• Journal of Information Technology Services
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• v.14 no.3
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• pp.85-97
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• 2015

The information and communications construction business has the characteristics of an infrastructure industry and responsibility for the construction and maintenance of all ICT infrastructures. With the recent proliferation of the smart convergence of various industries based on ICT infrastructure, the role of the information and communications construction business has been highlighted to accommodate the convergence and implementation environment in construction and medical industries. Therefore, this paper seeks policy measures to establish the new role of the information and communications business under the rapidly developing smart convergence environment and the priorities of policy measures to strengthen the capability of the information and communications business using a quantitative model. The analysis result suggests that the difference in importance of each policy measure should be considered in order to execute effectively the policy of promoting the information and communications construction business. Given the constraint of limited budget, policy priorities include the development of new markets, and establishment of incentive for new technology. This study is significant for its theoretical contribution, being the first quantitative approach to policy priorities for the promotion of information and communications construction business under the smart convertgence environment.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.2065-2069
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• 2004

This paper presents an adaptive equalizer using finite impulse response (FIR) filter and least-mean square (LMS) algorithm. Herein, the variable step-size technique (VSLMS) for compensating the amplitude of chrominance signal is utilized. The proposed equalizer can be enhanced and compressed the chrominance signal at color subcarrier. The LMS algorithm employed in simplicity structure but gives slow convergence speed. Thus, the variable step-size is very attractive algorithm due to its computational efficiencies and the speed of convergence is improved. In addition, experimental results are carried out by using the modulated 20T sine squared test signal. It is shown here that the adaptive equalizer can be equalized the amplitude chrominance distortion in color television transmission without relative delay distortion.

• Convergence Security Journal
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• v.16 no.6_2
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• pp.23-32
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• 2016

Rapid advances in information and communications technology are new challenges and also opportunities for the police. For the purpose of identifying its implications, this study reviews utilization cases of information and communications technology in the field of public security in South Korea and other countries. As theoretical basis for utilization of information and communications technology, this study introduces intelligence-led policing, predictive policing and evidence-based policing. Also, utilization of big-data based crime analysis and crime prediction technology, as well as advancement of information and communications system and command and control technology of the police, are discussed. Based on the identified implications in this study, the following proposals are made. They are (1) procuring basic data, (2) creating an integrated database, (3) increasing utilization of policy decision-makers, (4) exchange and cooperation between related institutions, (5) training professional analyzers, (6) establishing legal basis and practical guidelines for an integrated database.

• Proceedings of the Korea Information Processing Society Conference
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• 2003.11a
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• pp.305-308
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• 2003

본 논문은 토너먼트 선택을 사용한 Deceptive Problem에서 최적 해(optimum)를 찾으면서 수렴(Convergence)속도를 향상시키기 위한 최적의 조건을 찾고자 한다. 이를 위해 적합도가 높은 염색체(cromosome)를 다음 세대로 전달하면서 동시에 적합도가 낮은 염색체에 대해서도 적정 수준 전달되게 하였다. 또한 기존의 여러 선택기법 중 가장 일반적으로 사용되는 토너먼트 선택 기법의 문제점을 고찰하고, 제안 방법으로 최적도 및 수렴속도를 모의 실험을 통해 비교 및 분석한다. 실험 결과로부터 제안 방법에 대한 수렴속도의 경향을 고찰하였다.

• Journal of Institute of Control, Robotics and Systems
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• v.9 no.11
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• pp.917-924
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• 2003

Recurrent neural networks have been successfully applied to communications channel equalization. Major disadvantages of gradient-based learning algorithms commonly employed to train recurrent neural networks are slow convergence rates and long training sequences required for satisfactory performance. In a high-speed communications system, fast convergence speed and short training symbols are essential. We propose decision feedback equalizers using a recurrent neural network trained with Kalman filtering algorithms. The main features of the proposed recurrent neural equalizers, utilizing extended Kalman filter (EKF) and unscented Kalman filter (UKF), are fast convergence rates and good performance using relatively short training symbols. Experimental results for two time-varying channels are presented to evaluate the performance of the proposed approaches over a conventional recurrent neural equalizer.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.445-445
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• 2000

This paper proposes the MIMO indirect adaptive fuzzy controller to control the two-link manipulators. The input-output linearization technique, equivalent control input plus integral term, augmented error model and recursive least square adaptive law are used fer the controller. The linear type of fuzzifier-defuzzifier fuzzy logic system used for nonlinear function makes easy to farm the error model and able to follow the adaptive system approach. Such that control approach, the control system is not required joint speed and accerelation measurement and easy to implement and tune. The simulation results showed that the proposed controller has good control performance, stability, very small tracking error, decoupling, fast convergence, robust to parameter variation and load.

• Journal of Communications and Networks
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• v.18 no.3
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• pp.411-419
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• 2016

This article investigates the problem of distributed channel selection in opportunistic spectrum access networks from a perspective of interference minimization. The traditional physical (PHY)-layer interference model is for information theoretic analysis. When practical multiple access mechanisms are considered, the recently developed binary medium access control (MAC)-layer interference model in the previous work is more useful, in which the experienced interference of a user is defined as the number of competing users. However, the binary model is not accurate in mathematics analysis with poor achievable performance. Therefore, we propose a real-valued one called stochastic MAC-layer interference model, where the utility of a player is defined as a function of the aggregate weight of the stochastic interference of competing neighbors. Then, the distributed channel selection problem in the stochastic MAC-layer interference model is formulated as a weighted stochastic MAC-layer interference minimization game and we proved that the game is an exact potential game which exists one pure strategy Nash equilibrium point at least. By using the proposed stochastic learning-automata based uncoupled algorithm with heterogeneous learning parameter (SLA-H), we can achieve suboptimal convergence averagely and this result can be verified in the simulation. Moreover, the simulated results also prove that the proposed stochastic model can achieve higher throughput performance and faster convergence behavior than the binary one.

• Communications of the Korean Institute of Information Scientists and Engineers
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• v.28 no.7
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• pp.44-51
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• 2010

• Communications of the Korean Institute of Information Scientists and Engineers
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• v.31 no.3
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• pp.10-21
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• 2013

• Communications of the Korean Institute of Information Scientists and Engineers
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• v.31 no.2
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• pp.54-62
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• 2013