• International Journal of Computer Science & Network Security
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• v.21 no.3
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• pp.83-93
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• 2021

COVID-19 poses a major risk to global health, highlighting the importance of faster and proper diagnosis. To handle the rise in the number of patients and eliminate redundant tests, healthcare information exchange and medical data are transmitted between healthcare centres. Medical data sharing helps speed up patient treatment; consequently, exchanging healthcare data is the requirement of the present era. Since healthcare professionals share data through the internet, security remains a critical challenge, which needs to be addressed. During the COVID-19 pandemic, computed tomography (CT) and X-ray images play a vital part in the diagnosis process, constituting information that needs to be shared among hospitals. Encryption and image steganography techniques can be employed to achieve secure data transmission of COVID-19 images. This study presents a new encryption with the image steganography model for secure data transmission (EIS-SDT) for COVID-19 diagnosis. The EIS-SDT model uses a multilevel discrete wavelet transform for image decomposition and Manta Ray Foraging Optimization algorithm for optimal pixel selection. The EIS-SDT method uses a double logistic chaotic map (DLCM) is employed for secret image encryption. The application of the DLCM-based encryption procedure provides an additional level of security to the image steganography technique. An extensive simulation results analysis ensures the effective performance of the EIS-SDT model and the results are investigated under several evaluation parameters. The outcome indicates that the EIS-SDT model has outperformed the existing methods considerably.

• International Journal of Naval Architecture and Ocean Engineering
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• v.12 no.1
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• pp.367-375
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• 2020

This paper presents an integrated analysis about dynamic performance of a Floating Offshore Wind Turbine (FOWT) OC4 DeepCwind with semi-submersible platform under real sea environment. The emphasis of this paper is to investigate how the wave mean drift force and slow-drift wave excitation load (Quadratic transfer function, namely QTF) influence the platform motions, mooring line tension and tower base bending moments. Second order potential theory is being used for computing linear and nonlinear wave effects, including first order wave force, mean drift force and slow-drift excitation loads. Morison model is utilized to account the viscous effect from fluid. This approach considers floating wind turbine as an integrated coupled system. Two time-domain solvers, SIMA (SIMO/RIFLEX/AERODYN) and FAST are being chosen to analyze the global response of the integrated coupled system under small, moderate and severe sea condition. Results show that second order mean drift force and slow-drift force will drift the floater away along wave propagation direction. At the same time, slow-drift force has larger effect than mean drift force. Also tension of the mooring line at fairlead and tower base loads are increased accordingly in all sea conditions under investigation.

• Journal of Microbiology and Biotechnology
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• v.31 no.1
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• pp.104-114
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• 2021

Petroleum-contaminated soil is considered among the most important potential anthropogenic atmospheric methane sources. Additionally, various rhizoremediation factors can affect methane emissions by altering soil ecosystem carbon cycles. Nonetheless, greenhouse gas emissions from soil have not been given due importance as a potentially relevant parameter in rhizoremediation techniques. Therefore, in this study we sought to investigate the effects of different plant and soil amendments on both remediation efficiencies and methane emission characteristics in diesel-contaminated soil. An indoor pot experiment consisting of three plant treatments (control, maize, tall fescue) and two soil amendments (chemical nutrient, compost) was performed for 95 days. Total petroleum hydrocarbon (TPH) removal efficiency, dehydrogenase activity, and alkB (i.e., an alkane compound-degrading enzyme) gene abundance were the highest in the tall fescue and maize soil system amended with compost. Compost addition enhanced both the overall remediation efficiencies, as well as pmoA (i.e., a methane-oxidizing enzyme) gene abundance in soils. Moreover, the potential methane emission of diesel-contaminated soil was relatively low when maize was introduced to the soil system. After microbial community analysis, various TPH-degrading microorganisms (Nocardioides, Marinobacter, Immitisolibacter, Acinetobacter, Kocuria, Mycobacterium, Pseudomonas, Alcanivorax) and methane-oxidizing microorganisms (Methylocapsa, Methylosarcina) were observed in the rhizosphere soil. The effects of major rhizoremediation factors on soil remediation efficiency and greenhouse gas emissions discussed herein are expected to contribute to the development of sustainable biological remediation technologies in response to global climate change.

• Membrane and Water Treatment
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• v.13 no.3
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• pp.147-166
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• 2022

Liquid-liquid membrane contactor (LLMC), a device that exchanges dissolved gas molecules between the two sides of a hydrophobic membrane through membrane pores, can be employed to extract ammoniacal nitrogen from a feed solution, which is transported across the membrane and accumulated in a stripping solution. This LLMC process offers the promise of improving the sustainability of the global nitrogen cycle by cost-effectively recovering ammonia from wastewater. Despite recent technological advances in LLMC processes, a comprehensive review of their feasibility for ammonia recovery is rarely found in the literature. Our paper aims to close this knowledge gap, and in addition to analyze the challenges and provide potential solutions for improvement. We begin with discussions on the operational principles of the LLMC process for ammonia recovery and membrane types and membrane configurations commonly used in the process. We then assess the performance of the process by reviewing publications that demonstrate its practical application. Challenges involved in the implementation of the LLMC process, such as membrane fouling, membrane wetting, and chemical requirements, are presented, along with discussions on potential strategies to address each. These strategies, including membrane modification, hybrid process design, and process optimization based on cost-benefit analysis, guide the reader to identify key areas of future research and development.

• Atmosphere
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• v.32 no.3
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• pp.191-206
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• 2022

Assimilation trials were performed using the Korea Institute of Atmospheric Prediction Systems (KIAPS) Korea Integrated Model (KIM) semi-operational forecast system to assess the impact of ground-based Global Navigation Satellite System (GNSS) Zenith Total Delay (ZTD) on forecast. To use the optimal observation in data assimilation of KIM forecast system, in this study, the ZTD observation were pre-processed. It involves the bias correction using long term background of KIM, the quality control based on background and the thinning of ZTD data. Also, to give the effect of observation directly to data assimilation, the observation operator which include non-linear model, tangent linear model, adjoint model, and jacobian code was developed and verified. As a result, impact of ZTD observation in both analysis and forecast was neutral or slightly positive on most meteorological variables, but positive on geopotential height. In addition, ZTD observations contributed to the improvement on precipitation of KIM forecast, specially over 5 mm/day precipitation intensity.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.21 no.3
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• pp.100-109
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• 2022

In this study, calibration technology that increases the alignment accuracy in large flexible flat panels was studied. For precise of calibration, a systematization of the calibration algorithm was established, and a calibration correction technique was studied to revise calibration errors. A coordinate systems of camera and UVW stage was established to get the global position of the mark, and equations for translational and rotational calibration were systematically derived based on geometrical analysis. Correction process for the calibration data was carried, and alignment experiments were performed sequentially in cases of the presence or absence of calibration-correction. Alignment results of both calibration correction and non-calibration correction showed accuracy performance less than 1㎛. On the other hand, the standard deviation in calibration-correction is smaller than non-calibration correction. Therefore, calibration correction showed improvement of the alignment repeatability.

• Korean Journal of Remote Sensing
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• v.39 no.4
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• pp.459-466
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• 2023

In the last decade, artificial intelligence's dramatic advancement with the development of various deep learning techniques has significantly contributed to remote sensing fields and satellite image applications. Among many prominent areas, super-resolution research has seen substantial growth with the release of several benchmark datasets and the rise of generative adversarial network-based studies. However, most previously published remote sensing benchmark datasets represent spatial resolution within approximately 10 meters, imposing limitations when directly applying for super-resolution of small objects with cm unit spatial resolution. Furthermore, if the dataset lacks a global spatial distribution and is specialized in particular land covers, the consequent lack of feature diversity can directly impact the quantitative performance and prevent the formation of robust foundation models. To overcome these issues, this paper proposes a method to generate benchmark datasets by simulating the modulation transfer functions of the sensor. The proposed approach leverages the simulation method with a solid theoretical foundation, notably recognized in image fusion. Additionally, the generated benchmark dataset is applied to state-of-the-art super-resolution base models for quantitative and visual analysis and discusses the shortcomings of the existing datasets. Through these efforts, we anticipate that the proposed benchmark dataset will facilitate various super-resolution research shortly in Korea.

• Journal of Positioning, Navigation, and Timing
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• v.12 no.2
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• pp.121-128
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• 2023

When calculating the user's position using satellite signals, the signals originating from the satellite pass through the ionosphere and troposphere to the user. In particular, the ionosphere delay error that occurs when passing through the ionosphere delays when the signal is transmitted, generating a pseudorange error and position error at a large rate. Therefore, to improve position accuracy, it is essential to correct the ionosphere layer error. In a receiver capable of receiving dual frequency, the ionosphere error can be eliminated through a double difference, but in a single frequency receiver, an ionosphere correction model transmitted from a Global Navigation Satellite System (GNSS) satellite is used. The popularly used Klobuchar model is designed to improve performance globally. As such, it does not perform perfectly in the Korea region. In this paper, the characteristics of the delay in the ionosphere in the Korean region are identified through an analysis of 10 years of data, and an improved ionosphere correction model for the Korean region is presented using the widely employed Klobuchar model. Through the proposed model, vertical position error can be improved by up to 40% relative to the original Klobuchar model in the Korea region.

• Journal of Information Processing Systems
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• v.19 no.2
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• pp.149-163
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• 2023

Affected by external factors, errors in time series data collected by sensors are common. Using the traditional method of constraining the speed change rate to clean the errors can get good performance. However, they are only limited to the data of stable changing speed because of fixed constraint rules. Actually, data with uneven changing speed is common in practice. To solve this problem, an online cleaning algorithm for time series data based on dynamic speed change rate constraints is proposed in this paper. Since time series data usually changes periodically, we use the extreme learning machine to learn the law of speed changes from past data and predict the speed ranges that change over time to detect the data. In order to realize online data repair, a dual-window mechanism is proposed to transform the global optimal into the local optimal, and the traditional minimum change principle and median theorem are applied in the selection of the repair strategy. Aiming at the problem that the repair method based on the minimum change principle cannot correct consecutive abnormal points, through quantitative analysis, it is believed that the repair strategy should be the boundary of the repair candidate set. The experimental results obtained on the dataset show that the method proposed in this paper can get a better repair effect.

• The Journal of Industrial Distribution & Business
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• v.13 no.1
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• pp.1-9
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• 2022

Purpose: This study aims to find empirical evidence and clarity on the phenomenon of the direct and indirect effect of perceived behavioral control on fraud prevention through whistleblowing intention. This study also aims to understand the influence of organizational ethical culture moderating between whistleblowing intention and fraud prevention. Research design, data, methodology: The samples of this research are 236 respondents consisting of the Head of the Finance Subdivision and Head of the Reporting Planning Subdivision and the finance staff who were determined using the purposive sampling method. The data obtained were analyzed using the Structural Equation Modeling technique. Results: The study results show that perceived behavioral control positively and significantly affects whistleblowing intention. In addition, perceived behavioral control does not affect fraud prevention mediated by whistleblowing intention. Furthermore, organizational ethical culture moderates whistleblowing intention and has a positive and significant effect on fraud prevention. Conclusions: This study concludes that the phenomenon of scandal that often occurs on a television is not a habit that must be followed. It requires an active role from the community as a form of concern for whistleblowing. Futher researchers can add other construct variables, such as good corporate governance to assess the performance improvement of the organizational layers, both internally and externally