• The Journal of Asian Finance, Economics and Business
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• v.8 no.1
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• pp.563-572
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• 2021

This study aims to investigate the implementation of village fund (VF) policy in Indonesia by addressing the following issues: (1) what is the VF policy; (2) factors that support and hinder policy implementation; (3) impact of policy implementation; and (4) model for implementing village fund policies that can improve community welfare. Through a descriptive qualitative-based approach, several indicators are measured, namely, the substance of implementing rules, the results of project implementation, supporting and inhibiting factors for policies, participation factors, and the impact generated by village fund policies, which include social and economic effects. The extraction of this information and indicators will lead this study to produce ideal models and propositions for quantitative confirmatory research as a future research agenda. This study was conducted in two villages (Mojomulyo and Tambakromo) in Pati District, Central Java, Indonesia. Data collection model using interviews and observations from all actors who play a role (e.g., village government, village supervisory agency, and community). The study results show that policies have been implemented by normative rules; there are several supporting and inhibiting factors both internal and external. The study results also confirm the relevance of the articulated theory and some comprehensive input to our study.

• Korean Journal of Remote Sensing
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• v.34 no.5
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• pp.709-720
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• 2018

In order to optimize the evaluation of biomass in crop monitoring, accurate and timely data of the crop-field are required. Evaluating above-ground biomass helps to monitor crop vitality and to predict yield. Unmanned Aerial Vehicle (UAV) imagery are being assessed for analyzing within field spatial variability for agricultural precision management, because UAV imagery may be acquired quickly during critical periods of rapid crop growth. This study reports on the development of remote sensing techniques for evaluating the biomass of winter crop. Specific objective was to develop statistical models for estimating the dry weight of barley and wheat using a Excess Green index ($E{\times}G$) based Vegetation Fraction (VF) and a Crop Surface Model (CSM) based Plant Height (PH) value. As a result, the multiple linear regression equations consisting of three independent variables (VF, PH, and $VF{\times}PH$) and above-ground dry weight provided good fits with coefficients of determination ($R^2$) ranging from 0.86 to 0.99 with 5 cultivars. In the case of the barley, the coefficient of determination was 0.91 and the root mean squared error of measurement was $102.09g/m^2$. And for the wheat, the coefficient of determination was 0.90 and the root mean squared error of measurement was $110.87g/m^2$. Therefore, it will be possible to evaluate the biomass of winter crop through the UAV image for the crop growth monitoring.

• The Journal of the Acoustical Society of Korea
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• v.40 no.3
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• pp.234-240
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• 2021

In this paper, the mask-based speech enhancement is improved for effective speech recognition in noise environments. In the mask-based speech enhancement, enhanced spectrum is obtained by multiplying the noisy speech spectrum by the mask. The VoiceFilter (VF) model is used as the mask estimation, and the Spectrogram Inpainting (SI) technique is used to remove residual noise of enhanced spectrum. In this paper, we propose a combined loss to further improve speech enhancement. In order to effectively remove the residual noise in the speech, the positive part of the Triplet loss is used with the component loss. For the experiment TIMIT database is re-constructed using NOISEX92 noise and background music samples with various Signal to Noise Ratio (SNR) conditions. Source to Distortion Ratio (SDR), Perceptual Evaluation of Speech Quality (PESQ), and Short-Time Objective Intelligibility (STOI) are used as the metrics of performance evaluation. When the VF was trained with the mean squared error and the SI model was trained with the combined loss, SDR, PESQ, and STOI were improved by 0.5, 0.06, and 0.002 respectively compared to the system trained only with the mean squared error.

• Nuclear Engineering and Technology
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• v.54 no.5
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• pp.1549-1559
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• 2022

As an accident tolerant fuel (ATF) concept, oxide dispersion strengthened Zircaloy-4 (ODS Zry-4) cladding has been developed to enhance the mechanical properties of cladding using laser processing technology. In this study, a simulation technique was established to investigate the mechanical properties and effects of Y₂O₃ particles for the ODS Zry-4. A 3D representative volume element (RVE) model was developed considering the parameters of the size, shape, distribution and volume fraction (VF) of the Y₂O₃ particles. From the 3D RVE model, the Young's modulus, coefficient of thermal expansion (CTE) and creep strain rate of the ODS Zry-4 were effectively calculated. It was observed that the VF of Y₂O₃ particles had a significant effect on the aforementioned mechanical properties. In addition, the predicted properties of ODS Zry-4 were applied to a simulation model to investigate cladding deformation under a transient condition. The ODS Zry-4 cladding showed better performance, such as a delay in large deformation compared to Zry-4 cladding, which was also found experimentally. Accordingly, it is expected that the simulation approach developed here can be efficiently employed to predict more properties and to provide useful information with which to improve ODS Zry-4.

• Wind and Structures
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• v.9 no.4
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• pp.297-313
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• 2006

The concentration of air pollution along roads is higher than the surrounding area because ventilation efficiency has decreased due to the high-density use of space along roads in recent years. In this study, ventilation efficiency around a heavily traffic road covered by an elevated highway and hemmed in along its side by buildings is evaluated using Visitation Frequency (VF, the frequency for pollutant to return to the objective domain) and Purging Flow Rate (PFR, the air flow rate for defining the local domain-averaged concentration). These are analyzed using Computational Fluid Dynamics (CFD) based on the standard $k-{\varepsilon}$ model. The VF and PFR characteristics of four objective domains are analyzed in terms of the changes in wind direction and arrangements of the fencing dividing up and down direction in the road center under the elevated highway. The resulting VFs are more than 1.0 for all cases, which means that pollutants return to the objective domain restricted by the elevated highway and side buildings. The influence of the arrangement of the buildings around the objective domain and the structure in the domain on the VF is substantial. In cases where there are no obstacles under the elevated highway, the local air exchange rate in the domain tends to be improved. Using these indices, the urban ventilation efficiencies between different urban areas can be compared easily.

• 한국정보통신설비학회:학술대회논문집
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• 2007.08a
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• pp.27-30
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• 2007

This paper deals with an equivalent circuit model for RF passive components. Rational functions are obtained from the frequency responses of EM simulation by using Foster canonical partial fraction expressions. The Vector Fitting(VF) and the Adaptive Frequency Sampling(AFS) scheme are also implemented to obtain the rational functions. A passivity enforcement algorithm is applied to ensure the stability of the equivalent circuit model. In order to verify the schemes, S parameters of the equivalent circuit model is compared to those of EM simulation in case of the microstrip line structure with 3 slots in ground.

• Computers and Concrete
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• v.25 no.5
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• pp.433-445
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• 2020

A method is proposed in this paper to estimate the workability of self-compacting concrete (SCC) in different mixing conditions with different mixers and mixing volumes by recording the mixing process based on deep learning (DL). The SCC mixing videos were transformed into a series of image sequences to fit the DL model to predict the SF and VF values of SCC, with four groups in total and approximately thirty thousand image sequence samples. The workability of three groups SCC whose mixing conditions were learned by the DL model, was estimated. One additionally collected group of the SCC whose mixing condition was not learned, was also predicted. The results indicate that whether the SCC mixing condition is included in the training set and learned by the model, the trained model can estimate SCC with different workability effectively at the same time. Our goal to estimate SCC workability in different mixing conditions is achieved.

• The Transactions of the Korea Information Processing Society
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• v.7 no.2S
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• pp.711-720
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• 2000

BADA-IV/XML is a system designed specifically for managing XML. Documents and is essential to various electronic document applications as a fundamental system. BADA-IV/XML supports all of aspects of data model, querying and manipulation operations for managing XML documents. This paper provides an overview of these aspects of the BADA-IV/XML, as well as defines schema classes for stroing, querying and maintaining hierarchical semantics of multimedia documents and structural semantics of complex documents linked with each other, Also a multimedia document query language is designed and implemented to support essential operations for efficient searching and managing multimedia documents. Finally, some simulation results show the performance of the paged VF(Virtual Fragmentation) model and the search model using element's identifier as compared with a general model.

• Computers and Concrete
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• v.11 no.2
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• pp.149-167
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• 2013

The complete stress-strain behavior of steel fiber reinforced concrete in compression is needed for the analysis and design of structures. An experimental investigation was carried out to generate the complete stress-strain curve of high-performance steel fiber reinforced concrete (HPSFRC) with a strength range of 52-80 MPa. The variation in concrete strength was achieved by varying the water-to-cementitious materials ratio of 0.40-0.25 and steel fiber content (Vf = 0.5, 1.0 and 1.5% with l/d = 80 and 55) in terms of fiber reinforcing parameter, at 10% silica fume replacement. The effects of these parameters on the shape of stress-strain curves are presented. Based on the test data, a simple model is proposed to generate the complete stress-strain relationship for HPSFRC. The proposed model has been found to give good correlation with the stress-strain curves generated experimentally. Inclusion of fibers into HPC improved the ductility considerably. Equations to quantify the effect of fibers on compressive strength, strain at peak stress and toughness of concrete in terms of fiber reinforcing index are also proposed, which predicted the test data quite accurately. Compressive strength prediction model was validated with the strength data of earlier researchers with an absolute variation of 2.1%.

• Advances in concrete construction
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• v.10 no.6
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• pp.479-488
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• 2020

The experimental and numerical works were carried out on high performance fiber reinforced concrete (HPFRC) with w/cm ratios ranging from 0.25 to 0.40, fiber volume fraction (Vf)=0-1.5% and 10% silica fume replacement. Improvements in compressive and flexural strengths obtained for HPFRC are moderate and significant, respectively, Empirical equations developed for the compressive strength and flexural strength of HPFRC as a function of fiber volume fraction. A relation between flexural strength and compressive strength of HPFRC with R=0.78 was developed. Due to the complex mix proportions and non-linear relationship between the mix proportions and properties, models with reliable predictive capabilities are not developed and also research on HPFRC was empirical. In this paper due to the inadequacy of present method, a back propagation-neural network (BP-NN) was employed to estimate the 28-day compressive strength of HPFRC mixes. BP-NN model was built to implement the highly non-linear relationship between the mix proportions and their properties. This paper describes the data sets collected, training of ANNs and comparison of the experimental results obtained for various mixtures. On statistical analyses of collected data, a multiple linear regression (MLR) model with R2=0.78 was developed for the prediction of compressive strength of HPFRC mixes, and average absolute error (AAE) obtained is 6.5%. On validation of the data sets by NNs, the error range was within 2% of the actual values. ANN model has given the significant degree of accuracy and reliability compared to the MLR model. ANN approach can be effectively used to estimate the 28-day compressive strength of fibrous concrete mixes and is practical.