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Service-oriented architecture is an emerging software architecture, in which web service (WS) plays a crucial role. In this architecture, the task of WS composition and verification is required when handling complex requirement of services from users. When the number of WS becomes very huge in practice, the complexity of the composition and verification is also correspondingly high. In this paper, the authors aim to propose a logic-based clustering approach to solve this problem by separating the original repository of WS into clusters. Moreover, they also propose a so-called quality-controlled clustering approach to ensure the quality of generated clusters in a reasonable execution time.

The approach represents WSs as logical formulas on which the authors conduct the clustering task. They also combine two most popular clustering approaches of hierarchical agglomerative clustering (HAC) and k-means to ensure the quality of generated clusters.

This logic-based clustering approach really helps to increase the performance of the WS composition and verification significantly. Furthermore, the logic-based approach helps us to maintain the soundness and completeness of the composition solution. Eventually, the quality-controlled strategy can ensure the quality of generated clusters in low complexity time.

The work discussed in this paper is just implemented as a research tool known as WSCOVER. More work is needed to make it a practical and usable system for real life applications.

In this paper, the authors propose a logic-based paradigm to represent and cluster WSs. Moreover, they also propose an approach of quality-controlled clustering which combines and takes advantages of two most popular clustering approaches of HAC and k-means.

COVID-19 presents a serious and unprecedented challenge around the globe. Street vendors are the most vulnerable group during this pandemic regarding livelihood loss and contagion risk. This research aims to examine the roles of risk communication work in enhancing COVID-19 risk perceptions and adoption of COVID-19 preventive behaviors among street vendors.

The data were collected from the street vendors in urban Vietnam. A binary probit model was used for analyzing the relationships among exposure to risk communication, risk perception and adoption of preventive behaviors.

The analysis reveals the outreach of risk communication work to the street vendors. A rather large proportion of the respondents perceive high risks associated with COVID-19. All respondents adopt COVID-19 preventive behaviors; however, the proportion of regular adoption is moderate and even very low for most behaviors. Their frequent exposure to risk communication significantly raises their risk perceptions and encourages their regular adoption of preventive behaviors, particularly regarding the measures that are affordable and less detrimental to their livelihood.

This research is among the first attempts to examine risk communication to the vulnerable group, how they perceive risks and the extent to which they adopt preventive behaviors during a public health crisis. This research draws some implications for risk communication and social welfare policies to obtain sustainable development goals.