• Journal of the Korean Society of Safety
• /
• v.12 no.3
• /
• pp.178-184
• /
• 1997

Many mathematical techniques have been developed to determine the muscle forces and force distribution in biomechanical human model, because it is so important to understand internal forces resisting external loading. However, a three-dimensional mathematical model of wrist joint, which is essential to develop solid modeling and artificial wrist joint, has not been well developed. This study proposed to define three-dimensional mathematical model of distal radius and ulna of the human wrist and to develop a detailed two-dimensional finite element through comparisons to existing analytical models and experimental tests. This mathematical model were accurately recreated, allowing the internal tendon force as well as force transmission and distribution through the distal radios and ulna during dynamic loadings. The results found in this study indicate and support the findings of other investigator that cyclic loading condition results in higher compression force on distal radius and ulna and may be source of wrist disorder.

• The Journal of Society for e-Business Studies
• /
• v.21 no.4
• /
• pp.1-14
• /
• 2016

Semantic search is known as a series of activities and techniques to improve the search accuracy by clearly understanding users' search intent without big cognitive efforts. Usually, semantic search engines requires ontology and semantic metadata to analyze user queries. However, building a particular ontology and semantic metadata intended for large amounts of data is a very time-consuming and costly task. This is why commercialization practices of semantic search are insufficient. In order to resolve this problem, we propose a novel semantic search method which takes advantage of our previous semantic tensor space model. Since each term is represented as the 2nd-order 'document-by-concept' tensor (i.e., matrix), and each concept as the 2nd-order 'document-by-term' tensor in the model, our proposed semantic search method does not require to build ontology. Nevertheless, through extensive experiments using the OHSUMED document collection and SCOPUS journal abstract data, we show that our proposed method outperforms the vector space model-based search method.

• Korean Journal of Cognitive Science
• /
• v.19 no.2
• /
• pp.107-123
• /
• 2008

The existing studies of a dialogue system can be classified into two major parts. One is a study for a practical system, and the other is a study to understand a principal of dialogue phenomena. The former focuses on robustness in real environment for dialogue systems. However, it cannot guarantee its performance in complicated dialogue environment. The latter has studied as the plan-based model typically. It has strong points that it can reflect complex dialogue phenomena and can infer user's intention in various situations. However, an initial design of this model is so complicated, and it is difficult for this model to be extended to the interaction model for response generation in a practical dialogue system. This paper proposes a new dialogue modeling using plan recognition and a discourse stark to effectively generate response in a practical dialogue system.

• Archives of design research
• /
• v.14
• /
• pp.87-106
• /
• 1996

Recent rapid development of electronic technologies and semiconductors has made it possible to perform diverse intelligent functions even in simple products. This technological sophistication, in turn, made it difficult to get required information on the usage of products by just its shape. Under these new circumstances, User-interface design became more important. However existing studies were mainly done with the emphasis of software development and focusing on the evaluation-stage after development of alternatives. This study sets the objective for developing modeling technique which can be applied to product design and the stage of concept development. At first the role of modeling was discussed to understand the nature of modeling. Then the existing techniques of modeling were reviewed for identifying advantages and limits. The review of existing modeling techniques revealed general objectives which new modeling techniques should fulfill. Based on objectives new modeling techniques were proposed. Following this new techniques, actual case of modeling a existing product were demonstrated to evaluate the validity of new technique and show the actual application. Finally findings were summarized and the limits of the study were identified.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.19 no.6
• /
• pp.865-871
• /
• 2009

In this paper, a novel feedback linearization is proposed for discrete-time nonlinear systems described by discrete-time T-S fuzzy models. The local linear models of a T-S fuzzy model are transformed to a controllable canonical form respectively, and their T-S fuzzy combination results in a feedback linearizable Tagaki-Sugeno fuzzy model. Based on this model, a nonlinear state feedback linearizing input is determined. Nonlinear state transformation is inferred from the linear state transformations for the controllable canonical forms. The proposed method of this paper is more intuitive and easier to understand mathematically compared to the well-known feedback linearization technique which requires a profound mathematical background. The feedback linearizable condition of this paper is also weakened compared to the conventional feedback linearization. This means that larger class of nonlinear systems is linearizable compared to the case of classical linearization.

• Proceedings of the Korea Water Resources Association Conference
• /
• 2019.05a
• /
• pp.119-119
• /
• 2019

최근 기후변화와 이상기후의 영향으로 국지성 호우 및 가뭄, 홍수, 태풍 등 재해 발생 규모가 커지고 그 빈도 또한 많아지고 있다. 이러한 자연재해 및 이상현상에 대한 피해를 예방하고 빠르게 대처하기 위해서는 정확한 강우량 추정 및 강우의 시간적 예측이 필요하다. 이러한 강우의 불확실성을 해결하기 위해서 기상청 등에서는 단일 수치예보가 가지는 결정론적인 예측의 한계를 보완한 초기조건, 물리과정, 경계조건 등이 다른 여러 개의 모델을 수행하여, 확률적으로 미래를 예측하는 앙상블 예측 시스템을 예보기술에 응용하고 있으며 기존 수치모델의 정보와 예보 불확실성에 대한 정보를 동시에 제공하고 있다. 그러나 다양한 자연조건에 대한 불완전한 물리적 이해와 연산 능력 등의 한계로 높은 불확실성이 내포되어 있으므로 불확실성을 최소화하기 위한 편의보정이 수행될 필요가 있다. 강우분석의 적용 이전에 해당 자료의 타당성과 신뢰도의 분석이 필요하다. 본 연구에서는 LENS(Local ENsemble prediction System) 예측값과 시강우 관측값을 단기예측모델에 맞추어 3시간 누적하여 비교하였다. 비교 기간은 호우가 집중되는 2016년 10월로 선정하였으며 대상지역은 울산중구로 선정하였다. LENS를 대상 지역의 관측소 지점값과 행정구역 면적값을 따로 추출한 후, 불확실성을 최소화하기 위해 활용되고 있는 CF 기법과 QM 기법을 이용하여 LENS 모델을 재가공하고 이에 따른 편의보정 기법에 따른 LENS 모델을 과거의 실제강우 관측값과의 비교분석을 이용해 적용성을 검토 및 평가하였다.

• Knowledge Management Research
• /
• v.22 no.3
• /
• pp.91-106
• /
• 2021

With the recent rapid development of deep learning technology, the demand for analyzing huge text documents in the national R&D field from various perspectives is rapidly increasing. In particular, interest in the application of a BERT(Bidirectional Encoder Representations from Transformers) language model that has pre-trained a large corpus is growing. However, the terminology used frequently in highly specialized fields such as national R&D are often not sufficiently learned in basic BERT. This is pointed out as a limitation of understanding documents in specialized fields through BERT. Therefore, this study proposes a method to build an R&D KoBERT language model that transfers national R&D field knowledge to basic BERT using further pre-training. In addition, in order to evaluate the performance of the proposed model, we performed classification analysis on about 116,000 R&D reports in the health care and information and communication fields. Experimental results showed that our proposed model showed higher performance in terms of accuracy compared to the pure KoBERT model.

• Journal of the Korea Society of Computer and Information
• /
• v.27 no.8
• /
• pp.41-47
• /
• 2022

In this paper, we propose how to implement text summaries for colloquial data that are not clearly organized. For this study, SAMSum data, which is colloquial data, was used, and the BERTSumExtAbs model proposed in the previous study of the automatic summary model was applied. More than 70% of the SAMSum dataset consists of conversations between two people, and the remaining 30% consists of conversations between three or more people. As a result, by applying the automatic text summarization model to colloquial data, a result of 42.43 or higher was derived in the ROUGE Score R-1. In addition, a high score of 45.81 was derived by fine-tuning the BERTSum model, which was previously proposed as a text summarization model. Through this study, the performance of colloquial generation summary has been proven, and it is hoped that the computer will understand human natural language as it is and be used as basic data to solve various tasks.

• Journal of the Korea Society of Computer and Information
• /
• v.28 no.12
• /
• pp.67-77
• /
• 2023

This study represents an innovative research conducted in the smart farm environment, developing a deep learning-based disease and pest detection model and applying it to the Intelligent Internet of Things (IoT) platform to explore new possibilities in the implementation of digital agricultural environments. The core of the research was the integration of the latest ImageNet models such as Pseudo-Labeling, RegNet, EfficientNet, and preprocessing methods to detect various diseases and pests in complex agricultural environments with high accuracy. To this end, ensemble learning techniques were applied to maximize the accuracy and stability of the model, and the model was evaluated using various performance indicators such as mean Average Precision (mAP), precision, recall, accuracy, and box loss. Additionally, the SHAP framework was utilized to gain a deeper understanding of the model's prediction criteria, making the decision-making process more transparent. This analysis provided significant insights into how the model considers various variables to detect diseases and pests.

• The Journal of the Convergence on Culture Technology
• /
• v.10 no.4
• /
• pp.271-283
• /
• 2024

The study seeks to examine the alignment between the Model of Human Occupation (MOHO) and the Six Principles of the Individuals with Disabilities Education Act (IDEA) through qualitative analysis. The study utilizes a qualitative methodology that entails a comprehensive review of the existing literature to establish connections between MOHO and Individuals with Disabilities Education Act (IDEA) principles, with a specific focus on collaborative special education environments. Data collection involves examining academic literature on MOHO, Individuals with Disabilities Education Act (IDEA) principles, and the partnership between occupational therapists and special education teachers. Thematic analysis is employed to identify recurrent themes and relationships, offering valuable insights into the theoretical foundations of MOHO and its compatibility with the Individuals with Disabilities Education Act (IDEA)The Model of Human Occupation (MOHO) highlights the significance of active engagement and meaningful participation in inclusive education. It promotes the development of independence and self-determination in occupational performance for children with special needs. Moreover, MOHO stresses the importance of offering tailored support and adjustments for these children.