Today's rapid shifts toward a new paradigm are combining city spaces with reality and technology, which is known as a ubiquitous environment. An ubiquitous environment means that 'whenever' and 'wherever' become connected. It is a great possibility that this will change our future lifestyle. Korea has the biggest advantage in the implementation of this new environment, such as having an excellent network infrastructure. Using these attributes of a ubiquitous environment, changes are being made toward ubiquitous cities within developing fields of construction, landscaping, streets, art, and the environment. This research is based on background of research that activated media pole in public city space has been done research about reality of digital skill, fusion, and sense of ubitizen, and Kang-Nam U-street applied by ubiquitous technique. While reflecting an environment that can be utilized in a modern digital society, the application of ubiquitous technology to media pole can be a space for the two-way communication of the current paradigm. It would also be meaningful to create a new cultural space through media pole. Through evaluation, citizens of the ubiquitous age are going to interact to raise the satisfaction that media pole in city space can prevent giving direction to develop and trial and error about service ability, identity, and publicity. Finally, the media pole can be used as a fundamental element to suggest directions for change when viewed as future development.
The purpose of this study to find the factors influencing the fire alarms using IoT firefighting facility management system data of Seoul Fire & Disaster Headquarters, and to present academic implications for establishing an effective prevention system of fire situation. As the number of high and complex buildings increases and former bulidings are advanced, the fire detection facilities that can quickly respond to emergency situations are also increasing. However, if the accuracy of the fire situation is incorrectly detected and the accuracy is lowered, the inconvenience of the residents increases and the reliability decreases. Therefore, it is necessary to improve accuracy of the system through efficient inspection and the internal environment investigation of buildings. The purpose of this study is to find out that false detection may occur due to building characteristics such as usage or time, and to aim of emphasizing the need for efficient system inspection and controlling the internal environment. As a result, it is found that the size(total area) of the building had the greatest effect on the fire alarms, and the fire alarms increased as private buildings, R-type receivers, and a large number of failure or shutoff days. In addition, factors that influencing fire alarms were different depending on the main usage of the building. In terms of time, it was found to follow people's daily patterns during weekdays(9 am to 6 pm), and each peaked around 10 am and 2 pm. This study was claimed that it is necessary to investigate the building environment that caused the fire alarms, along with the system internal inspection. Also, it propose additional recording of building environment data in real-time for follow-up research and system enhancement.
In order to minimize damage to oil spill accidents in the ocean, it is essential to collect a spilled area as soon as possible. Thus satellite-based remote sensing is a powerful source to detect oil spills in the ocean. With the recent rapid increase in the number of available satellites, it has become possible to generate a status report of marine oil spills soon after the accident. In this study, the oil spill area was calculated using various satellite images for the Symphony oil spill accident that occurred off the coast of Qingdao Port, China, on April 27, 2021. In particular, improving the accuracy of oil spill area determination was applied using high-resolution commercial satellite images with a spatial resolution of 2m. Sentinel-1, Sentinel-2, LANDSAT-8, GEO-KOMPSAT-2B (GOCI-II) and Skysat satellite images were collected from April 27 to May 13, but five images were available considering the weather conditions. The spilled oil had spread northeastward, bound for coastal region of China. This trend was confirmed in the Skysat image and also similar to the movement prediction of oil particles from the accident location. From this result, the look-alike patch observed in the north area from the Sentinel-1A (2021.05.01) image was discriminated as a false alarm. Through the survey period, the spilled oil area tends to increase linearly after the accident. This study showed that high-resolution optical satellites can be used to calculate more accurately the distribution area of spilled oil and contribute to establishing efficient response strategies for oil spill accidents.
This study encompassed the responses of 284 elementary school teachers, focusing on their teaching experiences, readiness, and needs for science education concerning the risk posed by science and technology. The key findings are summarized as follows. First, a significant portion of teachers lacked prior experience in addressing risks associated with science and technology within their science education practices. Second, a greater number of teachers were aware of the inclusion of risk-related content in the 2022 revised science curriculum's achievement standards than those who were not. Third, in terms of teachers' understanding of risk perception, risk assessment, and risk management, they demonstrated a relatively high level of understanding of risk perception but a lower level of understanding of risk assessment. Fourth, most teachers had not undergone any formal education or training related to risk. Fifth, among the 10 objectives of risk education, teachers displayed the highest competence in teaching "information use" and "action skills," while their lowest competence was observed in "interpreting probabilities" and "evaluating risk assessment." Sixth, a majority of teachers believe that it is important to teach about the risks posed by science and technology in school science classes, with "action skills," "information use," and "decision-making skills" being considered the most important and "action skills," "information use," and "influence of mass media" being regarded as the most urgent. However, teachers anticipated difficulties in addressing risk in school science classes, including a lack of relevant educational materials, a lack of understanding of teaching theories related to risk education, and the relationship between science curriculum content and achievement standards. Seventh, as a result of calculating the educational needs for each of the 10 goals of risk education, "influence of risk perception," "decision-making skills," "action skills," and "evaluate risk assessment" were the priority needs of elementary school teachers.
From January 2020 to October 2021, more than 500,000 academic studies related to COVID-19 (Coronavirus-2, a fatal respiratory syndrome) have been published. The rapid increase in the number of papers related to COVID-19 is putting time and technical constraints on healthcare professionals and policy makers to quickly find important research. Therefore, in this study, we propose a method of extracting useful information from text data of extensive literature using LDA and Word2vec algorithm. Papers related to keywords to be searched were extracted from papers related to COVID-19, and detailed topics were identified. The data used the CORD-19 data set on Kaggle, a free academic resource prepared by major research groups and the White House to respond to the COVID-19 pandemic, updated weekly. The research methods are divided into two main categories. First, 41,062 articles were collected through data filtering and pre-processing of the abstracts of 47,110 academic papers including full text. For this purpose, the number of publications related to COVID-19 by year was analyzed through exploratory data analysis using a Python program, and the top 10 journals under active research were identified. LDA and Word2vec algorithm were used to derive research topics related to COVID-19, and after analyzing related words, similarity was measured. Second, papers containing 'vaccine' and 'treatment' were extracted from among the topics derived from all papers, and a total of 4,555 papers related to 'vaccine' and 5,971 papers related to 'treatment' were extracted. did For each collected paper, detailed topics were analyzed using LDA and Word2vec algorithms, and a clustering method through PCA dimension reduction was applied to visualize groups of papers with similar themes using the t-SNE algorithm. A noteworthy point from the results of this study is that the topics that were not derived from the topics derived for all papers being researched in relation to COVID-19 (