• Journal of Korean Society on Water Environment
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• v.38 no.4
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• pp.177-189
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• 2022

Nature-based Solutions (NbS) are defined as practical and technical approaches to restoring functioning ecosystems and biodiversity as a means to address socio-environmental challenges and provide human-nature co-benefits. This study reviews NbS-related literature to identify its key characteristics, techniques, and challenges for its application in climate-adaptive water management. The review finds that NbS has been commonly used as an umbrella term incorporating a wide range of existing ecosystem-based approaches such as low-impact development (LID), best management practices (BMP), forest landscape restoration (FLR), and blue-green infrastructure (BGI), rather than being a uniquely-situated practice. Its technical form and operation can vary significantly depending on the spatial scale (small versus large), objective (mitigation, adaptation, naturalization), and problem (water supply, quality, flooding). Commonly cited techniques include green spaces, permeable surfaces, wetlands, infiltration ponds, and riparian buffers in urban sites, while afforestation, floodplain restoration, and reed beds appear common in non- and less-urban settings. There is a greater lack of operational clarity for large-scale NbS than for small-scale NbS in urban areas. NbS can be a powerful tool that enables an integrated and coordinated action embracing not only water management, but also microclimate moderation, ecosystem conservation, and emissions reduction. This study points out the importance of developing decision-making guidelines that can inform practitioners of the selection, operation, and evaluation of NbS for specific sites. The absence of this framework is one of the obstacles to mainstreaming NbS for water management. More case studies are needed for empirical assessment of NbS.

• International Journal of Computer Science & Network Security
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• v.24 no.3
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• pp.23-28
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• 2024

The multi-tenancy and high scalability of the cloud have inspired businesses and organizations across various sectors to adopt and deploy cloud computing. Cloud computing provides cost-effective, reliable, and convenient access to pooled resources, including storage, servers, and networking. Cloud service models, SaaS, PaaS, and IaaS, enable organizations, developers, and end users to access resources, develop and deploy applications, and provide access to pooled computing infrastructure. Despite the benefits, cloud service models are vulnerable to multiple security and privacy attacks and threats. The SaaS layer is on top of the PaaS, and the IaaS is the bottom layer of the model. The software is hosted by a platform offered as a service through an infrastructure provided by a cloud computing provider. The Hypertext Transfer Protocol (HTTP) delivers cloud-based apps through a web browser. The stateless nature of HTTP facilitates session hijacking and related attacks. The Open Web Applications Security Project identifies web apps' most critical security risks as SQL injections, cross-site scripting, sensitive data leakage, lack of functional access control, and broken authentication. The systematic literature review reveals that data security, application-level security, and authentication are the primary security threats in the SaaS model. The recommended solutions to enhance security in SaaS include Elliptic-curve cryptography and Identity-based encryption. Integration and security challenges in PaaS and IaaS can be effectively addressed using well-defined APIs, implementing Service Level Agreements (SLAs), and standard syntax for cloud provisioning.

• Journal of Korean Society of Water and Wastewater
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• v.35 no.3
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• pp.237-246
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• 2021

The ILI, developed by the IWA (International Water Association), has been used in many countries as an indicator of water leakage. In Korea, the revenue water has been used as a performance indicator for waterworks although there is an opinion to replace it with the ILI. Hence, it has been necessary to investigate whether the ILI can replace the revenue water in Korea. The four main operating indicators (i.e., water service population, profit-loss ratio, fiscal self-reliance, and aged pipe rate) of 162 Korean waterworks were compared with the ILI with the linear regression method. Local water authorities with more than 1 million water service population, with more than 60% profit-loss ratio, more than 40% and less than 60% fiscal self-reliance, and more than 20% aged pipe rate showed meaningful correlation between the four parameters and the ILI. In the remaining cases, their correlations were little or weak. This means that using the ILI may not be an efficient method to represent the performance of the water supply system in Korea because of the lack of UARL (Unavoidable Annual Real Losses) data accuracy. To use the ILI in Korea, it will be required to carry out an additional research to accumulate reliable CARL (Current Annual Real Losses) and UARL data in the future.

• Korean Journal of Construction Engineering and Management
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• v.5 no.3 s.19
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• pp.55-62
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• 2004

The purpose of this study is to suggest a systematic procedural model for selecting competent project promoter. The proposed model was made by comparing domestic regulations and procedures with foreign nations', and through interviews with experts and literatures survey. The summaries of this paper are as follows. The current promoter selection procedure was evaluated by reviewing relevant papers, regulations and existing model. Some obstructions which hinder PPI project activation were identified, those are inadequacy of promoter qualification and negotiation process, lack of communication between parties, etc. Some alternatives which remove major obstructions are embodied in the model. The suggested model is comprised of PQ(prequalification), two phased evaluation for the technical proposals which include alternate, communication meeting, etc. To manage the overall procedure well, an involvement of professional "project promoter selection team" would be highly recommended. They will participate in each evaluation stage with full activities, and provide government with some technical materials for selecting promoter as coordinator.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.39 no.2
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• pp.54-63
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• 2016

As technology has developed and cost for data processing has reduced, big data market has grown bigger. Developed countries such as the United States have constantly invested in big data industry and achieved some remarkable results like improving advertisement effects and getting patents for customer service. Every company aims to achieve long-term survival and profit maximization, but it needs to establish a good strategy, considering current industrial conditions so that it can accomplish its goal in big data industry. However, since domestic big data industry is at its initial stage, local companies lack systematic method to establish competitive strategy. Therefore, this research aims to help local companies diagnose their big data capabilities through a reference model and big data capability assessment system. Big data reference model consists of five maturity levels such as Ad hoc, Repeatable, Defined, Managed and Optimizing and five key dimensions such as Organization, Resources, Infrastructure, People, and Analytics. Big data assessment system is planned based on the reference model's key factors. In the Organization area, there are 4 key diagnosis factors, big data leadership, big data strategy, analytical culture and data governance. In Resource area, there are 3 factors, data management, data integrity and data security/privacy. In Infrastructure area, there are 2 factors, big data platform and data management technology. In People area, there are 3 factors, training, big data skills and business-IT alignment. In Analytics area, there are 2 factors, data analysis and data visualization. These reference model and assessment system would be a useful guideline for local companies.

• International Commerce and Information Review
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• v.12 no.1
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• pp.3-33
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• 2010

Paperless trade is a new trade paradigm that has innovated on traditional trade procedures, which relied on manual work in the past, and applied an IT-based e-document standard. To realize paperless trade in Korea, a lot of efforts have been made. Korea has overcome many difficulties, a lack of awareness, trials and errors, etc. at the initial introduction stage and strived to establish a stable infrastructure through the government's policy support and active cooperation with the trade business communities and related organizations. Now, Korea became a well-known leader in IT industry, especially in the paperless trade infrastructure and strategic policies. The one-stop trading system named 'uTradeHub' is operated by a paperless trade service provider, Korea Trade Network(KTNET). uTradeHub includes trade finance and settlement, customs clearance and export and import logistics, improving trading procedures and reducing related expenses. Private-Public joint efforts from Korean government and private sectors which have respectively fulfilled their role and function with market-oriented practical policies and strategies has lead Korea a world leading country in paperless trade. Moreover, Korea expended its efforts to the global areas. Korea has started to activate multi-national paperless trade alliances such as PAA(Pan-Asia e-Commerce Alliance), ASEAL(Asia Europe Alliance for Paperless Trading) as well as established the bilateral cooperative networks with China and Taiwan. The one-stop trading system, uTradeHub should keep close cooperations between nations since trade itself is implemented in a cross-border ways. In the near future, it is expected uTradeHub can achieve best results in the simplification of procedures and cost savings when an international linkage is completely established with international cooperations.

• International Journal of Computer Science & Network Security
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• v.22 no.11
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• pp.11-18
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• 2022

Linking Ukraine's education system with the trends of global digitalization is mandatory to ensure the sustainable, long-term development of the country, as well as to increase the sustainability of the education system and the economy as a whole during the crisis period. Now the main problems of the education system in Ukraine are manifested in a complex context caused by Russian armed aggression. In the context of war, problems include differences in adaptation to online learning among educational institutions, limited access to education for vulnerable groups in the zone of active hostilities, the lack of digital educational resources suitable for online learning, and the lack of basic digital skills and competencies among students and teachers necessary to properly conduct online classes. Some of the problems of online learning were solved in the pandemic, but in the context of war Ukrainian society needs a new vision of education and continuous efforts of all social structures in the public and private environment. In the context of war, concerted action is needed to keep education on track and restore it in active zones, adapting to the needs of a dynamic society and an increasingly digitized economy. Among the urgent needs of the education system are a change in the teaching-learning paradigm, which is based on content presentation, memorization, and reproduction, and the adoption of a new, hybrid educational model that will encourage the development of necessary skills and abilities for students and learners in a digitized society and enable citizens close to war zones to learn.

• Fisheries and Aquatic Sciences
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• v.25 no.4
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• pp.214-230
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• 2022

Loss and damage have become a vital contemporary issue in climate change studies and actions in developing countries. However, studies are scant on this in the fisheries sector around the world. In Bangladesh, there is no study on the loss and damage in fisheries dependent communities. This study assesses economic and non-economic loss and damage to coastal shrimp farms due to cyclone Bulbul in Gabura Union of Shyamnagar Upazila, Satkhira district, using a mixed method approach. Results show that all shrimp farms' dependent communities are affected by cyclone Bulbul to some extent. About 14%, 57%, and 29% of the farms were totally, heavily and moderately damaged due to farm inundation and dyke damage. The estimated mean loss and damage per shrimp farm was worth USD 4,633. Around 31% and 72% of the farms' fencing nets and traps were lost, which was worth USD 333 per farm. There were also loss and damage to other resources such as houses, solar panels, livestock and agricultural crops where the estimated mean loss and damage per household was worth USD 3,170. This study reported that the rich shrimp farmers encountered proportionately more economic loss and damage than their poor counterparts. However, this does not mean that the poor suffered less. The current study found a range of non-economic loss and damage in different aspects of the shrimp farmers' household members such as unbearable mental pain, deterioration of health, physical injuries, disabilities, etc. and access to services (e.g., inadequate food, lack of safe drinking water, lack of medical facilities, disruption of education systems), social infrastructure (e.g., damage of roads and markets) and disturbance of cultural functions. The findings suggest that urgent short- and long-term actions may be taken to save the aquaculture farms and dependent livelihoods from economic and non-economic loss and damage to cyclones in future.

• Journal of Korean Public Health Nursing
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• v.19 no.2
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• pp.177-187
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• 2005

The purpose of this study was to 1) identify the current management status of the Visiting Health Care Services (VHCS) and 2) to analyze the workload of the staff in the VHCS located in the Public Health Centers (PHCs) in the urban and rural areas. Method: A descriptive research design and a prospective, time and motion research design were used. A total of 18 PHCs in Gangwon Province participated in this study. A questionnaire and semi-structured observational sheet were utilized. A total of 650 self report records of the work load from the VHCS personnel were collected for a 10 day period at each of the 18 PHCs. A descriptive analysis was then done. Results: The major results were as follows. 1) The VHCS staff (nurses and nurse aids) was being assigned additional work such as maternal health care, chronic disease care, mental health care and health promotion on top of their VHCS duties. 2) The average number of home visits per client during the past year was 5.8. More specifically, the clients in the severe dependent group received an average of 27.1 visits, those clients in the moderate dependent group received 14.0 visits those clients in the slightly dependent group received 5.0 visits and those clients in the self-care group received 1.6 visits. 3) The time required for the work duties of the VHCS staff totaled 488 minutes per day. The percentage of time for home visits was only 17.4%, and this didn't include travel time. Conclusion: The main problems of VHCS were identified as a lack of personnel and a lack of time for the home visits. Strategies that are directed at the construction of a better infrastructure for VHCS are needed.

• Smart Structures and Systems
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• v.29 no.1
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• pp.237-250
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• 2022

Structural health monitoring (SHM) plays an important role in ensuring the safety and functionality of critical civil infrastructure. In recent years, numerous researchers have conducted studies to develop computer vision and machine learning techniques for SHM purposes, offering the potential to reduce the laborious nature and improve the effectiveness of field inspections. However, high-quality vision data from various types of damaged structures is relatively difficult to obtain, because of the rare occurrence of damaged structures. The lack of data is particularly acute for fatigue crack in steel bridge girder. As a result, the lack of data for training purposes is one of the main issues that hinders wider application of these powerful techniques for SHM. To address this problem, the use of synthetic data is proposed in this article to augment real-world datasets used for training neural networks that can identify fatigue cracks in steel structures. First, random textures representing the surface of steel structures with fatigue cracks are created and mapped onto a 3D graphics model. Subsequently, this model is used to generate synthetic images for various lighting conditions and camera angles. A fully convolutional network is then trained for two cases: (1) using only real-word data, and (2) using both synthetic and real-word data. By employing synthetic data augmentation in the training process, the crack identification performance of the neural network for the test dataset is seen to improve from 35% to 40% and 49% to 62% for intersection over union (IoU) and precision, respectively, demonstrating the efficacy of the proposed approach.