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Grounded in ethnic identity theory, critical race theory (CRT) and critical discourse analysis (CDA), this chapter’s objective is to demonstrate the role of news media in the (mis)construction of the identity formation of undocumented youth and the resulting implications of this (mis)construction within the field of education. This study uses mixed methods that include a CDA of Spanish and English language evening television news reports about the Development, Relief, and Education for Alien Minors Act of 2010, and qualitative analysis of interviews with undocumented youth. The implications for undocumented youth traverse from greater society and into schools, and we argue that education leaders must actively challenge and disrupt the (mis)constructions in direct and intentional ways. We provide a theoretical argument and practical steps for how education leaders can support undocumented youth in their communities.

This study aims to investigate whether the protection motivation theory (PMT) and religiosity can explain the intention of at-home worship adaptive behavior during the COVID-19 pandemic. This study further explores factors that may affect this adaptive behavior, namely, the intention to adapt behavior, religiosity, social influence and trust in the government.

Data were collected through an online survey to purposively sample the respondents, resulting in 368 responses that were valid for structural analysis using partial least squares structual equation modeling (SEM).

This study found that PMT, and not religiosity, directly predicts an individual’s intention to adapt his/her behavior to at-home worship during the pandemic. Religiosity, however, has a role in evoking a coping appraisal that leads to the intention to enact the adaptive behavior. Further, this study found that intention, social influence and trust in the government predict an individual’s adaptive behavior for at-home worship.

This study may guide the government to create a policy that could enhance people’s adherence to adaptive behavior during the pandemic, particularly regarding their communication strategy by focusing on the cognitive and psychological aspects. In particular, framing based on this study’s result may serve as an insight for better prevention of virus transmission through a focused communications strategy.

First, the utilization of PMT to explain adaptive behavior in the context of at-home worship during the pandemic was extended. Second, the research of religiosity in the context of a pandemic was advanced and how it influences adaptive behavior was investigated. Finally, the utilization of partial least squares-SEM techniques to investigate individual adaptive behavior during the COVID-19 pandemic was extended.

This paper holds a big advantage to enable to recognize faces, regardless of time and place. Also this provides an independent performance of smart phone, because of its process by a computer of third party not by that of the mobile device. In addition, it is desirable to minimize the expensive operations in mobile device with constraint computational power (i.e. battery consumption). Thus, the authors exclude the process of transmission failed from the input device. The paper aims to discuss these issues.

In this paper, the authors have proposed a new face detection and verification algorithm, based on skin color detection to enable extracting the face region from color images of the mobile phone. And then extracted the facial feature as eigenface, verified whether or not the identity of users is right, applied support vector machine to the region of detected face.

The experimental results for two datasets show that the proposed method achieves slightly higher efficiencies at the detection and verification of user identity, compared with other method, where varying lighting conditions with complex backgrounds, according to be fast and accurate than any other previous methods.

The proposed algorithm enables to implement fast and accurate search using triangle-square transformation for detection of human faces in a digital still color images, obtained by the mobile device camera under unconstraint environments, using advanced skin color model and characteristic points in a detected face.