• The Journal of the Convergence on Culture Technology
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• v.5 no.4
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• pp.37-41
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• 2019

The following study, as the importance of military role in a national disaster is emerging as a part of comprehensive security, there has been a number of elements of social disaster-related support in support of each type of national disaster aimed to improve the military's role towards comprehensive security but there has been no regular study of this topic. The point of this study is to analyze various aspects and hardships during the mission and improve the effectiveness of future support missions by observing and interviewing the military personnel which substituted the role of train drivers in the Seoul Metro in 2016, when the Korean Railroad Corporation [KORAIL] Workers Union was on strike [72 days] which is the longest period of a national disaster requiring military assistance.

• Journal of IKEEE
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• v.22 no.4
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• pp.1079-1087
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• 2018

Recently, computer vision field based deep learning artificial intelligence has become a hot topic among various image analysis boundaries. In this study, flames are detected in fire images using the Faster R-CNN algorithm, which is used to detect objects within the image, among various image recognition algorithms based on deep learning. In order to improve fire detection accuracy through a small amount of data sets in the learning process, we use image augmentation techniques, and learn image augmentation by dividing into 6 types and compare accuracy, precision and detection rate. As a result, the detection rate increases as the type of image augmentation increases. However, as with the general accuracy and detection rate of other object detection models, the false detection rate is also increased from 10% to 30%.

• Tuberculosis and Respiratory Diseases
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• v.82 no.4
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• pp.285-297
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• 2019

Connective tissue disease (CTD) is a collection of disorders characterized by various signs and symptoms such as circulation of autoantibodies in the entire system causing damage to internal organs. Interstitial lung disease (ILD) which is associated with CTD is referred to as CTD-ILD. Patients diagnosed with ILD should be thoroughly examined for the cooccurrence of CTD, since the treatment procedures and prognosis of CTD-ILD are vary from those of idiopathic interstitial pneumonia. The representative types of CTD which may accompany ILD include rheumatoid arthritis, systemic sclerosis (SSc), Sjogren's syndrome, mixed CTD, idiopathic inflammatory myopathies, and systemic lupus erythematous. Of these, ILD most frequently co-exists with SSc. If an ILD is observed in the chest, high resolution computed tomography and specific diagnostic criteria for any type of CTD are met, then a diagnosis of CTD-ILD is made. It is challenging to conduct a properly designed randomized study on CTD-ILD, due to low incidence. Therefore, CTD-ILD treatment approach is yet to been established in absence of randomized controlled clinical trials, with the exception of SSc-ILD. When a patient is presented with acute CTD-ILD or if symptoms occur due to progression of the disease, steroid and immunosuppressive therapy are generally considered.

• The Journal of the Korea Contents Association
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• v.21 no.10
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• pp.11-20
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• 2021

The analysis of citing and cited phrases provides an opportunity to enhance search-centric academic information services. However, most current studies focus only on citation analysis among academic associations, researchers, and articles, making it challenging to develop higher citation-based information services. This study proposes citation analysis service methods using citing and cited phrases. First, to verify the feasibility of suggested services, we have collected the most highly cited articles with specific domain terms and followed their citing relationship; after that, we found formal citation types and ratios in the original articles. And we conducted structural analysis, especially with three topics, "Deep Learning," "Green Energy," and "Aging," and then structurally illustrates the citation characteristics of related articles. Finally, we collected four most cited articles and all their citing ones for each subject from Google Scholar and analyzed the ratio of citation types and citation spread. We hope that various citation analysis studies and information services can be further developed based on our discussion for designing better information services.

• Journal of Digital Convergence
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• v.17 no.11
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• pp.233-240
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• 2019

In order to predict and respond to cyber attacks, a number of security companies quickly identify the methods, types and characteristics of attack techniques and are publishing Security Intelligence Reports(SIRs) on them. However, the SIRs distributed by each company are huge and unstructured. In this paper, we propose a framework that uses five analytic techniques to formulate a report and extract key information in order to reduce the time required to extract information on large unstructured SIRs efficiently. Since the SIRs data do not have the correct answer label, we propose four analysis techniques, Keyword Extraction, Topic Modeling, Summarization, and Document Similarity, through Unsupervised Learning. Finally, has built the data to extract threat information from SIRs, analysis applies to the Named Entity Recognition (NER) technology to recognize the words belonging to the IP, Domain/URL, Hash, Malware and determine if the word belongs to which type We propose a framework that applies a total of five analysis techniques, including technology.

• Journal of the Korea Society of Computer and Information
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• v.25 no.12
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• pp.261-270
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• 2020

In this study, we identify promising technologies for Piggyback transportation system by analyzing the relevant patent information. In order for this, we first develop the patent database by extracting relevant technology keywords from the pioneering research papers for the Piggyback flactcar system. We then employed textmining to identify the frequently referred words from the patent database, and using these words, we applied the LDA (Latent Dirichlet Allocation) algorithm in order to identify "topics" that are corresponding to "key" technologies for the Piggyback system. Finally, we employ the ARIMA model to forecast the trends of these "key" technologies for technology forecasting, and identify the promising technologies for the Piggyback system. with keyword search method the patent analysis. The results show that data-driven integrated management system, operation planning system and special cargo (especially fluid and gas) handling/storage technologies are identified to be the "key" promising technolgies for the future of the Piggyback system, and data reception/analysis techniques must be developed in order to improve the system performance. The proposed procedure and analysis method provides useful insights to develop the R&D strategy and the technology roadmap for the Piggyback system.

• The Journal of the Korea Contents Association
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• v.21 no.3
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• pp.10-22
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• 2021

This study conducted usability test to users in 20s in order to find problems for improving news apps of the major broadcasting companies. Efficiency, effectiveness, and satisfaction were evaluated by mobile news content type. Also there is including analysis of the news topics (hard news, soft news) and broadcasters (MBC, SBS). As a result, same problems were found in common items according to mobile news content types. And in the news topic, there was a difference in the news values and news attributes that need to be improved. This study gives practical implications to the news producers to improve the contents of news apps.

• International Journal of Computer Science & Network Security
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• v.22 no.5
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• pp.342-347
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• 2022

On Cloud, the important data of the user that is protected on remote servers can be accessed via internet. Due to rapid shift in technology nowadays, there is a swift increase in the confidential and pivotal data. This comes up with the requirement of data security of the user's data. Data is of different type and each need discrete degree of conservation. The idea of data security data science permits building the computing procedure more applicable and bright as compared to conventional ones in the estate of data security. Our focus with this paper is to enhance the safety of data on the cloud and also to obliterate the problems associated with the data security. In our suggested plan, some basic solutions of security like cryptographic techniques and authentication are allotted in cloud computing world. This paper put your heads together about how machine learning techniques is used in data security in both offensive and defensive ventures, including analysis on cyber-attacks focused at machine learning techniques. The machine learning technique is based on the Supervised, UnSupervised, Semi-Supervised and Reinforcement Learning. Although numerous research has been done on this topic but in reference with the future scope a lot more investigation is required to be carried out in this field to determine how the data can be secured more firmly on cloud in respect with the Machine Learning Techniques and cryptographic methods.

• Pediatric Gastroenterology, Hepatology & Nutrition
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• v.25 no.3
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• pp.194-210
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• 2022

Human milk contains a number of nutritional and bioactive molecules including microorganisms that constitute the so-called "Human Milk Microbiota (HMM)". Recent studies have shown that not only bacterial but also viral, fungal, and archaeal components are present in the HMM. Previous research has established, a "core" microbiome, consisting of Firmicutes (i.e., Streptococcus, Staphylococcus), Proteobacteria (i.e., Serratia, Pseudomonas, Ralstonia, Sphingomonas, Bradyrhizobium), and Actinobacteria (i.e., Propionibacterium, Corynebacterium). This review aims to summarize the main characteristics of HMM and the role it plays in shaping a child's health. We reviewed the most recent literature on the topic (2019-2021), using the PubMed database. The main sources of HMM origin were identified as the retrograde flow and the entero-mammary pathway. Several factors can influence its composition, such as maternal body mass index and diet, use of antibiotics, time and type of delivery, and mode of breastfeeding. The COVID-19 pandemic, by altering the mother-infant dyad and modifying many of our previous habits, has emerged as a new risk factor for the modification of HMM. HMM is an important contributor to gastrointestinal colonization in children and therefore, it is fundamental to avoid any form of perturbation in the HMM that can alter the microbial equilibrium, especially in the first 100 days of life. Microbial dysbiosis can be a trigger point for the development of necrotizing enterocolitis, especially in preterm infants, and for onset of chronic diseases, such as asthma and obesity, later in life.

• Journal of the Korea Society of Computer and Information
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• v.28 no.4
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• pp.209-216
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• 2023

In this paper, artificial intelligence agents ChatGPT and Stable Diffusion were used to explore the possibility of educational use by implementing a program to recommend picture materials for teaching and learning according to the class topic entered by teachers. The average time spent recommending all picture materials is about 6 minutes. In general, pictures related to keywords were recommended, and the letters in the recommended pictures could only know the intention to represent the letters, and the letters could not be recognized and the meaning could not be known. However, further research seems to be needed on the fact that the type or content of the recommended picture depends entirely on the response of ChatGPT and that it is not possible to accurately recommend the picture for all keywords. In addition, it was concluded that it is true that the recommended picture is related to the keyword, but the evaluation of whether it has educational value is the subject of discussion that should be left to the judgment of human teachers.