Yong Jin Park

This study examined the impact of three dimensions of digital literacy on privacy-related online behaviors: (a) familiarity with technical aspects of the Internet, (b) awareness of common institutional practices, and (c) understanding of current privacy policy. Hierarchical regression models analyzed data from a national sample of 419 adult Internet users. The analyses showed strong predictive powers of user knowledge, as indicated by the three discrete dimensions, on privacy control behavior. H

AgInS 2 nanoparticles of various sizes were synthesized over a range of reaction temperature from 120 to 180 °C. The band gap energies, obtained directly from photoluminescence spectra for the first time, were well correlated to the quantum confinement effects as a function of nanoparticle size, because the band gap shift was explained by the finite-depth-well effective mass approximation. The chalcopyrite and orthorhombic phases were observed to coexist in the AgInS 2 nanoparticles, although th

The adsorption equilibria of O 2, N 2, and Ar on carbon molecular sieve (CMS) and zeolites 10X, 13X, and LiX were measured by the gravimetric method. The equilibrium measurement was conducted at (293.15, 303.15, and 313.15) K and pressure up to 80 kPa. The experimental data were correlated by the Langmuir, Sips, and Toth equations. The Sips equation showed the smallest deviation from all the experimental data of adsorbents. The isosteric enthalpies of adsorption were calculated for O 2, N 2, and

Mobile communication emerged as a dominant channel for networked teenagers. While some theorists celebrate possibilities for autonomy, others are concerned that the increased reliance on mobile-based communication leads to disparities in digital skill and status replication. We examined how mobile-mediated behavior among teens interacted with the characteristics of socio-demographics and mobile access to predict (1) levels of diverse use and skill and (2) consequences of skill/use differences (

Governments around the world have increasingly relied on technology to promote public health , such as using electronic health records and portable fitness devices. During the COVID-19 pandemic, “contact tracing apps” for smartphones have also been promoted in many countries as a way to allow public officials to facilitate contact tracing. But uptake in virtually all countries where such apps have been promoted is slow, one reason being privacy concerns. Conducting three experiments across Franc

This study presents a conceptual model of understanding algorithmic digital surveillance systems, borrowing insight from Giddens, who proposed the notion of structuration as social practices deriving from the intersection between structure and agents. We argue that the status of privacy, or lack of it, is a product of these interactions, of which the personal data practices and related interests constitute the reproduction of a data ecosystem. We trace the process of data production and consumpt

PURPOSE: We aimed to evaluate the performance of a deep learning system for differential diagnosis of lung cancer with conventional CT and FDG PET/CT using transfer learning (TL) and metadata. METHODS: A total of 359 patients with a lung mass or nodule who underwent noncontrast chest CT and FDG PET/CT prior to treatment were enrolled retrospectively. All pulmonary lesions were classified by pathology (257 malignant, 102 benign). Deep learning classification models based on ResNet-18 were develop

This study tested the reproduction hypothesis that the Internet produces positive payoffs for those in privileged social positions, while disfavoring marginalized communities. Using a national sample of adult Internet users ( n = 419), the first premise of this study investigated the impacts of (1) sociodemographic status, (2) Internet access indicators, and (3) their interactions on the variations of capabilities, as assessed through discrete measures of Internet-related personal information sk