• Title/Summary/Keyword: conditional variation

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A Similitude Study of Soil-Wheel System for Identifying the Dimension of Pertinent Soil Parameter(I) -Pull Prediction Analysis- (구동륜(驅動輪)의 성능예측(性能豫測)에 적합한 토양변수(土壤變數)의 차원해석(次元解析)을 위한 차륜(車輪)-토양(土壤) 시스템의 상사성(相似性) 연구(硏究)(I) -견인력(牽引力) 예측(豫測) 분석(分析)-)

  • Lee, K.S.;Chung, C.J.
    • Journal of Biosystems Engineering
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    • v.14 no.2
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    • pp.67-79
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    • 1989
  • This study was conducted to investigate the applicability of true model theory for pull prediction in a powered lugged wheel-soil system and to examine the possibility of using principles of similitude in investigating the dimensions of soil parameters pertinent to a powered lugged wheel-soil system concerning the pull prediction. The following conclusions were derived from the study; 1) The pull of prototype wheels proved to be predicted by those of the model wheels for the range of the dynamic weight tested. The pull curves of models and prototype were respectively very similar in the shape. From this basic knowledge, it was enabled to apply the similitude theory to the performance prediction of the true model. 2) A conditional equation which can be used for the prediction of pull of prototype by model test was derived as follows. $n_f=n_1^{-b}$ where $n_f$ : force scale = $w/w_m$ $n_1$ : length scale = ${\ell}/{\ell}_m$ b : exponent on the length dimension of the soil property ${\alpha}$ The range of the numerical value of b, which was determined by the least square method, was found to be -2.0~-2.6. 3) Considering a relatively wide variation of b values in the pull prediction, b is considered to be a function of many variales. Thus it was concluded that there are several soil properties which are pertinent to the powered lugged-wheel-soil system concerning the pull prediction, and these soil properties may have the different effects on the pull of model and protytype wheels, to give the different dimension on the soil parameters.

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Pre-Computation Based Selective Probing (PCSP) Scheme for Distributed Quality of Service (QoS) Routing with Imprecise State Information

  • Lee Won-Ick;Lee Byeong-Gi
    • Journal of Communications and Networks
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    • v.8 no.1
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    • pp.70-84
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    • 2006
  • We propose a new distributed QoS routing scheme called pre-computation based selective probing (PCSP). The PCSP scheme is designed to provide an exact solution to the constrained optimization problem with moderate overhead, considering the practical environment where the state information available for the routing decision is not exact. It does not limit the number of probe messages, instead, employs a qualitative (or conditional) selective probing approach. It considers both the cost and QoS metrics of the least-cost and the best-QoS paths to calculate the end-to-end cost of the found feasible paths and find QoS-satisfying least-cost paths. It defines strict probing condition that excludes not only the non-feasible paths but also the non-optimal paths. It additionally pre-computes the QoS variation taking into account the impreciseness of the state information and applies two modified QoS-satisfying conditions to the selection rules. This strict probing condition and carefully designed probing approaches enable to strictly limit the set of neighbor nodes involved in the probing process, thereby reducing the message overhead without sacrificing the optimal properties. However, the PCSP scheme may suffer from high message overhead due to its conservative search process in the worst case. In order to bound such message overhead, we extend the PCSP algorithm by applying additional quantitative heuristics. Computer simulations reveal that the PCSP scheme reduces message overhead and possesses ideal success ratio with guaranteed optimal search. In addition, the quantitative extensions of the PCSP scheme turn out to bound the worst-case message overhead with slight performance degradation.

Study on characteristics of noncontact vibrating displacement sensor (비접촉식 진동 변위센서의 특성에 관한 연구)

  • Cho, C.W.;Cho, S.T.;Yang, K.H.
    • Journal of Power System Engineering
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    • v.15 no.2
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    • pp.13-18
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    • 2011
  • This thesis is about the result of conducting a specific experiment for the development of noncontact vibration displacement sensor for measuring the spindle vibration that is used for conditional monitoring of machinery. One should be careful when using the eddy current type displacement sensor because the sensitivity of it is different according to the quality of the material. While the probe used for nondestructive inspection adopts the effect of transmitting the material by using the high frequency domain, the eddy current type displacement sensor uses the lower frequency of around 1MHz. Also, while the nondestructive probe uses the method of enhancing output by using the resonance zone, the vibration displacement sensor utilizes the stable zone by avoiding the resonance zone. Since the oscillator of the converter uses the "L" element as Probe, its characteristic changes with the variation of a relevant impedance. In other words, if the length of Probe's Cable gets extended (Impedance increase), the sensitivity declines accordingly. The effect of surrounding temperature was small, but the influence of the quality of Sensor Coil used was high. Moreover, following an experimental demonstration of the phenomenon where the sensitivity decreases as the frequency of the tested material increases from a frequency response test, the maximum frequency that could be measured was approximately 1KHz. It was noted that the degree of precision could be maintained by using the gap of the probe in the linear zone at the installation site.

Optimization of Data Recovery using Non-Linear Equalizer in Cellular Mobile Channel (셀룰라 이동통신 채널에서 비선형 등화기를 이용한 최적의 데이터 복원)

  • Choi, Sang-Ho;Ho, Kwang-Chun;Kim, Yung-Kwon
    • Journal of IKEEE
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    • v.5 no.1 s.8
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    • pp.1-7
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    • 2001
  • In this paper, we have investigated the CDMA(Code Division Multiple Access) Cellular System with non-linear equalizer in reverse link channel. In general, due to unknown characteristics of channel in the wireless communication, the distribution of the observables cannot be specified by a finite set of parameters; instead, we partitioned the m-dimensional sample space Into a finite number of disjointed regions by using quantiles and a vector quantizer based on training samples. The algorithm proposed is based on a piecewise approximation to regression function based on quantiles and conditional partition moments which are estimated by Robbins Monro Stochastic Approximation (RMSA) algorithm. The resulting equalizers and detectors are robust in the sense that they are insensitive to variations in noise distributions. The main idea is that the robust equalizers and robust partition detectors yield better performance in equiprobably partitioned subspace of observations than the conventional equalizer in unpartitioned observation space under any condition. And also, we apply this idea to the CDMA system and analyze the BER performance.

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RNN-LSTM Based Soil Moisture Estimation Using Terra MODIS NDVI and LST (Terra MODIS NDVI 및 LST 자료와 RNN-LSTM을 활용한 토양수분 산정)

  • Jang, Wonjin;Lee, Yonggwan;Lee, Jiwan;Kim, Seongjoon
    • Journal of The Korean Society of Agricultural Engineers
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    • v.61 no.6
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    • pp.123-132
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    • 2019
  • This study is to estimate the spatial soil moisture using Terra MODIS (Moderate Resolution Imaging Spectroradiometer) satellite data and machine learning technique. Using the 3 years (2015~2017) data of MODIS 16 days composite NDVI (Normalized Difference Vegetation Index) and daily Land Surface Temperature (LST), ground measured precipitation and sunshine hour of KMA (Korea Meteorological Administration), the RDA (Rural Development Administration) 10 cm~30 cm average TDR (Time Domain Reflectometry) measured soil moisture at 78 locations was tested. For daily analysis, the missing values of MODIS LST by clouds were interpolated by conditional merging method using KMA surface temperature observation data, and the 16 days NDVI was linearly interpolated to 1 day interval. By applying the RNN-LSTM (Recurrent Neural Network-Long Short Term Memory) artificial neural network model, 70% of the total period was trained and the rest 30% period was verified. The results showed that the coefficient of determination ($R^2$), Root Mean Square Error (RMSE), and Nash-Sutcliffe Efficiency were 0.78, 2.76%, and 0.75 respectively. In average, the clay soil moisture was estimated well comparing with the other soil types of silt, loam, and sand. This is because the clay has the intrinsic physical property for having narrow range of soil moisture variation between field capacity and wilting point.

Stability Bounds of Unstructured and Time-Varying Delayed State Uncertainties for Discrete Interval Time-Varying System (이산 시변 구간 시스템의 비구조화된 불확실성과 시변 지연시간 상태변수 불확실성의 안정범위)

  • Hyung-seok Han
    • Journal of Advanced Navigation Technology
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    • v.27 no.6
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    • pp.871-876
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    • 2023
  • In this paper, we deal with the stable conditions when two uncertainties exist simultaneously in a linear discrete time-varying interval system with time-varying delay time. The interval system is a system in which system matrices are given in the form of an interval matrix, and this paper targets the system in which the delay time of these interval system matrices and state variables is time-varying. We propose the system stability condition when there is simultaneous unstructured uncertainty that includes nonlinearity and only its magnitude and uncertainty in the system matrix of delayed state variables. The stable bounds for two types of uncertainty are derived as an analytical equation. The proposed stability condition and bounds can include previous stability condition for various linear discrete systems, and the values such as time-varying delay time variation size, uncertainty size, and range of interval matrix are all included in the conditional equation. The new bounds of stability are compared with previous results through numerical example, and its effectiveness and excellence are verified.

Recurrent Neural Network Modeling of Etch Tool Data: a Preliminary for Fault Inference via Bayesian Networks

  • Nawaz, Javeria;Arshad, Muhammad Zeeshan;Park, Jin-Su;Shin, Sung-Won;Hong, Sang-Jeen
    • Proceedings of the Korean Vacuum Society Conference
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    • 2012.02a
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    • pp.239-240
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    • 2012
  • With advancements in semiconductor device technologies, manufacturing processes are getting more complex and it became more difficult to maintain tighter process control. As the number of processing step increased for fabricating complex chip structure, potential fault inducing factors are prevail and their allowable margins are continuously reduced. Therefore, one of the key to success in semiconductor manufacturing is highly accurate and fast fault detection and classification at each stage to reduce any undesired variation and identify the cause of the fault. Sensors in the equipment are used to monitor the state of the process. The idea is that whenever there is a fault in the process, it appears as some variation in the output from any of the sensors monitoring the process. These sensors may refer to information about pressure, RF power or gas flow and etc. in the equipment. By relating the data from these sensors to the process condition, any abnormality in the process can be identified, but it still holds some degree of certainty. Our hypothesis in this research is to capture the features of equipment condition data from healthy process library. We can use the health data as a reference for upcoming processes and this is made possible by mathematically modeling of the acquired data. In this work we demonstrate the use of recurrent neural network (RNN) has been used. RNN is a dynamic neural network that makes the output as a function of previous inputs. In our case we have etch equipment tool set data, consisting of 22 parameters and 9 runs. This data was first synchronized using the Dynamic Time Warping (DTW) algorithm. The synchronized data from the sensors in the form of time series is then provided to RNN which trains and restructures itself according to the input and then predicts a value, one step ahead in time, which depends on the past values of data. Eight runs of process data were used to train the network, while in order to check the performance of the network, one run was used as a test input. Next, a mean squared error based probability generating function was used to assign probability of fault in each parameter by comparing the predicted and actual values of the data. In the future we will make use of the Bayesian Networks to classify the detected faults. Bayesian Networks use directed acyclic graphs that relate different parameters through their conditional dependencies in order to find inference among them. The relationships between parameters from the data will be used to generate the structure of Bayesian Network and then posterior probability of different faults will be calculated using inference algorithms.

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A study on the Seoul Street Monitoring Analysis for Safety Walking Environment - In case of Gangdong-gu - (안전보행환경을 위한 서울거리모니터링 분석에 관한 연구 - 강동구 사례를 중심으로 한 -)

  • Kim, Sung Soo;Cho, Min Gee;Lee, Tae Shik
    • Journal of Korean Society of Disaster and Security
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    • v.6 no.2
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    • pp.31-39
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    • 2013
  • Seoul city has been carried out the actual conditional investigation about street monitoring from January to June of 2013. As the result of this investigation, it has been performed aleady the Seoul city's BSI goal of 2013. The 9,722 cases were reported through the street monitoring activities. Despite of increasing drastically for 1,151 cases's record of 2012, Street monitoring activity appeared wide variations in the region, ages, vocation and gender. Also it depended on 14 outstanding persons of merely 2.2%. They reported 6,546 cases that run to 67.3%. On the basis of Herbert W. Heinrich's law of 1:29:300, the dead of 28, seriously and the slightly injured of 816 and the latent injured of 8,442 were decreased. It respected and protected the 9,287 Seoul citizen's life. This study reseted a definite goal of monitoring and estimated a performance possibility as well as suggested a monitoring expert system, monitor increase, grade evaluation incentive, general evaluation method throughout priority analysis of Gangdong-gu case.

Determination of flood-inducing rainfall and runoff for highly urbanized area based on high-resolution radar-gauge composite rainfall data and flooded area GIS Data

  • Anh, Dao Duc;Kim, Dongkyun;Kim, Soohyun;Park, Jeongha
    • Proceedings of the Korea Water Resources Association Conference
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    • 2019.05a
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    • pp.157-157
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    • 2019
  • This study derived the Flood-Inducing-Rainfall (FIR) and the Flood-Inducing-Runoff (FIRO) from the radar-gage composite data to be used as the basis of the flood warning initiation for the urban area of Seoul. For this, we derived the rainfall depth-duration relationship for the 261 flood events at 239 watersheds during the years 2010 and 2011 based on the 10-minute 1km-1km radar-gauge composite rainfall field. The relationship was further refined by the discrete ranges of the proportion of the flooded area in the watershed (FP) and the coefficient variation of the rainfall time series (CV). Then, the slope of the straight line that contains all data points in the depth-duration relationship plot was determined as the FIR for the specified range of the FP and the CV. Similar methodology was applied to derive the FIRO, which used the runoff depths that were estimated using the NRCS Curve Number method. We found that FIR and FIRO vary at the range of 37mm/hr-63mm/hr and the range of 10mm/hr-42mm/hr, respectively. The large variability was well explained by the FP and the CV: As the FP increases, FIR and FIRO increased too, suggesting that the greater rainfall causes larger flooded area; as the rainfall CV increases, FIR and FIRO decreased, which suggests that the temporally concentrated rainfall requires less total of rainfall to cause the flood in the area. We verified our result against the 21 flood events that occurred for the period of 2012 through 2015 for the same study area. When the 5 percent of the flooded area was tolerated, the ratio of hit-and-miss of the warning system based on the rainfall was 44.2 percent and 9.5 percent, respectively. The ratio of hit-and-miss of the warning system based on the runoff was 67 percent and 4.7 percent, respectively. Lastly, we showed the importance of considering the radar-gauge composite rainfall data as well as rainfall and runoff temporal variability in flood warning system by comparing our results to the ones based on the gauge-only or radar-only rainfall data and to the one that does not account for the temporal variability.

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Dynamic of heat production partitioning in rooster by indirect calorimetry

  • Rony Lizana, Riveros;Rosiane, de Sousa Camargos;Marcos, Macari;Matheus, de Paula Reis;Bruno Balbino, Leme;Nilva Kazue, Sakomura
    • Animal Bioscience
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    • v.36 no.1
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    • pp.75-83
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    • 2023
  • Objective: The objective of this study was to describe a methodological procedure to quantify the heat production (HP) partitioning in basal metabolism or fasting heat production (FHP), heat production due to physical activity (HPA), and the thermic effect of feeding (TEF) in roosters. Methods: Eighteen 54-wk-old Hy Line Brown roosters (2.916±0.15 kg) were allocated in an open-circuit chamber of respirometry for O2 consumption (VO2), CO2 production (VCO2), and physical activity (PA) measurements, under environmental comfort conditions, following the protocol: adaptation (3 d), ad libitum feeding (1 d), and fasting conditions (1 d). The Brouwer equation was used to calculate the HP from VO2 and VCO2. The plateau-FHP (parameter L) was estimated through the broken line model: HP = U×(R-t)×I+L; I = 1 if t<R or I = 0 if t>R; Where the broken-point (R) was assigned as the time (t) that defined the difference between a short and long fasting period, I is conditional, and U is the decreasing rate after the feed was withdrawn. The HP components description was characterized by three events: ad libitum feeding and short and long fasting periods. Linear regression was adjusted between physical activity (PA) and HP to determine the HPA and to estimate the standardized FHP (st-FHP) as the intercept of PA = 0. Results: The time when plateau-FHP was reached at 11.7 h after withdrawal feed, with a mean value of 386 kJ/kg0.75/d, differing in 32 kJ from st-FHP (354 kJ/kg0.75/d). The slope of HP per unit of PA was 4.52 kJ/mV. The total HP in roosters partitioned into the st-FHP, termal effect of feeding (TEF), and HPA was 56.6%, 25.7%, and 17.7%, respectively. Conclusion: The FHP represents the largest fraction of energy expenditure in roosters, followed by the TEF. Furthermore, the PA increased the variation of HP measurements.