• Journal of the Korean Data and Information Science Society
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• v.26 no.2
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• pp.525-533
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• 2015

Modern production process is a very complex structure combined observations which are correlated with several factors. When the error signal occurs in the process, it is very difficult to know the root causes of an out-of-control signal because of insufficient information. However, if we know the time of the change, the system can be controlled more easily. To know it, we derive a maximum likelihood estimator (MLE) of the change point in a process when observations are from a multivariate IMA(1,1) process by monitoring residual vectors of the model. In this paper, numerical results show that the MLE of change point is effective in detecting changes in a process.

• Journal of Biomedical Engineering Research
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• v.13 no.1
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• pp.1-8
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• 1992

In the field of prosthesis arm control, the pattern classification of the EMG signal is a required basis process and also the estimation of force from collected EMG data is another necessary duty. But unfortunately, what we've got is not real force but an EMG signal which contains the information of force. This is the reason why we estimate the force from the EMG data. In this paper, when we handle the EMG signal to estimate the force, spatial prewhitening process is applied from which the spatial correlation between the channels are removed. And after the orthogonal transformation which is used in the force estimation process, the transformed signal Is inputed into the probabilistic model for pattern classification. To verify the different results of the multiple channels, SNR(signal to noise ratio) function is introduced.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.2 no.3
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• pp.17-22
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• 2009

The objective of this study was to develop a signal process software for a Electromyograph(EMG). And this paper was developed to general signal process software for a Electromyograph using biomechanics. It was used the clinic, rehabilitation, ergonomics and sports. It was composed to the module type for the monitoring frequency analysis, the zero crossing and comparison analysis etc. It's UI(User Interface) made up the continuous monitoring, the reports and the user-friendly-approach. This developed Electromyography will be applied to biomedical engineering system.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.6 no.8
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• pp.1913-1925
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• 2012

In order to efficiently utilize limited radio resources, resource allocation schemes in OFDMA-based wireless networks have gained intensive attention recently. Instead of improving the throughput performance, the utility is adopted as the metric for resource allocation, which provides reasonable methods to build up the relationship between user experience and various quality-of-service (QoS) metrics. After formulating the optimization problem by using a weighted bipartite graph, a modified bipartite matching method is proposed to find a suboptimal solution for the resource allocation problem in OFDMA-based wireless systems with feasible computational complexity. Finally, simulation results are presented to validate the effectiveness of the proposed method.

• Proceedings of the Korean Society of Computer Information Conference
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• 2016.01a
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• pp.321-322
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• 2016

본 논문에서는 수배전반에서 부하 설비 또는 외부의 영향을 확인할 수 있는 장치 및 보호설비가 설치되어 있으나 자체 사고를 신속히 검출하고 판단할 수 있는 기술의 확보를 위하여 해상도가 낮은 저가의 열화상 센서에 고속 DSP(Digital Signal Process)를 사용하여 영상 처리 기법인 이차원 보간법 기술을 이용하여 아크플래시에 의해 발생되는 열 특성을 검출하고 검출된 데이터를 전송하여 전기화재사고를 미연에 방지할 수 있는 장치 개발을 위한 기초 특성 연구를 수행하였다.

• Journal of Institute of Control, Robotics and Systems
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• v.4 no.4
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• pp.506-516
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• 1998

In this paper, an algorithm is proposed to detect the malfunction of plasma-etching characteristics using EPD signal trajectories. EPD signal trajectories offer many information on plasma-etching process state, so they must be considered as the most important data sets to predict the wafer states in plasma-etching process. A recent work has shown that EPD signal trajectories were successfully incorporated into process modeling through critical parameter extraction, but this method consumes much effort and time. So Principal component analysis(PCA) can be applied. PCA is the linear transformation algorithm which converts correlated high-dimensional data sets to uncorrelated low-dimensional data sets. Based on this reason neural network model can improve its performance and convergence speed when it uses the features which are extracted from raw EPD signals by PCA. Wafer-state variables, Critical Dimension(CD) and uniformity can be estimated by simulation using neural network model into which EPD signals are incorporated. After CD and uniformity values are predicted, proposed algorithm determines whether malfunction values are produced or not. If malfunction values arise, the etching process is stopped immediately. As a result, through simulation, we can keep the abnormal state of etching process from propagating into the next run. All the procedures of this algorithm can be performed on-line, i.e. wafer to wafer.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.17 no.8
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• pp.1784-1789
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• 2013

In this paper, parallel orthogonal matching pursuit (POMP) is proposed to supplement the orthogonal matching pursuit (OMP) which has been widely used as a greedy algorithm for sparse signal recovery. The process of POMP is simple but effective: (1) multiple indexes maximally correlated with the observation vector are chosen at the firest iteration, (2) the conventional OMP process is carried out in parallel for each selected index, (3) the index set which yields the minimum residual is selected for reconstructing the original sparse signal. Empirical simulations show that POMP outperforms than the existing sparse signal recovery algorithms in terms of exact recovery ratio (ERR) for sparse pattern and mean-squared error (MSE) between the estimated signal and the original signal.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.4 no.1
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• pp.45-61
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• 2010

In the communication channel, the received signal is affected by many factors that can cause errors. These effects mean that received signal strength (RSS) based methods incur more errors in measuring distance and consequently result in low precision in the location detection process. As one of the approaches to overcome these problems, we propose using direction calibration to improve the performance of the RSS-based method for distance measurement, and sequentially a weighted least squares (WLS) method using reliability factors in conjunction with a conventional RSS weighting matrix is proposed to solve an over-determined localization process. The proposed scheme focuses on the features of the RSS method to improve the performance, and these effects are proved by the simulation results.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.7 no.2
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• pp.216-233
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• 2013

Conventional optimization designs of wireless networks mainly focus on spectral efficiency (SE) as a performance metric. However, as diverse media services are emerging, a green wireless network, which not only meets the quality of experience (QoE) requirements for users and also improves energy efficiency (EE), is the most appropriate solution. In this paper, we firstly propose the unit QoE per Watt, which is termed QoE efficiency (QEE), as a user-oriented metric to evaluate EE for wireless networks. We then analyze which is the kind of wireless resource given priority to use under different scenarios to obtain an acceptable QEE. Particularly, power, delay and data-rate related to QoE are separately addressed for several typical services, such as file download, video stream and web browsing services. Next, the fundamental tradeoffs are investigated between QEE and SE for wireless networks. Our analytical results are helpful for network design and optimization to strike a good balance between the users perceived QoE and energy consumption.

• Journal of the Semiconductor & Display Technology
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• v.20 no.1
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• pp.18-24
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• 2021

The current settlement and distribution used in theme, background and signal music market other than conventional music is being carried out with either the comprehensive settlement method or the measured meter-rate settlement method in the payment process of collected user fees and compensation depending on the use-permission types. In this settlement and distribution process, however, the reliability issues are often being raised because of the difficulty of tracking rights due to changes in music source rights management information, etc, and the opaque settlement and distribution method itself. This paper proposes a new settlement and distribution platform using a blockchain for the reliable collection and distribution of copyright fees among music user group, monitoring organization group, trust organization group and copyright holders, based on the monitoring information of the theme, background and signal music usage. This platform also provides the transparency in settlement and distribution process among stakeholders through smart contract system.