• Asian Journal for Public Opinion Research
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• v.9 no.4
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• pp.310-330
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• 2021

Driven by the need for remote learning, the COVID-19 pandemic led to the rise of use of videoconferencing tools. Scholars began noticing an emerging phenomenon of feeling tired and exhausted during virtual meetings. This study determined the predictors of videoconference or Zoom fatigue among nursing students in a large, private, non-sectarian university in the Philippines. This cross-sectional online survey involves 597 nursing students in the Philippines using the Zoom Exhaustion and Fatigue Scale. Multiple linear regression analysis was used to examine predictors of videoconference fatigue. Results indicated that nursing students experienced high levels of videoconference fatigue. Gender, self-reported academic performance, Internet connection stability, attitude toward videoconferencing, frequency, and duration of videoconferences predicted videoconference fatigue. The regression model explained 25.3% of the variances of the videoconference fatigue. Videoconference fatigue is relatively prevalent and may be taking its toll on nursing students. Developing strategic interventions that can protect or mitigate the impact of fatigue during virtual meetings is needed.

• Cross-Cultural Studies
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• v.26
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• pp.73-94
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• 2012

In the present context of systemic global crisis, this paper focuses on a sustainable society. Throughout the World there are vast members of the unemployes. A secure job lasting a lifetime has become more and more rare. Nowadays majority of jobs are part-time or temporary. $Andr{\acute{e}}$ Gorz found a solution in a policy of the progessive reduction in labor time. This is the potential which automated production opens up for a culture society. Nevertheless, Gorz's proposal is based on utopion ideals. This paper focuses on a dynamic force for a culture society, especially art, learning and the third sector. Adrienne Goehler underlines that a culture in the broad sense of the word produces economical and social productivity. In this connection Goehler give attention to 'Cultrual Creatives' and the Creative Class. Cultural creatives are comprised of people who have participated in the process of creating a new culture with enlightened creativity. The Creative Class is a class of workers whose job is to create economic growth through innovation. Creativity is important for a sustainable society. Gore and Rifkin both come close to the ecological thinking. Gore claims that ecosystem of nature have a self-organizing capacity. In this context tried to prove this article that ecosystem is closely connected with a creative environment.

• Cross-Cultural Studies
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• v.19
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• pp.205-232
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• 2010

The purpose of this paper is to examine the possibility of application of some French and German movies to teaching of multi-culture in elementary, middle and high schools. Three different films are selected. (2005), a French animation film directed by B?n?dicte Galup and Michel Ocelot, is appropriate for the education of understanding cultural relativity and improving multi-cultural sensitivity in elementary school. is a French short film directed by Walter Salles and Daniela Thomaso and included in omnibus style film (2006). This short film relating a story of an immigrated woman who leaves her baby in a cr?che and travels through Paris to work for a bourgeois mother can be used for developing a bond of sympathy between natives and immigrants. It is recommended for the class of junior high school. Finally (2007), a German film directed by Fatih Akin, provide a learning model for the education of multi-culture in high school classrooms. The cinematographic aesthetic of this film is focused on a process of reconciliation with others over the cultural, racial, national and generational differences. Analyzing the structure of the film and being guided by teachers the students can understand better in improving abilities to understand others.

• Genomics & Informatics
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• v.17 no.2
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• pp.17.1-17.3
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• 2019

Text mining has become an important research method in biology, with its original purpose to extract biological entities, such as genes, proteins and phenotypic traits, to extend knowledge from scientific papers. However, few thorough studies on text mining and application development, for plant molecular biology data, have been performed, especially for rice, resulting in a lack of datasets available to solve named-entity recognition tasks for this species. Since there are rare benchmarks available for rice, we faced various difficulties in exploiting advanced machine learning methods for accurate analysis of the rice literature. To evaluate several approaches to automatically extract information from gene/protein entities, we built a new dataset for rice as a benchmark. This dataset is composed of a set of titles and abstracts, extracted from scientific papers focusing on the rice species, and is downloaded from PubMed. During the 5th Biomedical Linked Annotation Hackathon, a portion of the dataset was uploaded to PubAnnotation for sharing. Our ultimate goal is to offer a shared task of rice gene/protein name recognition through the BioNLP Open Shared Tasks framework using the dataset, to facilitate an open comparison and evaluation of different approaches to the task.

• Human Ecology Research
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• v.61 no.1
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• pp.1-13
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• 2023

Household chaos, represented by high levels of disorganization and instability in the home, has been linked with suboptimal outcomes for preschoolers. The aim of this study was to examine the roles that sleep problems and executive function play in the association between household chaos and preschoolers' aggression and prosocial behavior. The sample for the study consisted of 420 preschoolers and their mothers. The mothers provided reports on the level of chaos in the home and their preschoolers' sleep problems, executive function, and social behavior, including aggression and prosocial behavior. The data was analyzed using structural equation modeling. When preschoolers' sleep problems and executive function were included in the model as mediators, the results indicated that household chaos did not have direct effects on preschoolers' aggression and prosocial behavior. Such effects were instead serially mediated by preschoolers' sleep problems and executive function, respectively. The higher the degree of household chaos, the more preschoolers displayed sleep problems and deficits in executive function, resulting in more aggression and less prosocial behavior. The findings from this study emphasize the significance of reducing household chaos in order to reduce preschoolers' aggression and promote prosocial behavior. They also underscore the need to identify additional variables that mediate the impact of household chaos on preschoolers' social outcomes.

• Journal of Korean society of Dental Hygiene
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• v.23 no.5
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• pp.379-386
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• 2023

Objectives: This study aimed to prepare basic data to improve the health-related quality of life of cancer survivors by confirming their oral and mental health statuses and identifying factors affecting their health-related quality of life. Methods: Of all participants in the 8th KNHANES (2019-2020), adults aged 19 years or older who responded 'yes' to the diagnosis of cancer and 404 cancer survivors who responded 'none' to the current cancer prevalence item were selected as the final research participants. Multiple regression analysis was conducted to confirm the effect of cancer survivors' oral and mental health on health-related quality of life. Results: Subjective oral health (p<0.01), chewing problems (p<0.05), subjective health (p<0.001), and depression (p<0.01) had an effect on health-related quality of life from multiple regression analyses. Conclusions: Therefore, oral and mental health promotion may improve health-related quality of life. Thus, it is necessary to recognize the importance of oral and mental health and implement preventive education and programs.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.18 no.4
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• pp.1020-1041
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• 2024

With the development of covert communication technologies, the number of covert communication technologies using blockchain as a carrier is increasing. However, using the transaction amount of digital currency as a carrier for covert communication has problems such as low embedding rate, large consumption of transaction amount, and easy detection. In this paper, firstly, by experimentally analyzing the distribution of bitcoin transaction amounts, we determine the most suitable range of amounts for matrix decomposition. Secondly, we design a novel matrix decomposition method that can successfully decompose a large amount matrix into two small amount matrices and utilize the elements in the small amount matrices for covert communication. Finally, we analyze the feasibility of the novel matrix decomposition method in this scheme in detail from four aspects, and verify it by experimental comparison, which proves that our scheme not only improves the embedding rate and reduces the consumption of transaction amount, but also has a certain degree of resistance to detection.

• Archives of Plastic Surgery
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• v.47 no.1
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• pp.70-77
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• 2020

Background As the demand for cosmetic surgery continues to rise, plastic surgery programs and the training core curriculum have evolved to reflect these changes. This study aims to evaluate the perceived quality of current cosmetic surgery training in terms of case exposure and educational methods. Methods A 16-question survey was sent to graduates who completed their training at a U.S. plastic surgery training program in 2017. The survey assessed graduates' exposure to cosmetic surgery, teaching modalities employed and their overall perceived competence. Case complexity was characterized by the minimum number of cases needed by the graduate to feel confident in performing the procedure. Results There was a 25% response rate. The majority of respondents were residents (83%, n=92) and the remaining were fellows (17%, n=18). Almost three quarters of respondents were satisfied with their cosmetic training. Respondents rated virtual training as the most effective learning modality and observing attendings' patients/cases as least effective. Perceived competence was more closely aligned with core curriculum status than case complexity, i.e. graduates feel more prepared for core cosmetic procedures despite being more technically difficult than non-core procedures. Conclusions Despite the variability in cosmetic exposure during training, most plastic surgery graduates are satisfied with their aesthetic training. Incorporation of teaching modalities, such as virtual training, can increase case exposure and allow trainees more autonomy. The recommended core curriculum is adequately training plastic surgery graduates for common procedures and more specialized procedures should be consigned to aesthetic fellowship training.

• Korean Journal of Radiology
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• v.21 no.7
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• pp.869-879
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• 2020

Objective: To evaluate the performance of a convolutional neural network (CNN) model that can automatically detect and classify rib fractures, and output structured reports from computed tomography (CT) images. Materials and Methods: This study included 1079 patients (median age, 55 years; men, 718) from three hospitals, between January 2011 and January 2019, who were divided into a monocentric training set (n = 876; median age, 55 years; men, 582), five multicenter/multiparameter validation sets (n = 173; median age, 59 years; men, 118) with different slice thicknesses and image pixels, and a normal control set (n = 30; median age, 53 years; men, 18). Three classifications (fresh, healing, and old fracture) combined with fracture location (corresponding CT layers) were detected automatically and delivered in a structured report. Precision, recall, and F1-score were selected as metrics to measure the optimum CNN model. Detection/diagnosis time, precision, and sensitivity were employed to compare the diagnostic efficiency of the structured report and that of experienced radiologists. Results: A total of 25054 annotations (fresh fracture, 10089; healing fracture, 10922; old fracture, 4043) were labelled for training (18584) and validation (6470). The detection efficiency was higher for fresh fractures and healing fractures than for old fractures (F1-scores, 0.849, 0.856, 0.770, respectively, p = 0.023 for each), and the robustness of the model was good in the five multicenter/multiparameter validation sets (all mean F1-scores > 0.8 except validation set 5 [512 x 512 pixels; F1-score = 0.757]). The precision of the five radiologists improved from 80.3% to 91.1%, and the sensitivity increased from 62.4% to 86.3% with artificial intelligence-assisted diagnosis. On average, the diagnosis time of the radiologists was reduced by 73.9 seconds. Conclusion: Our CNN model for automatic rib fracture detection could assist radiologists in improving diagnostic efficiency, reducing diagnosis time and radiologists' workload.

• Genomics & Informatics
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• v.18 no.2
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• pp.15.1-15.6
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• 2020

Named entity recognition tools are used to identify mentions of biomedical entities in free text and are essential components of high-quality information retrieval and extraction systems. Without good entity recognition, methods will mislabel searched text and will miss important information or identify spurious text that will frustrate users. Most tools do not capture non-contiguous entities which are separate spans of text that together refer to an entity, e.g., the entity "type 1 diabetes" in the phrase "type 1 and type 2 diabetes." This type is commonly found in biomedical texts, especially in lists, where multiple biomedical entities are named in shortened form to avoid repeating words. Most text annotation systems, that enable users to view and edit entity annotations, do not support non-contiguous entities. Therefore, experts cannot even visualize non-contiguous entities, let alone annotate them to build valuable datasets for machine learning methods. To combat this problem and as part of the BLAH6 hackathon, we extended the TextAE platform to allow visualization and annotation of non-contiguous entities. This enables users to add new subspans to existing entities by selecting additional text. We integrate this new functionality with TextAE's existing editing functionality to allow easy changes to entity annotation and editing of relation annotations involving non-contiguous entities, with importing and exporting to the PubAnnotation format. Finally, we roughly quantify the problem across the entire accessible biomedical literature to highlight that there are a substantial number of non-contiguous entities that appear in lists that would be missed by most text mining systems.