• Journal of Korean Society of Coastal and Ocean Engineers
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• v.28 no.1
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• pp.53-62
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• 2016

Extreme wind speeds at four sites including Mokpo, Gunsan, Incheon and Jeju near the Western Coast have been estimated with a tool of Monte Carlo simulation and typhoon data. Results of sensitivity analysis show that closeness between distance to the eye and the radius to maximum wind is most sensitive. While location angle and pressure deficit are sensitive too, but translation velocity is not. A standard typhoon, which results in extreme wind speeds having various return period, can be constructed by combination of parameter informations of each site. Then, with a numerical modelling of the typhoon, extreme surge heights having the same return period can also be obtained. To be added, by analysing the data which only including those based on navigable semicircle, it is possible to produce a standard typhoon which could result in setting-down of sea level.

• Journal of Environmental Science International
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• v.18 no.6
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• pp.655-665
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• 2009

This study aims to identify the impacts of air quality in the Korean Peninsula according to the China's environmental policies in preparation of the Beijing 2008 Olympic Games. The measurement of emission variations in China, aircraft measurement, and modelling were carried out. The reduction measures in Beijing, China and its emission changes resulted in $30{\sim}65%$ in decrease out of the total emissions within the Beijing region, whereas when it comes to the whole nation of China, the reduction rate was about $4{\sim}9%$. Comparing the concentration of the air pollutants in Seoul and Ganghwa in August 2008 during around the period of Beijing Olympic Games with one in $2004{\sim}2007$ showed that the $SO_2$ concentrations in the past was above 5ppb, while the concentration in the 2008 olympic period was 4ppb and below. The NOx at the Seokmori site in Ganghwa tended to be lower in concentration in 2008 than in between $2004{\sim}2007$. As for $O_3$ and $PM_{2.5}$, the concentration tended to be rather low since August 11. The air current track that showed during the period of aircraft measurement presented to be flowed into Korea through the Northeast part of China and the coast of Bohai Bay, while the concentrations of $SO_2$. NOx, and $O_3$ over the west sea on August 20 and 24 were 0.54 (0.28ppb), 0.86 (1.84ppb), and 54.0 (41.5ppb) respectively, similar or lower than the ones measured in the past in the similar current patterns. The modelling result showed similar patterns to the data of aircraft measurement, in particular in $SO_2$. Overall, the reduction measures in Beijing, China affected directly and indirectly the air quality in the Korean peninsular, but the impact was not significant as it was momentary and limited to the intended area.

• Korean Journal of Remote Sensing
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• v.28 no.1
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• pp.171-180
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• 2012

The field of wildlife habitat conservation research has attracted attention as integrated biodiversity management strategies. Considering the status of the species surveying data and the environmental variables in Korea, the GARP and Maxent models optimized for presence-only data could be one of the most suitable models in habitat modeling. For make sure applicability in the domestic environment we applied the machine learning species distribution model for analyzing habitats of the Korea water deer($Hydropotes$ $inermis$ $argyropus$) in the $Sapgyocheon$ watershed, $Chungcheong$ province. We used the $3^{rd}$ National Natural Environment Survey data and 10 environment variables by literature review for the modelling. Analysis results showed that habitats for the Korea water deer were predicted 16.3%(Maxent) and 27.1%(GARP), respectively. In terms of accuracy(training/test) the Maxent(0.85/0.69) was higher than the GARP(0.65/0.61), and the Spearman's rank correlation coefficient result of the Maxent(${\rho}$=0.71, p<0.01) was higher than the result of GARP(${\rho}$=0.55, p<0.05). However results could be depended on sites and target species, therefore selection of the appropriate model considering on the situation will be important to analyzing habitats.

• Economic and Environmental Geology
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• v.54 no.1
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• pp.69-76
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• 2021

This study is to identify the mineralogical properties of caprock samples from drilling cores of the Pohang basin, which is the research area for the demonstration-scale CO2 storage project in Korea. The interaction of water-rock-gas that can occur due to CO2 injection was identified using geochemical modeling. Results of mineralogical studies, together with petrographic data of caprock and data on the physicochemical parameters of pore water were used for geochemical modeling. Modelling was carried out using the The Geochemist's Workbench 14.0.1 geochemical simulator. Two steps of modeling enabled prediction of immediate changes in the caprocks impacted by the first stage of CO2 injection and the assessment of long-term effects of sequestration. Results of minerlaogical analysis showed that the caprock samples are mainly composed of quartz, K-feldspar, plagioclase and a small amount of pyrite, calcite, kaolinite and montmollonite. After the injection of carbon dioxide, the porosity of the caprock increased due to the dissolution of calcite, and dawsonite and chalcedony were precipitated as a result of the dissolution of albite and k-feldspar. In the second step after the injection was completed, the precipitation of dawsonite and chalcedony occurred as a result of dissolution of calcite and albite, and the pH was increased due to this reaction. Results of these studies are expected to be used as data to quantitatively evaluate the efficiency of mineral trapping capture in long-term storage of carbon dioxide.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.22 no.6
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• pp.32-48
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• 2023

Autonomous driving technology is shaping the future of personalized travel, encouraging personalized travel, and traffic impact could be influenced by individualized travel behavior during the transition of driving entity from human to machine. In order to evaluate traffic impact, it is necessary to estimate the total number of trips based on an understanding of individual travel characteristics. The Activity-based model(ABM), which allows for the reflection of individual travel characteristics, deals with all travel sequences of an individual. Understanding the relationship between travel and travel must be important for assessing traffic impact using ABM. However, the ABM has a limitation in the data hunger model. It is difficult to adjust in the actual demand forecasting. Therefore, we utilized a Tour-based model that can explain the relationship between travels based on household travel survey data instead. After that, vehicle registration and population data were used for correction. The result showed that, compared to the KTDB one, the traffic generation exhibited a 13% increase in total trips and approximately 9% reduction in working trips, valid within an acceptable margin of error. As a result, it can be used as a generation correction method based on Tour, which can reflect individual travel characteristics, prior to building an activity-based model to predict demand due to the introduction of autonomous vehicles in terms of road operation, which is the ultimate goal of this study.

• Journal of the Korean Institute of Traditional Landscape Architecture
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• v.36 no.4
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• pp.105-112
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• 2018

This study aims to apply 3D scanning technology to the field of landscape planning design. Through this, 3D scans were conducted on Soswaewon Garden and Seongrakwon Gardens to find directions for traditional landscape planning and designs. The results as follows. First, the actual measurement of the traditional garden through a 3D scan confirmed that a precise three-dimensional modeling of ${\pm}3-5mm$ error was constructed through the merging of coordinate values based on point data acquired at each observation point and postprocessing. Second, as a result of the 3D survey, the Soswaewon Garden obtained survey data on Jewoldang House, Gwangpunggak Pavilion, the surrounding wall, stone axis, and Aeyangdan wall, while the Seongnakwon Garden obtained survey data on the topography, rocks and waterways around the Yeongbyeokji pond area. The above data have the advantage of being able to monitor the changing appearance of the garden. Third, spatial information developed through 3D scans could be developed with a three-dimensional drawing preparation and inspection tool that included precise real-world data, and this process ensured the economic feasibility of time and manpower in the actual survey and investigation of landscaping space. In addition, modelling with a three-dimensional 1:1 scale is expected to be highly efficient in that reliable spatial data can be maintained and reprocessed to a specific size depending on the size of the design. In addition, from a long-term perspective, the deployment of 3D scan data is easy to predict and simulate changes in traditional landscaping space over time.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.18 no.3
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• pp.141-156
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• 2023

Due to the unprecedented worldwide pandemic of the new Covid-19 infection, business trends of companies have changed significantly. Therefore, it is strongly required to monitor the rapid changes of innovation trends to design and plan future businesses. Since the pandemic, many studies have attempted to analyze business changes, but they are limited to specific industries and are insufficient in terms of data objectivity. In response, this study aims to analyze business trends after Covid-19 using Crunchbase, a global startup data. The data is collected and preprocessed every two years from 2018 to 2021 to compare the business trends. To capture the major trends, a network analysis is conducted for the industry groups and industry information based on the co-occurrence. To analyze the minor trends, LDA-based topic modelling and word2vec-based clustering is used. As a result, e-commerce, education, delivery, game and entertainment industries are promising based on their technological advances, showing extension and diversification of industry boundaries as well as digitalization and servitization of business contents. This study is expected to help venture capitalists and entrepreneurs to understand the rapid changes under the impact of Covid-19 and to make right decisions for the future.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.45 no.5
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• pp.192-200
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• 2008

Multimodal biometrics is a method for personal authentication and verification using more than two types of biometrics data. RBF based score-level fusion uses pattern recognition algorithm for multimodal biometrics, seeking the optimal decision boundary to classify score feature vectors each of which consists of matching scores obtained from several unimodal biometrics system for each sample. In this case, all matching scores are assumed to have the same reliability. However, in recent research it is reported that the quality of input sample affects the result of biometrics. Currently the matching scores having low reliability caused by low quality of samples are not currently considered for pattern recognition modelling in multimodal biometrics. To solve this problem, in this paper, we proposed the RBF based score-level fusion approach which employs quality information of input biometrics data to adjust decision boundary. As a result the proposed method with Qualify information showed better recognition performance than both the unimodal biometrics and the usual RBF based score-level fusion without using quality information.

• Journal of Contemporary Eastern Asia
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• v.13 no.1
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• pp.5-18
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• 2014

This exploratory study investigates the use of a computational knowledge engine (WolframAlpha) and social networking sites (Gmail, Yahoo and Facebook) by 200 students at De La Salle-College of Saint Benilde, their "friends" and their "friends of friends" during the 2009 through 2013 school years, and how this appears to have added value in knowledge generation. The primary aim is to identify what enhances productiveness in knowledge generation in Philippine Tertiary Education. The phenomenological approach is used, therefore there are no specific research questions or hypotheses proposed in this paper. Considering that knowledge generation is a complex phenomenon, a stochastic modelling approach is also used for the investigation that was developed specifically to study un-deterministic complex systems. A list of salient features for knowledge generation is presented as a result. In addition to these features, various problem types are identified from literature. These are then integrated to provide a proposed framework of inclusive (friendly) and innovative social networks, for knowledge generation in Philippine tertiary education. Such a framework is necessarily multidisciplinary and useful for problem-solving in a globalized and pluralist reality. The implementation of this framework is illustrated in the three parts of the study: Part 1: Online lessons, discussions, and examinations in General Psychology, Introduction to Sociology, and Life and Works of Jose Rizal, for the author's students in De La Salle-College of Saint Benilde; Part 2: Facebook Report analytics of students and teachers, their friends and their friends of friends via WolframAlpha; and Part 3: Social Network Analysis of the people and groups influencing the courses' scope-and-sequence in the new General Education Curriculum for Tertiary Schools and Institutions in the Philippines.

• Proceedings of the Korean Society for Agricultural Machinery Conference
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• 2017.04a
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• pp.135-135
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• 2017

Greenhouse have been developed to provide the plants with good environmental conditions for cultivation crop, two major factors of which are the inside air temperature and humidity. The inside temperature are influenced by the heating systems, ventilators and for systems among others, which in turn are geverned by some type of controller. Likewise, humidity environment is the result of complex mass exchanges between the inside air and the several elements of the greenhouse and the outside boundaries. Most of the existing models are based on the energy balance method and heat balance equation for modelling the heat and mass fluxes and generating dynamic elements. However, greenhouse are classified as complex system, and need to make a sophisticated modeling. Furthermore, there is a difficulty in using classical control methods for complex process system due to the process are non linear and multi-output(MIMO) systems. In order to predict the time evolution of conditions in certain greenhouse as a function, we present here to use of recurrent neural networks(RNN) which has been used to implement the direct dynamics of the inside temperature and inside humidity of greenhouse. For the training, we used algorithm of a backpropagation Through Time (BPTT). Because the environmental parameters are shared by all time steps in the network, the gradient at each output depends not only on the calculations of the current time step, but also the previous time steps. The training data was emulated to 13 input variables during March 1 to 7, and the model was tested with database file of March 8. The RMSE of results of the temperature modeling was $0.976^{\circ}C$, and the RMSE of humidity simulation was 4.11%, which will be given to prove the performance of RNN in prediction of the greenhouse environment.