• Proceedings of the Korea Water Resources Association Conference
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• 2023.05a
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• pp.182-182
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• 2023

Since China adopted Public Private Partnerships (PPPs) in the 1980s, China has relied on water PPPs to expand appropriate water facilities.. According to the World Bank data from 1994 to 2020, the top five provinces hosted over 40 percent of total PPPs, with four of them located in the Huadong area and one in the Henan area. A vast gap exists between the group attracting the most PPPs and the group hosting the least. This study explores Guangdong and Shandong provinces, which have led most PPPs in China. Coincidently, these areas are also famous for the typical areas to show the Chinese economic policy after the open-door policy. They have achieved economic development and rapid urbanization rates based on the large scale of Foreign Direct Investment inflow and export-oriented manufacturing industry, as well as their active participation in PPPs over the last thirty years. An economic approach can provide valuable insights into the development of water infrastructure. Adequate urban infrastructure has been shown to impact local economic development positively. Water infrastructure also provides a basic and sustainable environment for economic activities by satisfying more water usage, improving the efficiency of the water supply, and reducing water pollution caused by industrial activities. However, it remains only partially understood without inclusive research on the issues related to water resources in each province. For instance, existing studies have been limited to explaining slightly different patterns of water PPPs between Guangdong and Shandong at the beginning of the PPP era. This study aims to elucidate the development pattern of water PPPs in each province from multi-dimensional aspects. Therefore, the study will help understand why China boosted the development of the private water market.

• Journal of Fashion Business
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• v.27 no.4
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• pp.141-162
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• 2023

With the prospect that integrating creative AI in the fashion design field will become more visible, this study considered the case of creative fashion design development through Human-AI Co-creation (HAIC). Methodologically, this research encompasses a literature review and empirical investigations. In the literature review, the fashion design and creative HAIC processes, and the possibilities of integrating AI in fashion design were considered. In the empirical study, based on the case analysis of generating fashion design through HAIC, the HAIC type according to the role and interaction method, and characteristics of humans and AI was considered, and the HAIC process for fashion design was derived. The results of this study are summarized as follows. First, HAIC types in fashion design are divided into four types: AI-driven passive HAIC, human-driven passive HAIC, flexible interaction-based HAIC, and integrated interaction-based value creation HAIC. Second, the stages of the HAIC process for creative fashion design can be broadly divided into semantic data integration, visual ideation, design creation and expansion, design presentation, and design/manufacturing solution and UX platform creation. Third, in fashion design, HAIC contributes to human ability, enhancement of creativity, achievement of efficient workflow, and creation of new values. This research suggests that HAIC has the potential to revolutionize the fashion design industry by facilitating collaboration between humans and AI; consequently, enhancing creativity, and improving the efficiency of the design process. It also offers a framework for understanding the different types of HAIC and the stages involved in the creative fashion design process.

• Journal of Radiopharmaceuticals and Molecular Probes
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• v.7 no.2
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• pp.79-84
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• 2021

Radiopharmaceuticals are important for tumor diagnosis and therapy. To deliver a radiotracer at the desired target excluding non-targeted tissues is difficult The development of a targeted tracer that has a good clearance profile while maintaining high biostability and biocompatibility is key to optimizing its biodistribution and transport across biological barriers. Improving the hydrophilicity of radiotracers by PEGylation can reduce serum binding, allowing the tracer to circulate without retention and reducing its affinity for non-targeted tissues. In this study, we synthesized a new benzamido tracer (SnBz-PEG₃₆) with the introduction of a low molecular weight polyethylene glycol unit (PEG₃₆, ~2,100 Da). The tumor targeting efficiency and biodistribution of [¹³¹I]-Bz-PEG₃₆ or radiotracer-loaded liposomes were evaluated after their administration to normal mice or mouse tumor models including CT26 (xenograft) and 4T1 (xenograft and orthotopic). Most of the radiotracer was cleared out rapidly (1-24 h post-administration) through the kidney and there was little tumor uptake.

• Journal of Korean Society on Water Environment
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• v.39 no.4
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• pp.343-355
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• 2023

After the implementation of the total pollution load control system, the effect of improving river water quality by expanding investments in basic environmental facilities, inducing operational efficiency, and reducing the load of various pollutants was clear. However, since the implementation of the system, the management of non-point pollutants has been neglected; management focused on specific substances (biochemical oxygen demand (BOD) and total phosphorus (T-P)) and lacked specific cause analysis and action plans, failed to establish a relationship between water quality and pollution load, failed to reflect stakeholder demands for river water quality management, and failed to apply technical conditions. Therefore, to overcome the limitations raised and achieve a practical and efficient advanced total pollution system, the current system was partially improved and will continue to be improved. This study analyzed the performance and limitations of the total pollution system and introduced recent improvements and the contents that are being improved. The main contents included reducing emissions and reduction monitoring, using water quality tele-monitoring system (TMS) data and self-measurement data, adding population-inducing facilities, and adjusting regional development projects from 20 to 30 multi-family housing units, currentizing each pollutant source according to the roadmap. If the system is improved in a developmental direction and responds to various changes, it will be a more practical and effective policy.

• Journal of the Korea Society for Simulation
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• v.18 no.4
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• pp.149-155
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• 2009

Attacks in wireless sensor networks (WSN), are similar to the attacks in ad-hoc networks because there are deployed on a wireless environment. However existing security mechanism cannot apply to WSN, because it has limited resource and hostile environment. One of the typical attack in WSN is setting up wrong route that using wormhole. To overcome this threat, Ji-Hoon Yun et al. proposed WODEM (WOrmhole attack DEfense Mechanism) which can detect and counter with wormhole. In this scheme, it can detect and counter with wormhole attacks by comparing hop count and initial TTL (Time To Live) which is pre-defined. The selection of a initial TTL is important since it can provide a tradeoff between detection ability ratio and energy consumption. In this paper, we proposed a fuzzy rule-based system for TTL determination that can conserve energy, while it provides sufficient detection ratio in wormhole attack.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.8
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• pp.2016-2029
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• 2023

Accurate prediction of critical illness is significant for ensuring the lives and health of patients. The selection of indicators affects the real-time capability and accuracy of the prediction for critical illness. However, the diversity and complexity of these indicators make it difficult to find potential connections between them and critical illnesses. For the first time, this study proposes an indicator analysis model to extract key indicators from the preoperative and intraoperative clinical indicators and laboratory results of critical illnesses. In this study, preoperative and intraoperative data of heart failure and respiratory failure are used to verify the model. The proposed model processes the datum and extracts key indicators through four parts. To test the effectiveness of the proposed model, the key indicators are used to predict the two critical illnesses. The classifiers used in the prediction are light gradient boosting machine (LightGBM) and eXtreme Gradient Boosting (XGBoost). The predictive performance using key indicators is better than that using all indicators. In the prediction of heart failure, LightGBM and XGBoost have sensitivities of 0.889 and 0.892, and specificities of 0.939 and 0.937, respectively. For respiratory failure, LightGBM and XGBoost have sensitivities of 0.709 and 0.689, and specificity of 0.936 and 0.940, respectively. The proposed model can effectively analyze the correlation between indicators and postoperative critical illness. The analytical results make it possible to find the key indicators for postoperative critical illnesses. This model is meaningful to assist doctors in extracting key indicators in time and improving the reliability and efficiency of prediction.

• Journal of Advanced Navigation Technology
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• v.27 no.4
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• pp.481-487
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• 2023

Recently, interest in UAM (Urban Air Mobility) has surged as a critical solution to urban traffic congestion and air pollution issues. However, efficient UAM operation requires accurate 3D Point Cloud data processing, particularly in separating the ground and objects. This paper proposes and validates a method for effectively separating ground and objects in a UAM environment, taking into account its dynamic and complex characteristics. Our approach combines attitude information from MEMS sensors with ground plane estimation using RANSAC, allowing for ground/object separation that isless affected by GPS errors. Simulation results demonstrate that this method effectively operates in UAM settings, marking a significant step toward enhancing safety and efficiency in urban air mobility. Future research will focus on improving the accuracy of this algorithm, evaluating its performance in various UAM scenarios, and proceeding with actual drone tests.

• The Journal of the Convergence on Culture Technology
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• v.9 no.1
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• pp.191-197
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• 2023

The purpose of the study was to provide an educational environment for designing and producing virtual reality practice contents that can be used in semiconductor production lines and clean rooms. Through this process, the user can acquire practical knowledge through experiences close to reality, such as experiencing the main semiconductor solar cell manufacturing facilities as well as procedural knowledge before and after entering the clean room.. In particular, it provides users with an immersion experience close to reality by creating an environment for experiential content necessary for semiconductor and solar cell manufacturing processes and clean room entrance procedure experiential content, which is expected to improve education immersion, realism, cost, efficiency, and education satisfaction. Depending on the characteristics of Dangerous, Impossible, Counter-productive etc, immersive content makes learners immersed in the learning content, induces proactive/active learning, and embodies the learning content, resulting in positive results in the field of improving educational effectiveness.

• Journal of the Institute of Convergence Signal Processing
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• v.23 no.4
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• pp.249-255
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• 2022

Potholes are an important clue to the structural defects of asphalt pavement and cause many casualties and property damage. Therefore, accurate pothole detection is an important task in road surface maintenance. Many machine learning technologies are being introduced for pothole detection, and data preprocessing is required to increase the efficiency of deep learning models. In this paper, we propose a preprocessing method that emphasizes important textures and shapes in pothole datasets. The proposed preprocessing method uses intensity transformation to reduce unnecessary elements of the road and emphasize the texture and shape of the pothole. In addition, the feature of the porthole is detected using Superpixel and Sobel edge detection. Through performance comparison between the proposed preprocessing method and the existing preprocessing method, it is shown that the proposed preprocessing method is a more effective method than the existing method in detecting potholes.

• Journal of Korean Society for Quality Management
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• v.51 no.1
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• pp.55-65
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• 2023

Purpose: The purpose of this study is to propose an optimization process to improve product yield in the process using process data. Recently, research for low-cost and high-efficiency production in the manufacturing process using machine learning or deep learning has continued. Therefore, this study derives major variables that affect product defects in the manufacturing process using eXplainable Artificial Intelligence(XAI) method. After that, the optimal range of the variables is presented to propose a methodology for improving product yield. Methods: This study is conducted using the injection molding machine AI dataset released on the Korea AI Manufacturing Platform(KAMP) organized by KAIST. Using the XAI-based SHAP method, major variables affecting product defects are extracted from each process data. XGBoost and LightGBM were used as learning algorithms, 5-6 variables are extracted as the main process variables for the injection process. Subsequently, the optimal control range of each process variable is presented using the ICE method. Finally, the product yield improvement methodology of this study is proposed through a validation process using Test Data. Results: The results of this study are as follows. In the injection process data, it was confirmed that XGBoost had an improvement defect rate of 0.21% and LightGBM had an improvement defect rate of 0.29%, which were improved by 0.79%p and 0.71%p, respectively, compared to the existing defect rate of 1.00%. Conclusion: This study is a case study. A research methodology was proposed in the injection process, and it was confirmed that the product yield was improved through verification.