• Toxicological Research
• /
• v.29 no.4
• /
• pp.221-227
• /
• 2013

Embryonic stem (ES) cells have potential for use in evaluation of developmental toxicity because they are generated in large numbers and differentiate into three germ layers following formation of embryoid bodies (EBs). In earlier study, embryonic stem cell test (EST) was established for assessment of the embryotoxic potential of compounds. Using EBs indicating the onset of differentiation of mouse ES cells, many toxicologists have refined the developmental toxicity of a variety of compounds. However, due to some limitation of the EST method resulting from species-specific differences between humans and mouse, it is an incomplete approach. In this regard, we examined the effects of several developmental toxic chemicals on formation of EBs using human ES cells. Although human ES cells are fastidious in culture and differentiation, we concluded that the relevancy of our experimental method is more accurate than that of EST using mouse ES cells. These types of studies could extend our understanding of how human ES cells could be used for monitoring developmental toxicity and its relevance in relation to its differentiation progress. In addition, this concept will be used as a model system for screening for developmental toxicity of various chemicals. This article might update new information about the usage of embryonic stem cells in the context of their possible ability in the toxicological fields.

• Journal of Institute of Control, Robotics and Systems
• /
• v.11 no.5
• /
• pp.398-405
• /
• 2005

The intelligent robots that will be needed in the near future are human-friendly robots that are able to coexist with humans and support humans effectively. To realize this, robots need to recognize their position and posture in known environment as well as unknown environment. Moreover, it is necessary for their localization to occur naturally. It is desirable for a robot to estimate of his position by solving uncertainty for mobile robot navigation, as one of the best important problems. In this paper, we describe a method for the localization of a mobile robot using image information of a moving object. This method combines the observed position from dead-reckoning sensors and the estimated position from the images captured by a fixed camera to localize a mobile robot. Using a priori known path of a moving object in the world coordinates and a perspective camera model, we derive the geometric constraint equations which represent the relation between image frame coordinates for a moving object and the estimated robot's position. Also, the control method is proposed to estimate position and direction between the walking human and the mobile robot, and the Kalman filter scheme is used for the estimation of the mobile robot localization. And its performance is verified by the computer simulation and the experiment.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.15 no.5
• /
• pp.1630-1648
• /
• 2021

Owing to the unprecedented COVID-19 pandemic, the pharmaceutical industry has attracted considerable attention, spurred by the widespread expectation of vaccine development. In this study, we collect relevant topics from news articles related to COVID-19 and explore their links with two South Korean pharmaceutical indices, the Drug and Medicine index of the Korea Composite Stock Price Index (KOSPI) and the Korean Securities Dealers Automated Quotations (KOSDAQ) Pharmaceutical index. We use generalized Dirichlet-multinomial regression (g-DMR) to reveal the dynamic topic distributions over metadata of index values. The results of our analysis, obtained using g-DMR, reveal that a greater focus on specific news topics has a significant relationship with fluctuations in the indices. We also provide practical and theoretical implications based on this analysis.

• KIPS Transactions on Software and Data Engineering
• /
• v.7 no.12
• /
• pp.485-496
• /
• 2018

So far, the deep learning, a field of artificial intelligence, has achieved remarkable results in solving problems from unstructured data. However, it is difficult to comprehensively judge situations like humans, and did not reach the level of intelligence that deduced their relations and predicted the next situation. Recently, deep neural networks show that artificial intelligence can possess powerful relational reasoning that is core intellectual ability of human being. In this paper, to analyze and observe the performance of Relation Networks (RN) among the neural networks for relational reasoning, two types of RN-based deep neural network models were constructed and compared with the baseline model. One is a visual question answering RN model using Sort-of-CLEVR and the other is a text-based question answering RN model using bAbI task. In order to maximize the performance of the RN-based model, various performance improvement experiments such as hyper parameters tuning have been proposed and performed. The effectiveness of the proposed performance improvement methods has been verified by applying to the visual QA RN model and the text-based QA RN model, and the new domain model using the dialogue-based LL dataset. As a result of the various experiments, it is found that the initial learning rate is a key factor in determining the performance of the model in both types of RN models. We have observed that the optimal initial learning rate setting found by the proposed random search method can improve the performance of the model up to 99.8%.

• Proceedings of the Acoustical Society of Korea Conference
• /
• 1992.06a
• /
• pp.3-8
• /
• 1992

The theory of subjective preference with temporal and spatial factors which include sound signals arriving at both ears is described. Then, auditory evoked potentials which may relate to a primitive subjective response namely subjective preference are discussed. According to such fundamental phenomena, a workable model of human auditory-brain system is proposed. For eample, important subjective attributes, such as loudness, coloration, threshold of preception of a reflection and echo distrubance as well as subjective preference in relation to the initial time delay gap between the direct sound and the first reflection, and the subsequent reverberation time are well described by the autocorrelation function of source signals. Speech clarity, subjective diffuseness as well as subjective preference are related to the magnitude of inter-aural crosscorrelation function (IACC). Even the caktail party effects may be eplained by spatialization of human brain, i.e., independence of temporal and spatial factors.

• 한국정보디스플레이학회:학술대회논문집
• /
• 2009.10a
• /
• pp.1228-1231
• /
• 2009

This paper presented an automatic system for display quality measurement by image processing. The goal is to replace human eyes for display quality evaluation by computer vision and get the objective quality review for consumer to make purchase of monitor or TV. Color, contrast, brightness, sharpness and motion blur are the main five factors to affect display quality that could be measured by supplying patterns and analyzing the corresponding images captured from webcam. The scores are calculated by image processing techniques. Linear regression model is then adopted to find the relation between human score and the measured display performance.

• Annual Conference on Human and Language Technology
• /
• 2022.10a
• /
• pp.379-384
• /
• 2022

관계 추출은 두 개체 간의 관계를 식별하는 작업이며, 비정형 텍스트를 구조화시키는 역할을 하는 작업 중 하나이다. 현재 관계 추출에서 다양한 모델에 대한 연구들이 진행되고 있지만, 한국어 관계 추출 모델에 대한 연구는 영어에 비해 부족하다. 따라서 본 논문에서는 NE(Named Entity)태그 정보가 반영된 TEM(Typed Entity Marker)과 의존 구문 그래프를 이용한 한국어 관계 추출 모델을 제안한다. 모델의 학습과 평가 말뭉치는 KLUE에서 제공하는 관계 추출 학습 말뭉치를 사용하였다. 실험 결과 제안 모델이 68.57%의 F1 점수로 실험 모델 중 가장 높은 성능을 보여 NE태그와 구문 정보가 관계 추출 성능을 향상시킬 수 있음을 보였다.

• Annual Conference on Human and Language Technology
• /
• 2021.10a
• /
• pp.235-240
• /
• 2021

구문 트리의 구조적 정보는 문장 수준 관계 추출을 수행하는데 있어 매우 중요한 자질 중 하나다. 기존 관계 추출 연구는 구문 트리에서 최단 의존 경로를 적용하는 방식으로 관계 추출에 필요한 정보를 추출해서 활용했다. 그러나 이런 트리 가지치기 기반의 정보 추출은 관계 추출에 필요한 어휘 정보를 소실할 수도 있다는 문제점이 존재한다. 본 논문은 이 문제점을 해소하기 위해 개체 중심으로 구문 트리를 재구축하고 모든 노드의 정보를 관계 추출에 활용하는 모델을 제안한다. 제안 모델은 TACRED에서 F1 점수 74.9 %, KLUE-RE 데이터셋에서 72.0%로 가장 높은 성능을 보였다.

• Annual Conference on Human and Language Technology
• /
• 2020.10a
• /
• pp.124-127
• /
• 2020

관계 추출은 문장에서 두 개의 엔티티가 주어졌을 때 두 개의 엔티티에 대한 의미적 이해를 통해 관계를 분류하는 작업이다. 이와 같이 관계 추출에서 관계를 분류하기 위해서는 두 개의 엔티티에 대한 정보가 필요하다. 본 연구에서는 관계 추출을 하기 위해 문장에서 엔티티들의 표현을 다르게하여 관계 추출의 성능을 비교 실험하였다. 첫번째로는 문장에서 [CLS] 토큰(Token)으로 관계를 분류하는 Standard 엔티티 정보 표현과 두번째로는 엔티티의 앞과 뒤에 Special Token을 추가하여 관계를 분류하는 Entity-Markers 엔티티 정보 표현했다. 이를 기반으로 문장의 문맥 정보를 학습한 사전 학습(Pre-trained)모델인 BERT-Large와 ALBERT-Large를 적용하여 실험을 진행하였다. 실험 결과 Special Token을 추가한 Entity-Markers의 성능이 높았으며, BERT-Large에서 더 높은 성능 결과를 확인하였다.

• Korean Journal of Social Welfare Studies
• /
• v.42 no.4
• /
• pp.413-443
• /
• 2011

The objectives of this study were to survey the level of social capital owned by self-support program participants, and to analyze the direct and indirect effects of social capital on their quality of life. Particularly because an individual's life is highly likely to be influenced by multiple aspects including human relation, this study purposed to determine the mediating effect of job satisfaction in the relation between social capital and the quality of life. The survey used a structured questionnaire, and in the contents of the questionnaire, the quality of life was selected as a dependent variable, social capital as an independent variable, and the job satisfaction as a mediating variable affecting the relation between social capital and the quality of life. The results of this study were as follows. First, as to the relation between self-support program participants' social capital and the quality of life, the network level and the normative level hand an important effect on the quality of life. Second, as to the relation between self-support program participants' social capital and job satisfaction, social capital had a negative effect on job satisfaction. Third, in the relation between self-support program participants' social capital and their quality of life, the mediating effect of job satisfaction was positive and this supports the spillover model among hypotheses on the relation between job satisfaction and the quality of life.