• International conference on construction engineering and project management
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• 2015.10a
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• pp.639-640
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• 2015

Traditional construction planning based on historical data and heuristic adjustment can no longer incorporate all the operational details and guarantee the expected performance. The variation between the expected and the actual production leads to cost overruns or delay. Although predicting reliable productivity on construction site is getting more important, the difficulty of this increases. In this regard, this paper suggested to develop BIM-integrated simulation framework. This framework could predict productivity dynamics by considering factors affecting on construction productivity at operational phase. We developed the following processes; 1) enabling a BIM model to produce input data for simulation; 2) developing the construction operation simulation; 3) running simulation using BIM data and obtaining productivity results. The BIM-integrated simulation framework was tested with structural steel erection model because steel erection work is one of the most critical process influencing on the whole construction budget and duration. We could improve to predict more dynamic productivity from this framework, and this reliable productivity helps construction managers to optimize resource allocation, increase schedule reliability, save storage cost, and reduce material loss.

• Computers and Concrete
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• v.32 no.4
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• pp.373-381
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• 2023

Fly ash, granulated blast furnace slag, marble waste powder, etc. are just some of the by-products of other sectors that the construction industry is looking to include into the many types of concrete they produce. This research seeks to use surrogate machine learning methods to forecast the compressive strength of self-compacting concrete. The surrogate models were developed using Gradient Boosting Machine (GBM), Support Vector Machine (SVM), Random Forest (RF), and Gaussian Process Regression (GPR) techniques. Compressive strength is used as the output variable, with nano silica content, cement content, coarse aggregate content, fine aggregate content, superplasticizer, curing duration, and water-binder ratio as input variables. Of the four models, GBM had the highest accuracy in determining the compressive strength of SCC. The concrete's compressive strength is worst predicted by GPR. Compressive strength of SCC with nano silica is found to be most affected by curing time and least by fine aggregate.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.31 no.4B
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• pp.353-360
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• 2011

The objectives of this study were to analyzes temporal variation of local scour depth in the downstream of weir with shapes. Prediction of maximum or equilibrium scour depth was the main focus of engineers and researchers in the downstream of weir. However, it is necessary to analyzes temporal variation of local scour depth in the downstream of weir to predict real time scour depth. Experiment were performed with various weir shapes like sharp crest and inclined stepped with time variation and non-dimensional scourhole shapes, scour depths were proposed. A formula for predicting scour depths with temporal variation for weir were proposed through non-linear regression analysis. Temporal variation of scour depths could be estimated with suggested formula and 4 input data (Equilibrium scour depth, weir height, overflow depths, and water depth downstream). Suggested formula could make it possible to design a apron and bed protection economically in the downstream of a weir by considering flood duration time.

• Korean Journal of Agricultural and Forest Meteorology
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• v.12 no.4
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• pp.232-237
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• 2010

While global solar radiation is an essential input variable in crop models, the observation stations are relatively sparse compared with other meteorological elements. Instead of using measured solar radiation, the Angstrom-Prescott model estimates have been widely used. Monthly data for solar radiation and sunshine duration are a convenient basis for deriving Angstrom-Prescott coefficients (a, b), but it is uncertain whether daily solar radiation could be estimated with a sufficient accuracy by the monthly data - derived coefficients. We derived the Angstrom-Prescott coefficients from the 25 years observed global solar radiation and sunshine duration data at 18 locations across South Korea. In order to figure out any improvements in estimating daily solar radiation by replacing monthly data with daily data, the coefficients (a, b) for each month were derived separately from daily data and monthly data. Local coefficients for eight validation sites were extracted from the spatially interpolated maps of the coefficients and used to estimate daily solar radiation from September 2008 to August 2009 when, pyranometers were operated at the same sites for validation purpose. Comparison with the measured radiation showed a better performance of the daily data - derived coefficients in estimating daily global solar radiation than the monthly data - derived coefficients, showing 9.3% decrease in the root mean square error (RMSE).

• The Journal of the Acoustical Society of Korea
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• v.25 no.6
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• pp.277-281
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• 2006

This paper presents a method for the automatic recognition of pitch accents over syllables. The method that we propose is based on the time-delay recursive neural network (TDRNN). which is a neural network classifier with two different representation of dynamic context: the delayed input nodes allow the representation of an explicit trajectory F0(t) along time. while the recursive nodes provide long-term context information that reflects the characteristics of pitch accentuation in spoken English. We apply the TDRNN to pitch accent recognition in two forms: in the normal TDRNN. all of the prosodic features (pitch. energy, duration) are used as an entire set in a single TDRNN. while in the distributed TDRNN. the network consists of several TDRNNs each taking a single prosodic feature as the input. The final output of the distributed TDRNN is weighted sum of the output of individual TDRNN. We used the Boston Radio News Corpus (BRNC) for the experiments on the speaker-independent pitch accent recognition. π 1e experimental results show that the distributed TDRNN exhibits an average recognition accuracy of 83.64% over both pitch events and non-events.

• Magazine of the Korean Society of Agricultural Engineers
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• v.31 no.4
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• pp.31-49
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• 1989

It is of the most urgent necessity to get hydrological time series of long duration for the establishment of rational design and operation criterion for the Agricultural hydraulic structures. This study was conducted to select best fitted frequency distribution for the monthly runoff and to simulate long series of generated flows by multi-season first order Markov model with comparison of statistical parameters which are derivated from observed and sy- nthetic flows in the five watersheds along Geum river basin. The results summarized through this study are as follows. 1. Both two parameter gamma and two parameter lognormal distribution were judged to be as good fitted distributions for monthly discharge by Kolmogorov-Smirnov method for goodness of fit test in all watersheds. 2. Statistical parameters were obtained from synthetic flows simulated by two parameter gamma distribution were closer to the results from observed flows than those of two para- meter lognormal distribution in all watersheds. 3. In general, fluctuation for the coefficient of variation based on two parameter gamma distribution was shown as more good agreement with the observed flow than that of two parameter lognormal distribution. Especially, coefficient of variation based on two parameter lognormal distribution was quite closer to that of observed flow during June and August in all years. 4. Monthly synthetic flows based on two parameter gamma distribution are considered to give more reasonably good results than those of two parameter lognormal distribution in the multi-season first order Markov model in all watersheds. 5. Synthetic monthly flows with 100 years for eack watershed were sjmulated by multi- season first order Markov model based on two parameter gamma distribution which is ack- nowledged to fit the actual distribution of monthly discharges of watersheds. Simulated sy- nthetic monthly flows may be considered to be contributed to the long series of discharges as an input data for the development of water resources. 6. It is to be desired that generation technique of synthetic flow in this study would be compared with other simulation techniques for the objective time series.

• Journal of the Korean GEO-environmental Society
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• v.8 no.2
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• pp.41-48
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• 2007

Zevo-valent iron (ZVI) has been widely used in permeable reactive barriers for reducing organic contaminants, such as trichloroethylene (TCE). The rapid reaction time, however, leads to decrease in reactivity and availability of ZVI. Shewanella algae BrY, a strain of dissimilatory iron reducing bacteria, can reduce the oxidized Fe (III) to Fe (II) and reduced Fe (II) can be reused to reduce the contaminant. The effect of Shewanella algae BrY on the reduction of the oxidized ZVI column and further TCE removal in the contaminated groundwater were studied at different flow rates and TCE input concentrations in this study. High input concentration of TCE and flow rate increase the amount of input contaminant and make to lower the effect of reduction by Shewanella algae BrY. Specially, the fast flow rate inhibits the direct contact and implantation on the surface of iron. The reduction of oxidized iron reactive barrier by Shewanella algae BrY can decrease the decreation of duration of PRBs by the precipitation of oxidized iron produced by dechlorination of TCE.

• The Korean Journal of Physiology and Pharmacology
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• v.8 no.1
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• pp.7-15
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• 2004

Nitric oxide (NO) system has been implicated in a wide range of physiological functions in the nervous system. However, the role of NO in regulating the neural activity in the gustatory zone of nucleus tractus solitarius (NTS) has not been established. The present study was aimed to investigate the role of NO in the gustatory NTS neurons. Sprague-Dawley rats, weighing about 50 g, were used. Whole cell patch recording and immunohistochemistry were done to determine the electrophysiological characteristics of the rostral gustatory nucleus of the tractus solitaries and distribution of NO synthases (NOS). Neuronal NOS (nNOS) immunoreactivity was strongly detected along the solitary tract extending from rostral to caudal medulla. Resting membrane potentials of NTS neurons were $-49.2{\pm}2\;mV$ and action potential amplitudes were $68.5{\pm}2\;mV$ with a mean duration measured at half amplitude of $1.7{\pm}0.3\;ms$. Input resistance, determined from the response to a 150 ms, -100 pA hyperpolarizing current pulse, was $385{\pm}15\;M{\Omega}$, Superfusion of SNAP or SNP, NO donors, produced either hyperpolarization (68%), depolarization (5%), or no effect (27%). The hyperpolarization was mostly accompanied by a decrease in input resistance. The hyperpolarization caused by SNAP or SNP increased the time to initiate the first action potential, and decreased the number of action potentials elicited by current injection. SNP or SNAP also markedly decreased the number of firing neural discharges of the spontaneous NTS neural activity under zero current. Superfusion of L-NAME, a NOS inhibitor, slightly depolarized the membrane potential and increased the firing rate of NTS neurons induced by current injection. ODQ, a soluble guanylate cyclase inhibitor, ameliorated the SNAP-induced changes in membrane potential, input resistance and firing rates. 8-Br-cGMP, a non-degradable cell-permeable cGMP, hyperpolarized the membrane potential and decreased the number of action potentials. It is suggested that NO in the gustatory NTS has an inhibitory role on the neural activity of NTS through activating soluble guanylate cyclase.

• Journal of Korean Society of Transportation
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• v.34 no.2
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• pp.158-167
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• 2016

This study evaluates potential sources of errors in k-NN(k-nearest neighbor) algorithm such as procedures, variables, and input data. Previous research has been thoroughly reviewed for understanding fundamentals of k-NN algorithm that has been widely used for short-term traffic states prediction. The framework of this algorithm commonly includes historical data smoothing, pattern database, similarity measure, k-value, and prediction horizon. The outcomes of this study suggests that: i) historical data smoothing is recommended to reduce random noise of measured traffic data; ii) the historical database should contain traffic state information on both normal and event conditions; and iii) trial and error method can improve the prediction accuracy by better searching for the optimum input time series and k-value. The study results also demonstrates that predicted error increases with the duration of prediction horizon and rapidly changing traffic states.

• Journal of IKEEE
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• v.19 no.2
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• pp.186-192
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• 2015

This paper proposes an automatic generation technology of test case based on API in source code for software's quality improvement. The proposed technology is comprised of four processes which are analyzing source code by using the Doxygen open source tool, defining API specification by using analyzed results, creating test design, generating a test case by adapting Pairwise test technology. Analyzing source code by using the Doxygen open source tool is the phase in which API information in source code such as the API name, input parameter and return parameter are extracted. Defined API specification by using analyzed results is the phase where API informations, which is needed to generate test case, are defined as a form of database by SQLite database on the basis of extracted API information. Creating test design is the phase in which the scenario is designed in order to be composed as database by defining threshold of input and return parameters and setting limitations based on the defined API. Generating a test case by adapting Pairwise test technique is the phase where real test cases are created and changed into database by adapting Pairwise technique on the base of test design information. To evaluate the efficiency of proposed technology, the research was conducted by begin compared to specification based test case creation. The result shows wider test coverage which means the more cases were created in the similar duration of time. The reduction of manpower and time for developing products is expected by changing the process of quality improving in software developing from man-powered handwork system into automatic test case generation based on API of source code.