• 수산해양기술연구
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• 제27권3호
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• pp.193-210
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• 1991

For the deckhouse or superstructure, attention is directed to the reduction of vibration from a human susceptibility point of view. The two basic requirements for obtaining a low vibration level in the accommodation are to ensure that excitation forces from propeller and/or main engine are small and to avoid resonance excitation of the hull and superstructure. In recent years increased attention has been directed towards the problems of vibration and noise in deckhouse, which have caused major problems with regard to the environmental quality in the living quarters for crews. Accordingly, in this paper, the characteristic of the vibration of deckhouse of fishing boat, of which the length/height ratio is also relatively high, are studied systematically with regard to the shape and modelling of deckhouse based on finite element method of 1-dimensional, 2-dimensional and 3-dimensional model. This study is divided into 4-part. 1st part is the global deckhouse vibration, 2nd part is the local deckhouse vibration, 3rd part consists of the estimation for stiffness of foundational support and 4th part is the application to TUNA LONG LINER of 416 ton class. For the global vibration analysis, the severity of the vibration depends on the longitudinal shear and bending stiffness of the deckhouse, on the vertical deckhouse support(fore, aft and sides). However, even if the design is technically sound, vibration problems may arise due to vertical or longitudinal hull girder or afterbody resonances. Author applied the method of this study to the analysis of, deep-sea fishing vessel of G.T. 416 ton class with relatively low height and long deckhouse, and investigated the vibrational characteristic of the fishing vessel with earlier structural feature. According to this investigation, the vibration, response of above vessel was confirmed of which main hull and deckhouse behave as one body. It is at the bottom of vibrational trouble which a accommodation part of the fishing vessel is raised, that is the local vibration for side wall, fore-aft wall and deck plate of deckhouse rather than thief fect of fore-aft vibration of deckhouse for above fishing vessel. and the resonance of main hull, deckhouse and driving system such as the main engine, propeller in exciting source is mainly brought up as the trouble.

• 한국지진공학회논문집
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• 제2권1호
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• pp.35-46
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• 1998

대부분의 손상도 추정법들을 부재의 손상을 해당부재의 평균적인 강성감소로 표현하였다. 본 연구에서는 보다 실제적인 손상도를 추정하기 위하여, 접합부의 손상을 도입하였다. 접합부의 모형화를 위하여 보의 양단에 회전스프링을 추가하였으며, 접합부 손상을 접합부 강성의 감소로 정의하였다. 접합부의 손상도를 계측된 모드벡터를 바탕으로하여, 신경망기법을 추정하였다. 효율적인 훈련패턴을 만들기 위하여 Latin Hypercube Sampling 기법을 도입하였으며, 국부영역에서의 손상도추정을 위하여 부구조법을 도입하였다. 제안된 기법의 효율성을 검증하기 위하여 10층 프레임구조물에 대한 수치해석결과를 이용하였다. 예제해석을 통하여 추정결과가 상당히 정확함을 확인하여, 실제 적용 가능한 방법임을 알수 있었다.

• International Journal of Computer Science & Network Security
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• 제22권2호
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• pp.123-130
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• 2022

During the past decades, detection of gear defects remains as a major problem, especially when the gears are subject to non-stationary phenomena. The idea of this paper is to mixture a multilevel wavelet transform with a fast EMD decomposition in order to early detect gear defects. The sensitivity of a kurtosis is used as an indicator of gears defect burn. When the gear is damaged, the appearance of a crack on the gear tooth disrupts the signal. This is due to the presence of periodic pulses. Nevertheless, the existence of background noise induced by the random excitation can have an impact on the values of these temporal indicators. The denoising of these signals by multilevel wavelet transform improves the sensitivity of these indicators and increases the reliability of the investigation. Finally, a defect diagnosis result can be obtained after the fast transformation of the EMD. The proposed approach consists in applying a multi-resolution wavelet analysis with variable decomposition levels related to the severity of gear faults, then a fast EMD is used to early detect faults. The proposed mixed methods are evaluated on vibratory signals from the test bench, CETIM. The obtained results have shown the occurrence of a teeth defect on gear on the 5th and 8th day. This result agrees with the report of the appraisal made on this gear system.

• Smart Structures and Systems
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• 제30권6호
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• pp.673-686
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• 2022

Deep learning algorithms for Structural Health Monitoring (SHM) have been extracting the interest of researchers and engineers. These algorithms commonly used loss functions and evaluation indices like the mean square error (MSE) which were not originally designed for SHM problems. An updated loss function which was specifically constructed for deep-learning-based structural damage detection problems has been proposed in this study. By tuning the coefficients of the loss function, the weights for damage localization and quantification can be adapted to the real situation and the deep learning network can avoid unnecessary iterations on damage localization and focus on the damage severity identification. To prove efficiency of the proposed method, structural damage detection using convolutional neural networks (CNNs) was conducted on a truss bridge model. Results showed that the validation curve with the updated loss function converged faster than the traditional MSE. Data augmentation was conducted to improve the anti-noise ability of the proposed method. For reducing the training time, the normalized modal strain energy change (NMSEC) was extracted, and the principal component analysis (PCA) was adopted for dimension reduction. The results showed that the training time was reduced by 90% and the damage identification accuracy could also have a slight increase. Furthermore, the effect of different modes and elements on the training dataset was also analyzed. The proposed method could greatly improve the performance for structural damage detection on both the training time and detection accuracy.

• Structural Engineering and Mechanics
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• 제86권6호
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• pp.715-730
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• 2023

Broad studies have addressed the issue of structural element damage identification, however, rubber bearing, as a key component of load transmission between the superstructure and substructure, is essential to the operational safety of a bridge, which should be paid more attention to its health condition. However, regarding the limitations of the traditional bearing damage detection methods as well as few studies have been conducted on this topic, in this paper, inspired by the model updating-based structural damage identification, a two-stage bearing damage identification method has been proposed. In the first stage, we deduce a novel bearing damage localization indicator, called element relative MSE, to accurately determine the bearing damage location. In the second one, the prior knowledge of bearing damage localization is combined with sailfish optimization (SFO) to perform the bearing damage estimation. In order to validate the feasibility, a numerical example of a 5-span continuous beam is introduced, also the noise robustness has been investigated. Meanwhile, the effectiveness and engineering applicability are further verified based on an experimental simply supported beam and actual engineering of the I-40 Bridge. The obtained results are good, which indicate that the proposed method is not only suitable for simple structures but also can accurately locate the bearing damage site and identify its severity for complex structure. To summarize, the proposed method provides a good guideline for the issue of bridge bearing detection, which could be used to reduce the difficulty of the traditional bearing failure detection approach, further saving labor costs and economic expenses.

• Smart Structures and Systems
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• 제31권1호
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• pp.57-68
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• 2023

Bridge hangers, such as those in suspension and cable-stayed bridges, suffer from cumulative fatigue damage caused by dynamic loads (e.g., cyclic traffic and wind loads) in their service condition. Thus, the identification of damage to hangers is important in preserving the service life of the bridge structure. This study develops a new method for condition assessment of bridge hangers. The tension force of the bridge and the damages in the element level can be identified using the Bayesian optimization method. To improve the number of observed data, the additional mass method is combined the Bayesian optimization method. Numerical studies are presented to verify the accuracy and efficiency of the proposed method. The influence of different acquisition functions, which include expected improvement (EI), probability-of-improvement (PI), lower confidence bound (LCB), and expected improvement per second (EIPC), on the identification of damage to the bridge hanger is studied. Results show that the errors identified by the EI acquisition function are smaller than those identified by the other acquisition functions. The identification of the damage to the bridge hanger with various types of boundary conditions and different levels of measurement noise are also studied. Results show that both the severity of the damage and the tension force can be identified via the proposed method, thereby verifying the robustness of the proposed method. Compared to the genetic algorithm (GA), particle swarm optimization (PSO), and nonlinear least-square method (NLS), the Bayesian optimization (BO) performs best in identifying the structural damage and tension force.

• 중환자간호학회지
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• 제16권2호
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• pp.1-14
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• 2023

Purpose : Sleep disturbances in patients in the intensive care unit (ICU) are related to health problems after discharge. Therefore, active prevention and management are required. Hence, identification of the factors that affect sleep in patients who are critically ill is necessary. Methods : The PubMed, Cochrane Library, CINAHL, EMBASE, and Web of Science databases were searched. Selection criteria were observational and experimental studies that assessed sleep as an outcome, included adult patients admitted to the ICU, and published between November 2015 and April 2022. Results : A total of 21,136 articles were identified through search engines and manual searches, and 42 articles were selected. From these, 22 influencing factors and 11 interventions were identified. Individual factors included disease severity, age, pain, delirium, comorbidities, alcohol consumption, sex, sleep disturbance before hospitalization, chronic obstructive pulmonary disease (COPD), cardiovascular disease, and high diastolic blood pressure (DBP), low hemoglobin (Hb), and low respiratory rate (RR). Environmental factors included light level, noise level, and temperature. Furthermore, treatment-related factors included use of sedatives, melatonin administration, sleep management guidelines, ventilator application, nursing treatment, and length of ICU stay. Regarding sleep interventions, massage, eye mask and earplugs, quiet time and multicomponent protocols, aromatherapy, acupressure, sounds of the sea, adaptive intervention, circulation lighting, and single occupation in a room were identified. Conclusion : Based on these results, we propose the development and application of various interventions to improve sleep quality in patients who are critically ill.

• 전기전자학회논문지
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• 제27권4호
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• pp.518-523
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• 2023

고정자 권선단락은 미세한 턴이 단락되어 급격히 고장이 심각해짐에 따라 ITSC의 진단이 중요시되고 있다. 그러나, 3상 유도전동기의 노이즈 및 손실등과 유사한 특징을 가짐에 따라 ITSC진단에 많은 어려움이 있다. 이를 효율적으로 진단하기 위해서 인공지능 기법으로 연구되고 있으나, 현장에서는 모델기반 기법이 두루 활용되고 있음에 따라 모델기반 기법에 대한 진단 성능개선 연구가 필요한 실정이다. 이에 본 논문에서는 회전하고 있는 자속에 변화를 무시하며, 전류 성분만을 이용할 수 있도록 Clarke변환 방법을 응용하여 진단방법을 제안하였다. 이에 30분간의 정상 및 ITSC 상태의 측정 결과, 정상상태를 ITSC 상태로 오인식하는 경우 0.2[%], ITSC상태를 정상상태로 오거부하는 경우 0.26[%]로 효율적인 진단 방법임을 실험을 통해 알 수 있었다.

• 한국의학물리학회지:의학물리
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• 제16권4호
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• pp.192-201
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• 2005

본 연구에서는 PET/CT 시스템에서 CT 영상을 이용한 감쇠 보정 시 조영제가 PET 영상에 미치는 영향을 관찰하기 위해 팬텀실험과 모의실험을 수행하였다. 다양한 농도로 희석한 조영제를 채운 플라스틱 병을 스티로폼을 이용하여 전신 팬텀 내에 고정시킨 후 투과 영상을 획득하였다 모의실험을 위해 인체 기관 중간을 가진 수학적 방출 맵과 투과 맵을 각각 생성하였다. 조영제의 비균일 증강, 조영제의 다양한 농도 및 분포 크기, 잡음 정도, 영상의 해상도, 재구성 알고리듬, 조영제의 저-감쇠, 그리고 각각 다른 시간상에 대한 조영제의 분포의 차이와 같은 다양한 인자들에 대하여 평가하였다. 팬텀실험으로부터 CT의 Hounsfield 값이 조영제의 농도 및 전압 값에 의존함을 확인할 수 있었다. 모의실험으로부터 조영제가 감쇠 보정한 PET 영상에서 인공산물을 생성하고 영상의 질을 떨어뜨리는 것을 관찰할 수 있었다. 조영제의 영향은 조영제의 농도 및 분포 크기, 잡음 정도, 영상의 해상도 등에 의해 영향을 받는 것으로 나타났다. 본 연구 결과들은 임상적 PET/CT 영상에서 조영제로 인해 발생할 수 있는 잠재적 문제를 충분히 이해하고 이를 고려해야 함을 보여 주었다.

• 대한후두음성언어의학회지
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• 제32권2호
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• pp.81-86
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• 2021

Background and Objectives Therapies have been reported to treat the glottal gap previously. However, these voice therapies showed the limits because many techniques focused only on one among breathing, resonance and phonation. In addition patients often have difficulties visiting hospital frequently. 'Gliding and humming' is vocal training technique that readjusts total vocal patterns such as breathing, resonance and phonation. This technique can be easily applied during short term sessions. The purpose of this study is to evaluate the efficiency of voice therapy with 'gliding and humming' for patients with glottic gap during short-term treatment sessions. Materials and Method Twenty-three patients with glottal gap were selected. Of all patients, 14 patients had sulcus vocalis and 12 patients had muscle tension dysphonia (MTD). Voice therapies were performed 1.9 sessions in average. GRBAS, jitter, shimmer, noise to harmonic ratio, semitone range, closed quotient_vowel and maximum phonation time were compared before and after the therapies. In addition, changes of glottal gap and MTD severity were evaluated. Results Statistically significant improvement was observed. MTD improvement was observed only among the patients with glottal gap improvement. Also sulcus vocalis group showed the statistically significant improvement. Conclusion 'Gliding and humming' was effective to the patients with glottic gap and sulcus vocalis. Also, among patients who have both glottic gap and MTD, the data suggests that voice therapy for glottic gap also makes improvement in MTD.