• International Journal of Fuzzy Logic and Intelligent Systems
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• v.8 no.3
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• pp.185-191
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• 2008

In this paper, experimental studies of a neural network (NN) control technique for non-model based position control of the x-y table robot are presented. Decentralized neural networks are used to control each axis of the x-y table robot separately. For an each neural network compensator, an inverse control technique is used. The neural network control technique called the reference compensation technique (RCT) is conceptually different from the existing neural controllers in that the NN controller compensates for uncertainties in the dynamical system by modifying desired trajectories. The back-propagation learning algorithm is developed in a real time DSP board for on-line learning. Practical real time position control experiments are conducted on the x-y table robot. Experimental results of using neural networks show more excellent position tracking than that of when PD controllers are used only.

• Proceedings of the Korea Water Resources Association Conference
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• 2019.05a
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• pp.29-29
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• 2019

급격한 도시화와 기후변화로 인한 자연적인 물순환 구조의 변화는 기존 수자원 이용 경향을 변화시키며 하천건천화 현상을 유발하고 있다. 이를 관리하기 위해 하천건천화 평가 및 예측이 가능한 영향 평가 기술이 필요하며, 국내에서는 GIS 기반의 분포형 수문 모형인 Drying Stream Assessment Tool and Water Flow Tracking (DrySAT-WFT)이 개발되어 활용되고 있다. 그러나 격자기반의 물수지 모형은 단위 cell 안의 수직적인 물의 거동은 파악하기 용이하나, 모형의 특성상 저수지, 댐, 보와 같은 수리 시설물의 방류량에 따른 하도의 흐름 추적에는 어려움이 있다. 본 연구의 목적은 DrySAT-WFT 모형에 댐?보 방류량 자료와 연계한 하도추적 알고리즘을 개발하여 모형의 유출 모의 성능을 개선하고, 1976년부터 2015년까지의 유출 모의를 통해 전국 표준유역을 대상으로 각 유역에 대한 하천건천화 원인 추적 및 평가를 수행하고자 한다. 하천건천화영향요소를 고려하기 위한 모형의 입력 자료로 산림높이, 도로망, 지하수 이용량, 토지이용, 토심, 기상 변화에 대해 1976년부터 2015년까지 구축한 시계열 전국 자료를 활용하였으며, 일별 강우량, 상대습도, 평균풍속, 평균 및 최고, 최저 기온, 일조시간의 기상자료를 구축하였다. 개선된 DrySAT-WFT 유출 모의 결과는 선행 연구와의 비교를 통해 모의 개선점을 정량적으로 제시하고자 한다.

• The Transactions of the Korean Institute of Power Electronics
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• v.26 no.3
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• pp.227-236
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• 2021

This research proposes a modeling and controller design of a three-level boost (TLB) converter for the implementation of maximum power point tracking (MPPT) in the photovoltaic power conditioning system (PCS). Contrary to the output voltage control of the conventional controller, the Photovoltaic PCS requires an input voltage controller for MPPT operation. A TLB converter has the advantage of decreasing the inductor size and increasing efficiency compared with the existing booster converter. However, an optimal controller is difficult to design due to the complexity of the TLB operations, which have two operational modes on the duty ratio boundary of 0.5. Therefore, the unified linear model equations of the TLB converters, which can be applicable to both operational modes, are derived using linearized solar cell expressions. Furthermore, the transfer functions are obtained for the controller design. The MPPT voltage controller is designed using MATLAB SISOTOOL. In addition, a controller for capacitor voltage unbalancing is described and designed. The simulations and experimental verifications are conducted to verify the effectiveness of the small-signal analysis and control system design.

• Journal of Internet Computing and Services
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• v.22 no.3
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• pp.59-66
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• 2021

This study proposes a requirements monitoring method that systematically performs traceability management and change management for requirements in order to improve the quality of software systems in the software development process. To this end, we present the artifact change history management models to systematically perform change management for individual artifacts and the traceability matrixes to define the relationship between artifacts. It also proposes a visual dashboard that makes it easy to grasp the situation in which changes are propagated to related artifacts when specific artifacts change.

• The Journal of the Korea institute of electronic communication sciences
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• v.17 no.6
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• pp.1283-1292
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• 2022

At present, several artificial intelligence projects in the healthcare and medical field are competing with each other, and the interfaces between the systems lack unified specifications. Thus, this study presents an artificial intelligence platform for healthcare and medical fields which adopts the deep learning technology to provide algorithms, models and service support for the health and medical enterprise applications. The suggested platform can provide a large number of heterogeneous data processing, intelligent services, model managements, typical application scenarios, and other services for different types of business. In connection with the suggested platform application, we represents a medical service which is corresponding to the trusted and comprehensible tracking and analyzing patient behavior system for Health and Medical treatment using Internet of Behavior concept.

• Journal of Positioning, Navigation, and Timing
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• v.10 no.4
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• pp.279-289
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• 2021

GNSS receivers capable of tracking multiple Global Navigation Systems (GNSSs) simultaneously are widely used. In order to estimate accurate user position and velocity, it is necessary to consider the key elements that contribute to the interoperability of the different GNSSs. Typical examples are the time system and the coordinate system. Each GNSS is operated based on its own reference time system depending on when the system was developed and whether the leap seconds are applied. In addition, each GNSS is designed based on its own coordinate system based on earth model constant values. This paper addresses the interoperability issues from the viewpoint of Single Point Positioning (SPP) users utilizing multiple GNSS signals from GPS, GLONASS, BeiDou, and Galileo. Since the broadcast ephemerides of each GNSS are based on their own time and coordinate systems, the time and the coordinate systems should be unified for any user algorithm. For this purpose, this paper proposes a method of converting each GNSS coordinate system into the reference coordinate system through Helmert transformation. The error of the broadcast ephemerides was calculated with the precise ephemerides provided by the International GNSS Service (IGS). The effectiveness of the proposed multi-GNSS correction and transformation method is verified using the Multi-GNSS Experiment (MGEX) station data.

• Transactions of the Society of Information Storage Systems
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• v.2 no.3
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• pp.208-213
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• 2006

The present state of the design of swing arm actuators for optical disc drives is to obtain the high efficient dynamic characteristics within a very compact volume. As a necessary consequence, the need of the small form factor (SFF) storage device has been arisen as major interests in the information storage technology. In this paper, we suggest the miniaturized swing arm type actuator that has high efficient dynamic characteristics for SFF optical disk drive (ODD). For the operating mechanism, it uses a tracking electromagnetic (EM) circuit for a focusing motion together. Moreover, due to the size constraint, the thermal stability of optical head is important. Therefore, the actuator is designed to emit the heat, which is generated by optical pick-up, along the actuator body easily. Initial model is designed based on the topology optimization method considering the thermal conductivity. Then, the structural parts of the actuator are modified to maintain the high sensitivity and to have wide control bandwidth by the design of experiments method (DOE) and new concept of decreasing mass and inertia. Finally, a swing arm type actuator for SFF ODD is suggested and its dynamic characteristics are verified.

• Wind and Structures
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• v.36 no.2
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• pp.75-90
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• 2023

Turbulent wind flow over hilly terrains has been extensively investigated in the scientific literature and main findings have been included in technical standards. In particular, turbulent wind flow over nominally two-dimensional hills is often adopted as a benchmark to investigate wind turbine siting, estimate wind loading, and dispersion of particles transported by the wind, such as atmospheric pollutants, wind-driven rain, windblown snow. Windblown sand transport affects human-built structures and natural ecosystems in sandy desert and coastal regions, such as transport infrastructures and coastal sand dunes. Windblown sand transport taking place around any kind of obstacle is rarely in equilibrium conditions. As a result, the modelling of windblown sand transport over complex orographies is fundamental, even if seldomly investigated. In this study, the authors present a wind-sand tunnel test campaign carried out on a nominally two-dimensional sinusoidal hill. A first test is carried out on a flat sand fetch without any obstacle to assess sand transport in open field conditions. Then, a second test is carried out on the hill model to assess the sand flux overcoming the hill and the morphodynamic evolution of the sand sedimenting over its upwind slope. Finally, obtained results are condensed into a dimensionless parameter describing its sedimentation capability and compared with values resulting from other nominally two-dimensional obstacles from the literature.

• Smart Media Journal
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• v.12 no.2
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• pp.36-41
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• 2023

With the advent of applicant tracking systems, online recruitment has become more popular, and recruitment fraud has become a serious problem. This research aims to develop a reliable model to detect recruitment fraud in online recruitment environments to reduce cost losses and enhance privacy. The main contribution of this paper is to provide an automated methodology that leverages insights gained from exploratory analysis of data to distinguish which job postings are fraudulent and which are legitimate. Using EMSCAD, a recruitment fraud dataset provided by Kaggle, we trained and evaluated various single-classifier and ensemble-classifier-based machine learning models, and found that the ensemble classifier, the random forest classifier, performed best with an accuracy of 98.67% and an F1 score of 0.81.

• Proceedings of the Korean Nuclear Society Conference
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• 1996.05b
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• pp.691-698
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• 1996

This paper propose a procedure to estimate the system lifetime distribution using simulation method in a parametric framework and also develop the criterion for terminating the simulation. We assume that a system is composed of many components whose lifetime and repair time distributions are general, and repair of each component is imperfect or not. General simulation algorithms can not be adopted for this case, due to the dependency of successive operating times and the discontinuity in base line intensity function of failure process. Then we propose algorithms for generating failure times subject to imperfect repair. We develop the event time tracking logic for identifying the system failure time, and also develop the criterion for terminating the simulation. Our procedure is composed of two phases. The first phase of the procedure is to generate the system failure times from the inputs. The second phase is to estimate the lifetime distribution of the system. The best model is selected by a fully automated procedure among well-known parametric families, and the required parameters are estimated. We give examples to show the accuracy of our procedure and the effect of repair effect of components to system MTTF(Mean Time To Failure).