• Journal of Mushroom
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• v.21 no.3
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• pp.145-149
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• 2023

This study was conducted to reduce the phenomenon of the biased cultivation of certain mushroom varieties and to develop a competitive variety of Pleurotus nebrodensis. We have collected and tested characteristics of genetic resources from domestic and overseas varieties since 2015. We bred the domestic variety 'Boram'. The optimal temperature was 26~29℃ for mycelial growth and 15~18℃ for fruit body growth temperature. This variety was similar to the control variety (Uram) in terms of the number of cultivation days and yield per bottle. The shape of the new cultivar was round, whereas that of the control group was spatula-like. The yield was 181.1 g/bottle, which was statistically similar to that of the control variety. When incubating the parent and control varieties, the replacement line was clear. Moreover, polymerase chain reaction analysis of mycelial DNA resulted in different band patterns between the parent and control varieties, confirming the hybrid species.

• International Journal of Computer Science & Network Security
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• v.23 no.4
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• pp.55-68
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• 2023

In recent years, the Television White Space (TVWS) has attracted the interest of many researchers due to its propagation characteristics obtainable between 470MHz and 790MHz spectrum bands. The plenty of unused channels in the TV spectrum allows the secondary users (SUs) to use the channels for broadband services especially in rural areas. However, when the number of SUs increases in the TVWS wireless network the aggregate interference also increases. Aggregate interferences are the combined harmful interferences that can include both co-channel and adjacent interferences. The aggregate interference on the side of Primary Users (PUs) has been extensively scrutinized. Therefore, resource allocation (power and spectrum) is crucial when designing the TVWS network to avoid interferences from Secondary Users (SUs) to PUs and among SUs themselves. This paper proposes a model to improve the resource allocation for reducing the aggregate interface among SUs for broadband services in rural areas. The proposed model uses joint power and spectrum hybrid Firefly algorithm (FA), Genetic algorithm (GA), and Particle Swarm Optimization algorithm (PSO) which is considered the Co-channel interference (CCI) and Adjacent Channel Interference (ACI). The algorithm is integrated with the admission control algorithm so that; there is a possibility to remove some of the SUs in the TVWS network whenever the SINR threshold for SUs and PU are not met. We considered the infeasible system whereby all SUs and PU may not be supported simultaneously. Therefore, we proposed a joint spectrum and power allocation with an admission control algorithm whose better complexity and performance than the ones which have been proposed in the existing algorithms in the literature. The performance of the proposed algorithm is compared using the metrics such as sum throughput, PU SINR, algorithm running time and SU SINR less than threshold and the results show that the PSOFAGA with ELGR admission control algorithm has best performance compared to GA, PSO, FA, and FAGAPSO algorithms.

• 한국정보교육학회:학술대회논문집
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• 2021.08a
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• pp.377-383
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• 2021

The purpose of this study is to present the direction of elementary school AI education by analyzing cases of classes related to AI education in actual school settings. For this purpose, 19 classes were collected as elementary school class cases based on AI education. According to the result of analyzing the class case, it was confirmed that the class was designed in a hybrid aspect of learning content and method using AI. As a result of analyzing the achievement standards and learning goals, action verbs related to memory, understanding, and application were found in 8 classes using AI from a tool perspective. When class was divided into introduction, development, and rearrangement stages, the AI education element appeared the most in the development stage. On the other hand, when looking at the ratio of learning content and learning method of AI education elements in the development stage, the learning time for approaching AI education as a learning method was overwhelmingly high. Based on this, the following implications were derived. First, when designing the curriculum for schools and grades, it should be designed to comprehensively deal with AI as a learning content and method. Second, to supplement the understanding of AI, in the short term, it is necessary to secure the number of hours in practical subjects or creative experience activities, and in the long term, it is necessary to secure information subjects.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.29 no.5B
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• pp.397-408
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• 2009

In this study, a stochastic precipitation generation framework for simultaneous simulation of daily precipitation at multiple sites is presented. The precipitation occurrence at individual sites is generated using hybrid-order Markov chain model which allows higher-order dependence for dry sequences. The precipitation amounts are reproduced using Anscombe residuals and gamma distributions. Multisite spatial correlations in the precipitation occurrence and amount series are represented with spatially correlated random numbers. The proposed model is applied for a network of 17 locations in the middle of Korean peninsular. Evaluation statistics are reported by generating 50 realizations of the precipitation of length equal to the observed record. The analysis of results show that the model reproduces wet day number, wet and dry day spell, and mean and standard deviation of wet day amount fairly well. However, mean values of 50 realizations of generated precipitation series yield around 23% Root Mean Square Errors (RMSE) of the average value of observed maximum numbers of consecutive wet and dry days and 17% RMSE of the average value of observed annual maximum precipitations for return periods of 100 and 200 years. The provided model also reproduces spatial correlations in observed precipitation occurrence and amount series accurately.

• International Journal of Computer Science & Network Security
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• v.24 no.9
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• pp.30-40
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• 2024

Building an accurate 3-D spatial road network model has become an active area of research now-a-days that profess to be a new paradigm in developing Smart roads and intelligent transportation system (ITS) which will help the public and private road impresario for better road mobility and eco-routing so that better road traffic, less carbon emission and road safety may be ensured. Dealing with such a large scale 3-D road network data poses challenges in getting accurate elevation information of a road network to better estimate the CO₂ emission and accurate routing for the vehicles in Internet of Vehicle (IoV) scenario. Clustering and regression techniques are found suitable in discovering the missing elevation information in 3-D spatial road network dataset for some points in the road network which is envisaged of helping the public a better eco-routing experience. Further, recently Explainable Artificial Intelligence (xAI) draws attention of the researchers to better interprete, transparent and comprehensible, thus enabling to design efficient choice based models choices depending upon users requirements. The 3-D road network dataset, comprising of spatial attributes (longitude, latitude, altitude) of North Jutland, Denmark, collected from publicly available UCI repositories is preprocessed through feature engineering and scaling to ensure optimal accuracy for clustering and regression tasks. K-Means clustering and regression using Support Vector Machine (SVM) with radial basis function (RBF) kernel are employed for 3-D road network analysis. Silhouette scores and number of clusters are chosen for measuring cluster quality whereas error metric such as MAE ( Mean Absolute Error) and RMSE (Root Mean Square Error) are considered for evaluating the regression method. To have better interpretability of the Clustering and regression models, SHAP (Shapley Additive Explanations), a powerful xAI technique is employed in this research. From extensive experiments , it is observed that SHAP analysis validated the importance of latitude and altitude in predicting longitude, particularly in the four-cluster setup, providing critical insights into model behavior and feature contributions SHAP analysis validated the importance of latitude and altitude in predicting longitude, particularly in the four-cluster setup, providing critical insights into model behavior and feature contributions with an accuracy of 97.22% and strong performance metrics across all classes having MAE of 0.0346, and MSE of 0.0018. On the other hand, the ten-cluster setup, while faster in SHAP analysis, presented challenges in interpretability due to increased clustering complexity. Hence, K-Means clustering with K=4 and SVM hybrid models demonstrated superior performance and interpretability, highlighting the importance of careful cluster selection to balance model complexity and predictive accuracy.

• Journal of Korean Society of Forest Science
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• v.31 no.1
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• pp.8-20
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• 1976

For study on the variation of natural stand, three populations of Pinus densiflora S. et Z. were selected at samsanri Yongogmyun Myongjugun Kangwondo (4), Hawonri seomyun Uljingun Kyongbuk (5), and Emogdong Suweon Kyongkido (6) successibely after the selection of three population in 1974. Twenty individual trees were chosen from each population and the morphological characteristics of trees, needle and wood properties were investigated on the trees. The results are summerized as follows; 1. Serration density, resin canal number in needle did not show significant differences, however stomata row number in the both sides of needle showed highly significant differences among 3 populations. But significant differences were calculated among individual trees in a population regarding any character of needles. 2. Ail population had high correlation on the stomata row between abaxial and adaxial side of needle. 3. The Myongjungun population showed the highest value of resin duct index, which means the population had the highest degree of hybrid character. 4. The ring segment width and summerwood percentage in the wood properties had significant differences, and yet specific gravity and tracheid length had not significant differences statistically among 3 populations. But all the values were significant statistically among the ring segments within population. 5. The ring segment width decreased rapidly with increasing tree age but summerwood percentage, specific gravity, tracheid length increased slowly to the middle age of tree and then decreased slowly after the age. But the patterns of decrease or increase were some different by population. 6. The values of Uljingun population were generally high in the coefficient of variation on all the needle characters. And the values of Suweon population were always the highest and those of Myongjugun population the lowest in the coefficient of variation on all the wood properties.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.18
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• pp.28-53
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• 1975

Experiments on the physiological root activity and its related characteristics of rice varieties were carried out in order to obtain some basic informations for the application of the results obtained to a rice breeding program. A significant positive correlation was found not only among the various characteristics related to conducting and ventilating systems which connects top and root of rice plant, but also between these characteristics and root activity. On the other hand, a significant difference in physiological root activity was recognized among different varieties and also between different groups of recognized 7 rice varieties differing in the their origin. It was also found that varieties with higher root activity (root activity indices) after ear formation stage tended to have more number of lower green leaves and consequently resulted in higher grain yield. Therefore, it may be possible to diagnose indirectly the root activity by examining the number of green leaves of the rice plant at later growth stage when breeders make selections of parent material for crossing or of hybrid lines in pedigree nurseries.

• Journal of Intelligence and Information Systems
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• v.17 no.4
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• pp.241-254
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• 2011

Financial time-series forecasting is one of the most important issues because it is essential for the risk management of financial institutions. Therefore, researchers have tried to forecast financial time-series using various data mining techniques such as regression, artificial neural networks, decision trees, k-nearest neighbor etc. Recently, support vector machines (SVMs) are popularly applied to this research area because they have advantages that they don't require huge training data and have low possibility of overfitting. However, a user must determine several design factors by heuristics in order to use SVM. For example, the selection of appropriate kernel function and its parameters and proper feature subset selection are major design factors of SVM. Other than these factors, the proper selection of instance subset may also improve the forecasting performance of SVM by eliminating irrelevant and distorting training instances. Nonetheless, there have been few studies that have applied instance selection to SVM, especially in the domain of stock market prediction. Instance selection tries to choose proper instance subsets from original training data. It may be considered as a method of knowledge refinement and it maintains the instance-base. This study proposes the novel instance selection algorithm for SVMs. The proposed technique in this study uses genetic algorithm (GA) to optimize instance selection process with parameter optimization simultaneously. We call the model as ISVM (SVM with Instance selection) in this study. Experiments on stock market data are implemented using ISVM. In this study, the GA searches for optimal or near-optimal values of kernel parameters and relevant instances for SVMs. This study needs two sets of parameters in chromosomes in GA setting : The codes for kernel parameters and for instance selection. For the controlling parameters of the GA search, the population size is set at 50 organisms and the value of the crossover rate is set at 0.7 while the mutation rate is 0.1. As the stopping condition, 50 generations are permitted. The application data used in this study consists of technical indicators and the direction of change in the daily Korea stock price index (KOSPI). The total number of samples is 2218 trading days. We separate the whole data into three subsets as training, test, hold-out data set. The number of data in each subset is 1056, 581, 581 respectively. This study compares ISVM to several comparative models including logistic regression (logit), backpropagation neural networks (ANN), nearest neighbor (1-NN), conventional SVM (SVM) and SVM with the optimized parameters (PSVM). In especial, PSVM uses optimized kernel parameters by the genetic algorithm. The experimental results show that ISVM outperforms 1-NN by 15.32%, ANN by 6.89%, Logit and SVM by 5.34%, and PSVM by 4.82% for the holdout data. For ISVM, only 556 data from 1056 original training data are used to produce the result. In addition, the two-sample test for proportions is used to examine whether ISVM significantly outperforms other comparative models. The results indicate that ISVM outperforms ANN and 1-NN at the 1% statistical significance level. In addition, ISVM performs better than Logit, SVM and PSVM at the 5% statistical significance level.

• Korean Journal of Plant Taxonomy
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• v.39 no.1
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• pp.12-23
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• 2009

To verify hybridity of Asplenium castaneo-viride, external morphology, spore morphology, anatomy and chromosomes of the species and of the two presumed parental species, A. incisum and A. ruprechtii, were examined. A. castaneo-viride usually had 1-pinnately divided frond. However, some individuals had almost simple fronds with pinnatisect basal parts similar to A. ruprechtii, while others had fronds similar to A. incisum in having oblanceolate blades and basal pinnae with triangular, 2-3 lobed apices. On the surface of the spores, sculpturing consisted of folds that were usually prominent; forming long wings, and irregular or incomplete reticulation. However, reticulation patterns varied among species. A. castaneo-viride showed a wide range of variation from sparse to dense patterns, whereas A. incisum showed only from sparse to intermediate patterns. A. ruprechtii showed from intermediate to dense patterns. The spore size of A. castaneo-viride was $54.63{\mu}m$, larger than other two species ($47.81{\mu}m$ in A. incisum and $44.22{\mu}m$ in A. ruprechtii). The level of undulation of epidermal cell wall was also different. A. incisum had the most shallowly undulated wall, and A. castaneo-viride had a pattern intermediate between the two presumed parental species. This same patterns was recognized in the density of stomata. The density of $45.91/mm^2$ in A. castaneo-viride was intermediate between the two presumed parental species ($67.00/mm^2$ in A. incisum, and $37.86/mm^2$ in A. ruprechtii). Chromosome number was constant (2x =2n = 72) as in A. incisum and A. ruprechtii. However, A. castaneo-viride showed a different ploidy level. The populations of Mt. Mai (Jeonbuk province) and Mt. Duryun (Jeonnam province) were diploid (2n = 72) which is a new record for this taxon, whereas the population of Mt. Buram (Seoul) was tetraploid (2n = 144). Conclusively, A. castaneo-viride was revealed to be a hybrid of A. ruprechtii and A. incisum based on evidence involving leaves, spores, epidermal cells, stomata and chromosome number.

• Korean Journal of Animal Reproduction
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• v.25 no.2
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• pp.163-169
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• 2001

OSBA(oocytes-sperm binding assay) is a tool developed for rapid test of optimal condition of IVF medium and protein source by binding ability of mouse sperm and egg. Mouse oocyte-cumulus complexes were prepared by removing of the cumulus cells with 0.1% hyaluronidase. 10$\pm$2 oocytes per 30 ${mu}ell$ medium drop were inseminated with 3 ${mu}ell$ sperm suspension and were cultured f3r 3 hours and 24 hours, respectively. And the oocytes were recovered gently and the No. of sperm bound on oocytes were counted. In the Exp. 1, the ratio of oocytes bound with one sperm at least were 60.2%(50/83), 2%(2/77) and 100%(79/79) in the medium with no protein, FBS(15%, v/v) and BSA(0.4%. w/v), respectively, Fetal bovine serum(FBS) seriously inhibited sperm binding on oocyte, although bovine serum albumin(BSA) promoted the binding ability. The inhibiting effect of FBS was dependent on the concentration of FBS. The sperm binding ability according to oocyte maturity was tested in the Exp. 2. There was no significant difference between Met. II (mature) and Met. I (intermediate mature) oocytes in the number of oocytes bound with sperm and the number of sperm bound on oocytes. Finally, in Exp. 3, two batches of Ham's F10 medium with good and poor quality by OSBA were tested (The ratios of embryos developed from PN 1-cell stage to hatched blastocyst; 25% vs. 70%). In the medium with good quality, sperm binding ability was significantly increased (P ＜ 0.05). The ratio of oocytes bound with one sperm at least was 66% and 90% in the medium with poor and good quality, respectively. Conclusively, It was possible to test IVF medium condition rapidly and easily by OSBA.