• ETRI Journal
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• v.41 no.6
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• pp.750-759
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• 2019

Presently, the extraction of hand-crafted features is still the dominant method in radar emitter recognition. To solve the complicated problems of selection and updation of empirical features, we present a novel automatic feature extraction structure based on deep learning. In particular, a convolutional neural network (CNN) is adopted to extract high-level abstract representations from the time-frequency images of emitter signals. Thus, the redundant process of designing discriminative features can be avoided. Furthermore, to address the performance degradation of a single platform, we propose the construction of an ensemble learning-based architecture for multi-platform fusion recognition. Experimental results indicate that the proposed algorithms are feasible and effective, and they outperform other typical feature extraction and fusion recognition methods in terms of accuracy. Moreover, the proposed structure could be extended to other prevalent ensemble learning alternatives.

• Korean Journal of Construction Engineering and Management
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• v.19 no.3
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• pp.52-60
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• 2018

Korea's public construction projects are under construction through bidding, however, due to the nature of the bidding, collusion between participants can occur. The collusion of bids accordingly damages the client. So, it is necessary to calculate the appropriate fictitious competition price to compensate for this. In this regard, econometrics methods are generally used, but there are limitations and issues arising from the nature of construction, especially design-build bid. Therefore, this study proposes a method to estimate reasonable competitive bid-price in design-build bid. It derives the lowest bid-price from the design submitted by the proponent and estimates the competitive bid-price by examining the factors according to the penetration rate according to the technical level of the tester, the skill level of the competitor, and the type of tester. Based on the method proposed in this study, a reasonable price can be derived that reflects the characteristics of the design and construction bidding bidder selection method and also it can be used as a reference material in the actual bidding process as well as calculating the damage due to the answer.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.16 no.9
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• pp.6297-6304
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• 2015

Nuclear power plant decommissioning has attracted attention according to the shutdown decision of Kori 1 which is Korea's first nuclear power plant. Nuclear power plant decommissioning is the one who never experienced ever in our country. So, its process is difficult and time-consuming. In addition, it is difficult to determine the decommissioning quantity. This study proposed the plan that can be used in quantity take-off for nuclear power plant decommissioning using BIM technology being utilized in recent construction industry. As a result, we suggested the method of BIM-based quantity take-off such as the selection decommissioning method and process, setting up of BIM modeling environment, establishment of OBS & WBS, integrated BIM modeling, the definition of quantity property. The proposed plan can be utilized usefully from when permanent stopping nuclear power plant occurs intensively. Furthermore, the overseas nuclear power plant decommissioning project order also are expected through technology securement based on this plan.

• JSTS:Journal of Semiconductor Technology and Science
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• v.11 no.3
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• pp.135-145
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• 2011

Accurate process characterization and optimization are the first step for a successful advanced process control (APC), and they should be followed by continuous monitoring and control in order to run manufacturing processes most efficiently. In this paper, process characterization and recipe optimization methods with multiple outputs are presented in high density plasma-chemical vapor deposition (HDP-CVD) silicon dioxide deposition process. Five controllable process variables of Top $SiH_4$, Bottom $SiH_4$, $O_2$, Top RF Power, and Bottom RF Power, and two responses of interest, such as deposition rate and uniformity, are simultaneously considered employing both statistical response surface methodology (RSM) and neural networks (NNs) based genetic algorithm (GA). Statistically, two phases of experimental design was performed, and the established statistical models were optimized using performance index (PI). Artificial intelligently, NN process model with two outputs were established, and recipe synthesis was performed employing GA. Statistical RSM offers minimum numbers of experiment to build regression models and response surface models, but the analysis of the data need to satisfy underlying assumption and statistical data analysis capability. NN based-GA does not require any underlying assumption for data modeling; however, the selection of the input data for the model establishment is important for accurate model construction. Both statistical and artificial intelligent methods suggest competitive characterization and optimization results in HDP-CVD $SiO_2$ deposition process, and the NN based-GA method showed 26% uniformity improvement with 36% less $SiH_4$ gas usage yielding 20.8 ${\AA}/sec$ deposition rate.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.60 no.2
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• pp.398-406
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• 2011

In this paper, we introduce a new architecture of PSO-based Polynomial Neural Networks (PNN) and discuss its comprehensive design methodology. The conventional PNN is based on a extended Group Method of Data Handling (GMDH) method, and utilized the polynomial order (viz. linear, quadratic, and modified quadratic) as well as the number of node inputs fixed (selected in advance by designer) at Polynomial Neurons located in each layer through a growth process of the network. Moreover it does not guarantee that the conventional PNN generated through learning results in the optimal network architecture. The PSO-based PNN results in a structurally optimized structure and comes with a higher level of flexibility that the one encountered in the conventional PNN. The PSO-based design procedure being applied at each layer of PNN leads to the selection of preferred PNs with specific local characteristics (such as the number of input variables, input variables, and the order of the polynomial) available within the PNN. In the sequel, two general optimization mechanisms of the PSO-based PNN are explored: the structural optimization is realized via PSO whereas in case of the parametric optimization we proceed with a standard least square method-based learning. To evaluate the performance of the PSO-based PNN, the model is experimented with using Gas furnace process data, and pH neutralization process data. For the characteristic analysis of the given entire data with non-linearity and the construction of efficient model, the given entire system data is partitioned into two type such as Division I(Training dataset and Testing dataset) and Division II(Training dataset, Validation dataset, and Testing dataset). A comparative analysis shows that the proposed PSO-based PNN is model with higher accuracy as well as more superb predictive capability than other intelligent models presented previously.

• The Journal of the Korea institute of electronic communication sciences
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• v.9 no.10
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• pp.1153-1159
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• 2014

In this paper we propose novel method for cost of harbor facility of redevelopment of Mookho harbor at Donghae city by using ICT(Information Communication Technology) and Social Network System that is able to participate most residents instead of partly participation for harbor development. In order to do this, we analyze urban marketing which was maximally reflected opinion of resident by using previous simple questionnaire as well as various SNS (Social Network System) as method of effective resident's participation in process harbor redevelopment. We perform optimal selection for ratio of resident's participation. We also propose calculation of optimal construction cost and method of urban marketing.

• Korean Journal of Construction Engineering and Management
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• v.24 no.1
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• pp.61-70
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• 2023

Due to economic or environmental reasons, green remodeling projects for old buildings are being actively carried out. Meanwhile, in the process of performing the green remodeling, the plan of green remodeling including passive and active elements has been decided based on the subjective experience and knowledge of engineers currently. Therefore, in this study, an ontology-based green remodeling decision-making support model, which can analyze the properties of old buildings and suggest appropriate remodeling plans, was established. In the developed model, once the basic properties of a building are entered, an appropriate remodeling plan composed of passive and active elements can be provided. By utilizing the results developed through the research, it is expected that it will be possible to support decision-making on more objective and appropriate remodeling alternatives development through web-based meta data search in accordance with the accumulation in remodeling cases.

• The Plant Pathology Journal
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• v.35 no.2
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• pp.164-171
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• 2019

An assay for detecting Apple scar skin viroid (ASSVd) was developed based on nucleic acid sequence based amplification (NASBA) in combination with realtime detection during the amplification process using molecular beacon. The ASSVd specific primers for amplification of the viroid RNA and molecular beacon for detecting the viroid were designed based on highly conserved regions of several ASSVd sequences including Korean isolate. The assay had a detection range of $1{\times}10^4$ to $1{\times}10^{12}$ ASSVd RNA $copies/{\mu}l$ with reproducibility and precision. Following the construction of standard curves based on time to positive (TTP) value for the serial dilutions ranging from $1{\times}10^7$ to $1{\times}10^{12}$ copies of the recombinant plasmid, a standard regression line was constructed by plotting the TTP values versus the logarithm of the starting ASSVd RNA copy number of 10-fold dilutions each. Compared to the established RT-PCR methods, our method was more sensitive for detecting ASSVd. The real-time quantitative NASBA method will be fast, sensitive, and reliable for routine diagnosis and selection of viroid-free stock materials. Furthermore, real-time quantitative NASBA may be especially useful for detecting low levels in apple trees with early viroid-infection stage and for monitoring the influence on tree growth.

• Journal of Fisheries and Marine Sciences Education
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• v.29 no.3
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• pp.677-688
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• 2017

The purpose of this study is to analyze the action learning lesson about the improvement process of the job support program of P university students. As a research method, we applied the related classes during the semester to the students who took courses in the course of 'Human Resource Development', which is a subject of P university, and analyzed the learner's reflection journal, interview data. As a result of the research, we went through the problem selection stage, the team construction and the team building stage. And then we searched for the root cause of the problem, clarified the problem, derived the possible solution, determined the priority and created the action plan. There are 10 solutions to the practical problems of poor job camps. Through two interviews with field experts it offered final solutions focused on promoting employment and Camp students participate in the management of post-employment into six camps. According to the first rank, job board integration, vendor selection upon student feedback, reflecting improved late questionnaire, public relations utilizing KakaoTalk, recruiting additional selection criteria, the camp provides recorded images in order. The results of this study suggest that the university's employment support program will strengthen the competitiveness of students' employment and become the basic data for the customized employment support program.

• Journal of Environmental Science International
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• v.16 no.6
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• pp.735-743
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• 2007

A grouting method is the way to effectively prevent pollutants from spreading into the ground during the digging process of groundwater. This study, based on the comparative study of grouting methods being generally accepted, suggests various construction methods which are suitable for geological structure as follows: In Jeju Island, it is very likely that rocks may fall in shuttered zones such as cracks, joints, scoria layers, and clinker layers. For this reason, it is recommended that materials be injected from the bottom toward the top, not from the top to the bottom. In the case where the amount of injected materials become too large in the areas of cracks or joints because of high level of permeability coefficient, grouting materials which smeared into surrounding areas may cause unwanted cut in the aquifer of the bottom level. To avoid this, the amount of water should be reduced from the typical water-cement ratio of 1:2, and grouting materials with larger grading should be used. If the deep excavation of ground is made in Jeju Island, it is likely to have lots of voids because of geological characteristics. Based on the results of this research, it is found that to construct interior casing, the centralizer should be attached to the casing to prevent the casing from being in contact with the counter fort. The grouting in Jeju Island should be thicker than usual. To avoid over-use of grouting materials, to prevent grouting in more than necessary zone, and to facilitate grouting of void areas, the flexible selection of materials is required. And, to exactly figure out the interior of dug well, an examination through CCTV should necessarily be performed when grouting work is in progress.