• Quality Improvement in Health Care
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• v.27 no.2
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• pp.57-72
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• 2021

Purpose: At present, there are a variety of serious patient safety incidents related to problems in health information technology (HIT), specifically involving electronic medical records (EMRs). This emphasizes the need for an enhanced electronic medical record system (EMRS). As such, this study analyzed both the nature of and potential to prevent incidents associated with HIT/EMRS based on data from the Korea Patient Safety Reporting and Learning System (KOPS). Methods: This study analyzed patient safety incidents submitted to KOPS between August 2016 and December 2019. HIT keywords were used to extract HIT/EMRS incidents. Each case was reviewed to confirm whether the contributing factors were related to HIT/EMRS (HIT/EMRS-related incidents) and if the incident could have been prevented (HIT/EMRS-preventable incidents). The selected reports were summarized for general clarity (e.g., incident type, and degree of harm). Results: Of the 25,515 obtained reports, 2,664 incidents (10.4%) were HIT-related, while 2,525 (9.9%) were EMRS-related. HIT/EMRS-related incidents were the third largest type of incident followed by 'fall' and 'medication incidents.' More than 80% of HIT/EMRS-related incidents were medication-related, accounting for approximately one-third of the total number of medication incidents. Approximately 10% of HIT/EMRS-related incidents resulted in patient harm, with more than 94% of these deemed as preventable; further, sentinel events were wholly preventable. Conclusion: This study provides basic data for improving EMR use/safety standards based on real-world patient safety incidents. Such improvements entail the establishment of long-term plans, research, and incident analysis, thus ensuring a safe healthcare environment for patients and healthcare providers.

• The Journal of the Korea institute of electronic communication sciences
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• v.17 no.3
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• pp.515-520
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• 2022

In context awareness using multiple sensors, when using sensor data detected and sent by each sensor, it is necessary to give different weights for each sensor. Even if the same type of sensor is configured for the same situation, sometimes it is necessary to assign different weights due to other secondary factors. It is inevitable to assign weights to events in the real world, and it can be said that a weighting method that can be used in a context awareness system using multiple sensors is necessary. In this study, we propose a weighting method for each sensor that reports to the host while the sensors continue to detect over time. In most IoT environments, the sensor continues the detection activity, and when the detected value shows a change pattern beyond a predetermined range, it is basically reported to the host. This can be called a kind of data stream environment. A weighting method was proposed for sensing data from multiple sensors in a data stream environment, and the new weighting method was to select and assign weights to data that indicates a context change in the stream.

• Journal of Cadastre & Land InformatiX
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• v.51 no.2
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• pp.21-34
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• 2021

Considering the role of roads in cities and the purpose of the Road Name Address Act, it is natural that the road name of the address is registered as the nearest road section adjacent to the building. Therefore, the Enforcement Decree of the Road Name Address Act also stipulates that mayor assign building numbers based on the basic numbers of road sections adjacent to the main entrances of buildings. However, there were cases where addresses are given from distant roads rather than adjacent roads among the actual road name addresses. Most of them are caused by misinterpretation of the case where the entrance faces more than one road. In this study, institutional and systematic improvement plans were proposed with the aim of enabling accurate selection of address information reference objects by demonstrating the limitations of the current building numbering method and presenting institutional improvement plans. Road name addresses were implemented for the core purpose of improving the inconvenience of locating the lot number address. Although some still complained of the inconvenience of road name addresses, successful settlement was possible because of the intuitive principle that most countries around the world could use it and find buildings along the road. Therefore, the system and system improvement should be made quickly in terms of accurate address information quality management and revitalization of related industries.

• The Journal of the Korea Contents Association
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• v.22 no.4
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• pp.222-230
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• 2022

Recently, Korea's cultural content industry is developing, and behind the growing recognition around the world is the real-time sharing service of global network users due to the development of science and technology. In particular, in the case of YouTube, its propagation power is fast and powerful in that everyone, not limited users, can become potential video providers. As more than 80% of mobile phone users are using YouTube in Korea, YouTube's information means that psychological factors of users are reflected. For example, information such as the number of video views, likes, and comments of a channel with a specific personality shows a measure of the channel's personality interest. This is highly related to the fact that information such as the frequency of keyword search on portal sites is closely related to the stock market economically and psychologically. Therefore, in this study, YouTube information from a representative entertainment company is collected through a crawling algorithm and analyzed for the causal relationship with major variables related to stock prices. This study is considered meaningful in that it conducted research by combining cultural content, IT, and financial fields in accordance with the era of the fourth industry.

• Journal of Korea Society of Industrial Information Systems
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• v.27 no.3
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• pp.29-46
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• 2022

COVID-19 has radically changed the behavior of members of society for exchange. In particular, the strong contagiousness of the virus is increasing networking on online platforms while reducing people's networking in the real world. Recently, the metaverse, which strengthened the presence based on 3D technology, is attracting attention from members of society such as individuals and companies. We present a method to improve metaverse utilization from the perspective of organizations and employees who have introduced metaverse for work. In other words, we check the effect of metaverse social function and telepresence on the employee's intention to offer support by improving the trust of the metaverse participants. We obtained samples through questionnaires targeting employees of organizations that introduced metaverse to their work, and verified the research hypothesis by applying the structural equation model. As a result, social interactivity, reciprocal favor, and telepresence of metaverse partially affected metaverse trust (platform, peer, organization), and metaverse trust increased the intention to offer support. Our study suggests a strategic direction to improve the metaverse utilization and exchange level of employees of organizations who want to use the metaverse for business.

• Tuberculosis and Respiratory Diseases
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• v.85 no.2
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• pp.155-164
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• 2022

Background: The remarkable efficacy of osimertinib in non-small cell lung cancer (NSCLC) with acquired T790M mutation has been widely documented in clinical trials and real-world practice. However, some patients show primary resistance to this drug. Even patients who initially show a favorable response have inconsistent clinical outcomes later. Therefore, the aim of this study was to identify additional clinical predictive factors for osimertinib efficacy. Methods: A prospective cohort of patients with acquired T790M positive stage IV lung adenocarcinoma treated with osimertinib salvage therapy in Hallym University Medical Center were analyzed. Results: Sixty-one eligible patients were analyzed, including 38 (62%) women and 39 (64%) who never smoked. Their mean age was 63.3 years. The median follow-up after treatment with epidermal growth factor receptor (EGFR) tyrosine kinase inhibitors (TKIs) was 36.0 months (interquartile range, 24.7-50.2 months). The majority (n=45, 74%) of patients were deceased. Based on univariate analysis, low baseline neutrophil-to-lymphocyte ratios (NLR), age ≥50 years, never-smoking history, stage IVA at osimertinib initiation, and prolonged response to previous TKIs (≥10 months) were associated with a significantly longer progression-free survival (PFS). Multivariate analysis showed that never-smoking status (hazard ratio [HR], 0.54; 95% confidence interval [CI], 0.30-0.98; p=0.041) and a baseline NLR less than or equal to 3.5 (HR, 0.23; 95% CI, 0.12-0.45; p<0.001) were independently associated with a prolonged PFS with osimertinib. Conclusion: Smoking history and high NLR were independent negative predictors of osimertinib PFS in patients with advanced NSCLC developing EGFR T790M resistance after the initial EGFR-TKI treatment.

• International Journal of Computer Science & Network Security
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• v.22 no.7
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• pp.213-219
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• 2022

Building Ukraine as an independent, sovereign state requires the education of a citizen-patriot, able to live and work in a democracy, ensure the unity of Ukraine, feel constant responsibility for themselves, their people, country, seek to make a real contribution to the reform process. Modern modernization of the education system requires the search for new information and communication technologies that can ensure the formation of a citizen with an active civic position, which involves not only students mastering the rights and responsibilities of citizens, convincing them of the feasibility of democratic transformation of society, patriotic qualities and feelings, but also the identification of motivated civic actions. The pandemic and hostilities have led to significant changes in the field of education around the world, they have caused educational problems in Ukraine. At the beginning of the quarantine in the spring of 2020, all educational institutions in the emergency mode switched to distance learning. Intensive use of information and communication technologies in the life of modern society has led to a rethinking of the content of education and training of future professionals: the main role is played not so much by the information itself as the ability to work with it, critically comprehend and produce new knowledge; the main thing is not the amount of information, but its quality; information is needed for further practical application and transformation into knowledge, and the ability to work with information becomes one of the important competencies of the modern specialist in the new transformation of society: from information to the knowledge society. In this context, one of the main forms of training is distance learning, which is able to respond to the challenges of society. The main methodological positions that are taken into account in the construction of the structure and dynamics of the formation of civic responsibility of the individual during the use of information and communication technologies are highlighted. The structure of civil responsibility as a holistic system of information and communication technologies is outlined, which includes three subsystems that characterize the natural, social and systemic qualities of citizenship, interconnected hierarchically and synergistically.The constituent elements of the structural part of the model of civic culture of the individual are analyzed.

• Korean Journal of Remote Sensing
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• v.38 no.6_1
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• pp.1515-1526
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• 2022

Image-based 3D reconstruction is to restore the shape and color of real-world objects, and image sensors mounted on mobile platforms are used for positioning and mapping purposes in indoor and outdoor environments. Due to the increase in accidents in underground space, the location accuracy problem of underground spatial information has been raised. Image-based location estimation studies have been conducted with the advantage of being able to determine the 3D location and simultaneously identify internal damage from image data acquired from the inside of pipeline-type underground facilities. In this study, we studied 3D reconstruction based on the images acquired inside the pipe-type underground facility and reference data. An unmanned mobile system equipped with a stereo camera was used to acquire data and image data within a pipe-type underground facility where reference data were placed at the entrance and exit. Using the acquired image and reference data, the pipe-type underground facility is reconstructed to a geo-referenced 3D shape. The accuracy of the 3D reconstruction result was verified by location and length. It was confirmed that the location was determined with an accuracy of 20 to 60 cm and the length was estimated with an accuracy of about 20 cm. Using the image-based 3D reconstruction method, the position and line-shape of the pipe-type underground facility will be effectively updated.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.40 no.2
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• pp.91-108
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• 2022

In most cases, optical images have been used as training data of DL (Deep Learning) models for object detection, recognition, identification, classification, semantic segmentation, and instance segmentation. However, properties of 3D objects in the real-world could not be fully explored with 2D images. One of the major sources of the 3D geospatial information is DSM (Digital Surface Model). In this matter, characteristic information derived from DSM would be effective to analyze 3D terrain features. Especially, man-made objects such as buildings having geometrically unique shape could be described by geometric elements that are obtained from 3D geospatial data. The background and motivation of this paper were drawn from concept of the intrinsic image that is involved in high-level visual information processing. This paper aims to extract buildings after classifying terrain features by training DL model with DSM-derived information including slope, aspect, and SRI (Shaded Relief Image). The experiments were carried out using DSM and label dataset provided by ISPRS (International Society for Photogrammetry and Remote Sensing) for CNN-based SegNet model. In particular, experiments focus on combining multi-source information to improve training performance and synergistic effect of the DL model. The results demonstrate that buildings were effectively classified and extracted by the proposed approach.

• 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.