• Korean Journal of Poultry Science
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• v.32 no.1
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• pp.23-27
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• 2005

The aim of this study was to investigate differentially expressed proteins between normal chicken liver and chicken liver inffeted by Salmonella pullorum. 2-dimensional electrophoresis (2DE) and mass spectrometry (MS) were used to identify the proteins. More than 300 protein spots were detected on silver stained 2DE gels using pH 3$\~$10 gradients. The most outstanding protein spot was further analyzed by MALDI-TOF MS and protein database using the Mascot search engine. The protein was finally identified as APOAI (Apolipoprotein AI). Based on the known function of the APOAI, this gene acts protective action against the accumulation of platelet thrombin at the site of vascular damage for the pullorum disease. Therefore APOAI protein, identified in this study, can be a valuable biomarker in relation to the pullorum disease in chicken.

• Journal of the Society of Disaster Information
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• v.16 no.4
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• pp.842-848
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• 2020

Purpose: It is important to operate safely and economically in obsolescent power plant facilities. Economical operation is related in the balance of the supply and demand. Safety operation predicts the possible risks in the facilities and then, takes measures to the facilities. For the monitoring of the power plant facilities, we needs several kinds of the sensing system. From the sensors data, we can predict the possible risk. Method: We installed the acoustic, vibration, electric and smoke sensors in the power plant facilities. Using the data, we developed 3 kinds of prediction models, such as, demand prediction, plant engine abnormal prediction model, and risk prediction model. Results: Accuracy of the demand prediction model is over 90%. The other models make a stable operation of the system. Conclusion: For the sustainable operation of the obsolescent power plant, we developed 3 kinds of AI prediction models. The model apply to JB company's power plant facilities.

• Journal of the Korea Convergence Society
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• v.10 no.5
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• pp.9-16
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• 2019

In this paper, it will analyze security problems, so technology's potential can apply to business security area. First, in order to deep learning do security tasks sufficiently in the business area, deep learning requires repetitive learning with large amounts of data. In this paper, to acquire learning ability to do stable business tasks, it must detect abnormal IP packets and attack such as normal software with malicious code. Therefore, this paper will analyze whether deep learning has the cognitive ability to detect various attack. In this paper, to deep learning to reach the system and reliably execute the business model which has problem, this paper will develop deep learning technology which is equipped with security engine to analyze new IP about Session and do log analysis and solve the problem of mathematical role which can extract abnormal data and distinguish infringement of system data. Then it will apply to business model to drop the vulnerability and improve the business performance.

• Smart Media Journal
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• v.10 no.2
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• pp.110-118
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• 2021

The Internet of Things (IoT) technology, a key growth engine of the 4th industrial revolution, has grown to a stage where it can autonomously communicate with each other and process data according to space and circumstances. Accordingly, the IT infrastructure becomes increasingly complex and the importance of the monitoring field for maintaining the system stably is increasing. Monitoring technology has been used in the past, but there is a need to find a flexible monitoring system that can respond to the rapidly changing ICT technology. This paper conducts research on designing and testing an open source-based Prometheus monitoring system. We builds a simple infrastructure based on IoT devices and collects data about devices through the Exporter. Prometheus collects data based on pull and then integrates into one dashboard using Grafana and visualizes data to monitor device information.

• Journal of Convergence for Information Technology
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• v.11 no.3
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• pp.1-6
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• 2021

Most of the match-3 puzzle games supports automatic play using the MCTS algorithm. However, implementing reinforcement learning agents is not an easy job because it requires both the knowledge of machine learning and the way of complex interactions within the development environment. This study proposes a method in which we can easily design reinforcement learning agents and implement game play agents by applying PPO(Proximal Policy Optimization) algorithms. And we could identify the performance was increased about 44% than the conventional method. The tools we used are the Unity 3D game engine and Unity ML SDK. The experimental result shows that agents became to learn game rules and make better strategic decisions as experiments go on. On average, the puzzle gameplay agents implemented in this study played puzzle games better than normal people. It is expected that the designed agent could be used to speed up the game level design process.

• Journal of the Korean Society of Marine Environment & Safety
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• v.28 no.3
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• pp.451-458
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• 2022

In Korea, five major ports have been designated as sulfur oxide emission control areas to reduce air pollutant emissions, in accordance with Article 10 of the "Special Act on Port Air Quality" and Article 32 of the "Ship Pollution Prevention Regulations". As regulations against vessel-originated air pollutants (such as PM, CO2, NOx, and SOx) have been strengthened, the Ministry of Oceans and Fisheries(MOF) enacted rules that newly built public ships should adopt eco-friendly propulsion systems. However, particularly in diesel-electric hybrid propulsion systems,the demand for precise control schemes continues to grow as the fuel saving rate significantly varies depending on the control strategy applied. The conventional Power Take In-Power Take Off(PTI - PTO) mode control adopts a rule-based strategy, but this strategy is applied only in the low-load range and PTI mode; thus, an additional method is required to determine the optimal fuel consumption point. The proposed control method is designed to optimize fuel consumption by applying the equivalent consumption minimization strategy(ECMS) to the PTI - PTO mode by considering the characteristics of the specific fuel oil consumption(SFOC) of the engine in a diesel-electric hybrid propulsion system. To apply this method, a specific fishing vessel model operating on the Korean coast was selected to simulate the load operation environment of the ship. In this study, a 10.2% reduction was achieved in the MATLAB/SimDrive and SimElectric simulation by comparing the fuel consumption and CO2 emissions of the ship to which the conventional rule-based strategy was applied and that to which the ECMS was applied.

• The Journal of the Convergence on Culture Technology
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• v.10 no.2
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• pp.453-458
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• 2024

Optical Character Recognition is the technology that recognizes text in images and converts them into digital format. Deep learning-based OCR is being used in many industries with large quantities of recorded data due to its high recognition performance. To improve medical services, deep learning-based OCR was actively introduced by the medical industry. In this paper, we discussed trends in OCR engines and medical OCR and provided a roadmap for development of medical OCR. By using natural language processing on detected text data, current medical OCR has improved its recognition performance. However, there are limits to the recognition performance, especially for non-standard handwriting and modified text. To develop advanced medical OCR, databaseization of medical data, image pre-processing, and natural language processing are necessary.

• Proceedings of the KWS Conference
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• 2002.10a
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• pp.235-243
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• 2002

Ni-base superalloys are used extensively in industry, both in aeroengines and land based turbines. About 60% by weight of most modern gas turbine engine structural components are made of Ni-base superalloys. To satisfy practical demands, the efficiency of gas turbine engines has been steadily and systematically increased by design modifications to handle higher turbine inlet or firing temperatures. However, the increase in operating temperatures has lead to a decrease in the life of components and increase in costs of replacement. Moreover, around 80% of the large frame size industrial/utility gas turbines operating in the world today were installed in the mid-sixties to early seventies and are now 25 to 30 years old. Consequently, there are greater opportunities now to repair and refurbish the older models. Basically, there are two major factors influencing the weldability of the cast alloys: strain-age cracking and liquation cracking. Susceptibility to strain-age cracking is due to the total Ti plus AI content of the alloy; Liquation cracking is due either to the presence of low melting constituents or constitutional liquation of constituents. Though Rene 41 superalloy has 4.5wt.% total Ti and Al content and falls just below the safe limit proposed by Prager et al., controlled grain size and special heat treatments are needed to obtain crack-free welds. Varying heat treatments and filler materials were used in a laboratory study, then the actual welding of service parts was carried out to verity the possibility of crack-tree weld of components fabricated from Rene 41 superalloy. The microstructural observations indicated that there were two kinds of carbides in the FCC matrix. MC carbides were located along the grain boundaries, while M$_{23}$C$_{6}$ carbide was located both inter and intra granularly. Two kinds of filler materials, Rene 41 and Hastelloy X were used to gas tungsten arc weld a patch into the sheet metal, along with varying pre-weld heat treatments. The microstructure, hardness and tensile tests were determined. The service distressed parts were categorized into three classes: with large cracks, with medium cracks and with small or no visible cracks. No significant difference in microstructure among the specimens was observed. Specimens were cut from the corner and the straight edge of the patch repair, away from the corner. The only cracks present were found to be associated with inadequate surface preparation to remove oxidation. Guidelines for oxide removal and the welding procedures developed in the research enabled crack-free welds to be produced.d.

• Journal of the Korean Society of Fisheries and Ocean Technology
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• v.14 no.2
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• pp.69-78
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• 1978

It is well known that the aluminizing steel is excellent in corrosion resistance and heat resistance. Therefore it has been used as boiler parts, heat exchanger parts and guide rails which are used under comparatively simple conditions. Recently, it has been noticed that aluminizing steel has high resistance to various atmosphere, high temperature oxidation and seawater resistance. So its usage has been extended widely to the production of parts such as intake and exhaust valve of internal combustion engine, turbine blade and pipelines On ships which required such properties. It is considered that aluminium coated steel is excellent in wear resistance because of high hardness on main ingredient FezAIs of Fe-AI alloy layer existed in diffusion coating layer. And it will beused as a new material taking wear resitance with seawater resistance in marine field. However it is difficult to findout any report concering the wear behaviors or properties of alum in izing steel. In this study the experiment was carried out under the condition of rolling-sliding contact using an Amsler-type wear testing machine at 0.80, 0.91, 1. 10, 1. 25% of slip ratio and 55.43, 78.38, 110.85 kg/mm^2 of Hertz's contact stress in run-in period for the purpose of service-ability test of aluminizing steel as a wear resisting material and obtaining the available design data. The followings are the obtained results from the experimen tal study; 1) The 2nd diffusion material has most excellent wear resistance. This material has brought out about 18% decrease of wear weight in a lower friction load level and 40~G decrease in a higher level comparing to the raw material. 2) Satisfactory effect of wear resistivity cannot be much expected in 2nd diffusion specimens. This is considered due to the formation of fine void in the alloy layer near the boundary to the aluminium layer. 3) Fracture on friction surface of aluminizing steel by the rolling-sliding contact is spalling, and spalling crack occurres initially beneath the specimen surface near the boundary in diffusion coating layer.

• Journal of Digital Convergence
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• v.16 no.7
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• pp.223-229
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• 2018

Recently, the necessity of safety diagnosis of electrical devices has been increasing as the fire caused by electric devices has increased rapidly. This study is concerned with the safety diagnosis of electric equipment using intelligent Fuzzy technology. It is used as a diagnostic input for the multiple electrical safety factors such as the use current, cumulative use time, deterioration and arc characteristics inherent to the equipment. In order to extract these information in real time, a device composed of various sensor circuits, DSP signal processing, and communication circuit is implemented. The fuzzy logic algorithm using the Gaussian function for each information is designed and compiled to be implemented on a small DSP board. The fuzzy logic receives the four diagnostic information, deduces it by the fuzzy engine, and outputs the overall safety status of the device as a 100-step analog fuzzy value familiar to human sensibility. By experiments of a device that combines hardware and fuzzy algorithm implemented in this study, it is verified that it can be implemented in a small DSP board with human-friendly fuzzy value, diagnosing real-time safety conditions during operation of electric equipment. In the future, we expect to be able to study more intelligent diagnostic systems based on artificial intelligent with AI dedicated Micom.