• Tunnel and Underground Space
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• v.24 no.6
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• pp.430-439
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• 2014

This study developed a simulation program for truck-loader haulage systems in an underground mine. A limestone underground mine in Korea was selected as a study area and investigated to design the simulation algorithm for truck-loader haulage systems. GPSS/H simulation language was utilized to develop the simulation program. Simulations were conducted to analyze the optimal number of haulage trucks dispatched in the 540 ML loading point by using the developed program. The simulation results showed that 8 trucks can maximize the daily production (2,076 ton). The real production (1,850 ton/day) of limestone ores was very similar to the simulated one (1,850.35 ton/day) when considers 7 trucks dispatched in the 540 ML loading point. In addition, average waiting time at loader were similar (waiting time by time study : 1.39 min, simulated waiting time : 1.35 min).

• The Journal of Korean Institute of Communications and Information Sciences
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• v.34 no.6C
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• pp.642-648
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• 2009

In this paper, we use SA (Seysen's Algorithm) instead of LLL (Lenstra-Lenstra-Lovasz) to perform LRA (Lattice Reduction-Aided) detection. By using SA, the complexity of lattice reduction is reduced and the detection performance is improved Although the performance is improved using SA, there still exists a gap in the performance between SA-LRA and ML detection. To reduce the performance difference, we apply list of candidates scheme to SA-LRA. The list of candidates scheme finds a list of candidates. Then, the candidate with the smallest squared Euclidean distance is considered as the estimate of the transmitted signal. Simulation results show that the SA-LRA detection learn to quasi-ML performance. Moreover, the efficiency of the SA is shown to highly improve the channel matrix conditionality.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.40 no.6
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• pp.981-989
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• 2015

In a log likelihood ratio(LLR) calculation of the detected symbol, multiple-input multiple-output(MIMO) system applying an optimal or suboptimal algorithm such as a maximum likelihood(ML) detection, sphere decoding(SD), and QR decomposition with M-algorithm Maximum Likelihood Detection(QRM-MLD) suffers from exponential complexity growth with number of spatial streams and modulation order. In this paper, we propose a LLR calculation method with very low complexity in the QRM-MLD based symbol detector for a high order modulation based $N_T{\times}N_R$ MIMO system. It is able to approach bit error rate(BER) performance of full maximum likelihood detector to within 1 dB. We also analyze the BER performance through computer simulation to verify the validity of the proposed method.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.48 no.3
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• pp.13-18
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• 2011

Sphere Decoding (SD) is a decoding technique able to achieve the Maximum Likelihood (ML) performance in fading environments; nevertheless, the main disadvantage of this technique is its high complexity, especially in poor channel conditions. In this paper, we present an adaptive hybrid algorithm which reduces the conventional Sphere Decoder's complexity and keeps the ML performance. The system called Adaptive OSIC-SD modifies its operation based on Signal to Noise Ratio (SNR) information and achieves an optimal performance in terms of Bit Error Rate (BER) and complexity. Through simulations, we probe that the proposed system maintains almost the same bit error rate performance of the conventional SD, and exhibits a lower, quasi-constant complexity.

• Proceedings of the IEEK Conference
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• 2003.11a
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• pp.493-496
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• 2003

Recently, Ryu et al. proposed a multiple target DOA tracking algorithm, which has good features that it has no data association problem and simple structure. But its performance is seriously degraded in the low signal-to-noise ratio. In this paper, a measurement fusion method is presented based on ML(Maximum Likelihood), and the new DOA tracking algorithm is proposed by incorporating the presented fusion method into Ryu's algorithm. The proposed algorithm has a better tracking performance than that of Ryu's algorithm, and it sustains the good features of Ryu's algorithm.

• Proceedings of the IEEK Conference
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• 1999.11a
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• pp.569-572
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• 1999

In this paper we present a color image segmentation algorithm based on statistical models. A novel deterministic annealing Expectation Maximization(EM) formula is derived to estimate the parameters of the Gaussian Mixture Model(GMM) which represents the multi-colored objects statistically. The experimental results show that the proposed deterministic annealing EM is a global optimal solution for the ML parameter estimation and the image field is segmented efficiently by using the parameter estimates.

• Proceedings of the Korean Society of Computer Information Conference
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• 2023.01a
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• pp.205-208
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• 2023

양식장에서 최적의 생육환경을 유지할 수 있는 제어시스템 개발을 위해 수질에 영향을 미치는 요인들의 상관관계 분석을 위한 머신러닝 모델을 개발하고자 한다. 데이터간의 상관관계 분석 및 예측모델 생성을 위해 알고리즘의 결정계수와 MSE, RMSE 등의 수치를 통하여 데이터의 적합성을 검증하고자 한다.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.37 no.6C
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• pp.476-482
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• 2012

In this paper, we analyze and compare several co-channel interference mitigation algorithms for WBAN application in 2.4 GHz ISM frequency bands. ML (Maximum Likelihood), OC (Optimal Combining) and MMSE (Minimum Mean Square Error) has been considered for the possible techniques for interference cancellation in view of the trade off between the performance and the complexity of implementation. Based on the channel model of IEEE 802.15.6 standard, simulation results show that ML and OC attains the lower BER performance than that of MMSE if we assume the perfect channel estimation. But, ML and OC have the additional requirement of implementation for his own and other users's channel estimation process, hence, besides the BER performance, the complexity of implementation and the sensitivity to channel estimation error should be considered since it requires the simple and small sized equipment for WBAN system application. In addition, the gap of detection BER performance between ML, OC and MMSE is much decreased under the imperfect channel estimation if we adopt real channel estimation process, therefore, in order to apply to WBAN system, the trade off between the BER performance and complexity of implemetation should be seriously considered to decide the best co-channel interference cancellation for WBAN system application.

• Proceedings of the Korean Information Science Society Conference
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• 1999.10c
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• pp.566-568
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• 1999

현재는 데이터 통신망이 음성 통신망을 흡수하는 단계이다. 데이터 망이 기존의 음성 망이 가지는 영역을 포함하면서 광범위하게 활용되면서 앞으로 그 범위는 더욱 넓어질 것이다. 현재 급속히 팽창하고 있는 인터넷도 데이터 통신망이 진일보 하는데 커다란 역할을 하고 있다. 기존의 연결 지향형 방식의 패킷 통신과 달리 인터넷이 주로 비연결형 방식의 IP를 사용하기 때문에 새로운 개념의 데이터 전송이 요구되고 있다. 이러한 요구들로 인해 ATM, Gigabit Router, MPLS 등이 출현하게 되었고 현재는 MPLS가 가장 적합한 해결책으로 제시되고 있다. IETF 역시 이러한 MLS에 대한 표준안을 준비하고 있다. 이곳에서는 많은 장점을 가지는 MPLS(MultiProtocol Label Switch)망에서의 명령어 그리고 타이머를 가지는 레이블 예약방식의 경로 재설정 알고리즘을 제시한다. 방법은 경로 재설정시간을 단축하고 트래픽의 적절한 분배를 통하여 네트워크의 부하를 줄인다.

• Proceedings of the Korea Information Processing Society Conference
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• 2020.11a
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• pp.800-803
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• 2020

실 환경 로봇에 강화학습을 적용하기 위해서는 가상 환경 시뮬레이션이 필요하다. 그러나 가상 환경을 구축하는 플랫폼은 모두 다르고, 학습 알고리즘의 구현에 따른 성능 편차가 크다는 문제점이 있다. 또한 학습을 적용하고자 하는 대상이 실세계의 하드웨어 사양이 낮은 스마트 로봇인 경우, 계산량이 많은 학습 알고리즘을 적용하기는 쉽지 않다. 본 연구는 해당 문제를 해결하기 위해 Unity3D에서 제공하는 강화학습 프레임인 ML-Agents 모듈을 사용하여 실 환경의 저사양 스마트 로봇에 장애물을 회피하고 탐색하는 모델의 강화학습을 적용해본다. 본 연구의 유의점은 가상 환경과 실 환경의 유사함과 일정량의 노이즈 발생 처리이다. 로봇의 간단한 행동은 원만하게 학습 및 적용가능함을 확인할 수 있었다.