• Journal of the Korean Institute of Telematics and Electronics C
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• v.34C no.5
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• pp.9-18
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• 1997

The petri net is a graphic model which is adaptable in modeling a complex concurrent parallel ssystem, and it is widely used in the fields of industrial enginering, computer science, electric engineeringand chemistry. Recently, the net is applied to the communication protocol, and extended to represent complex systems. There are several extended petri nets named as TPN (timed petri net), SPN (stochastic petri net), FPN(fuzzy petri net) and TFPN(timed fuzzy petri net). Accodingly, this SPN (stochastic petri net), FPN (fuzzy petri net) and TFPN(timed fuzzy petri net). Accodingly, this paper proposes an advanced communication protocol modeling method using the fuzzy value of the transition and firing delay time as the arguments of the function. The proposed method can produce clearer firing rules, and it is supposed to be used to design and analyse communication protocols in great effection.

• Journal of Information Technology Services
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• v.11 no.sup
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• pp.51-60
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• 2012

In this paper, we provide the analysis of device model and method between device models for compatible M&S V&V of the NetSPIN. First of all, we analysis features, structure, and classification of the NetSPIN. The second, as a part of reliable V&V process, we analysis network system modeling process, correlation between device modeling process for M&S of the NetSPIN. The third, we suggest making a kind of pool of reference model and module of devices for the increase factor of reuse between device model. We also, at the point view of M&S V&V, conclude that there is the validity of the fidelity in device modeling process. Through the analysis of the NetSPIN device model and suggestion of the method for higher compatibility between device modes, the development process of device model be clearly understood. Also we present the effective method of the development for reliable device mode as the point of V&V.

• The Journal of Fisheries Business Administration
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• v.51 no.1
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• pp.81-96
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• 2020

The purpose of this paper is to analyze factors affecting the net income of regional and industrial fisheries cooperatives in South Korea using panel data. This paper utilizes linear or GLS regression models such as pooled OLS model, fixed effects model, and random effects model to estimate affecting factors of the net income of regional and industrial fisheries cooperatives. After reviewing various tests, we eventually select random effects model. The results, based on panel data between 2013 and 2018 year and 64 fisheries cooperatives, indicate that capital and area dummy variables have positive effects and employment has negative effect on the net income of regional and industrial fisheries cooperatives as predicted. However, debt are opposite with our predictions. Specifically, it turns out that debt has positive effect on the net income of regional and industrial fisheries cooperatives although it has been increased. Additionally, this paper shows that the member of confreres does not show any significant effect on the net income of regional and industrial fisheries cooperatives in South Korea. This study is significant in that it analyzes the major factors influencing changes in the net income that have not been conducted recently for the fisheries cooperatives by region and industry.

• Journal of Power System Engineering
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• v.9 no.4
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• pp.187-193
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• 2005

In this paper, we proposes a man-machine interface design for fault diagnosis system with inter-node search method in a Petri net model. First, complicated fault cases are modeled as the Petri net graph expressions. Next, to find out causes of the faults on which we focus, a Petri net model is analyzed using the backward reasoning of transition-invariance in the Petri net. In this step, the inter-node search method algorithm is applied to the Petri net model for reducing the range of sources in faults. Finally, the proposed method is applied to a fault diagnosis of a refrigeration system to confirm the validity of the proposed method.

• Journal of the Korean Society of Fisheries and Ocean Technology
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• v.43 no.2
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• pp.101-115
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• 2007

The pound net fishery is very important one in Korean coastal fishery and it need to grasp the characteristics of the net affected by many factors. It is considered that the structure and the shape of the pound net can be changed by the direction and speed of current, wave height, depth and conditions of sea bed. However, most of all, the speed of current and wave height influence more upon the pound net than any other factors to deform and flutter. In this study, author carried out the experiments with a model of double one-side pound net made by the similarity law as 1:100 scales at a real experimental area, and additionally the model net experiments were conducted in the circulating water channel in Pukyong National University. The author analyzed the data of transformation of shape and tension of the model pound net to recognize the characteristics of the current and wave acting on it. Regardless of the direction of flow affecting on the fish court net or bag net, the deformed angle and depth to the side panel and bottom of box nets becomes bigger as the wave gets higher and the period of wave is faster. The tension in both upward or downward tends to be changed by the speed of wave. Those value of changes occurred similarly in either fish court net or bag net. Generally, when bag net is located at upward of flow, the value of tension was bigger 10% than any other location or nets. Regardless of the setting direction, the tension of the pound net is increased in proportion to flow speed, wave height and period of wave, and it becomes bigger about 15-30% at upward to flow than downward. Where the flow is upward in the court net, the tension in the wave increased to 37% compared to the one in the flow only in the condition of flow of 0.1-0.3m/s. Where the flow is upward in the bag net, the tension in the wave increased to 52% in the flow of 0.1m/s, and the tension increased to 48% in the flow of 0.2-0.3m/s.

• Journal of the Korean Society of Fisheries and Ocean Technology
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• v.44 no.2
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• pp.99-111
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• 2008

The purpose of this study is to develop the jellyfish separator system(JSS) for reducing fishery damage by the increase of jellyfish in the sea area of Korea in summer. First of all, to find the optimum structure of a JSS, six types of JSS in trawl fishery were designed and manufactured, the underwater shape of JSS and the separating process by JSS were observed in the circulating water channel(CWC). And the field experiments were carried out in July and September 2004 in the southern sea of Korea. For the moving path of the jellyfish model in the CWC, in case that the model was larger than the mesh size of the separator net, it was guided toward the lower part of the separator net by the guiding net and discharged through the outlet. In case that the model was smaller than the mesh size of the separator net, some models which passed through the upper part of the guiding net were smaller than the mesh size of the guiding net and discharged through the outlet and most of the model which passed through the lower part of the guiding net moved to the codend passing through the separator net. According to the field experiment result, the optimum tilt angle of separator net was inferred $20^{\circ}$ that the discharge rate of jellyfish was higher than the other tilt angle of separator net and the optimum structure of JSS was inferred GS type(consists of guiding net and separator net) that the discharge rate of jellyfish was higher than S type(consists of separator net). It was demamded to carry out more study for the countermeasure to reduce loss of fish.

• Journal of Korea Water Resources Association
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• v.54 no.5
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• pp.301-309
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• 2021

In this study, we tried to improve the performance of the existing U-net-based deep learning rainfall prediction model, which can weaken the meaning of time series order. For this, ConvLSTM2D U-Net structure model considering temporal consistency of data was applied, and we evaluated accuracy of the ConvLSTM2D U-Net model using a RainNet model and an extrapolation-based advection model. In addition, we tried to improve the uncertainty in the model training process by performing learning not only with a single model but also with 10 ensemble models. The trained neural network rainfall prediction model was optimized to generate 10-minute advance prediction data using four consecutive data of the past 30 minutes from the present. The results of deep learning rainfall prediction models are difficult to identify schematically distinct differences, but with ConvLSTM2D U-Net, the magnitude of the prediction error is the smallest and the location of rainfall is relatively accurate. In particular, the ensemble ConvLSTM2D U-Net showed high CSI, low MAE, and a narrow error range, and predicted rainfall more accurately and stable prediction performance than other models. However, the prediction performance for a specific point was very low compared to the prediction performance for the entire area, and the deep learning rainfall prediction model also had limitations. Through this study, it was confirmed that the ConvLSTM2D U-Net neural network structure to account for the change of time could increase the prediction accuracy, but there is still a limitation of the convolution deep neural network model due to spatial smoothing in the strong rainfall region or detailed rainfall prediction.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.27 no.6
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• pp.59-67
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• 2013

This paper presents a neural net type process model for enhancing learning compensation function in hot strip finishing rolling mill. Adequate input and output variables of process model are chosen, the proposed model was designed as single layer neural net. Equivalent carbon content, strip thickness and rolling speed are suggested as input variables, and looper's manipulation variable is proposed as output variable. According to simulation result using process data to show the validity of the proposed process model, neural net type process model's outputs give almost similar data to process output under same input conditions.

• International Journal of Internet, Broadcasting and Communication
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• v.14 no.2
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• pp.136-146
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• 2022

Some surface defects make the weak quality of steel materials. To limit these defects, we advocate a one-stage detector model RetinaNet among diverse detection algorithms in deep learning. There are several backbones in the RetinaNet model. We acknowledged two backbones, which are ResNet50 and VGG19. To validate our model, we compared and analyzed several traditional models, one-stage models like YOLO and SSD models and two-stage models like Faster-RCNN, EDDN, and Xception models, with simulations based on steel individual classes. We also performed the correlation of the time factor between one-stage and two-stage models. Comparative analysis shows that the proposed model achieves excellent results on the dataset of the Northeastern University surface defect detection dataset. We would like to work on different backbones to check the efficiency of the model for real world, increasing the datasets through augmentation and focus on improving our limitation.

• Journal of the Korean Society for Precision Engineering
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• v.15 no.3
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• pp.82-87
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• 1998

In order to provide a manufacturing system with efficiency and flexibility to cope with the changes in shop floor status, the integration of process planning and operations scheduling is required. In this paper, an integrated system of process planning and operations scheduling based on the concept of process net model and genetic algorithm is suggested. The process net model includes the alternative process plans. The integrated system is applied for prismatic parts.