• Korean Journal of Construction Engineering and Management
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• v.25 no.3
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• pp.27-36
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• 2024

The effective control of cost overrun is a crucial issue for construction companies to secure profitability. Especially in situations where cost pressures are significant due to factors such as rising raw material prices and increased financial costs due to high-interest rate policies, cost overruns resulting from project failures have a highly detrimental impact on the profitability of construction firms. The objective of this study is to analyze the current status of cost overrun control measures adopted by construction companies using the IPA technique and provide key characteristics and implications. The IPA analysis results showed that practitioners in general contractors exhibit a high level of interest and effort regarding cost overrun while the performance level is relatively low. Nevertheless, the measures considered important to control cost overruns generally show a high tendency for execution as well. Cost overrun control measures that show high importance but low execution are primarily related to collaboration and communication sectors. To effectively control cost overruns, enhancing collaboration and communication with construction supervisors/CM, headquarters, and regulatory authorities emerged as the most urgent need. Through this study, the current status and areas for improvement regarding cost overrun control measures in general contractors can be identified. This can be valuable for deriving directions and enhancements for future cost overrun control strategy development.

• Journal of Korean Library and Information Science Society
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• v.54 no.4
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• pp.415-436
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• 2023

In this study, we aimed to examine the level of implementation of the second comprehensive plan for promoting academic libraries (2019-2023) by analyzing key statistics of academic libraries and gathering perceptions from library staff. We analyzed the changes in major statistical indicators of libraries over the past five years. Additionally, we surveyed library staff to understand their overall perceptions of the plan and their attitudes towards the 17 sub-tasks outlined in it. The analysis of 369 survey responses revealed several key findings. Firstly, most respondents comprehended the plan well and frequently utilized it for developing their libraries' development and implementation plans. Secondly, the IPA results indicated that regardless of the type of university, there should be a continuous focus on facility improvement, teaching-learning support, and expanding access to academic resources. Efforts to develop library policies and strengthen human and financial resources were identified as crucial. Thirdly, four-year universities particularly emphasized the importance of expanding access to international academic resources compared to junior colleges. Conversely, junior colleges perceived foundational skill-building programs and inclusive services as more significant than four-year universities. The application of the IPA diagonal model revealed that the performance levels of all sub-tasks were lower than their perceived importance levels, suggesting the need for strategies to enhance effectiveness in future comprehensive plan formulation.

• Korean Journal of Radiology
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• v.23 no.3
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• pp.343-354
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• 2022

Objective: To develop and evaluate a deep learning-based artificial intelligence (AI) model for detecting skull fractures on plain radiographs in children. Materials and Methods: This retrospective multi-center study consisted of a development dataset acquired from two hospitals (n = 149 and 264) and an external test set (n = 95) from a third hospital. Datasets included children with head trauma who underwent both skull radiography and cranial computed tomography (CT). The development dataset was split into training, tuning, and internal test sets in a ratio of 7:1:2. The reference standard for skull fracture was cranial CT. Two radiology residents, a pediatric radiologist, and two emergency physicians participated in a two-session observer study on an external test set with and without AI assistance. We obtained the area under the receiver operating characteristic curve (AUROC), sensitivity, and specificity along with their 95% confidence intervals (CIs). Results: The AI model showed an AUROC of 0.922 (95% CI, 0.842-0.969) in the internal test set and 0.870 (95% CI, 0.785-0.930) in the external test set. The model had a sensitivity of 81.1% (95% CI, 64.8%-92.0%) and specificity of 91.3% (95% CI, 79.2%-97.6%) for the internal test set and 78.9% (95% CI, 54.4%-93.9%) and 88.2% (95% CI, 78.7%-94.4%), respectively, for the external test set. With the model's assistance, significant AUROC improvement was observed in radiology residents (pooled results) and emergency physicians (pooled results) with the difference from reading without AI assistance of 0.094 (95% CI, 0.020-0.168; p = 0.012) and 0.069 (95% CI, 0.002-0.136; p = 0.043), respectively, but not in the pediatric radiologist with the difference of 0.008 (95% CI, -0.074-0.090; p = 0.850). Conclusion: A deep learning-based AI model improved the performance of inexperienced radiologists and emergency physicians in diagnosing pediatric skull fractures on plain radiographs.

• Information Systems Review
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• v.19 no.3
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• pp.23-45
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• 2017

The ROK military is making a great effort and investment in establishing network-centric warfare, a future battlefield concept, as a major step in the establishment of a basic plan for military innovation. In the military organization level, an advanced process is introduced to shorten the command control time of the military and the business process is improved to shorten the decision time. In the information system dimension, an efficient resource management is achieved by establishing an automated command control system and a resource management information system by using the battle management information system. However, despite these efforts, we must evaluate the present level of informatization in an objective manner and assess the current progress toward the future goal of the military by using objective indicators. In promoting informatization, we must systematically identify the correct areas of improvement and identify policy directions to supplement in the future. Therefore, by analyzing preliminary research, workshops, and expert discussions on the major informatization level evaluation models at home and abroad, this study develops an evaluation model and several indicators that systematically reflect the characteristics of military organizations. The developed informatization level evaluation model is verified by conducting a feasibility test for the troops of the operation class or higher. We expect that this model will be able to objectively diagnose the level of informatization of the ROK military by putting budget and resources into the right place at the right time and to rapidly improve the vulnerability of the information sector.

• Journal of the International Relations & Interdisciplinary Education
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• v.4 no.1
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• pp.1-18
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• 2024

This study is a qualitative case study on the experience of an on-site, audience-participatory educational play conducted by four college students majoring in theater under the title 'Hooni and Choroki' for 7-year-old kindergarten students about to enter elementary school. The core theme of the play is to help relieve anxiety about school life before entering elementary school and to communicate smoothly with peers. To this end, college students participate in scenario planning, kindergarten recruitment, and 40-minute training at three kindergartens. He even conducted theatrical performances. As a result of the study, the key components of 'another growth in my life', 'improvement of happiness through meeting children', and 'new challenge toward dreams' were derived. The greatest significance of this study is that the audience-participatory educational theater experience allowed college students to practice sharing the results of their learning with someone else, and through this practice of sharing learning, they were able to realize their somewhat vague career paths and dreams. It was an opportunity that allowed me to experience 'improved confidence' and 'a resonance in my heart' so that I could set a direction. We hope that future educational theater with audience participation will be widely implemented in various aspects.

• The Journal of Korean Academy of Sensory Integration
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• v.21 no.3
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• pp.39-53
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• 2023

Objective : The purpose was the effect of sensory integration therapy combined with an eye tracker on the sensory processing and visual perception of children with developmental disabilities. Methods : It was a single-subject study with a multiple baseline design between subjects, and the intervention applied sensory integration therapy combined with an eye tracker. Visual-motor speed and saccadic eye movements were assessed at each session of baseline and intervention periods. As pre- and post-evaluation, sensory profile, Korean-Developmental Test of Visual Perception and Trail Making Test were conducted. The results of each session evaluation and pre- and post-evaluation researched the effectiveness of the intervention through visual analysis and trend line analysis. Results : As a result of the evaluation for each session, the slope of the trend line for all children in visual-motor speed and saccadic eye movement increased sharply during the intervention compared to the baseline. As a result of the pre- and post-evaluation, the sensory processing of movement, body position, and visual changed from more than that of peers to a level similar to that of peers. In visual perception, all children's ability of Visual Closure increased. As a result of Trail Making Test conducted to confirm the improvement of children's visual tracking and visual-motor abilities, all children showed a decrease in performance time after the test compared to before. Conclusion : It was confirmed that sensory integration therapy combined with an eye tracker for developmental disabilities has effect on sensory processing and visual perception. It is expected to play an important role clinically as it can stimulate children's interest and motivation in line with recent technological improvements and the spread of smart devices.

• Journal of the Korean Applied Science and Technology
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• v.40 no.6
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• pp.1498-1505
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• 2023

This study attempted to investigate the difference in service orientation according to the individual characteristics of hair salon workers, and to identify the internal marketing factors of hair salon that influence service orientation. Questionnaires for empirical research were collected from hair salon workers in Gyeongnam, and the results of analyzing the collected questionnaires through IBM SPSS Statistics 26 are as follows. First, as a result of analyzing the difference in service orientation according to the individual characteristics of hair salon workers, the '40s or older' group and the 'working period of 10 years or longer' group showed statistically higher service orientation than other groups. Second, as a result of analyzing the causal relationship between internal marketing and service orientation, it was found that welfare, compensation system, education and training of internal marketings had the statistical effect on service orientation, and in particular, the compensation system had the strongest effect on service orientation. Therefore, service orientation for customers should be improved through internal marketing activities that take into account the individual characteristics of hair salon workers. The improvement of service orientation means the customer's intention to reuse, suggesting that ultimately the management performance of hair salon companies can be further improved.

• Journal of Korea Water Resources Association
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• v.57 no.2
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• pp.127-137
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• 2024

Physical models, which are often used for water resource management, are difficult to build and operate with input data and may involve the subjective views of users. In recent years, research using data-driven models such as machine learning has been actively conducted to compensate for these problems in the field of water resources, and in this study, an artificial neural network was used to simulate long-term rainfall runoff in the Osipcheon watershed in Samcheok-si, Gangwon-do. For this purpose, three input data groups (meteorological observations, daily precipitation and potential evapotranspiration, and daily precipitation - potential evapotranspiration) were constructed from meteorological data, and the results of training the LSTM (Long Short-term Memory) artificial neural network model were compared and analyzed. As a result, the performance of LSTM-Model 1 using only meteorological observations was the highest, and six LSTM-MLP ensemble models with MLP artificial neural networks were built to simulate long-term runoff in the Fifty Thousand Watershed. The comparison between the LSTM and LSTM-MLP models showed that both models had generally similar results, but the MAE, MSE, and RMSE of LSTM-MLP were reduced compared to LSTM, especially in the low-flow part. As the results of LSTM-MLP show an improvement in the low-flow part, it is judged that in the future, in addition to the LSTM-MLP model, various ensemble models such as CNN can be used to build physical models and create sulfur curves in large basins that take a long time to run and unmeasured basins that lack input data.

• Journal of the Korean Association of Geographic Information Studies
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• v.27 no.1
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• pp.115-127
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• 2024

This research aimed to construct models with various structures based on the Transformer module and to perform land cover classification, thereby examining the applicability of the Transformer module. For the classification of land cover, the Unet model, which has a CNN structure, was selected as the base model, and a total of four deep learning models were constructed by combining both the encoder and decoder parts with the Transformer module. During the training process of the deep learning models, the training was repeated 10 times under the same conditions to evaluate the generalization performance. The evaluation of the classification accuracy of the deep learning models showed that the Model D, which utilized the Transformer module in both the encoder and decoder structures, achieved the highest overall accuracy with an average of approximately 89.4% and a Kappa coefficient average of about 73.2%. In terms of training time, models based on CNN were the most efficient. however, the use of Transformer-based models resulted in an average improvement of 0.5% in classification accuracy based on the Kappa coefficient. It is considered necessary to refine the model by considering various variables such as adjusting hyperparameters and image patch sizes during the integration process with CNN models. A common issue identified in all models during the land cover classification process was the difficulty in detecting small-scale objects. To improve this misclassification phenomenon, it is deemed necessary to explore the use of high-resolution input data and integrate multidimensional data that includes terrain and texture information.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.23 no.3
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• pp.48-66
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• 2024

According to the three amended Laws of the Data Economy and the Data Industry Act of Korea, systems for pseudonymous data integration and Data Safe Zones have been operated separately by selected agencies, eventually causing a burden of use in SMEs, startups, and general users because of complicated and ineffective procedures. An over-stringent pseudonymization policy to prevent data breaches has also compromised data quality. Such trials should be improved to ensure the convenience of use and data quality. This paper proposes a prototype system of the Integrated Data Safe Zone based on redesigned and optimized pseudonymization workflows. Conventional workflows of pseudonymization were redesigned by applying the amended guidelines and selectively revising existing guidelines for business process redesign. The proposed prototype has been shown quantitatively to outperform the conventional one: 6-fold increase in time efficiency, 1.28-fold in cost reduction, and 1.3-fold improvement in data quality.