• Journal of the Korean Statistical Society
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• 제30권1호
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• pp.21-30
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• 2001

Suppose we observe a set of data (X$_1$,Y$_1$(, …, (X$_{n}$,Y$_{n}$) and use the Nadaraya-Watson regression estimator to estimate m(x)=E(Y│X=x). in this article bandwidth selection problem for the Nadaraya-Watson regression estimator is investigated. In particular cross validation method based on average square error(ASE) is considered. Theoretical results here include a central limit theorem that quantifies convergence rates of the bandwidth selector.tor.

• 전자공학회논문지C
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• 제35C권5호
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• pp.59-68
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• 1998

This paper proposes a neural network algorithm for a channel assignment in cellular mobile communications. The proposed algorithm is developed base on hopfield neural network in order to minimize the number of channel without a confliction between cells. To compare the performance of the proposed algorithm, we used seven benchmark problems selected from kunz's and funabiki's papers. Experimental results show that the convergence times are reduced form 27% to 66% compared with Kunz's and funabiki's algorithm and vonvergence rates are improved to 100%.

• 한국전산유체공학회:학술대회논문집
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• 한국전산유체공학회 1998년도 춘계 학술대회논문집
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• pp.29-34
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• 1998

An efficient 3-dimensional compressible solver is developed using the second-order upwind TVD scheme and the multigrid diagonalized ADI method. The multigrid method is improved so that the present DADI algorithm obtains better convergence rates. Results are computed on Cray C90 computer for transonic unsaperated flows past ONERA-M6 wing to demonstrate the accuracy and efficiency. The results show good agreement with experimetal data. A reduction of four orders of residual for 3-dimensional transonic flow is obtained about 99 seconds.

• Journal of the Korean Data and Information Science Society
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• 제10권2호
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• pp.465-472
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• 1999

We considered a bootstrap method for constructing confidenc intervals for a one parameter model using multinomial sampling. The convergence rates or the proposed bootstrap method are calculated for model-based maximum likelihood estimators(MLE) using multinomial sampling. Monte Carlo simulation was used to compare the performance of bootstrap methods with normal approximations in terms of the average coverage probability criterion.

• 한국광학회:학술대회논문집
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• 한국광학회 1989년도 제4회 파동 및 레이저 학술발표회 4th Conference on Waves and lasers 논문집 - 한국광학회
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• pp.89-94
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• 1989

In this paper, we propose a hybrid optical/digital version of the associative memory which improve hardware efficiency and increase convergence rates. Multifocus hololens are used as space-varient optical element for performing inner product and summation function. The real-time input and the stored states of memory matrix is formated using LCTV. One method of adaptively changing the weights of stored vectors during each iteration is implemented electronically. A design for a optical implementation scheme is discussed and the proposed architecture is demonstrated the ability of retrieving with computer simmulation.

• 한국컴퓨터정보학회논문지
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• 제7권4호
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• pp.204-210
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• 2002

자기조직화 지도(self-organizing feature map)는 학습시 수렴하기 위하여 많은 입력패턴을 필요로 하는 단점이 있다. 본 논문에서는 자기조직화 지도 학습시 학습률이 일정한 이웃 상호작용 집합을 동적 가우시안 함수로 변환하여 수렴속도와 수렴도를 개선할 수 있는 방법을 제안한다. 제안한 방법은 이웃 상호작용 함수로 사용된 가우시안 함수의 편차와 폭을 학습 회수에 따라 감소하는 동적 성질과 승자 뉴런으로부터의 위상학적 위치에 따라 각기 다른 학습률을 갖도록 하였다. 따라서 본 논문에서는 자기조직화 지도의 수렴속도와 수렴도를 향상시켰다.

• 한국전기전자재료학회:학술대회논문집
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• 한국전기전자재료학회 2007년도 추계학술대회 논문집
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• pp.214-215
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• 2007

Etch rates and surface chemistry of phenol formaldehyde-based photoresist after short time $O_2\;and\;N_2O$ radio frequency (RF) plasma treatment depending on exposure time were investigated. It was found that the etch rate of photoresist sharply increased after discharge turn on and reached a limit with increase in plasma exposure time in both gases. X-ray photoelectron spectroscopy (XPS) analysis showed that the surface chemical structure become nearly constant after the treatment of 15 sec. Concentration of surface oxygen-containing groups after processing both in oxygen and in $N_2O$ plasmas is similar.

• 인터넷정보학회논문지
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• 제22권5호
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• pp.27-33
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• 2021

With the broad adoption of the Internet of Things (IoT) in a variety of scenarios and application services, management and orchestration entities require upgrading the traditional architecture and develop intelligent models with ultra-reliable methods. In a heterogeneous network environment, mission-critical IoT applications are significant to consider. With erroneous priorities and high failure rates, catastrophic losses in terms of human lives, great business assets, and privacy leakage will occur in emergent scenarios. In this paper, an efficient resource slicing scheme for optimizing federated learning in software-defined IoT (SDIoT) is proposed. The decentralized support vector regression (SVR) based controllers predict the IoT slices via packet inspection data during peak hour central congestion to achieve a time-sensitive condition. In off-peak hour intervals, a centralized deep neural networks (DNN) model is used within computation-intensive aspects on fine-grained slicing and remodified decentralized controller outputs. With known slice and prioritization, federated learning communications iteratively process through the adjusted resources by virtual network functions forwarding graph (VNFFG) descriptor set up in software-defined networking (SDN) and network functions virtualization (NFV) enabled architecture. To demonstrate the theoretical approach, Mininet emulator was conducted to evaluate between reference and proposed schemes by capturing the key Quality of Service (QoS) performance metrics.

• 인터넷정보학회논문지
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• 제22권3호
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• pp.37-43
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• 2021

본 논문에서는 모바일 환경에서 실시간으로 전면과 후면 카메라의 객체를 인식하여 객체 픽셀의 영역을 분할하고 이미지 처리를 통해 합성하는 방법을 연구하였다. 이를 위해 Apple사의 iOS에서 제공하는 듀얼 카메라에 DeepLabV3 머신러닝 모델을 적용하여 객체를 분할하였다. 또한 이미지 합성 및 후처리를 위해 Apple사의 코어 이미지와 코어 그래픽 라이브러리를 이용하여 영역의 배경 제거 및 합성 방식을 제안하고 구현하였다. 또한, 이전 연구에 비해 CPU 사용량을 개선하였고 깊이와 DeepLabV3의 처리 속도를 비교하여 처리 결과에 영향을 주는 요소를 분석하였다. 마지막으로 이 두 방식을 활용한 카메라 애플리케이션을 개발하였다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제17권1호
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• pp.280-294
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• 2023

Unmanned aerial vehicles (UAVs) and millimeter-wave frequencies play key roles in supporting 5G wireless communication systems. They expand the field of wireless communication by increasing the data capacities of communication systems and supporting high data rates. However, short wavelengths, owing to the high millimeter-wave frequencies can cause problems, such as signal attenuation and path loss. To address these limitations, research on high directional beamforming technologies continue to garner interest. Furthermore, owing to the mobility of the UAVs, it is essential to track the beam angle accurately to obtain full beamforming gain. This study presents a beam tracking method based on the unscented Kalman filter using hybrid beamforming. The simulation results reveal that the proposed beam tracking scheme improves the overall performance in terms of the mean-squared error and spectral efficiency. In addition, by expanding analog beamforming to hybrid beamforming, the proposed algorithm can be used even in multi-user and multi-stream environments to increase data capacity, thereby increasing utilization in new-radio multiple-input multiple-output orthogonal frequency-division multiplexing systems.