• Journal of Radiation Protection and Research
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• v.48 no.2
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• pp.90-99
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• 2023

Background: Quantitative risk assessments should be accompanied by uncertainty analyses of the risk models employed in the calculations. In this study, we aim to develop a computational code named SUMRAY for use in cancer risk projections from radiation exposure taking into account uncertainties. We also aim to make SUMRAY publicly available as a resource for further improvement of risk projection. Materials and Methods: SUMRAY has two versions of code written in R and Python. The risk models used in SUMRAY for all-solid-cancer mortality and incidence were those published in the Life Span Study of a cohort of the atomic bomb survivors in Hiroshima and Nagasaki. The confidence intervals associated with the evaluated risks were derived by propagating the statistical uncertainties in the risk model parameter estimates by the Monte Carlo method. Results and Discussion: SUMRAY was used to calculate the lifetime or time-integrated attributable risks of cancer under an exposure scenario (baseline rates, dose[s], age[s] at exposure, age at the end of follow-up, sex) specified by the user. The results were compared with those calculated using another well-known web-based tool, Radiation Risk Assessment Tool (RadRAT; National Institutes of Health), and showed a reasonable agreement within the estimated confidential interval. Compared with RadRAT, SUMRAY can be used for a wide range of applications, as it allows the risk projection with arbitrarily specified risk models and/or population reference data. Conclusion: The reliabilities of SUMRAY with the present risk-model parameters and their variance-covariance matrices were verified by comparing them with those of the other codes. The SUMRAY code is distributed to the public as an open-source code under the Massachusetts Institute of Technology license.

• Journal of the Korea Society of Computer and Information
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• v.28 no.7
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• pp.29-37
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• 2023

Due to climate change, interest in crop production and distribution is increasing, and attempts are being made to use bigdata and AI to predict production volume and control shipments and distribution stages. Prediction of agricultural product imports not only affects prices, but also controls shipments of farms and distributions of distribution companies, so it is important information for establishing marketing strategies. In this paper, we create an artificial intelligence prediction model that predicts the future import volume based on the wholesale market melon import volume data disclosed by the agricultural statistics information system and evaluate its accuracy. We create prediction models using three models: the Neural Prophet technique, the Ensembled Neural Prophet model, and the GRU model. As a result of evaluating the performance of the model by comparing two major indicators, MAE and RMSE, the Ensembled Neural Prophet model predicted the most accurately, and the GRU model also showed similar performance to the ensemble model. The model developed in this study is published on the web and used in the field for 1 year and 6 months, and is used to predict melon production in the near future and to establish marketing and distribution strategies.

• Journal of the Korean Society for information Management
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• v.39 no.4
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• pp.241-268
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• 2022

Records related to a certain cultural heritage are concrete evidence that prove the value of the cultural heritage and become a criterion for long-term preservation of its records. The value of the records is as important as cultural heritage value. In the case of specific cultural heritage with national or socially important values, various studies are conducted on cultural heritage as one theme, and various programs about cultural heritage are developed. However, it is difficult to grasp the scope, record types, and contents of the records because they have been distributed and managed in many institutes. They also appear in various forms. As a solution to these problems, this study collected records of a major cultural heritage with social and historical values such as Hwangnyongsa from 11 public institutions and web services and analyzed the types of records, activities related to the records, and metadata. Through data analysis, an ontology that can understand the range and relationship of the entire record was suggested so that the record can be understood with a focus on specific cultural heritage.

• Korean Journal of Construction Engineering and Management
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• v.24 no.1
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• pp.61-70
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• 2023

Due to economic or environmental reasons, green remodeling projects for old buildings are being actively carried out. Meanwhile, in the process of performing the green remodeling, the plan of green remodeling including passive and active elements has been decided based on the subjective experience and knowledge of engineers currently. Therefore, in this study, an ontology-based green remodeling decision-making support model, which can analyze the properties of old buildings and suggest appropriate remodeling plans, was established. In the developed model, once the basic properties of a building are entered, an appropriate remodeling plan composed of passive and active elements can be provided. By utilizing the results developed through the research, it is expected that it will be possible to support decision-making on more objective and appropriate remodeling alternatives development through web-based meta data search in accordance with the accumulation in remodeling cases.

• The Journal of the Convergence on Culture Technology
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• v.9 no.5
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• pp.509-515
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• 2023

Despite the continued development of alternative energies, fuel consumption is increasing. In particular, the price of gasoline fluctuates greatly according to fluctuations in international oil prices. Gas stations adjust their gasoline inventory to respond to gasoline price fluctuations. In this study, news datasets is used to analyze the gasoline consumption patterns through fluctuations of the gasoline inventory. First, collecting news datasets with web crawling. Second, summarizing news datasets using KoBART, which summarizes the Korean text datasets. Finally, preprocessing and deriving the fluctuations factors through N-Gram Language Model and TF-IDF. Through this study, it is possible to analyze and predict gasoline consumption patterns.

• Women's Health Nursing
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• v.29 no.3
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• pp.160-178
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• 2023

Purpose: Since technology-based interventions can facilitate convenient access to healthcare for women with breast cancer, it is crucial to understand innovative approaches to maintaining the effectiveness of these interventions. Therefore, we conducted a systematic review of technology-based self-management interventions for women with breast cancer in six countries. We analyzed the characteristics of these interventions and examined their diverse health outcomes. Methods: Six databases were systematically searched to extract research articles using the keywords "breast cancer," "technology," and "self-management." The search was carried out up until June 12, 2023. From the 1,288 studies retrieved from the database search, 10 eligible papers were identified based on inclusion/exclusion criteria. Two authors independently extracted and compared the data from these articles, resolving any discrepancies through discussion. Results: Most of the 10 studies utilized web- or mobile-based technology, and one used artificial intelligence-based technology. Among the 12 health-related outcome variables, quality of life and symptom distress were the most frequently mentioned, appearing in six articles. Furthermore, an analysis of the intervention programs revealed a variety of common constructs and the involvement of managers in the self-management intervention. Conclusion: Incorporating key components such as self-management planning, diary keeping, and communication support in technology-based interventions could significantly improve the self-management process for breast cancer survivors. The practical application of technology has the potential to empower women diagnosed with breast cancer and improve their overall quality of life, by providing timely and sustainable interventions, and by leveraging available resources and tools.

• International Journal of Computer Science & Network Security
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• v.24 no.6
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• pp.119-130
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• 2024

Universities are open systems that aim to prepare students to meet academic and industrial programs' expectations. It is important for universities to recognize these expectations and to make sure that they are achievable. To do so, graduates' progression tracking system is an essential tool for universities' development to ensure graduate students meet the market requirements. The purpose of this paper is to create automatic tracing system that captures information about students after graduation and creates annual report that represents the status of university students in term of employment or completing their study. It mainly assists graduates to find appropriate jobs that meet their desires or enabling them to complete their higher education by providing all these opportunities in one platform. The system main objective is to improve communication between graduate students, the university and companies. It also aims to identify the difficulties associated with graduate employability and changes are required to serve current students in term of creating new programs or activities. This helps universities to identify and address the existing curriculums and program's strengths and weaknesses and their adequacy, quality and competencies of a graduate in the labor market, which enhances the quality of higher education. we analyzed and implemented the tracing system using PHP language, which speeds up custom web application development and MySQL database, which guarantee data security, high performance, and other features. Graduate students found the proposed system usable and valuable.

• Journal of the Korean Society of Industry Convergence
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• v.27 no.3
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• pp.563-572
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• 2024

Image processing and computer vision technologies are becoming increasingly important in a variety of application fields that require techniques and tools for sophisticated image analysis. In particular, image segmentation is a technology that plays an important role in image analysis. In this study, in order to identify recent research trends on image segmentation techniques, we used the Web of Science(WoS) database to analyze the R&D topography based on the network structure of the author's keyword co-occurrence matrix. As a result, from 2015 to 2023, as a result of the analysis of the R&D map of research articles on image segmentation, R&D in this field is largely focused on four areas of research and development: (1) researches on collecting and preprocessing image data to build higher-performance image segmentation models, (2) the researches on image segmentation using statistics-based models or machine learning algorithms, (3) the researches on image segmentation for medical image analysis, and (4) deep learning-based image segmentation-related R&D. The scientometrics-based analysis performed in this study can not only map the trajectory of R&D related to image segmentation, but can also serve as a marker for future exploration in this dynamic field.

• Child Health Nursing Research
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• v.30 no.2
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• pp.87-96
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• 2024

Purpose: The rising prevalence of smartphone overdependence among adolescents and its detrimental impact on mental health have become a growing concern. This study aimed to investigate the association between smartphone overdependence and the mental health of Korean adolescents. Methods: Participants were drawn from the 16th Korea Youth Risk Behavior Web-based Survey conducted in 2020. The dependent variable as smartphone overdependence, while the main exposure of interest was mental health, encompassing generalized anxiety disorder (GAD), perceived stress, sources of perceived stress, perceived loneliness, and perceived depressive symptoms. The study employed the Rao-Scott chi-square test and multiple logistic regression using IBM SPSS version 26.0. Results: The participants comprised 54,948 adolescents aged 13 to 18 years. Among them, 25.1% (n=13,775) were categorized as smartphone overdependence group. Specifically, 20.3% of adolescents who reported GAD ≥10 and 22.5% of those who reported experiencing high levels of perceived loneliness were identified as smartphone overdependent. The GAD increased a risk of smartphone overdependence by 2.61 times (95% confidence interval [95% CI]: 2.46-2.77). Perceived loneliness was associated with 1.98-fold (95% CI: 1.87-2.09) increased risk of smartphone overdependence. Additionally, conflict with peers was found to increase the risk of smartphone overdependence by 4.63-fold (95% CI: 3.89-5.52), followed by conflict with parents (odds ratio [OR]: 4.52, 95% CI: 3.84-5.31), and family environment (OR: 4.52, 95% CI: 3.75-5.46). Conclusion: The findings underscore a significant association between smartphone overdependence and mental health in Korean adolescents. Healthcare services to improve their emotional coping and interpersonal skills are necessary.

• International Journal of Knowledge Content Development & Technology
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• v.14 no.1
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• pp.19-31
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• 2024

In order to support the mission of the institution in which they are attached, academic libraries provide services in both manual and digital but COVID -19 pandemic that spanned between March and September, 2020 has changed the scenario. With particular reference to Nigeria, about 249,606 cases were confirmed and in order to curb the scourge of this deadly disease, physical academic activities were prevented by Nigeria Centre for Disease Control (NCDC). With this development, innovative tools became indispensable tools for successful delivery of library services in Nigerian academic libraries. Whether or not these tools are still in use for reformation of library service during post- Covid era remains unclear, hence, need for this study. This study examined librarians' use of innovative tools for information dissemination in Nigerian academic libraries during the post-Covid era using a descriptive survey design. Data were obtained both in quantitative and qualitative formats from one hundred and forty-four librarians as respondents. A total enumeration sampling technique was adopted because the population was minimal. Findings of the study revealed that innovative tools such as videoconferencing, WhatsApp, teleconferencing, Facebook, LinkedIn, and web-based learning applications are still in use by librarians for the dissemination of information during the post-Covid era. These tools are useful and beneficial to librarians during the post-COVID era, as they facilitate easy participation and engagement of library users in various discussions. Inadequate funding and lack of advanced technology skills were also identified as major impediments to the successful use of innovative tools for information dissemination. As a result, it was suggested that academic libraries throughout Nigeria prioritize staff training on the necessary digital skills needed to cope in this advanced technology era.