• Research in Plant Disease
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• v.28 no.1
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• pp.32-38
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• 2022

A survey of Barley yellow dwarf virus (BYDV) was conducted in major oat-growing areas of Korea in 2020. BYDV is an economically important pathogen of cereal crops that can be transmitted by aphids. The present study evaluated the genetic composition of BYDV in oat from eight geographical areas in Korea. Multiplex reverse transcription-polymerase chain reaction was used to screen 322 oat leaf samples for six BYDV strains (PAV, MAV, SGV, PAS, RPV, and RMV). The 125 samples (~39%) tested positive for BYDV. BYDV-PAV, BYDV-SGV, BYDV-PAS, and BYDV-RPV were detected from oat in different areas. Most of the BYDV-infected samples were assigned to subgroup I (n=112). The results indicate that BYDV-PAV could be dominant throughout Korea. Also, the phylogenetic analysis of coat protein sequences indicated that 23 BYDV isolates from Korea could be separated into two clades, which exhibited high nucleotide sequence similarity. In conclusion, the present survey provides a BYDV infection assessment for domestic oat varieties in Korea and basic information for the development of BYDV control measures in Korea's oat industry.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.4
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• pp.1276-1295
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• 2023

Sensor networks are now an essential aspect of wireless communication, especially with the introduction of new gadgets and protocols. Their ability to be deployed anywhere, especially where human presence is undesirable, makes them perfect choices for remote observation and control. Despite their vast range of applications from home to hostile territory monitoring, limited battery power remains a limiting factor in their efficacy. To analyze and transmit data, it requires intelligent use of available battery power. Several studies have established effective routing algorithms based on clustering. However, choosing optimal cluster heads and similarity measures for clustering significantly increases computing time and cost. This work proposes and implements a simple two-phase technique of route creation and maintenance to ensure route reliability by employing nature-inspired ant colony optimization followed by the fuzzy decision engine (FDE). Benchmark methods such as PSO, ACO and GWO are compared with the proposed HRCM's performance. The objective has been focused towards establishing the superiority of proposed work amongst existing optimization methods in a standalone configuration. An average of 15% improvement in energy consumption followed by 12% improvement in latency reduction is observed in proposed hybrid model over standalone optimization methods.

• Cartoon and Animation Studies
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• s.40
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• pp.477-496
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• 2015

Emotional awareness is the image of a person is represented by different tendencies. Currently, the emotion computing to objectively evaluate the emotion recognition research is being actively studied. However, existing emotional computing research has many problems to run. First, the non-objective in emotion recognition if it is inaccurate. Second, the correlation between the emotion recognition is unclear points. So to test the regularity of image sensitivity to the need of the present study is to control emotions in the computing system. In addition, the screen number of the emotion recognized for the purpose of this study, applying the method of objective image emotional computing system and compared with a similar degree of emotion of the person. The key features of the image emotional computing system calculates the emotion recognized as numbered digital form. And to study the background of emotion computing is a key advantage of the effect of the James A. Russell for digitization of emotion (Core Affect). Pleasure emotions about the core axis (X axis) of pleasure and displeasure, tension (Y-axis) axis of tension and relaxation of emotion, emotion is applied to the computing research. Emotional axis with associated representative sensibility very happy, excited, elated, happy, contentment, calm, relaxing, quiet, tired, helpless, depressed, sad, angry, stress, anxiety, pieces 16 of tense emotional separated by a sensibility ComputingIt applies. Course of the present study is to use the color of the color key elements of the image computing formula sensitivity, brightness, and saturation applied to the sensitivity property elements. Property and calculating the rate sensitivity factors are applied to the importance weight, measured by free-level sensitivity score (X-axis) and the tension (Y-axis). Emotion won again expanded on the basis of emotion crossed point, and included a representative selection in Sensibility size of the top five ranking representative of the main emotion. In addition, measuring the emotional image of a person with 16 representative emotional score, and separated by a representative of the top five senses. Compare the main representative of the main representatives of Emotion and Sensibility people aware of the sensitivity of the results to verify the similarity degree computing emotion emotional emotions depending on the number of representative matches. The emotional similarity computing results represent the average concordance rate of major sensitivity was 51%, representing 2.5 sensibilities were consistent with the person's emotion recognition. Similar measures were the degree of emotion computing calculation and emotion recognition in this study who were given the objective criteria of the sensitivity calculation. Future research will need to be maintained weight room and the study of the emotional equation of a higher concordance rate improved.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.33 no.1
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• pp.45-52
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• 2015

The interoperability of multi-source data has become more important due to various digital maps, produced from public institutions and enterprises. In this study, the automatic matching algorithm of multi-source building data using hierarchical matching was proposed. At first, we divide digital maps into blocks and perform the primary geometric registration of buildings with the ICP algorithm. Then, corresponding building pairs were determined by evaluating the similarity of overlap area, and the matching threshold value of similarity was automatically derived by the Otsu binary thresholding. After the first matching, we extracted error matching candidates buildings which are similar with threshold value to conduct the secondary ICP matching and to make a matching decision using turning angle function analysis. For the evaluation, the proposed method was applied to representative public digital maps, road name address map and digital topographic map 2.0. As a result, the F measures of matching and non-matching buildings increased by 2% and 17%, respectively. Therefore, the proposed method is efficient for the matching of building polygons from multi-source digital maps.

• Journal of Korean Society for Geospatial Information Science
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• v.25 no.1
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• pp.37-46
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• 2017

Recently, disaster caused by social factors is frequently occurring in Korea. Prediction about what crisis could happen is difficult, raising the citizen's concern. In this study, we developed a program to acquire tweet data by applying Python language based Tweepy plug-in, regarding social disasters such as 'Nonspecific motive crimes' and 'Oxy' products. These data were used to evaluate psychological trauma and anxiety of citizens through the text clustering analysis and the opinion mining analysis of the R Studio program after natural language processing. In the analysis of the 'Oxy' case, the accident of Sewol ferry, the continual sale of Oxy products of the Oxy had the highest similarity and 'Nonspecific motive crimes', the coping measures of the government against unexpected incidents such as the 'incident' of the screen door, the accident of Sewol ferry and 'Nonspecific motive crime' due to misogyny in Busan, had the highest similarity. In addition, the average index of the Citizens sentiment score in Nonspecific motive crimes was more negative than that in the Oxy case by 11.61%p. Therefore, it is expected that the findings will be utilized to predict the mental health of citizens to prevent future accidents.

• Journal of Korea Spatial Information System Society
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• v.8 no.2 s.17
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• pp.109-120
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• 2006

This paper addresses techniques for predicting a future path of an object moving on a road network. Most prior methods for future prediction mainly focus their attention on objects moving in Euclidean space. A variety of applications such as telematics, however, deal with objects that move only over road networks in most cases, thereby requiring an effective method of future prediction of moving objects on road networks. In this paper, we propose a novel method for predicting a future path of an object by analyzing past trajectories whose changing pattern is similar to that of a current trajectory of a query object. We devise a new function that measures a similarity between trajectories by reflecting the characteristics of road networks. By using this function, we predict a future path of a given moving object as follows: First, we search for candidate trajectories that contain subtrajectories similar to a given query trajectory by accessing past trajectories stored in moving object databases. Then, we predict a future path of a query object by analyzing the moving paths along with a current position to a destination of candidate trajectories thus retrieved. Also, we suggest a method that improves the accuracy of path prediction by regarding moving paths that have just small differences as the same group.

• Korean Journal of Environment and Ecology
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• v.31 no.5
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• pp.433-443
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• 2017

Securing the species compositional integrity (typicalness and representativeness) is the essential prerequisite for an integrated management of vegetation resources using the phytosociological $relev\acute{e}s$ and plant communities of the Z.-M. school. This study is intended to develop a tool for qualitative and quantitative evaluation of species compositional homotoneity of a set of $relev\acute{e}s$ per syntaxon. The new homotoneities, actual homotoneity ($H_{act}$), and optimal homotoneity ($H_{opt}$) taking into account the heterogeneous factors of $relev\acute{e}s$ are proposed. The correlations between the floristic variables such as the vegetation type, the new homotoneities, and the previously studied homogeneous measures (e.g. Pfeiffer's homogeneity, basic homotoneity-coefficient, corrected homotoneity-coefficient, and mean floristic similarity) are analyzed by using Spearman's rank correlation coefficient. $H_{act}$ and $H_{opt}$ are effective in determining the difference of inter-synthesized units and of inter-$relev\acute{e}s$, respectively. $H_{act}$ is the homotoneity that is the most independent of the number of $relev\acute{e}s$. On actual vegetation with long-term human impact in the Korean Peninsula, $H_{opt}$ has become an aid to the more precise understanding of $H_{act}$ as substantive homogeneousness of species composition of syntaxa. It is expected that $H_{act}$ and $H_{opt}$ can be used for the selection of a sort of homogeneous vegetation data to build a phytosociological $relev\acute{e}$-database with consistency and objectiveness for national vegetation resources.

• Korean Journal of Environment and Ecology
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• v.33 no.1
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• pp.64-74
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• 2019

The purpose of this study is to assess the degree of vegetation recovery such as the vegetation change and the effect of artificial restoration measures according to the number of years since the restoration works at the damaged Jungbong and Nuebong area in Mudeungsan National Park. We set up a total of 21 survey areas including 11 monitoring areas to analyze the flora, relative dominance, species diversity, and similarity in the restored site after relocation of Zungbong army base in 1996 and the restored site after the demolition of Neeebong telecommunication facility in 1999 and 10 control areas in the adjacent natural forest to assess the vegetation recovery in the restored sites and the nearby natural forest. The Mean Similarity Index of seed composition was relatively low at 3.5% in the Jungbong restoration site 17 years after the restoration, and the height of shrub layer, in which azaleas and furred azaleas appeared, recovered to the level of 82.6%. We concluded that it is necessary to continue monitoring the restored sites to develop the recovery assessment method and recovery work technology for sub-alpine areas in Mudeungsan National Park and other national park areas.

• Journal of Korea Water Resources Association
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• v.52 no.5
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• pp.337-347
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• 2019

This study proposes the framework to select the representative general circulation model (GCM) for climate change projection. The grid-based results of GCMs were transformed to all considered meteorological stations using inverse distance weighted (IDW) method and its results were compared to the observed precipitation. Six quantile mapping methods and random forest method were used to correct the bias between GCM's and the observation data. Thus, the empirical quantile which belongs to non-parameteric transformation method was selected as a best bias correction method by comparing the measures of performance indicators. Then, one of the multi-criteria decision techniques, TOPSIS (Technique for Order of Preference by Ideal Solution), was used to find the representative GCM using the performances of four GCMs after the bias correction using empirical quantile method. As a result, GISS-E2-R was the best and followed by MIROC5, CSIRO-Mk3-6-0, and CCSM4. Because these results are limited several GCMs, different results will be expected if more GCM data considered.

• Journal of the Korea Society of Computer and Information
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• v.28 no.3
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• pp.25-33
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• 2023

Noise generated during the acquisition and transmission of CT images acts as a factor that degrades image quality. Therefore, noise removal to solve this problem is an important preprocessing process in image processing. In this paper, we remove noise by using a deformable convolutional autoencoder (DeCAE) model in which deformable convolution operation is applied instead of the existing convolution operation in the convolutional autoencoder (CAE) model of deep learning. Here, the deformable convolution operation can extract features of an image in a more flexible area than the conventional convolution operation. The proposed DeCAE model has the same encoder-decoder structure as the existing CAE model, but the encoder is composed of deformable convolutional layers and the decoder is composed of conventional convolutional layers for efficient noise removal. To evaluate the performance of the DeCAE model proposed in this paper, experiments were conducted on CT images corrupted by various noises, that is, Gaussian noise, impulse noise, and Poisson noise. As a result of the performance experiment, the DeCAE model has more qualitative and quantitative measures than the traditional filters, that is, the Mean filter, Median filter, Bilateral filter and NL-means method, as well as the existing CAE models, that is, MAE (Mean Absolute Error), PSNR (Peak Signal-to-Noise Ratio) and SSIM. (Structural Similarity Index Measure) showed excellent results.