• 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.

• International conference on construction engineering and project management
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• 2022.06a
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• pp.353-360
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• 2022

Due to the dense and complicated working environment, the construction industry is susceptible to many accidents. Worker's fall is a severe problem at the construction site, including falling into holes or openings because of the inadequate coverings as per the safety rules. During the construction or demolition of a building, openings and holes are formed in the floors and roofs. Many workers neglect to cover openings for ease of work while being aware of the risks of holes, openings, and gaps at heights. However, there are safety rules for worker safety; the holes and openings must be covered to prevent falls. The safety inspector typically examines it by visiting the construction site, which is time-consuming and requires safety manager efforts. Therefore, this study presented a worker-driven approach (the worker is involved in the reporting process) to facilitate safety managers by developing integrated computer vision and inertia sensors-based mobile applications to identify openings. The TensorFlow framework is used to design Convolutional Neural Network (CNN); the designed CNN is trained on a custom dataset for binary class openings and covered and deployed on an android smartphone. When an application captures an image, the device also extracts the accelerometer values to determine the inclination in parallel with the classification task of the device to predict the final output as floor (openings/ covered), wall (openings/covered), and roof (openings / covered). The proposed worker-driven approach will be extended with other case scenarios at the construction site.

• Journal of Korea Water Resources Association
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• v.56 no.4
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• pp.273-284
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• 2023

Water supply is continuously suffering from frequent droughts under climate change, and such extreme events are expected to become more frequent due to climate change. In this study, the decision scaling method was introduced to evaluate the drought vulnerability under future climate change in a wider range. As a result, the water supply reliability of the Boryeong Dam ranged from 95.80% to 98.13% to the condition of the aqueduct which was constructed at the Boryeong Dam. Furthermore, the Boryeong Dam was discovered to be vulnerable under climate change scenarios. Hence, genetic algorithm-based hedging rules were developed to evaluate the reduction effect of drought vulnerability. Moreover, three demand scenarios (high, standard, and low demand) were also considered to reflect the future socio-economic change in the Boryeong Dam. By analyzing quantitative reliability and the probability of extreme drought occurrence under 5% of the water storage rate, all hedging rules demonstrated that they were superior in preparing for extreme drought under low-demand scenarios.

• Proceedings of the Korea Water Resources Association Conference
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• 2020.06a
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• pp.405-405
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• 2020

최근 선제적인 가뭄대응을 위하여 관계부처가 상시 가뭄 관리체계를 지속하고, 범정부적 가뭄예방 대처를 위한 가뭄종합대책이 수립되었다. 가뭄종합대책에는 통합적 가뭄 위기대응체계를 마련해 단계별로 가뭄에 체계적으로 대응하고, 극한가뭄에 대비해 선제적 용수확보와 가뭄 전문가 지역 협의체 운영 등을 통해 대응 역량을 강화하는 계획이 포함되어있다. 또한 국가재난관리체계에 따라 지자체는 지역별 재난안전대책본부를 수립하고, 현장조치 행동메뉴얼에 따라 단계별 제한급수대책 수립, 재난대응 단계별 행동요령 (징후 감지, 초기 대응, 비상 대응) 등을 수행한다. 이처럼 가뭄은 발생 후 해갈까지 많은 시간과 지속적인 관리가 필요하며, 사회전반에 걸처 영향을 주는 대형복합재난으로 국가적 차원의 통합적 관리가 필요한 재난으로 국가가뭄대응체계 및 비상대처계획 (Emergency Action Plan, EAP) 수립이 필요하다. 미국은 1998년 국가가뭄정책법(National Drought Policy Act)을 제정해 가뭄관리에 대한 법제도적 기반을 마련하였으며, 2006년 국가통합가뭄정보시스템법 (National Integrated Drought Information System Act)을 제정해(Public Law 109-430) 현재의 국가통합가뭄정보시스템 (NIDIS)이 설립되었다. 이후 국가가뭄회복력파트너십 (National Drought Resilience Partnership, NDRP)을 발족하여 2016년 장기가뭄 회복력을 위한 국가재해대응정책을 수립하였다 (Federal Action Plan for Long-Term Drought Resilience). 미국의 경우 1982년 콜로라도 주, 사우스다코타 주, 뉴욕 주를 시작으로 2020년 현재 48개 주에서 연방정부단위의 가뭄대응계획을 수립하였다. 본 연구에서는 미국에서 실행되고 있는 가뭄 적응 대책 및 비상대처계획을 조사, 분석하고, 향후 메가 가뭄 발생시 국가단위의 가뭄 재난위기관리 매뉴얼, 정부 및 지자체의 가뭄 대응 체계 및 대응 방안을 보완할 수 있는 방안을 제시하고자 한다.

• Convergence Security Journal
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• v.22 no.3
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• pp.33-39
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• 2022

Recently, cyberattacks on infrastructure have been continuously occurring with the starting of neutralizing the user authentication function of information systems. Accordingly, the vulnerabilities of system are increasing day by day, such as the increase in the vulnerabilities of the encryption system. In this paper, an alternative technique for the symmetric key algorithm has been developed in order to build the encryption algorithm that is not easy for beginners to understand and apply. Vigenere Cipher is a method of encrypting alphabetic text and it uses a simple form of polyalphabetic substitution. The encryption application system proposed in this study uses the simple form of polyalphabetic substitution method to present an application model that integrates the three steps of encryption table creation, encryption and decryption as a framework. The encryption of the original text is done using the Vigenère square or Vigenère table. When applying to the automatic generation of secret keys on the information system this model is expected that integrated authentication work, and analysis will be possible on target system. ubstitution alphabets[3].

• Journal of Korean Society for Quality Management
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• v.51 no.2
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• pp.171-184
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• 2023

Purpose: First, this paper suggests an alternative approach to find optimal portfolio (stocks, bonds and ESG stocks) under the maximizing utility of investors. Second, we include ESG stocks in our optimal portfolio, and compare improvement of welfares in the case with and without ESG stocks in portfolio. Methods: Our main method of analysis follows Brennan et al(2002), designed under the continuous time framework. We assume that the dynamics of stock price follow the Geometric Brownian Motion (GBM) while the short rate have the Vasicek model. For the utility function of investors, we use the Power Utility Function, which commonly used in financial studies. The optimal portfolio and welfares are derived in the partial equilibrium. The parameters are estimated by using Kalman filter and ordinary least square method. Results: During the overall analysis period, the portfolio including ESG, did not show clear welfare improvement. In 2017, it has slightly exceeded this benchmark 1, showing the possibility of improvement, but the ESG stocks we selected have not strongly shown statistically significant welfare improvement results. This paper showed that the factors affecting optimal asset allocation and welfare improvement were different each other. We also found that the proportion of optimal asset allocation was affected by factors such as asset return, volatility, and inverse correlation between stocks and bonds, similar to traditional financial theory. Conclusion: The portfolio with ESG investment did not show significant results in welfare improvement is due to that 1) the KRX ESG Leaders 150 selected in our study is an index based on ESG integrated scores, which are designed to affect stability rather than profitability. And 2) Korea has a short history of ESG investment. During the limited analysis period, the performance of stock-related assets was inferior to bond assets at the time of the interest rate drop.

• Proceedings of the Korea Water Resources Association Conference
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• 2022.05a
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• pp.153-153
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• 2022

Large-scale and accurate observations at fine spatial resolution through a means of remote sensing offer an effective tool for capturing rainfall variability over the traditional rain gauges and weather radars. Although satellite rainfall products (SRPs) derived using two major estimation approaches were evaluated worldwide, their practical applications suffered from limitations. In particular, the traditional top-down SRPs (e.g., IMERG), which are based on direct estimation of rain rate from microwave satellite observations, are mainly restricted with their coarse spatial resolution, while applications of the bottom-up approach, which allows backward estimation of rainfall from soil moisture signals, to novel high spatial resolution soil moisture satellite sensors over South Korea are not introduced. Thus, this study aims to evaluate the performances of a state-of-the-art bottom-up SRP (the self-calibrated SM2RAIN model) applied to the C-band SAR Sentinel-1, a statistically downscaled version of the conventional top-down IMERG SRP, and their integration for a targeted high spatial resolution of 0.01° (~ 1-km) over central South Korea, where the differences in climate zones (coastal region vs. mainland region) and vegetation covers (croplands vs. mixed forests) are highlighted. The results indicated that each single SRP can provide plus points in distinct climatic and vegetated conditions, while their drawbacks have existed. Superior performance was obtained by merging these individual SRPs, providing preliminary results on a complementary high spatial resolution SRP over central South Korea. This study results shed light on the further development of integration framework and a complementary high spatial resolution rainfall product from multi-satellite sensors as well as multi-observing systems (integrated gauge-radar-satellite) extending for entire South Korea, toward the demands for urban hydrology and microscale agriculture.

• Annual Conference of KIPS
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• 2023.11a
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• pp.97-99
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• 2023

소프트웨어를 개발하거나 실행하는 환경은 매우 다양하다. 최근에 혁신을 이끌고 있는 인공지능 모델은 오픈소스 프로젝트룰 통해 공개되는 코드나 라이브러리를 활용하여 구현하는 경우가 많다. 하지만 실행을 위한 환경 설치 과정이 쉽지 않고, 데이터 혹은 기학습된 모델 사이즈가 대용량일 경우에는 로컬 컴퓨터에서 실행하는 것이 불가능한 경우도 발생하고, 동료와 작업을 공유하거나 수동 배포의 어려움 등 다양한 문제에 직면한다. 이러한 문제를 해결하기 위하여, 소프트웨어가 유연하게 동작할 수 있도록 효율적인 리소스를 관리할 수 있는 컨테이너 기술을 많이 활용한다. 이 기술을 활용하는 이유는 AI 모델이 시스템에 관계없이 정확히 동일하게 재현될 수 있도록 하기 위함이다. 본 연구에서는 인공지능 모델 개발과 관련하여 코드가 실행되는 환경을 편리하게 관리하기 위하여 소프트웨어를 컨테이너화하여 배포할 수 있는 기능을 제공하는 연구소프트웨어 개발 통합 프레임워크를 제안한다.

• Journal of Korean Neurosurgical Society
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• v.66 no.6
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• pp.632-641
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• 2023

Central nervous system tumors are identified as tumors of the brain and spinal cord. The associated morbidity and mortality of cerebrospinal tumors are disproportionately high compared to other malignancies. While minimally invasive techniques have initiated a revolution in neurosurgery, artificial intelligence (AI) is expediting it. Our study aims to analyze AI's role in the neurosurgical management of cerebrospinal tumors. We conducted a scoping review using the Arksey and O'Malley framework. Upon screening, data extraction and analysis were focused on exploring all potential implications of AI, classification of these implications in the management of cerebrospinal tumors. AI has enhanced the precision of diagnosis of these tumors, enables surgeons to excise the tumor margins completely, thereby reducing the risk of recurrence, and helps to make a more accurate prediction of the patient's prognosis than the conventional methods. AI also offers real-time training to neurosurgeons using virtual and 3D simulation, thereby increasing their confidence and skills during procedures. In addition, robotics is integrated into neurosurgery and identified to increase patient outcomes by making surgery less invasive. AI, including machine learning, is rigorously considered for its applications in the neurosurgical management of cerebrospinal tumors. This field requires further research focused on areas clinically essential in improving the outcome that is also economically feasible for clinical use. The authors suggest that data analysts and neurosurgeons collaborate to explore the full potential of AI.

• Convergence Security Journal
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• v.24 no.2
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• pp.19-29
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• 2024

A crypto-jacking attack is an attack that infringes on the availability of users by stealing computing resources required for cryptocurrency mining. The target of the attack is gradually diversifying from general desktop or server environments to cloud environments. Therefore, it is essential to apply a crypto-minor detection technique suitable for various computing environments. However, since the existing detection methodologies have only been detected in a specific environment, comparative analysis has not been properly performed on the methodologies that can be applied to each environment. Therefore, in this study, classification criteria for conventional crypto-minor detection techniques are established, and a complex and integrated detection framework applicable to the cloud environment is presented through in-depth comparative analysis of existing crypto-minor detection techniques based on different experimental environments and datasets.