• Current Optics and Photonics
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• v.2 no.6
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• pp.540-546
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• 2018

We propose an implementation scheme for an optical encryption system with hybrid-pattern random keys. In the encryption process, a pair of random phase keys composed of a white-noise phase key and a structured phase key are positioned in the input plane and Fourier-spectrum plane respectively. The output image is recoverable by digital reconstruction, using the conjugate of the encryption key in the Fourier-spectrum plane. We discuss the system encryption performance when different combinations of phase-key pairs are used. To measure the effectiveness of the proposed method, we calculate the statistical indicators between original and encrypted images. The results are compared to those generated from a classical double random phase encoding. Computer simulations are presented to show the validity of the method.

• International Journal of Advanced Culture Technology
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• v.11 no.3
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• pp.310-314
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• 2023

The purpose of this study is to predict the remaining capacity of lithium-ion batteries and evaluate their performance using five artificial intelligence models, including linear regression analysis, decision tree, random forest, neural network, and ensemble model. We is in the study, measured Excel data from the CS2 lithium-ion battery was used, and the prediction accuracy of the model was measured using evaluation indicators such as mean square error, mean absolute error, coefficient of determination, and root mean square error. As a result of this study, the Root Mean Square Error(RMSE) of the linear regression model was 0.045, the decision tree model was 0.038, the random forest model was 0.034, the neural network model was 0.032, and the ensemble model was 0.030. The ensemble model had the best prediction performance, with the neural network model taking second place. The decision tree model and random forest model also performed quite well, and the linear regression model showed poor prediction performance compared to other models. Therefore, through this study, ensemble models and neural network models are most suitable for predicting the remaining capacity of lithium-ion batteries, and decision tree and random forest models also showed good performance. Linear regression models showed relatively poor predictive performance. Therefore, it was concluded that it is appropriate to prioritize ensemble models and neural network models in order to improve the efficiency of battery management and energy systems.

• Nuclear Engineering and Technology
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• v.47 no.4
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• pp.461-471
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• 2015

Recently, the estimation of the social cost of energy sources has been emphasized as various novel energy options become feasible in addition to conventional ones. In particular, the social cost of introducing measures to protect power-distribution systems from power-source instability and the cost of accident-risk response for various power sources must be investigated. To account for these risk factors, an integrated societal risk assessment framework, based on power-uncertainty analysis and accident-consequence analysis, is proposed. In this study, we applied the proposed framework to nuclear power plants, solar photovoltaic systems, and wind-turbine generators. The required capacity of gas-turbine power plants to be used as backup power facilities to compensate for fluctuations in the power output from the main power source was estimated based on the performance indicators of each power source. The average individual health risk per terawatt-hours (TWh) of electricity produced by each power source was quantitatively estimated by assessing accident frequency and the consequences of specific accident scenarios based on the probabilistic risk assessment methodology. This study is expected to provide insight into integrated societal risk analysis, and can be used to estimate the social cost of various power sources.

• Korean Journal of Computational Design and Engineering
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• v.21 no.3
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• pp.281-295
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• 2016

Lately, the management of domestic BIM performance is quite lacking, as the evaluation and management data from successful cases of BIM implementation both on projects and in companies, and related effects (time, cost and other physical gains) are not well kept for future use in BIM development. In order to overcome the above obstacles, a systematic approach to evaluating BIM adoption with focus on particular elements like BIM implementation environment and processes, and the physical factors yielded by BIM, is necessary. In this study, objective and detailed assessment indicators and weights that are appropriate for the domestic situation were derived through research for purposes of developing a web-based BIM maturity measurement program that is tailor-made for the Korean construction atmosphere. Through a company's self-maturity measurement, excellent quality of BIM deliverables and output can be achieved and managed. Furthermore, the domestic BIM capacity can gradually increase since design firms' BIM capability can be judged during procurement basing on measurement indicators.

• Safety and Health at Work
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• v.6 no.2
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• pp.77-84
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• 2015

Background: A unique framework for performance optimization of generation companies (GENCOs) based on health, safety, environment, and ergonomics (HSEE) indicators is presented. Methods: To rank this sector of industry, the combination of data envelopment analysis (DEA), principal component analysis (PCA), and Taguchi are used for all branches of GENCOs. These methods are applied in an integrated manner to measure the performance of GENCO. The preferred model between DEA, PCA, and Taguchi is selected based on sensitivity analysis and maximum correlation between rankings. To achieve the stated objectives, noise is introduced into input data. Results: The results show that Taguchi outperforms other methods. Moreover, a comprehensive experiment is carried out to identify the most influential factor for ranking GENCOs. Conclusion: The approach developed in this study could be used for continuous assessment and improvement of GENCO's performance in supplying energy with respect to HSEE factors. The results of such studies would help managers to have better understanding of weak and strong points in terms of HSEE factors.

• Journal of the Korean Society of Safety
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• v.23 no.6
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• pp.57-61
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• 2008

In order to maintain the continual safety management in a company, it needs to evaluate and monitor its implementation of safety management. Because the number of major-accidents is not an effective method of indicating company's safety performance, various efforts to develop more reasonable indicators have been made in world wide. After Korean government has legally required the PSM report, PSM compliance audit has been developed and made by the authorities concerned since 2005. However, this audit consists of complicate procedures difficult to utilize as companies' own audit program and corresponds to only a conformity check that confirms whether the PSM be operated and maintained properly. So a new index by which to measure easily the level of safety performance and self-monitor the implementation of safety management is needed. We have studied a new method that may quantitatively evaluate the performance of safety management by investigating application cases in foreign countries and doing the domestic survey of lots of companies subject to PSM regulation in Korea. This study proposes three of safety performance indices(SPI) together with the several prerequisite preconditions and the timing for application of each index. Although the first draft of SPI needs further legal support, it might help to evaluate every company's safety level. The second draft of SPI is a voluntarily evaluating method based on web-site online program. The last draft of SPI consists of a series of simple questions about 12 elements of PSM. Also each of 3 indices has differences in evaluation methodology and application area and, therefore, they may be used concurrently.

• Journal of Korean Society on Water Environment
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• v.36 no.6
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• pp.535-545
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• 2020

This study aims to conserve and monitor energy use in public sewage treatment plants by utilizing data from the SCADA system and by controlling the aeration rate required for maintaining effluent water quality. Power consumption in the sewage treatment process was predicted using the equipment's uptime, efficiency, and inherent power consumption. The predicted energy consumption was calibrated by measured data. Additionally, energy efficiency indicators were proposed based on statistical data for energy use, capacity, and effluent quality. In one case study, a sewage treatment plant operated via the SBR process used ~30% of energy consumed in maintaining the bioreactors and treated water tanks (included decanting pump and cleaning systems). Energy consumption analysis with the K-ECO Tool-kit was conducted for unit processing. The results showed that about 58.7% of total energy consumed was used in the preliminary and biological treatment rotating equipment such as the blower and pump. In addition, the energy consumption rate was higher to the order of 19.2% in the phosphorus removal process, 16.0% during sludge treatment, and 6.1% during disinfection and discharge. In terms of equipment energy usage, feeding and decanting pumps accounted for 40% of total energy consumed following 27% for blowers. By controlling the aeration rate based on the proposed feedback control system, the DO concentration was reduced by 56% compared pre-controls and the aeration amount decreased by 28%. The overall power consumption of the plant was reduced by 6% via aeration control.

• KIEAE Journal
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• v.13 no.2
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• pp.141-149
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• 2013

This paper aims to provide pragmatic application guidelines of the interior finish materials for apartment houses with newly-established evaluation methodology of the sustainable degree of interior products. With reference to the standards and criteria of domestic eco-labeling accreditation schemes for sustainable products in the area of architecture which focus on the sustainable elements classified as the health, recyclability, durability, and energy efficiency, in this study, a systematic evaluation method has been established for interior finish products with quantifiable indicators for sustainable performance. Base on the evaluation system introduced here, most interior finish products can be classified into a database and applied effectively to the realities from the perspective of the sustainability. There are the necessities of enforcement issues with the idea of revising or taking remedial measures of the current performance criteria of domestic eco-labeling accreditation to bolster their reliability. As well as already-commercialized products, hereafter, continued efforts are needed to control the whole process of manufacturing new interior finish products from their designing, constructing, consuming, recycling and to dismantling in terms of sustainability, which promises more pragmatic follow-up measures for the detail embodiment of the environment-friendly spaces.

• Bulletin of the Korean Space Science Society
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• 2008.10a
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• pp.37.3-37.3
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• 2008

STJ(Superconducting Tunnel Junction) technique offers next generation photon detectors exhibiting high energy resolution, high quantum efficiency and photon counting ability over the broad wavelength range from X-ray to NIR. We report the succcess in fabrication of Ta/Al-AlOx-Al/Ta and Nb/Al-AlOx-Al/Nb micro structure deposited on sapphire substrates using various techniques including UV photolithography, DC Sputtering, RIE, and PECVD technique. The characterization experiment was undertaken in an Adiabatic Demagnetization Refrigerator at an operating temperature below 50mK. The details of experimental investigations for electrical characterization of STJ of $20\sim80{\mu}m$ in side-lengths are discussed. The measured I-V curves were used to derive The detector performance indicators such as energy gap, energy resolution, normal resistance, normal resistivity, dynamic resistance, dynamic resistivity, and quality factor.

• Smart Structures and Systems
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• v.33 no.1
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• pp.41-53
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• 2024

Grouting sleeves are an essential connecting component of prefabricated components, and the quality of grouting has a significant influence on structural integrity and seismic performance. The embedded grouting sleeve (EGS)'s grouting defects are highly undetectable and random, and no effective monitoring method exists. This paper proposes an ultrasonic guided wave method and provides a set of guidelines for selecting the optimal frequency and suitable period for the EGS. The optimal frequency was determined by considering the group velocity, wave structure, and wave attenuation of the selected mode. Guided waves are prone to multi-modality, modal conversion, energy leakage, and dispersion in the EGS, which is a multi-layer structure. Therefore, a time-reversal (TR)-based multi-mode focusing and dispersion automatic compensation technology is introduced to eliminate the multi-mode phase difference in the EGS. First, the influence of defects on guided waves is analyzed according to the TR coefficient. Second, two major types of damage indicators, namely, the time domain and the wavelet packet energy, are constructed according to the influence method. The constructed wavelet packet energy indicator is more sensitive to the changes of defecting than the conventional time-domain similarity indicator. Both numerical and experimental results show that the proposed method is feasible and beneficial for the detection and quantitative estimation of the grouting defects of the EGS.