• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.16 no.6
• /
• pp.4228-4236
• /
• 2015

Due to the rapid advance in web and mobile computing technologies, normal users have become to produce, provide, and share a varied form of spatial data and information. In the domain of spatial information, numerous researches on GIS have been conducted to provide spatial information services based on a geo-sensor network and a data integration and processing technology. However, to provide user-oriented information, a context information model is necessary to associate GIS data with web and sensor data. Context awareness services is designed to provide specific information, minimizing users' interference. For which, the context information model expresses the relationship of various data from sensor networks and mobile applications and provides a user-specific information considering location and area of interest. Thus, this research aims to develops a context information model based air-pollution information system that obtains and analyses air pollution data and reflects the analysis results on an air-pollution policy. Also, this system aims to raise citizens' awareness on air-pollution and to promote citizens' participatory to improve city's air quality.

• Journal of Digital Convergence
• /
• v.17 no.3
• /
• pp.221-226
• /
• 2019

The characteristic of the beta wave among the EEG waves corresponds to the stress area of human perception. The over-bandwidth of the stress is extracted by analyzing the beta-wave correlation between the low-bandwidth and high-bandwidth. We present a KMeans clustering analysis model for unsupervised machine learning to construct an analytical model for analyzing and extracting the beta-wave correlation. The proposed model classifies the beta wave region into clusters of similar regions and identifies anomalous waveforms in the corresponding clustering category. The abnormal group of waveform clusters and the normal category leaving region are discriminated from the stress risk group. Using this model, it is possible to discriminate the degree of stress of the cognitive state through the EEG waveform, and it is possible to manage and apply the cognitive state of the individual.

• 한국IT서비스학회:학술대회논문집
• /
• 2007.05a
• /
• pp.506-506
• /
• 2007

유비쿼터스 환경 하에서 새로운 첨단 핵심기술 및 서비스가 하나의 제품 안에 집중되어가는 시대적 요구가 대두되고 있다. 이에 부응하여 탄생한 컨버전스 제품인 텔레매틱스의 전망 역시 두드러지고 있다. 본 연구는 Davis[14]가 제안한 기술수용모델(Technology Acceptance Model:TAM)을 통하여 텔레매틱스 사용의도에 관한 수용모형을 제시하였다. 기술수용모델의 내부 요인인 사용의도, 인지된 유용성과 인지된 이용용이성 외에도 업체 신뢰도, 정황 인식성, 자기 효능감의 외부 요인으로 확장하여 요인 간의 구조적 관계를 위한 모형을 개발하였다. 실증분석을 한 결과 정황 인식성, 자기 효능감이 각각 인지된 유용성과 이용용이성에 영향을 미치는 것으로 나타났다. 이러한 결과를 토대로 텔레매틱스의 이용자에게 중요시 되는 특성에 대해 논의하였다.

• Proceedings of the Korean Society of Computer Information Conference
• /
• 2020.07a
• /
• pp.587-589
• /
• 2020

사용자의 관심사를 고려하면 상황 인지 서비스의 질을 높일 수 있다. 기존의 사용자의 관심사를 고려하는 서비스에는 지식베이스(KB)가 사용 되었으나, 최근 새로운 방법인 wikidata를 이용한 엔티티 링크를 활용한 방법도 활발히 연구가 진행되고 있다. wikidata가 적용된 엔티티 링크는 기존의 KB를 이용하는 방법보다 데이터의 변경, 보완이 쉽고 가볍다. 이에 본 논문에서는 wikidata가 적용된 엔티티 링크 모델을 이용한 상황인지 서비스를 제공 할 수 있는 프레임워크를 제안한다.

• Proceedings of the Korean Society of Computer Information Conference
• /
• 2022.07a
• /
• pp.495-497
• /
• 2022

본 데이터 GAN 기법 데이터 증강기법을 적용하여 가속도 데이터를 증강하는 방법에 대해 연구한다. 가속도 데이터는 사람의 활동패턴을 인지하는데 있어 가장 기본적인 데이터로 활용된다. 가속도 데이터를 증강한 뒤, 활동패턴을 인지하는 머신러닝 모델 훈련에 사용한 결과 생성한 데이터가 육안으로 확인하였을 때 실제 데이터와 유사한 패턴을 형성하였고, 실제 활동패턴인지 모델 훈련에 사용한 결과 정확도(Accuracy)는 기존 데이터로만 훈련한 경우 74%인데 비해 증강된 데이터를 혼합하여 훈련하였을 때 약 88%로 개선된 것을 확인하였다.

• Proceedings of the Korean Society of Broadcast Engineers Conference
• /
• 2012.07a
• /
• pp.95-98
• /
• 2012

본 논문에서는 DCT 변환 공간상의 배경휘도와 주파수를 고려한 2차원의 개선된 광-적응 효과(luminance adaptation: LA) JND 모델을 제안한다. 기존의 LA JND 모델은 배경 휘도가 중간점인 회색에 가까울수록 JND가 낮고, 배경 휘도가 어두워지거나 밝아질수록 JND 값이 증가하는 U자형의 1차원 함수형태를 보였다. 그러나 기존 LA JND 모델은 주파수에 따른 영향이 반영되지 않았기 때문에 DCT와 같은 주파수 공간상 JND 모델로는 부정확 한 단점이 있다. 본 논문에서는 주파수와 배경휘도에 따른 2차원 LA JND 모델을 제안한다. 주파수에 따른 LA JND 값을 실제 실험을 통해 획득하였다. 실험 방법은 9가지 크기의 배경 휘도가 다르고 공간적 복잡도가 없는 균일한 영상을 대상으로 $8{\times}8$ 실수형 DCT를 수행한 다음, 15가지 경우의 주파수 크기가 다른 계수들에 대해 사람이 인지 할 때 까지 노이즈를 증가시켜서 JND 값을 찾는 방식을 사용하였다. 실험 결과 4 cpd(cycle per degree) 보다 작은 주파수 대역 에서는 기존의 LA JND 모델과 유사한 결과를 얻었지만 4 cpd보다 큰 주파수 대역에서는 오히려 배경휘도가 작은 값을 가질수록 JND가 감소하는 형태를 보였다. 수행한 실험 결과를 반영하여 주파수가 반영된 2차원 LA JND 모델을 제안한다.

• The Journal of Korean society of community based occupational therapy
• /
• v.9 no.2
• /
• pp.23-31
• /
• 2019

Objective : The purpose of this study is to repeatedly conduct task-oriented training in scopolamine-induced dementia rats and as a result observe changes in the content of acetylcholine, a marker of cognitive function and central nervous system plasticity, to identify the improvement effect of dementia. Methods : It consisted of two groups. One group I was that did not perform task-oriented training in scopolamine-induced dementia rats and the other group II was that performed task-oriented training. Task-oriented training involved stretching, grasping and moving arms and walking obstacles on the legs. We performed a quantified passive avoidance test in the measurement of memory for cognitive function and compared the change in the content of acetylcholine for the plasticity of the central nervous system. Results : The results of the study are as follows: First, there was a significant improvement in cognitive function since the 4th days after task-oriented training of scopolamine-induced dementia rats(.00). Second, task-oriented training applied to scopolamine-induced dementia rats showed a significant increase in acetylcholine content. Conclusion : In this study, task-oriented training, which is often performed on senile dementia patients during occupational therapy intervention, was scientifically demonstrated in scopolamine-induced dementia rats by enhancement of cognitive function through memory improvement and increase in the content of acetylcholine confirming central nervous system plasticity.

• The Journal of The Korea Institute of Intelligent Transport Systems
• /
• v.19 no.5
• /
• pp.162-177
• /
• 2020

The perception of traffic environment based on various sensors in autonomous driving system has a direct relationship with driving safety. Recently, as the perception model based on deep neural network is used due to the development of machine learning/in-depth neural network technology, a the perception model training and high quality of a training dataset are required. However, there are several realistic difficulties to collect data on all situations that may occur in self-driving. The performance of the perception model may be deteriorated due to the difference between the overseas and domestic traffic environments, and data on bad weather where the sensors can not operate normally can not guarantee the qualitative part. Therefore, it is necessary to build a virtual road environment in the simulator rather than the actual road to collect the traning data. In this paper, a training dataset collection process is suggested by diversifying the weather, illumination, sensor position, type and counts of vehicles in the simulator environment that simulates the domestic road situation according to the domestic situation. In order to achieve better performance, the authors changed the domain of image to be closer to due diligence and diversified. And the performance evaluation was conducted on the test data collected in the actual road environment, and the performance was similar to that of the model learned only by the actual environmental data.

• Journal of Broadcast Engineering
• /
• v.19 no.4
• /
• pp.468-477
• /
• 2014

This paper proposes a novel perceptual quality-based (PQ-based) video coding method with foveated contrast sensitivity (FCS). Conventional methods on PQ-based video coding with FCS achieve minimum loss on perceptual quality of compressed video by exploiting the property of human visual system (HVS), that is, its sensitivity differs by the spatial frequency of visual stimuli. On the other hand, PQ-based video coding with foveated masking (FM) exploits the difference of the sensitivity of the HVS between the central vision and the peripheral vision. In this study, a novel FCS model is proposed which considers both the conventional DCT-based JND model and the FM model. Psychological study is conducted to construct the proposed FCS model, and the proposed model is applied to PQ-based video coding algorithm implemented on HM10.0 reference software. Experimental results show that the proposed method decreases bitrate by the average of 10% without loss on the perceptual quality.

• Korean Journal of Cognitive Science
• /
• v.23 no.3
• /
• pp.367-388
• /
• 2012

The centennial of Alan Mathison Turing(23 June 1912 - 7 June 1954) is an appropriate occasion on which to assess his profound influence on the development of cognitive science. His contributions to and attitudes toward that field are discussed from the metamathematical perspective. This essay addresses (i)Turing's mathematical analysis of cognition, (ii)universal Turing machines, (iii)the limitations of universal Turing machines, (iv)oracle Turing machine beyond universal Turing machine, and (v)Turing test for cognitive science. Turing was a ground-breaker, eager to move on to new fields. He actually opened wider the scientific windows to the mind. The results show that first, by means of mathematical logic Turing discovered a new bridge between the mind and the physical world. Second, Turing gave a new formal analysis of operations of the mind. Third, Turing investigated oracle Turing machines and connectionist network machines as new models of minds beyond the limitations of his own universal machines. This paper explores why the cognitive scientist would be ever expecting a new Turing Test on the shoulder of Alan Turing.