• Journal of Korean Society of Industrial and Systems Engineering
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• v.43 no.2
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• pp.48-55
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• 2020

Recently, a study of prognosis and health management (PHM) was conducted to diagnose failure and predict the life of air craft engine parts using sensor data. PHM is a framework that provides individualized solutions for managing system health. This study predicted the remaining useful life (RUL) of aeroengine using degradation data collected by sensors provided by the IEEE 2008 PHM Conference Challenge. There are 218 engine sensor data that has initial wear and production deviations. It was difficult to determine the characteristics of the engine parts since the system and domain-specific information was not provided. Each engine has a different cycle, making it difficult to use time series models. Therefore, this analysis was performed using machine learning algorithms rather than statistical time series models. The machine learning algorithms used were a random forest, gradient boost tree analysis and XG boost. A sliding window was applied to develop RUL predictions. We compared model performance before and after applying the sliding window, and proposed a data preprocessing method to develop RUL predictions. The model was evaluated by R-square scores and root mean squares error (RMSE). It was shown that the XG boost model of the random split method using the sliding window preprocessing approach has the best predictive performance.

• Journal of Korea Multimedia Society
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• v.24 no.1
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• pp.30-39
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• 2021

Research in the field of health lighting has continued to advance to reproduce the color temperature of natural light which periodically changes. However, most of this research could only reproduce a uniform circadian color temperature of natural light, therefore failing to realize the characteristics of the circadian cycle of color temperature difference by latitude and longitude. To reproduce the color temperature of natural light on which the characteristics of a region are reflected, the collection technology of real-time characteristics of natural light is needed. If the color temperatures which are not within a periodical pattern due to climate changes, etc., are measured, it will be difficult to judge the occurrence (presence) of the anomalies and to reproduce the circadian cycle of the color temperature of natural light. Therefore, this study proposes an algorithm for judging the anomalies in real time based on the sliding window to reproduce the color temperature of natural light. First, the natural light characteristics DB collected through the on-site measurement were analyzed, the differential values at a one-minute interval were calculated and examined, and then representative color temperature circadian patterns by solar terms were drawn. The anomalies were then detected by the application of the sliding window that calculated the deviation of the color temperature for the measured color temperature data set, which was collected through RGB sensors, while moving along the time sequence. In addition, the presence of anomalies was verified through the comparison study between the detection results and the representative circadian cycle of the color temperature by solar term. The judgment method for the anomalies from the measured color temperature of natural light was proposed for the first time, confirming that the proposed method was capable of detecting the anomalies with an average accuracy of 94.6%.

• KIEAE Journal
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• v.17 no.3
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• pp.15-21
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• 2017

Purpose: "Building energy design standard" is used to limit the thermal transmittance of building in Korea. However, it only covers the insulation standard for each appropriate elements of a building, not the thermal performance of Junction thermal bridge of windows and doors installed in wall. Therefore in this study, we have evaluated the thermal performance of Junction thermal bridge depending on installation method and position of windows and provide it as design data. Method: We analyzed heat transfer of 4-Track sliding window and tilt & turn triple glazed window that are placed in the first class category on window energy efficiency rating using Window 7.4 and Therm 7.4. Result : First, linear thermal transmittance of 4-Track sliding window differs by 2.2 times or more depending of installation method and location. It is higher than the linear thermal transmittance, 0.01W/mK, proposed by Passivhaus. Second, linear thermal transmittance of Tilt & turn triple glazed window differs by 7.7 times or more depending of installation method and location. The average linear thermal transmittance was less than 0.01W /mK when windows were installed on the internal wall insulation by the fixed hardware attachment method. Third, the thermal losses of a window caused by a junction thermal bridge are inversely proportional to the window area and converge gradually as the area increased.

• The Journal of Society for e-Business Studies
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• v.23 no.3
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• pp.225-237
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• 2018

The demand for processing large data streams is growing rapidly as the generation and processing of large volumes of data become more popular. A variety of large data processing technologies are being developed to suit the increasing demand. One of the technologies that researchers have particularly observed is the data stream clustering with sliding windows. Data stream clustering with sliding windows may create a new set of clusters whenever the window moves. Previous data stream clustering techniques with sliding windows exploit the coresets, also known as group features that summarize the data. In this paper, we present some reformable elements of a group-feature based algorithm, and propose our algorithm that modified the clustering algorithm of the original one. We conduct a performance comparison between two algorithms by using different parameter values. Finally, we provide some guideline for the selective use of those algorithms with regard to the parameter values and their impacts on the performance.

• Journal of the Korea Institute of Military Science and Technology
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• v.3 no.1
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• pp.116-126
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• 2000

Turbo codes are the most exciting and potentially important development in coding theory in recent years. They were introduced in 1993 by Berrou, Glavieux and $Thitimajshima,({(1)}$ and claimed to achieve near Shannon-limit error correction performance with relatively simple component codes and large interleavers. A required Eb/N0 of 0.7㏈ was reported for BER of $10^{-5}$ and code rate of $l/2.^{(1)}$ However, to implement the turbo code system, there are various important details that are necessary to reproduce these results such as AGC gain control, optimal wordlength determination, and metric rescaling. Further, the memory required to implement MAP-based turbo decoder is relatively considerable. In this paper, we confirmed the accuracy of these claims by computer simulation considering these points, and presented a optimal wordlength for Turbo code design. First, based on the analysis and simulation of the turbo decoder, we determined an optimal wordlength of Turbo decoder. Second, we suggested the MAP decoding algorithm based on sliding-window method which reduces the system memory significantly. By computer simulation, we could demonstrate that the suggested fixed-point Turbo decoder operates well with negligible performance loss.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.48 no.7
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• pp.9-16
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• 2011

In this paper, various kinds of high throughput turbo decoding schemes are introduced, and a new turbo decoding scheme using the advantages of each scheme is proposed. The proposed scheme uses the decoding structure of double flow scheme, sliding window scheme and shuffled turbo decoding scheme. Simulation results show that the proposed scheme offers a BER performance equivalent to those of existing turbo decoding schemes with less clock cycles. We also show that the required memory can be reduced by choosing proper size of sliding window. Consequently, we can design a high throughput turbo decoder requiring low power and low area.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.4 no.2
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• pp.103-110
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• 2011

It is necessary to accurate and efficient management for measured digital data from sensors in u-health system. It is not efficient that sensor network process input stream data of mass storage stored in database the same time. We propose to improve the processing performance of multidimensional stream data continuous incoming from multiple sensor. We propose process query based on sliding window for efficient input stream and found multiple query plan to Mjoin method and we reduce stored data using backpropagation algorithm. As a result, we obtained to efficient result about 18.3% reduction rate of database using 14,324 data sets.

• Journal of Communications and Networks
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• v.9 no.3
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• pp.330-341
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• 2007

This work analyzes the performance of the parallel packet switch (PPS) with a sliding window (SW) method. The PPS involves numerous packet switches that operate independently and in parallel. The conventional PPS dispatch algorithm adopts a round robin (RR) method. The class of PPS is characterized by deployment of parallel low-speed switches whose all memory buffers run more slowly than the external line rate. In this work, a novel SW packet switching method for PPS, called SW-PPS, is proposed. The SW-PPS employs memory space more effectively than the existing PPS using RR algorithm. Under identical Bernoulli and bursty data traffic, the SW-PPS provided significantly improved performance when compared to PPS with RR method. Moreover, this investigation presents a novel mathematical analytical model to evaluate the performance of the PPS using RR and SW method. Under various operating conditions, our proposed model and analysis successfully exhibit these performance characteristics including throughput, cell delay, and cell drop rate.

• Journal of Power Electronics
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• v.10 no.4
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• pp.412-418
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• 2010

This paper proposes a new algorithm to generate a reference signal for an active power filter using a sliding-window FFT operation to improve the steady-state performance of the active power filter. In the proposed algorithm the sliding-window FFT operation is applied to the load current to generate the reference value for the compensating current. The magnitude and phase-angle for each order of harmonics are respectively averaged for 14 periods. Furthermore, the phase-angle delay for each order of harmonics passing through the controller is corrected in advance to improve the compensation performance. The steady-state and transient performance of the proposed algorithm was verified through computer simulations and experimental work with a hardware prototype. A single-phase active power filter with the proposed algorithm can offer a reduction in THD from 75% to 4% when it is applied to a non-linear load composed of a diode bridge and a RC circuit. The active power filter with the proposed reference generation method shows accurate harmonic compensation performance compared with previously developed methods, in which the THD of source current is higher than 5%.

• Journal of Computing Science and Engineering
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• v.7 no.4
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• pp.220-230
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• 2013

In recent years, progress in hardware technology has resulted in the possibility of monitoring many events in real time. The volume of incoming data may be so large, that monitoring all individual data might be intractable. Revisiting any particular record can also be impossible in this environment. Therefore, many database schemes, such as aggregation, join, frequent pattern mining, and indexing, become more challenging in this context. This paper surveys the previous efforts to resolve these issues in processing data streams. The emphasis is on specifying and processing sliding window queries, which are supported in many stream processing engines. We also review the related work on stream query processing, including synopsis structures, plan sharing, operator scheduling, load shedding, and disorder control.