• Journal of Species Research
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• v.10 no.2
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• pp.117-133
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• 2021

In 2019, 43 bacterial strains were isolated from food, soil, marine environments, human, and animals related sources from the Republic of Korea. Based on the analysis of 16S rRNA gene sequence, these isolates were allocated to the phyla Bacteroidetes and Firmicutes as unrecorded species in Korea. The 10 Bacteroidetes strains were classified into the families Bacteroidaceae, Chitinophagaceae, Cytophagaceae, Flavobacteriaceae, and Prolixibacteraceae (of the orders Bacteroidales, Chitinophagales, Cytophagales, Flavobacteriales, and Marinilabiliales, respectively). The 33 Firmicutes strains belonged to the families Bacillaceae, Paenibacillaceae, Planococcaceae, Staphylococcaceae, Clostridiaceae, Lachnospiraceae, Peptostreptococcaceae, Enterococcaceae, Lactobacillaceae, Leuconostocaceae, and Streptococcaceae (of the orders Bacillales, Clostridiales, and Lactobacillales). These unrecorded bacteria were determined based on taxonomic criterion (>98.7%; 16S rRNA gene sequence similarity). In addition, their phylogenetic affiliation, as well as cell and colony morphologies, staining reactions, and physiological and biochemical properties were investigated. Therefore, we report 43 isolates as unrecorded species, and described basic features, isolation source, and locations of these strains.

• Design Convergence Study
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• v.15 no.2
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• pp.237-250
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• 2016

Along with rapid development, progress of the network technology and digital information technology, human are stepping into the intelligent society of internet. Thereby the quality of living environment and working environment are keep improving. Under the big background of internet era, the timeliness and convenience of smart home system has been improved greatly. While lots of smart products have gradually penetrated into people's daily life. The household appliances are among most popular ones. This paper is intended to compare smart features of household living products among most representative brands in China, Japan and South Korea. The smart features include self-learning, self-adapting, self-coordinating, self-diagnosing, self-inferring, self-organizing, and self adjusting. As result, most smart features of these products showed great similarity. While some features were dominated according to countries such as remote control feature in Korea, energy saving feature in Japan, and one button operation feature in China.

• Journal of the Korea Society of Computer and Information
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• v.28 no.7
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• pp.85-93
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• 2023

Software birthmark refers to a unique feature inherent in software that can be extracted from program binaries even in the absence of the original source code of the program. Like human genetic information, the similarity between programs can be calculated numerically, so it can be used to determine whether software is stolen or copied. In this paper, we propose a new birthmark technique for Android applications developed using Unity. The source codes of Unity-based Android applications use C# language, and since the core logic of the program is included in the DLL module, it must be approached in a different way from normal Android applications. In this paper, a Unity birthmark extraction and comparison system was implemented, and reliability and resilience were evaluated. The use of the Unity birthmark technique proposed in this paper is expected to be effective in preventing illegal copy or code theft of the Unity-based Android applications.

• Fisheries and Aquatic Sciences
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• v.26 no.7
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• pp.437-446
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• 2023

Cyprinids are popular species for aquaculture worldwide, with Asia being a significant contributor to their production. In Korea, common carp (Cyprinus carpio), koi carp (Cyprinus rubrofuscus), and goldfish (Carassius auratus) are cultivated domestically and imported for ornamental or human consumption purposes. Among the viruses that infect cyprinids, cyprinid herpesvirus-2 (CyHV-2), koi herpesvirus (KHV, also known as cyprinid herpesvirus-3), and carp edema virus (CEV) are of particular concern as they cause substantial economic losses to the aquaculture industry. In this study, we investigated these viruses in both of domestic and imported cyprinids. Our results revealed that CyHV-2 was only detected in imported goldfish from Thailand. To further investigate the genetic characteristics of them, the marker A region was analyzed. Despite belonging to the same cluster with isolates from China, France, Poland, and Israel, CyHV-2 detected in this study showed distinct differences in their repetitive sequence sizes. Furthermore, two different forms of KHV/CEV coinfection were identified from domestic koi carp, both of which exhibited typical symptoms. Phylogenetic analysis showed that one KHV isolate (ScKc-2105-K) was of the Asian type and closely related to isolates from Japan, Indonesia, Belgium, Taiwan, and China. Two CEV isolates (ScKc-2105-CE and GhKc-2207-CE) be- longed to the IIa type and showed high similarity with isolates from the USA, France, and Korea. Notably, koi carp injected with cultured KHV (ScKc-2105-K) showed 78.0% cumulative mortality within 14 days post-injection (dpi). Our findings support the importance of regular surveillance of viral diseases in cyprinids.

• Journal of Ocean Engineering and Technology
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• v.38 no.2
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• pp.64-73
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• 2024

Oil spills pose significant threats to marine ecosystems, human health, socioeconomic aspects, and coastal communities. Accurate real-time predictions of oil slick transport along coastlines are paramount for quick preparedness and response efforts. This study used an open-source OpenOil numerical model to simulate the fate and trajectories of oil slicks released during the 2007 Hebei Spirit accident along the Korean coasts. Six combinations of input parameters, derived from a five-day met-ocean dataset incorporating various hydrodynamic, meteorological, and wave models, were investigated to determine the input variables that lead to the most reasonable results. The predictive performance of each combination was evaluated quantitatively by comparing the dimensions and matching rates between the simulated and observed oil slicks extracted from synthetic aperture radar (SAR) data on the ocean surface. The results show that the combination incorporating the Hybrid Coordinate Ocean Model (HYCOM) for hydrodynamic parameters exhibited more substantial agreement with the observed spill areas than Copernicus Marine Environment Monitoring Service (CMEMS), yielding up to 88% and 53% similarity, respectively, during a more than four-day oil transportation near Taean coasts. This study underscores the importance of integrating high-resolution met-ocean models into oil spill modeling efforts to enhance the predictive accuracy regarding oil spill dynamics and weathering processes.

• Journal of Internet Computing and Services
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• v.25 no.2
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• pp.29-38
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• 2024

After Transcatheter Aortic Valve Replacement (TAVR), comprehensive management of complications, including the need for Permanent Pacemaker Implantation (PPI), is crucial, increasing the demand for accurate prediction models. Departing from traditional image-based methods, this study developed an optimal PPI prediction model based on ECG data using the XGBoost algorithm. Focusing on ECG signals like DeltaPR and DeltaQRS as key indicators, the model effectively identifies the correlation between conduction disorders and PPI needs, achieving superior performance with an AUC of 0.91. Validated using data from two hospitals, it demonstrated a high similarity rate of 95.28% in predicting PPI from ECG characteristics. This confirms the model's effective applicability across diverse hospital data, establishing a significant advancement in the development of reliable and practical PPI prediction models with reduced dependence on human intervention and costly medical imaging.

• Journal of Korea Society of Industrial Information Systems
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• v.29 no.4
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• pp.91-103
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• 2024

A tourist destination ranking system was designed that employs a semantic search to extract information with reasonable accuracy. To this end the process involves collecting data, preprocessing text reviews of tourist spots, and embedding the corpus and queries with SBERT. We calculate the similarity between data points, filter out those below a specified threshold, and then rank the remaining tourist destinations using a count-based algorithm to align them semantically with the query. To assess the efficacy of the ranking algorithm experiments were conducted with four queries. Furthermore, 58,175 sentences were directly labeled to ascertain their semantic relevance to the third query, 'crowdedness'. Notably, human-labeled data for crowdedness showed similar results. Despite challenges including optimizing thresholds and imbalanced data, this study shows that a semantic search is a powerful method for understanding user intent and recommending tourist destinations with less time and costs.

• Journal of Intelligence and Information Systems
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• v.24 no.2
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• pp.125-148
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• 2018

Recently, as the demand for big data analysis increases, cases of analyzing unstructured data and using the results are also increasing. Among the various types of unstructured data, text is used as a means of communicating information in almost all fields. In addition, many analysts are interested in the amount of data is very large and relatively easy to collect compared to other unstructured and structured data. Among the various text analysis applications, document classification which classifies documents into predetermined categories, topic modeling which extracts major topics from a large number of documents, sentimental analysis or opinion mining that identifies emotions or opinions contained in texts, and Text Summarization which summarize the main contents from one document or several documents have been actively studied. Especially, the text summarization technique is actively applied in the business through the news summary service, the privacy policy summary service, ect. In addition, much research has been done in academia in accordance with the extraction approach which provides the main elements of the document selectively and the abstraction approach which extracts the elements of the document and composes new sentences by combining them. However, the technique of evaluating the quality of automatically summarized documents has not made much progress compared to the technique of automatic text summarization. Most of existing studies dealing with the quality evaluation of summarization were carried out manual summarization of document, using them as reference documents, and measuring the similarity between the automatic summary and reference document. Specifically, automatic summarization is performed through various techniques from full text, and comparison with reference document, which is an ideal summary document, is performed for measuring the quality of automatic summarization. Reference documents are provided in two major ways, the most common way is manual summarization, in which a person creates an ideal summary by hand. Since this method requires human intervention in the process of preparing the summary, it takes a lot of time and cost to write the summary, and there is a limitation that the evaluation result may be different depending on the subject of the summarizer. Therefore, in order to overcome these limitations, attempts have been made to measure the quality of summary documents without human intervention. On the other hand, as a representative attempt to overcome these limitations, a method has been recently devised to reduce the size of the full text and to measure the similarity of the reduced full text and the automatic summary. In this method, the more frequent term in the full text appears in the summary, the better the quality of the summary. However, since summarization essentially means minimizing a lot of content while minimizing content omissions, it is unreasonable to say that a "good summary" based on only frequency always means a "good summary" in its essential meaning. In order to overcome the limitations of this previous study of summarization evaluation, this study proposes an automatic quality evaluation for text summarization method based on the essential meaning of summarization. Specifically, the concept of succinctness is defined as an element indicating how few duplicated contents among the sentences of the summary, and completeness is defined as an element that indicating how few of the contents are not included in the summary. In this paper, we propose a method for automatic quality evaluation of text summarization based on the concepts of succinctness and completeness. In order to evaluate the practical applicability of the proposed methodology, 29,671 sentences were extracted from TripAdvisor 's hotel reviews, summarized the reviews by each hotel and presented the results of the experiments conducted on evaluation of the quality of summaries in accordance to the proposed methodology. It also provides a way to integrate the completeness and succinctness in the trade-off relationship into the F-Score, and propose a method to perform the optimal summarization by changing the threshold of the sentence similarity.

• Journal of Life Science
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• v.27 no.11
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• pp.1369-1375
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• 2017

The purpose of this study was to investigate the cellular characterization of phospholipase C-${\delta}1$ in olive flounders (Paralichthys olivaceus). In general, phospholipase C signaling pathways are distributed in nuclei at plasma membranes and in cytoplasms, although the pathways' nuclear localization mechanisms are unclear. P. olivaceus duplicates type-A PoPLC-${\delta}1$ (PoPLC-${\delta}1A$), which has a high similarity to the human isoform PLC-${\delta}$; type-B PoPLC-${\delta}1$ (PoPLC-${\delta}1B$ [Sf]), which has a low similarity to the human isoform PLC-${\delta}$ and the alternative splice variant PoPLC-${\delta}1B$ (Lf), which has a nuclear localization signal (NLS) and a nuclear export signal (NES) for nuclear imports and exports, respectively. This study confirmed the effects of the cellular localization and translocation of GFP-tagged PoPLC-${\delta}1A$, PoPLC-${\delta}1B$ (Sf) and PoPLC-${\delta}1B$ (Lf). It administered treatments of $Ca^{2+}$ ionophore ionomycin and endoplasmic reticulum (ER)-$Ca^{2+}$ pump inhibitor thapsigargin to hirame natural-embryo (HINAE) cells. A laser-scanning confocal microscope was used. GFP-tagged PoPLC-${\delta}1A$ was distributed to the cellular organelles, rather than to the cytoplasms and cytomembranes, when PoPLC-${\delta}1B$ (Lf) and PoPLC-${\delta}1B$ (Sf) were localized at the plasma membranes. The treatments of ionomycin and thapsigargin showed the accumulation of PoPLC-${\delta}1A$ in the nuclei when PoPLC-${\delta}1B$ (Lf) nucleocytoplasmic shuttling and PoPLC-${\delta}1B$ (Sf) nucleocytoplasmic shuttling were not observed. The results were the first evidence that PoPLC-${\delta}1A$, which contains functional, intact NES sequences, has a main role in nucleocytoplasmic shuttling and translocation in fish.

• Journal of Intelligence and Information Systems
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• v.21 no.4
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• pp.17-35
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• 2015

Demand forecasting is the activity of estimating the quantity of a product or service that consumers will purchase for a certain period of time. Developing precise forecasting models are considered important since corporates can make strategic decisions on new markets based on future demand estimated by the models. Many studies have developed market growth curve models, such as Bass, Logistic, Gompertz models, which estimate future demand when a market is in its early stage. Among the models, Bass model, which explains the demand from two types of adopters, innovators and imitators, has been widely used in forecasting. Such models require sufficient demand observations to ensure qualified results. In the beginning of a new market, however, observations are not sufficient for the models to precisely estimate the market's future demand. For this reason, as an alternative, demands guessed from those of most adjacent markets are often used as references in such cases. Reference markets can be those whose products are developed with the same categorical technologies. A market's demand may be expected to have the similar pattern with that of a reference market in case the adoption pattern of a product in the market is determined mainly by the technology related to the product. However, such processes may not always ensure pleasing results because the similarity between markets depends on intuition and/or experience. There are two major drawbacks that human experts cannot effectively handle in this approach. One is the abundance of candidate reference markets to consider, and the other is the difficulty in calculating the similarity between markets. First, there can be too many markets to consider in selecting reference markets. Mostly, markets in the same category in an industrial hierarchy can be reference markets because they are usually based on the similar technologies. However, markets can be classified into different categories even if they are based on the same generic technologies. Therefore, markets in other categories also need to be considered as potential candidates. Next, even domain experts cannot consistently calculate the similarity between markets with their own qualitative standards. The inconsistency implies missing adjacent reference markets, which may lead to the imprecise estimation of future demand. Even though there are no missing reference markets, the new market's parameters can be hardly estimated from the reference markets without quantitative standards. For this reason, this study proposes a case-based expert system that helps experts overcome the drawbacks in discovering referential markets. First, this study proposes the use of Euclidean distance measure to calculate the similarity between markets. Based on their similarities, markets are grouped into clusters. Then, missing markets with the characteristics of the cluster are searched for. Potential candidate reference markets are extracted and recommended to users. After the iteration of these steps, definite reference markets are determined according to the user's selection among those candidates. Then, finally, the new market's parameters are estimated from the reference markets. For this procedure, two techniques are used in the model. One is clustering data mining technique, and the other content-based filtering of recommender systems. The proposed system implemented with those techniques can determine the most adjacent markets based on whether a user accepts candidate markets. Experiments were conducted to validate the usefulness of the system with five ICT experts involved. In the experiments, the experts were given the list of 16 ICT markets whose parameters to be estimated. For each of the markets, the experts estimated its parameters of growth curve models with intuition at first, and then with the system. The comparison of the experiments results show that the estimated parameters are closer when they use the system in comparison with the results when they guessed them without the system.