• The Korean Society of Law and Medicine
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• v.24 no.4
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• pp.67-101
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• 2023

The utilization of generative AI in the medical field is also being rapidly researched. Access to vast data sets reduces the time and energy spent in selecting information. However, as the effort put into content creation decreases, there is a greater likelihood of associated issues arising. For example, with generative AI, users must discern the accuracy of results themselves, as these AIs learn from data within a set period and generate outcomes. While the answers may appear plausible, their sources are often unclear, making it challenging to determine their veracity. Additionally, the possibility of presenting results from a biased or distorted perspective cannot be discounted at present on ethical grounds. Despite these concerns, the field of generative AI is continually advancing, with an increasing number of users leveraging it in various sectors, including biomedical and life sciences. This raises important legal considerations regarding who bears responsibility and to what extent for any damages caused by these high-performance AI algorithms. A general overview of issues with generative AI includes those discussed above, but another perspective arises from its fundamental nature as a large-scale language model ('LLM') AI. There is a civil law concern regarding "the memorization of training data within artificial neural networks and its subsequent reproduction". Medical data, by nature, often reflects personal characteristics of patients, potentially leading to issues such as the regeneration of personal information. The extensive application of generative AI in scenarios beyond traditional AI brings forth the possibility of legal challenges that cannot be ignored. Upon examining the technical characteristics of generative AI and focusing on legal issues, especially concerning the protection of personal information, it's evident that current laws regarding personal information protection, particularly in the context of health and medical data utilization, are inadequate. These laws provide processes for anonymizing and de-identification, specific personal information but fall short when generative AI is applied as software in medical devices. To address the functionalities of generative AI in clinical software, a reevaluation and adjustment of existing laws for the protection of personal information are imperative.

• Information Systems Review
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• v.21 no.4
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• pp.143-156
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• 2019

Types of innovation can be categorized into simplification, information, automation, and intelligence. Intelligence is the highest level of innovation, and RPA can be seen as one of intelligence. Robotic Process Automation(RPA), a software robot with artificial intelligence, is an example of intelligence that is suited for simple, repetitive, large-scale transaction processing tasks. The RPA, which is already in operation in many companies in Korea, shows what needs to be done to naturally focus on the core tasks in a situation where the need for a strong organizational culture is increasing and the emphasis is on voluntary leadership, strong teamwork and execution, and a professional working culture. The introduction was considered naturally according to the need to find. Robotic Process Automation, or RPA, is a technology that replaces human tasks with the goal of quickly and efficiently handling structural tasks. RPA is implemented through software robots that mimic humans using software such as ERP systems or productivity tools. RPA robots are software installed on a computer and are called robots by the principle of operation. RPA is integrated throughout the IT system through the front end, unlike traditional software that communicates with other IT systems through the back end. In practice, this means that software robots use IT systems in the same way as humans, repeat the correct steps, and respond to events on the computer screen instead of communicating with the system's application programming interface(API). Designing software that mimics humans to communicate with other software can be less intuitive, but there are many advantages to this approach. First, you can integrate RPA with virtually any software you use, regardless of your openness to third-party applications. Many enterprise IT systems are proprietary because they do not have many common APIs, and their ability to communicate with other systems is severely limited, but RPA solves this problem. Second, RPA can be implemented in a very short time. Traditional software development methods, such as enterprise software integration, are relatively time consuming, but RPAs can be implemented in a relatively short period of two to four weeks. Third, automated processes through software robots can be easily modified by system users. While traditional approaches require advanced coding techniques to drastically modify how they work, RPA can be instructed by modifying relatively simple logical statements, or by modifying screen captures or graphical process charts of human-run processes. This makes RPA very versatile and flexible. This RPA is a good example of the application of digital to intelligence(D2I).

• Nuclear Engineering and Technology
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• v.56 no.4
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• pp.1526-1531
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• 2024

¹³¹I is a fission product produced in a nuclear reactor by irradiating tellurium dioxide, with a half-life of 8.02 day. The most important and widely used method for making ¹³¹I is irradiation using a nuclear reactor and post-irradiation followed by dry distillation. The advantage of the dry distillation process is that the process and the equipment are relatively simple, namely TeO₂ (m.p. 750 ℃), which can withstand heating during reactor irradiation. Based on TeO₂ irradiation by neutron following the technique of dry distillation was explained for production of ¹³¹I on a large scale. A dry distillation followed the radioisotope production operation using the 30 MW GA Siwabessy nuclear reactor to meet national demand. TeO₂ targets are 25 and 50 g irradiated for 87-100 h. The resulting ¹³¹I activity is 20.29339-368.50335GBq. According to the requirements imposed on the radionuclide purity of the preparation, the contribution of ¹³¹I training in the resulting preparation was not less than 99.9 %

• The Journal of Engineering Geology
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• v.34 no.2
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• pp.279-294
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• 2024

Large-scale civil engineering structures such as dams require a systematic approach to jointed rock-mass grouting to prevent water leakage into the foundations and to ensure safe operation. In South Korea, rock grouting design often relies on the experience of field engineers that was gained in similar projects, highlighting the need for a more systematic and reliable approach. Rock-mass grouting is affected mainly by hydrogeology and the presence of discontinuities, involving factors such as the rock quality designation (RQD), joint spacing (Js), Lugeon value (Lu), and secondary permeability index (SPI). This study, based on data from field investigations of 14 domestic sites, analyzed the correlation between hydrogeological factors (Lu and SPI), discontinuity characteristics (RQD and Js), and grout take, and systematically established a design method for rock grouting. Analysis of correlation between the variables RQD, Js, Lu, and SPI yielded Pearson correlation (r) values as follows: Lu-SPI, 0.92; RQD-Lu, -0.75; RQD-Js, 0.69; RQD-SPI, -0.65; Js-Lu, -0.47; and SPI-Js, -0.41. The grout take increases with Lu and SPI values, but there is no significant correlation between RQD and Js. The proposed approach for grouting design based on SPI values was verified through analysis and comparison with actual curtain-grouting construction, and is expected to be useful in practical applications and future studies.

• Journal of Korean Tunnelling and Underground Space Association
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• v.26 no.2
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• pp.129-152
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• 2024

In the application of deep learning object detection via CCTV in tunnels, a large number of false positive detections occur due to the poor environmental conditions of tunnels, such as low illumination and severe perspective effect. This problem directly impacts the reliability of the tunnel CCTV-based accident detection system reliant on object detection performance. Hence, it is necessary to reduce the number of false positive detections while also enhancing the number of true positive detections. Based on a deep learning object detection model, this paper proposes a false positive data training method that not only reduces false positives but also improves true positive detection performance through retraining of false positive data. This paper's false positive data training method is based on the following steps: initial training of a training dataset - inference of a validation dataset - correction of false positive data and dataset composition - addition to the training dataset and retraining. In this paper, experiments were conducted to verify the performance of this method. First, the optimal hyperparameters of the deep learning object detection model to be applied in this experiment were determined through previous experiments. Then, in this experiment, training image format was determined, and experiments were conducted sequentially to check the long-term performance improvement through retraining of repeated false detection datasets. As a result, in the first experiment, it was found that the inclusion of the background in the inferred image was more advantageous for object detection performance than the removal of the background excluding the object. In the second experiment, it was found that retraining by accumulating false positives from each level of retraining was more advantageous than retraining independently for each level of retraining in terms of continuous improvement of object detection performance. After retraining the false positive data with the method determined in the two experiments, the car object class showed excellent inference performance with an AP value of 0.95 or higher after the first retraining, and by the fifth retraining, the inference performance was improved by about 1.06 times compared to the initial inference. And the person object class continued to improve its inference performance as retraining progressed, and by the 18th retraining, it showed that it could self-improve its inference performance by more than 2.3 times compared to the initial inference.

• Korean Journal of Radiology
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• v.21 no.7
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• pp.880-890
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• 2020

Objective: Patients with chronic obstructive pulmonary disease (COPD) are known to be at risk of osteoporosis. The purpose of this study was to evaluate the association between thoracic vertebral bone density measured on chest CT (D_Thorax) and clinical variables, including survival, in patients with COPD. Materials and Methods: A total of 322 patients with COPD were selected from the Korean Obstructive Lung Disease (KOLD) cohort. D_Thorax was measured by averaging the CT values of three consecutive vertebral bodies at the level of the left main coronary artery with a round region of interest as large as possible within the anterior column of each vertebral body using an in-house software. Associations between D_Thorax and clinical variables, including survival, pulmonary function test (PFT) results, and CT densitometry, were evaluated. Results: The median follow-up time was 7.3 years (range: 0.1-12.4 years). Fifty-six patients (17.4%) died. D_Thorax differed significantly between the different Global Initiative for Chronic Obstructive Lung Disease stages. D_Thorax correlated positively with body mass index (BMI), some PFT results, and the six-minute walk distance, and correlated negatively with the emphysema index (EI) (all p < 0.05). In the univariate Cox analysis, older age (hazard ratio [HR], 3.617; 95% confidence interval [CI], 2.119-6.173, p < 0.001), lower BMI (HR, 3.589; 95% CI, 2.122-6.071, p < 0.001), lower forced expiratory volume in one second (FEV₁) (HR, 2.975; 95% CI, 1.682-5.262, p < 0.001), lower diffusing capacity of the lung for carbon monoxide corrected with hemoglobin (DL_CO) (HR, 4.595; 95% CI, 2.665-7.924, p < 0.001), higher EI (HR, 3.722; 95% CI, 2.192-6.319, p < 0.001), presence of vertebral fractures (HR, 2.062; 95% CI, 1.154-3.683, p = 0.015), and lower D_Thorax (HR, 2.773; 95% CI, 1.620-4.746, p < 0.001) were significantly associated with all-cause mortality and lung-related mortality. In the multivariate Cox analysis, lower D_Thorax (HR, 1.957; 95% CI, 1.075-3.563, p = 0.028) along with older age, lower BMI, lower FEV₁, and lower DL_CO were independent predictors of all-cause mortality. Conclusion: The thoracic vertebral bone density measured on chest CT demonstrated significant associations with the patients' mortality and clinical variables of disease severity in the COPD patients included in KOLD cohort.

• Journal of the Korean Society of Marine Environment & Safety
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• v.30 no.1
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• pp.127-134
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• 2024

With the growth of offshore wind power generation market, the corresponding installation vessel market is also growing. It is anticipated that approximately 100 installation vessels will be required in the of shore wind power generation market by 2030. With a price range of 300 to 400 billion Korean won per vessel, this represents a high-value market compared to merchant vessels. Particularly, the demand for large installation vessels with a capacity of 11 MW or more is increasing. The rapid growth of the offshore wind power generation market in the Asia-Pacific region, centered around China, has led to several discussions on orders for operational installation vessels in this region. The seabed geology in the Asia-Pacific region is dominated by clay layers with low bearing capacity. Owing to these characteristics, during vessel operations, significant spudcan and leg penetration depths occur as the installation vessel rises and descends above the water surface. In this study, using penetration variables ranging from 3 to 21 m, the unique vibration period, structural safety of the legs, and conductivity safety index were assessed based on penetration depths. As the penetration depth increases, the natural vibration period and the moment length of the leg become shorter, increasing the margin of structural strength. It is safe against overturning moment at all angles of incidence, and the maximum value occurs at 270 degrees. The conditions reviewed through this study can be used as crucial data to determine the operation of the legs according to the penetration depth when developing operating procedures for WTIV in soft soil. In conclusion, accurately determining the safety of the leg structure according to the penetration depth is directly related to the safety of the WTIV.

• Information Systems Review
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• v.25 no.2
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• pp.145-162
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• 2023

Asset management is a complex and difficult field that requires insight into numerous variables and even human psychology. Thus, it has traditionally been the domain of professionals, and these services have been expensive to obtain. Changes are taking place in these markets, and the driving force is the digital revolution, so-called the fourth industrial revolution. Among them, the Robo-Advisor service using artificial intelligence technology is the highlight. The reason is that it is possible to popularize investment advisory services with convenient accessibility and low cost. This study aims to clarify what factors are critically important when selecting robo-advisors for service users and providers in Korea, and what perception differences exist in the selection factors between user and provider groups. The framework of the study was based on the marketing mix 4C model, and the design and analysis of the model used Delphi survey and AHP. Through the study design, 4 main criteria and 15 sub-criteria were derived, and the findings of the study are as follows. First, the importance of the four main criteria was in the order of customer needs > customer convenience > customer cost > customer communication for both groups. Second, looking at the 15 sub-criteria, it was found that investment purpose coverage, investment propensity coverage, fee level and accessibility factors were the most important. Third, when comparing between groups, the user group found that the fee level and accessibility factors were the most important, and the provider group recognized the investment purpose coverage and investment propensity coverage factors as important. This study derived useful implications in practice. First, when designing for the spread of the robo-advisor service, the basis for constructing a user-oriented system was prepared by considering the priority of importance according to the weight difference between the four main criteria and the 15 sub-criteria. In addition, the difference in priority of each sub-criteria shown in the group comparison and the cause of the sub-criteria with large weight differences were identified. In addition, it was suggested that it is very important to form a consensus to resolve the difference in perception of factors between those in charge of strategy and marketing and system development within the provider group. Academically, it is meaningful in that it is an early study that presented various perspectives and perspectives by deriving a number of robo-advisor selection factors. Through the findings of this study, it is expected that a successful user-oriented robo-advisor system can be built and spread in Korea to help users.

• Korean Journal of Heritage: History & Science
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• v.57 no.1
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• pp.146-159
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• 2024

In this study, a study on the production technology of the Buddha statue and the production of raw material origin was conducted through scientific analysis on the Bronze seated Bodhisattva Statue of Goseongsa Temple, a treasure. As a result of microstructure analysis through a metal microscope, it was confirmed that the microstructure of the Bronze seated Bodhisattva Statue of Goseongsa Temple was a process-type dendritic structure, and the casting structure of bronze was well represented, so it was manufactured through casting. Subsequently, as a result of analyzing the alloy composition ratio through SEM-EDS, it was identified as a ternary alloy with 81.26 wt% of copper (Cu) and 16.42 wt% of tin (Sn) and 1.72 wt% of lead (Pb). The results of the analysis of lead isotope ratios using a thermal ionization mass spectrometer (TIMS) were substituted into the distribution of lead isotope ratios on the Korean Peninsula, it was shown in corresponding to Jeolla-do and Chungcheong-do regions and North and South Gyeongsang Province. This suggests that the raw materials used in their production were likely sourced from the mines around Goseong Temple in Gangjin. Despite the fact that the statue is a medium and large Buddha with a total height of 51 centimeters, 1.72 wt% of lead (Pb) was found as a result of alloy composition ratio analysis, which showed a similar composition to the lead content ratio of small bronze and gilt-bronze Buddha statues. Therefore, we compared and analyzed the results of the analysis of the composition ratio of the alloys of bronze and gilt bronze statues, which has been scientifically analyzed with a compositional age similar to that of the Bronze seated Bodhisattva Statue of Goseongsa Temple. Comparison results, Various factors, such as the size of the Buddha statue as well as its stylistic characteristics and the age of composition, may exist in determining the alloy composition ratio of the bronze and gilt bronze Buddha statues, and it was confirmed that the alloy composition ratio or casting technology was properly adjusted when the Buddha statue was created. In other words, it is judged that a more comprehensive system of Buddha statue production technology should be investigated by conducting archaeological and art history studies on stylistic characteristics and age of composition, as well as scientific analysis results such as observation of internal structure, microstructure observation, and analysis of alloy composition ratio using radiation transmission irradiation.

• Journal of the Korean Society of Radiology
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• v.84 no.1
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• pp.185-196
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• 2023

Purpose This study aimed to investigate radiomics analysis of ultrasonographic images to develop a potential biomarker for predicting lymph node metastasis in papillary thyroid carcinoma (PTC) patients. Materials and Methods This study included 431 PTC patients from August 2013 to May 2014 and classified them into the training and validation sets. A total of 730 radiomics features, including texture matrices of gray-level co-occurrence matrix and gray-level run-length matrix and single-level discrete two-dimensional wavelet transform and other functions, were obtained. The least absolute shrinkage and selection operator method was used for selecting the most predictive features in the training data set. Results Lymph node metastasis was associated with the radiomics score (p < 0.001). It was also associated with other clinical variables such as young age (p = 0.007) and large tumor size (p = 0.007). The area under the receiver operating characteristic curve was 0.687 (95% confidence interval: 0.616-0.759) for the training set and 0.650 (95% confidence interval: 0.575-0.726) for the validation set. Conclusion This study showed the potential of ultrasonography-based radiomics to predict cervical lymph node metastasis in patients with PTC; thus, ultrasonography-based radiomics can act as a biomarker for PTC.