• Economic and Environmental Geology
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• v.45 no.5
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• pp.513-523
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• 2012

The upper sedimentary layer of the Ulleung Basin in the East Sea shows stacked mass-flow deposits such as slide/slump deposits in the upper slope, debris-flow deposits in the middle and lower slope, and turbidites in the basin plain. Shallow gases or gas hydrates are also reported in many area of the Ulleung Basin, which are very important in terms of marine resources, environmental changes, and geohazard. This paper aims at studying acoustic characteristics and distribution pattern of gas-related structures such as acoustic column, enhanced reflector, dome structure, pockmark, and gas seepage in the upper sedimentary layer, by analysing high-resolution chirp profiles. Acoustic column shows a transparent pillar shape in the sedimentary layer and mainly occurs in the basin plain. Enhanced reflector is characterized by an increased amplitude and laterally extended to several tens up kilometers. Dome structure is characterized by an upward convex feature at the seabed, and mainly occurs in the lower slope. The pockmark shows a small crater-like feature and usually occurs in the middle and lower slope. Gas seepage is commonly found in the middle slope of the southern Ulleung Basin. These gas-related structures seem to be mainly caused by gas migration and escape in the sedimentary layer. The distribution pattern of the gas-related structures indicates that formation of these structures in the Ulleung Basin is controlled not only by sedimentary facies in upper sedimentary layer but also by gas-solubility changes depending on water depth. Especially, it is interpreted that the chaotic and discontinuous sedimentary structures of debris-flow deposits cause the facilitation of gas migration, whereas the continuous sedimentary layers of turbidites restrict the vertical migration of gases.

• Korean Journal of Environment and Ecology
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• v.33 no.2
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• pp.237-251
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• 2019

This study evaluated the ecological value of waterside parks by investigating the animal distribution and ecological feature in 92 waterside parks and analyzed the change of ecological awareness by users and non-users of waterside parks through ecological education and promotion based on the investigation results. The result confirmed inhabitation of various animals including 9 endangered species (Pernis ptilorhynchus orientalis, Accipiter soloensis, Falco subbuteo, Charadrius placidus, Felis bengalensis euptilura, Lutra lutra, Kaloula borealis, Polyphylla laticollis manchurica, and Leptalina unicolor) in waterside parks. Although waterside parks were constructed to be hydrophilic areas for human use, some of them with high natural characteristics are valued as biological habitat. We investigated user status in 5 areas (Daejeon, Sejong, Cheongju, Kongju, and Buyeo) located at Guem river basin to evaluate people's perception of waterside parks and carried out the ecological education and promotion based on the investigation result. The survey of 200 people showed that there were more users of waterside parks than non-users and that people in their 40's showed the highest use rate. The use frequency of waterside parks located in Daejeon and Cheongju was lower than in other areas (Sejong, Kongju, and Buyeo). We considered it was because Daejeon and Cheongju were urban areas and had relatively more leisure areas such as sports facilities and cafe than other areas, and thus the residents had a lower reliance on waterside parks. Moreover, users used waterside parks more frequently when they were nearer to users' residence. It is because most users perceived waterside parks as the leisure sports facility and thus preferred them to be within walking distance. The users' perception of waterside parks as the ecological space "to be preserved" increased after the ecological education and promotion. The change of the perception was higher among users (80%) than non-users (38%). Therefore, ecological education and promotion were potentially more effective to people who user waterside parks and thus had a higher understanding of the characteristics and specification. In conclusion, 1) although waterside parks were constructed for human use, some parts had high ecological value for the distribution of endangered species and outstanding natural beauty, and 2) it is necessary to change the perception of waterside parks from the hydrophilic attribute to the conservation attribute. Such change of perception would contribute to establishing waterside parks that feature both hydrophilic and conservation attributes in the management or upgrading plan of waterside parks in the future.

• Progress in Medical Physics
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• v.23 no.4
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• pp.219-228
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• 2012

The tangential breast intensity modulated radiotherapy (T-B IMRT) technique, which uses the same tangential fields as conventional 3-dimensional conformal radiotherapy (3D-CRT) plans with physical wedges, was analyzed in terms of the calculated dose distribution feature and dosimetric accuracy of beam delivery during treatment. T-B IMRT plans were prepared for 15 patients with breast cancer who were already treated with conventional 3D-CRT. The homogeneity of the dose distribution to the target volume was improved, and the dose delivered to the normal tissues and critical organs was reduced compared with that in 3D-CRT plans. Quality assurance (QA) plans with the appropriate phantoms were used to analyze the dosimetric accuracy of T-B IMRT. An ionization chamber placed at the hole of an acrylic cylindrical phantom was used for the point dose measurement, and the mean error from the calculated dose was $0.7{\pm}1.4%$. The accuracy of the dose distribution was verified with a 2D diode detector array, and the mean pass rate calculated from the gamma evaluation was $97.3{\pm}2.9%$. We confirmed the advantages of a T-B IMRT in the dose distribution and verified the dosimetric accuracy from the QA performance which should still be regarded as an important process even in the simple technique as T-B IMRT in order to maintain a good quality.

• Journal of Intelligence and Information Systems
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• v.25 no.1
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• pp.163-177
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• 2019

As smartphones are getting widely used, human activity recognition (HAR) tasks for recognizing personal activities of smartphone users with multimodal data have been actively studied recently. The research area is expanding from the recognition of the simple body movement of an individual user to the recognition of low-level behavior and high-level behavior. However, HAR tasks for recognizing interaction behavior with other people, such as whether the user is accompanying or communicating with someone else, have gotten less attention so far. And previous research for recognizing interaction behavior has usually depended on audio, Bluetooth, and Wi-Fi sensors, which are vulnerable to privacy issues and require much time to collect enough data. Whereas physical sensors including accelerometer, magnetic field and gyroscope sensors are less vulnerable to privacy issues and can collect a large amount of data within a short time. In this paper, a method for detecting accompanying status based on deep learning model by only using multimodal physical sensor data, such as an accelerometer, magnetic field and gyroscope, was proposed. The accompanying status was defined as a redefinition of a part of the user interaction behavior, including whether the user is accompanying with an acquaintance at a close distance and the user is actively communicating with the acquaintance. A framework based on convolutional neural networks (CNN) and long short-term memory (LSTM) recurrent networks for classifying accompanying and conversation was proposed. First, a data preprocessing method which consists of time synchronization of multimodal data from different physical sensors, data normalization and sequence data generation was introduced. We applied the nearest interpolation to synchronize the time of collected data from different sensors. Normalization was performed for each x, y, z axis value of the sensor data, and the sequence data was generated according to the sliding window method. Then, the sequence data became the input for CNN, where feature maps representing local dependencies of the original sequence are extracted. The CNN consisted of 3 convolutional layers and did not have a pooling layer to maintain the temporal information of the sequence data. Next, LSTM recurrent networks received the feature maps, learned long-term dependencies from them and extracted features. The LSTM recurrent networks consisted of two layers, each with 128 cells. Finally, the extracted features were used for classification by softmax classifier. The loss function of the model was cross entropy function and the weights of the model were randomly initialized on a normal distribution with an average of 0 and a standard deviation of 0.1. The model was trained using adaptive moment estimation (ADAM) optimization algorithm and the mini batch size was set to 128. We applied dropout to input values of the LSTM recurrent networks to prevent overfitting. The initial learning rate was set to 0.001, and it decreased exponentially by 0.99 at the end of each epoch training. An Android smartphone application was developed and released to collect data. We collected smartphone data for a total of 18 subjects. Using the data, the model classified accompanying and conversation by 98.74% and 98.83% accuracy each. Both the F1 score and accuracy of the model were higher than the F1 score and accuracy of the majority vote classifier, support vector machine, and deep recurrent neural network. In the future research, we will focus on more rigorous multimodal sensor data synchronization methods that minimize the time stamp differences. In addition, we will further study transfer learning method that enables transfer of trained models tailored to the training data to the evaluation data that follows a different distribution. It is expected that a model capable of exhibiting robust recognition performance against changes in data that is not considered in the model learning stage will be obtained.

• Journal of Korean Society of Transportation
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• v.19 no.4
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• pp.35-47
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• 2001

Traffic represents one of the largest sources of primary air pollutants in urban area. As a consequence. numerous abatement strategies are being pursued to decrease the ambient concentration of pollutants. A characteristic of most of the these strategies is a requirement for accurate data on both the quantity and spatial distribution of emissions to air in the form of an atmospheric emission inventory database. In the case of traffic pollution, such an inventory must be compiled using activity statistics and emission factors for vehicle types. The majority of inventories are compiled using passive data from either surveys or transportation models and by their very nature tend to be out-of-date by the time they are compiled. The study of current trends are towards integrating urban traffic control systems and assessments of the environmental effects of motor vehicles. In this study, a methodology of motor vehicle emission calculation by using real-time traffic data was studied. A methodology for estimating emissions of CO at a test area in Seoul. Traffic data, which are required on a street-by-street basis, is obtained from induction loops of traffic control system. It was calculated speed-related mass of CO emission from traffic tail pipe of data from traffic system, and parameters are considered, volume, composition, average velocity, link length. And, the result was compared with that of a method of emission calculation by VKT(Vehicle Kilometer Travelled) of vehicles of category.

• Tuberculosis and Respiratory Diseases
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• v.55 no.3
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• pp.287-296
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• 2003

Background : Drowning represents the third most common cause of all accidental deaths worldwide. Although few studies of submersion injury were done in Korea, the subjects were mainly pediatric patients. The purpose of this study is to describe the clinical feature of submersion injury in adults. Methods : The medical records of 31 patients with submersion injury who were >15 years of age and admitted to Kyungpook National University Hospital from July 1990 to March 2003 were retrospectively examined. Results : The most common age-group, cause, and site of submersion accidents in adults were 15-24 years of age, inability to swim, and river followed by more than 65 years of age, drinking, and public bath respectively. The initial chest radiographics showed bilaterally and centrally predominant distribution of pulmonary edema at lung base in about 90% of patients with pulmonary edema represented by submersion injury but at only upper lung zone in 10%. Eventually, 25 patients (80.6%) survived without any neurologic deficit and 2 patients (6.5%) with significant neurologic deficit, and 4 patients (12.9%) died. Age, arterial gas oxygenation, and mental status among baseline variables showed significant difference for prognosis. Conclusions : More than 65 year of age, drinking, and occurrence in public bath were relatively important in submersion injury of adults, and the successful survival of 80.6% of patients suggests that cardiopulmonary resuscitation should be intensively done in even adults.

• Journal of the Korean Association of Geographic Information Studies
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• v.22 no.1
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• pp.168-182
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• 2019

The objectives of this study were to examine the production processes and methods of "Forest Type Map Actualization Production (Database (DB) Construction Work Manual)" (Work Manual) identify issues associated with the production processes and methods, and suggest solutions for them by applying evaluation items to a 1:5k digital forest type map. The evaluation items applied to a forest type map were divided into zoning and attributes, and the issues associated with the production processes and methods of Work Manual were derived through analyzing the characteristics of the stand structure and fragmentation by administrative districts. Korea is divided into five divisions, where one is set as the area changed naturally and the other four areas set as the area changed artificially. The area changed naturally has been updated every five years, and those changed artificially have been updated annually. The fragmentation of South Korea was analyzed in order to examine the consistency of the DB established for each region. The results showed that, in South Korea, the number of patches increased and the mean patch size decreased. As a result, the degree of fragmentation and the complexity of shapes increased. The degree of fragmentation and the complexity of shapes decreased in four regions out of 17 regions (metropolitan cities and provinces). The results indicated that there were spatial variations. The "Forest Classification" defines the minimum area of a zoning as 0.1ha. This study examined the criteria for the minimum area of a zoning by estimating the divided object (polygon unit) in a forest type map. The results of this study revealed that approximately 26% of objects were smaller than the minimum area of a zoning. The results implied that it would be necessary to establish the definition and the regeneration interval of "Areas Changed Artificially and Areas Changed Naturally", and improve the standard for the minimum area of a zoning. Among the attributes of Work Manual, "Species Change" item classifies terrain features into 52 types, and 43 types of them belong to stocking land. This study examined distribution ratios by extracting species information from the forest type map. It was found that each of 23 species, approximately 53% of species, occupied less than 0.1% of Forested land. The top three species were pine and other species. Although undergrowth on unstocked forest land are classified in the terrain feature system, their definition and classification criteria are not established in the "Forest Classification" item. Therefore, it will be needed to reestablish the terrain feature system and set the definitions of undergrowth.

• Korean Journal of Agricultural and Forest Meteorology
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• v.25 no.2
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• pp.80-98
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• 2023

This study explores the effectiveness of various data preprocessing algorithms for improving subseasonal to seasonal (S2S) climate predictions from six climate forecast models and their Multi-Model Ensemble (MME) using a deep learning-based postprocessing model. A pipeline of data transformation algorithms was constructed to convert raw S2S prediction data into the training data processed with several statistical distribution. A dimensionality reduction algorithm for selecting features through rankings of correlation coefficients between the observed and the input data. The training model in the study was designed with TimeDistributed wrapper applied to all convolutional layers of U-Net: The TimeDistributed wrapper allows a U-Net convolutional layer to be directly applied to 5-dimensional time series data while maintaining the time axis of data, but every input should be at least 3D in U-Net. We found that Robust and Standard transformation algorithms are most suitable for improving S2S predictions. The dimensionality reduction based on feature selections did not significantly improve predictions of daily precipitation for six climate models and even worsened predictions of daily maximum and minimum temperatures. While deep learning-based postprocessing was also improved MME S2S precipitation predictions, it did not have a significant effect on temperature predictions, particularly for the lead time of weeks 1 and 2. Further research is needed to develop an optimal deep learning model for improving S2S temperature predictions by testing various models and parameters.

• Journal of the Korean Geographical Society
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• v.49 no.5
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• pp.761-778
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• 2014

There has been relatively little study to model price for commercial property because of its low transaction volume in the market. Despite of this thin market character, this paper tried to estimate prices for commercial lots as accurate as possible. We constructed a model whose components consist of mean structure(global trend), exponential covariance function and a pure error term, and applied it to actual sales price data of Seoul. We explicitly took account of spatial autocorrelation of land price by utilizing a kriging technique, a representative method of spatial interpolation, because the land price of commercial lots has feature of differential price forming pattern depending on submarkets they belong to. In addition, we chose to apply a bayesian kriging to overcome data scarcity by incorporating experts' knowledge into prior probability distribution. The chosen model's excellent performance was verified by the result from validation data. We confirmed that the excellence of the model is attributed to incorporating both autocorexperts' knowledge and spatial autocorrelation in the model construction. This paper is differentiated from previous studies in the sense that it applied the bayesian kriging technique to estimate price for commercial lots and explicitly combined experts' knowledge with data. It is expected that the result of this paper would provide a useful guide for the circumstances under which property price has to be estimated reliably based on sparse transaction data.

• 한국해양학회지
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• v.18 no.2
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• pp.104-110
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• 1983

The Intermittent phenomena of the turbulent momentrm transports were closely examined in order to know the nature of intermittency and its fluid dynamic implications in the oceanic turbulent boundary layer. Also the connection between the observed intermittency and the bursting phenomenon was studied in detail. In this investigation, strong intermittency of turbulent momentum transports were found and the peak values of Reynolds stress (i,e., u'w') was about 408 times greater than average Reynolds stress (u',w') in the mid-layer and 270 times greater in the uppcrlayer of the turbulent boundary layer. These values are far greater than presently known maximum value, namely 30 times greater than the average Reynolds stress reported by Gordon (1974) and Heathersaw (1974). The distribution of Reynolds stress were extremely non-normal with the mean peak occurrence period of 5 minutes in the mid-layer and 1. 1 minutes in the upper layer of the turbulent boundary layer. Each teak lasted about 2 seconds in the mid-layer and 1.1 seconds in the upper layer of the turbulent boundary layer. Our dimensionless period of peak occurrence are found to be 33.3 in the mid-layer and 7.3 in the upper-layer, which are substantially larger than the often quoted values of 3.2-6.8 for the bursting period (Jackson, 1976). Some workers have interpreted that the intermittency phenomenon is the retlect of burst across their probe of the currentmeter (Gordon, 1974; Heathersaw, 1974). However, it was known that the burst can be found very near bottom boundary with smoothed bottom (i,e., friction Reynolds number$\leq$3,000) in the laboratory experiments. Through this investigation, it was found that the intermittent strength of the turbulent momentum transports does not conclusively indicate the characteristic feature of the boundary layer turbulence with a rough bottom (i,e., friction Reynolds number$\geq$10$\^$5/).