• Title/Summary/Keyword: Domain Model

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Practical Numerical Model for Nonlinear Analyses of Wave Propagation and Soil-Structure Interaction in Infinite Poroelastic Media (무한 다공성 매질에서의 비선형 파전파 해석과 지반-구조물 상호작용 해석을 위한 실용적 수치 모형)

  • Lee, Jin Ho
    • Journal of the Earthquake Engineering Society of Korea
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    • v.22 no.7
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    • pp.379-390
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    • 2018
  • In this study, a numerical approach based on mid-point integrated finite elements and a viscous boundary is proposed for time-domain wave-propagation analyses in infinite poroelastic media. The proposed approach is accurate, efficient, and easy to implement in time-domain analyses. In the approach, an infinite domain is truncated at some distance. The truncated domain is represented by mid-point integrated finite elements with real element-lengths and a viscous boundary is attached to the end of the domain. Given that the dynamic behaviors of the proposed model can be expressed in terms of mass, damping, and stiffness matrices only, it can be implemented easily in the displacement-based finite-element formulation. No convolutional operations are required for time-domain calculations because the coefficient matrices are constant. The proposed numerical approach is applied to typical wave-propagation and soil-structure interaction problems. The model is verified to produce accurate and stable results. It is demonstrated that the numerical approach can be applied successfully to nonlinear soil-structure interaction problems.

Multi-channel Long Short-Term Memory with Domain Knowledge for Context Awareness and User Intention

  • Cho, Dan-Bi;Lee, Hyun-Young;Kang, Seung-Shik
    • Journal of Information Processing Systems
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    • v.17 no.5
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    • pp.867-878
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    • 2021
  • In context awareness and user intention tasks, dataset construction is expensive because specific domain data are required. Although pretraining with a large corpus can effectively resolve the issue of lack of data, it ignores domain knowledge. Herein, we concentrate on data domain knowledge while addressing data scarcity and accordingly propose a multi-channel long short-term memory (LSTM). Because multi-channel LSTM integrates pretrained vectors such as task and general knowledge, it effectively prevents catastrophic forgetting between vectors of task and general knowledge to represent the context as a set of features. To evaluate the proposed model with reference to the baseline model, which is a single-channel LSTM, we performed two tasks: voice phishing with context awareness and movie review sentiment classification. The results verified that multi-channel LSTM outperforms single-channel LSTM in both tasks. We further experimented on different multi-channel LSTMs depending on the domain and data size of general knowledge in the model and confirmed that the effect of multi-channel LSTM integrating the two types of knowledge from downstream task data and raw data to overcome the lack of data.

An Efficient Comparing and Updating Method of Rights Management Information for Integrated Public Domain Image Search Engine

  • Kim, Il-Hwan;Hong, Deok-Gi;Kim, Jae-Keun;Kim, Young-Mo;Kim, Seok-Yoon
    • Journal of the Korea Society of Computer and Information
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    • v.24 no.1
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    • pp.57-65
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    • 2019
  • In this paper, we propose a Rights Management Information(RMI) expression systems for individual sites are integrated and the performance evaluation is performed to find out an efficient comparing and updating method of RMI through various image feature point search techniques. In addition, we proposed a weighted scoring model for both public domain sites and posts in order to use the most latest RMI based on reliable data. To solve problem that most public domain sites are exposed to copyright infringement by providing inconsistent RMI(Rights Management Information) expression system and non-up-to-date RMI information. The weighted scoring model proposed in this paper makes it possible to use the latest RMI for duplicated images that have been verified through the performance evaluation experiments of SIFT and CNN techniques and to improve the accuracy when applied to search engines. In addition, there is an advantage in providing users with accurate original public domain images and their RMI from the search engine even when some modified public domain images are searched by users.

Exploring the feasibility of fine-tuning large-scale speech recognition models for domain-specific applications: A case study on Whisper model and KsponSpeech dataset

  • Jungwon Chang;Hosung Nam
    • Phonetics and Speech Sciences
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    • v.15 no.3
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    • pp.83-88
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    • 2023
  • This study investigates the fine-tuning of large-scale Automatic Speech Recognition (ASR) models, specifically OpenAI's Whisper model, for domain-specific applications using the KsponSpeech dataset. The primary research questions address the effectiveness of targeted lexical item emphasis during fine-tuning, its impact on domain-specific performance, and whether the fine-tuned model can maintain generalization capabilities across different languages and environments. Experiments were conducted using two fine-tuning datasets: Set A, a small subset emphasizing specific lexical items, and Set B, consisting of the entire KsponSpeech dataset. Results showed that fine-tuning with targeted lexical items increased recognition accuracy and improved domain-specific performance, with generalization capabilities maintained when fine-tuned with a smaller dataset. For noisier environments, a trade-off between specificity and generalization capabilities was observed. This study highlights the potential of fine-tuning using minimal domain-specific data to achieve satisfactory results, emphasizing the importance of balancing specialization and generalization for ASR models. Future research could explore different fine-tuning strategies and novel technologies such as prompting to further enhance large-scale ASR models' domain-specific performance.

Stress Induced-Domain Formation Mechanism in LiNbO3 Single Crystals (LiNbO3단결정에서 내부응력에 의한 Domain형성기구)

  • 최종건;오근호
    • Journal of the Korean Ceramic Society
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    • v.26 no.1
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    • pp.37-42
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    • 1989
  • Periodic layered domain structures in doped LiNbO3 crystals grown by Czochralski method were obtained by thermal fluctuation and crystal rotation with inhomogeneous radial temprature distribution. The stressinduced domain formation mechanism model was suggested and discussed.

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Utilizing a Model Registry to Secure Interoperability Among Urban Domain Information Models (도메인 정보 모델 간의 상호운용성 확보를 위한 모델 레지스트리 활용방안)

  • Won Wook Choi;Sang Ki Hong
    • The Transactions of the Korea Information Processing Society
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    • v.13 no.2
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    • pp.18-25
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    • 2024
  • This study proposes the utilization of a model registry to secure interoperability among urban domain information models. It reviews urban information and data sharing along with related standards and standardization activities. By analyzing registry use cases in the context of Spatial Data Infrastructure (SDI), it presents the concept of a model registry for facilitating information sharing and exchange among urban domain information models. An use case linking urban domain information models using the model registry is developed with a prerequisite of seamless implementation of smart city services. The paper discusses technical requirements and outlines technology implementation and validation through prototype development, highlighting them as future research tasks.

Hybrid Parallelization for High Performance of CFD_NIMR Model (기상 모델 CFD_NIMR의 최적 성능을 위한 혼합형 병렬 프로그램 구현)

  • Kim, Min-Wook;Choi, Young-Jean;Kim, Young-Tae
    • Atmosphere
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    • v.22 no.1
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    • pp.109-115
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    • 2012
  • We parallelized the CFD_NIMR model, which is a numerical meteorological model, for best performance on both of distributed and shared memory parallel computers. This hybrid parallelization uses MPI (Message Passing Interface) to apply horizontal 2-dimensional sub-domain out of the 3-dimensional computing domain for distributed memory system, as well as uses OpenMP (Open Multi-Processing) to apply vertical 1-dimensional sub-domain for utilizing advantage of shared memory structure. We validated the parallel model with the original sequential model, and the parallel CFD_NIMR model shows efficient speedup on the distributed and shared memory system.

Tuning Algorithm for PID Controller Using Model Reduction in frequency Domain (주파수 영역에서의 모델 축소를 이용한 PID 제어기의 동조 알고리즘)

  • Cho, Joon-Ho;Choi, Jung-Nae;Hwang, Hyung-Soo
    • Proceedings of the KIEE Conference
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    • 2001.07d
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    • pp.2114-2116
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    • 2001
  • Model reduction from high order systems to low order systems in frequency domain is considered four point (${\angle}$G(jw)=0, - ${\pi}/2$, ${\pi}$, and -3${\pi}$/2) instead of two point (${\angle}$G(jw) = - ${\pi}$/2,- ${\pi}$) of existing method in Nyquist curve. The Performances of reduced order model by proposed approach is similar to original model. In this paper, we proposed a new tuning algorithm for PID controller using model reduction in frequency domain. Simulations for some examples with varies dynamic characteristics are provided to show the effectiveness of the proposed tuning algorithm for PID controller using model reduction.

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A Phase-Domain Equivalent Representation for Electromagnetic Transients Studies (전력계통 과도현상 해석을 위한 상영역에서의 등가축약 기법)

  • Jung, B.T.;Kim, S.H.;Heo, S.I.;Ahn, B.S.;Hong, J.H.
    • Proceedings of the KIEE Conference
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    • 1996.07b
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    • pp.731-733
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    • 1996
  • In this paper, a new time-domain reduction method for unbalanced 3 phase power systems will be represented. The impulse response of the system is used to identify a discrete-time equivalent filter model. The model is formulated directly in the phase domain. Each phase has a self-mode equivalent model and two mutual-mode equivalent models. The equivalent model is determined by the transfer function identification technique based on the Prony analysis. The model is implemented in EMTDC and tested with an unbalanced 3 phase network. The result of test showed that the equivalent model is accurate.

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A micromechanics-based time-domain viscoelastic constitutive model for particulate composites: Theory and experimental validation

  • You, Hangil;Lim, Hyoung Jun;Yun, Gun Jin
    • Advances in aircraft and spacecraft science
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    • v.9 no.3
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    • pp.217-242
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    • 2022
  • This paper proposes a novel time-domain homogenization model combining the viscoelastic constitutive law with Eshelby's inclusion theory-based micromechanics model to predict the mechanical behavior of the particle reinforced composite material. The proposed model is intuitive and straightforward capable of predicting composites' viscoelastic behavior in the time domain. The isotropization technique for non-uniform stress-strain fields and incremental Mori-Tanaka schemes for high volume fraction are adopted in this study. Effects of the imperfectly bonded interphase layer on the viscoelastic behavior on the dynamic mechanical behavior are also investigated. The proposed model is verified by the direct numerical simulation and DMA (dynamic mechanical analysis) experimental results. The proposed model is useful for multiscale analysis of viscoelastic composite materials, and it can also be extended to predict the nonlinear viscoelastic response of composite materials.