• Journal of the Korean Society of Costume
• /
• v.57 no.1 s.110
• /
• pp.1-16
• /
• 2007

This study is to design costumes of each characters, seen in the film of 'TITANIC' directed by James Cameron in 1997, by analyzing various costumes for each roles in the film. The 'TITANIC' has got the 'Oscar Award' in 1998 in 11 sectors for its' high box office record and the finest of the work, based on successful visualization of the costumes for the contemporary characters by historical research. The social background of 'TITANIC' would be presumed in the year of 1912, of which era was also called by 'La Belle Epoque', to say, 'good period'. This study, therefore, traced the representative art trend for the 1910's, together with political, economical and social backgrounds as 1st step. The 2nd step is the consideration of fashion trends of costume affected by the contemporary trends such as Art Nouveau and Art Deco in the period. The 3rd step is the analysis of costumes in the film of 'TITANIC'. Finally, this work has designed the virtual costumes of the characters, in imaginary scenes, which could denote the nature of the personality. Hopefully, this study could help designers show sustainable development in creating cinema costumes and other related projects, based on the understandings of this work.

• Journal of Ocean Engineering and Technology
• /
• v.35 no.5
• /
• pp.369-381
• /
• 2021

The International Ice Patrol (IIP) was established after the Titanic collided with an iceberg off the eastern coast of Canada in 1912 and sank, killing more than 1,500 people. Recently, the IIP has analyzed satellite images and provided safe operation information to vessels by tracking the occurrence and movement of icebergs. A large number of recent arctic studies mainly deal with sea ice formed by freezing seawater related to sea routes and resource development. The iceberg that collided with the Titanic was land-based ice that dislodged from a glacier and fell into the sea. The properties of these two types of ice are different. In addition, vessels operating in ice-covered waters such as the Arctic sea have an ice-breaking function or minimum ice-strengthened functions. Ships operating on transatlantic routes including the eastern coast of Canada do not necessarily require ice-strengthened functions. Hundreds to thousands of icebergs are discovered each year near the area where the Titanic sank. In this study, the status of ship-iceberg collision accidents was investigated to provide useful information to researchers, and the physical and mechanical characteristics of icebergs were investigated and summarized.

• Proceedings of the Korea Society of Costume Conference
• /
• 2005.05a
• /
• pp.115-115
• /
• 2005

• Korean Journal of Materials Research
• /
• v.27 no.11
• /
• pp.577-582
• /
• 2017

Self-cleaning and photocatalytic $TiO_2$ thin films were prepared by a facile sol-gel method followed by spin coating using peroxo titanic acid as a precursor. The as-prepared thin films were heated at low temperature($110^{\circ}C$) and high temperature ($400^{\circ}C$). Thin films were characterized by X-ray diffraction(XRD), Field-emission scanning electron microscopy(FESEM), UV-Visible spectroscopy and water contact angle measurement. XRD analysis confirms the low crystallinity of thin films prepared at low temperature, while crystalline anatase phase was found the for high temperature thin film. The photocatalytic activity of thin films was studied by the photocatalytic degradation of methylene blue dye solution. Self-cleaning and photocatalytic performance of both low and high temperature thin films were compared.

• Journal of the Korean Crystal Growth and Crystal Technology
• /
• v.8 no.2
• /
• pp.342-342
• /
• 1998

The effect of pH on the dehydration reaction of TiCl₄solution. KOH and HCl were used as a accelerater and retarder in dehydration. Results are follow. Neutralization point is pH 7.4 in the system of $TiCl_4-KOH$ and the production which is produced at acidic side is Ti-gel of poly metatitanic acid. The production which is produced at alkalic side is aligomer and crystalline potasium titanate is not detected.

• Proceedings of the Materials Research Society of Korea Conference
• /
• 2005.05a
• /
• pp.303-303
• /
• 2005

• The Korean Journal of Applied Statistics
• /
• v.21 no.5
• /
• pp.875-888
• /
• 2008

Mosaic plots, proposed by Hartigan and Kleiner (1981, 1984), are very useful in visualizing categorical data. In mosaic plot, multi-way classified cell frequencies are represented by rectangles with proportional area. The plot is easy to understand while preserving the information contained in the data. Plot's appearance, however, does change substantially depending on the order of variables and the orders of categories with variable put into the plot. In this study, we propose the algorithms for ordering variables and categories of the categorical data to be explored via mosaic plots. We demonstrate our methods to three well-known datasets: Titanic, Housing and PreSex.

• Journal of the Korean Crystal Growth and Crystal Technology
• /
• v.8 no.2
• /
• pp.343-349
• /
• 1998

The effect of pH on the dehydration reaction of $TiCL_4$ solution. KOH and HC1 were used as a accelerater and retarder in dehydration. Results are follow. Neutralization point is pH 7.4 in the system of $TiCL_4$- KOH and the production which is produced at acidic side is Ti -gel of poly metatitanic acid. The production which is produced at alkalic side is aligomer and crystalline potasium titanate is not detected.

• Journal of Internet Computing and Services
• /
• v.25 no.4
• /
• pp.121-130
• /
• 2024

As internet and communication technology (ICT) is improved exponentially, types and amount of available data also increase. Even though data analysis including statistics is significant to utilize this large amount of data, there are inevitable limits to process various and complex data in general way. Meanwhile, there are many attempts to apply machine learning (ML) in various fields to solve the problems according to the enhancement in computational performance and increase in demands for autonomous systems. Especially, data processing for the model input and designing the model to solve the objective function are critical to achieve the model performance. Data processing methods according to the type and property have been presented through many studies and the performance of ML highly varies depending on the methods. Nevertheless, there are difficulties in deciding which data processing method for data analysis since the types and characteristics of data have become more diverse. Specifically, multi-variate data processing is essential for solving non-linear problem based on ML. In this paper, we present a multi-variate tabular data processing scheme for ML-aided data analysis by using Titanic dataset from Kaggle including various kinds of data. We present the methods like input variable filtering applying statistical analysis and normalization according to the data property. In addition, we analyze the data structure using visualization. Lastly, we design an ML model and train the model by applying the proposed multi-variate data process. After that, we analyze the passenger's survival prediction performance of the trained model. We expect that the proposed multi-variate data processing and visualization can be extended to various environments for ML based analysis.

• Journal of IKEEE
• /
• v.24 no.3
• /
• pp.766-776
• /
• 2020

Recently, as interest in machine learning (ML) has increased and research using ML has become active, it is becoming more important to find an optimal hyperparameter combination for various ML models. In this paper, among various hyperparameters, we focused on ML optimizers, and measured and compared the performance of major optimizers using various datasets. In particular, we compared the performance of nine optimizers ranging from SGD, which is the most basic, to Momentum, NAG, AdaGrad, RMSProp, AdaDelta, Adam, AdaMax, and Nadam, using the MNIST, CIFAR-10, IRIS, TITANIC, and Boston Housing Price datasets. Experimental results showed that when Adam or Nadam was used, the loss of various ML models decreased most rapidly and their F1 score was also increased. Meanwhile, AdaMax showed a lot of instability during training and AdaDelta showed slower convergence speed and lower performance than other optimizers.