• The Korean Journal of Applied Statistics
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• v.35 no.2
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• pp.189-201
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• 2022

In this study, we propose factor augmentation to improve forecasting power of cryptocurrency return. We consider financial and economic variables as well as psychological aspect for possible factors. To be more specific, financial and economic factors are obtained by applying principal factor analysis. Psychological factor is summarized by news sentiment analysis. We also visualize such factors through impulse response analysis. In the modeling perspective, we consider ARIMAX as the classical model, and random forest and deep learning to accommodate nonlinear features. As a result, we show that factor augmentation reduces prediction error and the GRU performed the best amongst all models considered.

• Journal of Korea Spatial Information System Society
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• v.8 no.2 s.17
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• pp.13-38
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• 2006

Range query is one of the most important operations for spatial objects, it retrieves all spatial objects that overlap a given query region in multi-dimensional space. The DOT(DOuble Transformation) is known as an efficient indexing methods, it transforms the MBR of a spatial object into a single numeric value using a space filling curve, and stores the value in a $B^+$-tree. The DOT index is possible to be employed as a primary index for spatial objects. However, the range query processing based on the DOT index requires much overhead for spatial transformations to get the query region in the final space. Also, the detailed range query processing method for 2-dimensional spatial objects has not been studied yet in this paper, we propose an efficient multi-dimensional range query processing technique based on the DOT index. The proposed technique exploits the regularities in the moving patterns of space filling curves to divide a query region into a set of maximal sub-legions within which space filling curves traverse without interruption. Such division reduces the number of spatial transformations required to perform the range query and thus improves the performance of range query processing. A visual simulator is developed to show the evaluation method and the performance of our technique.

• Journal of the Korea institute for structural maintenance and inspection
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• v.21 no.6
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• pp.132-139
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• 2017

A huge amount of de-icing agent is sprayed during winter to promote traffic safety in cold regions, and the quantity of de-icing agent sprayed has increased each year. The main ingredients in commonly used de-icing agents are chlorides, such as calcium chloride($CaCl_2$) and sodium chloride(NaCl). While calcium chloride is mostly used in Korea and sodium chloride is usually used in the U.S. and Japan, all de-icing agents include chloride ions. The chlorides included in sprayed calcium chloride-based de-icing agents have severe adverse effects, including the corrosion of reinforcing steels through salt damage by infiltrating into road structures, reduced structural performance of pavement or damage to bridge structures, and surface scaling, in combination with freezing damage in winter, as well as water pollution. In addition, the deterioration of paved concrete road surface that occurs after the use of calcium chloride-based de-icing agent accelerates the development of visual problems with traffic structures. Therefore, the present study was performed to prepare an environment-friendly liquid de-icing agent through a reaction between waste organic acids and calcium-based by-products, which are industrial by-products, and to analyze the properties of the de-icing agent in order to evaluate its applicability to road facilities.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.36S no.9
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• pp.91-102
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• 1999

It is known that the digital image enlargement technique which only uses spatially neighbored pixels information in a still image can increase the size of the image but the practical enhancement of resolution is small because the frequency bandwidth of the image is basically limited. To solve this problem, this paper proposes the digital image enlargement technique that improves the reconstruction of the edge components by selectively transposing the direction of the subwindows of pseudomedian filter according to the distribution of neighbored pixels to the interpolation point. The pseudomedian filter has the better performance in aspect of the reconstruction of edge information when the pixel values masked by two subwindows parallel to the interpolation point are very similar and the pixel values masked by another subwindow that is orthogonal to the above two subwindows are similar to each other. In this paper, the computer simulation for digital image enlargement was performed with consideration of these characteristics when selecting the subwindows of pseudomedina filter. Based on this simulation result, the performance of the proposed method was analysed and its effectiveness was assessed. According to the proposed method, visual artifacts that result from using the limited samples can be effectively suppressed, and most characteristics and shapes of the original image can be preserved as well.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.13 no.3
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• pp.197-205
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• 2020

Korean language has the characteristics that the pronunciation of phoneme units such as vowels and consonants are fixed and the pronunciation associated with a notation does not change, so that foreign learners can approach rather easily Korean language. However, when one pronounces words, phrases, or sentences, the pronunciation changes in a manner of a wide variation and complexity at the boundaries of syllables, and the association of notation and pronunciation does not hold any more. Consequently, it is very difficult for foreign learners to study Korean standard pronunciations. Despite these difficulties, it is believed that systematic analysis of pronunciation errors for Korean words is possible according to the advantageous observations that the relationship between Korean notations and pronunciations can be described as a set of firm rules without exceptions unlike other languages including English. In this paper, we propose a visualization framework which shows the differences between standard pronunciations and erratic ones as quantitative measures on the computer screen. Previous researches only show color representation and 3D graphics of speech properties, or an animated view of changing shapes of lips and mouth cavity. Moreover, the features used in the analysis are only point data such as the average of a speech range. In this study, we propose a method which can directly use the time-series data instead of using summary or distorted data. This was realized by using the deep learning-based technique which combines Self-organizing map, variational autoencoder model, and Markov model, and we achieved a superior performance enhancement compared to the method using the point-based data.

• Journal of KIISE:Software and Applications
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• v.32 no.7
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• pp.663-673
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• 2005

An analysis model for the dynamics information of two-dimensional time-series patterns is described. In the proposed model, two novel transforms that visualize the dynamic characteristics are proposed. The first transform, referred to as speed equalization, reproduces a time-series pattern assuming a constant linear velocity to effectively model the temporal characteristics of the signing process. The second transform, referred to as velocity transform, maps the signal onto a horizontal vs. vertical velocity plane where the variation oi the velocities over time is represented as a visible shape. With the transforms, the dynamic characteristics in the original signing process are reflected in the shape of the transformed patterns. An analysis in the context of these shapes then naturally results in an effective analysis of the dynamic characteristics. The proposed transform technique is applied to an online signature verification problem for evaluation. Experimenting on a large signature database, the performance evaluated in EER(Equal Error Rate) was improved to 1.17$\%$ compared to 1.93$\%$ of the traditional signature verification algorithm in which no transformed patterns are utilized. In the case of skilled forgery experiments, the improvement was more outstanding; it was demonstrated that the parameter set extracted from the transformed patterns was more discriminative in rejecting forgeries

• Journal of Internet Computing and Services
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• v.23 no.3
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• pp.35-45
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• 2022

Even in recent years, treatment of first-aid patients is still often delayed due to a shortage of medical resources in marginalized areas. Research on automating the analysis of medical data to solve the problems of inaccessibility for medical services and shortage of medical personnel is ongoing. Computer vision-based medical inspection automation requires a lot of cost in data collection and labeling for training purposes. These problems stand out in the works of classifying lesion that are rare, or pathological features and pathogenesis that are difficult to clearly define visually. Anomaly detection is attracting as a method that can significantly reduce the cost of data collection by adopting an unsupervised learning strategy. In this paper, we propose methods for detecting abnormal images on chest X-RAY images as follows based on existing anomaly detection techniques. (1) Normalize the brightness range of medical images resampled as optimal resolution. (2) Some feature vectors with high representative power are selected in set of patch features extracted as intermediate-level from lesion-free images. (3) Measure the difference from the feature vectors of lesion-free data selected based on the nearest neighbor search algorithm. The proposed system can simultaneously perform anomaly classification and localization for each image. In this paper, the anomaly detection performance of the proposed system for chest X-RAY images of PA projection is measured and presented by detailed conditions. We demonstrate effect of anomaly detection for medical images by showing 0.705 classification AUROC for random subset extracted from the PadChest dataset. The proposed system can be usefully used to improve the clinical diagnosis workflow of medical institutions, and can effectively support early diagnosis in medically poor area.

• Journal of the Korean Society of Marine Environment & Safety
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• v.27 no.2
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• pp.363-368
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• 2021

Ship engine rooms have improved automation systems owing to the advancement of technology. However, there are many variables at sea, such as wind, waves, vibration, and equipment aging, which cause loosening, cutting, and leakage, which are not measured by automated systems. There are cases in which only one engineer is available for patrolling. This entails many risk factors in the engine room, where rotating equipment is operating at high temperature and high pressure. When the engineer patrols, he uses his five senses, with particular high dependence on vision. We hereby present a preliminary study to implement an engine-room patrol robot that detects and informs the machine room while a robot patrols the engine room. Images of ship engine-room equipment were classified using a convolutional neural network (CNN). After constructing the image dataset of the ship engine room, the network was trained with a pre-trained CNN model. Classification performance of the trained model showed high reproducibility. Images were visualized with a class activation map. Although it cannot be generalized because the amount of data was limited, it is thought that if the data of each ship were learned through transfer learning, a model suitable for the characteristics of each ship could be constructed with little time and cost expenditure.

• Journal of the Korea Computer Graphics Society
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• v.28 no.3
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• pp.79-89
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• 2022

With the popularity and the advanced graphics hardware technology of mobile devices, various mobile applications that help children with physical activities have been studied. This paper presents SandUp, a mobile application that guides the play of building sand castles using artificial intelligence and augmented reality(AR) technology. In the process of building the sandcastle, children can interactively explore the target virtual sandcastle through the smartphone display using AR technology. In addition, to help children complete the sandcastle, SandUp informs the sand shape and task required step by step and provides visual and auditory feedback while recognizing progress in real-time using the phone's camera and deep learning classification. We prototyped our SandUp app using Flutter and TensorFlow Lite. To evaluate the usability and effectiveness of the proposed SandUp, we conducted a questionnaire survey on 50 adults and a user study on 20 children aged 4~7 years. The survey results showed that SandUp effectively helps build the sandcastle with proper interactive guidance. Based on the results from the user study on children and feedback from their parents, we also derived usability issues that can be further improved and suggested future research directions.

• Progress in Medical Physics
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• v.18 no.2
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• pp.98-106
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• 2007

In June 2005, Yonsei University Medical Center, Severance Hospital upgraded a full-PACS system by adding twenty (5 mega pixels) Totoku ME511L flat panel LCD display devices for diagnostic interpretation purposes. Here we report upon the quantitative (or visual) acceptance testing of the twenty Totoku ME511L display devices for reflection, luminance response, luminance spatial dependency, resolution, noise, veiling glare, and display chromaticity based on AAPM TG 18 report. The tools used in the tests included a telescopic photometer, which was used as a colorimeter, illuminance meter, light sources for reflection assessment, light-blocking devices, and digital TG18 test patterns. For selected 8 flat panel displays, mean diffuse reflection coefficient ($R_d$) was $0.019{\pm}0.02sr^{-1}$. In the luminance response test, luminance ratio (LR), maximum luminance difference ($L_{max}$), and deviation of contrast response were $550{\pm}100,\;2.0{\pm}1.9%\;and\;5.8{\pm}1.8%$, respectively. In the luminance uniformity test, maximum luminance deviation was $14.3{\pm}5.5%$ for the 10% luminance of the TG18-UNL10 test pattern. In the resolution test with luminance measurement method, percent luminance (${\Dalta}L$) at the center was $0.94{\pm}0.64%$. In all cases of noise testing, rectangular target In every square in the three quadrants was visible and all 15 targets except the smallest one in the every corner pattern and the center pattern. The glare ratio (GR) was $12,346{\pm}1,995$. The color uniformity, (u',v'), was $0.0025{\pm}0.0008$. Also, the research results of qualify control guideline of primary disply devices suitable for domestic circumstance are presented All test results are in-line with the criteria recommended by AAPM TG18 report and are thus fully acceptable for diagnostic image interpretation. As a result, the acceptance testing schedule described provides not only an acceptance standard but also guidelines for quality control, optimized viewing conditions, and a means for determining the upgrading time of LCD display devices for diagnostic interpretation.