• Journal of the Korea Institute of Military Science and Technology
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• v.26 no.4
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• pp.361-370
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• 2023

Swarm has recently become a critical component of offensive and defensive systems. Multi-agent reinforcement learning(MARL) empowers swarm systems to handle a wide range of scenarios. However, the main challenge lies in MARL's scalability issue - as the number of agents increases, the performance of the learning decreases. In this study, transfer learning is applied to advanced MARL algorithm to resolve the scalability issue. Validation results show that the training efficiency has significantly improved, reducing computational time by 31 %.

• Proceedings of the Korea Society of Environmental Toocicology Conference
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• 2003.10a
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• pp.169-169
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• 2003

In Korea, there is no CRA studies and has not well known CRA and not well established their methodologies. Therefore, objectives of this study is to establish the framework of CRA consisting of health risk, economic risk and perceived risk and the detail methodologies of three main component of estimating and comparing those risks for on the three environmental problems of air pollution, indoor air pollution and drinking water contamination which being subjective to the eight sub-problems of hazardous ai. pollutants (HAPs), regulated pollutants (representative as PM10) and Dioxins (PCDDS/ PCDFs) in air pollution, and indoor ai. pollutants (IAPs) and Radon in indoor air pollution, and drinking water pollutants (DWPs), disinfection-by- products(DBPs) and radionuclides in drinking water contamination in Seoul, Korea. And then, their problems set priorities by individual and integrated risk. As a results, ranking of health risk were the following order of indoor air pollution, air pollution and then drinking water contamination, in three environmental problems and of radon, PM10, IAPs, HAPs, DWPs, Dioxins, DBPs, and then radionuclides in eight sub-problems. And that of economic risk were the same order. In the contrary, ranking of perceived risk were the following order of air pollution, drinking water contamination, and then indoor air pollution, and of HAPs, Dioxins, radionuclides, PM10, DWPs, IAPs, Radon and then DBPs.

• Journal of Korea Society of Industrial Information Systems
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• v.28 no.6
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• pp.1-10
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• 2023

The nuclear power plant(NPP)'s Instrumentation and Control(I&C) system periodically conducts integrity checks for the maintenance of self-diagnostic function during normal operation. Additionally, it performs functionality and performance checks during planned preventive maintenance periods. However, there is a need for technological development to diagnose failures and prevent accidents in advance. In this paper, we studied methods for estimating the reliability function by utilizing environmental data and self-diagnostic data of the I&C equipment. To obtain failure data, we assumed probability distributions for component features of the I&C equipment and generated virtual failure data. Using this failure data, we estimated the reliability function using representative artificial intelligence(AI) models used in survival analysis(DeepSurve, DeepHit). And we also estimated the reliability function through the Cox regression model of the traditional semi-parametric method. We confirmed the feasibility through the residual lifetime calculations based on environmental and diagnostic data.

• Journal of Korea Society of Industrial Information Systems
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• v.29 no.1
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• pp.31-48
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• 2024

The domestic automotive industry must consider a strategic shift from traditional automotive component manufacturing to align with future trends such as connectivity, autonomous driving, sharing, and electrification. This research conducted topic modeling on R&D projects in the future automotive sector funded by the Ministry of Trade, Industry, and Energy from 2013 to 2021. We found that topics such as sensors, communication, driver assistance technology, and battery and power technology remained consistently prominent throughout the entire period. Conversely, topics like high-strength lightweight chassis were observed only in the first period, while topics like AI, big data, and hydrogen fuel cells gained increasing importance in the second and third periods. Furthermore, this research analyzed the areas of concentrated investment for each period based on topic-specific government investment amounts and investment growth rates.

• Journal of the Korean Applied Science and Technology
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• v.36 no.1
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• pp.47-58
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• 2019

This study aimed to investigate the improvement effect of turmeric (Curcuma longa L.) on the lipid component, protein and electrolyte concentration in dyslipidemic rats. Sprague-Dawley rats (24 male) were divided into four groups, namely the ND (normal-nondyslipidemic diet), NT (normal-nondyslipidemic diet+5% turmeric), DD (control-dyslipidemic diet), and DT groups (dyslipidemic diet+5% turmeric). Rats were sacrificed at the end of 5 weeks after experiment diet. In this study, turmeric diet (NT, DT) groups in lipid composition as evidenced from the significantly reduction of serum total cholesterol, low density lipoprotein-cholesterol (LDL-cholesterol), atherosclerotic index (AI), cardiac risk factor (CRF), triglyceride (TG), phospholipid (PL), free cholesterol, cholesteryl ester, blood glucose and non esterified fatty acid (NEFA), and elevation of high density lipoprotein-cholesterol (HDL-cholesterol) (p<0.05). The serum globulin concentration was significantly decreased (p<0.05), and the albumin concentrations were increased in turmeric diet than dyslipidemic rats. Concentrations of sodium (Na) and chlorine (Cl) in sera were lower in the DT group than DD group. Concentrations of total calcium (T-Ca), phosphorus (Pi) and potassium (K) in sera were higher in the ND, NT and DT groups than DD group. Therefore, it was concluded that the 5% turmeric diet used in the condition of this study had a beneficial effect on dyslipidemia.

• Journal of Internet of Things and Convergence
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• v.9 no.2
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• pp.61-69
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• 2023

In recent years, due to heightened environmental awareness, Electric Power Steering (EPS) has been increasingly adopted as the steering control unit in manufactured vehicles. This has had numerous benefits, such as improved steering power, elimination of hydraulic hose leaks and reduced fuel consumption. However, for EPS systems to respond to actions, sensors must be employed; this means that the consistency of the sensor's linear variation is integral to the stability of the steering response. To ensure quality control, a reliable method for detecting defects and assessing linearity is required to assess the sensitivity of the EPS sensor to changes in the internal design characters. This paper proposes a data-driven defect and linearity assessment monitoring system, which can be used to analyze EPS component defects and linearity based on vehicle speed interval division. The approach is validated experimentally using data collected from an EPS test jig and is further enhanced by the inclusion of a Graphical User Interface (GUI). Based on the design, the developed system effectively performs defect detection with an accuracy of 0.99 percent and obtains a linearity assessment score at varying vehicle speeds.

• The Journal of the Convergence on Culture Technology
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• v.10 no.2
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• pp.517-524
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• 2024

This study aims to train and implement a deep learning model for the fusion of website creation and artificial intelligence, in the era known as the AI revolution following the launch of the ChatGPT service. The deep learning model was trained using 3,000 collected web page images, processed based on a system of component and layout classification. This process was divided into three stages. First, prior research on AI models was reviewed to select the most appropriate algorithm for the model we intended to implement. Second, suitable web page and paragraph images were collected, categorized, and processed. Third, the deep learning model was trained, and a serving interface was integrated to verify the actual outcomes of the model. This implemented model will be used to detect multiple paragraphs on a web page, analyzing the number of lines, elements, and features in each paragraph, and deriving meaningful data based on the classification system. This process is expected to evolve, enabling more precise analysis of web pages. Furthermore, it is anticipated that the development of precise analysis techniques will lay the groundwork for research into AI's capability to automatically generate perfect web pages.

• Journal of the Korean Society for information Management
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• v.41 no.1
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• pp.261-282
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• 2024

This study proposed and evaluated electroencephalography (EEG)-based and eye-tracking-based methods to determine relevance by utilizing users' implicit relevance feedback while navigating content in a digital library. For this, EEG/eye-tracking experiments were conducted on 32 participants using video, image, and text data. To assess the usefulness of the proposed methods, deep learning-based artificial intelligence (AI) techniques were used as a competitive benchmark. The evaluation results showed that EEG component-based methods (av_P600 and f_P3b components) demonstrated high classification accuracy in selecting relevant videos and images (faces/emotions). In contrast, AI-based methods, specifically object recognition and natural language processing, showed high classification accuracy for selecting images (objects) and texts (newspaper articles). Finally, guidelines for implementing a digital library interface based on EEG, eye-tracking, and artificial intelligence technologies have been proposed. Specifically, a system model based on implicit relevance feedback has been presented. Moreover, to enhance classification accuracy, methods suitable for each media type have been suggested, including EEG-based, eye-tracking-based, and AI-based approaches.

• Asian Pacific Journal of Cancer Prevention
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• v.15 no.4
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• pp.1863-1869
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• 2014

The amplification of telomerase component (TERC) gene could play an important role in generation and treatment of haematological malignancies. This present study was aimed to investigate copy number amplification status of TERC gene in chronic myeloid leukaemia (CML) patients who were being treated with imatinib mesylate (IM). Genomic DNA was extracted from peripheral blood of CML-IM Resistant (n=63), CML-IM Respond (n=63) and healthy individuals (n=30). TERC gene copy number predicted (CNP) and copy number calculated (CNC) were determined based on $Taqman^{(R)}$ Copy Number Assay. Fluorescence in situ hybridization (FISH) analysis was performed to confirm the normal signal pattern in C4 (calibrator) for TERC gene. Nine of CML patients showed TERC gene amplification (CNP=3), others had 2 CNP. A total of 17 CML patients expressed CNC>2.31 and the rest had 2.31>CNC>1.5. TERC gene CNP value in healthy individuals was 2 and their CNC value showed in range 1.59-2.31. The average CNC TERC gene copy number was 2.07, 1.99 and 1.94 in CML-IM Resistant patients, CML-IM Respond and healthy groups, respectively. No significant difference of TERC gene amplification observed between CML-IM Resistant and CML-IM Respond patients. Low levels of TERC gene amplification might not have a huge impact in haematological disorders especially in terms of resistance towards IM treatment.

• Natural Product Sciences
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• v.14 no.4
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• pp.260-264
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• 2008

To find the antidiabetic activity of the tripterpenoid-rich fractions of Rubus coreanus (TRF-cor) and R. crataegifolius (TRF-cra) leaves or its main component niga-ichigoside $F_1$ (Niga-$F_1$), anti-hyperglycemic and antihyperlipidemic effects were investigated in the diabetic rat model induced by streptozotocin (STZ). Treatments of rats with 200 mg/kg of the TRF-cor, TRF-cra (each, p.o.) or 20 mg/kg of Niga-$F_1$ significantly inhibited the increase of blood glucose concentration about 44.8%, 28.7% or 20.6%, respectively, in the diabetic rats. In addition, treatments with those fractions inhibited the increase of serum concentrations of triglyceride, total cholesterol or LDL-cholesterol caused by STZ. The inhibitory rate on atherogenic index (AI) values of the TRFcor (200 mg/kg), TRF-cra (200 mg/kg) or Niga-$F_1$ (20 mg/kg)-treated groups were decreased about 55.7%, 36.3% or 22.6%, respectively, comparable to STZ-treated group. In the oral glucose tolerance test, treatment of TRF-cor or TRF-cra inhibited the increase of blood glucose concentration in the STZ-induced rats. Administration of 20 mg/kg of Niga-$F_1$ (p.o.) also exhibited similar effects with the effects of both TRFs at 200 mg/kg dose (p.o.). These results support that the triterpenoids, in particular Niga-$F_1$, are contributed to the antidiabetic effects of R. coreanus or R. crataegifolius.