• Journal of Environmental Impact Assessment
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• v.6 no.2
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• pp.103-112
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• 1997

The object of this study is the introduction and the application of Ecological Footprint(EF) for sustainability of regional people activities. It is a tool for the evaluation of specific projects through various lifestyles or consumption to area of broad policy and budgets. But in Korea there is no assessment for consumption level of human activities by EF. Therefore this study try to analyse ecologically productive land for human activities of Cheju-island in order to assess the sustainability in Cheju and compares with another industrized countries. We analyze the human activities level of Cheju-island then the EF is about 0.9(ha/cap). This value is not more than another countries like Canada and United States. EF assists in choosing technologies, policies and Life Cycle Assessment(LCA) which can perform a certain task with the smallest ecological footprint. It will help society to avoid collapse and move towards sustainability and ecological efficiency.

• Journal of Electrical Engineering and Technology
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• v.9 no.6
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• pp.2118-2125
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• 2014

Gait Recognition is a new technique to identify the people by the way they walk. Human gait is a spatio-temporal phenomenon that typifies the motion characteristics of an individual. The proposed method makes a simple but efficient attempt to gait recognition. For each video file, spatial silhouettes of a walker are extracted by an improved background subtraction procedure using Gaussian Mixture Model (GMM). Here GMM is used as a parametric probability density function represented as a weighted sum of Gaussian component densities. Then, the relevant features are extracted from the silhouette tracked from the given video file using the Principal Component Analysis (PCA) method. The Fisher Linear Discriminant Analysis (FLDA) classifier is used in the classification of dimensional reduced image derived by the PCA method for gait recognition. Although gait images can be easily acquired, the gait recognition is affected by clothes, shoes, carrying status and specific physical condition of an individual. To overcome this problem, it is combined with footprint as a multimodal biometric system. The minutiae is extracted from the footprint and then fused with silhouette image using the Discrete Stationary Wavelet Transform (DSWT). The experimental result shows that the efficiency of proposed fusion algorithm works well and attains better result while comparing with other fusion schemes.

• Journal of the Korea Institute of Military Science and Technology
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• v.21 no.4
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• pp.551-561
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• 2018

Footprint is defined as ground area that is projected from the outer edges of the battle space protected by a defence system. This concept can be effectively used for making decisions on site selection of anti missile systems to defend against enemy's ballistic missiles. In this paper, simulations of ballistic missile trajectories based on various launch conditions are performed first and then the footprint is derived with engagement zone set as a boundary condition. Results of the simulation with various relative positions between the defense system and defended asset are also presented. The proposed method, in which the trajectories are generated based on launch point of the ballistic missile, has an advantage of approximating the defended area close to reality. Two applications are introduced in the present paper to describe how the derivation of defended area could be utilized in deployment decision of defense systems.

• Journal of Soil and Groundwater Environment
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• v.20 no.3
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• pp.7-14
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• 2015

In this study, land farming and chemical oxidation of a diesel-contaminated site is compared to evaluate the environmental impact during soil remediation using the Spreadsheet for Environmental Footprint Analysis by U.S. EPA. Each remediation process is divided into four phases, consisting of soil excavation, backfill and transportation (Phase 0), construction of remediation facility (Phase 1), remediation operation (Phase 2), and restoration of site and waste disposal (Phase 3). Environmental footprints, such as material use, energy consumption, air emission, water use and waste generation, are analyzed to find the way to minimize the environmental impact. In material use and waste generation, land farming has more environmental effect than chemical oxidation due to the concrete and backfill material used to construct land farming facility in Phase 1. Also, in energy use, land farming use about six times more energy than chemical oxidation because of cement production and fuel use of heavy machinery, such as backhoe and truck. However, carbon dioxide, commonly considered as important factor of environmental impact due to global warming effect, is emitted more in chemical oxidation because of hydrogen peroxide production. Water use of chemical oxidation is also 2.1 times higher than land farming.

• Journal of Korea Multimedia Society
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• v.11 no.11
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• pp.1615-1623
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• 2008

This paper proposes methods to classify scanned insect footprints. We propose improved SOM and ART2 algorithms for extracting segments, basic areas for feature extraction, and utilize Trace transform and fuzzy weighted mean methods for extracting feature values for classification of the footprints. In the proposed method, regions are extracted by a morphological method in the beginning, and then improved SOM and ART2 algorithms are utilized to extract segments regardless of kinds of insects. Next, A Trace transform method is used to find feature values suitable for various kinds of deformation of insect footprints. In the Trace transform method, Triple features from reconstructed combination of diverse functions, are used to classify the footprints. In general, it is very difficult to decide automatically whether the extracted footprint segment is meaningful for classification or not. So we use a fuzzy weighted mean method for not excluding uncertain footprint segments because the uncertain footprint segments may be possible candidates for classification. We present experimental results of footprint segment extraction and segment classification by the proposed methods.

• Journal of Korean Society of Water and Wastewater
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• v.25 no.5
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• pp.691-697
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• 2011

In this study, by using the Water footprint technique, the water consumption by washing machines, which holds higher ranks in using water than any other electric appliances, was analyzed during their life cycle. The life cycle is defined as raw materials production step, manufacturing step, and using step. In raw materials production step, Input materials were researched by using LCI DB(Life Cycle Inventory Database) and the water consumption was calculated with consideration of approximately 65% Input materials which were based weight. In manufacturing step, the water consumption was calculated by the amount of energy used in assembly factories and components subcontractors and emission factor of energy. In using step, referring to guidelines on carbon footprint labeling, the life cycle is applied as 5 years for a washing machine and 218 cycles for annual bounds of usage. The water and power consumption for operating was calculated by referring to posted materials on the manufacture's websites. The water consumption by nation unit was calculated with the result of water consumption by a unit of washing machine. As a result, it shows that water consumption per life cycle s 110,105 kg/unit. The water consumption of each step is 90,495 kg/unit for using, 18,603 kg for raw materials production and 1,006 kg/unit for manufacturing, which apparently shows that the using step consume the most water resource. The water consumption by nation unit is 371,269,584tons in total based on 2006, 83,385,649 tons in both steps of raw material production and manufacturing, and 287,883,935 tons in using step.

• Publications of The Korean Astronomical Society
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• v.30 no.2
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• pp.61-64
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• 2015

The brightness of Io's magnetic footprint, an indicator of electromagnetic interaction at the satellite, appears to be strongly connected to the satellite's distance from the plasma equator. As a result, the brightest footprints were detected when Io is near the interception location between the satellite's orbital plane and the plasma equator. However, volcanic activities on Io show strong correlation with the equatorward shift of Jupiter's main auroral oval, consequently causing the disappearance of Io's footprint. The same conclusion was suggested via the observation of Jupiter's hectometric radio emission, called HOM, which closely corresponds to Jupiter's auroral activity. The plasma environment near the Jovian satellites was found to vary significantly at different observational epochs. The electron density increased by approximately a factor of three from the Voyager epoch (1979) to the Galileo epoch (1995), while the electron density was found to be significantly higher (~ 5 times) in the Cassini epoch (2001). In this current study, the magnetic footprints were clearly brighter ten years ago (from peak brightness in 1998-2001) than the footprints detected in 2007. For volcanic activities on Io in 2007, there are two clear activities in February and late May. The magnetic footprint appeared to be dimmer in March 2007, expected to be the result of volcano activities in Feb 2007. However, the magnetic footprint brightness in June appeared to be slightly brighter than the footprints observed in May. The reason could be the time delay between the brightening of the sodium nebula on approximately May 31st and, a while later, the enhancement of flux tube content peaking on approximately June 5th. On the other hand, Io's magnetic footprints were observed during June 1st - 10th when they may not yet have been affected by the increase in mass outflow due to the increase of plasma density.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.12 no.6
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• pp.1095-1100
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• 2008

In a process of insect foot recognition, footprint segments as basic areas for recognition need to be extracted from scanned insect footprints and appropriate features should be found from the footprint segments in order to discriminate kinds of insects, because the characteristics of the features are important to classify insects. In this paper, we propose methods for automatic footprint segmentation and feature extraction. We use a Trace transform method in order to find out appropriate features from the extracted segments by the above methods. The Trace transform method builds a new type of data structure from the segmented images by functions using parallel trace lines and the new type of data structure has characteristics invariant to translation, rotation and reflection of images. This data structure is converted to Triple features by Diametric and Circus functions, and the Triple features are used for discriminating patterns of insect footprints. In this paper, we show that the Triple features found by the proposed methods are enough distinguishable and appropriate for classifying kinds of insects.

• Korean Journal of Environmental Agriculture
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• v.38 no.3
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• pp.159-165
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• 2019

BACKGROUND: The water footprint (WF) is an indicator of freshwater use that appears not only at direct water use of a consumer or producer, but also at the indirect water use. As an indicator of 'water use', the water footprint includes the green, blue, and grey WF, and differs from the classical measure of 'water withdrawal' because of green and grey WF. This study was conducted to assess and estimate the water footprint of the soybean and Chinese cabbage. METHODS AND RESULTS: APEX model with weather data, soil and water quality data from NAS (National Institute of Agricultural Sciences), and farming data from RDA (Rural Development Administration) was operated for analyzing the WF of the crops. As the result of comparing the yield estimated from APEX with the yield extracted from statistic data of each county, the coefficients of determination were 0.83 for soybean and 0.97 for Chinese cabbage and p-value was statistically significant. The WFs of the soybean and Chinese cabbage at production procedure were 1,985 L/Kg and 58 L/Kg, respectively. This difference may have originated from the cultivation duration. The WF ratios of soybean were 91.1% for green WF and 8.9% for grey WF, but the WF ratios of Chinese cabbage were 41.5% for green WF and 58.5% for grey WF. CONCLUSION: These results mean that the efficiency of water use for soybean is better than that for Chinese cabbage. The results could also be useful as an information to assess environmental impact of water use and agricultural farming on soybean and Chinese cabbage.

• Journal of the Korean Society of Earth Science Education
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• v.14 no.3
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• pp.292-301
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• 2021

This study is a basic research to apply ESD linked to SDGs to pre-service teachers majoring in earth science education. The purpose of this study is to evaluate carbon literacy by analyzing the awareness, attitude and knowledge, subjective norms, and behavioral control of the carbon footprint internalized by pre-service teachers. Pre-service teachers recognize the carbon footprint as their responsibility, but are not willing to pay the cost and accept inconveniences of the actions to reduce carbon footprint. They also support actions to reduce carbon footprint, but do not demand the actions from others. While they have sufficient knowledge about carbon mitigation actions, their conception of causes and effects of global warming is unstable. Pre-service teachers will go out to school sites and teach millions of students about global warming. It is essential to educate these teachers on the economic cost and social responsibility of reducing their carbon footprints. It is also important to find ways to bridge the gap between their thought and action. It is hoped that this study on pre-service teachers' carbon literacy will lead to realizing ESD.