• Imaging Science in Dentistry
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• v.51 no.1
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• pp.9-16
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• 2021

Purpose: The purpose of this study was to analyze the reliability of 7 panoramic radiographic signs for predicting proximity of the root apices of mandibular third molars to the mandibular canal using cone-beam computed tomography and to correlate these findings with the Pell and Gregory and the Winter classification systems. Materials and Methods: An observational, cross-sectional, descriptive study was conducted on 74 patients with bilateral impacted mandibular third molars. Four panoramic radiographic signs were observed in the tooth root (darkening, deflection, and narrowing of the root apices, and bifid apices), and another 3 in the mandibular canal (diversion, narrowing, and interruption of the mandibular canal). Cone-beam computed tomography images were analyzed to identify disruption and diversion of the mandibular canal and root deflection. Results: Binary logistic regression showed that only 4 of the 7 panoramic radiographic signs were able to predict proximity of the root apices of the mandibular third molars to the mandibular canal: darkening of the root, deflection of the root, narrowing of the root, and interruption of the mandibular canal(P<0.05). Conclusion: Darkening, deflection, and narrowing of the root, in tandem with the interruption of the mandibular canal on panoramic radiographs, indicate that cone-beam computed tomography should be performed when planning the extraction of impacted mandibular third molars. Proximity between mandibular third molars and the mandibular canal is correlated with the Winter classification.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.5
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• pp.641-648
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• 2022

This paper is a study to find out the factors affecting the defects that occur during the use of Electron Beam Melting (EBM), one of the 3D printer output methods, through data analysis. By referring to factors identified as major causes of defects in previous studies, log files occurring between processes were analyzed and related variables were extracted. In addition, focusing on the fact that the data is time series data, the concept of a window was introduced to compose variables including data from all three layers. The dependent variable is a binary classification problem with the presence or absence of defects, and due to the problem that the proportion of defect layers is low (about 4%), balanced training data were created through the SMOTE technique. For the analysis, I use XGBoost using Gridsearch CV, and evaluate the classification performance based on the confusion matrix. I conclude results of the stuy by analyzing the importance of variables through SHAP values.

• International Journal of Computer Science & Network Security
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• v.22 no.6
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• pp.45-50
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• 2022

The article substantiates the feasibility of using and actively implementing innovative technologies in the practice of organizing the educational process. The need for the use of telecommunication technologies, which provide constant communication between students and the teacher outside the classroom, has been identified. Particular attention is paid to the latest approaches to the use of various forms of multimedia technologies in student education, which intensify the process of acceptance and assimilation of educational material by foreign students. The advantages of using innovative means of distance education are determined, which thanks to modern electronic educational systems allow students to receive quality higher education. Innovative technologies promote the development of cognitive interest in students, they learn to systematize and summarize the material studied, discuss and debate. In this regard, the reorientation of the system of higher education in Europe towards innovation is becoming the most important tool in ensuring the competitiveness of graduates in the labor market. In addition, the investment attractiveness of a university often depends on the innovative nature of the development of scientific, educational and practical activities of the subjects of the educational process, their inclusion in the national innovation system. The article analyzes that in the universities of the European Union in the training of specialists in the management of basic interactive methods, forms and tools are binary lecture, briefing, webinar, video conference, video lecture, virtual consultation, virtual tutorial, slide lecture, comp. utheric tests. Various classes on slide technology took active forms during the training of management specialists.

• Health Policy and Management
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• v.33 no.3
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• pp.273-294
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• 2023

Background: Most developed countries are working to improve their universal health coverage systems. This study investigates regional disparities in unmet healthcare needs and their causes in South Korea. Additionally, it compares the unmet healthcare needs rate in South Korea with that of 33 European countries. Methods: The analysis incorporates information from 13,359 adults aged 19 or older, using data from the Korea Health Panel. The dependent variables encompass the experience of unmet healthcare needs and the three causes of occurrence: "burden of medical expenses," "time constraints," and "lack of care." The primary variable of interest is the region of residence, while control variables encompass 14 socio-demographic, health, and functional characteristics. Multivariable binary logistic regression analysis, accounting for the sampling design, is conducted. Results: The rate of unmet healthcare needs in Korea is 11.7% (95% confidence interval [CI], 11.0%-13.3%), which is approximately 30 times higher than that of Austria (0.4%). The causes of unmet healthcare needs, ranked in descending order, are "lack of care," "time constraints," and "burden of medical expenses." Predictive probabilities for experiencing unmet healthcare needs and each cause differ significantly between regions. For instance, the probability of experiencing unmet healthcare needs due to "lack of care" is approximately 10 times higher in Gangwon-do (13.5%; 95% CI, 13.0%-14.1%) than in Busan (1.3%; 95% CI, 1.3%-1.4%). The probability due to "burden of medical expenses" is approximately 14 times higher in Seoul (4.1%; 95% CI, 3.6%-4.6%) compared to Jeollanam-do (0.3%; 95% CI, 0.2%-0.4%). Conclusion: Amid rapid sociodemographic transitions, South Korea must make significant efforts to alleviate unmet healthcare needs and the associated regional disparities. To effectively achieve this, it is recommended that South Korea involves the National Assembly in healthcare policy-making, while maintaining a centralized financing model and delegating healthcare planning and implementation to regional authorities for their local residents-similar to the approaches of the United Kingdom and France.

• KIPS Transactions on Computer and Communication Systems
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• v.12 no.4
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• pp.127-134
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• 2023

This paper describes how to port the eCos operating system and PROFINET communication stack developed based on gcc to the IAR compiler. The eCos operating system provides basic functions such as multi-thread, TCP/IP, and device driver for PROFINET operation, so there is no need to change it when developing PROFINET applications. Therefore, in this study, we reuse an eCos library built with gcc and it link with PROFINET communication stack that are ported to IAR complier. Due to the different of the gcc and IAR linker, symbol definitions and address of the constructors should be changed using the external tool that generates symbol definitions and address of the constructors from MAP file. In order to verify the proposed method, it was confirmed that the actual I/O was operating normally through PROFINET IRT communication by connecting to the Siemens PLC. IAR compiler has better performance in both the compile time and the size of the generated binary. The proposed method in this study is expected to help port various open sources as well as eCos and PROFINET communication stacks to other compilers.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.46 no.1
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• pp.32-41
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• 2023

Recently, many studies are being conducted to extract emotion from text and verify its information power in the field of finance, along with the recent development of big data analysis technology. A number of prior studies use pre-defined sentiment dictionaries or machine learning methods to extract sentiment from the financial documents. However, both methods have the disadvantage of being labor-intensive and subjective because it requires a manual sentiment learning process. In this study, we developed a financial sentiment dictionary that automatically extracts sentiment from the body text of analyst reports by using modified Bayes rule and verified the performance of the model through a binary classification model which predicts actual stock price movements. As a result of the prediction, it was found that the proposed financial dictionary from this research has about 4% better predictive power for actual stock price movements than the representative Loughran and McDonald's (2011) financial dictionary. The sentiment extraction method proposed in this study enables efficient and objective judgment because it automatically learns the sentiment of words using both the change in target price and the cumulative abnormal returns. In addition, the dictionary can be easily updated by re-calculating conditional probabilities. The results of this study are expected to be readily expandable and applicable not only to analyst reports, but also to financial field texts such as performance reports, IR reports, press articles, and social media.

• Journal of the Korea Society of Computer and Information
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• v.28 no.11
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• pp.81-87
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• 2023

Intrusion detection systems that learn metadata of network packets have been proposed recently. However these approaches require time to analyze packets to generate metadata for model learning, and time to pre-process metadata before learning. In addition, models that have learned specific metadata cannot detect intrusion by using original packets flowing into the network as they are. To address the problem, this paper propose a natural language processing-based intrusion detection system that detects intrusions by learning the packet payload as a single sentence without an additional conversion process. To verify the performance of our approach, we utilized the UNSW-NB15 and Transformer models. First, the PCAP files of the dataset were labeled, and then two Transformer (BERT, DistilBERT) models were trained directly in the form of sentences to analyze the detection performance. The experimental results showed that the binary classification accuracy was 99.03% and 99.05%, respectively, which is similar or superior to the detection performance of the techniques proposed in previous studies. Multi-class classification showed better performance with 86.63% and 86.36%, respectively.

• Journal of The Korean Astronomical Society
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• v.56 no.2
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• pp.277-286
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• 2023

It is difficult to distinguish the pure signal produced by an orbiting planetary companion around giant stars from other possible sources, such as stellar spots, pulsations, or certain activities. Since 2003, we have obtained radial (RV) data from evolved stars using the high-resolution, fiber-fed Bohyunsan Observatory Echelle Spectrograph (BOES) at the Bohyunsan Optical Astronomy Observatory (BOAO). Here, we report the results of RV variations in the binary star HD 135438. We found two significant periods: 494.98 d with eccentricity of 0.23 and 8494.1 d with eccentricity of 0.83. Considering orbital stability, it is impossible to have two companions in such close orbits with high eccentricity. To determine the nature of the changes in the RV variability, we analyzed indicators of stellar spot and stellar chromospheric activity to find that there are no signals related to the significant period of 494.98 d. However, we calculated the upper limits of rotation period of the rotational velocity and found this to be 478-536 d. One possible interpretation is that this may be closely related to the rotational modulation of an orbital inclination at 67-90 degrees. The other signal corresponding to the period of 8494.1 d is probably associated with a stellar companion orbiting the giant star. A Markov Chain Monte Carlo (MCMC) simulation considering a single companion indicates that HD 135438 system hosts a stellar companion with 0.57^+0.017 _-0.017 M_⊙ with an orbital period of 8498 d.

• Convergence Security Journal
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• v.23 no.5
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• pp.125-133
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• 2023

This paper proposes an AI model that determines parking and non-parking zones based on return authentication photos to address parking issues that may arise in shared electric scooter systems. In this study, we used a pre-trained Segformer_b0 model on ADE20K and fine-tuned it on tactile blocks and electric scooters to extract segmentation maps of objects related to parking and non-parking areas. We also presented a method to perform binary classification of parking and non-parking zones using the Swin model. Finally, after labeling a total of 1,689 images and fine-tuning the SegFomer model, it achieved an mAP of 81.26%, recognizing electric scooters and tactile blocks. The classification model, trained on a total of 2,817 images, achieved an accuracy of 92.11% and an F1-Score of 91.50% for classifying parking and non-parking areas.

• Journal of Preventive Medicine and Public Health
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• v.57 no.1
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• pp.65-72
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• 2024

Objectives: Protecting people against financial hardship caused by illness stands as a fundamental obligation within healthcare systems and constitutes a pivotal component in achieving universal health coverage. The objective of this study was to analyze the prevalence and determinants of catastrophic health expenditures (CHE) in Iran, over the period of 2013 to 2019. Methods: Data were obtained from 7 annual national surveys conducted between 2013 and 2019 on the income and expenditures of Iranian households. The prevalence of CHE was determined using a threshold of 40% of household capacity to pay for healthcare. A binary logistic regression model was used to identify the determinants influencing CHE. Results: The prevalence of CHE increased from 3.60% in 2013 to 3.95% in 2019. In all the years analyzed, the extent of CHE occurrence among rural populations exceeded that of urban populations. Living in an urban area, having a higher wealth index, possessing health insurance coverage, and having employed family members, an employed household head, and a literate household head are all associated with a reduced likelihood of CHE (p<0.05). Conversely, the use of dental, outpatient, and inpatient care, and the presence of elderly members in the household, are associated with an increased probability of facing CHE (p<0.05). Conclusions: Throughout the study period, CHE consistently exceeded the 1% threshold designated in the national development plan. Continuous monitoring of CHE and its determinants at both household and health system levels is essential for the implementation of effective strategies aimed at enhancing financial protection.