• Journal of the Korea Society of Computer and Information
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• v.27 no.7
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• pp.187-194
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• 2022

LNG is known as the transitional energy source for the future eco-friendly, attracting enormous market attention due to global eco-friendly regulations, Covid-19 Pandemic, Russia-Ukraine War. In addition, since new LNG suppliers such as the U.S. and Australia are also diversifying, the LNG spot market is expected to grow. On the other hand, research on the LNG transportation market has been marginalized. Therefore, this study attempted to predict short-term LNG 160K spot rates and compared the prediction performance between artificial neural networks and the ARIMA model. As a result of this paper, while it was difficult to determine the superiority and superiority of ARIMA and artificial neural networks, considering the relative free of ANN's contraints, we confirmed the feasibility of ANN in LNG 160K spot rate prediction. This study has academic significance as the first attempt to apply an artificial neural network to forecasting LNG 160K spot rates and are expected to contribute significantly in practice in that they can improve the quality of short-term investment decisions by market participants by increasing the accuracy of short-term prediction.

• Journal of Internet of Things and Convergence
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• v.9 no.1
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• pp.77-87
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• 2023

Applying various association rule mining algorithms to the network intrusion detection task involves two critical issues: too large size of generated rule set which is hard to be utilized for IoT systems and hardness of control of false negative/positive rates. In this research, we propose an association rule mining algorithm based on the newly defined measures called coverage and exclusion. Coverage shows how frequently a pattern is discovered among the transactions of a class and exclusion does how frequently a pattern is not discovered in the transactions of the other classes. We compare our algorithm experimentally with the Apriori algorithm which is the most famous algorithm using the public dataset called KDDcup99. Compared to Apriori, the proposed algorithm reduces the resulting rule set size by up to 93.2 percent while keeping accuracy completely. The proposed algorithm also controls perfectly the false negative/positive rates of the generated rules by parameters. Therefore, network analysts can effectively apply the proposed association rule mining to the network intrusion detection task by solving two issues.

• Journal of the Korean Society of Industry Convergence
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• v.26 no.5
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• pp.885-894
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• 2023

Setting RAM target value for a defense system plays a crucial role in the development and design phases and the production phase as well. It is apparent that the achieved RAM target value can help maximizing the combat capability of a defense system and improving its performance throughout the system's life cycle from acquisition phase to disposal. Usually a defense system operates according to its OMS/MP (Operational Mode Summary / Mission Profile) and it consists of several subsystems which are supposed to be operated at each utilization rate under its operating conditions and the mission profiles assigned. In this study, a method of setting RAM target value is proposed for a defense system that are composed of several independent subsystems considering their utilization rates and the mission profiles assigned. And the case study of applying the proposed method of setting RAM target value to system A is dealt with.

• Journal of Digital Policy
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• v.2 no.4
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• pp.17-23
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• 2023

In this paper, in order to improve production processing for small and medium-sized precision processing companies, we apply a manufacturing execution system to existing process methods and integrate precision processing data to strengthen process management within the company, increase facility operation efficiency, and realize a reduction in defect rates. The differences in productivity improvement and cost reduction rates were compared and analyzed. As a result, production productivity improved by 7.0% and product defect rate improved by 0.1% point due to the introduction of the manufacturing execution system. It was confirmed that manufacturing cost reduction improved by 10.0% and delivery compliance rate improved by 1.1%. If additional smart factory technology is applied based on the manufacturing execution system proposed in this study in the future, sales and profits in the processing industry are expected to increase due to an increase in the PQCD index.

• Proceedings of the Korean Vacuum Society Conference
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• 2012.08a
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• pp.440-440
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• 2012

Nanomaterials have emerged as new building blocks to construct light energy harvesting assemblies. Size dependent properties provide the basis for developing new and effective systems with semiconductor nanoparticles, quantized charging effects in metal nanoparticle or their combinations in 2 and 3 dimensions for expanding the possibility of developing new strategies for photovoltaic system. As top-down approach, we developed a simple and effective method for the large scale formation of self-assembled Cu(In,Ga)$Se_2$ (CIGS) nanostructures by ion beam irradiation. The compositional changes and morphological evolution were observed as a function of the irradiation time. As the ion irradiation time increased, the nano-dots were transformed into a nano-ridge structure due to the difference in the sputtering yields and diffusion rates of each element and the competition between sputtering and diffusion processes during irradiation. As bottom-up approach, we developed the growth of CIGS nanowires using thermal-chemical vapor deposition (CVD) method. Vapor-phase synthesis is probably the most extensively explored approach to the formation of 1D nanostructures such as whiskers, nanorods, and nanowires. However, unlike binary or ternary chalcogenides, the synthesis of quaternary CIGS nanostructures is challenging because of the difficulty in controlling the stoichiometry and phase structure. We introduced a method for synthesis of the single crystalline CIGS nanowires in the form of chalcopyrite using thermal-CVD without catalyst. It was confirmed that the CIGS nanowires are epitaxially grown on a sapphire substrate, having a length ranged from 3 to 100 micrometers and a diameter from 30 to 500 nm.

• Journal of Digital Convergence
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• v.14 no.10
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• pp.261-269
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• 2016

This paper aims to propose a novel technology of network convergence to provide ultra high speed internet services over CATV networks, by which a CMC(cable modem concentrator) and CM(cable modem) of 1Gbps level are designed. This technology not only lowers the production cost in comparison to the existing bonding technology with DOCSIS specification but also enables the adjustment of data speed based on the channel bandwidth. According to the experiments, when convolutional code rate with 128QAM is changed to 1/2, 2/3, 3/4 and 7/8, the data recorded the maximum transmission speed of up to 299 Mbps at the zero error rate. As the convolutional code rates with 256QAM is increased, it showed 334Mbps at the error rate of $10^{-5}$. Based on the findings of this paper, if we secure the channel bandwidth of 200MHz and adjust the modulation order of QAM and the convolution code rate depending on the channel status, we can get the transmission speed of more than 1Gbps, which is much more competitive in its function and price than the existing technology based on DOCSIS.

• Journal of the Korea Convergence Society
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• v.11 no.8
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• pp.159-163
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• 2020

In this study, the flow analyses around according to the existence or non- existence of the trailer's deflector and the shapes were carried out. In the absence of a deflector, the kinetic energy of the turbulence behind the container also generates higher kinetic energy in a wider area than in the presence of a deflector, which adversely affects the vehicle's driving performance. As a trailer's wind deflector-free model has unstable flow rates around the trailer and high kinetic energy of turbulence than a model with a deflector, it can be thought that the increase of fuel economy can be expected by installing a deflector in the trailer. By applying the study result on flow analysis near trailer due to shape of wind deflector, this study is seen to be suitable for the aesthetic convergence.

• Journal of the Korea Convergence Society
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• v.11 no.8
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• pp.39-45
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• 2020

Recently the terrors have been attempted in the public places of the nations such as United states, England and Japan by explosive things, toxic materials and so on. It is understood that the method in which dangerous objects are put in public places is one of the difficult types in detection. While there are the cameras recording videos for many spots in public places, it is very hard for the security personnel to monitor every videos. Nowadays the smart softwares which can analyzing videos automatically are utilized to detect abandoned objects. The method by Lin et al. shows comparatively high detection rates for abandoned objects but it is not easy to obtain the shape information because there is a tendency that the number of the pixels decreases abruptly along the time goes due to the characteristics of short-term background images. In this research a novel method is proposed to successfully extract the shape of the abandoned object by analysing the characteristics of area variation. The experiment results show that the proposed method has better performance in extracting shape information in comparison with the precedent approach.

• Journal of the Korea Convergence Society
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• v.8 no.5
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• pp.13-17
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• 2017

Existing Speech feature extracting method in speech Signal, there are incorrect recognition rates due to incorrect speech which is not clear threshold value. In this article, the modeling method for improving speech recognition performance that combines the feature extraction for speech and silence characteristics normalized to the non-speech. The proposed method is minimized the noise affect, and speech recognition model are convergence of speech signal feature extraction to each speech frame and the silence feature normalization. Also, this method create the original speech signal with energy spectrum similar to entropy, therefore speech noise effects are to receive less of the noise. the performance values are improved in signal to noise ration by the silence feature normalization. We fixed speech and non speech classification standard value in cepstrum For th Performance analysis of the method presented in this paper is showed by comparing the results with CHMM HMM, the recognition rate was improved 2.7%p in the speech dependent and advanced 0.7%p in the speech independent.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.29 no.9
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• pp.552-558
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• 2016

Goethite, ${\alpha}$-FeOOH have various applications such as absorbent, pigment and source for magnetic materials. Goethite particles were synthesized in a two step process, where $Fe(OH)_2$ were synthesized in nitrogen atmosphere using $FeSO_4$ as a raw material in the first process, and after that acicular goethite particles were obtained in an air oxidation process of $Fe(OH)_2$ in highly alkaline aqueous solution. Their phase and microstructure were investigated with XRD and FE-SEM. It was found that the morphology of goethite and the ratio of length-to-width (aspect ratio) of acicular goethite are dependent on the some factors such as R value ($OH^-/Fe^{2+}$), air flow rate and pH conditions. In particular, R value has the strongest influence on the synthesized goethite morphology. It is considered that the optimal value R is 4.5 because X-ray diffraction peaks of goethite have the highest intensity at that value. Morphology of goethite particles was controlled by air flow rates, showing that their size and aspect ratio are getting smaller and decrease, respectively as air flow rate increases. The largest goethite particle obtained is about 1,500 nm in length and 150 nm in diameter.