• Journal of the Korean Society for information Management
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• v.34 no.1
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• pp.135-154
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• 2017

The purpose of the study is to identify the barriers to using mobile health applications based on the Diffusion of Innovations Theory. The study employed a purposive sampling to recruit college students who were non-adopters or rejecters. The study participants were a total of 44 students, who consist of 32 males and 12 females, and paper-based interviews were conducted. The findings of the study indicated that attributes such as relative advantages, complexity, trialability and observability were not considerable factors of impeding the adoption or continuous use of health applications, whereas relative disadvantages and compatibility were. The study suggests that health application developers and service providers minimize relative disadvantages and enhance compatibility of the innovation with consumers' life styles, rather than try to improve relative advantages and complexity, to more effectively encourage non-adopters to try and maintain using the innovation.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.40 no.11
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• pp.997-1003
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• 2012

GNSS and ARS are the most common sensors in low-end UAVs. However, these sensors are vulnerable to built-in errors and cannot measure the body heading independently. The GNSS/INS cannot fully compensate the IMU errors in initial alignment process and rectilinear flights. For an unmanned helicopter, a magnetometer can be more useful than any other sensors to obtain heading information. However, the electric motor which drives small helicopter UAV keeps the magnetometer from reading the pure magnetotelluric vector. This paper shows the effects of electric motor on the magnetometer readings, and presents a method to compensate the effects. The results are verified with flight test data. The simulation and experimental results in this paper proves that aiding GNSS/INS with magnetometer increases observability and improves accuracy.

• 한국태양에너지학회:학술대회논문집
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• 2012.03a
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• pp.419-424
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• 2012

This paper discusses the state-of-the-art techniques in real-time state estimation for the Smart Microgrids. The most popular method used in traditional power system state estimation is a Weighted Least Square(WLS) algorithm which is based on Maximum Likelihood(ML) estimation under the assumption of static system state being a set of deterministic variables. In this paper, we present a survey of dynamic state estimation techniques for Smart Microgrids based on Belief Propagation (BP) when the system state is a set of stochastic variables. The measurements are often too sparse to fulfill the system observability in the distribution network of microgrids. The BP algorithm calculates posterior distributions of the state variables for real-time sparse measurements. Smart Microgrids are modeled as a factor graph suitable for characterizing the linear correlations among the state variables. The state estimator performs the BP algorithm on the factor graph based the stochastic model. The factor graph model can integrate new models for solar and wind correlation. It provides the Smart Microgrids with a way of integrating the distributed renewable energy generation. Our study on Smart Microgrid state estimation can be extended to the estimation of unbalanced three phase distribution systems as well as the optimal placement of smart meters.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 1995.04a
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• pp.240-245
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• 1995

제어이론의 역사적 발전사를 고찰해보면 1930년대부터 1960년대까지를 고전 제어(classical control) 시대로 분류되고 이때 주로 사용되었던 용어들은 주파수역(frequency domain)에서 사용된 개념인 극점(pole), 영점(zero), Nyquist, 근궤적(root-Locus) 선도(plot)등으로 대표된다. 그 다음단계인 현대 제어(modern control) 시대 (1960년대-1980년대)때는 새로운 개념들이 도입 되었는데 시간역(time domain)에서 사용되는 상태공간(state-space) 모델, 가제어성(controllability), 가관측성(observability), Kalman 필터, LQG 제어 등이다. 1980년대부터 현재까지를 강인제어(robust control) 시대로 분류하는데 이것의 특징들은 극점이나 영점 대신 상태공간 모델을 사용하여 주파수역에서 정의되는 개념들인 H$_{\infty}$ 합성법, .$\mu$ 해석법, LQG/LTR 및 QFT, Lyapunov 등으로 대표된다. 현대제어시대때는 제어기 K는 공칭 플랜트 모델 G$_{0}$를 기준으로 설계되었으나 실제로 공칭 플랜트 모델은 실제 플랜트와 항상 같을 수가 없었다. 따라서 실제 플랜트 G는 G=G$_{0}$ + .DELTA.G로 표현되며 여기서 .DELTA.G는 플랜트 불 확실성(plant uncertainty), 즉 실제 플랜트와 공칭 플랜트의 차이를 나타낸 다. 이 플랜트 불확실성은 제어기가 실제 응용되어 사용되었을 때 제대로 작동하지 않는 주요 이유중에 하나이다. 이와 같은 상황에서 안정도 강인성 (stability robustness) 및 성능 강인성(performance rosubtness)의 보장은 상 당히 중요한 문제로 대두되었으며 주어진 플랜트 불확실성하에서 이러한 강이성들이 보장되는 제어이론들 중 H$_{\infty}$ 제어이론이 많이 연구/응용 되고 있다. 특히 공칭 플랜트 모델과 함께 사용되는 플랜트 모델과 함께 사용되는 플랜트 불확실성 모델은 직접적으로 성능 및 안정도에 영향을 미치므로 주의 깊게 선정해야 한다.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2008.10a
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• pp.289-292
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• 2008

This paper presents a branch prediction algorithm and a 4-way set-associative cache for performance improvement of OpenRISC processor and a clock gating algorithm using ODC (Observability Don't Care) operation for a low-power processor. The branch prediction algorithm has a structure using BTB(Branch Target Buffer) and 4-way set associative cache has lower miss rate than direct-mapped cache. The clock gating algorithm reduces dynamic power consumption. As a result of estimation of performance and dynamic power, the performance of the OpenRISC processor using the proposed algorithm is improved about 8.9% and dynamic power of the processor using samsung $0.18{\mu}m$ technology library is reduced by 13.9%.

• Journal of the Korean Society of Clothing and Textiles
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• v.30 no.1 s.149
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• pp.146-156
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• 2006

The purpose of this study is to investigate the factors that influence consumers' adoption of performance infants' wear made of functional textiles. Based on Innovation Diffusion Model, product attributes, consumer traits, and communication characteristics were considered. A survey was carried out with a convenience sample of 241 housewives who have infants under 4 year-old, living in the Seoul metropolitan area. To analyze the data, SPSS 10.0 was used employing ANOVA, Duncan's post-hoc comparison, $X^2$, and f-test. The participants were classified into 4 groups based on their levels of adoption of performance infants' wear: No-Cognition, Negative Attitude, Positive Attitude, and Purchasing groups. There were significant differences among the four groups in terms of their perception of product attributes, communication characteristics, and personal traits. In terms of product attributes, the Positive Attitude group and Purchasing group showed higher perception of relative advantage, compatibility, trialability and observability than other groups. These groups were also high in terms of their tendency of actively seeking for additional product information, and particularly relied on the information from experts on TV or the Internet, personal experience posted on the Internet, or their own experience. Those who were in professional, well-educated and high income brackets were more likely to be Purchasing group than Positive Attitude group, which means once the positive attitude was formed they are likely to purchase the product.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• v.1
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• pp.277-282
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• 2006

It is well known that Kalman filtering is an optimal real-time data fusion method for GPS/INS integration. However, it has some limitations in terms of stability, adaptability and observability. A Kalman filter can perform optimally only when its dynamic model is correctly defined and the noise statistics for the measurement and process are completely known. It is found that estimated Kalman filter states could be influenced by several factors, including vehicle dynamic variations, filter tuning results, and environment changes, etc., which are difficult to model. Neural networks can map input-output relationships without apriori knowledge about them; hence a proper designed neural network is capable of learning and extracting these complex relationships with enough training. This paper presents a GPS/INS integrated system that combines Kalman filtering and neural network algorithms to improve navigation solutions during GPS outages. An Extended Kalman filter estimates INS measurement errors, plus position, velocity and attitude errors etc. Kalman filter states, and gives precise navigation solutions while GPS signals are available. At the same time, a multi-layer neural network is trained to map the vehicle dynamics with corresponding Kalman filter states, at the same rate of measurement update. After the output of the neural network meets a similarity threshold, it can be used to correct INS measurements when no GPS measurements are available. Selecting suitable inputs and outputs of the neural network is critical for this hybrid method. Detailed analysis unveils that some Kalman filter states are highly correlated with vehicle dynamic variations. The filter states that heavily impact system navigation solutions are selected as the neural network outputs. The principle of this hybrid method and the neural network design are presented. Field test data are processed to evaluate the performance of the proposed method.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.14 no.2
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• pp.453-461
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• 2010

This paper presents a branch prediction algorithm and a 4-way set-associative cache for performance improvement of embedded RISC core and a clock-gating algorithm using ODC (Observability Don't Care) operation to improve the power consumption of the core. The branch prediction algorithm has a structure using BTB(Branch Target Buffer) and 4-way set associative cache has lower miss rate than direct-mapped cache. Pseudo-LRU Policy, which is one of the Line Replacement Policies, is used for decreasing the number of bits that store LRU value. The clock gating algorithm reduces dynamic power consumption. As a result of estimation of performance and dynamic power, the performance of the OpenRISC core applied the proposed architecture is improved about 29% and dynamic power of the core using Chartered $0.18{\mu}m$ technology library is reduced by 16%.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.37 no.10
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• pp.1002-1009
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• 2009

Precision guidance filter design for a tactical missile with a strapdown seeker aided by low-cost strapdown sensors has been addressed in this paper. The low-cost strapdown sensors consist of an IMU with 3-axis accelerometers and gyroscopes, 3-axis magnetometers, and a barometer. Missile's position, velocity, attitude, and bias error of the barometer are considered as state variables. Since the state and measurement equations are highly nonlinear, we adopt UKF(Unscented Kalman Filter). The proposed guidance filter has a function of a navigation filter if target position error is not considered. In the case that the target position error is introduced, the proposed filter can effectively estimate the relative states of the missile to the true target. For specific engagement scenarios, we can observe that observability problems occur.

• Journal of the Korea Institute of Military Science and Technology
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• v.19 no.1
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• pp.35-42
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• 2016

Modern aircraft is facing the increase of power demands and thermal challenges. In accordance with the application of more electric technology and advanced mission requirement, aircraft system requires increase of power generation and it cause increase of internal heat generation. Simultaneously, restrictions have significantly been imposed to the thermal management system. Modern aircraft must maintain low radar observability and infra-red signature. In addition, new composite aircraft skins have reduced the amount of heat that can be rejected to the environment. The combination of these characteristics has increased the challenges faced by thermal management. In order to mitigate the thermal challenges, the concept of system level thermal management should be applied and new modeling and simulation tools need to be developed. To develop and utilize system level thermal management technology, three key points are considered. Firstly, the performance changes of subsystems and components must be assessed at an integrated thermal system. It is because that each subsystem and component interacts with other subsystems or components and it can directly effects on overall system performance. Secondly, system level thermal management requirements and solutions must be evaluated early in conceptual design process as vehicle and propulsion system configuration decisions are being made. Finally, new component level thermal management technologies must focus on reducing heat generation and increasing the availability of heat sinks.