• Korean Journal of Plant Resources
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• v.36 no.5
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• pp.496-507
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• 2023

The in vitro organogenesis is one of important issues in plant embryology, and somaclonal variations are existing in calli and/or regenerants induced from a process of the organogenesis with in vitro circumstances. In this study, expressions of organogenesis-related genes were evaluated and genetic stability of regenerants derived from the process of in vitro organogenesis were measured using ISSR markers in Imperata cylindrica 'Rubra', Poaceae. The expressions of organogenesis-related genes were detected all of regenerants at the process of the organogenesis. All ISSR markers produced with an average of 71 bands per in vitro-cultured regenerants, and the scorable bands were varied from two to eight with an average of 5.14 bands per a primer. The polymorphism rates of the in vitro regenerants were higher than that of mother plants (1.4%), showing 4.1% (pot-cultured regenerants), 4.3% (field-cultured regenerants), 4.2% (in vitro-cultured regenerants), 5.6% (calli with green shoots) and 1.4% (calli), respectively. The genetic similarity matrix (GSM) among all accessions ranged from 0.747 to 1.0 with a mean of 0.868. GSM of the regenerants showed differences (from 0.972 to 1.00) compared with that of mother plants (0.991). According to the clustering analysis, two independent groups were divided into; the one is mother plants and regenerants cultured at room and open field, the other is regenerants cultured in vitro. The results give a new insight for understanding the dynamics of organogenesis in monocot plant.

• Journal of Korea Water Resources Association
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• v.57 no.7
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• pp.437-449
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• 2024

Rainfall-runoff prediction studies using deep learning while considering catchment attributes have been gaining attention. In this study, we selected two models: the Transformer model, which is suitable for large-scale data training through the self-attention mechanism, and the LSTM-based multi-state-vector sequence-to-sequence (LSTM-MSV-S2S) model with an encoder-decoder structure. These models were constructed to incorporate catchment attributes and predict the inflow of 10 multi-purpose dam watersheds in South Korea. The experimental design consisted of three training methods: Single-basin Training (ST), Pretraining (PT), and Pretraining-Finetuning (PT-FT). The input data for the models included 10 selected watershed attributes along with meteorological data. The inflow prediction performance was compared based on the training methods. The results showed that the Transformer model outperformed the LSTM-MSV-S2S model when using the PT and PT-FT methods, with the PT-FT method yielding the highest performance. The LSTM-MSV-S2S model showed better performance than the Transformer when using the ST method; however, it showed lower performance when using the PT and PT-FT methods. Additionally, the embedding layer activation vectors and raw catchment attributes were used to cluster watersheds and analyze whether the models learned the similarities between them. The Transformer model demonstrated improved performance among watersheds with similar activation vectors, proving that utilizing information from other pre-trained watersheds enhances the prediction performance. This study compared the suitable models and training methods for each multi-purpose dam and highlighted the necessity of constructing deep learning models using PT and PT-FT methods for domestic watersheds. Furthermore, the results confirmed that the Transformer model outperforms the LSTM-MSV-S2S model when applying PT and PT-FT methods.

• Journal of Intelligence and Information Systems
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• v.21 no.4
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• pp.111-131
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• 2015

There are only a handful number of research conducted on pattern analysis of corporate distress as compared with research for bankruptcy prediction. The few that exists mainly focus on audited firms because financial data collection is easier for these firms. But in reality, corporate financial distress is a far more common and critical phenomenon for non-audited firms which are mainly comprised of small and medium sized firms. The purpose of this paper is to classify non-audited firms under distress according to their financial ratio using data mining; Self-Organizing Map (SOM). SOM is a type of artificial neural network that is trained using unsupervised learning to produce a lower dimensional discretized representation of the input space of the training samples, called a map. SOM is different from other artificial neural networks as it applies competitive learning as opposed to error-correction learning such as backpropagation with gradient descent, and in the sense that it uses a neighborhood function to preserve the topological properties of the input space. It is one of the popular and successful clustering algorithm. In this study, we classify types of financial distress firms, specially, non-audited firms. In the empirical test, we collect 10 financial ratios of 100 non-audited firms under distress in 2004 for the previous two years (2002 and 2003). Using these financial ratios and the SOM algorithm, five distinct patterns were distinguished. In pattern 1, financial distress was very serious in almost all financial ratios. 12% of the firms are included in these patterns. In pattern 2, financial distress was weak in almost financial ratios. 14% of the firms are included in pattern 2. In pattern 3, growth ratio was the worst among all patterns. It is speculated that the firms of this pattern may be under distress due to severe competition in their industries. Approximately 30% of the firms fell into this group. In pattern 4, the growth ratio was higher than any other pattern but the cash ratio and profitability ratio were not at the level of the growth ratio. It is concluded that the firms of this pattern were under distress in pursuit of expanding their business. About 25% of the firms were in this pattern. Last, pattern 5 encompassed very solvent firms. Perhaps firms of this pattern were distressed due to a bad short-term strategic decision or due to problems with the enterpriser of the firms. Approximately 18% of the firms were under this pattern. This study has the academic and empirical contribution. In the perspectives of the academic contribution, non-audited companies that tend to be easily bankrupt and have the unstructured or easily manipulated financial data are classified by the data mining technology (Self-Organizing Map) rather than big sized audited firms that have the well prepared and reliable financial data. In the perspectives of the empirical one, even though the financial data of the non-audited firms are conducted to analyze, it is useful for find out the first order symptom of financial distress, which makes us to forecast the prediction of bankruptcy of the firms and to manage the early warning and alert signal. These are the academic and empirical contribution of this study. The limitation of this research is to analyze only 100 corporates due to the difficulty of collecting the financial data of the non-audited firms, which make us to be hard to proceed to the analysis by the category or size difference. Also, non-financial qualitative data is crucial for the analysis of bankruptcy. Thus, the non-financial qualitative factor is taken into account for the next study. This study sheds some light on the non-audited small and medium sized firms' distress prediction in the future.

• Journal of Sasang Constitutional Medicine
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• v.8 no.1
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• pp.247-294
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• 1996

By means of the statistical data which has been collected with newly revised QSCC made use of the outpatient group examined at Kyung-Hee Medical Center and an open ordinary person group, the author proceeded statistical analysis for the validation study of the revised questionnaire itself. First, check the accurate discrimination rate by performing discriminant analysis on the statistical data of the patient group. And next, sought T-score by applying the norms gained in process of standadization of the open ordinary person group to the Sasang scale score of the outpatient group and investigated the distinctive feature between the subpopulations which was devided in the process of multivarite cluster analysis. The result was summarized as follows ; 1. The validity of the questionnaire was established through the fact that the accurate discrimination rate the ratio between predicted group and actual group was figured out 70.08%. 2. At the profile analysis the response to the relevant scale showed notable upward tendency in each constitutional group and therefore it seems to be pertinent in the field of constitutional discrimination. 3. In the observation of the power of expression through the profile analysis of each constitutional group the Soyang group demonstrated the most remarkable outcome, the Soeum group was the most inferior and the Taieum group revealed a sort of dual property. 4. What is called the group of seceder out of three subpopulation of each constitutional group distinguished definitely from the contrasted groups at the point of the distinctive profile feature and the content is like following description. (1) The seceder group of Soyang-in showed considerably passive disposition differently from general character of ordinary Soyang group and an appearance attracting the attention is that they demonstrated comparatively higher response at Soeum scale (2) The seceder group of Taieum-in gained low scores in general that informed the passive disposition of the group and the other way of the general property of Taieum group which showed accompanied ascension in Taiyang-Taieum scales they demonstrated sharply declined score at Taiyang scale (3) The seceder group of Soeum-in demonstrated distinctive property similar to the profile feature of Soyang group and it notifies that the passive property of Soeum group was diluted for the most part. According to the above result, the validity of newly revised questionnaire has been proven successfully and the property of seceder groups could be noticed to some degree through the profile analysis on the course of this study. The result of this study is expected to use as a research materials to produce next edition of the questionnaire and it is regarded that further inquisition about the difference between the seceder group and the contrasted group is required for the promotion of the questionnaire as it refered several times in the contents of the main discourse.

• Journal of Intelligence and Information Systems
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• v.23 no.4
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• pp.77-110
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• 2017

Recently, the diversification and individualization of consumption patterns through the web and mobile devices based on the Internet have been rapid. As this happens, the efficient operation of the offline store, which is a traditional distribution channel, has become more important. In order to raise both the sales and profits of stores, stores need to supply and sell the most attractive products to consumers in a timely manner. However, there is a lack of research on which SKUs, out of many products, can increase sales probability and reduce inventory costs. In particular, if a company sells products through multiple in-store stores across multiple locations, it would be helpful to increase sales and profitability of stores if SKUs appealing to customers are recommended. In this study, the recommender system (recommender system such as collaborative filtering and hybrid filtering), which has been used for personalization recommendation, is suggested by SKU recommendation method of a store unit of a distribution company that handles a homogeneous brand through a plurality of sales stores by country and region. We calculated the similarity of each store by using the purchase data of each store's handling items, filtering the collaboration according to the sales history of each store by each SKU, and finally recommending the individual SKU to the store. In addition, the store is classified into four clusters through PCA (Principal Component Analysis) and cluster analysis (Clustering) using the store profile data. The recommendation system is implemented by the hybrid filtering method that applies the collaborative filtering in each cluster and measured the performance of both methods based on actual sales data. Most of the existing recommendation systems have been studied by recommending items such as movies and music to the users. In practice, industrial applications have also become popular. In the meantime, there has been little research on recommending SKUs for each store by applying these recommendation systems, which have been mainly dealt with in the field of personalization services, to the store units of distributors handling similar brands. If the recommendation method of the existing recommendation methodology was 'the individual field', this study expanded the scope of the store beyond the individual domain through a plurality of sales stores by country and region and dealt with the store unit of the distribution company handling the same brand SKU while suggesting a recommendation method. In addition, if the existing recommendation system is limited to online, it is recommended to apply the data mining technique to develop an algorithm suitable for expanding to the store area rather than expanding the utilization range offline and analyzing based on the existing individual. The significance of the results of this study is that the personalization recommendation algorithm is applied to a plurality of sales outlets handling the same brand. A meaningful result is derived and a concrete methodology that can be constructed and used as a system for actual companies is proposed. It is also meaningful that this is the first attempt to expand the research area of the academic field related to the existing recommendation system, which was focused on the personalization domain, to a sales store of a company handling the same brand. From 05 to 03 in 2014, the number of stores' sales volume of the top 100 SKUs are limited to 52 SKUs by collaborative filtering and the hybrid filtering method SKU recommended. We compared the performance of the two recommendation methods by totaling the sales results. The reason for comparing the two recommendation methods is that the recommendation method of this study is defined as the reference model in which offline collaborative filtering is applied to demonstrate higher performance than the existing recommendation method. The results of this model are compared with the Hybrid filtering method, which is a model that reflects the characteristics of the offline store view. The proposed method showed a higher performance than the existing recommendation method. The proposed method was proved by using actual sales data of large Korean apparel companies. In this study, we propose a method to extend the recommendation system of the individual level to the group level and to efficiently approach it. In addition to the theoretical framework, which is of great value.

• Journal of the Korean Society of Marine Environment & Safety
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• v.27 no.7
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• pp.924-942
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• 2021

The expansion of the Changjiang Diluted Water (CDW) plume during summer is known to be a major factor influencing phytoplankton diversity, community structure, and the regional marine environment of the northern East China Sea (ECS). The discharge of the CDW plume was very high in the summer of 2020, and cruise surveys and stationary monitoring were conducted to understand the dynamics of changes in environmental characteristics and the impact on phytoplankton diversity and community structure. A cruise survey was conducted from August 16 to 17, 2020, using R/V Eardo, and a stay survey at the Ieodo Ocean Research Station (IORS) from August 15 to 21, 2020, to analyze phytoplankton diversity and community structure. The southwestern part of the survey area exhibited low salinity and high chlorophyll a fluorescence under the influence of the CDW plume, whereas the southeastern part of the survey area presented high salinity and low chlorophyll a fluorescence under the influence of the Tsushima Warm Current (TWC). The total chlorophyll a concentrations of surface water samples from 12 sampling stations indicated that nano-phytoplankton (20-3 ㎛) and micro-phytoplankton (> 20 ㎛) were the dominant groups during the survey period. Only stations strongly influenced by the TWC presented approximately 50% of the biomass contributed by pico-phytoplankton (< 3 ㎛). The size distribution of phytoplankton in the surface water samples is related to nutrient supplies, and areas where high nutrient (nitrate) supplies were provided by the CDW plume displayed higher biomass contribution by micro-phytoplankton groups. A total of 45 genera of nano- and micro-phytoplankton groups were classified using morphological analysis. Among them, the dominant taxa were the diatoms Guinardia flaccida and Nitzschia spp. and the dinoflagellates Gonyaulax monacantha, Noctiluca scintillans, Gymnodinium spirale, Heterocapsa spp., Prorocentrum micans, and Tripos furca. The sampling stations affected by the TWC and low in nitrate concentrations presented high concentrations of photosynthetic pico-eukaryotes (PPE) and photosynthetic pico-prokaryotes (PPP). Most sampling stations had phosphate-limited conditions. Higher Synechococcus concentrations were enumerated for the sampling stations influenced by low-nutrient water of the TWC using flow cytometry. The NGS analysis revealed 29 clades of Synechococcus among PPP, and 11 clades displayed a dominance rate of 1% or more at least once in one sample. Clade II was the dominant group in the surface water, whereas various clades (Clades I, IV, etc.) were found to be the next dominant groups in the SCM layers. The Prochlorococcus group, belonging to the PPP, observed in the warm water region, presented a high-light-adapted ecotype and did not appear in the northern part of the survey region. PPE analysis resulted in 163 operational taxonomic units (OTUs), indicating very high diversity. Among them, 11 major taxa showed dominant OTUs with more than 5% in at least one sample, while Amphidinium testudo was the dominant taxon in the surface water in the low-salinity region affected by the CDW plume, and the chlorophyta was dominant in the SCM layer. In the warm water region affected by the TWC, various groups of haptophytes were dominant. Observations from the IORS also presented similar results to the cruise survey results for biomass, size distribution, and diversity of phytoplankton. The results revealed the various dynamic responses of phytoplankton influenced by the CDW plume. By comparing the results from the IORS and research cruise studies, the study confirmed that the IORS is an important observational station to monitor the dynamic impact of the CDW plume. In future research, it is necessary to establish an effective use of IORS in preparation for changes in the ECS summer environment and ecosystem due to climate change.

• Journal of Korean Home Economics Education Association
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• v.18 no.1 s.39
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• pp.65-76
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• 2006

The purposes of this study were to segment adolescents into groups by Satir's communication and self-esteem and to investigate the differences among the groups regarding impulse buying of clothing and clothing behavior. The study distributed the questionnaires to the adolescents who were high school students in seoul. The total respondents were 596. The data were analyzed by factor analysis, k-means cluster analysis, ANOVA, Duncan test, regression and ${\chi}2-test$. Factor analysis showed that impulse buying of clothing had three dimensions: sensitive aspects of products stimulation, marketing situation stimulation and non-Plan stimulation. K-means cluster analysis showed that adolescents were segmented into four groups(blame-high self esteem, placate-high self esteem, blame-low self esteem, placate-low self esteem). The four groups were significantly different in regard to three dimensions of sensitive aspects of products stimulation, marketing situation stimulation and non-plan stimulation. For example, placate-high and low self esteem groups were influenced by sensitive aspects of products stimulation and marketing situation stimulation(-). And blame-high and low self esteem groups were influenced by marketing situation stimulation.

• Korean Journal of Ecology and Environment
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• v.37 no.1 s.106
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• pp.36-46
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• 2004

We evaluated the effect of limiting nutrients and N/P ratio on the growth of phytoplankton in a small eutrophic reservoir from November 2002 to December 2003. Nutrient limitation was investigated seasonally using nutrient enrichment bioassay (NEB). DIN/DTP and TN/TP ratio (by weight) of the reservoir during the study period ranged 17${\sim}$187 and 13${\sim}$60, respectively. Most of nitrogen in the reservoir account for $NO_3$-N, but sharp increase of ammonia was evident during the spring season. Seasonal variation of dissolved inorganic phosphorus concentration was relatively small. DTP ranged 26.5${\sim}$10.1 ${\mu}g\;P\;L^{-1}$, and the highest and lowest concentration was observed in August and December, respectively. Chlorophyll a concentration ranged 28.8${\sim}$109.7 ${\mu}g\;L^{-1}$, and its temporal variation was similar to that of cell density of phytoplankton. Dominant phytoplankton species were Bacillariphyceae (Melosira varians) and Chlorophyceae (Dictyosphaerium puchellum) in Spring (March${\sim}$April). Cyanophyceae, such as Osillatoria spp., Microcystis spp., Aphanizomenon sp. dominated from May to the freezing time. TN/TP ratio ranged from 46 to 13 (Avg. 27${\pm}$6) from June to December when cyanobacteria (Microcystis spp.) dominated. p limitation for algal growth measured in all NEB experiments (17cases), while N limitation occurred in 8 out of 17 cases. The growth rates of phytoplankton slightly increased with decreasing of DIN/DTP ratio. Evident increase was observed in the N/P ratio of > 30, and it was sustained with DTP increase until 50 ${\mu}g\;P\;L^{-1}$. Under the same N/P mass ratio with the different N concentrations (0.07, 0.7and 3.5 mg N $L^{-1}$), Microcystis spp. showed the highest growth rate in the N/P ratio of< 1 with nitrogen concentration of 3.5 mg N $L^{-1}$). The responses of phytoplankton growth to phosphate addition were clearly greater with increase of N concentration. These results indicate that the higher nitrogen concentration in the water likely induce the stronger P-limitation on the phytoplankton growth, while nitrogen deficiency is not likely the case of nutrient limitation.

• Journal of Wetlands Research
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• v.3 no.1
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• pp.1-17
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• 2001

The flora, vegetation structure, distribution of the vascular plants, physico-chemical characteristics of sediment, and nutrient contents of palnts were investigated in the ten disturbed and undisturbed wetlands around the littoral zone of Namgang, Jinju-si, Gyongsangnam-do, Korea from August 7 to August 15 in 1999. 217 taxa of the vascular plants distributed into 2 formas, 26 varieties, 189 species belong to 142 genera under 52 families were sampled or recorded. Dominant species of the undisturbed and the disturbed area were Persicaria thunbergii and Ambrosia artemisiifolia var. elatior, of which importance values were 13.86, and 15.81, respectively. Among 26 species of the naturalized plants, importance value of Ambrosia artemisiifolia var. elatior was highest as 9.54. The ranges of species diversity indices (H') were 1.370~1.819, and highest in the site 1 of the undisturbed area. The ranges of eqitability (J') were 0.779~0.902, and highest in the site 8 of the disturbed area. The ranges of community similarity indices ($CC_s$) were 0.341~0.578 among the ten wetlands, and highest between site 1 and site 2 which were the undisturbed area. The ranges of sediment properties such as pH, conductivity, organic matter, total phosphorus, and total nitrogen were 5.17~7.35, $24.67{\sim}74.33{\mu}mhocm^{-1}$, 1.09~3.82%, 0.0008~0.0034 mg/100g, and 0.06~0.15%, respectively. Nutrient contents of plants such as total nitrogen and total phosphorus were 1.52~2.65% and $0.010{\sim}0.039mg100g^{-1}$, respectively. It was recommended that the establishment of the conservation area was necessary to ensure the habitat for wild life and to maintain the diversity of the vascular hydrophytes and hygrophytes.

• Journal of Environmental Impact Assessment
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• v.26 no.2
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• pp.160-170
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• 2017

The purpose of this study is to perform clustering of the habitat types and to identify the characteristics of species in the habitat types using mammal data (70,562) of the 3rd National Ecosystem Survey conducted from 2006 to 2012. The 15 habitat types recorded in the field-paper of the 3rd National ecosystem survey were reclassified, which was followed by the statistical analysis of mammal habitat types. In the habitat types cluster analysis, non-hierarchical cluster analysis (k-means cluster analysis), hierarchical cluster analysis, and non-metric multidimensional scaling method were applied to 14 habitat types recorded more than 30 times. A total of 7 Orders, 16 Families, and 39 Species of mammals were identified in the 3rd National Ecosystem Survey collected nationwide. When 11 clusters were classified by habitat types, the simple structure index was the highest (ssi = 0.07). As a result of the similarities and hierarchies between habitat types suggested by the hierarchical clustering analysis, the residential areas were the most different habitat types for mammals; the next following type was a cluster together with rivers and coasts. The results of the non-metric multidimensional scaling analysis demonstrated that both Mus musculus and Rattus norvegicus restrictively appeared in a residential area, which is the most discriminating habitat type. Lutra lutra restrictively appeared in coastal and river areas. In summary, according to our results, the mammalian habitat can be divided into the following four types: (1) the forest type (using forest as the main habitat and migration route); (2) the river type (using water as the main habitat); (3) the residence habitat (living near residential area); and (4) the lowland type (consuming grain or seeds as the main feeding resource).