• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.24 no.2
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• pp.15-21
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• 2024

The purpose of this study is to propose a framework for the introduction and evaluation of artificial intelligence (AI) services not only in general applications but also in public policies. To achieve this, the study explores AI service management and governance toolkits, providing insights into how to introduce AI services in public policies. Firstly, it offers guidelines on the direction of AI service development and what aspects to avoid. Secondly, in the development phase, it recommends using the AI governance toolkit to review content through checklists at each stage of design, development, and deployment. Thirdly, when operating AI services, it emphasizes the importance of adhering to principles related to 1) planning and design, 2) the lifecycle, 3) model construction and validation, 4) deployment and monitoring, and 5) accountability. The governance perspective of AI services is crucial for mitigating risks associated with service provision, and research in risk management aspects should be conducted. While embracing the advantages of AI, proactive measures should be taken to address limitations and risks. Efforts should be made to efficiently formulate policies using AI technology to create high value and provide meaningful societal impacts.

• Journal of Korean Neurosurgical Society
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• v.67 no.3
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• pp.345-353
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• 2024

Objective : Blood-blister aneurysms (BBAs) of the internal carotid artery (ICA) are challenging lesions with high morbidity and mortality rates. Although research on BBAs is well documented in different populations, the study of BBAs in the Tibetan population is extremely rare. This study aimed to evaluate the characteristics of BBAs and analyze the treatment modalities and long-term outcomes in the Tibetan population in comparison with the Han population. Methods : The characteristics of patients with BBAs of the ICA from January 2009 to January 2021 at our institution were reviewed. The features of aneurysms, treatment modalities, complications, and follow-up outcomes were retrospectively analyzed. Results : A total of 130 patients (41 Tibetan and 89 Han patients) with BBAs of the ICA who underwent treatment were enrolled. Compared with the Han group, the Tibetan group significantly demonstrated a high ratio of BBAs among ICAs (8.6%, 41/477 vs. 1.6%, 89/5563; p<0.05), a high ratio of vasospasm (34.1%, 14/41 vs. 6.7%, 6/89; p=0.001), a high risk of ischemic events (43.9%, 18/41 vs. 22.5%, 20/89; p<0.05), and a low ratio of good outcomes (modified Rankin scale, 0-2) at the 1-year follow-up (51.2%, 21/41 vs. 74.2%, 66/89; p<0.05). The multivariate regression model showed that ischemic events significantly contributed to the prediction of outcomes at 1 year. Further analysis revealed that microsurgery and vasospasm were associated with ischemic events. Conclusion : In comparison with Han patients, the Tibetan population had a high ratio of BBA occurrence, a high incidence of ischemic events, and a high ratio of poor outcomes. The endovascular approach showed more benefits in BBA patients.

• The Journal of the Convergence on Culture Technology
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• v.10 no.1
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• pp.403-409
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• 2024

In this paper, the guidelines for the design of an Artificial Intelligence(AI) based Integrated Process Safety Management(PSM) system to enhance workplace safety using data from process safety reports submitted by hazardous and risky facility operators in accordance with the Occupational Safety and Health Act is proposed. The system composed of the proposed guidelines is to be implemented separately by individual facility operators and specialized process safety management agencies for single or multiple workplaces. It is structured with key components and stages, including data collection and preprocessing, expansion and segmentation, labeling, and the construction of training datasets. It enables the collection of process operation data and change approval data from various processes, allowing potential fault prediction and maintenance planning through the analysis of all data generated in workplace operations, thereby supporting decision-making during process operation. Moreover, it offers utility and effectiveness in time and cost savings, detection and prediction of various risk factors, including human errors, and continuous model improvement through the use of accurate and reliable training data and specialized datasets. Through this approach, it becomes possible to enhance workplace safety and prevent accidents.

• Journal of Radiation Industry
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• v.17 no.1
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• pp.33-44
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• 2023

The deep geological repository of high-level radioactive waste shall be designed to meet the safety objective set in the form of radiation dose or corresponding risk to protect human and the environment from radiation exposure. Engineering feasibility and conformity with the safety objective of the facility conceptual design can be demonstrated by comparing the assessment result using the computational model for scenario(s) describing the radionuclide release and transport from repository to biosphere system. In this study, as the preliminary study for developing the high-level radioactive waste disposal facility in Korea, we reviewed and analyzed the entire list of FEPs and how to handle each FEP from a general point of view, which are selected for the geosphere region in the radiological safety assessment performed for the license application of the KBS-3 type deep geological repository in Finland and Sweden. In Finland, five FEPs (i.e., stress redistribution, creep, stress redistribution, erosion and sedimentation in fractures, methane hydrate formation, and salt exclusion) were excluded or ignored in the radionuclide release and transport assessment. And, in Sweden, six FEPs (i.e., creep, surface weathering and erosion, erosion/sedimentation in fractures, methane hydrate formation, radiation effects (rock and grout), and earth current) were not considered for all time frames and earthquake out of a total of 25 FEPs for the geosphere. Based on these results, an FEP list (draft) for the geosphere was derived, and the relative importance of each item was evaluated for conducting the radiological safety assessment of the domestic deep geological disposal facility. Since most of information on the disposal facility in Korea has not been determined as of now, it is judged that all FEP items presented in Table 3 should be considered for the radiological safety assessment, and the relative importance derived from this study can be used in determining whether to apply each item in the future.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.37 no.4
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• pp.251-258
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• 2024

This study investigated the effect of bearing aging on the seismic response of a three-span continuous concrete girder bridge with pot bearings installed. The pot bearings were modeled as elastic springs in the longitudinal, transverse, and vertical directions of the bridge to reflect the stiffness of fixed and movable supports. The effect of bearing aging on the seismic response of the bridge was examined by considering two factors: a decrease in the horizontal stiffness of the fixed bearings and an increase in the horizontal stiffness of the movable bearings. The finite element model of the three-span continuous girder bridge was validated by comparing its numerical natural frequencies with the designed natural frequencies. Using artificial ground motions that conform to the design response spectrum specified by the KDS bridge seismic design code, the seismic responses of the bridge's girders and bearings were calculated, considering the bearing stiffness variation due to aging. The results of a numerical analysis revealed that a decrease in the horizontal stiffness of the fixed bearings led to an increase in the absolute maximum relative displacement of the bearings during an earthquake. This increases the risk of the mortar block that supports the bearing cracking and the anchor bolt breaking. However, an increase in the horizontal stiffness of the movable bearings due to aging decreased the absolute maximum shear on the fixed bearings. Despite the shear reduction in the fixed bearings, the aging of the pot bearings change could cause additional tensile bending stress in the girder section above the free bearings, which could lead to unexpected structural damage to the continuous bridge during an earthquake.

• Biomolecules & Therapeutics
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• v.32 no.5
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• pp.647-657
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• 2024

Gefitinib is the well-tolerated first-line treatment of non-small cell lung cancer. As it needs analgesics during oncology treatment, particularly in the context of the coronavirus disease, where patients are more susceptible to contract high fever and sore throat. This has increased the likelihood of taking both gefitinib and antipyretic analgesic acetaminophen (APAP). Given that gefitinib and APAP overdose can predispose patients to liver injury or even acute liver failure, there is a risk of severe hepatotoxicity when these two drugs are used concomitantly. However, little is known regarding their safety at therapeutic doses. This study simulated the administration of gefitinib and APAP at clinically relevant doses in an animal model and confirmed that gefitinib in combination with APAP exhibited additional hepatotoxicity. We found that gefitinib plus APAP significantly exacerbated cell death, whereas each drug by itself had little or minor effect on hepatocyte survival. Mechanistically, combination of gefitinib and APAP induces hepatocyte death via the apoptotic pathway obviously. Reactive oxygen species (ROS) generation and DNA damage accumulation are involved in hepatocyte apoptosis. Gefitinib plus APAP also promotes the expression of Kelch-like ECH-associated protein 1 (Keap1) and downregulated the antioxidant factor, Nuclear factor erythroid 2-related factor 2 (Nrf2), by inhibiting p62 expression. Taken together, this study revealed the potential ROS-mediated apoptosis-dependent hepatotoxicity effect of the combination of gefitinib and APAP, in which the p62/Keap1/Nrf2 signaling pathway participates and plays an important regulatory role.

• Journal of Preventive Medicine and Public Health
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• v.32 no.3
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• pp.361-373
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• 1999

Objectives: Receive Operating Characteristic(ROC) curve with the area under the ROC curve(AUC) is one of the most popular indicator to evaluate the criterion validity of the measurement tool. This study was conducted to develop a standardized questionnaire to discriminate workers at high-risk of work-related musculoskeletal disorders using ROC analysis. Methods: The diagnostic results determined by rehabilitation medicine specialists in 370 persons(89 shipyard CAD workers, 113 telephone directory assistant operators, 79 women with occupation, and 89 housewives) were compared with participant's own replies to 'the questionnair on the worker's subjective physical symptoms'(Kwon, 1996). The AUC's from four models with different methods in item selection and weighting were compared with each other. These 4 models were applied to 225 persons, working in an assembly line of motor vehicle, for the purpose of AUC reliability test. Results: In a weighted model with 11 items, the AUC was 0.8155 in the primary study population, and 0.8026 in the secondary study population(p=0.3780). It was superior in the aspects of discriminability, reliability and convenience. A new questionnaire of musculoskeletal disorder could be constructed by this model. Conclusion: A more valid questionnaire with a small number of items and the quantitative weight scores useful for the relative comparisons are the main results of this study. While the absolute reference value applicable to the wide range of populations was not estimated, the basic intent of this study, developing a surveillance fool through quantitative validation of the measures, would serve for the systematic disease prevention activities.

• Asia pacific journal of information systems
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• v.22 no.2
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• pp.21-38
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• 2012

Until recently, successful implementation of ERP systems has been a popular topic among ERP researchers, who have attempted to identify its various contributing factors. None of these efforts, however, explicitly recognize the need to identify disparities that can exist between organizational information requirements and ERP systems. Since ERP systems are in fact "packages" -that is, software programs developed by independent software vendors for sale to organizations that use them-they are designed to meet the general needs of numerous organizations, rather than the unique needs of a particular organization, as is the case with custom-developed software. By adopting standard packages, organizations can substantially reduce many of the potential implementation risks commonly associated with custom-developed software. However, it is also true that the nature of the package itself could be a risk factor as the features and functions of the ERP systems may not completely comply with a particular organization's informational requirements. In this study, based on the organizational memory mismatch perspective that was derived from organizational memory theory and cognitive dissonance theory, we define the nature of disparities, which we call "mismatches," and propose that the mismatch between organizational information requirements and ERP systems is one of the primary determinants in the successful implementation of ERP systems. Furthermore, we suggest that customization efforts as a coping strategy for mismatches can play a significant role in increasing the possibilities of success. In order to examine the contention we propose in this study, we employed a survey-based field study of ERP project team members, resulting in a total of 77 responses. The results of this study show that, as anticipated from the organizational memory mismatch perspective, the mismatch between organizational information requirements and ERP systems makes a significantly negative impact on the implementation success of ERP systems. This finding confirms our hypothesis that the more mismatch there is, the more difficult successful ERP implementation is, and thus requires more attention to be drawn to mismatch as a major failure source in ERP implementation. This study also found that as a coping strategy on mismatch, the effects of customization are significant. In other words, utilizing the appropriate customization method could lead to the implementation success of ERP systems. This is somewhat interesting because it runs counter to the argument of some literature and ERP vendors that minimized customization (or even the lack thereof) is required for successful ERP implementation. In many ERP projects, there is a tendency among ERP developers to adopt default ERP functions without any customization, adhering to the slogan of "the introduction of best practices." However, this study asserts that we cannot expect successful implementation if we don't attempt to customize ERP systems when mismatches exist. For a more detailed analysis, we identified three types of mismatches-Non-ERP, Non-Procedure, and Hybrid. Among these, only Non-ERP mismatches (a situation in which ERP systems cannot support the existing information needs that are currently fulfilled) were found to have a direct influence on the implementation of ERP systems. Neither Non-Procedure nor Hybrid mismatches were found to have significant impact in the ERP context. These findings provide meaningful insights since they could serve as the basis for discussing how the ERP implementation process should be defined and what activities should be included in the implementation process. They show that ERP developers may not want to include organizational (or business processes) changes in the implementation process, suggesting that doing so could lead to failed implementation. And in fact, this suggestion eventually turned out to be true when we found that the application of process customization led to higher possibilities of failure. From these discussions, we are convinced that Non-ERP is the only type of mismatch we need to focus on during the implementation process, implying that organizational changes must be made before, rather than during, the implementation process. Finally, this study found that among the various customization approaches, bolt-on development methods in particular seemed to have significantly positive effects. Interestingly again, this finding is not in the same line of thought as that of the vendors in the ERP industry. The vendors' recommendations are to apply as many best practices as possible, thereby resulting in the minimization of customization and utilization of bolt-on development methods. They particularly advise against changing the source code and rather recommend employing, when necessary, the method of programming additional software code using the computer language of the vendor. As previously stated, however, our study found active customization, especially bolt-on development methods, to have positive effects on ERP, and found source code changes in particular to have the most significant effects. Moreover, our study found programming additional software to be ineffective, suggesting there is much difference between ERP developers and vendors in viewpoints and strategies toward ERP customization. In summary, mismatches are inherent in the ERP implementation context and play an important role in determining its success. Considering the significance of mismatches, this study proposes a new model for successful ERP implementation, developed from the organizational memory mismatch perspective, and provides many insights by empirically confirming the model's usefulness.

• Korean Journal of Psychosomatic Medicine
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• v.12 no.1
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• pp.15-22
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• 2004

Objectives: Delirium after head trauma results in various cognitive and behavioral dysfunction. This study aimed at developing and validating a predicitive model for clinical improvement after delirium based on precipitating factors during hospitalization Method: Data were collected on 45 patients who developed delirium after head trauma using 5 year retrospective design, based on reviews of medical charts including psychiatric consultation reports. The differences of the group who sustained residual symptoms of delirium(The RS group) and the group of full recovery(The FR group) at 4 week follow-up visits were compared by motoric type of delirium, socio-demographic variables, neuroimaging variables and clinical variables of interest. Result: There was significant difference in reason for initial consultation between two groups, in terms of hyperactivity(p<.01). The presence of compensation claim, subcortical gray matter lesion was significantly associated with the RS group(p<.05). Total length of intensive care unit(ICU) admission and of hospital stay were significantly longer in RS group than FR group(p<.01). Conclusion: This study shows that hyperactivity on initial consultation, compensation claims, specific brain lesion were altogether significant factors in explaining prolonged duration of delirium after head trauma. A simple predictive model based on the presence of precipitating factors might be used to identify delirious patients at high risk for prolonged cognitive dysfunction. Early psychiatric intervention would be required for evaluating efficacious management and shortening admission period.

• Journal of Intelligence and Information Systems
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• v.17 no.4
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• pp.241-254
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• 2011

Financial time-series forecasting is one of the most important issues because it is essential for the risk management of financial institutions. Therefore, researchers have tried to forecast financial time-series using various data mining techniques such as regression, artificial neural networks, decision trees, k-nearest neighbor etc. Recently, support vector machines (SVMs) are popularly applied to this research area because they have advantages that they don't require huge training data and have low possibility of overfitting. However, a user must determine several design factors by heuristics in order to use SVM. For example, the selection of appropriate kernel function and its parameters and proper feature subset selection are major design factors of SVM. Other than these factors, the proper selection of instance subset may also improve the forecasting performance of SVM by eliminating irrelevant and distorting training instances. Nonetheless, there have been few studies that have applied instance selection to SVM, especially in the domain of stock market prediction. Instance selection tries to choose proper instance subsets from original training data. It may be considered as a method of knowledge refinement and it maintains the instance-base. This study proposes the novel instance selection algorithm for SVMs. The proposed technique in this study uses genetic algorithm (GA) to optimize instance selection process with parameter optimization simultaneously. We call the model as ISVM (SVM with Instance selection) in this study. Experiments on stock market data are implemented using ISVM. In this study, the GA searches for optimal or near-optimal values of kernel parameters and relevant instances for SVMs. This study needs two sets of parameters in chromosomes in GA setting : The codes for kernel parameters and for instance selection. For the controlling parameters of the GA search, the population size is set at 50 organisms and the value of the crossover rate is set at 0.7 while the mutation rate is 0.1. As the stopping condition, 50 generations are permitted. The application data used in this study consists of technical indicators and the direction of change in the daily Korea stock price index (KOSPI). The total number of samples is 2218 trading days. We separate the whole data into three subsets as training, test, hold-out data set. The number of data in each subset is 1056, 581, 581 respectively. This study compares ISVM to several comparative models including logistic regression (logit), backpropagation neural networks (ANN), nearest neighbor (1-NN), conventional SVM (SVM) and SVM with the optimized parameters (PSVM). In especial, PSVM uses optimized kernel parameters by the genetic algorithm. The experimental results show that ISVM outperforms 1-NN by 15.32%, ANN by 6.89%, Logit and SVM by 5.34%, and PSVM by 4.82% for the holdout data. For ISVM, only 556 data from 1056 original training data are used to produce the result. In addition, the two-sample test for proportions is used to examine whether ISVM significantly outperforms other comparative models. The results indicate that ISVM outperforms ANN and 1-NN at the 1% statistical significance level. In addition, ISVM performs better than Logit, SVM and PSVM at the 5% statistical significance level.