• KSCE Journal of Civil and Environmental Engineering Research
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• v.34 no.5
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• pp.1477-1488
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• 2014

Prevalent construction of impermeable pavements in urban areas causes diverse water-related environmental issues, such as lowering ground water levels and shortage of water supply for the living. In order to resolve such problems, a rainwater reservoir can be an effective and useful solution. The rainwater reservoir facilitates the hydrologic cycle in urban areas by temporarily retaining precipitation-runoff within a shallow subsurface layer for later use in a dry season. However, in order to use the stored water of precipitation-runoff, non-point source pollutants mostly retained in initial rainfall should be removed before being stored in the reservoir. Therefore, the purification system to filter out the non-point source pollutants is essential for the rainwater reservoir. The conventional soil filtration technology is well known to be able to capture non-point source pollutants in a economical and efficient way. This study adopted a sand filter layer (SFL) as a non-point source pollutant removal system in the rainwater reservoir, and conducted a series of lab-scale chamber tests and field tests to evaluate the pollutant removal efficiency and applicability of SFL. During the laboratory chamber experiments, three types of SFL with the different grain size characteristics were compared in the chamber with a dimension of $20cm{\times}30cm{\times}60cm$. To evaluate performance of the reservoir systems, the concentration of the polluted water in terms of TSS (Total Suspended Solids) and COD (Chemical Oxygen Demand) were measured and compared. In addition, a reduction in hydraulic conductivity of SFL due to pollutant clogging was indirectly estimated. The optimum SFL selected through the laboratory chamber experiments was verified on the in-situ rainwater reservoir for field applicability.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.40 no.12
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• pp.2469-2475
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• 2015

A structured XML has been widely used to present services on various Web-services. The XML is also used for digital documents and digital signatures and for the representation of multimedia files in email systems. The XML document should be firstly parsed to access elements in the XML. The parsing is the most compute-instensive task in the use of XML documents. Most of the previous work has focused on hardware based XML parsers in order to improve parsing performance, while a little work has studied parsing techniques. We present the high performance parsing technique which can be used all of XML parsers and design hardware based XML parser using an FPGA. The proposed parsing technique uses element analyzers instead of the state machine and performs multibyte-based element matching. As a result, our parsing technique can reduce the number of clock cycles per byte(CPB) and does not need to require any preprocessing, such as loading XML data into memory. Compared to other parsers, our parser acheives 1.33~1.82 times improvement in the system performance. Therefore, the proposed parsing technique can process XML documents in real time and is suitable for applying to all of XML parsers.

• Journal of the Korea Organic Resources Recycling Association
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• v.18 no.3
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• pp.77-86
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• 2010

In this study, the model of the indirect wind suction waste sorting machine for characteristics of the screening of waste was studied using computational fluid dynamics and the drag coefficient for the model and the suction wind speed were obtained. The wind separator are developing by installing a cyclone air outlet to the suction blower impeller waste is selective in a way that does not pass the features and characteristics of the inlet pipe of the pressure loss and separation efficiency can have a significant impact on. Using Wind separator for selection of waste in the waste prior research on the aerodynamic properties are essential. For plastic cases, it is reasonable to take the drag coefficient between 0.8 and 1.0, and for cans, compression depending on whether the cans, the drag coefficient is in the range from 0.2 to 0.7. The separation efficiency of waste as change suction speed was the highest efficiency when the suction speed was 25~26 m/s. Shape of the inlet, depending on how the transfer pipe of the duct pressure loss occurs because the inlet velocity changes through the appropriate design standards to allow for continued research is needed.

• Journal of the Korean Association of Geographic Information Studies
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• v.10 no.3
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• pp.13-21
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• 2007

Recently, very short-term rainfall forecast using radar is required for regional flash flood according to climate change. This research is to evaluate the feasibility of GIS based distributed model using radar rainfall which can express temporal and spatial distribution in actual dam watershed during flood runoff period. Vflo model which was developed Oklahoma university was used as physical based distributed model, and Namgang dam watershed ($2,293km^2$) was applied as study site. Distributed rainfall according to grid resolution was generated by using K-RainVieux, preprocess program of radar rainfall, from JIN radar. Also, GIS hydrological parameters were extracted from basic GIS data such as DEM, land cover and soil map, and used as input data of distributed model(Vflo). Results of this research can provide a base for building of real-time short-term rainfall runoff forecast system according to flash flood in near future.

• Journal of Biomedical Engineering Research
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• v.23 no.3
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• pp.197-205
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• 2002

The objectives of this Paper is to implement a diagnostic classifier of differential laryngeal diseases from acoustic signals acquired in a noisy room. For this Purpose, the voice signals of the vowel /a/ were collected from Patients in a soundproof chamber and got mixed with noise. Then, the acoustic Parameters were analyzed, and hierarchical neural networks were applied to the data classification. The classifier had a structure of five-step hierarchical neural networks. The first neural network classified the group into normal and benign or malign laryngeal disease cases. The second network classified the group into normal or benign laryngeal disease cases The following network distinguished polyp. nodule. Palsy from the benign laryngeal cases. Glottic cancer cases were discriminated into T1, T2. T3, T4 by the fourth and fifth networks All the neural networks were based on multilayer perceptron model which classified non-linear Patterns effectively and learned by an error back-propagation algorithm. We chose some acoustic Parameters for classification by investigating the distribution of laryngeal diseases and Pilot classification results of those Parameters derived from MDVP. The classifier was tested by using the chosen parameters to find the optimum ones. Then the networks were improved by including such Pre-Processing steps as linear and z-score transformation. Results showed that 90% of T1, 100% of T2-4 were correctly distinguished. On the other hand. 88.23% of vocal Polyps, 100% of normal cases. vocal nodules. and vocal cord Paralysis were classified from the data collected in a noisy room.

• Journal of Korean Society for Geospatial Information Science
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• v.16 no.1
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• pp.23-32
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• 2008

According to recent frequent local flash flood due to climate change, the very short-term rainfall forecast using remotely sensed rainfall like radar is necessary to establish. This research is to evaluate the feasibility of GIS-based distributed model coupled with radar rainfall, which can express temporal and spatial distribution, for multipurpose dam operation during flood season. $Vflo^{TM}$ model was used as physically based distributed hydrologic model. The study area was Yongdam dam basin ($930\;km^2$) and the 3 storm events of local convective rainfall in August 2005, and the typhoon.Ewiniar.and.Bilis.collected from Jindo radar was adopted for runoff simulation. Distributed rainfall consistent with hydrologic model grid resolution was generated by using K-RainVieux, pre-processor program for radar rainfall. The local bias correction for original radar rainfall shows reasonable results of which the percent error from the gauge observation is less than 2% and the bias value is $0.886{\sim}0.908$. The parameters for the $Vflo^{TM}$ were estimated from basic GIS data such as DEM, land cover and soil map. As a result of the 3 events of multiple peak hydrographs, the bias of total accumulated runoff and peak flow is less than 20%, which can provide a reasonable base for building operational real-time short-term rainfall-runoff forecast system.

• Journal of Korean Society for Geospatial Information Science
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• v.18 no.4
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• pp.21-30
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• 2010

In this paper, the parallel distributed rainfall runoff model(K-DRUM) using MPI(Message Passing Interface) technique was developed to solve the problem of calculation time as it is one of the demerits of the distributed model for performing physical and complicated numerical calculations for large scale watersheds. The K-DRUM model which is based on GIS can simulate temporal and spatial distribution of surface flow and sub-surface flow during flood period, and input parameters of ASCII format as pre-process can be extracted using ArcView. The comparison studies were performed with various domain divisions in Namgang Dam watershed in case of typoon 'Ewiniar' at 2006. The numerical simulation using the cluster system was performed to check a parallelization effectiveness increasing the domain divisions from 1 to 25. As a result, the computer memory size reduced and the calculation time was decreased with increase of divided domains. And also, the tool was suggested in order to decreasing the discharge error on each domain connections. The result shows that the calculation and communication times in each domain have to repeats three times at each time steps in order to minimization of discharge error.

• Journal of Korea Water Resources Association
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• v.41 no.3
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• pp.341-351
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• 2008

Since the damage from the torrential rain increases recently due to climate change and global warming, the significance of flood forecasting and warning becomes important in medium and small streams as well as large river. Through the preprocess and main processes for estimating runoff, diverse errors occur and are accumulated, so that the outcome contains the errors in the existing flood forecasting and warning method. And estimating the parameters needed for runoff models requires a lot of data and the processes contain various uncertainty. In order to overcome the difficulties of the existing flood forecasting and warning system and the uncertainty problem, ANFIS(Adaptive Neuro-Fuzzy Inference System) technique has been presented in this study. ANFIS, a data driven model using the fuzzy inference theory with neural network, can forecast stream level only by using the precipitation and stream level data in catchment without using a lot of physical data that are necessary in existing physical model. Time series data for precipitation and stream level are used as input, and stream levels for t+1, t+2, and t+3 are forecasted with this model. The applicability and the appropriateness of the model is examined by actual rainfall and stream level data from 2003 to 2005 in the Tancheon catchment area. The results of applying ANFIS to the Tancheon catchment area for the actual data show that the stream level can be simulated without large error.

• The KIPS Transactions:PartA
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• v.11A no.4
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• pp.243-250
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• 2004

Monitoring is used to see if a real-time system provides a service on time. Generally, monitoring for real-time focuses on investigating the current status of a real-time system. To support a stable performance of a real-time system, it should have not only a function to see the current status of real-time process but also a function to predict executions of real-time processes, however. The legacy prediction model has some limitation to apply it to a real-time monitoring. First, it performs a static prediction after a real-time process finished. Second, it needs a statistical pre-analysis before a prediction. Third, transition probability and data about clustering is not based on the current data. We propose the execution prediction model based on learning algorithm to solve these problems and apply it to real-time monitoring. This model gets rid of unnecessary pre-processing and supports a precise prediction based on current data. In addition, this supports multi-level prediction by a trend analysis of past execution data. Most of all, We designed the model to support dynamic prediction which is performed within a real-time process' execution. The results from some experiments show that the judgment accuracy is greater than 80% if the size of a training set is set to over 10, and, in the case of the multi-level prediction, that the prediction difference of the multi-level prediction is minimized if the number of execution is bigger than the size of a training set. The execution prediction model proposed in this model has some limitation that the model used the most simplest learning algorithm and that it didn't consider the multi-regional space model managing CPU, memory and I/O data. The execution prediction model based on a learning algorithm proposed in this paper is used in some areas related to real-time monitoring and control.

• The Korean Journal of Pesticide Science
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• v.17 no.4
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• pp.264-270
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• 2013

Imidacloprid is a systemic insecticide which act as an insect neurotoxin. It used for control of pest such as aphids and other sucking insects in fruits and vegetables. Systemic pesticides move inside a crop following absorption by the plant, and these were converted into a variety of metabolites. Sometimes these metabolites make a problem about safety of agricultural products. So a simultaneous determination method of pesticide and its metabolites is needed, to monitor their presence in agricultural product and study on the fate of pesticide in a plant. This study's aim is to investigate simultaneous analysis method of imidacloprid and its metabolites, imidacloprid guanidine, imidacloprid olefin, imidacloprid urea, and 6-chloronicotinic acid in red pepper using QuEChERS method and LC-MS/MS systems. QuEChERS method was modifed beacuase $MgSO_4$ salts decreased the recoveries of 6-chloronicotinic acid in extraction procedure. Imidacloprid and its metabolites were extracted by acetonitrile with 1% glacial acetic acid and the extracts were purified through QuEChERS with primary secondary amine (PSA) and $C_{18}$ and analyzed with LC-MS/MS in ESI positive mode. Standard calibration curves were made by matrix matched standards and their correlation coefficients were higher than 0.999. Recovery studies were carried out on spiked pepper blank sample at four concentration levels (0.01, 0.04 and 0.1, 0.4 mg/kg). The average recoveries of imidacloprid and its metabolites were in the range of 70~120% with < 20% RSD. This result indicated that the method using QuEChERS and LC-MS/MS was suitable for the simultaneous determination of imidacloprid and its metabolites in red pepper.