• Journal of Korean Society of Coastal and Ocean Engineers
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• v.28 no.6
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• pp.319-331
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• 2016

This study explores the signal characteristics for different averaging intervals and defines representative verticies for each observatory by criterion of percent rate and variance. The shorter averaging interval shows the higher frequency variation, though the lower percent rate. In the tidal currents, we could hardly find the differences between 60-minute and 20-minute averaging. The newly defined criterion improves reliability of HF-radar data compared with the present reference which deselects the half by percent rate.

• Journal of Biomedical Engineering Research
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• v.22 no.5
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• pp.439-448
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• 2001

This paper considers the acoustical characteristics of the closing click sounds of the mechanical valves employed in an implantable biventricular assist device (BYAD) and their re1evance to the Physical states of the valved. Bj rk Shiley Convexo Concave tilting disk valve was chosen for the study and acoustic measurement was made for the BYAD operated in a mock circulatory system as well as implanted in an animal (sheep). In the BYAD operated in the mock circulatory system. three different states of the valve were examined, ie. normal. mechanically damaged. pseudo-thrombus attached. Microphone measurement for the BVAD implanted in the animal was carried out for five days at a regular time interval from one day after implantation. Characteristic spectrum of the sound from the valve was estimated using Multiple Signal Classification (MUSIC) in which the optimal order was determined according to Bayesian Information Criterion (BIC) . It was observed that the mechanical damage of the valve resulted in changes of the structure of the acoustic spectrum. In contrast. the thrombus formed on the valve did not change much the basic structure of the spectrum but brought about altering the spectral Peak frequencies and energies. Maximum spectral Peak (MSP) with the greatest energy was seen at 2 kHz for the normal valve and it was shifted to 3 kHz for the calve attaching the Pseudo-thrombus. Unlike the normal valve, strong spectral Peak appeared around 7 kHz in the sound from the valve mechanically damaged. In the case of the BYAD implanted in the animal. as the thrombus grew, acoustic energy was reduced relatively more in the low frequency components (〈 2 kHz) and the frequencies of the 1st, 2nd and 3rd MSP were increased little. The thrombus formation would result in reduction in both the variability of the 1st, 2nd and 3rd MSP and the value of the BIC optimal order.

• Journal of Food Hygiene and Safety
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• v.38 no.4
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• pp.193-201
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• 2023

Antimicrobials in human medicine are classified by The World Health Organization (WHO) into three groups: critically important antimicrobials (CIA), highly important antimicrobials (HIA), and important antimicrobials (IA). CIA are antibiotic classes that satisfy two main criteria: that they are the sole or the only available limited therapeutic option to effectively treat severe bacterial infections in humans (Criterion 1), and infections where bacteria are transmitted to humans from non-human sources or have the potential to acquire resistance genes from non-human sources (Criterion 2). WHO emphasizes the need for cautious and responsible use of the CIA to mitigate risk and safeguard human health. Specific antimicrobials within the CIA with a high priority for management are reclassified as "highest priority critically important antimicrobials (HP-CIA)" and include the 3^rd generation of cephalosporins and the next generation of macrolides, quinolones, glycopeptides, and polymyxins. The CIA list is the scientific basis for risk assessment and risk management policies that warrant using antimicrobials to reduce antimicrobial resistance in several countries. In addition, the CIA list ensures food safety in the food industry, including for the popular food chain companies McDonald's and KFC. The continuous update of the CIA list reflects the advancement in research and emerging future challenges. Thus, active and deliberate evaluation of antimicrobial resistance and the construction of a list that reflects the specific circumstances of a country are essential to safeguarding food security.

• Geophysics and Geophysical Exploration
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• v.13 no.3
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• pp.203-218
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• 2010

The site categorization and corresponding site amplification factors in the current Korean seismic design guideline are based on provisions for the western United States (US), although the site effects resulting in the amplification of earthquake ground motions are directly dependent on the regional and local site characteristic conditions. In these seismic codes, two amplification factors called site coefficients, $F_a$ and $F_v$, for the short-period band and midperiod band, respectively, are listed according to a criterion, mean shear wave velocity ($V_S$) to a depth of 30 m, into five classes composed of A to E. To suggest a site classification system reflecting Korean site conditions, in this study, systematic site characterization was carried out at four regional areas, Gyeongju, Hongsung, Haemi and Sacheon, to obtain the $V_S$ profiles from surface to bedrock in field and the non-linear soil properties in laboratory. The soil deposits in Korea, which were shallower and stiffer than those in the western US, were examined, and thus the site period in Korea was distributed in the low and narrow band comparing with those in western US. Based on the geotechnical characteristic properties obtained in the field and laboratory, various site-specific seismic response analyses were conducted for total 75 sites by adopting both equivalent-linear and non-linear methods. The analysis results showed that the site coefficients specified in the current Korean provision underestimate the ground motion in the short-period range and overestimate in the mid-period range. These differences can be explained by the differences in the local site characteristics including the depth to bedrock between Korea and western US. Based on the analysis results in this study and the prior research results for the Korean peninsula, new site classification system was developed by introducing the site period as representative criterion and the mean $V_S$ to a depth of shallower than 30 m as additional criterion, to reliably determine the ground motions and the corresponding design spectra taking into account the regional site characteristics in Korea.

• Journal of the Korean Institute of Landscape Architecture
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• v.51 no.3
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• pp.70-82
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• 2023

The recent surge of IT and data acquisition is shifting the paradigm in all aspects of life, and these advances are also affecting academic fields. Research topics and methods are being improved through academic exchange and connections. In particular, data-based research methods are employed in various academic fields, including landscape architecture, where continuous research is needed. Therefore, this study aims to investigate the possibility of developing a landscape preference evaluation and prediction model using machine learning, a branch of Artificial Intelligence, reflecting the current situation. To achieve the goal of this study, machine learning techniques were applied to the landscaping field to build a landscape preference evaluation and prediction model to verify the simulation accuracy of the model. For this, wind power facility landscape images, recently attracting attention as a renewable energy source, were selected as the research objects. For analysis, images of the wind power facility landscapes were collected using web crawling techniques, and an analysis dataset was built. Orange version 3.33, a program from the University of Ljubljana was used for machine learning analysis to derive a prediction model with excellent performance. IA model that integrates the evaluation criteria of machine learning and a separate model structure for the evaluation criteria were used to generate a model using kNN, SVM, Random Forest, Logistic Regression, and Neural Network algorithms suitable for machine learning classification models. The performance evaluation of the generated models was conducted to derive the most suitable prediction model. The prediction model derived in this study separately evaluates three evaluation criteria, including classification by type of landscape, classification by distance between landscape and target, and classification by preference, and then synthesizes and predicts results. As a result of the study, a prediction model with a high accuracy of 0.986 for the evaluation criterion according to the type of landscape, 0.973 for the evaluation criterion according to the distance, and 0.952 for the evaluation criterion according to the preference was developed, and it can be seen that the verification process through the evaluation of data prediction results exceeds the required performance value of the model. As an experimental attempt to investigate the possibility of developing a prediction model using machine learning in landscape-related research, this study was able to confirm the possibility of creating a high-performance prediction model by building a data set through the collection and refinement of image data and subsequently utilizing it in landscape-related research fields. Based on the results, implications, and limitations of this study, it is believed that it is possible to develop various types of landscape prediction models, including wind power facility natural, and cultural landscapes. Machine learning techniques can be more useful and valuable in the field of landscape architecture by exploring and applying research methods appropriate to the topic, reducing the time of data classification through the study of a model that classifies images according to landscape types or analyzing the importance of landscape planning factors through the analysis of landscape prediction factors using machine learning.

• Economic and Environmental Geology
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• v.36 no.3
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• pp.191-200
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• 2003

Investigations on the contaminated lands due to heavy metals from mining activities or hydrocarbons from oil spillage for example, should be planned based on specific fitness-for-purpose criteria(FFP criteria). A FFP criterion is site specific or varies with situation, based on which not only the data quality but also the decision quality can be determined. The limiting factors on the qualities can be, for example, the total budget for the investigation, regulatory guidance or expert's subjective fitness-for-purpose criterion. This paper deals with planning of investigation methods that can satisfy each suggested FFP criterion based on economic factors and the data quality. To this aim, a probabilistic loss function was applied to derive the cost effective investigation method that balances the measurement uncertainty, which estimates the degree of the data quality, with the decision quality. In addition, investigation planning methods when the objectives of investigations do not lie in the classification of the land but simply in producing the estimation of the mean concentration of the contaminant at the site(e.g. for the use in risk assessment), were also suggested. Furthermore, the efficient allocation of resources between sampling and analysis was also devised. These methods were applied to the two contaminated sites in the UK to test the validity of each method.

• Journal of Environmental Policy
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• v.14 no.1
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• pp.53-83
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• 2015

Recently, climate change risk assessment has been discussed as a medium process for making climate change adaptation policies in the research field of climate change adaptation. Climate change risk assessment has been understood to have an intermediary role among impact assessment, vulnerable assessment and policy, and is used in the process of devising adaptation policies in the United Kingdom (UK). This paper quantitatively assessed the risks of climate change in Korea, applied the methods used in the UK, underwent the classification process and suggested implications of Korean adaptation policies. A survey of experts, based on Delphi's method and the classification criterion developed by Klinke and Renn(2002), was also carried out. A list of climate risks was created from the climate change impact and vulnerability assessment report of Korea, first national adaptation policy of Korea, and general climate risks of the UK. From the results, 42 risks out of total 125 risks were selected based on their importance. The assessed risks with factors, such as high impact and urgency, are related to repeated and large scale damage from storms and floods caused by abnormal or extreme weather events. Ecological changes and social infrastructure risks were engaged as required as a policy response for medium to longer term. As for making the classification, types of climate risks were suggested to manage the basic capacity in relation to social trust, triggering mechanism and responsibility. Following suggestions are put forward as the base of autonomous adaptation: increasing the capacity of civil society, mutual trust and civil participation in adaptation policy process.

• Korean Journal of Remote Sensing
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• v.33 no.6_2
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• pp.1061-1073
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• 2017

In this study, images were classified using convolutional neural network (CNN) - a deep learning technique - to investigate the feasibility of information production through a combination of artificial intelligence and spatial data. CNN determines kernel attributes based on a classification criterion and extracts information from feature maps to classify each pixel. In this study, a CNN network was constructed to classify materials with similar spectral characteristics and attribute information; this is difficult to achieve by conventional image processing techniques. A Compact Airborne Spectrographic Imager(CASI) and an Airborne Imaging Spectrometer for Application (AISA) were used on the following three study sites to test this method: Site 1, Site 2, and Site 3. Site 1 and Site 2 were agricultural lands covered in various crops,such as potato, onion, and rice. Site 3 included different buildings,such as single and joint residential facilities. Results indicated that the classification of crop species at Site 1 and Site 2 using this method yielded accuracies of 96% and 99%, respectively. At Site 3, the designation of buildings according to their purpose yielded an accuracy of 96%. Using a combination of existing land cover maps and spatial data, we propose a thematic environmental map that provides seasonal crop types and facilitates the creation of a land cover map.

• The Journal of Korean Society for School & Community Health Education
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• v.6
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• pp.117-126
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• 2005

This study attempted to extract a suggestive point to help the design of a program, which is used to promote physical activities, by applying a social cognitive theory based on literature review on the physical activity based on a social cognitive theory. This study considers 10 journal articles that used a social cognitive theory, physical activity, and exercise as the major variable using the EBSCOhost Academic Search Premier and Educator's Reference Desk (ERIC). The type of papers was analyzed using a certain criterion, which can be configured according to the number of each year's papers, characteristics of research subjects, application type of a social cognitive theory, and classification of the application of objects in a social cognitive theory. The characteristics of each year's papers presented no specific characteristics for each year's papers, but the study in 2004 especially presented a high level. The characteristics of research subjects presented four highest cases in the case of the college student, and there were zero cases for children. The application type of studies on physical activities using a social cognitive theory can be largely classified as three types. The results of the measurement using a sectional investigation for SCT objects were 2 cases, the application of SCT for promoting physical activities was 1 case, and the demonstration of evaluation for the effect of SCT objects presented 8 highest cases. Although the social cognitive theory in the characteristics of the classification of object applications can be classified as 10 objects, there were no cases that used 10 all objects, partial applications of the object were measured in 8 studies, and two cases presented no detailed considerations on the object. Most of studies used a part of the object where the application of self-efficacy were measured by 8 highest cases. In addition, there were no measurements on the situation, observation learning, answer and response, and self-management. The elements of attitude, cognitive activity, self-efficacy, and handicaps among the SCT object were commonly used, and studies that the self-efficacy largely affects on the promotion of physical activities presented the main current.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.22 no.1
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• pp.65-80
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• 2023

In this study, a classification analysis was performed based on the type of traffic situation. The purpose was to derive the major variable factors that could represent the traffic situation. The TTI(Travel Time Index) was used as a criterion for determining traffic conditions, and analysis was performed using data generally detected by the Vehicle Detecting System(VDS). First, the major factors influencing the traffic situation were selected through factor analysis, and traffic conditions were clustered through a cluster analysis of the major factors. After that, variance analysis for each cluster was performed based on the TTI, and similar clusters were merged to categorize the type of traffic situation. The analysis derived, the maximum queue length and occupancy as major factors that could represent the traffic situation. Through this study, it is expected that efficient management of traffic congestion would be possible by just concentrating on the main variable factors that affect the traffic situation.