• Journal of Navigation and Port Research
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• v.44 no.4
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• pp.305-311
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• 2020

Rising sea levels along the coast from global warming causes the increase of wave energy along the coast. This rise in sea levels results in relatively deep water levels, which would incur the loss of sand that had not occurred in the past from erosion in coastal areas. Generally, it has been challenging to protect against coastal erosion, and the slope, cross-sectional shape, and materials are selected for the site conditions depending on the change in external forces. However, the application of counter measures based on insufficient understanding of the phenomenon is causing various damage, indicating the need for technological development and converging technologies to improve credibility. In this study, we developed eco-friendly permeable biopolymer concrete blocks to control the coastal erosion by using the Bio-Coast, an effective porous structure that mitigates the destructive erosion caused by the rising sea levels. The hexagonal design of Bio-Coast was derived from the honeycomb, columnar joints, and clover, which are durable and stable structures in nature, and the design was changed to apply bumps on the Bio-Coast filling in the form of a clover to reduce wave overtopping and run-up. Applying the field condition of beaches on the east coast of Korea, the block weight and size were decided and the prototype blocks were manufactured and are ready for field placement. In particular, it is intended to protect coastal areas from destructive erosion by natural and artificial external forces, and to extend the design to river,s lakes, and natural walking trails, to improve the efficiency of quality control and process control through the use of blocks.

• Korean Journal of Construction Engineering and Management
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• v.16 no.1
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• pp.74-81
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• 2015

As one of urban infrastructure system, the electricity substation is critical for urban life and industrial activity as the electricity demands get higher than ever. However the substation is generally regarded as unpleasant or dangerous facility, which finally results in the continuous opposition movement by resident due to the belief of unidentified negative effect in apartment prices. Accordingly, as the scientifically objective and quantitative analysis is required to solve the social conflict, this study intends to examine the variation affected by urban infrastructure system, expecially for substation. After the independent variable defining the price of apartment and the dependent variable, which is apartment price, are identified and their spatial data has been filed, the forecasting model has been developed through the hedonic price function as well as artificial neural networks system. The research finding indicated that the spatial range affected by substation is not notable and the range of some case was applicable for less than 600m. It is expected that these research findings can be applied for establishing the one of solid cases for the analysis of economical effect to local housing market by the urban infrastructure system.

• Korean Journal of Ecology and Environment
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• v.46 no.2
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• pp.310-318
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• 2013

In territorial ecosystem, soil has stored considerable amount of carbon, and it is vulnerable to weakness release much of the carbon to atmosphere. In this study, we have been effort realization and discussion to the error between inter-instruments and measurement methods, time and special variations, gap filling and separation from each source included in soil respiration, used to collect soil respiration data in various ecosystems in Korea. In conclusion, it have to collect calibration data throughout comparison test between methods and instruments because accumulated data from past and accumulating data in present did not calibrated. In predicting change of soil carbon dynamic using the model method, it needs important data such as longterm and short-term data, artificial handling data of major factor, data from various ecosystem, soil texture, soil depth etc. In company with, we should collect highly qualified data through deep consideration of present problems.

• Journal of Korean Tunnelling and Underground Space Association
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• v.22 no.4
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• pp.337-346
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• 2020

Traffic jam and congestion in urban areas has caused the need to improve the utility of underground space. In response, research on underground structures is increasingly being conducted. Notably, a double-deck tunnel is one of the most widely used of all those underground structures. This double-deck tunnel is separated by the middle slab into the upper and lower roadways. Both vehicle load and earthquake load cause the middle slab to exhibit dynamic behavior. Earthquake-related response characteristics, in particular, are highly complex and difficult to interpret in a theoretical context, and thus experimental research is required. The aim of the present study is to assess the stability of a double-deck tunnel's middle slab of the Collapse Prevention Level and Seismic Category 1 with regard to the presence of vibration-damping Rubber Bearings. In vibration table tests, the ratio of similitude was set to 1/4. Linings and vibrating platforms were fixed during scaled model tests to represent the integrated behavior of the ground and the applied models. In doing so, it was possible to minimize relative behavior. The standard TBM cross-section for the virtual double-deck tunnel was selected as a test subject. The level of ground motion exerted on the bedrock was set to 0.154 g (artificial seismic wave, Collapse Prevention Level and Seismic Category 1). A seismic wave with the maximum acceleration of 0.154 g was applied to the vibration table input (bedrock) to analyze resultant amplification in the models. As a result, the seismic stability of the middle slab was evaluated and analyzed with respect to the presence of vibration-damping rubber bearings. It was confirmed that the presence of vibration-damping rubber bearings improved its earthquake acceleration damping performance by up to 40%.

• Journal of Digital Convergence
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• v.15 no.8
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• pp.333-340
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• 2017

Timelapse is an imaging technique that captures motion at regular intervals and then projects it at normal speed. We looked at Timelapse advertising images of global brands and presented a model for analyzing components and expression methods of Timelapse, a new image technique. In previous research, literature research, Internet data survey, and YouTube data were investigated. Continuous photography has been developed as an imaging technique, and we have examined the current production status applied to domestic and foreign documentary, domestic and foreign drama, film, and advertisement. In 2015-2016, I will analyze the techniques of iPhones (2016), Ralph Lauren Polo Ads (2015), and Canon EOS (2013) videos that use Timelapse techniques in their recent advertisements. The results show that the Timelapse component is a static element, the static motif is mainly an artificial structure, the place is outdoor, the color is taken at a time showing the characteristics of the place, and the layout is all centered. The dynamic motif is a moving object. The dynamic line consists of a story based on the object. The time is about 11-15 seconds, the longest is about 1 minute and 30 seconds, and the editing is mainly focused on the product with the brand logo emphasized. In conclusion, it is the role of the image to pay attention to the advertisement and catch the eye. In order to motivate the buyer's mind, it is necessary to direct and edit such as Timelapse, which stimulates the emotions inherent in the mind and stimulates the non-verbal symbols. Future research is likely to reveal various attempts at temporal editing of images.

• 한국지구물리탐사학회:학술대회논문집
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• 2004.08a
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• pp.25-48
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• 2004

Structures show the phehomena of deformation and lowering of function with time-lapse by artificial environments and changes of geotechnical conditions or accumulation of initial deformation elements. This study aims the structural assessment of cultural property, Chum-Sung-Dae, located in Kyeongju city, Korea. It was built about 1,300 years ago, and has undergone deformation and ground-subsidence with time-lapse. Non-destructive evaluation techniques were applied to the Chum-Sung-Dae, to protect it from survey Because of this reason, 3D precise laser scanning surveying system was applied to measure the exact size of Chum-Sung-Dae, displacement and declining angles. Geophysical exploration also was applied to study the subsurface distribution of geotechnical parameters or physical properties. Natural frequencies were measured from real and model of Chum-Sung-Dae to study the dynamic characteristics of vibration and/or earthquake load and stiffness of structures.

• Science of Emotion and Sensibility
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• v.13 no.1
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• pp.235-242
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• 2010

Emotion science is one of the rapidly expanding engineering/scientific disciplines which has a major impact on human society. Such growing interests in emotion science and engineering owe the recent trend that various academic fields are being merged. In this paper we review the recent techniques in the measuring the emotion related elements and applications which include animal model system to investigate the neural network and behaviour, artificial nose/neuronal chip for in-depth understanding of sensing the outer stimuli, metabolic controlling using emotional stimulant such as sounds. In particular, microfabrication techniques made it possible to construct nano/micron scale sensing parts/chips to accommodate the olfactory cells and neuron cells and gave us a new opportunities to investigate the emotion precisely. Recent developments in the measurement techniques will be able to help combine the social sciences and natural sciences, and consequently expand the scope of studies.

• Journal of the Korean Institute of Intelligent Systems
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• v.24 no.2
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• pp.173-178
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• 2014

In this study, we introduce ASM-based face recognition classifier and its design methodology with the aid of 2-dimensional 2-directional hybird preprocessing algorithm. Since the image of face recognition is easily affected by external environments, ASM(active shape model) as image preprocessing algorithm is used to resolve such problem. In particular, ASM is used widely for the purpose of feature extraction for human face. After extracting face image area by using ASM, the dimensionality of the extracted face image data is reduced by using $(2D)^2$hybrid preprocessing algorithm based on LDA and PCA. Face image data through preprocessing algorithm is used as input data for the design of the proposed polynomials based radial basis function neural network. Unlike as the case in existing neural networks, the proposed pattern classifier has the characteristics of a robust neural network and it is also superior from the view point of predictive ability as well as ability to resolve the problem of multi-dimensionality. The essential design parameters (the number of row eigenvectors, column eigenvectors, and clusters, and fuzzification coefficient) of the classifier are optimized by means of ABC(artificial bee colony) algorithm. The performance of the proposed classifier is quantified through yale and AT&T dataset widely used in the face recognition.

• Journal of Wetlands Research
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• v.19 no.2
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• pp.202-210
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• 2017

Shear stress is one of the most important mechanical factors used in various fields and is important for the design of artificial channels. Current shear stresses have been used in the past, but there are factors that are difficult to actually measure or calculate, such as bed shear stress and energy slope in the equation used. In particular, the energy slope is a very difficult factor to estimate, and it is difficult to estimate the slope and flow velocity of the boundary layer although the energy slope can be used to obtain the shear stress distribution. In addition, the bed shear stress among the shear stress distribution is very difficult to measure directly, and the research is somewhat slower than the velocity. In this study, we have studied the simple calculation of the average flow velocity and the shear stress distribution using entropy M without reflecting the energy gradient, and we used existing laboratory data to demonstrate the utility of the applied equation. The stress distribution in the graphs was comparatively analyzed. In the case of the uniform flow and the non-uniform flow, the correlation coefficient was almost identical to 0.930-0.998.

• Journal of KIISE
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• v.43 no.10
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• pp.1085-1093
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• 2016

Community-based Question Answering system is a system which provides answers for each question from the documents uploaded on web communities. In order to enhance the capacity of question analysis, former methods have developed specific rules suitable for a target region or have applied machine learning to partial processes. However, these methods incur an excessive cost for expanding fields or lead to cases in which system is overfitted for a specific field. This paper proposes a multiple machine learning method which automates the overall process by adapting appropriate machine learning in each procedure for efficient processing of community-based Question Answering system. This system can be divided into question analysis part and answer selection part. The question analysis part consists of the question focus extractor, which analyzes the focused phrases in questions and uses conditional random fields, and the question type classifier, which classifies topics of questions and uses support vector machine. In the answer selection part, the we trains weights that are used by the similarity estimation models through an artificial neural network. Also these are a number of cases in which the results of morphological analysis are not reliable for the data uploaded on web communities. Therefore, we suggest a method that minimizes the impact of morphological analysis by using character features in the stage of question analysis. The proposed system outperforms the former system by showing a Mean Average Precision criteria of 0.765 and R-Precision criteria of 0.872.