• Journal of Food Hygiene and Safety
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• v.26 no.2
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• pp.120-124
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• 2011

Predictive mathematical models were developed for predicting the kinetics of growth of Listeria monocytogenes in smoked salmon, which is the popular ready-to-eat foods in the world, as a function of temperature (4, 10, 20 and $30^{\circ}C$). At these storage temperature, the primary growth curve fit well ($r^2$=0.989~0.996) to a Gompertz equation to obtain specific growth rate (SGR) and lag time (LT). The Polynomial model for natural logarithm transformation of the SGR and LT as a function of temperature was obtained by nonlinear regression (Prism, version 4.0, GraphPad Software). Results indicate L. monocytogenes growth was affected by temperature mainly, and SGR model equation is $365.3-31.94^*Temperature+0.6661^*Temperature^{\wedge^2}$ and LT model equation is $0.1162-0.01674^*Temperature+0.0009303^*Temperature{\wedge^2}$. As storage temperature decreased $30^{\circ}C$ to $4^{\circ}C$, SGR decreased and LT increased respectively. Polynomial model was identified as appropriate secondary model for SGR and LT on the basis of most statistical indices such as bias factor (1.01 by SGR, 1.55 by LT) and accuracy factor (1.03 by SGR, 1.58 by LT).

• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.10
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• pp.102-109
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• 2017

The high pressure pump of a diesel injection system compresses the fuel supplied at low pressure into high pressure fuel and maintains the fuel of the common rail at the required pressure level according to the engine operating conditions. The high pressure pump is required to operate normally in order to compress the fuel to a high pressure of 2000 bar during the entire lifetime of the vehicle. Consequently, a suitable design technique, material durability and high precision machining are required. In this study, the high pressure pump simulation model of a 1-plunger radial piston pump is modelled by using the AMESim code. The main simulation parameters are the displacement, flow rate and pressure characteristics of the inlet and outlet valves, cam torque characteristics, and operating characteristics of the fuel metering valve and overflow valve. In addition, the operating characteristics of the pump are simulated according to the parameter changes of the hole diameter and the spring initial force of the inlet valve. The simulation results show that the operation of the developed pump model is logically valid. This paper also proposes a simulation model that can be used for current pump design changes and new pump designs.

• Journal of The Korean Society of Grassland and Forage Science
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• v.41 no.1
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• pp.47-55
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• 2021

The objective of this study was to access the effect of climate and soil factors on alfalfa dry matter yield (DMY) by the contribution through constructing the yield prediction model in a general linear model considering climate and soil physical variables. The processes of constructing the yield prediction model for alfalfa was performed in sequence of data collection of alfalfa yield, meteorological and soil, preparation, statistical analysis, and model construction. The alfalfa yield prediction model used a multiple regression analysis to select the climate variables which are quantitative data and a general linear model considering the selected climate variables and soil physical variables which are qualitative data. As a result, the growth degree days(GDD) and growing days(GD), and the clay content(CC) were selected as the climate and soil physical variables that affect alfalfa DMY, respectively. The contributions of climate and soil factors affecting alfalfa DMY were 32% (GDD, 21%, GD 11%) and 63%, respectively. Therefore, this study indicates that the soil factor more contributes to alfalfa DMY than climate factor. However, for examming the correct contribution, the factors such as other climate and soil factors, and the cultivation technology factors which were not treated in this study should be considered as a factor in the model for future study.

• Journal of the Institute of Convergence Signal Processing
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• v.22 no.4
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• pp.149-155
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• 2021

In this study, we intend to develop a defective road surface object recognition model that automatically detects road surface defects that restrict the movement of the transportation handicapped using electric mobile devices with deep learning. For this purpose, road surface information was collected from the pedestrian and running routes where the electric mobility aid device is expected to move in five areas within the city of Busan. For data, images were collected by dividing the road surface and surroundings into objects constituting the surroundings. A series of recognition items such as the detection of breakage levels of sidewalk blocks were defined by classifying according to the degree of impeding the movement of the transportation handicapped in traffic from the collected data. A road surface object recognition deep learning model was implemented. In the final stage of the study, the performance verification process of a deep learning model that automatically detects defective road surface objects through model learning and validation after processing, refining, and annotation of image data separated and collected in units of objects through actual driving. proceeded.

• Journal of the Korea Society of Computer and Information
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• v.27 no.8
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• pp.49-59
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• 2022

In this paper, we designed a new enzyme function prediction model PSCREM based on a study that compared and evaluated CNN and LSTM/GRU models, which are the most widely used deep learning models in the field of predicting functions and structures using protein sequences in 2020, under the same conditions. Sequence evolution information was used to preserve detailed patterns which would miss in CNN convolution, and the relationship information between amino acids with functional significance was extracted through overlapping RNNs. It was referenced to feature map production. The RNN family of algorithms used in small CNN-RNN models are LSTM algorithms and GRU algorithms, which are usually stacked two to three times over 100 units, but in this paper, small RNNs consisting of 10 and 20 units are overlapped. The model used the PSSM profile, which is transformed from protein sequence data. The experiment proved 86.4% the performance for the problem of predicting the main classes of enzyme number, and it was confirmed that the performance was 84.4% accurate up to the sub-sub classes of enzyme number. Thus, PSCREM better identifies unique patterns related to protein function through overlapped RNN, and Overlapped RNN is proposed as a novel methodology for protein function and structure prediction extraction.

• Journal of the Korean Society of Food Science and Nutrition
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• v.43 no.1
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• pp.128-134
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• 2014

To develop a crab-like flavorant from snow crab cooker effluent (SCCE, $20^{\circ}Brix$), optimal reaction conditions were determined using response surface methodology (RSM) combined with reaction flavoring technology (RFT). Using five variables (proline, glycine, arginine, methionine, fructose), RSM based on a five-level central composite design was applied to evaluate sensory acceptance (odor, taste, and overall acceptance) as dependent variables. A model equation obtained from RSM showed 0.88 of R-square for odor, 0.90 for taste, and 0.95 for overall acceptance with 0.07 lack of fit in overall acceptance (P<0.05). Odor score (predicted value) was 7.21 in the saddle point. Optimal flavoring conditions for making a crab-like flavorant were as follows: addition of 0.29 g of proline, 0.63 g of glycine, 0.61 g of arginine, 0.02 g of methionine, and 1.07 g% (w/v) of fructose into SCCE with RFT (90 min at $130^{\circ}C$). Odor score obtained under optimal conditions was 7.56, which was higher than the predicted value.

• Journal of the Korean Society for Marine Environment & Energy
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• v.11 no.2
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• pp.86-91
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• 2008

Ships operating in littoral sea are likely to be subjected to accidental load such as stranding. Once she has damage on the hull structure, her ultimate strength will be reduced. This paper is to investigate the effect of the stranding damage on ultimate strength of ship structure by using a series of collapse tests. For the experiment, 720 mm $\times$720 mm in section and 900mm in length of five box-girder models with stiffeners were pre- pared. Of the five, one has no damage and faur have an diamond shaped damage which represents the shape of rock section in seabed. The damage size is different between models. Among the damaged models, the damages of 3 of them were made by cutting the plate and one by pressing to represent stranding damage. Experiments were carried out under pure bending load and the applied load and displacements were recorded. The ultimate strength is reduced as the damage size increases, as expected. The largest damaged model has the damage size of 30% of breadth and its ultimate strength is reduced by 21% than that of no damaged one. The pressed one has lower ultimate strength than cut one. This might be due to the fact that the plate around the pressed damage area effect negatively on the ultimate strength.

• The KIPS Transactions:PartA
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• v.16A no.6
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• pp.427-436
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• 2009

Digital virtual manufacturing is a technology that aims for the rapid development of products and the verification of production-process in ways that are more efficient by integrating digital models within the entire manufacturing process. These digital models utilize various information technologies, such as 3D CAD and simulations. Mixed reality, which represents graphical objects for only needed parts against real scene, can bring a more enriched sense of reality to an existing virtual manufacturing system that is in a pure virtual environment, and it can reduce the time and money needed for modeling the environment. This paper suggests a method for planning virtual factory layouts based on mixed reality using legacy datathat are already constructed in the real field. To do this, we developed the method to acquire simulation data from legacy data and process this acquired data for visualization based on mixed reality. And then we construct display system based on mixed reality, which can simulate virtual factory layout with processed data. Developed system can reduce errors related with factory layout by verifying the location and application of equipments in advance before arrangement of real ones at the practical job site.

• Transactions of the Korean Society of Mechanical Engineers
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• v.9 no.5
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• pp.590-597
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• 1985

A recursive geometric adaptive control method to compensate for machining straightness error in the finished surface due to tool deflection and guideway error generated by end milling process is developed. The relationship between the tool deflection and the feedrate is modeled by a modified Taylor's tool life equation. Without a priori knowledge on the variations off cutting parameters, time varying parameters are then estimated by an exponentially windowed recursive least squares method with only post-process measurements of the straightness error. The location error is controlled by shifting the milling bed in the direction perpendicular to the finished surface and adding a certain amount of feedrate with respect to the tool deflection model before cutting. The waviness error is compensated by adjusting the feedrate during machining. Experimental results show that location error is controlled within a range of fixturing error of the bed on the guideway and that about 60% reduction in the waviness error can be achieved within a few steps of parameter adaption under wide operating ranges of cutting conditions even if the parameters do not converge to fixed values.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.16 no.10
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• pp.7071-7077
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• 2015

In recently, the demand of cover-glass is increased because smart phone, tablet pc, and electrical device has become widely used. The display of mobile device is enlarged, so it is necessary to have a high strength against the external force such as contact or falling. In fabrication process of cover-glass, a grinding process is very important process to obtain high strength of glass. Conventional grinding process using a grinding wheel is caused such as a scratch, chipping, notch, and micro-crack on a surface. In this paper, polishing system using a abrasive film was developed for a grinding of mobile cover-glass. To evaluate structural stability of the designed system, finite element model of the polishing system is generated, and multi-body dynamic analysis of abrasive film polishing machine is proposed. As a result of the analysis, stress and displacement analysis of abrasive film polishing system are performed, and using laser displacement sensor, structural stability of abrasive film polishing system is confirmed by measuring displacement.