• Title/Summary/Keyword: R&D Input

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Development of Performance Analysis Model for SMEs through Meta-Analysis

  • Heon-Wook Lim
    • International Journal of Advanced Culture Technology
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    • v.11 no.1
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    • pp.171-180
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    • 2023
  • This study is to develop a performance analysis model for SMEs.Based on similar performance indicators through previous studies, performance indicators for SMEs were rewritten.Through the Korean Journal Citation Index (KCI), 75 related data were classified and a comprehensive SME performance analysis model was developed.Performance analysis was divided into two axes and classified into tables.The horizontal axis is the spatial performance range, which is divided into three areas: performance management by department/function, integrated performance management for the entire organization, and governance performance management requiring policy feedback. The vertical axis is subdivided into short-term, mid-term, and long-term by time and growth stage, and is divided into three parts: technical performance according to technological input, economic performance as organizational performance, and social performance for policy utilization. Then, performance indicators were mapped to each column. As a result of the survey, 28% of technical performance was analyzed as a result of frequency analysis, and performance indicators were organized into five categories: IT, R&D, certification, patent, and innovation. Economic performance was divided into 29%, BSC, HRD, logistics, production quality management, financial support, asset management, etc. 6 categories, social performance 43%, ESG, marketing, export, policy support, consulting, cooperation, etc. 7 categories.Limitations of the study include the narrowness of the survey that derived only performance indicators despite being a meta-analysis, and the performance model was mapped and classified according to growth stage and support period.however Insufficiency of validity due to lack of evidence, performance indicators were developed, but there were limitations in utilization for practical use.

BEPU analysis of a CANDU LBLOCA RD-14M experiment using RELAP/SCDAPSIM

  • A.K. Trivedi;D.R. Novog
    • Nuclear Engineering and Technology
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    • v.55 no.4
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    • pp.1448-1459
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    • 2023
  • A key element of the safety analysis is Loss of Coolant Analysis (LOCA) which must be performed using system thermal-hydraulic codes. These codes are extensively validated against separate effect and integral experiments. RELAP/SCDAPSIM is one such code that may be used to predict LBLOCA response in a CANDU reactor. The RD-14M experiment selected for the Best Estimate Plus Uncertainty study is a 44 mm (22.7%) inlet header break test with no Emergency Coolant Injection. This work has two objectives first is to simulate pipe break with RELAP and compare these results to those available from experiment and from comparable TRACE calculations. The second objective is to quantify uncertainty in the fuel element sheath (FES) temperature arising from model coefficient as well as input parameter uncertainties using Integrated Uncertainty Analysis package. RELAP calculated results are found to be in good agreement with those of TRACE and with those of experiments. The base case maximum FES temperature is 335.5 ℃ while that of 95% confidence 95th percentile is 407.41 ℃ for the first order Wilk's formula. The experimental measurements fall within the predicted band and the trends and sensitivities are similar to those reported for the TRACE code.

Design and Implementation of FMCW Radar Based on two-chip for Autonomous Driving Sensor (자율주행센서로서 개발한 2-chip 기반의 FMCW MIMO 레이다 설계 및 구현)

  • Choi, Junhyeok;Park, Shinmyong;Lee, Changhyun;Baek, Seungyeol;Lee, Milim
    • The Journal of the Institute of Internet, Broadcasting and Communication
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    • v.22 no.6
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    • pp.43-49
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    • 2022
  • FMCW(Frequency Modulated Continuous Wave) Radar is very useful for vehicle collision warning system and autonomous driving sensor. In this paper, the design and implementation of FMCW radar based on two chip MMIC developed as an autonomous driving sensor was described. Especially, generation of frame-based and chirp-based waveform generation and signal processing are mixed to have the strength of maximum detection speed and compensation of speed. This implemented system was analyzed for performance and commercialization potential through lab. test and driving test in K-city.

Relay-assisted multiuser MIMO-DQSM system for correlated fading channels

  • Francisco R. Castillo-Soria;Carlos Gutierrez;Fermin M. Maciel-Barboza;Viktor I. Rodriguez Abdala;Jayanta Datta
    • ETRI Journal
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    • v.46 no.2
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    • pp.184-193
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    • 2024
  • This paper presents the performance evaluation of an amplify-and-forward (AF) relay-assisted multiuser multiple input-multiple output (MU-MIMO) downlink transmission system for correlated fading channels. The overall system performance was improved by incorporating a double-quadrature spatial modulation (DQSM) scheme. The bit error rate (BER) performance and detection complexity of the AF-MU-MIMO-DQSM system were analyzed and compared with those of a conventional AF-MU-MIMO system under the same conditions and parameters. The results showed that the correlated fading channel severely affected the performance of systems with higher spectral efficiency (SE). Considering an SE of 12 bpcu/user, the AF-MU-MIMO-DQSM system yielded a gain of up to 3 dB in BER performance compared with that of its conventional counterpart for the analyzed cases. In terms of detection complexity, the AF-MU-MIMO-DQSM system showed a reduction of up to 56 % compared with that of the conventional system for the optimal maximum likelihood detection criterion.

Enhancing Autonomous Vehicle RADAR Performance Prediction Model Using Stacking Ensemble (머신러닝 스태킹 앙상블을 이용한 자율주행 자동차 RADAR 성능 향상)

  • Si-yeon Jang;Hye-lim Choi;Yun-ju Oh
    • Journal of Internet Computing and Services
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    • v.25 no.2
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    • pp.21-28
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    • 2024
  • Radar is an essential sensor component in autonomous vehicles, and the market for radar applications in this context is steadily expanding with a growing variety of products. In this study, we aimed to enhance the stability and performance of radar systems by developing and evaluating a radar performance prediction model that can predict radar defects. We selected seven machine learning and deep learning algorithms and trained the model with a total of 49 input data types. Ultimately, when we employed an ensemble of 17 models, it exhibited the highest performance. We anticipate that these research findings will assist in predicting product defects at the production stage, thereby maximizing production yield and minimizing the costs associated with defective products.

Evaluation of Performance of Artificial Neural Network based Hardening Model for Titanium Alloy Considering Strain Rate and Temperature (티타늄 합금의 변형률속도 및 온도를 고려한 인공신경망 기반 경화모델 성능평가)

  • M. Kim;S. Lim;Y. Kim
    • Transactions of Materials Processing
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    • v.33 no.2
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    • pp.96-102
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    • 2024
  • This study addresses evaluation of performance of hardening model for a titanium alloy (Ti6Al4V) based on the artificial neural network (ANN) regarding the strain rate and the temperature. Uniaxial compression tests were carried out at different strain rates from 0.001 /s to 10 /s and temperatures from 575 ℃ To 975 ℃. Using the experimental data, ANN models were trained and tested with different hyperparameters, such as size of hidden layer and optimizer. The input features were determined with the equivalent plastic strain, strain rate, and temperature while the output value was set to the equivalent stress. When the number of data is sufficient with a smooth tendency, both the Bayesian regulation (BR) and the Levenberg-Marquardt (LM) show good performance to predict the flow behavior. However, only BR algorithm shows a predictability when the number of data is insufficient. Furthermore, a proper size of the hidden layer must be confirmed to describe the behavior with the limited number of the data.

Building a Traffic Accident Frequency Prediction Model at Unsignalized Intersections in Urban Areas by Using Adaptive Neuro-Fuzzy Inference System (적응 뉴로-퍼지를 이용한 도시부 비신호교차로 교통사고예측모형 구축)

  • Kim, Kyung Whan;Kang, Jung Hyun;Kang, Jong Ho
    • KSCE Journal of Civil and Environmental Engineering Research
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    • v.32 no.2D
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    • pp.137-145
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    • 2012
  • According to the National Police Agency, the total number of traffic accidents which occurred in 2010 was 226,878. Intersection accidents accounts for 44.8%, the largest portion of the entire traffic accidents. An research on the signalized intersection is constantly made, while an research on the unsignalized intersection is yet insufficient. This study selected traffic volume, road width, and sight distance as the input variables which affect unsignalized intersection accidents, and number of accidents as the output variable to build a model using ANFIS(Adaptive Neuro-Fuzzy Inference System). The forecast performance of this model is evaluated by comparing the actual measurement value with the forecasted value. The compatibility is evaluated by R2, the coefficient of determination, along with Mean Absolute Error (MAE) and Mean Square Error (MSE), the indicators which represent the degree of error and distribution. The result shows that the $R^2$ is 0.9817, while MAE and MSE are 0.4773 and 0.3037 respectively, which means that the explanatory power of the model is quite decent. This study is expected to provide the basic data for establishment of safety measure for unsignalized intersection and the improvement of traffic accidents.

Analysis of QRS-wave Using Wavelet Transform of Electrocardiogram (웨이블릿 변환을 이용한 심전도의 QRS파 신호 분석)

  • Choi, Chang-Hyun;Kim, Yong-Joo;Kim, Tae-Hyeong;Ahn, Yong-Hee;Shin, Dong-Ryeol
    • Journal of Biosystems Engineering
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    • v.33 no.5
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    • pp.317-325
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    • 2008
  • The electrocardiogram (ECG) measurement system consists of I/O interface to input the ECG signals from two electrodes, FPGA (Field programmable gate arrays) module to process the signal conditioning, and real time module to control the system. The algorithms based on wavelet transform were developed to remove the noise of the ECG signals and to determine the QRS-waves. Triangular wave tests were conducted to determine the optimal factors of the wavelet filter by analyzing the SNRs (signal to noise ratios) and RMSEs (root mean square errors). The hybrid rule, soft method, and symlets of order 5 were selected as thresholding rule, thresholding method, and mother wavelet, respectively. The developed wavelet filter showed good performance to remove the noise of the triangular waves with 10.98 dB of SNR and 0.140 mV of RMSE. The ECG signals from a total of 6 subjects were measured at different measuring postures such as lying, sitting, and standing. The durations of QRS-waves, the amplitudes of R-waves, the intervals of RR-waves were analyzed by using the finite impulse response (FIR) filter and the developed wavelet filter. The wavelet filter showed good performance to determine the features of QRS-waves, but the FIR filter had some problems to detect the peaks of Q and S waves. The measuring postures affected accuracy and precision of the ECG signals. The noises of the ECG signals were increased due to the movement of the subject during measurement. The results showed that the wavelet filter was a useful tool to remove the noise of the ECG signals and to determine the features of the QRS-waves.

A new approach to estimate the factor of safety for rooted slopes with an emphasis on the soil property, geometry and vegetated coverage

  • Maedeh, Pouyan Abbasi;Wu, Wei;da Fonseca, Antonio Viana;Irdmoosa, Kourosh Ghaffari;Acharya, Madhu Sudan;Bodaghi, Ehsan
    • Advances in Computational Design
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    • v.3 no.3
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    • pp.269-288
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    • 2018
  • 180 different 2D numerical analyses have been carried out to estimate the factor of safety (FOS) for rooted slopes. Four different types of vegetated coverage and a variety of slope geometry considering three types of soil have been evaluated in this study. The highly influenced parameters on the slope's FOS are determined. They have been chosen as the input parameters for developing a new practical relationship to estimate the FOS with an emphasis on the roots effects. The dependency of sliding mode and shape considering the soil and roots-type has been evaluated by using the numerical finite element model. It is observed that the inclination and height of the slope and the coverage type are the most important effective factors in FOS. While the soil strength parameters and its physical properties would be considered as the second major group that affects the FOS. Achieved results from the developed relationship have shown the acceptable estimation for the roots slope. The extracted R square from the proposed relationship considering nonlinear estimation has been achieved up to 0.85. As a further cross check, the achieved R square from a multi-layer neural network has also been observed to be around 0.92. The numerical verification considering different scenarios has been done in the current evaluation.

A Study on the Development of a Simulation Model for Predicting Soil Moisture Content and Scheduling Irrigation (토양수분함량 예측 및 계획관개 모의 모형 개발에 관한 연구(I))

  • 김철회;고재군
    • Magazine of the Korean Society of Agricultural Engineers
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    • v.19 no.1
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    • pp.4279-4295
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    • 1977
  • Two types of model were established in order to product the soil moisture content by which information on irrigation could be obtained. Model-I was to represent the soil moisture depletion and was established based on the concept of water balance in a given soil profile. Model-II was a mathematical model derived from the analysis of soil moisture variation curves which were drawn from the observed data. In establishing the Model-I, the method and procedure to estimate parameters for the determination of the variables such as evapotranspirations, effective rainfalls, and drainage amounts were discussed. Empirical equations representing soil moisture variation curves were derived from the observed data as the Model-II. The procedure for forecasting timing and amounts of irrigation under the given soil moisture content was discussed. The established models were checked by comparing the observed data with those predicted by the model. Obtained results are summarized as follows: 1. As a water balance model of a given soil profile, the soil moisture depletion D, could be represented as the equation(2). 2. Among the various empirical formulae for potential evapotranspiration (Etp), Penman's formula was best fit to the data observed with the evaporation pans and tanks in Suweon area. High degree of positive correlation between Penman's predicted data and observed data with a large evaporation pan was confirmed. and the regression enquation was Y=0.7436X+17.2918, where Y represents evaporation rate from large evaporation pan, in mm/10days, and X represents potential evapotranspiration rate estimated by use of Penman's formula. 3. Evapotranspiration, Et, could be estimated from the potential evapotranspiration, Etp, by introducing the consumptive use coefficient, Kc, which was repre sensed by the following relationship: Kc=Kco$.$Ka+Ks‥‥‥(Eq. 6) where Kco : crop coefficient Ka : coefficient depending on the soil moisture content Ks : correction coefficient a. Crop coefficient. Kco. Crop coefficients of barley, bean, and wheat for each growth stage were found to be dependent on the crop. b. Coefficient depending on the soil moisture content, Ka. The values of Ka for clay loam, sandy loam, and loamy sand revealed a similar tendency to those of Pierce type. c. Correction coefficent, Ks. Following relationships were established to estimate Ks values: Ks=Kc-Kco$.$Ka, where Ks=0 if Kc,=Kco$.$K0$\geq$1.0, otherwise Ks=1-Kco$.$Ka 4. Effective rainfall, Re, was estimated by using following relationships : Re=D, if R-D$\geq$0, otherwise, Re=R 5. The difference between rainfall, R, and the soil moisture depletion D, was taken as drainage amount, Wd. {{{{D= SUM from { {i }=1} to n (Et-Re-I+Wd)}}}} if Wd=0, otherwise, {{{{D= SUM from { {i }=tf} to n (Et-Re-I+Wd)}}}} where tf=2∼3 days. 6. The curves and their corresponding empirical equations for the variation of soil moisture depending on the soil types, soil depths are shown on Fig. 8 (a,b.c,d). The general mathematical model on soil moisture variation depending on seasons, weather, and soil types were as follow: {{{{SMC= SUM ( { C}_{i }Exp( { - lambda }_{i } { t}_{i } )+ { Re}_{i } - { Excess}_{i } )}}}} where SMC : soil moisture content C : constant depending on an initial soil moisture content $\lambda$ : constant depending on season t : time Re : effective rainfall Excess : drainage and excess soil moisture other than drainage. The values of $\lambda$ are shown on Table 1. 7. The timing and amount of irrigation could be predicted by the equation (9-a) and (9-b,c), respectively. 8. Under the given conditions, the model for scheduling irrigation was completed. Fig. 9 show computer flow charts of the model. a. To estimate a potential evapotranspiration, Penman's equation was used if a complete observed meteorological data were available, and Jensen-Haise's equation was used if a forecasted meteorological data were available, However none of the observed or forecasted data were available, the equation (15) was used. b. As an input time data, a crop carlender was used, which was made based on the time when the growth stage of the crop shows it's maximum effective leaf coverage. 9. For the purpose of validation of the models, observed data of soil moiture content under various conditions from May, 1975 to July, 1975 were compared to the data predicted by Model-I and Model-II. Model-I shows the relative error of 4.6 to 14.3 percent which is an acceptable range of error in view of engineering purpose. Model-II shows 3 to 16.7 percent of relative error which is a little larger than the one from the Model-I. 10. Comparing two models, the followings are concluded: Model-I established on the theoretical background can predict with a satisfiable reliability far practical use provided that forecasted meteorological data are available. On the other hand, Model-II was superior to Model-I in it's simplicity, but it needs long period and wide scope of observed data to predict acceptable soil moisture content. Further studies are needed on the Model-II to make it acceptable in practical use.

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