Wenda Wei, Chengxia Liu and Jianing Wang
Nowadays, most methods of illusion garment evaluation are based on the subjective evaluation of experienced practitioners, which consumes time and the results are too subjective…
Abstract
Purpose
Nowadays, most methods of illusion garment evaluation are based on the subjective evaluation of experienced practitioners, which consumes time and the results are too subjective to be accurate enough. It is necessary to explore a method that can quantify professional experience into objective indicators to evaluate the sensory comfort of the optical illusion skirt quickly and accurately. The purpose of this paper is to propose a method to objectively evaluate the sensory comfort of optical illusion skirt patterns by combining texture feature extraction and prediction model construction.
Design/methodology/approach
Firstly, 10 optical illusion sample skirts are produced, and 10 experimental images are collected for each sample skirt. Then a Likert five-level evaluation scale is designed to obtain the sensory comfort level of each skirt through the questionnaire survey. Synchronously, the coarseness, contrast, directionality, line-likeness, regularity and roughness of the sample image are calculated based on Tamura texture feature algorithm, and the mean, contrast and entropy are extracted of the image transformed by Gabor wavelet. Both are set as objective parameters. Two final indicators T1 and T2 are refined from the objective parameters previously obtained to construct the predictive model of the subjective comfort of the visual illusion skirt. The linear regression model and the MLP neural network model are constructed.
Findings
Results show that the accuracy of the linear regression model is 92%, and prediction accuracy of the MLP neural network model is 97.9%. It is feasible to use Tamura texture features, Gabor wavelet transform and MLP neural network methods to objectively predict the sensory comfort of visual illusion skirt images.
Originality/value
Compared with the existing uncertain and non-reproducible subjective evaluation of optical illusion clothing based on experienced experts. The main advantage of the authors' method is that this method can objectively obtain evaluation parameters, quickly and accurately obtain evaluation grades without repeated evaluation by experienced experts. It is a method of objectively quantifying the experience of experts.
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Jingjing Wang, Zhiqiang Li, Huanhuan Feng, Yuanjing Guo, Zhengbo Liang, Luyao Wang, Xing Wan and Yalin Wang
Recently, sharing economy is gradually accepted by people, and it has expanded from life to knowledge. It is important to encourage people to produce high quality content in…
Abstract
Recently, sharing economy is gradually accepted by people, and it has expanded from life to knowledge. It is important to encourage people to produce high quality content in knowledge sharing area, and knowledge payment is one of the most effective ways to achieve it. Therefore, the knowledge payment has been regarded as a huge business opportunity, and it is of great meaning to study the development trend and feasibility of knowledge payment. This chapter, through big data methods, analyzes the business model of Zhihu (a Chinese platform of knowledge sharing) after it introduced knowledge payment projects, such as Zhihu Live and Pay Consultation. According to data of Zhihu users’ Q&A, concerned fields and others, this chapter tries to outline its user profile to find out the target groups of different topics, the proper form of knowledge payment and the hot topics of Zhihu Live. Through the analysis of knowledge graph, this chapter finds that Zhihu Live is expected to be the mainstream knowledge payment form in the future, and the most potential topics are mainly focused on science, law, and business. Meanwhile, it establishes a pricing model for Zhihu Live, and provides suggestions for the development of knowledge payment.
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The purpose of this paper is to provide a historical review of China’s anti-corruption efforts, from the ancient period of Chinese slavery societies to the late 1970s before China…
Abstract
Purpose
The purpose of this paper is to provide a historical review of China’s anti-corruption efforts, from the ancient period of Chinese slavery societies to the late 1970s before China launched its profound economic reform, under the current status of the harsh crusade against corruption that the Chinese new leadership initiated.
Design/methodology/approach
This paper is mainly based on a great deal of historical literature and empirical findings, with relevant comparative analysis on policies and regulations between various periods of China.
Findings
The phenomenon of corruption has existed in Chinese history for thousands of years, throughout Chinese slavery societies, feudal societies, republic period and the People’s Republic of China (PRC). Anti-corruption laws formed an important part of ancient Chinese legal system, and each dynasty has made continuous and commendable progress on fighting such misconduct. Innumerable initiatives have also been taken by the ruling party Chinese Communist Party (CCP) since the founding of the PRC. The PRC government created various specially designed government organizations and a series of updated regulations for preventing economic crimes. They have realized that periodic movements against corruption would no longer be helpful, and the paramount issue nowadays is indeed how bold the leaders are in striking out those unhealthy tendencies.
Originality/value
This paper fills in the blanks in the Western world with a comprehensive description of, and comments on, the historical efforts on China’s corruption and economic crime prevention. It also, in various ways, provides meaningful information that links to China’s current furious war against corruption.
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Samira Farivar, Fang Wang and Ofir Turel
With growing concerns about users’ well-being on social media, research stresses the importance of threat appraisals as a crucial first step in motivating self-protective actions…
Abstract
Purpose
With growing concerns about users’ well-being on social media, research stresses the importance of threat appraisals as a crucial first step in motivating self-protective actions. This study, in view of the prevalence of parasocial relationships between followers and social media influencers, aims to unravel the complex dynamics of followers’ threat perceptions within these relationships. Specifically, it examines how factors such as perceived self-efficacy to disengage and the positive affect of social media use influence threat appraisals.
Design/methodology/approach
A theoretical model is proposed based on appraisal theory to examine the impact of parasocial relationships on threat perception in engagement. It is empirically tested with data from 186 Instagram users.
Findings
The study reveals an overall positive relationship between parasocial relationships and perceived threat. This relationship is moderated by followers’ perception of self-efficacy to disengage – followers with a high sense of self-efficacy to disengage experience a decrease in threat perception as their parasocial relationships strengthen, whereas followers with a low sense of self-efficacy to disengage report an increase in threat perception with higher levels of parasocial relationships. This interplay is pronounced when followers experience average or below-average levels of positive affect on social media but diminishes when the positive affect is high.
Originality/value
This work contributes insights into social media influencers, threat appraisal dynamics and digital well-being research. Bridging a critical gap in existing knowledge, the study identifies the pivotal roles of followers’ self-efficacy to disengage and positive affect in shaping their threat appraisals toward parasocial relationships with social media influencers. This not only advances theoretical frameworks but also enhances our understanding of the nuanced dynamics of user reactions to parasocial engagements. Our findings offer practical insights for researchers, practitioners and platform developers aiming to cultivate healthy and responsible social media engagement in the digital era, ultimately contributing to individual well-being.