• Smart Structures and Systems
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• v.31 no.5
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• pp.485-500
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• 2023

Machine learning-based structural health monitoring (ML-based SHM) methods are researched extensively in the recent decade due to the availability of advanced information and sensing technology. ML methods are well-known for their pattern recognition capability for complex problems. However, the main obstacle of ML-based SHM is that it often requires pre-collected historical data for model training. In most actual scenarios, damage presence can be detected using the unsupervised learning method through anomaly detection, but to further identify the damage types would require prior knowledge or historical events as references. This creates the cold-start problem, especially for new and unobserved structures. Modal-based methods identify damages based on the changes in the structural global properties but often require dense measurements for accurate results. Therefore, a two-stage hybrid modal-machine learning damage detection scheme is proposed. The first stage detects damage presence using Principal Component Analysis-Frequency Response Function (PCA-FRF) in an unsupervised manner, whereas the second stage further identifies the damage. To solve the cold-start problem, mode shape assessment using the first mode is initiated when no trained model is available yet in the second stage. The damage identified by the modal-based method would be stored for future training. This work highlights the performance of the scheme in alleviating the cold-start issue as it transitions through different phases, starting from zero damage sample available. Results showed that single and multiple damages can be identified at an acceptable accuracy level even when training samples are limited.

• Journal of Korean Society for Atmospheric Environment
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• v.21 no.6
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• pp.649-655
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• 2005

Automotive exhaust is suspected to be one of the main reasons of the rapid increase in greenhouse effect gases in ambient air. Although methane emissions are generally orders of magnitude lower than emissions of $CO_{2}$, the global warming potential (GWP) of methane is greater than that of $CO_{2}$. The environmental impact of methane emissions from vehicles is negligible and is likely to remain so for the foreseeable future. In this study, in order to investigate greenhouse gas emission characteristics from gasoline passenger cars, 20 vehicles were tested on the chassis dynamometer and methane emissions were measured. The emission characteristics by model year, mileage, vehicle speed were discussed. Test mode is CVS-15 mode that have been used to regulate for light-duty vehicle in Korea. It was found that $CH_{4}$ emissions showed higher for cold start, old model year and long mileage than hot start, new model year and short mileage, respectively. These results were compared with IPCC emission factors and the overall our results were anticipated to contribute for domestic greenhouse gas emissions calculation.

• International Journal of Automotive Technology
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• v.6 no.5
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• pp.437-444
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• 2005

Unburned hydrocarbon (UBHC) emissions from gasoline engines remain a primary engineering research and development concern due to stricter emission regulations. Gasoline engines produce more UBHC emissions during cold start and warm-up than during any other stage of operation, because of insufficient fuel-air mixing, particularly in view of the additional fuel enrichment used for early starting. Impingement of fuel droplets on the cylinder wall is a major source of UBHC and a concern for oil dilution. This paper describes an experimental study that was carried out to investigate the distribution and 'footprint' of fuel droplets impinging on the cylinder wall during the intake stroke under engine starting conditions. Injectors having different targeting and atomization characteristics were used in a 4-Valve engine with optical access to the intake port and combustion chamber. The spray and targeting performance were characterized using high-speed visualization and Phase Doppler Interferometry techniques. The fuel droplets impinging on the port, cylinder wall and piston top were characterized using a color imaging technique during simulated engine start-up from room temperature. Highly absorbent filter paper was placed around the circumference of the cylinder liner and on the piston top to collect fuel droplets during the intake strokes. A small amount of colored dye, which dissolves completely in gasoline, was used as the tracer. Color density on the paper, which is correlated with the amount of fuel deposited and its distribution on the cylinder wall, was measured using image analysis. The results show that by comparing the locations of the wetted footprints and their color intensities, the influence of fuel injection and engine conditions can be qualitatively and quantitatively examined. Fast FID measurements of UBHC were also performed on the engine for correlation to the mixture formation results.

• Journal of Physiology & Pathology in Korean Medicine
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• v.22 no.1
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• pp.234-245
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• 2008

Yeonkyopaedok-san(YPS) extract is widely used to treat the common cold. The purpose of this study was to evaluate the efficacy of YPS on the common cold. Two hundred Patients with common colds of recent onset were randomized to the double blind, placebo-controlled study. They received 800 mg YPS extract or placebo in capsules, orally dissolved 3 times a day for 7 days. The total symptom score was assessed by the physician, using a 5-point scale on start and finish. Resolution of cold symptoms based on subjective daily symptoms. Total symptom score was significantly decreased in YPS groups in comparison to that in placebo group (p=0.027). Headache (p=0.012), loss of appetite (p=0.037), eyeball discomfort (p=0.002) were more affected. Time to resolution of cold symptoms did not show significant effect (p=0.592). Adverse effects were less in the YPS group than placebo group (2% vs 3%). In this community-based, randomized controlled trial, YPS were effective in treating cold symptoms in college students.

• Proceedings of the Korean Vacuum Society Conference
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• 2015.08a
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• pp.104-104
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• 2015

Due to the demand of the cold neutron flux in the neutron science and beam utilization technology, the cold neutron source (CNS) has been constructed and operating in the nuclear research reactor all over the world. The majority of the heat load removal scheme in the CNS is two-phase thermosiphon using the liquid hydrogen as a moderator. The CNS moderates thermal neutrons through a cryogenic moderator, liquid hydrogen, into cold neutrons with the generation of the nuclear heat load. The liquid hydrogen in a moderator cell is evaporated for the removal of the generated heat load from the neutron moderation and flows upward into a heat exchanger, where the hydrogen gas is liquefied by the cryogenic helium gas supplied from a helium refrigeration system. The liquefied hydrogen flows down to the moderator cell. To keep the required liquid hydrogen stable in the moderator cell, the CNS consists of an in-pool assembly (IPA) connected with the hydrogen system to handle the required hydrogen gas, the vacuum system to create the thermal insulation, and the helium refrigeration system to provide the cooling capacity. If one of systems is running out of order, the operating research reactor shall be tripped because the integrity of the CNS-IPA is not secured under the full power operation of the reactor. To prevent unscheduled reactor shutdown during a long time because the research reactor has been operating with the multi-purposes, the introduction of the standby cooling system (STS) can be a solution. In this presentation, the design considerations are considered how to design the STS satisfied with the following objectives: (a) to keep the moderator cell less than 350 K during the full power operation of the reactor under loss of the vacuum, loss of the cooling power, loss of common electrical power, or loss of instrument air cases; (b) to circulate smoothly helium gas in the STS circulation loop; (c) to re-start-up the reactor within 1 hour after its trip to avoid the Xenon build-up because more than certain concentration of Xenon makes that the reactor cannot start-up again; (d) to minimize the possibility of the hydrogen-oxygen reaction in the hydrogen boundary.

• 한국연소학회:학술대회논문집
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• 2003.12a
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• pp.257-262
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• 2003

Engine-out HC emissions were investigated during engine start. The tests were conducted on a 1.5L, 4-cylinder, 16 valve, multipoint-port-fuel-injection gasoline engine at different coolant temperatures and fuel injection-skip methods; no skip, 1 cycle-skip and 3 cycle-skip. To understand the characteristics of engine-out HC emissions, HC concentration was measured at a exhaust port using a Fast Response Flame Ionization Detector (FRFID). The result show that HC emissions were emitted at the cold coolant temperature much higher than those of the hot coolant. In additions, the fuel injection skip highly reduced engine-out HC emissions. It is convinced that optimized fuel injection skips according to coolant temperatures could be applied to reduce HC emissions during SI engine start.

• Proceedings of the SAREK Conference
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• 2004.06a
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• pp.163-163
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• 2004

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.19 no.8
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• pp.585-592
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• 2007

Good cold start characteristics are essential for satisfactory operation of fuel cell vehicles. In this study, the melting process has been numerically investigated for a water tank used in fuel cell vehicles. The 2-D model of the tank containing ice and plate heaters was assumed and the unsteady melting process of the ice was calculated. The enthalpy method was used for the description of the melting process, and a FVM code was used to solve the problem. The feasibility study compared with other experiment showed that the developed program was able to describe the melting process well. From the numerical analysis carried out for different wall temperatures of the pate heaters, some important design factors could be found such as local overheating and pressurization in the tank.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.19 no.6
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• pp.434-440
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• 2007

One of the cold start problems of a FCV is the freezing of the water in the water tank when a FCV is not in operation and the surrounding temperature drops below $0^{\circ}C$. The ice in the tank should be melted as quickly as possible for a satisfactory operation of fuel cell vehicles. In this study, the melting process for the constant heat fluxes of the plate heaters was numerically calculated in the 2-D model of the tank and plate heaters. The enthalpy method and FVM code was used for this analysis. The changes of the temperature with heat fluxes and the heat transfer area could be investigated. The energy balance error was found to increase with the heat flux. From this numerical analysis, the proper heat flux value and some important design factors relating local overheating and pressurization of the water tank could be examined.

• Journal of Computing Science and Engineering
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• v.7 no.1
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• pp.21-29
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• 2013

The introduction of recommender systems to existing online services is now practically inevitable, with the increasing number of items and users on online services. Popular recommender systems have successfully implemented satisfactory systems, which are usually based on collaborative filtering. However, collaborative filtering-based recommenders suffer from well-known problems, such as popularity bias, and the cold-start problem. In this paper, we propose an innovative collaborative-filtering based recommender system, which uses the concepts of Experts and Novices to create fine-grained recommendations that focus on being novel, while being kept relevant. Experts and Novices are defined using pre-made clusters of similar items, and the distribution of users' ratings among these clusters. Thus, in order to generate recommendations, the experts are found dynamically depending on the seed items of the novice. The proposed recommender system was built using the MovieLens 1 M dataset, and evaluated with novelty metrics. Results show that the proposed system outperforms matrix factorization methods according to discovery-based novelty metrics, and can be a solution to popularity bias and the cold-start problem, while still retaining collaborative filtering.