• Journal of Fisheries and Marine Sciences Education
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• v.26 no.2
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• pp.357-367
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• 2014

The path of the search has been long and complex but rich in cultural, economic, religious, and human aspects. The relations between these two ports, Malta and Trieste, full of a painful and difficult but also glorious and fair history, have had their ups and downs as a theater, not so much land as the sea, and in this case the Mediterranean. This area has led to a similar vision of the historical aspects of the various dominations, and has a significant influence on the habits, customs and life of the people of Malta and Trieste. Their particularly complex history has unfolded with ups and downs, contrasting with other difficult times more happier and constructive as it has always, however, in the history of man. The purpose of this article is to analyze and arrange manifestly the history of commercial and maritime interchanges between Malta and Trieste, not achieved in Korea until now. This material has high scientific value gathering sufficient data for this article.

• Journal of Korean Medical classics
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• v.32 no.1
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• pp.171-189
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• 2019

Objectives : This study analyzes herbs combinations and primary virtues that constitute the prescriptions of Gyeji-tang, Mahwang-tang, and Daecheongryong-tang to effectively analyze medication preparations described in "Shanghanlun" using database, and test the results of the data structure and effectiveness of queries. Methods : This study enters "Sanghanjapbyeongronyeonggudaeseong" as the original text into the database, and even uses one provision as independent knowledge by dividing provisions in accordance with the content. Results : Five tables and 12 queries were created and used for data input and analysis. Using the types of Herbs included in the prescriptions, this study manages to search for the same or supplemented prescriptions, and the primary virtues of the prescriptions were collected and compared. Conclusions : Subject to the combination of herbs and pathology for the prescriptions described in "Shanghanlun" utilizing the database, this study found relevant texts and combinations of herbs and pathologies, and using this, the time required for theoretical research between prescriptions could be shortened.

• Journal of Korea Multimedia Society
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• v.13 no.12
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• pp.1739-1747
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• 2010

The damage of natural disasters has occurred on huge scale more frequently than before. The damage caused by the disasters are summarized and are analyzed, and are managed as a very general type of documentation, not showing the position of previous damage records and related information such as weather, facilities of CCTV, hospitals, and gas station on the maps. Therefore, it needs to provide map-based searching systems considering damaged area as well as search key-words. This paper focuses on the development of a search system based on the map to manage previous disaster records and related information each disaster using spatial databases. This system consists of three modules, which are databases to store disaster data, the SQL procedure-based search module to extract needed information from the constructed databases, and the map module to express the search results on the map. This paper will contribute to provide framework of a system development for managing the disaster information according to each year and disaster based on the maps and to be utilized as the basic framework in developing damage prediction and prevention systems for disasters in future.

• Asian Pacific Journal of Cancer Prevention
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• v.15 no.8
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• pp.3465-3470
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• 2014

Background: Previous studies have generated conflicting evidence regarding associations between family history and survival after gastric cancer surgery. In this study, we investigated this question using a meta-analysis. Materials and Methods: To identify relevant studies, PubMed and Embase databases were searched up to June 2013. Two reviewers independently assessed search results and data extraction of included studies. Hazard ratios (HRs) and 95% confidence intervals (CIs) for overall survival (OS) were calculated based on fixed- or random-effects models. Homogeneity of effects across studies was assessed using $x^2$ test statistics and quantified by $I^2$. Results: A total of five studies were selected according to the inclusion criteria. The total number of patients included was 2,030, which ranged from 145 to 598 per study. There was no significant difference in OS by family history of cancer (HR=0.83, 95%CIs=0.50-1.38), but subgroup analysis of patients with a first-degree family history of cancer (HR=0.74, 95%CIs=0.60-0.93) and gastric cancer family history (HR=0.56, 95%CIs=0.41-0.76) tended to show better OS in these patients. Conclusions: This meta-analysis suggests that a first-degree family history of cancer or gastric cancer family history is associated with better survival of gastric cancer patients after surgery, after a systematic review of five previous studies. These results can be applied by clinicians when counselling patients regarding their risk of death from gastric cancer. Further study is needed to investigate the underlying mechanism between family history and survival in gastric cancer patients.

• The Journal of the Korea institute of electronic communication sciences
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• v.14 no.3
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• pp.587-594
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• 2019

This paper proposes a personalized web search technique that produces ranked results reflecting user's query intents and individual interests. The performance of personalized search relies on an effective users' profiling strategy to accurately capture their interests and preferences. User profile is a data set of words and customized weights based on recent user queries and the topic words of web documents from their click history. Personal profile is used to expand a user query to the personalized query before the web search. To determine the exact meaning of ambiguous queries and topic words, this strategy uses WordNet to calculate semantic similarities to words in the user personal profile. Experimental results with query expansion and re-ranking modules installed on general search systems shows enhanced performance with this personalized search technique in terms of precision and recall.

• Journal of the Korean Society of Costume
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• v.52 no.4
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• pp.15-23
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• 2002

The purpose of this study was to pave the way to improve the quality of historical clothing and textiles and to search for the advisable direction of future studies by examining and analyzing the interdisciplinary approach of historical clothing and textiles related articles published in The Korean Society of Costume. For this analysis, the data were included 124 historical clothing and textiles research articles published in The Korean Society of Costume from 1980 to 2001 March. The followings show the results of this study. 1. The five dominant interdisciplinary fields of historical clothing and textiles were Identified : anthropology, art history, pop music, archaeology, sociology 2. The interdisciplinary research has been actively approached in historical clothing and textiles. 3. The most frequently approached field of the interdisciplinary researches of historical clothing and textiles was art history 4. The period that has most variety interdisciplinary fields was the present age. The studies of future historical clothing and textiles should be approached in more diverse areas of interdisciplinary way and time periods.

• Advances in aircraft and spacecraft science
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• v.9 no.1
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• pp.1-15
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• 2022

This paper presents calibration of flush air data sensing systems during ascent period of a satellite launch vehicle. Aerodynamic results are numerically computed by solving three-dimensional time dependent compressible Euler equations over a payload shroud of a satellite launch vehicle. The flush air data system consists of four pressure ports flushed on a blunt-cone section of the payload shroud and connected to on board differential pressure transducers. The inverse algorithm uses calibration charts which are based on computed and measured data. A controlled random search method coupled with neural network technique is employed to estimate pitch and yaw angles from measured transient differential pressure history. The algorithm predicts the flow direction stepwise with the function of flight Mach numbers and can be termed as an online method. Flow direction of the launch vehicle is compared with the reconstructed trajectory data. The estimated values of the flow direction are in good agreement with them.

• Information Systems Review
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• v.23 no.4
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• pp.69-86
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• 2021

As artificial intelligence technology advances, personalized recommendation systems using big data have attracted huge attention. In the case of beauty products, product preferences are clearly divided depending on customers' skin types and sensitivity along with individual tastes, so it is necessary to provide customized recommendation services based on accumulated customer data. Therefore, by employing deep learning methods, this study proposes a neural network-based recommendation model utilizing both product search history and context information such as gender, skin types and skin worries of customers. The results show that our model with context information outperforms collaborative filtering-based recommender system models using customer search history.

• Journal of the Korea Society of Computer and Information
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• v.26 no.1
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• pp.265-274
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• 2021

In this paper, we propose a novel recommendation model based on Doc2vec using search keywords and product details. Until now, a lot of prior studies on recommender systems have proposed collaborative filtering (CF) as the main algorithm for recommendation, which uses only structured input data such as customers' purchase history or ratings. However, the use of unstructured data like online customer review in CF may lead to better recommendation. Under this background, we propose to use search keyword data and product detail information, which are seldom used in previous studies, for product recommendation. The proposed model makes recommendation by using CF which simultaneously considers ratings, search keywords and detailed information of the products purchased by customers. To extract quantitative patterns from these unstructured data, Doc2vec is applied. As a result of the experiment, the proposed model was found to outperform the conventional recommendation model. In addition, it was confirmed that search keywords and product details had a significant effect on recommendation. This study has academic significance in that it tries to apply the customers' online behavior information to the recommendation system and that it mitigates the cold start problem, which is one of the critical limitations of CF.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.49 no.2
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• pp.7-12
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• 2012

Recently the medical field to efficiently process the vast amounts of information to decision trees, neural networks, Bayesian Networks, including the application method of various data mining techniques are investigated. In addition, the basic personal information or patient history, family history, in addition to information such as MRI, HRCT images and additional information to collect and leverage in the diagnosis of disease, improved diagnostic accuracy is to promote a common status. But in real world situations that affect the results much because of the variable exists for a particular data mining techniques to obtain information through the enemy can be seen fairly limited. Medical images were taken as well as a minor can not give a positive impact on the diagnosis, but the proportion increased subjective judgments by the automated system is to deal with difficult issues. As a result of a complex reality, the situation is more advantageous to deal with the relative probability of the multivariate model based on Bayesian network, or TAN in the K2 search algorithm improves due to expansion model has been proposed. At this point, depending on the type of search algorithm applied significantly influenced the performance characteristics of the extended Bayesian network, the performance and suitability of each technique for evaluation of the facts is required. In this paper, we extend the Bayesian network for diagnosis of diseases using the same data were carried out, K2, TAN and changes in search algorithms such as classification accuracy was measured. In the 10-fold cross-validation experiment was performed to compare the performance evaluation based on the analysis and the onset of high-risk classification for patients with HRCT images could be possible to identify high-risk data.