• The Journal of Korean Obstetrics and Gynecology
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• v.35 no.3
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• pp.105-121
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• 2022

Objectives: It is a statistical analysis study to examine the results of CaPSPI (Diagnostic System for Climacteric and Postmenopausal Syndrome Pattern Identification), developed for objective defecation of climacteric and postmenopausal syndrome. Methods: Total 341 people's questionnaire responses were statistically analyzed. 275 people involved in developing CaPSPI 2018 (E) and 146 people involved in 2019-2020 study of research1,3). Results: The frequency of diagnosis for examination was the highest at liver depression, 93.8% for 320 times, the lowest at heartheat, 62.8% for 214 times. The frequency of treatment for examination was the highest at liver depression, 54.3% for 185 times, and the lowest at dual deficiency of heart-spleen, 16.7% for 57 times. The diagnosis ratio was the lowest at dual deficiency of heart-spleen, 19.72%, and the highest at liver depression, 57.81%. As a result of comparing these diagnoses with the Kupperman's index, all showed significant differences. As a result of comparing these disease elements, all showed significant differences. The correlation between diagnosis and dialectic elements was found to have similar results with the korean medical pathology, and in 7 dialectics except for heartheat, the treatment version was more severe or progressing to perjury than for examination. Conclusions: The CaPSPI shows the characteristics of korean medicine well, and it is needed to utilize the high correlative disease elements to upgrade the system.

• Korean Journal of Clinical Laboratory Science
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• v.54 no.3
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• pp.179-191
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• 2022

Carbapenem-resistant Enterobacteriaceae (CRE) poses an increasing public health threat and has limited treatment options with high associated mortality. Genotypes of carbapenemase that threaten public health (bla_KPC, bla_NDM, bla_IMP, and bla_VIM) and bla_OXA-48-like genes were detected by phenotypic and molecular diagnosis, and related gene distribution patterns were investigated. Phenotypic testing using the modified Hodge test confirmed positivity in all 41 strains examined, and carbapenemase inhibitory testing using meropenem+phenyl boronic acid or meropenem+EDTA confirmed positivity in 18 and 8 strains, respectively. Polymerase chain reaction revealed the presence of amplification products in 28 strains of bla_KPC, 25 strains of bla_NDM, 5 strains of bla_IMP, 1 strain of bla_VIM, and 13 bla_OXA-48-like strains. In addition, 7 strains of bla_KPC+bla_NDM, 1 strain of bla_KPC+bla_IMP, 1 strain of bla_NDM+bla_OXA-48-like, 1 strain of bla_NDM+bla_VIM, 4 strains of bla_KPC+bla_NDM+bla_IMP, and 4 strains of bla_KPC+bla_NDM+bla_OXA-48-like were identified. Melting curve analysis using real-time PCR was wholly consistent with PCR results. The study shows genetic identification of highly specific CRE by real-time PCR could be used to provide early diagnoses and infection control, improve surveillance, and prevent the transmission of CRE.

• Journal of the Korea Society of Computer and Information
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• v.27 no.9
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• pp.49-57
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• 2022

Currently, the problem of food shortage is emerging in our society due to climate problems and an increase population in the world. As a solution to this problem, we propose a multi-remote control smart farm that combines artificial intelligence (AI) and information and communication technology (ICT) technologies. The proposed smart farm integrates ICT technology to remotely control and manage crops without restrictions in space and time, and to multi-control the growing environment of crops. In addition, using Arduino and deep-learning technology, a smart farm capable of multiple control through a smart-phone application (APP) was proposed, and Ai technology with various data securing and diagnosis functions while observing crop growth in real-time was included. Various sensors in the smart farm are controlled by using the Arduino, and the data values of the sensors are stored in the built database, so that the user can check the stored data with the APP. For multiple control for multiple crops, each LED, COOLING FAN, and WATER PUMP for two or more growing environments were applied so that the user could control it conveniently. And by implementing an APP that diagnoses the growth stage through the Tensor-Flow framework using deep-learning technology, we developed an application that helps users to easily diagnose the growth status of the current crop.

• Journal of Korea Entertainment Industry Association
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• v.14 no.5
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• pp.131-146
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• 2020

This research is based on social flow that is in need of sports welfare that diagnoses the delivery system of sports program pass that is typical business of national sports welfare services and operation structure, and analyze the supplier, operator, beneficiary and all that is related to business from multilateral aspects, therefore seek for operation systems for provision systems of sports welfare services. To clearly grasp the operating mechanisms of service provision system that is happening in real field, there were in-depth interview done by the 18 people of suppliers, operators, and beneficiaries that are the main participants of business, and through which drew an ideal agreed point for sports welfare services to get in the right direction. The result of this study is as following: First, based on the limited government budget for the compilation of budget for the business of sports welfare services it is found that there is need of constructing a pragmatic service provision system that can bring maximum of efficiency. Second, voucher that was introduced for market logic application and greater transparency of the business of sports welfare services has a complex structure that it is in need of simplification of structure which that is well fit with its characteristics. Third, for convenience enlargement in administration and management, make management policy of provision system be reflected and therefore enlarge the independence of management and secure the power of negotiation regarding fee savings through centralized budget management.

• Journal of the Korea Society of Computer and Information
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• v.27 no.8
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• pp.241-251
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• 2022

Diagnosis and management of customer's skin condition is an important essential function in the cosmetics and beauty industry. As the social media environment spreads and generalizes to all fields of society, the interaction of questions and answers to various and delicate concerns and requirements regarding the diagnosis and management of skin conditions is being actively dealt with in the social media community. However, since social media information is very diverse and atypical big data, an intelligent skin condition diagnosis system that combines appropriate skin condition information analysis and artificial intelligence technology is necessary. In this paper, we developed the skin condition diagnosis system SCDIS to intelligently diagnose and manage the skin condition of customers by processing the text analysis information of social media into learning data. In SCDIS, an artificial neural network model, AnnTFIDF, that automatically diagnoses skin condition types using artificial neural network technology, a deep learning machine learning method, was built up and used. The performance of the artificial neural network model AnnTFIDF was analyzed using test sample data, and the accuracy of the skin condition type diagnosis prediction value showed a high performance of about 95%. Through the experimental and performance analysis results of this paper, SCDIS can be evaluated as an intelligent tool that can be used efficiently in the skin condition analysis and diagnosis management process in the cosmetic and beauty industry. And this study can be used as a basic research to solve the new technology trend, customized cosmetics manufacturing and consumer-oriented beauty industry technology demand.

• The Journal of the Korea Contents Association
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• v.22 no.2
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• pp.125-134
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• 2022

Due to the development of smartphone technology, as of 2020, 91.9% of people use the Internet[1] to frequently acquire information through websites and mobile apps. As the number of homepages in charge of providing information is increasing every year, the number of applications for web vulnerability diagnosis, which diagnoses the safety of homepages, is also increasing. In the existing web vulnerability check, the number of diagnostic personnel should increase in proportion to the number of homepages that need diagnosis because the diagnosticians manually test the homepages for vulnerabilities. In reality, however, there is a limit to securing a web vulnerability diagnosis manpower, and if the number of diagnosis manpower is increased, a lot of costs are incurred. To solve these problems, an automatic diagnosis tool is used to replace a part of the manual diagnosis. This paper explores a new method to expand the current automatic diagnosis range. In other words, automatic diagnosis possible items were derived by analyzing the impact of web vulnerability diagnosis items. Furthermore, automatic diagnosis identified possible items through comparative analysis of diagnosis results by performing manual and automatic diagnosis on the website in operation. In addition, it is possible to replace manual diagnosis for possible items, but not all vulnerability items, through the improvement of automatic diagnosis tools. This paper will explore some suggestions that can help improve plans to support and implement automatic diagnosis. Through this, it will be possible to contribute to the creation of a safe website operating environment by focusing on the parts that require precise diagnosis.

• Journal of Science Education
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• v.45 no.3
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• pp.349-363
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• 2021

The purpose of this study is to develop an instrument for school STEAM education diagnostic assessment. Literature reviews, the developmental study of a prototype instrument, experts' advices, and pilot study were administrated. The school STEAM education diagnostic assessment was consist of five areas: 'STEM education action and sustainability plan,' 'STEAM curriculum and instruction,' 'STEAM professional development,' 'process-based evaluation,' and 'community and partnerships.' Each area had one to five sub-areas. A total of 14 diagnosis items were developed, including items that can diagnose the school's STEAM environment base and STEAM education execution level at the school unit and member level for each area. The validation of the diagnostic assessment was conducted through the content validity of the expert group and the validity of a survey targeting school teachers. For applying the instrument for STEAM Education School Assessment to schools, a total of 267 elementary, middle, and high schools participated. As a result, the average of the five areas was 1.46 to 2.18. This instrument comprehensively diagnoses and evaluates the implementation and effectiveness of STEAM education in schools, and is expected to be used as basic data and core data for implementing STEAM education.

• The Korean Society of Law and Medicine
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• v.24 no.1
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• pp.43-65
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• 2023

The healthcare industry is a digital healthcare that combines technology based on the 4th Industrial Revolution, dealing with information on individual health and medical care, and is a fusion of health care services and medical science and technology. It is questionable whether digital healthcare according to the paradigm change can be discussed by the concept of medical practice under the existing Medical Act. There is no clear definition of the concept of medical practice in the Medical Service Act, but the concept is established through precedents. In addition, under the Medical Service Act, the subject of medical practice is limited to medical personnel. However, digital healthcare sometimes diagnoses and treats diseases using digital technology by medical personnel. On the other hand, what is possible by non-medical personnel is digital healthcare. This is because digital healthcare is understood as a concept that includes health care such as exercise, eating habits, and weight control. For this reason, if the concept of medical practice under the "Medical Act" on digital healthcare is included, it is subject to criminal punishment for "unlicensed medical practice" prescribed in Article 27 of the "Medical Act". In the health and medical industry, digital transformation and convergence with information and communication technology are rapidly progressing. As a result, there is a need to newly define it as 'digitalized medical practice' or 'information and communication technology (ICT)-based medical practice' separately from existing medical practices. The concept of medical practice has variability, not a fixed and invariable concept. However, in response to this demand, it is not an infinite expansion of the concept of medical practice, but a request to reset its scope. Therefore, the concept of medical practice should be legislated by reflecting the demand of consumers for the medical service system.

• Korean Journal of Acupuncture
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• v.40 no.3
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• pp.62-78
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• 2023

Objectives : This study aims to assess the impact of acupotomy on migraine through an examination of clinical studies conducted since 2015. Methods : We conducted a comprehensive search for randomized controlled trials (RCTs) and non-randomized controlled trials (nRCTs) related to acupotomy treatment for migraine, utilizing five Korean online databases (OASIS, Science ON, DBPIA, KISS, RISS), as well as four foreign online databases (CNKI, PubMed, EMBASE, Cochrane Library). We identified a total of 10 relevant studies for analysis. Participants characteristics, treatment points, combination treatments, treatment cycles or frequencies, evaluation indices, efficacy, and adverse events were analyzed. The risk of bias in the 10 RCTs was assessed using the Revised Cochrane risk-of-bias tool for randomized trials (RoB 2.0). Results : A total of 931 participants were included in 10 studies. In the intervention group, the average duration of migraine morbidity ranged from 15.5±4.5 months to 15.9±4.2 years. Six studies based their diagnoses on the International Classification of Headache Disorders (ICHD), while five studies relied on Chinese diagnostic criteria. All studies specified the treatment area as the region exhibiting tenderness or induration on the head and neck. Treatment cycles ranged from a minimum of 2 days to a maximum of 1 week, with the number of days per treatment course varied from 5 days to 4 weeks. The diameter of acupuncture needles used varied between 0.3 mm and 1 mm. Of the eight studies specifying needle length, the shortest was 20 mm, and the longest was 40 mm. A total of eight evaluation indices were employed, with total efficacy rate (TER) and visual analogue scale (VAS) being the most frequently used. Statistically, all intervention groups showed more significant results compared to the control groups. Adverse events were reported in only two studies within the intervention group. Overall, the risk of bias assessment for the selected RCTs ranged from 'some concerns' to 'high risk of bias.' Conclusions : This study showed that acupotomy treatments for migraine were effective.

• Journal of Korea Water Resources Association
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• v.55 no.spc1
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• pp.1177-1185
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• 2022

The water and sewage system is an infrastructure that provides safe and clean water to people. In particular, since the water and sewage pipelines are buried underground, it is very difficult to detect system defects. For this reason, the diagnosis of pipelines is limited to post-defect detection, such as system diagnosis based on the images taken after taking pictures and videos with cameras and drones inside the pipelines. Therefore, real-time detection technology of pipelines is required. Recently, pipeline diagnosis technology using advanced equipment and artificial intelligence techniques is being developed, but AI-based defect detection technology requires a variety of learning data because the types and numbers of defect data affect the detection performance. Therefore, in this study, various defect scenarios are implemented using 3D printing model to improve the detection performance when detecting defects in pipelines. Afterwards, the collected images are performed to pre-processing such as classification according to the degree of risk and labeling of objects, and real-time defect detection is performed. The proposed technique can provide real-time feedback in the pipeline defect detection process, and it would be minimizing the possibility of missing diagnoses and improve the existing water and sewerage pipe diagnosis processing capability.