• Smart Structures and Systems
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• v.21 no.3
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• pp.349-358
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• 2018

This paper investigates the free vibration analysis of double-beam system coupled by a two-degree-of-freedom mass-spring system. In order to generalize the model, the main beams are assumed to be elastically restrained against translation and rotation at one end and free at the other. Furthermore, the mass-spring system is elastically connected to the beams at adjustable positions by means of four translational and rotational springs. The governing differential equations of the beams and the mass-spring system are derived and analytically solved by using the Fourier transform method. Moreover, as a second way, a finite element solution is derived. The frequency parameters and mode shapes of some diverse cases are obtained using both methods. Comparison of obtained results by two methods shows the accuracy of both solutions. The influence of system parameters on the free vibration response of the studied mechanical system is examined.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.26 no.6
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• pp.611-616
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• 2008

When extracting geo-referenced 3D data from cameras mounted on Mobile Mapping Systems, one of important properties for accuracy of extracted data is the alignment of the relative translation(lever-arm) and rotation(bore-sight) between the coordinate systems of Inertial Measurement Unit(IMU)/Ground Positioning System(GPS) and cameras. Since the conventional method calculates absolute camera orientation using ground control points (GCP), the alignment is determined in one Coordinated System (GPS Coordinated System). It basically require GCP. We proposed a mathematical model for the alignment using the initially uncoupled data of cameras and IMU/GPS without GCPs.

• Proceedings of the Korea Information Processing Society Conference
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• 2019.10a
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• pp.598-601
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• 2019

최근 딥러닝과 신경망 기술을 바탕으로 한 다양한 번역 시스템이 상용화되고 있다. 그러나 문맥을 고려해야하는 경우나 의료, 법학 등 전문적인 지식을 요구하는 경우, 기존의 번역 시스템으로는 원문 작성자가 의도한 대로 자연스러운 번역 결과물을 얻기 어려운 문제점이 있다. 이로 인해 전문적인 지식을 요구하는 문서는 전문 번역 기관에 의뢰하여 번역이 이루어지고 있으며 소비자의 입장에서는 업체로부터 받은 번역물을 평가 과정 없이 사용할 수밖에 없는 상황이다. 따라서 본 논문에서는 사람이 직접 번역한 결과물을 사용자가 가진 번역 신뢰 점수를 반영하여 평가함으로써 양질의 결과물을 도출하고 번역 활동 기여도에 따라 암호화폐로 보상금을 지급하는 블록체인 기반 보상형 공동 번역 모델을 제안한다. 다수의 번역 평가자들로부터 높은 점수를 받은 우수한 번역 결과물을 도출하고, 번역글 평가에 사용되는 사용자별 신뢰도 점수를 블록체인에 저장하여 조작을 방지함으로써 믿을 수 있는 번역 생태계를 조성할 것으로 기대한다.

• Bulletin of the Korean Chemical Society
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• v.13 no.1
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• pp.11-17
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• 1992

Vibration-to-vibration energy transfer probabilities for $HF(v=n)+H_2(v=0){\to}HF(v=n-1)+H_2(v=1)$ and $DF(v=n)+D_2(v=0){\to}DF(v=n-1)+D_2(v=1)$ including both the vibration-to-vibration and translation (V-V, T) and vibration-to-vibration and rotation (V-V, R) energy transfer paths have been calculated semiclassically using a simplified collision model and Morse-type intermolecular interaction potential. The calculated results are in reasonably good agreement with those obtained by experimental studies. They also show that the transition processes for $HF(v=1-3)+H_2(v=0){\to}HF(v=0-2)+H_2(v=1)$ and $DF(v=1,\;4)+D_2(v=0){\to}DF(v=0,\;3)+D_2(v=1)$ are strongly dependent on the V-V, T path at low temperature but occur predominantly via the V-V, R path with rising temperature. The vibration-to-vibration energy transfer for $HF(v=4)+H_2(v=0){\to}HF(v=3)+H_2(v=1)$ and $DF(v=2-3)+D_2(v=0){\to}DF(v=1-2)+D_2(v=1)$ occur predominantly via V-V, R path and V-V, T path through whole temperatures, respectively.

• Journal of Korea Multimedia Society
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• v.21 no.11
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• pp.1305-1316
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• 2018

Graphical user interface(GUI) has a very important role to interact with software users. However, designing and coding of GUI are tedious and pain taking processes. In many studies, the researchers are trying to convert GUI elements or widgets to code or describe formally their structures by help of domain knowledge of stochastic methods. In this paper, we propose the GUI elements detection approach based on object detection strategy using deep neural networks(DNN). Object detection with DNN is the approach that integrates localization and classification techniques. From the experimental result, if we selected the appropriate object detection model, the results can be used for automatic code generation from the sketch or capture images. The successful GUI elements detection can describe the objects as hierarchical structures of elements and transform their information to appropriate code by object description translator that will be studied at future.

• BMB Reports
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• v.52 no.5
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• pp.304-311
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• 2019

The cytoplasmic FMR1-interacting protein family (CYFIP1 and CYFIP2) are evolutionarily conserved proteins originally identified as binding partners of the fragile X mental retardation protein (FMRP), a messenger RNA (mRNA)-binding protein whose loss causes the fragile X syndrome. Moreover, CYFIP is a key component of the heteropentameric WAVE regulatory complex (WRC), a critical regulator of neuronal actin dynamics. Therefore, CYFIP may play key roles in regulating both mRNA translation and actin polymerization, which are critically involved in proper neuronal development and function. Nevertheless, compared to CYFIP1, neuronal function and dysfunction of CYFIP2 remain largely unknown, possibly due to the relatively less well established association between CYFIP2 and brain disorders. Despite high amino acid sequence homology between CYFIP1 and CYFIP2, several in vitro and animal model studies have suggested that CYFIP2 has some unique neuronal functions distinct from those of CYFIP1. Furthermore, recent whole-exome sequencing studies identified de novo hot spot variants of CYFIP2 in patients with early infantile epileptic encephalopathy (EIEE), clearly implicating CYFIP2 dysfunction in neurological disorders. In this review, we highlight these recent investigations into the neuronal function and dysfunction of CYFIP2, and also discuss several key questions remaining about this intriguing neuronal protein.

• International Journal of Internet, Broadcasting and Communication
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• v.14 no.4
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• pp.121-131
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• 2022

We look at the initial stage of Meta (previous Facebook)'s new metaverse platform and investigate its platform design in pre-launch and ignition life stage. From the Rocket Model (RM)'s theoretical logic, the results reveal that Meta firstly focuses on investing in key content developers by acquiring virtual reality (VR), video, music content firms and offering production support platform of the augmented reality (AR) content, 'Spark AR' last three years (2019~2021) for attracting high-potential developers and users. In terms of three matching criteria, Meta develops an Artificial Intelligence (AI) powered translation software, partners with Microsoft (MS) for cloud computing and AI, and develops an AI platform for realistic avatar, MyoSuite. In 'connect' function, Meta curates the game concept submitted by game developers, welcomes other game and SNS based metaverse apps, and expands Horizon Worlds (HW) on VR devices to PCs and mobile devices. In 'transact' function, Meta offers 'HW Creator Funding' program for metaverse, launches the first commercialized Meta Avatar Store on Meta's conventional SNS and Messaging apps by inviting all fashion creators to design and sell clothing in this store. Mata also launches an initial test of non-fungible token (NFT) display on Instagram and expands it to Facebook in the US. Lastly, regarding optimization, especially in the face of recent data privacy issues that have adversely affected corporate key performance indicators (KPIs), Meta assures not to collect any new data and to make its privacy policy easier to understand and update its terms of service more user friendly.

• Annual Conference on Human and Language Technology
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• 2023.10a
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• pp.80-85
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• 2023

기계 번역에서 품질 검증은 정답 문장 없이 기계 번역 시스템에서 생성된 번역의 품질을 자동으로 추정하는 것을 목표로 한다. 일반적으로 이 작업은 상용화된 기계 번역 시스템에서 후처리 모듈 역할을 하여 사용자에게 잠재적인 번역 오류를 경고한다. 품질 검증의 하위 작업인 치명적인 오류 탐지는 번역의 오류 중에서도 정치, 경제, 사회적으로 문제를 일으킬 수 있을 만큼 심각한 오류를 찾는 것을 목표로 한다. 본 논문은 치명적인 오류의 유무를 분류하는 것을 넘어 문장에서 치명적인 오류가 존재하는 부분을 제시하기 위한 새로운 데이터셋과 모델을 제안한다. 이 데이터셋은 거대 언어 모델을 활용하는 구축 방식을 채택하여 오류의 구체적인 범위를 표시한다. 또한, 우리는 우리의 데이터를 효과적으로 활용할 수 있는 다중 작업 학습 모델을 제시하여 오류 범위 탐지에서 뛰어난 성능을 입증한다. 추가적으로 언어 모델을 활용하여 번역 오류를 삽입하는 데이터 증강 방법을 통해 보다 향상된 성능을 제시한다. 우리의 연구는 기계 번역의 품질을 향상시키고 치명적인 오류를 줄이는 실질적인 해결책을 제공할 것이다.

• The Journal of Korean Medical History
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• v.36 no.2
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• pp.89-98
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• 2023

Objectives: This study applied Havruta, a learner-centered educational method, and verified its effectiveness, to break from the existing mechanical memorization methods of scripture reading classes, which are basic subjects of East Asian medicine at East Asian medicine universities. Method: To this end, D University's scripture reading course was redesigned according to Havruta's teaching model, and Havruta classes were conducted according to the instructional design. Results: As a result of the class, students' Chinese translation ability improved, and they were able to concentrate on class (M=4.24). Through class, they acquired knowledge in the field (M=4.21) and their ability to communicate with others improved (M=4.21). M=4.25), it can be inferred and interpreted that the learner is engaged. Conclusion: The results of this study are examples of applying various teaching and learning methods required in the East Asian medicine evaluation and certification of East Asian medicine at East Asian medicine universities, and can be used as practical basic data that can be applied not only to scripture reading subjects but also to other subjects.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.45 no.6
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• pp.27-37
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• 2008

Applications of 3D data increase with advancement of multimedia technique and contents, and it is necessary to manage and to retrieve for 3D data efficiently. In this paper, we propose a new method using the sliced shape which extracts efficiently a feature description for shape-based retrieval of 3D models. Since the feature descriptor of 3D model should be invariant to translation, rotation and scale for its model, normalization of models requires for 3D model retrieval system. This paper uses principal component analysis(PCA) method in order to normalize all the models. The proposed algorithm finds a direction of each axis by the PCA and creates orthogonal n planes in each axis. These planes are orthogonalized with each axis, and are used to extract sliced shape image. Sliced shape image is the 2D plane created by intersecting at between 3D model and these planes. The proposed feature descriptor is a distribution of Euclidean distances from center point of sliced shape image to its outline. A performed evaluation is used for average of the normalize modified retrieval rank(ANMRR) with a standard evaluation from MPEG-7. In our experimental results, we demonstrate that the proposed method is an efficient 3D model retrieval.