• International Journal of CAD/CAM
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• v.6 no.1
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• pp.9-17
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• 2006

Performing inspections for Hull Condition Monitoring and Assessment as stipulated in IACS unified requirements and IMO's Condition Assessment Scheme (CAS) IMO Resolution MEPC.94(46), 2001, Condition Assessment Scheme, IMO Resolution MEPC.111(50), 2003, Amendments to regulation 13G, addition of new regulation 13H involves a huge amount of measurement data to be collected, processed, analysed and maintained. Information to be recorded consists of thickness measurements and visual assessment of coating and cracks. The amount of data and increasing requirements with respect to condition assessment demand efficient computer support. Currently, due to the lack of standardization for this kind of data, the thickness measurements are recorded manually on ship drawings or tables. In this form, handling of the measurements is tedious and error-prone and assessment is difficult. Data reporting and analysis takes a long time, leading to some repairs being performed only at the next docking of the ship or making an additional docking necessary. The recently started ED funded project CAS addresses this topic and develops-as a first step-a data model for Hull Condition Monitoring and Assessment (HCMA) based on XML-technology. The model includes simple geometry representation to facilitate a graphically supported data collection as well as an easy visualisation of the measurement results. In order to ensure compatibility with the current way of working, the content of the data model is strictly confined to the requirements of the measurement process. Appropriate data interfaces to classification software will enable rapid assessment by the classification societies, thus improving the process in terms of time and cost savings. In particular, decision-making can be done while the ship is still in the dock for maintenance.

• Food Science of Animal Resources
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• v.35 no.1
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• pp.108-113
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• 2015

The purpose of this study was to develop predictive models for the growth of Listeria monocytogenes in pork Bulgogi at various storage temperatures. A two-strain mixture of L. monocytogenes (ATCC 15313 and isolated from pork Bulgogi) was inoculated on pork Bulgogi at 3 Log CFU/g. L. monocytogenes strains were enumerated using general plating method on Listeria selective medium. The inoculated samples were stored at 5, 15, and $25^{\circ}C$ for primary models. Primary models were developed using the Baranyi model equations, and the maximum specific growth rate was shown to be dependent on storage temperature. A secondary model of growth rate as a function of storage temperature was also developed. As the storage temperature increased, the lag time (LT) values decreased dramatically and the specific growth rate of L. monocytogenes increased. The mathematically predicted growth parameters were evaluated based on the modified bias factor ($B_f$), accuracy factor ($A_f$), root mean square error (RMSE), coefficient of determination ($R^2$), and relative errors (RE). These values indicated that the developed models were reliably able to predict the growth of L. monocytogenes in pork Bulgogi. Hence, the predictive models may be used to assess microbiological hygiene in the meat supply chain as a function of storage temperature.

• Journal of Environmental Science International
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• v.22 no.5
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• pp.555-562
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• 2013

Jeju Island, the heaviest raining area in Korea, is a volcanic Island located at the southernmost of Korea, but most streams are of the dry due to its hydrological/geological characteristics different from those of inland areas. Therefore, there are limitations in applying the results from the mainland to the studies on stream run-off characteristics analysis and water resource analysis of Jeju Island. In this study, the SWAT(soil & water assessment tool) model is used for the Hwabuk stream watershed located east of the downtown to calculate the long-term stream run-off rate, and WMS(watershed modeling system) and HEC-HMS(hydrologic modeling system) models are used to figure out the stream run-off characteristics due to short-term heavy rainfall. As the result of SWAT modelling for the long-term rainfall-runoff model for Hwabuk stream watershed in 2008, 5.66% of the average precipitation of the entire basin was run off, with 3.47% in 2009, 8.12% in 2010, and root mean square error(RMSE) and determination coefficient($R^2$) was 496.9 and 0.87, respectively, with model efficient(ME) of 0.72. From the results of WMS and HEC-HMS models which are short-term rainfall-runoff models, unless there was a preceding rainfall, the runoff occurred only for rainfall of 40mm or greater, and the run-off duration averaged 10~14 hours.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.10 no.3
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• pp.459-466
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• 2006

Numerical values of thermodynamic properties such as temperature, pressure, dryness, volume, enthalpy and entropy are required in numerical analysis on evaluating the thermal performance. But the steam table itself cannot be used without modelling. From this point of view the neural network with function approximation characteristics can be an alternative. the multi-layer neural networks were made for saturated vapor region and superheated vapor region separately. For saturated vapor region the neural network consists of one input layer with 1 node, two hidden layers with 10 and 20 nodes each and one output layer with 7 nodes. For superheated vapor region it consists of one input layer with 2 nodes, two hidden layers with 15 and 25 nodes each and one output layer with 3 nodes. The proposed model gives very successful results with ${\pm}0.005%$ of percentage error for temperature, enthalpy and entropy and ${\pm}0.025%$ for pressure and specific volume. From these successful results, it is confirmed that the neural networks could be powerful method in function approximation of the steam table.

• Environmental Engineering Research
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• v.25 no.4
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• pp.479-487
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• 2020

Current assumptions are used in the formulation of pseudo-first (PFO) and second-order (PSO) models to describe the kinetic data of filtration based on ideal operating conditions. This paper presents a new model developed with pseudo n^th order and based on real assumption. A comparison was performed between PFO, PSO and the new model to highlight their performance and the optimisation of the pseudo-order equation, using MATLAB software. Adsorption characteristic of bovine serum albumin adsorption on the track-etched membrane are used as a medium based on protein filtration data were extracted from the literature for different concentrations to demonstrate the comparison between PFO/PSO and the new model. The pseudo first and second-order kinetic models were applied to test the experimental data and they did not provide reasonable values. The results show that the predicted values are consistent with experimental values giving a good correlation coefficient R² = 0.997 and a minimum root mean squared error RMSE = 0.0171. Indeed, the experimental results follow the new model and the optimal pseudo equation order n = 1.115, the most suitable curves for the new model. As a result, we used different experimental adsorption data from the literature to examine and check the applicability and validity of the model.

• Journal of Environmental Impact Assessment
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• v.20 no.5
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• pp.705-716
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• 2011

For the efficient discovery of knowledge and information from the observed systems, data mining techniques can be an useful tool for the prediction of water quality at intake station in rivers. Deterioration of water quality can be caused at intake station in dry season due to insufficient flow. This demands additional outflow from dam since some extent of deterioration can be attenuated by dam reservoir operation to control outflow considering predicted water quality. A seasonal occurrence of high ammonia nitrogen ($NH_3$-N) concentrations has hampered chemical treatment processes of a water plant in Geum river. Monthly flow allocation from upstream dam is important for downstream $NH_3$-N control. In this study, prediction models of water quality based on multiple regression (MR), artificial neural network and data mining methods were developed to understand water quality variation and to support dam operations through providing predicted $NH_3$-N concentrations at intake station. The models were calibrated with eight years of monthly data and verified with another two years of independent data. In those models, the $NH_3$-N concentration for next time step is dependent on dam outflow, river water quality such as alkalinity, temperature, and $NH_3$-N of previous time step. The model performances are compared and evaluated by error analysis and statistical characteristics like correlation and determination coefficients between the observed and the predicted water quality. It is expected that these data mining techniques can present more efficient data-driven tools in modelling stage and it is found that those models can be applied well to predict water quality in stream river systems.

• Journal of Korean Society of Water and Wastewater
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• v.28 no.6
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• pp.735-745
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• 2014

This paper presents PKES(PuKyung -Excel based Simulator) for WWTPs(wastewater treatment plants) by using MS Excel and VBA(Visual Basic for Application). PKES is a user-friendly simulator for the design and optimization of the whole plant including biological and physico-chemical processes for the wastewater and sludge treatment. PKES calculates the performance under steady or dynamic state and allows changing the mathematical model by the user. Mathematical model implemented in PKES is a improved integration model based on ASM2d and ADM1 for simulation of AS(activated sludge) and AD(anaerobic digestion). Gaseous components of $N_2$, $N_2O$, $CO_2$ and $CH_4$ are added for estimation of GHGs(greenhouse gases) emission. The simulation results for comparison between PKES and Aquasim(EAWAG) showed about the same effluent concentrations. As a result of verification using by measured data of BOD, TSS, TN and TP for 2 years of operation, calculated effluent concentrations were similar to measured effluent concentrations. The values of average RMSE(root mean square error) were 1.9, 0.8, 1.6 and 0.2 mg/L for BOD, TSS, TN and TP, respectively. Total GHGs emission of WWTP calculated by PKES was 138.5 ton-$CO_2$/day and GHGs emissions of $N_2O$, $CO_2$ and $CH_4$ were calculated at 21.7, 28.9 and 87.9 ton-$CO_2$/day, respectively. GHGs emission of activated sludge was 32.5 % and that of anaerobic digestion was 67.5 %.

• Journal of the Korean Institute of Telematics and Electronics
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• v.22 no.3
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• pp.95-102
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• 1985

An efficient numerical scheme for assessing the two-dimensional diffusion problem for modelling impurity profile in semiconductor is described. 4 unique combination of ADI (Al-ternating Direction Bmplicit) method and Gauss Elimination has resulted in a reduction of CPU time for most diffusion processes by a factor of 3, compared to other iteration schemes such as SOR (Successive Over-Relaxation) or Stone's iterative method without additional storage re-quirement. Various numerical schemes were compared for 2-D as well as 1-0 diffusion profile in terms of their CPU time while retaining the magnitude of relative error within 0.001%. good agree-ment between 1-D and 2-D simulation profile as well as between 1-D simulation profile and experiment has been obtained.

• Journal of Korea Water Resources Association
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• v.43 no.3
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• pp.275-282
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• 2010

The purpose of culvert design is to determine optimum size for a safe drainage of flood discharge. The present method of culvert design in Korea is generally carried out by using "Road Drainage Design" of Korea Expressway Corporation (1991), which is based on the manual of Federal Highway Association (FHWA) of USA. However, this method may result in subjective error because of using graphs and the usage of nomograph can be a major obstacle for computer modelling. Some errors found in the previous works of culvert design are corrected, and a new logic has been developed for a simple determination of culvert size in this study. FHWA (1985) presents a nomograph to determine the critical water depth and the velocity head for a circular pipe, but in this study simple explicit equations have been developed to determine both respectively.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.21 no.4
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• pp.365-371
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• 2003

Digital high resolution cameras are widely available, and are increasingly use in digital close-range photogrammetry. And photogrammetry instruments are developing rapidly and the precision is improving continuously. The building of 3D terrains of high precision are possible and the calculation of the areas or the earthwork volumes have high precision due to the development of the techlique of the spatial information system using computer. Using the digital camera which has capacity of keeping numerical value by itself and easy carrying, we analyze the positioning error according to various change of photographing condition. Also we try to find a effective method of acquiring basis data for 3D monitoring of high-accuracy in pixel degree through digital close-range photogrammetry with bundle adjustment for local terrain model generation and 3D embodiment of tumulus. In the study is about to efficient analysis of digital information data fer conservation of cultural properties.