• Membrane Journal
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• v.29 no.3
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• pp.130-139
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• 2019

Various two-dimensional nano materials such as graphene, zeolite, and metal-organic framework have been utilized to develop an ultra-thin high-performance membrane for water purification, gas separation, and so on. Particularly, in the case of graphene oxide, synthesis methods and thin film coating techniques have been accumulated and established since early 2000s, therefore graphene oxide has been rapidly applied to membrane field. The multi-layered graphene oxide thin film can filter molecules separately by the molecular sieving of interlayer spacing between adjacent layers, and it is also possible to separate various materials depending on the surface functional groups or the degree of interaction to intercalated materials. This review mainly focuses on the nanofiltration application of graphene oxide. The major factors affecting the separation performance of graphene oxide membrane in solvent are summarized and other technical elements required for the commercialization of graphene oxide membranes will be discussed including stability issue and fabrication method.

• BMB Reports
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• v.52 no.1
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• pp.56-63
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• 2019

Aging is a complex and progressive process characterized by physiological and functional decline with time that increases susceptibility to diseases. Aged-related functional change is accompanied by a low-grade, unresolved chronic inflammation as a major underlying mechanism. In order to explain aging in the context of chronic inflammation, a new integrative concept on age-related chronic inflammation is necessary that encompasses much broader and wider characteristics of cells, tissues, organs, systems, and interactions between immune and non-immune cells, metabolic and non-metabolic organs. We have previously proposed a novel concept of senescent (seno)-inflammation and provided its frameworks. This review summarizes senoinflammation concept and additionally elaborates modulation of senoinflammation by calorie restriction (CR). Based on aging and CR studies and systems-biological analysis of Omics big data, we observed that senescence associated secretory phenotype (SASP) primarily composed of cytokines and chemokines was notably upregulated during aging whereas CR suppressed them. This result further strengthens the novel concept of senoinflammation in aging process. Collectively, such evidence of senoinflammation and modulatory role of CR provide insights into aging mechanism and potential interventions, thereby promoting healthy longevity.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.24 no.3
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• pp.1-18
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• 2021

England's green belt policy as it delivered its framework to designating the development restriction zones(DRZ) in Korea is the key to address issues which try to change green belt boundary or/and housing development. Therefore it should necessarily be reviewed on the understanding of how England has been formulating a national policy to deal with the issues focusing on opportunities for housing development and recreation. This study explored the discourse and framework of England's green belt policy as well as driver changes of housing development and recreation. Results show several characteristics of England's green belt policy which are civil society consensus on conservation and management, limited small-scale housing development through management of release rates, a systematic procedure for application and approval, open-recreation space expansion and utilisation under the premise of conservation of natural green areas, and management structure by the involvement of NGO organisations. Therefore, five suggestions can be delivered to developing Korea's DRZ frameworks: first, preceding social consensus on the preservation value of development-restricted zones, second, addressing housing shortages in different alternatives e.g.) environmental-friendly small-scale housing, third, institutionalising the total proportion of release, fourth, establishing an open-recreation space, fifth, introducing expanded public-private partnerships. Ultimately securing the legitimacy of the nation's development-restricted zone system can contribute positively to the environment preservation and human health by promoting public leisure activities in terms of the recent increase in external activities caused by the Covid-19 crisis. Concluding remarks are here that the understanding of England's green belt policy can be delivered to and help formulate domestic policy addressing current issues.

• Journal of Korea Multimedia Society
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• v.24 no.1
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• pp.75-94
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• 2021

The 4th industrial revolution needs a fusion of artificial intelligence, robotics, the Internet of Things (IoT), edge computing, and other technologies. For the fusion of technologies, cloud computing technology can provide flexible and high-performance computing resources so that cloud computing can be the foundation technology of new emerging services. The emerging services become a global-scale, and require much higher performance, availability, and reliability. Public cloud providers already provide global-scale services. However, their services, costs, performance, and policies are different. Enterprises/ developers to come out with a new inter-operable service are experiencing vendor lock-in problems. Therefore, multi-cloud technology that federatively resolves the limitations of single cloud providers is required. We propose a software platform, denoted as Cloud-Barista. Cloud-Barista is a multi-cloud service common platform for federating multiple clouds. It makes multiple cloud services as a single service. We explain the functional architecture of the proposed platform that consists of several frameworks, and then discuss the main design and implementation issues of each framework. To verify the feasibility of our proposal, we show a demonstration which is to create 18 virtual machines on several cloud providers, combine them as a single resource, and manage it.

• Journal of Broadcast Engineering
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• v.27 no.3
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• pp.341-350
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• 2022

In this paper, we propose a deep learning based on-device augmented reality (AR) system in which multiple input images are used to implement the correct occlusion in a real environment. The proposed system is composed of three technical steps; camera pose estimation, depth estimation, and object augmentation. Each step employs various mobile frameworks to optimize the processing on the on-device environment. Firstly, in the camera pose estimation stage, the massive computation involved in feature extraction is parallelized using OpenCL which is the GPU parallelization framework. Next, in depth estimation, monocular and multiple image-based depth image inference is accelerated using the mobile deep learning framework, i.e. TensorFlow Lite. Finally, object augmentation and occlusion handling are performed on the OpenGL ES mobile graphics framework. The proposed augmented reality system is implemented as an application in the Android environment. We evaluate the performance of the proposed system in terms of augmentation accuracy and the processing time in the mobile as well as PC environments.

• International Journal of Computer Science & Network Security
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• v.21 no.12
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• pp.45-52
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• 2021

The article proves the relevance of developing conceptual frameworks for managing the quality assurance of logistics activities in the context of socio-economic interaction of their participants. It is established that the fundamental difference of the logistic approach in management from traditional approaches is the allocation of a single management function of previously separated, disparate material flows, as well as economic, technological, information integration of chain links into a single system capable of effective management of these flows. It is substantiated that the functioning of the enterprise as a logistics system can be represented in the form of a triad of logistics components, namely: supply logistics, production logistics, sales logistics. Management of quality assurance processes of logistics activities in the context of socio-economic interaction of their participants is a functional component of the entire logistics system due to the quality of work and interaction of all participants in the implementation of certain activities. The quality of logistics activities will affect the level of economic potential, rationalization and optimization of all logistics flows. It is proved that the management of quality assurance processes of logistics activities in the context of socio-economic interaction of their participants involves the following main areas: the introduction of a quality system of logistics processes; development and implementation of the general strategy of quality improvement at the enterprise; internal integration; controlling. Management of quality assurance processes of logistics activities in the context of socio-economic interaction of its participants requires compliance with the following requirements: systematic and comprehensive management of all flow processes; coordination of criteria and indicators for assessing the effectiveness of the entire logistics system; dissemination of the use and application of information technology; ensuring partnerships and close interaction of all participants in sales networks.

• Proceedings of the National Institute of Ecology of the Republic of Korea
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• v.3 no.2
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• pp.67-72
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• 2022

Ecological research relies on the interpretation of large amounts of visual data obtained from extensive wildlife surveys, but such large-scale image interpretation is costly and time-consuming. Using an artificial intelligence (AI) machine learning model, especially convolution neural networks (CNN), it is possible to streamline these manual tasks on image information and to protect wildlife and record and predict behavior. Ecological research using deep-learning-based object recognition technology includes various research purposes such as identifying, detecting, and identifying species of wild animals, and identification of the location of poachers in real-time. These advances in the application of AI technology can enable efficient management of endangered wildlife, animal detection in various environments, and real-time analysis of image information collected by unmanned aerial vehicles. Furthermore, the need for school education and social use on biodiversity and environmental issues using AI is raised. School education and citizen science related to ecological activities using AI technology can enhance environmental awareness, and strengthen more knowledge and problem-solving skills in science and research processes. Under these prospects, in this paper, we compare the results of our early 2013 study, which automatically identified African cichlid fish species using photographic data of them, with the results of reanalysis by CNN deep learning method. By using PyTorch and PyTorch Lightning frameworks, we achieve an accuracy of 82.54% and an F1-score of 0.77 with minimal programming and data preprocessing effort. This is a significant improvement over the previous our machine learning methods, which required heavy feature engineering costs and had 78% accuracy.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.2
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• pp.271-277
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• 2022

PBFT (Practical Byzantine Fault Tolerant) is a consensus algorithm that can achieve consensus by resolving unintentional and intentional faults in a distributed network environment and can guarantee high performance and absolute finality. However, as the size of the network increases, the network load also increases due to message broadcasting that repeatedly occurs during the consensus process. Due to the characteristics of the PBFT algorithm, it is suitable for small/private blockchain, but there is a limit to its application to large/public blockchain. Because PBFT affects the performance of blockchain networks, the industry should test whether PBFT is suitable for products and services, and academia needs a unified evaluation metric and technology for PBFT performance improvement research. In this paper, quantitative evaluation metrics and evaluation frameworks that can evaluate PBFT family consensus algorithms are studied. In addition, the throughput, latency, and fault tolerance of PBFT are evaluated using the proposed PBFT evaluation framework.

• International Journal of Computer Science & Network Security
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• v.23 no.5
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• pp.21-32
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• 2023

The design of complex man-made systems mostly involves a conceptual modeling phase; therefore, it is important to ensure an appropriate analysis method for these models. A key concept for such analysis is the development of a diagramming technique (e.g., UML) because diagrams can describe entities and processes and emphasize important aspects of the systems being described. The analysis also includes an examination of ontological concepts such as states and events, which are used as a basis for the modeling process. Studying fundamental concepts allows us to understand more deeply the relationship between these concepts and modeling frameworks. In this paper, we critically analyze the classic definition of a state utilizing the Thinging machine (TM) model. States in state machine diagrams are considered the appropriate basis for modeling system behavioral aspects. Despite its wide application in hardware design, the integration of a state machine model into a software system's modeling requirements increased the difficulty of graphical representation (e.g., integration between structural and behavioral diagrams). To understand such a problem, in this paper, we project (create an equivalent representation of) states in TM machines. As a case study, we re-modeled a state machine of an assembly line system in a TM. Additionally, we added possible triggers (transitions) of the given states to the TM representation. The outcome is a complicated picture of assembly line behavior. Therefore, as an alternative solution, we re-modeled the assembly line based solely on the TM. This new model presents a clear contrast between state-based modeling of assembly line behavior and the TM approach. The TM modeling seems more systematic than its counterpart, the state machine, and its notions are well defined. In a TM, states are just compound events. A model of a more complex system than the one in the assembly line has strengthened such a conclusion.

• Asia pacific journal of information systems
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• v.34 no.1
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• pp.150-190
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• 2024

This article proposes a framework to elucidate the structural dynamics of the generative AI ecosystem. It also outlines the practical application of this proposed framework through illustrative policies, with a specific emphasis on the development of the Korean generative AI ecosystem and its implications of platform strategies at AI platform-squared. We propose a comprehensive classification scheme within generative AI ecosystems, including app builders, technology partners, app stores, foundational AI models operating as operating systems, cloud services, and chip manufacturers. The market competitiveness for both app builders and technology partners will be highly contingent on their ability to effectively navigate the customer decision journey (CDJ) while offering localized services that fill the gaps left by foundational models. The strategically important platform of platforms in the generative AI ecosystem (i.e., AI platform-squared) is constituted by app stores, foundational AIs as operating systems, and cloud services. A few companies, primarily in the U.S. and China, are projected to dominate this AI platform squared, and consequently, they are likely to become the primary targets of non-market strategies by diverse governments and communities. Korea still has chances in AI platform-squared, but the window of opportunities is narrowing. A cautious approach is necessary when considering potential regulations for domestic large AI models and platforms. Hastily importing foreign regulatory frameworks and non-market strategies, such as those from Europe, could overlook the essential hierarchical structure that our framework underscores. Our study suggests a clear strategic pathway for Korea to emerge as a generative AI powerhouse. As one of the few countries boasting significant companies within the foundational AI models (which need to collaborate with each other) and chip manufacturing sectors, it is vital for Korea to leverage its unique position and strategically penetrate the platform-squared segment-app stores, operating systems, and cloud services. Given the potential network effects and winner-takes-all dynamics in AI platform-squared, this endeavor is of immediate urgency. To facilitate this transition, it is recommended that the government implement promotional policies that strategically nurture these AI platform-squared, rather than restrict them through regulations and stakeholder pressures.