• Computers and Concrete
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• v.21 no.6
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• pp.697-703
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• 2018

Compressive strength is one of the most important engineering properties of concrete, and testing of the compressive strength of concrete specimens is often costly and time consuming. In order to provide the time for concrete form removal, re-shoring to slab, project scheduling and quality control, it is necessary to predict the concrete strength based upon the early strength data. However, concrete compressive strength is affected by many factors, such as quality of raw materials, water cement ratio, ratio of fine aggregate to coarse aggregate, age of concrete, compaction of concrete, temperature, relative humidity and curing of concrete. The concrete compressive strength is a quite nonlinear function that changes depend on the materials used in the concrete and the time. This paper presents an adaptive neuro-fuzzy inference system (ANFIS) for the prediction of concrete compressive strength. The training of fuzzy system was performed by a hybrid method of gradient descent method and least squares algorithm, and the subtractive clustering algorithm (SCA) was utilized for optimizing the number of fuzzy rules. Experimental data on concrete compressive strength in the literature were used to validate and evaluate the performance of the proposed ANFIS model. Further, predictions from three models (the back propagation neural network model, the statistics model, and the ANFIS model) were compared with the experimental data. The results show that the proposed ANFIS model is a feasible, efficient, and accurate tool for predicting the concrete compressive strength.

• Journal of Nuclear Fuel Cycle and Waste Technology(JNFCWT)
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• v.20 no.1
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• pp.23-32
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• 2022

Pyroprocessing is a promising technology for managing spent nuclear fuel. The nuclear material accounting of feed material is a challenging issue in safeguarding pyroprocessing facilities. The input material in pyroprocessing is in a solid-state, unlike the solution state in an input accountability tank used in conventional wet-type reprocessing. To reduce the uncertainty of the input material accounting, a double-stage homogenization process is proposed in considering the process throughput, remote controllability, and remote maintenance of an engineering-scale pyroprocessing facility. This study tests two types of mixing equipment in the proposed double-stage homogenization process using surrogate materials. The expected heterogeneity and accounting uncertainty of Pu are calculated based on the surrogate test results. The heterogeneity of Pu was 0.584% obtained from Pressurized Water Reactor (PWR) spent fuel of 59 WGd/tU when the relative standard deviation of the mass ratio, tested from the surrogate powder, is 1%. The uncertainty of the Pu accounting can be lower than 1% when the uncertainty of the spent fuel mass charged into the first mixers is 2%, and the uncertainty of the first sampling mass is 5%.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.49 no.7
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• pp.32-38
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• 2012

In this paper, to eliminate intersymbol interference of the received signal due to multipath propagation, a parallel equalization algorithm using two error estimation functions is proposed. In the proposed algorithm, multilevel two-dimensional signals are considered as equivalent binary signals, then error signals are estimated using the sigmoid nonlinearity effective at the initial phase equalization and threshold nonlinearity with high steady-state performance. The two errors are scaled by a weight depending on the relative accuracy of the two error estimations, then two filters are updated differentially. As a result, the combined output of two filters was to be the optimum value, fast convergence at initial stage of equalization and low steady-state error level were achieved at the same time thanks to the combining effect of two operation modes smoothly. Usefulness of the proposed algorithm was verified and compared with the conventional method through computer simulations.

• Journal of the Society of Naval Architects of Korea
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• v.50 no.4
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• pp.217-223
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• 2013

This paper presents the wet damping estimation of the segmented hull model using the random decrement technique together with the continuous wavelet transform. The tested 16 sea states are grouped together based on the speed of the ship in order to figure out the possible influence of the ship speed on the damping ratio. The measured time histories of vertical bending moment for each tested sea state were processed with random decrement technique to derive the free decay signal, from which the damping ratios are estimated. Also, the autocorrelation functions of the filtered signal were calculated and comparison was made with the free decay signal obtained from the random decrement technique. Then the wet damping ratios for each sea state group, as well as precise wet natural frequencies, are estimated by using continuous wavelet transform. It turned out that the wet natural frequencies derived from the measured signal did not show any significant discrepancy compared with those obtained by wet hammering test, whereas the damping ratio did. It was considered that the discrepancy of the damping ratio between in calm and moving water may be attributed to the viscous effects caused by dramatically different flow pattern and relative velocity between the vibrating structure and surrounding fluid particles.

• Proceedings of the KIEE Conference
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• 2011.07a
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• pp.1738-1739
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• 2011

In this paper, the range difference based the moving target tracking problem using multiple UAVs is solved within the new framework of linear robust state estimation. To do this, the relative kinematics is modeled as an uncertain linear system containing stochastic parametric uncertainties in its measurement matrix. Applying the non-conservative robust Kalman filter for the uncertain system, a quasi-optimal linear target tracking filter is designed. For its recursive linear filter structure, the proposed method can ensure the fast convergence and reliable target tracking performance. Moreover, it is suitable for real-time applications using multiple UAVs.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.4 no.2
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• pp.21-58
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• 2009

The Purpose of this study is working out of the scientific-theoretical and practical recommendations directed on perfection of strategic planning of development of the enterprises of mining and gold mining branch. The methodological basis of research is based on the economic theory developed by a domestic and foreign science. At processing, generalisation and a writing of materials of the master's thesis following methods were applied: - supervision, - comparison, - the analysis and synthesis, - methods of an induction and deduction, - statistical groupings, - average and relative sizes, - the system approach. Finally, the theoretical and practical importance of this research consists that results of research will allow generating a basis of statement of effective system of strategic planning of a long-term sustainable development of the gold mining enterprises reducing risk of acceptance of inefficient strategic decisions. I would like to express many thanks to the NGO "Semey- My Home" and "EastGeoResources" LLP for their help and support in providing the data collection and data analysis stages of my research from 2006.

• Korean Journal of Geomatics
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• v.5 no.1
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• pp.1-6
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• 2005

When merging various datasets the perennial problem of relative weighting arises. In case of two datasets an iterative algorithm has been developed recently that allows the rigorous determination of optimal variance components of type repro-BIQUUE even for large amounts of data, along with the estimation of the joint parameters. Here we shall present this new algorithm, and show its versatility in an example that will entail the merging of two regional geoid estimates (derived from EGM 96 and CHAMP) in terms of certain series expansions which have been proven previously to belong to the most efficient ones (e.g., wavelets, Hardy's multi-quadrics, etc.). Future attempts will be devoted to the sequential merging of altimeter and tide gauge data.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.36 no.1
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• pp.58-67
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• 1987

By use of the real recorded data obtained from a power plant, nonlinear low-order state space models are developed for an once-through type power plant boiler. In order to understand the boiler dynamics and to use for the back-up controller design, the unknown model parameters have been estimated using the nonlinear estimation technique, i.e. Extended Kalman Filter method. It is shown that the simulation results coincide with the measurement data within 5% relative error range, which are acceptable from a back-up controller design point of view.

• Journal of Korean Society for Atmospheric Environment
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• v.13 no.2
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• pp.161-170
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• 1997

The concentrations of dimethylsulfide (DMS) were determined using samples collected from a station located at Kosan, Cheju Island during two field campaigns held in December 1996 and January 1997. The atmospheric DMS concentrations measured at 6-hr intervals during the entire campaign periods, after excluding a few extreme values, spanned in the range of 14 to 410 pptv with mean and 1 SD value of 127 $\pm$ 94 pptv (N=42). Between two month periods during which the field campaigns were conducted, a notable reduction in DMS levels was observed which was comparable to the dramatic shift in air temperature. A considerable difference was also noted in DMS levels, when data were grouped by day/night basis. The cause of unexpected, high day-to-night DMS ratios is best explained in terms of high efficiency of daytime source processes relative to low efficiency of nighttime sink processes due to the characteristics of the study location. The surface water DMS of the study site, although scarcely measured, also behaved similarly to its atmospheric counterpart with its range from 0.3 to 19 nM (N=11). When correlation analysis was conducted between the atmospheric DMS concentration and other concurrently determined parameters, significant correlations were observed from most basic meteorological parameters such as windspeed, relative humidy, and air temperature. However, the existence of "not-so-strong" correlations between air temperature and DMS concentrations relative to other ones indicated that the effect of temperature on DMS behavior must be reflected in more complicated manners at the study site. The sea-to-air flux of DMS was approximated through an application of the mass-balance flux calculation method of Wylie and de Mora (1996) under the assumption that sink mechanism within the marine boundary layer is in steady-state condition with its counterpart, source mechanism. Based on this estimation method, we reached a conclusion that oceanic DMS emitted from the southwest sea of the Korean Peninsula can amount to approximately 9 $\sim$ 36 Gg S $yr^{-1}$.$yr^{-1}$.

• Journal of Korea Multimedia Society
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• v.12 no.10
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• pp.1436-1449
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• 2009

The value of sensing information is decided according to positions of sensor nodes, which are very important in sensor networks. In this paper, we propose a method that estimates positions of nodes by using adjacent node information and received signal strength in a sensor network. With the proposed method, we can find positions of nodes easily because we use information that nodes have. Moreover, we can find distribution easily for all the nodes because we can measure a relative position for a node whose position is not known based on anchor nodes whose positions are already known. We utilized Use case diagram, activity diagram and State machine diagram among several diagrams of UML to implement proposed method in sensor networks that is dynamic system. We can understand exact flow for each function of the proposed method in node position estimation system can be implemented easily. And we can be confirmed that the position of estimated nodes has a little error.