• Journal of the Institute of Convergence Signal Processing
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• v.13 no.2
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• pp.99-105
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• 2012

The focus of this paper is a proposal for a computationally efficient dynamic subcarrier allocation (DSA) algorithm for orthogonal frequency-division multiple access (OFDMA) systems. The proposed DSA algorithm considerably reduces the computational complexity and the amount of channel quality information (CQI) compared to amplitude craving greedy (ACG) algorithms, which use full CQI. At the same time, the performance of the proposed algorithm closely appear to ACG algorithms. Moreover, the authors present a new bandwidth-assignment algorithm produced by modifying bandwidth assignment based on the signal-to-noise ratio (BABS). This modified BABS algorithm enables the proposed DSA algorithm to produce a strong outage performance gain over the conventional scheme.

• Journal of the Regional Association of Architectural Institute of Korea
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• v.20 no.6
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• pp.113-119
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• 2018

Occupancy-based heating control is effective in reducing heating energy by preventing unnecessary heating during unoccupied period. Various technologies on detecting human occupancy have been developed using complicated machine learning algorithm and stochastic methodologies. This study aims at deriving low-cost and simple algorithm of occupancy inference that can be implemented to residential buildings. The core concept of the algorithm is to combine the occupancy probabilities based on indoor CO2 concentration and PIR(passive infrared) signals. The probability was estimated by applying different levels of decrement ratio depending on CO2 concentration change rate and aggregated PIR signals. The developed algorithm was validated by comparing the inference results with the occupancy schedule in a real residential building. The results showed that the inference algorithm can achieve the accuracy of 75~99%, which would be successfully implemented to the control of residential heating systems.

• ETRI Journal
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• v.28 no.2
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• pp.155-161
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• 2006

In this paper, we introduce an escalator (ESC) algorithm based on the least squares (LS) criterion. The proposed algorithm is relatively insensitive to the eigenvalue spread ratio (ESR) of an input signal and has a faster convergence speed than the conventional ESC algorithms. This algorithm exploits the fast adaptation ability of least squares methods and the orthogonalization property of the ESC structure. From the simulation results, the proposed algorithm shows superior convergence performance.

• ETRI Journal
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• v.33 no.3
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• pp.401-406
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• 2011

This paper presents a fast block-matching algorithm based on the normalized cross-correlation, where the elimination order is determined based on the gradient magnitudes of subblocks in the current macroblock. Multilevel Cauchy-Schwartz inequality is derived to skip unnecessary block-matching calculations in the proposed algorithm. Also, additional complexity reduction is achieved re-using the normalized cross correlation values for the spatially neighboring macroblock because the search areas of adjacent macroblocks are overlapped. Simulation results show that the proposed algorithm can improve the speed-up ratio up to about 3 times in comparison with the existing algorithm.

• Journal of electromagnetic engineering and science
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• v.4 no.2
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• pp.93-96
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• 2004

In this paper we introduce a new escalator(ESC) structure-based adaptation algorithm. The proposed algorithm is independent of eigenvalues spread ratio(ESR) of channel and has faster convergence speed than that of the conventional ESC algorithms. This algorithm combines the fast adaptation ability of least square methods and the orthogonalization property of the ESC structure. From the simulation results the proposed algorithm shows superior convergence speed and no slowing down of convergence speed when we increase the ESR of the channel.

• Proceedings of the KSPS conference
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• 2003.05a
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• pp.137-140
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• 2003

In this paper, we propose a robust endpoint detection algorithm for speaker verification. Proposed algorithm uses energy and cepstral distance parameters, and it replaces the detected endpoints with endpoints of voiced speech, when the estimated signal-to-noise ratio (SNR) is low. Experimental results show that proposed algorithm is superior to energy-based endpoint detection algorithm.

• The Korean Journal of Community Living Science
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• v.27 no.2
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• pp.281-294
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• 2016

This study was conducted to promote consumer interest in Geothermal Heat Pump (Ground Source Heat Pump, GSHP) and district heating and cooling (District Heating & Cooling, DHC) systems, which are competing with each other in the heating and cooling field. Considering not only the required cost data of energy itself, but also external influence factors, the optimal mix ratio of these two energy systems was studied as follows. The quantitative data of the two energy systems was entered into a database and the non-quantitative factors of external influence were applied in the form of coefficients. Considering both of these factors, the optimal mix ratio of GSHP and DHC systems and minimum Life Cycle Cost (LCC) were obtained using an algorithm model design. The Optimal Energy Mix of GSHP & DHC (OEMGD) algorithm was developed using a software program (Octave 4.0). The numerical result was able to reflect the variety of external influence factors through the OEMGD algorithm. The OEMGD model found that the DHC system is more economical than the GSHP system and was able to represent the optimal energy mix ratio and LCC of mixed energy systems according to changes in the external influences. The OEMGD algorithm could be of help to improve the consumers' experience and rationalize their energy usage.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.16 no.10
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• pp.2303-2308
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• 2012

In this paper, we deal with the problem of scheduling parallel tasks with deadlines. Parallel tasks can be simultaneously executed on various machines and specially, we consider the malleable tasks, that is, the tasks whose execution time is given by a function of the number of machines on which they are executed. The goal of the problem is to maximize the throughput of tasks completed within their deadlines. This problem is well-known as NP-hard problem. Thus we will find an approximation algorithm, and its performance is compared with that of the optimal algorithm and analyzed by finding the approximation ratio. In particular, the algorithm has more resources, that is, more machines, than the optimal algorithm. This is called the resource augmentation analysis. We propose an algorithm to guarantee the approximation ratio of 3.67 using 1.5 times machines.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.37 no.6
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• pp.60-69
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• 2000

In this paper we propose a new two-color signal processing algorithm for efficient target tracking under complicated condition including interfernces such as background noises and countermeasures. For the efficient target tracking, we adopt two detection bands, and define the ratio between two band signals which represents the spectral distribution characteristics of a target or interference. The proposed algorithm detects the ratio of interference, and extracts only the target signal from the target and the interference mixed signal by using it. To evaluate the performance of the proposed algorithm, we apply it to a rosette tracker and perform various simulations. The simulation results show that the proposed algorithm extracts the target signal from the mixed signal well. The proposed algorithm is also ready to be applied to a real system since it is simple and adaptive for environment change.

• Journal of the Optical Society of Korea
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• v.15 no.3
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• pp.209-215
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• 2011

A new iterative algorithm is developed to estimate LIDAR ratio for a thin cirrus cloud over an aerosol layer. First, the thin cirrus cloud is screened out and replaced by a modeled LIDAR signal and the extinction coefficients of the aerosol layer are derived using the Fernald backward method. These aerosol coefficients are referred as the "actual values". Second, the original LIDAR signal which includes the thin cirrus cloud is also inverted by the Fernald backward method down to the aerosol layer but using different LIDAR ratio for the thin cirrus cloud. Depending on the different assumptions about the LIDAR ratio of the thin cirrus cloud, different sets of aerosol extinction can be derived. The "actual values" which are found in the first step can be used to constrain this iterative progress and the correct LIDAR ratio of the thin cirrus cloud can be found. The detailed description of this method and retrieval examples are given in the paper. The cases compared with other methods are presented and the statistical result is also shown and agrees well with other studies.