• Journal of the Korean Society of Fisheries and Ocean Technology
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• v.41 no.3
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• pp.227-233
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• 2005

In order to estimate the effective horse power(EHP) in towing net of a bottom trawl ship, the ship's resistance was calculated by using a series data of Yamagata and Wigley formula. Also the effective horse power for a ship(EHPs) was estimated versus the ship speed in sailing and the propulsive efficiency was calculated with the brake horse power and the effective horse power. Then the effective horse power for a ship and a trawl net were estimated in the application of the propulsive efficiency in towing net. The total effective horse power($EHP_T$) was average 187.6kW and the effective horse power for a 1.awl net($EHP_n$) was average 176.7kW at a smooth sea state in towing net. The ratio of $EHP_n$ to $EHP_T$ was about 94.0% and the value was higher slightly than was already informed at a smooth sea state. The power for keeping up a townet speed was required more about 20% of a maximum continuous power at a rather rough sea state than a smooth sea state. In the future, if the residual resistance is considered with a sea state, $EHP_n$ will be estimated more correctly Also the data of EHP estimated by this method will be used as the basic data to design a trawl net.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.1
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• pp.1-15
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• 2022

The MobileNetV3 is specially designed for mobile devices with limited memory and computing power. To reduce the network parameters and improve the network inference speed, a new lightweight network is proposed based on MobileNetV3. Firstly, to reduce the computation of residual blocks, a partial residual structure is designed by dividing the input feature maps into two parts. The designed partial residual structure is used to replace the residual block in MobileNetV3. Secondly, a dual-path feature extraction structure is designed to further reduce the computation of MobileNetV3. Different convolution kernel sizes are used in the two paths to extract feature maps with different sizes. Besides, a transition layer is also designed for fusing features to reduce the influence of the new structure on accuracy. The CIFAR-100 dataset and Image Net dataset are used to test the performance of the proposed partial residual structure. The ResNet based on the proposed partial residual structure has smaller parameters and FLOPs than the original ResNet. The performance of improved MobileNetV3 is tested on CIFAR-10, CIFAR-100 and ImageNet image classification task dataset. Comparing MobileNetV3, GhostNet and MobileNetV2, the improved MobileNetV3 has smaller parameters and FLOPs. Besides, the improved MobileNetV3 is also tested on CPU and Raspberry Pi. It is faster than other networks

• Fibers and Polymers
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• v.7 no.1
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• pp.51-56
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• 2006

Power net fabric is one of the highly extensible two-way fabrics. Power net structure shows special characteristics in the wearing of final functional clothes. This research evaluated effects of treatment temperature on proportional extensibility and shrinkage ratio of spandex at a given wale length. As treatment temperature increased, extensibility increased proportionally to the standard length of the sample and the shrinkage ratio in the direction of course and wale increased. The pulling-out length increased proportionally to the standard length of the sample. However it was affected by the effect of treatment time and temperature due to the thermal properties of spandex filament yarn.

• Proceedings of the KIEE Conference
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• 1989.11a
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• pp.224-227
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• 1989

In this paper, The implementation of modular neural net for fault diagnosis in power system is presented. Until now, there have been many researches on expert system for fault diagnosis. On expert system, a lot of time for searching goal is needed. But, neural net processes with high speed, as it has parallel distributed processing structure. So neural net has good performance in on-line fault diagnosis. For fault diagnosis in large power system, the constitution of modular neural net with partition of large power system is presented.

• Bulletin of the Korean Mathematical Society
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• v.49 no.5
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• pp.961-987
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• 2012

A compartment model of the flow driven by pumping without valves (valveless pumping) in an open tank system is proposed. By the open tank system, we mean that two rigid cylindrical tanks are connected with an elastic tube. An incompressible fluid fills this system up to a certain level in tanks under the gravity. The compartment model for analyzing such open system is derived from the energy principle which will be called the energy conserving compartment model or shortly the ECCM. Based on this ECCM of valveless pumping, we explore the occurrence of directional net flow or directional net power by a specific excitation at an asymmetric part of the elastic tube. The interaction between deformable elastic tube and the fluid inside is considered in the ECCM. The reliability of the ECCMis investigated through some physical examples. The ECCM shows the existence of directional net power of the valveless pump system with open tanks and confirms that the direction and magnitude of the net power depend on the pumping frequency as well. Furthermore, the phase synchronization in time between the fluid pressure difference and the external pinching force over the pumping region is highly related to the direction of energy storing or net power.

• KIPS Transactions on Software and Data Engineering
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• v.11 no.7
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• pp.307-314
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• 2022

Recently, researches using deep learning-based models are being actively conducted to replace statistical-based time series forecast techniques to predict electric power demand. The result of analyzing the researches shows that the performance of the LSTM-based prediction model is acceptable, but it is not sufficient for long-term regional-wide power demand prediction. In this paper, we propose a WaveNet deep learning model to predict electric power demand 24-hour-ahead with temperature data in order to achieve the prediction accuracy better than MAPE value of 2% which statistical-based time series forecast techniques can present. First of all, we illustrate a delated causal one-dimensional convolutional neural network architecture of WaveNet and the preprocessing mechanism of the input data of electric power demand and temperature. Second, we present the training process and walk forward validation with the modified WaveNet. The performance comparison results show that the prediction model with temperature data achieves MAPE value of 1.33%, which is better than MAPE Value (2.33%) of the same model without temperature data.

• Journal of the Korean Society of Fisheries and Ocean Technology
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• v.35 no.1
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• pp.65-76
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• 1999

Our status of off-shore stow-net fishery is in face with many difficult problems; the lack of fisherman by evading the 3-D occupation, the safety accident by unskilled crew and old type fishing system. In order to solve those problems, it is necessary to save the man power and ensure the safety of fishing work by the effective utilization of power and automatization of fishing gear system. This is consists of the side drum driven by main engine, the net hauler, the bow and stern capstan, jib crane etc. Therefore, we suggest the design on unification of power device of fishing gear system as follows; (1) fishing system by uni-hydraulic power and (2) fishing system by electric motor and electro-hydraulic power.

• Journal of the Korean Solar Energy Society
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• v.28 no.5
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• pp.1-7
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• 2008

Flashed steam system is one of the important geothermal power production methods. In this paper, optimum operations and performances of single and double flash systems are presented. It is shown that double flash system can produce about 26.5% more power than single flash system. Temperature of geothermal water($T_R$) is the most important parameter in the geothermal system. Optimum single and double flash temperatures and net power produced with these optimum conditions are expressed as a function of $T_R$ in this study. Thus net power output from geothermal resources can be estimated with the results of this work. Condenser Temperature($T_{con}$) is also important and the net power production can be shown as a function of ($T_R-T_{con}$. Volume flow rate per unit power is also to be considered as the condenser temperature decreases.

• Journal of the Korean Society of Fisheries and Ocean Technology
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• v.41 no.2
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• pp.147-155
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• 2005

This study was conducted in order to improve the automatic fishing operation system for anchovy boat seine by comparison with the fishing gear geometry and efficiency using the labor saving nets and the combined type net with midwater trawl. Field experiments were carried out to observe the geometry of nets and improve the fishing operation system by catcher boats. The vertical net opening of fore wing net, square, fore bag net and after bag net of the combined type net were varied in the range of 9.9~12.9. 16.2~28.2, 6.8~12.1 and 9.5~15.2m respectively, when the towing speed was 1.0m/sec and the distance between boats were 100m, 200m, 300m. The vertical net opening of the combined type nets was gradually decreased as function of with increasing the distance between catcher boats. Labor saving net which was maintained the net opening and towing depth stable was more suitable for the automatic hauling operation system by improvement of bag net rather than the combined type nets which was impossible in swallow depth and near to anchovy school. 3 boats hauling operation system of the labor saving net was carried out by crane with power block in 2 catcher boats for improvement of hauling operation and pushing equipment of anchovy cooking system in the processing boat for maintain more anchovy in dry frame. From the results of field experiments, 3 boats hauling operation system with power block and improved cooking system was very 3 boats hauling operation system with power block and improved cooking system was very useful and more practical as hauling time 20~35min and No. of fishermen 12~13 in comparison with the traditional system such as hauling time 30~50 min and No. of fishmen 28~38.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.1727-1731
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• 2003

In this paper we proposed backward fuzzy Petri-net to diagnoses faults in power systems by using the time sequence information of protection system. As the complexity of power systems increases, especially in the case of multiple faults or incorrect operation of protective devices, fault diagnosis requires new and systematic methods to the reasoning process, which improves both its accuracy and its efficiency. The fuzzy Petri-net models of protection system are composed of the operating process of protective devices and the fault diagnosis process. Fault diagnosis model, which makes use of the nature of fuzzy Petri-net, is developed to overcome the drawbacks of methods that depend on operator knowledge. The proposed method can reduce processing time and increase accuracy when compared with the traditional methods. And also this method covers online processing of real-time data from SCADA (Supervisory Control and Data Acquisition)