• Korean Journal of Environment and Ecology
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• v.37 no.4
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• pp.259-272
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• 2023

This study set up 49 survey areas with an area of about 400 square meters in Abies koreana natural habitat to identify the species composition and vegetation structure of the A. koreana forest in the Mt. Jiri Nation Park, conducted field surveys using phytosociological methods, and performed the cluster analysis using the Two-Way Indicator Species Analysis (TWINSPAN) and Table manipulation. Subsequently, species composition analysis using the importance value, species diversity analysis, DBH analysis, sapling analysis, and similarity analysis was conducted by each cluster type. The cluster analysis classified the A. koreana forest in Mt. Jiri into five clusters, A, B, C, D, and E. The forest was divided into two clusters, Magnolia sieboldii-Dryopteris crassirhizoma-Sasa borealis and Betula ermanii-Solidago virgaurea-Calamagrostis arundinacea. The former was classified as type A and B by Cornus controversa-Hydrangea macrophylla, and the latter was classified as type E, a typical community, and a Sorbus commixta-Rhododendron mucronulatum cluster. And the S. commixta-R. mucronulatum cluster was divided into C type and D type by Picea jezoensis-Ligularia fischeri and Ainsliaea acerifolia. Through vegetation analysis, the importance value of A. koreana, Quercus mongolica, Acer pseudosieboldianum, Fraxinus sieboldiana, and B. ermanii was highly expressed in the A. koreana forest in Mt. Jiri. Regarding species diversity, the results were similar to those reported in other studies of A. koreana forests in Mt. Jiri. The analysis of diameter at breast height (DBH) showed that A. koreana dominated all layers, and the growth of saplings was also good, indicating that the dominance of A. koreana is expected to continue for a while. However, when considering the value of biodiversity that is expected to increase and threats caused by climate change, systematic preservation and management are required to respond to various threats based on continuous monitoring.

• Korean Journal of Environment and Ecology
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• v.38 no.3
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• pp.246-262
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• 2024

The survey conducted from 2018 to 2020 aimed to investigate the changes in fish fauna and community characteristics in the upper reaches of the Seomgang River, Korea. During the survey period, 35 sites were selected, resulting in the collection of 7,817 fish belonging to 12 families and 40 species. The dominant species was Zacco koreanus, with a relative abundance of 34.5%, followed by Z. platypus at 28.7%. Other significant species included Rhynchocypris oxycephalus (10.2%), Pungtungia herzi (5.3%), and Squalidus gracilis majimae (4.3%). Notably, four protected species - Acheilognathus signifer, Gobiobotia brevibarba, and Cottus koreanus, designated as class II endangered wildlife by the Ministry of Environment- were identified. These species predominantly inhabit the middle and lower reaches, except for Gobiobotia brevibarba, which is found in the upper reaches. Nineteen species, accounting for a 47.5% endemism rate, were endemic to Korea. The study also noted the presence of one climate-sensitive species, Cottus koreanus, and two exotic species, Carassius cuvieri and Micropterus salmoides. Community analysis indicated a trend of decreasing dominance and increasing diversity and richness from upstream to downstream, with a distinct division into uppermost reaches, upper reaches, middle and lower reaches, and lakes. The construction of the Hwaseong Dam has had a significant direct and indirect impact on the fish community. The habitat and abundance of endangered species such as R. pseudosericeus, A. signifer, and G. brevibarba decreased dramatically immediately after the dam's construction, transforming the submerged area from lotic to lentic environments. Approximately 20 years later, the habitats have stabilized, leading to an increase in the fish population and a recovery of the previously diminished endangered species. The river health (FAI) was also evaluated, with 27 sites rated as very good (A), seven as good (B), and one as fair (C). However, endangered species such as A. signifer continue to face threats from dam and river construction, while C. Koreanus has experienced a severe population decline due to river works. Additionally, the presence of the ecosystem-disrupting species M. salmoides in Hwaseong Lake raises concerns. To ensure a stable habitat for fish in the upper reaches of the Seomgang River, it is crucial to avoid indiscriminate river construction, urgently implement restoration policies for endangered species such as A. signifer, and develop management strategies to control the spread of invasive species such as bass.

• Journal of Intelligence and Information Systems
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• v.17 no.1
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• pp.53-69
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• 2011

Vision and voice-based technologies are commonly utilized for human-robot interaction. But it is widely recognized that the performance of vision and voice-based interaction systems is deteriorated by a large margin in the real-world situations due to environmental and user variances. Human users need to be very cooperative to get reasonable performance, which significantly limits the usability of the vision and voice-based human-robot interaction technologies. As a result, touch screens are still the major medium of human-robot interaction for the real-world applications. To empower the usability of robots for various services, alternative interaction technologies should be developed to complement the problems of vision and voice-based technologies. In this paper, we propose the use of accelerometer-based gesture interface as one of the alternative technologies, because accelerometers are effective in detecting the movements of human body, while their performance is not limited by environmental contexts such as lighting conditions or camera's field-of-view. Moreover, accelerometers are widely available nowadays in many mobile devices. We tackle the problem of classifying acceleration signal patterns of 26 English alphabets, which is one of the essential repertoires for the realization of education services based on robots. Recognizing 26 English handwriting patterns based on accelerometers is a very difficult task to take over because of its large scale of pattern classes and the complexity of each pattern. The most difficult problem that has been undertaken which is similar to our problem was recognizing acceleration signal patterns of 10 handwritten digits. Most previous studies dealt with pattern sets of 8~10 simple and easily distinguishable gestures that are useful for controlling home appliances, computer applications, robots etc. Good features are essential for the success of pattern recognition. To promote the discriminative power upon complex English alphabet patterns, we extracted 'motion trajectories' out of input acceleration signal and used them as the main feature. Investigative experiments showed that classifiers based on trajectory performed 3%~5% better than those with raw features e.g. acceleration signal itself or statistical figures. To minimize the distortion of trajectories, we applied a simple but effective set of smoothing filters and band-pass filters. It is well known that acceleration patterns for the same gesture is very different among different performers. To tackle the problem, online incremental learning is applied for our system to make it adaptive to the users' distinctive motion properties. Our system is based on instance-based learning (IBL) where each training sample is memorized as a reference pattern. Brute-force incremental learning in IBL continuously accumulates reference patterns, which is a problem because it not only slows down the classification but also downgrades the recall performance. Regarding the latter phenomenon, we observed a tendency that as the number of reference patterns grows, some reference patterns contribute more to the false positive classification. Thus, we devised an algorithm for optimizing the reference pattern set based on the positive and negative contribution of each reference pattern. The algorithm is performed periodically to remove reference patterns that have a very low positive contribution or a high negative contribution. Experiments were performed on 6500 gesture patterns collected from 50 adults of 30~50 years old. Each alphabet was performed 5 times per participant using $Nintendo{(R)}$ $Wii^{TM}$ remote. Acceleration signal was sampled in 100hz on 3 axes. Mean recall rate for all the alphabets was 95.48%. Some alphabets recorded very low recall rate and exhibited very high pairwise confusion rate. Major confusion pairs are D(88%) and P(74%), I(81%) and U(75%), N(88%) and W(100%). Though W was recalled perfectly, it contributed much to the false positive classification of N. By comparison with major previous results from VTT (96% for 8 control gestures), CMU (97% for 10 control gestures) and Samsung Electronics(97% for 10 digits and a control gesture), we could find that the performance of our system is superior regarding the number of pattern classes and the complexity of patterns. Using our gesture interaction system, we conducted 2 case studies of robot-based edutainment services. The services were implemented on various robot platforms and mobile devices including $iPhone^{TM}$. The participating children exhibited improved concentration and active reaction on the service with our gesture interface. To prove the effectiveness of our gesture interface, a test was taken by the children after experiencing an English teaching service. The test result showed that those who played with the gesture interface-based robot content marked 10% better score than those with conventional teaching. We conclude that the accelerometer-based gesture interface is a promising technology for flourishing real-world robot-based services and content by complementing the limits of today's conventional interfaces e.g. touch screen, vision and voice.

• Korean Journal of Environmental Agriculture
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• v.32 no.3
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• pp.214-223
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• 2013

BACKGROUND: This study focused on the development of an analytical method about dichlorprop (DCPP; 2-(2,4-dichlorophenoxy)propionic acid) which is a plant growth regulator, a synthetic auxin for agricultural commodities. DCPP prevents falling of fruits during their growth periods. However, the overdose of DCPP caused the unwanted maturing time and reduce the safe storage period. If we take fruits with exceeding maximum residue limits, it could be harmful. Therefore, this study presented the analytical method of DCPP in agricultural commodities for the nation-wide pesticide residues monitoring program of the Ministry of Food and Drug Safety. METHODS AND RESULTS: We adopted the analytical method for DCPP in agricultural commodities by gas chromatograph in cooperated with Electron Capture Detector(ECD). Sample extraction and purification by ion-associated partition method were applied, then quantitation was done by GC/ECD with DB-17, a moderate polarity column under the temperature-rising condition with nitrogen as a carrier gas and split-less mode. Standard calibration curve presented linearity with the correlation coefficient ($r^2$) > 0.9998, analysed from 0.1 to 2.0 mg/L concentration. Limit of quantitation in agricultural commodities represents 0.05 mg/kg, and average recoveries ranged from 78.8 to 102.2%. The repeatability of measurements expressed as coefficient of variation (CV %) was less than 9.5% in 0.05, 0.10, and 0.50 mg/kg. CONCLUSION(S): Our newly improved analytical method for DCPP residues in agricultural commodities was applicable to the nation-wide pesticide residues monitoring program with the acceptable level of sensitivity, repeatability and reproducibility.