• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.1
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• pp.688-695
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• 2017

This paper deals with characteristics analysis of a permanent magnet (PM) linear generator using analytical methods for wave energy harvesting. The wave energy is carried out from the movement of a yo-yo system. A linear generator using permanent magnets to generate a magnetic force itself does not require a separate power supply and has the advantage of simple maintenance. In addition to the use of a rare earth, a permanent magnet having a high-energy density can be miniaturized and lightweight, and can obtain high energy-conversion efficiency. We derived magnetic field solutions produced by the permanent magnet and armature reaction based on 2D polar coordinates and magnetic vector potential. Induced voltage is obtained via arbitrary sinusoidal input. In addition, electrical parameters are obtained, such as back-EMF constant, resistance, and self- and mutual-winding inductances. The space harmonic method used in this paper is confirmed by comparing it with finite element method (FEM) results. These facilitate the characterization of the PM-type linear generator and provide a basis for comparative studies, design optimization, and machine dynamic modeling.

• Journal of Korean Society of Environmental Engineers
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• v.36 no.9
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• pp.641-647
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• 2014

In this study, sludge waste which has a difficulty in treating it was used to manufacture a fiber type of biosorbent. To solve the problems such as the release of organic pollutants and the difficulty in separating solid from treated water, entrapment method using Ca-alginate was used to immobilize sludge waste. Considering ease of manufacture as well as improvement of adsorptive ability, the biosorbent was manufactured in the form of fiber type. Optimum immobilization condition for minimizing the amount of alginate used and maximizing the performance of biosorbent was determined to be 10 g/L alginate concentration, 40 g/L sludge concentration, and 0.3-0.4 mm fiber diameter. The maximum Cd(II) uptake of the biosorbent was 60.73 mg/g. Pseudo-second-order kinetic model and Langmuir isotherm model adequately described the dynamic and equilibrium behaviors of Cd(II) biosorption onto the biosorbent, respectively. In conclusion, sludge waste generated from wastewater treatment process is a cheap raw material for the manufacture of biosorbent which can be used to remove toxic heavy metals from industrial wastewaters efficiently.

• Journal of KIISE:Information Networking
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• v.34 no.6
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• pp.514-524
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• 2007

Recent advances in the speed of multi-rate wireless local area networks (WLANs) and the proliferation of WLAN devices have made rate adaptive, opportunistic scheduling critical for throughput optimization. As WLAN traffic evolves to be more symmetric due to the emerging new applications such as VoWLAN, collaborative download, and peer-to-peer file sharing, opportunistic scheduling at the downlink becomes insufficient for optimized utilization of the single shared wireless channel. However, opportunistic scheduling on the uplink of a WLAN is challenging because wireless channel condition is dynamic and asymmetric. Each transmitting client has to probe the access point to maintain the updated channel conditions at the access point. Moreover, the scheduling decisions must be coordinated at all clients for consistency. This paper presents JUDS, a joint uplink/downlink opportunistic scheduling for WLANs. Through synergistic integration of both the uplink and the downlink scheduling, JUDS maximizes channel diversity at significantly reduced scheduling overhead. It also enforces fair channel sharing between the downlink and uplink traffic. Through extensive QualNet simulations, we show that JUDS improves the overall throughput by up to 127% and achieves close-to-perfect fairness between uplink and downlink traffic.

• Journal of the Korea Society of Computer and Information
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• v.15 no.10
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• pp.229-237
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• 2010

Recently, forest management objectives become more complex and complicated, and spatial constraints were necessarily considered for ecological stability. Now forest planning is required to provide an optimized solution that is able to achieve a number of management objectives and constraints. In this study, we developed a decision supporting system based on the one of dynamic planning techniques, Tabu Search (TS) heuristic algorithm, which enable one to generate an optimized solution for given objectives and constraints. For this purpose, we analyzed the logical flow of the algorithm and designed the subsequence of processes. To develop a high-performance computing system, we examined a number of strategy to minimize execution time and workloads in each process and to maximize efficiency of using system resources. We examined two model based on the original TS algorithm and revised version of TS algorithm and compared their performance in optimization process. The results showed high performance of the developed system in providing feasible solutions for several management objectives and constraints. Moreover, the revised version of TS algorithm was appeared to be more stable for providing results with minimum variation. The developed system is expected to use for developing forest management plans in Korea.

• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.2
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• pp.203-209
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• 2013

Digital Radiography (DR) has improved a quality of resolution based on a wide dynamic range, high detective quantum efficiency (DQE), and modulation transfer function (MTF), compared with film/screen(F/s). Unlike expectation that a low level of radiation can be used in examination, high level of signal to noise ratio(SNR) due to over-exposure caused increase of exposed dose to patients. Also, the auto exposure control (AEC) using Kilovolage(kVp) in F/S can cause over-exposure. Hence, in this study, we proposed a proper method for using DR, in which effect of tubing Kilovolage on device's image, DR MTF measurement with changes of tubing current (mA), and the quantitative evaluation of skull phantom captured images' PSNR were evaluated. Changes of contrast with tubing Kilovolage can be improved by retouching, and MTF changes according to tubing current(1.41~1.39 lp/mm in 50% area, and 3.19~2.8 lp/mm in 10% area) does not influence on resolution of image. As a result, high tubing Kilovoltage, and tubing current will be suitable to use of DR.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.46 no.5
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• pp.56-63
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• 2009

The IEEE 802.11 standard has been used for wireless data networks such as wireless LAN, ad-hoc network, and vehicular ad-hoc network. Thus, the performance analysis of the IEEE 802.11 specification has been one of the hottest issues for network optimization and resource management. Most of the analysis studies were performed in a data plane of the IEEE 802.11 unicast. However, IEEE 802.11 broadcast is widely used for topology management, path management, and data dissemination. Thus, it is important to understand the performance of the broadcast scheme for the design of efficient wireless data network. In this contort, we analyze the IEEE 802.11 broadcast scheme in terms of the broadcast frame reception probability according to the distance from a sending node. Unlike the other works, our analysis framework includes not only the system parameters of the IEEE 802.11 specification such as transmission range, data rate, minimum contention window but also the networking environments such as the number of nodes, network load, and the radio propagation environments. Therefore, our analysis framework is expected to be used for the development of protocols and algorithms in a dynamic wireless data network.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.45 no.6
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• pp.60-67
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• 2008

A low-power 2.4GHz fractional-N frequency synthesizer has been designed for 2.4GHz ISM band applications such as Bluetooth, Zigbee, and WLAN. To achieve low-power characteristic, the design has been focused on the power optimization of power-hungry blocks such as VCO, prescaler, and ${\Sigma}-{\Delta}$ modulator. An NP-core type VCO is adopted to optimize both phase noise and power consumption. Dynamic D-F/Fs with no static DC current are employed in designing the low-power prescaler circuit. The ${\Sigma}-{\Delta}$ modulator is designed using a modulus mapping circuit for reducing hardware complexity and power consumption. The designed frequency synthesizer which was fabricated using a $0.18{\mu}m$ CMOS process consumes 7.9mA from a single 1.8V supply voltage. The experimental results show that a phase noise of -118dBc/Hz at 1MHz offset, the reference spur of -70dBc at 25MHz offset, and the channel switching time of $15{\mu}s$ over 25MHz transition have been achieved. The designed chip occupies an area of $1.16mm^2$ including pads where the core area is only $0.64mm^2$.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.39 no.3
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• pp.18-31
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• 2002

In this study, we introduce a concept of advanced neurofuzzy polynomial networks(ANFPN), a hybrid modeling architecture combining neurofuzzy networks(NFN) and polynomial neural networks(PNN). These networks are highly nonlinear rule-based models. The development of the ANFPN dwells on the technologies of Computational Intelligence(Cl), namely fuzzy sets, neural networks and genetic algorithms. NFN contributes to the formation of the premise part of the rule-based structure of the ANFPN. The consequence part of the ANFPN is designed using PNN. At the premise part of the ANFPN, NFN uses both the simplified fuzzy inference and error back-propagation learning rule. The parameters of the membership functions, learning rates and momentum coefficients are adjusted with the use of genetic optimization. As the consequence structure of ANFPN, PNN is a flexible network architecture whose structure(topology) is developed through learning. In particular, the number of layers and nodes of the PNN are not fixed in advance but is generated in a dynamic way. In this study, we introduce two kinds of ANFPN architectures, namely the basic and the modified one. Here the basic and the modified architecture depend on the number of input variables and the order of polynomial in each layer of PNN structure. Owing to the specific features of two combined architectures, it is possible to consider the nonlinear characteristics of process system and to obtain the better output performance with superb predictive ability. The availability and feasibility of the ANFPN are discussed and illustrated with the aid of two representative numerical examples. The results show that the proposed ANFPN can produce the model with higher accuracy and predictive ability than any other method presented previously.

• Journal of the Korea Society of Computer and Information
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• v.19 no.1
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• pp.191-201
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• 2014

The purpose of this study is to propose strategies of puzzle-based learning for Informatics gifted education through analyzing Informatics gifted elementary students' computational problem solving approaches in puzzle-based learning contexts. Six types of educational puzzles, which are constraints, optimization, probability, statistically speaking, pattern recognition, and strategy, were used in teaching 14 Informatics gifted students for 8 sessions. The results of pre and post test and each students' answers were analyzed to identify why students were not able to solve the puzzles. We also analysed what essential computational strategies are needed to solve each type of puzzles, and what students did not know in solving puzzle problems. We identified some problems caused by puzzle representation methods, and various students' intuitions that disturb puzzle solving. Also, we identified essential computational strategies to solve puzzles: backtracking, dynamic programming, abstraction, modeling, and reduction of big problem. However, students had difficulties in applying these strategies to solve their puzzle problems. We proposed the revised puzzle-based learning strategies, which is based on the improved problem representation, just-in-time cognitive feedbacks, and web-based learning system.

• Journal of the Korea Society of Computer and Information
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• v.24 no.12
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• pp.25-33
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• 2019

This paper presents a novel evolutionary framework for optimizing a bio-inspired fully dynamic neurocontroller for the maneuverable flapping flight of a simulated bird-sized ornithopter robot which takes advantage of the morphological computation and mechansensory feedback to improve flight stability. In order to cope with the difficulty of generating robust flapping flight and its maneuver, the wing of robot is modelled as a series of sub-plates joined by passive torsional springs, which implements the simplified version of feathers attached to the forearm skeleton. The neural controller is designed to have a bilaterally symmetric structure which consists of two fully connected neural network modules receiving mirrored sensory inputs from a series of flight navigation sensors as well as feather mechanosensors to let them participate in pattern generation. The synergy of wing compliance and its sensory reflexes gives a possibility that the robot can feel and exploit aerodynamic forces on its wings to potentially contribute to the agility and stability during flight. The evolved robot exhibited target-following flight maneuver using asymmetric wing movements as well as its tail, showing robustness to external aerodynamic disturbances.