesting a moderating role of gender.

Practical implications

To mitigate the devastating impact of unexpected consumers' boycott campaigns, this study advises that global brand management and attractive online channels are essential while considering the differential impact of gender.

Originality/value

By conceptualizing three dimensions of actual purchase behavior capturing behavioral changes before and after a boycott, this study highlights the linkages between psychological and motivational factors, intentions and behaviors. Additionally, this study attempts to clarify the previously conflicting evidence on gender's role in boycott campaigns while taking a culture-inclusive psychologies approach to gender.

Details

International Journal of Emerging Markets, vol. 18 no. 12
Type: Research Article
ISSN: 1746-8809

Keywords

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