• Title/Summary/Keyword: mathematical modeling

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The Study on the Temperature Compensation of Ultrasonic Motor for Robot Actuator Using Fuzzy Controller (퍼지제어기를 이용한 로보트 액츄에이터용 초음파 모터의 온도 보상에 관한 연구)

  • 차인수;유권종;백형래;김영동
    • The Transactions of the Korean Institute of Power Electronics
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    • v.3 no.3
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    • pp.165-172
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    • 1998
  • The electromechanical energy conversion conditioning and processing implementation in USM direct motion control system is generally divided into two power stages: the two-phase high-frequency ac power inversion stage for driving piezoelectric ceramic PZT transducer array off the USM stator and the mechanical thrust power conversion stage based on the frictional force between the piezo electric stator array and the rotary slider of the USM. However, the dynamic and steady-state mathematical modeling of the USM is extremely default from a theoretical point of view because it contains many complicated an nonlinear characteristics dependant on operation temperature. In +2$0^{\circ}C$~3$0^{\circ}C$, the operating characteristics of the USM has represented normal condition. But the other temperature, it has abnormal condition so that driving frequency, current and motor speed will be down. The recent USM has controller without temperature compensation. This study represents the fuzzy controller for speed compensation according to operating temperature by driving frequency.

A Flexible Statistical Growth Model for Describing Plant Disease Progress (식물병(植物病) 진전(進展)의 한 유연적(柔軟的)인 통계적(統計的) 생장(生長) 모델)

  • Kim, Choong-Hoe
    • Korean journal of applied entomology
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    • v.26 no.1 s.70
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    • pp.31-36
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    • 1987
  • A piecewise linear regression model able to describe disease progress curves with simplicity and flexibility was developed in this study. The model divides whole epidemic into several pieces of simple linear regression based on changes in pattern of disease progress in the epidemic and then incorporates the pieces of linear regression into a single mathematical function using indicator variables. When twelve epidemic data obtained from the field experiments were fitted to the piecewise linear regression model, logistic model and Gompertz model to compare statistical fit, goodness of fit was greatly improved with piecewise linear regression compared to other two models. Simplicity, flexibility, accuracy and ease in parameter estimation of the piece-wise linear regression model were described with examples of real epidemic data. The result in this study suggests that piecewise linear regression model is an useful technique for modeling plant disease epidemic.

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Preparation of PVDF Hollow Fiber Membrane and Absorption of SO2 from Flue Gas Using Bench Scale Gas-Liquid Contactor (PVDF 중공사막 제조 및 벤치규모 기-액 접촉기를 이용한 SO2 흡수특성)

  • Park, Hyun-Hee;Jo, Hang-Dae;Kim, In-Won;Lee, Hyung-Keun
    • Korean Chemical Engineering Research
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    • v.46 no.3
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    • pp.521-528
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    • 2008
  • The micro-porous asymmetric PVDF hollow fiber membranes for gas-liquid contactor were prepared by the dry-jet wet phase inversion process and the characteristics of hollow fiber membranes were evaluated by the gas permeation method and scanning electron microscope. The chemical absorbent for removal of $SO_2$ gas was sodium hydroxide at bench scale hollow fiber membrane contactor. The experiments were performed in a counter-current mode of operation with gas in the shell side and liquid in the fiber lumen of the module to examine the effect of various operating variables such as concentration of absorbent, gas flow rate, L/G ratio and concentration of inlet $SO_2$ gas on the $SO_2$ removal efficiency using PVDF hollow fiber membrane contactor. Membrane mass transfer coefficient($k_m$) was calculated by mathematical modeling. The volumetric overall mass transfer coefficient increased with increasing the concentration of absorbent and L/G ratio. The increase of the absorbent concentration and L/G ratio not only provides more sufficient alkalinity but also decreases liquid phase resistance. The volumetric overall mass transfer coefficient increased with increasing gas flow rate due to decreasing the gas phase resistance.

An Accurate Radio Channel Model for Wireless Sensor Networks Simulation

  • Alejandro Martfnez-Sala;Jose-Maria Molina-Garcia-Pardo;Esteban Egea-Lopez;Javier Vales-Alonso;Leandro Juan-Llacer;Joan Garcia-Haro
    • Journal of Communications and Networks
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    • v.7 no.4
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    • pp.401-407
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    • 2005
  • Simulations are currently an essential tool to develop and test wireless sensor networks (WSNs) protocols and to analyze future WSNs applications performance. Researchers often simulate their proposals rather than deploying high-cost test-beds or develop complex mathematical analysis. However, simulation results rely on physical layer assumptions, which are not usually accurate enough to capture the real behavior of a WSN. Such an issue can lead to mistaken or questionable results. Besides, most of the envisioned applications for WSNs consider the nodes to be at the ground level. However, there is a lack of radio propagation characterization and validation by measurements with nodes at ground level for actual sensor hardware. In this paper, we propose to use a low-computational cost, two slope, log-normal path­loss near ground outdoor channel model at 868 MHz in WSN simulations. The model is validated by extensive real hardware measurements obtained in different scenarios. In addition, accurate model parameters are provided. This model is compared with the well-known one slope path-loss model. We demonstrate that the two slope log-normal model provides more accurate WSN simulations at almost the same computational cost as the single slope one. It is also shown that the radio propagation characterization heavily depends on the adjusted model parameters for a target deployment scenario: The model parameters have a considerable impact on the average number of neighbors and on the network connectivity.

Performance Prediction Model of Solid Oxide Fuel Cell Stack Using Deep Neural Network Technique (심층 신경망 기법을 이용한 고체 산화물 연료전지 스택의 성능 예측 모델)

  • LEE, JAEYOON;PINEDA, ISRAEL TORRES;GIAP, VAN-TIEN;LEE, DONGKEUN;KIM, YOUNG SANG;AHN, KOOK YOUNG;LEE, YOUNG DUK
    • Transactions of the Korean hydrogen and new energy society
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    • v.31 no.5
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    • pp.436-443
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    • 2020
  • The performance prediction model of a solid oxide fuel cell stack has been developed using deep neural network technique, one of the machine learning methods. The machine learning has been received much interest in various fields, including energy system mo- deling. Using machine learning technique can save time and cost requried in developing an energy system model being compared to the conventional method, that is a combination of a mathematical modeling and an experimental validation. Results reveal that the mean average percent error, root mean square error, and coefficient of determination (R2) range 1.7515, 0.1342, 0.8597, repectively, in maximum. To improve the predictability of the model, the pre-processing is effective and interpolative machine learning and application is more accurate than the extrapolative cases.

A study on MERS-CoV outbreak in Korea using Bayesian negative binomial branching processes (베이지안 음이항 분기과정을 이용한 한국 메르스 발생 연구)

  • Park, Yuha;Choi, Ilsu
    • Journal of the Korean Data and Information Science Society
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    • v.28 no.1
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    • pp.153-161
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    • 2017
  • Branching processes which is used for epidemic dispersion as stochastic process model have advantages to estimate parameters by real data. We have to estimate both mean and dispersion parameter in order to use the negative binomial distribution as an offspring distribution on branching processes. In existing studies on biology and epidemiology, it is estimated using maximum-likelihood methods. However, for most of epidemic data, it is hard to get the best precision of maximum-likelihood estimator. We suggest a Bayesian inference that have good properties of statistics for small-sample. After estimating dispersion parameter we modelled the posterior distribution for 2015 Korea MERS cases. As the result, we found that the estimated dispersion parameter is relatively stable no matter how we assume prior distribution. We also computed extinction probabilities on branching processes using estimated dispersion parameters.

Daily Stock Price Forecasting Using Deep Neural Network Model (심층 신경회로망 모델을 이용한 일별 주가 예측)

  • Hwang, Heesoo
    • Journal of the Korea Convergence Society
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    • v.9 no.6
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    • pp.39-44
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    • 2018
  • The application of deep neural networks to finance has received a great deal of attention from researchers because no assumption about a suitable mathematical model has to be made prior to forecasting and they are capable of extracting useful information from large sets of data, which is required to describe nonlinear input-output relations of financial time series. The paper presents a new deep neural network model where single layered autoencoder and 4 layered neural network are serially coupled for stock price forecasting. The autoencoder extracts deep features, which are fed into multi-layer neural networks to predict the next day's stock closing prices. The proposed deep neural network is progressively learned layer by layer ahead of the final learning of the total network. The proposed model to predict daily close prices of KOrea composite Stock Price Index (KOSPI) is built, and its performance is demonstrated.

Modeling and Analysis of Dynamic Characteristic for Bundle Fluid System (집속체 유동계의 모델링과 운동 특성해석)

  • Kim, Jong-Sung;Heo, Yu;Kim, Yoon-Hyuk
    • Proceedings of the Korean Society of Precision Engineering Conference
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    • 2003.06a
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    • pp.1643-1646
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    • 2003
  • Drawing is a mechanical operation that attenuates thick material to an appropriate thickness for the next processing or end usage. When the input material has the form of a bundle or bundles made of very thin and long shaped wire or fibers, this attenuation operation is called "bundle drawing" or "drafting" Drafting is being used widely in manufacturing staple yarns. which is indispensable for the textile industry. However, the bundle processed by this operation undertake more or less defects in the evenness of linear density. Such irregularities cause many problems not only for the product quality but also for the efficiency of the next successive processes. Since long there have been many researches tying to find out factors affecting the irregularity of linear desity, to obtain optimal drafting conditions, to develop efficient measuring and analysis methods of linear density of bundle, etc., but there exists yet no fundamental equation describing the dynamic behavior of the flowing bundle during processing. In this research a mathematical model for the dynamic behavior of the bundle fluid is to be set up on the basis of general physical lows representing physical variables, i.e. linear density and velocity as the dynamic state of bundle. The conservation of mass and momentum balance was applied to the fluid field of bundle. while the movement of′ individual material was taken into account. The constitutive model relating the surface force and the deformation of bundle was introduced by considering a representative prodedure that stands for the bundle movement. Then a fundamental equations system could be simplified considering a steady state of the process. On the basis of the simplified model, the simulation was performed and the results could be confirmed by the experiments under various conditions.

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Stabilization Design of Large Rotating Stand Using Sliding Mode Control (슬라이딩모드 제어 기법을 이용한 대형 구동기 안정화 설계)

  • Kim, Sungryong;Park, Dongmyung;Moon, Wooyong
    • Transactions of the Korean Society of Mechanical Engineers A
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    • v.39 no.10
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    • pp.1045-1052
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    • 2015
  • In this paper, a stabilized control algorithm for the large rotating stand of a long-range surveillance radar (LRSR) system is introduced. The stabilized control algorithm for this large rotating stand system was designed using mathematical plant modeling. The LRSR system is located on high ground and has a wide surface, making it susceptible to the effects of wind, which increases the bearing friction and reduces the stability of the rotating stand. The disturbance caused by the wind was analyzed using computational fluid dynamics (CFD) in this study. The results of the CFD analysis were used to construct a control algorithm for the disturbance . The performance of the proposed control algorithm was demonstrated experimentally and through simulations. The plant model and the control algorithm were constructed in Matlab/Simulink.

A hybrid seismic response control to improve performance of a two-span bridge

  • Heo, Gwanghee;Kim, Chunggil;Jeon, Seunggon;Lee, Chinok;Jeon, Joonryong
    • Structural Engineering and Mechanics
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    • v.61 no.5
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    • pp.675-684
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    • 2017
  • In this paper, a hybrid seismic response control (HSRC) system was developed to control bridge behavior caused by the seismic load. It was aimed at optimum vibration control, composed of a rubber bearing of passive type and MR-damper of semi-active type. Its mathematical modeling was driven and applied to a bridge model so as to prove its validity. The bridge model was built for the experiment, a two-span bridge of 8.3 meters in length with the HSRC system put up on it. Then, inflicting the EI Centro seismic load on it, shaking table tests were carried out to confirm the system's validity. The experiments were conducted under the basic structure state (without an MR-damper applied) first, and then under the state with an MR-damper applied. It was also done under the basic structure state with a reinforced rubber bearing applied, then the passive on/off state of the HSRC system, and finally the semi-active state where the control algorithm was applied to the system. From the experiments, it was observed that pounding rather increased when the MR-damper alone was applied, and also that the application of the HSRC system effectively prevented it from occurring. That is, the experiments showed that the system successfully mitigated structural behavior by 70% against the basic structure state, and, further, when control algorithm is applied for the operation of the MR-damper, relative displacement was found to be effectively mitigated by 80%. As a result, the HSRC system was proven to be effective in mitigating responses of the two-span bridge under seismic load.