• Safety and Health at Work
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• v.11 no.1
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• pp.103-108
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• 2020

Background: Presenteeism has emerged as an important health-related issue and has been studied in a variety of occupation groups. This study examines the relationship between emotional labor and presenteeism in nurses in Republic of Korea. Methods: As a cross-sectional study, our study was conducted on 328 female nurses participating in the fourth Korean Working Conditions Survey (2015). Nurses were identified by the Korean Industry Classification Code. Multivariable logistic regression analysis was performed to explore the association between emotional labor and presenteeism. Results: Female nurses who always or sometimes hide their emotions in the workplace were found to have a high risk for presenteeism compared with female nurses who rarely hide their emotions in the workplace {odds ratio [OR] = 2.40 [95% confidence interval (CI) 1.04-5.54]; OR = 4.12 [95% CI 1.72-9.84], respectively}. Furthermore, the risk of presenteeism was higher in nurses who sometimes engaged with complaining customers compared with nurses who rarely did so, but it lacked statistical significance. Conclusion: Presenteeism in nurses can cause various negative secondary effects; therefore, an alternative should be sought to mediate nurses' emotional labor to prevent presenteeism.

• International Journal of Computer Science & Network Security
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• v.22 no.4
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• pp.203-208
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• 2022

The occurrence of Type 2 Diabetes Mellitus (T2DM) is hoarding globally. All kinds of Diabetes Mellitus is controlled to disrupt over 415 million grownups worldwide. It was the seventh prime cause of demise widespread with a measured 1.6 million deaths right prompted by diabetes during 2016. Over 90% of diabetes cases are T2DM, with the utmost persons having at smallest one other chronic condition in UK. In valuation of contemporary applications of Big Data (BD) to Diabetes Medicare by sighted its upcoming abilities, it is compulsory to transmit out a bottomless revision over foremost theoretical literatures. The long-term growth in medicine and, in explicit, in the field of "Diabetology", is powerfully encroached to a sequence of differences and inventions. The medical and healthcare data from varied bases like analysis and treatment tactics which assistances healthcare workers to guess the actual perceptions about the development of Diabetes Medicare measures accessible by them. Apache Spark extracts "Resilient Distributed Dataset (RDD)", a vital data structure distributed finished a cluster on machines. Machine Learning (ML) deals a note-worthy method for building elegant and automatic algorithms. ML library involving of communal ML algorithms like Support Vector Classification and Random Forest are investigated in this projected work by using Jupiter Notebook - Python code, where significant quantity of result (Accuracy) is carried out by the models.

• The Journal of Society for e-Business Studies
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• v.13 no.4
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• pp.173-191
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• 2008

As volumes of electronic commerce increase rapidly, customers are faced with information overload, and it becomes difficult for them to find necessary information and select what they need. In this situation, recommender systems can help the customers search and select the products and services they need more conveniently. These days, the recommender systems play important roles in customer relationship management. In this research, we develop a recommender system that recommends the books to the customers of Internet bookstore. In previous researches on recommender systems, collaborative filtering technique has been often employed. For the collaborative filtering technique to be used, the rating scores on books given by previous purchasers have to be collected. However, the collection of rating scores is not an easy task in reality. Therefore, in this research, we employed case-based reasoning technique that can work only with the book purchase history of customers. The accuracy of recommendation of the resulting book recommender system was about 40% on the level 3 classification code.

• Journal of the Korean Society of Radiology
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• v.18 no.3
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• pp.267-273
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• 2024

Using a cloud-based vertex AI platform that can develop an artificial intelligence learning model without coding, this study easily developed an artificial intelligence learning model by the non-professional general public and confirmed its clinical applicability. Nine dental diseases and 2,999 root disease X-ray images released on the Kaggle site were used for the learning data, and learning, verification, and test data images were randomly classified. Image classification and multi-label learning were performed through hyper-parameter tuning work using a learning pipeline in vertex AI's basic learning model workflow. As a result of performing AutoML(Automated Machine Learning), AUC(Area Under Curve) was found to be 0.967, precision was 95.6%, and reproduction rate was 95.2%. It was confirmed that the learned artificial intelligence model was sufficient for clinical diagnosis.

• Journal of the Korea Computer Graphics Society
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• v.22 no.3
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• pp.21-29
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• 2016

Cell segmentation is an important but time-consuming and laborious task in biological image analysis. An automated, robust, and fast method is required to overcome such burdensome processes. These needs are, however, challenging due to various cell shapes, intensity, and incomplete boundaries. A precise cell segmentation will allow to making a pathological diagnosis of tissue samples. A vast body of literature exists on cell segmentation in microscopy images [1]. The majority of existing work is based on input images and predefined feature models only - for example, using a deformable model to extract edge boundaries in the image. Only a handful of recent methods employ data-driven approaches, such as supervised learning. In this paper, we propose a novel data-driven cell segmentation algorithm for bright-field microscopy images. The proposed method minimizes an energy formula defined by two dictionaries - one is for input images and the other is for their manual segmentation results - and a common sparse code, which aims to find the pixel-level classification by deploying the learned dictionaries on new images. In contrast to deformable models, we do not need to know a prior knowledge of objects. We also employed convolutional sparse coding and Alternating Direction of Multiplier Method (ADMM) for fast dictionary learning and energy minimization. Unlike an existing method [1], our method trains both dictionaries concurrently, and is implemented using the GPU device for faster performance.

• (The)Study of the Eastern Classic
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• no.69
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• pp.9-44
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• 2017

Seonsaengan(先生案) is the predecessor's lists. The list includes the names of the predecessor, the date of the appointment, the date of return, the previous job, and the next job. Therefore, previous studies on the local recruitment and Jungin (中人) that can not be found in general personnel information of the Joseon dynasty were conducted. However, the status and classification of the list has not been achieved yet. So this study aims to clarify the status, classification and data characteristics of the list. 176 books, are the Joseon dynasty lists of predecessors, remain to this day. These lists are in Jangseogak(47 cases), Kyujanggak(80 cases), the National Library of Korea(24 cases) and other collections(25 cases). Jangseogak has lists of royal government officials, Kyujanggak has lists of central government officials, and the National Library of Korea and other collections have lists of local government officials. However, this paper focuses on accessible Jangseogak list of 47 cases. As I mentioned earlier, the Jangsaegak lists are generally related to the royal government officails. This classification includes 18 central government officials, 5 local government officials, and 24 royal government officails. If the list is classified as contents, it can be classified into six rituals and diplomatic officials, 12 royal government officials, 5 local government officials, 14 royal tombs officials, and 10 royal education officials. Through the information on the list, the following six characteristics can be summarized. First, it can be finded the basic personal information about the recorded person. Second, the period of office and reasons for leaving the office and office can be known. Third, changes in the office system can be confirmed. Fourth, it can be looked at one aspect of the personnel administration system of the Joseon Dynasty through the previous workplace and the next job. Fifth, it is possible to know days that are particularly important for each government. Sixth, the contents of work evaluation can be confirmed. This is the reality of the Joseon Dynasty, which is different from the contents recorded in the Code. Through this, it is possible to look at the personnel administration system of the Joseon Dynasty. However, in order to carry out a precise review, it is necessary to make a database for 176 lists. In addition, if data is analyzed in connection with existing genealogy data, it will be possible to establish a basis for understanding the personnel administration system of the Joseon Dynasty.

• Archives of design research
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• v.16 no.3
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• pp.309-318
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• 2003

A work of Art is not supposed to be isolated from the world, but it should be influenced by its cultural background and situations of the times. Therefore, Art itself reflects its era. In other words, it is created being based on the thought of its artist and simultaneously interacting with external conditions or circumstances of the era, so it would also affect the cultural code of its society. This is why modern art made by the individual living in this complicated and diversified society is quite avant-garde. Various demands from its society and diversified senses have been influencing diversification of works of Art. Now we can say that a mode of art is also dose to current stream of the times. A lot of artists have been trying to get out of traditional way of presentation techniques and classification of genres. In that point, the emergence of Multimedia Alt is inevitable in this digital era. The terms of Internet or multimedia are now familiar with everybody in the world, and a lot of works like Technology Art, Information Art, Computer Art, Digital Art, New Media Art, and so on have been coming into the world by using multimedia. Unlike other works of Art, these works from multimedia are practically used by being combined with technologies. Hereupon, in this paper I would like to find out a concept of Multimedia Art, its social function, and the future prospect of this brand-new form of art.