• Proceedings of the Korea Water Resources Association Conference
• /
• 2021.06a
• /
• pp.140-140
• /
• 2021

Urban flood management is a crucial and challenging task, particularly in developed cities. Therefore, accurate prediction of urban flooding under heavy precipitation is critically important to address such a challenge. In recent years, machine learning techniques have received considerable attention for their strong learning ability and suitability for modeling complex and nonlinear hydrological processes. Moreover, a survey of the published literature finds that hybrid computational intelligent methods using nature-inspired algorithms have been increasingly employed to predict or simulate the streamflow with high reliability. The present study is aimed to propose a novel approach, an ensemble tree, Bayesian Additive Regression Trees (BART) model incorporating a nature-inspired algorithm to predict hourly multi-step ahead streamflow. For this reason, a hybrid intelligent model was developed, namely GA-BART, containing BART model integrating with Genetic algorithm (GA). The Jungrang urban basin located in Seoul, South Korea, was selected as a case study for the purpose. A database was established based on 39 heavy rainfall events during 2003 and 2020 that collected from the rain gauges and monitoring stations system in the basin. For the goal of this study, the different step ahead models will be developed based in the methods, including 1-hour, 2-hour, 3-hour, 4-hour, 5-hour, and 6-hour step ahead streamflow predictions. In addition, the comparison of the hybrid BART model with a baseline model such as super vector regression models is examined in this study. It is expected that the hybrid BART model has a robust performance and can be an optional choice in streamflow forecasting for urban basins.

• Journal of Industrial Convergence
• /
• v.21 no.12
• /
• pp.37-43
• /
• 2023

In today's business landscape, collaboration and interoperability are crucial for organizational success and profitability. However, integrating operations across multiple organizations is challenging due to differing roles and policies in Identity and Access Management (IAM). User-centric identity (UCI) adopts a personalized approach to digital identity management, centering on the end-user for authentication and access control. It provides a decentralized system that ensures secure and customized access for each user. UCI aims to address complex security challenges by aligning access privileges with individual user requirements. This research delves into UCI's ability to streamline resource access amidst conflicting IAM roles and protocols across various organizations. The study presents a UCI-based multi-domain access control (MDAC) framework, which encompasses an ontology, a unified method for articulating access roles and policies across domains, and software services melding with UCI infrastructure. The goal is to enhance organizational resource management and decision-making by offering clear guidelines on access roles and policy management across diverse domains, ultimately boosting companies' return on investment.

• Journal of Information Technology Services
• /
• v.23 no.1
• /
• pp.1-10
• /
• 2024

The IT environment is changing due to the acceleration of digital transformation in enterprises and organizations. This expansion of the digital space makes centralized cybersecurity controls more difficult. For this reason, cyberattacks are increasing in frequency and severity and are becoming more sophisticated, such as ransomware and digital supply chain attacks. Even in large organizations with numerous security personnel and systems, security incidents continue to occur due to unmanaged and unknown threats and vulnerabilities to IT assets. It's time to move beyond the current focus on detecting and responding to security threats to managing the full range of cyber risks. This requires the implementation of asset Inventory for comprehensive management by collecting and integrating all IT assets of the enterprise and organization in a wide range. IT Asset Management(ITAM) systems exist to identify and manage various assets from a financial and administrative perspective. However, the asset information managed in this way is not complete, and there are problems with duplication of data. Also, it is insufficient to update of data-set, including Network Infrastructure, Active Directory, Virtualization Management, and Cloud Platforms. In this study, we, the researcher group propose a new framework for automated 'Comprehensive IT Asset Management(CITAM)' required for security operations by designing a process to automatically collect asset data-set. Such as the Hostname, IP, MAC address, Serial, OS, installed software information, last seen time, those are already distributed and stored in operating IT security systems. CITAM framwork could classify them into unique device units through analysis processes in term of aggregation, normalization, deduplication, validation, and integration.

• International Journal of Computer Science & Network Security
• /
• v.24 no.5
• /
• pp.172-180
• /
• 2024

Since the beginning of 2015, corporate social responsibility (CSR) models have been changing in connection with the trend towards the transition of joint value creation of corporate activities and consideration of stakeholders' interests. The purpose of the academic paper lies in empirically studying the current practice of social responsibility of transnational corporations (TNCs). The research methodology has combined the method of qualitative analysis, the method of cases of agricultural holdings in emerging markets within the framework of resource theory, institutional theory and stakeholders' theory. The results show that the practice of CSR is integrated into the strategy of sustainable development of TNCs, which determine the methods, techniques and forms of communication, as well as areas of stakeholders' responsibility. The internal practice of CSR is aimed at developing norms and standards of moral behaviour with stakeholders in order to maximize economic and social goals. Economic goals are focused not only on making a profit, but also on minimizing costs due to the potential risks of corruption, fraud, conflict of interest. The system of corporate social responsibility of modern TNCs is clearly regulated by internal documents that define the list of interested parties and stakeholders, their areas of responsibility, greatly simplifying the processes of cooperation and responsibility. As a result, corporations form their own internal institutional environment. Ethical norms help to avoid the risks of opportunistic behaviour of personnel, conflicts of interest, cases of bribery, corruption, and fraud. The theoretical value of the research lies in supplementing the theory of CSR in the context of the importance of a complex, systematic approach to integrating the theory of resources, institutional theory, theory of stakeholders in the development of strategies for sustainable development of TNCs, the practice of corporate governance and social responsibility.

• Journal of Ocean Engineering and Technology
• /
• v.38 no.2
• /
• pp.64-73
• /
• 2024

Oil spills pose significant threats to marine ecosystems, human health, socioeconomic aspects, and coastal communities. Accurate real-time predictions of oil slick transport along coastlines are paramount for quick preparedness and response efforts. This study used an open-source OpenOil numerical model to simulate the fate and trajectories of oil slicks released during the 2007 Hebei Spirit accident along the Korean coasts. Six combinations of input parameters, derived from a five-day met-ocean dataset incorporating various hydrodynamic, meteorological, and wave models, were investigated to determine the input variables that lead to the most reasonable results. The predictive performance of each combination was evaluated quantitatively by comparing the dimensions and matching rates between the simulated and observed oil slicks extracted from synthetic aperture radar (SAR) data on the ocean surface. The results show that the combination incorporating the Hybrid Coordinate Ocean Model (HYCOM) for hydrodynamic parameters exhibited more substantial agreement with the observed spill areas than Copernicus Marine Environment Monitoring Service (CMEMS), yielding up to 88% and 53% similarity, respectively, during a more than four-day oil transportation near Taean coasts. This study underscores the importance of integrating high-resolution met-ocean models into oil spill modeling efforts to enhance the predictive accuracy regarding oil spill dynamics and weathering processes.

• Journal of Hospice and Palliative Care
• /
• v.20 no.1
• /
• pp.1-7
• /
• 2017

The paper describes The Narrative Communication Model of Hope Seeking Intervention developed by the authors as an approach to help clients to have individually specific hope experiences. The Model is founded upon the existential conceptualization of hope that views hope as subjective, unique experiences of meaning and processes. The Model has been developed based on the findings both in the literature and the authors' work on the nature of hope and hope experiences and integrating the concept of hope as subjective meanings and experiences, the processes of story-telling and the concept of narrative configuration as a way to engage in person-specific experiences, and person-centered communication. The results of the experiences with the application of the model in a study are used to clarify the model further. The Model incorporating story-telling and narrative construction through person-centered communication is identified in three components-the story-telling, the narrative intervention, and the communication components. These components are processed as an intervention to culminate into person-specific hope experiences in which active participation of clients as the story-teller and of interventionist as the communicative facilitator is required to produce narratives of hope with individual specific thematic plots that become the basis for hope experiences. The application of the Model has shown positive outcomes in clients with successful seeking of own hope experiences. The success of the Model application seems to depend upon interventionists' understanding of the model and the competency with the application of person-centered communication strategies.

• Journal of Korea Water Resources Association
• /
• v.54 no.9
• /
• pp.681-692
• /
• 2021

Vegetation processes have a significant impact on rainfall runoff processes through evapotranspiration control, but are rarely considered in the conceptual lumped hydrological model. This study evaluated the model performance of the Hapcheon Dam watershed by integrating the ecological module expressing the leaf area index data sensed remotely from the satellite into the hydrological partition module. The proposed eco-hydrological model has three main features to better represent the eco-hydrological process in humid regions. 1) The growth rate of vegetation is constrained by water shortage stress in the watershed. 2) The maximum growth of vegetation is limited by the energy of the watershed climate. 3) The interaction of vegetation and aquifers is reflected. The proposed model simultaneously simulates hydrologic components and vegetation dynamics of watershed scale. The following findings were found from the validation results using the model parameters estimated by the SCEM algorithm. 1) Estimating the parameters of the eco-hydrological model using the leaf area index and streamflow data can predict the streamflow with similar accuracy and robustness to the hydrological model without the ecological module. 2) Using the remotely sensed leaf area index without filtering as input data is not helpful in estimating streamflow. 3) The integrated eco-hydrological model can provide an excellent estimate of the seasonal variability of the leaf area index.

• KSCE Journal of Civil and Environmental Engineering Research
• /
• v.26 no.6D
• /
• pp.969-974
• /
• 2006

Labor shortages are a serious problem for Korea's construction industry. The problem is both quantitative and qualitative. There is a shortage in supply as due to a decrease in the influx of new labor, and existing workers are less productive as they age. The problem will only get worse as more and more major public projects are being planned. Options for increasing the labor supply are somewhat limited, and thus efforts need to be made to adopt new technologies that can improve the productivity and efficiency of field work and their processes. This paper introduces seven innovation technologies that have the best potential to increase productivity and thus reduce the burden of labor shortage problems. These include 1) Substitution by use of robotics and automation, 2) development and applications of Innovative materials to reduce on site field work, 3) increase in productivity through the implementation of Information Technology, 4) improved productivity through the application of modules, and prefabrication, 5) prevention of rework and redesign, 6) diversification of labor by integrating labor skills, and 7) improved productivity by standardizing site processes.

• KIPS Transactions on Software and Data Engineering
• /
• v.13 no.1
• /
• pp.1-16
• /
• 2024

Over recent years, 6 Sigma has become a key methodology in manufacturing for quality improvement and cost reduction. However, challenges have arisen due to the difficulty in analyzing large-scale data generated by smart factories and its traditional, formal application. To address these limitations, a big data-based 6 Sigma approach has been developed, integrating the strengths of 6 Sigma and big data analysis, including statistical verification, mathematical optimization, interpretability, and machine learning. Despite its potential, the practical impact of this big data-based 6 Sigma on manufacturing processes and management performance has not been adequately verified, leading to its limited reliability and underutilization in practice. This study investigates the efficiency impact of DX SS, a big data-based 6 Sigma, on manufacturing processes, and identifies key success policies for its effective introduction and implementation in enterprises. The study highlights the importance of involving all executives and employees and researching key success policies, as demonstrated by cases where methodology implementation failed due to incorrect policies. This research aims to assist manufacturing companies in achieving successful outcomes by actively adopting and utilizing the methodologies presented.

• Journal of Soil and Groundwater Environment
• /
• v.14 no.2
• /
• pp.33-44
• /
• 2009

The objective of the study was to develop a hybrid technology integrating biological and physicochemical technologies to efficiently remediate arsenic contaminated lands such as abandoned mine area. The tailing soil samples contaminated with As at a high level were obtained from Songchon abandoned mine, and the content of arsenic and heavy metals as well as physicochemical properties and mineral composition were investigated. In addition, two sets of sequential extraction methods were applied to analyze chemical speciations of arsenic and heavy metals to expect their leachability and mobility in geoenvironment. Based on these geochemical data of arsenic and heavy metal contaminants, column-type experiments on the bioleaching of arsenic were undertaken. Subsequently, experiments on the hybrid process incorporating bioleaching and electrokinetics were accomplished and its removal efficiency of arsenic was compared with that of the individual electrokinetic process. With the results, finally, the feasibilty of the hybrid technnology was evaluated. The arsenic removal efficiencies of the individual electrokinetic process (44 days) and the hybrid process incorporating bioleaching (28 days) and electrokinetics (16 dyas) were measured 57.8% and 64.5%, respectively, when both two processes were operated in an identical condition. On the contrary, the arsenic removal efficiency during the bioleaching process (28 days) appeared relatively lower (11.8%), and the result indicates that the bioleaching process enhanced the efficacy of the electrokinetic process as a result of mobilization of arsenic rather than removed arsenic by itself. In particular, the arsenic removal rate of the electrokinetics integrated with bioleaching was observed over than 2 times larger than that obtained by the electrokinetics alone. From the results of the study, if the bioleaching which is considered a relatively economic process is applied sufficiently prior to electrokinetics, the removal efficiency and rate of arsenic can be significantly improved. Consequently, the study proves the feasibility of the hybrid process integrating both technologies.