• ETRI Journal
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• 제41권6호
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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.

• 한국건설관리학회논문집
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• 제19권3호
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• pp.52-60
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• 2018

우리나라의 공공건설공사는 입찰을 통해 공사를 발주하고 있으나 하지만 입찰의 특성상 참여자들간의 담합이 발생할 수 있다. 이에 따른 입찰담합은 발주자에게 손해를 가하는바, 이를 배상할 수 있도록 적절한 가상경쟁가격을 산정해야 한다. 이와 관련하여 계량경제학적 방법이 일반적으로 활용되고 있으나 건설공사, 특히 설계 시공일괄입찰의 특성상 여러 한계와 쟁점이 발생할 수밖에 없다. 따라서 본 연구에서는 설계 시공일괄입찰에서 합리적인 가상경쟁가격을 추정할 수 있는 방안을 제안한다. 이는 입찰 참가자가 제출한 설계도서로부터 한계비용을 도출하고, 입찰 참가자의 기술 수준과 경쟁업체의 기술 수준 및 입찰 형태에 따라 입찰율에 따른 요인을 검토하여 가상경쟁가격을 추정하는 방법이다. 본 연구에서 제안한 방법을 토대로 설계 시공일괄입찰 낙찰자 결정 방식의 특성이 반영된 합리적인 가격이 도출될 수 있으며, 답함에 따른 손해액 산정뿐만 아니라 실제 입찰 과정에서의 참고자료로 활용할 수 있을 것이라 판단된다.

• 한국산학기술학회논문지
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• 제16권9호
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• pp.6297-6304
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• 2015

우리나라 최초의 원자력발전소인 고리 원전 1호기의 폐쇄가 결정됨에 따라 원전 해체가 화두가 되고 있다. 원전 해체는 우리나라에서 한번도 경험해 보지 못한 일로 해체 과정도 어렵고 시간도 많이 소요된다. 그 일부분인 해체물량 또한 파악이 어렵다. 본 연구에서는 최근 건설산업에 많이 활용되고 있는 BIM 기술을 원전 해체 물량산출에 활용할 수 있는 방안을 제시하였다. 그 결과, 원전 해체 공법선정 및 공정 확립, BIM 모델링 환경 준비, 작업분류체계 구축, 객체분류체계 구축, BIM 통합모델 작성, BIM 객체에 물량 속성 배분 등의 방안을 제시하였다. 제시한 방안은 영구정지 대상 원전이 집중적으로 발생하는 시기부터 유용하게 활용될 수 있다. 이에 기반한 기술확보를 통해 나아가 해외 원전 해체 사업 수주에도 유리하게 작용할 것으로 기대된다.

• JSTS:Journal of Semiconductor Technology and Science
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• 제11권3호
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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.

• 전기학회논문지
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• 제60권2호
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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.

• 한국전자통신학회논문지
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• 제9권10호
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• pp.1153-1159
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• 2014

본 논문은 항만 개발에서 일부분의 주민참여가 아닌 대부분의 주민들이 참여가 가능한 ICT(Information Communication Technology)과 소셜 네트워크 기술을 적용하여 동해시의 묵호항 재개발 사업 친수 시설 규모 산정방안에 대한 새로운 방법을 제시한다. 이를 위해 항만 재개발 과정에서 효과적인 주민참여를 위한 방법으로 기존의 단순한 설문조사 방식과 더불어 다양한 SNS(Social Network System)을 적용하여 주민들의 의견 최대화한 도시 마케팅 방안을 분석한다. 또한 이를 위해서 주민 참여에 대한 비율을 최적 선정을 수행하고 최적 건설비 산정과 도시 마케팅 방안을 제시한다.

• 한국건설관리학회논문집
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• 제24권1호
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• pp.61-70
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• 2023

경제적인 측면이나 친환경적인 측면의 사유로 인해, 노후 건축물을 대상으로 그린리모델링 사업이 활발하게 진행되고 있다. 한편, 그린리모델링 사업을 추진하는 과정에서, 기존에는 설계자 및 엔지니어의 주관적 경험 및 지식에 기반하여 그린리모델링 계획이 개발되어 왔고, 이로 인해 경제성 등의 측면에서 효율적인 의사결정이 부족했다. 이에 본 연구에서는 노후 건축물의 속성을 분석하고 이에 따른 적정 리모델링 계획을 제안할 수 있는 온톨로지 기반 그린리모델링 의사결정 지원 모델을 구축하였다. 개발된 모델에서는 건축물의 기본 속성을 입력하면 온톨로지를 통한 웹검색을 기반으로 패시브 액티브 요소로 구성된 적정 리모델링 계획을 제공할 수 있다. 연구를 통해 개발된 결과물을 활용하면, 리모델링 사례의 증가에 따른 웹기반의 메타 데이터 검색을 통해 보다 객관적인 적정 리모델링 대안에 대한 의사결정 지원이 가능할 것으로 기대된다.

• The Plant Pathology Journal
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• 제35권2호
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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.

• 수산해양교육연구
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• 제29권3호
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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.

• 한국환경과학회지
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• 제16권6호
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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.