• Resources Recycling
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• v.29 no.6
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• pp.15-26
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• 2020

In recent years, there is an increasing interest in environmental friendly treatment of waste-plastics in terms of the generation of microplastics. Accordingly, the recycling of waste-plastics is very important because it provides advantages of volume reduction, mitigation of carbon dioxide emission, and reproduction of value-added products. In particular, in order to recycle the eco-friendly waste-plastics, it is necessary to use a physical separation methods, and among them, flotation separation, which can separate material (i.e., polymer component) in waste-plastics is well known as a very effective separation method in terms of material recycle. Therefore, in this review, the research trend of flotation separation for effective separation of mixture waste-plastics was investigated. In addition, through the reported research results, approaches to use as new functional materials from polymers, which are raw materials for waste-plastics, are summarized.

• Journal of Korean Society of Forest Science
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• v.100 no.3
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• pp.315-326
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• 2011

In recent years, domestic and international interests focus on climate change, and importance of forest as carbon sink have been also increased. Particularly REDD+ mechanism expanded from REDD (Reduced Emissions from Deforestation and Degradation) is expected to perform a new mechanism for reducing greenhouse gas in post 2012. To conduct this mechanism, countries which try to get a carbon credit have to certify effectiveness of their activities by MRV (Measuring, Reporting and Verification) system. This study analyzed the approaches for detecting land cover change and estimating carbon stock by remote sensing technology which is considered as the effective method to develop MRV system. The most appropriate remote sensing for detection of land cover change is optical medium resolution sensors and satellite SAR (Synthetic Aperture Radar) according to cost efficiency and uncertainty assessment. In case of estimating carbon stock, integration of low uncertainty techniques, airborne LiDAR (Light Detection and Ranging), SAR, and cost efficient techniques, optical medium resolution sensors and satellite SAR, could be more appropriate. However, due to absence of certificate authority, guideline, and standard of uncertainty, we should pay continuously our attention on international information flow and establish appropriate methods. Moreover, to apply monitoring system to developing countries, close collaboration and monitoring method reflected characteristics of each countries should be considered.

• The Journal of Korean Philosophical History
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• no.39
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• pp.53-83
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• 2013

This paper aims to examine how issues related to the heaven-human relation (or nature-culture relation) affected Joseon intellectuals in the eighteenth century by considering Huang Yun Seok as a reference. As a significant indicator, the heaven-human relation issue has traditionally been a critical theme in the history of Confucianism. Since Huang Yun Seok accepted Western Learning based on Zhuxi Learning, he is a good example for examining this issue. Huang's ideas didn't depart too much from Confucianism, but he naturally became interested in Western Learning because of the enthusiastic admiration he had of Ancient Learning since he was a child. Principle-Number was consistent with Ancient Learning and Western Learning, and this was somewhat different from the original notion of numerology. It was used for understanding and explaining astronomical phenomenon. In understanding astronomical phenomenon, Huang used both fact-determined and value-centered approaches. Western astronomy allowed him to make an advance in terms of fact-determined approach while the value-centered approach gave him a portentological perspective on astronomical variation such as solar and lunar eclipses. This indicates one of the ways to keep Zhuxi Learning's identity itself amidst an inflow of new learnings.

• The Southeast Asian review
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• v.28 no.2
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• pp.47-84
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• 2018

Domestic debates on 'international development' has hitherto been rather more focused on the narrow topic of Official Development Assistance (ODA) - therefore, practical and practice-oriented enquiries for the former's effective implementation have dominated the field as a result. However, such lack of foundational debates on 'development' has rendered the field inept to respond to the rapidly changing development landscape since the new millennium both globally and in Southeast Asia. With this particular problematique in mind, the paper argues for the utility of critical Southeast Asian studies in enriching theoretical debates in Korea's international development studies. In doing so, we analysed the trend of academic research published since 2000, of which theme concern international development with a specific geographical focus on Southeast Asia. The result shows that such publication and the thematic issues have witnessed rapid quantitative growth since 2007 - while the nature of the publications still clearly remained practical and practice-oriented for effective execution of ODA. We therefore propose the critical Southeast Asian studies to overcome the problematique above by emphasising more inter-/multi-disciplinary approaches that challenge the hegemonic paradigm in the field.

• Journal of Wetlands Research
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• v.23 no.2
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• pp.122-132
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• 2021

We reviewed the methods employed in Korean tidal flat surveys to measure the local abundance of the endangered wildlife and marine protected species, the fiddler crab, Austruca lactea. A complete census for infinite population is impossible even in a limited habitat within a tidal flat, and density estimates from samples strongly vary due to diverse biological and ecological factors. The habitat boundaries and areas shift with periodicities or rhythmic activities of organisms as well as measurement errors. Hence the local abundance calculated from density and habitat areas should be regarded as transient. This conjecture was valid based on the spatio-temporal variations of the density averages, standard error ranges, and spatial distribution of the crab, A. lactea observed for 3 years (2015-2017) in Songdo tidal flat in Incheon. We proposed the potential habitat areas using the occurrence probability of 50% from logistic regression model, reflecting the importance of habitat conservation value as an alternative to local abundance. The spatial shape of potential habitat predicted from a generalized model would remain constant over time unless the species' critical environmental conditions change rapidly. The species-specific model is expected to be used for the introduction of desired species in future habitat restoration/creation projects.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.16 no.3
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• pp.73-86
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• 2021

The primary purpose of this paper is to explore the advanced models that predict entrepreneurial innovativeness most accurately. For the first time in the field of entrepreneurship research, it presents a model that predicts entrepreneurial innovativeness based on machine learning corresponding to data scientific approaches. It uses 22,099 the Global Entrepreneurship Monitor (GEM) data from 62 countries to build predictive models. Based on the data set consisting of 27 explanatory variables, it builds predictive models that are traditional statistical methods such as multiple regression analysis and machine learning models such as regression tree, random forest, XG boost, and artificial neural networks. Then, it compares the performance of each model. It uses indicators such as root mean square error (RMSE), mean analysis error (MAE) and correlation to evaluate the performance of the model. The analysis of result is that all five machine learning models perform better than traditional methods, while the best predictive performance model was XG boost. In predicting it through XG boost, the variables with high contribution are entrepreneurial opportunities and cross-term variables of market expansion, which indicates that the type of entrepreneur who wants to acquire opportunities in new markets exhibits high innovativeness.

• KIPS Transactions on Computer and Communication Systems
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• v.9 no.12
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• pp.291-306
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• 2020

Nowadays, Data-Network-AI (DNA)-based intelligent services and applications have become a reality to provide a new dimension of services that improve the quality of life and productivity of businesses. Artificial intelligence (AI) can enhance the value of IoT data (data collected by IoT devices). The internet of things (IoT) promotes the learning and intelligence capability of AI. To extract insights from massive volume IoT data in real-time using deep learning, processing capability needs to happen in the IoT end devices where data is generated. However, deep learning requires a significant number of computational resources that may not be available at the IoT end devices. Such problems have been addressed by transporting bulks of data from the IoT end devices to the cloud datacenters for processing. But transferring IoT big data to the cloud incurs prohibitively high transmission delay and privacy issues which are a major concern. Edge computing, where distributed computing nodes are placed close to the IoT end devices, is a viable solution to meet the high computation and low-latency requirements and to preserve the privacy of users. This paper provides a comprehensive review of the current state of leveraging deep learning within edge computing to unleash the potential of IoT big data generated from IoT end devices. We believe that the revision will have a contribution to the development of DNA-based intelligent services and applications. It describes the different distributed training and inference architectures of deep learning models across multiple nodes of the edge computing platform. It also provides the different privacy-preserving approaches of deep learning on the edge computing environment and the various application domains where deep learning on the network edge can be useful. Finally, it discusses open issues and challenges leveraging deep learning within edge computing.

• Korean Chemical Engineering Research
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• v.60 no.2
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• pp.300-307
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• 2022

Time-resolved serial femtosecond crystallography (TR-SFX) is a powerful technique for determining temporal variations in the structural properties of biomacromolecules on ultra-short time scales without causing structure damage by employing femtosecond X-ray laser pulses generated by an X-ray free electron laser (XFEL). The mixing rate of reactants and biomolecule samples, as well as the hit rate between crystal samples and x-ray pulses, are critical factors determining TR-SFX performance, such as accurate image acquisition and efficient sample consumption. We here develop two distinct sample delivery systems that enable ultra-fast mixing and on-demand droplet injecting via pneumatic application with a square pulse signal. The first strategy relies on inertial mixing, which is caused by the high-speed collision and subsequent coalescence of droplets ejected through a double nozzle, while the second relies on on-demand pneumatic jetting embedded with a 3D-printed micromixer. First, the colliding behaviors of the droplets ejected through the double nozzle, as well as the inertial mixing within the coalesced droplets, are investigated experimentally and numerically. The mixing performance of the pneumatic jetting system with an integrated micromixer is then evaluated by using similar approaches. The sample delivery system devised in this work is very valuable for three-dimensional biomolecular structure analysis, which is critical for elucidating the mechanisms by which certain proteins cause disease, as well as searching for antibody drugs and new drug candidates.

• Journal of Korea Port Economic Association
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• v.37 no.4
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• pp.13-31
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• 2021

Since the signing of the Korea-Europe Free Trade Agreement, the volume of trade transactions between South Korea and Europe has increased. The traditional single-mode transport system has been transformed into an intermodal transport system using two or more modes of transport. In addition, the conventional sea and air transport routes have been restricted, leading to a decline in Korean exports to Europe, and the rail transport mode is becoming mainstream in the market due to the influence of COVID-19. This paper focuses on the China-Railway Express to explore a new intermodal transport route from Korea to Europe. First, the fuzzy analytic hierarchy process (AHP) is used to evaluate the factor weights when selecting intermodal transport routes from Korea to Europe. Then, the TOPSIS (Technique for Order of Preference by Similarity to Ideal Solution) method is used to rank three alternatives. The results show that among the four factors (total cost, total time, transportation capability, and service reliability), the total cost is the most significant factor, followed by the total time, service reliability, and transportation capability. Furthermore, the alternative route 1 (Incheon-Dalian-Manchuria-Hamburg) is preferred.

• Fisheries and Aquatic Sciences
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• v.25 no.9
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• pp.473-488
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• 2022

To have a better understanding of the impact of the PETRONAS oil and gas platform on commercial fisheries activities, Universiti Malaysia Terengganu (UMT) examined two approaches which are data collection from satellite and data collection from fishermen and anglers. By profiling the anglers who utilize reefed oil and gas structures for fishing, it can determine if the design and location of the reef platforms will benefit or negatively impacts those anglers and fisherman. Furthermore, this assessment will be contributing to the knowledge regarding the value of offshore oil and gas platforms as fisheries resources. Collectively, the apparent fishing activity data included, combined with the findings in the reefing viability index will help to inform PETRONAS's future decommissioning decisions and may help determine if the design and proposed locations for future rigs-to-reefs candidates would benefit commercial fishing groups, further qualifying them as appropriate artificial reef candidates. The method applied in this study is approaching by using a data satellite known as Google's Global Fishing Watch technology, which is one of the applications to measure commercial fishing efforts around the globe. The apparent commercial fishing effort around the selected twelve PETRONAS platforms was analyzed from January 2012 to December 2018. Using the data collection from fishermen which is the total estimation of commercial fish value cost (in Malaysia ringgit, MYR [RM]) in Peninsular Malaysia Asset, Sabah Asset, and Sarawak Operation region. The data were extracted every month from 2016 to 2018 from the National Oceanic and Atmospheric Administration database. Most of the selected platforms that show a high frequency of vessels around the year are platform KP-A, platform BG-A and platform PL-B. The estimated values of commercial fishes varied between platforms, with ranged from RM 10,209.92 to RM 89,023.78. Thus, platforms with high commercial fish value are selected for reefing in-situ and will serve multi-purposes and benefit the locals as well as the country. The current study has successfully assessed the potential reefing area of the Malaysian offshore environment with greater representativeness and this paper focused on its potential as a new fishing ground.