• Journal of the Korea Institute of Construction Safety
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• v.6 no.1
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• pp.27-32
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• 2024

In this study, based on accident cases of manned and unmanned tower cranes, the types and causes of accidents were analyzed and tower crane accident prevention measures were proposed accordingly. As a result, 'lack of communication' was commonly analyzed as the biggest cause of accidents. Therefore, in this study, we investigated domestic and international systems and laws regarding signalmen responsible for communication between tower crane operators and workers and proposed the following three improvement methods. First, the signalman system must be legally and institutionally reestablished. Second, national agencies and private organizations with expertise should create standardized training manuals and distribute them to signalman educators, and create checklists to manage educators. Third, in the case of a site using a tower crane, the employer must mandatorily deploy a signalman with professional qualifications. Lastly, the results of this study are expected to highlight the differences in accident types and causes of manned and unmanned tower cranes and the need for legal and institutional improvement in the signal system.

• Journal of the Korean earth science society
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• v.45 no.2
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• pp.111-120
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• 2024

Cloud coverage is a key factor in determining whether to proceed with observations. In the past, human judgment played an important role in weather evaluation for observations. However, the development of remote and robotic observation has diminished the role of human judgment. Moreover, it is not easy to evaluate weather conditions automatically because of the diverse cloud shapes and their rapid movement. In this paper, we present the development of a cloud monitoring program by applying a machine learning-based Python module "cloudynight" on all-sky camera images obtained at Miryang Arirang Astronomical Observatory (MAAO). The machine learning model was built by training 39,996 subregions divided from 1,212 images with altitude/azimuth angles and extracting 16 feature spaces. For our training model, the F1-score from the validation samples was 0.97, indicating good performance in identifying clouds in the all-sky image. As a result, this program calculates "Cloudiness" as the ratio of the number of total subregions to the number of subregions predicted to be covered by clouds. In the robotic observation, we set a policy that allows the telescope system to halt the observation when the "Cloudiness" exceeds 0.6 during the last 30 minutes. Following this policy, we found that there were no improper halts in the telescope system due to incorrect program decisions. We expect that robotic observation with the 0.7 m telescope at MAAO can be successfully operated using the cloud monitoring program.

• The Journal of the Convergence on Culture Technology
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• v.10 no.2
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• pp.517-524
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• 2024

This study aims to train and implement a deep learning model for the fusion of website creation and artificial intelligence, in the era known as the AI revolution following the launch of the ChatGPT service. The deep learning model was trained using 3,000 collected web page images, processed based on a system of component and layout classification. This process was divided into three stages. First, prior research on AI models was reviewed to select the most appropriate algorithm for the model we intended to implement. Second, suitable web page and paragraph images were collected, categorized, and processed. Third, the deep learning model was trained, and a serving interface was integrated to verify the actual outcomes of the model. This implemented model will be used to detect multiple paragraphs on a web page, analyzing the number of lines, elements, and features in each paragraph, and deriving meaningful data based on the classification system. This process is expected to evolve, enabling more precise analysis of web pages. Furthermore, it is anticipated that the development of precise analysis techniques will lay the groundwork for research into AI's capability to automatically generate perfect web pages.

• Journal of Korean Medicine Rehabilitation
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• v.34 no.1
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• pp.65-81
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• 2024

Objectives This study aimed to understand the general research trends, applicated disease, and methodology of transcutaneous/percutaneous vagus nerve stimulation, contemplating its clinical use in traditional Korean medicine and future research directions. Methods A scoping review was conducted following Arksey and O'Malley Framework Stage and adhering to the PRISMA extension for scoping reviews: checklist and explanation. Papers published until October 30, 2023, were investigated across 10 databases (PubMed, Embase, Scopus, Web of Science, China National Knowledge Infrastructure, Oriental Medicine Advanced Searching Integrated System, Korean Studies Information Service System, KMbase, Science ON, Research Information Sharing Service. The search terms used were 'Transcutaneous/Percutaneous vagus nerve stimulation'. Results Since 2021, the application of transcutaneous/percutaneous vagus nerve stimulation for musculoskeletal symptoms has been actively researched, predominantly in Asia (37%), Europe (37%), and North America (21%). All 19 papers were part of clinical studies. Chronic pain was noted that most applied disease, it also was found to potentially aid in acute post-surgical pain relief. Major assessment tools include not only simple pain metrics but also pain perception, vagal nerve tension, quality of life, and inflammatory markers. Most procedures were carried out through the ear, which offers a favorable site for therapeutic stimulation without notable side effects. And parameter analysis, frequencies typically ranged around 25 Hz to 30 Hz, while pulse widths were commonly set at 250 ㎲ or 300 ㎲. Conclusions Transcutaneous/percutaneous vagus nerve stimulation is easily accessible through acupuncture in Korean medicine. Therefore, if future studies establish parameters and clinical significance, it could be utilized as a therapeutic modality.

• Journal of Gastric Cancer
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• v.24 no.3
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• pp.327-340
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• 2024

Purpose: Results of initial endoscopic biopsy of gastric lesions often differ from those of the final pathological diagnosis. We evaluated whether an artificial intelligence-based gastric lesion detection and diagnostic system, ENdoscopy as AI-powered Device Computer Aided Diagnosis for Gastroscopy (ENAD CAD-G), could reduce this discrepancy. Materials and Methods: We retrospectively collected 24,948 endoscopic images of early gastric cancers (EGCs), dysplasia, and benign lesions from 9,892 patients who underwent esophagogastroduodenoscopy between 2011 and 2021. The diagnostic performance of ENAD CAD-G was evaluated using the following real-world datasets: patients referred from community clinics with initial biopsy results of atypia (n=154), participants who underwent endoscopic resection for neoplasms (Internal video set, n=140), and participants who underwent endoscopy for screening or suspicion of gastric neoplasm referred from community clinics (External video set, n=296). Results: ENAD CAD-G classified the referred gastric lesions of atypia into EGC (accuracy, 82.47%; 95% confidence interval [CI], 76.46%-88.47%), dysplasia (88.31%; 83.24%-93.39%), and benign lesions (83.12%; 77.20%-89.03%). In the Internal video set, ENAD CAD-G identified dysplasia and EGC with diagnostic accuracies of 88.57% (95% CI, 83.30%-93.84%) and 91.43% (86.79%-96.07%), respectively, compared with an accuracy of 60.71% (52.62%-68.80%) for the initial biopsy results (P<0.001). In the External video set, ENAD CAD-G classified EGC, dysplasia, and benign lesions with diagnostic accuracies of 87.50% (83.73%-91.27%), 90.54% (87.21%-93.87%), and 88.85% (85.27%-92.44%), respectively. Conclusions: ENAD CAD-G is superior to initial biopsy for the detection and diagnosis of gastric lesions that require endoscopic resection. ENAD CAD-G can assist community endoscopists in identifying gastric lesions that require endoscopic resection.

• The Journal of the Convergence on Culture Technology
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• v.10 no.5
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• pp.445-452
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• 2024

Through the pandemic, the topography of dining culture is rapidly changing due to the advancement of the food delivery market. Competition in the domestic market is intensifying as Coupang Eats recently surpassed Yogiyo and jumped to second place, and Baedal Minjok(Baemin), the industry's No. 1 company, is also preparing to introduce a subscription system. While the growth of the delivery market is slowing, the use of takeout and pick-up services is increasing due to rising delivery costs and food prices. From Generation Z's perspective, the main factors influencing the active use of app services were identified through prior research as usability and convenience, cost sensitivity, and hedonic motivation. While, they are leading the trend of minimizing spending through 'stepping stone consumption' and delivery pot process instead of choosing a subscription system. Accordingly, we aim to provide customers with a better experience and help strengthen competitiveness by proposing ways to improve and revitalize new delivery apps that reflect the characteristics of Gen.Z. As a result of the expert Delphi survey, we will receive impact evaluation scores in the following order: direct view of accumulated discounts, addition of family benefits, coupon reinforcement, SNS promotion, pick-up walk, in-store promotion, and discount rate display, and review their application to practice. It presents academic and policy implications regarding the food tech market.

• Journal of Intelligence and Information Systems
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• v.20 no.2
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• pp.109-122
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• 2014

People are nowadays creating a tremendous amount of data on Social Network Service (SNS). In particular, the incorporation of SNS into mobile devices has resulted in massive amounts of data generation, thereby greatly influencing society. This is an unmatched phenomenon in history, and now we live in the Age of Big Data. SNS Data is defined as a condition of Big Data where the amount of data (volume), data input and output speeds (velocity), and the variety of data types (variety) are satisfied. If someone intends to discover the trend of an issue in SNS Big Data, this information can be used as a new important source for the creation of new values because this information covers the whole of society. In this study, a Twitter Issue Tracking System (TITS) is designed and established to meet the needs of analyzing SNS Big Data. TITS extracts issues from Twitter texts and visualizes them on the web. The proposed system provides the following four functions: (1) Provide the topic keyword set that corresponds to daily ranking; (2) Visualize the daily time series graph of a topic for the duration of a month; (3) Provide the importance of a topic through a treemap based on the score system and frequency; (4) Visualize the daily time-series graph of keywords by searching the keyword; The present study analyzes the Big Data generated by SNS in real time. SNS Big Data analysis requires various natural language processing techniques, including the removal of stop words, and noun extraction for processing various unrefined forms of unstructured data. In addition, such analysis requires the latest big data technology to process rapidly a large amount of real-time data, such as the Hadoop distributed system or NoSQL, which is an alternative to relational database. We built TITS based on Hadoop to optimize the processing of big data because Hadoop is designed to scale up from single node computing to thousands of machines. Furthermore, we use MongoDB, which is classified as a NoSQL database. In addition, MongoDB is an open source platform, document-oriented database that provides high performance, high availability, and automatic scaling. Unlike existing relational database, there are no schema or tables with MongoDB, and its most important goal is that of data accessibility and data processing performance. In the Age of Big Data, the visualization of Big Data is more attractive to the Big Data community because it helps analysts to examine such data easily and clearly. Therefore, TITS uses the d3.js library as a visualization tool. This library is designed for the purpose of creating Data Driven Documents that bind document object model (DOM) and any data; the interaction between data is easy and useful for managing real-time data stream with smooth animation. In addition, TITS uses a bootstrap made of pre-configured plug-in style sheets and JavaScript libraries to build a web system. The TITS Graphical User Interface (GUI) is designed using these libraries, and it is capable of detecting issues on Twitter in an easy and intuitive manner. The proposed work demonstrates the superiority of our issue detection techniques by matching detected issues with corresponding online news articles. The contributions of the present study are threefold. First, we suggest an alternative approach to real-time big data analysis, which has become an extremely important issue. Second, we apply a topic modeling technique that is used in various research areas, including Library and Information Science (LIS). Based on this, we can confirm the utility of storytelling and time series analysis. Third, we develop a web-based system, and make the system available for the real-time discovery of topics. The present study conducted experiments with nearly 150 million tweets in Korea during March 2013.

• Journal of Intelligence and Information Systems
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• v.24 no.4
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• pp.111-136
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• 2018

In this paper, we propose a methodology to extract answer information about queries from various types of unstructured documents collected from multi-sources existing on web in order to expand knowledge base. The proposed methodology is divided into the following steps. 1) Collect relevant documents from Wikipedia, Naver encyclopedia, and Naver news sources for "subject-predicate" separated queries and classify the proper documents. 2) Determine whether the sentence is suitable for extracting information and derive the confidence. 3) Based on the predicate feature, extract the information in the proper sentence and derive the overall confidence of the information extraction result. In order to evaluate the performance of the information extraction system, we selected 400 queries from the artificial intelligence speaker of SK-Telecom. Compared with the baseline model, it is confirmed that it shows higher performance index than the existing model. The contribution of this study is that we develop a sequence tagging model based on bi-directional LSTM-CRF using the predicate feature of the query, with this we developed a robust model that can maintain high recall performance even in various types of unstructured documents collected from multiple sources. The problem of information extraction for knowledge base extension should take into account heterogeneous characteristics of source-specific document types. The proposed methodology proved to extract information effectively from various types of unstructured documents compared to the baseline model. There is a limitation in previous research that the performance is poor when extracting information about the document type that is different from the training data. In addition, this study can prevent unnecessary information extraction attempts from the documents that do not include the answer information through the process for predicting the suitability of information extraction of documents and sentences before the information extraction step. It is meaningful that we provided a method that precision performance can be maintained even in actual web environment. The information extraction problem for the knowledge base expansion has the characteristic that it can not guarantee whether the document includes the correct answer because it is aimed at the unstructured document existing in the real web. When the question answering is performed on a real web, previous machine reading comprehension studies has a limitation that it shows a low level of precision because it frequently attempts to extract an answer even in a document in which there is no correct answer. The policy that predicts the suitability of document and sentence information extraction is meaningful in that it contributes to maintaining the performance of information extraction even in real web environment. The limitations of this study and future research directions are as follows. First, it is a problem related to data preprocessing. In this study, the unit of knowledge extraction is classified through the morphological analysis based on the open source Konlpy python package, and the information extraction result can be improperly performed because morphological analysis is not performed properly. To enhance the performance of information extraction results, it is necessary to develop an advanced morpheme analyzer. Second, it is a problem of entity ambiguity. The information extraction system of this study can not distinguish the same name that has different intention. If several people with the same name appear in the news, the system may not extract information about the intended query. In future research, it is necessary to take measures to identify the person with the same name. Third, it is a problem of evaluation query data. In this study, we selected 400 of user queries collected from SK Telecom 's interactive artificial intelligent speaker to evaluate the performance of the information extraction system. n this study, we developed evaluation data set using 800 documents (400 questions * 7 articles per question (1 Wikipedia, 3 Naver encyclopedia, 3 Naver news) by judging whether a correct answer is included or not. To ensure the external validity of the study, it is desirable to use more queries to determine the performance of the system. This is a costly activity that must be done manually. Future research needs to evaluate the system for more queries. It is also necessary to develop a Korean benchmark data set of information extraction system for queries from multi-source web documents to build an environment that can evaluate the results more objectively.

• Journal of Korean Academy of Nursing
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• v.30 no.6
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• pp.1488-1502
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• 2000

This study, based on current home nursing services, aims at promoting measures for establishing a community-based home nursing system derived from the pilot home nursing demonstration project conducted by the Seoul Nurses Association. The study was based on an analysis of home nursing records from march 1993 to December 1999. The following is a summary analysis, based on individual characteristics of the patients, the organization, which recommended the service for their patients and personnel services. 1. The service has been used by many elderly people 60years of age or older(66.4%). and married people(60.9%). The average number of visits by service personnel for patients of city government was 23.5. This is 2.5 times as many visits by general patients. General patients(20.2%) had only one visit from service personnel, while 65.5% of patients of city government had 10 or more visits. Particularly, for government recommended patients, 72.7% of the patients were recommended by nurses, while only 21.9% where referred to the services by doctors. The main focus of a home nursing service was to maintain present health status (53.4%), and hospice(11.6%). Also to increase hospital-based home nursing services focused on recovery(55.9%) and maintain present health conditions (19.0%). 2. For general patients, 42.0% of patients were suffering from problems related to CVA, 11.3% from high blood pressure, and for patients referred from city, 21.2% from skeletal muscular disease. Results of home nursing services 29.4% of patients were able to recover or maintain their health status, but 48.9% of the patients died. Another main point of community-based home nursing services is medication(6.7%), other basic nursing services(6.1%), special treatment, instructions on how to use medical devices(5.9%), change of physical posture(4.6%), and training on changing physical positions(4.7%). As mentioned above there were some differences between the characteristics of patients who used the pilot home nursing service conducted by the Seoul Nurses Association and those hospital-based service users. The results are believed to be useful to support a community-based home nursing service model. Particularly, patients under medical supervision and patients recommended by government-run health clinics show a higher frequency and longer use of home nursing services compared to general patients or hospital-based home nursing service users. According to the study, nurses accounted for a large number of recommendations for home nursing services. Many patients with CVA, high blood pressure, skeletal muscular disease and bedsores used community-based home nursing services, while others used the service for minor treatments or maintaining their current health status. Based on the study, the researchers make several suggestions to establish a community- based home nursing service system. First, different ways of setting up a community-based home nursing system have to be mapped out based on the evaluation of the pilot home nursing service conducted by the Seoul Nurses Association. Secondly, a new, community-based, home health care nursing service model, and reimbursement payment system have to be developed. This is based on the outcome of the analysis, and implemented policy. Accordingly, efforts are needed to develop a community- based home nursing system with an intermediary role to promote the visiting nursing services of government-run health centers.

• Journal of Korean Academy of Nursing
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• v.13 no.1
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• pp.7-21
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• 1983

For the flexible and rational distribution of limited existing health resources based on measurements of individual risk, the socalled Risk Approach is being proposed by the World Health Organization as a managerial tool in maternal and child health care program. This approach, in principle, puts us under the necessity of developing a technique by which we will be able to measure the degree of risk or to discriminate the future outcomes of pregnancy on the basis of prior information obtainable at prenatal care delivery settings. Numerous recent studies have focussed on the identification of relevant risk factors as the Prior infer mation and on defining the adverse outcomes of pregnancy to be dicriminated, and also have tried on how to develope scoring system of risk factors for the quantitative assessment of the factors as the determinant of pregnancy outcomes. Once the scoring system is established the technique of classifying the patients into with normal and with adverse outcomes will be easily de veloped. The scoring system should be developed to meet the following four basic requirements. 1) Easy to construct 2) Easy to use 3) To be theoretically sound 4) To be valid In searching for a feasible methodology which will meet these requirements, the author has attempted to apply the“Likelihood Method”, one of the well known principles in statistical analysis, to develop such scoring system according to the process as follows. Step 1. Classify the patients into four groups: Group $A_1$: With adverse outcomes on fetal (neonatal) side only. Group $A_2$: With adverse outcomes on maternal side only. Group $A_3$: With adverse outcome on both maternal and fetal (neonatal) sides. Group B: With normal outcomes. Step 2. Construct the marginal tabulation on the distribution of risk factors for each group. Step 3. For the calculation of risk score, take logarithmic transformation of relative proport-ions of the distribution and round them off to integers. Step 4. Test the validity of the score chart. h total of 2, 282 maternity records registered during the period of January 1, 1982-December 31, 1982 at Ewha Womans University Hospital were used for this study and the“Questionnaire for Maternity Record for Prenatal and Intrapartum High Risk Screening”developed by the Korean Institute for Population and Health was used to rearrange the information on the records into an easy analytic form. The findings of the study are summarized as follows. 1) The risk score chart constructed on the basis of“Likelihood Method”ispresented in Table 4 in the main text. 2) From the analysis of the risk score chart it was observed that a total of 24 risk factors could be identified as having significant predicting power for the discrimination of pregnancy outcomes into four groups as defined above. They are: (1) age (2) marital status (3) age at first pregnancy (4) medical insurance (5) number of pregnancies (6) history of Cesarean sections (7). number of living child (8) history of premature infants (9) history of over weighted new born (10) history of congenital anomalies (11) history of multiple pregnancies (12) history of abnormal presentation (13) history of obstetric abnormalities (14) past illness (15) hemoglobin level (16) blood pressure (17) heart status (18) general appearance (19) edema status (20) result of abdominal examination (21) cervix status (22) pelvis status (23) chief complaints (24) Reasons for examination 3) The validity of the score chart turned out to be as follows: a) Sensitivity: Group $A_1$: 0.75 Group $A_2$: 0.78 Group $A_3$: 0.92 All combined : 0.85 b) Specificity : 0.68 4) The diagnosabilities of the“score chart”for a set of hypothetical prevalence of adverse outcomes were calculated as follows (the sensitivity“for all combined”was used). Hypothetidal Prevalence : 5％ 10％ 20％ 30％ 40％ 50％ 60％ Diagnosability : 12% 23% 40% 53% 64% 75% 80%.