• Korean Journal of Environmental Biology
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• v.42 no.1
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• pp.62-79
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• 2024

Garlic mustard (Alliaria petiolata) is a species that has devastated the United States and Canada. It is known to play a role in destroying the ecosystem. In this study, the domestic distribution of garlic mustard was confirmed and a detailed distribution map was created for the Samcheok region, where the largest population has been established in South Korea. This study investigated the growth environment, life cycle, and population dynamics of the species in the Samcheok region. Garlic mustard was found in a total of 301 locations in Samcheok, with a total distribution area of 2,957 square meters. Annual plants germinated in mid-April, overwintered in rosette form, underwent vegetative growth from April 10 to April 24 the following year, and flowered from April 24 to May 7. Individuals producing seeds began to die off from June. Both annual and biennial individuals showed a trend of increasing and then decreasing in number around April 27 (118 days). Garlic mustard grew well under favorable light conditions in early spring. They showed less growth on leaf litter, short distance from roads, lower altitude, deciduous broad-leaved forest of middle and lower parts of the slope and forest edge. Without proper control measures in the Samcheok region, it is likely to spread more rapidly in deciduous broad-leaved forests along hiking trails in the Galyasan Mountains. In particular, it is more likely to extend to oak community where light enters the site during flowering than to pine community where there is less light in the site.

• Journal of Plant Biotechnology
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• v.35 no.4
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• pp.245-256
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• 2008

The current legislation in South Korea clearly states that the tolerance threshold on the adventitious presence of GMO in environment-friendly agricultural products is 3.0% and no GM seed should be detected in their planting seed batches. To date, in Korea, there is no approved GM crop for commercial cultivation in field. However, several GM crops including rice, Chinese cabbage, potato and wild turf grass are currently under risk assessment for their environmental release. Also Korean government (Rural Development Administration, RDA) announced that 11 institutes including universities have been currently certified to carry out a risk assessment of GM crops. Meanwhile, the cultivated area and certified quantities of environment-friendly crops (organic, pesticide-free and low-pesticide) are sharply increasing every year according to the report of National Agricultural Products Quality Management Service (NAQS). In detail, in 2007, the certified quantities of environment-friendly agricultural products were elevated up to 100-fold for organic, 171-fold for pesticide-free and 2,324-fold for low-pesticide crops when compared with those in 1999. The total certified quantity of environment-friendly cereal crops in 2007 was equivalent to 6.4% of total production of cereal crops. Moreover, 24% of total production of root and tuber crops such as potato and sweet potato were certified for environment-friendly agricultural products. In these circumstances, I strongly suggest that current legislations on GM crop's safety management should be revised to include strategies for the coexistence of GM with non-GM crops, especially environment-friendly crops before GM crop is approved to be cultivated for commercialization. Since all types of crops are grown in an open environment, the adventitious presence of GM crops among non-GM crops is inevitable if appropriate measures for coexistence are not established for species by species such as isolation distance, workable management measures to minimize admixture.

• Journal of Intelligence and Information Systems
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• v.27 no.1
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• pp.129-149
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• 2021

Recently, interest in social robots that can socially interact with humans is increasing. Thanks to the development of ICT technology, social robots have become easier to provide personalized services and emotional connection to individuals, and the role of social robots is drawing attention as a means to solve modern social problems and the resulting decline in the quality of individual lives. Along with the interest in social robots, the spread of social robots is also increasing significantly. Many companies are introducing robot products to the market to target various target markets, but so far there is no clear trend leading the market. Accordingly, there are more and more attempts to differentiate robots through the design of social robots. In particular, anthropomorphism has been studied importantly in social robot design, and many approaches have been attempted to anthropomorphize social robots to produce positive effects. However, there is a lack of research that systematically describes the mechanism by which anthropomorphism for social robots is formed. Most of the existing studies have focused on verifying the positive effects of the anthropomorphism of social robots on consumers. In addition, the formation of anthropomorphism of social robots may vary depending on the individual's motivation or temperament, but there are not many studies examining this. A vague understanding of anthropomorphism makes it difficult to derive design optimal points for shaping the anthropomorphism of social robots. The purpose of this study is to verify the mechanism by which the anthropomorphism of social robots is formed. This study confirmed the effect of the human-likeness of social robots(Within-subjects) and the construal level of consumers(Between-subjects) on the formation of anthropomorphism through an experimental study of 3×2 mixed design. Research hypotheses on the mechanism by which anthropomorphism is formed were presented, and the hypotheses were verified by analyzing data from a sample of 206 people. The first hypothesis in this study is that the higher the human-likeness of the robot, the higher the level of anthropomorphism for the robot. Hypothesis 1 was supported by a one-way repeated measures ANOVA and a post hoc test. The second hypothesis in this study is that depending on the construal level of consumers, the effect of human-likeness on the level of anthropomorphism will be different. First, this study predicts that the difference in the level of anthropomorphism as human-likeness increases will be greater under high construal condition than under low construal condition.Second, If the robot has no human-likeness, there will be no difference in the level of anthropomorphism according to the construal level. Thirdly,If the robot has low human-likeness, the low construal level condition will make the robot more anthropomorphic than the high construal level condition. Finally, If the robot has high human-likeness, the high construal levelcondition will make the robot more anthropomorphic than the low construal level condition. We performed two-way repeated measures ANOVA to test these hypotheses, and confirmed that the interaction effect of human-likeness and construal level was significant. Further analysis to specifically confirm interaction effect has also provided results in support of our hypotheses. The analysis shows that the human-likeness of the robot increases the level of anthropomorphism of social robots, and the effect of human-likeness on anthropomorphism varies depending on the construal level of consumers. This study has implications in that it explains the mechanism by which anthropomorphism is formed by considering the human-likeness, which is the design attribute of social robots, and the construal level of consumers, which is the way of thinking of individuals. We expect to use the findings of this study as the basis for design optimization for the formation of anthropomorphism in social robots.

• Journal of the Korean Society of Marine Environment & Safety
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• v.29 no.2
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• pp.188-196
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• 2023

Among marine accidents caused by bad weather, visibility restrictions caused by sea fog occurrence cause accidents such as ship strand and ship bottom damage, and at the same time involve casualties caused by accidents, which continue to occur every year. In addition, low visibility at sea is emerging as a social problem such as causing considerable inconvenience to islanders in using transportation as passenger ships are collectively delayed and controlled even if there are local differences between regions. Moreover, such measures are becoming more problematic as they cannot objectively quantify them due to regional deviations or different criteria for judging observations from person to person. Currently, the VTS of each port controls the operation of the ship if the visibility distance is less than 1km, and in this case, there is a limit to the evaluation of objective data collection to the extent that the visibility of sea fog depends on the visibility meter or visual observation. The government is building a marine weather signal sign and sea fog observation networks for sea fog detection and prediction as part of solving these obstacles to marine traffic safety, but the system for observing locally occurring sea fog is in a very insufficient practical situation. Accordingly, this paper examines domestic and foreign policy trends to solve social problems caused by low visibility at sea and provides basic data on the need for government support to ensure maritime traffic safety due to sea fog by factually investigating and analyzing social problems. Also, this aims to establish a more stable maritime traffic operation system by blocking marine safety risks that may ultimately arise from sea fog in advance.

• Korean Journal of Environment and Ecology
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• v.32 no.5
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• pp.478-485
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• 2018

With the total population of 3,356 worldwide as of 2016, the black-faced spoonbill (Platalea minor) is designated as "endangered (EN)" species by IUCN. About 70% of population breeds on the uninhabited islands near the west coast of Korea and wintering area is Taiwan, China, Hong Kong, etc. However, there is few detail research in Korea and East Asia on black-faced spoonbill's long range migration and its habitat when migrating southward. We studied black-faced spoonbill's migration route, distribution, stopover, wintering sites, and timing of migration movements using a wild-tracker (WT-200, GPS-Mobile phone based telemetry, KoEco). We caught the black-faced spoonbills in the breeding sites (Gugi island, Bi island, Sangyeobawi, Chilsan island) in Korea in late June 2014. We attached the wild-tracker to 10 juvenile black-faced spoonbills. The tracking showed that the black-faced spoonbills started southward migration between late October and early November. The traveling distance to wintering site was maximum at 1,820 km, minimum at 746 km, the average at 1,201km. The maximum daily traveling distance was 1,479 km with an average of 782 km. The average days it took from breeding site to wintering site was 10 days (SD=10.7). The shortest duration was 2 days, and the longest duration was 34 days. Most individuals used 2-3 stopover sites between the breeding sites to the wintering sites and stayed almost 1-2 days (maximum 31 days). Stopover sites were wetlands such as rivers, streams, reservoir, and mud flat. The wintering sites were coastal areas (five individuals) in China, inland (one individual) in China, Taiwan (three individuals), and Japan (one individual). In conclusion, it is necessary to preserve the stopover sites and wintering site of the black-faced spoonbills through consultation and protection policy between countries and establish the systematic preservation measures and activity plans through continued moniting and additional studies.

• Journal of Intelligence and Information Systems
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• v.17 no.1
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• pp.111-125
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• 2011

Clustering is a process of grouping similar or relevant documents into a cluster and assigning a meaningful concept to the cluster. By this process, clustering facilitates fast and correct search for the relevant documents by narrowing down the range of searching only to the collection of documents belonging to related clusters. For effective clustering, techniques are required for identifying similar documents and grouping them into a cluster, and discovering a concept that is most relevant to the cluster. One of the problems often appearing in this context is the detection of a complex concept that overlaps with several simple concepts at the same hierarchical level. Previous clustering methods were unable to identify and represent a complex concept that belongs to several different clusters at the same level in the concept hierarchy, and also could not validate the semantic hierarchical relationship between a complex concept and each of simple concepts. In order to solve these problems, this paper proposes a new clustering method that identifies and represents complex concepts efficiently. We developed the Hierarchical Overlapping Clustering (HOC) algorithm that modified the traditional Agglomerative Hierarchical Clustering algorithm to allow overlapped clusters at the same level in the concept hierarchy. The HOC algorithm represents the clustering result not by a tree but by a lattice to detect complex concepts. We developed a system that employs the HOC algorithm to carry out the goal of complex concept detection. This system operates in three phases; 1) the preprocessing of documents, 2) the clustering using the HOC algorithm, and 3) the validation of semantic hierarchical relationships among the concepts in the lattice obtained as a result of clustering. The preprocessing phase represents the documents as x-y coordinate values in a 2-dimensional space by considering the weights of terms appearing in the documents. First, it goes through some refinement process by applying stopwords removal and stemming to extract index terms. Then, each index term is assigned a TF-IDF weight value and the x-y coordinate value for each document is determined by combining the TF-IDF values of the terms in it. The clustering phase uses the HOC algorithm in which the similarity between the documents is calculated by applying the Euclidean distance method. Initially, a cluster is generated for each document by grouping those documents that are closest to it. Then, the distance between any two clusters is measured, grouping the closest clusters as a new cluster. This process is repeated until the root cluster is generated. In the validation phase, the feature selection method is applied to validate the appropriateness of the cluster concepts built by the HOC algorithm to see if they have meaningful hierarchical relationships. Feature selection is a method of extracting key features from a document by identifying and assigning weight values to important and representative terms in the document. In order to correctly select key features, a method is needed to determine how each term contributes to the class of the document. Among several methods achieving this goal, this paper adopted the $x^2$�� statistics, which measures the dependency degree of a term t to a class c, and represents the relationship between t and c by a numerical value. To demonstrate the effectiveness of the HOC algorithm, a series of performance evaluation is carried out by using a well-known Reuter-21578 news collection. The result of performance evaluation showed that the HOC algorithm greatly contributes to detecting and producing complex concepts by generating the concept hierarchy in a lattice structure.

• Journal of Korean Society of Forest Science
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• v.84 no.2
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• pp.239-246
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• 1995

This research aimed at the contribution to obtaining the scientifical data which were required for planning she environmentally sound and sustainable management, particularly in the field of the logging road construction. Main natural environmental variables including natural vegetation, rainfall, soil runoff were measured in the logging road on-sites and analysed. This project was carried out at the (mt.)Paekunsan Research sorest of Seoul National University, located in Gwangyang, Chollanam-do in southern part of Korea, from 1993 to 1994. 1. The explanatory variables for erosion and sedimentation on logging road surface were accumulated rainfall, erosion distance, cross-sectional gradient, and soil hardness. The erosion and sedimentation on logging road was increasing positively in proportion to the accumulated rainfall, soil distance from starting point of the logging road, and cross-sectional gradient. 2. On cut-slope of logging road, cut-slope shape, part of the slope, plant coverage, soil hardness, sand content, accumulated rainfall, clay content, and silt content were effective factors. Cut-slope erosion and sedimentation on logging roam increased as with the lower plant coverage, the lower accumulated rainfall, the high sand content in the soil. 3. On fill-slope of logging road, there were three significant variables such as total rainfall and number of rainfall-storm. Fill-slope erosion and sedimentation had a positive correlation with the amount of rainfall, the number of rainfall, the soil hardness. 4. The total erosion and sedimentation on logging road were $5.04{\times}10^{-2}m^2/m^2$ in logging road construction year, $7.37{\times}10^{-2}m^2/m^2$ in next year. The erosion and sedimentation on logging road surface were 32.7% of total erosion and sedimentation on Logging road in construction year, and 57.1% in next year, respectively. The erosion and sedimentation on cut-slopes were 30.4% on logging road in construction year, fill-slopes of total erosion and sedimentation and 21.0% in next year, respectively. The erosion and sedimentation on fill-slopes were 36.9% on logging road in construction year, 21.9 in next year. To decrease the erosion and sedimentation at the logging road from the beginning stage of construction, the effective revegetation works should be implemented on the cut-slope and fill slopes, and erosion control measures such as optima. road design must be constructed on read surface.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.38 no.4
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• pp.363-373
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• 2020

During last decades numerous studies generating orthoimage have been carried out. Traditional methods require exterior orientation parameters of aerial images and precise 3D object modeling data and DTM (Digital Terrain Model) to detect and recover occlusion areas. Furthermore, it is challenging task to automate the complicated process. In this paper, we proposed a new concept of true orthoimage generation using DL (Deep Learning). DL is rapidly used in wide range of fields. In particular, GAN (Generative Adversarial Network) is one of the DL models for various tasks in imaging processing and computer vision. The generator tries to produce results similar to the real images, while discriminator judges fake and real images until the results are satisfied. Such mutually adversarial mechanism improves quality of the results. Experiments were performed using GAN-based Pix2Pix model by utilizing IR (Infrared) orthoimages, intensity from LiDAR data provided by the German Society for Photogrammetry, Remote Sensing and Geoinformation (DGPF) through the ISPRS (International Society for Photogrammetry and Remote Sensing). Two approaches were implemented: (1) One-step training with intensity data and high resolution orthoimages, (2) Recursive training with intensity data and color-coded low resolution intensity images for progressive enhancement of the results. Two methods provided similar quality based on FID (Fréchet Inception Distance) measures. However, if quality of the input data is close to the target image, better results could be obtained by increasing epoch. This paper is an early experimental study for feasibility of DL-based true orthoimage generation and further improvement would be necessary.

• Journal of Intelligence and Information Systems
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• v.18 no.2
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• pp.47-60
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• 2012

Video data comes in the form of the unstructured and the complex structure. As the importance of efficient management and retrieval for video data increases, studies on the video parsing based on the visual features contained in the video contents are researched to reconstruct video data as the meaningful structure. The early studies on video parsing are focused on splitting video data into shots, but detecting the shot boundary defined with the physical boundary does not cosider the semantic association of video data. Recently, studies on structuralizing video shots having the semantic association to the video scene defined with the semantic boundary by utilizing clustering methods are actively progressed. Previous studies on detecting the video scene try to detect video scenes by utilizing clustering algorithms based on the similarity measure between video shots mainly depended on color features. However, the correct identification of a video shot or scene and the detection of the gradual transitions such as dissolve, fade and wipe are difficult because color features of video data contain a noise and are abruptly changed due to the intervention of an unexpected object. In this paper, to solve these problems, we propose the Scene Detector by using Color histogram, corner Edge and Object color histogram (SDCEO) that clusters similar shots organizing same event based on visual features including the color histogram, the corner edge and the object color histogram to detect video scenes. The SDCEO is worthy of notice in a sense that it uses the edge feature with the color feature, and as a result, it effectively detects the gradual transitions as well as the abrupt transitions. The SDCEO consists of the Shot Bound Identifier and the Video Scene Detector. The Shot Bound Identifier is comprised of the Color Histogram Analysis step and the Corner Edge Analysis step. In the Color Histogram Analysis step, SDCEO uses the color histogram feature to organizing shot boundaries. The color histogram, recording the percentage of each quantized color among all pixels in a frame, are chosen for their good performance, as also reported in other work of content-based image and video analysis. To organize shot boundaries, SDCEO joins associated sequential frames into shot boundaries by measuring the similarity of the color histogram between frames. In the Corner Edge Analysis step, SDCEO identifies the final shot boundaries by using the corner edge feature. SDCEO detect associated shot boundaries comparing the corner edge feature between the last frame of previous shot boundary and the first frame of next shot boundary. In the Key-frame Extraction step, SDCEO compares each frame with all frames and measures the similarity by using histogram euclidean distance, and then select the frame the most similar with all frames contained in same shot boundary as the key-frame. Video Scene Detector clusters associated shots organizing same event by utilizing the hierarchical agglomerative clustering method based on the visual features including the color histogram and the object color histogram. After detecting video scenes, SDCEO organizes final video scene by repetitive clustering until the simiarity distance between shot boundaries less than the threshold h. In this paper, we construct the prototype of SDCEO and experiments are carried out with the baseline data that are manually constructed, and the experimental results that the precision of shot boundary detection is 93.3% and the precision of video scene detection is 83.3% are satisfactory.

• Journal of radiological science and technology
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• v.40 no.4
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• pp.549-556
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• 2017

This study compared the spatial scattered dose distribution according to whether the recently developed radiation shielding is used or not in order to understand the spatial scattered dose distribution of C-arm. The horizontal side distribution increased by $30^{\circ}$ in the interval of the radius 50 cm on the height of 95 cm based on the head of the patient, and it was measured by increasing $30^{\circ}$ with the interval of 50 cm in the vertical side of each horizontal side. In the same method, the radiation shielding was installed and measured. The result of measurement shows that the horizontal side of 50 cm distance was $0^{\circ}$, $90^{\circ}$ and $180^{\circ}$, was $1.77{\pm}0.12$, $1.90{\pm}0.13$, $2.12{\pm}0.14$, and $2.69{\pm}0.15mSv/h$ in the $270^{\circ}$ direction, and was $1.59{\pm}0.12$, $0.99{\pm}0.09$, $1.47{\pm}0.11$, and $1.37{\pm}0.11mSv/h$ after the use of the radiation shielding. In addition, the vertical distribution in horizontal direction $90^{\circ}$ with 50 cm distance was $30^{\circ}$, $60^{\circ}$, $120^{\circ}$, was $3.85{\pm}0.18$, $9.15{\pm}0.28$, $10.82{\pm}0.31$, and $5.40{\pm}0.22mSv/h$ in $150^{\circ}$, and was $2.03{\pm}0.13$, $4.32{\pm}0.19$, $2.76{\pm}0.16$, and $1.92{\pm}0.13mSv/h\;mR/h$ after the use of the radiation shielding. Both direction showed decrease according to the use of the radiation shielding. Therefore, radiation related workers who work in operating rooms should recognize the spatial scattered dose distribution exactly and need to try to prevent the risk of radiation exposure with proper protective measures.