• Korean Journal of Applied Biomechanics
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• v.34 no.2
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• pp.71-80
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• 2024

Objective: This study aimed to explore the brain connectivity between brain and biomechanical variables by exploring motion recognition through FFT (fast fourier transform) analysis and AI (artificial intelligence) focusing on quiet standing movement patterns. Method: Participants included 12 young adult males, comprising university students (n=6) and elite gymnasts (n=6). The first experiment involved FFT of biomechanical signals (f_CoP, f_AJtorque and f_EEG), and the second experiment explored the optimization of AI-based GRU (gated recurrent unit) using f_EEG data. Results: Significant differences (p<.05) were observed in frequency bands and maximum power based on group and posture types in the first experiment. The second study improved motion prediction accuracy through GRU performance metrics derived from brain signals. Conclusion: This study delved into the movement pattern of upright standing posture through the analysis of bio-signals linking the cerebral cortex to motor performance, culminating in the attainment of motion recognition prediction performance.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.29B no.8
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• pp.7-14
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• 1992

This paper persents how the signal is expressed by an implied unit data and the implied unit data is regenerated into the original signal. This shows that the regenerated signal is equal or similar to the original signal depending on the number of chaos prediction. The algorithm quoted above is implemented from the signal composed of 30 data. This algorithm will be applied to the applied science of data communication: information storage, speech processing, CAD, character recognition, etc...

• Korean Journal of Hydrosciences
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• v.3
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• pp.97-104
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• 1992

To design the minor structures in the small watersheds, it is required to calculate the peak discharge. For these calculations the simple peak flow prediction equations, the unit hydrograph method. the syntheic unit hydrograph methods or the runoff simulation models are adopted. To use these methods it is generally requried to know the amount and the distributions of the design rainfall; which are the uniform distribution, the trangular distribution, the trapezoidal distribution, or the Huff type distribution. In this study, the peak discharges are calculated by the different rainfall distributions and the results are compared.

• Journal of the Korean Association of Geographic Information Studies
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• v.20 no.1
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• pp.15-25
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• 2017

In recent years, polar research has been focused on climate change, natural resources, and development of a new North Pole Route. Since 2010, the Korea Polar Research Institute has been collecting various in situ data from the Arctic/Antarctic oceans using ARAON, which is the first effort of Korea toward leading global polar research. As a part of these activities, a web-based GIS service was developed to collect in situ data and to standardize data formats. Visualizations of in situ measurements and thematic maps were also developed to improve both the quantitative and qualitative quality of polar ocean research, and to increase accessibility of polar oceanographic data. This system will ultimately share all of the data acquired from the Arctic/Antarctic oceans with international research groups.

• International journal of advanced smart convergence
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• v.10 no.3
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• pp.122-130
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• 2021

This study is about an Artificial Intelligence-based fake news identification system and its methods to determine the authenticity of content distributed over the Internet. Among the news we encounter is news that an individual or organization intentionally writes something that is not true to achieve a particular purpose, so-called fake news. In this study, we intend to design a system that uses Artificial Intelligence techniques to identify fake content that exists within the news. The proposed identification model will propose a method of extracting multiple unit factors from the target content. Through this, attempts will be made to classify unit factors into different types. In addition, the design of the preprocessing process will be carried out to parse only the necessary information by analyzing the unit factor. Based on these results, we will design the part where the unit fact is analyzed using the deep learning prediction model as a predetermined unit. The model will also include a design for a database that determines the degree of fake news in the target content and stores the information in the identified unit factor through the analyzed unit factor.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.40 no.8
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• pp.670-677
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• 2012

In this paper, mechanical property of biomorphic C/SiC composite was calculated by unit cell analysis. The microstructural arrangements of carbonized pine and radiata pine which were impregnated with silicon, were idealized as square and hexagonal arrays. Unit cell was then defined and equivalent elastic constants were calculated. A single and double unit cell structures were considered. The effect of void distribution was also studied by monte carlo simulation.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.13 no.11
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• pp.1125-1133
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• 2001

Since the surface temperature of the evaporating tube in an ammonia unit cooled is lower than the dew point of atmosphere, the moisture in the atmosphere condenses and the frost grows on the tube. The frost of liquid film decreases the heat transfer rate. The reliable analysis of the heat transfer is required for the prediction of the optimal design of the ammonia unit cooler. For the specific commercial model, the performance was numerical1y estimated for the variation of operating condition and geometric configuration. It is found that there exists an optimum range for the parameters such as mass flow rate of air and refrigerant, humidity, refrigerant quality, fin pitch, the number of step, the number of rows and the pattern of refrigerant path.

• Proceedings of the Korea Information Processing Society Conference
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• 2002.04b
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• pp.1627-1630
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• 2002

본 논문은 역추적 예견 알고리즘을 사용한 비터비 복호기에서의 TB단의 Polling 구조의 단순화 방법을 제시한다. 비터비 복호기의 3대 Unit중 하나인 Trace Back에서 역추적 예견 알고리즘을 사용할 경우 복호화 시점에서의 최소 State Metric 값을 찾아야 하는 번거로움을 줄일 수 있다. 하지만 복호 신호의 신뢰도 분산에 따라 Polling Unit 이 추가되어야 함에 따라 실제 하드웨어 복잡도에서의 이득은 미미한 것으로 알려져 있다. 제시된 구조에서는 Polling Unit을 단순화 할 수 있는 방법을 적용하였다. 기존 하드웨어와의 비교 평가를 위하여 IEEE802.11a의 표준에 따른 부호화율 1/2, 구속장 7을 갖는 비터비 디코더에 대하여 역추적 예견 알고리즘과 파이프라인 구조만을 갖는 경우와 제안된 단순화한 Polling Unit을 적용한 구조와의 비교에서 Trace Back Unit에서 약 45%의 감소 효과를 보였다.

• ETRI Journal
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• v.38 no.5
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• pp.807-817
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• 2016

A novel fast algorithm is suggested for a coding unit (CU) mode decision using pseudo rate-distortion based on a separated encoding structure in High Efficiency Video Coding (HEVC). A conventional HEVC encoder requires a large computational time for a CU mode prediction because prediction and transformation procedures are applied to obtain a rate-distortion cost. Hence, for the practical application of HEVC encoding, it is necessary to significantly reduce the computational time of CU mode prediction. As described in this paper, under the proposed separated encoder structure, it is possible to decide the CU prediction mode without a full processing of the prediction and transformation to obtain a rate-distortion cost based on a suitable condition. Furthermore, to construct a suitable condition to improve the encoding speed, we employ a pseudo rate-distortion estimation based on a Hadamard transformation and a simple quantization. The experimental results show that the proposed method achieves a 38.68% reduction in the total encoding time with a similar coding performance to that of the HEVC reference model.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.31 no.5C
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• pp.534-539
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• 2006

In this paper, we propose a new frame prediction filtering technique and a hardware(H/W) architecture for scalable video coding. We try to evaluate MCTF(motion compensated temporal filtering) and hierarchical B-picture which are a technique for eliminate correlation between video frames. Since the techniques correspond to non-causal system in time, these have fundamental defects which are long latency time and large size of frame buffer. We propose a new architecture to be efficiently implemented by reconfiguring non-causal system to causal system. We use the property of a repetitive arithmetic and propose a new frame prediction filtering cell(FPFC). By expanding FPFC we reconfigure the whole arithmetic architecture. After the operational sequence of arithmetic is analyzed in detail and the causality is imposed to implement in hardware, the unit cell is optimized. A new FPFC kernel was organized as simple as possible by repeatedly arranging the unit cells and a FPFC processor is realized for scalable video coding.