• Journal of Electrical Engineering and Technology
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• 제9권1호
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• pp.352-362
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• 2014

In this paper, a fuzzy logic controller is designed for a DC motor which can be used for navigation control of mobile robots. These mobile robots can be used for agricultural, defense and assorted social applications. The robots used in these fields can reduce manpower, save human life and can be operated using remote control from a distant place. The developed fuzzy logic controller is used to control navigation speed and steering angle according to the desired reference position. Differential drive is used to control the steering angle and the speed of the robot. Two DC motors are connected with the rear wheels of the robot. They are controlled by a fuzzy logic controller to offer accurate steering angle and the driving speed of the robot. Its location is monitored using GPS (Global Positioning System) on a real time basis. IR sensors in the robot detect obstacles around the robot. The designed fuzzy logic controller has been implemented in a robot, which depicts that the robot could avoid obstacle as well as perform its operation efficiently with remote online control.

• International Journal of Fuzzy Logic and Intelligent Systems
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• 제10권2호
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• pp.101-106
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• 2010

We propose an approach to estimate the real-time moving trajectory of an object in this paper. The object's position is obtained from the image data of a CCD camera, while a state estimator predicts the linear and angular velocities of the moving object. To overcome the uncertainties and noises residing in the input data, a Extended Kalman Filter(EKF) and neural networks are utilized cooperatively. Since the EKF needs to approximate a nonlinear system into a linear model in order to estimate the states, there still exist errors as well as uncertainties. To resolve this problem, in this approach the Kohonen networks, which have a high adaptability to the memory of the inputoutput relationship, are utilized for the nonlinear region. In addition to this, the Kohonen network, as a sort of neural network, can effectively adapt to the dynamic variations and become robust against noises. This approach is derived from the observation that the Kohonen network is a type of self-organized map and is spatially oriented, which makes it suitable for determining the trajectories of moving objects. The superiority of the proposed algorithm compared with the EKF is demonstrated through real experiments.

• 한국자동차공학회논문집
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• 제13권2호
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• pp.44-51
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• 2005

According to the increasing concern on the global environment, the $CO_2$ regulation has been discussed including automobile emission regulation. In order to cope with this rapid changing circumstances, the development of an ultra low emission and super fuel economy automobile is essential. Direct injection LPG engine is the one of the possible future engine to maximize the engine efficiency. This experimental study for the development of direct injection LPG engine technology is promoted with two parts; spray characteristics of high pressure swirl injector, and performance characteristics of direct injection LPG engine. Engine characteristics according to the fuel was analyzed in order to establish stratified combustion technology for LPG engine by using the DISI engine. In the engine experiment, control system was manufactured for gasoline and LPG fuel. The engine was modified 2,000 cc GDI engine (fuel supply device, fuel injection device). Through this experiment, engine operating condition, engine speed and spark timing (MBT), fuel injection position, and fuel rate were investigated.

• 산업경영시스템학회지
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• 제41권3호
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• pp.162-169
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• 2018

Net neutrality, which has not been a problem, has recently become a problem for ISPs (Internet Service Providers), and their complaints have been paid by domestic platform companies, but overseas global IT companies such as Google and YouTube, generate huge revenues from domestic markets. In this situation, domestic IT companies claim that it is natural to impose more expensive charges or restrict speed on users who generate huge traffic. On the other side, however, the telecommunication network has become an essential public good that is essential to our everyday life, and because it has been given a monopoly position by a private company to efficiently respond to the explosive demand for telecommunication services, It is necessary to provide equal and universal service and fulfill public duty. In this paper, we deal with the network neutrality problem, focusing on the price elasticity between the CP (Contents Provider) and the ISP, rather than the user who is one side of the two-sided market for the already saturated satellites communication market. We present a game model that determines the optimal price for each platform by Nash equilibrium and analyze how the net neutrality affects CP according to the change of exogenous variables through the proposed game model.

• 한국전자거래학회지
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• 제12권2호
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• pp.1-16
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• 2007

최근에 이동 통신 기술의 발달과 모바일 단말기의 급속한 확산에 맞추어 사용자의 위치정보를 바탕으로 사용자에게 여러 가지 서비스를 제공하는 위치기반 서비스(LBS, Location Based Service)에 대한 연구가 활발하게 진행되고 있다. 모바일 기기를 이용한 이런 서비스 소비과정에서 사용자 주변환경의 변화는 상대적으로 빈번하며 이런 상황의 변화는 서비스의 진행에 직접 혹은 간접적으로 영향을 주게 된다. 지능화된 사용자 중심의 서비스의 실현을 위하여 모바일 디바이스의 컨텍스트를 인식하는 기술과 수집된 컨텍스트를 응용프로그램에 적용하는 방법에 대한 연구가 필요하다. 본 논문에서는 모바일 환경에서 GIS 웹 서비스에 필요한 사용자 컨텍스트 정보의 분류와 구조를 분석하였다. 또한 사용자 디바이스의 컨텍스트 정보를 자동 처리하는 액티브프록시를 제안하였다.

• 전자공학회논문지S
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• 제35S권4호
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• pp.67-75
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• 1998

In general, Evoluationary Algorithm(EAs) are refered to as methods of population-based optimization. And EAs are considered as very efficient methods of optimal sytem design because they can provice much opportunity for obtaining the global optimal solution. This paper presents a co-evolution scheme of artifical neural networks, which has two different, still cooperatively working, populations, called as a host popuation and a parasite population, respectively. Using the conventional generatic algorithm the host population is evolved in the given environment, and the parastie population composed of schemata is evolved to find useful schema for the host population. the structure of artificial neural network is a diagonal recurrent neural netork which has self-feedback loops only in its hidden nodes. To find optimal neural networks we should take into account the structure of the neural network as well as the adaptive parameters, weight of neurons. So we use the genetic algorithm that searches the structure of the neural network by the co-evolution mechanism, and for the weights learning we adopted the evolutionary stategies. As a results of co-evolution we will find the optimal structure of the neural network in a short time with a small population. The validity and effectiveness of the proposed method are inspected by applying it to the stabilization and position control of the invered-pendulum system. And we will show that the result of co-evolution is better than that of the conventioal genetic algorithm.

• Journal of Positioning, Navigation, and Timing
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• 제3권3호
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• pp.107-116
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• 2014

When an incoming Global Positioning System (GPS) signal is acquired, pull-in search performs a finer search of the Doppler frequency of the incoming signal so that phase lock loop can be quickly stabilized and the receiver can produce an accurate pseudo-range measurement. However, increasing the accuracy of the Doppler frequency estimation often involves a higher computational cost for weaker GPS signals, which delays the position fix. In this paper, we show that the Doppler frequency detectable by a long coherent auto-correlation can be accurately estimated using a complex-weighted sum of consecutive short coherent auto-correlation outputs with a different Doppler frequency hypothesis, and by exploiting this we propose a noise resistant, low-cost and highly accurate Doppler frequency and phase estimation technique based on a reverse directional application of the finite rate of innovation (FRI) technique. We provide a performance and computational complexity analysis to show the feasibility of the proposed technique and compare the performance to conventional techniques using numerous Monte Carlo simulations.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2016년도 학술발표회
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• pp.250-250
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• 2016

인공위성을 이용한 강수관측은 전 지구적 규모에서 시공간적으로 균일한 강수정보를 지속적으로 제공할 수 있으며, 가뭄에 중요한 하나의 변수로서 가뭄정보를 제공할 수 있다는 장점이 있어 점차적으로 미계측지역 수문학적으로 활용성이 증대되고 있다. 그러나 인공위성 기반 강수관측자료는 지상관측 강우자료에 비해 시 공간해상도가 낮고, 관측 당시의 대기 상태, 관측기기, 시 공간적 대표성 문제 등에서 기인한 많은 불확실성을 포함하고 있다. 이러한 불확실성을 보완하기 위한 목적으로 미국 항공우주국 (National Aeronautics and Space Administration: NASA)는 GPM(Global Precipitation Measurement) 위성을 핵심위성으로 한 다중 위성자료를 이용하여 전지구적으로 30분 간격, 10 km 해상도의 GPM IMERG (Integrated Multi-satellitE Retrievals for GPM)를 생산 제공하고 있다. 본 연구에서는 다중 인공위성 추정 강수의 가뭄 활용성을 검토하기 위한 목적으로 GPM IMERG 위성 강우 자료(Early run, Late run, Final run)의 검증 및 평가를 수행하고자 하였으며, 각각의 자료들을 강수사례에 적용하여 10 km, 30분 해상도를 가지는 1.5km CAPPI (Constant Altitude Plan Position Indicator) 레이더 및 지상 강우자료와 비교 검증하였다.

• 한국측량학회지
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• 제37권5호
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• pp.397-402
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• 2019

Recently, with the emergence of autonomous vehicles and the increasing interest in safety, a variety of research has been being actively conducted to precisely estimate the position of a vehicle by fusing sensors. Previously, researches were conducted to determine the location of moving objects using GNSS (Global Navigation Satellite Systems) and/or IMU (Inertial Measurement Unit). However, precise positioning of a moving vehicle has lately been performed by fusing data obtained from various sensors, such as LiDAR (Light Detection and Ranging), on-board vehicle sensors, and cameras. This study is designed to enhance kinematic vehicle positioning performance by using feature-based recognition. Therefore, an analysis of the required precision of the observations obtained from the images has carried out in this study. Velocity and attitude observations, which are assumed to be obtained from images, were generated by simulation. Various magnitudes of errors were added to the generated velocities and attitudes. By applying these observations to the positioning algorithm, the effects of the additional velocity and attitude information on positioning accuracy in GNSS signal blockages were analyzed based on Kalman filter. The results have shown that yaw information with a precision smaller than 0.5 degrees should be used to improve existing positioning algorithms by more than 10%.

• International Journal of Advanced Culture Technology
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• 제10권4호
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• pp.255-260
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• 2022

It is true that traditional markets have become a great foundation for changes in today's production and distribution. However, with the development of science and information communication gradually, the perspective of distribution has been newly developed. In particular, the digital economy system and the pursuit of perfect competition in the global era have placed a great burden on the traditional market. Accordingly, the government has made numerous efforts to revitalize traditional markets, which has led to the present day. However, the change in production, distribution, and transactional perspectives of newly introduced e-commerce in the position of not being able to deviate from the characteristics of the traditional market, that is, the traditional market, poses another major crisis. Therefore, while maintaining the tradition of the traditional market, the introduction of a new method of electronic trading has a good advantage to become an advanced market, but it has not pursued major changes due to fundamental management methods and small-scale operation. Therefore, I believe that it is urgent to introduce and apply new e-commerce to secure transitional competitiveness in order for the traditional market to be reborn and to pursue change and development into a new advanced market.