• 대한기계학회:학술대회논문집
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• 대한기계학회 2007년도 춘계학술대회A
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• pp.1590-1594
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• 2007

This paper describes a case study on dynamic characteristics analysis of a 5-axis multi-tasking machine tool of ram-head typed. Natural frequency and corresponding vibration modes of the machine tool structure were obtained by using both FEM modal analysis and an experimental modal test(impulse hammer test). Both the theoretical and experiment analysis results showed good agreement with each other. Finally, some discussion and review, from the view point of resonance vibration and/or mode coupled chatter, were made based on the analysis results.

• 한국소음진동공학회논문집
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• 제17권7호
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• pp.579-586
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• 2007

Analytical method to analyze the effect of tolerance on the modal characteristic of multi-body systems in dynamic equilibrium position is suggested in this paper. Monte-Carlo method is conventionally employed to perform the tolerance analysis. However, Monte-Carlo method spends too much time for analysis and has a greater or less accuracy depending on sample condition. To resolve these problems, an analytical method is suggested in this paper. Sensitivity equations for damped natural frequencies and the transfer function are derived at the dynamic equilibrium position. By employing the sensitivity information of mass, damping and stiffness matrices, the sensitivities of damped natural frequencies and the transfer function can be calculated.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제6권4호
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• pp.1090-1105
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• 2012

A multi-modal sensing M2M healthcare monitoring system for the continuous monitoring of patients under their natural physiological states or elderly persons with chronic diseases is summarized. The system is designed for homecare or the monitoring of the elderly who live in country side or small rest home without enough support from caregivers or doctors, instead of patient monitoring in big hospital environment. Further insights into the natural cause and progression of diseases are afforded by context-aware sensing, which includes the use of accelerometers to monitor patient activities, or by location-aware indoor tracking based on ultrasonic and RF sensing. Moreover, indoor location tracking provides information about the location of patients in their physical environment and helps the caregiver in the provision of appropriate support.

• 제어로봇시스템학회논문지
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• 제20권6호
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• pp.619-624
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• 2014

This paper introduces a robot-based learning system which is designed to teach multiplication to children. In addition to a small humanoid and a smart device delivering educational content, we employ a type of mixed-initiative operation which provides enhanced multi-modal cognition to the r-learning system through human intervention. To investigate major factors that influence people's intention to use the r-learning system and to see how the multi-modality affects the connections, we performed a user study based on TAM (Technology Acceptance Model). The results support the fact that the quality of the system and the natural interaction are key factors for the r-learning system to be used, and they also reveal very interesting implications related to the human behaviors.

• 디자인학연구
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• 제18권2호
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• pp.273-282
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• 2005

본 연구는 유비쿼터스 컴퓨팅 환경구축에 활용하기 위한 상황인지 모델과 이를 활용한 멀티모달 인터랙션 디자인 프레임웍을 제안하였다. 먼저 상황인지 모델개발을 위해 사용자의 인터랙션 상황을 파악하는 방법과 수집된 상황의 의미를 추론하여 사용자 요구에 맞는 멀티모달 인터랙션 서비스를 제공하는 방법을 연구하였다. 또한 상황인지 모델(Context cube)을 활용한 멀티모달 인터랙션 디자인 프레임웍을 제안하였으며, 이 프레임웍의 활용성을 검증하는 사례연구를 수행하고, 개인화된 유비쿼터스 서비스 도출 및 이 서비스의 산업화 가능성을 제시하였다. 상황인지는 사용자의 기본 행위(Basic Activity), 공간에서의 사용자 위치 및 공간내의 기기 및 환경 요소, 시간 요소와 사용자의 일상적인 스케줄 정보 요소에 의해 파악할 수 있으며, 이러한 요소들을 종합하여 공간적인 개념의 상황인지 모델(Context Cube)을 개발함으로써, 구체적인 공간 모델 내에서의 다양하고 개인화 된 유비쿼터스 서비스의 제안이 가능하였다. 또한, 실제적인 사용자 시나리오에 의한 사례연구를 통해 개념 모델을 구축하는 과정 및 각 과정에서 요구되는 정보의 유형을 검증하고, 상황인지 모델에서의 구성요소의 내용과 배열 등을 정의함으로써 개념모델의 완성도를 높였으며, 상황인지 모델에서 표현되는 사용자의 인터랙션 특징을 바탕으로 멀티모달 인터랙션 디자인의 접근방법을 개발함으로서 이를 디자인 프레임웍으로 구체화할 수 있었다.

• 방송공학회논문지
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• 제23권3호
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• pp.351-360
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• 2018

인간 감정 인식은 컴퓨터 비전 및 인공 지능 영역에서 지속적인 관심을 받는 연구 주제이다. 본 논문에서는 wild 환경에서 이미지, 얼굴 특징점 및 음성신호로 구성된 multi-modal 신호를 기반으로 여러 신경망을 통해 인간의 감정을 분류하는 방법을 제안한다. 제안 방법은 다음과 같은 특징을 갖는다. 첫째, multi task learning과 비디오의 시공간 특성을 이용한 준 감독 학습을 사용함으로써 영상 기반 네트워크의 학습 성능을 크게 향상시켰다. 둘째, 얼굴의 1 차원 랜드 마크 정보를 2 차원 영상으로 변환하는 모델을 새로 제안하였고, 이를 바탕으로 한 CNN-LSTM 네트워크를 제안하여 감정 인식을 향상시켰다. 셋째, 특정 감정에 오디오 신호가 매우 효과적이라는 관측을 기반으로 특정 감정에 robust한 오디오 심층 학습 메커니즘을 제안한다. 마지막으로 소위 적응적 감정 융합 (emotion adaptive fusion)을 적용하여 여러 네트워크의 시너지 효과를 극대화한다. 제안 네트워크는 기존의 지도 학습과 반 지도학습 네트워크를 적절히 융합하여 감정 분류 성능을 향상시켰다. EmotiW2017 대회에서 주어진 테스트 셋에 대한 5번째 시도에서, 제안 방법은 57.12 %의 분류 정확도를 달성하였다.

• Structural Engineering and Mechanics
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• 제25권1호
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• pp.53-73
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• 2007

In this study, an effective load increment method for multi modal adaptive non-linear static (pushover) analysis (NSA) for building type structures is presented. In the method, lumped plastisicity approach is adopted and geometrical non-linearties (second-order effects) are included. Non-linear yield conditions of column elements and geometrical non-linearity effects between successive plastic sections are linearized. Thus, load increment needed for formation of plastic sections can be determined directly (without applying iteration or step-by-step techniques) by using linearized yield conditions. After formation of each plastic section, the higher mode effects are considered by utilizing the essentials of traditional response spectrum analysis at linearized regions between plastic sections. Changing dynamic properties due to plastification in the system are used on the calculation of modal lateral loads. Thus, the effects of stiffness changes and local mechanism at the system on lateral load distribution are included. By using the proposed method, solution can be obtained effectively for multi-mode whereby the properties change due to plastifications in the system. In the study, a new procedure for determination of modal lateral loads is also proposed. In order to evaluate the proposed method, a 20 story RC frame building is analyzed and compared with Non-linear Dynamic Analysis (NDA) results and FEMA 356 Non-linear Static Analysis (NSA) procedures using fixed loads distributions (first mode, SRSS and uniform distribution) in terms of different parameters. Second-order effects on response quantities and periods are also investigated. When the NDA results are taken as reference, it is seen that proposed method yield generally better results than all FEMA 356 procedures for all investigated response quantities.

• Design & Manufacturing
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• 제15권1호
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• pp.66-71
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• 2021

In this study, die turning injection(DTI) mold design for manufacturing reservoir fluid tanks used for cooling in-vehicle batteries, inverters, and motors was conducted based on multi-field CAE. Part design, performance evaluation, and mold design of the reservoir fluid tank was performed. The frequency response characteristics through modal and harmonic response analysis to satisfy the automotive performance test items for the designed part were examined. Analysis of re-melting characteristics and structural analysis of the driving part for designing the rotating die of the DTI mold were performed. Part design was possible when the natural frequency performance value of 32Hz or higher was satisfied through finite element analysis, and the temperature distribution and deformation characteristics of the part after injection molding were found through the first injection molding analysis. In addition, it can be seen that the temperature change of the primary part greatly influences the re-melting characteristics during the secondary injection. The minimum force for driving the turning die of the designed mold was calculated through structural analysis. Hydraulic system design was possible. Finally, a precise and efficient DTI mold design for the reservoir fluid tank was possible through presented multi-field CAE process.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제18권3호
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• pp.670-684
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• 2024

3D Cross-Modal Retrieval (3DCMR) is a task that retrieves 3D objects regardless of modalities, such as images, meshes, and point clouds. One of the most prominent methods used for 3DCMR is the Cross-Modal Center Loss Function (CLF) which applies the conventional center loss strategy for 3D cross-modal search and retrieval. Since CLF is based on center loss, the center features in CLF are also susceptible to subtle changes in hyperparameters and external inferences. For instance, performance degradation is observed when the batch size is too small. Furthermore, the Mean Squared Error (MSE) used in CLF is unable to adapt to changes in batch size and is vulnerable to data variations that occur during actual inference due to the use of simple Euclidean distance between multi-modal features. To address the problems that arise from small batch training, we propose a Noisy Center Loss (NCL) method to estimate the optimal center features. In addition, we apply the simple Siamese representation learning method (SimSiam) during optimal center feature estimation to compare projected features, making the proposed method robust to changes in batch size and variations in data. As a result, the proposed approach demonstrates improved performance in ModelNet40 dataset compared to the conventional methods.

• Wind and Structures
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• 제37권6호
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• pp.445-460
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• 2023

Accurate estimation of modal parameters (i.e., natural frequency, damping ratio) of tall buildings is of great importance to their structural design, structural health monitoring, vibration control, and state assessment. Based on the combination of variational mode decomposition, smoothed discrete energy separation algorithm-1, and Half-cycle energy operator (VMD-SH), this paper presents a method for structural modal parameter estimation. The variational mode decomposition is proved to be effective and reliable for decomposing the mixed-signal with low frequencies and damping ratios, and the validity of both smoothed discrete energy separation algorithm-1 and Half-cycle energy operator in the modal identification of a single modal system is verified. By incorporating these techniques, the VMD-SH method is able to accurately identify and extract the various modes present in a signal, providing improved insights into its underlying structure and behavior. Subsequently, a numerical study of a four-story frame structure is conducted using the Newmark-β method, and it is found that the relative errors of natural frequency and damping ratio estimated by the presented method are much smaller than those by traditional methods, validating the effectiveness and accuracy of the combined method for the modal identification of the multi-modal system. Furthermore, the presented method is employed to estimate modal parameters of a full-scale tall building utilizing acceleration responses. The identified results verify the applicability and accuracy of the presented VMD-SH method in field measurements. The study demonstrates the effectiveness and robustness of the proposed VMD-SH method in accurately estimating modal parameters of tall buildings from acceleration response data.