• Elastomers and Composites
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• v.39 no.4
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• pp.318-323
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• 2004

Cloud-point and bubble-point curves for poly(ethylene-co-13.8 mol% octene) ($PEO_{13.8}$) and Poly(ethylene-co-15.3 mol% octene) ($PEO_{15.3}$) were determined up to $150^{\circ}C$ and 450 bar in hydrocarbons which have different molecular size and structure. Whereas ($PEO_{15.3}$+ n-pentane) system has cloud-point and bubble-point type transitions, ($PEO_{15.3}$+ n-propane) and ($PEO_{15.3}$+ n-butane) systems do only cloud-point type transition. In cyclo-pentane, -hexane, -heptane, and -octane, $PEO_{15.3}$ has a bubble-point transition. ($PEO_{13.8}$+ n-butane) mixture has a critical mixture concentration at 5 wt% PEO. (PEO + hydrocarbon) mixtures exhibit LCST type behavior. Solubility of PEO increases with hydrocarbon size due to increasing dispersion interaction which is favorable to dissolve PEO.

• Current Optics and Photonics
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• v.4 no.4
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• pp.286-292
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• 2020

Imaging through multicore fiber (MCF) is of great significance in the biomedical domain. Although several techniques have been developed to image an object from a signal passing through MCF, these methods are strongly dependent on the surroundings, such as vibration and the temperature fluctuation of the fiber's environment. In this paper, we apply a new, strong technique called deep learning to reconstruct the phase image through a MCF in which each core is multimode. To evaluate the network, we employ the binary cross-entropy as the loss function of a convolutional neural network (CNN) with improved U-net structure. The high-quality reconstruction of input objects upon spatial light modulation (SLM) can be realized from the speckle patterns of intensity that contain the information about the objects. Moreover, we study the effect of MCF length on image recovery. It is shown that the shorter the fiber, the better the imaging quality. Based on our findings, MCF may have applications in fields such as endoscopic imaging and optical communication.

• The Journal of the Acoustical Society of Korea
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• v.40 no.4
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• pp.337-346
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• 2021

Detection of abnormal signal generally can be done by using features of normal signals as main information because of data imbalance. This paper propose an efficient method for abnormal signal detection using parallel AutoEncoder (AE) which can use features of abnormal signals as well. The proposed Parallel AE (PAE) is composed of a normal and an abnormal reconstructors having identical AE structure and train features of normal and abnormal signals, respectively. The PAE can effectively solve the imbalanced data problem by sequentially training normal and abnormal data. For further detection performance improvement, additional binary classifier can be added to the PAE. Through experiments using public acoustic data, we obtain that the proposed PAE shows Area Under Curve (AUC) improvement of minimum 22 % at the expenses of training time increased by 1.31 ~ 1.61 times to the single AE. Furthermore, the PAE shows 93 % AUC improvement in detecting abnormal underwater acoustic signal when pre-trained PAE is transferred to train open underwater acoustic data.

• Journal of the Korea Convergence Society
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• v.10 no.2
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• pp.1-6
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• 2019

The proposed model is developed to minimize the loss of information in incomplete data including missing data. The first step is to transform the learning data to compensate for the loss information using the data extension technique. In this conversion process, the attribute values of the data are filled with binary or probability values in one-hot encoding. Next, this conversion data is input to the deep learning model, where the number of entries is not constant depending on the cardinality of each attribute. Then, the entry values of each attribute are assigned to the respective input nodes, and learning proceeds. This is different from existing learning models, and has an unusual structure in which arbitrary attribute values are distributedly input to multiple nodes in the input layer. In order to evaluate the learning performance of the proposed model, various experiments are performed on the missing data and it shows that it is superior in terms of performance. The proposed model will be useful as an algorithm to minimize the loss in the ubiquitous environment.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.38 no.6
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• pp.933-940
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• 2018

The conversion of the internal combustion engine vehicle to the electric vehicle is suggested as a solution to the problem of global climate change and environmental pollution. Accordingly, this study was started to promote the use of electric vehicles. The purpose of this study is to identify the basic background knowledge and current status of electric vehicles in Korea and abroad, and expand from previous understanding on which factors affect ones choice on electric vehicles by considering individual characteristics and context in detail. In the analysis, a set of demand forecasting models were constructed by grouping the respondents based on the household characteristics as well as the vehicle ownership. At the time in need for better understanding of the feasibility of electric vehicles, it is expected that the research can assist the promotion of electric vehicles. In the follow-up study, I would like to continue the research on the activation of electric vehicles.

• The Journal of the Korea Contents Association
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• v.22 no.7
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• pp.548-562
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• 2022

This study was conducted to diagnose the issues of AI ethics in global content and to discuss what kind of discourse is needed to strengthen human identity. To this end, the study selected Netflix original content "The Social Dilemma" for analysis and adopted narrative analysis as the research method. The analysis results confirmed that "Social Dilemma" showed the structure of a traditional current affairs documentary and mainly used experts and statistical data to develop the story. It also reinforced core content claims by enumerating domestic and foreign cases such as the 2021 Myanmar massacre and the spread of fake news. In addition, the relationship between the characters clearly revealed the binary opposition between developers and media companies as well as users and advertisers. For the solution to the problem, strong regulations on businesses and the suspension of social media use were reached. However, "The Social Dilemma" merely pointed out the misuse of AI technology and had a narrative that ignored human identity and social relationships. Such results raise the need for creating contents that emphasize the importance of human sociality, relationships, and learning ability in the age of AI.

• Journal of Software Assessment and Valuation
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• v.16 no.1
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• pp.37-44
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• 2020

The similarity of the software is extracted by the verification of comparing with the source code. The source code is the intellectual copyright of the developer written in the programming language. And the source code written in text format contains the contents of the developer's expertise and ideas. The verification for judging the illegal use of software copyright is performed by comparing the structure and contents of files with the source code of the original and the illegal copy. However, there is hard to do the one-to-one comparison in practice. Cause the suspected source code do not submitted Intentionally or unconsciously. It is now increasing practically. In this case, the comparative evaluation with execution code should be performed, and indirect methods such as reverse assembling method, reverse engineering technique, and sequence analysis of function execution are applied. In this paper, we analyzed the effectiveness of indirect comparison results by practical evaluation . It also proposes a method to utilize to the system and executable code files as a verification results.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2023.05a
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• pp.98-99
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• 2023

In the maritime digital forensic part, it is very important and difficult process that analysis of data and information with vessel navigation system's binary log data for situation awareness of maritime accident. In recent years, analysis of vessel's navigation system's trajectory information is an essential element of maritime accident investigation. So, we made an experiment about corruption with various memory device in navigation system. The analysis of corruption test in seawater give us important information about the valid pulling time of sunken ship for acquirement useful trajectory information.

• The Transactions of the Korea Information Processing Society
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• v.13 no.2
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• pp.13-17
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• 2024

In this paper, union-based rule antecedent neuro-fuzzy controller, which can guarantee a parsimonious knowledge base with reduced number of rules, is proposed. The proposed neuro-fuzzy controller allows union operation of input fuzzy sets in the antecedents to cover bigger input domain compared with the complete structure rule which consists of AND combination of all input variables in its premise. To construct the proposed neuro-fuzzy controller, we consider the multiple-term unified logic processor (MULP) which consists of OR and AND fuzzy neurons. The fuzzy neurons exhibit learning abilities as they come with a collection of adjustable connection weights. In the development stage, the genetic algorithm (GA) constructs a Boolean skeleton of the proposed neuro-fuzzy controller, while the stochastic reinforcement learning refines the binary connections of the GA-optimized controller for further improvement of the performance index. An inverted pendulum system is considered to verify the effectiveness of the proposed method by simulation and experiment.

• Journal of the Korean institute of surface engineering
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• v.41 no.5
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• pp.181-188
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• 2008

A.C. impedance properties of HA/Ti compound layer coated Ti-30Ta-($3{\sim}15$)Nb alloys have been studied by electrochemical method. Ti-30Ta binary alloys contained 3, 7, 10 and 15 wt% Nb were manufactured by the vacuum furnace system. And then specimen was homogenized at $1000^{\circ}C$ for 24 hrs. The sample was cut and polished for corrosion test and coating. It was coated with HA/Ti compound layer by magnetron sputter. The non-coated and coated morphology of Ti alloy were analyzed by X-ray diffractometer (XRD), energy X-ray dispersive spectroscopy (EDX) and filed emission scanning electron microscope (FE-SEM). The corrosion behaviors were investigated using A.C. impedance test (PARSTAT 2273, USA) in 0.9% NaCl solution at $36.5{\pm}1^{\circ}C$. Ti-30Ta-($3{\sim}15\;wt%$)Nb alloys showed the ${\alpha}+{\beta}$ phase, and $\beta$ phase peak was predominantly appeared in the case of increasingly Nb contents. The microstructures of Ti alloy were transformed from needle-like structure to equiaxed structure as Nb content increased. From the analysis of coating surface, HA/Ti composite surface uniformed coating layer with 750 nm thickness. The growth directions of film were (211), (112), (300) and (202) for HA/Ti composite coating on the surface after heat treatment at $550^{\circ}C$, whereas, the growth direction of film was (110) for Ti coating. The polarization resistance ($R_p$) of HA/Ti composite coated Ti-alloys were higher than those of the Ti and HA coated samples in 0.9% NaCl solution at $36.5{\pm}1^{\circ}C$. Especially, corrosion resistance of Ti-Ta-Nb system increased as Nb content increased.