• Journal of Electrical Engineering and Technology
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• 제13권4호
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• pp.1614-1622
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• 2018

The research related to fault diagnosis in permanent magnet synchronous motors (PMSMs) has attracted considerable attention in recent years because various faults such as permanent magnet demagnetization and short-circuited turns can occur and result in unexpected failure of motor related system. Several conventional current and back electromotive force (BEMF) analysis techniques were proposed to detect certain faults in PMSMs; however, they generally deal with a single fault only. On the contrary, cases of multiple faults are common in PMSMs. We propose a fault diagnosis method for PMSMs with single and multiple combined faults. Our method uses three phase BEMF voltages based on the fast Fourier transform (FFT), support vector machine(SVM), and visualization tools for identifying fault types and severities in PMSMs. Principal component analysis (PCA) and t-distributed stochastic neighbor embedding (t-SNE) are used to visualize the high-dimensional data into two-dimensional space. Experimental results show good visualization performance and high classification accuracy to identify fault types and severities for single and multiple faults in PMSMs.

• 한국정밀공학회지
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• 제33권5호
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• pp.409-417
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• 2016

It is well known that Morpho butterflies show distinctive, brilliant and iridescent colors and have micro-nano scale structures, instead of dyes and pigments, on their wings. This structural coloration is regarded as a novel technique to express color with a long lifetime, ease and precise tenability. Here, we studied optical multilayer thin films with thickness of several tens of nm ($TiO_2$ and $SiO_2$) and lens-shape micro-patterns. Fabrication and characterization of the multilayer stacking structure and the micro-pattern structure were performed and the films were analyzed via several optical measuring techniques. Finally, we discussed how the micro-pattern structure could enhance independence with color changes according to the viewing angle.

• Geomechanics and Engineering
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• 제13권6호
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• pp.1027-1044
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• 2017

Membrane penetration is the most important factor influencing the measurement of volume change for triaxial consolidated-drained shear test for coarse-grained soil. The effective pressure p, average particle size $d_{50}$, thickness $t_m$ and elastic modulus $E_m$ of membrane, contact area between membrane and soil $A_m$ as well as the initial void ratio e are the major factors influencing membrane penetration. According to the membrane deformation model given by Kramer and Sivaneswaran, an analytical solution of the membrane penetration considering the initial void ratio is deduced using the energy conservation law. The basic equations from theory of plates and shells and the elastic mechanics are employed during the derivation. To verify the presented solution, isotropic consolidation tests of a coarse-grained soil are performed by using the method of embedding different diameter of iron rods in the triaxial samples, and volume changes due to membrane penetration are obtained. The predictions from presented solution and previous analytical solutions are compared with the test results. It is found that the prediction from presented analytical solution agrees well with the test results.

• International Journal of Computer Science & Network Security
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• 제22권7호
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• pp.352-358
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• 2022

Text mining is an important process used for analyzing the data collected from different sources like videos, audio, social media, and so on. The tools like Natural Language Processing (NLP) are mostly used in real-time applications. In the earlier research, text mining approaches were implemented using long-short memory (LSTM) networks. In this paper, text mining is performed using average-stochastic gradient descent weight-dropped (AWD)-LSTM techniques to obtain better accuracy and performance. The proposed model is effectively demonstrated by considering the internet movie database (IMDB) reviews. To implement the proposed model Python language was used due to easy adaptability and flexibility while dealing with massive data sets/databases. From the results, it is seen that the proposed LSTM plus weight dropped plus embedding model demonstrated an accuracy of 88.36% as compared to the previous models of AWD LSTM as 85.64. This result proved to be far better when compared with the results obtained by just LSTM model (with 85.16%) accuracy. Finally, the loss function proved to decrease from 0.341 to 0.299 using the proposed model

• 한국전자통신학회논문지
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• 제17권5호
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• pp.801-808
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• 2022

대규모 링크드 데이터에 어떻게 지식을 임베딩하고, 엔티티 매칭을 위해 어떻게 신경망 모델을 적용할 것인가에 대한 연구는 상대적으로 많이 부족한 상황이다. 이에 대한 가장 근본적인 문제는 서로 다른 레이블이 어휘 이질성을 초래한다는 것이다. 본 논문에서는 이러한 어휘 이질성 문제를 해결하기 위해 재정렬 구조를 결합한 확장된 GCN(Graph Convolutional Network) 모델을 제안한다. 제안된 모델은 기존 임베디드 기반 MTransE 및 BootEA 모델과 비교하여 각각 53% 및 40% 성능이 향상되었으며, GCN 기반 RDGCN 모델과 비교하여 성능이 5.1% 향상되었다.

• Geomechanics and Engineering
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• 제30권2호
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• pp.107-121
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• 2022

Coal pillar assessment is of broad importance to underground engineering structure, as the pillar failure can lead to enormous disasters. Because of the highly non-linear correlation between the pillar failure and its influential attributes, conventional forecasting techniques cannot generate accurate outcomes. To approximate the complex behavior of coal pillar, this paper elucidates a new idea to forecast the underground coal pillar stability using combined unsupervised-supervised learning. In order to build a database of the study, a total of 90 patterns of pillar cases were collected from authentic engineering structures. A state-of-the art feature depletion method, t-distribution symmetric neighbor embedding (t-SNE) has been employed to reduce significance of actual data features. Consequently, an unsupervised machine learning technique K-mean clustering was followed to reassign the t-SNE dimensionality reduced data in order to compute the relative class of coal pillar cases. Following that, the reassign dataset was divided into two parts: 70 percent for training dataset and 30 percent for testing dataset, respectively. The accuracy of the predicted data was then examined using support vector classifier (SVC) model performance measures such as precision, recall, and f₁-score. As a result, the proposed model can be employed for properly predicting the pillar failure class in a variety of underground rock engineering projects.

• 한국IT서비스학회지
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• 제22권2호
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• pp.93-127
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• 2023

This study analyzed the CEO New Year's addresses of major Korean companies, extracting key topics for employees via text mining techniques. An intended contribution of this study is to assist reporters, analysts, and researchers in gaining a better understanding of the New Year's addresses by elucidating the implicit and implicative features of messages within. To this end, this study collected and analyzed 545 New Year's addresses published between 2012 and 2021 by the top 66 Korean companies in terms of market capitalization. Research methodologies applied include text clustering, word embedding of keywords, frequency analysis, and topic modeling. Our main findings suggest that the messages in the New Year's addresses were categorized into nine topics-organizational culture, global advancement, substantial management, business reorganization, capacity building, market leadership, management innovation, sustainable management, and technology development. Next, this study further analyzed the managerial significance of each topic and discussed their characteristics from the perspectives of time, industry, and corporate groups. Companies were typically found to emphasize sound management, market leadership, and business reorganization during economic downturns while stressing capacity building and organizational culture during market transition periods. Also, companies belonging to corporate groups tended to emphasize founding philosophy and corporate culture.

• 한국컴퓨터정보학회논문지
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• 제14권7호
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• pp.81-88
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• 2009

핑거프린팅 기법은 디지털 데이터의 저작권을 보호하기 위하여 암호학적인 기법들을 이용한 방버이다. 디지털 데이터에 구매자 각각의 유일한 핑거프린트를 삽입하고 이를 이용하여 디지털 데이터를 불법적으로 재배포한 구매자를 찾아내게 된다. 핑거프린팅 기법은 구매자의 프라이버시 보호를 위하여 비대칭성이 보장되어야 한다. 본 논문에서는 대칭키 암호를 기반으로 하지만 비대칭성 만족을 위하여 신뢰기관의 참여가 필요하지 않는 프린팅 기법에 대하여 제안한다. 제안한 프로토콜은 대칭키 암호를 기반으로 하지만 신뢰기관이 구매자의 핑거프린트 생성에 참여하지 않으면서도 비대칭성을 만족한다. 신뢰기관의 비 참여로 인하여 제안한 프로토콜에서는 신뢰기관의 관리가 필요 없으며 구매자는 공모 공격으로부터 안전할 수 있다.

• Computers and Concrete
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• 제33권2호
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• pp.121-136
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• 2024

In recent times, there has been a growing need to retrofit and strengthen reinforced concrete (RC) structures that have been damaged. Numerous studies have explored various methods for strengthening RC beams. However, there is a significant dearth of research investigating the utilization of ultra-high-performance concrete (UHPC) for retrofitting damaged RC beams within a concrete frame. This study aims to develop a finite element (FE) model capable of accurately simulating the nonlinear behavior of RC beams and subsequently implementing it in an RC concrete frame. The RC frame is subjected to loading until failure at two distinct degrees, followed by retrofitting and strengthening using Ultra high performance shotcrete (UHPS) through two different methods. The results indicate the successful simulation of the load-displacement curve and crack patterns by the FE model, aligning well with experimental observations. Novel techniques for reinforcing deteriorated concrete frame structures through ABAQUS are introduced. The second strengthening method notably improves both the load-carrying capacity and initial stiffness of the load-displacement curve. By incorporating embedded rebars in the frame's columns, the beam's load-carrying capacity is enhanced by up to 31% compared to cases without embedding. These findings indicate the potential for improving the design of strengthening methods for damaged RC beams and utilizing the FE model to predict the strengthening capacity of UHPS for damaged concrete structures.

• Composites Research
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• 제18권4호
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• pp.1-7
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• 2005

삽입된 광섬유 브래그 격자(fiber Bragg grating, FBG) 센서를 이용하여 수압시험 동안에 필라멘트 와인딩 된 복합재료 압력탱크의 실시간 구조 건전성 모니터링을 수행하였다. 일반적으로 압력탱크의 내부와 외부의 유한요소해석 결과는 변형률과 응력 모두 큰 차이를 보인다. 그러므로, 압력탱크의 건전성을 검증하기 위해서는 운용 중 탱크 내부의 변형률 값을 정확하게 측정해야 한다. 여러 광섬유 센서 중 FBG 센서는 변형률 게이지에 비해 구조물에 삽입이 용이하고 많은 수의 센서를 한 가닥의 광섬유에 파장 분할 다중화(wavelength division multiplexing, WDM) 기법을 통해 쉽게 다중화 할 수 있다. 본 연구에서는 다중화 된 FBG 센서를 삽입한 표준압력용기(standard testing and evaluation bottle, STEB)를 제작하고 수압시험을 수행하였다. 삽입된 센서의 생존율을 높이기 위해 격자 부분에 대한 보강법을 포함한 새로운 삽입 적용 기법을 고안하였다. 제작된 탱크에 대한 수압 시험을 통해 FBG 센서가 필라멘트 와인딩 된 복합재 압력탱크의 건전성 모니터링을 위해 성공적으로 삽입 적용될 수 있음을 확인하였다.