• Journal of Institute of Control, Robotics and Systems
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• v.13 no.12
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• pp.1207-1212
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• 2007

We propose a haptic interface algorithm for joystick operators working in remote control systems of unmanned vehicles. The haptic interface algorithm is implemented using a force-feedback joystick, which is equipped with low price DC motors without encoders. Generating specific amounts of forces on the joystick pole according to the distance between a remote controlled vehicle and obstacles, the haptic interface enables the operator to perceive the distance information by the sense of touch. For the case of no joystick operation or no obstacles in the working area, we propose an origin control algorithm, which positions the joystick pole at the origin. The origin control algorithm prevents the false movement of the remote vehicles and provides the operator with a realistic force resisting the joystick pole's movement. The experiment results obtained under various scenarios exemplify the validity of the proposed haptic interface algorithm and the origin control algorithm.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2007.10a
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• pp.615-618
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• 2007

It has able to express digital video/audio data from analog and to broadcast it via improvement of video/audio compression technology and publishing standard of MPEG-2 System. Nowaday many System Operators are provide regular digital broadcasting program to customer with their own access program. To provide access program, two process needs that are creating broadcasting information and remultiplexing it with video/audio data, and this solution is providing with high-cost system only. For this reason, digital access program bas week point to product. In this paper, we designed and implemented Generating PSIP Information System to product digital access program which generate PSIP information via receiving broadcasting information from user, and map PSIP information directly to video/audio data.

• Korean Journal of Computational Design and Engineering
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• v.21 no.1
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• pp.9-19
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• 2016

Applying human engineering simulation to analyzing work capability and movements of operators during manufacturing is highly demanded. However, difficulty in modeling digital human required for simulation makes engineers to be reluctant to utilize human simulation for their tasks. This paper addresses such problem on human engineering simulation by developing the technology to automatize human modeling with multiple Kinects at different depths. The Kinects enable us to acquire the movements of digital human which are essential data for implementing human engineering simulation. In this paper, we present a system for modeling automation of digital human. Especially, the system provides a way of generating the digital model of workers' movement and position using multiple Kinects which cannot be generated by single Kinect. Lastly, we verify the effects of the developed system in terms of modeling time and accuracy by applying the system to four different scenarios. In conclusion, the proposed system makes it possible to generate the digital human model easily and reduce costs and time for human engineering simulation.

• Proceedings of the KIEE Conference
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• 2006.10b
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• pp.185-190
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• 2006

Frequency and phasor are the most important quantities in power system operation because they can reflect the whole power system situation. Frequency reflects the dynamic energy balance between load and generating power, while operators use phasor to constitute the state of system and, moreover, phasor based line relays are currently used in most power systems. So frequency and phasor are regarded as indices for the operating power systems in practice. The proposed technique is suitable for estimation near-nominal, nomina), and off-nominal frequencies. It is useful in designing microprocessor-based relays and meters that need to measure power system frequency. Performance test results, using signals from EMTP source and Excel program, indicate that the proposed technique can provide accurate estimates within 16ms. Maximum estimation errors observed during testing are of the order of 0.006Hz for nominal, near-nominal, and off-nominal frequencies. The proposed technique provides accurate estimates in presence of noise and harmonics and in case ground fault. The rate change of the phase angle is used for estimation. To confirm the validity of the proposed algorithm, the simulation studies carried out on a typical 154[KV] double T/L system by using EMTP software. Some test results are presented in the paper.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.4
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• pp.1579-1602
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• 2020

In the design of production system, buffer capacity allocation is a major step. Through polymorphism analysis of production capacity and production capability, this paper investigates a buffer allocation optimization problem aiming at the multi-stage production line including unreliable machines, which is concerned with maximizing the system theoretical production rate and minimizing the system state entropy for a certain amount of buffers simultaneously. Stochastic process analysis is employed to establish Markov models for repairable modular machines. Considering the complex structure, an improved vector UGF (Universal Generating Function) technique and composition operators are introduced to construct the system model. Then the measures to assess the system's multi-state reliability and structural complexity are given. Based on system theoretical production rate and system state entropy, mathematical model for buffer capacity optimization is built and optimized by a specific genetic algorithm. The feasibility and effectiveness of the proposed method is verified by an application of an engine head production line.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.59 no.1
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• pp.33-39
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• 2010

In order to operate the power system satisfactory for both system operators and customers, it is important to limit the harmonic currents to the allowable levels which injected into the system from the distorting installations. In this regard, the principles for the allocation of emission limits on individual customer were introduced in the technical report of IEC61000-3-6. According to these general principles, the emission limits are dependent on the agreed power of the customer, the power of the harmonic-generating equipment, and the system characteristics. The considerations in this report are very comprehensive and the process introduced is practical enough to implement as it is. However, there is a fact not appropriately dealing in the report that could be a very tickle but has a huge impact on determining the emission limit. This is the effect of non-harmonic load currents. More precisely, these are from the equipments which do not emit any harmonic or may emit harmonics but this specific order under the consideration by themselves if the source power is sinusoidal. The load currents originated from these equipments have an effect of active filter against the specific order of harmonic therefore, these should be dealt as a significant factoron the process of determining the emission limits for individual customer.

• Journal of Electrical Engineering and Technology
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• v.10 no.5
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• pp.1940-1949
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• 2015

This paper presents an Enhanced Particle Swarm Optimization (EPSO) to solve short-term hydrothermal scheduling (STHS) problem with non-convex fuel cost function and a variety of operational constraints related to hydro and thermal units. The operators of the conventional PSO are dynamically controlled using exponential functions for better exploration and exploitation of the search space. The overall methodology efficiently regulates the velocity of particles during their flight and results in substantial improvement in the conventional PSO. The effectiveness of the proposed method has been tested for STHS of two standard test generating systems while considering several operational constraints like system power balance constraints, power generation limit constraints, reservoir storage volume limit constraints, water discharge rate limit constraints, water dynamic balance constraints, initial and end reservoir storage volume limit constraints, valve-point loading effect, etc. The application results show that the proposed EPSO method is capable to solve the hard combinatorial constraint optimization problems very efficiently.

• Journal of Electrical Engineering and Technology
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• v.12 no.4
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• pp.1406-1416
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• 2017

In complex and large-scale industries, properly designed fault detection and identification (FDI) systems considerably improve safety, reliability and availability of target processes. In thermal power plants (TPPs), generating units operate under very dangerous conditions; system failures can cause severe loss of life and property. In this paper, we propose a bagged auto-associative kernel regression (AAKR)-based FDI approach for steam boilers in TPPs. AAKR estimates new query vectors by online local modeling, and is suitable for TPPs operating under various load levels. By combining the bagging method, more stable and reliable estimations can be achieved, since the effects of random fluctuations decrease because of ensemble averaging. To validate performance, the proposed method and comparison methods (i.e., a clustering-based method and principal component analysis) are applied to failure data due to water wall tube leakage gathered from a 250 MW coal-fired TPP. Experimental results show that the proposed method fulfills reasonable false alarm rates and, at the same time, achieves better fault detection performance than the comparison methods. After performing fault detection, contribution analysis is carried out to identify fault variables; this helps operators to confirm the types of faults and efficiently take preventive actions.

• Journal of Korea Society of Digital Industry and Information Management
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• v.8 no.2
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• pp.145-160
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• 2012

The globe-trotting trend has been converted from tourism for the simple purposes of sightseeing and enjoyment to a form of learning and practicing the more specialized contents by directly participation. Traditional cultural resources have sufficient potential as culture and tourism assets that fit this kind of trend. Therefore, building proper tourist resources for their application has become a very urgent and important matter. To make masterpiece tourism packages through combined services of traditional cultural resources, it is necessary for operators to ponder diverse methods that can be used to develop various experience programs and conserve traditional cultural properties by continuously generating profits. The major results of this research are as follows. Firstly, this study proposes plans for unified tourist information and combined services of traditional cultural resources based on ubiquitous IT. Secondly, it is ascertained that the organization of combined operational consultative groups and the improvement of operator' capability are required to execute combined services of traditional cultural resources. Thirdly, we propose business plans to generate profits in both product aspect and network aspect.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.5
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• pp.2468-2483
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• 2017

The construction of completely random sensing matrices of Compressive Sensing requires a large number of random numbers while that of deterministic sensing operators often needs complex mathematical operations. Thus both of them have difficulty in acquiring large signals efficiently. This paper focuses on the enhancement of the practicability of the structurally random matrices and proposes a semi-deterministic sensing matrix called Partial Kronecker product of Identity and Hadamard (PKIH) matrix. The proposed matrix can be viewed as a sub matrix of a well-structured, sparse, and orthogonal matrix. Only the row index is selected at random and the positions of the entries of each row are determined by a deterministic sequence. Therefore, the PKIH significantly decreases the requirement of random numbers, which has a complex generating algorithm, in matrix construction and further reduces the complexity of sampling. Besides, in order to process large signals, the corresponding fast sampling algorithm is developed, which can be easily parallelized and realized in hardware. Simulation results illustrate that the proposed sensing matrix maintains almost the same performance but with at least 50% less random numbers comparing with the popular sampling matrices. Meanwhile, it saved roughly 15%-35% processing time in comparison to that of the SRM matrices.