• Journal of the Semiconductor & Display Technology
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• v.20 no.3
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• pp.93-96
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• 2021

The desire for a technology that can mechanically acquire 2D images starting with the manual method of drawing has been making possible a wide range of modern image-based technologies and applications over a period. Moreover, this trend of the utilization of image-related technology as well as image-based information is likely to continue. Naturally, as like other technology areas, the function that humans produce and utilize by using images needs to be automated by using computing-based technologies. Surprisingly, technology using images in the future will be able to discover knowledge that humans have never known before through the information-related process that enables new perception, far beyond the scope of use that human has used before. Regarding this trend, the manipulation and configuration of massively distributed image database system is strongly demanded. In this paper, we discuss image identifier production methods based on the utilization of the image hashing technique which especially puts emphasis over an entropy operator.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.37 no.2
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• pp.85-93
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• 2024

In this paper, we propose a method for establishing a state-space equation model for the motion analysis of floating structures subjected to wave loads, by applying system-identification techniques. Traditionally, the motion of floating structures has been analyzed in the time domain by integrating the Cummins equation over time, which utilizes a convolution integral term to account for the effects of the retardation function. State-space equation models have been studied as a way to efficiently solve floating-motion equations in the time domain. The proposed approach outlines a procedure to derive the target transfer function for the load-displacement input/output relationship in the frequency domain and subsequently determine the state-space equation that closely approximates it. To obtain the state-space equation, the method employs the N4SID system-identification method and an optimization approach that treats the coefficients of the numerator and denominator polynomials as design variables. To illustrate the effectiveness of the proposed method, we applied it to the analysis of a single-degree-of-freedom model and the motion of a six-degree-of-freedom barge. Our findings demonstrate that the presented state-space equation model aligns well with the existing analysis results in both the frequency and time domains. Notably, the method ensures computational accuracy in the time-domain analysis while significantly reducing the calculation time.

• Korean Chemical Engineering Research
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• v.52 no.5
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• pp.581-586
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• 2014

Main objects for wastewater treatment operation are to maintain effluent water quality and minimize operation cost. However, the optimal operation is difficult because of the change of influent flow rate and concentrations, the nonlinear dynamics of microbiology growth rate and other environmental factors. Therefore, many wastewater treatment plants are operated for much more redundant oxygen or chemical dosing than the necessary. In this study, the optimal control scheme for dissolved oxygen (DO) is suggested to prevent over-aeration and the reduction of the electric cost in plant operation while maintaining the dissolved oxygen (DO) concentration for the metabolism of microorganisms in oxic reactor. The oxygen uptake rate (OUR) is real-time measured for the identification of influent characterization and the identification of microorganisms' oxygen requirement in oxic reactor. Optimal DO set-point needed for the micro-organism is suggested based on real-time measurement of oxygen uptake of micro-organism and the control of air blower. Therefore, both stable effluent quality and minimization of electric cost are satisfied with a suggested optimal set-point decision system by providing the necessary oxygen supply requirement to the micro-organisms coping with the variations of influent loading.

• Journal of Ginseng Research
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• v.40 no.4
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• pp.453-461
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• 2016

Background: This study aims to describe the characterization of Paenibacillus polymyxa GBR-1 (GBR-1) with respect to its positive and negative effects on plants. Methods: The morphological characteristics of GBR-1 were identified with microscopy, and subjected to Biolog analysis for identification. Bacterial population and media optimization were determined by a growth curve. The potential for GBR-1 as a growth promoting agent, to have antagonistic activity, and to have hydrolytic activity at different temperatures was assessed. The coinoculation of GBR-1 with other microorganisms and its pathogenicity on various stored plants, including ginseng, were assessed. Results: Colony morphology, endospore-bearing cells, and cell division of GBR-1 were identified by microscopy; identification was performed by utilizing the Biolog system, gas chromatography of fatty acid methyl esters (GC-FAME). GBR-1 showed the strongest antagonistic activity against fungal and bacterial pathogens. GBR-1 cell numbers were relatively higher when the cells were cultured in brain heart infusion (BHI) medium when compared with other media. Furthermore, the starch-hydrolytic activity was influenced by GBR-1 at higher temperature compared to low temperatures. GBR-1 was pathogenic to some of the storage plants. Coinoculation of GBR-1 with other pathogens causes differences in rotting on ginseng roots. A significant growth promotion was observed in tobacco seedlings treated with GBR-1 suspensions under in vitro conditions, suggesting that its volatile organic compounds (VOCs) might play a role in growth promotion. Conclusion: The results of this study indicate that GBR-1 has both positive and negative effects on ginseng root and other stored plants as a potential biocontrol agent and eliciting in vitro growth promotion.

• Journal of Information Technology Services
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• v.21 no.4
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• pp.63-74
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• 2022

Globally researchers at medical institutions are actively sharing COHORT data of patients to develop vaccines and treatments to overcome the COVID-19 crisis. OMOP-CDM, a common data model that efficiently shares medical data research independently operated by individual medical institutions has patient personal information (e.g. PII, PHI). Although PII and PHI are managed and shared indistinguishably through de-identification or anonymization in medical institutions they could not be guaranteed at 100% by complete de-identification and anonymization. For this reason the security of the OMOP-CDM database is important but there is no detailed and specific OMOP-CDM security inspection tool so risk mitigation measures are being taken with a general security inspection tool. This study intends to study and present a model for implementing a tool to check the security vulnerability of OMOP-CDM by analyzing the security guidelines for the US database and security controls of the personal information protection of the NIST. Additionally it intends to verify the implementation feasibility by real field demonstration in an actual 3 hospitals environment. As a result of checking the security status of the test server and the CDM database of the three hospitals in operation, most of the database audit and encryption functions were found to be insufficient. Based on these inspection results it was applied to the optimization study of the complex and time-consuming CDM CSF developed in the "Development of Security Framework Required for CDM-based Distributed Research" task of the Korea Health Industry Promotion Agency. According to several recent newspaper articles, Ramsomware attacks on financially large hospitals are intensifying. Organizations that are currently operating or will operate CDM databases need to install database audits(proofing) and encryption (data protection) that are not provided by the OMOP-CDM database template to prevent attackers from compromising.

• Smart Structures and Systems
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• v.33 no.2
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• pp.165-175
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• 2024

Rotating beams play a crucial role in representing complex mechanical components that are prevalent in vital sectors like energy and transportation industries. These components are susceptible to the initiation and propagation of cracks, posing a substantial risk to their structural integrity. This study presents a two-stage methodology for detecting the location and estimating the size of an open-edge transverse crack in a rotating Euler-Bernoulli beam with a uniform cross-section. Understanding the dynamic behavior of beams is vital for the effective design and evaluation of their operational performance. In this regard, modal parameters such as natural frequencies and eigenmodes are frequently employed to detect and identify damages in mechanical components. In this instance, the Frobenius method has been employed to determine the first two natural frequencies and corresponding eigenmodes associated with flapwise bending vibration. These calculations have been performed by solving the governing differential equation that describes the motion of the beam. Various parameters have been considered, such as rotational speed, beam slenderness, hub radius, and crack size and location. The effect of the crack has been replaced by a rotational spring whose stiffness represents the increase in local flexibility as a result of the damage presence. In the initial phase of the proposed methodology, a damage index utilizing the slope of the beam's eigenmode has been employed to estimate the location of the crack. After detecting the presence of damage, the size of the crack is determined using a Genetic Algorithm optimization technique. The ultimate goal of the proposed methodology is to enable the development of more suitable and reliable maintenance plans.

• Microbiology and Biotechnology Letters
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• v.49 no.2
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• pp.181-191
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• 2021

The present study addresses isolation, optimization, partial purification, and characterization of a haloalkaline serine protease from a newly isolated haloarchaeal strain isolated from Wadi El Natrun in Egypt. We expected that a two-step sequential statistical approach (one variable at a time, followed by response surface methodology) might maximize the production of the haloalkaline serine protease. The enzyme was partially purified using Hiprep 16/60 sephacryl S-100 HR gel filtration column. Molecular identification revealed the newly isolated haloarchaeon to be Natrialba hulunbeirensis strain WNHS14. Among several tested physicochemical determinants, casamino acids, KCl, and NaCl showed the most significant effects on enzyme production as determined from results of the One-Variable-At-A-time (OVAT) study. The BoxBehnken design localized the optimal levels of the three key determinants; casamino acids, KCl, and NaCl to be 0.5% (w/v), 0.02% (w/v), and 15% (w/v), respectively, obtaining 62.9 U/ml as the maximal amount of protease produced after treatment at 40℃, and pH 9 for 9 days with 6-fold enhancement in yield. The enzyme was partially purified after size exclusion chromatography with specific activity, purification fold, and yield of 1282.63 U/mg, 8.9, and 23%, respectively. The enzyme showed its maximal activity at pH, temperature, and NaCl concentration optima of 10, 75℃, and 2 M, respectively. Phenylmethylsulfonyl fluoride (PMSF, 5 mM) completely inhibited enzyme activity.

• Nuclear Engineering and Technology
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• v.53 no.1
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• pp.148-163
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• 2021

Timely fault identification is important for safe and reliable operation of the electric valve system. Many research works have utilized different data-driven approach for fault diagnosis in complex systems. However, they do not consider specific characteristics of critical control components such as electric valves. This work presents an integrated shallow-deep fault diagnostic model, developed based on signals extracted from DN50 electric valve. First, the local optimal issue of particle swarm optimization algorithm is solved by optimizing the weight search capability, the particle speed, and position update strategy. Then, to develop a shallow diagnostic model, the modified particle swarm algorithm is combined with support vector machine to form a hybrid improved particle swarm-support vector machine (IPs-SVM). To decouple the influence of the background noise, the wavelet packet transform method is used to reconstruct the vibration signal. Thereafter, the IPs-SVM is used to classify phase imbalance and damaged valve faults, and the performance was evaluated against other models developed using the conventional SVM and particle swarm optimized SVM. Secondly, three different deep belief network (DBN) models are developed, using different acoustic signal structures: raw signal, wavelet transformed signal and time-series (sequential) signal. The models are developed to estimate internal leakage sizes in the electric valve. The predictive performance of the DBN and the evaluation results of the proposed IPs-SVM are also presented in this paper.

• Journal of Advanced Marine Engineering and Technology
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• v.38 no.6
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• pp.716-722
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• 2014

In order to design the speed controller of the DC motor system, firstly, parameters estimation of the system must be preceded. In this paper, we proposed the application of genetic algorithm(GA) optimization in estimating the parameters of DC motor. Estimated models are considered both first and second order models, and each estimated model is optimized by minimizing three different types of the evaluation function of GA. Also, GA is imported in comparison with estimation result of numerical analysis method because of its power in searching entire solution space with more probability of finding the global optimum. Data for parameter estimation is acquired from input and output signals of the actual experiment device and the butterworth filter also designs for removing noise in the signals. Finally comparison between real data of the actual device and estimated models is presented to indicate effectiveness and resolution of proposed identification method.

• Journal of the Society of Naval Architects of Korea
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• v.57 no.3
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• pp.160-167
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• 2020

A two-stroke diesel engine and a propeller normally adopted in large merchant ships are regarded as major ship vibration sources. They are directly connected and generate various excitation components proportional to the rotating speed of diesel engine. Among the components, the magnitude of two excitation components with the same frequency generated by both engine and propeller can be compensated by the adjustment of their phase difference. It can be done by the optimization of propeller assembly angle but requires a number of burdensome trials to find the optimal angle. In this paper, the efficient estimation method to determine optimal propeller assembly angle is proposed. Its application requires the axial vibration measurement in sea trial and the numerical vibration analysis for propulsion shafting which can be substituted by additional vibration measurement after one-trial modification of propeller assembly angle. In order to verify the validity of the proposed method, the phase difference between two fifth order excitation components generated by both diesel engine and propeller of a real ship is calculated by the finite element analysis and its result is indirectly validated by the comparison of axial vibration responses at intermediate shaft obtained by the numerical analysis and the measurement in sea trial. Finally, it is numerically confirmed that axial vibration response at intermediate shaft at a resonant speed can be decreased more than 87 % if the optimal propeller assembly angle determined by the proposed method is applied.